Note: Descriptions are shown in the official language in which they were submitted.
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INTERFERENCE SUPPRESSION IN CDMA SYSTEMS
DES CRIPTION
TECHNICAL FIELD:
The invention relates to Code-Division Multiple Access (CDMA) communications
systems, which may be terrestrial or satellite systems, and in particular to
interference
suppression in CDMA communications systems.
BACKGROUND ART:
Code-Division Multiple Access communications systems are well known. For a
general discussion of such systems, the reader is directed to a paper entitled
"Multiuser
Detection for CDMA Systems" by Duel-Hallen, Holtzman and Zvonar, IEEE Personal
Communications, pp.46-58, April 1995.
In CDMA systems, the signals from different users all use the same bandwidth,
so each user's signal constitutes noise or interference for the other users.
On the uplink
(transmissions from the mobiles) the interference is mainly that from other
transmitting
mobiles. Power control attempts to maintain the received powers at values that
balance
the interference observed by the various mobiles, but, in many cases, cannot
deal
satisfactorily with excessive interference. Where mobiles with different
transmission
rates are supported within the same cells, the high-rate mobiles manifest
strong
interference to the low-rate mobiles. On the downlink (transmission towards
the
mobiles) transmissions from base-stations of other cells as well as strong
interference
from the same base-station to other mobiles may result in strong interference
to the
intended signal. Downlink power control may be imprecise or absent altogether.
In all
these so called near-far problem cases, the transmission quality can be
improved, or the
transmitted power reduced, by reducing the interference. In turn, for the same
transmission quality, the number of calls supported within the cell may be
increased,
resulting in improved spectrum utilization.
Power control is presently used to minimize the near-far problem, but with
limited success. It requires a large number of power control updates,
typically 800 times
per second, to reduce the power mismatch between the lower-rate and higher-
rate users.
It is desirable to reduce the number of communications involved in such power
control
systems, since they constitute overhead and reduce overall transmission
efficiencies.
Nevertheless, it is expected that future CDMA applications will require even
tighter
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power control with twice the number of updates, yet the near-far problem will
not be
completely eliminated. It is preferable to improve the interference
suppression without
increasing the number of transmissions by the power control system.
Multiuser detectors achieve interference suppression to provide potential
benefits
to CDMA systems such as improvement in capacity and reduced precision
requirements
for power control. However, none of these detectors is cost-effective to build
with
significant enough performance advantage over present day systems. For
example, the
complexity of the optimal maximum likelihood sequence detector (MLSD) is
exponential
in the number of interfering signals to be cancelled, which makes its
implementation
excessively complex. Alternative suboptimal detectors fall into two groups:
linear and
subtractive. The linear detectors include decorrelators, as disclosed by K.S.
Schneider,
"Optimum detection of code division multiplexed signals", IEEE Trans. on
Aerospace
and Electronic Systems, vol. 15, pp. 181-185, January 1979 and R. Kohno, M.
Hatori,
and H. Imai, "Cancellation techniques of co-channel interference in
asynchronous spread
spectrum multiple access systems", Electronics and Communications in Japan,
vol.
66-A, no. 5, pp. 20-29, 1983. A disadvantage of such decorrelators is that
they cause
noise enhancement.
Z. Xie, R.T. Short, and C.K. Rushforth, "A family of suboptimum detectors for
coherent multiuser communications", IEEE Journal on Selected Areas in
Communications, vol. 8, no. 4, pp. 683-690, May 1990, disclosed the minimum
mean
square error linear (MMSE) detector, but such detectors are sensitive to
channel and
power estimation errors. In both cases, the processing burden still appears to
present
implementation difficulties.
Subtractive interference cancellation detectors take the form of successive
interference cancellers (SIC), as disclosed by R. Kohno et al, "Combination of
an
adaptive array antenna and a canceller of interference for direct-sequence
spread-spectrum multiple-access system", IEEE Journal on Selected Areas in
Communications, vol. 8, no. 4, pp. 675-682, May 1990, and parallel
interference
cancellers (PIC) as disclosed by M.K. Varanasi and B. Aazhang, "Multistage
detection
in asynchronous code-division multiple-access communications", IEEE Trams. on
Communications, vol. 38, no. 4, pp. 509-519, April 1990, and R. Kohno et al,
"Combination of an adaptive array antenna and a canceller of interference for
direct-sequence spread-spectrum multiple-access system", IEEE Journal on
Selected
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Areas in Communications, vol. 8, no. 4, pp. 675-682, May 1990. Both SIC
detectors
and PIC detectors require mufti-stage processing and the interference
cancellation
achieved is limited by the amount of delay or complexity tolerated. These
detectors are
also very sensitive to channel, power and data estimation errors.
One particular subtractive technique was disclosed by Shimon Moshavi in a
paper
entitled "Mufti-User Detection for DS-CDMA Communications", IEEE
Communications
Magazine, pp. 124-136, October 1996. Figure 5 of Moshavi's paper shows a
subtractive
interference cancellation (SIC) scheme in which the signal for a particular
user is
extracted in the usual way using a matched filter and then spread again using
the same
spreading code for that particular user, i.e., the spreading code used to
encode the signal
at the remote transmitter. The spread-again signal then is subtracted from the
signal
received from the antenna and the resulting signal is applied to the next
user's
despreader. This process is repeated for each successive despreader. Moshavi
discloses
a parallel version that uses similar principles.
A disadvantage of this approach is its sensitivity to the data and power
estimates,
i. e. , their accuracy and the sign of the data. A wrong decision will result
in the
interference component being added rather than subtracted, which will have
totally the
wrong effect.
For more information about these techniques, the reader is directed to a paper
by
P. Patel and J. Holtzman entitled "Analysis of a Simple Successive
Interference
Cancellation Scheme in a DS/CDMA System", IEEE Journal on Selected Areas in
Communications, Vol. 12, No. 5, pp. 796-807, June 1994.
In a paper entitled "A New Receiver Structure for Asynchronous CDMA: STAR
The Spatio-Temporal Array-Receiver" , IEEE Transaction on Selected Areas in
Communications, Vol. 16, No. 8, October 1998, S. Affes and P. Mermelstein (two
of
the present inventors), disclosed a technique for improving reception despite
near/far
effects and mufti-user interference. In contrast to known systems in which the
spread-
again signal is supplied to the input of the despreader of the channel to be
corrected,
Affes' and Mermelstein's proposed system treated all of the users' signals
together and
processed them as a combined noise signal. If the components of the received
signal
from the different users all had equal power, or substantially equal power,
this process
would be optimal. In practice, however, there will be significant differences
between
the power levels at which the different users' signals are received at the
base station
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antenna. The same applies to the downlink. For example, a data user may
generate
much more power than a voice user simply because of the more dense information
content of the data signal. Also, imperfect power control will result in power
differences, i.e., channel variations may result in received powers different
from their
intended values, despite the best effort of the power-control process to
equalize them.
DISCLOSURE OF INVENTION:
The present invention addresses the need for improved interference suppression
without the number of transmissions by the power control system being
increased, and,
to this end, provides a receiver for a CDMA communications system in which
selective
multiuser detection is employed in combination with interference subspace
rejection to
obtain a substantially unity response for a propagation channel via which a
corresponding
user's signal was received and a substantially null response to interference
components
from selected signals of other user stations.
According to the present invention, there is provided a receiver for a CDMA
communications system in which a plurality of user stations communicate with a
base
station having a reception antenna, each of the user stations having spreading
means for
using a spreading code unique to that station to spread a corresponding one of
a plurality
of user signals and for transmitting the spread user signals to the base
station via a
propagation channel unique to that user station. The receiver comprises a
plurality of
receiver modules for receiving from the antenna an observation signal vector
comprising
a plurality of spread data vectors corresponding to the signals from the
different user
stations received by the reception antenna, the receiver modules being
arranged to
process the observation signal vector to produce a plurality of output
signals,
respectively, corresponding to the plurality of user signals, respectively.
