Note: Descriptions are shown in the official language in which they were submitted.
CA 02727686 2011-01-12
SPECIFICATION
CHANNEL ESTIMATION DEVICE AND METHOD, DEMODULATION DEVICE AND
METHOD, AND FADING FREQUENCY DECISION DEVICE AND METHOD
TECHNICAL FIELD
The present invention relates to a channel estimation
device and method, a demodulation device and method, and
a fading frequency decision device and method. More
specifically, the present invention relates to a channel
estimation device, a demodulation device, or the like that
is applicable to a mobile communication method for
transmitting sounds and data in a fast fading environment.
In addition, the present invention relates to a
demodulation device and method in conformity with the CDMA
method which carries out multidimensional connections by
diffusing data to signals over a broad band using a
diffusion code operating at a rate higher than a data rate.
BACKGROUND ART
In a mobile communication environment, the amplitude
or phase varies due to Rayleigh fading associated with
movement of the relative locations of a mobile station and
a ground station. According to the phase modulation
method for transmitting information using a carrier phase,
differential coding is generally used to load information
on relative phases of a preceding and a following symbols,
-~-
CA 02727686 2011-01-12
and a receiver carries out delayed detection to identify
and determine the information data. This delayed
detection, however, differentially codes the transmitted
data as described above, whereby one-bit error within a
wireless section corresponds to a two-bit error in the
information data. Thus, at the same signal power to
interference/noise power ratio (SNIR), the two-phase phase
modulation method (BPSK modulation) has a higher reception
error rate than synchronous detection by 3 dB.
In addition, absolute synchronous detection that
identifies and determines an absolute phase of a received
signal for each symbol has an efficient reception
characteristic, but it is difficult to determine the
absolute phase in a Rayleigh fading environment.
To solve this problem, a method has, been proposed
which inserts pilot symbols between data symbols so as to
use these pilot symbols to estimate a channel for the data
symbols. One of the methods for inserting pilot symbols,
for example, time-multiplexes data symbols and pilot
symbols into one channel (time multiplexing method; FIG.
16). Documents 1 to 3, which will be cited below, propose
channel estimation methods using this time multiplexing
method.
The document 1 (Electronic Information
Communication Society Journal Vol. J72-B-11, No.1, pp. 7
to 15, January 1989, SANPEI "Land Mobile Communication
16QAM Fading Distortion Compensation") proposes a method
2 -
CA 02727686 2011-01-12
for solving the above problem by estimating and
compensating for fading distortion using pilot symbols
inserted between data symbols (information symbols) at a
fixed cycle and the phases of which are known. This method
inserts the pilot symbols into a communication channel at
the rate of one pilot symbol per several data symbols to
estimate a transmission path based on received phases of
the pilot symbols. Signals received during each pass of
each transmitter are measured at pilot symbols before and
after a desired data symbol section for amplitude and phase,
and the measured values are interpolated to estimate and
compensate for transmission path variations within the
data symbol section.
Document 2 (Electronic Information Communication
Society Technical Report RCS97-74, ANDO at el. "RAKE
Reception Using the Multislot Weighted Averaging Channel
Estimation Method with Pilot Symbols in DS-CDMA") proposes
a method for carrying out more accurate channel estimation
using more pilot symbols. A channel for data symbols is
estimated using pilot symbols inserted between data
symbols at a fixed cycle. Specifically, pilot symbols
(estimated complex fading envelope) in a plurality of slots
before and after a slot for which a channel is estimated
are averaged (in-phase addition), and the average value
is subjected to weighted averaging using a weighting factor
to obtain a channel estimated value. The channel
estimation accuracy is thereby improved to prevent thermal
3 -
CA 02727686 2011-01-12
noise or multipass interference and interference from
other stations.
Document 3 (Electronic Information Communication
Society Technical Report RCS98-20, ABETA at el.
"Characteristics of the DC-CDMA Adaptive Plural Symbol
Weighted Averaging Pilot Channel Transmission Path
Estimation Method") proposes a method of adaptively
controlling a weighting factor to reduce the effects of
thermal noise while improving the capability of following
fading variations. According to this method, channel
estimation involves weighted averaging, and this weighting
factor is sequentially varied using an adaptive signal to
determine an optimal weighting factor.
The pilot symbol insertion methods include not only
the time multiplexing method but also a parallel time
multiplexing method (FIG. 1) and a parallel method (FIG.
22) that time-multiplex pilot symbols into a control
channel parallel-multiplexed for a data channel.
For the parallel time multiplexing method, it is
desirable to execute accurate channel estimation by.
subjecting the pilot symbols to weighted averaging to
calculate a channel estimated value for the data symbols
in the data channel.
In addition, according to the methods in Documents
1 to 3, channel variations within each slot are assumed
to be small, and the same pilot symbol is used for all the
data symbols within one slot to obtain the same channel
4 -
CA 02727686 2011-01-12
estimated value. Consequently, the characteristics are
disadvantageously degraded during fast fading.
Further, the method in the Document 2 provides a fixed
weighting factor, and when the weighting factor for slots
temporally remote from a desired slot is increased to
reduce the effects of thermal noise, the capability of
following fading variations is disadvantageously degraded,
thereby causing the channel estimation accuracy to be
degraded. Another problem of the method in the Document
3 is that despite the solution of the problem of the
Document 2, the use of the adaptive signal process may make
the configuration of a demodulation device complicated.
In the mobile communication environment, the
amplitude or phase varies due to Rayleigh fading associated
with movement of the relative locations of a mobile station
and a ground station. The synchronous detection process
using pilot signals is known as a method for compensating
for the variations of the amplitude or phase to effectively
synthesize multiple passes.
According to this method, a transmitter transmits a
known pilot signal, while a receiver demodulates and
temporally averages this pilot signal to estimate a channel.
Then, the estimated channel vector is used to correct a
phase of a data signal, which is then subjected to RAKE
synthesis, thereby achieving demodulation using power of
the received signal.
Since the channel estimation accuracy directly
5 -
CA 02727686 2011-01-12
affects data quality, averaging must be carried out using
appropriate temporal sections and an appropriate weight
sequence. One sequence that improves the channel
estimation accuracy is conventionally used as the weight
sequence.
When the receiver estimates a channel, the channel
estimation accuracy can be improved to enable high-quality
communication, by using an appropriate weight sequence to
average pilot signals. The appropriate weight sequence,
however, depends on propagation conditions, principally,
the movement speed, as described above.
That is, at a lower movement speed, channel
variations occur at a lower speed, so that a weight sequence
that increases the averaging time is effective, whereas
at a higher movement speed, fast channel variations must
be followed, so that a weight sequence that reduces the
averaging time to some degree is effective.
However, the known channel estimation method using
only the one weight sequence fails to enable averaging
suitable for every movement speed, resulting in
degradation of communication quality, an increase in
transmission power required, a decrease in communication
capacity achieved.
In addition, methods for varying the weight sequence
depending on the movement speed include a method of
detecting the movement speed to vary the weight sequence
depending on the detected speed. A problem of this method,
6 -
CA 02727686 2011-01-12
however, is that if the speed detection accuracy or the
detection following capability is degraded, improvement
of communication quality, a reduction in transmission
power required, and an increase in capacity cannot be
realized.
DISCLOSURE OF THE INVENTION
It is an object of the present invention to carry out
accurate channel estimation in the parallel time
multiplexing method by subjecting pilot symbols to
weighted averaging to calculate a channel estimated value
for data symbols in a data channel.
It is another object of the present invention to carry
out accurate channel estimation by dividing data symbols
within a slot into a plurality of data symbol sections,
selecting pilot symbols appropriate for calculation of a
channel estimated value for data symbols within each of
the data symbol sections, and subjecting the pilot symbols
to weighted averaging to calculate the channel estimated
value for the data symbols in each data symbol section.
It is yet another object of the present invention to
decide a fading frequency based on an inner product value
of the pilot symbols. It is still another object of the
present invention to realize channel estimation optimal
for the fading frequency using a simpler configuration.
It is still another object of the present invention
to directly determine from reception quality, weight
7 -
CA 02727686 2011-01-12
sequences effective on various movement speeds for use,
thereby improving communication quality, reducing the
amount of transmission power required, and increasing the
communication capacity.
