Note: Descriptions are shown in the official language in which they were submitted.
DEMANDES OU BREVETS VOLUMINEUX
LA PRESENTE PARTIE DE CETTE DEMANDE OU CE BREVETS
= COMPREND PLUS D'UN TOME.
CECI EST LE TOME 1 DE 2
NOTE: Pour les tomes additionels, veillez contacter le Bureau Canadien des
Brevets.
JUMBO APPLICATIONS / PATENTS
THIS SECTION OF THE APPLICATION / PATENT CONTAINS MORE
THAN ONE VOLUME.
THIS IS VOLUME 1 OF 2
NOTE: For additional volumes please contact the Canadian Patent Office.
=
= SYSTEM AND METHODS FOR COPING WITH DOPPLER EFFECTS IN
DISTRIBUTED-INPUT DISTRIBUTED-OUTPUT WIRELESS SYSTEMS
RELATED APPLICATIONS
100011 This application is related to the following co-pending
U.S. Patent Applications:
100021 U.S. Application Serial No. 12/917,257, filed November 1,
2010, entitled "Systems
And Methods To Coordinate Transmissions In Distributed Wireless Systems Via
User
Clustering"; U.S. Application Serial No. 12/802,988, filed June 16, 2010,
entitled "Interference
Management, Handoff, Power Control And Link Adaptation In Distributed-Input
Distributed-
Output (DIDO) Communication Systems"; U.S. Application Serial No. 12/802,976,
filed June
16, 2010, entitled "System And Method For Adjusting DIDO Interference
Cancellation Based
On Signal Strength Measurements", now U.S. Issued Patent 8,170,081, Issued on
May 1, 2012;
U.S. Application Serial No. 12/802,974, filed June 16, 2010, entitled "System
And Method For
Managing Inter-Cluster Handoff Of Clients Which Traverse Multiple DIDO
Clusters"; U.S.
Application Serial No. 12/802,989, filed June 16, 2010, entitled "System And
Method For
Managing Handoff Of A Client Between Different Distributed-Input-Distributed-
Output (DIDO)
Networks Based On Detected Velocity Of The Client"; U.S. Application Serial
No. 12/802,958,
filed June 16, 2010, entitled "System And Method For Power Control And Antenna
Grouping In
A Distributed-Input-Distributed-Output (DIDO) Network"; U.S. Application
Serial No.
12/802,975, filed June 16, 2010, entitled "System And Method For Link
adaptation In DIDO
Multicarrier Systems"; U.S. Application Serial No. 12/802,938, filed June 16,
2010, entitled
"System And Method For DIDO Precoding Interpolation In Multicarrier Systems";
U.S.
Application Serial No. 12/630,627, filed December 3, 2009, entitled "System
and Method For
Distributed Antenna Wireless Communications"; U.S. Application Serial No.
12/143,503, filed
June 20, 2008 entitled "System and Method For Distributed Input-Distributed
Output Wireless
Communications", now U.S. Issued Patent 8,160,121, Issued on April 17, 2009;
U.S.
Application Serial No. 11/894,394, filed August 20, 2007 entitled, "System and
Method for
Distributed Input Distributed Output Wireless Communications", now U.S. Issued
Patent
7,599,420, Issued on October 6, 2009; U.S. Application Serial No. 11/894,362,
filed August 20,
2007 entitled, "System and method for Distributed Input-Distributed Wireless
Communications",
now U.S. Issued Patent, 7,633,994, Issued on December 15, 2009; U.S.
Application Serial No.
11/894,540, filed August 20, 2007 entitled "System and Method For Distributed
Input-
Distributed Output Wireless Communications", now U.S. Issued Patent No.
7,636,381, Issued on
December 22, 2009; U.S. Application Serial No. 11/256,478, filed October 21,
2005 entitled
"System and Method For Spatial-Multiplexed Tropospheric Scatter
Communications", now U.S.
1
CA 2872502 2020-03-06
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
Issued Patent 7,711,030, Issued on May 4, 2010; U.S. Application Serial No.
10/817,731, filed
April 2, 2004 entitled "System and Method For Enhancing Near Vertical
Incidence Skyw-ave
("NVIS") Communication Using Space-Time Coding", now U.S. Issued Patent No.
7,885,354,
Issued on February 28, 2011.
BACKGROUND
[0003] Prior art multi-user wireless systems may include only a single base
station or
several base stations.
[0004] A single WiFi base station (e.g., utilizing 2.4 GHz 802.11b, g or n
protocols)
attached to a broadband wired Internet connection in an area where there are
no other WiFi
access points (e.g. a WiFi access point attached to DSL within a rural home)
is an example of a
relatively simple multi-user wireless system that is a single base station
that is shared by one or
more users that are within its transmission range. If a user is in the same
room as the wireless
access point, the user will typically experience a high-speed link with few
transmission
disruptions (e.g. there may be packet loss from 2.4GHz interferers, like
microwave ovens, but
not from spectrum sharing with other WiFi devices), If a user is a medium
distance away or with
a few obstructions in the path between the user and WiFi access point, the
user will likely
experience a medium-speed link. If a user is approaching the edge of the range
of the WiFi
access point, the user will likely experience a low-speed link, and may be
subject to periodic
drop-outs if changes to the channel result in the signal SNR dropping below
usable levels. And,
finally, if the user is beyond the range of the WiFi base station, the user
will have no link at all.
[0005] When multiple users access the WiFi base station simultaneously,
then the available
data throughput is shared among them. Different users will typically place
different throughput
demands on a WiFi base station at a given time, but at times when the
aggregate throughput
demands exceed the available throughput from the WiFi base station to the
users, then some or
all users will receive less data throughput than they are seeking. In an
extreme situation where a
WiFi access point is shared among a very large number of users, throughput to
each user can
slow down to a crawl, and worse, data throughput to each user may arrive in
short bursts
separated by long periods of no data throughput at all, during which time
other users are served.
This "choppy" data delivery may impair certain applications, like media
streaming.
[0006] Adding additional WiFi base stations in situations with a large
number of users will
only help up to a point. Within the 2.4GHz ISM band in the U.S., there are 3
non-interfering
channels that can be used for WiFi, and if 3 WiFi base stations in the same
coverage area are
configured to each use a different non-interfering channel, then the aggregate
throughput of the
coverage area among multiple users will be increased up to a factor of 3. But,
beyond that,
2
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
adding more WiFi base stations in the same coverage area will not increase
aggregate
throughput, since they will start sharing the same available spectrum among
them, effectually
utilizing time-division multiplexed access (TDMA) by "taking turns" using the
spectrum. This
situation is often seen in coverage areas with high population density, such
as within multi-
dwelling units. For example, a user in a large apartment building with a WiFi
adapter may well
experience very poor throughput due to dozens of other interfering WiFi
networks (e.g. in other
apartments) serving other users that are in the same coverage area, even if
the user's access point
is in the same room as the client device accessing the base station. Although
the link quality is
likely good in that situation, the user would be receiving interference from
neighbor WiFi
adapters operating in the same frequency band, reducing the effective
throughput to the user.
[0007] Current multiuser wireless systems, including both unlicensed
spectrum, such as
WiFi, and licensed spectrum, suffer from several limitations. These include
coverage area,
downlink (DL) data rate and uplink (UL) data rate. Key goals of next
generation wireless
systems, such as VViMAX and LTE, are to improve coverage area and DL and UL
data rate via
multiple-input multiple-output (MIMO) technology. MIMO employs multiple
antennas at
transmit and receive sides of wireless links to improve link quality
(resulting in wider coverage)
or data rate (by creating multiple non-interfering spatial channels to every
user). If enough data
rate is available for every user (note, the terms "user" and "client" are used
herein
interchangeably), however, it may be desirable to exploit channel spatial
diversity to create non-
interfering channels to multiple users (rather than single user), according to
multiuser M1MU
(MU-MIMO) techniques. See, e.g., the following references:
[0008] G. Caire and S. Shamai, "On the achievable throughput of a
multiantenna Gaussian
broadcast channel," IEEE Trans. Info.Th., vol. 49, pp. 1691-1706, July 2003.
[0009] P. Viswanath and D. Tse, "Sum capacity of the vector Gaussian
broadcast channel
and uplink-downlink duality," IEEE Trans. Info. Th., vol. 49, pp. 1912-1921,
Aug. 2003.
100101 S Vishwanath, N. Jindal, and A. Goldsmith, "Duality, achievable
rates, and sum-
rate capacity of Gaussian MIMO broadcast channels," IEEE Trans. Info. Th.,
vol. 49, pp. 2658-
2668, Oct. 2003.
[0011] W. Yu and J. Cioffi, "Sum capacity of Gaussian vector broadcast
channels," IEEE
Trans. Info. Th., vol. 50, pp. 1875-1892, Sep. 2004.
[0012] M. Costa, "Writing on dirty paper," IEEE Transactions on Information
Theory, vol.
29, pp. 439-441, May 1983.
[0013] M. Bengtsson, "A pragmatic approach to multi-user spatial
multiplexing," Proc. of
Sensor Array and Multichannel Sign.Proc. Workshop, pp. 130-134, Aug. 2002.
3
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[0014] K.-K. Wong, R. D. Murch, and K. B. Letaief, "Performance enhancement
of
multiuser MIMO wireless communication systems," IEEE Trans. Comm., vol. 50,
pp. 1960-
1970, Dec. 2002.
[0015] M. Sharif and B. Hassibi, "On the capacity of MIMO broadcast channel
with partial
side information," IEEE Trans. Info.Th., vol. 51, pp. 506-522, Feb. 2005.
[0016] For example, in MIMO 4x4 systems (i.e., four transmit and four
receive antennas),
10MHz bandwidth, 16-QAM modulation and forward error correction (FEC) coding
with rate
3/4 (yielding spectral efficiency of 3bps/Hz), the ideal peak data rate
achievable at the physical
layer for every user is 4x30Mbps=120Mbps, which is much higher than required
to deliver high
definition video content (which may only require ¨10Mbps). In MU-MIMO systems
with four
transmit antennas, four users and single antenna per user, in ideal scenarios
(i.e., independent
identically distributed, i.i.d., channels) downlink data rate may be shared
across the four users
and channel spatial diversity may be exploited to create four parallel 30Mbps
data links to the
users.
Different MU-MIMO schemes have been proposed as part of the LIE standard as
described, for
example, in 3GPP, "Multiple Input Multiple Output in UTRA", 3GPP TR 25.876
V7Ø0, Mar.
2007; 3GPP, "Base Physical channels and modulation", IS 36.211, V8.7.0, May
2009; and
3GPP, "Multiplexing and channel coding", IS 36.212, V8.7.0, May 2009. However,
these
schemes can provide only up to 2X improvement in DL data rate with four
transmit antennas.
Practical implementations of MU-M1MU techniques in standard and proprietary
cellular systems
by companies like ArrayComm (see, e.g., ArrayComm, "Field-proven results",
http://www.arraycomm.comiserve.php?page=proof) have yielded up to a ¨3X
increase (with four
transmit antennas) in DL data rate via space division multiple access (SDMA).
A key limitation
of MU-MIMO schemes in cellular networks is lack of spatial diversity at the
transmit side.
Spatial diversity is a function of antenna spacing and multipath angular
spread in the wireless
links. In cellular systems employing MU-MIMO techniques, transmit antennas at
a base station
are typically clustered together and placed only one or two wavelengths apart
due to limited real
estate on antenna support structures (referred to herein as "towers," whether
physically tall or
not) and due to limitations on where towers may be located. Moreover,
multipath angular spread
is low since cell towers are typically placed high up (10 meters or more)
above obstacles to yield
wider coverage.
100171 Other practical issues with cellular system deployment include
excessive cost and
limited availability of locations for cellular antenna locations (e.g. due to
municipal restrictions
on antenna placement, cost of real-estate, physical obstructions, etc.) and
the cost and/or
availability of network connectivity to the transmitters (referred to herein
as "backhaul").
4
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
Further, cellular systems often have difficulty reaching clients located
deeply in buildings due to
losses from walls, ceilings, floors, furniture and other impediments.
[0018] Indeed, the entire concept of a cellular structure for wide-area
network wireless
presupposes a rather rigid placement of cellular towers, an alternation of
frequencies between
adjacent cells, and frequently sectorization, so as to avoid interference
among transmitters (either
base stations or users) that are using the same frequency. As a result, a
given sector of a given
cell ends up being a shared block of DL and UL spectrum among all of the users
in the cell
sector, which is then shared among these users primarily in only the time
domain. For example,
cellular systems based on Time Division Multiple Access (TDMA) and Code
Division Multiple
Access (CDMA) both share spectrum among users in the time domain. By
overlaying such
cellular systems with sectorization, perhaps a 2-3X spatial domain benefit can
be achieved. And,
then by overlaying such cellular systems with a MU-MIMO system, such as those
described
previously, perhaps another 2-3X space-time domain benefit can be achieved.
But, given that the
cells and sectors of the cellular system are typically in fixed locations,
often dictated by where
towers can be placed, even such limited benefits are difficult to exploit if
user density (or data
rate demands) at a given time does not match up well with tower/sector
placement. A cellular
smart phone user often experiences the consequence of this today where the
user may be talking
on the phone or downloading a web page without any trouble at all, and then
after driving (or
even walking) to a new location will suddenly see the voice quality drop or
the web page slow to
a crawl, or even lose the connection entirely. But, on a different day, the
user may have the
exact opposite occur in each location. What the user is probably experiencing,
assuming the
environmental conditions are the same, is the fact that user density (or data
rate demands) is
highly variable, but the available total spectrum (and thereby total data
rate, using prior art
techniques) to be shared among users at a given location is largely fixed.
[0019] Further, prior art cellular systems rely upon using different
frequencies in different
adjacent cells, typically 3 different frequencies. For a given amount of
spectrum, this reduces the
available data rate by 3X.
[0020] So, in summary, prior art cellular systems may lose perhaps 3X in
spectrum
utilization due to cellularization, and may improve spectrum utilization by
perhaps 3X through
sectorization and perhaps 3X more through MU-MIMO techniques, resulting in a
net 3*3/3 = 3X
potential spectrum utilization. Then, that bandwidth is typically divided up
among users in the
time domain, based upon what sector of what cell the users fall into at a
given time. There are
even further inefficiencies that result due to the fact that a given user's
data rate demands are
typically independent of the user's location, but the available data rate
varies depending on the
link quality between the user and the base station. For example, a user
further from a cellular
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
base station will typically have less available data rate than a user closer
to a base station. Since
the data rate is typically shared among all of the users in a given cellular
sector, the result of this
is that all users are impacted by high data rate demands from distant users
with poor link quality
(e.g. on the edge of a cell) since such users will still demand the same
amount of data rate, yet
they will be consuming more of the shared spectrum to get it.
[0021] Other proposed spectrum sharing systems, such as that used by WiFi
(e.g., 802.11b,
g, and n) and those proposed by the White Spaces Coalition, share spectrum
very inefficiently
since simultaneous transmissions by base stations within range of a user
result in interference,
and as such, the systems utilize collision avoidance and sharing protocols.
These spectrum
sharing protocols are within the time domain, and so, when there are a large
number of
interfering base stations and users, no matter how efficient each base station
itself is in spectrum
utilization, collectively the base stations are limited to time domain sharing
of the spectrum
among each other. Other prior art spectrum sharing systems similarly rely upon
similar methods
to mitigate interference among base stations (be they cellular base stations
with antennas on
towers or small scale base stations, such as WiFi Access Points (APs)). These
methods include
limiting transmission power from the base station so as to limit the range of
interference,
beamforming (via synthetic or physical means) to narrow the area of
interference, time-domain
multiplexing of spectrum and/or MU-MIMO techniques with multiple clustered
antennas on the
user device, the base station or both. And, in the case of advanced cellular
networks in place or
planned today, frequently many of these techniques are used at once.
[0022] But, what is apparent by the fact that even advanced cellular
systems can achieve
only about a 3X increase in spectrum utilization compared to a single user
utilizing the spectrum
is that all of these techniques have done little to increase the aggregate
data rate among shared
users for a given area of coverage. In particular, as a given coverage area
scales in terms of users,
it becomes increasingly difficult to scale the available data rate within a
given amount of
spectrum to keep pace with the growth of users. For example, with cellular
systems, to increase
the aggregate data rate within a given area, typically the cells are
subdivided into smaller cells
(often called nano-cells or femto-cells). Such small cells can become
extremely expensive given
the limitations on where towers can be placed, and the requirement that towers
must be placed in
a fairly structured pattern so as to provide coverage with a minimum of "dead
zones", yet avoid
interference between nearby cells using the same frequencies. Essentially, the
coverage area
must be mapped out, the available locations for placing towers or base
stations must be
identified, and then given these constraints, the designers of the cellular
system must make do
with the best they can. And, of course, if user data rate demands grow over
time, then the
designers of the cellular system must yet again remap the coverage area, try
to find locations for
6
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
towers or base stations, and once again work within the constraints of the
circumstances. And,
very often, there simply is no good solution, resulting in dead zones or
inadequate aggregate data
rate capacity in a coverage area. In other words, the rigid physical placement
requirements of a
cellular system to avoid interference among towers or base stations utilizing
the same frequency
results in significant difficulties and constraints in cellular system design,
and often is unable to
meet user data rate and coverage requirements.
100231 So-called prior art "cooperative" and "cognitive" radio systems seek
to increase the
spectral utilization in a given area by using intelligent algorithms within
radios such that they can
minimize interference among each other and/or such that they can potentially
"listen" for other
spectrum use so as to wait until the channel is clear. Such systems are
proposed for use
particularly in unlicensed spectrum in an effort to increase the spectrum
utilization of such
spectrum.
[0024] A mobile ad hoc network (MANET) (see http://en.wikipedia.org/wikii
Mobile_ad_hoc_network) is an example of a cooperative self-configuring network
intended to
provide peer-to-peer communications, and could be used to establish
communication among
radios without cellular infrastructure, and with sufficiently low-power
communications, can
potentially mitigate interference among simultaneous transmissions that arc
out of range of each
other. A vast number of routing protocols have been proposed and implemented
for MANET
systems (see http://en.wikipedia.org/wiki/List_of ad-hoc_routing_protocols for
a list of dozens
of routing protocols in a wide range of classes), but a common theme among
them is they are all
techniques for routing (e.g. repeating) transmissions in such a way to
minimize transmitter
interference within the available spectrum, towards the goal of particular
efficiency or reliability
paradigms.
100251 All of the prior art multi-user wireless systems seek to improve
spectrum utilization
within a given coverage area by utilizing techniques to allow for simultaneous
spectrum
utilization among base stations and multiple users. Notably, in all of these
cases, the techniques
utilized for simultaneous spectrum utilization among base stations and
multiple users achieve the
simultaneous spectrum use by multiple users by mitigating interference among
the waveforms to
the multiple users. For example, in the case of 3 base stations each using a
different frequency to
transmit to one of 3 users, there interference is mitigated because the 3
transmissions are at 3
different frequencies. In the case of sectorization from a base station to 3
different users, each
180 degrees apart relative to the base station, interference is mitigated
because the beamforming
prevents the 3 transmissions from overlapping at any user.
[0026] When such techniques are augmented with MU-MIMO, and, for example,
each base
station has 4 antennas, then this has the potential to increase downlink
throughput by a factor of
7
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
4, by creating four non-interfering spatial channels to the users in given
coverage area. But it is
still the case that some technique must be utilized to mitigate the
interference among multiple
simultaneous transmissions to multiple users in different coverage areas.
[0027] And, as previously discussed, such prior art techniques (e.g.
eellularization,
sectorization) not only typically suffer from increasing the cost of the multi-
user wireless system
and/or the flexibility of deployment, but they typically run into physical or
practical limitations
of aggregate throughput in a given coverage area. For example, in a cellular
system, there may
not be enough available locations to install more base stations to create
smaller cells. And, in an
MU-MIMO system, given the clustered antenna spacing at each base station
location, the limited
spatial diversity results in asymptotically diminishing returns in throughput
as more antennas are
added to the base station.
[0028] And further, in the case of multi-user wireless systems where the
user location and
density is unpredictable, it results in unpredictable (with frequently abrupt
changes) in
throughput, which is inconvenient to the user and renders some applications
(e.g. the delivery of
services requiring predictable throughput) impractical or of low quality.
Thus, prior art multi-
user wireless systems still leave much to be desired in terms of their ability
to provide
predictable and/or high-quality services to users.
[0029] Despite the extraordinary sophistication and complexity that has
been developed for
prior art multi-user wireless systems over time, there exist common themes:
transmissions are
distributed among different base stations (or ad hoc transceivers) and are
structured and/or
controlled so as to avoid the RF waveform transmissions from the different
base stations and/or
different ad hoc transceivers from interfering with each other at the receiver
of a given user.
[0030] Or, to put it another way, it is taken as a given that if a user
happens to receive
transmissions from more than one base station or ad hoc transceiver at the
same time, the
interference from the multiple simultaneous transmissions will result in a
reduction of the SNR
and/or bandwidth of the signal to the user which, if severe enough, will
result in loss of all or
some of the potential data (or analog information) that would otherwise have
been received by
the user.
[0031] Thus, in a multiuser wireless system, it is necessary to utilize one
or more spectrum
sharing approaches or another to avoid or mitigate such interference to users
from multiple base
stations or ad hoc transceivers transmitting at the same frequency at the same
time. There are a
vast number of prior art approaches to avoiding such interference, including
controlling base
stations' physical locations (e.g. cellularization), limiting power output of
base stations and/or ad
hoc transceivers (e.g. limiting transmit range), beamforming/sectorization,
and time domain
multiplexing. In short, all of these spectrum sharing systems seek to address
the limitation of
8
SUBSTITUTE SHEET (RULE 26)
multiuser wireless systems that when multiple base stations and/or ad hoc
transceivers transmitting
simultaneously at the same frequency are received by the same user, the
resulting interference reduces or
destroys the data throughput to the affected user. If a large percentage, or
all, of the users in the multi-user
wireless system are subject to interference from multiple base stations and/or
ad hoc transceivers (e.g. in
the event of the malfunction of a component of a multi-user wireless system),
then it can result in a
situation where the aggregate throughput of the multi-user wireless system is
dramatically reduced, or
even rendered non- functional.
[0032] Prior art multi-user wireless systems add complexity and introduce
limitations to wireless
networks and frequently result in a situation where a given user's experience
(e.g. available bandwidth,
latency, predictability, reliability) is impacted by the utilization of the
spectrum by other users in the area.
Given the increasing demands for aggregate bandwidth within wireless spectrum
shared by multiple
users, and the increasing growth of applications that can rely upon multi-user
wireless network reliability,
predictability and low latency for a given user, it is apparent that prior art
multi-user wireless technology
suffers from many limitations. Indeed, with the limited availability of
spectrum suitable for particular
types of wireless communications (e.g. at wavelengths that are efficient in
penetrating building walls), it
may be the case that prior art wireless techniques will be insufficient to
meet the increasing demands for
bandwidth that is reliable, predictable and low-latency.
[0033] Prior art related to the current invention describes beamforming
systems and methods for
null-steering in multiuser scenarios. Beamforming was originally conceived to
maximize received signal-
to-noise ratio (SNR) by dynamically adjusting phase and/or amplitude of the
signals (i.e., beamforming
weights) fed to the antennas of the array, thereby focusing energy toward the
user's direction. In multiuser
scenarios, beamforming can be used to suppress interfering sources and
maximize signal-to-interference-
plus-noise ratio (SINR). For example, when beamforming is used at the receiver
of a wireless link, the
weights are computed to create nulls in the direction of the interfering
sources. When beamforming is
used at the transmitter in multiuser downlink scenarios, the weights are
calculated to pre-cancel inter-user
interference and maximize the SINR to every user. Alternative techniques for
multiuser systems, such as
BD precoding, compute the precoding weights to maximize throughput in the
downlink broadcast
channel. The co-pending applications describe the foregoing techniques (see co-
pending applications for
specific citations).
SUMMARY OF THE INVENTION
[0033a] Accordingly, it is an object of this invention to at least
partially overcome some of the
disadvantages of the prior art.
9
CA 2872502 2019-04-25
10033b] Accordingly, in one of its aspects, this invention resides in a
multiuser (MU) multiple
antenna system (MAS) comprising: one or more centralized units communicatively
coupled to
multiple distributed transceiver stations or antennas via a network; the
network comprising
wireline or wireless links or a combination of both, employed as a backhaul
communication
channel; the one or more centralized units communicating with the distributed
transceiver stations
or antennas over the network to adaptively reconfigure communications between
the distributed
transceiver stations or antennas and users to compensate for Doppler effects
due to user mobility
or changes in the propagation environment; wherein the MU-MAS system comprises
one or more
sets of user equipment (UE), base transceiver stations (BTSs), controllers
(CTRs), centralized
processors (CPs) and base station networks (BSNs); and wherein the CP
adaptively selects the
BTSs to be used for low- or high-mobility UEs based on latency over the BSN.
[0033c] In a further aspect, the present invention resides in a method
implemented within a
multiuser (MU) multiple antenna system (MAS) to compensate for Doppler effects
comprising, the
MU-MAS system comprising at least one centralized unit communicatively coupled
to multiple
distributed base transceiver stations (BTSs) over a network, the method
comprising: measuring
Doppler velocity of a first mobile user relative to the plurality of BTSs; and
the centralized unit
communicating with the BTSs over the network to adaptively reconfigure
communications
between the BTSs and users, wherein adaptively reconfiguring includes
dynamically assigning the
first mobile user to a first BTS of the plurality of BTSs or to a first set of
BTSs based on the
measured Doppler velocity for the first BTS relative to other BTSs.
[0033d] In a further aspect, the present invention resides in a multiuser
(MU) multiple antenna
system (MAS) to compensate for Doppler effects comprising: a plurality of base
transceiver
stations (BTSs); a network coupling the plurality of BTSs to at least one
centralized processor
(CP); a first mobile user establishing a communication link with each of the
BTSs; the CP
communicating with the BTSs over the network to adaptively reconfigure
communications
between the BTSs and users, wherein adaptively reconfiguring includes
measuring Doppler
velocity of a first mobile user relative to each of the BTSs and dynamically
assigning the first
mobile user to a first BTS of the plurality of BTSs based on the measured
Doppler velocity for the
first BTS relative to other BTSs.
[0033e] In a further aspect, the present invention resides in a multiuser
(MU) multiple antenna
system (MAS) comprising: one or more centralized units communicatively coupled
to multiple
distributed transceiver stations or antennas via a network; the network
comprising wireline or
wireless links or a combination of both, employed as a backhaul communication
channel; the one
or more centralized units communicating with the distributed transceiver
stations or antennas over
the network to adaptively reconfigure communications between the distributed
transceiver stations
or antennas and users to compensate for Doppler effects due to user mobility
or changes in the
9a
CA 2872502 2018-04-30
propagation environment; wherein the MU-MAS system comprises one or more sets
of user
equipment (UE), base transceiver stations (BTSs), controllers (CTRs),
centralized processors
(CPs) and base station networks (BSNs); and wherein the CP adaptively selects
the BTSs to be
used for low- or high-mobility UEs based on the Doppler velocities of every
BTS-UE link.
[00331] In a further aspect, the present invention resides in a multiuser
(MU) multiple antenna
system (MAS) comprising: one or more centralized units communicatively coupled
to multiple
distributed transceiver stations or antennas via a network; the network
comprising wireline or
wireless links or a combination of both, employed as a backhaul communication
channel; the one
or more centralized units communicating with the distributed transceiver
stations or antennas over
the network to adaptively reconfigure communications between the distributed
transceiver stations
or antennas and users to compensate for Doppler effects due to user mobility
or changes in the
propagation environment; wherein the MU-MAS system comprises one or more sets
of user
equipment (UE), base transceiver stations (BTSs), controllers (CTRs),
centralized processors
(CPs) and base station networks (BSNs); and wherein linear prediction is
employed to estimate the
CSI or MU-MAS precoding weights in the future, thereby eliminating the adverse
effect of
Doppler on the performance of the MU-MAS.
[0033g] Further aspects of the invention will become apparent upon reading
the following
detailed description and drawings, which illustrate the invention and
preferred embodiments of the
invention.
BRIEF DESCRIPTION OF THE DRAWINGS
[0034] A better understanding of the present invention can be obtained from
the following
detailed description in conjunction with the drawings, in which:
9b
CA 2872502 2018-04-30
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[0035] FIG. 1 illustrates a main DIDO cluster surrounded by neighboring
DIDO clusters in
one embodiment of the invention.
[0036] FIG. 2 illustrates frequency division multiple access (FDMA)
techniques employed
in one embodiment of the invention.
[0037] FIG. 3 illustrates time division multiple access (TDMA) techniques
employed in
one embodiment of the invention.
[0038] FIG. 4 illustrates different types of interfering zones addressed in
one embodiment
of the invention.
[0039] FIG. 5 illustrates a framework employed in one embodiment of the
invention.
[0040] FIG. 6 illustrates a graph showing SER as a function of the SNR,
assuming
SIR=10dB for the target client in the interfering zone.
[0041] FIG. 7 illustrates a graph showing SER derived from two IDCI-
precoding
techniques.
[0042] FIG. 8 illustrates an exemplary scenario in which a target client
moves from a main
DIDO cluster to an interfering cluster.
[0043] FIG. 9 illustrates the signal-to-interference-plus-noise ratio
(S1NR) as a function of
distance (D).
[0044] FIG. 10 illustrates the symbol error rate (SER) performance of the
three scenarios
for 4-QAM modulation in flat-fading narrowband channels.
[0045] FIG. 11 illustrates a method tor IDCI precoding according to one
embodiment of
the invention.
[0046] FIG. 12 illustrates the SINR variation in one embodiment as a
function of the
client's distance from the center of main DIDO clusters.
[0047] FIG. 13 illustrates one embodiment in which the SER is derived for 4-
QAM
modulation.
100481 FIG. 14 illustrates one embodiment of the invention in which a
finite state machine
implements a handoff algorithm.
[0049] FIG. 15 illustrates depicts one embodiment of a handoff strategy in
the presence of
shadowing.
[0050] FIG. 16 illustrates a hysteresis loop mechanism when switching
between any two
states in Fig. 93.
[0051] FIG. 17 illustrates one embodiment of a DIDO system with power
control.
[0052] FIG. 18 illustrates the SER versus SNR assuming four DIDO transmit
antennas and
four clients in different scenarios.
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[0053] FIG. 19 illustrates MPE power density as a function of distance from
the source of
RF radiation for different values of transmit power according to one
embodiment of the
invention.
[0054] FIGS. 20a-b illustrate different distributions of low-power and high-
power DIDO
distributed antennas.
[0055] FIGS. 21a-b illustrate two power distributions corresponding to the
configurations
in Figs. 20a and 20b, respectively.
[0056] FIG. 22a-b illustrate the rate distribution for the two scenarios
shown in Figs. 99a
and 99b, respectively.
[0057] FIG. 23 illustrates one embodiment of a DIDO system with power
control.
[0058] FIG. 24 illustrates one embodiment of a method which iterates across
all antenna
groups according to Round-Robin scheduling policy for transmitting data.
[0059] FIG. 25 illustrates a comparison of the uncoded SER performance of
power control
with antenna grouping against conventional eigenmode selection in U.S. Patent
No. 7,636,381.
[0060] FIGS. 26a-c illustrate three scenarios in which BD precoding
dynamically adjusts
the precoding weights to account for different power levels over the wireless
links between
DIDO antennas and clients.
[0061] FIG. 27 illustrates the amplitude of low frequency selective
channels (assuming
= 1) over delay domain or instantaneous PDP (upper plot) and frequency domain
(lower plot)
for DIDO 2x2 systems
[0062] FIG. 28 illustrates one embodiment of a channel matrix frequency
response for
DIDO 2x2, with a single antenna per client.
[0063] FIG. 29 illustrates one embodiment of a channel matrix frequency
response for
DIDO 2x2, with a single antenna per client for channels characterized by high
frequency
selectivity (e.g., with )6' = 0.1).
[0064] FIG. 30 illustrates exemplary SER for different QAM schemes (i.e., 4-
QAM, 16-
QAM, 64-QAM).
[0065] FIG. 31 illustrates one embodiment of a method for implementing link
adaptation
(LA) techniques.
[0066] FIG. 32 illustrates SER performance of one embodiment of the link
adaptation (LA)
techniques.
[0067] FIG. 33 illustrates the entries of the matrix in equation (28) as a
function of the
OFDM tone index for DIDO 2x2 systems with Ar = 64 and Lo = 8.
[0068] FIG. 34 illustrates the SER versus SNR for Lo = 8, M=Nt=2 transmit
antennas and
a variable number of P.
11
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[0069] FIG. 35 illustrates the SER performance of one embodiment of an
interpolation
method for different DIDO orders and Lo = 16.
[0070] FIG. 36 illustrates one embodiment of a system which employs super-
clusters,
DIDO-clusters and user-clusters.
[0071] FIG. 37 illustrates a system with user clusters according to one
embodiment of the
invention.
[0072] FIGS. 38a-b illustrate link quality metric thresholds employed in
one embodiment
of the invention.
[0073] FIGS. 39-41 illustrate examples of link-quality matrices for
establishing user
clusters.
[0074] FIG. 42 illustrates an embodiment in which a client moves across
different different
DIDO clusters.
[0075] FIGS. 43-46 illustrate relationships between the resolution of
spherical arrays and
their area A in one embodiment of the invention.
[0076] FIG. 47 illustrates the degrees of freedom of MIMO systems in
practical indoor and
outdoor propagation scenarios.
[0077] FIG. 48 illustrates the degrees of freedom in DIDO systems as a
function of the
array diameter.
[0078] FIG. 49 illustrates one embodiment which includes multiple
centralized processors
(CP) and distributed nodes (DN) that communicate via wirclinc or wireless
connections.
[0079] FIG. 50 illustrates one embodiment in which CPs exchange control
information with
the unlicensed DNs and reconfigure them to shut down the frequency bands for
licensed use.
[0080] FIG. 51 illustrates one embodiment in which an entire spectrum is
allocated to thc
new service and control information is used by the CPs to shut down all
unlicensed DNs to avoid
interference with the licensed DNs.
[0081] FIG. 52 illustrates one embodiment of a cloud wireless system
including multiple
CPs, distributed nodes and a network interconnecting the CPs to the DNs.
[0082] FIGS. 53-59 illustrate embodiments of a multiuser (MU) multiple
antenna system
(MAS) that adaptively reconfigures parameters to compensate for Doppler
effects due to user
mobility or changes in the propagation environment.
[0083] FIG 60 illustrates a plurality of BTSs, some of which have good SNR
and some of
which have low Doppler with respect to a UE.
[0084] FIG. 61 illustrates one embodiment of a matrix containing values of
SNR and
Doppler recorded by a CP for a plurality of BTS-UE links.
12
SUBSTITUTE SHEET (RULE 26)
[0085] FIG. 62 illustrates the channel gain (or CS!) at different times in
accordance with
one embodiment of the invention.
DETAILED DESCRIPTION
[0086] One solution to overcome many of the above prior art limitations is
an embodiment
of Distributed-Input Distributed-Output (DIDO) technology. DIDO technology is
described in
the following patents and patent applications, all of which are assigned the
assignee of the
present patent. The present application is a continuation in part (CIP) to
these patent
applications. These patents and applications are sometimes referred to
collectively herein
as the "related patents and applications":
[0087] U.S. Application Serial No. 13/232,996, filed September 14, 2011,
entitled "Systems
And Methods To Exploit Areas of Coherence in Wirless Systems"
100881 U.S. Application Serial No. 13/233,006, filed filed September 14,
2011, entitled
"Systems and Methods for Planned Evoluation and Obsolescence of Multiuser
Spectrum,"
[0089] U.S. Application Serial No. 12/917,257, filed November 1, 2010,
entitled "Systems
And Methods To Coordinate Transmissions In Distributed Wireless Systems Via
User
Clustering"
[0090] U.S. Application Serial No. 12/802,988, filed June 16, 2010,
entitled "Interference
Management, Handoff, Power Control And Link Adaptation In Distributed-Input
Distributed-
Output (DIDO) Communication Systems"
[0091] U.S. Application Serial No. 12/802,976, filed June 16, 2010,
entitled "System And
Method For Adjusting DIDO Interference Cancellation Based On Signal Strength
Measurements"
[0092] U.S. Application Serial No. 12/802,974, filed June 16, 2010,
entitled "System And
Method For Managing Inter-Cluster Handoff Of Clients Which Traverse Multiple
DIDO
Clusters"
100931 U.S. Application Serial No. 12/802,989, filed June 16, 2010,
entitled "System And
Method For Managing Handoff Of A Client Between Different Distributed-Input-
Distributed-
Output (DIDO) Networks Based On Detected Velocity Of The Client"
[0094] U.S. Application Serial No. 12/802,958, filed June 16, 2010,
entitled "System And
Method For Power Control And Antenna Grouping In A Distributed-Input-
Distributed-Output
(DIDO) Network"
[0095] U.S. Application Serial No. 12/802,975, filed June 16, 2010,
entitled "System And
Method For Link adaptation In DIDO Multicarrier Systems"
100961 U.S. Application Serial No. 12/802,938, filed June 16, 2010,
entitled "System And
Method For DIDO Precoding Interpolation In Multicarrier Systems"
13
CA 2872502 2019-04-25
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[0097] U.S. Application Serial No. 12/630,627, filed December 2, 2009,
entitled -System
and Method For Distributed Antenna Wireless Communications"
[0098] U.S. Patent No. 7,599,420, filed August 20, 2007, issued Oct. 6,
2009, entitled
"System and Method for Distributed Input Distributed Output Wireless
Communication";
[0099] U.S. Patent No. 7,633,994, filed August 20, 2007, issued Dec. 15,
2009, entitled
"System and Method for Distributed Input Distributed Output Wireless
Communication";
[00100] U.S. Patent No. 7,636,381, filed August 20, 2007, issued Dec. 22,
2009, entitled
"System and Method for Distributed Input Distributed Output Wireless
Communication";
[00101] U.S. Application Serial No. 12/143,503, filed June 20, 2008
entitled, "System and
Method For Distributed Input-Distributed Output Wireless Communications";
[00102] U.S. Application Serial No. 11/256,478, filed October 21, 2005
entitled "System and
Method For Spatial-Multiplexed Tropospheric Scatter Communications";
[00103] U.S. Patent No. 7,418,053, filed July 30, 2004, issued August 26,
2008, entitled
"System and Method for Distributed Input Distributed Output Wireless
Communication";
[00104] U.S. Application Serial No. 10/817,731, filed April 2,2004 entitled
"System and
Method For Enhancing Near Vertical Incidence Skywave ("NVIS") Communication
Using
Space-Time Coding.
[00105] To reduce the size and complexity of the present patent
application, the disclosure of
some of the related patents and applications is not explicitly set forth
below. Please see the
related patents and applications tor a full detailed description of the
disclosure.
[00106] Note that section I below (Disclosure From Related Application
Serial No.
12/802,988) utilizes its own set of endnotes which refer to prior art
references and prior
applications assigned to the assignee of the present application. The endnote
citations are listed
at the end of section I (just prior to the heading for Section II). Citations
in Section II uses may
have numerical designations for its citations which overlap with those used in
Section I even
through these numerical designations identify different references (listed at
the end of Section
II). Thus, references identified by a particular numerical designation may be
identified within
the section in which the numerical designation is used.
I. Disclosure From Related Application Serial No. 12/802,988
1. Methods to Remove Inter-cluster Interference
1001211 Described below are wireless radio frequency (RF) communication
systems and
methods employing a plurality of distributed transmitting antennas to create
locations in space
with zero RF energy. When M transmit antennas are employed, it is possible to
create up to (M-
1) points of zero RF energy in predefined locations. In one embodiment of the
invention, the
points of zero RF energy are wireless devices and the transmit antennas are
aware of the channel
14
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
state information (CSI) between the transmitters and the receivers. In one
embodiment, the CSI
is computed at the receivers and fed back to the transmitters. In another
embodiment, the CSI is
computed at the transmitter via training from the receivers, assuming channel
reciprocity is
exploited. The transmitters may utilize the CSI to determine the interfering
signals to be
simultaneously transmitted. In one embodiment, block diagonalization (BD)
precoding is
employed at the transmit antennas to generate points of zero RF energy.
[00122] The system and methods described herein differ from the
conventional
receive/transmit beamforming techniques described above. In fact, receive
beamforming
computes the weights to suppress interference at the receive side (via null-
steering), whereas
some embodiments of the invention described herein apply weights at the
transmit side to create
interference patters that result in one or multiple locations in space with
"zero RF energy."
Unlike conventional transmit beamforming or BD precoding designed to maximize
signal quality
(or SINR) to every user or downlink throughput, respectively, the systems and
methods
described herein minimize signal quality under certain conditions and/or from
certain
transmitters, thereby creating points of zero RF energy at the client devices
(sometimes referred
to herein as "users"). Moreover, in the context of distributed-input
distributed-output (DIDO)
systems (described in our related patents and applications), transmit antennas
distributed in space
provide higher degrees of freedom (i.e., higher channel spatial diversity)
that can be exploited to
create multiple points of zero RF energy and/or maximum SINR to different
users. For example,
with M transmit antennas it is possible to create up to (M-1) points of RI'
energy. By contrast,
practical beamforming or BD multiuser systems are typically designed with
closely spaced
antennas at the transmit side that limit the number of simultaneous users that
can be serviced
over the wireless link, for any number of transmit antennas M.
[00123] Consider a system with M transmit antennas and K users, with K<M.
We assume the
transmitter is aware of the CSI (H E Ci(xm) between the M transmit antennas
and K users. For
simplicity, every user is assumed to be equipped with single antenna, but the
same method can
be extended to multiple receive antennas per user. The precoding weights (w E
Cmxl) that create
zero RF energy at the K users' locations are computed to satisfy the following
condition
Hw , ()Ku_
where OK is the vector with all zero entries and H is the channel matrix
obtained by
combining the channel vectors (hk E C"m) from the M transmit antennas to the K
users as
hi -
H = Ilk.
hK_
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
In one embodiment, singular value decomposition (SVD) of the channel matrix H
is
computed and the precoding weight w is defined as the right singular vector
corresponding to
the null subspace (identified by zero singular value) of H.
The transmit antennas employ the weight vector defined above to transmit RF
energy, while
creating K points of zero RF energy at the locations of the K users such that
the signal
received at the kth user is given by
rk = hkwsk + nk = 0 + nk
where nk E exi is the additive white Gaussian noise (AWGN) at the kth user.
In one embodiment, singular value decomposition (SVD) of the channel matrix H
is computed
and the precoding weight w is defined as the right singular vector
corresponding to the null
subspace (identified by zero singular value) of H.
[00124] In another embodiment, the wireless system is a DIDO system and
points of zero RF
energy are created to pre-cancel interference to the clients between different
DIDO coverage
areas. In U.S. Application Serial No. 12/630,627, a DIDO system is described
which includes:
= DIDO clients
= DIDO distributed antennas
= DIDO base transceiver stations (BTS)
= DIDO base station network (BSN)
Every BTS is connected via the BSN to multiple distributed antennas that
provide service to
given coverage area called DIDO cluster. In the present patent application we
describe a system
and method for removing interference between adjacent DIDO clusters. As
illustrated in Figure
1, we assume the main DIDO cluster hosts the client (i.e. a user device served
by the multi-user
DIDO system) affected by interference (or target client) from the neighbor
clusters.
[00125] In one embodiment, neighboring clusters operate at different
frequencies according
to frequency division multiple access (FDMA) techniques similar to
conventional cellular
systems. For example, with frequency reuse factor of 3, the same carrier
frequency is reused
every third DIDO cluster as illustrated in Figure 2. In Figure 2, the
different carrier frequencies
are identified as F1, F2 and F3. While this embodiment may be used in some
implementations,
this solution yields loss in spectral efficiency since the available spectrum
is divided in multiple
subbands and only a subset of DIDO clusters operate in the same subband.
Moreover, it requires
complex cell planning to associate different DIDO clusters to different
frequencies, thereby
preventing interference. Like prior art cellular systems, such cellular
planning requires specific
placement of antennas and limiting of transmit power to as to avoid
interference between clusters
using the same frequency.
16
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[00126] In another embodiment, neighbor clusters operate in the same
frequency band, but at
different time slots according to time division multiple access (TDMA)
technique. For example,
as illustrated in Figure 3 DIDO transmission is allowed only in time slots T1,
T2, and T3 for
certain clusters, as illustrated. Time slots can be assigned equally to
different clusters, such that
different clusters are scheduled according to a Round-Robin policy. If
different clusters are
characterized by different data rate requirements (i.e., clusters in crowded
urban environments as
opposed to clusters in rural areas with fewer number of clients per area of
coverage), different
priorities are assigned to different clusters such that more time slots are
assigned to the clusters
with larger data rate requirements. While TDMA as described above may be
employed in one
embodiment of the invention, a TDMA approach may require time synchronization
across
different clusters and may result in lower spectral efficiency since
interfering clusters cannot use
the same frequency at the same time.
[00127] In one embodiment, all neighboring clusters transmit at the same
time in the same
frequency band and use spatial processing across clusters to avoid
interference. In this
embodiment, the multi-cluster DIDO system: (i) uses conventional DIDO
precoding within the
main cluster to transmit simultaneous non-interfering data streams within the
same frequency
band to multiple clients (such as described in the related patents and
applications, including
7,599,420; 7,633,994; 7,636,381; and Application Serial No. 12/143,503); (ii)
uses DIDO
precoding with interference cancellation in the neighbor clusters to avoid
interference to the
clients lying in the interfering zones 801U in Figure 4, by creating points of
zero radio frequency
(RF) energy at the locations of the target clients. If a target client is in
an interfering zone 410, it
will receive the sum of the RF containing the data stream from the main
cluster 411 and the zero
RF energy from the interfering cluster 412-413, which will simply be the RF
containing the data
stream from the main cluster. Thus, adjacent clusters can utilize the same
frequency
simultaneously without target clients in the interfering zone suffering from
interference.
1001281 In practical systems, the performance of DIDO precoding may be
affected by
different factors such as: channel estimation error or Doppler effects
(yielding obsolete channel
state information at the DIDO distributed antennas); intermodulation
distortion (IMD) in
multicarrier DIDO systems; time or frequency offsets. As a result of these
effects, it may be
impractical to achieve points of zero RF energy. However, as long as the RF
energy at the target
client from the interfering clusters is negligible compared to the RF energy
from the main
cluster, the link performance at the target client is unaffected by the
interference. For example,
let us assume the client requires 20dB signal-to-noise ratio (SNR) to
demodulate 4-QAM
constellations using forward error correction (FEC) coding to achieve target
bit error rate (BER)
of 10-6. If the RF energy at the target client received from the interfering
cluster is 20dB below
17
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
the RF energy received from the main cluster, the interference is negligible
and the client can
demodulate data successfully within the predefined BER target. Thus, the term
"zero RF energy"
as used herein does not necessarily mean that the RF energy from interfering
RF signals is zero.
Rather, it means that the RF energy is sufficiently low relative to the RF
energy of the desired
RF signal such that the desired RF signal may be received at the receiver.
Moreover, while
certain desirable thresholds for interfering RF energy relative to desired RF
energy are described,
the underlying principles of the invention are not limited to any particular
threshold values.
[00129] There
are different types of interfering zones 8010 as shown in Figure 4. For
example, "type A" zones (as indicated by the letter "A" in Figure 80) are
affected by interference
from only one neighbor cluster, whereas "type B" zones (as indicated by the
letter "B") account
for interference from two or multiple neighbor clusters.
[00130] Figure
5 depicts a framework employed in one embodiment of the invention. The
dots denote DIDO distributed antennas, the crosses refer to the DIDO clients
and the arrows
indicate the directions of propagation of RF energy. The DIDO antennas in the
main cluster
transmit precoded data signals to the clients MC 501 in that cluster.
Likewise, the DIDO
antennas in the interfering cluster serve the clients IC 502 within that
cluster via conventional
DIDO precoding. The green cross 503 denotes the target client TC 503 in the
interfering zone.
The DIDO antennas in the main cluster 511 transmit precoded data signals to
the target client
(black arrows) via conventional DIDO precoding. The DIDO antennas in the
interfering cluster
512 use precoding to create zero RI energy towards the directions of the
target client 503 (green
arrows).
[00131] The
received signal at target client k in any interfering zone 410A, B in Figure 4
is
given by
rk = HkWksk + Hk ZuU=1 Wu Su + EcC=.1 c,i S c,i nk (1)
u#k
where k=1,...,K, with K being the number of clients in the interfering zone
8010A, B, U is the
number of clients in the main DIDO cluster, C is the number of interfering
DIDO clusters 412-
413 and Ic is the number of clients in the interfering cluster c. Moreover, rk
E CNxm is the vector
containing the receive data streams at client k, assuming M transmit DIDO
antennas and N
receive antennas at the client devices; sk E CNx1 is the vector of transmit
data streams to client k
in the main DIDO cluster; su E CNx1 is the vector of transmit data streams to
client u in the main
DIDO cluster; sc,, E CNxi- is the vector of transmit data streams to client i
in the cth interfering
DIDO cluster; nk E CNx1 is the vector of additive white Gaussian noise (AWGN)
at the N
receive antennas of client k; Hk E CNxm is the DIDO channel matrix from the M
transmit DIDO
antennas to the N receive antennas at client k in the main DIDO cluster; Hc,k
E CNxm is the
18
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
DIDO channel matrix from the M transmit DIDO antennas to the Nreceive antennas
t client kin
the cth interfering DIDO cluster; Wk E CmxN is the matrix of DIDO precoding
weights to client k
in the main DIDO cluster; Wk E CillixN is the matrix of DIDO precoding weights
to client u in the
main DIDO cluster; Wo E C' is the matrix of DIDO precoding weights to client i
in the cth
interfering DIDO cluster.
[00132] To
simplify the notation and without loss of generality, we assume all clients
are
equipped with N receive antennas and there are M DIDO distributed antennas in
every DIDO
cluster, with M > (N = U) and M > (N = Is),Vc = 1, ..., C. If M is larger than
the total number of
receive antennas in the cluster, the extra transmit antennas are used to pre-
cancel interference to
the target clients in the interfering zone or to improve link robustness to
the clients within the
same cluster via diversity schemes described in the related patents and
applications, including
7,599,420; 7,633,994; 7,636,381; and Application Serial No. 12/143,503.
[00133] The
DIDO precoding weights are computed to pre-cancel inter-client interference
within the same DIDO cluster. For example, block diagonalization (BD)
precoding described in
the related patents and applications, including 7,599,420; 7,633,994;
7,636,381; and Application
Serial No. 12/143,503 and [7] can be used to remove inter-client interference,
such that the
following condition is satisfied in the main cluster
Hkwu = oNxN; V u = 1, , U; with u k. (2)
The precoding weight matrices in the neighbor DIDO clusters are designedsuch
that the
following condition is satisfied
= oN xN ; V c = 1, C and V i = 1, ...,I. (3)
To compute the precoding matrices W, the downlink channel from the A/ transmit
antennas to
the Ic clients in the interfering cluster as well as to client k in the
interfering zone is estimated
and the precoding matrix is computed by the DIDO BTS in the interfering
cluster. If BD method
is used to compute the precoding matrices in the interfering clusters, the
following effective
channel matrix is built to compute the weights to the ith client in the
neighbor clusters
= IHJ,k1
(4)
" [1-1c,i
where fi is the matrix obtained from the channel matrix tic C Casi'ic)xm for
the interfering
cluster c, where the rows corresponding to the ith client are removed.
Substituting conditions (2) and (3) into (1), we obtain the received data
streams for target client
k, where intra-cluster and inter-cluster interference is removed
rk = HkWksk nk. (5)
The precoding weights Wc,i in (1) computed in the neighbor clusters are
designed to transmit
precoded data streams to all clients in those clusters, while pre-cancelling
interference to the
19
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
target client in the interfering zone. The target client receives precoded
data only from its main
cluster. In a different embodiment, the same data stream is sent to the target
client from both
main and neighbor clusters to obtain diversity gain. In this case, the signal
model in (5) is
expressed as
rk = (Hk Wk d-EcC=1 Hc,k141c,k)Sk + Ilk (6)
where Wc,k is the DIDO precoding matrix from the DIDO transmitters in the Cth
cluster to the
target client k in thc interfering zone. Note that the method in (6) requires
time synchronization
across neighboring clusters, which may be complex to achieve in large systems,
but nonetheless,
is quite feasible if the diversity gain benefit justifies the cost of
implementation.
[00134] We
begin by evaluating the performance of the proposed method in terms of symbol
error rate (SER) as a function of the signal-to-noise ratio (SNR). Without
loss of generality, we
define the following signal model assuming single antenna per client and
reformulate (I) as
rk = SMIR hkwk sk + JiTii hc,k EL, we,, sc,j + nk (7)
where INR is the interference-to-noise ratio defined as INR=SNR/SIR and SIR is
the signal-to-
interference ratio.
[00135] Figure
6 shows the SER as a function of the SNR, assuming SIR=10dB for the
target client in the interfering zone. Without loss of generality, we measured
the SER for 4-QAM
and 16-QAM without forwards error correction (FEC) coding. We fix the target
SER to 1% for
uncoded systems. This target corresponds to different values of SNR depending
on the
modulation order (i.e., SNR=20dB for 4-QAM and SNR=28dB for 16-QAM). Lower SER
targets can be satisfied for the same values of SNR when using FEC coding due
to coding gain.