The receiver
modules comprise a first group of receiver modules for processing spread data
vectors
from user stations whose signals constitute strong interference to signals of
other user
stations, and a second group of receiver modules for processing spread data
vectors from
said other user stations. Each of the receiver modules in the first group
comprises means
for providing coefficients representing channel characteristics of the
associated
propagation channel, a spreader for spreading symbols of the output signal and
channel
replication means having coefficients corresponding to the channel
characteristics for
filtering the spread symbols to produce a re-spread signal, corresponding to
the spread
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data vector for the corresponding user signal in the observation vector, and
supplying the
re-spread signal to each of the receiver modules of the second group. Each of
the
receiver modules of the second group comprises a first despreader for
extracting from
the observation vector a despread data vector for the corresponding user
signal and
supply the despread data vector to a beamformer, means for providing
coefficients
representing channel characteristics of the associated propagation channel, a
second
despreader for despreading the re-spread signals from the receiver modules of
the first
group to produce interference vectors and for supplying the interference
vectors to the
beamformer. The beamformer has coefficients adjustable by the interference
vectors and
the channel coefficients and employs selective multiuser detection (SMD) and
interference subspace rejection (ISR) to process the despread data vectors and
produce
user signal component estimates. The arrangement is such that, during
successive
symbol periods, the beamformer coefficients are adjusted so as to tune the
beamformer
for substantially unity response for the spread data vector and a
substantially null
response to interference components corresponding to the user signals of the
receivers
of the first group. Each receiver module further comprises means responsive to
the
output of the corresponding beamformer for providing estimates of the symbols
of the
corresponding user signal.
Embodiments of the invention may employ one of several alternative modes of
implementing interference subspace rejection (ISR). In a first embodiment,
using a first
mode conveniently designated ISR-TR, each receiver module in the first group
generates
its re-spread signal taking into account the amplitude and sign of the symbol
and the
channel characteristics. The re-spread signals from all of the receiver
modules of the
first group are summed to produce a total realization which is supplied to all
of the
receiver modules in the second group.
Whereas, in ISR-TR embodiments, just one null constraint is dedicated to the
sum, in a second embodiment, which uses a second mode conveniently designated
ISR-R, estimated realisations of all the interferers are used, and a null
constraint is
dedicated to each interference vector. In this second embodiment, in each
receiver
module of the first group, the symbols spread by the spreader comprise
estimated
realisations of the symbols of the output signal and each receiver module of
the second
group further comprises delay means for delaying symbols of the despread data
vectors
before their application to the beamformer. Thus, the receiver module
estimates
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separately the contribution to the interference from each unwanted
(interfering) user and
cancels it by a dedicated null-constraint in the minti-source spatio-temporal
beamformer.
In most cases, estimation of the interference requires estimates of the past,
present and
future data symbols transmitted from the interferers, in which case the
receiver requires
a maximum delay of one symbol and one processing cycle for the lower-rate or
weak
users and, at most a single null constraint per interferes.
In a third embodiment using a third mode conveniently designated ISR-H because
it implements null-responses in beamforming over all possible realisations of
the
interference, without any delay, each receiver module of the first group
further
comprises means for supplying to the spreader possible values of the instant
symbols of
the output signal and the spreader supplies a corresponding plurality of re-
spread signals
to each of the receiver modules of the second group. In each receiver module
of the
second group, the despreader despreads the plurality of re-spread signals and
supplies
corresponding despread vectors to the beamformer. This embodiment suppresses
any
sensitivity to data estimation errors and, in most cases, requires a maximum
of 3 null
constraints per interferes.
In a fourth embodiment using a fourth mode conveniently designated ISR-RH
because it uses the past and present interference symbol estimates, in each
receiver
module of the first group, the spreader spreads the symbols of the output
signal itself and
each receiver of the second group further comprises delay means for delaying
the
despread data vector from the first despreader by a period equivalent to the
time taken
to process interference data of the present block to provide its symbol
estimate before
its application to the beamformer. The beamformer then implements null-
responses over
reduced possibilities/hypotheses of the interference realization.
Conveniently, the output
of the first despreader will be delayed slightly before application to the
beamformer, to
allow time for estimation of the interferer's symbol. In most cases, the
beamformer will
provide a maximum of 2 null constraints per interferes.
In any embodiments of the invention, the channel identification unit may
generate
the set of channel coefficients in dependence upon the extracted despread data
vectors
and the user signal component estimate.
Where the reception antenna comprises only one antenna element, the beamformer
unit may comprise a temporal processor only.
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Where the reception antenna comprises a plurality of antenna elements,
however,
the beamformer unit may comprise a spatio-temporal processor, such as a filter
which
has coefficients tuned by the estimated interference signals. Over a number of
symbol
periods, the spatio-temporal filter is tuned to a unity response for the
propagation channel
via which the user's signal was received (tuning out the interference
components from
all the channels received with the current channel's signal).
Preferably, not all of the channels will extract an interference signal and
feed it
back to the other channels. In practice, the stronger interference signals
will be selected
and their feedback estimate signals fed to the beamformer units of the other
channels for
suppression of the corresponding interference components.
Of course, that does not preclude having all channels feed their interference
components to all other channels.
The foregoing and other objects, features, aspects and advantages of the
present
invention will become more apparent from the following detailed description,
in
conjunction with the accompanying drawings, of preferred embodiments of the
invention.
BRIEF DESCRIPTION OF THE DRAWINGS:
Figure 1 is a schematic diagram illustrating a portion of a CDMA
communications system comprising a plurality of user stations, typically
mobile, and a
base station having a reception antenna comprising an array of antenna
elements, and
illustrates multipath communication between one of the user stations and the
array of
antennas;
Figure 2 is a simplified schematic diagram representing a model of the part of
the
system illustrated in Figure 1;
Figure 3 is a simplified block schematic diagram of a base station receiver;
Figure 4 is a simplified schematic block diagram of a first embodiment of the
present invention, namely a receiver employing selective multiuser detection
and
interference subspace rejection based upon total realization of interference
(ISR-TR);
Figure 5 is a simplified schematic block diagram of a second embodiment of the
present invention, namely a receiver employing selective multiuser detection
and
interference subspace rejection based upon individual realisations of the
interferers (ISR-
R);
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Figure 6 is a simplified schematic block diagram of a third embodiment of the
present invention, namely a receiver employing selective multiuser detection
and
interference subspace rejection based upon hypothetical values of the symbols
(ISR-H);
Figures 7 and 8 illustrate bit sequences g'(t), gz(t) and g3(t) generated in
the
receiver of Figure 6; and
Figure 9 is a simplified schematic block diagram of a fourth embodiment of the
present invention, namely a receiver employing selective multiuser detection
and
interference subspace rejection based upon reduced hypotheses (ISR-RH).
BEST MODES) FOR CARRYING OUT THE INVENTION:
In the following description, identical or similar items in the different
Figures
have the same reference numerals.
The description refers to several published articles. For convenience, the
articles
are cited in full in a numbered list at the end of the description and cited
by that number
in the description itself. The contents of these articles are incorporated
herein by
reference and the reader is directed to them for reference.
Figures l and 2 illustrate the uplink of a typical asynchronous cellular CDMA
system wherein a plurality of mobile stations 10'... l0U communicate with a
base-station
11 equipped with a receiving antenna comprising an array of several antenna
elements
12'...12M. For clarity of depiction, and to facilitate the following detailed
description,
Figures 1 and 2 illustrate only five of a large number (U) of mobile stations
and
corresponding propagation channels of the typical CDMA system, one for each of
a
corresponding plurality of users. It will be appreciated that the mobile
stations 10'...10°
will each comprise other circuitry for processing the user input signals, but,
for clarity
of depiction, only the spreaders are shown in Figure 2. The "other circuitry
will be
known to those skilled in the art and need not be described here. Referring to
Figure
2, the mobile stations 10'... l0U comprise spreaders 13'...13°,
respectively, which spread
a plurality of digital signals b'o...bUo of a corresponding plurality of
users, respectively,
all to the same bandwidth, using spreading codes c'(t)...c°(t),
respectively. The mobile
stations 101...10° transmit the resulting user signals to the base
station 11 via channels
14'...14", respectively. The channels 14'...14'' have different response
characteristics
H'(t)...HU(t), respectively, using a suitable modulation scheme, such as
differential
binary phase shift keying (DBPSK). Each of the mobile stations 10'...10U
receives
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commands from the base station 11 to monitor the total received power, i.e,
the product
of transmitted power and that user's code and attenuation for the associated
channel and
uses the measurements to apply power control to the corresponding signals to
compensate
for the attenuation of the channel. This is represented in Figure 2 by
multipliers
15'...15" which multiply the spread signals by adjustment factors
~yi(t)...tGU(t),
respectively. The array of M omni-directional antenna elements 12'...12M at
the base
station 11 each receive all of the spread signals in common, as illustrated in
more detail
in Figure 1, for only one of the channels, designated channel 14°.