In order to accomplish the object aforementioned,
according to the invention as claimed in claim 1, a channel
estimation device comprises:
weighting factor generating means for generating
weighting factors for weighting and averaging pilot
symbols, which are time multiplexed with a control channel,
which is parallel multiplexed with a data channel; and
channel estimation value calculating means for
weighting and averaging the pilot symbols using the
weighting factors and calculating a channel estimation
value of data symbols of the data channel.
According to the invention as claimed in claim 2, in
the channel estimation device as claimed in claim 1, the
weighting factor generating means generates weighting
factors to be used for weighting and averaging mean values
of the pilot symbols in a plurality of slots of the control
channel, and the channel estimation value calculating
means weights and averages the mean values of the pilot
symbols using the weighting factors and calculates the
channel estimation value of the data symbols of the data
channel.
According to the invention as claimed in claim 3, in
the channel estimation device as claimed in claim 1 or 2,
- 8 -
CA 02727686 2011-01-12
the weighting factors are determined according to the
positions of the pilot symbols in the slots of the control
channel.
According to the invention as claimed in claim 4, in
the channel estimation device as claimed in any one of
claims 1-3, the weighting factor generating means divides
the data symbols in the slots of the data channel into a
plurality of data symbol sections, selects the pilot
symbols appropriate for calculating the channel estimation
value of the data symbols in each of the data symbol
sections, and generates the weighting factors to be used
for weighting and averaging the pilot symbols; and the
channel estimation value calculating means takes weighted
average of the pilot symbols using the weighting factors
and calculates the channel estimation value of the data
symbols of each of the data symbol sections.
According to the invention as claimed in claim 5, in
the channel estimation device as claimed in claim 4,
wherein in order to calculate the channel estimation value
of the data symbols of the last data symbol section of the
i-th (i: integer) slot and to calculate the channel
estimation value of the data symbols of the first data
symbol section of the (i+l) -th slot, the weighting factor
generating means selects the same pilot symbol and
generates the weighting factors to be used for weighting
and averaging the pilot symbols.
According to the invention as claimed in claim 6, the
9 -
CA 02727686 2011-01-12
channel estimation device as claimed in any one of claims
1-5, further comprises:
fading frequency decision means for deciding the
fading frequency based on an inner product value of the
pilot symbols; and
factor altering means for altering the factors that
are used in taking the weighted average according to the
fading frequency decided by the fading frequency decision
means.
According to the invention as claimed in claim 7, in
the channel estimation device as claimed in any one of
claims 1-6, a transmission rate of the data channel differs
from the transmission rate of the control channel.
According to the invention as claimed in claim 8, a
demodulation device comprises:
weighting factor generating means for generating
weighting factors to be used for weighting and averaging
pilot symbols being time multiplexed in a control channel
that was parallel multiplexed together with a data channel;
channel estimation value calculating means for
weighting and averaging the pilot symbols using the
weighting factors and for calculating a channel estimation
value of data symbols of the data channel; and
channel variation compensating means for
compensating channel variation of the data symbols using
the channel estimation value calculated by the channel
estimation value calculating means.
-10-
CA 02727686 2011-01-12
According to the invention as claimed in claim 9, a
fading frequency decision device comprises:
inner product value calculating means for
calculating an inner product value of pilot symbols, which
are time multiplexed with a control channel, which is
parallel multiplexed with a data channel; and
decision means for deciding a fading frequency based
on the inner product value calculated by the inner product
value calculating means.
According to the invention as claimed in claim 10,
in the fading frequency decision device as claimed in claim
9,
the inner product value calculating means comprises:
normalizing means for normalizing mean values
of the pilot symbols in each of two slots of the control
channel;
inner product value calculation executing
means for calculating an inner product value of the mean
values of the two pilot symbols normalized by the
normalizing means; and
inner product value averaging means for
averaging inner product values calculated by the inner
product value calculation executing means over a plurality
of slots of the control channel, and
the decision means comprises
decision executing means for deciding the
fading frequency by comparing the inner product value
CA 02727686 2011-01-12
averaged by the inner product value averaging means and
a threshold value.
According to the invention as claimed in claim 11,
in the fading frequency decision device as claimed in claim
10, when the inner product value averaged by the inner
product value averaging means is larger than a certain
constant value, the fading frequency decision device
performs the normalizing, the inner product value
calculation, and the inner product value averaging on mean
values of the pilot symbols in each of two slots having
a farther interval in the control channel, and decides the
fading frequency by comparing the averaged inner product
value so obtained and a threshold value corresponding to
the farther interval.
According to the invention as claimed in claim 12,
in the fading frequency decision device as claimed in claim
9,
the inner product value calculating means comprises:
normalizing means for normalizing the mean
values of the pilot symbols in each of two slots of the
control channel with respect to each of multipath signals
to be used for RAKE combining;
inner product value calculation executing
means for calculating the inner product value of the mean
values of the two pilot symbols normalized by the
normalizing means with respect to each of the multipath
signals;
12 -
CA 02727686 2011-01-12
first inner product value averaging means for
averaging the inner product values of each of the multipath
signals calculated by the inner product value calculation
executing means; and
second inner product value averaging means for
averaging the inner product values averaged by the first
inner product value averaging means over a plurality of
slots of the control channel, and
the decision means comprises
decision executing means for deciding the
fading frequency by comparing the inner product value
averaged by the second inner product value averaging means
and a threshold value.
According to the invention as claimed in claim 13,
in the fading frequency decision device as claimed in claim
12, when the inner product value averaged by the second
inner product value averaging means is larger than a
certain constant value, the fading frequency decision
device performs the normalizing, the inner product value
calculation, averaging of the inner product values of each
of the multipath signals, and averaging of the inner
product values over the plurality of slots on the mean
values of the pilot symbols in each of two slots having
a farther interval in the control channel, and decides the
fading frequency by comparing the averaged inner product
value so obtained and a threshold value corresponding to
the farther interval.
13 -
CA 02727686 2011-01-12
According to the invention as claimed in claim 14,
in the fading frequency decision device as claimed in claim
9,
the inner product value calculating means comprises:
normalizing means for normalizing the mean
values of the pilot symbols in each of two slots in the
control channel;
inner product value calculation executing
means for calculating the inner product value of the mean
values of the two pilot symbols normalized.by the
normalizing means for two or more cases with varying inner
product measuring interval; and
inner product value averaging means for
averaging the inner product value calculated by the inner
product value calculation executing means over a plurality
of slots of the control channel with respect to each of
the inner product measuring intervals, and
the decision means comprises
decision executing means for deciding the
fading frequency using the inner product value for each
of the inner product measuring intervals averaged by the
inner product value averaging means.
According to the invention as claimed in claim 15,
in the fading frequency decision device as claimed in claim
14, further comprising difference calculating means for
calculating the difference of the inner product values for
two inner product measuring intervals averaged by the inner
14 -
CA 02727686 2011-01-12
product value averaging means, wherein the decision
executing means decides the fading frequency using also
the difference calculated by the difference calculating
means.
According to the invention as claimed in claim 16,
in the fading frequency decision device as claimed in claim
9,
the inner product value calculating means comprises:
normalizing means for normalizing mean values
of the pilot symbols in each of two slots in the control
channel with respect to each of multipath signals to be
used for RAKE combining;
inner product value calculation executing
means for calculating the inner product value of the mean
values of the two pilot symbols normalized by the
normalizing means for two or more cases with varying inner
product measuring interval with respect to each of the
multipath signals;
first inner product value averaging means for
averaging the inner product values of each of the multipath
signals calculated by the inner product value calculation
executing means with respect to each of the inner product
measuring intervals; and
second inner product value averaging means for
averaging the inner product values averaged by the first
inner product value averaging means over a plurality of
slots of the control channel with respect to each of the
15 -
CA 02727686 2011-01-12
inner product measuring intervals, and
the decision means comprises
decision executing means for deciding the
fading frequency using the inner product value for each
of the inner product measuring intervals averaged by the
second inner product value averaging means.
According to the invention as claimed in claim 17,
the fading frequency decision device as claimed in claim
16, further comprises difference calculating means for
calculating the difference of the inner product values for
two inner product measuring intervals averaged by the
second inner product value averaging means, wherein the
decision executing means decides the fading frequency
using also the difference calculated by the difference
calculating means.