We consider the scenario of two clusters (one main cluster and one interfering
cluster) with two
DIDO antennas and two clients (equipped with single antenna each) per cluster.
One of the
clients in the main cluster lies in the interfering zone. We assume flat-
fading narrowband
channels, but the following results can be extended to frequency selective
multicarrier (OFDM)
systems, where each subcarrier undergoes flat-fading. We consider two
scenarios: (i) one with
inter-DIDO-duster interference (IDCI) where the precoding weights wo are
computed without
accounting for the target client in the interfering zone; and (ii) the other
where the IDCI is
removed by computing the weights wo, to cancel IDCI to the target client. We
observe that in
presence of IDCI the SER is high and above the predefined target. With IDCI-
precoding at the
neighbor cluster the interference to the target client is removed and the SER
targets are reached
for SNR>20dB.
[00136] The
results in Figure 6 assumes IDCI-precoding as in (5). If IDCI-precoding at the
neighbor clusters is also used to precode data streams to the target client in
the interfering zone
as in (6), additional diversity gain is obtained. Figure 7 compares the SER
derived from two
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
techniques: (i) "Method 1" using the IDCI-precoding in (5); (ii) "Method 2-
employing IDCI-
precoding in (6) where the neighbor clusters also transmit precoded data
stream to the target
client. Method 2 yields ¨3dB gain compared to conventional IDCI-precoding due
to additional
array gain provided by the DIDO antennas in the neighbor cluster used to
transmit precoded data
stream to the target client. More generally, the array gain of Method 2 over
Method 1 is
proportional to 10*loglO(C+1), where C is the number of neighbor clusters and
the factor "1"
refers to the main cluster.
[00137] Next,
we evaluate the performance of the above method as a function of the target
client's location with respect to the interfering zone. We consider one simple
scenario where a
target client 8401 moves from the main DIDO cluster 802 to the interfering
cluster 803, as
depicted in Figure 8. We assume all DIDO antennas 812 within the main cluster
802 employ BD
precoding to cancel intra-cluster interference to satisfy condition (2). We
assume single
interfering DIDO cluster, single receiver antenna at the client device 801 and
equal pathloss from
all DIDO antennas in the main or interfering cluster to the client (i.e., DIDO
antennas placed in
circle around the client). We use one simplified pathloss model with pathloss
exponent 4 (as in
typical urban environments) [11].
The analysis hereafter is based on the following simplified signal model that
extends (7) to
account for pathloss
SNR.D4 SNR.D4
rk = hkwksk + _\1()4 hc.k wc.i sc.i + Thk (8)
where the signal-to-interference (SIR) is derived as SIR=((1-D)/D)4. In
modeling the IDCI, we
consider three scenarios: i) ideal case with no IDCI; ii) IDCI pre-cancelled
via BD precoding in
the interfering cluster to satisfy condition (3); iii) with IDCI, not pre-
cancelled by the neighbor
cluster.
[00138] Figure
9 shows the signal-to-interference-plus-noise ratio (SINR) as a function of D
(i.e., as the target client moves from the main cluster 802 towards the DIDO
antennas 813 in the
interfering cluster 8403). The SINR is derived as the ratio of signal power
and interference plus
noise power using the signal model in (8). We assume that D0=0.1 and SNR=50dB
for D=Do. In
absence of IDCI the wireless link performance is only affected by noise and
the SINR decreases
due to pathless. In presence of IDCI (i.e., without IDCI-precoding) the
interference from the
DIDO antennas in the neighbor cluster contributes to reduce the SINR.
[00139] Figure
10 shows the symbol error rate (SER) performance of the three scenarios
above for 4-QAM modulation in flat-fading narrowband channels. These SER
results correspond
to the SINR in Figure 9. We assume SER threshold of 1% for uncoded systems
(i.e., without
FEC) corresponding to SINR threshold SINRT=20dB in Figure 9. The SINR
threshold depends
21
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
on the modulation order used for data transmission. Higher modulation orders
are typically
characterized by higher SINRT to achieve the same target error rate. With FEC,
lower target
SER can be achieved for the same SINR value due to coding gain. In case of
IDCI without
precoding, the target SER is achieved only within the range D<0.25. With IDCI-
precoding at the
neighbor cluster the range that satisfies the target SER is extended up to
D<0.6. Beyond that
range, the SINR increases due to pathloss and the SER target is not satisfied.
[00140] One
embodiment of a method for IDCI precoding is shown in Figure 11 and
consists of the following steps:
= SIR estimate 1101: Clients estimate the signal power from the main DIDO
cluster
(i.e., based on received precoded data) and the interference-plus-noise signal
power
from the neighbor DIDO clusters. In single-carrier DIDO systems, the frame
structure
can be designed with short periods of silence. For example, periods of silence
can be
defined between training for channel estimation and precoded data
transmissions
during channel state information (CSI) feedback. In one embodiment, the
interference-plus-noise signal power from neighbor clusters is measured during
the
periods of silence from the DIDO antennas in the main cluster. In practical
DIDO
multicarrier (OFDM) systems, null tones are typically used to prevent direct
current
(DC) offset and attenuation at the edge of the band due to filtering at
transmit and
receive sides. In another embodiment employing multicarrier systems, the
interference-plus-noise signal power is estimated from the null tones.
Correction
factors can be used to compensate for transmit/receive filter attenuation at
the edge of
the band. Once the signal-plus-interference-and-noise power (Ps) from the main
cluster and the interference-plus-noise power from neighbor clusters (PIN) are
estimated, the client computes the SINR as
-PIN
SINR ¨ Ps (9)
PIN
Alternatively, the SINR estimate is derived from the received signal strength
indication (RSSI) used in typical wireless communication systems to measure
the
radio signal power.
We observe the metric in (9) cannot discriminate between noise and
interference
power level. For example, clients affected by shadowing (i.e., behind
obstacles that
attenuate the signal power from all DIDO distributed antennas in the main
cluster) in
interference-free environments may estimate low SINR even though they are not
affected by inter-cluster interference.
A more reliable metric for the proposed method is the SIR computed as
22
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
SIR = Ps-PIN (10)
PIN-PN
where PN is the noise power. In practical multicarrier OFDM systems, the noise
power PN in (10) is estimated from the null tones, assuming all DIDO antennas
from
main and neighbor clusters use the same set of null tones. The interference-
plus-noise
power (PIN), is estimated from the period of silence as mentioned above.
Finally, the
signal-plus-interference-and-noise power (Ps) is derived from the data tones.
From
these estimates, the client computes the SIR in (10).
= Channel estimation at neighbor clusters 1102-1103: If the estimated SIR
in (10) is
below predefined threshold (SIR"), determined at 8702 in Figure 11, the client
starts
listening to training signals from neighbor clusters. Note that SIRT depends
on the
modulation and FEC coding scheme (MCS) used for data transmission. Different
SIR targets are defined depending on the client's MCS. When DIDO distributed
antennas from different clusters are time-synchronized (i.e., locked to the
same pulse-
per-second, PPS, time reference), the client exploits the training sequence to
deliver
its channel estimates to the DTDO antennas in the neighbor clusters at R703
The
training sequence for channel estimation in the neighbor clusters are designed
to be
orthogonal to the training from the main cluster. Alternatively, when DIDO
antennas
in different clusters are not time-synchronized, orthogonal sequences (with
good
cross-correlation properties) are used for time synchronization in different
DIDO
clusters. Once the client locks to the time/frequency reference of the
neighbor
clusters, channel estimation is carried out at 1103.
= IDCI Precoding 1104: Once the channel estimates are available at the DIDO
BTS in
the neighbor clusters, IDCI-precoding is computed to satisfy the condition in
(3). The
DIDO antennas in the neighbor clusters transmit precoded data streams only to
the
clients in their cluster, while pre-cancelling interference to the clients in
the
interfering zone 410 in Figure 4. We observe that if the client lies in the
type B
interfering zone 410 in Figure 4, interference to the client is generated by
multiple
clusters and DC I-precoding is carried out by all neighbor clusters at the
same time.
Methods for Handoff
[00141]
Hereafter, we describe different handoff methods for clients that move across
DIDO
clusters populated by distributed antennas that are located in separate areas
or that provide
different kinds of services (i.e., low- or high-mobility services).
a. Handoff Between Adjacent DIDO Clusters
23
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[00142] In one embodiment, the IDCI-precoder to remove inter-cluster
interference described
above is used as a baseline for handoff methods in DIDO systems. Conventional
handoff in
cellular systems is conceived for clients to switch seamlessly across cells
served by different
base stations. In DIDO systems, handoff allows clients to move from one
cluster to another
without loss of connection.
[00143] To illustrate one embodiment of a handoff strategy for DIDO
systems, we consider
again the example in Figure 8 with only two clusters 802 and 803. As the
client 801 moves from
the main cluster (Cl) 802 to the neighbor cluster (C2) 803, one embodiment of
a handoff method
dynamically calculates the signal quality in different clusters and selects
the cluster that yields
the lowest error rate performance to the client.
[00144] Figure 12 shows the SINR variation as a function of the client's
distance from the
center of clusters Cl. For 4-QAM modulation without FEC coding, we consider
target
SINR=20dB. The line identified by circles represents the SINR for the target
client being served
by the DIDO antennas in Cl, when both Cl and C2 use DIDO precoding without
interference
cancellation. The SINR decreases as a function of D due to pathloss and
interference from the
neighboring cluster. When IDCI-precoding is implemented at the neighboring
cluster, the SINR
loss is only due to pathloss (as shown by the line with triangles), since
interference is completely
removed. Symmetric behavior is experienced when the client is served from the
neighboring
cluster. One embodiment of the handoff strategy is defined such that, as the
client moves from
(21 to C2, the algorithm switches between different DIDO schemes to maintain
the SINK above
predefined target.
[00145] From the plots in Figure 12, we derive the SER for 4-QAM modulation
in Figure
13. We observe that, by switching between different precoding strategies, the
SER is maintained
within predefined target.
[00146] One embodiment of the handoff strategy is as follows.
= Cl-DIDO and C2-DIDO precoding: When the client lies within Cl, away from
the
interfering zone, both clusters Cl and C2 operate with conventional DIDO
precoding
independently.
= Cl-DIDO and C2-11DCI precoding: As the client moves towards the
interfering
zone, its SIR or SINR degrades. When the target SIN1141 is reached, the target
client
starts estimating the channel from all DIDO antennas in C2 and provides the
CSI to
the BTS of C2. The BTS in C2 computes IDCI-precoding and transmits to all
clients
in C2 while preventing interference to the target client. For as long as the
target client
is within the interfering zone, it will continue to provide its CSI to both Cl
and C2.
24
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
= CI-IDCI and C2-DIDO precoding: As the client moves towards C2, its SIR or
SINR keeps decreasing until it again reaches a target. At this point the
client decides
to switch to the neighbor cluster. In this case, Cl starts using the CSI from
the target
client to create zero interference towards its direction with IDCI-precoding,
whereas
the neighbor cluster uses the CSI for conventional DIDO-precoding. In one
embodiment, as the SIR estimate approaches the target, the clusters Cl and C2
try
both DIDO- and IDCI-precoding schemes alternatively, to allow the client to
estimate
the SIR in both cases. Then the client selects the best scheme, to maximize
certain
error rate performance metric. When this method is applied, the cross-over
point for
the handoff strategy occurs at the intersection of the curves with triangles
and
rhombus in Figure 12. One embodiment uses the modified IDCI-precoding method
described in (6) where the neighbor cluster also transmits precoded data
stream to the
target client to provide array gain. With this approach the handoff strategy
is
simplified, since the client does not need to estimate the SINR for both
strategies at
the cross-over point.
= Cl-DIDO and C2-DIDO precoding: As the client moves out of the
interference
zone towards C2, the main cluster Cl stops pre-cancelling interference towards
that
target client via IDCI-precoding and switches back to conventional DIDO-
precoding
to all clients remaining in Cl. This final cross-over point in our handoff
strategy is
useful to avoid unnecessary CSI feedback from the target client to Cl, thereby
reducing the overhead over the feedback channel. In one embodiment a second
target
SINRT7 is defined. When the SINR (or SIR) increases above this target, the
strategy is
switched to Cl-DIDO and C2-DIDO. In one embodiment, the cluster Cl keeps
alternating between DIDO- and IDCI-precoding to allow the client to estimate
the
SINR. Then the client selects the method for Cl that more closely approaches
the
target SINIITI from above.
[00147] The method described above computes the SINR or SIR estimates for
different
schemes in real time and uses them to select the optimal scheme. In one
embodiment, the
handoff algorithm is designed based on the finite-state machine illustrated in
Figure 14. The
client keeps track of its current state and switches to the next state when
the SINR or SIR drops
below or above the predefined thresholds illustrated in Figure 12. As
discussed above, in state
1201, both clusters Cl and C2 operate with conventional DIDO precoding
independently and the
client is served by cluster Cl; in state 1202, the client is served by cluster
Cl, the BTS in C2
computes IDCI-precoding and cluster Cl operates using conventional DIDO
precoding; in state
1203, the client is served by cluster C2, the BTS in Cl computes IDCI-
precoding and cluster C2
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
operates using conventional DIDO precoding; and in state 1204, the client is
served by cluster
C2, and both clusters Cl and C2 operate with conventional DIDO precoding
independently.
[00148] In presence of shadowing effects, the signal quality or SIR may
fluctuate around the
thresholds as shown in Figure 15, causing repetitive switching between
consecutive states in
Figure 14. Changing states repetitively is an undesired effect, since it
results in significant
overhead on the control channels between clients and BTSs to enable switching
between
transmission schemes. Figure 15 depicts one example of a handoff strategy in
the presence of
shadowing. In one embodiment, the shadowing coefficient is simulated according
to log-normal
distribution with variance 3 [3]. Hereafter, we define some methods to prevent
repetitive
switching effect during DIDO handoff.
[00149] One embodiment of the invention employs a hysteresis loop to cope
with state
switching effects. For example, when switching between "C 1 -DIDO,C2-IDCI"
9302 and "Cl -
IDCI,C2-DIDO" 9303 states in Figure 14 (or vice versa) the threshold SINRTi
can be adjusted
within the range Al. This method avoids repetitive switches between states as
the signal quality
oscillates around SINRI 1. For example, Figure 16 shows the hysteresis loop
mechanism when
switching between any two states in Figure 14. To switch from state B to A the
SIR must be
larger than (SIRI1+A1/2), but to switch back from A to B the SIR must drop
below (SIRII-A1/2).
[00150] In a different embodiment, the threshold SINRT) is adjusted to
avoid repetitive
switching between the first and second (or third and fourth) states of the
finite-state machine in
Figure 14. For example, a range of values A2 may be defined such that the
threshold SIN RT2 IS
chosen within that range depending on channel condition and shadowing effects.
[00151] In one embodiment, depending on the variance of shadowing expected
over the
wireless link, the SINR threshold is dynamically adjusted within the range
[SINRp,
SINR-2+A2]. The variance of the log-normal distribution can be estimated from
the variance of
the received signal strength (or RSSI) as the client moves from its current
cluster to the neighbor
cluster.
1001521 The methods above assume the client triggers the handoff strategy.
In one
embodiment, the handoff decision is deferred to the DIDO BTSs, assuming
communication
across multiple BTSs is enabled.
1001531 For simplicity, the methods above are derived assuming no FEC
coding and 4-QAM.
More generally, the SINR or SIR thresholds are derived for different
modulation coding schemes
(MCSs) and the handoff strategy is designed in combination with link
adaptation (see, e.g., U.S.
Patent No. 7,636,381) to optimize downlink data rate to each client in the
interfering zone.
26
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
b. Handoff Between Low- and High-Doppler DIDO Networks
[00154] DIDO systems employ closed-loop transmission schemes to precode
data streams
over the downlink channel. Closed-loop schemes are inherently constrained by
latency over the
feedback channel. In practical DIDO systems, computational time can be reduced
by transceivers
with high processing power and it is expected that most of the latency is
introduced by the DIDO
BSN, when delivering CSI and baseband precoded data from the BTS to the
distributed
antennas. The BSN can be comprised of various network technologies including,
but not limited
to, digital subscriber lines (DSL), cable modems, fiber rings, Ti lines,
hybrid fiber coaxial
(HFC) networks, and/or fixed wireless (e.g., WiFi). Dedicated fiber typically
has very large
bandwidth and low latency, potentially less than a millisecond in local
region, but it is less
widely deployed than DSL and cable modems. Today, DSL and cable modem
connections
typically have between 10-25ms in last-mile latency in the United States, but
they are very
widely deployed.
[00155] The maximum latency over the BSN determines the maximum Doppler
frequency
that can be tolerated over the DIDO wireless link without performance
degradation of DIDO
precoding. For example, in [1] we showed that at the carrier frequency of
400MHz, networks
with latency of about 10msec (i.e., DSL) can tolerate clients' velocity up to
8mph (running
speed), whereas networks with lmsec latency (i.e., fiber ring) can support
speed up to 70mph
(i.e., freeway traffic).
[00156] We define two or multiple DIDO sub-networks depending on the
maximum Doppler
frequency that can be tolerated over the BSN. For example, a BSN with high-
latency DSL
connections between the DIDO BTS and distributed antennas can only deliver low
mobility or
fixed-wireless services (i.e., low-Doppler network), whereas a low-latency BSN
over a low-
latency fiber ring can tolerate high mobility (i.e., high-Doppler network). We
observe that the
majority of broadband users are not moving when they use broadband, and
further, most are
unlikely to he located near areas with many high speed objects moving by
(e.g., next to a
highway) since such locations are typically less desirable places to live or
operate an office.
However, there are broadband users who will be using broadband at high speeds
(e.g., while in a
car driving on the highway) or will be near high speed objects (e.g., in a
store located near a
highway). To address these two differing user Doppler scenarios, in one
embodiment, a low-
Doppler DIDO network consists of a typically larger number of DIDO antennas
with relatively
low power (i.e., 1W to 100W, for indoor or rooftop installation) spread across
a wide area,
whereas a high-Doppler network consists of a typically lower number of DIDO
antennas with
high power transmission (i.e., 100W for rooftop or tower installation). The
low-Doppler DIDO
network serves the typically larger number of low-Doppler users and can do so
at typically lower
27
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
connectivity cost using inexpensive high-latency broadband connections, such
as DSL and cable
modems. The high-Doppler DIDO network serves the typically fewer number of
high-Doppler
users and can do so at typically higher connectivity cost using more expensive
low-latency
broadband connections, such as fiber.
[00157] To
avoid interference across different types of DIDO networks (e.g. low-Doppler
and high-Doppler), different multiple access techniques can be employed such
as: time division
multiple access (TDMA), frequency division multiple access (FDMA), or code
division multiple
access (CDMA).
[00158]
Hereafter, we propose methods to assign clients to different types of DIDO
networks
and enable handoff between them. The network selection is based on the type of
mobility of each
client. The client's velocity (v) is proportional to the maximum Doppler shift
according to the
following equation [6]
fd = ¨ sin 0 (11)
a
where fd is the maximum Doppler shift, A is the wavelength corresponding to
the carrier
frequency and 0 is the angle between the vector indicating the direction
transmitter-client and the
velocity vector.
[00159] In one
embodiment, the Doppler shift of every client is calculated via blind
estimation techniques For example, the Doppler shift can he estimated by
sending RF energy to
the client and analyzing the reflected signal, similar to Doppler radar
systems.
[00160] In
another embodiment, one or multiple DIDO antennas send training signals to the
client. Based on those training signals, the client estimates the Doppler
shift using techniques
such as counting the zero-crossing rate of the channel gain, or performing
spectrum analysis.
We observe that for fixed velocity v and client's trajectory, the angular
velocity v sin 61 in (11)
may depend on the relative distance of the client from every DIDO antenna. For
example, DIDO
antennas in the proximity of a moving client yield larger angular velocity and
Doppler shift than
faraway antennas. In one embodiment, the Doppler velocity is estimated from
multiple DIDO
antennas at different distances from the client and the average, weighted
average or standard
deviation is used as an indicator for the client's mobility. Based on the
estimated Doppler
indicator, the DIDO BTS decides whether to assign the client to low- or high-
Doppler networks.
[00161] The
Doppler indicator is periodically monitored for all clients and sent back to
the
BTS. When one or multiple clients change their Doppler velocity (i.e., client
riding in the bus
versus client walking or sitting), those clients are dynamically re-assigned
to different DIDO
network that can tolerate their level of mobility.
28
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[00162]
Although the Doppler of low-velocity clients can be affected by being in the
vicinity
of high-velocity objects (e.g. near a highway), the Doppler is typically far
less than the Doppler
of clients that are in motion themselves. As such, in one embodiment, the
velocity of the client is
estimated (e.g. by using a means such as monitoring the clients position using
GPS), and if the
velocity is low, the client is assigned to a low-Doppler network, and if the
velocity if high, the
client is assigned to a high-Doppler network.
Methods for Power Control and Antenna Grouping
[00163] The
block diagram of DIDO systems with power control is depicted in Figure 17.
One or multiple data streams (sk) for every client (1,...,0 are first
multiplied by the weights
generated by the DIDO precoding unit. Precoded data streams are multiplied by
power scaling
factor computed by the power control unit, based on the input channel quality
information (COI).
The CQI is either fed back from the clients to DIDO BTS or derived from the
uplink channel
assuming uplink-downlink channel reciprocity. The Uprecoded streams for
different clients are
then combined and multiplexed into M data streams (t,i), one for each of the M
transmit
antennas. Finally, the streams tn., are sent to the digital-to-analog
converter (DAC) unit, the radio
frequency (RF) unit, power amplifier (PA) unit and finally to the antennas.
[00164] The
power control unit measures the CQI for all clients. In one embodiment, the
CQI
is the average SNR or RSSI. The CQI varies for different clients depending on
pathloss or
shadowing. Our power control method adjusts the transmit power scaling factors
Pk for different
clients and multiplies them by the precoded data streams generated for
different clients. Note that
one or multiple data streams may be generated for every client, depending on
the number of
clients' receive antennas.
[00165] To
evaluate the performance of the proposed method, we defined the following
signal model based on (5), including pathloss and power control parameters
rk = .ISNR ________________________ Pk ak HkWksk + nk (12)
where k=1,...,U, U is the number of clients, SNR=Po/No, with P, being the
average transmit
power, No the noise power and ak the pathloss/shadowing coefficient. To model
pathloss/shadowing, we use the following simplified model
ak-i
ak = e u (13)
where a=4 is the pathloss exponent and we assume the pathloss increases with
the clients' index
(i.e., clients are located at increasing distance from the DIDO antennas).
[00166] Figure
18 shows the SER versus SNR assuming four DIDO transmit antennas and
four clients in different scenarios. The ideal case assumes all clients have
the same pathloss (i.e.,
a=0), yielding PA=1 for all clients. The plot with squares refers to the case
where clients have
different pathloss coefficients and no power control. The curve with dots is
derived from the
29
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
same scenario (with pathloss) where the power control coefficients are chosen
such that Pk =
1/ak. With the power control method, more power is assigned to the data
streams intended to the
clients that undergo higher pathloss/shadowing, resulting in 9dB SNR gain (for
this particular
scenario) compared to the case with no power control.
[00167] The Federal Communications Commission (FCC) (and other
international regulatory
agencies) defines constraints on the maximum power that can be transmitted
from wireless
devices to limit the exposure of human body to electromagnetic (FM) radiation.
There are two
types of limits [2]: i) "occupational/controlled" limit, where people are made
fully aware of the
radio frequency (RF) source via fences, warnings or labels; ii) "general
population/uncontrolled"
limit where there is no control over the exposure.
[00168] Different emission levels are defined for different types of
wireless devices. In
general, DIDO distributed antennas used for indoor/outdoor applications
qualify for the FCC
category of "mobile" devices, defined as [2]:
"transmitting devices designed to be used in other than fixed locations that
would normally be
used with radiating structures maintained 20 cm or more from the body of the
user or nearby
persons."
[00169] The EM emission of "mobile" devices is measured in terms of maximum
permissible
exposure (MPE), expressed in mW/cm2. Figure 19 shows the MPE power density as
a function
of distance from the source of RE radiation for different values of transmit
power at 700MHz
carrier frequency. The maximum allowed transmit power to meet the FCC
"uncontrolled" limit
for devices that typically operate beyond 20cm from the human body is 1W.
[00170] Less restrictive power emission constraints are defined for
transmitters installed on
rooftops or buildings, away from the "general population-. For these "rooftop
transmitters- the
FCC defines a looser emission limit of 1000W, measured in terms of effective
radiated power
(ERP).
[00171] Based on the above FCC constraints, in one embodiment we define two
types of
DIDO distributed antennas for practical systems:
= Low-power (LP) transmitters: located anywhere (i.e., indoor or outdoor)
at any
height, with maximum transmit power of 1W and 5Mbps consumer-grade broadband
(e.g. DSL, cable modem, Fibc To The Home (FTTH)) backhaul connectivity.
= High-power (HP) transmitters: rooftop or building mounted antennas at
height of
approximately 10 meters, with transmit power of 100W and a commercial-grade
broadband (e.g. optical fiber ring) backhaul (with effectively "unlimited"
data rate
compared to the throughput available over the DIDO wireless links).
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[00172] Note
that LP transmitters with DSL or cable modem connectivity are good
candidates for low-Doppler DIDO networks (as described in the previous
section), since their
clients are mostly fixed or have low mobility. HP transmitters with commercial
fiber
connectivity can tolerate higher client's mobility and can be used in high-
Doppler DIDO
networks.
[00173] To
gain practical intuition on the performance of DIDO systems with different
types
of LP/HP transmitters, we consider the practical case of DIDO antenna
installation in downtown
Palo Alto, CA. Figure 20a shows a. random distribution of Nu=100 low-power
DIDO
distributed antennas in Palo Alto. In Figure 20b, 50 LP antennas are
substituted with NHp=50
high-power transmitters.
[00174] Based
on the DIDO antenna distributions in Figures 20a-b, we derive the coverage
maps in Palo Alto for systems using DIDO technology. Figures 21a and 21b show
two power
distributions corresponding to the configurations in Figure 20a and Figure
20b, respectively.
The received power distribution (expressed in dBm) is derived assuming the
pathloss/shadowing
model for urban environments defined by the 3GPP standard [3] at the carrier
frequency of
700MHz. We observe that using 50% of HP transmitters yields better coverage
over the selected
area.
[00175]
Figures 22a-b depict the rate distribution for the two scenarios above. The
throughput (expressed in Mbps) is derived based on power thresholds tor
different modulation
coding schemes defined in the 3GPP long-term evolution (LTE) standard in
[4,5]. The total
available bandwidth is fixed to 10MHz at 700MHz carrier frequency. Two
different frequency
allocation plans are considered: i) 5MHz spectrum allocated only to the LP
stations; ii) 9MHz to
HP transmitters and 1MHz to LP transmitters. Note that lower bandwidth is
typically allocated to
LP stations due to their DSL backhaul connectivity with limited throughput.
Figures 22a-b
shows that when using 50% of HP transmitters it is possible to increase
significantly the rate
distribution, raising the average per-client data rate from 2.4Mbps in Figure
22a to 38Mbps in
Figure 22b.
[00176] Next,
we defined algorithms to control power transmission of LP stations such that
higher power is allowed at any given time, thereby increasing the throughput
over the downlink
channel of DIDO systems in Figure 22b. We observe that the FCC limits on the
power density is
defined based on average over time as [2]
S = ETAT/--iSn (14)
TmpE
31
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
where I'mPE = ZnN=1 tn is the MPE averaging time, tri is the period of time of
exposure to
radiation with power density S. For "controlled" exposure the average time is
6 minutes,
whereas for "uncontrolled" exposure it is increased up to 30 minutes. Then,
any power source is
allowed to transmit at larger power levels than the MPE limits, as long as the
average power
density in (14) satisfies the FCC limit over 30 minute average for
"uncontrolled" exposure.
[00177] Based
on this analysis, we define adaptive power control methods to increase
instantaneous per-antenna transmit power, while maintaining average power per
DIDO antenna
below MPE limits. We consider DIDO systems with more transmit antennas than
active clients.
This is a reasonable assumption given that DIDO antennas can be conceived as
inexpensive
wireless devices (similar to WiFi access points) and can be placed anywhere
there is DSL, cable
modem, optical fiber, or other Internet connectivity.
[00178] The
framework of DIDO systems with adaptive per-antenna power control is
depicted in Figure 23. The amplitude of the digital signal coming out of the
multiplexer 234 is
dynamically adjusted with power scaling factors Si,...,Sm, before being sent
to the DAC units
235. The power scaling factors are computed by the power control unit 232
based on the CQI
233.
[00179] In one
embodiment, Ng DIDO antenna groups are defined. Every group contains at
least as many DIDO antennas as the number of active clients (K). At any given
time, only one
group has A I-0>K active DIDO antennas transmitting to the clients at larger
power level (S0) than
MPE limit (MPE). One method iterates across all antenna groups according to
Round-Robin
scheduling policy depicted in Figure 24. In another embodiment, different
scheduling techniques
(i.e., proportional-fair scheduling [8]) are employed for cluster selection to
optimize error rate or
throughput performance.
[00180]
Assuming Round-Robin power allocation, from (14) we derive the average
transmit
power for every DIDO antenna as
to
S = So ¨ < MPE (15)
TmpE
where t, is the period of time over which the antenna group is active and
TmpE=30min is the
average time defined by the FCC guidelines [2]. The ratio in (15) is the duty
factor (DF) of the
groups, defined such that the average transmit power from every DIDO antenna
satisfies the
MPE limit (MPE). The duty factor depends on the number of active clients, the
number of
groups and active antennas per-group, according to the following definition
DF K =to (16)
NsiNa TmpE
The SNR gain (in dB) obtained in DIDO systems with power control and antenna
grouping is
expressed as a function of the duty factor as
32
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
G dB = 10 log10
(¨õ)' (17)
We observe the gain in (17) is achieved at the expense of GdB additional
transmit power across
all DIDO antennas.
In general, the total transmit power from all AT, of all Ng groups is defined
as
(18)
where the P,, is the average per-antenna transmit power given by
rTmpE
= ......L..Si j(t) dt MPE (19)
TmpE u
and S,,(t) is the power spectral density for the ith transmit antenna within
the j'}' group. In one
embodiment, the power spectral density in (19) is designed for every antenna
to optimize error
rate or throughput performance.
[00181] To
gain some intuition on the performance of the proposed method, consider 400
DIDO distributed antennas in a given coverage area and 400 clients subscribing
to a wireless
Internet service offered over DIDO systems. It is unlikely that every Internet
connection will be
fully utilized all the time. Let us assume that 10% of the clients will be
actively using the
wireless Internet connection at any given time. Then, 400 DIDO antennas can be
divided in
Ng=10 groups of Na=40 antennas each, every group serving K=40 active clients
at any given time
with duty factor DF=0.1. The SNR gain resulting from this transmission scheme
is
GdB=10logio(1/DF)=10dB, provided by 10dB additional transmit power from all
DIDO antennas.
We observe, however, that the average per-antenna transmit power is constant
and is within the
MPE limit.
[00182] Figure
25 compares the (uncoded) SER performance of the above power control
with antenna grouping against conventional eigenmode selection in U.S. Patent
No. 7,636,381.
All schemes use BD precoding with four clients, each client equipped with
single antenna. The
SNR refers to the ratio of per-transmit-antenna power over noise power (i.e.,
per-antenna
transmit SNR). The curve denoted with DIDO 4x4 assumes four transmit antenna
and BD
precoding. The curve with squares denotes the SER performance with two extra
transmit
antennas and BD with eigenmode selection, yielding 10dB SNR gain (at 1% SER
target) over
conventional BD precoding. Power control with antenna grouping and DF=1/10
yields 10dB
gain at the same SER target as well. We observe that eigenmode selection
changes the slope of
the SER curve due to diversity gain, whereas our power control method shifts
the SER curve to
the left (maintaining the same slope) due to increased average transmit power.
For comparison,
the SER with larger duty factor DF=1/50 is shown to provide additional 7dB
gain compared to
DF=1/10.
33
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[00183] Note
that our power control may have lower complexity than conventional
eigenmode selection methods. In fact, the antenna ID of every group can be pre-
computed and
shared among DIDO antennas and clients via lookup tables, such that only K
channel estimates
are required at any given time. For eigenmode selection, (K+2) channel
estimates are computed
and additional computational processing is required to select the eigenmode
that minimizes the
SER at any given time for all clients.
[00184] Next,
we describe another method involving DIDO antenna grouping to reduce CSI
feedback overhead in some special scenarios. Figure 26a shows one scenario
where clients
(dots) are spread randomly in one area covered by multiple DIDO distributed
antennas (crosses).
The average power over every transmit-receive wireless link can be computed as
A = {11112}. (20)
where H is the channel estimation matrix available at the DIDO BTS.
[00185] The
matrices A in Figures 26a-c are obtained numerically by averaging the channel
matrices over 1000 instances. Two alternative scenarios are depicted in Figure
26b and Figure
26c, respectively, where clients are grouped together around a subset of DIDO
antennas and
receive negligible power from DIDO antennas located far away. For example,
Figure 26b shows
two groups of antennas yielding block diagonal matrix A. One extreme scenario
is when every
client is very close to only one transmitter and the transmitters are far away
from one another,
such that the power from all other DIDO antennas is negligible. In this case,
the DIDO link
degenerates in multiple SISO links and A is a diagonal matrix as in Figure
26c.
1001861 In all
three scenarios above, the BD precoding dynamically adjusts the precoding
weights to account for different power levels over the wireless links between
DIDO antennas and
clients. It is convenient, however, to identify multiple groups within the
DIDO cluster and
operate DIDO precoding only within each group. Our proposed grouping method
yields the
following advantages:
= Computational gain: DIDO precoding is computed only within every group in
the
cluster. For example, if BD precoding is used, singular value decomposition
(SVD)
has complexity 0(n3), where n is the minimum dimension of the channel matrix
H. If
I-I can be reduced to a block diagonal matrix, the SVD is computed for every
block
with reduced complexity. In fact, if the channel matrix is divided into two
block
matrices with dimensions n1 and n7 such that n=ni+n), the complexity of the
SVD is
only 0(n13)+0(n73)<O(n3). In the extreme case, if H is diagonal matrix, the
DIDO
link reduce to multiple SISO links and no SVD calculation is required.
= Reduced CSI feedback overhead: When DIDO antennas and clients are divided
into
groups, in one embodiment, the CSI is computed from the clients to the
antennas only
34
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
within the same group. In TDD systems, assuming channel reciprocity, antenna
grouping reduces the number of channel estimates to compute the channel matrix
H.
In FDD systems where the CSI is fed back over the wireless link, antenna
grouping
further yields reduction of CSI feedback overhead over the wireless links
between
DIDO antennas and clients.
Multiple Access Techniques for the DIDO Uplink Channel
[00187] In one embodiment of the invention, different multiple access
techniques are defined
for the DIDO uplink channel. These techniques can be used to feedback the CSI
or transmit data
streams from the clients to the DIDO antennas over the uplink. Hereafter, we
refer to feedback
CST and data streams as uplink streams.
= Multiple-input multiple-output (MIMO): the uplink streams are transmitted
from the
client to the DIDO antennas via open-loop MIMO multiplexing schemes. This
method
assumes all clients are time/frequency synchronized. In one embodiment,
synchronization among clients is achieved via training from the downlink and
all DIDO
antennas are assumed to be locked to the same time/frequency reference clock.
Note that
variations in delay spread at different clients may generate jitter between
the clocks of
different clients that may affect the performance of MIMO uplink scheme. After
the
clients send uplink streams via MIMO multiplexing schemes, the receive DIDO
antennas
may use non-linear (i.e., maximum likelihood, ML) or linear (i.e., zeros-
forcing,
minimum mean squared error) receivers to cancel co-channel interference and
demodulate the uplink streams individually.
= Time division multiple access (TDMA): Different clients are assigned to
different time
slots. Every client sends its uplink stream when its time slot is available.
= Frequency division multiple access (FDMA): Different clients are assigned
to different
carrier frequencies. In multicarrier (OFDM) systems, subsets of tones arc
assigned to
different clients that transmit the uplink streams simultaneously, thereby
reducing
latency.
= Code division multiple access (CDMA): Every client is assigned to a
different pseudo-
random sequence and orthogonality across clients is achieved in the code
domain.
[00188] In one embodiment of the invention, the clients are wireless
devices that transmit at
much lower power than the DIDO antennas. In this case, the DIDO BTS defines
client sub-
groups based on the uplink SNR information, such that interference across sub-
groups is
minimized. Within every sub-group, the above multiple access techniques are
employed to create
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
orthogonal channels in time, frequency, space or code domains thereby avoiding
uplink
interference across different clients.
[00189] In
another embodiment, the uplink multiple access techniques described above are
used in combination with antenna grouping methods presented in the previous
section to define
different client groups within the DIDO cluster.
System and Method for Link Adaptation in DIDO Multicarrier Systems
[00190] Link
adaptation methods for DIDO systems exploiting time, frequency and space
selectivity of wireless channels were defined in U.S. Patent No. 7,636,381.
Described below are
embodiments of the invention for link adaptation in multicarrier (OFDM) DIDO
systems that
exploit time/frequency selectivity of wireless channels.
[00191] We
simulate Rayleigh fading channels according to the exponentially decaying
power delay profile (PDP) or Saleh-Valenzuela model in [9]. For simplicity, we
assume single-
cluster channel with multipath PDP defined as
Pn = em3n (21)
where n=0,...,L-1, is the index of the channel tap, L is the number of channel
taps and ig =
'/DS is the PDP exponent that is an indicator of the channel coherence
bandwidth, inverse
proportional to the channel delay spread (o-Ds). Low values of 16 yield
frequency-flat channels,
whereas high values of 16 produce frequency selective channels. The PDP in
(21) is normalized
such that the total average power for all L channel taps is unitary
F _ n 22) (
n Ere' Pl
Figure 27 depicts the amplitude of low frequency selective channels (assuming
16' = 1) over
delay domain or instantaneous PDP (upper plot) and frequency domain (lower
plot) for DIDO
2x2 systems. The first subscript indicates the client, the second subscript
the transmit antenna.
High frequency selective channels (with = 0.1) are shown in Figure 28.
[00192] Next,
we study the performance of DIDO precoding in frequency selective channels.
We compute the DIDO precoding weights via BD, assuming the signal model in (1)
that satisfies
the condition in (2). We reformulate the DIDO receive signal model in (5),
with the condition in
(2), as
rk = Hek Sk '1k= (23)
[00193] where
Hek = Hk Wk is the effective channel matrix for user k. For DIDO 2x2, with a
single antenna per client, the effective channel matrix reduces to one value
with a frequency
response shown in Figure 29 and for channels characterized by high frequency
selectivity (e.g.,
with ig = 0.1) in Figure 28. The continuous line in Figure 29 refers to client
1, whereas the line
36
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
with dots refers to client 2. Based on the channel quality metric in Figure 29
we define
time/frequency domain link adaptation (LA) methods that dynamically adjust
MCSs, depending
on the changing channel conditions.
[00194] We begin by evaluating the performance of different MCSs in AWGN
and Rayleigh
fading SISO channels. For simplicity, we assume no FEC coding, but the
following LA methods
can be extended to systems that include FEC.
[00195] Figure 30 shows the SER for different QAM schemes (i.e., 4-QAM, 16-
QAM, 64-
QAM). Without loss of generality, we assume target SER of 1% for uncoded
systems. The SNR
thresholds to meet that target SER in AWGN channels are 8dB, 15.5dB and 22dB
for the three
modulation schemes, respectively. In Rayleigh fading channels, it is well
known the SER
performance of the above modulation schemes is worse than AWGN [13] and the
SNR
thresholds are: 18.6dB, 27.3dB and 34.1dB, respectively. We observe that DIDO
precoding
transforms the multi-user downlink channel into a set of parallel SISO links.
Hence, the same
SNR thresholds as in Figure 30 for SISO systems hold for DIDO systems on a
client-by-client
basis. Moreover, if instantaneous LA is carried out, the thresholds in AWGN
channels are used.
[00196] The key idea of the proposed LA method for DIDO systems is to use
low MCS
orders when the channel undergoes deep fades in the time domain or frequency
domain (depicted
in Figure 28) to provide link-robustness. Contrarily, when the channel is
characterized by large
gain, the LA method switches to higher MCS orders to increase spectral
efficiency. One
contribution of the present application compared to U.S. Patent No. 7,636,381
is to use the
effective channel matrix in (23) and in Figure 29 as a metric to enable
adaptation.
[00197] The general framework of the LA methods is depicted in Figure 31
and defined as
follows:
= CSI estimation: At 3171 the DIDO BTS computes the CSI from all users.
Users may be
equipped with single or multiple receive antennas.
= DIDO precoding: At 3172, the BTS computes the DIDO precoding weights for
all users.
In one embodiment, BD is used to compute these weights. The precoding weights
are
calculated on a tone-by-tone basis.
= Link-quality metric calculation: At 3173 the BTS computes the frequency-
domain link
quality metrics. In OFDM systems, the metrics are calculated from the CSI and
DIDO
precoding weights for every tone. In one embodiment of the invention, the link-
quality
metric is the average SNR over all OFDM tones. We define this method as LA1
(based
on average SNR performance). In another embodiment, the link quality metric is
the
frequency response of the effective channel in (23). We define this method as
LA2
(based on tone-by-tone performance to exploit frequency diversity). If every
client has
37
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
single antenna, the frequency-domain effective channel is depicted in Figure
29. If the
clients have multiple receive antennas, the link-quality metric is defined as
the Frobenius
norm of the effective channel matrix for every tone. Alternatively, multiple
link-quality
metrics are defined for every client as the singular values of the effective
channel matrix
in (23).
= Bit-loading algorithm: At 3174, based on the link-quality metrics, the
BTS determines
the MCSs for different clients and different OFDM tones. For LA1 method, the
same
MCS is used for all clients and all OFDM tones based on the SNR thresholds for
Rayleigh fading channels in Figure 30. For LA2, different MCSs are assigned to
different OFDM tones to exploit channel frequency diversity.
= Precoded data transmission: At 3175, the BTS transmits precoded data
streams from
the DIDO distributed antennas to the clients using the MCSs derived from the
bit-loading
algorithm. One header is attached to the precoded data to communicate the MCSs
for
different tones to the clients. For example, if eight MCSs are available and
the OFDM
symbols are defined with N=64 tone, log2(8)*N=192 bits are required to
communicate
the current MCS to every client. Assuming 4-QAM (2 bits/symbol spectral
efficiency) is
used to map those bits into symbols, only 192/2/N=1.5 OFDM symbols are
required to
map the MCS information. In another embodiment, multiple subcamers (or OFDM
tones) are grouped into subbands and the same MCS is assigned to all tones in
the same
subband to reduce the overhead due to control information. Moreover, the MCS
are
adjusted based on temporal variations of the channel gain (proportional to the
coherence
time). In fixed-wireless channel (characterized by low Doppler effect) the MCS
are
recalculated every fraction of the channel coherence time, thereby reducing
the overhead
required for control information.
[00198] Figure 32 shows the SER performance of the LA methods described
above. For
comparison, the SER performance in Rayleigh fading channels is plotted for
each of the three
QAM schemes used. The LA2 method adapts the MCSs to the fluctuation of the
effective
channel in the frequency domain, thereby providing 1.8bps/Hz gain in spectral
efficiency for low
SNR (i.e., SNR=20dB) and 15dB gain in SNR (for SNR>35dB) compared to LA1.
System and Method for DIDO Precoding Interpolation in Multicarrier Systems
[00199] The computational complexity of DIDO systems is mostly localized at
the
centralized processor or BTS. The most computationally expensive operation is
the calculation
of the precoding weights for all clients from their CSI. When BD precoding is
employed, the
BTS has to carry out as many singular value decomposition (SVD) operations as
the number of
38
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
clients in the system. One way to reduce complexity is through parallelized
processing, where
the SVD is computed on a separate processor for every client.
[00200] In
multicarrier DIDO systems, each subcarrier undergoes flat-fading channel and
the
SVD is carried out for every client over every subcarrier. Clearly the
complexity of the system
increases linearly with the number of subcarriers. For example, in OFDM
systems with 1MHz
signal bandwidth, the cyclic prefix (L0) must have at least eight channel taps
(i.e., duration of 8
microseconds) to avoid intersymbol interference in outdoor urban macrocell
environments with
large delay spread [3]. The size (NFFT) of the fast Fourier transform (FFT)
used to generate the
OFDM symbols is typically set to multiple of L0 to reduce loss of data rate.
If NFFT=64, the
effective spectral efficiency of the system is limited by a factor NFFT/(
NFFT+L0)=89%. Larger
values of NrFT yield higher spectral efficiency at the expense of higher
computational complexity
at the DIDO precoder.
[00201] One
way to reduce computational complexity at the D1DO precoder is to carry out
the SVD operation over a subset of tones (that we call pilot tones) and derive
the precoding
weights for the remaining tones via interpolation. Weight interpolation is one
source of error that
results in inter-client interference. In one embodiment, optimal weight
interpolation techniques
are employed to reduce inter-client interference, yielding improved error rate
performance and
lower computational complexity in multicarrier systems. In DIDO systems with M
transmit
antennas, U clients and A/ receive antennas per clients, the condition for the
precodmg weights of
the kth client (Wk) that guarantees zero interference to the other clients u
is derived from (2) as
Huwk = oNxN ; Vu =1,...,U; with u # k (24)
where Hu are the channel matrices corresponding to the other DIDO clients in
the system.
[00202] In one
embodiment of the invention, the objective function of the weight
interpolation method is defined as
f(0k) = Euu=111HuCi'1k(Ok)11F (25)
uk
where Ok is the set of parameters to be optimized for user k, Wk(Ok) is the
weight interpolation
matrix and II IF denotes the Frobenius norm of a matrix. The optimization
problem is formulated
as
Okopt = arg minokuok f(0k) (26)
where Ok is the feasible set of the optimization problem and Okopt is the
optimal solution.
1002031 The
objective function in (25) is defined for one OFDM tone. In another
embodiment of the invention, the objective function is defined as linear
combination of the
39
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
Frobenius norm in (25) of the matrices for all the OFDM tones to be
interpolated. In another
embodiment, the OFDM spectrum is divided into subsets of tones and the optimal
solution is
given by
ek,opt = arg minokEok maxnEA f(n, 0k) (27)
where n is the OFDM tone index and A is the subset of tones.
[00204] The
weight interpolation matrix Wk (0k) in (25) is expressed as a function of a
set of
parameters Ok . Once the optimal set is determined according to (26) or (27),
the optimal weight
matrix is computed. In one embodiment of the invention, the weight
interpolation matrix of
given OFDM tone n is defined as linear combination of the weight matrices of
the pilot tones.
One example of weight interpolation function for beamforming systems with
single client was
defined in [11]. In DIDO multi-client systems we write the weight
interpolation matrix as
firk (1No n, Ok) = (1 ¨ cii) = W(1) + cnejek = W(1 + 1) (28)
where 0 (L0-
1), L0 is the number of pilot tones and cn. = (n ¨ 1)/N0, with No = NFFT/
Lo. The weight matrix in (28) is then normalized such that F
NM to guarantee unitary
power transmission from every antenna. If N=1 (single receive antenna per
client), the matrix in
(28) becomes a vector that is normalized with respect to its norm In one
embodiment of the
invention, the pilot tones are chosen uniformly within the range of the OFDM
tones. In another
embodiment, the pilot tones are adaptively chosen based on the CSI to minimize
the
interpolation error.
[00205] We
observe that one key difference of the system and method in [11] against the
one
proposed in this patent application is the objective function. In particular,
the systems in [11]
assumes multiple transmit antennas and single client, so the related method is
designed to
maximize the product of the precoding weight by the channel to maximize the
receive SNR for
the client. This method, however, does not work in multi-client scenarios,
since it yields inter-
client interference due to interpolation error. By contrast, our method is
designed to minimize
inter-client interference thereby improving error rate performance to all
clients.
[00206] Figure
33 shows the entries of the matrix in (28) as a function of the OFDM tone
index for DIDO 2x2 systems with NFFT = 64 and Lo = 8. The channel PDP is
generated
according to the model in (21) with t3 = 1 and the channel consists of only
eight channel taps.
We observe that Lo must be chosen to be larger than the number of channel
taps. The solid lines
in Figure 33 represent the ideal functions, whereas the dotted lines are the
interpolated ones. The
interpolated weights match the ideal ones for the pilot tones, according to
the definition in (28).
The weights computed over the remaining tones only approximate the ideal case
due to
estimation error.
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[00207] One way to implement the weight interpolation method is via
exhaustive search over
the feasible set ek in (26). To reduce the complexity of the search, we
quantize the feasible set
into P values uniformly in the range [0,27r]. Figure 34 shows the SER versus
SNR for Lo = 8,
M=Nt=2 transmit antennas and variable number of P. As the number of
quantization levels
increases, the SER performance improves. We observe the case P=10 approaches
the
performance of P=100 for much lower computational complexity, due to reduced
number of
searches,
[00208] Figure 35 shows the SER performance of the interpolation method for
different
DIDO orders and Lo = 16. We assume the number of clients is the same as the
number of
transmit antennas and every client is equipped with single antenna. As the
number of clients
increases the SER performance degrades due to increase inter-client
interference produced by
weight interpolation errors.
[00209] In another embodiment of the invention, weight interpolation
functions other than
those in (28) are used. For example, linear prediction autoregressive models
[12] can be used to
interpolate the weights across different OFDM tones, based on estimates of the
channel
frequency correlation.
References
[00210] [1] A. Forenza and S. G. Perlman, "System and method for
distributed antenna
wireless communications", U.S. Application Serial No. 12/630,627, filed
December 2, 2009,
entitled "System and Method For Distributed Antenna Wireless Communications"
[00211] [2] FCC, "Evaluating compliance with FCC guidelines for human
exposure to
radiofrequency electromagnetic fields," OET Bulletin 65, Ed. 97-01, Aug. 1997
[00212] [3] 3GPP, "Spatial Channel Model AHG (Combined ad-hoc from 3GPP &
3GPP2)",
SCM Text V6.0, April 22, 2003
[00213] [4] 3GPP TR 25.912, "Feasibility Study for Evolved UTRA and UTRAN",
V9Ø0
(2009-10)
[00214] [5] 3GPP TR 25.913, "Requirements for Evolved UTRA (E-UTRA) and
Evolved
UTRAN (E-UTRAN)", V8Ø0 (2009-01)
[00215] [6] W. C. Jakes, Microwave Mobile Communications, IEEE Press, 1974
[00216] [7] K. K. Wong, et al., "A joint channel diagonalization for
multiuser MIMO
antenna systems," IEEE Trans. Wireless Comm., vol. 2, pp. 773-786, July 2003;
[00217] [8] P. Viswanath, et al., "Opportunistic beamforming using dump
antennas," IEEE
Trans. On Inform. Theory, vol. 48, pp. 1277-1294, June 2002.
[00218] [9] A. A. M. Saleh, et al., "A statistical model for indoor
multipath propagation,"
IEEE Jour. Select. Areas in Comm., vol. 195 SAC-5, no. 2, pp. 128-137, Feb.
1987.
41
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[00219] [10] A. Paulraj, et al., Introduction to Space-Time Wireless
Communications,
Cambridge University Press, 40 West 20th Street, New York, NY, USA, 2003.
[00220] [11] J. Choi, et at., "Interpolation Based Transmit Beamforming for
MIMO-OFDM
with Limited Feedback," IEEE Trans. on Signal Processing, vol. 53, no. 11, pp.
4125-4135, Nov.
2005.
[00221] [12] I. Wong, et al., "Long Range Channel Prediction for Adaptive
OFDM
Systems," Proc. of the IEEE Asilomar Conf on Signals, Systems, and Computers,
vol. "pp. 723-
736, Pacific Grove, CA, USA, Nov. 7-10, 2004.
[00222] [13] J. G. Proakis, Communication System Engineering, Prentice
Hall, 1994
1002231 [14] B.D.Van Veen, et al., "Beamforming: a versatile approach to
spatial filtering,"
IEEE ASSP Magazine, Apr. 1988.
[00224] [15] R.G. Vaughan, "On optimum combining at the mobile," IEEE
Trans. On Vehic.
Tech., vo137, n.4, pp.181-188, Nov. 1988
[00225] [16] F.Qian, "Partially adaptive beamforming for correlated
interference rejection,"
IEEE Trans. On Sign. Proc., vol.43, n.2, pp.506-515, Fcb.1995
[00226] [17] H.Krim, et. al., "Two decades of array signal processing
research," IEEE Signal
Proc. Magazine, pp.67-94, July 1996
[00227] [19] W.R. Remley, "Digital beamforming system", US Patent N.
4,003,016, Jan.
1977
[00228] [18] R.J. Masak, "Beamforming/null-steering adaptive array", US
Patent N.