Hence, channel 14"
represents communication via as many as P paths between the single antenna of
the
associated mobile station 10° and each of the base station antenna
elements 12'...12M.
The other channels are similarly multipath.
In such a CDMA system, the signal of each of the mobile stations
10'...10°
constitutes interference for the signals of the other mobile stations. Some of
the mobile
stations, however, will, for various reasons, generate more interference than
others. One
of these "interfering" user stations and its associated channel are
illustrated in Figures
1 and 2 with their components identified by the index "i" . One of the other
"desired"
user stations and its associated channel also are illustrated and identified
by the index
"d". The significance of this grouping of "interfering" and "desired" user
stations will
be explained later.
At the base station 11, the spread data vector signals X'(t)...X"(t) from the
base
station antenna elements 12'...12M, respectively, are received simultaneously,
as
indicated by the adder 16 (Figure 2), and the resulting observation vector
X(t) is supplied
to the receiver (see Figure 3). The sum of the spread data vectors (signals)
X'(t)...XU(t)
will be subject to thermal noise. This is illustrated by the addition of a
noise signal
component N~(t) by adder 16. The noise signal N~,(t) comprises a vector,
elements of
which correspond to the noise received by the different antenna elements.
Figure 3 illustrates a spatio-temporal array receiver (STAR), as described
generally by two of the present inventors in reference 12, which is suitable
for reception
of the signal X(t) at the base station. The receiver comprises a plurality of
receiver
modules comprising a plurality of despreaders 17'...17" connected to a
plurality of
spatio-temporal array receiver (STAR) modules 18'...18°, respectively.
The received
observation vector X(t) is supplied in common to the despreaders
17'...17°, which have
respective spreading code generators (not shown) for providing spreading codes
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c'(t)...c"(t), respectively, as used by the spreaders 13'...13U of the
corresponding mobile
user stations 10'...10''. Each of the despreaders 17'...17° correlates
its spreading code
with the observation vector X(t) to extract the corresponding one of a
plurality of
despread data vectors ~n , , , ~n , The despreaders 17'. . .17" each sample
the received
5 observation vector X(t) at the chip rate, taking L samples, thereby
producing, in essence,
a set of space-time signal vectors ~1."~U each of dimension M x L. These
despread
n n
vectors ~1.,.~U are processed by the STAR modules 18'...18", respectively, to
produce
n n
symbol estimates ,,fin _",~ri for the corresponding symbols of the user
signals and power
estimates ~ ~n ~ 2... ~ ~n ~ 2 which are supplied to subsequent stages (not
shown) of the
10 receiver for processing in known manner.
The STAR modules 18'...18° all comprise the same elements, so the
construction
and operation of only one of them, STAR module 18°, will now be
described.
The STAR module 18° comprises a beamformer 19°, a channel
identification unit
20°, a decision rule unit 21° and a power estimation unit
22°. The channel identification
unit 20° is connected to the input and output, respectively, of the
beamformer 19° to
receive the despread data vectors ~n and the raw filtered despread signal
component
estimates ~ri , respectively. The channel identification unit 20°
replicates, for each
block M x L, the characteristics H~(t), in space and time, of the associated
user's
transmission channel 14°. More specifically, it uses the signals ~u and
sn to derive
n
coefficients Win, which it uses to update the coefficients of the beamformer
19" in
succeeding symbol periods. The symbol period corresponds to the data frame of
MxL
elements.
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The beamformer 19° comprises a spatio-temporal maximum ratio
combining
(MRC) filter which filters the space-time vector ~u to produce the despread
signal
n
component estimate ,fin , which it supplies to both the decision rule unit
21° and the
power estimation unit 22°. The decision-rule unit 21° outputs a
binary symbol
,fin according to the sign of the signal ~ri , The binary output signal ,&n
constitutes
the output of the decision rule unit 21° and is an estimate of the
corresponding user
signal b°o spread by spreader 13° of the corresponding user
station 10° (Figures l and 2).
The output signal sn will be differentially decoded and, possibly,
deinterleaved
and the data decoded--if the corresponding inverse operations were done before
transmission.
The power estimation unit 22° uses the raw signal component estimate
,~ri to
derive an estimate ~~n~ 2 of the power in that user's signal component sri of
the
received signal X(t) and supplies the power estimate i~n~ 2 to the subsequent
stages
(not shown) of the receiver for derivation of power level adjustment signals
in known
manner.
The receiver shown in Figure 3 will perform satisfactorily if there are no
strong
interferers, i. e. , if it can be assumed that all users transmit with the
same modulation and
at the same rate, and that the base-station knows all the spreading codes of
the terminals
with which it is communicating. On that basis, operation of the system will be
described
with reference to the user channel identified by index u. Thus, the mobile
station 10°
first differentially encodes its user's binary phase shift keyed (BPSK) bit
sequence at the
rate 1/T, where T is the bit duration, using circuitry (not shown) that is
well-known to
persons skilled in this art. Its spreader 13° then spreads the
resulting differential binary
phase shift keyed (DBPSK) sequence b"(t) by a periodic personal code c"(t) at
a rate 1/T~,
where T~ is the chip pulse duration. The processing gain is given by L=TIT.
For
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convenience, it is assumed that short codes are used, with the period of c"(t)
assumed to
be equal to the bit duration T, though the system could employ long codes, as
will be
discussed later, with other applications and assumptions. Following weighting
by the
total received power ( ~,u ( t ) ) 2, the spread signal is transmitted to the
base station 11
via channel 14°. The following description also assumes a multipath
fading environment
with P resolvable paths where the delay spread Dr is small compared to the bit
duration
(i. e. , OT ~ T) .
At time t, the observation vector X(t) received by the elements 12'...12M of
the
antenna array of the one particular cell shown in Figures 1 and 2 can be
written as
follows:
a
X ~ t~ - ~ X ° ~ t) + Ntn ~ t) (1)
a=1
where U is the total number of mobile stations whose signals are received at
the desired
base-station 11 from inside or outside the cell, X"(t) is the received signal
vector from
the mobile station 10°, i.e., of index u, and N~,(t) is the thermal
noise received at the M
antenna elements. The contribution X"(t~ of the u-th mobile station 10°
to the observation
vector X(t) is given by:
Xu~t~ =l~lu(t)H~~t~~C~~t:~.~7"~t~
(la)
=1~u(t) ~ Cip(t)Ep(t)C~~Wtb(t))~7u(t-Tp~t))
p=1
where H"(t) is the response of the channel 14° between the u-th mobile
station 10° and
the antenna array and ~ denotes time-convolution. In the right-hand term of
the above
equation, TP ~ t ) E ~ o , T] are the propagation time-delays along the P
paths, p = 1,~~~,
P, (see Figure 1), GP ( t ) are the propagation vectors and Ep ( t ) Z are the
fractions
along each path ( i , a , , ~p 1 Ep ( t ) 2 = 1 ) of the total power ,~" (t)2
received from
the u-th mobile station 10°. Estimation of the received power includes
the effects of path
CA 02293097 1999-12-23
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loss, Rayleigh fading and shadowing. It is assumed that the time-variations
of ~p ~ t ) and ~"(t~2 are very slow and locally constant relative to the bit
duration T.
In the despreader 1T', the post-correlation observation vector Zn ~ t ) of
frame
number n over the time-interval [0, ~ in successive frames of period T is
determined
as:
Zn (t) = 1 f TX(nT+anT/2+t+t~)c°(t~)dt~ (2)
T o
where an E {o ,1 } stands for a possible time-shift by T/2 to avoid, if
necessary, the
frame edges lying in the middle of the delay spread (see reference 12). For
the sake of
simplicity, it is assumed in the following that an = 0 .