According to the invention as claimed in claim 18,
a channel estimation device for calculating a channel
estimation value of data symbols using pilot symbols in
a channel in which the data symbols and the pilot symbols
are time multiplexed, comprises:
weighting factor generating means for dividing data
symbols in a slot of the channel into a plurality of data
symbol intervals, selecting pilot symbols suitable for
calculation of a channel estimation value of data symbols
during each data symbol interval and generating weighting
factors for weighting and averaging the pilot symbols; and
channel estimation value calculating means for
16 -
CA 02727686 2011-01-12
weighting and averaging the pilot symbols using the
weighting factors and calculating a channel estimation
value of data symbols during each data symbol interval.
According to the invention as claimed in claim 19,
in the channel estimation device as claimed in claim 18,
in order to calculate the channel estimation value of the
data symbols in the last data symbol section in the i-
th (i: integer) slot and to calculate the channel
estimation value of the data symbols of the first data
symbol section in the (i+l) -th slot, the weighting factor
generating means selects the same pilot symbol and
generates the weighting factors to be used for weighting
and averaging the pilot symbols.
According to the invention as claimed in claim 20,
in the channel estimation device as claimed in claim 18
or 19, the weighting factor generating means generates the
weighting factors to be used for weighting and averaging
mean values of the pilot symbols for each of the plurality
of slots of the channel, and the channel estimation value
calculating means takes weighted average of the mean values
of the pilot symbols using the weighting factors and
calculates the channel estimation value of the data symbols
in each of the data symbol sections.
According to the invention as claimed in claim 21,
in the channel estimation device as claimed in any one of
claims 18-20, the weighting factors are determined
according to positions of the pilot symbols in the slots
17 -
CA 02727686 2011-01-12
of the channel.
According to the invention as claimed in claim 22,
the channel estimation device as claimed in any one of
claims 18-21, further comprises:
fading frequency decision means for deciding the
fading frequency based on the inner product value of the
pilot symbols; and
factor altering means for altering the factors to
be used for taking the weighted averaging according to the
fading frequency decided by the fading frequency decision
means.
According to the invention as claimed in claim 23,
a demodulation device comprises:
weighting factor generating means for dividing
data symbols in the slots of a channel into which the data
symbols and pilot symbols are time multiplexed into a
plurality of data symbol sections, selecting pilot symbols
appropriate for calculating the channel estimation value
of the data symbols in each of the data symbol sections,
and generating the weighting factors to be used for
weighting and averaging the pilot symbols;
channel estimation value calculating means for
weighting and averaging the pilot symbols using the
weighting factors and calculating the channel estimation
value of the data symbols in each of data symbol sections;
and
channel variation compensating means for
-i8-
CA 02727686 2011-01-12
compensating channel variation of the data symbols using
the channel estimation value calculated by the channel
estimation value calculating means.
According to the invention as claimed in claim 24,
a fading frequency decision device comprises:
inner product value calculating means for
calculating an inner product value of pilot symbols in a
channel in which data symbols and the pilot symbols are
time multiplexed; and
decision means for deciding a fading frequency based
on the inner product value calculated by the inner product
value calculating means.
According to the invention as claimed in claim 25,
in the fading frequency decision device as claimed in claim
24,
the inner product value calculating means comprises:
normalizing means for normalizing mean values
of the pilot symbols in each of two slots of the channel;
inner product value calculation executing
means for calculating the inner product value of the mean
values of the two pilot symbols normalized by the
normalizing means; and
inner product value averaging means for
averaging the inner product values calculated by the inner
product value calculation executing means over a plurality
of slots of the channel, and
the decision means comprises
19 -
CA 02727686 2011-01-12
decision executing means for deciding the
fading frequency by comparing the inner product value
averaged by the inner product value averaging means and
a threshold value.
According to the invention as claimed in claim 26,
in the fading frequency decision device as clamed in claim
25, when the inner product value averaged by the inner
product value averaging means is larger than a certain
constant value, the fading frequency decision device
performs the normalizing, the inner product value
calculation, and the inner product value averaging on mean
values of the pilot symbols in each of two slots having
a farther interval in the control channel, and decides the
fading frequency by comparing the averaged inner product
value so obtained and a threshold value corresponding to
the farther interval.
According to the invention as claimed in claim 27,
in the fading frequency decision device as claimed in claim
24,
the inner product value calculating means comprises:
normalizing means for normalizing mean values
of the pilot symbols in each of two slots of the control
channel with respect to each of multipath signals to be
used for RAKE combining;
inner product value calculation executing
means for calculating the inner product value of the mean
values of the two pilot symbols normalized by the
-20-
CA 02727686 2011-01-12
normalizing means with respect to each of the multipath
signals;
first inner product value averaging means for
averaging the inner product values of each of the multipath
signals calculated by the inner product value calculation
executing means; and
second inner product value averaging means for
averaging the inner product values averaged by the first
inner product value averaging means over a plurality of
slots of the channel, and
the decision means comprises
decision executing means for deciding the
fading frequency by comparing the inner product value
averaged by the second inner product value averaging means
and a threshold value.
According to the invention as claimed in claim 28,
in the fading frequency decision device as claimed in claim
27, when the inner product value averaged by the second
inner product value averaging means is larger than a
certain constant value, the fading frequency decision
device performs the normalizing, the inner product value
calculation, averaging of the inner product values of each
of the multipath signals, and averaging of the inner
product values over the plurality of slots on the mean
values of the pilot symbols in each of two slots having
a farther interval in the control channel, and decides the
fading frequency by comparing the averaged inner product
21 -
CA 02727686 2011-01-12
value so obtained and a threshold value corresponding to
the farther interval.
According to the invention as claimed in claim 29,
in the fading frequency decision device as claimed in claim
24,
the inner product value calculating means comprises:
normalizing means for normalizing the mean
values of the pilot symbols in each of two slots of the
channel;
inner product value calculation executing
means for calculating the inner product value of the mean
values of the two pilot symbols normalized by the
normalizing means for two or more cases with varying inner
product measuring interval; and
inner product value averaging means for
averaging the inner product values calculated by the inner
product value calculation executing means over a plurality
of slots of the control channel with respect to each of
the inner product measuring intervals, and
the decision means comprises
decision executing means for deciding the
fading frequency using the inner product value for each
of the inner product measuring intervals averaged by the
inner product value averaging means.
According to the invention as claimed in claim 30,
the fading frequency decision device as claimed in claim
29, further comprises difference calculating means for
22 -
CA 02727686 2011-01-12
calculating the difference of the inner product values for
two inner product measuring intervals averaged by the inner
product value averaging means, wherein the decision
executing means decides the fading frequency also using
the difference calculated by the difference calculating
means.
According to the invention as claimed in claim 31,
in the fading frequency decision device as claimed in claim
24,
the inner product value calculating means
comprises:
normalizing means for normalizing mean values
of the pilot symbols in each of two slots of the channel
with respect to each of multipath signals to be used for
RAKE combination;
inner product value calculation executing
means for calculating the inner product value of the mean
values of two pilot symbols normalized by the normalizing
means for two or more cases with varying inner product
measuring interval with respect to each of the multipath
signals;
first inner product value averaging means for
averaging the inner product value of each of the multipath
signals calculated by the inner product value calculation
executing means with respect to each of the inner product
measuring intervals; and
second inner product value averaging means for
23 -
CA 02727686 2011-01-12
averaging the inner product values averaged by the first
inner product value averaging means over a plurality of
slots of the control channel with respect to each of the
inner product measuring intervals, and
the decision means comprises
decision executing means for deciding the
fading frequency using the inner product value for each
of the inner product measuring intervals averaged by the
second inner product value averaging means.
According to the invention as claimed in claim 32,
in the fading frequency decision device as claimed in claim
31, further comprising difference calculating means for
calculating the difference of the inner product values for
two inner product measuring intervals averaged by the
second inner product value averaging means, wherein the
decision executing means decides the fading frequency also
using the difference calculated by the difference
calculating means.
According to the invention as claimed in claim 33,
a channel estimation device that calculates a channel
estimation value of data symbols of a data channel using
pilot symbols of a pilot channel which is parallel
multiplexed with the data channel, comprises:
weighting factor generating means for dividing data
symbols in the channel into a plurality of data symbol
intervals, selecting pilot symbols suitable for
calculation of a channel estimation value of data symbols
24 -
CA 02727686 2011-01-12
during each data symbol interval and generating weighting
factors for weighting and averaging the pilot symbols; and
channel estimation value calculating means for
weighting and averaging the pilot symbols using the
weighting factors and calculating a channel estimation
value of data symbols during each data symbol interval.