4,771,289, Sep.1988
[00229] [20] K.-B.Yu, et. al., "Adaptive digital beamforming architecture
and algorithm for
nulling mainlobe and multiple sidelobe radar jammers while preserving
monopulse ratio angle
estimation accuracy", US Patent 5,600,326, Feb.1997
[00230] [21] H.Boche, et al., "Analysis of different precoding/decoding
strategies for
multiuser beamforming", IEEE Vehic. Tech. Conf., vc-)1.1, Apr. 2003
[00231] [22] M.Schubert, et al., "Joint 'dirty paper' pre-coding and
downlink beamforming,"
vol.2, pp.536-540, Dec. 2002
1002321 [23] H.Boche, et al." A general duality theory for uplink and
downlink
beamformingc", vol.1, pp.87-91, Dec. 2002
1002331 [24] K. K. Wong, R. D. Murch, and K. B. Letaief, "A joint channel
diagonalization
for multiuser MIMO antenna systems," IEEE Trans. Wireless Comm., vol. 2, pp.
773-786, Jul
2003;
42
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[00234] [25] Q. H. Spencer, A. L. Swindlehurst, and M. Haardt, "Zero
forcing methods for
downlink spatial multiplexing in multiuser MIMO channels," IEEE Trans. Sig.
Proc., vol. 52, pp.
461-471, Feb. 2004.
II. DISCLOSURE FROM RELATED APPLICATION SERIAL NO. 12/917,257
[00235] Described below are wireless radio frequency (RF) communication
systems and
methods employing a plurality of distributed transmitting antennas operating
cooperatively to
create wireless links to given users, while suppressing interference to other
users. Coordination
across different transmitting antennas is enabled via user-clustering. The
user cluster is a subset
of transmitting antennas whose signal can be reliably detected by given user
(i.e., received signal
strength above noise or interference level). Every user in the system defines
its own user-cluter.
The waveforms sent by the transmitting antennas within the same user-cluster
coherently
combine to create RF energy at the target user's location and points of zero
RF interference at
the location of any other user reachable by those antennas.
[00236] Consider a system with M transmit antennas within one user-cluster
and K users
reachable by those M antennas, with K < M. We assume the transmitters are
aware of the CSI
(H E Cmcm) between the Mtransmit antennas and K users. For simplicity, every
user is assumed
to be equipped with a single antenna, but the same method can be extended to
multiple receive
antennas per user. Consider the channel matrix H obtained by combining the
channel vectors
(hk E C''') from the M transmit antennas to the K users as
h1 1
H = "k.
hK
The precoding weights (wk E Cmxl) that create RF energy to user k and zero RF
energy to all
other K-1 users are computed to satisfy the following condition
fikwk =._ (you
where ilk is the effective channel matrix of user k obtained by removing the k-
th row of matrix
H and 0' is the vector with all zero entries
1002371 In one embodiment, the wireless system is a DIDO system and user
clustering is
employed to create a wireless communication link to the target user, while pre-
cancelling
interference to any other user reachable by the antennas lying within the user-
cluster. In U.S.
Application Serial No. 12/630,627, a DIDO system is described which includes:
= DIDO clients: user terminals equipped with one or multiple antennas;
43
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
= DIDO distributed antennas: transceiver stations operating cooperatively
to transmit
precoded data streams to multiple users, thereby suppressing inter-user
interference;
= DIDO base transceiver stations (BTS): centralized processor generating
precoded
waveforms to the DIDO distributed antennas;
= DIDO base station network (BSN): wired backhaul connecting the BTS to the
DIDO
distributed antennas or to other BTSs.
The DIDO distributed antennas are grouped into different subsets depending on
their spatial
distribution relative to the location of the BTSs or DIDO clients. We define
three types of
clusters, as depicted in Figure 36:
= Super-cluster 3640: is the set of DIDO distributed antennas connected to
one or multiple
BTSs such that the round-trip latency between all BTSs and the respective
users is within the
constraint of the DIDO precoding loop;
= DIDO-cluster 3641: is the set of DIDO distributed antennas connected to
the same BTS.
When the super-cluster contains only one BTS, its definition coincides with
the DIDO-
cluster;
= User-cluster 3642: is the set of DIDO distributed antennas that
cooperatively transmit
precoded data to given user.
[00238] For example, the BTSs are local hubs connected to other BTSs and to
the DIDO
distributed antennas via the BSN. The BSN can be comprised of various network
technologies
including, but not limited to, digital subscriber lines (DSL), ADSL, VDSL [6],
cable modems,
fiber rings, TI lines, hybrid fiber coaxial (HFC) networks, and/or fixed
wireless (e.g., WiFi). All
BTSs within the same super-cluster share information about DIDO precoding via
the BSN such
that the round-trip latency is within the DIDO precoding loop.
[00239] In Figure 37, the dots denote DIDO distributed antennas, the
crosses are the users
and the dashed lines indicate the user-clusters for users U 1 and U8,
respectively. The method
described hereafter is designed to create a communication link to the target
user U 1 while
creating points of zero RF energy to any other user (U2-U8) inside or outside
the user-cluster.
[00240] We proposed similar method in [5], where points of zero RF energy
were created to
remove interference in the overlapping regions between DIDO clusters. Extra
antennas were
required to transmit signal to the clients within the DIDO cluster while
suppressing inter-cluster
interference. One embodiment of a method proposed in the present application
does not attempt
to remove inter-DIDO-cluster interference; rather it assumes the cluster is
bound to the client
(i.e., user-cluster) and guarantees that no interference (or negligible
interference) is generated to
any other client in that neighborhood.
44
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[00241] One idea associated with the proposed method is that users far
enough from the user-
cluster are not affected by radiation from the transmit antennas, due to large
pathloss. Users close
or within the user-cluster receive interference-free signal due to precoding.
Moreover, additional
transmit antennas can be added to the user-cluster (as shown in Figure 37)
such that the
condition K < M is satisfied.
[00242] One embodiment of a method employing user clustering consists of
the following
steps:
a. Link-quality measurements: the link quality between every DIDO
distributed
antenna and every user is reported to the BTS. The link-quality metric
consists of signal-to-noise
ratio (SNR) or signal-to-interference-plus-noise ratio (SINR).
In one embodiment, the DIDO distributed antennas transmit training signals and
the users
estimate the received signal quality based on that training. The training
signals are designed to be
orthogonal in time, frequency or code domains such that the users can
distinguish across
different transmitters. Alternatively, the DIDO antennas transmit narrowband
signals (i.e., single
tone) at one particular frequency (i.e., a beacon channel) and the users
estimate the link-quality
based on that beacon signal. One threshold is defined as the minimum signal
amplitude (or
power) above the noise level to demodulate data successfully as shown in
Figure 38a. Any link-
quality metric value below this threshold is assumed to be zero. The link-
quality metric is
quantized over a finite number of bits and fed back to the transmitter.
In a different embodiment, the training signals or beacons are sent from the
users and the link
quality is estimated at the DIDO transmit antennas (as in Figure 38b),
assuming reciprocity
between uplink (UL) and downlink (DL) pathloss. Note that pathloss reciprocity
is a realistic
assumption in time division duplexing (TDD) systems (with UL and DL channels
at the same
frequency) and frequency division duplexing (FDD) systems when the UL and DL
frequency
bands are reatively close.
Information about the link-quality metrics is shared across different BTSs
through the BSN as
depicted in Figure 37 such that all BTSs are aware of the link-quality between
every
antenna/user couple across different DIDO clusters.
b. Definition of user-clusters: the link-quality metrics of all wireless
links in the
DIDO clusters are the entries to the link-quality matrix shared across all
BTSs via the BSN. One
example of link-quality matrix for the scenario in Figure 37 is depicted in
Figure 39.
The link-quality matrix is used to define the user clusters. For example,
Figure 39 shows the
selection of the user cluster for user U8. The subset of transmitters with non-
zero link-quality
metrics (i.e., active transmitters) to user U8 is first identified. These
transmitters populate the
user-cluster for the user U8. Then the sub-matrix containing non-zero entries
from the
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
transmitters within the user-cluster to the other users is selected. Note that
since the link-quality
metrics are only used to select the user cluster, they can be quantized with
only two bits (i.e., to
identify the state above or below the thresholds in Figure 38) thereby
reducing feedback
overhead.
[00243] Another example is depicted in Figure 40 for user Ul. In this case
the number of
active transmitters is lower than the number of users in the sub-matrix,
thereby violating the
condition K < M. Therefore, one or more columns are added to the sub-matrix to
satisfy that
condition. If the number of transmitters exceeds the number of users, the
extra antennas can be
used for diversity schemes (i.e., antenna or eigenmode selection).
[00244] Yet another example is shown in Figure 41 for user U4. We observe
that the sub-
matrix can be obtained as combination of two sub-matrices.
c. CSI report to the BTSs: Once the user clusters are selected, the CSI
from all
transmitters within the user-cluster to every user reached by those
transmitters is made available
to all BTSs. The CSI information is shared across all BTSs via the BSN. In TDD
systems,
UL/DL channel reciprocity can be exploited to derive the CSI from training
over the UL channel.
In FDD systems, feedback channels from all users to the BTSs are required. To
reduce the
amount of feedback, only the CSI corresponding to the non-zero entries of the
link-quality
matrix are fed back.
d. DIDO precoding: Finally, DIDO precoding is applied to every CSI sub-
matrix
corresponding to different user clusters (as described, for example, in the
related U.S. Patent
Applications).
In one embodiment, singular value decomposition (SVD) of the effective channel
matrix 1kis
computed and the precoding weight \irk for user k is defined as the right
sigular vector
corresponding to the null subspace of ilk. Alternatively, if M>K and the SVD
decomposes the
effective channel matrix as ilk = VkZkUkH, the DIDO precoding weight for user
k is given by
Wk = Uo (U011 hkT)
where U. is the matrix with columns being the singular vectors of the null
subspace of tik.
From basic linear algebra considerations, we observe that the right singular
vector in the null
subspace of the matrix Ii is equal to the eigenvetor of C corresponding to the
zero eigenvalue
C = = (vzuH)H (vzuH) = u E2
where the effective channel matrix is decomposed as ii = VEUH, according to
the SVD. Then,
one alternative to computing the SVD of 11k is to calculate the eigenvalue
decomposition of C.
There are several methods to compute eigenvalue decomposition such as the
power method.
46
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
Since we are only interested to the eigenvector corresponding to the null
subspace of C, we use
the inverse power method described by the iteration
(C ¨ A)-1 ui
= _________________________________________
11(C ¨ )1)-1 uil
where the vector (ui) at the first iteration is a random vector.
Given that the eigenvalue (A.) of the null subspace is known (i.e., zero) the
inverse power method
requires only one iteration to converge, thereby reducing computational
complexity. Then, we
write the precoding weight vector as
w = C-1 u1
where u1 is the vector with real entries equal to I (i.e., the precoding
weight vector is the sum of
the columns of C-1).
The DIDO precoding calculation requires one matrix inversion. There are
several numerical
solutions to reduce the complexity of matrix inversions such as the Strassen's
algorithm [1] or
the Coppersmith-Winograd's algorithm [2,3]. Since C is Hermitian matrix by
definition, an
alternative solution is to decompose C in its real and imaginary components
and compute matrix
inversion of a real matrix, according to the method in [4, Section 11.4].
[00245] Another feature of the proposed method and system is its
reconfigurability. As the
client moves across different DIDO clusters as in Figure 42, the user-cluster
follows its moves.
In other words, the subset of transmit antennas is constantly updated as the
client changes its
position and the effective channel matrix (and corresponding precoding
weights) are recomputed.
[00246] The method proposed herein works within the super-cluster in Figure
36, since the
links between the BTSs via the BSN must be low-latency. To suppress
interference in the
overlapping regions of different super-clusters, it is possible to use our
method in [5] that uses
extra antennas to create points of zero RF energy in the interfering regions
between DIDO
clusters.
[00247] It should be noted that the terms "user" and "client" are used
interchangeably herein.
References
1002481 [I] S. Robinson, "Toward an Optimal Algorithm for Matrix
Multiplication", SIAM
News. Volume 38, Number 9, November 2005.
[00249] [2] D. Coppersmith and S. Winograd, "Matrix Multiplication via
Arithmetic
Progression", J. Symb. Comp. vol.9, p.251-280, 1990.
[00250] [3] H. Cohn, R. Kleinberg, B. Szegedy, C. Umans, "Group-theoretic
Algorithms for
Matrix Multiplication", p. 379-388, Nov, 2005.
47
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[00251] [4] W.H. Press, S.A. Teukolsky, W. T. Vetterling, B.P. Flannery
"NUMERICAL
RECIPES IN C: THE ART OF SCIENTIFIC COMPUTING", Cambridge University Press,
1992.
[00252] [5] A. Forenza and S.G.Perlman, "INTERFERENCE MANAGEMENT, HANDOEF,
POWER
CONTROL AND LINK ADAPTATION IN DISTRIBUTED-INPUT DISTRIBUTED-OUTPUT (DIDO)
COMMUNICATION SYSTEMS", Patent Application Serial No. 12/802,988, filed June
16, 2010.
[00253] [6] Per-Erik Eriksson and Bjorn Odenhammar, "VDSL2: Next important
broadband
technology", Ericsson Review No. 1, 2006.
SYSTEMS AND METHODS TO EXPLOIT AREAS OF COHERENCE IN
WIRELESS SYSTEMS
[00254] The capacity of multiple antenna systems (MAS) in practical
propagation
environments is a function of the spatial diversity available over the
wireless link. Spatial
diversity is determined by the distribution of scattering objects in the
wireless channel as well as
the geometry of transmit and receive antenna arrays.
[00255] One popular model for MAS channels is the so called clustered
channel model, that
defines groups of scatterers as clusters located around the transmitters and
receivers. In general,
the more clusters and the larger their angular spread, the higher spatial
diversity and capacity
achievable over wireless links. Clustered channel models have been validated
through practical
measurements [1-2] and variations of those models have been adopted by
different indoor (i.e.,
IEEE 802.11n Technical Group [3] for WLAN) and outdoor (3GPP Technical
Specification
Group for 3G cellular systems [4]) wireless standards.
[00256] Other factors that determine the spatial diversity in wireless
channels are the
characteristics of the antenna arrays, including: antenna element spacing [5-
7], number of
antennas [8-9], array aperture [10-11], array geometry [5,12,13], polarization
and antenna pattern
[14-2S].
[00257] A unified model describing the effects of antenna array design as
well as the
characteristics of the propagation channel on the spatial diversity (or
degrees of freedom) of
wireless links was presented in [29]. The received signal model in [29] is
given by
y(q) = C(q, p)x(p)dp + z(q)
where x(p) E C3 is the polarized vector describing the transmit signal, p, q E
R3 are the
polarized vector positions describing the transmit and receive arrays,
respectively, and C(.,.) E
C 3X3 is the matrix describing the system response between transmit and
receive vector positions
given by
48
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
C(q, p) = A, (q, iti)H (ft, ii)At(u, p)chidiri
where At(y), Ar(,.) E C3x3 are the transmit and receive array responses
respectively and
Ii) E C3x3 is the channel response matrix with entries being the complex gains
between
transmit direction Ii and receive direction ril. In DIDO systems, user devices
may have single or
multiple antennas. For the sake of simplicity, we assume single antenna
receivers with ideal
isotropic patterns and rewrite the system response matrix as
C(q, p) = f H(q,11)A(1, p)dli
where only the transmit antenna pattern A(11, p) is considered.
[00258] From
the Maxwell equations and the far-field term of the Green function, the array
response can be approximated as [29]
ineputo
A(11, p) ¨ _____________________ 2 (I 111111) a01, p)
2X. do
with p IP, P is the space that defines the antenna array and where
p) = exp(¨j2ir p)
with p) n 0
x P. For unpolarized antennas, studying the array response is equivalent to
study
the integral kernel above. Hereafter, we show closed for expressions of the
integral kernels for
different types of arrays.
Unpolarized Linear Arrays
[00259] For
unpolarized linear arrays of length L (normalized by the wavelength) and
antenna elements oriented along the z-axis and centered at the origin, the
integral kernel is given
by [29]
a(cos 0 , p,) = exp(¨ja p, cos 0) .
[00260]
Expanding the above equation into a series of shifted dyads, we obtain that
the sine
function have resolution of 1/L and the dimension of the array-limited and
approximately
wavevector-limited subspace (i.e., degrees of freedom) is
DF = L
where no = {cos 0 : OE }. We observe that for broadside arrays lOol = 101
whereas for endfire
1001 "=-' ielzi2.
Unpolarized Spherical Arrays
[00261] The
integral kernel for a spherical array of radius R (normalized by the
wavelength)
is given by [29]
a(ii, p) = expt ¨j27ER [sin 0 sin 0 cos(4) ¨ 0') + cos 0 cos 0 ] }.
49
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[00262] Decomposing the above function with sum of spherical Bessel
functions of the first
kind we obtain the resolution of spherical arrays is 1/(icR2) and the degrees
of freedom are given
by
DF = AII = 1LR21S21
[00263] where A is the area of the spherical array and
c [0,n) x [0,270.
Areas of Coherence in Wireless Channels
[00264] The relation between the resolution of spherical arrays and their
area A is depicted in
Figure 43. The sphere in the middle is the spherical array of area A. The
projection of the
channel clusters on the unit sphere defines different scattering regions of
size proportional to the
angular spread of the clusters. The area of size 1/A within each cluster,
which we call "area of
coherence", denotes the projection of the basis functions of the radiated
field of the array and
defines the resolution of the array in the wayevector domain.
[00265] Comparing Figure 43 with Figure 44, we observe that the size of the
area of
coherence decreases as the inverse of the size of the array. In fact, larger
arrays can focus energy
into smaller areas, yielding larger number of degrees of freedom D. Note that
to total number of
degrees of freedom depends also on the angular spread of the cluster, as shown
in the definition
above.
[00266] Figure 45 depicts another example where the array size covers even
larger area than
Figure 44, yielding additional degrees of freedom. In DIDO systems, the array
aperture can be
approximated by the total area covered by all DIDO transmitters (assuming
antennas are spaced
fractions of wavelength apart). Then Figure 45 shows that DIDO systems can
achieve increasing
numbers of degrees of freedom by distributing antennas in space, thereby
reducing the size of the
areas of coherence. Note that these figures are generated assuming ideal
spherical arrays. In
practical scenarios, DIDO antennas spread random across wide areas and the
resulting shape of
the areas of coherence may not be as regular as in the figures.
[00267] Figure 46 shows that, as the array size increases, more clusters
are included within
the wireless channel as radio waves are scatterered by increasing number of
objects between
DIDO transmitters. Hence, it is possible to excite an increasing number of
basis functions (that
span the radiated field) ,yielding additional degrees of freedom, in agreement
with the definition
above.
[00268] The multi-user (MU) multiple antenna systems (MAS) described in
this patent
application exploit the area of coherence of wireless channels to create
multiple simultaneous
independent non-interfering data streams to different users. For given channel
conditions and
user distribution, the basis functions of the radiated field are selected to
create independent and
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
simultaneous wireless links to different users in such a way that every user
experiences
interference-free links. As the MU-MAS is aware of the channel between every
transmitter and
every user, the precoding transmission is adjusted based on that information
to create separate
areas of coherence to different users.
[00269] In one embodiment of the invention, the MU-MAS employs non-linear
precoding,
such as dirty-paper coding (DPC) [30-31] or Tomlinson-Harashima (TH) [32-33]
precoding. In
another embodiment of the invention, the MU-MAS employs non-linear precoding,
such as
block diagonalization (BD) as in our previous patent applications [0003-0009]
or zero-forcing
beamforming (ZF-BF) [34].
[00270] To enable precoding, the MU-MAS requires knowledge of the channel
state
information (CSI). The CSI is made available to the MU-MAS via a feedback
channel or
estimated over the uplink channel, assuming uplink/downlink channel
reciprocity is possible in
time division duplex (TDD) systems. One way to reduce the amount of feedback
required for
CSI, is to use limited feedback techniques [35-37]. In one embodiment, the MU-
MAS uses
limited feedback techniques to reduce the CSI overhead of the control channel.
Codebook design
is critical in limited feedback techniques. One embodiment defines the
codebook from the basis
functions that span the radiated field of the transmit array.
1002711 As the users move in space or the propagation environment changes
over time due to
mobile objects (such as people or cars), the areas of coherence change their
locations and shape.
this is due to well know Doppler effect in wireless communications. "t he MU-
MAS described in
this patent application adjusts the precoding to adapt the areas of coherence
constantly for every
user as the environment changes due to Doppler effects. This adaptation of the
areas of
coherence is such to create simultaneous non-interfering channels to different
users.
[00272] Another embodiment of the invention adaptively selects a subset of
antennas of the
MU-MAS system to create areas of coherence of different sizes. For example, if
the users are
sparsely distributed in space (i.e., rural area or times of the day with low
usage of wireless
resources), only a small subset of antennas is selected and the size of the
area of coherence are
large relative to the array size as in Figure 43. Alternatively, in densely
populated areas (i.e.,
urban areas or time of the day with peak usage of wireless services) more
antennas are selected
to create small areas of coherence for users in direct vicinity of each other.
[00273] In one embodiment of the invention, the MU-MAS is a DIDO system as
described in
previous patent applications [0003-0009]. The DIDO system uses linear or non-
linear precoding
and/or limited feedback techniques to create area of coherence to different
users.
Numerical Results
51
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[00274] We
begin by computing the number of degrees of freedom in conventional multiple-
input multiple-output (MIMO) systems as a function of the array size. We
consider unpolarized
linear arrays and two types of channel models: indoor as in the IEEE 802.11n
standard for WiFi
systems and outdoor as in the 3GPP-LTE standard for cellular systems. The
indoor channel
mode in [3] defines the number of clusters in the range [2, 6] and angular
spread in the range
[15 , 401. The outdoor channel model for urban micro defines about 6 clusters
and the angular
spread at the base station of about 20'.
[00275] Figure
47 shows the degrees of freedom of MIMO systems in practical indoor and
outdoor propagation scenarios. For example, considering linear arrays with ten
antennas spaced
one wavelength apart, the maximum degrees of freedom (or number of spatial
channels)
available over the wireless link is limited to about 3 for outdoor scenarios
and 7 for indoor. Of
course, indoor channels provide more degrees of freedom due to the larger
angular spread.
[00276] Next
we compute the degrees of freedom in DIDO systems. We consider the case
where the antennas distributed over 3D space, such as downtown urban scenarios
where DIDO
access points may be distributed on different floors of adjacent building. As
such, we model the
DIDO transmit antennas (all connected to each other via fiber or DSL backbone)
as a spherical
array. Also, we assume the clusters are uniformly distributed across the solid
angle.
[00277] Figure
48 shows the degrees of freedom in DIDO systems as a function of the array
diameter. We observe that for a diameter equal to ten wavelengths, about 1000
degrees of
freedom are available in the D1DU system. In theory, it is possible to create
up to 1000 non-
interfering channels to the users. The increased spatial diversity due to
distributed antennas in
space is the key to the multiplexing gain provided by DIDO over conventional
MIMO systems.
[00278] As a
comparison, we show the degrees of freedom achievable in suburban
environments with DIDO systems. We assume the clusters are distributed within
the elevation
angles [a, it - a], and define the solid angle for the clusters as lI = 41r
cos a. For example, in
suburban scenarios with two-story buildings, the elevation angle of the
scatterers can be a =
600. In that case, the number of degrees of freedom as a function of the
wavelength is shown in
Figure 48.
References
[00279] [1] A.
A. M. Saleh and R. A. Valenzuela, "A statistical model for indoor
multipath propagation," IEEE Jour. Select. Areas in Comm., vol.195 SAC-5, no.
2, pp. 128-137,
Feb. 1987.
[00280] [2] J.
W. Wallace and M. A. Jensen, "Statistical characteristics of measured
MIMO wireless channel data and comparison to conventional models," Proc. IEEE
Veh.
Technol. Conf., vol. 2, no. 7-11, pp. 1078-1082, Oct. 2001.
52
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[00281] [3] V. Erceg et al., "TGn channel models,- IEEE 802.11-03/940r4,
May 2004.
[00282] [4] 3GPP Technical Specification Group, "Spatial channel model, SCM-
134 text
V6.0," Spatial Channel Model AHG (Combined ad-hoc from 3GPP and 3GPP2), Apr.
2003.
[00283] [5] D.-S. Shiu, G. J. Foschini, M. J. Gans, and J. M. Kahn, "Fading
correlation
and its effect on the capacity of multielement antenna systems," IEEE Trans.
Comm., vol. 48,
no. 3, pp. 502-513, Mar. 2000.
[00284] [6] V. Pohl, V. Jungnickel, T. Haustein, and C. von Helmoit,
"Antenna spacing in
MIMO indoor channels," Proc. IEEE Veh. Technol. Conf., vol. 2, pp. 749-753,
May 2002.
[00285] [7] M. Stoytchev, H. Safar, A. L. Moustakas, and S. Simon, "Compact
antenna
arrays for MIMO applications," Proc. IEEE Antennas and Prop. Symp., vol. 3,
pp. 708-711, July
2001.
[00286] [8] K. Sulonen, P. Suvikunnas, L. Vuokko, J. Kivinen, and P.
Vainikainen,
"Comparison of MIMO antenna configurations in picocell and microcell
environments," IEEE
Jour. Select. Areas in Comm., vol. 21, pp. 703-712, June 2003.
[00287] [9] Shuangqing Wei, D. L. Goeckel, and R. Janaswamy, "On the
asymptoticcapacity of MIMO systems with fixed length linear antenna arrays,"
Proc. IEEE Int.
Conf. on Comm., vol. 4, pp. 2633-2637,2003.
[00288] [10] T. S. Pollock, T. D. Abhayapala, and R. A. Kennedy, "Antenna
saturation
effects on MIMO capacity," Proc. IEEE Int. Conf. on Comm., 192 vol. 4, pp.
2301-2305, May
2003.
[00289] [11] M. L. Morris and M. A. Jensen, "The impact of array
configuration on
MIMO wireless channel capacity," Proc. IEEE Antennas and Prop. Symp., vol. 3,
pp. 214-217,
June 2002.
[00290] [12] Liang Xiao, Lin Dal, Hairuo Zhuang, Shidong Zhou, and Yan Yao,
"A
comparative study of MIMO capacity with different antenna topologies," IEEE
ICCS'02, vol. 1,
pp. 431-435, Nov. 2002.
[00291] [13] A. Forenza and R. W. Heath Jr., "Impact of antenna geometry on
MIMO
communication in indoor clustered channels," Proc. IEEE Antennas and Prop.
Symp., vol. 2, pp.
1700-1703, June 2004.
1002921 [14] M. R. Andrews, P. P. Mitra, and R. deCaryalho, "Tripling the
capacity of
wireless communications using electromagnetic polarization," Nature, vol. 409,
pp. 316-318,
Jan. 2001.
[00293] [15] D.D. Stancil, A. Berson, J.P. Van't Hof, R. Negi, S. Sheth,
and P. Patel,
"Doubling wireless channel capacity using co-polarised, co-located electric
and magnetic
dipoles," Electronics Letters, vol. 38, pp. 746-747, July 2002.
53
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[00294] [16] T. Svantesson, "On capacity and correlation of multi-antenna
systems
employing multiple polarizations," Proc. IEEE Antennas and Prop. Symp., vol.
3, pp. 202-205,
June 2002.
[00295] [17] C. Degen and W. Keusgen, "Performance evaluation of MIMO
systems
using dual-polarized antennas," Proc. IEEE Int. Conf. on Telecommun., vol. 2,
pp. 1520-1525,
Feb. 2003.
[00296] [18] R. Vaughan, "Switched parasitic elements for antenna
diversity," IEEE
Trans. Antennas Propagat., vol. 47, pp. 399-405, Feb. 1999.
[00297] [19] P. Mattheijssen, M. H. A. J. Herben, G. Dolmans, and L.
Leyten, "Antenna-
pattern diversity versus space diversity for use at handhelds," IEEE Trans. on
Veh. Technol., vol.
53, pp. 1035-1042, July 2004.
[00298] [20] L. Dong, H. Ling, and R. W. Heath Jr., "Multiple-input
multiple-output
wireless communication systems using antenna pattern diversity," Proc. IEEE
Glob. Telecom.
Conf., vol. 1, pp. 997-1001, Nov. 2002.
[00299] [21] J. B. Andersen and B. N. Getu, "The MIMO cube-a compact MIMO
antenna," IEEE Proc. of Wireless Personal Multimedia Communications Int.
Symp., vol. 1, pp.
112-114, Oct. 2002.
[00300] [22] C. Waldschmidt, C. Kuhnert, S. Schulteis, and W. Wiesbeck,
"Compact
MIMO-arrays based on polarisation-diversity," Proc. IEEE Antennas and Prop.
Symp., vol. 2,
pp. 499-502, June 2003.
[00301] [23] C. B. Dietrich Jr, K. Dietze, J. R. Nealy, and W. L. Stutzman,
"Spatial,
polarization, and pattern diversity for wireless handheld terminals," Proc.
IEEE Antennas and
Prop. Symp., vol. 49, pp. 1271-1281, Sep. 2001.
[00302] [24] S. Visuri and D. T. Slock, "Colocated antenna arrays: design
desiderata for
wireless communications," Proc. of Sensor Array and Multichannel Sign. Proc.
Workshop, pp.
580-584, Aug. 2002.
[00303] [25] A. Forenza and R. W. Heath Jr., "Benefit of pattern diversity
via 2-element
array of circular patch antennas in indoor clustered MIMO channels," IEEE
Trans. on
Communications, vol. 54, no. 5, pp. 943-954, May 2006.
1003041 [26] A. Forenza and R. W. Heath, Jr., "Optimization Methodology for
Designing 2-CPAs Exploiting Pattern Diversity in Clustered MIMO Channels",
IEEE Trans. on
Communications, Vol. 56, no. 10, pp. 1748-1759, Oct. 2008.
[00305] [27] D. Piazza, N. J. Kirsch, A. Forenza, R. W. Heath, Jr., and K.
R. Dandekar,
"Design and Evaluation of a Reconfigurable Antenna Array for MIMO Systems,"
IEEE
Transactions on Antennas and Propagation, vol. 56, no. 3, pp. 869-881, March
2008.
54
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[00306] [28] R. Bhagavatula, R. W. Heath, Jr., A. Forenza, and S.
Vishwanath, "Sizing
up MIMO Arrays," IEEE Vehicular Technology Magazine, vol. 3, no. 4, pp. 31-38,
Dec. 2008.
[00307] [29] Ada Poon, R. Brodersen and D. Tse, "Degrees of Freedom in
Multiple
Antenna Channels: A Signal Space Approach" , IEEE Transactions on Information
Theory, vol.
51(2), Feb. 2005, pp. 523-536.
[00308] [30] M. Costa, "Writing on dirty paper," IEEE Transactions on
Information
Theory, Vol. 29, No. 3, Page(s): 439 - 441, May 1983.
[00309] [31] U. Erez, S. Shamai (Shitz), and R. Zamir, "Capacity and
lattice-strategies for
cancelling known interference," Proceedings of International Symposium on
Information
Theory, Honolulu, Hawaii, Nov. 2000.
[00310] [32] M. Tomlinson, "New automatic equalizer employing modulo
arithmetic,"
Electronics Letters, Page(s): 138- 139, March 1971.
[00311] [33] H. Miyakawa and H. Harashima, "A method of code conversion for
digital
communication channels with intersymbol interference," Transactions of the
Institute of
Electronic
[00312] [34] R. A. Monziano and T. W. Miller, Introduction to Adaptive
Arrays, New
York: Wiley, 1980.
[00313] [35] T. Yoo, N. Jindal, and A. Goldsmith, "Multi-antenna broadcast
channels with
limited feedback and user selection," IEEE Journal on Scl. Areas in
Communications, vol. 25,
pp. 1478-91, July '2007.
[00314] [36] P. Ding, D. J. Love, and M. D. Zoltowski, "On the sum rate of
channel
subspace feedback for multi-antenna broadcast channels," in Proc., IEEE
Globeeom, vol. 5, pp.
2699-2703, November 2005.
[00315] [37] N. Jindal, "MIMO broadcast channels with finite-rate
feedback," IEEE
Trans. on Info. Theory, vol. 52, pp. 5045-60, November 2006.
IV. SYSTEM AND METHODS FOR PLANNED EVOLUTION AND
OBSOLESCENCE OF MULTIUSER SPECTRUM
1003161 The growing demand for high-speed wireless services and the
increasing number
of cellular telephone subscribers has produced a radical technology revolution
in the wireless
industry over the past three decades from initial analog voice services (AMPS
11-21) to standards
that support digital voice (GSM [3-4], IS-95 CDMA [51), data traffic (EDGE
[6], EV-DO [7])
and Internet browsing (WiFi [8-9], WiMAX [10-11], 3G [12-13], 4G [14-151).
This wireless
technology growth throughout the years has been enabled by two major efforts:
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
i) The federal communications commission (FCC) [16] has been allocating new
spectrum
to support new emerging standards. For example, in the first generation AMPS
systems
the number of channels allocated by the FCC grew from the initial 333 in 1983
to 416 in
the late 1980s to support the increasing number of cellular clients. More
recently, the
commercialization of technologies like Wi-Fi, Bluetooth and ZigBee has been
possible
with the use of the unlicensed ISM band allocated by the FCC back in 1985
[17].
ii) The wireless industry has been producing new technologies that utilize
the limited
available spectrum more efficiently to support higher data rate links and
increased
numbers of subscribers. One big revolution in the wireless world was the
migration from
the analog AMPS systems to digital D-AMPS and GSM in the 1990s, that enabled
much
higher call volume for a given frequency band due to improved spectral
efficiency.
Another radical shift was produced in the early 2000s by spatial processing
techniques
such as multiple-input multiple-output (MIMO), yielding 4x improvement in data
rate
over previous wireless networks and adopted by different standards (i.e., IEEE
802.11n
for Wi-Fi, IEEE 802.16 for WiMAX, 3G1313 for 4G-LTE).
[00317] Despite efforts to provide solutions for high-speed wireless
connectivity, the
wireless industry is facing new challenges: to offer high-definition (HD)
video streaming to
satisfy the growing demand for services like gaming and to provide wireless
coverage
everywhere (including rural areas, where building the wireline backbone is
costly and
impractical). Currently, the most advanced wireless standard systems (i.e.,
4(i-L 1E) cannot
provide data rate requirements and latency constraints to support HD streaming
services,
particularly when the network is overloaded with a high volume of concurrent
links. Once again,
the main drawbacks have been the limited spectrum availability and lack of
spectrally efficient
technologies that can truly enhance data rate and provide complete coverage.
[00318] A new technology has emerged in recent years called distributed-
input
distributed-output (DIDO) [18-21] and described in our previous patent
applications [0002-
0009]. DIDO technology promises orders of magnitude increase in spectral
efficiency, making
HD wireless streaming services possible in overloaded networks.
1003191 At the same time, the US government has been addressing the issue
of spectrum
scarcity by launching a plan that will free 500MHz of spectrum over the next
10 years. This plan
was released on June 28th, 2010 with the goal of allowing new emerging
wireless technologies to
operate in the new frequency bands and providing high-speed wireless coverage
in urban and
rural areas [22]. As part of this plan, on September 23th, 2010 the FCC opened
up about 200MHz
of the VHF and UHF spectrum for unlicensed use called "white spaces" [23]. One
restriction to
operate in those frequency bands is that harmful interference must not be
created with existing
56
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
wireless microphone devices operating in the same band. As such, on July 22",
2011 the IEEE
802.22 working group finalized the standard for a new wireless system
employing cognitive
radio technology (or spectrum sensing) with the key feature of dynamically
monitoring the
spectrum and operating in the available bands, thereby avoiding harmful
interference with
coexisting wireless devices [24]. Only recently has there been debates to
allocate part of the
white spaces to licensed use and open it up to spectrum auction [25].
[00320] The coexistence of unlicensed devices within the same frequency
bands and
spectrum contention for unlicensed versus licensed use have been two major
issues for FCC
spectrum allocation plans throughout the years. For example, in white spaces,
coexistence
between wireless microphones and wireless communications devices has been
enabled via
cognitive radio technology. Cognitive radio, however, can provide only a
fraction of the spectral
efficiency of other technologies using spatial processing like DIDO.
Similarly, the performance
of Wi-Fi systems have been degrading significantly over the past decade due to
increasing
number of access points and the use of Bluetooth/ZigBee devices that operate
in the same
unlicensed ISM band and generate uncontrolled interference. One shortcoming of
the unlicensed
spectrum is unregulated use of RF devices that will continue to pollute the
spectrum for years to
come. RF pollution also prevents the unlicensed spectrum from being used for
future licensed
operations, thereby limiting important market opportunities for wireless
broadband commercial
services and spectrum auctions.
1003211 We propose a new system and methods that allow dynamic allocation
of the
wireless spectrum to enable coexistence and evolution of different services
and standards. One
embodiment of our method dynamically assigns entitlements to RF transceivers
to operate in
certain parts of the spectrum and enables obsolescence of the same RF devices
to provide:
i) Spectrum reconfigurability to enable new types of wireless operations
(i.e., licensed -Vs.
unlicensed) and/or meet new RF power emission limits. This feature allows
spectrum
auctions whenever is necessary, without need to plan in advance for use of
licensed
versus unlicensed spectrum. It also allows transmit power levels to be
adjusted to meet
new power emission levels enforced by the FCC.
ii) Coexistence of different technologies operating in the same band (i.e.,
white spaces and
wireless microphones, WiFi and Bluetooth/ZigBee) such that the band can be
dynamically reallocated as new technologies are created, while avoiding
interference
with existing technologies.
iii) Seamless evolution of wireless infrastructure as systems migrate to
more advanced
technologies that can offer higher spectral efficiency, better coverage and
improved
57
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
performance to support new types of services demanding higher QoS (i.e., HD
video
streaming).
[00322] Hereafter, we describe a system and method for planned evolution
and
obsolescence of a multiuser spectrum. One embodiment of the system consists of
one or multiple
centralized processors (CP) 4901-4904 and one or multiple distributed nodes
(DN) 4911-4913
that communicate via wireline or wireless connections as depicted in Figure
49. For example, in
the context of 4G-LTE networks [26], the centralized processor is the access
core gateway
(ACGW) connected to several Node B transceivers. In the context of Wi-Fi, the
centralized
processor is the internet service provider (ISP) and the distributed nodes are
Wi-Fi access points
connected to the ISP via moderns or direct connection to cable or DSL. In
another embodiment
of the invention, the system is a distributed-input distributed-output (DIDO)
system [0002-0009]
with one centralized processor (or BTS) and distributed nodes being the DIDO
access points (or
DIDO distributed antennas connected to the BTS via the BSN).
1003231 The DNs 4911-4913 communicate with the CPs 4901-4904. The
information
exchanged from the DNs to the CP is used to dynamically adjust the
configuration of the nodes
to the evolving design of the network architecture. In one embodiment, the DNs
4911-4913 share
their identification number with the CP. The CP store the identification
numbers of all DNs
connected through the network into lookup tables or shared database. Those
lookup tables or
database can be shared with other CPs and that information is synchronized
such that all CPs
have always access to the most up to date information about all llNs on the
network.
[00324] For example, the FCC may decide to allocate a certain portion of
the spectrum to
unlicensed use and the proposed system may be designed to operate within that
spectrum. Due
to scarcity of spectrum, the FCC may subsequently need to allocate part of
that spectrum to
licensed use for commercial carriers (i.e., AT&T, Verizon, or Sprint),
defense, or public safety.
In conventional wireless systems, this coexistence would not be possible,
since existing wireless
devices operating in the unlicensed hand would create harmful interference to
the licensed RF
transceivers. In our proposed system, the distributed nodes exchange control
information with
the CPs 4901-4903 to adapt their RF transmission to the evolving band plan. In
one embodiment,
the DNs 4911-4913 were originally designed to operate over different frequency
bands within
the available spectrum. As the FCC allocates one or multiple portions of that
spectrum to
licensed operation, the CPs exchange control information with the unlicensed
DNs and
reconfigure them to shut down the frequency bands for licensed use, such that
the unlicensed
DNs do not interfere with the licensed DNs. This scenario is depicted in
Figure 50 where the
unlicensed nodes (e.g., 5002) are indicated with solid circles and the
licensed nodes with empty
circles (e.g., 5001). In another embodiment, the whole spectrum can be
allocated to the new
58
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
licensed service and the control information is used by the CPs to shut down
all unlicensed DNs
to avoid interference with the licensed DNs. This scenario is shown in Figure
51 where the
obsolete unlicensed nodes are covered with a cross.
[00325] By way of another example, it may be necessary to restrict power
emissions for
certain devices operating at given frequency band to meet the FCC exposure
limits [27]. For
instance, the wireless system may originally be designed for fixed wireless
links with the DNs
4911-4913 connected to outdoor rooftop transceiver antennas. Subsequently, the
same system
may be updated to support DNs with indoor portable antennas to offer better
indoor coverage.
The FCC exposure limits of portable devices are more restrictive than rooftop
transmitters, due
to possibly closer proximity to the human body. In this case, the old DNs
designed for outdoor
applications can be re-used for indoor applications as long as the transmit
power setting is
adjusted. In one embodiment of the invention the DNs are designed with
predefined sets of
transmit power levels and the CPs 4901-4903 send control information to the
DNs 4911-4913 to
select new power levels as the system is upgraded, thereby meeting the FCC
exposure limits. In
another embodiment, the DNs are manufactured with only one power emission
setting and those
DNs exceeding the new power emission levels are shut down remotely by the CP.
[00326] In one embodiment, the CPs 4901-4903 monitor periodically all DNs
4911-4913
in the network to define their entitlement to operate as RF transceivers
according to a certain
standard. Those DNs that are not up to date can be marked as obsolete and
removed from the
network. For example, the DNs that operate within the current power limit and
frequency band
are kept active in the network, and all the others are shut down. Note that
the DN parameters
controlled by the CP are not limited to power emission and frequency band; it
can be any
parameter that defines the wireless link between the DN and the client
devices.
[00327] In another embodiment of the invention, the DNs 4911-4913 can be
reconfigured
to enable the coexistence of different standard systems within the same
spectrum. For example,
the power emission, frequency band or other configuration parameters of
certain DNs operating
in the context of WLAN can be adjusted to accommodate the adoption of new DNs
designed for
WPAN applications, while avoiding harmful interference.
1003281 As new wireless standards are developed to enhance data rate and
coverage in the
wireless network, the DNs 4911-4913 can be updated to support those standards.
In one
embodiment, the DNs are software defined radios (SDR) equipped with
programmable
computational capability such as FPGA, DSP, CPU, GPU and/or GPGPU that run
algorithms for
baseband signal processing. If the standard is upgraded, new baseband
algorithms can be
remotely uploaded from the CP to the DNs to reflect the new standard. For
example, in one
embodiment the first standard is CDMA-based and subsequently it is replaced by
OFDM
59
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
technology to support different types of systems. Similarly, the sample rate,
power and other
parameters can be updated remotely to the DNs. This SDR feature of the DNs
allows for
continuous upgrades of the network as new technologies are developed to
improve overall
system performance.
[00329] In another embodiment, the system described herein is a cloud
wireless system
consisting of multiple CPs, distributed nodes and a network interconnecting
the CPs to the DNs.
Figure 52 shows one example of cloud wireless system where the nodes
identified with solid
circles (e.g., 5203) communicate to CP 5206, the nodes identified with empty
circles
communicate to CP 5205 and the CPs 5205-5206 communicate between each other
all through
the network 5201. In one embodiment of the invention, the cloud wireless
system is a DIDO
system and the DNs are connected to the CP and exchange information to
reconfigure
periodically or instantly system parameters, and dynamically adjust to the
changing conditions of
the wireless architecture. In the DIDO system, the CP is the DIDO BTS, the
distributed nodes
are the DIDO distributed antennas, the network is the BSN and multiple BTSs
are interconnected
with each other via the DIDO centralized processor as described in our
previous patent
applications [0002-0009].
[00330]
All DNs 5202-5203 within the cloud wireless system can be grouped in different
sets. These sets
of DNs can simultaneously create non-interfering wireless links to the
multitude of client
devices, while each set supporting a different multiple access techniques
(e.g., 1DMA, FDMA,
CDMA, OFDMA and/or SDMA), different modulations (e.g., QAM, OFDM) and/or
coding
schemes (e.g., convolutional coding, LDPC, turbo codes). Similarly, every
client may be served
with different multiple access techniques and/or different modulation/coding
schemes. Based on
the active clients in the system and the standard they adopt for their
wireless links, the CPs 5205-
5206 dynamically select the subset of DNs that can support those standards and
that are within
range of the client devices.
Reference
1003311 [1] Wikipedia, "Advanced Mobile Phone System"
http://en.wikipedia.org/wiki/Advanced Mobile Phone System
1003321 [2] AT&T, "1946: First Mobile Telephone Call"
http ://www.corp. att. c om/attlab s/reputation/timeline/46mobile. html
[00333] [3] GSMA, "GSM technology"
http ://www.gsmworld.com/technology/index.htm
[00334] [4] ETSI, "Mobile technologies GSM"
http ://www.etsi. org/WebSite/Technologies/gsm. aspx
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
[00335] [5] Wikipedia,
http://en.wikipedia.org/wiki/IS-95
[00336] [6] Ericsson, "The evolution of EDGE"
http://www.eriesson.com/res/does/whitepapers/evolution_to_edge.pdf
[00337] [7] Q. Bi (2004-03). "A Forward Link Performance Study of the 1xEV-
DO Rel. 0
System Using Field Measurements and Simulations" (PDF). Lucent Technologies.
http://www.edg.orgiresources/white_papers/files/Lueent%201xEV-
D0%20Rev /0200%20Mar%2004.pdf
[00338] [8] Wi-Fi alliance, http://www.wi-fi.org/
1003391 [9] Wi-Fi alliance, "Wi-Fi certified makes it Wi-Fi"
http://www.wi-fi.org/files/WFA_Certification_Overview_WP_en.pdf
[00340] [10] WiMAX forum, http://www.wimaxforum.org/
[00341] [11] C. Eklund, R. B. Marks, K. L. Stanwood and S. Wang, "IEEE
Standard
802.16: A Technical Overview of the WirelessMAN1mAir Interface for Broadband
Wireless
Access"
http ://ieee802. org/16/docs/02/C 80216-02_05 .pdf
[00342] [12] 3GPP, "UMTS", http://www.3gpp.org/article/umts
[00343] [13] H. Ekstrom, A. Furuskar, J. Karlsson, M. Meyer, S. Parkvall,
J. Torsner, and
M. Wahlqvist "Technical Solutions for the 3G Long-Term Evolution", IEEE
Communications
Magazine, pp.38-45, Mar. 2006
[00344] [14] 3GPP, "LTE", http://www.3gpp.org/LTE
[00345] [15] Motorola, "Long Term Evolution (LTE): A Technical Overview",
http://business.motorola.com/experiencelte/pdf/LTETechnicalOverview.pdf
[00346] [16] Federal Communications Commission, "Authorization of Spread
Spectrum
Systems Under Parts 15 and 90 of the FCC Rules and Regulations", June 1985.
[00347] [1 7] ITU, "ISM band" http://www.itthint/ITU-
R/terrestrial/faq/index.html#013
[00348] [18] S. Perlman and A. Forenza "Distributed-input distributed-
output (DIDO)
wireless technology: a new approach to multiuser wireless", Aug. 2011
http://www.rearden.com/DIDO/DIDO White Paper 110727.pdf
1003491 [19] Bloomberg Businessweek, "Steve Penman's Wireless Fix", July
27, 2011
http://www.businessweek.com/magazine/the-edison-of-silicon-valley-
07272011.html
[00350] [20] Wired, "Has OnLive's Steve Perlman Discovered Holy Grail of
Wireless?",
June 30, 2011
http://www.wired.com/epicenter/2011/06/perlman-holy-grail-wireless/
61
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464
PCT/US2013/039580
[00351] [21] The Wall Street Journal "Silicon Valley Inventor's Radical
Rewrite of
Wireless", July 28, 2011
http://blogs. wsj .com/digits/2011/07/28/silicon-valley-inventors-radical-
rewrite-of-wireless/
[00352] [22] The White House, "Presidential Memorandum: Unleashing the
Wireless
Broadband Revolution", June 28, 2010
http ://www.whitehouse. gov/the-press-office/presidential-memorandum-
unleashing-wireless-
broadband-revolution
[00353] [23] FCC, "Open commission meeting", Sept. 23th, 2010
http://reboot.fcc.gov/open-meetings/2010/september
1003541 [24] IEEE 802.22, "IEEE 802.22 Working Group on Wireless Regional
Area
Networks", http ://www. i eee802. org/22/
[00355] [25] "A bill",112th congress, lst session, July 12, 2011
http ://repub lic ans. energycommerc e.house.gov/M
edia/file/Hearings/Telecom/071511/D is cus sion
Draft.pdf
[00356] [26] H. Ekstrom, A. Furuskar, J. Karlsson, M. Meyer, S. Parkvall,
J. Torsner, and
M. Wahlqvist "Technical Solutions for the 3G Long-Term Evolution", IEEE
Communications
Magazine, pp.38-45, Mar. 2006
[00357] [27] FCC, "Evaluating compliance with FCC guidelines for human
exposure to
radiofrequeney electromagnetic fields," OET Bulletin 65, Edition 97-01, Aug.
1997
V. SYSTEM AND
METHOD TO COMPENSATE FOR DOPPLER EFFECTS IN
DISTRIBUTED-INPUT DISTRIBUTED-OUTPUT WIRELESS SYSTEMS
[00358] In this portion of the detailed description we describe a multiuser
(MU) multiple
antenna system (MAS) for multiuser wireless transmissions that adaptively
reconfigures its
parameters to compensate for Doppler effects due to user mobility or changes
in the propagation
environment. In one embodiment, the MAS is a distributed-input distributed-
output (DIDO)
system as described the co-pending patent applications [0002-0016] and
depicted in Figure 53.
The DIDO system of one embodiment includes the following components:
= User Equipment (UE): The UE 5301 of one embodiment includes an RF
transceiver for
fixed or mobile clients receiving data streams over the downlink (DL) channel
from the
DIDO backhaul and transmitting data to the DIDO backhaul via the uplink (UL)
channel
= Base Transceiver Station (BTS): The BTSs 5310-5314 of one embodiment
interface the
DIDO backhaul with the wireless channel. BTSs 5310-5314 are access points
consisting
of DAC/ADC and radio frequency (RF) chain to convert the baseband signal to
RF. In
some cases, the BTS is a simple RF transceiver equipped with power
amplifier/antenna
62
SUBSTITUTE SHEET (RULE 26)
CA 02872502 2014-11-03
WO 2013/166464 PCT/US2013/039580
and the RF signal is carried to the BTS via RF-over-fiber technology as
described in our
patent application [0010].
= Controller (CTR): The CTR 5320 in one embodiment is one particular type
of BTS
designed for certain specialized features such as transmitting training
signals for
time/frequency synchronization of the BTSs and/or the UEs,
receiving/transmitting
control information from/to the UEs, receiving the channel state information
(CSI) or
channel quality information from the UEs.
= Centralized Processor (CP): The CP 5340 of one embodiment is a DIDO
server
interfacing the Internet or other types of external networks 5350 with the
DIDO
backhaul. The CP computes the DIDO baseband processing and sends the waveforms
to
the distributed BTSs for DL transmission
= Base Station Network (BSN): The BSN 5330 of one embodiment is the network
connecting the CP to the distributed BTSs carrying information for either the
DL or the
UL channel. The BSN is a wireline or a wireless network or a combination of
the two.
For example, the BSN is a DSL, cable, optical fiber network, or line-of-sight
or non-line-
of-sight wireless link. Furthermore, the BSN is a proprietary network, or a
local area
network, or the Internet.
1003591 As described in the co-pending applications, the DIDO system
creates independent
channels to multiple users, such that each user receives interference-free
channels. In DIDO
systems, this is achieved by employing distributed antennas or BTSs to exploit
spatial diversity.
In one embodiment, the DIDO system exploits spatial, polarization and/or
pattern diversity to
increase the degrees of freedom within each channel. The increased degrees of
freedom of the
wireless link are used to transmit independent data streams to an increased
number of UEs (i.e.,
multiplexing gain) and/or improve coverage (i.e., diversity gain).
[00360] The BTSs 5310-5314 are placed anywhere that is convenient where
there is access to
the Internet or BSN. In one embodiment of the invention, the UEs 5301-5305 are
placed
randomly between, around and/or surrounded by the BTSs or distributed antennas
as depicted in
Figure 54.
[00361] In one embodiment, the BTSs 5310-5314 send a training signal and/or
independent
data streams to the UEs 5301 over the DL channel as depicted in Figure 55. The
training signal
is used by the UEs for different purposes, such as time/frequency
synchronization, channel
estimation and/or estimation of the channel state information (CSI). In one
embodiment of the
invention, the MU-MAS DL employs non-linear precoding, such as dirty-paper
coding (DPC)
[1-2] or Tomlinson-Harashima (TH) [3-4] precoding. In another embodiment of
the invention,
the MU-MAS DL employs non-linear precoding, such as block diagonalization (BD)
as
63
SUBSTITUTE SHEET (RULE 26)
S
= described in the co-pending patent applications [0003-0009] or zero-
forcing beamforming (ZF-
BF) [5]. If the number of BTSs is larger than the UEs, the extra BTSs are used
to increase link
quality to every UE via diversity schemes such as antenna selection or
eigenmode selection
described in [0002-0016]. If the number of BTSs is smaller than the UEs, the
extra UEs share the
wireless links with the other UEs via conventional multiplexing techniques
(e.g., TDMA,
FDMA, CDMA, OFDMA).