As described in reference 12, after sampling at the chip rate and framing at
the
bit rate, despreader 1T' derives the post-correlation data model (PCM) as:
Zn = Hn sn + Nn (3)
where Z~ is the spatio-temporal observation matrix, Hrt is the spatio-temporal
propagation matrix, Sn =brt ~,n is the signal component and Nn is the spatio-
temporal
noise matrix. Equation 3 provides an instantaneous mixture model at the bit
rate where
the signal subspace is one-dimensional in the M x L matrix space. For
convenience,
the despreader 17" transforms the matrices Zn ~ H" and Nrt into (M x L)-
dimensional
vectors Zn, Hn and Zn, respectively, by concatenating their columns into one
spatio-temporal column vector to yield the following narrowband form of the
PCM
model (see reference 12):
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(4)
n n n n
To avoid the ambiguity due to a multiplicative factor between gn and Sn ~ the
norm
of gu is fixed to ~,
n
The PCM model eliminates inter-symbol interference. It represents an
instantaneous mixture model of a narrowband source in a one-dimensional signal
subspace and enables exploitation of low complexity narrowband processing
methods
after despreading. Processing after despreading exploits the processing gain
to reduce
the interference and to ease its cancellation in subsequent steps.
As discussed in reference 12, the spatio-temporal array-receiver (STAR) can be
used to detect each user separately at the base-station 11. This receiver is
found to
provide fast and accurate time-varying multipath acquisition and tracking.
Moreover,
it significantly improves call capacity by spatio-temporal maximum ratio
combining
(MRC) in a coherent detection scheme implemented without a pilot signal. For
the sake
of clarity, the steps of STAR that are relevant to the implementation of the
present
invention are briefly described below. For additional details, the reader is
directed to
reference 12.
As shown in Figure 3, the despreader 1'T' supplies the column vector, despread
data vector Zu, to the channel identification unit 20° and the MRC
beamformer 19°.
-n
For the mobile station 10°, assigned the index a in the cell shown in
Figures 1 and 2,
an estimate of the coefficients Hn of its channel gn is provided by STAR
receiver
module 18°, specifically by the channel identification unit 20°,
at each block iteration.
The beamformer 19° uses spatio-temporal matched filtering such that wn
= Hn~M (i.e.,
spatio-temporal maximum ratio combining), to provide estimates of signal
CA 02293097 1999-12-23
component Sn , its DBPSK bit sequence b,~ and its total received power ~,nz as
follows:
U
Sn = Real {~~n } = Real ~~n (S)
Fn = Sign {sn ~ (6)
~nz = ~ 1 - OG ) ~nZl + OG I Sari 12
where « is a smoothing factor. Second, the channel identification unit
20° updates the
channel coefficients estimate Hu by means of a decision feedback
identification (DFI)
-n
scheme whereby the signal component estimate sn for ~,n brs ~ is fed back as a
reference signal in the following eigen-subspace tracking procedure:
10 Hn+1 =Hn + ~~Ztn'Hns~n)san
where ~, is an adaptation step-size. This DFI scheme allows a 3 dB coherent
detection
gain in noise reduction by recovering the channel phase offsets within a sign
ambiguity
without a pilot. The procedure that further enhances the channel estimate H~
to
-nil
obtain Hu from the knowledge of its spatio-temporal structure (i. e. manifold)
allows
-n+1
15 a fast and accurate estimation of the multipath time-delays ~ i,n , ... ~ ~
p,n in both the
acquisition and the tracking modes (both versions of this procedure can be
found in
reference 12). This improved estimation accuracy achieves robustness to
channel
estimation errors when STAR is used in multiuser operation.
CA 02293097 1999-12-23
16
For further information about such a STAR receiver, the reader is directed to
the
articles by Affes and Mermelstein identified as references 12 and 16.
If, as was assumed in reference 12, the spatio-temporal noise vector Nu is
-n
spatially uncorrelated, power control on the uplink is generally able to
equalize the
received signal powers. However, it becomes insufficient when the power of
particular
users (e. g. , "priority links", acquisition, higher-order modulations or
higher data-rates
in mixed-rate traffic) is increased intentionally. As stated earlier, in the
present case,
it is assumed that all users employ the same modulation at the same rate.
Therefore,
among the mobile stations in the desired cell, there will be a group I of
"strong
interferers", one of which is identified in Figures 1 and 2 by index "i",
which require
a higher received power, and a second group D of other "desired" users, one of
which
is identified in Figures l and 2 by index "d", which require a regular "unit"
received
power and whose reception may be degraded by the presence of the strong
interferers.
The STAR receiver shown in Figure 3 would receive the signals from all of the
user stations independently of each other. It should be noted that there is no
cross-
connection between the receiver modules, specifically between the STAR modules
18'...18°...18°, far suppression of interference from the
signals of mobile stations which
constitute strong interferers. While the matched beamformer of Equation 5 is
optimal
in uncorrelated white noise, it is suboptimal when receiving the desired users
due to
spatial correlation of the interference terms. To allow the accommodation of
additional
users in the presence of much stronger interfering mobiles in the target cell,
the present
invention upgrades the receiver of Figure 3 to obtain much stronger near-far
resistance
by assigning the beamformer of Equation 5 to reject the interference
contributions from
the interfering users in a multiuser scheme.
Assuming the presence of NI interfering users assigned the indices i = 1 to
Nl,
then the spatio-temporal observation vector of any interfering user (u = i E
{1,...,NI})
is given from Equation 4 by:
~n ° linsn + jYn
CA 02293097 1999-12-23
17
where N~ can still be assumed as an uncorrelated white noise vector if the
processing
-n
gain of this user is not very low. (Otherwise, it is understood that one would
also apply
to any interfering mobile the coloured noise model below and the near-far
resistant
solution proposed for the desired user as described later.) On the other hand,
from the
point of view of any desired user ~ a = d ~ ~1, ... , NI ~ , the spatio-
temporal observation
vector is:
NI
~d = ~d Sn + ~d + ~ ~d. i
n n n n (1~)
i=1
+~+~d~tr
n n n
where, in addition to the uncorrelated white noise vector Nd, there is
included a
-n
random coloured spatio-temporal interference vector from each interfering
mobile station
denoted by Id.= for i = 1,...,Nl. At a frame number n, a realization of this
vector
-n
results from the chip-rate sampling, the bit-rate framing and the
matrix/vector reshaping
of the post-correlation interference vector from the i-th interfering mobile
given over the
time-interval [0, Tj by:
f T
In'1(t) - TJo X1~~T+t+t~) Cd~t~)dt~ (11)
Embodiments of the present invention provide a near-far resistant solution for
the
desired users that rejects these additional interference terms and provides
interference
suppression within a STAR receiver unit by a combination of selective mufti-
user
detection (SMD) and interference subspace rejection (ISR), as will now be
described with
reference to Figures 4 to 9. The first embodiment of the invention, the SMD-
ISR STAR
receiver illustrated in Figure 4, which (i) readily exploits the processing
gain in
interference reduction, (ii) allows accurate time-delay synchronization and
tracking of the
multipath delays, and (iii) shows inherent robustness to interference, will
now be
described. Then, for the particular case of the desired user, the way in which
the
CA 02293097 1999-12-23
18
beamforming step of STAR is modified to introduce a near-far resistant
solution based
on selective multiuser detection (SMD) will be described. Finally, efficient
alternatives
for implementing SMD by interference subspace rejection (ISR) will be
described with
reference to Figures 5, 6 and 9.
Interference Subspace Rejection over Total Realisations (ISR-TR)
In the receiver unit shown in Figure 4, the receiver modules are in two
groups,
I and D, separated by a broken line 23. Group I comprises the receiver modules
of
signals of NI strongly interfering mobile stations (one of which is identified
by index i
in Figures 1 and 2) and group D comprises the receiver modules for signals of
other,
"desired", users, one of which is identified by index d in Figures 1 and 2.