According to the invention as claimed in claim 34,
in the channel estimation device as claimed in claim 33,
the weighting factor generating means generates the
weighting factors to be used for weighting and averaging
mean values of the pilot symbols in each of a plurality
of sections in the pilot channel, and the channel
estimation value calculating means takes weighted average
of the mean values of the pilot symbols using the weighting
factors and calculates the channel estimation value of the
data symbols in each of the data symbol sections.
According to the invention as claimed in claim 35,
the channel estimation device as claimed in claim 33 or
34, further comprises:
fading frequency decision means for deciding the
fading frequency based on the inner product value of the
pilot symbols; and
factor altering means for altering the factors to
be used for taking the weighted average according to the
fading frequency decided by the fading frequency decision
means.
According to the invention as claimed in claim 36,
25 -
CA 02727686 2011-01-12
in the channel estimation device as claimed in any one of
claims 33-35, wherein a transmission rate of the data
channel differs from the transmission rate of the pilot
channel.
According to the invention as claimed in claim 37,
a demodulation device comprises:
weighting factor generating means for dividing
data symbols of a data channel into a plurality of data
symbol sections, selecting pilot symbols of a pilot channel
that was parallel multiplexed together with the data
channel, appropriate for calculating the channel
estimation value of the data symbols in each of the data
symbol sections, and generating weighting factors to be
used for weighting and averaging the pilot symbols;
channel estimation value calculating means for
weighting and averaging the pilot symbols using the
weighting factors and calculating the channel estimation
value of the data symbols of each of the data symbol
sections; and
channel variation compensating means for
compensating the channel variation of the data symbols
using the channel estimation value calculated by the
channel estimation value calculating means.
According to the invention as claimed in claim 38,
a fading frequency decision device comprises:
inner product value calculating means for
calculating an inner product value of pilot symbols in a
26 -
CA 02727686 2011-01-12
pilot channel which is parallel multiplexed with a data
channel; and
decision means for deciding a fading frequency based
on the inner product value calculated by the inner product
value calculating means.
According to the invention as claimed in claim 39,
in the fading frequency decision device as claimed in claim
38,
the inner product value calculating means comprises:
normalizing means for normalizing the mean
value of the pilot symbols in each of two sections of the
pilot channel;
inner product value calculation executing
means for calculating an inner product value of mean values
of the two pilot symbols normalized by the normalizing
means; and
inner product value averaging means for
averaging the inner product values calculated by the inner
product value calculation executing means over a plurality
of sections of the channel, and
the decision means comprises
decision executing means for deciding the
fading frequency by comparing the inner product value
averaged by the inner product value averaging means and
a threshold value.
According to the invention as claimed in claim 40,
in the fading frequency decision device as claimed in claim
27 -
CA 02727686 2011-01-12
39, when the inner product value averaged by the inner
product value averaging means is larger than a certain
constant value, the frequency decision device performs the
normalizing, the inner product value calculation, and the
averaging of the inner product values with respect to the
mean values of the pilot symbols in each of two sections
having a farther interval in the pilot channel, and decides
the fading frequency by comparing the averaged inner
product value so obtained and a threshold value
corresponding to the farther interval.
According to the invention as claimed in claim 41,
in the fading frequency decision device as claimed in claim
38,
the inner product value calculating means comprises:
normalizing means for normalizing the mean
values of the pilot symbols in each of the two sections
of the pilot channel with respect to each of multipath
signals to be used for RAKE combining;
inner product value calculation executing
means for calculating the inner product value of the mean
values of the two pilot symbols normalized by the
normalizing means with respect to each of the multipath
signals;
first inner product value averaging means for
averaging the inner product values of respective paths of
the multipath calculated by the inner product value
calculation executing means; and
28 -
CA 02727686 2011-01-12
second inner product value averaging means for
averaging the inner product values averaged by the first
inner product value averaging means over a plurality of
sections of the pilot channel, and
the decision means comprises
decision executing means for deciding the
fading frequency by comparing the inner product value
averaged by the second inner product value averaging means
and a threshold value.
According to the invention as claimed in claim 42,
in the fading frequency decision device as claimed in claim
41, when the inner product value averaged by the second
inner product value averaging means is larger than a
certain constant value, the fading frequency decision
device performs the normalizing, the inner product value
calculation, averaging of the inner product values of each
of the multipath signals, and averaging of the inner
product values over the plurality of sections with respect
,to the mean values of the pilot symbols in each of two
sections having a farther interval in the pilot channel,
and decides the fading frequency by comparing the averaged
inner product value so obtained and a threshold value
corresponding to the farther interval.
According to the invention as claimed in claim 43,
in the fading frequency decision device as claimed in claim
38,
the inner product value calculating means comprises:
29 -
CA 02727686 2011-01-12
normalizing means for normalizing the mean
values of the pilot symbols in each of the two sections
of the pilot channel;
inner product value calculation executing
means for calculating the inner product value of the mean
values of the two pilot symbols normalized by the
normalizing means for two or more cases with varying inner
product measuring interval; and
inner product value averaging means for
averaging the inner product vales calculated by the inner
product value calculation executing means over a plurality
of sections of the control channel with respect to each
of the inner product measuring intervals, and
the decision means comprises
fading frequency decision means for deciding
the fading frequency using the inner product value for each
of the inner product measuring intervals averaged by the
inner product value averaging means.
According to the invention as claimed in claim 44,
in the fading frequency decision device as claimed in claim
43, further comprising difference calculating means for
calculating the difference of the inner product values for
the two inner product measuring intervals averaged by the
inner product value averaging means, wherein the decision
executing means decides the fading frequency using also
the difference calculated by the difference calculating
means.
-
CA 02727686 2011-01-12
According to the invention as claimed in claim 45,
in the fading frequency decision device as claimed in claim
38,
the inner product value calculating means comprises:
normalizing means for normalizing the mean
values of the pilot symbols in each of the two sections
of the pilot channel with respect to each of multipath
signals to be used for RAKE combining;
inner product value calculation executing
means for calculating the inner product value of the mean
values of the two pilot symbols normalized by the
normalizing means for two or more cases with varying inner
product measuring interval with respect to each of the
multipath signals;
first inner product value averaging means for
averaging the inner product value for each path of the
multipath calculated by the inner product value
calculation executing means with respect to each of the
inner product measuring intervals; and
second inner product value averaging means for
averaging the inner product values averaged by the first
inner product value averaging means for a plurality of
sections of the control channel with respect to each of
the inner product measuring intervals, and
the decision means comprises
decision executing means for deciding the
fading frequency using the inner product value for each
31 -
CA 02727686 2011-01-12
of the inner product measuring intervals averaged by the
second inner product value averaging means.
According to the invention as claimed in claim 46,
the fading frequency decision device as claimed in claim
45, further comprises difference calculating means for
calculating the difference of the inner product values for
two inner product intervals averaged by the second inner
product value averaging means, wherein the decision
executing means decides the fading frequency also using
the difference calculated by the difference calculating
means.
According to the invention as claimed in claim 47,
a method for estimating a channel, comprises the steps of:
generating weighting factors to be used for weighting
and averaging pilot symbols being time multiplexed in a
control channel that was parallel multiplexed together
with a data channel; and
averaging the pilot symbols using the weighting
factors and calculating a channel estimation value of data
symbols of the data channel.
According to the invention as claimed in claim 48,
a method for deciding the fading frequency, comprises the
steps of:
calculating an inner product value of pilot symbols
being time multiplexed in a control channel that was
parallel multiplexed together with a data channel; and
deciding the fading frequency based on the inner
- 32 -
CA 02727686 2011-01-12
product value.
According to the invention as claimed in claim 49,
a channel estimation method for calculating a channel
estimation value of data symbols using pilot symbols in
a channel in which the data symbols and pilot symbols are
time multiplexed, comprises the steps of:
dividing the data symbols in the slots of the channel
into a plurality of data symbol sections, selecting the
pilot symbols appropriate for acquiring the channel
estimation value of the data symbols in each of the data
symbol sections, and generating weighting factors to be
used for weighting and averaging the pilot symbols; and
weighting and averaging the pilot symbols using the
weighting factors and calculating the channel estimation
value of the data symbols in each of the data symbol
sections.