100362] The UL channel is used to transmit data from the UEs
5301 to the CP 5340 and/or
the CSI (or channel quality information) employed by the DIDO precoder. In one
embodiment,
the UL channels from the UEs are multiplexed via conventional multiplexing
techniques (e.g.,
TDMA, FDMA, CDMA, OFDMA) to the CTR as depicted in Figure 56 or to the closest
BTS.
In another embodiment of the invention, spatial processing techniques are used
to separate the
UL channels from the UEs 5301 to the distributed BTSs 5310-5314 as depicted in
Figure 57.
For example, UL streams are transmitted from the client to the DIDO antennas
via multiple-input
multiple-output (MIMO) multiplexing schemes. The MIMO multiplexing schemes
include
transmitting independent data streams from the clients and using linear or non-
linear receivers at
the DIDO antennas to remove co-channel interference. In another embodiment,
the downlink
weights are used over the uplink to demodulate the uplink streams, assuming
UL/DL channel
reciprocity holds and the channel does not vary significantly between DL and
UL transmission
due to Doppler effects. In another embodiment, a maximum ratio combining (MRC)
receiver is
used over the UL channel to increase signal quality at the DIDO antennas from
every client.
1003631 The data, control information and CSI sent over the
DL/UL channels is shared
between the CP 5340 and the BTSs 5310-5314 via the BSN 5330. The known
training signals
for the DL channel can be stored in memory at the BTSs 5310-5314 to reduce
overhead over the
BSN 5330. Depending on the type of network (i.e., wireless versus wireline,
DSL versus cable or
fiber optic), there may not be a sufficient data rate available over the BSN
5330 to exchange
information between the CP 5340 and the BTSs 5310-5314, especially when the
baseband signal
is delivered to the BTSs. For example, let us assume the BTSs transmit 10Mbps
independent
data streams to every UE over 5MHz bandwidth (depending on the digital
modulation and FEC
coding scheme used over the wireless link). If 16 bits of quantization are
used for the real and 16
for the imaginary components, the baseband signal requires 160Mbps of data
throughput from
the CP to the BTSs over the BSN. In one embodiment, the CP and the BTSs are
equipped with
encoders and decoders to compress and decompress information sent over the
BSN. In the
forward link, the precoded baseband data sent from the CP to the BTSs is
compressed to reduce
the amount of bits and overhead sent over the BSN. Similarly, in the reverse
link, the CSI as well
as data (sent over the uplink channel from the UEs to the BTSs) are compressed
before being
64
CA 2872502 2020-03-06
S
= transmitted over the BSN from the BTSs to the CP. Different compression
algorithms are
employed to reduce the amount of bits and overhead sent over the BSN,
including but not limited
to lossless and/or lossy techniques [6].
1003641 One feature of DIDO systems employed in one embodiment
is making the CP 5340
aware of the CSI or channel quality information between all BTSs 53105314 and
UEs 5301 to
enable precoding. As explained in [0006], the performance of DIDO depends on
the rate at
which the CSI is delivered to the CP relative to the rate of change of the
wireless links. It is well
known that variations of the channel complex gain are due to UE mobility
and/or changes in the
propagation environment that cause Doppler effects. The rate of change of the
channel is
measured in terms of channel coherence time (TO that is inversely proportional
to the maximum
Doppler shift. For DIDO transmissions to perform reliably, the latency due to
CSI feedback must
be a fraction (e.g., 1/10 or less) of the channel coherence time. In one
embodiment, the latency
over the CSI feedback loop is measured as the time between the time at which
the CSI training is
sent and the time the precoded data is demodulated at the UE side, as depicted
in Figure 58.
1003651 In frequency division duplex (FDD) DIDO systems the BTSs
5310-5314 send CSI
training to the UEs 5301, that estimate the CSI and feedback to the BTSs. Then
the BTSs send
the CSI via the BSN to the CP 5340, that computes the DIDO precoded data
streams and sends
those back to the BTSs via the BSN 5330. Finally the BTSs send precoded
streams to the UEs
that demodulate the data. Referring to Figure 58, the overall latency for the
DIDO feedback loop
is given by
2*TDL + TUL TBSN TCP
where TDL and TuL include the times to build, send and process the downlink
and uplink frames,
respectively, TBSN is the round-trip delay over the BSN and Tcp is the time
taken by the CP to
process the CSI, generate the precoded data streams for the UEs and schedule
different UEs for
the current transmission. In this case, TDL is multiplied by 2 to account for
the training signal
time (from the BTS to the UE) and the feedback signal time (from the UE to the
BTS). In time
division duplex (TDD), if channel reciprocity can be exploited, the first step
is skipped (i.e.,
transitting a CSI training signal from the BTS to the UE) as the UEs send CSI
training to the
BTSs that compute the CSI and send it to the CP. Hence, in this embodiment,
the overall latency
for the DIDO feedback loop is
TDL + TuL + Taw + Tcp
1003661 The latency TBSN depends on the type of BSN whether
dedicated cable, DSL, fiber
optic connection or general Internet. Typical values may vary between
fractions of lmsec to
50msec. The computational time at the CP can be reduced if the DIDO processing
is
implemented at the CP on dedicated processors such as ASIC, FPGA, DSP, CPU,
GPU and/or
CA 2872502 2020-03-06
=
= GPGPU. Moreover, if the number of BTSs 5310-5314 exceeds the number of
UEs 5301, all the
UEs can be served at the same time, thereby removing latency due to multiuser
scheduling.
Hence, the latency TCp is negligible compared to TBsN. Finally, transmit and
receive processing
for the DL and UL is typically implemented on ASIC, FPGA or DSP with
negligible
computational time and if the signal bandwidth is relatively large (e.g. more
than 1MHz) the
frame duration can be made very small (i.e., less than lmsec). Therefore, also
TDL and Tim are
negligible compared to TBsN.
[00367] In one embodiment of the invention, the CP 5340 tracks
the Doppler velocity of all
UEs 5301 and dynamically assigns the BTSs 5310-5314 with the lowest TBsN to
the UEs with
higher Doppler. This adaptation is based on different criteria:
= Type of BSN: For example, dedicated fiber optic links typically
experience lower
latency than cable modems or DSL. Then the lower latency BSNs are used for
high-
mobility UEs (e.g., cars on freeways, trains), whereas the higher-latency BSNs
are used
for the fixed-wireless or low-mobility UEs (e.g., home equipment, pedestrians,
cars in
residential areas)
= Type of QoS: For example, the BSN can support different types of DIDO or
non-DIDO
traffic. It is possible to define quality of service (QoS) with different
priorities for
different types of traffic. For example, the BSN assigns high priority to DIDO
traffic
and low priority to non-DIDO traffic. Alternatively, high priority QoS is
assigned to
traffic for high-mobility UEs and low priority QoS to UEs with low-mobility.
= Long-term statistics: For example, the traffic over the BSN may vary
significantly
depending on the time of the day (e.g., night use for homes and day use for
offices).
Higher traffic load may result in higher latency. Then, in different times of
the day, the
BSNs with higher traffic, if it results in higher latency, are used for low-
mobility UEs,
whereas the BSNs with lower traffic, if it results in lower latency, are used
for the high-
mobility UEs
= Short-term statistics: For example, any BSN can be affected by temporary
network
congestion that can result in higher latency. Then the CP can adaptively
select the BTSs
from congested BSNs, if the congestion cause higher latency, for the low-
mobility UEs
and the remaining BSNs, if they are lower latency, for the high-mobility UEs.
[00368] In another embodiment of the invention, the. BTSs 5310-
5314 are selected based on
the Doppler experienced on each individual BTS-UE link. For example, in the
line-of-sight
(LOS) link B in Figure 59, the maximum Doppler shift is a function of the
angle (0) between
the BTS-UE link and the vehicular velocity (v), according to the well known
equation
66
CA 2872502 2020-03-06
S
=fd = -A = cos cf)
where A is the wavelength corresponding to the carrier frequency. Hence, in
LOS channels the
Doppler shift is maximum for link A and nearly zero for link C in Figure 59.
In non-LOS
(NLOS) the maximum Doppler shift depends on the direction of the multipaths
around the UEs,
but in general because of the distributed nature of the BTSs in DIDO systems,
some BTSs will
experience higher Doppler for a given HE (e.g., BTS 5312) whereas other BTSs
will experience
lower Doppler for that given HE (e.g., BTS 5314).
1003691 In one embodiment, the CP tracks the Doppler velocity
over every BTS-UE link and
selects only the links with the lowest Doppler effect for every UE. Similarly
to the techniques
described in [0002], the CP 5340 defines the "user cluster" for every HE 5301.
The user cluster
is the set of BTSs with good link quality (defined based on certain signal-to-
noise ratio, SNR,
threshold) to the UE and low Doppler (defined, for example, based on a
predefined Doppler
threshold) as depicted in Figure 60. In Figure 60, BTSs 5 through 10 all have
good SNR to the
HE 1, but only BTSs 6 through 9 experience low Doppler effect (e.g., below the
specified
threshold).
1003701 The CP of this embodiement records all of the values of
SNR and Doppler for every
BTS-UE link into a matrix and for each IJE it selects the submatrix that
satisfies the SNR and
Doppler thresholds. In the example depicted in Figure 61, the submatrix is
identified by the
green dotted line surrounding C2,6, C2,7, C3,9, C4,7, C4,8, C4,9, and C5,6.
DIDO precoding weights
are computed for that UE based on that submatrix. Note that BTSs 5 and 10 are
reachable by
UEs 2,3,4,5 and 7 as shown in the table in Figure 61. Then, to avoid
interference to UE1 when
transmitting to those other UEs, the BTSs 5 and 10 either must switched off or
assigned to
different orthogonal channels based on conventional multiplexing techniques
such as TDMA,
FDMA, CDMA or OFDMA.
1003711 In another embodiment, the adverse effect of Doppler on
the performance of DIDO
precoding systems is reduced via linear prediction, which is one technique to
estimate the
complex channel coefficients in the future based on past channel estimates. By
way of example
and not limitation, different prediction algorithms for single-input single-
output (SISO) and
OFDM wireless systems were proposed in [7-11]. Knowing the future channel
complex
coefficients it is possible to reduce the error due to outdated CSI. For
example, Figure 62 shows
the channel gain (or CSI) at different times: i) ten is the time at which the
CTR in Figure 58
receives the CSI from the UEs in FDD systems (or equivalently the BTSs
estimate the CSI from
the UL channel exploiting DL/UL reciprocity in TDD systems); ii) tcp is the
time at which the
CSI is delivered to the CP via the BSN; iii) tBTS is the time at which the CSI
is used for
67
CA 2872502 2020-03-06
S
= precoding over the wireless link. In Figure 62 we observe that due to the
delay TBsN (also
depicted in Figure 58), the CSI estimated at time tc-TR will be outdated
(i.e., complex channel
gain has changed) by the time is used for wireless transmission over the DL
channel at time twrs.
One way to avoid this effect due to Doppler is to run the prediction method at
the CP. The CSI
estimates available at the CP at time tCTR is delayed of TBsN/2 due to CTR-to-
CP latency and
corresponds to the channel gain at time to in Figure 62. Then, the CP uses all
or part of the CSI
estimated before time to and stored in memory to predict the future channel
coefficient at time
to+TssN = tap. If the prediction algorithm has minimal error propagation, the
predicted CSI at
time tcp reproduces reliably the channel gain in the future. The time
difference between the
predicted CSI and the current CSI is called prediction horizon and in SISO
systems typically
scales with the channel coherence time.
[00372] In DIDO systems the prediction algorithm is more complex
since it estimates the
future channel coefficients both in time and space domains. Linear prediction
algorithms
exploiting spatio-temporal characteristics of MIMO wireless channels were
described in [12-13].
In [13] it was shown that the performance of the prediction algorithms in MIMO
systems
(measured in terms of mean squared error, or MSE) improves for higher channel
coherence time
(i.e., reduce Doppler effect) and lower channel coherence distance (due to
lower spatial
correlation). Hence the prediction horizon (expressed in seconds) of spatial-
temporal methods is
directly proportional to the channel coherence time and inversely proportional
to the channel
coherence distance. In DIDO systems the coherence distance is low due to high
spatial
selectivity produce by the distributed antennas.
100373] Described herein is are prediction techniques that
exploit temporal and spatial
diversity of DIDO systems to predict the vector channel (i.e.. CSI from the
BTSs to the UEs) in
the future. These embodiments exploit spatial diversity available in wireless
channels to obtain
negligible CSI prediction error and an extended prediction horizon over any
existing SISO and
MIMO prediction algorithms. One important feature of these techniques is to
exploit distributed
antennas given that they receive uncorrelated complex channel coefficients
from the distributed
UEs.
1003741 In one embodiment of the invention, the spatial and
temporal predictor is combined
with estimator in the frequency domain to allow CS1 prediction over all the
available subcarriers
in the system, such as in OFDM systems. In another embodiment of the
invention, the DIDO
precoding weights are predicted (rather than the CSI) based on previous
estimates of the DIDO
weights.
References
68
CA 2872502 2020-03-06
S
= [00375] [1] M. Costa, "Writing on dirty paper," IEEE Transactions
on Information
Theory, Vol. 29, No. 3, Page(s): 439 -441, May 1983.
[00376] [2] U. Erez, S. Shamai (Shitz), and R. Zamir,
"Capacity and lattice-strategies for
cancelling known interference," Proceedings of International Symposium on
Information
Theory, Honolulu, Hawaii, Nov. 2000.
[00377] [3] M. Tomlinson, "New automatic equalizer employing
modulo arithmetic,"
Electronics Letters, Page(s): 138 - 139, March 1971.
[00378] [4] H. Miyakawa and H. Harashima, "A method of code
conversion for digital
communication channels with intersymbol interference," Transactions of the
Institute of
Electronic
[00379] [5] R. A. Monziano and T. W. Miller, Introduction to
Adaptive Arrays, New
York: Wiley, 1980.
[00380] [6] Guy E. Blelloch, "Introduction to Data
Compression", Carnegie Mellon
University Tech. Report Sept. 2010
[00381] [7] A. Duel-Hallen, S. Hu, and H. Hallen, "Long-Range
Prediction of Fading
Signals," IEEE Signal Processing Mag., vol. 17, no. 3, pp. 62-75, May 2000.
[00382] [8] A. Forenza and R. W. Heath, Jr., "Link Adaptation
and Channel Prediction in
Wireless OFDM Systems," in Proc. IEEE Midwest Symp. on Circuits and Sys., Aug
2002, pp.
211-214.
[00383] [9] M. Stemad and D. Aronsson, "Channel estimation and
prediction for adaptive
OFDM downlinks [vehicular applications]," in Proc. IEEE Vehicular Technology
Conference,
vol. 2, Oct 2003, pp. 1283-1287.
[00384] [10] D. Schafhuber and G. Matz, "MMSE and Adaptive
Prediction of Time-
Varying Channels for OFDM Systems," IEEE Trans. Wireless Commun., vol. 4, no.
2, pp. 593-
602, Mar 2005.
[00385] [1111. C. Wong and B. L. Evans, "Joint Channel
Estimation and Prediction for
OFDM Systems," in Proc. IEEE Global Telecommunications Conference, St. Louis,
MO, Dec
2005.
[00386] [12] M. Guillaud and D. Slock, "A specular approach to
MIMO
frequencyselective channel tracking and prediction," in Proc. IEEE Signal
Processing Advances
in Wireless Communications, July 2004, pp. 59-63.
[00387] [13] Wong, I.C. Evans, B.L., "Exploiting Spatio-
Temporal Correlations in
MIMO Wireless Channel Prediction", IEEE Globecom Conf., pp.1-5, Dec. 2006
[00388] Embodiments of the invention may include various steps as
set forth above. The
steps may be embodied in machine-executable instructions which cause a general-
purpose or
69
CA 2872502 2020-03-06
S
= special-purpose processor to perform certain steps. For example, the
various components within
the Base Stations/APs and Client Devices described above may be implemented as
software
executed on a general purpose or special purpose processor. To avoid obscuring
the pertinent
aspects of the invention, various well known personal computer components such
as computer
memory, hard drive, input devices, etc., have been left out of the figures.
[00389] Alternatively, in one embodiment, the various functional
modules illustrated herein
and the associated steps may be performed by specific hardware components that
contain
hardwired logic for performing the steps, such as an application-specific
integrated circuit
("ASIC") or by any combination of programmed computer components and custom
hardware
components.
[00390] In one embodiment, certain modules such as the Coding,
Modulation and Signal
Processing Logic 903 described above may be implemented on a programmable
digital signal
processor ("DSP") (or group of DSPs) such as a DSP using a Texas Instruments'
TMS320x
architecture (e.g., a TMS320C6000, TMS320C5000, . . . etc). The DSP in this
embodiment may
be embedded within an add-on card to a personal computer such as, for example,
a PCI card. Of
course, a variety of different DSP architectures may be used while still
complying with the
underlying principles of the invention.
[00391] Elements of the present invention may also be provided
as a machine-readable
medium for storing the machine-executable instructions. The machine-readable
medium may
include, but is not limited to, flash memory, optical disks, CD-ROMs, DVD
ROMs, RAMs,
EPROMs, EEPROMs, magnetic or optical cards, propagation media or other type of
machine-
readable media suitable for storing electronic instructions. For example, the
present invention
may be downloaded as a computer program which may be transferred from a remote
computer
(e.g., a server) to a requesting computer (e.g., a client) by way of data
signals embodied in a
carrier wave or other propagation medium via a communication link (e.g., a
modem or network
connection).
[00392] Throughout the foregoing description, for the purposes
of explanation, numerous
specific details were set forth in order to provide a thorough understanding
of the present system
and method. It will be apparent, however, to one skilled in the art that the
system and method
may be practiced without some of these specific details. Accordingly, the
scope and spirit of the
present invention should be judged in terms of the claims which follow.
[00393] Moreover, throughout the foregoing description, numerous
publications were cited
to provide a more thorough understanding of the present invention. All of
these cited references
are incorporated into the present application by reference.
CA 2872502 2020-03-06
APPENDIX
U.S. Application No. 11/256,478 filed on 21 October 2005
U.S. Issued Patent 7711030 issued on 04 May 2010
"System and Method for Spatial-Multiplexed Tropospheric Scatter
Communications"
Attorney Docket No. 6181P514X (corrected from 6181P014X)
U.S. Application No. 12/630,627 filed on 03 December 2009
"System and Method for Distributing Antenna Wireless Communications"
Attorney Docket No. 6181P515X
71
CA 2872502 2020-03-06
3 WO 2013/166464
PCT/US2013/039580
06181.P014X
Patent
UNITED STATES PATENT APPLICATION
for
SYSTEM AND METHOD FOR SPATIAL-MULTIPLEXED TROPOSPHERIC
SCATTER COMMUNICATIONS
INVENTOR.
Steve Perlman
Prepared by:
BLAKELY, SOKOLOFF, TAYLOR & ZAFMAN, LLP
12400 WILSHIRE BOULEVARD
SEVENTH FLOOR
LOS ANGELES, CALIFORNIA 90025
(408) 720-8598
Attorney's Docket No. 06181.P014X
72
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
SYSTEM AND METHOD FOR SPATIAL-MULTIPLEXED TROPOSPHERIC
SCATTER COMMUNICATIONS
BACKGROUND OF THE INVENTION
Field of the Invention
[0001] This application is a continuation-in-part of co-pending U.S. Patent
Application No. 10/902,978, entitled, "System And Method For Distributed Input-
Distributed Output Wireless Communications" filed on July 30, 2004.
[0002] This invention relates generally to the field of communication systems.
More particularly, the invention relates to a system and method for
distributed
input-distributed output wireless communications using space-time coding
techniques.
Description of the Related Art
Space-Time Coding of Communication Signals
[0003] A relatively new development in wireless technology is known as spatial
multiplexing and space-time coding. One particular type of space-time coding
is
called MIMO for "Multiple Input Multiple Output" because several antennas are
used on each end. By using multiple antennas to send and receive, multiple
independent radio waves may be transmitted at the same time within the same
frequency range. The following articles provide an overview of MIMO:
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL.
21, NO. 3, APRIL 2003: "From Theory to Practice: An Overview of MIMO
Space¨Time Coded Wireless Systems", by David Gesbert, Member, IEEE,
Exp. Mail No.: EV4717133726US
06181.P014X
73
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
Mansoor Shafi, Fellow, IEEE, Da-shan Shiu, Member, IEEE, Peter J. Smith,
Member, IEEE, and Ayman Naguib, Senior Member, IEEE.
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 50, NO. 12,
DECEMBER 2002: "Outdoor MIMO Wireless Channels: Models and
Performance Prediction", David Gesbert, Member, IEEE, Helmut BOIcskei,
Member, IEEE, Dhananjay A. Gore, and Arogyaswami J. Paulraj, Fellow, IEEE.
[0004] Fundamentally, MIMO technology is based on the use of spatially
distributed antennas for creating parallel spatial data streams within a
common
frequency band. The radio waves are transmitted in such a way that the
individual signals can be separated at the receiver and demodulated, even
though they are transmitted within the same frequency band, which can result
in
multiple statistically independent (i.e. effectively separate) communications
channels. Thus, in contrast to standard wireless communication systems which
attempt to inhibit multi-path signals (i.e., multiple signals at the same
frequency
delayed in time, and modified in amplitude and phase), MIMO can rely on
uncorrelated or weakly-correlated multi-path signals to achieve a higher
throughput and improved signal-to-noise ratio within a given frequency band.
By
way of example, using MIMO technology within an 802.11g system, Airgo
Networks was recently able to achieve 108 Mbps in the same spectrum where a
conventional 802.11g system can achieve only 54 Mbps (this is described on
Airgo's website, currently at htto://www.aircionetworks.com).
Exp. Mail No.: EV4717133726US
06181.P014X
74
SUBSTITUTE SHEET (RULE 26)
CA 2872 502 2 020-0 3-0 6
WO 2013/166464
PCT/US2013/039580
[0005] MIMO systems typically face a practical limitation of fewer than 10
antennas per device (and therefore less than 10X throughput improvement in the
network) for several reasons:
1. Physical limitations: MIMO antennas on a given device must have
sufficient separation between them so that each receives a statistically
independent signal. Although MIMO bandwidth improvements can be seen with
antenna spacing of even one-sixth wavelength (A/6), the efficiency rapidly
deteriorates as the antennas get closer, resulting in lower MIMO bandwidth
multipliers. Also, as the antennas are crowded together, the antennas
typically
must be made smaller, which can impact bandwidth efficiency as well. Finally,
with lower frequencies and longer wavelengths, the physical size of a single
MIMO device can become unmanageable. An extreme example is in the HF
band, where MI MO device antennas may have to be separated from each other
by 10 meters or more.
2. Noise limitations. Each MIMO receiver/transmitter subsystem
produces a certain level of noise. As more and more of these subsystems are
placed in close proximity to each other, the noise floor increases. Meanwhile,
as
increasingly more distinct signals need to be distinguished from each other in
a
many-antenna MIMO system, an increasingly lower noise floor is required.
3. Cost and power limitations. Although there are MIMO applications
where cost and power consumption are not at issue, in a typical wireless
product,
both cost and power consumption are critical constraints in developing a
Exp. Mail No.: EV4717133726US
06181.P014X
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT1US2013/039580
successful product. A separate RF subsystem is required for each MIMO
antenna, including separate Analog-to-Digital (ND) and Digital-to-Analog (D/A)
converters. Unlike many aspects of digital systems which scale with Moore's
Law, such analog-intensive subsystems typically have certain physical
structural
size and power requirements, and scale in cost and power linearly. So, a many-
antenna MIMO device would become prohibitively expensive and power
consumptive compared to a single-antenna device.
[0006] As a result of the above, most MIMO systems contemplated today are on
the order of 2-to-4 antennas, resulting in a 2-to-4X increase in bandwidth,
and
some increase in SNR due to the diversity benefits of a multi-antenna system.
Up
to 10 antenna MIMO systems have been contemplated (particularly at higher
microwave frequencies due to shorter wavelengths and closer antenna spacing),
but much beyond that is impractical except for very specialized and cost-
insensitive applications.
Virtual Antenna Arrays
[0007] One particular application of MIMO-type technology is a virtual antenna
array. Such a system is proposed in a research paper presented at European
Cooperation in the field of Scientific and Technical Research, EURO-COST,
Barcelona, Spain, Jan 15-17, 2003: Center for Telecommunications Research,
King's College London, UK: "A step towards MIMO: Virtual Antenna Arrays",
Mischa Dohler & Hamid Aghvami.
Exp. Mail No.: EV4717133726US
06181.P014X
76
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
1 WO 2013/166464
PCT/US2013/039580
[0008] Virtual antenna arrays, as presented in this paper, are systems of
cooperative wireless devices (such as cell phones), which communicate amongst
each other (if and when they are near enough to each other) on a separate
communications channel than their primary communications channel to the their
base station so as to operate cooperatively (e.g. if they are GSM cellular
phones
in the UHF band, this might be a 5 GHz Industrial Scientific and Medical (ISM)
wireless band). This allows single antenna devices, for example, to
potentially
achieve MIMO-like increases in bandwidth by relaying information among several
devices in range of each other (in addition to being in range of the base
station)
to operate as if they are physically one device with multiple antennas.
[0009] In practice, however, such a system is extremely difficult to implement
and of limited utility. For one thing, there are now a minimum of two distinct
communications paths per device that must be maintained to achieve improved
throughput, with the second relaying link often of uncertain availability.
Also, the
devices are more expensive, physically larger, and consume more power since
they have at a minimum a second communications subsystem and greater
computational needs. In addition, the system is reliant on very sophisticated
real-time of coordination of all devices, potentially through a variety of
communications links. Finally, as the simultaneous channel utilization (e.g.
the
simultaneous phone call transmissions utilizing MIMO techniques) grows, the
computational burden for each device grows (potentially exponentially as
channel
utilization increases linearly), which may very well be impractical for
portable
devices with tight power and size constraints.
Exp. Mail No.: EV4717133726US
06181.P014X
77
CA 2 8 7250 2 2 02 0 -0 3-0 6 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/1JS2013/039500
SUMMARY OF THE INVENTION
[0010] A method is described comprising: transmitting a training signal from
each antenna of a base station to each of a plurality of client devices
utilizing
tropospheric scatter, each of the client devices analyzing each training
signal to
generate channel characterization data, and transmitting the channel
characterization data back to the base station utilizing tropospheric scatter;
storing the channel characterization data for each of the plurality of client
devices; receiving data to be transmitted to each of the client devices; and
precoding the data using the channel characterization data associated with
each
respective client device to generate precoded data signals for each antenna of
the base station; and transmitting the precoded data signals through each
antenna of the base station to each respective client device.
Exp. Mail No.: EV4717133726US
06181.P014X
78
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
1 WO 2013/166464
PCT/US2013/039580
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] A better understanding of the present invention can be obtained from
the
following detailed description in conjunction with the drawings, in which:
[0012] FIG. 1 illustrates a prior art M IMO system.
[0013] FIG. 2 illustrates an N-antenna Base Station communicating with a
plurality of Single-antenna Client Devices.
[0014] FIG. 3 illustrates a three Antenna Base Station communicating with
three
Single-Antenna Client Devices
[0015] FIG. 4 illustrates training signal techniques employed in one
embodiment
of the invention.
[0016] FIG. 5 illustrates channel characterization data transmitted from a
client
device to a base station according to one embodiment of the invention.
[0017] FIG. 6 illustrates a Multiple-Input Distributed-Output ("MIDO")
downstream transmission according to one embodiment of the invention.
[0018] FIG. 7 illustrates a Multiple-Input Multiple Output ("MIMO") upstream
transmission according to one embodiment of the invention.
[0019] FIG. 8 illustrates a base station cycling through different client
groups to
allocate bandwidth according to one embodiment of the invention.
Exp. Mail No.: EV4717133726US
06181.P014X
79
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
[0020] FIG. 9 illustrates a grouping of clients based on proximity according
to
one embodiment of the invention.
[0021] FIG. 10 illustrates an embodiment of the invention employed within an
NVIS system.
[0022] FIG. 11 illustrates an embodiment of the invention employing the use of
tropospheric scatter.
[0023] FIG. 12 illustrates a prior art tropospheric scatter transmission
system.
[0024] FIG. 13 illustrates an embodiment of the invention employing the use of
a
tropospheric scatter transmission system over a coverage area.
[0025] FIG. 14 illustrates a Direct Broadcast Satellite dish and RF signal
paths in
an embodiment of the invention.
[0026] FIG. 15 illustrates an embodiment of the invention employing the use of
conventional MI MO with tropospheric scatter.
[0027] Figure 16 illustrates an overhead view of a coverage area surrounded by
12 clusters of 3 antennas.
[0028] Figures 17a-c illustrates 3 client antennas in a coverage area from
different elevation views.
Exp. Mail No.: EV4717133726US
06181.P014X
CA 2872502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS
[0029] In the following description, for the purposes of explanation, numerous
specific details are set forth in order to provide a thorough understanding of
the
present invention. It will be apparent, however, to one skilled in the art
that the
present invention may be practiced without some of these specific details. In
other instances, well-known structures and devices are shown in block diagram
form to avoid obscuring the underlying principles of the invention.
[0030] Figure 1 shows a prior art MIMO system with transmit antennas 104 and
receive antennas 105. Such a system can achieve up to 3X the throughput that
would normally be achievable in the available channel. There are a number of
different approaches in which to implement the details of such a MIMO system
which are described in published literature on the subject, and the following
explanation describes one such approach.
[0031] Before data is transmitted in the MIMO system of Figure 1, the channel
is
"characterized." This is accomplished by initially transmitting a "training
signal"
from each of the transmit antennas 104 to each of the receivers 105. The
training signal is generated by the coding and modulation subsystem 102,
converted to analog by a D/A converter (not shown), and then converted from
baseband to RE by each transmitter 103, in succession. Each receive antenna
105 coupled to its RF Receiver 106 receives each training signal and converts
it
to baseband. The baseband signal is converted to digital by a D/A converter
(not
shown), and the signal processing subsystem 107 characterizes the training
Exp. Mail No.: EV4717133726US
06181.P014X
81
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
410 WO 2013/166464
PCT/US2013/039580
110
signal. Each signal's characterization may include many factors including, for
example, phase and amplitude relative to a reference internal to the receiver,
an
absolute reference, a relative reference, characteristic noise, or other
factors.
Each signal's characterization is typically defined as a vector that
characterizes
phase and amplitude changes of several aspects of the signal when it is
transmitted across the channel. For example, in a quadrature amplitude
modulation ("QAM")-modulated signal the characterization might be a vector of
the phase and amplitude offsets of several multipath images of the signal. As
another example, in an orthogonal frequency division multiplexing ("OFDM")-
modulated signal, it might be a vector of the phase and amplitude offsets of
several or all of the individual sub-signals in the OFDM spectrum.
[0032] The signal processing subsystem 107 stores the channel characterization
received by each receiving antenna 105 and corresponding receiver 106. After
all three transmit antennas 104 have completed their training signal
transmissions, then the signal processing subsystem 107 will have stored three
channel characterizations for each of three receiving antennas 105, resulting
in a
3x3 matrix 108, designated as the channel characterization matrix, "FT." Each
individual matrix element Ho is the channel characterization (which is
typically a
vector, as described above) of the training signal transmission of transmit
antenna 104 i as received by the receive antenna 105j.
[0033] At this point, the signal processing subsystem 107 inverts the matrix
II
108, to produce H-1, and awaits transmission of actual data from transmit
Exp. Mail No.: EV4717133726US
06181.P014X
82
SUBSTITUTE SHEET (RULE 26)
CA 2872502 2020-03-06
SWO 2013/166464
PCT/US2013/039580
=
antennas 104. Note that various prior art M IMO techniques described in
available
literature, can be utilized to ensure that the H matrix 108 can be inverted.
[0034] In operation, a payload of data to be transmitted is presented to the
data
Input subsystem 100. It is then divided up into three parts by splitter 101
prior to
being presented to coding and modulation subsystem 102. For example, if the
payload is the ASCII bits for "abcdef," it might be divided up into three sub-
payloads of ASCII bits for "ad," "be," and "cf by Splitter 101. Then, each of
these
sub-payloads is presented individually to the coding and modulation subsystem
102.
[0035] Each of the sub-payloads is individually coded by using a coding system
suitable for both statistical independence of each signal and error correction
capability. These include, but are not limited to Reed-Solomon coding, Viterbi
coding, and Turbo Codes. Finally, each of the three coded sub-payloads is
modulated using an appropriate modulation scheme for the channel. Example
modulation schemes are differential phase shift key ("DPSK") modulation, 64-
QAM modulation and OFDM. It should be noted here that the diversity gains
provided by MI MO allow for higher-order modulation constellations that would
otherwise be feasible in a SISO (Single Input-Single Output) system utilizing
the
same channel. Each coded and modulated signal is then transmitted through its
own antenna 104 following D/A conversion by a D/A conversion unit (not shown)
and RF generation by each transmitter 103.
Exp. Mail No.: EV4717133726US
06181.P014X
83
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
411
[0036] Assuming that adequate spatial diversity exists amongst the transmit
and
receive antennas, each of the receiving antennas 105 will receive a different
combination of the three transmitted signals from antennas 104. Each signal is
received and converted down to baseband by each RF receiver 106, and
digitized by an ND converter (not shown). If yõ is the signal received by the
nth
receive antenna 105, and xõ is the signal transmitted by nth transmit antenna
104, and N is noise, this can be described by the following three equations.
yi X1 FIII -I- X2 1121 +X3 1131 +N
Y2 - X1 H12 + X2 H22 + X3 H32 N
y3 = x H13 + X2 H23 + X3 H33 +N
[0037] Given that this is a system of three equations with three unknowns, it
is a
matter of linear algebra for the signal processing subsystem 107 to derive X1,
X2,
and x3 (assuming that N is at a low enough level to permit decoding of the
signals):
xl= YI11-111 + Y211-112 Y3H-113
X2= Y1H-121 + Y2H-I22 + Y3H-123
X3= Y1H 131 + Y2H 132 + Y3H 133
[0038] Once the three transmitted signals xn are thus derived, they are then
demodulated, decoded, and error-corrected by signal processing subsystem 107
to recover the three bit streams that were originally separated out by
splitter 101.
These bit streams are combined in combiner unit 108, and output as a single
Exp. Mail No.: EV4717133726US
06181.P014X
84
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
data stream from the data output 109. Assuming the robustness of the system is
able to overcome the noise impairments, the data output 109 will produce the
same bit stream that was introduced to the data Input 100.
[0039] Although the prior art system just described is generally practical up
to
four antennas, and perhaps up to as many as 10, for the reasons described in
the Background section of this disclosure, it becomes impractical with large
numbers of antennas (e.g. 25, 100, or 1000).
[0040] Typically, such a prior art system is two-way, and the return path is
implemented exactly the same way, but in reverse, with each side of the
communications channels having both transmit and receive subsystems.
[0041] Figure 2 illustrates one embodiment of the invention in which a Base
Station 200 is configured with a Wide Area Network interface (e.g. to the
Internet
through a Ti or other high speed connection) 201 and is provisioned with a
number (n) of antennas 202. There are a number of Client Devices 203-207,
each with a single antenna, which are served wirelessly from the Base Station
200. Although for the purposes of this example it is easiest to think about
such a
Base Station as being located in an office environment where it is serving
Client
Devices 203-207 that are wireless-network equipped personal computers, this
architecture will apply to a large number of applications, both indoor and
outdoor,
where a Base Station is serving wireless clients. For example, the Base
Station
could be based at a cellular phone tower, or on a television broadcast tower.
In
one embodiment, the Base Station 200 is positioned on the ground and is
Exp. Mail No.: EV4717133726US
06181.P014X
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
0
configured to transmit upward at HF frequencies (e.g., frequencies up to
24MHz)
to bounce signals off the ionosphere as described in co-pending application
entitled SYSTEM AND METHOD FOR ENHANCING NEAR VERTICAL
INCIDENCE SKYWAVE ("NVIS") COMMUNICATION USING SPACE-TIME
CODING, Serial No. 10/817,731, Filed April 2, 2004 which is assigned to the
assignee of the present application and which is incorporated herein by
reference. In another embodiment, the Base Station 200 is positioned on the
ground and is configured to transmit at angle into the troposphere using
tropospheric scatter ("troposcatter") techniques.
[0042] Certain details associated with the Base Station 200 and Client Devices
203-207 set forth above are for the purpose of illustration only and are not
required for complying with the underlying principles of the invention. For
example, the Base Station may be connected to a variety of different types of
wide area networks via WAN interface 201 including application-specific wide
area networks such as those used for digital video distribution. Similarly,
the
Client Devices may be any variety of wireless data processing and/or
communication devices including, but not limited to cellular phones, personal
digital assistants ("PDAs"), receivers, and wireless cameras.
[0043] In one embodiment, the Base Station's n Antennas 202 are separated
spatially such that each is transmitting and receiving signals which are not
spatially correlated, just as if the Base Station was a prior art MIMO
transceiver.
As described in the Background, experiments have been done where antennas
Exp. Mail No.: EV4717133726US
06181.P014X
86
SUBSTITUTE SHEET (RULE 26)
CA 2872502 2020-03-06
=
WO 2013/166464 PCT/US2013/039580
placed within )1/4/6 (i.e. 1/6 wavelength) apart successfully achieve an
increase in
bandwidth from MI MO, but generally speaking, the further apart these Base
Station antennas are placed, the better the system performance, and A/2 is a
desirable minimum. Of course, the underlying principles of the invention are
not
limited to any particular separation between antennas.
[0044] Note that a single Base Station 200 may very well have its antennas
located very far apart. For example, in the HF spectrum, the antennas may be
10
meters apart or more (e.g., in an NVIS implementation mentioned above). If 100
such antennas are used, the Base Station's antenna array could well occupy
several square kilometers.
[0045] In addition to spatial diversity techniques, one embodiment of the
invention polarizes the signal in order to increase the effective bandwidth of
the
system. Increasing channel bandwidth through polarization is a well known
technique which has been employed by satellite television providers for years.
Using polarization, it is possible to have multiple (e.g., three) Base Station
antennas very close to each other, and still be not spatially correlated.
Although
conventional RF systems usually will only benefit from the diversity of two
dimensions (e.g. x and y) of polarization, the architecture descried herein
may
further benefit from the diversity of three dimensions of polarization (x, y
and z).
[0046] Figure 3 provides additional detail of one embodiment of the Base
Station 200 and Client Devices 203-207 shown in Figure 2. For the purposes of
simplicity, the Base Station 300 is shown with only three antennas 305 and
only
Exp. Mail No.: EV4717133726US
06181.P014X
87
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
=
three Client Devices 306-308. It will be noted, however, that the embodiments
of
the invention described herein may be implemented with a virtually unlimited
number of antennas 305 (i.e., limited only by available space and noise) and
Client Devices 306-308.
[0047] Figure 3 is similar to the prior art MIMO architecture shown in Figure
1 in
that both have three antennas on each sides of a communication channel. A
notable difference is that in the prior art MIMO system the three antennas 105
on
the right side of Figure 1 are all a fixed distance from one another (e.g.,
integrated on a single device), and the received signals from each of the
antennas 105 are processed together in the Signal Processing subsystem 107.
By contrast, in Figure 3, the three antennas 309 on the right side of the
diagram
are each coupled to a different Client Device 306-308, each of which may be
distributed anywhere within range of the Base Station 305. As such, the signal
that each Client Device receives is processed independently from the other two
received signals in its Coding, Modulation, Signal Processing subsystem 311.
Thus, in contrast to a Multiple-Input (i.e. antennas 105) Multiple-Output
(i.e.
antennas 104) "MIMO" system, Figure 3 illustrates a Multiple Input (i.e.
antennas
309) Distributed Output (i.e. antennas 305) system, referred to hereinafter as
a
"MIDO" system.
[0048] The MIDO architecture shown in Figure 3 achieves a similar bandwidth
increase as MIMO over a SISO system for a given number of transmitting
antennas. However, one difference between MIMO and the particular MIDO
Exp. Mail No.: EV4717133726US
06181.P014X
88
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
embodiment illustrated in Figure 3 is that, to achieve the bandwidth increase
provided by multiple base station antennas, each MIDO Client Device 306-308
requires only a single receiving antenna, whereas with MIMO, each Client
Device
requires as least as many receiving antennas as the bandwidth multiple that is
hoped to be achieved. Given that there is usually a practical limit to how
many
antennas can be placed on a Client Device (as explained in the Background),
this typically limits MIMO systems to between four to ten antennas (and 4X to
10X bandwidth multiple). Since the Base Station 300 is typically serving many
Client Devices from a fixed and powered location, is it practical to expand it
to far
more antennas than ten, and to separate the antennas by a suitable distance to
achieve spatial diversity. As illustrated, each antenna is equipped with a
transceiver 304 and a portion of the processing power of a Coding, Modulation,
and Signal Processing section 303. Significantly, in this embodiment, no
matter
how much Base Station 300 is expanded, each Client Device 306-308 only will
require one antenna 309, so the cost for an individual user Client Device 306-
308
will be low, and the cost of Base Station 300 can be shared among a large base
of users.
[0049] An example of how a MIDO transmission from the Base Station 300 to
the Client Devices 306-308 can be accomplished is illustrated in Figures 4
through 6.
[0050] In one embodiment of the invention, before a MIDO transmission begins,
the channel is characterized. As with a MIMO system, a training signal is
Exp. Mail No.: EV4717133726US
06181.P014X
89
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCMS2013/039580
=
transmitted (in the embodiment herein described), one-by-one, by each of the
antennas 405. Figure 4 illustrates only the first training signal
transmission, but
with three antennas 405 there are three separate transmissions in total. Each
training signal is generated by the Coding, Modulation, and Signal Processing
subsystem 403, converted to analog through a D/A converter, and transmitted as
RF through each RE Transceiver 404. Various different coding, modulation and
signal processing techniques may be employed including, but not limited to,
those described above (e.g., Reed Solomon, Viterbi coding; QAM, DPSK, QPSK
modulation,. .. etc).
[0051] Each Client Device 406-408 receives a training signal through its
antenna
409 and converts the training signal to baseband by Transceiver 410. An AID
converter (not shown) converts the signal to digital where is it processed by
each
Coding, Modulation, and Signal Processing subsystem 411. Signal
characterization logic 320 then characterizes the resulting signal (e.g.,
identifying
phase and amplitude distortions as described above) and stores the
characterization in memory. This characterization process is similar to that
of
prior art M IMO systems, with a notable difference being that the each client
device only computes the characterization vector for its one antenna, rather
than
for n antennas. For example, the Coding Modulation and Signal Processing
subsystem 420 of client device 406 is initialized with a known pattern of the
training signal (either at the time of manufacturing, by receiving it in a
transmitted
message, or through another initialization process). When antenna 405
transmits
the training signal with this known pattern, Coding Modulation and Signal
Exp. Mail No.: EV4717133726US
06181.P014X
SUBSTITUTE SHEET (RULE 26)
CA 2872 502 2 020-0 3-0 6
=
WO 2013/166464 PCT/US2013/039580
=
Processing subsystem 420 uses correlation methods to find the strongest
received pattern of the training signal, it stores the phase and amplitude
offset,
then it subtracts this pattern from the received signal. Next, it finds then
second
strongest received pattern that correlates to the training signal, it stores
the
phase and amplitude offset, then it subtracts this second strongest pattern
from
the received signal. This process continues until either some fixed number of
phase and amplitude offsets are stored (e.g. eight), or a detectable training
signal
pattern drops below a given noise floor. This vector of phase/amplitude
offsets
becomes element H11 of the vector 413. Simultaneously, Coding Modulation and
Signal Processing subsystems for Client Devices 407 and 408 implement the
same processing to produce their vector elements H21 and H31.
[0052] The memory in which the characterization is stored may be a non-
volatile
memory such as a Flash memory or a hard drive and/or a volatile memory such
as a random access memory (e.g., SDRAM, RDAM). Moreover, different Client
Devices may concurrently employ different types of memories to store the
characterization information (e.g., PDA's may use Flash memory whereas
notebook computers may use a hard drive). The underlying principles of the
invention are not limited to any particular type of storage mechanism on the
various Client Devices or the Base Station.
[0053] As mentioned above, depending on the scheme employed, since each
Client Device 406-408 has only one antenna, each only stores a 1x3 column
413-415 of the H matrix. Figure 4 illustrates the stage after the first
training
Exp. Mail No.: EV4717133726US
06181.P014X
91
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
signal transmission where the first row of 1x3 columns 413-415 has been stored
with channel characterization information for the first of the three Base
Station
antennas 405. The remaining two columns are stored following the channel
characterization of the next two training signal transmissions from the
remaining
two base station antennas. Note that for the sake of illustration the three
training
signals are transmitted at separate times. If the three training signal
patterns are
chosen such as not to be correlated to one another, they may be transmitted
simultaneously, thereby reducing training time.
[0054] As indicated in Figure 5, after all three pilot transmissions are
complete,
each Client Device 506-508 transmits back to the Base Station 500 the 1x3
column 513-515 of matrix H that it has stored. To the sake of simplicity, only
one
Client Device 506 is illustrated transmitting its characterization information
in
Figure 5. An appropriate modulation scheme (e g DPSK, 640AM, OFDM) for
the channel combined with adequate error correction coding (e.g. Reed
Solomon, Viterbi, and/or Turbo codes) may be employed to make sure that the
Base Station 500 receives the data in the columns 513-515 accurately.
[0055] Although all three antennas 505 are shown receiving the signal in
Figure
5, it is sufficient for a single antenna and transceiver of the Base Station
500 to
receive each 1x3 column 513-515 transmission. However, utilizing many or all
of
antennas 505 and Transceivers 504 to receive each transmission (i.e.,
utilizing
prior art Single-Input Multiple-Output ("SIMO") processing techniques in the
Coding, Modulation and Signal Processing subsystem 503) may yield a better
Exp. Mail No.: EV4717133726US
06181.P014X
92
SUBSTITUTE SHEET (RULE 26)
CA 2872 502 2 020-0 3-0 6
WO 2013/166464
PCT/US2013/039580
=
signal-to-noise ratio ("SNR") than utilizing a single antenna 505 and
Transceiver
504 under certain conditions.
[0056] As the Coding, Modulation and Signal Processing subsystem 503 of Base
Station 500 receives the 1x3 column 513-515, from each Client Device 507-508,
it stores it in a 3x3 H matrix 516. As with the Client Devices, the Base
Station
may employ various different storage technologies including, but not limited
to
non-volatile mass storage memories (e.g., hard drives) and/or volatile
memories
(e.g., SDRAM) to store the matrix 516. Figure 5 illustrates a stage at which
the
Base Station 500 has received and stored the 1x3 column 513 from Client
Device 509. The 1x3 columns 514 and 515 may be transmitted and stored in H
matrix 516 as they are received from the remaining Client Devices, until the
entire H matrix 516 is stored.
[0057] One embodiment of a MIDO transmission from a Base Station 600 to
Client Devices 606-608 will now be described with reference to Figure 6.
Because each Client Device 606-608 is an independent device, typically each
device is receiving a different data transmission. As such, one embodiment of
a
Base Station 600 includes a Router 602 communicatively positioned between the
WAN Interface 601 and the Coding, Modulation and Signal Processing
subsystem 603 that sources multiple data streams (formatted into bit streams)
from the WAN interface 601 and routes them as separate bit streams u1- u3
intended for each Client Device 606-608, respectively. Various well known
routing techniques may be employed by the router 602 for this purpose.
Exp. Mail No.: EV4717133726US
06181.P014X
93
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
[0058] The three bit streams, ul- u3, shown in Figure 6 are then routed into
the
Coding, Modulation and Signal Processing subsystem 603 and coded into
statistically distinct, error correcting streams (e.g. using Reed Solomon,
Viterbi,
or Turbo Codes) and modulated using an appropriate modulation scheme for the
channel (such as DPSK, 64QAM or OFDM). In addition, the embodiment
illustrated in Figure 6 includes signal precoding logic 630 for uniquely
coding the
signals transmitted from each of the antennas 605 based on the signal
characterization matrix 616. More specifically, rather than routing each of
the
three coded and modulated bit streams to a separate antenna (as is done in
Figure 1), in one embodiment, the precoding logic 630 multiplies the three bit
streams 741-743 in Figure 6 by the inverse of the H matrix 616, producing
three
new bit streams, u'r u'3. The three precoded bit streams are then converted to
analog by D/A converters (not shown) and transmitted as RF by Transceivers
604 and antennas 605.
[0059] Before explaining how the bit streams are received by the Client
Devices
606-608, the operations performed by the precoding module 630 will be
described. Similar to the MIMO example from Figure 1 above, the coded and
modulated signal for each of the three source bit streams will be designated
with
un. In the embodiment illustrated in Figure 6, each ui contains the data from
one
of the three bit streams routed by the Router 602, and each such bit stream is
intended for one of the three Client Devices 606-608.
Exp. Mail No.: EV4717133726US
06181.P014X
94
CA 2 8 7250 2 2 02 0 -0 3-0 6 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
[0060] However, unlike the MIMO example of Figure 1, where each x, is
transmitted by each antenna 104, in the embodiment of the invention
illustrated
in Figure 6, each ui is received at each Client Device antenna 609 (plus
whatever noise N there is in the channel). To achieve this result, the output
of
each of the three antennas 605 (each of which we will designate as vi) is a
function of u, and the H matrix that characterizes the channel for each Client
Device. In one embodiment, each vi is calculated by the precoding logic 630
within the Coding, Modulation and Signal Processing subsystem 603 by
implementing the following formulas:
Vi = u,H-111 + u2H-112 + u3H-113v2¨ u1H-121 + u21-1-122 + u31-1-123
1/3= u111 131 u2H 132 u3H 133
[0061] Thus, unlike M I MO, where each xi is calculated at the receiver after
the
signals have been transformed by the channel, the embodiments of the invention
described herein solve for each vi at the transmitter before the signals have
been
transformed by the channel. Each antenna 609 receives ui already separated
from the other un_i bit streams intended for the other antennas 609. Each
Transceiver 610 converts each received signal to baseband, where it is
digitized
by an A/D converter (now shown), and each Coding, Modulation and Signal
Processing subsystem 611, demodulates and decodes the x, bit stream intended
for it, and sends its bit stream to a Data Interface 612 to be used by the
Client
Device (e.g., by an application on the client device).
Exp. Mail No.: EV4717133726US
06181.P014X
SUBSTITUTE SHEET (RULE 26)
CA 2872502 2020-03-06
=
WO 2013/166464 PCT/US2013/039580
[0062] The embodiments of the invention described herein may be implemented
using a variety of different coding and modulation schemes. For example, in an
OFDM implementation, where the frequency spectrum is separated into a
plurality of sub-bands, the techniques described herein may be employed to
characterize each individual sub-band. As mentioned above, however, the
underlying principles of the invention are not limited to any particular
modulation
scheme.
[0063] If the Client Devices 606-608 are portable data processing devices such
as PDAs, notebook computers, and/or wireless telephones the channel
characterization may change frequently as the Client Devices may move from
one location to another. As such, in one embodiment of the invention, the
channel characterization matrix 616 at the Base Station is continually
updated.
In one embodiment, the Base Station 600 periodically (e.g., every 250
milliseconds) sends out a new training signal to each Client Device, and each
Client Device continually transmits its channel characterization vector back
to the
Base Station 600 to ensure that the channel characterization remains accurate
(e.g. if the environment changes so as to affect the channel or if a Client
Device
moves). In one embodiment, the training signal is interleaved within the
actual
data signal sent to each client device. Typically, the training signals are
much
lower bandwidth than the data signals, so this would have little impact on the
overall throughput of the system. Accordingly, in this embodiment, the channel
characterization matrix 616 may be updated continuously as the Base Station
actively communicates with each Client Device, thereby maintaining an accurate
Exp. Mail No.: EV4717133726US
06181.P014X
96
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
channel characterization as the Client Devices move from one location to the
next or if the environment changes so as to affect the channel.
[0064] One embodiment of the invention illustrated in Figure 7 employs MIMO
techniques to improve the upstream communication channel (i.e., the channel
from the Client Devices 706-708 to the Base Station 700). In this embodiment,
the channel from each of the Client Devices is continually analyzed and
characterized by upstream channel characterization logic 741 within the Base
Station. More specifically, each of the Client Devices 706-708 transmits a
training signal to the Base Station 700 which the channel characterization
logic
741 analyzes (e.g., as in a typical MIMO system) to generate an N x M channel
characterization matrix 741, where N is the number of Client Devices and M is
the number of antennas employed by the Base Station. The embodiment
illustrated in Figure 7 employs three antennas 705 at the Base Station and
three
Client Devices 706-608, resulting in a 3x3 channel characterization matrix 741
stored at the Base Station 700. The MIMO upstream transmission illustrated in
Figure 7 may be used by the Client Devices both for transmitting data back to
the Base Station 700, and for transmitting channel characterization vectors
back
to the Base Station 700 as illustrated in Figure 5. But unlike the embodiment
illustrated in Figure 5 in which each Client Device's channel characterization
vector is transmitted at a separate time, the method shown in Figure 7 allows
for
the simultaneous transmission of channel characterization vectors from
multiple
Client Devices back to the Base Station 700, thereby dramatically reducing the
channel characterization vectors' impact on return channel throughput.