The signals
in group I also constitute "desired" user signals. Because they are so strong,
they may
not require special ISR processing to reduce interference, though that does
not preclude
it. The receiver modules of group I comprise despreaders 17"...1T'...17n'",
which are
identical to those of Figure 3 and produce a corresponding set of despread
vectors ~n".~nl~ and STAR modules 18"...18''...18INI for processing the
vectors
zn... z~' ... 'jnNl respectively, to produce the corresponding despread
signals ,&n ". ,fin ~~, ,fin I and power estimation signals ~ ~n ~ 2". ~ ~n ~
2,., ~ ~nl~ 2 , The
STAR modules 18"...18''...18IN' comprise MRC beamformers 19"...19''...19n'",
channel
identification units 20"...20''...208'", decision rule units
21"...21''...21n'", and power
estimation units 22"...22''...22Q'", respectively, which are identical to
those shown in
Figure 3 and so will not be described in detail. The group I receiver modules
of Figure
4 differ from those of Figure 3, however, in that they have spreaders
24"...24''...248'",
respectively, which spread again the signals ,fin ". Sn ~~~ ~n r from the STAR
modules
18"...18''...18", respectively, channel replication units 25"...25''...25",
and multipliers
26"...26''...26", respectively. Each of the spreaders 24"...24''...24" uses
the spreading
code for that particular channel/mobile station. Each of the spreaders
24"...24''...24IN'
and the associated one of the power estimation units 22"...22''...22" have
their outputs
, CA 02293097 1999-12-23
19
connected to respective inputs of the corresponding one of the multipliers
26I'...26''...26~, respective outputs of which are connected the inputs of the
channel
replication units 25I'...25''...25~". In operation, the re-spread symbols
.fin ... bn ... .&n I a~'e scaled by the total amplitudes ~,n ... ~,~ ", ~,M ~
respectively, and
then filtered by channel replication filter units 25I'...25''...25IN',
respectively, to produce
re-spread signals ~1 ( t) ", ~ji ( t) ." ~NI ( t) ~ respectively. It should be
noted that the
spreaders 24"...24IN', multipliers 26"...26~'I and channel filters 2S"...2SIN'
correspond
to the elements 13', 15' and 14' in the interfering user channels of Figure 2.
The
coefficients of the channel replication filter units 25"...25''...25IN' are
updated in
successive symbol periods by the channel identification units
20"...20''...20°'" using the
same coefficients H1 ( t) .., Hi ( t) ... ~.NI ( t) used to update their
respective MRC
beamformers 19"...19''...19'N', i.e., with the characteristics
I~1 ( t) ... ~i ( t) ... ~N~ ( t) corresponding to the transmission channels
14"...14''...14IN', respectively. It will be appreciated that the re-spread
signals ~1 ( t) ,., Xi ( t) ... XNI ( t) from the channel replication filter
units
25"...25''...258'", respectively, include information derived from both the
sign and the
amplitude of each symbol, and channel characteristics information, and so are
the
equivalents of the strong interferer's spread signals as received by the base
station
antenna elements 12'...12M. Hence, when summed, they approximate that portion
of the
received signal X(t). (The sum can be called total realization (TR) of the
interference.)
An adder 27 sums the re-spread signals ~1 ( t) ... Ji'~ ( t) ... ~NI ( t) and
supplies the
resulting sum; denoted by X~r ~ t ) ~ to each of the "desired" user receiver
modules of
group D where they are used to suppress the interference caused by the signals
of group
I, as will now be described. The strong interferers of group I will be
assigned to the
appropriate receiver modules based upon the usual exchange of information
during
initialization.
CA 02293097 1999-12-23
The receiver modules of group D differ from those of group I, and those shown
in Figure 3, because each includes an additional despreader and a delay and
their
beamformers each employ selective multi-user detection and interference
subspace
rejection (SMD-ISR), as will be explained later. The receiver modules of group
D are
5 identical so only one, for channel d, is shown in Figure 4 and will now be
described.
The received observation vector signal X(t) is despread by a first despreader
17° which
correlates the received observation vector signal with the spreading code
cd(t) used by
mobile station l0a to produce a despread matrix signal ~a which, as before, is
a block
n
of M x L samples, at the chip rate, with the columns concatenated. It should
be noted
10 that the despread data vector ~d from the first despreader 17a is equal
n
to gd S d + ~', tr + ~d where gd is the channel response for user station
n n n n' n
10d, sn is the signal transmitted at the outset by the mobile station l0d of
user
d, Vin, tr is the interference component present in the signal ~d as a result
of
n
interference from the signals from the other user stations 10' in Group I,
where Id,tr is
-n
15 as defined in equation 10. The value ~ is additional noise which might
comprise, for
n
example, the summation of the interference from all of the other users on the
system at
that time, as well as thermal noise. "Other users" means other than those
covered by
the channels in group I.
A delay unit 28d delays the despread signal samples ~d by one symbol period
n
20 and one processing cycle before applying the delayed block of samples ~d to
the
n-1
respective inputs of an SMD-ISR beamformer 29d and a channel identification
unit 20d
of an SMD-ISR STAR receiver module 18d', the prime signifying that it is not
identical
CA 02293097 1999-12-23
21
to the receiver modules 18d because the SMD-ISR beamformer 29° is a
modified spatio-
temporal filter unit. The channel identification unit 20d is similar to those
in Figure 3;
it replicates the characteristics of the transmission path of channel 14d and
updates the
coefficients of the SMD-ISR beamformer 29d in each bit period n with a set of
coefficients ~°'
n-1 '
The total interference vector ~ tZ ~ ~ ~ which, as previously defined, is the
sum
of the "interfering" signals of group I, is supplied to second despreader 30d
which uses
the spreading code c°(t) of spreader 13d of user station l0a to
despread it to produce an
interference estimate ~~ tr which it applies to the SMD-ISR beamformer 29d.
The
n-1
estimate ~. tr is the estimate of the interference in the despread data vector
~d caused
n-1 n
by the signals of the strong interferers of group I and comprises a vector
having the same
dimensions as the despread data vector ~d, The hat symbol (") indicates that
this is
n
an estimate of the interference vector. Hence, in addition to the vector ~d ,
the SMD-
n-1
ISR beamformer 29d receives an interference estimate ~~ rr which approximates
the
n-1
total interference in the vector ~d
n-1'
The SMD-ISR beamformer 29a filter has its coefficients updated in each symbol
period by both the coefficients ~n 1 from the channel identification unit 20d,
and the
estimate Id_~~ of the total interference realization (after despreading). [As
explained
previously, the estimate ~'~~ is the sum from i=1 to i=IVI of ~'~~1. ] The way
in
which the beamformer 29° uses these two sets of coefficients will be
described later.
, , CA 02293097 1999-12-23
22
The beamformer 29d adjusts its coefficients so that, over a period of time, it
will nullify
the corresponding interference components in the delayed despread data
vector ~n 1 received from the first despreader 17d via delay 28d. At the same
time, the
coefficients of SMD-ISR beamformer 29d will be tuned so that it has a unity
response
for the extracted signal, i.e. signal component estimate s" 1
The operation of the SMD-ISR beamformer 29d will now be described, beginning
with a description of Selective Multiuser Detection (SMD). Known mufti-user
approaches, such as those disclosed in references l and 2, usually detect each
user's
signal by joint processing of all the signals from the mobile stations in the
desired cell,
regardless of their relative interference power. In contrast, the present
invention teaches
a "selective" multiuser detection (SMD) approach in the sense that it
suppresses only the
signals from mobile stations that cause strong interference. Usually, only a
few such
"jammers" are encountered. The SMD approach allocates processing resources
where
they are most needed and saves computational complexity.
In addition, an interference subspace rejection approach is employed, which
exploits the mufti-source (i. e. , multiuser) beamforming technique taught in
reference 13
(called adaptive source-subspace and extraction technique (ASSET) and
incorporating the
tracking of a selected set of multiple moving targets). The ASSET technique,
in which
common methods of linearly constrained beamforming were generalized to
incorporate
the tracking of a selected set of moving targets, simultaneously estimates the
positions
of the selected set of sources and directs a time-adjusted unit-response
constraint to each
source to be extracted and time-adjusted null-constraints to the others. An
additional
attractive feature of the STAR receiver reported in reference 12 is that the
PCM model
of Equation 4 allows the use of simple narrowband processing techniques. The
flexibility in design of narrowband beamformers developed in reference 12 is
exploited
in STAR to implement near-far resistance by time-variable minti-source
constraints.