According to the invention as claimed in claim 50,
a method for deciding the fading frequency, comprises the
step of:
calculating an inner product value of pilot symbols
in a channel in which data symbols and pilot symbols are
time multiplexed; and
deciding the fading frequency based on the inner
product value.
According to the invention as claimed in claim 51,
a channel estimation method for calculating a channel
estimation value of data symbols of a data channel using
33 -
CA 02727686 2011-01-12
pilot symbols of a pilot channel that was parallel
multiplexed together with the data channel, comprises the
steps of:
dividing the data symbols of the data channel into
a plurality of data symbol sections, selecting pilot
symbols appropriate for calculating the-channel estimation
value of the data symbols in each of the data symbol
sections, and generating weighting factors to be used for
weighting and averaging the pilot symbols; and
weighting and averaging the pilot symbols using the
weighting factors and calculating the channel estimation
value of the data symbols in each of the data symbol
sections.
According to the invention as claimed in claim 52,
in a method for deciding the fading frequency, the fading
frequency is decided based on an inner product value of
pilot symbols of a pilot channel that was parallel
multiplexed together with a data channel.
According to the invention as claimed in claim 53,
a demodulation device comprises:
channel estimating means for deriving N (N is natural
number greater than or equal to two) in number of channel
estimation values by weighted averaging of pilot signals
in time using N in number of weighted sequences;
compensating means for compensating data sequences
using the respective channel estimation values;
RAKE combining means for RAKE combining respective
34 -
CA 02727686 2011-01-12
of the N data sequences after compensation; and
reliability judgment means for selecting one data
sequence having highest reliability from the N data
sequences after RAKE combination.
According to the invention as claimed in claim 54,
a demodulation device comprises:
channel estimating means for deriving N (N is natural
number greater than or equal to two) in number of channel
estimation values by weighted averaging of pilot signal
in time using N in number of weighted sequences for data
sequences of predetermined frame number;
compensating means for compensating data sequence
using the respective channel estimation values;
RAKE combining means for RAKE combining of the N data
sequences after compensation; and
reliability judgment means for selecting N' (N':
natural number, N' < N) in number of weighting sequences
from the N data sequence after RAKE combining and selecting
one data sequence having the highest reliability from N
data sequences,
selection of the N' weighting sequences being
performed per a predetermined period, for remaining data
sequences until performing the reliability judgement again
the channel estimation means deriving N' channel
estimation value by weighted averaging in time using N'
weighting sequences, the compensating means compensating
data sequences using N' channel estimation values, the RAKE
-
CA 02727686 2011-01-12
combining means RAKE combining respective of N' data
sequences after compensation, and the reliability judgment
means selecting one data sequence having the highest
reliability from the N' data sequences.
According to the invention as claimed in claim 55,
in the demodulation device as claimed in claim 53 or 54,
the reliability judging means for judging reliability of
the data sequence comprises:
error-correction decoding means for performing
error-correction decoding of the data sequence after the
RAKE combination;
CRC (Cyclic Redundancy Check) bit extracting means
for extracting CRC bits added to the data sequence;
CRC decoding means for decoding the CRC for the data
sequence;
frame error detecting means for detecting the
presence or absence of a frame error based on a decoding
result of the CRC;
number-of-frame-error counting means for counting
the number of the frame errors in a previously-determined
measuring time; and
weight sequence and data selecting means for
selecting the weight sequence having high reliability and
the data sequence that is demodulated using the weight
sequence so selected based on the counting result of the
frame errors.
According to the invention as claimed in claim 56,
36 -
CA 02727686 2011-01-12
in the demodulation device as claimed in claim 53 or 54,
the reliability judging means for judging reliability of
the data sequence comprises:
error-correction decoding means for performing
error-correction decoding of the data sequence after the
RAKE combination;
likelihood information extracting means for
extracting likelihood information that is calculated when
performing the error-correction decoding of each of the
data sequences;
likelihood averaging means for averaging the
extracted likelihood information for a previously-
determined measuring time; and
weight sequence and data selecting means for
selecting the weight sequence having high reliability and
the data sequence that is demodulated using the weight
sequence so selected based on the averaged likelihood
information.
According to the invention as claimed in claim 57,
in the demodulation device as claimed in claim 53 or 54,
the reliability judging means for judging reliability of
the data sequence comprises:
electric power calculating means for calculating
electric power of each of the data sequences after the RAKE
combination;
electric power averaging means for averaging the
calculation result of the electric power for a
37 -
CA 02727686 2011-01-12
previously-determined measuring time; and
weight sequence and data selecting means for
selecting the weight sequence having high reliability and
data sequence that is demodulated using the weight sequence
so selected based on the averaged electric power.
According to the invention as claimed in claim 58,
in the demodulation device as claimed in claim 53 or 54,
the reliability judging means for judging reliability of
the data sequence comprises:
signal-to-noise ratio(ratio of a signal power to
a noise power) calculating means for calculating a
signal-to-noise ratio of each of the data sequences after
the RAKE combination;
signal-to-noise ratio averaging means for
averaging the calculation result of the signal-to-noise
ratio for a previously-determined measuring time; and
weight sequence and data selecting means for
selecting the weight sequence having high reliability and
the data sequence that is demodulated using the weight
sequence so selected based on the averaged signal-to-noise
ratio.
According to the invention as claimed in claim 59,
in the demodulation device as claimed in claim 53 or 54,
the reliability judging means for judging reliability of
the data sequence comprises:
error-correction decoding means for performing
error-correction decoding of the data sequence after the
38 -
CA 02727686 2011-01-12
RAKE combination;
CRC bit extracting means for extracting CRC bits
added to the data sequence;
CRC decoding means for decoding the CRC for the data
sequence;
frame error detecting means for detecting the
presence or absence of a frame error based on a decoding
result of the CRC;
number-of-frame-error counting means for counting
the number of the frame errors in a previously-determined
measuring time;
likelihood information extracting means for
extracting likelihood information that is calculated when
performing error-correction decoding of each of the data
sequences;
likelihood averaging means for averaging the
extracted likelihood information for a previously-
determined measuring time; and
weight sequence and data selecting means for
selecting the weight sequence having high reliability and
the data sequence that is demodulated using the weight
sequence so selected based on the counted number of frame
errors of the plurality of data sequences and the averaged
likelihood information.
According to the invention as claimed in claim 60,
in the demodulation device as claimed in claim 53 or 54,
the reliability judging means for judging reliability of
39 -
CA 02727686 2011-01-12
the data sequence comprises:
error-correction decoding means for performing
error-correction decoding of the data sequence after the
RAKE combination;
CRC bit extracting means for extracting CRC bits
added to the data sequence;
CRC decoding means for decoding the CRC for the data
sequence;
frame error detecting means for detecting the
presence or absence of a frame error based on a decoding
result of the CRC;
number-of-frame-error counting means for counting
the number of the frame errors in a previously-determined
measuring time;
electric power calculating means for calculating
electric power of each of the data sequences after the RAKE
combination;
electric power averaging means for averaging the
calculation result of the electric power for a
previously-determined measuring time; and
weight sequence and data selecting means for
selecting the weight sequence having high reliability and
the data sequence that is demodulated using the weight
sequence so selected based on the number of frame errors
and the averaged electric power.
According to the invention as claimed in claim 61,
in the demodulation device as claimed in claim 53 or 54,
- 40 -
CA 02727686 2011-01-12
the reliability judging means for judging reliability of
the data sequence comprises:
error-correction decoding means for performing
error-correction decoding of the data sequence after the
RAKE combination;
CRC bit extracting means for extracting CRC bits
added to the data sequence;
CRC decoding means for decoding the CRC for the data
sequence;
frame error detecting means for detecting the
presence or absence of a frame error based on a decoding
result of the CRC;
number-of-frame-error counting means for counting
the number of the frame errors in a previously-determined
measuring time;
signal-to-noise ratio calculating means for
calculating a signal-to-noise ratio (ratio of a signal
power to a noise power) of each of the data sequences after
the RAKE combination;
signal-to-noise ratio averaging means for
averaging the calculation result of the signal-to-noise
ratio for a previously-determined measuring time; and
weight sequence and data selecting means for
selecting weight sequence having high reliability and the
data sequence that is demodulated using the weight sequence
so selected based on the number of frame errors and the
averaged signal-to-noise ratio.