Exp. Mail No.: EV4717133726US
06181.P014X
97
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
[0065] As mentioned above, each signal's characterization may include many
factors including, for example, phase and amplitude relative to a reference
internal to the receiver, an absolute reference, a relative reference,
characteristic
noise, or other factors. For example, in a quadrature amplitude modulation
("QAM")-modulated signal the characterization might be a vector of the phase
and amplitude offsets of several multipath images of the signal. As another
example, in an orthogonal frequency division multiplexing ("OFDM")-modulated
signal, it might be a vector of the phase and amplitude offsets of several or
all of
the individual sub-signals in the OFDM spectrum. The training signal may be
generated by each Client Device's coding and modulation subsystem 711,
converted to analog by a D/A converter (not shown), and then converted from
baseband to RF by each Client Device's transmitter 709. In one embodiment, in
order to ensure that the training signals are synchronized, Client Devices
only
transmit training signals when requested by the Base Station (e.g., in a round
robin manner). In addition, training signals may be interleaved within or
transmitted concurrently with the actual data signal sent from each client
device.
Thus, even if the Client Devices 706-708 are mobile, the training signals may
be
continuously transmitted and analyzed by the upstream channel characterization
logic 741, thereby ensuring that the channel characterization matrix 741
remains
up-to-date.
[0066] The total channel bandwidth supported by the foregoing embodiments of
the invention may be defined as min (N, M) where N is the number of Client
Devices and M is the number of Base Station antennas. That is, the capacity is
Exp. Mail No.: EV4717133726US
06181.P014X
98
SUBSTITUTE SHEET (RULE 26)
CA 2872502 2020-03-06
=
WO 2013/166464 PCT1US2013/039580
11
limited by the number of antennas on either the Base Station side or the
Client
side. As such, one embodiment of the invention employs synchronization
techniques to ensure that no more than min (N, M) antennas are transmitting/
receiving at a given time.
[0067] In a typical scenario, the number of antennas 705 on the Base Station
700 will be less than the number of Client Devices 706-708. An exemplary
scenario is illustrated in Figure 8 which shows five Client Devices 804-808
communicating with a base station having three antennas 802. In this
embodiment, after determining the total number of Client Devices 804-808, and
collecting the necessary channel characterization information (e.g., as
described
above), the Base Station 800 chooses a first group of three clients 810 with
which to communicate (three clients in the example because min (N, M) = 3).
After communicating with the first group of clients 810 for a designated
period of
time, the Base Station then selects another group of three clients 811 with
which
to communicate. To distribute the communication channel evenly, the Base
Station 800 selects the two Client Devices 807, 808 which were not included in
the first group. In addition, because an extra antenna is available, the Base
Station 800 selects an additional client device 806 included in the first
group. In
one embodiment, the Base Station 800 cycles between groups of clients in this
manner such that each client is effectively allocated the same amount of
bandwidth over time. For example, to allocate bandwidth evenly, the Base
Station may subsequently select any combination of three Client Devices which
Exp. Mail No.: EV4717133726US
06181.P014X
99
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
=
excludes Client Device 806 (i.e., because Client Device 806 was engaged in
communication with the Base Station for the first two cycles).
[0068] In one embodiment, in addition to standard data communications, the
Base Station may employ the foregoing techniques to transmit training signals
to
each of the Client Devices and receive training signals and signal
characterization data from each of the Client Devices.
[0069] In one embodiment, certain Client Devices or groups of client devices
may be allocated different levels of bandwidth. For example, Client Devices
may
be prioritized such that relatively higher priority Client Devices may be
guaranteed more communication cycles (i.e., more bandwidth) than relatively
lower priority client devices. The "priority" of a Client Device may be
selected
based on a number of variables including, for example, the designated level of
a
user's subscription to the wireless service (e.g., user's may be willing to
pay
more for additional bandwidth) and/or the type of data being communicated
to/from the Client Device (e.g., real-time communication such as telephony
audio
and video may take priority over non-real time communication such as email).
[0070] In one embodiment of the Base Station dynamically allocates bandwidth
based on the Current Load required by each Client Device. For example, if
Client Device 804 is streaming live video and the other devices 805-808 are
performing non-real time functions such as email, then the Base Station 800
may
allocate relatively more bandwidth to this client 804. It should be noted,
however,
Exp. Mail No.: EV4717133726US
06181.P014X
100
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039500
that the underlying principles of the invention are not limited to any
particular
bandwidth allocation technique.
[0071] As illustrated in Figure 9, two Client Devices 907, 908 may be so close
in
proximity, that the channel characterization for the clients is effectively
the same.
As a result, the Base Station will receive and store effectively equivalent
channel
characterization vectors for the two Client Devices 907, 908 and therefore
will not
be able to create unique, spatially distributed signals for each Client
Device.
Accordingly, in one embodiment, the Base Station will ensure that any two or
more Client Devices which are in close proximity to one another are allocated
to
different groups. In Figure 9, for example, the Base Station 900 first
communicates with a first group 910 of Client Devices 904, 905 and 908; and
then with a second group 911 of Client Devices 905, 906, 907, ensuring that
Client Devices 907 and 908 are in different groups.
[0072] Alternatively, in one embodiment, the Base Station 900 communicates
with both Client Devices 907 and 908 concurrently, but multiplexes the
communication channel using known channel multiplexing techniques. For
example, the Base Station may employ time division multiplexing ("TDM"),
frequency division multiplexing ("FDM") or code division multiple access
("CDMA") techniques to divide the single, spatially-correlated signal between
Client Devices 907 and 908.
[0073] Although each Client Device described above is equipped with a single
antenna, the underlying principles of the invention may be employed using
Client
Exp. Mail No.: EV4717133726US
06181.P014X
101
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
Devices with multiple antennas to increase throughput. For example, when used
on the wireless systems described above, a client with 2 antennas will realize
a
2x increase in throughput, a client with 3 antennas will realize a 3x increase
in
throughput, and so on (i.e., assuming that the spatial and angular separation
between the antennas is sufficient). The Base Station may apply the same
general rules when cycling through Client Devices with multiple antennas. For
example, it may treat each antenna as a separate client and allocate bandwidth
to that "client" as it would any other client (e.g., ensuring that each client
is
provided with an adequate or equivalent period of communication).
[0074] As mentioned above, one embodiment of the invention employs the
MIDO and/or MI MO signal transmission techniques described above to increase
the signal-to-noise ratio and transmission bandwidth within a Near Vertical
Incidence Skywave ("NVIS") system. Referring to Figure 10, in one embodiment
of the invention, a first NVIS station 1001 equipped with a matrix of N
antennas
1002 is configured to communicate with M client devices 1004. The NVIS
antennas 1002 and antennas of the various client devices 1004 transmit signals
upward to within about 15 degrees of vertical in order to achieve the desired
NVIS and minimize ground wave interference effects. In one embodiment, the
antennas 1002 and client devices 1004, support multiple independent data
streams 1006 using the various MIDO and MI MO techniques described above at
a designated frequency within the NVIS spectrum (e.g., at a carrier frequency
at
or below 23 MHz, but typically below 10 MHz), thereby significantly increasing
Exp. Mail No.: EV4717133726US
06181.P014X
102
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
1110
the bandwidth at the designated frequency (i.e., by a factor proportional to
the
number of statistically independent data streams).
[0075] The NVIS antennas serving a given station may be physically very far
apart from each other. Given the long wavelengths below 10 MHz and the long
distance traveled for the signals (as much as 300 miles round trip), physical
separation of the antennas by 100s of yards, and even miles, can provide
advantages in diversity. In such situations, the individual antenna signals
may be
brought back to a centralized location to be processed using conventional
wired
or wireless communications systems. Alternatively, each antenna can have a
local facility to process its signals, then use conventional wired or wireless
communications systems to communicate the data back to a centralized location.
In one embodiment of the invention, NVIS Station 1001 has a broadband link
1015 to the Internet 1010 (or other wide area network), thereby providing the
client devices 1003 with remote, high speed, wireless network access.
[0076] As mentioned above, one embodiment of the invention employs the
MIDO and/or MI MO signal transmission techniques described above (collective
referred to heretofore as "DIDO") to increase the signal-to-noise ratio and
transmission bandwidth within a tropospheric scatter ("troposcatter") system.
Referring to Figure 11, in one embodiment of the invention, a first
troposcatter
station 1101 equipped with a matrix of N antennas 1102 is configured to
communicate with M client devices 1104. (The upward angle of transmission is
exaggerated for illustration purposes in Figure 11. A more typical low angle
for
Exp. Mail No.: EV4717133726US
06181.P014X
103
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
4110
troposcatter transmission is shown in prior art Figure 12.) The antennas of
the
various client devices 1104 transmit signals back through tropospheric
scatter,
and they are received by base station antennas 1102.
[0077] The troposcatter base station antennas 1102 are aimed at an upward
angle so that part of the transmission scatters and reflects off the
troposphere so
as to hit the target area where the M client devices 1104 are located.
Calculating
specific antenna elevation angles and optimizing antennas for troposcatter is
well
understood to those skilled in the art, and several online calculators exist
for
making such calculations. As an example, one such calculator can be
downloaded at htto://home.planet.nl/-alohe078/oropaqatl.htm. This particular
troposcatter calculator's input parameters include distance between the
transmit
and receive antennas, transmission frequency, antenna heights, output power,
station noise characteristics, obstacle distance/heights, antenna gain, and
bandwidth.
[0078] An exemplary prior art troposcatter radio terminal (i.e. transceiver
and
antenna) that is currently in use by the US Military is the AN/TRC-170V3
Tropospheric Microwave Radio Terminal. The system has a nominal
transmission range of 100 miles. Such a system typically transmits less than 1
Mbps. Newer troposcatter modems such as the General Dynamics and Radyne
Corporation TM-20 modem can achieve up to 20 Mbps. But, both systems only
can achieve such data rates with a single data stream in a given channel,
Exp. Mail No.: EV4717133726US
06181.P014X
104
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
[0079] In one embodiment, the antennas 1102 and client devices 1104, support
multiple independent data streams 1106 using the various DIDO techniques
described herein at a designated frequency within the troposcatter spectrum
(e.g., at a carrier frequency from below 50 MHz to above 10 GHz). These DIDO
techniques include, but are not limited to, the transmission of training
signals, the
characterization of the channel vectors, and the transmission back to the
troposcatter base station 1101 of the channel vectors so as to form a channel
matrix.
[0080] The troposcatter antennas served by a given troposcatter base station
1101 may be close (e.g. as close as 2,16) or physically very far apart (10s or
100s
of miles) from each other and/or they may be clustered in groups. So, the term
"troposcatter base station 1101" as used herein refers to a common channel
matrix computation system, similar to Figure 2's Base Station 200, but one in
which the transmitting antennas 1102 may in fact be distributed very far from
a
given site. The specific configuration will depend on the desired coverage
area,
the need to avoid obstacles in the terrain, and if necessary, the need to
achieve
more diversity and/or a wider angle between transmit antennas. As previously
described, a DIDO base station, by utilizing channel state information
feedback
from the client devices after sending training signals, will produce a
combination
of transmitted signals from its antennas 1102, such that the client devices
will
receive independent signals. And, when the client devices 1104 transmit back
to
the base stations antennas 1102, the base station will use the channel state
information determined from client device training signals.
Exp. Mail No.: EV4717133726US
06181.P014X
105
CA 2872502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
110
[0081] Because troposcatter largely preserves polarization, 2D and 3D
polarization can be used with antennas 1102 and 1104 to achieve further
diversity.
[0082] In one embodiment of the invention, troposcatter Station 1101 has a
broadband link 1115 to the Internet 1110 (or other wide area network), thereby
providing the client devices 1103 with remote, high speed, wireless network
access.
[0083] The troposcatter base station antennas 1102 and the client device
antennas 1104 will work best if they each have a line-of-sight (LOS) view of
the
troposphere to the common volume 1121. The common volume 1121 is an area
of the troposphere where tropospheric scattering will cause some of the
transmitted signal to reflect back to the ground. Typically, most of the
transmitted
signal will pass through the troposphere as indicated by 1120. Perfect LOS
transmissions over long distances with very narrow angles between antennas
may result in poor diversity. This can be mitigated by separating the base
station
antennas 1102 by large distances, but the scattering effect of the troposphere
itself may also create diversity.
[0084] While a LOS path to the common volume 1121 can be planned for when
the base station antennas 1102 are installed, it is more difficult to
guarantee that
a client device antenna 1104 has a LOS view of the common volume 1121. In
particular, the common volume 1121 is often going to be at a low angle in the
sky. If, for example, a consumer wishes to place a client device antenna 1104
in
Exp. Mail No.: EV4717133726US
06181.P014X
106
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
a window of her house, or on the roof of her house, even though the antenna
may have a view of some of the sky, it may be obstructed from having a view of
the particular patch of the sky which contains the common volume 1121.
[0085] This issue can be mitigated by having multiple troposcatter base
station
antennas 1102 transmitting from various directions over a coverage area. One
such configuration is illustrated in Figure 13 from an overhead ("plan") view.
Troposcatter base station 1301 serves the same function as troposcatter base
station 1101, but its antennas are deliberately distributed far apart in
antenna
clusters 1341-1344. The antenna clusters 1341-1344 are aimed such that their
transmissions reflect from the troposphere to a common ground coverage area
1360. This coverage area may be a town, a city, a rural area, or an
uninhabited
area under exploration. It may also be an area on a body of water. Antenna
cluster 1341 transmits RF transmission 1330, which scatters in common volume
1321 and then reflects back to earth as RF reflection 1331 into coverage area
1360 where it then is received in coverage area 1360 by one or more client
antennas 1361-1363. Simultaneously, antenna clusters 1342-1344 transmit RF
that scatters in common volumes 1322-1324, respectively, and then the RF
reflects back to earth in to coverage area 1360 where it is then received by
one
or more client antennas 1361-1363. And, one or more client antennas 1361-1363
transmit back through common volumes 1321-1324 to antenna clusters 1341-
1344 as a return path.
Exp. Mail No.: EV4717133726US
06181.P014X
107
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
[0086] Some or all client antennas 1361-1363 may not have a LOS view the sky
to see all common volumes 1321-1324. But so long as each client antenna 1361-
1363 can see at least one common volume 1321-1324, then it will be able to
have communications with the troposcatter base station 1301. Clearly, the more
antenna clusters 1341-1344 that are established around the coverage area 1360,
the less chance that a client antenna 1361 will be unable to see at least one
common volume 1321-1324.
[0087] The troposcatter base station 1101 communicates to the antenna clusters
1341-1344 through communication links 1351-1354. These communications links
1351-1354 may be physically implemented via various means, including optical
fiber, leased communications lines, such as DS3 lines, or they may be
implemented through wireless communications. In fact, communication links
1351-1354 may be implemented utilizing troposcatter communications.
[0088] Because of the long distances required for the communications links
1351-1354, in the presently preferred embodiment, each of the antenna clusters
1341-1344 will have its own local RE transceivers which are directed by the
troposcatter base 1301 as to precisely what RF signals are to be generated in
synchrony so that all antenna clusters 1341-1344 work in a coordinated fashion
as a single DIDO system.
[0089] In an alternative embodiment, each antenna cluster 1341-1344 will have
its own base station 1301 and will operate independently from the other
antenna
clusters 1341-1344. In this situation each antenna cluster may transmit at a
Exp. Mail No.: EV4717133726US
06181.P014X
108
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
different frequency so as to avoid interfering with the others, or directional
antennas maybe used for client antennas 1361-1363 may so as to reject
transmission from all but a signal antenna cluster 1341-1344.
[0090] An alternative embodiment of the system illustrated in Figure 13 is
illustrated in Figures 16 and Figures 17a-c. The communications links, then
base station and the common volumes from Figure 13 are not shown in Figures
16 and Figures 17a-c for the sake of clarity, but such components still exist,
and
are implemented as previously described.
[0091] Figure 16 shows an overhead (plan) view of a coverage area 1360
surrounded by 12 clusters 1611-1643 of 3 antennas 1651-1653 each, for a total
of 36 antennas. All of these antennas are aimed such that when they scatter
off
of their respective common volumes, the reflected RF reaches the coverage area
1360. Coverage area 1360 has many client antennas, of which 3, 1361-1363 are
illustrated. Figure 16 also indicates the north/south/east/west orientation of
the
illustration.
[0092] Figures 17a-c shows the 3 client antennas 1361-1363 in the coverage
area 1360 schematically as antennas 1701. Figure 17a shows the antennas
1701 in an elevation view from the south; Figure 17b shows the antennas 1701
in an elevation view from the west; and Figure 17c shows the antennas 1701 in
an overhead (plan) view from above. Note the schematic illustration of the
antennas 1701 shows them as triangles in the elevation views and as squares in
the overhead view, but they are the same antennas. The antennas could be any
Exp. Mail No.: EV4717133726US
06181.P014X
109
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
WO 20131166464
PCT/US2013/039580
of many prior art antenna shapes. And, rather than being in a row, the 3
antennas may be located in many different positions relative to each other,
including being miles apart. And finally, in one embodiment, far more than 3
antennas are deployed in a given coverage area.
[0093] Figure 17a-c shows how the RF beams from the various antennas in
Figure 16 arrive at a large variety of angles to antennas 1701. For example,
antenna cluster 1613's transmission arrives at angle 1713, 1612's transmission
arrives at angle 1712, and 1611's transmission arrives at angle 1711. This is
due
to the fact that the antenna clusters 1613-1615 are positioned successively
further from coverage area 1360, but are all aimed to reflect down to coverage
area 1360, resulting in varied angles of arrival. Likewise, antenna clusters'
1631-
1633's transmission arrive at angles 1731-1733, respectively; clusters 1621-
1623
arrive at angles 1721-1723, respectively; and clusters 1641-1643 arrive at
angles
1741-1743, respectively.
[0094] Additionally, it can be seen in Figure 17c that transmission from each
group of antenna clusters in the north, south, east and west of Figure 16
arrive
from their respective directions, and further the 3 antennas 1651-1653 of
antenna
cluster 1611 arrive at angles 1751-1753, respectively. And the rest of the
individual antennas (not numbered) all arrive at different angles.
[0095] All of the varied arrival angles illustrated in Figure 17a-c result in
significant angular diversity. Such diversity can be exploited using either
prior art
MIMO techniques or the DIDO techniques described herein, or other spatial
Exp. Mail No.: EV4717133726US
06181.P014X
110
CA 2 8 7 250 2 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
=
WO 2013/166464 PCT/US2013/039580
=
multiplexing techniques to achieve significant improvements in overall channel
bandwidth and SNR. Also, if some of the arrival angles are obstructed from
reaching some antennas 1701, then with so many arrival angles, there is a high
probability that at least some of the RF arrival angles will reach each
antenna.
[0096] This same diversity can be exploited in the return path when antennas
1701 transmit back to the various antenna clusters 1611-1643. In one
embodiment, some or all of antennas 1701 may be directional and only utilize
certain transmission and reception angles. This may be used to either increase
the gain off the signal (e.g. using a dish antenna), or can be used to limit
the
return path transmissions to certain angles to avoid interfering with other
receivers using a similar frequency.
[0097] One desirable frequency range to use for tropospheric communications is
above 12 GHz. Some of the 12 GHz band is currently used in the US for Direct
Broadcast Satellite (DBS) communications. Typically, DBS radio signals are
transmitted from geostationary satellites, and a consumer has a dish installed
on
the roof of his home (or someplace where the dish as a view of the southern
sky
in the direction of the desired satellite). The satellite signal is received
at angle
1410 of Figure 14, and then is collected by dish 1401 and reflected to antenna
and low-noise block (LNB) 1402. Some satellite dishes 1401 are constructed to
receive satellite signals from 2 or 3 angles, and reflect them to multiple
LNBs
1402. The 12 GHz band is largely unutilized in the US except for this purpose.
Because of the high frequency 12 GHz is easily absorbed by various terrestrial
Exp. Mail No.: EV4717133726US
06181.P014X
1 1 1
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
=
objects (e.g. tree leaves) and as a result is difficult to use for other than
LOS
applications.
[0098] In one embodiment of this invention the DI DO troposcatter system
described above, and illustrated in Figures 11 and 13 is used at the same
frequency as DBS satellite transmission 1410, but the base station antennas
(either 1102 or 1341-1344) are positioned and angled such that the angle(s) of
RF reflection from the common volume(s) 1121 or 1321-1324 are such that they
will not be reflected by the satellite dishes 1401 into their LNBs 1402. This
can be
accomplished by placing the base station antennas 1102 or 1341-1344 at angles
so that they never transmit in the same direction as the satellite signal 1410
(e.g.
always transmit from the north, since all geosynchronous satellites transmit
from
the south), or choose an elevation angle for the transmission such that the RF
reflection 1420 back to the ground bounces away from the LNBs 1402.
[0099] Care must also be used on the return path transmission from the client
antennas 1104 or 1361-1363 to the base station so that they do not interfere
with
LNB 1402. This can be accomplished by using a directional return path antenna,
similar to the dish antenna 1401 used to receive the satellite signal.
[00100] In an alternative embodiment the 12 GHz troposcatter
approach
just described not only applies to DIDO systems, but can be also used for 1-
way
conventional broadcast without return path or spatial multiplexing. In this
case,
each client receiver would receive the same signal.
Exp. Mail No.: EV4717133726US
06181.P014X
112
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
=
[0100] In an alternative embodiment, conventional 2-way M IMO techniques are
used with troposcatter communications, as shown in Figure 15. In this
embodiment, both the base station 1101 and the client station 1102 have
multiple
antennas, and each receiver creates a full H matrix after training, and then
inverts that matrix and multiplies it by the received data from the multiple
antennas. The configuration of a conventional MIMO system is show in Figure 1,
[0101] Embodiments of the invention may include various steps as set forth
above. The steps may be embodied in machine-executable instructions which
cause a general-purpose or special-purpose processor to perform certain steps.
For example, the various components within the Base Stations and Client
Devices described above may be implemented as software executed on a
general purpose or special purpose processor. To avoid obscuring the pertinent
aspects of the invention, various well known personal computer components
such as computer memory, hard drive, input devices,. . . etc, have been left
out
of the figures.
[0102] Alternatively, in one embodiment, the various functional modules
illustrated herein and the associated steps may be performed by specific
hardware components that contain hardwired logic for performing the steps,
such
as an application-specific integrated circuit ("ASIC") or by any combination
of
programmed computer components and custom hardware components.
[0103] In one embodiment, certain modules such as the Coding, Modulation and
Signal Processing Logic 603 described above may be implemented on a
Express Mail No.: EV471133726US
06181.P014
113
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
=
programmable digital signal processor ("DSP") (or group of DSPs) such as a
DSP using a Texas Instruments' TMS320x architecture (e.g., a TMS320C6000,
TMS320C5000, . . . etc). The DSP in this embodiment may be embedded within
an add-on card to a personal computer such as, for example, a PCI card. Of
course, a variety of different DSP architectures may be used while still
complying
with the underlying principles of the invention.
[0104] Elements of the present invention may also be provided as a machine-
readable medium for storing the machine-executable instructions. The machine-
readable medium may include, but is not limited to, flash memory, optical
disks,
CD-ROMs, DVD ROMs, RAMs, EPROMs, EEPROMs, magnetic or optical cards,
propagation media or other type of machine-readable media suitable for storing
electronic instructions. For example, the present invention may be downloaded
as a computer program which may be transferred from a remote computer (e.g.,
a server) to a requesting computer (e.g., a client) by way of data signals
embodied in a carrier wave or other propagation medium via a communication
link (e.g., a modem or network connection).
[0105] Throughout the foregoing description, for the purposes of explanation,
numerous specific details were set forth in order to provide a thorough
understanding of the present system and method. It will be apparent, however,
to one skilled in the art that the system and method may be practiced without
some of these specific details. Accordingly, the scope and spirit of the
present
invention should be judged in terms of the claims which follow.
Express Mail No.: EV471133726US
06181.P014
114
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
CLAIMS
What is claimed is:
1. A method comprising:
using tropospheric scatter to transmit a training signal from each antenna
of a base station to each of a plurality of client devices, each of the client
devices
analyzing each training signal to generate channel characterization data, and
transmitting the channel characterization data back to the base station;
storing the channel characterization data for each of the plurality of client
devices;
receiving data to be transmitted to each of the client devices; and
precoding the data using the channel characterization data associated
with each respective client device to generate precoded data signals for each
antenna of the base station; and
using tropospheric scatter to transmit the precoded data signals through
each antenna of the base station to each respective client device.
Express Mail No.: EV471133726US
06181.P014
115
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
wo 2013/166464
PCT/1JS2013/039580
111
ABSTRACT
A method is described comprising: transmitting a training signal from each
antenna of a base station to each of a plurality of client devices utilizing
tropospheric scatter, each of the client devices analyzing each training
signal to
generate channel characterization data, and transmitting the channel
characterization data back to the base station utilizing tropospheric scatter;
storing the channel characterization data for each of the plurality of client
devices; receiving data to be transmitted to each of the client devices; and
precoding the data using the channel characterization data associated with
each
respective client device to generate precoded data signals for each antenna of
the base station; and transmitting the precoded data signals through each
antenna of the base station to each respective client device.
Express Mail No.: EV471133726US
06181.P014
116
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
1111 WO 2013/166464
PCT/US2013/039580
=
...........t , ...... (Ls
Data Output
,_....1
1 _______________ co
r.......5
i Combiner
:
....,,-
I d --4:
µ, ....-t ,-..
<=,
.3
, .
1 , .. Signal Processing
v õ/ -. :,::
1 i ¨ _____
..,_,_.....1_,
I
.=,,,, '6
'= ',-;
cle.
0
r>.-- '''=Z>
= i
.."
;$4n. ,! gF . = . . = . . ... ,
.... T...
(...) cl-
,-
,
....
0. -----L>
F" .......... ,''''''.= %)
-.,....
..--
1--
!" P
1
(,)
i-
m Fi
--..--. = -1"."
I (.4
o
I I ___
.1. ¨
Coding and Modulation
i
A A ___ A
r.
0
............L.,...,c,...----- r.
S plater
A _______
0
0
HData Input ---c¨ ,..-
117
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
to
ct .,
.. ¨,
to -..---
:=:3 ----1... V ill --,-N I
s ;4! 1, :''i :.t. 1
.. õ
4:.:$ c.µ,. k., c:1 0
: ______________________________________________ I a)
......
>
Q.)
0
04 t.
A
>s- ...4 ___________ 1 =..g :; c
C
----i a.)
'6 el T
(1.)
c c.,
.3
.,..z Ol.o),z/..Akz>>1$10g103*A033>q0 5
=,..,,<)- ,,<:.,
,:.,,e._,,=<õ,,=,==õx,_== .4.4.= ==,,x,.., c , 14.
c c c
=-=.: 0
..c ,..0 .....,....-
(..) a CU
(0
csi n Antennas E
_
*
04 .
= * = CD
cf)
07.1
CO
c cti
31 0 a
Ca co ea C
(1)
c
r}'
i- c
8
2 tt3
4 t
3'.
c
118
SUBSTITUTE SHEET (RULE 26)
CA 2 8 7 2 5 0 2 2 0 2 0 -0 3 -0 6
* 0
0
Iv
co
-.1
I)
tri
o
0
n.) 300
310
tO
n.)
ii ---------------------------------------------------------------------------
--------------- -
"304
ei
1
309 320 312 a,
n.) 305-
, 1
ei
3.11
a,
i
1
oi Base q,..troõ,,;,%====
;
i
,.1 j I=i, &,.. '
w Station ¨ ¨ /
oi
zt-,,ze: raf:ierit Devi.c.
cil a
1
f-I=ca: . 1
4.........i
,I.A.1. 4 iti.i....' 0.
;--) 4¨* Tiansceiver ____________ 1---! Trenr-
xeiver 114---* ' __
Cneiirej.
cel W , ... .
0 *
IA
'
C * K
0
V ,..,>.
zt===.v
kx:
113 > eL .....:,..s.
eiiert Device 2 __ - [ i 307 i
X
,- AZ
S. CharKIcter::mi'i,:;r: 1 1, _ .. :
CI) Z 30 ¨ 1 ¨..;
4....01. '..:ate. 4...4.4.
CD
¨I .41-4-0, 5 .4--* _____________________ c
-4, *--10. Transceiver ',$:=4",-"rk TrarisceiveF' 4 k ;
¨I CO CD
--% 0 "fe , _____
L.
SiTlai Prcz=Aw-ing -1 .
.....,tt .
C =
.
CD V=k",=,:la -----
----------_¨_-______ _
V : Cfierit ri'evice 3 _________ i- 1 -i
308 ! rrl g a- ,v----
i _____ , S. ct.c.....thrtz,k.,7,
...,.. õ..
__
... t.........õ, .. j4-1 ¨4. 7-7.--,-
4-40-111=11
===';:s_t , ,......._ Crxim). t=AcAciacr:in.
irli:30',"::".4 i :
M `42) 7) '
1
''', s i.tlii Pr.:cesiis
rna , --------
- .... ............ -
¨1 ...... 0 ......
7J
\"\ 0
co
cf)
5Channel
C Impairments
v\
I¨ ea
111
1%3 - \-
CM
...... 301 302
\--\
303
oo
n
1-3
8
3-Antenna Base Station with 3 Single-Antenna Client Devices
cp
t..0
Fig. 3 w
8
w
i./.
cio
c.
0 =
0
1=3
CO
.4
i \ )
01
0
0
i \ )
hi
n.)
o
1-,
o w
m 400
o
404 c7,
O
410 c.
w
fi
/I 405
.A.
411
=., A
a,
.6
409
' '
iri 421 0
ol
412
:
01 Base
\ ______________________________________________ ifj ri
rJ
Station ....... _ -
........ $
0 V
,1 1
1
_______________________________________________________________________________
____________
0 ,Fx:
Cm D1 1 __________________
CI) CL
03 co
____________________________________________________________________ Traw-
x,i,x,..r .4*------0. '---;)".-- -
___________________________________________________________________________ i
,..od;;I.-.i. M;yivlat:cx-,. 11 1 ;:,-,14.,-..;=3:-.4-=.;14-7+
C./) = :=,..::==
i Si;),.-:a i"--(sx*I.5-.::,.:,-, ri :
o ______________________________________________________ y ...,.... i
.--...----...-.....
.1 >
X3 a ..
, aien: Device 2 __ f-P õ ;1_
407
C Z o c rz.,..-...s. \ \\I __
g. 4-012:artv.eivar __________________________________ ! ...fA .
-0 ,
i S C.,h;lr.s.::=...:NI:gatz.:4-= 1 1 : _ ; =
M =====
CD ar.
: :14
t __________________________________________________________________________
, = ,..,.(x.w. ,..,.c.4.1::::nt......, ! 1 ,r,(::::=-=-
f.v..* %, ;
Cn = k!:.A i :
-1 ,' Sigrzi P.1-..xessi.lv.1 =
s
- F ,
SD C---7 t .
,.. "
,-.^µ
.
========1;.:4.
ent De,ix,v -' 408 :
M = . ______________ ...,,,
14-44'------7=4.7 ' 4 . =:... i -
,,
..., 1.4-1w ArAr.:_,.:1:=.:;r:
¨I 13) 4---P'' Ttanscesver
,r,.....,/ r.,,,,,, 4 =
.
_______________________________________________________________________________
___ ..
/
' L---------t ----4 / 'I CS:tit =''''?'::1:-.=;:.;;
s
. = c --------------------- a
....... 0 _ ----
r- 0 Channel
111 \ Impairments vs
0
IP 1
IV 5-
......- .
401 402
\ _
\
\
'''',.....--\
-....-...,. n
403
\
\
413
414 415
b..)
eD
Antenna 1 Pilot Signal Transmission
-
'-d
c..)
4:.
Fig. 4
=
410 0
0
Iv
co
--.1
n.)
01
o
0
I)
b.)
504
.
0
w
n.) 508 fj 510
0 o
il ,<=...
511
-------------------------------------------------------------------------------
------------------------ . ,..<
y505 1 1
....,ia'si'i 1 520 r 51.2
w Base
Station fi _____________ if
¨
I .
;-
f _____________________________ ..... .'.::'. '
õ
ifr--*Tralsceiver ________________________________________________ !
________ I S. CI),:o..,1<,,
CA CC:t .e. ;
Traiii,;i3v(Sr 14-11. i ....µ --;:¨.----
CO 0
V ..
C/) >
¨I Z
70 0_
0 r=-=
.....ii*,::1;
*".A. \ It- i.7.-.1.1t De:vR..;a 2 il 1 .. ,... ,,.. . ;
..,:.. : ii- 607
¨I 4--,--10. 3" 4¨* C *--* i.?...). 4¨*
'Tran6ccf.iv6r -,-- ...µ,-..
C g 6 0 .-.,,,sx:.
: Tiansoe.,,f 4-4. . . . = 1 44-0. ,o,
õ,..õ,, ,
Sivlai 7-'rfx:EN },- I =
V, % y:õ.1 _______ ...
0 csn i........../v
Cl) _ < csient
De,ace 3 ________ ...< t- 508 !
1
M 11
¨I a
7 ,
-------------------------------------------------------------------------------
---------------- . __ 0
,
\... _ o _
CD
(,) Channel t. --
C cf,
1¨ 5 Impairments
it:: i
mco i __
r...1 H.
____ ------ -- -,-,,,.... ..\:õ...:c\_ - _ -
I
.
/ 14 õ1
501 502
503
\----\
s...¨
\
\
\
....-..\
\
\ ho
(1
513 514 515LidLJ
1-3
cn
Client Device 1 H Column Transmission
w
ni
-
w
Fig. 5 'a
i..)
516
cil
co
c:,
= 0
0
1=3
CO
-.1
I)
01
o
0
n.)
t.a
o
I)
1-.
o
600 w
m 604
610
o
.............. -ii
1
ct,
oi
A
605 609
620 c=N
co ¨... --------- '
612 .I:.
I 611
oI Base 0 1
i I
01 Station 8. ts,.....,.$4,.
-,.....õ
,,:õ., t=
j\., y.../ µ
lir tviõ....:
.. .A.,
cr.) S.:/, -
1 __ I
I/ 'i C;iert De.k1 1
- %
Cl) 4`
____________________________________________________________________ LX:ivc?!
I, .. is
. _____________________ ...i.L.... f. +1.4{' Trartsceiv:
0
......_____ 1 -',.1(:):=f,:w;f:: i :
I
CO co
1- &ix:3i Proceisir:f.? r
-.a
'
______¨_-... ........ ------___________
__________________¨.
0
V:-
-1 - I Z > =
CherA DeviCe 2 -1 I 607 ---: '
¨I 0 = (..0
____________________________________________ is "... S. Clmracterizat
=
¨
C = C 012:::411-1 ____________ tg-- +¨MI Tforksceiver ¨
- Signal Pr(.=.cossin __ r ¨ :
(1) 0)
0 a ...!.....;), r
I. i':::? Client
DeYce 3 608 :
I tv 0 n
to
M t`) I s.5. = tri
cn u 3
_________________________________________ ',:i ,"1.*.kr3,10,:i-,=atr: 1 l'
17-i ' 1 '
_________________________________________________________________________ ' ' -
' .
M 3
4-401 It artac6vd, ..w;$c,c,:;er 14--10 , r,.. v- iii_r_or
-'...."?/: j C.::Ctrl. f...011,1ein(y...,, i i
;=.',.:::11.3,7c, ; ,
¨I 1.13
/ : __
,
.
, Sisrat, Pc:.xes$irlc.; 11
-
...............................................................................
.......................
7J
C
II ____________________________
17 Channel
F o I
rri 4r-
Impairments
r.) 1, __
a)
\ -1 ----- , \
..-. t.
601 602 I 603 630
f
Iv
r)
it:.
f4
Multipie-Input Distributed-Output (MOO)
.
...
Downstream Transmission
w
616
Fig. 6
a,
=
= =
0
1=3
CO
.4
I)
01
0
0
i..)
741
r.)
o
m
.
cn
oi
4,
oN
u.) 700 i i = ,, 741
4,
o1
704 710
01
ill 7ii
__,' _
' 705 709
i
I 720 712
,
,
711
Ba5e .11 J
i I
706 '..
1/)
if ''''
=,... _
C Station t¨ ' V '
,L....,....ti....
,..11
1
03 r C
-a 1 .:''. ¨ ,-:',/------
\\/ '; Ci.:61*D,3vi,..-A 1 1 -- -
U) I co i .
i
,...i...¨........¨
' 4: =-=,:::,a,-,,,,,,,:,..:
1 4...ie2+{
rane,......opeer ..1,-;,.: , :
: :..!.;;;;;:k id......-1..' '
1 i
't?..:1s.:-.-..,A.;:e .1.41- '10. 1 ¨..7.-- '''''''''' ril¨li'l
Ca I :;:.<':',. :
______ :. LO:7%*2. Mt=::-.;1:-:S2::,eia
3 I ,'...-.
...2.::"
-I ________ S'2.F.'1 F--`,=:274:snu.4.i2:il 4 =
C ...z.,-.:r- 2
=
NK -=:: =
M > 1 : D".;;
.12-r---" ____ ==1 707 :
X 1 __
i f , =
1--,
1 fif--4* '"'""1 4 -111.=
i tV .4-1-10. 5 141-4. C 4 ___________________________ " IP
Transce ver rer;ii,-.4;v.er 111----IN _
FT; -44
s.:,=:õ.: Proc=O'-'44','
- =
, r
m (.1 =
__________________________________________ , 4
a)
708 : C
I 7J
i :-..,'=
r.:;,v-.-.1(;?e ; ,.- :/: '= 1 ,
. . ii, o = __
C4 ' * = Transcetver
,.."..... ____ 1---',.... '''.'Fry:sce4c.?: * ;- <
rõ,.......1,õ,,,... ;,......,4,
r
m
I .....
01-3
1 =-,;:igr,at. Ph3Les4r= = i
-------------------------------------------------------------------------------
------------------------- . .
N
\
V
n
1-3
a)
..... imp ah ai r nn n/ C
leen1 t s
701 702 703 630
v)
0
..,
MIMO Upstream Transmission
w
....
,..,
Fig. 7
.
0 WO 2013/166464
PCT/IJS2013/039580
0
,
a
ZO. =,-
to
\
..
;.' . 2 v 'i. ,õ 1 : il. õ, 15 ,-. S 0 (r)
S: ; . co : 3"; 0 , sy t., o, ,P .,::, cz,
.j'i
..,
2
¨ ................._.,... ____
c> > -1 > j > ..... 1 0
-E'
a)
......
(,) o
g-
< = = = = w"....eVR>: .s.,V,>====?>>14t>>>0:
='>' ==== =" , - '= '= , k,.."====%:..x",../. ' s:ex, ' ?4,.. / ..A. = c
0 E
CO
9 8 c sg.
03 , 22
..c ,N, a)
CA.
E int Lt.
_
,.._........._.---____õ
.tr.....
a> -
CI)
c C ...¨
a; '----2..õ, al = ¨
(...)
I
cv
o
z ro
< t
..!
124
SUBSTITUTE SHEET (RULE 26)
CA 2872 502 2 020 -0 3 -0 6
=
WO 2013/166464 PCT/US2013/039580
0
v--
1-
Of
r
\
1
I6A C4
g a :
.: > '
:
,
, ¨ .................................
r: -* ' 't ?$. 0 f%
I
g õ*. ..1, g
() 6 , (-1 ca
, k _________________________________ , .'1 '''' I
0 r,
0
.1.---=
E
>.....] ; c>....._ >j
Cl...
V; 0
1\
7,4E
,Z?.?'44c.',,?..... '=$.. \:.s<,', .'k>, \:,K,ZC,5<'.,:,...): ..',:**-
0140<.?vggee:' NV' 'V
',..?4,4m,-,:q.,=.--,,Ae;,,,.-)<,.. ,>:,.. .-,4..e. .,..k,,,,-4, = ,..ix<>"
..,...N,,,,,s, c- Ea) <I)
v) a)
8 8 c
cii
OD ti)
0 P-
c v)
.....
.....
õ...=...r...r.o.,/, __________________________ N c
co ,......
= -
t:>) 0
01
m ,z1al ,-
co 0
L.
(9
, 8
¨ ets
a v
4'
125
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
= =
0
N.1
CO
.s.1
n
0
.)
NJ
01
---.._-------..___....------------._--. _
0
0
o-,
trJ
n.)
-. , __________________________________________________________________
1 ()nos p her a 1005
7,
-
_______________________________________________________________________________
_____ _____....._
r..)
lAVNOWWWWW\
*
_
cn
____________________________________ - ____
4,
o
th4t4Wtof.titt0+00 \
en
m
T ,,tit,te* t Ottli ..,,, \
4,
o
1 i 01114 44,=,.* WA i\ \
1
ptifi..t,P :;,%,'s4!;4V,It \\
o
w
1
/AAPPN4V'''''':\
o
01
V)
C
03
W
m
,'/,\..:\:µ.\ Apip,00xr,õ,zy
cn
-*outwit Witifirrattitoso +,...- s \
, , . \ \ \
1 N.
ri C$ ' ! fl
/117#41 / \\.
\\µµ\
ITI
¨I
\ \1!- ' \ \ \ .1 \\''.:::\\,:\
7J
i
C
,.,/,,,y7/e ,,,
,
r-
ti \
rn
r..)
:' ?.!,' !== (i ,
cn
......
.., ,
r--- Remote Servers . . . A
.1Antenna N NVISe 6
p ii 6 il t 4 A
v
I (e.g., Web senters)
n
1-3
1020
1002
, u 6 0. Dieovoic:s
(,)
NJ
0
t=-=
I=J
0-
W
NVIS
,.z
-1.-- Internet
Station
(/1
ti
1015
Fig. 10
= =
C)
1.)
CO
--.1
N RF
Transmitted Thro.,.igh
01 \
0 \
/4-------- Troposphere 1120 0
N \ \ /
______
..--..*--
tsJ
0
1-,
IV
Go.1
-------.., ----
0
Troposphere 1106
.
I=3
______________________________________________ ...dial
ON
_______
0
I
ON V i Ni. ciPtitieWs --....---_-----c.......¨___ A
ON
0 CA44;00414pC'VeW \
i A
W
I Common --.) /,,ftS;A, skfitiit7t A \ , 0
Volume 1121
7 t i õAAA, = c \ \
a, titVAtWinAlvk A \ \
- iffi'vtitifiri*Ni \ \ \
CA
Fffri,frWA" I V\
C
03
¨1
7i
c
RFRrRaienivies,:eddba
m / a
u) RE Transmitted and :1. ':\\:\\\
,TFnescynd
.
9-16 km
2 'n.-) RE Received by iiirii / t k, '
\ ' Base Station -.....mra al ilt
1130 / 1131
41AtiffilIMINtaita÷.¨ ¨..eitullIk%%1Aryi),Illi UM Wiateis.--
M
\ , ' 1\111/444:\ \ --I
XI 1 #1/1T
' r /
c
m
IV
I
Remote Servers . .
(e.g., Web servers)
: N Troposcatter =
1120 1 ' I 'A Cient
*0
i i 1 i Antennas A i A
, A,r. evicei; en
i-3
a 1111
VJFAIPF 1102
1 1104
v)
c4
0
1-,
W
=
Internet -0-
Troposcatter
t.)
.0
.
tn Base Station
co 1110 Link 1101 o
1115
Fig. 11
0 WO 2013/166464
PCT/US2013/039580
0
Cr) 41
..414
,
0. ..
Axa
\ == vv.
, it ,
ageeii
i1 . = ......a"
i. '..-= e..0
Z ;
i,=-== I/ ... e.3 0
¨ / 1 = ..,
.. ..
, =......
"
I. .. :take
.4 ..
..
i.k.i. i 1 . =
>a i : . ,...s,
....... 1*""...".
1 i
aatt ei
= ,
'====3
% sk i t
1
= *4
c.v.'
CZ
;if' ....*
.õ
I # ...
= == i
,....
.-,
, .
\ ,
.......
j
e ...
\ .1 I k =
,i
' ...õ.
"
-.. , i , .., ......
/
....,.; 2 "
\ i A = =
.....
to
= ;--
.........
> 1
x t .. 7... 'I
I., ......
., ,......z, _
iii
\ kji I ,
? \ t 1 . '77:
. 1 y 4, = ,. a.
i . .
,,,
i ,
,, ....
.,
P 4
4,1 N *It
; \ =
= ss
tams
'. .
4 ..
...,õ,.
\
s i i:,
\
: .4
...
:,= i
\
.. =
Ø k
. z ..,
..
44.
128
SUBSTITUTE SHEET (RULE 26)
CA 2 8 7 2 5 0 2 2 0 2 0 ¨ 0 3 ¨ 0 6
= =
0
1=3
CO
--.1
I)
tri i
o !
0
I'.) Antenna
t..)
Cluster 000
0 1342
N3
F''N
0
ON
I
A
0
ON
W
A
0
01 \
COnl MOn
)
CI) Volume ,., fs
ilent
C 1322
CO
C/3 Antenna
¨I 1 RE Transmission RE
Reflection /1361
¨I 1 1330 1331 i
C
¨I 1362
M 0 \emeism6.6ymmaiwili.-- ----,
=
= ,^.
s-,
(I) /
õ....t..*..,...)
I r) 0 t
,../
M qD 0
=-,
Ill--I Antenna
Antenna
-55 Cluster Common 1363
Commix% Cluster
C 1341 Volume Coverage
Volume 1343
I¨
1323
M 1321 Area
I
r 1360
i
..)
cn µ
1
1352 1351 Common
Volume
. ti
1324 n
i
1-3
.
n.)
__________________________________________________________________ Antenna
eD
.
. .
0 0 0 Cluster
.
Troposcatter
L.t."
1354 1344
I
Base Station
i..e
_______________________________________________________________________________
___________________ i k.D
1301
tn
0:
1353
o
Fig. 13
= WO
2013/166464 PCT/US2013/039580
0
,..,
s,
ts,
'"S
N.
,
, c>
4 (NI
N + t
l
'4
NNNN
(Si
Y.N
'Sr
1C
V4t.
Vftk
I ss , t
cc.'63
... _______________________________________________________
...õ-- _____________________________________________________ I
/
,...
0
vt
130
CA 2872502 2020-03-06 SUBSTITUTE SHEET
(RULE 26)
= =
0
IV
CO
RF Transmiited Through
/
\ tn
/
0 \
4.....------ Troposphere 1120
rD
L.)
µ / o
r..)
\t, \ /
c..) n.) _ ________________
o
Troposphere 1105 V .
a, n.)
cf,
rD -- ________________________ ,---
_____________________________ ___________ A
I k SP
4;+Vit 4144'%Vta /44('Xif \ ¨
ON
0 S ',.4t i'"ett4i f A ',lit'
4 ' = &.
u..) Common ---)
iilow!,4,44,4%44#0,s`pt \,\
o1
Volume 1121 i r
titieiW00404 \\\
ch
/ 1 rtAk:4,404414's,i.\ 0:
i vtiovioli1/4,.\\\
Cl) v### 'Ark
c 1.4 .titit4 ty . \
//If,/ ,Ist,IA:\N'*\\ µ \
CI3
cn
-1
c
-1 RF Ttansmitsed ii
RF Transmitted and
d an
M Ilik, 1 \
:;.µ . . \ \ \ iiirli/i/ \ \ µ s RF Rece(vr.-:,r1 by
....--
?monis P=is-'151,..rf...
C/)
M Base Statton wawa SAltoirill01 .11111=.,....
.. INVINHOUVIAlt÷: ' 1,W 11111111,'"'"'"
¨I 1130 ffiii, 11#7, /
\µ\'µµ 8\c = .11CVN\
C
=.\\I \\\ \\
I¨
M /*Iffit
t.)
. , =
\\.,
, .
.
Remote Servers
4.
od
(e.g.. Web servers) A i "1 N Troposcatter =
. 1 M Client
,
n
i-i
1120 A 1 a j---
Antennas A' A -1AE1ennas
2
t
-I
1104
I.)
o
r.a
sa
r..4
Internet
Troposcatter 1
Troposeatter 1 o
1 ut
or>
Base Station
Client Strrition o
1110 Link 1101
1102
1115
Fig. 15
= =
C)
N.1
CO
,1
n.) Antenna __
in North
0 Cluster 0 0 0
0
n.) 4\ 1623
Ne
0
N.)
0
CA
N3 Antenna
_______________________________________________________ .
o Ouster 000
o,
oI
A
1622 oN
LA)
A
oI
West < ____________________________ > East Antenna r-----
01 Ouster 1 0 0 0
1621
cn
C
co
cn v Client
¨1 Antenna
¨1 South 1361
C
¨I
C/)
M 1651 _______________________ ______--, 1362
_ _,..--
,----
1652 0
000 0 $ $
I
....e 1
rn t-) o a =
Q
Ill 0 0 0 *
¨I õ_....
7:1 Antenna Antenna Antenna / \
Antenna Antenna Antenna
C Ouster Cluster Ouster / 1363
ouster cluster Cluster
r 1613 1612 1611 Coverage
1631 1632 1633
rfl Area
1.3
0) 1360
.4,
v
_____ Antenna
cn
1 o a :31 Cluster
1-3
1641
kJ
0
_____________________________________________________________ , Antenna
.
44
0 0 0 Ouster
o
ca
_____________________________________________________________ 4 1642
(A
ao
Fig. 16 F0 1 AnO 0
Clustertenna o
_.....__ _____________________________________________________
1643
= =
C)
F',
m
-.1
1711 1731 1721 1741
m
m
I
0
o
/732 1722
\\
/1742
t.a
0
F.') 1712
/
\ .
w
F'.)
o
'733 1723
1
\\\ \\
m
o
0,
1
4,
0
LA)
1 1713 477V-
0
01
=
cn
c
T , ,
y I
7
,
03
CA i
¨I 1
I
I
1 Fig. 17a i
c Fig. 17b -1
rn 1701
1701
cn
West < ___________ > East North < ________________ >
South
M c4
M
North
-4
PO 1 1
C
\ I
I¨
r
K.n)
a)
1751 -------
...
---* ¨ 1 t---- East oo
Vkilw 1762 * . 1 __
________________________________________________________________ 1 __ 1
4......¨_¨_-____ (-)
lit\
w
cm
t7a
-a-
1
w
FM
\
Fig. 17c g
South
0 WO 2013/166464
PCT/US2013/039580
0
Atty. Docket No. 6181P515X Patent
UNITED STATES PATENT APPLICATION
for
SYSTEM AND METHOD FOR DISTRIBUTED ANTENNA WIRELESS
COMMUNICATIONS
Inventors:
Antonio Forenza
Stephen G. Perlman
Prepared by:
BLAKELY, SOKOLOFF, TAYLOR & ZAFMAN, LLP
1279 OAKMEAD PARKWAY
SUNNYVALE, CALIFORNIA 94085
(408) 720-8300
Attorney's Docket No. 6181P515X
Filed Via EFS-Web
6181P515X
134
SUBSTITUTE SHEET (RULE 26)
CA 2872502 2020-03-06
=
WO 2013/166464 PCT/US2013/039500
III
SYSTEM AND METHOD FOR DISTRIBUTED ANTENNA WIRELESS
COMMUNICATIONS
RELATED APPLICATIONS
100011 This application is a continuation-in-part of the following co-pending
U.S.
Patent Applications:
100021 U.S. Application Serial No. 12/143,503, filed June 20, 2008 entitled,
"System and Method For Distributed Input-Distributed Output Wireless
Communications";
100031 U.S. Application Serial No. 11/894,394, filed August 20, 2007 entitled,
"System and Method for Distributed Input Distributed Output Wireless
Communications";
100041 U.S. Application Serial No. 11/894,362, filed August 20, 2007 entitled,
"System and method for Distributed Input-Distributed Wireless Communications";
[0005] U.S. Application Serial No. 11/894,540, filed August 20, 2007 entitled
"System and Method For Distributed Input-Distributed Output Wireless
Communications"
100061 U.S. Application Serial No. 11/256,478, filed October 21, 2005 entitled
"System and Method For Spatial-Multiplexed Tropospheric Scatter
Communications";
[00071 U.S. Application Serial No. 10/817,731, filed April 2, 2004 entitled
"System
and Method For Enhancing Near Vertical Incidence Skywave ("NVIS")
Communication Using Space-Time Coding.
Filed Via EFS-Web
6181P515X
135
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
0 WO 2013/166464
PC7UUS2013/039580
=
BACKGROUND
100081 Prior art multi-user wireless systems may include only a single base
station or several base stations.
100091 A single WiFi base station (e.g., utilizing 2.4 GHz 802.11b, g or n
protocols) attached to a broadband wired Internet connection in an area where
there are no other WiFi access points (e.g. a WiFi access point attached to
DSL
within a rural home) is an example of a relatively simple multi-user wireless
system that is a single base station that is shared by one or more users that
are
within its transmission range. If a user is in the same room as the wireless
access point, the user will typically experience a high-speed link with few
transmission disruptions (e.g. there may be packet loss from 2.4GHz
interferers,
like microwave ovens, but not from spectrum sharing with other WiFi devices),
If
a user is a medium distance away or with a few obstructions in the path
between
the user and WiFi access point, the user will likely experience a medium-speed
link. If a user is approaching the edge of the range of the WiFi access point,
the
user will likely experience a low-speed link, and may be subject to periodic
drop-
outs if changes to the channel result in the signal SNR dropping below usable
levels. And, finally, if the user is beyond the range of the WiFi base
station, the
user will have no link at all.