Accordingly, the beamformer 29d (Figure 4) of the receiver for desired user d
should
conform to the following two theoretical constraints, as taught in reference
12:
CA 02293097 1999-12-23
23
~n "Hn = 1
~n Hen, tr = ~ ( 12)
NI
where ~. tr is equal to ~. i ,
n ~ n
i=1
The first constraint guarantees a time-adjusted unit-response to the signal
from
desired user lOd, while the second stands for a time-adjusted null-constraint
over the
interference realization from the interfering users. It should be noted that
there is some
similarity between these constraints and some zero-forcing constraints in
equalization
techniques implemented by tapped-delay filtering, such as those disclosed in
references
9 and 11. However, the constraints specified above implement selective
interference
rejection by very simple narrowband beamforming.
The number of constraints (2) is usually far less than the very large number
of
degrees of freedom available for the spatio-temporal beamformer given by ML,
the
dimension of the PCM model. Therefore, a solution for the SMD scheme exists
and
implements these constraints without a noticeable enhancement of the white
noise
term pd of Equation 5. This solution is provided by the beamformer 29°
as follows:
n
NI
Seri = R2dl .~nH~n Sn +,[~nxjYn +jl7nX ~ .~n~i °' urn + Real
{l.~n"~} (13)
i=1
Implementation of the above-mentioned SMD according to the invention is
predicated upon a recognition that the post-correlation interference
vectors Id,1 . Via, i , ~a,Nr form a continuously variable interference
subspace. The
n-i " n-1 " n-1
SMD scheme requires the spatio-temporal beamformer 29d to be orthogonal to
this
subspace and hence translates into an interference subspace rejection (ISR)
approach.
CA 02293097 1999-12-23
24
Figure 4 illustrates one direct way to implement the SMD process of Equation
12
which uses estimated realisations of the spatio-temporal channel and
interference
vectors H n and j n~~ ~ respectively, and solves the corresponding set of
linear equations:
~ln H$n = 1
~a Hld, tr = 0 ~ ~ 14)
~d Kid, tr ~ ~
n n n n
This first mode is referred to as interference subspace rejection over total
realisations
(ISR-TR) because it uses the sum of estimates of realisations of the
interference vectors,
the necessary delay being provided by delay 28d. For a = d in Equation 5, the
beamformer 29d of the desired user d that directly implements the above
constraints is
then given by:
~n = Cn (C~n " Cn ~ -1 R ( 15)
where cn is an ML x 2 constraint matrix:
C" d = [ ~d Via, tr ~ ( 16)
n n
and R is a two-dimensional response vector:
R = [1, 0 ] T (17)
In Equation 16, the estimate of the channel vector Hd of the desired user d is
-n
given by Equation 8 with a = d. The estimate of each spatio-temporal
interference
vector jn.i conveniently is obtained from the chip-rate sampling, bit-rate
framing and
matrix/vector reshaping of the estimate ~e ~ t ~ of the post-correlation
interference
vector In~~ ~t~ in Equation 11, as follows:
CA 02293097 1999-12-23
~n.i ( t) = T ~oT'~l (12T + t +t~) C d ( t~) dt~ (18)
This estimate is obtained by despreading with the spreading sequence of the
desired user
of the reconstructed received signal vector X~ ~ t ) from the i-th interferer
given by:
~1(t) _~''~(t)l~=(t> ~.~~(t)C1(t) (19)
5 where H~ ~ t ~ and b ' ( t ) are the continuous-time estimates resulting
from the
discrete-time estimates H;~ ( or H' ) and bn , respectively.
-n
It should be noted that, in the reconstruction of X~ ( t ) ~ the total
amplitude ~,~ ( t ) of the i-th interferer is used.
Thus, in the ISR-TR embodiment described with reference to Figure 4, the
10 beamformer 29° uses only realisations Id.~ . Id,m of the interfering
signals, and takes
n-1 ~~ n-1
into account amplitude information and channel characteristics, i.e.,
substantially
reconstructs the complete interference signal ~~ i after despreading. The
delay 28°
delays the output of the first despreader 17d to allow time for the derivation
of these
realisations. The estimation of the spatio-temporal interference vector ~d~i
according
-n
15 to Equations 18 and 19 requires a processing memory of 2 frames due to
despreading,
and, due to the delay spread, 3 estimated bit signs from the interference data
(i.e., brt and the two bits bn-1 and bn+1 adjacent to it). Thus, to obtain
estimates of
the interferer bit signs from the next iteration ( i , a . , bn,, ) , the
processing of each
. CA 02293097 1999-12-23
26
desired user is further delayed by delay 28d of one bit duration and one
processing cycle
(pc) and all the corresponding data is saved.
The receiver illustrated in Figure 4 may be modified to reduce the
information used to generate the interfering signal estimates
~1 ( t) ... Jai ( t) ... XNI ( t) , specifically by omitting the amplitude of
the user signal
estimates, and adapting the SMD-ISR beamformer 29d to provide more (rTI) null
constraints. Such a modified receiver will now be described with reference to
Figure S.
Interference Subspace Re~iection over Realisations (ISR-R_l
In the receiver of Figure 5, the receiver modules in group I are identical to
those
of Figure 4 with the exception that the multipliers 26"...26''...268'" and the
adder 27 are
omitted, i.e., the outputs from the power estimation units
22"...22''...22°'" are not used
to scale the re-spread signals from the spreaders 24"...24''...24°'",
respectively. Hence,
in the receiver of Figure 5, the signals ,fin ", ,fin I from the STAR modules
18"...18''...18", respectively, are re-spread and then filtered by channel
replication filter
units 25"...25'N', respectively, to produce re-spread signals
respectively, which are supplied to each of the receiver modules
in group D. Again, only receiver module d is shown, and corresponds to that in
the
embodiment of Figure 4. The re-spread signals ~1 ( t) .,. ~NI ( t) from all of
the
"interfering" channels of group I are supplied to second despreader 30d which
uses the
spreading code cd(t) of spreader 13d of user station 1(>d to despread them to
produce a set
of interference estimates ~_i... ~_NI which it applies to the SMD-ISR
beamformer 29a.
Each of the estimates ~-1 . ~. Nz is, within a multiplication factor, the
estimate of the
n-1" n-1
interference in the despread data vector ~d caused by the corresponding one of
the
n-1
strong interference signals from group I and has the same dimension as the
despread data
CA 02293097 1999-12-23
27
vector ~d, The hat symbol (") indicates that these are estimates of the
interference
n
component. Hence, in addition to the vector ~~ 1, the SMD-ISR beamformer 29d
receives a set of interference estimates ~d . ~. Nz which approximate the
interference
n-1 " n-1
components in the vector ~d within a multiplicative factor.
n-1
In the receiver of Figure 5, the SMD-ISR beamformer 29° implements
the SMD
process of Equation 12 but uses estimated realisations of the spatio-temporal
channel and
interference vectors gn and jn>~ ~ respectively, and solves the corresponding
set of
linear equations:
hT n Hn 1 ~ xHn ~ 1 ~ (20)
x..
J~n ~'1=0 fOri=1,...,NI J~nN~,tr~0
This second mode, referred to as interference subspace rejection over
realisations
(ISR-R) also uses actual realisations of the interference vectors, but does
not use the
amplitude values ~,n ", ~,'n'1 and does not sum the interference estimates
x' ( t ) ... X"'' ( t ) before they are applied to despreader 30d. The
necessary delay again
is provided by delay 28°. For a = d in Equation 5, the beamformer 29d
of the desired
user d that directly implements the above constraints is then given by:
I~ = Cn (Cn H Cn ) 1 R (21)
where cn is an (ML) x (NI + 1) constraint matrix:
~a'.1 ~, i ~a, ws ~ (22)
n n, n ,..., n ,...~ n
CA 02293097 1999-12-23
28
and R is an (NI + 1)-dimensional response vector:
R= [1,0,...,0]T (23)
In Equation 22, the estimate of the channel vector Hd of the desired user d is
-n
given by Equation 8 with a = d. The estimate of each spatio-temporal
interference
vector I~.~ conveniently is obtained from the chip-rate sampling, bit-rate
framing and
matrix/vector reshaping of the estimate ~e ~ t ) of the post-correlation
interference
vector In ~i ~ t ) using Equation 18, as before.
This estimate is obtained by despreading with the spreading sequence of the
desired user of the reconstructed received signal vector X~ ~ t ) from the i-
th interferer
given by:
~ict~ =~zct) ~ sict>Cict~ c24)
where Hl ~ t ) and b t ~ t ) are the continuous-time estimates resulting from
the
discrete-time estimates g~ for Hn ) ~d bn , respectively. It should be noted
that, in
the reconstruction of X= ~ t ) ~ the total amplitude ~,i ( t ) of the i-th
interferer is
purposely omitted since the solution of Equation 20 is independent of the norm
of ~.t ; hence the expected very strong robustness to near-far situations as
well as the
enlarged margin for power control relaxation.