41 -
CA 02727686 2011-01-12
According to the invention as claimed in claim 62,
a demodulation device comprises:
channel estimating means for weighted averaging of
reception pilot signal using a plurality of weighting
sequences and deriving a plurality of channel estimation
values;
demodulating means for inputting data sequences and
outputting a plurality of demodulated data sequences using
the plurality of channel estimation values; and
reliability judging means for selecting one
demodulated data by making judgment of reliability of the
plurality of demodulated data sequences.
According to the invention as claimed in claim 63,
in the demodulation device as claimed in claim 62,
the reliability judging means comprises selecting
means for selecting predetermined number of the weight
sequences from among the plurality of weight sequences
based on a judgment result of reliability of the plurality
of demodulated data sequences, and
the demodulating means performs the demodulation
using only the predetermined number of the weight sequences,
when the predetermined number of the weight sequences were
selected.
According to the invention as claimed in claim 64,
in the demodulation device as claimed in any one of claims
53-63, the pilot signals are time multiplexed in a control
channel that was parallel multiplexed together with a data
42 -
CA 02727686 2011-01-12
channel in which the data sequence is contained.
According to the invention as claimed in claim 65,
in the demodulation device as claimed in any one of claims
53-63, the pilot signals are time multiplexed in one
channel together with the data sequence.
According to the invention as claimed in claim 66,
in the demodulation device as described in claim 65, the
channel estimating means divides the data sequence in the
slots of the channel into a plurality of data sequence
sections, selects pilot signals appropriate for
calculating the channel estimation value of the data in
each of the data sequence sections, and calculates the
channel estimation value of the data of each of the data
sequence sections by weighting and averaging the selected
pilot signals.
According to the invention as claimed in claim 67,
in the demodulation device as claimed in any one of claims
53-63, the pilot signals are contained in a pilot channel
that was parallel multiplexed together with the data
channel containing the data sequence.
According to the invention as claimed in claim 68,
in the demodulation device as claimed in claim 67, the
channel estimating means divides the data sequence into
a plurality of data sequence sections, selects pilot
signals appropriate for calculating the channel estimation
value of the data in each of the data sequence sections,
and calculates the channel estimation value of the data
43 -
CA 02727686 2011-01-12
in each of the data sequence sections by weighting and
averaging the selected pilot signals.
According to the invention as claimed in claim 69,
a demodulation method comprises:
the step of obtaining N pieces of channel estimation
values by time-weighting and averaging the pilot signals
using N (N: natural number greater than or equal to 2) sets
of weight sequences;
the step of compensating data sequence using each
of the channel estimation values; -
the step of RAKE combining each of the N sets of
the data sequences after the compensation; and
the reliability judgment step of selecting one set
of the data sequences having the highest reliability from
among the N sets of the data sequences after the RAKE
combination.
According to the invention as claimed in claim 70,
a demodulation method comprises:
the step of obtaining N (N: natural number greater
than or equal to 2) pieces of channel estimation values
by time-weighting and averaging pilot signals using N sets
of weight sequences with respect to a previously-
determined number of frames of data sequence;
the step of compensating the data sequence using
each of the channel estimation values;
the step of RAKE combining each of N sets of the
data sequences after the compensation; and
- 44 -
CA 02727686 2011-01-12
the reliability judgment step of selecting N' (N':
natural number; N'<N) sets of the weight sequences having
high reliability from among the N sets of the data sequences
after the RAKE combination and selecting one set of data
sequence having the highest reliability from among the N
sets of the data sequences after the RAKE combination,
wherein the selection of the N' sets of the weight
sequences,is conducted at regular intervals, and
throughout a period up to a time when the judgment of
reliability is made next time, with respect to remaining
part of the data sequence, in the step of estimating the
channel, N' pieces of the channel estimation values are
obtained by time-weighting and averaging the data sequence
using the N' sets of the weight sequences; in the step of
compensating, the data sequence is compensated using the
N' pieces of the channel estimation values; in the step
of the RAKE combination, each of the N' sets of the data
sequences after the compensation is RAKE combined; and in
the reliability judgment step, one set of the data sequence
having the highest reliability is selected from among the
N' sets of the data sequences.
According to the invention as claimed in claim 71,
in the demodulation method as claimed in claim 69 or 70,
the reliability judgment step comprises the steps of:
error-correction decoding the data sequence after
the RAKE combination;
extracting CRC bits added to the data sequence;
45 -
CA 02727686 2011-01-12
decoding the CRC with respect to the data sequence;
detecting the presence or absence of a frame error
based on the demodulation result of the CRC;
counting the number of the frame errors in a
previously-determined measuring time; and
selecting the weight sequence having high
reliability and the data sequence that is demodulated using
the weight sequence so selected based on the counting
result of the frame errors.
According to the invention as claimed in claim 72,
in the demodulation method as claimed in claim 69 or 70,
the reliability judgment step comprises the steps of:
error-correction decoding the data sequence after
the RAKE combination;
extracting likelihood information calculated when
performing error-correction decoding of each of the data
sequence;
averaging the extracted likelihood information for
a previously-determined measuring time; and
selecting the weight sequence having high
reliability and the data sequence that is demodulated using
the weight sequence so selected based on the averaged
likelihood information.
According to the invention as claimed in claim 73,
in the demodulation method as claimed in claim 69 or 70,
the reliability judgment step comprises the steps of:
calculating electric power of each of the data
46 -
CA 02727686 2011-01-12
sequences after the RAKE combination;
averaging the calculation result of the electric
power for a previously-determined measuring time; and
selecting the weight sequence having high
reliability and the data sequence that is demodulated using
the weight sequence so selected based on the averaged
electric power.
According to the invention as claimed in claim 74,
in the demodulation method as claimed in claim 69 or 70,
the reliability judgment step comprises the steps of:
calculating a signal-to-noise ratio of each of the
data sequences after the RAKE combination;
averaging the calculation result of the signal-
to-noise ratios for a previously-determined measuring
time; and
selecting the weight sequence having high
reliability and the data sequence that is demodulated using
the weight sequence so selected based on the averaged
signal-to-noise ratio.
According to the invention as claimed in claim 75,
in the demodulation method as claimed in claim 69 or 70,'
the reliability judgment step comprises the steps of:
performing error-correction decoding of the data
sequences after the RAKE combination;
extracting CRC bits added to the data sequence;
decoding the CRC with respect to the data sequence;
detecting the presence or absence of a frame error
47 -
CA 02727686 2011-01-12
based on the decoding result of the CRC;
counting the number of the frame errors in a
previously-determined measuring time;
extracting likelihood information that is
calculated when performing error-correction d decoding of
each of the data sequences;
averaging the extracted likelihood information for
a previously-determined measuring time; and
selecting the weight sequence having high
reliability and the data sequence that is demodulated using
the weight sequence so selected based on the measured
number of the frame errors of the plurality of the data
sequences and the averaged likelihood information.
According to the invention as claimed in claim 76,
in the demodulation method as claimed in either of claim
69 or 70, the reliability judgment step comprises the steps
of:
error-correction decoding the data sequences after
the RAKE combination;
extracting CRC bits added to the data sequence;
decoding the CRC with respect to the data sequence;
detecting the presence or absence of a frame error based
on the decoding result of the CRC;
counting the number of the frame errors in a
previously-determined measuring time;
calculating electric power of each of received data
sequences after the RAKE combination;
- 48 -
CA 02727686 2011-01-12
averaging the calculation result of the electric
power for a previously-determined measuring time; and
selecting the weight sequence having high
reliability and the data sequence that is demodulated using
the weight sequence so selected based on the number of frame
errors and the averaged electric power.
According to the invention as claimed in claim 77,
in the demodulation method of as claimed in claim 69 or
70, the reliability judgment step comprises the steps of:
error-correction decoding the data sequences after
the RAKE combination;
extracting CRC bits added to the data sequence;
decoding the CRC with respect to the data sequence;
detecting the presence or absence of a frame error
based on the decoding result of the CRC;
counting the number of the frame errors in a
previously-determined measuring time;
calculating a signal-to-noise ratio of each of the
data sequences after the RAKE combination;
averaging calculation result of the signal-to-
noise ratios for a previously-determined measuring time;
and
selecting the weight sequence having a high
reliability and the data sequence that is demodulated with
the weight sequence so selected based on the number of the
frame errors and the averaged signal-to-noise ratio.