[0010] When multiple users access the WiFi base station simultaneously, then
the available data throughput is shared among them. Different users will
typically
Filed Via EFS-Web
6181P515X
136
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 20131166464 PCT/US2013/039580
place different throughput demands on a WiFi base station at a given time, but
at
times when the aggregate throughput demands exceed the available throughput
from the WiFi base station to the users, then some or all users will receive
less
data throughput than they are seeking. In an extreme situation where a WiFi
access point is shared among a very large number of users, throughput to each
user can slow down to a crawl, and worse, data throughput to each user may
arrive in short bursts separated by long periods of no data throughput at all,
during which time other users are served. This "choppy" data delivery may
impair
certain applications, like media streaming.
[0011] Adding additional WiFi base stations in situations with a large number
of
users will only help up to a point. Within the 2.4GHz ISM band in the U.S.,
there
are 3 non-interfering channels that can be used for WiFi, and if 3 WiFi base
stations in the same coverage area are configured to each use a different non-
interfering channel, then the aggregate throughput of the coverage area among
multiple users will be increased up to a factor of 3. But, beyond that, adding
more
WiFi base stations in the same coverage area will not increase aggregate
throughput, since they will start sharing the same available spectrum among
them, effectually utilizing time-division multiplexed access (TDMA) by "taking
turns" using the spectrum. This situation is often seen in coverage areas with
high population density, such as within multi-dwelling units. For example, a
user
in a large apartment building with a WiFi adapter may well experience very
poor
throughput due to dozens of other interfering WiFi networks (e.g. in other
Filed Via EFS-Web
6181P515x
137
CA 2 8 7250 2 2 02 0-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
apartments) serving other users that are in the same coverage area, even if
the
user's access point is in the same room as the client device accessing the
base
station. Although the link quality is likely good in that situation, the user
would be
receiving interference from neighbor WiFi adapters operating in the same
frequency band, reducing the effective throughput to the user.
100121 Current multiuser wireless systems, including both unlicensed spectrum,
such as WiFi, and licensed spectrum, suffer from several limitations. These
include coverage area, downlink (DL) data rate and uplink (UL) data rate. Key
goals of next generation wireless systems, such as WiMAX and LTE, are to
improve coverage area and DL and UL data rate via multiple-input multiple-
output (MIMO) technology. MIMO employs multiple antennas at transmit and
receive sides of wireless links to improve link quality (resulting in wider
coverage)
or data rate (by creating multiple non-interfering spatial channels to every
user).
If enough data rate is available for every user (note, the terms "user" and
"client"
are used herein interchangeably), however, it may be desirable to exploit
channel
spatial diversity to create non-interfering channels to multiple users (rather
than
single user), according to multiuser MIMO (MU-MIMO) techniques [20-27]. . For
example, in MIMO 4x4 systems (i.e., four transmit and four receive antennas),
10MHz bandwidth, 16-QAM modulation and forward error correction (FEC)
coding with rate 3/4 (yielding spectral efficiency of 3bps/Hz), the ideal peak
data
rate achievable at the physical layer for every user is 4x30Mbps=120Mbps,
which
is much higher than required to deliver high definition video content (which
may
Filed Via EFS-Web
6181P515X
138
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
11110
only require -10Mbps). In MU-MIMO systems with four transmit antennas, four
users and single antenna per user, in ideal scenarios (i.e., independent
identically distributed, i.i.d., channels) downlink data rate may be shared
across
the four users and channel spatial diversity may be exploited to create four
parallel 30Mbps data links to the users.
[0013] Different MU-MIMO schemes have been proposed as part of the LTE
standard [1-3], but they can provide only up to 2X improvement in DL data rate
with four transmit antennas. Practical implementations of MU-MIMO techniques
in standard and proprietary cellular systems by companies like ArrayComm [4]
have yielded up to a -3X increase (with four transmit antennas) in DL data
rate
via space division multiple access (SDMA). A key limitation of MU-MIMO
schemes in cellular networks is lack of spatial diversity at the transmit
side.
Spatial diversity is a function of antenna spacing and multipath angular
spread in
the wireless links. In cellular systems employing MU-MIMO techniques, transmit
antennas at a base station are typically clustered together and placed only
one or
two wavelengths apart due to limited real estate on antenna support structures
(referred to herein as "towers," whether physically tall or not) and due to
limitations on where towers may be located. Moreover, multipath angular spread
is low since cell towers are typically placed high up (10 meters or more)
above
obstacles to yield wider coverage.
Filed Via EFS-Web
6181P515X
139
CA 2 8 7 250 2 2 02 0-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
0
[0014] Other practical issues with cellular system deployment include
excessive
cost and limited availability of locations for cellular antenna locations
(e.g. due to
municipal restrictions on antenna placement, cost of real-estate, physical
obstructions, etc.) and the cost and/or availability of network connectivity
to the
transmitters (referred to herein as "backhaul"). Further, cellular systems
often
have difficulty reaching clients located deeply in buildings due to losses
from
walls, ceilings, floors, furniture and other impediments.
[0015] Indeed, the entire concept of a cellular structure for wide-area
network
wireless presupposes a rather rigid placement of cellular towers, an
alternation of
frequencies between adjacent cells, and frequently sectorization, so as to
avoid
interference among transmitters (either base stations or users) that are using
the
same frequency. As a result, a given sector of a given cell ends up being a
shared block of DL and UL spectrum among all of the users in the cell sector,
which is then shared among these users primarily in only the time domain. For
example, cellular systems based on Time Division Multiple Access (TDMA) and
Code Division Multiple Access (CDMA) both share spectrum among users in the
time domain. By overlaying such cellular systems with sectorization, perhaps a
2-
3X spatial domain benefit can be achieved. And, then by overlaying such
cellular
systems with a MU-MIMO system, such as those described previously, perhaps
another 2-3X space-time domain benefit can be achieved. But, given that the
cells and sectors of the cellular system are typically in fixed locations,
often
dictated by where towers can be placed, even such limited benefits are
difficult to
Filed Via EFS-Web
6181 P515X
140
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
410
exploit if user density (or data rate demands) at a given time does not match
up
well with tower/sector placement. A cellular smart phone user often
experiences
the consequence of this today where the user may be talking on the phone or
downloading a web page without any trouble at all, and then after driving (or
even walking) to a new location will suddenly see the voice quality drop or
the
web page slow to a crawl, or even lose the connection entirely. But, on a
different day, the user may have the exact opposite occur in each location.
What
the user is probably experiencing, assuming the environmental conditions are
the
same, is the fact that user density (or data rate demands) is highly variable,
but
the available total spectrum (and thereby total data rate, using prior art
techniques) to be shared among users at a given location is largely fixed.
100161 Further, prior art cellular systems rely upon using different
frequencies in
different adjacent cells, typically 3 different frequencies. For a given
amount of
spectrum, this reduces the available data rate by 3X.
[0017] So, in summary, prior art cellular systems may lose perhaps 3X in
spectrum utilization due to cellularization, and may improve spectrum
utilization
by perhaps 3X through sectorization and perhaps 3X more through MU-MIMO
techniques, resulting in a net 3*3/3 = 3X potential spectrum utilization.
Then, that
bandwidth is typically divided up among users in the time domain, based upon
what sector of what cell the users fall into at a given time. There are even
further
inefficiencies that result due to the fact that a given user's data rate
demands are
Filed Via EFS-Web
6181P515X
141
CA 28 7 250 2 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
0
typically independent of the user's location, but the available data rate
varies
depending on the link quality between the user and the base station. For
example, a user further from a cellular base station will typically have less
available data rate than a user closer to a base station. Since the data rate
is
typically shared among all of the users in a given cellular sector, the result
of this
is that all users are impacted by high data rate demands from distant users
with
poor link quality (e.g. on the edge of a cell) since such users will still
demand the
same amount of data rate, yet they will be consuming more of the shared
spectrum to get it.
100181 Other proposed spectrum sharing systems, such as that used by WiFi
(e.g., 802.11b, g, and n) and those proposed by the White Spaces Coalition,
share spectrum very inefficiently since simultaneous transmissions by base
stations within range of a user result in interference, and as such, the
systems
utilize collision avoidance and sharing protocols. These spectrum sharing
protocols are within the time domain, and so, when there are a large number of
interfering base stations and users, no matter how efficient each base station
itself is in spectrum utilization, collectively the base stations are limited
to time
domain sharing of the spectrum among each other. Other prior art spectrum
sharing systems similarly rely upon similar methods to mitigate interference
among base stations (be they cellular base stations with antennas on towers or
small scale base stations, such as WiFi Access Points (APs)). These methods
include limiting transmission power from the base station so as to limit the
range
Filed Via EFS-Web
6181P515X
142
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
of interference, beamforming (via synthetic or physical means) to narrow the
area
of interference, time-domain multiplexing of spectrum and/or MU-M IMO
techniques with multiple clustered antennas on the user device, the base
station
or both. And, in the case of advanced cellular networks in place or planned
today, frequently many of these techniques are used at once.
[0019] But, what is apparent by the fact that even advanced cellular systems
can
achieve only about a 3X increase in spectrum utilization compared to a single
user utilizing the spectrum is that all of these techniques have done little
to
increase the aggregate data rate among shared users for a given area of
coverage. In particular, as a given coverage area scales in terms of users, it
becomes increasingly difficult to scale the available data rate within a given
amount of spectrum to keep pace with the growth of users. For example, with
cellular systems, to increase the aggregate data rate within a given area,
typically
the cells are subdivided into smaller cells (often called nano-cells or femto-
cells).
Such small cells can become extremely expensive given the limitations on where
towers can be placed, and the requirement that towers must be placed in a
fairly
structured pattern so as to provide coverage with a minimum of "dead zones",
yet
avoid interference between nearby cells using the same frequencies.
Essentially,
the coverage area must be mapped out, the available locations for placing
towers
or base stations must be identified, and then given these constraints, the
designers of the cellular system must make do with the best they can. And, of
course, if user data rate demands grow over time, then the designers of the
Filed Via EFS-Web
6181P515X
143
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
III
cellular system must yet again remap the coverage area, try to find locations
for
towers or base stations, and once again work within the constraints of the
circumstances. And, very often, there simply is no good solution, resulting in
dead zones or inadequate aggregate data rate capacity in a coverage area. In
other words, the rigid physical placement requirements of a cellular system to
avoid interference among towers or base stations utilizing the same frequency
results in significant difficulties and constraints in cellular system design,
and
often is unable to meet user data rate and coverage requirements.
100201 So-called prior art "cooperative" and "cognitive" radio systems seek to
increase the spectral utilization in a given area by using intelligent
algorithms
within radios such that they can minimize interference among each other and/or
such that they can potentially "listen" for other spectrum use so as to wait
until
the channel is clear. Such systems are proposed for use particularly in
unlicensed spectrum in an effort to increase the spectrum utilization of such
spectrum.
100211 A mobile ad hoc network (MANET) (see htto://en.wikioedia.org/wiki/
Mobile ad hoc network) is an example of a cooperative self-configuring network
intended to provide peer-to-peer communications, and could be used to
establish
communication among radios without cellular infrastructure, and with
sufficiently
low-power communications, can potentially mitigate interference among
simultaneous transmissions that are out of range of each other. A vast number
of
Filed Via EFS-Web
6181P515X
144
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
0 WO 2013/166464
PCT/US2013/039580
411)
routing protocols have been proposed and implemented for MANET systems
(see http://en.wikipedia.orgiwiki/List of ad-hoc routing protocols for a list
of
dozens of routing protocols in a wide range of classes), but a common theme
among them is they are all techniques for routing (e.g. repeating)
transmissions
in such a way to minimize transmitter interference within the available
spectrum,
towards the goal of particular efficiency or reliability paradigms.
100221 All of the prior art multi-user wireless systems seek to improve
spectrum
utilization within a given coverage area by utilizing techniques to allow for
simultaneous spectrum utilization among base stations and multiple users.
Notably, in all of these cases, the techniques utilized for simultaneous
spectrum
utilization among base stations and multiple users achieve the simultaneous
spectrum use by multiple users by mitigating interference among the waveforms
to the multiple users. For example, in the case of 3 base stations each using
a
different frequency to transmit to one of 3 users, there interference is
mitigated
because the 3 transmissions are at 3 different frequencies. In the case of
sectorization from a base station to 3 different users, each 180 degrees apart
relative to the base station, interference is mitigated because the
beamforming
prevents the 3 transmissions from overlapping at any user.
100231 When such techniques are augmented with MU-MIMO, and, for example,
each base station has 4 antennas, then this has the potential to increase
downlink throughput by a factor of 4, by creating four non-interfering spatial
channels to the users in given coverage area. But it is still the case that
some
Filed Via EFS-Web
6181P515X
145
CA 28 7 250 2 2 020 -0 3-0 6 SUBSTITUTE SHEET (RULE 26)
SWO 2013/166464
PCT/US2013/039580
=
technique must be utilized to mitigate the interference among multiple
simultaneous transmissions to multiple users in different coverage areas.
100241 And, as previously discussed, such prior art techniques (e.g.
cellularization, sectorization) not only typically suffer from increasing the
cost of
the multi-user wireless system and/or the flexibility of deployment, but they
typically run into physical or practical limitations of aggregate throughput
in a
given coverage area. For example, in a cellular system, there may not be
enough
available locations to install more base stations to create smaller cells.
And, in an
MU-MIMO system, given the clustered antenna spacing at each base station
location, the limited spatial diversity results in asymptotically diminishing
returns
in throughput as more antennas are added to the base station.
100251 And further, in the case of multi-user wireless systems where the user
location and density is unpredictable, it results in unpredictable (with
frequently
abrupt changes) in throughput, which is inconvenient to the user and renders
some applications (e.g. the delivery of services requiring predictable
throughput)
impractical or of low quality. Thus, prior art multi-user wireless systems
still leave
much to be desired in terms of their ability to provide predictable and/or
high-
quality services to users.
100261 Despite the extraordinary sophistication and complexity that has been
developed for prior art multi-user wireless systems over time, there exist
common
themes: transmissions are distributed among different base stations (or ad hoc
Filed Via EFS-Web
6181P515X
146
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
SWO 2013/166464
PCT/US2013/039580
110
transceivers) and are structured and/or controlled so as to avoid the RF
waveform transmissions from the different base stations and/or different ad
hoc
transceivers from interfering with each other at the receiver of a given user.
100271 Or, to put it another way, it is taken as a given that if a user
happens to
receive transmissions from more than one base station or ad hoc transceiver at
the same time, the interference from the multiple simultaneous transmissions
will
result in a reduction of the SNR and/or bandwidth of the signal to the user
which,
if severe enough, will result in loss of all or some of the potential data (or
analog
information) that would otherwise have been received by the user.
100281 Thus, in a multiuser wireless system, it is necessary to utilize one or
more
spectrum sharing approaches or another to avoid or mitigate such interference
to
users from multiple base stations or ad hoc transceivers transmitting at the
same
frequency at the same time. There are a vast number of prior art approaches to
avoiding such interference, including controlling base stations' physical
locations
(e.g. cellularization), limiting power output of base stations and/or ad hoc
transceivers (e.g. limiting transmit range), beamforming/sectorization, and
time
domain multiplexing. In short, all of these spectrum sharing systems seek to
address the limitation of multiuser wireless systems that when multiple base
stations and/or ad hoc transceivers transmitting simultaneously at the same
frequency are received by the same user, the resulting interference reduces or
destroys the data throughput to the affected user. If a large percentage, or
all, of
Filed Via EFS-Web
6181P515X
147
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
110
the users in the multi-user wireless system are subject to interference from
multiple base stations and/or ad hoc transceivers (e.g. in the event of the
malfunction of a component of a multi-user wireless system), then it can
result in
a situation where the aggregate throughput of the multi-user wireless system
is
dramatically reduced, or even rendered non-functional..
100291 Prior art multi-user wireless systems add complexity and introduce
limitations to wireless networks and frequently result in a situation where a
given
user's experience (e.g. available bandwidth, latency, predictability,
reliability) is
impacted by the utilization of the spectrum by other users in the area. Given
the
increasing demands for aggregate bandwidth within wireless spectrum shared by
multiple users, and the increasing growth of applications that can rely upon
multi-
user wireless network reliability, predictability and low latency for a given
user, it
is apparent that prior art multi-user wireless technology suffers from many
limitations. Indeed, with the limited availability of spectrum suitable for
particular
types of wireless communications (e.g. at wavelengths that are efficient in
penetrating building walls), it may be the case that prior art wireless
techniques
will be insufficient to meet the increasing demands for bandwidth that is
reliable,
predictable and low-latency.
[0030] What is needed is a multiuser wireless system that does not suffer from
the aforementioned limitations:
(a) limitations in aggregate bandwidth in a given amount
of spectrum;
Filed Via EFS-Web
6181P515X
148
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
0
(b) lack of reliable, predictable and low-latency communications for a
given user;
(c) one user's use of the wireless network negatively impacting another
user's use;
(d) lack of flexibility in the placement of transceivers and/or antennas
that form the multi-user wireless system;
(e) lack of flexibility allowing transceivers and/or antennas to be
installed either by commercial network providers or by individuals; or
(f) impractical or expensive implementations.
Filed Via EFS-Web
6181P515X
149
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCMJS2013/039580
=
BRIEF DESCRIPTION OF THE DRAWINGS
100011 A better understanding of the present invention can be
obtained from
the following detailed description in conjunction with the drawings, in which:
[0002] FIG. 1 illustrates a prior art MIMO system.
[0003] FIG. 2 illustrates an N-antenna Base Station
communicating with a
plurality of Single-antenna Client Devices.
100041 FIG. 3 illustrates a three Antenna Base Station
communicating with
three Single-Antenna Client Devices
100051 FIG. 4 illustrates training signal techniques employed
in one
embodiment of the invention.
[0006] FIG. 5 illustrates channel characterization data
transmitted from a client
device to a base station according to one embodiment of the invention.
[0007] FIG. 6 illustrates a Multiple-Input Distributed-Output
("MIDO")
downstream transmission according to one embodiment of the invention.
[0008] FIG. 7 illustrates a Multiple-Input Multiple Output
("MIMO") upstream
transmission according to one embodiment of the invention.
[0009] FIG. 8 illustrates a base station cycling through
different client groups to
allocate throughput according to one embodiment of the invention.
[0010] FIG. 9 illustrates a grouping of clients based on
proximity according to
one embodiment of the invention.
Filed Via EFS-Web
6181P515X
150
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
0 WO 2013/166464
PCT/US2013/039580
0
[0011] FIG. 10 illustrates an embodiment of the invention
employed within an
NVIS system.
[0012] FIG. 11 illustrates an embodiment of the DIDO
transmitter with I/Q
compensation functional units.
[0013] FIG. 12 a DIDO receiver with I/Q compensation
functional units.
[0014] FIG. 13 illustrates one embodiment of DIDO-OFDM systems
with I/Q
compensation.
[0015] FIG. 14 illustrates one embodiment of DIDO 2 x 2
performance with
and without I/Q compensation.
[0016] FIG. 15 illustrates one embodiment of DIDO 2 x 2
performance with
and without I/Q compensation.
[0017] FIG. 16 illustrates one embodiment of the SER (Symbol
Error Rate)
with and without I/Q compensation for different QAM constellations.
[0018] FIG. 17 illustrates one embodiment of DIDO 2 x 2
performances with
and without compensation in different user device locations.
[0019] FIG. 18 illustrates one embodiment of the SER with and
without I/Q
compensation in ideal (i.i.d. (independent and identically-distributed))
channels.
[0020] FIG. 19 illustrates one embodiment of a transmitter
framework of
adaptive DIDO systems.
Filed Via EFS-Web
6181P515X
151
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
[0021] FIG. 20 illustrates one embodiment of a receiver
framework of adaptive
DIDO systems.
[0022] FIG. 21 illustrates one embodiment of a method of
adaptive DIDO-
OFDM.
[0023] FIG. 22 illustrates one embodiment of the antenna
layout for DIDO
measurements.
[0024] FIG. 23 illustrates embodiments of array configurations
for different
order DIDO systems.
[0025] FIG. 24 illustrates the performance of different order
DIDO systems.
[0026] FIG. 25 illustrates one embodiment of the antenna
layout for DIDO
measurements.
[0027] FIG. 26 illustrates one embodiment of the DIDO 2 x 2
performance with
4-QAM and FEC rate 1/2 as function of the user device location.
[0028] FIG. 27 illustrates one embodiment of the antenna
layout for DIDO
measurements.
[0029] FIG. 28 illustrates how, in one embodiment, DIDO 8 x 8
yields larger
SE than DIDO 2 x 2 for lower TX power requirement.
[0030] FIG. 29 illustrates one embodiment of DIDO 2 x 2
performance with
antenna selection.
Filed Via EFS-Web
6181P515X
152
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
0 WO 2013/166464
PCT/US2013/039580
=
[0031] FIG. 30 illustrates average bit error rate (BER)
performance of different
DIDO precoding schemes in i.i.d. channels.
100321 FIG. 31 illustrates the signal to noise ratio (SNR)
gain of ASel as a
function of the number of extra transmit antennas in i.i.d. channels.
100331 FIG. 32 illustrates the SNR thresholds as a function of
the number of
users (M) for block diagnalization (BD) and ASel with 1 and 2 extra antennas
in
i.i.d. channels.
[0034] FIG. 33 illustrates the BER versus per-user average SNR
for two users
located at the same angular direction with different values of Angle Spread
(AS).
[0035] FIG. 34 illustrates similar results as FIG. 33, but
with higher angular
separation between the users.
[0036] FIG. 35 plots the SNR thresholds as a function of the
AS for different
values of the mean angles of arrival (A0As) of the users.
[0037] FIG. 36 illustrates the SNR threshold for an exemplary
case of five
users.
[0038] FIG. 37 provides a comparison of the SNR threshold of
BD and ASel,
with 1 and 2 extra antennas, for two user case.
[0039] FIG. 38 illustrates similar results as FIG. 37, but for
a five user case.
[0040] FIG. 39 illustrates the SNR thresholds for a BD scheme
with different
values of AS.
Filed Via EFS-Web
6181P515X
153
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
=
[0041] FIG. 40 illustrates the SNR thresholds in spatially
correlated channels
with AS= 0.1 for BD and ASel with 1 and 2 extra antennas.
[0042] FIG. 41 illustrates the computation of the SNR
thresholds for two more
channel scenarios with AS= 5 .
[0043] FIG. 42 illustrates the computation of the SNR
thresholds for two more
channel scenarios with AS= 10 .
[0044] FIGS. 43-44 illustrate the SNR thresholds as a function
of the number
of users (M) and angle spread (AS) for BD and ASel schemes, with 1 and 2 extra
antennas, respectively.
[0045] FIG 45 illustrates a receiver equipped with frequency
offset
estimator/compensator.
[0046] FIG. 46 illustrates DIDO 2 x 2 system model according
to one
embodiment of the invention.
[0047] FIG. 47 illustrates a method according to one
embodiment of the
invention.
[0048] FIG. 48 illustrates SER results of DIDO 2 x 2 systems
with and without
frequency offset.
[0049] FIG. 49 compares the performance of different DIDO
schemes in terms
of SNR thresholds.
Filed Via EFS-Web
6181P515X
154
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 20131166464 PCT/US2013/039580
0
[0050] FIG. 50 compares the amount of overhead required for
different
embodiments of methods.
[0051] FIG. 51 illustrates a simulation with a small frequency
offset of fmax =
2Hz and no integer offset correction.
[0052] FIG. 52 illustrates results when turning off the
integer offset estimator.
100531 FIG. 53 illustrates downlink spectral efficiency (SE)
in [bps/Hz] as a
function of mutual information in [bps/Hz].
[0054] FIG. 54 illustrates average per-user symbol error rare
(SER)
performance as a function of the mutual information in [bps/Hz].
[0055] FIG. 55 illustrates average per-user SER performance as
a function of
the minimum mutual information in [bps/Hz] and the thresholds used to switch
between different DIDO modes.
[0056] FIG. 56 illustrates average per-user SER vs. SNR for
fixed modulation
and adaptive DIDO systems.
100571 FIG. 57 illustrates downlink SE vs. SNR for fixed
modulation and
adaptive DIDO systems.
[0058] FIG. 58 illustrates average per-user SER vs. SNR for
adaptive DIDO
systems with different thresholds.
[0059] FIG. 59 illustrates downlink SE vs. SNR for adaptive
DIDO systems
with different thresholds
Filed Via EFS-Web
6181P515X
155
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PC171582013/039580
=
[0031] FIG. 60 illustrates average per-user SER performance as
a function of
the minimum singular value of the effective channel matrix and the CQI
threshold
for 4-QAM constellation.
[0032] FIG. 61 illustrates one embodiment of a circular
topology of base
transceiver stations (DIDO antennas)
[0033] FIG. 62 illustrates an one embodiment of an alternate
arrangement of
DIDO antennas.
[0034] FIG. 63 illustrates one embodiment in which a base
station network
(BSN) is used to deliver precoded baseband data from the centralized
processors (CPs) to DIDO antennas.
100351 FIG. 64 illustrates one embodiment in which the BSN is
used to carry
modulated signals.
[0036] FIG. 65 illustrates one embodiment comprised of two
DIDO base
stations perfectly synchronized and two users with Line Of Sight (LOS)
channels
100371 FIG. 66 illustrates the path loss of DIDO at 85MHz and
400MHz using
the Hata-Okumura model.
[0038] FIG. 67 illustrates the period maximum delay between
channel state
information and data transmission as a function of the relative velocity
between
transmitter and receiver for different frequencies in the UHF band.
[0039] FIG. 68 illustrates propagation effects in DIDO systems
for three
different carrier frequencies.
[0040] FIG. 69 illustrates the areas in the US territory
currently covered by
transceiver stations operating in the Maritime band. The colors identify the
Filed Via EFS-Web
6181P515X
156
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
wo 2013/166464 PCT/US2013/039580
number of active channels (out of the 146 channels available in the Maritime
band) that would cause harmful interference to DIDO-NVIS stations at any
location.
[0041] FIG. 70 illustrates sunspot number from the January
1900 throughout
June 2009.
100421 FIG. 71 illustrates the path loss of WiMAX, LTE and
NVIS systems.
[0043] FIG. 72 illustrates the locations of DIDO-NVIS
transmitter (TX) and
receiver (RX) stations
[0044] FIG. 73 illustrates DIDO-NVIS receive antenna location.
"lambda"
denotes the wavelength at 3.9MHz (-77meters)
[0045] FIG. 74 illustrates typical 4-QAM constellations
demodulated at three
users' locations over DIDO-NVIS links.
[0046] FIG. 75 illustrates SER as a function of PU-SNR for
DIDO-NVIS 3x3.
[0047] FIG. 76 illustrates DIDO-NVIS cells across the
territory of the 48
contiguous states of the USA.
=
Filed Via EFS-Web
6181 P515X
157
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
110 WO 2013/166464
PCT/US2013/039580
=
DETAILED DESCRIPTION
1. DIDO system description
[0048] One solution to overcome many of the above prior art limitations is an
embodiment of Distributed-Input Distributed-Output (DIDO) technology. DIDO
technology is described in the following patents and patent applications, all
of
which are assigned the assignee of the present patent and are incorporated by
reference:
[0049] U.S. Patent No. 7,599,420, filed August 20, 2007, issued Oct. 6, 2009,
entitled "System and Method for Distributed Input Distributed Output Wireless
Communication";
100501 U.S. Application Serial No. 12/143,503, filed June 20, 2008 entitled,
"System and Method For Distributed Input-Distributed Output Wireless
Communications";
[0051] U.S. Application Serial No. 11/894,394, filed August 20, 2007 entitled,
"System and Method for Distributed Input Distributed Output Wireless
Communications";
100521 U.S. Application Serial No. 11/894,362, filed August 20, 2007 entitled,
"System and method for Distributed Input-Distributed Wireless Communications":
100531 U.S. Application Serial No. 11/894,540, filed August 20, 2007 entitled
"System and Method For Distributed Input-Distributed Output Wireless
Communications"
Filed Via EFS-Web
6181P515X
158
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
[00541 U.S. Application Serial No. 11/256,478, filed October 21, 2005 entitled
"System and Method For Spatial-Multiplexed Tropospheric Scatter
Communications";
[0055] U.S. Patent No. 7,418,053, filed July 30, 2004, issued August 26, 2008,
entitled "System and Method for Distributed Input Distributed Output Wireless
Communication";
100561 U.S. Application Serial No. 10/817,731, filed April 2, 2004 entitled
"System
and Method For Enhancing Near Vertical Incidence Skywave ("NVIS")
Communication Using Space-Time Coding.
100571 The foregoing patent applications are referred to below as the "related
applications."
100581 DIDO systems are described in the related application U.S. Patent
7,418,053, where multiple antennas of the same DIDO base station in Figure 2
work cooperatively to pre-cancel interference and create parallel non-
interfering
data streams to multiple users. These antennas, with or without local
transmitters
and/or receivers may be spread across a wide coverage area and be
interconnected to the same DIDO base station via wired or wireless links,
including networks such as the Internet. For example, as disclosed in related
US
Patent 7,418,053 in the paragraph starting at column 6, line 31, a single base
station may have its antennas located very far apart, potentially resulting in
the
base station's antenna array occupying several square kilometers. And, for
example as disclosed in related US Patent 7,599,420 in the paragraph starting
at
column 17 line 4, and in paragraphs [0142] of U.S. Application Serial No.
Filed Via EFS-Web
6181P515X
159
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
11/894,362 and U.S. Application Serial No. 11/894,540, the separation of
antennas from a single DIDO base station may be physically separated by 100s
of yards or even miles, potentially providing diversity advantages, and the
signals
for each antenna installation may either processed locally at each antenna
location or brought back to a centralized location for processing. Further,
methods for practical deployment of DIDO systems, including addressing
practical issues associated with processing signals with widely distributed
DIDO
antennas, are described in the related applications U.S. Patent No. 7,599,420,
U.S. Application No. 11/894,362 and U.S. Application No. 11/894,540.
[0059] Recent publications [32,33] analyzed theoretically the performance of
cooperative base stations in the context of cellular systems. In practice,
when
those cooperative base stations are connected to one another via wireless,
wired, or optical network (i.e., wide area network, WAN backbone, router) to
share precoded data, control information and/or time/frequency synchronization
information as described in U.S. Patent No. 7,418,053, U.S. Patent No.
7,599,420, U.S. Application Serial No. 11/894,362 and U.S. Application Serial
No. 11/894,540 they function as multiple distributed antennas of a single DIDO
base station as shown in Figures 2 and 3. In the system in [32,33], however,
multiple base stations (or distributed antennas of the same DIDO base station)
are constrained by their physical placements derived from cell planning, as in
conventional cellular systems.
[0060] A significant advantage of DIDO systems over prior art systems is that
DIDO systems enable the distribution of multiple cooperative distributed
Filed Via EFS-Web
6181P515X
160
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
0
antennas, all using the same frequency at the same time in the same wide
coverage area, without significantly restricting the physical placement of the
distributed antennas. In contrast to prior art multi-user systems, which avoid
interference from multiple base transmitters at a given user receiver, the
simultaneous RF waveform transmissions from multiple DIDO distributed
antennas deliberately interfere with each other at each user's receiver. The
interference is a precisely controlled constructive and destructive
interference of
RF waveforms incident upon each receiving antenna which, rather than impairing
data reception, enhances data reception. It also achieves a valuable goal: it
results in multiple simultaneous non-interfering channels to the users via
space-
time precoding techniques, increasing the aggregate throughput in a given
coverage area, increasing the throughput to a given user, and significantly
increasing the reliability and predictability of throughput to a given user.
100611 Thus, when using DIDO, multiple distributed antenna RF waveform
transmission interference and user channel interference have an inverse
relationship: multiple distributed antenna RF waveform interference results in
simultaneous non-interfering user channels.
100621 With prior art multi-user systems, multiple base station (and/or ad hoc
transceivers) RF waveform transmission interference and user channel
interference have a direct relationship: multiple base station (and/or ad hoc
transceivers) RF waveform interference results in simultaneous interfering
user
channels.
Filed Via EFS-Web
6181P515X
161
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
0 WO 2013/166464
PCI7US2013/039580
Ili
100631 So, what DIDO utilizes and relies upon to achieve performance far
beyond
prior art systems is exactly what is avoided by, and results in impairment of,
prior
art systems.
[0064] And, because the number of non-interfering channels (and aggregate
throughput) grows largely proportionately with the number of DIDO distributed
antennas (unlike MU-MIMO systems, where the aggregate throughput
asymptotically levels off as the number of cluster antennas at a base station
is
increased), the spectrum utilization of a given coverage area can be scaled as
the number of users in an area scales, all without subdividing the coverage
area
by frequency or sector, and without requiring significant restrictions on the
placement of DIDO distributed antennas. This results in enormous efficiencies
in
spectrum utilization and aggregate user downlink (DL) and uplink (UL) data
rates,
and enormous placement flexibility for either commercial or consumer base
station installation.
100651 In this way, DIDO opens the door to a very large increase in multi-user
wireless spectrum efficiency by specifically doing exactly what prior art
systems
had been meticulously designed to avoid doing.
100661 As illustrated in Figures 61-62, in one embodiment, DIDO systems
consist
of:
= DIDO Clients 6110: wireless devices that estimate the channel state
information (CSI), feedback the CSI to the transmitters and demodulate
precoded
data. Typically each user would have a DIDO client device.
Filed Via EFS-Web
6181P515X
162
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
0 WO 2013/166464
PCT/US2013/039580
=
= DIDO Distributed Antennas 6113: wireless devices interconnected via a
network that transmit precoded data to all DIDO clients. A wide variety of
network types can be used to interconnect the distributed antennas 6113
including, but not limited to, a local area network (LAN), a wire area network
(WAN), the Internet, a commercial fiber optic loop, a wireless network, or any
combination thereof. In one embodiment, to provide a simultaneous independent
channel to each client, the number of DIDO distributed antennas is at least
equal
to the number of clients that are served via precoding, and thereby avoids
sharing channels among clients. More DIDO distributed antennas than clients
can be used to improve link reliability via transmit diversity techniques, or
can be
used in combination with multi-antenna clients to increase data rate and/or
improve link reliability. Note that "distributed antenna", as used herein, may
not
be merely an antenna, but refers to a device capable of transmitting and/or
receiving through at least one antenna. For example, the device may
incorporate
the network interface to the DIDO BTS 6112 (described below) and a
transceiver,
as well as an antenna attached to the transceiver. The distributed antennas
6113
are the antennas that the DIDO BTS 6112, utilizes to implement the DIDO multi-
user system.
= DIDO Base Transceiver Station ("BTS" or "base station") 6112:
computes the precoding weights based on the CSI obtained from all users in a
DIDO system and sends precoded data to the DIDO distributed antennas. The
BTS may be connected to the Internet, public switched telephone network
(PSTN) or private networks to provide connectivity between users and such
Filed Via EFS-Web
6161P515X
163
SUBSTITUTE SHEET (RULE 26)
CA 2872502 2020-03-06
=
WO 2013/166464 PCT/US2013/039580
networks. For example, upon clients' requests to access web content, the CP
fetches data through the Internet and transmits data to the clients via the
DIDO
distributed antennas.
= DIDO Base Station Network (BSN) 6111: One embodiment of DIDO
technology enables precisely controlled cooperation among multiple DIDO
distributed antennas spread over wide areas and interconnected by a network.
In
one embodiment, the network used to interconnect the DIDO distributed
antennas is a metro fiber optic ring (preferably, with the DIDO distributed
antennas connecting to the metro fiber optic ring at locations where it is
convenient), characterized by relatively low latency and reasonably high
throughput (e.g. throughput to each DIDO antenna comparable to the wireless
throughput achievable from that DIDO antenna). The fiber optic ring is used to
share control information and precoded data among different stations. Note
that
many other communication networks can be used instead of a metro fiber optic
ring, including fiber optic networks in different topologies other than a
ring, fiber-
to-the-home (FFTH), Digital Subscriber Lines (DSL), cable modems, wireless
links, data over power line, Ethernet, etc. The communication network
interconnecting the DIDO distributed antennas may well be made up of a
combination of different network technologies. For example, some DIDO
distributed antennas may be connected to DSL, some to fiber, some to cable
modems, some on Ethernet, etc. The network may be a private network, the
Internet, or a combination. Thus, much like prior art consumer and commercial
WiFi base stations are connected via a variety of network technologies, as is
Filed Via EFS-Web
6181P515X
164
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039590
=
convenient at each location, so may be the DIDO distributed antennas. Whatever
form this network takes, be it a uniform technology, or a variety of
technologies, it
is referred herein as the Base Station Network or "BSN." In one embodiment of
the BSN, there is an approximate 10-30msec round trip time (RU) latency
between BTS and the DIDO distributed antennas, due to the packet switched
nature of existing fiber or DSL networks. The variance of that latency (i.e.,
jitter)
is of the order of milliseconds. If lower latency (i.e., <lmsec) and jitter is
required
for DIDO systems, the BSN may be designed with dedicated fiber links.
Depending on the quality of service offered to different DIDO clients, a
combination of low and high latency BSNs can be employed.
100671 Depending on the layout of the network interconnecting the DIDO
distributed antennas 6113, one or multiple DIDO BTSs can be used in a given
coverage area. We define a DIDO cell as the coverage area served by one
DIDO BTS. One embodiment with circular topology is depicted in Figure 61 (the
dots are the DIDO clients 6110, and crosses are the DIDO distributed antennas
6113). In more realistic scenarios the BSN does not have circular shape as in
Figure 61. In fact, the DIDO distributed antennas may be placed randomly
within the DIDO cell, wherever connections to the BSN are available and/or
conveniently reached, as depicted in Figure 62. If the coverage area is one
city,
in one embodiment multiple DIDO cells (associated to multiple DIDO BTSs) can
be designed to cover the whole city. In that case, cellular planning is
required to
allocate different frequency channels to adjacent DIDO cells to avoid inter-
cell
interference. Alternatively, one DIDO cell can be designed to cover the entire
Filed Via EFS-Web
6181P515X
165
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
0
city at the expense of higher computational complexity at the DIDO BTS (e.g.,
more CSI data from all the users in the same DIDO cell to be processed by the
BTS) and larger throughput requirement over the network interconnecting the
DIDO distributed antennas.
100681 In one embodiment of the invention, the BSN 6111 is used to deliver
precoded baseband data from the BTS 6112 to the DIDO distributed antennas
6113. As shown in Figure 63, the DIDO distributed antenna 6313 includes a
radio transceiver 6330 equipped with digital-to-analog converter (DAC), analog-
to-digital converter (ADC), mixer and coupled to (or including) a power
amplifier
6338. Each DIDO distributed antenna receives the baseband precoded data
6332 over the BSN 6311 (such as fiber optic cable 6331) from the BTS 6312,
modulates the signal at the carrier frequency and transmits the modulated
signal
to the clients over the wireless link via antenna 6339. As illustrated in
Figure 63,
a reference clock signal is provided to the radio transceiver by a reference
clock
generator 6333.
[0069] In another embodiment of the invention, the BSN is used to carry
modulated signals as illustrated in Figure 64, which shows the structure of
DIDO
systems employing RF-over-fiber. For example, if the BSN is a fiber optic
channel 6431 with sufficient bandwidth, a radio frequency (RF) modulated
signal
is sent over the fiber according to a system such as that described in
[17,18].
Multiple radios 6440 (up to as many as the number of DIDO distributed
antennas) can be employed at the BTS 6412 to modulate the baseband signals
carrying precoded data. The RF modulated signal is converted into optical
signal
,
Filed Via EFS-Web
6181 P515X
166
SUBSTITUTE SHEET (RULE 26)
CA 2872 502 2 020-0 3-0 6
=
WO 2013/166464 PCMS2013/039580
=
by the radio interface unit (RIU) 6441. One example of an RIU for UHF is the
FORAX LOS1 by Syntonics [19]. The optical signal propagates from the BTS to
the DIDO distributed antennas 6413 over the BSN 6411. The DIDO distributed
antennas are equipped with one amplifier interface unit (AIU) 6445 that
converts
the optical signal to RF. The RE signal is amplified by amplifier 6448 and
sent
through the antenna 6449 over the wireless link. An advantage of DIDO with RF-
over-fiber solution is significant reduction in complexity and cost of the
DIDO
distributed antennas. In fact, the DIDO distributed antenna consists only of
one
AIU 6445, power amplifier 6448 and antenna 6449. Moreover, if the fiber
propagation delay is known and fixed, all the radios at the BTS can be locked
to
the same reference clock 6442 as in Figure 64, with an appropriate delay to
compensate for the propagation delay, and no time/frequency synchronization is
required at the DIDO distributed antenna, thereby simplifying further the
complexity of DIDO systems.
100701 In another embodiment, existing cellular towers with antennas,
transceivers, and backhaul connectivity are reconfigured such that the
backhauls
are connected to a DIDO BTS 6112. The backhaul connectivity becomes
functionally equivalent to the BSN 6111. Then, as described previously, the
cellular transceivers and antennas become functionally equivalent to the DIDO
distributed antennas 6113. Depending on the transceivers and antennas
installed
in existing cellular phone towers, they may need to be reconfigured or
replaced,
so as to be able to operate in a DIDO configuration. For example, the
transmitters may have been configured to transmit at a low power level so as
to
Filed Via EFS-Web
6181P515X
167
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
0
not cause interference with a nearby cell using the same frequency. With DIDO,
there is no need to mitigate such waveform interference, and indeed, such
waveform interference increases the spectrum utilization of the coverage area
beyond that achievable in a prior art cellular configuration.
100711 In another embodiment, existing cellular towers are partially used for
DIDO, as described in the preceding paragraph, and partially used as
conventional cellular towers, so as to support compatibility with existing
cellular
devices. Such a combined system can be implemented in a number of different
ways. In one embodiment, TDMA is used to alternate between DIDO use and
conventional cellular use. So, at any given time, the cellular towers are used
for
only DIDO or for conventional cellular communications.
[0072] Some key features and benefits of DIDO systems, compared to typical
multi-user wireless systems, including cellular systems employing MU-MIMO
techniques, are:
= Large spatial diversity: Because DIDO distributed antennas can be located
anywhere within a coverage area, and work cooperatively without channel
interference, this results in larger transmit antenna spacing and multipath
angular
spread. Thus, far more antennas can be used, while still maintaining spatial
diversity. Unlike prior art commercial or consumer base stations, DIDO
distributed antennas can be placed anywhere there is a reasonably fast
Internet
(or other network) connection, even if it is only a few feet from the ground,
indoor
or outdoor. Reduced coverage (e.g., due to lower transmit antenna height or
Filed Via EFS-Web
6181P515X
168
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039500
=
physical obstacles) can be compensated by larger transmit power (e.g., 100W
rather than -200mW as in typical cellular systems in urban areas or -250mW in
typical WiFi access points) because there is no concern (or far less concern
than
with prior art cellular systems) about higher-powered transmissions
interfering
with another cell or WiFi access point using the same frequency. Larger
spatial
diversity translates into a larger number of non-interfering channels that can
be
created to multiple users. Theoretically (e.g., due to large antenna spacing
and
angular spread), the number of spatial channels is equal to the number of
transmit DIDO stations. That yields an nX improvement in aggregate DL data
rate, where n is the number of DIDO stations. For example, whereas prior art
cellular system might achieve a maximum of net 3X improvement in aggregate
spectrum utilization, a DIDO system might achieve a 10X, 100X or even greater
improvement in aggregate spectrum utilization.
= Uniform rate distribution: Since the DIDO distributed antennas can be
dispersed throughout a wide area, far more users can be characterized by good
signal-to-noise ratio (SNR) from one or more DIDO distributed antennas. Then,
far more users can experience similar data rates, unlike cellular systems
where
cell-edge users suffer from poor link-budget and low data rate.
= Cost effective: DIDO distributed antennas can be designed as inexpensive
devices with single antenna transceivers (similar to WiFi access points).
Moreover, they do not require costly real estate or expensive installation as
cell
towers because of the ability to flexibly locate them within the coverage
area.
Filed Via EFS-Web
6181P515X
169
SUBSTITUTE SHEET (RULE 26)
CA 2872 502 2 020-0 3-0 6
0 WO 2013/166464
PCT/US2013/039580
410
2. Methods for Implementation and Deployment of DIDO systems
100731 The following describes different embodiments of practical deployment
of
DIDO systems.
a. Downlink channel
100741 The general algorithm used in one embodiment to enable DIDO
communications over wireless links is described as follows.
= CSI Computation: All DIDO clients compute the CSI from all DIDO
distributed antenna transmitters based on training sequences received from
DIDO distributed antennas as shown in Figure 4 . The CSI is fed back
wirelessly
from DIDO clients to DIDO distributed antennas 6113 via TDMA or MIMO
techniques as described in the related applications and in Figure 5, and then
the
DIDO distributed antennas 6113 send the CSI via the DIDO BSN 6111 to the
DIDO BTS 6112.
= Precodinq Computation: the DIDO BTS 6112 computes the precoding
weights from the CSI feedback from the entire DIDO cell. Precoded data are
sent
from the DIDO BTS 6112 to the DIDO distributed antennas in Figure 6 via the
DIDO BSN 6111. One precoded data stream is sent to each of the DIDO
distributed antennas.
= Precoded Data Transmission: the DIDO distributed antennas transmit
precoded data to all clients over the wireless links.
= Demodulation: the DIDO clients demodulate the precoded data streams.
100751 In DIDO systems, the feedback loop in Figures 19-20 consists of:
transmission of the training sequence for channel estimation from DIDO
Filed Via EFS-Web
6181P515X
170
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
410
distributed antennas to clients; CSI estimation by clients; CSI feedback from
clients via the DIDO distributed antennas through the DIDO BSN 6111 to the
DIDO BTS 6112; precoded data transmission from DIDO BTS 6112 through the
DIDO BSN 6111 to DIDO distributed antennas to clients. To guarantee the CSI is
up-to-date for successful DIDO precoding and data demodulation at the client
side, the delay over the feedback loop should be lower than the channel
coherence time. The feedback loop delay depends on the BTS computational
resources relative to the computational complexity of the DIDO precoding as
well
as latency over the BSN. Processing at each client and DIDO distributed
antenna
is typically very limited (i.e., on the order of a microsecond or less with a
single
DSP or CPU), depending on the hardware and processor speed. Most of the
feedback loop delay is due the latency for transmission of precoded data from
the DIDO BTS 6112 to the DIDO distributed antennas 6113 over the DIDO BSN
6111 (e.g., on the order of milliseconds).
100761 As discussed above, a low latency or high latency BSN can be used in
DIDO systems depending on the available network. In one embodiment, the
DIDO BTS 6112 switches among two or more types of BSN network
infrastructure based on the each users' channel coherence time. For example,
outdoor clients are typically characterized by more severe Doppler effects due
to
the potential of fast mobility of clients or objects within the channel (i.e.,
resulting
in low channel coherence time). Indoor clients have generally fixed wireless
or
low mobility links (e.g., high channel coherence time). In one embodiment,
DIDO
distributed antennas connected to low latency BSN network infrastructure
(e.g.,
Filed Via EFS-Web
6181P515X
171
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
0
dedicated fiber rings) are assigned to outdoor clients, whereas DIDO
distributed
antennas connected to high latency BSN network infrastructure (e.g., consumer
Internet connections such as DSL or cable modems) are assigned to serve
indoor clients. To avoid interference among transmissions to the different
types
of clients, indoor and outdoor clients can be multiplexed via TDMA, FDMA or
CDMA schemes.
100771 Moreover, DIDO distributed antennas connected to low latency BSNs can
also be used for delay-sensitive algorithms such as those used for client time
and
frequency synchronization.
100781 We observe that DIDO provides an inherently secure network when more
than one DIDO distributed antenna is used to reach a user. In fact, the
precoded
streams from the BTS to the DIDO distributed antennas consist of linear
combinations of data (for different clients) and DIDO precoding weights. Then,
the data stream sent from the BTS to the BSN generally cannot be demodulated
at the DIDO distributed antenna, since the DIDO distributed antenna is unaware
of the precoding weights used by the BTS. Also, the precoding weights change
over time as the complex gain of the wireless channels from DIDO distributed
antenna-to-client varies (due to Doppler effects), adding an additional level
of
security. Moreover, the data stream intended to each client can be demodulated
only at the client's location, where the precoded signals from all transmit
DIDO
distributed antennas recombine to provide user interference-free data. At any
other location, demodulation of data intended to one particular user is not
possible due to high levels of inter-user interference.
Filed Via EFS-Web
6181P515X
172
SUBSTITUTE SHEET (RULE 26)
CA 2872502 2020-03-06
=
WO 2013/166464 PCT/US2013/039580
0
b. Uplink channel
[0079] In the uplink (UL) channel, the clients send data (e.g., to request Web
content to the DIDO BTS 6112 from the Internet), CSI and control information
(e.g., time/frequency synchronization, channel quality information, modulation
scheme, etc.). In one embodiment, there are two alternatives for the UL
channel
that may be used separately or in combination: i) clients communicate directly
to
the DIDO BTS 6112 via TDMA, FDMA or CDMA schemes; ii) clients
communicate to multiple DIDO distributed antennas by creating spatial channels
via MIMO techniques as in Figure 7 (in the MIMO case, however, transmission
time synchronization among clients is required).
c. Time and frequency synchronization
100801 In one embodiment, the DIDO distributed antennas are synchronized in
time and frequency. If RE-over-fiber is employed as in Figure 64, all radio
transceivers at the BTS are locked to the same reference clock 6442, thereby
guaranteeing perfect time and frequency synchronization. Assuming negligible
jitter over the DIDO BSN 6111, artificial delays can be added to the transmit
RF
waveforms at the DIDO BTS 6112 side to compensate for propagation delays
over the DIDO BSN 6111 to different DIDO distributed antennas.
[0081] If the DIDO BSN 6111 is used to carry baseband waveforms as in Figure
63, time and frequency synchronization is required for the radio transceivers
at
Filed Via EFS-Web
6181P515X
173
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
different DIDO distributed antennas. There are various methods to achieve this
synchronization, and more than one method can be used at once.
i. Time and frequency synchronization via GPSDO
100821 In one embodiment time/frequency synchronization is achieved by
connecting the transmitter in radio transceiver 6330 to a GPS Disciplined
Oscillators (GPSDO). A crystal clock with high frequency stability and low
jitter
(e.g., Oven-Controlled Crystal Oscillator, OCXO) is used in one embodiment.
ii. Time and frequency synchronization via power line reference
100831 An alternate embodiment utilizes the 60Hz (in the United States, 50Hz
in
other regions) signal available over power lines as a common clock reference
for
all transmitters. Based on empirical measurements, the jitter of the 60Hz
reference signal (after low pass filtering) can be on the order of 100
nanoseconds. It would be necessary, however, to compensate for deterministic
offsets due to variable propagation path length along the power lines at
different
locations.
iii. Time and frequency synchronization with free-running clocks
[0084] An alternative embodiment is used to compensate the time and frequency
offsets across different DIDO distributed antennas whose clocks are not
synchronized to an external clock reference, but rather are free-running as
described in the related U.S. Patent No. 7,599,420 and in Figures 45, 46 and
47.
Filed Via EFS-Web
6181P515X
174
SUBSTITUTE SHEET (RULE 26)
CA 2872502 2020-03-06
0 WO 2013/166464
PCT/US2013/039580
0
= Coarse Time Synchronization: In one embodiment, all DIDO distributed
antennas have free-running clocks as illustrated in Figure 46 that can
generate a
periodic reference signal (one pulse per second (PPS) in one embodiment). The
DIDO BTS 6112 sends an initial trigger signal to all DIDO distributed antennas
via the DIDO BSN 6111 to trigger their transmission at the next PPS. The
roundtrip time (RU) over the BSN is assumed to be of the order of particular
time interval (10msec in one embodiment, or ¨5ms in each direction), so all
DIDO distributed antennas will start transmitting with a relative time offset
of at
most 1sec+5msec. Each DIDO distributed antenna sends one training signal
(i.e., Zadoff-Chu sequence or methods for GPS systems in [6]) to all users for
initial time offset estimation. Alternatively, only a subset of users (those
with
highest SNR) can be selected to reduce the complexity of the algorithm.
Training
signals from different DIDO distributed antennas are orthogonal or sent via
TDMA/FDMA to avoid interference. The users estimate the relative time of
arrival
from every transmitter by correlating the receive signal with the known
training
sequence. The same training sequence can be sent periodically and the
correlation can be averaged over a long period of time (e.g., on the order of
minutes in one embodiment) to average-out multipath effects, particularly in
the
case of mobile users. In one embodiment of the invention, time-reversal
techniques [31] can be applied to pre-compensate for multipath effects at the
transmitter and obtain precise time of arrival estimates. Then, the users
compute
the delays (i.e., deterministic time offsets) of each transmitter relative to
a given
Filed Via EFS-Web
6181P515X
175
SUBSTITUTE SHEET (RULE 26)
CA 2872502 2020-03-06
0 WO 2013/166464
PCT/US2013/039500
=
time reference (e.g., one of the DIDO distributed antennas can be chosen as an
absolute time reference). The relative time offset is fed back from the
clients to
the DIDO distributed antennas or directly to the DIDO BTS 6112. Then, each
DIDO antenna averages the time offset information obtained from all the users
and adjusts its PPS (and clock reference) according to that.
[0085] In one embodiment, the time offset is computed from measurements by
many users to average out the difference in propagation delay across users.