In the ISR-R embodiment described with reference to Figure 5, the beamformer
29d uses only realisations Id.1 , id,M of the interfering signals, and does
not take into
-n-1 ~~ -n-1
account amplitude information. The delay 28d delays the output of the first
despreader
,. T CA 02293097 1999-12-23
29
17d to allow time for the derivation of these realisations. The estimation of
the
spatio-temporal interference vector ~n.~ according to Equations 18 and 19
requires a
processing memory of 2 frames due to despreading, and, due to the delay
spread, 3
estimated bit signs from the interference data (i. e. , b~ and the two
bits bn-~ and bn+~ adjacent to it). Thus, to obtain estimates of the
interferes bit signs
from the next iteration ~ i , a . , b;,+~ ) , the processing of each desired
user is further
delayed by delay 28d of one bit duration and one processing cycle (pc) and all
the
corresponding data is saved.
It should be noted that, in the receivers of Figures 4 and 5, estimation
errors of
the interference bit signs may introduce differences between the estimated
constraints of
Equation 14 or Equation 20 and the theoretical ones of Equation 12. Hence
although
ISR-R and ISR-TR are satisfactory in most situations, it is possible that the
realisation
is erroneous, which affects the validity of the interference cancellation. To
avoid these
drawbacks, alternative ISR approaches to implementation of the SMD constraints
of
Equation 12 are envisaged and will now be described.
Interference Subspace Rejection over Hypotheses (ISR-H)
It is possible to use a set of signals which represent all possible or
hypothetical
values for the data of the interfering signal. Each of the interfering signals
constitutes
a vector in a particular domain. It is possible to predict all possible
occurrences for the
vectors and process all of them in the SMD-ISR beamformer and, therefore,
virtually
guarantee that the real or actual vector will have been nullified. As
mentioned, the
strong interferers are relatively few, so it is possible, in a practical
system, to determine
all of the likely positions of the interference vector and compensate or
nullify all of
them. Such an alternative embodiment, which will be called Interference
Subspace
Rejection over Hypotheses (ISR-H) because it uses all possibilities fvr the
realisations,
is illustrated in Figure 6.
,~ , CA 02293097 1999-12-23
The components of the "interferes" receiver modules of group I shown in Figure
6, namely the despreaders 17I1...17''...17IN' and STAR modules
18I'...18ti...18°''I, are
basically the same as those in the receiver of Figure 5 and so have the same
reference
numbers. In the embodiment of Figure 6, however, the symbol
5 estimates bn ." bn ", bn' from the outputs of the decision rule units
21"...21''...21n'" are
not supplied to the spreaders 24I'...24''...24°~I, respectively, but
are merely outputted to
other circuitry in the receiver (not shown).
Instead, bit sequence generators 31"...31I'...31~" each generate the three
possibilities gl ( t ) , g~ ( t ) , g3 ( t ) , which include the realisation
itself and cover all
10 possible estimated values of the previous, current and next bits of the
estimated data
sequences b n ", b'n'' (as explained later), and supply them to the spreaders
24I'...24v...24°~'I, respectively, which each spread each set of three
values again by the
corresponding one of the spreading codes. The resulting re-spread estimates
are filtered
by the channel replication filters 25"...25''...25IN', respectively. The bit
sequence
15 generators could, of course, be replaced by storage units.
The receiver modules of "desired" group D in Figure 6 comprise similar
components to those of the group D receiver modules shown in Figure 5, except
that,
because the "next" bit is being hypothesized, it need not be known, so the
delays 28d are
omitted.
20 Although compared with the embodiment of Figure 5, the number of vectors at
the output of the despreader 28d (and input to the SMD-ISR beamformer 29d) is
tripled,
but the processing in the beamformer 29d is carried out in exactly the same
way (see
equation 15). The beamformer coefficients are not identical, of course, but
the way in
which they are derived and applied in the beamformers is the same.
25 As mentioned above, the two bits adjacent to the processed bit of the i-th
interferes contribute in each bit frame to the corresponding interference
vector (symbol)
to be rejected. As shown in Figure 7, enumeration of all possible sequences of
the
processed and adjacent bits gives 23 = 8 triplets, each of three bits. Only
one of these
triplets could occur at any one time at each bit iteration as one possible
realization that
,. . CA 02293097 1999-12-23
31
generates the spatio-temporal interference vector Id>~ . These eight triplets
can be
n
identified within a sign ambiguity with one of the four triplets identified as
(a)...(d) in
the left-hand part of Figure 7, since the four triplets (e)...(h) are their
inverse.
Four generating bit sequences of the interfering mobile, denoted by g'~(t) for
k =
1,...,4, corresponding to these four template triplets ((a)...(d) or
(e)...(h)), may be
formulated as shown in Figure 8. It should be appreciated that Figure 6 has
only three
values, gl ( t ) , g ( t ) , g ( t ) because the dimension of the generated
signal subspace
is 3, as will be explained later. It should be noted that frames of duration
3T, taken
from these sequences at any bit rate instant, reproduce the eight possible
realisations of
the bit triplets of Figure 7 within a sign ambiguity. Therefore, at any bit
iteration, the
bit sequence b' (tJ of the interfering mobile station can be locally
identified as one of the
generating sequences g't(t), k = 1,...,4. Replacing its estimate bi (t) in
Equation 19
by g'~(tJ, k = 1,...,4, yields all possible realisations of the received
signal vector from the
i-th interfering mobile within a sign ambiguity. The possible realisations for
k = 1,...,4
are generated by:
Xk (t) =Fi1(t) ~ gk(t)Ci(t) (25)
Next, Xt ( t ) is replaced by Xk ( t ) in Equation 18 for despreading with the
spreading
sequence of the desired user. After chip-rate sampling, bit-rate framing and
matrix/vector reshaping of the resulting post-correlation vectors ~,n ( t ) ,
despreader
30d provides estimates of all possible realisations at iteration n of the
spatio-temporal
interference vector ~n,l , denoted here as jk,n for k = 1,...,4 within sign
ambiguities.
It should be noted that a continuous stream of generating sequences is used in
the
time convolution of Equation 25 to take account of the time-variations of the
spatio-temporal channel vector of the interfering mobile station.
,. ,, CA 02293097 1999-12-23
32
The vectors Ik,n cover all possible configurations of the spatio-temporal
interference from the i-th interfering mobile station given by the random
vector Iaa ,
-n
Hence, assigning the beamformer y,~d station (beamformer 29d) to reject all
possible
-n
realisations of the interference vectors, implicitly implements the SMD
constraint of
Equation 12 without any delay, as formulated by the following equation:
x~n = 1 .
x
Jan lx;n=O fork=1,..., 4 andfori =1,...,NI
uNxlln o~ 1 i
~a x~a, tr a 0 (26)
n n
In contrast to the ISR-R mode, where estimation errors over the interference
bit
signs bn may introduce differences between the estimated constraints of
Equation 20 and
the theoretical ones in Equation 12, the above constraints over all possible
realisations
could only observe negligible deviations due to small channel estimation
errors.
The four null-constraints of Equation 26 implement interference rejection in a
conservative way. It should be noted that, in any frame of duration 3T in
Figure 8, a
bit triplet of any of the four generating sequences is a linear combination of
the others.
Therefore, any one of the four possible realisations of each interference
vector is a linear
combination of the others and the corresponding null-constraint is implicitly
implemented
by the three remaining null-constraints. The four null-constraints are
restricted
arbitrarily to the first three possible realisations and the SMD scheme
implemented
without any delay by:
2O ~n x~n 1' ~x$n °' 1.
~x~;n=Ofork=1,..., 3andfori=1,...,NI ~ ~x~.tr=0
(27)
. , CA 02293097 1999-12-23
33
as follows:
d d,l d,l d,l d,i d,i d,i ,M d,Nl d,Ml (28)
Cn = [H , I , I , I , ..., I , I , I , ..., Id , I , II
n 1,n -2,n -3,n -l,n 2,n -3,n -l,n -2,n -3,n
where cn is an (ML) x (3NI+1) constraint matrix, and R is an (31VI+1)-
dimensional response vector
x = ~l,o,...,o~T. (29)
The beamformer solution for beamformer 29d is obtained by Equation 15.