According to the invention as claimed in claim 78,
49 -
CA 02727686 2011-01-12
a demodulation method comprises the steps of:
weighting and averaging pilot signals using a
plurality of weight sequences to obtain a plurality of
channel estimation values;
deriving a plurality of demodulated data sequences
from a data sequence using the plurality of channel
estimation values; and
selecting one output data sequence by making
judgment of reliability of the plurality of demodulated
data.
According to the invention as claimed in claim 79,
in the demodulation method as claimed in claim 78, based
on the judgment result of reliability of the plurality of
demodulated data sequences, a predetermined number of
weight sequences are selected from among the plurality of
weight sequences, and after the selection, demodulation
through the use of only the selected weight sequences is
performed .
According to the invention as claimed in claim 80,
in the demodulation method as claimed in any one of claims
69-79, the pilot signals are time multiplexed into a
control channel that is parallel multiplexed together with
the data channel in which the data sequence is contained.
According to the invention as claimed in claim 81,
in the demodulation method as claimed in any one of claims
69-79, the pilot signals are time multiplexed into one
channel together with the data sequence.
50 -
CA 02727686 2011-01-12
According to the invention as claimed in claim 82,
in the demodulation method as claimed in claim 81, the step
of estimating a channel divides the data sequence in the
slots of the channel into a plurality of data sequence
sections, selects pilot signals appropriate for
calculating the channel estimation value of the data of
each of the data sequence sections, and calculates a
channel estimation value of the data of each of the data
sequence sections by weighting and averaging the selected
pilot signals.
According to the invention as claimed in claim 83,
in the demodulation method as claimed in any one of claims
69-79, the pilot signals are contained in a pilot channel
that was parallel multiplexed together with the data
channel containing the data sequence.
According to the invention as claimed in claim 84,
in the demodulation method as claimed in claim 83, the step
of estimating a channel divides the data sequence into a
plurality of data sequence sections, selects pilot signals
appropriate for calculating the channel estimation value
of the data in each of the data sequence sections, and
calculates the channel estimation value of the data of each
of the data sequence sections by weighting and averaging
the selected pilot signals.
With the above configuration, accurate channel
estimation can be carried out in the parallel time
multiplexing method by subjecting pilot symbols to
51 -
CA 02727686 2011-01-12
weighted averaging to calculate a channel estimated value
for data symbols in a data channel.
In addition, accurate channel estimation can be
carried out by dividing data symbols within a slot into
a plurality of data symbol sections, selecting pilot
symbols appropriate for calculation of a channel estimated
value for data symbols within each of the data symbol
sections, and subjecting the pilot symbols to weighted
averaging to calculate the channel estimated value for the
data symbols in each data symbol section:
Further, a fading frequency can be decided based on
an inner product value of the pilot symbols. In addition,
channel estimation optimal for the fading frequency can
be realized using a simpler configuration.
In addition, with the above configuration of the
present invention, by preparing a plurality of weight
sequences ranging from one that becomes effective at a
lower movement speed for increasing the averaging time to
some degree to one that becomes-effective at a higher
movement speed for reducing the averaging time to some
degree and using all of the plural weight sequences
constantly or at fixed time intervals to execute
demodulation processing in parallel, a weight sequence
effective on various movement speeds can be directly
determined from reception quality for use, thereby
improving communication quality, reducing the amount of
transmission power required, and increasing the
52 -
CA 02727686 2011-01-12
communication capacity.
It is possible to use weighting sequences which are
adapted to various movement speeds to perform channel
estimation with high accuracy by performing channel
estimation using a plurality of weighting factors
constantly and selecting data sequence and weighting
factors with high reliability by reliability judgment
using received data sequence.
Further, by periodically selecting a small number of
weight factors and using only the selected weight factors
for channel estimation within a fixed period of time, loads
on the system can be diminished.
In addition, weight sequences effective on various
movement speeds are directly determined from reception
quality for use, thereby enabling improvement of
communication quality, a reduction in transmission power
required, and an increase in communication capacity
achieved.
The above and other objects, effects, features, and
advantages of the present invention will become more
apparent from the following description of embodiments
thereof taken in conjunction with the accompanying
drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
Fig. 1 is a view showing an exemplified configuration
of a frame structure of a signal received by a demodulation
- 53 -
CA 02727686 2011-01-12
device according to a first embodiment of the present
invention;
Fig. 2 is a view for use in describing how the
demodulation device according to the first embodiment of
the present invention estimates channels;
Fig. 3 is a block diagram showing a configuration of
a demodulation device according to the first embodiment;
Fig. 4 is a block diagram showing a configuration of
the channel estimation unit according to the first
embodiment;
Fig. 5 is a block diagram showing a configuration of
a fading frequency decision unit according to the first
embodiment;
Fig. 6 is a view illustrating an exemplified
calculation of the channel estimation value;
Fig. 7 is a view illustrating an operation to
calculate the channel estimation value for the respective
data symbol segments obtained by means of separating the
data symbols in a single slot;
Fig. 8 is a view illustrating calculations of the
channel estimation values for the respective data symbol
segments that are obtained by means of separating the data
symbols in a single slot;
Fig. 9 is a view illustrating calculations of the
channel estimation values for the respective data symbol
segments that are obtained by means of separating the data
symbols in a single slot;
54 -
CA 02727686 2011-01-12
Fig. 10 is a view illustrating calculations of the
channel estimation values for the respective data symbol
segments that are obtained by means of separating the data
symbols in a single slot;
Figs. 11A and-11B are views for use in describing a
concept of the fading frequency decision;
Fig. 12 is a graphical representation of a simulated
result obtained through a computer, in which the abscissa
represents a measurement time and the ordinate represents
a measured value with the fading frequency (fDTslot) being
used as a parameter;
Fig. 13 is a diagram showing relationship between
Figs. 13A and 13B;
Figs. 13A and 13B are block diagrams showing another
configuration of the fading frequency decision unit 150
according to the first embodiment;
Fig. 14 is a schematic diagram for explaining an
example of the fading frequency decision;
Fig. 15 shows an example of different transmission
rates for the data and control channels;
Fig. 16 is a drawing showing a frame configuration
example of a signal received by the demodulation device
in accordance with the second embodiment of the present
invention;
Fig. 17 is a block diagram showing a configuration
example of the demodulation device in accordance with the
second embodiment;
55 -
CA 02727686 2011-01-12
Fig. 18 is a drawing showing a case where data symbols
in one slot are divided into a plurality of data symbol
intervals and a channel estimation value is calculated for
every data symbol interval;
Fig. 19 is a drawing showing a case where data symbols
in one slot are divided into a plurality of data symbol
intervals and a channel estimation value is calculated for
every data symbol interval;
Fig. 20 is a drawing showing a case where data symbols
in one slot are divided into a plurality of data symbol
intervals and a channel estimation value is calculated for
every data symbol interval;
Fig., 21 is a drawing showing a case where data symbols
in one slot are divided into a plurality of data symbol
intervals and a channel estimation value is calculated for
every data symbol interval;
Fig. 22 is a drawing showing a frame configuration
example of a signal received by the demodulation device
in accordance with the third embodiment of the present
invention;
Fig. 23 is a block diagram showing a configuration
example of the demodulation device in accordance with the
third embodiment;
Fig. 24 is a block diagram showing a configuration
example of a channel estimation section in accordance with
the third embodiment;
Fig. 25 is a drawing showing a case where data symbols
56 -
CA 02727686 2011-01-12
in a data channel are divided into a plurality of data
symbol intervals and a channel estimation value is
calculated for every data symbol interval;
Fig. 26 is a drawing showing a case where data symbols
in a data channel are divided into a plurality of data
symbol intervals and a channel estimation value is
calculated for every data symbol interval;
Fig. 27 is a drawing showing a case where data symbols
in a data channel are divided into a plurality of data
symbol intervals and a channel estimation value is
calculated for every data symbol interval;
Figs. 28A and 28B are drawings to explain the concept
of determining a fading frequency;
Fig. 29 is a drawing showing an example of channel
estimation using pilot signals;
Fig. 30 is a diagram showing relationship between
Figs. 30A and 30B;
Figs. 30A and 30B are block diagrams showing the
fourth embodiment;
Fig. 31 is a diagram showing relationship between
Figs. 31A and 31B;
Figs. 31A and 31B are diagrams showing a modification
of the fourth embodiment;
Fig. 32 is a block diagram showing the reliability
judgment unit of the fifth embodiment;
Fig. 33 is a block diagram showing the reliability
judgment unit of the sixth embodiment;
57 -
CA 02727686 2011-01-12
Fig. 34 is a block diagram showing the reliability
judgment unit of the seventh embodiment;
Fig. 35 is a diagram showing relationship between
Figs. 35A and 35B;
Fig. 35A and 35B are block diagrams showing the
reliability judgment unit of the eighth embodiment;
Fig. 36 is a diagram showing relationship between
Figs. 36A and 36B;
Fig. 36A and 36B are block diagrams showing the
reliability judgment unit of the ninth embodiment;
Fig. 37 is a diagram showing relationship between
Figs. 37A and 37B;
Fig. 37A and 37B are block diagrams showing the
reliability judgment unit of the tenth embodiment; and
Fig. 38 is an illustration showing a dominant
conception in the fourth to tenth embodiments.