For
example, Figure 65 shows one case with two DIDO distributed antennas 6551
and 6552 perfectly synchronized (e.g., via GPSDO) and two users 6553 and
6554 with Line Of Sight (LOS) channels. We use TX1 6551 as the absolute time
reference. Since we assume the transmitters are perfectly synchronized, the
average time offset between users should be zero. However, if we average the
offset information only across two users, as in Figure 65, the average offset
of
TX2 6552 relative to TX1 6551 would be (7+(-2))/2 = 2.5usec. By relying on the
Monte Carlo method, we can average out this effect as the number of users
increases. It is possible to simulate the bias of this algorithm depending on
the
TX/RX distribution and channel delay spread.
= Fine Time Synchronization: Once the coarse time offset is removed, DIDO
distributed antennas can keep running the algorithm periodically to improve
the
offset estimates. Moreover, the DIDO transmit stations are typically at fixed
locations (e.g. transceiver DIDO distributed antennas connected to the DIDO
BSN 6111). Hence the algorithm should converge after a period of time. The
Filed Via EFS-Web
6181P515X
176
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
0
same algorithm is rerun every time one DIDO distributed antenna changes its
location or a new DIDO distributed antenna is added to the DIDO BSN 6111.
= Frequency Offset Compensation: once the 1 PPS reference signals at all
DIDO distributed antennas are synchronized, the DIDO distributed antennas
send training to one or multiple users to estimate the relative frequency
offset
between stations. Then, the frequency offset compensation method described in
the related U.S. Patent No. 7,599,420 and Figure 47 is applied to transmit
precoded data to all users while compensating for the offset. Note that for
the
best performance of this algorithm, two conditions need to be satisfied: i)
good
SNR between all DIDO transmitters and the user (or users) responsible for
frequency offset estimation; ii) good clock stability: if the OCX05 at the
DIDO
distributed antennas are stable, the frequency offset estimation can be
carried
out only occasionally, thereby reducing the feedback information.
d. Control channel via the BSN
100861 In one embodiment, the DIDO BSN 6111 is used for at least the following
three purposes:
= CSI Feedback: The DIDO clients feedback the CSI wirelessly to the DIDO
distributed antennas. If TDMA, FDMA or CDMA schemes are used for feedback,
only one DIDO distributed antenna (the one with best SNR to all users) is
selected to receive the CSI. If MIMO techniques are employed, all DIDO
distributed antennas are used simultaneously to demodulate the CSI from all
clients. Then the CSI is fed back from the DIDO distributed antennas to the
DIDO
BTS 6112 via the DIDO BSN 6111. Alternatively, the CSI can be fed back
Filed Via EFS-Web
6181P515X
177
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
wirelessly directly from the clients (or the DIDO distributed antennas) to a
DIDO
BTS 6112 equipped with one antenna via TDMA or CDMA schemes. This
second solution has the advantage of avoiding latency caused by the DIDO BSN
6111, but may not be achievable if the wireless link between each of the
clients
(or the DIDO distributed antennas) and the DIDO BTS 6112 is not of high enough
SNR and reliability. To reduce the throughput requirement over the UL channel,
the CSI may be quantized or any number of limited feedback algorithms known in
the art can be applied [28-30].
= Control Information: The DIDO BTS 6112 sends control information to the
DIDO distributed antennas via the DIDO BSN 6111. Examples of control
information are: transmit power for different DIDO distributed antennas (to
enable
power control algorithms); active DIDO distributed antenna IDs (to enable
antenna selection algorithms); trigger signals for time synchronization and
frequency offset values.
= Precoded data: the DIDO BTS 6112 sends precoded data to all DIDO
distributed antennas via the DIDO BSN 6111. That precoded data is then sent
from the DIDO distributed antennas synchronously to all clients over wireless
links.
Case study 1: DIDO in UHF spectrum
a. UHF and microwave spectrum allocation
[0087] Different frequency bands are available in the United States as
possible
candidates for DIDO system deployment: (i) the unused television frequency
Filed Via EFS-Web
6181P515X
178
SUBSTITUTE SHEET (RULE 26)
CA 2872502 2020-03-06
=
WO 2013/166464 PCMJS2013/039580
0
band between 54-698MHz (TV Channels 2-51 with 6MHz channel bandwidth),
recommended by the White Spaces Coalition to deliver high speed Internet
services; (ii) the 734-746MHz and 746-756MHz planned to be used for future
developments of LTE systems by AT&T and Verizon, respectively; (iii) the
2.5GHz band for broadband radio service (BRS), consisting of 67.5MHz of
spectrum split in five channels for future deployment of WiMAX systems.
b. Propagation channel in UHF spectrum
100881 We begin by computing the path loss of DIDO systems in urban
environments at different frequencies allocated for White Spaces. We use the
Hata-Okumura model described in [7], with transmit and receive antenna heights
of 1.5 meter (e.g., indoor installation of the DIDO distributed antennas) and
100W
transmit power. To determine the range, we use -90dBm target receive
sensitivity
of typical wireless devices. Figure 66 shows the path loss at 85MHz and
400MHz. In one embodiment, the expected range for DIDO systems is between
1Km and 3Km depending on the frequency.
[0089] Some prior art multi-user systems proposed for White Spaces have
similar
interference avoidance protocols as WiFi, although at UHF frequencies. We
compare DIDO UHF results against the path loss for WiFi systems with 250mW
transmit power. The range for WiFi extends only between 60 meters (indoor) and
200 meters (outdoor). Wider range achievable by DIDO systems is due to larger
transmit power and lower carrier frequency (subject to generally lower
attenuation from obstacles at UHF frequencies). But, we observe that WiFi
Filed Via EFS-Web
6181P515X
179
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
0 WO 2013/166464
PCT/US2013/039580
=
systems were deliberately limited in power because large transmit power would
create harmful interference to other users using WiFi systems (or other users
in
the 2.4GHz ISM spectrum) because only one interfering access point can be
transmitting at once, and by extending the range, increasingly more WiFi
access
points would interfere with one another. Contrarily, in DIDO systems inter-
user
interference is suppressed by multiple DIDO distributed antennas transmitting
precoded data to the clients.
[0090] Next, we summarize the parameters that characterize time, frequency and
space selectivity in UHF channels.
[0091] Time selectivity is caused by relative motion of transmitter and
receiver
that yields shift in the frequency domain of the received waveform, known as
the
Doppler effect. We model the Doppler spectrum according to the well known
Jakes' model for rich scattering environments (e.g., urban areas), and compute
the channel coherence time from the maximum Doppler shift according to [14].
As a rule of thumb, the channel complex gain can be considered constant over a
period of time corresponding to one tenth of the channel coherence time
( A t = Tau)). Figure 67 shows the period A t as a function of the relative
velocity
between transmitter and receiver for different frequencies in the UHF band.
100921 In DIDO systems, Lt provides the constraint to the maximum delay that
can be tolerated between estimation of the channel state information (CSI) and
data transmission via DIDO precoding. For example, if the constraint is A t =
nmsec, the maximum speed that can be tolerated by DIDO systems is 4mph at
700MHz, 7mph at 400MHz, and 57mph at 50MHz. If a low latency network is
Filed Via EFS-Web
6181P515X
180
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
wo 2013/166464 PCT/US2013/039580
=
used for the BSN and the DIDO BTS 6112 is in the vicinity of the DIDO
distributed antennas (so as to minimize network transit delay), far less than
10msec RU can be achieved A t. For example, if A t = imsec, at 400MHz,
DIDO can tolerate approximately highway speeds of 70Mph.
100931 Frequency selectivity depends on the channel delay spread. Typical
values of delay spread for indoor environments are below 300 nsec [8-10]. In
urban and suburban areas the delay spread ranges between 1 and 10 usec
[11,12]. In rural environments it is typically on the order of 10 to 30 usec
[11-13].
[0094] Space selectivity depends on the channel angular spread and antenna
spacing at transmit/receive side. In urban environments, the channel angular
spread is typically large due to rich scattering effects. In rich scattering
environments, it was shown that the minimum antenna spacing (either at
transmitter or receiver sides) to guarantee good spatial selectivity is about
one
wavelength [15,16] .
[0095] In Figure 68 we summarize the main propagation effects in DIDO systems
for three different carrier frequencies. We observe that lower frequencies
provide
better range and robustness to mobile speed at the expense of larger antenna
size and distance between transceivers. A good tradeoff is offered by the 400
MHz band. This band can support pedestrian speed at a ¨10msec limitation to
transmit control information from the centralized processor to the DIDO
distributed antennas over the Internet, and it can support highway speeds with
a
¨1msec limitation.
Filed Via EFS-Web
6181P515X
181
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
=
c. Practical implementation of DIDO systems in UHF spectrum
[0096] Based on the channel parameters and systems constraints described
above, we provide one embodiment of DIDO system design in UHF spectrum as
follows:
= Bandwidth: 5 to 10MHz, depending on UHF spectrum availability.
= Carrier frequency: 400MHz for best tradeoff between range/Doppler and
antenna size/spacing.
= Modulation: orthogonal frequency division multiplexing (OFDM) is used to
reduce receiver complexity and exploit channel frequency diversity (via
interleaving) as in Figure 11. The cyclic prefix is 10usec, based upon the
maximum delay spread expected in UHF channels, corresponding to 50 channel
taps at 5MHz bandwidth. The OFDM waveform can be designed with 1024
tones, corresponding to ¨5% loss in spectral efficiency. The total OFDM symbol
length (including cyclic prefix and data) is 215usec.
= Packet Size: is limited by the latency over the DIDO BSN 6111 and
Doppler effects. For example, the nominal RTT of one embodiment is 10msec.
Then, the time required to send precoded data from the DIDO BST 6112 to the
DIDO distributed antennas is ¨5msec (half RTT). Assuming maximum users'
speed of 7mph at 400MHz as in Figure 68, the channel gain can be considered
constant for approximately 10msec. Hence, we use the remaining 5msec to send
data and define the packet size as (5e-3/215e-6);t23 OFDM symbols. Note that
higher users' speeds yield a larger Doppler effect resulting in a lower number
of
Filed Via EFS-Web
6181P515X
182
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
0 WO 2013/166464
PCT/US2013/039580
=
OFDM symbols sent per packet, unless the latency over the DIDO BSN 6111 can
be reduced.
= CSI Estimation and Precoding: With the system parameters above,
training for CSI estimation is sent every 5msec. The users estimate/feedback
the
CSI and ¨5msec later they receive 5msec of precoded data to demodulate.
= DIDO Distributed Antenna Placement Within the Coverage Area: Although
DIDO distributed antennas can be placed on existing cell towers, as a
practical
matter, given limited real estate available at existing cell towers, there may
be a
limited number of antenna locations available. For example, if a maximum of
four
antennas were placed on each tower this might yield up to 3x increase in data
rate as shown in [4] (due to lack of spatial diversity). In this
configuration, latency
across DIDO transmitters is negligible, since they are all placed on the same
tower, but without additional spatial diversity, the gain in spectral
utilization will be
limited. In one embodiment, the DIDO distributed antennas are placed in random
locations throughout the coverage area all connected to the DIDO BSN 6111.
Unlike a the coverage area of given cell in a prior art cellular system, which
is
based on transmission range from the cell tower, the coverage area of a DIDO
cell is based instead on the transmission range of each DIDO distributed
antenna, which in accordance with the path loss model in one embodiment is
approximately 1Km. Thus, a user within 1Km of at least one DIDO distributed
antenna will receive service, and a user within range of several DIDO
distributed
antennas will get non-interfering service from the DIDO distributed antennas
within range.
Filed Via EFS-Web
6181P515X
183
SUBSTITUTE SHEET (RULE 26)
CA 2872502 2020-03-06
0 WO 2013/166464
PCT/US2013/039580
=
Case study 2: DIDO in NVIS links
[0097] Another application of DIDO technology is in the HF band. The key
advantage of HF systems is extended coverage in the 1-30MHz frequency band
due to reflection off of the ionosphere. One example of propagation via the
ionosphere is near-vertical incident skywave (NVIS) where signals sent towards
the sky with high elevation angles from the horizon bounce off the ionosphere
and return back to Earth. NVIS offers unprecedented coverage over conventional
terrestrial wireless systems: NVIS links extend between 20 and 300 miles,
whereas typical range of terrestrial systems is between 1 and 5 miles.
100981 Hereafter, we present the characteristics of NVIS links based on
results
obtained from the literature and our experimental data. Then we present a
practical implementation of DIDO systems in NVIS links that were described in
the related U.S. Patent No. 7,418,053, U.S. Patent No. 7,599,420, U.S.
Application No. 11/894,362, U.S. Application No. 11/894,394 U.S. Application
No. 11/143,503 and U.S. Application No. 11/894,540 and in Figure 10.
a. HF spectrum allocation
[0099] The HF band is divided into several subbands dedicated to different
types
of services. For example, the Maritime band is defined between 4MHz and
4.438MHz. According to the Federal Communications Commission (FCC)
licensing database (i.e., universal licensing systems, "ULS"), there are 1,070
licenses authorized to operate in this Maritime band. There are 146 channels
of 3
Filed Via EFS-Web
6181 P515X
184
CA 2872502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
0 WO 2013/166464
PCT/US2013/039580
110
KHz bandwidth each, covering 0.438MHz bandwidth. Most of the transceiver
stations operating in the Maritime band are located along the coast of the US
territory as depicted in Figure 69. Hence, DIDO-NVIS distributed antennas
operating inland (far away from the coast) would not cause harmful
interference
to those Maritime stations or vessels at sea. Moreover, along the coast,
cognitive
radio techniques can be applied to detect channels in use and avoid
transmission
over DIDO-NVIS links in those channels. For example, if the DIDO-NVIS system
is designed to transmit broadband OFDM waveforms (-1MHz bandwidth), the
OFDM tones corresponding to active channels in the Maritime band can be
suppressed to avoid interference.
[001001
Other portions of the HF spectrum are occupied by the Aeronautical
band within [3,3.155] MHz and [3.4,3.5] MHz, and the Amateur radio bands
defined in the ranges [1.8,2] MHz, [3.5,4] MHz, [5.3305,5.4035] MHz, [7,7.3]
MHz, [10.10,10.15] MHz, [14,14.35] MHz, [18.068,18.168] MHz, [21,21.450]
MHz, [24.89,24.99] MHz, [28,29.7] MHz. Our experimental measurements have
shown that the Amateur radio band is mostly unutilized, particularly during
daytime, allowing DIDO-NVIS links without causing harmful interference.
Moreover, similarly to the Maritime band, coexistence of DIDO-NVIS systems
with Amateur radio transceivers may be enabled by cognitive radio techniques.
Filed Via EFS-Web
6181P515X
185
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
0
b. NVIS propagation channel
[00101] We provide an overview of radio wave propagation
through the
ionosphere. Then we describe path loss, noise and time/frequency/space
selectivity in typical NVIS channels.
[00102] The ionosphere consists of ionized gas or plasma.
The plasma
behaves as an electromagnetic shield for radio waves propagating from Earth
upwards that are refracted and reflected back to Earth as in Figure 10. The
stronger the level of ionization, the higher the critical frequency of the
plasma and
number of reflections in the ionosphere, resulting in improved signal quality
over
NVIS links. The ionization level depends on the intensity of solar radiations
that
strike the ionosphere producing plasma. One empirical measure of the solar
activity is the sunspot number (SSN) that varies on 11-year cycles as shown in
Figure TO. Hence, the performance of DIDO-NVIS systems is expected to vary
throughout every 11-year cycle, yielding highest SNR and largest number of
usable HF bands at the peak of the cycle.
1001031 Due to the absence of obstacles in NVIS links, the
propagation loss
is mostly due to free space path loss (i.e., Friis formula), without
additional
attenuation factors as in standard terrestrial wireless systems. Depending on
the
time of the day and incident angle to the ionosphere, propagating waveforms
may suffer from additional 10-25dB loss due to attenuation from the D layer
(i.e.,
lowest layer of the ionosphere). Figure 71 compares the path loss in NVIS
links
against next generation wireless systems such as WiMAX and 3GPP long term
evolution (LTE) in macrocells with 43dBm transmit power. For WiMAX and LTE
Filed Via EFS-Web
6181P515X
186
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
.
we used 2.5GHz and 700MHz carrier frequencies, respectively. NVIS links yield
better signal quality (i.e., wider coverage) than standard systems for
distances
greater than -1 mile.
1001041 Any wireless system is affected by thermal noise
produced
internally to radio receivers. In contrast to standard wireless systems, HF
links
are severely affected by other external noise sources such as: atmospheric
noise, man-made noise and galactic noise. Man-made noise is due to
environmental sources such as power lines, machinery, ignition systems, and is
the main source of noise in the HF band. Its typical values range between -133
and -110 dBm/Hz depending on the environment (i.e., remote versus industrial).
1001051 From our Doppler measurements, we observed typical
channel
coherence time in NVIS links is of the order of seconds, That is about 100
times
larger than the At = 10msec constraint on the DIDO feedback loop over the
DIDO BSN 6111. Hence, in DIDO-NVIS systems a long feedback delay over the
DIDO BSN 6111 can be tolerated due to extremely high channel coherence time.
Note that our measurements assumed fixed wireless links. In case of mobile
stations, the channel coherence time is expected to be of the order of 2sec in
a
very high speed scenario (i.e., vehicle or airplane moving at 200mph) that is
still
orders of magnitude higher than the latency over the DIDO BSN 6111.
1001061 Typical values of delay spreads in NVIS channels are
around 2ms
corresponding, corresponding to the roundtrip propagation delay Earth-
ionosphere (about 300Km high). That value may be larger (-5msec) in presence
of multilayer refractions in the ionosphere.
Filed Via EFS-Web
6181P515X
187
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
[00107] The angular spread in NVIS links is typically very
small (less than 1
degree, based on our measurements and simulations). Hence, large antenna
spacing is required to obtain spatially selective channels and exploit spatial
diversity via DIDO techniques. Strangeways' simulator points to around twenty
wavelengths required for a long distance HF skywave link [34,35]. Some
experimental results for HF skywave with a spacing of around 0.7 wavelengths
indicated high correlation [36,37]. Similar results were obtained from our
measurements in NVIS links.
c. DIDO-NVIS experimental results
[00108] We measured the performance of DIDO-NVIS systems
with a
practical testbed consisting of three DIDO distributed antennas 6113 for
transmission and three DIDO clients 6110 for reception . The transmitters are
located in the area of Austin, Texas, as depicted in Figure 72: TX1 in central
Austin, TX2 in Pflugerville, TX3 in Lake Austin. All three receivers are
installed
with antenna spacing of about 10 wavelengths as in Figure 73. All six transmit
and receive antennas have the same orientation with respect to the direction
of
the North, since our goal was to evaluate DIDO-NVIS performance when only
space diversity is available, without polarization diversity.
[00109] The three transmitting distributed antennas are
locked to the same
GPSDO that provide time and frequency reference. The three receiving DIDO
clients have free-running clocks and synchronization algorithms are
implemented
Filed Via EFS-Web
6181P515X
188
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
0 WO 2013/166464
PCT/US2013/039580
=
to compensate for time/frequency offsets. The carrier frequency is 3.9MHz,
bandwidth is 3.125KHz and we use OFDM modulation with 4-QAM.
[00110] Typical 4-QAM constellations demodulated at the
three DIDO client
locations are depicted in Figure 74. Our DIDO-NVIS 3x3 testbed creates three
simultaneous spatial channels over NVIS links by pre-cancelling inter-user
interference at the transmit side and enabling successful demodulation at the
users' side.
[00111] We compute the symbol error rate (SER) performance
as a function
of the per-user SNR (PU-SNR) over about 1000 channel realizations as in
Figure 75. The dots are individual measurements for all three DIDO clients
6112
and the solid lines are the average per-user SER (PU-SER). The average SER
across all three DIDO clients 6112 is denoted as A-SER. About 40dB receive
SNR is require to successfully demodulate 4-QAM constellations in DIDO-NIVS
3x3 links with A-SER<1%. In fact, the transmit/receive antenna configuration
in
our experiments yields very low spatial diversity (due to relatively close
proximity
of the receive antennas, given the wavelength, and transmitters being all
located
on one side of the recevers rather than around the users). In more favorable
conditions (i.e., transmitters placed around the users in circle and at larger
distance as in Figure 61) much lower SNR (-20dB) is required to demodulate
QAM constellations with DIDO-NVIS, as derived via simulations in realistic
NVIS
propagation channels.
Filed Via EFS-Web
6181P515X
189
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
W. 2013/166464 PCT/US2013/039580
=
d. Practical implementation of DIDO systems in NVIS links
[00112]
Similarly to the case study 1, we provide one embodiment of DIDO-
NVIS system design as follows:
= Bandwidth: 1-3 MHz, depending on HF spectrum availability. Larger
bandwidths are less practical, since they require more challenging broadband
antenna designs. For example, 3MHz bandwidth at 4MHz carrier frequency
corresponds to fractional antenna bandwidth of 75%.
= Carrier Frequency: The HF frequencies corresponding to the
plasma critical frequency of the ionosphere are between 1 and 10 MHz. Radio
waves at lower frequencies (-1MHz) are typically reflected by the ionosphere
at
nighttime, whereas higher frequencies (-10MHz) at daytime. The frequency of
optimal transmission (FOT) at given time of the day varies with the SSN. In
practical DIDO-NVIS systems, the carrier frequency can be adjusted throughout
the day depending on the FOT provided by the ionospheric maps.
= Transmit Power: Based on the path loss results in Figure 71, the
average transmit power requirement for 1MHz bandwidth with receivers in
remote areas (i.e., man-made noise level of -133dBm/Hz) is between 10dBm and
30dBm, depending on QAM modulation and forward error correction (FEC)
coding schemes. In industrial areas (i.e., man-made noise level of -110dBm/Hz)
those levels increase of about 23dB up to 33-53dBm, depending on QAM
modulation and FEC coding schemes.
= Modulation: We assume OFDM modulation as in Figure 11. The
cyclic prefix is 2msec (based upon typical delay spread expected in NVIS
links)
Filed Via EFS-Web
6181P515X
190
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 20131166464 PCT/US2013/039580
corresponding to 2000 channel taps at 1MHz bandwidth. The OFDM waveform
can be designed with 214 tones, corresponding to ¨10% loss in spectral
efficiency
due to cyclic prefix. The total OFDM symbol duration (including cyclic prefix
and
data) at 1MHz bandwidth is 18.4msec.
= Packet Size: is limited by the minimum channel coherence time
expected in NVIS links. The minimum coherence time is approximately 1 sec and
the channel gain can be considered constant over one tenth of that duration
(-100msec) in the worst case scenario. Then, the packet size is about five
OFDM symbols. The packet size can be dynamically adjusted as the coherence
time varies over time.
= CSI Estimation and Precoding: With the system parameters above,
training for CSI estimation is sent every ¨100msec (or higher, when the
coherence time increases). The users estimate/feedback the CSI and ¨5msec
later (i.e., latency over the BSN feedback loop) they receive 100msec of
precoded data to demodulate.
= DIDO Distributed Antenna Placement Within the Coverage Area:
One practical solution to implement DIDO-NVIS systems is to place multiple
DIDO distributed antennas along the circumference of a circular region of
radius
¨100 miles as in Figure 61. These stations are connected to each other via a
BSN that carries control information. At the speed of light through optical
fiber,
the propagation latency along the circumference of radius 100 miles is ¨3.4
msec. This delay is much smaller than typical channel coherence time in NVIS
channels and can be tolerated without any significant performance degradation
Filed Via EFS-Web
6181P515X
191
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
wo 2013/166464 PCT/US2013/039580
11,
for the DIDO precoder. Note that if the optical fiber is shared across
different
operators, that delay may be larger (i.e., 10-30msec) due to the packet
switched
nature of the Internet. Multiple DIDO-NVIS cells as in Figure 76 can be
distributed to provide full coverage over the USA. For example, Figure 76
shows
that 109 DIDO cells of radius 125 miles are required to cover the entire
territory
of the 48 contiguous states in the USA.
References
1001131 The following references are referred to in the
above detailed
description, as indicated by the numbered brackets:
[1] 3GPP, "Multiple Input Multiple Output in UTRA", 3GPP TR 25.876 V7Ø0,
Mar. 2007
[2] 3GPP, "Base Physical channels and modulation", IS 36.211, V8.7.0, May
2009
[3] 3GPP, "Multiplexing and channel coding", TS 36.212, V8.7.0, May 2009
[4] ArrayComm, "Field-proven results",
http://www.arravcomm.com/serve.php?page=proof
[6] http://www.iackson-labs.com/docs/HP GPS Apps.pdf
[7] Oda, Y.; Tsuchihashi, R.; Tsunekawa, K.; Hata, M., "Measured path loss and
multipath propagation characteristics in UHF and microwave frequency bands for
urban mobile communications", Vehicular Technology Conference, Vol. 1,
pp.337-341, 2001
Filed Via EFS-Web
6181P515X
192
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
wo 2013/166464 PCT/US2013/039580
[8] Devasirvatham, D.M.J.; Krain, M.J.; Rappaport, D.A.; Banerjee, C., "Radio
propagation measurements at 850 MHz, 1.7 GHz and 4 GHz inside two
dissimilar office buildings", IEEE Electronics Letters, Vol. 26, n 7, pp.445 -
447 March 1990
[9] Devasirvatham, D., "Time delay spread and signal level measurements of 850
MHz radio waves in building environments", IEEE Trans. on Ant. and Prop., Vol.
34, n. 11, pp.1300 ¨ 1305, Nov 1986
[10] Devasirvatham, D.M.J.; Murray, R.R.; Banerjee, C., "Time delay spread
measurements at 850 MHz and 1.7 GHz inside a metropolitan office building",
IEEE Electronics Letters, Vol. 25, n 3, pp.194-196, Feb. 1989
[11] Garcia, C.R.; Lehner, A.; Strang, T.; Frank, K., "Channel Model for Train
to
Train Communication Using the 400 MHz Band", in Proc. of IEEE Vehicular
Technology Conference, pp.3082-3086, May 2008
[12] John Proakis, "Digital Communications", McGraw Hill, 4th Edition, 2001.
[13] Zogg, A., "Multipath delay spread in a hilly region at 210 MHz", IEEE
Transactions on Vehicular Technology, Vol. 36, n 4, Page(s): 184 ¨ 187, Nov
1987
[14] T.S. Rappaport, Wireless Communications, Prentice Hall, 2002
[15] A. Forenza and R. W. Heath, Jr., "Impact of Antenna Geometry on MIMO
Communication in Indoor Clustered Channels, (invited) Proc. of the IEEE AP-S
Intern. Symp., vol. 2, pp. 1700-1703, June 20-26, 2004.
Filed Via EFS-Web
6181P515X
193
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
11,
[16] M. L. Morris and M. A. Jensen, "Network Model for MIMO Systems With
Coupled Antennas and Noisy Amplifiers", IEEE TRANS. ON ANTENNAS AND
PROPAGATION, VOL. 53, NO. 1, pp. 545-552, Jan. 2005
[17] B.G. Montgomery, "Analog RF-over-fiber technology", Syntonics LLC, Jan.
2008
htto://chesamakebavaoc.oro/documents/Svntonics AOC RE over-
Fiber 19 Jan 08.0clf
[18] J. Daniel, "Introduction to public safety: RF signal distribution using
fiber
optics", 2009, http://www.rfsolutions.com/fiberodf
[19] Syntonics, "FORAX RF-over-fiber communications systems",
htto://www.svntonicscorp.com/oroducts/oroducts-foraxRF.html
[20] G. Caire and S. Shamai, "On the achievable throughput of a multiantenna
Gaussian broadcast channel," IEEE Trans. Info.Th., vol. 49, pp. 1691-1706,
July
2003.
[21] P. Viswanath and D. Tse, "Sum capacity of the vector Gaussian broadcast
channel and uplink-downlink duality," IEEE Trans. Info. Th., vol. 49, pp. 1912-
1921, Aug. 2003.
[22] S. Vishwanath, N. Jindal, and A. Goldsmith, "Duality, achievable rates,
and
sum-rate capacity of Gaussian MIMO broadcast channels," IEEE Trans. Info. Th.,
vol. 49, pp. 2658-2668, Oct. 2003.
[23] W. Yu and J. Cioffi, "Sum capacity of Gaussian vector broadcast
channels,"
IEEE Trans. Info. Th., vol. 50, pp. 1875-1892, Sep. 2004.
Filed Via EFS-Web
6181P515X
194
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
0 WO 2013/166464
PCMS2013/039580
=
[24] M. Costa, "Writing on dirty paper," IEEE Transactions on Information
Theory,
vol. 29, pp. 439-441, May 1983.[25] M. Bengtsson, "A pragmatic approach to
multi-user spatial multiplexing," Proc. of Sensor Array and Multichannel
Sign.Proc. Workshop, pp. 130-134, Aug. 2002.
[26] K.-K. Wong, R. D. Murch, and K. B. Letaief, "Performance enhancement of
multiuser MIMO wireless communication systems," IEEE Trans. Comm., vol. 50,
pp. 1960-1970, Dec. 2002.
[27] M. Sharif and B. Hassibi, "On the capacity of MIMO broadcast channel with
partial side information," IEEE Trans. Info.Th., vol. 51, pp. 506-522, Feb.
2005.
[28] T. Yoo, N. Jindal, and A. Goldsmith, "Multi-antenna broadcast channels
with
limited feedback and user selection," IEEE Journal on Se!. Areas in
Communications, vol. 25, pp. 1478-91, July 2007.
[29] P. Ding, D. J. Love, and M. D. Zoltowski, "On the sum rate of channel
subspace feedback for multi-antenna broadcast channels," in Proc., IEEE
Globecom, vol. 5, pp. 2699-2703, Nov. 2005.
[30] N. Jindal, "MIMO broadcast channels with finite-rate feedback," IEEE
Trans.
on Info. Theory, vol. 52, pp. 5045-60, Nov. 2006.
[31] T. Strohmer, M. Emami, J. Hansen, G. Papanicolaou, A. J. Pau!raj,
"Application of Time-Reversal with MMSE Equalizer to UWB Communications",
Proc. of IEEE Globecom, vol.5, pp.3123-3127, Nov. 2004.
[32] J. Zhang, R. Chen, J. G. Andrews, A. Ghosh, and R. W. Heath, Jr.,
"Coordinated Multi-cell MIMO Systems with Cellular Block Diagonalization,"
Filed Via EFS-Web
6181P515X
195
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
1111 wo 2013/166464
PCT/US2013/039580
Proc. of the IEEE Asilomar Conf. on Signals, Systems, and Computers, pp.
1669-1673, Pacific Grove, CA, Nov. 4-7, 2007
[33] J. Zhang, R. Chen, J. G. Andrews, A. Ghosh, and R. W. Heath, Jr.,
"Networked MIMO with Clustered Linear Precoding," IEEE Trans. on Wireless
vol. 8, no. 4, pp. 1910-1921, April 2009.
[34] H. J. Strangeways, "Determination of the correlation distance for spaced
antennas on multipath HF links and implications for design of SIMO and MIMO
systems,"
www.esaspaceweathernet/spweather/workshops/esww11/proc/Session3/Stranqe
ways HFMIMOposter.pdf
[35] H. J. Strangeways, "Investigation of signal correlation for spaced and co-
located antennas on multipath hf links and implications for the design of SIMO
and MIMO systems", IEEE First European Conf. on Antennas and Propagation
(EuCAP 2006), Vol. , n. 6-10, pp.1-6, Nov. 2006
[36] N. Abbasi, S.D. Gunashekar, E.M. Warrington, S. Salous, S. Feeney, L.
Bertel, D. Lemur and M. Oger, "Capacity estimation of HF-MIMO systems",
International Conference on Ionospheric Systems and Techniques, Apr. 2009
[37] S. Gunashekar, E.M. Warrington, S. Salous, S.M. Feeney, N.M. Abbasi, L.
Bertel, D. Lemur, M. Oger, "Investigations into the Feasibility of MIMO
Techniques within the HF Band: Preliminary Results", Radio Science (Special
Issue), 2009, (In Press)
Filed Via EFS-Web
6181P515X
196
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
4110 WO 2013/166464
PCT/US2013/039580
DISCLOSURE FROM RELATED APPLICATIONS
[00114] Figure 1 shows a prior art MIMO system with
transmit antennas
104 and receive antennas 105. Such a system can achieve up to 3X the
throughput that would normally be achievable in the available channel. There
are a number of different approaches in which to implement the details of such
a
MI MO system which are described in published literature on the subject, and
the
following explanation describes one such approach.
[00115] Before data is transmitted in the MIMO system of
Figure 1, the
channel is "characterized." This is accomplished by initially transmitting a
"training signal" from each of the transmit antennas 104 to each of the
receivers
105. The training signal is generated by the coding and modulation subsystem
102, converted to analog by a D/A converter (not shown), and then converted
from baseband to RF by each transmitter 103, in succession. Each receive
antenna 105 coupled to its RF Receiver 106 receives each training signal and
converts it to baseband. The baseband signal is converted to digital by a D/A
converter (not shown), and the signal processing subsystem 107 characterizes
the training signal. Each signal's characterization may include many factors
including, for example, phase and amplitude relative to a reference internal
to the
receiver, an absolute reference, a relative reference, characteristic noise,
or
other factors. Each signal's characterization is typically defined as a vector
that
characterizes phase and amplitude changes of several aspects of the signal
when it is transmitted across the channel. For example, in a quadrature
amplitude modulation ("QAM")-modulated signal the characterization might be a
Filed Via EFS-Web
6181P515X
197
CA 2 8 7 250 2 2 02 0-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
=
vector of the phase and amplitude offsets of several multipath images of the
signal. As another example, in an orthogonal frequency division multiplexing
("OFDM")-modulated signal, it might be a vector of the phase and amplitude
offsets of several or all of the individual sub-signals in the OFDM spectrum.
[00116] The signal processing subsystem 107 stores the
channel
characterization received by each receiving antenna 105 and corresponding
receiver 106. After all three transmit antennas 104 have completed their
training
signal transmissions, then the signal processing subsystem 107 will have
stored
three channel characterizations for each of three receiving antennas 105,
resulting in a 3x3 matrix 108, designated as the channel characterization
matrix,
"H." Each individual matrix element H,,i is the channel characterization
(which is
typically a vector, as described above) of the training signal transmission of
transmit antenna 104i as received by the receive antenna 105j.
[00117] At this point, the signal processing subsystem 107
inverts the
matrix H 108, to produce H-1, and awaits transmission of actual data from
transmit antennas 104. Note that various prior art MIMO techniques described
in
available literature, can be utilized to ensure that the H matrix 108 can be
inverted.
[00118] In operation, a payload of data to be transmitted
is presented to
the data Input subsystem 100. It is then divided up into three parts by
splitter
101 prior to being presented to coding and modulation subsystem 102. For
example, if the payload is the ASCII bits for "abcdef," it might be divided up
into
Filed Via EFS-Web
6181P515X
198
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
=
three sub-payloads of ASCII bits for "ad," "be," and "cf" by Splitter 101.
Then,
each of these sub-payloads is presented individually to the coding and
modulation
subsystem 102.
[00119] Each of the sub-payloads is individually coded by
using a coding
system suitable for both statistical independence of each signal and error
correction capability. These include, but are not limited to Reed-Solomon
coding,
Viterbi coding, and Turbo Codes. Finally, each of the three coded sub-payloads
is modulated using an appropriate modulation scheme for the channel.
Examples of modulation schemes are differential phase shift key ("DPSK")
modulation, 64-QAM modulation and OFDM. It should be noted here that the
diversity gains provided by M IMO allow for higher-order modulation
constellations that would otherwise be feasible in a SISO (Single Input-Single
Output) system utilizing the same channel. Each coded and modulated signal is
then transmitted through its own antenna 104 following D/A conversion by a D/A
conversion unit (not shown) and RF generation by each transmitter 103.
1001201 Assuming that adequate spatial diversity exists
amongst the
transmit and receive antennas, each of the receiving antennas 105 will receive
a
different combination of the three transmitted signals from antennas 104. Each
signal is received and converted down to baseband by each RF receiver 106,
and digitized by an AID converter (not shown). If yn is the signal received by
the
Filed Via EFS-Web
6181P515X
199
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
nth receive antenna 105, and xr, is the signal transmitted by nth transmit
antenna
104, and N is noise, this can be described by the following three equations:
=x1 H11 + X2 H12 + X3 H13 + N
Y2 = X1 H21 + X2 H22 + X3 H23 + N
y3 = Xi H31+ X2 H32 + X3 H33 + N
[00121] Given that this is a system of three equations
with three
unknowns, it is a matter of linear algebra for the signal processing subsystem
107 to derive x1, x2, and x3 (assuming that N is at a low enough level to
permit
decoding of the signals):
= y11-1-'11 v ,2E-1-112 y3H-113
x2= yill-121 y2H-122 + Y3[1123
x3= y1H-131 + y2H-132 y3H-133
[00122] Once the three transmitted signals x,, are thus
derived, they are then
demodulated, decoded, and error-corrected by signal processing subsystem 107
to
recover the three bit streams that were originally separated out by splitter
101. These bit
streams are combined in combiner unit 108, and output as a single data stream
from the
data output 109. Assuming the robustness of the system is able to overcome the
noise
impairments, the data output 109 will produce the same bit stream that was
introduced
to the data Input 100.
[00123] Although the prior art system just described is
generally practical up to
four antennas, and perhaps up to as many as 10, for the reasons described in
the
Background section of this disclosure, it becomes impractical with large
numbers of
antennas (e.g. 25, 100, or 1000) .
Filed Via EFS-Web
6181P515X
200
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
=
[00124] Typically, such a prior art system is two-way, and
the return path is
implemented exactly the same way, but in reverse, with each side of the
communications channels having both transmit and receive subsystems.
1001251 Figure 2 illustrates one embodiment of the
invention in which a
Base Station (BS) 200 is configured with a Wide Area Network (WAN) interface
(e.g. to the Internet through a Ti or other high speed connection) 201 and is
provisioned with a number (N) of antennas 202. For the time being, we use the
term "Base Station" to refer to any wireless station that communicates
wirelessly
with a set of clients from a fixed location. Examples of Base Stations are
access
points in wireless local area networks (WLANs) or WAN antenna tower or
antenna array. There are a number of Client Devices 203-207, each with a
single
antenna, which are served wirelessly from the Base Station 200. Although for
the purposes of this example it is easiest to think about such a Base Station
as
being located in an office environment where it is serving Client Devices 203-
207
that are wireless-network equipped personal computers, this architecture will
apply to a large number of applications, both indoor and outdoor, where a Base
Station is serving wireless clients. For example, the Base Station could be
based
at a cellular phone tower, or on a television broadcast tower. In one
embodiment, the Base Station 200 is positioned on the ground and is configured
to transmit upward at HF frequencies (e.g., frequencies up to 24MHz) to bounce
signals off the ionosphere as described in co-pending application entitled
SYSTEM AND METHOD FOR ENHANCING NEAR VERTICAL INCIDENCE
SKYWAVE ("NVIS") COMMUNICATION USING SPACE-TIME CODING, Serial
Filed Via EFS-Web
6181P515X
201
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
No. 10/817,731, Filed April 2, 2004, which is assigned to the assignee of the
present application and which is incorporated herein by reference.
[00126] Certain details associated with the Base Station
200 and Client
Devices 203-207 set forth above are for the purpose of illustration only and
are
not required for complying with the underlying principles of the invention.
For
example, the Base Station may be connected to a variety of different types of
wide area networks via WAN interface 201 including application-specific wide
area networks such as those used for digital video distribution. Similarly,
the
Client Devices may be any variety of wireless data processing and/or
communication devices including, but not limited to cellular phones, personal
digital assistants ("PDAs"), receivers, and wireless cameras.
[00127] In one embodiment, the Base Station's n Antennas
202 are
separated spatially such that each is transmitting and receiving signals which
are
not spatially correlated, just as if the Base Station was a prior art M I MO
transceiver. As described in the Background, experiments have been done
where antennas placed within A/6 (i.e. 1/6 wavelength) apart successfully
achieve an increase in throughput from MIMO, but generally speaking, the
further
apart these Base Station antennas are placed, the better the system
performance, and A/2 is a desirable minimum. Of course, the underlying
Filed Via EFS-Web
6181P515X
202
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCTTUS2013/039580
41111
principles of the invention are not limited to any particular separation
between
antennas.
[00128] Note that a single Base Station 200 may very well
have its
antennas located very far apart. For example, in the HF spectrum, the antennas
may be 10 meters apart or more (e.g., in an NVIS implementation mentioned
above). If 100 such antennas are used, the Base Station's antenna array could
well occupy several square kilometers.
1001291 In addition to spatial diversity techniques, one
embodiment of the
invention polarizes the signal in order to increase the effective throughput
of the
system. Increasing channel capacity through polarization is a well known
technique which has been employed by satellite television providers for years.
Using polarization, it is possible to have multiple (e.g., three) Base Station
or
users' antennas very close to each other, and still be not spatially
correlated.
Although conventional RF systems usually will only benefit from the diversity
of
two dimensions (e.g. x and y) of polarization, the architecture described
herein
may further benefit from the diversity of three dimensions of polarization (x,
y and
z).
1001301 In addition to space and polarization diversity,
one embodiment
of the invention employs antennas with near-orthogonal radiation patterns to
Filed Via EFS-Web
6181P515X
203
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039680
I
improve link performance via pattern diversity. Pattern diversity can improve
the
capacity and error-rate performance of MIMO systems and its benefits over
other
antenna diversity techniques have been shown in the following papers:
[13] L. Dong, H. Ling, and R. W. Heath Jr., "Multiple-input multiple-output
wireless communication systems using antenna pattern diversity," Proc. IEEE
Glob. Telecom. Conf., vol. 1, pp. 997 ¨ 1001, Nov. 2002.
[14] R. Vaughan, "Switched parasitic elements for antenna diversity," IEEE
Trans. Antennas Propagat., vol. 47, pp. 399 ¨405, Feb. 1999.
[15] P. Mattheijssen, M. H. A. J. Herben, G. Dolmans, and L. Leyten,
"Antenna-pattern diversity versus space diversity for use at handhelds," IEEE
Trans. on Veh. Technol., vol. 53, pp. 1035¨ 1042, July 2004.
[16] C. B. Dietrich Jr, K. Dietze, J. R. Nealy, and W. L. Stutzman, "Spatial,
polarization, and pattern diversity for wireless handheld terminals," Proc.
IEEE
Antennas and Prop. Symp., vol. 49, pp. 1271 ¨1281, Sep. 2001.
[17] A. Forenza and R. W. Heath, Jr., "Benefit of Pattern Diversity Via 2-
element Array of Circular Patch Antennas in Indoor Clustered MIMO Channels",
IEEE Trans. on Communications, vol. 54, no. 5, pp. 943-954, May 2006.
1001311 Using pattern diversity, it is possible to have
multiple Base Station or
users' antennas very close to each other, and still be not spatially
correlated.
1001321 Figure 3 provides additional detail of one
embodiment of the Base
Station 200 and Client Devices 203-207 shown in Figure 2. For the purposes of
simplicity, the Base Station 300 is shown with only three antennas 305 and
only three
Client Devices 306-308. It will be noted, however, that the embodiments of the
invention
Filed Via EFS-Web
6181P515X
204
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
described herein may be implemented with a virtually unlimited number of
antennas 305
(i.e., limited only by available space and noise) and Client Devices 306-308.
[00133] Figure 3 is similar to the prior art MIMO
architecture shown in
Figure 1 in that both have three antennas on each sides of a communication
channel. A notable difference is that in the prior art MI MO system the three
antennas 105 on the right side of Figure 1 are all a fixed distance from one
another (e.g., integrated on a single device), and the received signals from
each
of the antennas 105 are processed together in the Signal Processing subsystem
107. By contrast, in Figure 3, the three antennas 309 on the right side of the
diagram are each coupled to a different Client Device 306-308, each of which
may be distributed anywhere within range of the Base Station 305. As such, the
signal that each Client Device receives is processed independently from the
other two received signals in its Coding, Modulation, Signal Processing
subsystem 311. Thus, in contrast to a Multiple-Input (i.e. antennas 105)
Multiple-
Output (i.e. antennas 104) "MIMO" system, Figure 3 illustrates a Multiple
Input
(i.e. antennas 305) Distributed Output (i.e. antennas 305) system, referred to
hereinafter as a "MIDO" system.
[00134] Note that this application uses different
terminology than
previous applications, so as to better conform with academic and industry
practices. In previously cited co-pending application, SYSTEM AND METHOD
FOR ENHANCING NEAR VERTICAL INCIDENCE SKYWAVE ("NVIS")
COMMUNICATION USING SPACE-TIME CODING, Serial No. 10/817,731, Filed
April 2, 2004, and Application No. 10/902,978 filed July 30, 2004 for which
this is
application is a continuation-in-part, the meaning of "Input" and "Output" (in
the
Filed Via EFS-Web
6181P515X
205
SUBSTITUTE SHEET (RULE 26)
CA 2872502 2020-03-06
=
WO 2013/166464 PCMS2013/039580
0
context of SIMO, MISO, DIMO and MIDO) is reversed from how the terms are
used in this application. In the prior applications, "Input" referred to the
wireless
signals as they are input to the receiving antennas (e.g. antennas 309 in
Figure
3), and 'Output" referred to the wireless signals as they are output by the
transmitting antennas (e.g. antennas 305). In academia and the wireless
industry, the reverse meaning of "Input" and "Output" is commonly used, in
which
"Input" refers to the wireless signals as they are input to the channel (i.e.
the
transmitted wireless signals from antennas 305) and "Output" refers to the
wireless signals as they are output from the channel (i.e. wireless signals
received by antennas 309). This application adopts this terminology, which is
the
reverse of the applications cited previously in this paragraph. Thus, the
following
terminology equivalences shall be drawn between applications:
10/817,731 and 10/902,978 Current Application
SIMO = MISO
MISO = SIMO
DIMO = MIDO
MIDO = DIMO
[00135] The MIDO architecture shown in Figure 3 achieves a
similar capacity
increase as MIMO over a SISO system for a given number of transmitting
antennas.
However, one difference between MIMO and the particular MIDO embodiment
illustrated
in Figure 3 is that, to achieve the capacity increase provided by multiple
base station
antennas, each MIDO Client Device 306-308 requires only a single receiving
antenna,
whereas with MIMO, each Client Device requires as least as many receiving
antennas
Filed Via EFS-Web
6181P515X
206
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
411 W. 2013/166464
PCT/US2013/039580
as the capacity multiple that is hoped to be achieved. Given that there is
usually a
practical limit to how many antennas can be placed on a Client Device (as
explained in
the Background), this typically limits MIMO systems to between four to ten
antennas
(and 4X to 10X capacity multiple). Since the Base Station 300 is typically
serving many
Client Devices from a fixed and powered location, is it practical to expand it
to far more
antennas than ten, and to separate the antennas by a suitable distance to
achieve
spatial diversity. As illustrated, each antenna is equipped with a transceiver
304 and a
portion of the processing power of a Coding, Modulation, and Signal Processing
section
303. Significantly, in this embodiment, no matter how much Base Station 300 is
expanded, each Client Device 306-308 only will require one antenna 309, so the
cost for
an individual user Client Device 306-308 will be low, and the cost of Base
Station 300
can be shared among a large base of users.
(001361 An example of how a MIDO transmission from the Base
Station 300 to
the Client Devices 306-308 can be accomplished is illustrated in Figures 4
through 6.
[00137]
In one embodiment of the invention, before a MIDO transmission
begins, the channel is characterized. As with a MIMO system, a training signal
is
transmitted (in the embodiment herein described), one-by-one, by each of the
antennas 405. Figure 4 illustrates only the first training signal
transmission, but
with three antennas 405 there are three separate transmissions in total. Each
training signal is generated by the Coding, Modulation, and Signal Processing
subsystem 403, converted to analog through a D/A converter, and transmitted as
RF through each RE Transceiver 404. Various different coding, modulation and
signal processing techniques may be employed including, but not limited to,
those described above (e.g., Reed Solomon, Viterbi coding; QAM, DPSK, QPSK
modulation, . . . etc) .
Filed Via EFS-Web
6181P515X
207
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
100138] Each Client Device 406-408 receives a training
signal through its
antenna 409 and converts the training signal to baseband by Transceiver 410.
An AID converter (not shown) converts the signal to digital where is it
processed
by each Coding, Modulation, and Signal Processing subsystem 411. Signal
characterization logic 320 then characterizes the resulting signal (e.g.,
identifying
phase and amplitude distortions as described above) and stores the
characterization in memory. This characterization process is similar to that
of
prior art MIMO systems, with a notable difference being that the each client
device only computes the characterization vector for its one antenna, rather
than
for n antennas. For example, the Coding Modulation and Signal Processing
subsystem 420 of client device 406 is initialized with a known pattern of the
training signal (either at the time of manufacturing, by receiving it in a
transmitted
message, or through another initialization process). When antenna 405
transmits
the training signal with this known pattern, Coding Modulation and Signal
Processing subsystem 420 uses correlation methods to find the strongest
received pattern of the training signal, it stores the phase and amplitude
offset,
then it subtracts this pattern from the received signal. Next, it finds then
second
strongest received pattern that correlates to the training signal, it stores
the
phase and amplitude offset, then it subtracts this second strongest pattern
from
the received signal. This process continues until either some fixed number of
phase and amplitude offsets are stored (e.g. eight), or a detectable training
signal
pattern drops below a given noise floor. This vector of phase/amplitude
offsets
becomes element H11 of the vector 413. Simultaneously, Coding Modulation and
Filed Via EFS-Web
6181P515X
208
SUBSTITUTE SHEET (RULE 26)
CA 2872502 2 020-0 3-0 6
=
WO 2013/166464 PCT/US2013/039580
=
Signal Processing subsystems for Client Devices 407 and 408 implement the
produce their vector elements H21 and H31.
100139] The memory in which the characterization is stored
may be a non-
volatile memory such as a Flash memory or a hard drive and/or a volatile
memory such as a random access memory (e.g., SDRAM, RDAM). Moreover,
different Client Devices may concurrently employ different types of memories
to
store the characterization information (e.g., PDA's may use Flash memory
whereas notebook computers may use a hard drive). The underlying principles
of the invention are not limited to any particular type of storage mechanism
on
the various Client Devices or the Base Station.
1001401 As mentioned above, depending on the scheme
employed, since
each Client Device 406-408 has only one antenna, each only stores a 1x3 row
413-415 of the H matrix. Figure 4 illustrates the stage after the first
training
signal transmission where the first column of 1x3 rows 413-415 has been stored
with channel characterization information for the first of the three Base
Station
antennas 405. The remaining two columns are stored following the channel
characterization of the next two training signal transmissions from the
remaining
two base station antennas. Note that for the sake of illustration the three
training
signals are transmitted at separate times. If the three training signal
patterns are
chosen such as not to be correlated to one another, they may be transmitted
simultaneously, thereby reducing training time.
Filed Via EFS-Web
6181P515X
209
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCMS2013/039580
[00141] As indicated in Figure 5, after all three pilot
transmissions are
complete, each Client Device 506-508 transmits back to the Base Station 500
the
1x3 row 513-515 of matrix H that it has stored. To the sake of simplicity,
only
one Client Device 506 is illustrated transmitting its characterization
information in
Figure 5. An appropriate modulation scheme (e.g. DPSK, 64QAM, OFDM) for
the channel combined with adequate error correction coding (e.g. Reed
Solomon, Viterbi, and/or Turbo codes) may be employed to make sure that the
Base Station 500 receives the data in the rows 513-515 accurately.
1001421 Although all three antennas 505 are shown receiving
the signal in
Figure 5, it is sufficient for a single antenna and transceiver of the Base
Station
500 to receive each 1x3 row 513-515 transmission. However, utilizing many or
all of antennas 505 and Transceivers 504 to receive each transmission (i.e.,
utilizing prior art Single-Input Multiple-Output ("SIMO") processing
techniques in
the Coding, Modulation and Signal Processing subsystem 503) may yield a
better signal-to-noise ratio ("SNR") than utilizing a single antenna 505 and
Transceiver 504 under certain conditions.
[00143] As the Coding, Modulation and Signal Processing
subsystem 503
of Base Station 500 receives the 1x3 row 513-515, from each Client Device 507-
508, it stores it in a 3x3 H matrix 516. As with the Client Devices, the Base
Station may employ various different storage technologies including, but not
limited to non-volatile mass storage memories (e.g., hard drives) and/or
volatile
memories (e.g., SDRAM) to store the matrix 516. Figure 5 illustrates a stage
at
Filed Via EFS-Web
6181P515X
210
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039500
which the Base Station 500 has received and stored the 1x3 row 513 from Client
Device 509. The 1x3 rows 514 and 515 may be transmitted and stored in H
matrix 516 as they are received from the remaining Client Devices, until the
entire H matrix 516 is stored.
[00144] One embodiment of a MIDO transmission from a Base
Station 600
to Client Devices 606-608 will now be described with reference to Figure 66.
Because each Client Device 606-608 is an independent device, typically each
device is receiving a different data transmission. As such, one embodiment of
a
Base Station 600 includes a Router 602 communicatively positioned between the
WAN Interface 601 and the Coding, Modulation and Signal Processing
subsystem 603 that sources multiple data streams (formatted into bit streams)
from the WAN interface 601 and routes them as separate bit streams Ui- U3
intended for each Client Device 606-608, respectively_ Various well known
routing techniques may be employed by the router 602 for this purpose.