The ISR-H embodiment of Figure 6, which rejects all possible realisations of
the
interference vectors, gives much better performance in certain adverse
conditions, though
at the expense of greater complexity. Compared to the ISR-R mode, the ISR-H
mode
avoids processing delays and significantly increases robustness to data
estimation errors.
However, it also increases the degrees of freedom required per interferer from
1 to 3,
as well as the complexity.
A trade-off can be found in an intermediate mode which is illustrated in
Figure
9. In Figure 9, the receiver modules of both groups I and D are similar to
those of
Figure 5 and their components have the same reference numbers.
The receiver modules in group I also comprise symbol generators
33'1...33''...33'N', respectively, which each generate two hypothetical values
of "future"
symbols bln+l...b'n+l...bNn+1 for every symbol of the corresponding one of the
symbol
estimates ,fin , , , ,&n , , , ,fin and supply them to the spreaders
241'...24''...24°'1',
respectively. There are only two hypothetical values of the symbols, namely 1
and -1.
The symbol estimates ,fin , , , ,fin , , , Sn I themselves also are supplied
directly to the
spreaders 2411...24''...24°''1 as in the embodiment of Figure 5. The
spreaders
24'1...24''...24n'1' also have buffers (not shown) for storing previous values
En_1 . . . ,fin 1 ~ ~ ~ ,fin 1 of the symbol estimates from the decision rule
units
211'...211'...21°'11. Consequently, each of the spreaders has estimated
values for the instant
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34
and previous symbols and the two possible hypothetical values for the next
symbol,
which enables it to generate two triplets, namely ,&n 1, ,fin ,1 and ,&n 1,
,fin , _ 1, and
spread them. The spreaders 2411...241'...24IN' supply the spread triplets to
the channel
replication units 2511...25L...25IN1 which filter them to produce pairs of
vectors,
( Xi ( t ) , XZ ( t ) . . . Xi r ( t ) , Xz I ( t ) and supply them to the
despreaders 30d in the
receiver modules of group D. These group D receiver modules also differ
slightly from
those of Figure S. Thus, instead of the delay 28d, the group D channels each
have a
delay 32d which is of only 1 processing cycle duration, i.e., shorter than
delay 28d by
one bit period. Hence, the beamformer 29d uses the past symbol estimate b~_1
of the
interference data as well as the present one b~ (delayed by one processing
cycle, i.e.
the time taken to derive the interference estimates), and the unknown sign
of bn+1 reduces the number of possible bit triplets and the corresponding
realisations for
each interference vector to 2. If the two possible realisations of the i-th
interference
vector are denoted by ~~in and ~ in , then the SMD scheme is implemented with
a
delay of only one processing cycle by:
~n x~n = 1 ~ .fin ~~n °' 1 ~
I~n"~;n=Oforke(kl,k2} andfori=1,...,NI ~ ~n",,~~tra0
(30)
The beamformer solution for beamformer 29d again is obtained by Equation 15
with ad hoc modifications of Equations 28 and 29, as follows:
2~ G.d = rHd Id,l id,l Id,i Id,i ,M ,NI 31
n L ni -k~ni -~n~ ...~ _k'n~ _~n, ...~ ~ n ~ ~ n
,, , CA 02293097 1999-12-23
where cn is an (ML) x (2IVI + 1) constraint matrix and R is a (2I~TI + 1)-
dimensional
response vector
R = ~ 1, o , ... , o )'' (32)
This mode, conveniently referred to as ISR-RH, rejects reduced possibilities
of the
5 interference vector realisations. Compared to the ISR-H mode, it is more
sensitive to
data estimation errors over bn-~ and b~ and requires only 2 degrees of freedom
per
interferes instead of 3.
The table below provides a qualitative comparison of the relevant features of
the
various ISR modes:
10 SMD number of processing robustness
2 to estimation
errors
in
alternativeconstraintsdelay data power channel3
ISR-TR 2 1 BIT + 1 + + + +
PC
ISR-R 1VI 1 BIT + 1 + + + + + +
PC
ISR-RH 2rTI 1 PC + + + + + + +
15 ISR-H 3NI none + + + + + + + +
2 The number of constraints per interferes is given in the case of a full-rank
interference
subspace. It should be appreciated that, where the interference subspace is
not full-rank,
the number of constraints can be reduced.
20 3 Channel estimation errors are over multipath time-delays and normalized
fading channel
coefficients.
Hence, in the ISR-R mode and in the alternative ISR modes, the residual
interference (due to the strongest users) remaining after despreading is first
estimated
then eliminated. Embodiments of the invention which reject the residual
interference
25 after despreading by linearly-constrained spatio-temporal beamforming offer
much more
robustness to estimation errors.
,. . CA 02293097 1999-12-23
36
Thus, in contrast to known single-user structure, interference cancellers,
which
dramatically aggravate errors in adverse conditions whenever they subtract an
erroneous
amount of interference [see reference 2], embodiments of the present
invention, which
employ SMD-ISR, are robust to power estimation errors and allow significant
relaxation
of power control. They could still reject a part of interference without
deteriorating
performance even when they steer an estimate aside due to data or channel
estimation
errors. Regarding processing delays, embodiments of the invention employing
SMD-ISR
can reject multiple interferers in parallel, not necessarily iteratively as in
interference
cancellation schemes [see reference 2].
The selective multiuser detection (SMD) scheme of the present invention
cancels
the strongly interfering mobiles by linearly-constrained adaptive mufti-source
beamforming. By mufti-source spatio-temporal beamforming, SMD steers a simple
null-response in the direction of each interferer realization so as to
suppress it when
receiving a weak user's signal. Sensitivity to power variations in the
estimated
interference is significantly reduced in comparison to most multiuser
detectors and power
control requirements can be relaxed. Additionally, the receiver with
interference
rejection is significantly more robust to channel and data estimation errors.
Embodiments of the invention are not limited to DBPSK but could provide for
practical implementation of SMD in mixed-rate traffic with MPSK or MQAM
modulations without increased computing complexity. Even orthogonal Walsh
signalling
can be implemented at the cost of a computational increase corresponding to
the number
of Walsh sequences.
When used with a single antenna, SMD replaces spatio-temporal processing by
just temporal processing to suppress interference. Thus, the technique is
applicable as
well, on the downlink, to mobile receivers with only one receive antenna. It
can reject
strong interference from neighbouring base-stations or higher-rate mobiles
within the cell
of the targeted weaker-rate user.
In contrast to other multiuser detectors, the interference cancellation scheme
according to the present invention processes multipath fading in a single
temporal
dimension, whether the fading environment is selective or not. Thus,
complexity of the
interference cancellation does not increase with the number of multipaths.
Overall, embodiments of the invention employing SMD-ISR are more robust to
channel, data and power estimation errors and can be implemented with a lower
,. , CA 02293097 1999-12-23
37
complexity. With multiple interferers, simulations reveal a reduction in
interference of
as much as 7 dB. In contrast, SIC, for example, achieves less than 3 dB of
interference
reduction.
It should be noted that, although the above-described embodiments are
asynchronous, a skilled person would be able to apply the invention to
synchronous
systems without undue experimentation.
It should be appreciated that the decision rule units do not have to provide a
binary output; they could output the symbol and some other signal state.
The invention comprehends various other modifications to the above-described
embodiments. For example, long PN codes could be used, as could mixed rate or
mixed
modulations, large delay-spreads and large inter-user delay-spreads. Also, the
invention
can be used in CDMA systems employing pilot signals.
In most cases, the spreading codes are substantially random and quasi-
orthogonal,
so the interference vectors also are almost orthogonal and full rank. In some
situations,
however, the dimensionality of the interference subspace is reduced, in which
case it
might be desirable to estimate the reduced rank and to find an orthogonal set
of vectors
each of which is a combination of the estimated interference vectors.
REFERENCES
For further information, the reader is directed to the following documents,
the contents
of which are incorporated herein by reference.
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,~ , CA 02293097 1999-12-23
38
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CA 02293097 1999-12-23
39
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