1001451 The three bit streams, ur u3, shown in Figure 6 are
then routed
into the Coding, Modulation and Signal Processing subsystem 603 and coded
into statistically distinct, error correcting streams (e.g. using Reed
Solomon,
Viterbi, or Turbo Codes) and modulated using an appropriate modulation scheme
for the channel (such as DPSK, 64QAM or OFDM). In addition, the embodiment
illustrated in Figure 6 includes signal precoding logic 630 for uniquely
coding the
signals transmitted from each of the antennas 605 based on the signal
characterization matrix 616. More specifically, rather than routing each of
the
Filed Via EFS-Web
6181P515X
211
SUBSTITUTE SHEET (RULE 26)
CA 2872 502 2 020-0 3-0 6
WO 2013/166464
PCT/US2013/039580
three coded and modulated bit streams to a separate antenna (as is done in
Figure 1), in one embodiment, the precoding logic 630 multiplies the three bit
streams ur u3 in Figure 6 by the inverse of the H matrix 616, producing three
new bit streams, u'l- u'3. The three precoded bit streams are then converted
to
analog by D/A converters (not shown) and transmitted as RF by Transceivers
604 and antennas 605.
1001461 Before explaining how the bit streams are received by the
Client
Devices 606-608, the operations performed by the precoding module 630 will be
described. Similar to the MIMO example from Figure 1 above, the coded and
modulated signal for each of the three source bit streams will be designated
with
un. In the embodiment illustrated in Figure 6, each u, contains the data from
one
of the three bit streams routed by the Router 602, and each such bit stream is
intended for one of the three Client Devices 606-608.
1001471 However, unlike the MIMO example of Figure 1, where each xis
transmitted by each antenna 104, in the embodiment of the invention
illustrated
in Figure 6, each u, is received at each Client Device antenna 609 (plus
whatever noise N there is in the channel). To achieve this result, the output
of
each of the three antennas 605 (each of which we will designate as 1/1) is a
function of ui and the H matrix that characterizes the channel for each Client
Device. In one embodiment, each v, is calculated by the precoding logic 630
within the Coding, Modulation and Signal Processing subsystem 603 by
implementing the following formulas:
Filed Via EFS-Web
61B1P515X
212
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
= 1-11H-1 -1 -1
11 U2H12 U3 13
V2 = 1/1/1-1 21 U2H-122 U3H-1 23
V3 = 111H-131 + U211-132 + U3H-133
[00148] Thus, unlike MI MO, where each xi is calculated at
the receiver after
the signals have been transformed by the channel, the embodiments of the
invention described herein solve for each v, at the transmitter before the
signals
have been transformed by the channel. Each antenna 609 receives u1 already
separated from the other un_i bit streams intended for the other antennas 609.
Each Transceiver 610 converts each received signal to baseband, where it is
digitized by an AID converter (now shown), and each Coding, Modulation and
Signal Processing subsystem 611, demodulates and decodes the bit stream
intended for it, and sends its bit stream to a Data Interface 612 to be used
by the
Client Device (e.g., by an application on the client device).
[00149] The embodiments of the invention described herein
may be
implemented using a variety of different coding and modulation schemes. For
example, in an OFDM implementation, where the frequency spectrum is
separated into a plurality of sub-bands, the techniques described herein may
be
employed to characterize each individual sub-band. As mentioned above,
however, the underlying principles of the invention are not limited to any
particular modulation scheme.
[00150] If the Client Devices 606-608 are portable data
processing devices
such as PDAs, notebook computers, and/or wireless telephones the channel
Filed Via EFS-Web
6181P515X
213
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
4110
characterization may change frequently as the Client Devices may move from
one location to another. As such, in one embodiment of the invention, the
channel characterization matrix 616 at the Base Station is continually
updated.
In one embodiment, the Base Station 600 periodically (e.g., every 250
milliseconds) sends out a new training signal to each Client Device, and each
Client Device continually transmits its channel characterization vector back
to the
Base Station 600 to ensure that the channel characterization remains accurate
(e.g. if the environment changes so as to affect the channel or if a Client
Device
moves). In one embodiment, the training signal is interleaved within the
actual
data signal sent to each client device. Typically, the training signals are
much
lower throughput than the data signals, so this would have little impact on
the
overall throughput of the system. Accordingly, in this embodiment, the channel
characterization matrix 616 may be updated continuously as the Base Station
actively communicates with each Client Device, thereby maintaining an accurate
channel characterization as the Client Devices move from one location to the
next or if the environment changes so as to affect the channel.
[00151] One embodiment of the invention illustrated in
Figure 7 employs
MIMO techniques to improve the upstream communication channel (i.e., the
channel from the Client Devices 706-708 to the Base Station 700). In this
embodiment, the channel from each of the Client Devices is continually
analyzed
and characterized by upstream channel characterization logic 741 within the
Base Station. More specifically, each of the Client Devices 706-708 transmits
a
training signal to the Base Station 700 which the channel characterization
logic
Filed Via EFS-Web
6181P515X
214
SUBSTITUTE SHEET (RULE 26)
CA 2 8 7250 2 2 02 0-0 3-0 6
0 WO 2013/166464
PCT/US2013/039580
III
741 analyzes (e.g., as in a typical MIMO system) to generate an N x M channel
characterization matrix 741, where N is the number of Client Devices and M is
the number of antennas employed by the Base Station. The embodiment
illustrated in Figure 7 employs three antennas 705 at the Base Station and
three
Client Devices 706-608, resulting in a 3x3 channel characterization matrix 741
stored at the Base Station 700. The MIMO upstream transmission illustrated in
Figure 7 may be used by the Client Devices both for transmitting data back to
the Base Station 700, and for transmitting channel characterization vectors
back
to the Base Station 700 as illustrated in Figure 5. But unlike the embodiment
illustrated in Figure 5 in which each Client Device's channel characterization
vector is transmitted at a separate time, the method shown in Figure 7 allows
for
the simultaneous transmission of channel characterization vectors from
multiple
Client Devices back to the Base Station 700, thereby dramatically reducing the
channel characterization vectors' impact on return channel throughput.
1001521 As mentioned above, each signal's characterization
may include
many factors including, for example, phase and amplitude relative to a
reference
internal to the receiver, an absolute reference, a relative reference,
characteristic
noise, or other factors. For example, in a quadrature amplitude modulation
("QAM")-modulated signal the characterization might be a vector of the phase
and amplitude offsets of several multipath images of the signal. As another
example, in an orthogonal frequency division multiplexing ("OFDM")-modulated
signal, it might be a vector of the phase and amplitude offsets of several or
all of
the individual sub-signals in the OFDM spectrum. The training signal may be
Filed Via EFS-Web
6181P515X
215
CA 2872502 2 02 0-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
0
generated by each Client Device's coding and modulation subsystem 711,
converted to analog by a D/A converter (not shown), and then converted from
baseband to RF by each Client Device's transmitter 709. In one embodiment, in
order to ensure that the training signals are synchronized, Client Devices
only
transmit training signals when requested by the Base Station (e.g., in a round
robin manner). In addition, training signals may be interleaved within or
transmitted concurrently with the actual data signal sent from each client
device.
Thus, even if the Client Devices 706-708 are mobile, the training signals may
be
continuously transmitted and analyzed by the upstream channel characterization
logic 741, thereby ensuring that the channel characterization matrix 741
remains
up-to-date.
1001531 The total channel capacity supported by the
foregoing
embodiments of the invention may be defined as min (N, M) where M is the
number of Client Devices and N is the number of Base Station antennas. That
is, the capacity is limited by the number of antennas on either the Base
Station
side or the Client side. As such, one embodiment of the invention employs
synchronization techniques to ensure that no more than min (N, M) antennas are
transmitting/ receiving at a given time.
[00154] In a typical scenario, the number of antennas 705 on
the Base
Station 700 will be less than the number of Client Devices 706-708. An
exemplary scenario is illustrated in Figure 8 which shows five Client Devices
804-808 communicating with a base station having three antennas 802. In this
Filed Via EFS-Web
6181P515X
216
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
0
embodiment, after determining the total number of Client Devices 804-808, and
collecting the necessary channel characterization information (e.g., as
described
above), the Base Station 800 chooses a first group of three clients 810 with
which to communicate (three clients in the example because min (N, M) = 3).
After communicating with the first group of clients 810 for a designated
period of
time, the Base Station then selects another group of three clients 811 with
which
to communicate. To distribute the communication channel evenly, the Base
Station 800 selects the two Client Devices 807, 808 which were not included in
the first group. In addition, because an extra antenna is available, the Base
Station 800 selects an additional client device 806 included in the first
group. In
one embodiment, the Base Station 800 cycles between groups of clients in this
manner such that each client is effectively allocated the same amount of
throughput over time. For example, to allocate throughput evenly, the Base
Station may subsequently select any combination of three Client Devices which
excludes Client Device 806 (i.e., because Client Device 806 was engaged in
communication with the Base Station for the first two cycles).
[00155] In one embodiment, in addition to standard data
communications,
the Base Station may employ the foregoing techniques to transmit training
signals to each of the Client Devices and receive training signals and signal
characterization data from each of the Client Devices.
[00156] In one embodiment, certain Client Devices or groups
of client
devices may be allocated different levels of throughput. For example, Client
Filed Via EFS-Web
6181P515X
217
SUBSTITUTE SHEET (RULE 26)
CA 2872502 2020-03-06
=
WO 2013/166464 PCT/US2013/039580
4111
Devices may be prioritized such that relatively higher priority Client Devices
may
be guaranteed more communication cycles (i.e., more throughput) than
relatively
lower priority client devices. The "priority" of a Client Device may be
selected
based on a number of variables including, for example, the designated level of
a
user's subscription to the wireless service (e.g., user's may be willing to
pay
more for additional throughput) and/or the type of data being communicated
to/from the Client Device (e.g., real-time communication such as telephony
audio
and video may take priority over non-real time communication such as email).
[00157] In one embodiment of the Base Station dynamically
allocates
throughput based on the Current Load required by each Client Device. For
example, if Client Device 804 is streaming live video and the other devices
805-
808 are performing non-real time functions such as email, then the Base
Station
800 may allocate relatively more throughput to this client 804. It should be
noted,
however, that the underlying principles of the invention are not limited to
any
particular throughput allocation technique.
[00158] As illustrated in Figure 9, two Client Devices 907,
908 may be so
close in proximity, that the channel characterization for the clients is
effectively
the same. As a result, the Base Station will receive and store effectively
equivalent channel characterization vectors for the two Client Devices 907,
908
and therefore will not be able to create unique, spatially distributed signals
for
each Client Device. Accordingly, in one embodiment, the Base Station will
ensure that any two or more Client Devices which are in close proximity to one
Filed Via EFS-Web
6181 P515X
218
CA 2872502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
1111
another are allocated to different groups. In Figure 9, for example, the Base
Station 900 first communicates with a first group 910 of Client Devices 904,
905
and 908; and then with a second group 911 of Client Devices 905, 906, 907,
ensuring that Client Devices 907 and 908 are in different groups.
1001591 Alternatively, in one embodiment, the Base Station
900
communicates with both Client Devices 907 and 908 concurrently, but
multiplexes the communication channel using known channel multiplexing
techniques. For example, the Base Station may employ time division
multiplexing ("TDM"), frequency division multiplexing ("FDM") or code division
multiple access ("CDMA") techniques to divide the single, spatially-correlated
signal between Client Devices 907 and 908.
1001601 Although each Client Device described above is
equipped with a
single antenna, the underlying principles of the invention may be employed
using
Client Devices with multiple antennas to increase throughput. For example,
when used on the wireless systems described above, a client with 2 antennas
will realize a 2x increase in throughput, a client with 3 antennas will
realize a 3x
increase in throughput, and so on (i.e., assuming that the spatial and angular
separation between the antennas is sufficient). The Base Station may apply the
same general rules when cycling through Client Devices with multiple antennas.
For example, it may treat each antenna as a separate client and allocate
throughput to that "client" as it would any other client (e.g., ensuring that
each
client is provided with an adequate or equivalent period of communication).
Filed Via EFS-Web
6181P515X
219
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
111
1001611 As mentioned above, one embodiment of the invention
employs the
MIDO and/or MIMO signal transmission techniques described above to increase
the signal-to-noise ratio and throughput within a Near Vertical Incidence
Skywave
("NVIS") system. Referring to Figure 10, in one embodiment of the invention, a
first NVIS station 1001 equipped with a matrix of N antennas 1002 is
configured
to communicate with M client devices 1004. The NVIS antennas 1002 and
antennas of the various client devices 1004 transmit signals upward to within
about 15 degrees of vertical in order to achieve the desired NVIS and minimize
ground wave interference effects. In one embodiment, the antennas 1002 and
client devices 1004, support multiple independent data streams 1006 using the
various MIDO and MIMO techniques described above at a designated frequency
within the NVIS spectrum (e.g., at a carrier frequency at or below 23 MHz, but
typically below 10 MHz), thereby significantly increasing the throughput at
the
designated frequency (i.e., by a factor proportional to the number of
statistically
independent data streams).
1001621 The NVIS antennas serving a given station may be
physically very
far apart from each other. Given the long wavelengths below 10 MHz and the
long distance traveled for the signals (as much as 300 miles round trip),
physical
separation of the antennas by 100s of yards, and even miles, can provide
advantages in diversity. In such situations, the individual antenna signals
may be
brought back to a centralized location to be processed using conventional
wired
or wireless communications systems. Alternatively, each antenna can have a
local facility to process its signals, then use conventional wired or wireless
Filed Via EFS-Web
6181P515X
220
SUBSTITUTE SHEET (RULE 26)
CA 2872502 2020-03-06
=
WO 2013/166464 PCT/US2013/039580
communications systems to communicate the data back to a centralized location.
In one embodiment of the invention, NVIS Station 1001 has a broadband link
1015 to the Internet 1010 (or other wide area network), thereby providing the
client devices 1003 with remote, high speed, wireless network access.
[00163] In one embodiment, the Base Station and/or users
may exploit
polarization/pattern diversity techniques described above to reduce the array
size
and/or users' distance while providing diversity and increased throughput. As
an
example, in MIDO systems with HF transmissions, the users may be in the same
location and yet their signals be uncorrelated because of polarization/pattern
diversity. In particular, by using pattern diversity, one user may be
communicating to the Base Station via groundwave whereas the other user via
NVIS.
ADDITIONAL EMBODIMENTS OF THE INVENTION
DIDO-OFDM Precodinq with I/Q Imbalance
[00164] One embodiment of the invention employs a system
and method to
compensate for in-phase and quadrature (I/Q) imbalance in distributed-input
distributed-output (DIDO) systems with orthogonal frequency division
multiplexing (OFDM). Briefly, according to this embodiment, user devices
estimate the channel and feedback this information to the Base Station; the
Base
Station computes the precoding matrix to cancel inter-carrier and inter-user
interference caused by I/Q imbalance; and parallel data streams are
transmitted
to multiple user devices via DIDO precoding; the user devices demodulate data
Filed Via EFS-Web
6181P515X
221
SUBSTITUTE SHEET (RULE 26)
CA 2872 502 2 020-0 3-0 6
=
WO 2013/166464 PCT/US2013/039580
0
via zero-forcing (ZF), minimum mean-square error (MMSE) or maximum
likelihood (ML) receiver to suppress residual interference.
[001651 As described in detail below, some of the
significant features of
this embodiment of the invention include, but are not limited to:
[00166] Precoding to cancel inter-carrier interference
(ICI) from mirror tones
(due to I/Q mismatch) in OFDM systems;
[00167] Precoding to cancel inter-user interference and ICI
(due to I/Q
mismatch) in DIDO-OFDM systems;
[00168] Techniques to cancel ICI (due to I/Q mismatch) via
ZF receiver in
DIDO-OFDM systems employing block diagonalization (BD) precoder;
[00169] Techniques to cancel inter-user interference and
ICI (due to I/Q
mismatch) via precoding (at the transmitter) and a ZF or MMSE filter (at the
receiver) in DIDO-OFDM systems;
[00170] Techniques to cancel inter-user interference and
ICI (due to I/Q
mismatch) via pre-coding (at the transmitter) and a nonlinear detector like a
maximum likelihood (ML) detector (at the receiver) in DIDO-OFDM systems;
[00171] The use of pre-coding based on channel state
information to
cancel inter-carrier interference (ICI) from mirror tones (due to I/Q
mismatch) in
OFDM systems;
[00172] The use of pre-coding based on channel state
information to
cancel inter-carrier interference (ICI) from mirror tones (due to I/Q
mismatch) in
DIDO-OFDM systems;
Filed Via EFS-Web
6181P515X
222
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
[00173] The use of an I/Q mismatch aware DIDO precoder at
the station
and an I0-aware DIDO receiver at the user terminal;
[00174] The use of an I/O mismatch aware DIDO precoder at
the station, an
I/Q aware DIDO receiver at the user terminal, and an I/Q aware channel
estimator;
[00175] The use of an I/O mismatch aware DIDO precoder at
the station, an
I/O aware DIDO receiver at the user terminal, an I/Q aware channel estimator,
and an I/O aware DIDO feedback generator that sends channel state information
from the user terminal to the station;
[00176] The use of an I/Q mismatch-aware DIDO precoder at
the station
and an I/O aware DIDO configurator that uses I/O channel information to
perform
functions including user selection, adaptive coding and modulation, space-time-
frequency mapping, or precoder selection;
[00177] The use of an I/O aware DIDO receiver that cancels
ICI (due to I/O
mismatch) via ZF receiver in DIDO-OFDM systems employing block
diagonalization (BD) precoder;
[00178] The use of an I/O aware DIDO receiver that cancels
ICI (due to I/O
mismatch) via pre-coding (at the transmitter) and a nonlinear detector like a
maximum likelihood detector (at the receiver) in DIDO-OFDM systems; and
[00179] The use of an I/Q aware DIDO receiver that cancels
ICI (due to I/Q
mismatch) via ZF or MMSE filter in DIDO-OFDM systems.
Filed Via EFS-Web
6181P515X
223
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
a. Background
[00180] The transmit and receive signals of typical
wireless communication
systems consist of in-phase and quadrature (I/Q) components. In practical
systems, the inphase and quadrature components may be distorted due to
imperfections in the mixing and baseband operations. These distortions
manifest
as I/Q phase, gain and delay mismatch. Phase imbalance is caused by the sine
and cosine in the modulator/demodulator not being perfectly orthogonal. Gain
imbalance is caused by different amplifications between the inphase and
quadrature components. There may be an additional distortion, called delay
imbalance, due to difference in delays between the l-and Q-rails in the analog
circuitry.
[00181] In orthogonal frequency division multiplexing
(OFDM) systems,
I/Q imbalance causes inter-carrier interference (ICI) from the mirror tones.
This
effect has been studied in the literature and methods to compensate for I/Q
mismatch in single-input single-output SISO-OFDM systems have been
proposed in M. D. Benedetto and P. Mandarini, "Analysis of the effect of the
I/Q
baseband filter mismatch in an OFDM modem," Wireless personal
communications, pp. 175-186, 2000; S. Schuchert and R. Hasholzner, "A novel
I/Q imbalance compensation scheme for the reception of OFDM signals," IEEE
Transaction on Consumer Electronics, Aug. 2001; M. Valkama, M. Renfors, and
V. Koivunen, "Advanced methods for I/Q imbalance compensation in
communication receivers," IEEE Trans. Sig. Proc., Oct. 2001; R. Rao and B.
Daneshrad, "Analysis of I/Q mismatch and a cancellation scheme for OFDM
Filed Via EFS-Web
6181P515X
224
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
systems," 1ST Mobile Communication Summit, June 2004; A. Tarighat, R.
Bagheri, and A. H. Sayed, "Compensation schemes and performance analysis of
IQ imbalances in OFDM receivers," Signal Processing, IEEE Transactions on
[see also Acoustics, Speech, and Signal Processing, IEEE Transactions on],
vol.
53, pp. 3257-3268, Aug. 2005.
[00182] An extension of this work to multiple-input multiple-
output MIMO-
OFDM systems was presented in R. Rao and B. Daneshrad, "I/Q mismatch
cancellation for MIMO OFDM systems," in Personal, Indoor and Mobile Radio
Communications, 2004; PIMRC 2004. 15th IEEE International Symposium on,
vol. 4, 2004, pp. 2710-2714. R. M. Rao, W. Zhu, S. Lang, C. Oberli, D. Browne,
J. Bhatia, J. F. Frigon, J. Wang, P; Gupta, H. Lee, D. N. Liu, S. G. Wong, M.
Fitz,
B. Daneshrad, and 0. Takeshita, "Multiantenna testbeds for research and
education in wireless communications," IEEE Communications Magazine, vol.
42, no. 12, pp. 72-81, Dec. 2004; S. Lang, M. R. Rao, and B. Daneshrad,
"Design and development of a 5.25 GHz software defined wireless OFDM
communication platform," IEEE Communications Magazine, vol. 42, no. 6, pp. 6-
12, June 2004, for spatial multiplexing (SM) and in A. Tarighat and A. H.
Sayed,
"MIMO OFDM receivers for systems with IQ imbalances," IEEE Trans. Sig. Proc.,
vol. 53, pp. 3583-3596, Sep. 2005, for orthogonal space-time block codes
(OSTBC).
[00183] Unfortunately, there is currently no literature on
how to correct for
I/Q gain and phase imbalance errors in a distributed-input distributed-output
Filed Via EFS-Web
6181P515X
225
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
(DIDO) communication system. The embodiments of the invention described
below provide a solution to these problems.
[00184] DIDO systems consist of one Base Station with
distributed
antennas that transmits parallel data streams (via pre-coding) to multiple
users to
enhance downlink throughput, while exploiting the same wireless resources
(i.e.,
same slot duration and frequency band) as conventional SISO systems. A
detailed description of DIDO systems was presented in S. G. Perlman and T.
Cotter, "System and Method for Distributed Input-Distributed Output Wireless
Communications," Serial No. 10/902,978, filed July 30, 2004 ("Prior
Application"),
which is assigned to the assignee of the present application and which is
incorporated herein by reference.
[00185] There are many ways to implement DIDO precoders.
One solution
is block diagonalization (BD) described in Q. H. Spencer, A. L. Swindlehurst,
and
M. Haardt, "Zero forcing methods for downlink spatial multiplexing in
multiuser
MIMO channels," IEEE Trans. Sig. Proc., vol. 52, pp. 461-471, Feb. 2004. K. K.
Wong, R. D. Murch, and K. B. Letaief, "A joint channel diagonalization for
multiuser MIMO antenna systems," IEEE Trans. Wireless Comm., vol. 2, pp.
773-786, Jul 2003; L. U. Choi and R. D. Murch, "A transmit preprocessing
technique for multiuser MIMO systems using a decomposition approach," IEEE
Trans. Wireless Comm., vol. 3, pp. 20-24, Jan 2004; Z. Shen, J. G. Andrews, R.
W. Heath, and B. L. Evans, "Low complexity user selection algorithms for
multiuser MIMO systems with block diagonalization," accepted for publication
in
IEEE Trans. Sig. Proc., Sep. 2005; Z. Shen, R. Chen, J. G. Andrews, R. W.
Filed Via EFS-Web
6181P515X
226
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
=
Heath, and B. L. Evans, "Sum capacity of multiuser MI MO broadcast channels
with block diagonalization," submitted to IEEE Trans. Wireless Comm., Oct.
2005; R. Chen, R. W. Heath, and J. G. Andrews, "Transmit selection diversity
for
unitary precoded multiuser spatial multiplexing systems with linear
receivers,"
accepted to IEEE Trans. on Signal Processing, 2005. The methods for I/Q
compensation presented in this document assume BD precoder, but can be
extended to any type of DIDO precoder.
[00186] In DIDO-OFDM systems, I/Q mismatch causes two
effects: ICI and
inter-user interference. The former is due to interference from the mirror
tones as in
SISO-OFDM systems. The latter is due to the fact that I/Q mismatch destroys
the
orthogonality of the DIDO precoder yielding interference across users. Both of
these
types of interference can be cancelled at the transmitter and receiver through
the
methods described herein. Three methods for I/Q compensation in DIDO-OFDM
systems are described and their performance is compared against systems with
and
without I/C) mismatch. Results are presented based both on simulations and
practical
measurements carried out with the DIDO-OFDM prototype.
100187] The present embodiments are an extension of the
Prior Application. In
particular, these embodiments relate to the following features of the Prior
Application:
1001881 The system as described in the prior application,
where the I/Q
rails are affected by gain and phase imbalance;
[00189] The training signals employed for channel
estimation are used to
calculate the DIDO precoder with I/Q compensation at the transmitter; and
Filed Via EFS-Web
6181P515X
227
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039500
=
[00190] The signal characterization data accounts for
distortion due to
I/Q imbalance and is used at the transmitter to compute the DIDO precoder
according to the method proposed in this document.
b. Embodiments of the Invention
[00191] First, the mathematical model and framework of the
invention will
be described.
[00192] Before presenting the solution, it is useful to
explain the core
mathematical concept. We explain it assuming I/Q gain and phase imbalance
(phase delay is not included in the description but is dealt with
automatically in
the DIDO-OFDM version of the algorithm). To explain the basic idea, suppose
that we want to multiply two complex numbers s = Si + jso and h = hi + jho and
let
x = h * s. We use the subscripts to denote inphase and quadrature components.
Recall that
x1 = sihi ¨ s110
and
XQ = SlhQ S0h1 .
In matrix form this can be rewritten as
Xi
,
/IQ hi j
Note the unitary transformation by the channel matrix (H). Now suppose
that s is the transmitted symbol and h is the channel. The presence of I/Q
gain
Filed Via EFS-Web
6181 P515X
228
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
0 WO 2013/166464
PCT/US2013/039580
=
and phase imbalance can be modeled by creating a non-unitary transformation
as follows
_
X/ -
[
= h
-
_ i 1 /11.9
1121 h22¨ 81
,s,-,
¨ - - (A)
The trick is to recognize that it is possible to write
hu ii.:12µ _ 1 . lin + h22 F h 32 ¨ h21
4.. 1 ' 433 ¨ /IV h12 + h.:, i
42). 4...4 ¨ ::i %1.:4 .--- 421) hAl +
b.,!...! . ' '7.7? 114,µ + h2) itzi --
1 ............................ 413 + iqZ h t2 ¨ fl.'.,.1 I h t
1 ¨ ieZ2 ¨ihn 4' h',!! ) - 1 0
.- --(iN2 ¨ h2). ) )43) 14-22
2 it:i2 + h.,9 !? E I ¨ hze I) ¨1 . Now, rewriting (A)
Fri / = '1 !in + /12,:: 1112 -
h2I } / i + _1- { hil ¨ h12 ¨ (ht.: + h21 ) ] [ 1 0 ] [ 8/ I
J.Q 2 ¨I /112 ¨ h21) h I 1 + h-22 .5f.,? 2
hp. + /121 Ns ¨ h-22 0 ¨1 =*`,.;?
1 [ hi I + h'.32 h 12 ¨ 421 1 =9! i + _I [ h 1 :
¨ h22 ¨( h )2 h.:II i [ ,,./ I
V.' )
¨ T, - ish )2 )42)) 1/ I i I 1:.71 ..
.) tri2 -I- 11.2 3 h11 - /422 -- 6Q
Let us define
-
= I ill .1. h22 h 1,::, ¨h21
_
-1.-
2 ¨(h r2, ¨
h21) hll + h22
-
and
_ R , .. -
1 hi i ¨ /129.
¨ (hp + /7õ91 )
e = ¨ ,
' 9 h12 + /121. hql ¨ h22
Both of these matrices have a unitary structure thus can be equivalently
represented by complex scalars as
Filed Via EFS-Web
6181P515X
229
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
= hi" h22 - 42)
and
= hii /i.2 4- J(.h.21 h 12 ) .
Using all of these observations, we can put the effective equation back in
a scalar form with two channels: the equivalent channel he and the conjugate
channel hõ Then the effective transformation in (5) becomes
X = /4.9 -f- hos*
We refer to the first channel as the equivalent channel and the second
channel as the conjugate channel. The equivalent channel is the one you would
observe if there were no I/Q gain and phase imbalance.
Using similar arguments, it can be shown that the input-output
relationship of a discrete-time MIMO NxM system with I/Q gain and phase
imbalance is (using the scalar equivalents to build their matrix counterparts)
x[t] =Eh, reisp¨fl+11,[4]s.p¨il
e=0
where t is the discrete time index, he ,h, EC" k1,..., x,41
and L
is the number of channel taps.
In DIDO-OFDM systems, the received signal in the frequency domain is
represented. Recall from signals and systems that if
Filed Via EFS-Web
6181 P515X
230
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
410 WO 2013/166464
PCT/US2013/039580
FFTKIs[Ill = S[k] then F FT Kts=kn= [(- 10] = S. [K - kl fork = 0 ,1,..., K -1
.
With OFDM, the equivalent input-output relationship for a MIMO-OFDM system
for subcarrier k is
x[k]= He [k]s[k]+ 14,[k]s [K -k] (1)
where k = 0, 1, . . . ,K - 1 is the OFDM subcarrier index, He and it denote
the
equivalent and conjugate channel matrices, respectively, defined as
211k Ã
t=0
and
2ru, e
Hc[k] =Zhe[e]e K
t=0
The second contribution in (1) is interference from the mirror tone. It can
be dealt with by constructing the following stacked matrix system (note
carefully
the conjugates)
[ i[k],[k] H[k] ir Rid
1*[K - k]] 11
_H:[K - k] We[K - k][r [K -k]
where 1= rs.,,-;21, and I= , are the vectors of transmit and
receive symbols
in the frequency domain, respectively.
Using this approach, an effective matrix is built to use for DIDO operation.
For example, with DIDO 2 x 2 the input-output relationship (assuming each user
has a single receive antenna) the first user device sees (in the absence of
noise)
si[k]
[.71[k] 1=[ [k] [k] s7[K - k]
4 [K - k] - k] H [K - k] s 2[k]
s 2[K -k]
Filed Via EFS-Web
6181P515X
231
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
while the second user observes
2[k] H(,2) [k] [k] [K - k]
r - k]i= W2)* [K - k] 11(:)* [K - k]
_ 2 s2[k] (3)
S2 [K kJ
where H(:), Wm) E Clx2 denote the m-th row of the matrices He and H,
respectively, and w E C4x4 is the DIDO pre-coding matrix. From (2) and (3) it
is
observed that the received symbol -xm[k] of user m is affected by two sources
of
interference caused by I/Q imbalance: inter-carrier interference from the
mirror
tone (i.e., -s.õ,[K-k]) and inter-user interference (i.e., s[k] and -s; [K -k]
with
p#m). The DIDO precoding matrix W in (3) is designed to cancel these two
interference terms.
1001931 There are several different embodiments of the DIDO
precoder that
can be used here depending on joint detection applied at the receiver. In one
embodiment, block diagonalization (BD) is employed (see, e.g., Q. H. Spencer,
A. L. Swindlehurst, and M. Haardt, "Zeroforcing methods for downlink spatial
multiplexing in multiuser MIMO channels," IEEE Trans. Sig. Proc., vol. 52, pp.
461-471, Feb. 2004. K. K. Wong, R. D. Murch, and K. B. Letaief, "A joint -
channel diagonalization for multiuser MIMO antenna systems," IEEE Trans.
Wireless Comm., vol. 2, pp. 773-786, Jul 2003. L. U. Choi and R. D. Murch, "A
transmit preprocessing technique for multiuser MIMO systems using a
decomposition approach," IEEE Trans. Wireless Comm., vol. 3, pp. 20-24, Jan
2004. Z. Shen, J. G. Andrews, R. W. Heath, and B. L. Evans, "Low complexity
Filed Via EFS-Web
6181P515X
232
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
=
user selection algorithms for multiuser MIMO systems with block
diagonalization," accepted for publication in IEEE Trans. Sig. Proc., Sep.
2005.
Z. Shen, R. Chen, J. G. Andrews, R. W. Heath, and B. L. Evans, "Sum capacity
of multiuser MIMO broadcast channels with block diagonalization," submitted to
IEEE Trans. Wireless Comm., Oct. 2005, computed from the composite channel
[H(:),H(c-)] (rather than H(:) ). So, the current DIDO system chooses the
precoder
such that
H(e1)[k] ii(co[k] aLI 0 0 0
_ H H
H A H(c1). [K ¨ k] [K ¨ k] 0 a1,2 0 0 A
qt,(1'1)(v1,2)
H W =
I 1 (4)
= H (e2) [k] H2[k] 0 0 a2,1 0 = 2)
H(2)* [K ¨ k H (e2). [K ¨ kJ 0 0 0 a2,2
_ c
where a,j are constants and HILJ) e c2x2. This method is beneficial because
using this precoder, it is possible to keep other aspects of the DIDO precoder
the
same as before, since the effects of I/Q gain and phase imbalance are
completely cancelled at the transmitter.
1001941 It is also possible to design DIDO precoders that
pre-cancel inter-
user interference, without pre-cancelling ICI due to IQ imbalance. With this
approach, the receiver (instead of the transmitter) compensates for the IQ
imbalance by employing one of the receive filters described below. Then, the
pre-coding design criterion in (4) can be modified as
Filed Via EFS-Web
6181P515X
233
CA 2872502 2020-03-06 SUBSTITUTE SHEET
(RULE 26)
WO 2013/166464
PCT/US2013/039580
We') [k] 11(c1)[k] a1,1 a1,2 0 0
H H
H A ifc1).[K -k] H(e1)* [K -k] a2,1 _ a,,2 0 0 A [If_pv
(1,1) 1,2)
H w w (5)
= H2[k] H2[k] 0 0 a3,3 a3,4 = Hw(2,1) Th(2,2)
_ 11(2). [K - lc] Ife2)"[K - k] 0 0 a4,3 a"
c
-X1 [k]=ii .2) (6)
w
Vklo,) -110 si [k]
s2[ki
and
[k
;2 [k ]= HVi ,( Hv2,1) (7)
s2 [k]
where -sõ,[k]= [kl,[K -1(]]7.
for the m-th transmit symbol and
-x.[k]=[-xõ,[k],-;õ,[K -k]]T is the receive symbol vector for user m.
At the receive side, to estimate the transmit symbol vector -s.[k], user
m employs ZF filter and the estimated symbol vector is given by
H H
i(mzFlk1=[(11 w(mmt H I I w
m,@"))-1 (''')11-x,n[k] (8)
While the ZF filter is the easiest to understand, the receiver may apply
any number of other filters known to those skilled in the art. One popular
choice
is the MMSE filter where
H H _
i(MMsE)[kl= (H ,v(")t + p-10-1H,v(")H}v(")tx.[k] (9)
and p is the signal-to-noise ratio. Alternatively, the receiver may perform a
maximum likelihood symbol detection (or sphere decoder or iterative
variation).
For example, the first user might use the ML receiver and solve the following
optimization
Filed Via EFS-Web
6181P515X
234
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCIMS2013/039580
=
in,00-)[ki= II
arg min IF [k]¨ Lik,t) wo,2) ][sl[k1111 (10)
s,,s,es S2 [k]
where S is the set of all possible vectors s and depends on the constellation
size.
The ML receiver gives better performance at the expense of requiring more
complexity at the receiver. A similar set of equations applies for the second
user.
001951 Note that H(1,2) and Hµ(.2.1)in (6) and (7) are
assumed to have zero
entries. This assumption holds only if the transmit precoder is able to cancel
completely
I I
the inter-user interference as for the criterion in (4 12,2) are
). Similarly, H.0,1) and H
diagonal matrices only if the transmit precoder is able to cancel completely
the inter-
carrier interference (i.e., from the mirror tones).
1001961 Figure 13 illustrates one embodiment of a framework
for DIDO-
OFDM systems with I/Q compensation including IQ-DIDO precoder 1302 within a
Base Station (BS), a transmission channel 1304, channel estimation logic 1306
within a user device, and a ZF, MMSE or ML receiver 1308. The channel
estimation logic 1306 estimates the channels H,fm) and 1-/-) via training
symbols
and feedbacks these estimates to the precoder 1302 within the AP. The BS
computes the DIDO precoder weights (matrix W) to pre-cancel the interference
due to I/Q gain and phase imbalance as well as inter-user interference and
transmits the data to the users through the wireless channel 1304. User device
m employs the ZF, MMSE or ML receiver 1308, by exploiting the channel
estimates provided by the unit 1304, to cancel residual interference and
demodulates the data.
Filed Via EFS-Web
6181P515X
235
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
=
1001971 The following three embodiments may be employed to
implement this I/Q compensation algorithm:
Method 1 - TX compensation: In this embodiment, the transmitter
calculates the pre-coding matrix according to the criterion in (4). At the
receiver,
the user devices employ a "simplified" ZF receiver, where fiwo,') and I
,(v2.2) are
assumed to be diagonal matrices. Hence, equation (8) simplifies as
1/ a,, 0 1_
x. [k]. (10)
0 1/a.,,
Method 2 - FtX compensation: In this embodiment, the transmitter
calculates the pre-coding matrix based on the conventional BD method described
in R. Chen, R. W. Heath, and J. G. Andrews, "Transmit selection diversity for
unitary precoded multiuser spatial multiplexing systems with linear
receivers,"
accepted to IEEE Trans. on Signal Processing, 2005, without canceling inter-
carrier and inter-user interference as for the criterion in (4). With this
method, the
pre-coding matrix in (2) and (3) simplifies as
w11 [k] 0 w1,2[k] 0
0 wi*,i[K¨k] 0 w,',2[K¨k]
W= . (12)
14)2[k] 0 w2,2[k] 0
0 v4,1 [K ¨ k] 0 14,2[K k]
At the receiver, the user devices employ a ZF filter as in (8). Note that this
method does not pre-cancel the interference at the transmitter as in the
method 1 above. Hence, it cancels the inter-carrier interference at the
receiver, but it is not able to cancel the inter-user interference. Moreover,
in
Filed Via EFS-Web
61B1P515X
236
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
=
H
method 2 the users only need to feedback the vector H,(-) for the transmitter
to compute the DIDO precoder, as opposed to method 1 that requires
H H
feedback of both lin.) and Hc(m). Therefore, method 2 is particularly suitable
for DIDO systems with low rate feedback channels. On the other hand,
method 2 requires slightly higher computational complexity at the user device
to compute the ZF receiver in (8) rather than (11).
Method 3 - TX-FtX compensation: In one embodiment, the two methods
described above are combined. The transmitter calculates the pre-coding matrix
as in (4) and the receivers estimate the transmit symbols according to (8).
1001981 I/Q imbalance, whether phase imbalance, gain
imbalance, or delay
imbalance, creates a deleterious degradation in signal quality in wireless
communication systems. For this reason, circuit hardware in the past was
designed to have very low imbalance. As described above, however, it is
possible to correct this problem using digital signal processing in the form
of
transmit pre-coding and/or a special receiver. One embodiment of the invention
comprises a system with several new functional units, each of which is
important
for the implementation of I/Q correction in an OFDM communication system or a
DIDO-OFDM communication system.
1001991 One embodiment of the invention uses pre-coding
based on
channel state information to cancel inter-carrier interference (ICI) from
mirror
tones (due to I/Q mismatch) in an OFDM system. As illustrated in Figure 11, a
DIDO transmitter according to this embodiment includes a user selector unit
Filed Via EFS-Web
6181P515X
237
CA 2872502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
0 WO 2013/166464
PCT/US2013/039580
=
1102, a plurality of coding modulation units 1104, a corresponding plurality
of
mapping units 1106, a DIDO IQ-aware precoding unit 1108, a plurality of RF
transmitter units 1114, a user feedback unit 1112 and a DIDO configurator unit
1110.
[00200] The user selector unit 1102 selects data
associated with a
plurality of users Ul-UM, based on the feedback information obtained by the
feedback unit 1112, and provides this information each of the plurality of
coding
modulation units 1104. Each coding modulation unit 1104 encodes and
modulates the information bits of each user and send them to the mapping unit
1106. The mapping unit 1106 maps the input bits to complex symbols and sends
the results to the DIDO IQ-aware precoding unit 1108. The DIDO IQ-aware
precoding unit 1108 exploits the channel state information obtained by the
feedback unit 1112 from tk users to compute the DIDO IQ-aware precoding
weights and precoding the input symbols obtained from the mapping units 1106.
Each of the precoded data streams is sent by the DIDO IQ-aware precoding unit
1108 to the OFDM unit 1115 that computes the IFFT and adds the cyclic prefix.
This information is sent to the D/A unit 1116 that operates the digital to
analog
conversion and send it to the RF unit 1114. The RF unit 1114 upconverts the
baseband signal to intermediate/radio frequency and send it to the transmit
antenna.
[00201] The precoder operates on the regular and mirror
tones together
for the purpose cf compensating for I/Q imbalance. Any number of precoder
Filed Via EFS-Web
6181P515X
238
SUBSTITUTE SHEET (RULE 26)
CA 2872 502 2 020-0 3-0 6
=
WO 2013/166464 PCT/US2013/039580
=
design criteria may be used including ZF, MMSE, or weighted MMSE design. In a
preferred embodiment, the precoder completely removes the ICI due to I/Q
mismatch thus resulting in the receiver not having to perform any additional
compensation.
[00202] In one embodiment, the precoder uses a block
diagonalization
criterion to completeiy cancel inter-user interference while not completely
canceling the I/Q effects for each user, requiring additional receiver
processing.
In another embodiment, the precoder uses a zero-forcing criterion to
completely
cancel both inter-user interference and ICI due to I/Q imbalance. This
embodiment can use a conventional DIDO-OFDM processor at the receiver.
100203] One embodiment of the invention uses pre-coding
based on
channel state information to cancel inter-carrier interference (ICI) from
mirror
tones (due to I/Q mismatch) ,n a DIDO-OFDM system and each user employs an
IQ-aware DIDO receiver. As illustrated in Figure 12, in one embodiment of the
invention, a system including the receiver 1202 includes a plurality of RF
units
1208, a corresponding plurality of ND units 1210, an IQ-aware channel
estimator
unit 1204 and a DIDO feedback generator unit 1206.
1002041 The RF units 1208 receive signals transmitted from
the DIDO
transmitter units 1,14, downconverts the signals to baseband and provide the
downconverted signals to the AJD units 1210. The ND units 1210 then convert
the signal from analog to digital and send it to the OFDM units 1213. The OFDM
units 1213 remove the cyclic prefix and operates the FFT to report the signal
to
Filed Via EFS-Web
6181P515X
239
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
=
the frequency domain. During the training period the OFDM units 1213 send the
output to the IQ-aware channel estimate unit 1204 that computes the channel
estimates in the frequency domain. Alternatively, the channel estimates can be
computed in the time domain. During the data period the OFDM units 1213 send
the output to the IQ-aware receiver unit 1202. The IQ-aware receiver unit 1202
computes the IQ receiver and demodulates/decodes the signal to obtain the data
1214. The 10-aware channel estimate unit 1204 sends the channel estimates to
the DID feedback generator unit 1206 that may quantize the channel estimates
and send it back to the transmitter via the feedback control channel 1112.
[00205] The receiver 1202 illustrated in Figure 12 may
operate under
any number of criteria known to those skilled in the art including ZF, MMSE,
maximum likelihood, or MAP receiver. In one preferred embodiment, the receiver
uses an MMSE filter to cancel the ICI caused by IQ imbalance on the mirror
tones. In another preferred embodiment, the receiver uses a nonlinear detector
like a maximum likelihood search to jointly detect the symbols on the mirror
tones. This method has improved performance at the expense of higher
complexity.
[00206] In one embodiment, an IQ-aware channel estimator
1204 is used
to determine the receiver coefficients to remove ICI. Consequently we claim a
DIDO-OFDM system that uses pre-coding based on channel state information to
cancel inter-carrier interference (ICI) from mirror tones (due to I/Q
mismatch), an
IQ-aware DIDO receiver, and an IQ-aware channel estimator. The channel
Filed Via EFS-Web
6181P515X
240
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCT/US2013/039580
0
estimator may use a conventional training signal or may use specially
constructed training signals sent on the inphase and quadrature signals. Any
number of estimation algorithms may be implemented including least squares,
MMSE, or maximum likelihood. The IQ-aware channel estimator provides an
input for the IQ-aware receiver.
[00207] Channel state information can be provided to the
station through
channel reciprocity or through a feedback channel. One embodiment of the
invention comprises a DIDO-OFDM system, with I/Q-aware precoder, with an
I/Q-aware feedback channel for conveying channel state information from the
user terminals to the station. The feedback channel may be a physical or
logical
control channel. It may be dedicated or shared, as in a random access channel.
The feedback information may be generated using a DIDO feedback generator at
the user terminal, which we also claim. The DIDO feedback generator takes as
an input the output of the I/Q aware channel estimator. It may quantize the
channel coefficients or may use any number of limited feedback algorithms
known in the art.
[00208] The allocation of users, modulation and coding
rate, mapping to
space-time-frequency code slots may change depending on the results of the
DIDO feedback generator. Thus, one embodiment comprises an IQ-aware DIDO
configurator that uses an IQ-aware channel estimate from one or more users to
configure the DIDO IQ-aware precoder, choose the modulation rate, coding rate,
Filed Via EFS-Web
6181P515X
241
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCMJS2013/039580
subset of users allowed to transmit, and their mappings to space-time-
frequency
code slots.
[00209] To evaluate the performance of the proposed compensation
methods, three DIDO 2 x 2 systems will be compared:
1. With I/Q mismatch: transmit over all the tones (except DC and edge
tones), without compensation for I/Q mismatch;
2. With I/Q compensation: transmit over all the tones and compensate
for I/Q mismatch by using the "method 1" described above;
3. Ideal: transmit data only over the odd tones to avoid inter-user and
inter-carrier (i.e., from the mirror tones) interference caused to I/O
mismatch.
[00210] Hereafter, results obtained from measurements with the DIDO-
OFDM prototype in real propagation scenarios are presented. Figure 14 depicts
the 64-QAM constellations obtained from the three systems described above.
These constellations are obtained with the same users' locations and fixed
average signal-to-noise ratio (-45 dB). The first constellation 1401 is very
noisy
due to interference from the mirror tones caused by I/O imbalance. The second
constellation 1402 shows some improvements due to I/O compensations. Note
that the second constellation 1402 is not as clean as the ideal case shown as
constellation 1403 due to possible phase noise that yields inter-carrier
interference (ICI).
Filed Via EFS-Web
6181P515X
242
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
=
WO 20131166464 PCT/US2013/039580
=
[00211] Figure 15 shows the average SER (Symbol Error
Rate) 1501
and per-user goodput 1502 performance of DIDO 2x2 systems with 64-QAM and
coding rate 3/4, with and without I/Q mismatch. The OFDM bandwidth is 250
KHz, with 64 tones and cyclic prefix length 4p.4 Since in the ideal case we
transmit data only over a subset of tones, SER and goodput performance is
evaluated as a function of the average per-tone transmit power (rather than
total
transmit power) to guarantee a fair comparison across different cases.
Moreover,
in the following results, we use normalized values of transmit power
(expressed
in decibel), since our goal here is to compare the relative (rather than
absolute)
performance of different schemes. Figure 15 shows that in presence of I/Q
imbalance the SER saturates, without reaching the target SER (¨ 10-2),
consistently to the results reported in A. Tarighat and A. H. Sayed, "MIMO
OFDM
receivers for systems with IQ imbalances," IEEE Trans. Sig. Proc., vol. 53,
pp.
3583-3596, Sep. 2005. This saturation effect is due to the fact that both
signal
and interference (from the mirror tones) power increase as the TX power
increases. Through the proposed I/Q compensation method, however, it is
possible to cancel the interference and obtain better SER performance. Note
that
the slight increase in SER at high SNR is due to amplitude saturation effects
in
the DAC, due to the larger transmit power required for 64-QAM modulations.
[00212] Moreover, observe that the SER performance with
I/Q
compensation is very close to the ideal case. The 2 dB gap in TX power
between these two cases is due to possible phase noise that yields additional
interference between adjacent OFDM tones. Finally, the goodput curves 1502
Filed Via EFS-Web
6181P515X
243
CA 2872 502 2 020-0 3-0 6 SUBSTITUTE SHEET (RULE 26)
1. WO 2013/166464
PCMTS2013/039580
=
show that it is possible to transmit twice as much data when the I/Q method is
applied compared to the ideal case, since we use all the data tones rather
than
only the odd tones (as for the ideal case).
[00213] Figure 16 graphs the SER performance of different
QAM
constellations with and without I/Q compensation. We observe that, in this
embodiment, the proposed method is particularly beneficial for 64-QAM
constellations. For 4-QAM and 16-QAM the method for I/O compensation yields
worse performance than the case with I/Q mismatch, possibly because the
proP sed method requires larger power to enable both data transmission and
interference cancellation from the mirror tones. Moreover, 4-QAM and 16-QAM
are not as affected by I/Q mismatch as 64-QAM due to the larger minimum
distance between constellation points. See A. Tarighat, R. Bagheri, and A. H.
Sayed, "Compensation schemes and performance analysis of IQ imbalances in
OFDM receivers," IEEE Transactions on Signal Processing, vol. 53, pp. 3257-
3268, Aug. 2005. This can be also observed in Figure 16 by comparing the I/Q
mismatch against the ideal case for 4-QAM and 16-QAM. Hence, the additional
power required by the DIDO precoder with interference cancellation (from the
mirror tones) does not justify the small benefit of the I/Q compensation for
the
cases of 4-QAM and 16-QAM. Note that this issue may be fixed by employing
the methods 2 and 3 for I/Q compensation described above.
[00214] Finally, the relative SER performance of the three
methods
described above is measured in different propagation conditions. For
reference,
Filed Via EFS-Web
6181P515X
244
CA 28 7 250 2 2 020 -0 3-0 6 SUBSTITUTE SHEET (RULE 26)
=
WO 2013/166464 PCMJS2013/039580
0
also described is the SER performance in presence of I/O mismatch. Figure 17
depicts the SER measured for a DIDO 2 x 2 system with 64-QAM at carrier
frequency of 450.5 MHz and bandwidth of 250 KHz, at two different users'
locations. In Location 1 the users are ¨6A from the BS in different rooms and
NLOS (Non-Line of Sight)) conditions. In Location 2 the users are ¨A from the
BS in LOS (Line of Sight).
[00215] Figure 17 shows that all three compensation
methods always
outperform the case of no compensation. Moreover, it should be noted that
method 3 outperforms the other two compensation methods in any channel
scenario. The relative performance of method 1 and 2 depends on the
propagation conditions. It is observed through practical measurement
campaigns that method 1 generally outperforms method 2, since it pre-cancels
(at the transmitter) the inter-user interference caused by I/Q imbalance. When
this inter-user interference is minimal, method 2 may outperform method 1 as
illustrated in graph 1702 of Figure 17, since it does not suffer from power
loss
due to the I/Q compensation precoder.
[00216] So far, different methods have been compared by
considering only
a limited set of propagation scenarios as in Figure 17. Hereafter, the
relative
performance of these methods in ideal i.i.d.(independent and identically-
distributed) channels is measured. DIDO-OFDM systems are simulated with I/Q
phase and gain imbalance at the transmit and receive sides. Figure 18 shows
the performance of the proposed methods with only gain imbalance at the
Filed Via EFS-Web
6181P515X
245
CA 2872502 2020-03-06 SUBSTITUTE SHEET (RULE 26)
WO 2013/166464
PCT/US2013/039580
=
transmit side (i.e., with 0.8 gain on the I rail of the first transmit chain
and gain 1
on the other rails). It is observed that method 3 outperforms all the other
methods. Also, method 1 performs better than method 2 in i.i.d. channels, as
opposed to the results obtained in Location 2 in graph 1702 of Figure 17.
[00217] Thus, given the three novel methods to compensate
for I/Q
imbalance in DIDO-OFDM systems described above, Method 3 outperforms the
other proposed compensation methods. In systems with low rate feedback
channels, method 2 can be used to reduce the amount of feedback required for
the DIDO precoder, at the expense of worse SER performance.
II. Adaptive DIDO Transmission Scheme
[00218] Another embodiment of a system and method to
enhance
the performance of distributed-input distributed-output (DIDO) systems will
now
be described. This method dynamically allocates the wireless resources to
different user devices, by tracking the changing channel conditions, to
increase
throughput while satisfying certain target error rate. The user devices
estimate
the channel quality and feedback it to the Base Station (BS); the Base Station
processes the channel quality obtained from the user devices to select the
best
set of user devices, DIDO scheme, modulation/coding scheme (MCS) and array
configuration for the next transmission; the Base Station transmits parallel
data to
multiple user devices via pre-coding and the signals are demodulated at the
receiver.
Filed Via EFS-Web
6181P515X
246
CA 2872502 2 020 -0 3 -0 6 SUBSTITUTE SHEET (RULE 26)
DEMANDES OU BREVETS VOLUMINEUX
LA PRESENTE PARTIE DE CETTE DEMANDE OU CE BREVETS
= COMPREND PLUS D'UN TOME.
CECI EST LE TOME 1 DE 2
NOTE: Pour les tomes additionels, veillez contacter le Bureau Canadien des
Brevets.
JUMBO APPLICATIONS / PATENTS
THIS SECTION OF THE APPLICATION / PATENT CONTAINS MORE
THAN ONE VOLUME.
THIS IS VOLUME 1 OF 2
NOTE: For additional volumes please contact the Canadian Patent Office.