BEST MODE FOR CARRYING OUT THE INVENTION
The best mode for carrying out the invention will now
be described with reference to the accompanying drawings.
(First Embodiment)
Fig. 1 is a view showing an exemplified configuration
of a frame structure of a signal received by a demodulation
device according to a first embodiment of the present
invention. The demodulation device according to the
present invention receives and demodulates signals on a
- 58 -
CA 02727686 2011-01-12
data channel and a control channel that is parallel
multiplexed with the data channel. The control channel
carries time-multiplexed pilot symbols of a known
transmission pattern (of which phase is known, for example,
when phase modulation is the primary one). This is called
a parallel time multiplexing technique. The received
signal (phase and amplitude) at the pilot symbol is used
as a reference signal to estimate channel fluctuations of
data symbols on the data channel.
Fig. 2 is a view for use in describing how the
demodulation device according to the first embodiment of
the present invention estimates channels. The pilot
symbols are used for the channel estimation. More
specifically, the pilot symbols (estimated complex fading
envelopes) ~ are subjected to coherent combination to take
an average value thereof in two or more slots. A weighted
sum of the average values ~' are then taken with, for
example, weighting factors a 0, a 1 to thereby calculate a
channel estimation value a ''.
Fig. 2 is for the calculation of the channel
estimation value ~ '' (n) for the data symbols in the nth
slot with the channel estimation values of from ~'(n-2)
.to (n+3). The channel estimation value (n- 2) is
obtained from the average of the pilot symbols in the
(n-2) th pilot blocks that is formed of all pilot symbols
in the (n-2)th slot. The channel estimation value ~'(n+3)
is the one for the (n+3) th pilot block. The calculation
59 -
CA 02727686 2011-01-12
in Fig. 2 is carried out as follows:
3
"(n) Ia;= '(n+1) (1)
i=-2
With many pilot symbols belonging to different slots
enables highly accurate channel estimation. This is
because in an actual mobile propagation environment,
interference signals generated due to thermal noise (the
noise affects much particularly at cell edges to minimize
the transmission power), and by cross-correlation from
other users, are added to the desired signal of the current
channel, and the channel estimation accuracy is degraded
because of the phase and the amplitude of the received
signal that vary at every moment due to fading. For the
cases where the transmission power is controlled for each
slot, the pilot symbols in different slots have different
power. However, the channel estimation error due to the
power difference is less than the reduction effect by the
thermal noise and interference signals caused from using
pilot symbols in more slots.
Fig. 3 is a block diagram showing a configuration of
a demodulation device according to this embodiment. The
demodulation device of this embodiment comprises a data
channel matched filter 102, a delay unit 104, a control
channel matched filter 106, a channel estimation unit 120,
a multiplication unit 108, and a RAKE combiner 110. The
demodulation device according to this embodiment is based
60 -
CA 02727686 2011-01-12
on the code division multiple access (CDMA) architecture.
However, it is apparent that the present invention may be
applied to demodulation devices based on other
architectures including the time division multiple access
(TDMA) and the frequency division multiple access (FDMA) .
Fig. 4 is a block diagram showing a configuration of
the channel estimation unit according to this embodiment.
The channel estimation unit 120 of this embodiment
comprises a slot synchronization detector 122, a pilot
symbol averaging unit 124, delay units 126, 128, and 130,
multiplication units 132, 134, and 136, a weighting factor
controller 138, an adder 140, and a fading frequency
decision unit 150. The channel estimation unit 120 may
be implemented in the form of hardware. Alternatively,
it may be implemented in the form of software with, for
example, a digital signal processor (DSP).
Fig. 5 is a block diagram showing a configuration of
a fading frequency decision unit according to this
embodiment. The fading frequency decision unit 150 of
this embodiment comprises a normalization unit 152, an
inner product calculator 154, a first averaging unit 156,
a second averaging unit 158, and a threshold decision unit
160.
An operation of the demodulation device according to
this embodiment is now described with reference to Figs.
3 through 5. The data channel matched filter 102 despreads
a received spread signal on the data channel with a spread
61 -
CA 02727686 2011-01-12
code replica depending on the timing of the multiple path
reception by the individual users. The control channel
matched filter 106 despreads a received spread signal on
the control channel with the spread code replica depending
on the timing of the multiple path reception by the
individual users. The slot (pilot block) synchronization
detector 122 in the channel estimation unit 120 detects
the position of the pilot symbols on the control channel.
The pilot symbol averaging unit 124 averages the received
channels for the pilot symbols in each pilot block to
estimate the channel for the corresponding pilot block,
based on the timing information received.
The estimated channel information for each pilot
block is supplied to the delay units 126, 128, and 130 to
cause them to happen at the same time. Subsequently, with
the weighting factor generated by the weighting factor
controller 138, the multiplication units 132, 134, and 136,
and the adder 140 carries out the weighting averaging
(weighting sum) to calculate the channel estimation value.
As shown in, for example, Fig. 2, the channel
estimation value for the data symbol in the nth slot may
be calculated with the pilot blocks of from the (n-K+1) th
pilot block, wherein K is a natural number, to the (n+K)th
pilot block (K = 3 in the example in Fig. 2). Alternatively,
considering a delay, it may be calculated with the pilot
blocks of from (n-K+1) th pilot block to the nth pilot block.
Fig. 6 is a view illustrating an exemplified
62 -
CA 02727686 2011-01-12
calculation of the channel estimation value. In Fig. 6,
the channel estimation value for the data symbols in the
nth slot is calculated with the pilot blocks of from (n-1) th
pilot block to the (n+1)th pilot block. In this event,
a ratio of the weighting factors may be a _1: a0: a 1 =
0.4:1.0:0.4. It is preferable that the pilot blocks
closer (in time) to the data symbol of which channel
estimation value is to be calculated have a larger value
of the weighting factor. Such a closer pilot block
reflects more the state of a propagation path upon the
reception of the data symbol because the propagation path
varies at every moment. In the frame configuration in Fig.
6, the pilot blocks (pilot symbols) in the slot occur
previously (that is, they are located on the left side in
Fig. 6). It is thus possible that a better channel
estimation value be obtained with the ratio of the
weighting factors of, for example, a _1: a0: a 1 =
0.2 :1.0:0.6.. As apparent from the above, to determine the
weighting factors depending on the location of the pilot
symbols in the slot often results in the channel estimation
value of higher accuracy.
In Figs. 2 and 6, all pilot symbols in the slot are
used for the calculation of the channel estimation value.
In addition, the average of the pilot symbols in the pilot
block is calculated before taking the weighting average
thereof. However, the channel estimation value may be
calculated using only some of the pilot symbols in the slot.
63 -
CA 02727686 2011-01-12
The weighting factor may be determined for each pilot
symbol to take the weighting average of the pilot symbols.
No average calculation is required for the pilot block
having only one pilot symbol.
While the same channel estimation value is applied
to all data symbols in the single slot in Figs. 2 and 6,
the data symbols in the slot may be separated into two or
more data symbol segments to select a suitable pilot symbol
for the calculation of the channel estimation value in each
data symbol segment. In this event, the pilot symbols are
averaged with the weighting factors to estimate the channel
estimation value for the data symbols in each data symbol
segment.
Fig. 7 is a view illustrating an operation to
calculate the channel estimation value for the respective
data symbol segments obtained by means of separating the
data symbols in a single slot. In Fig. 7, the channel
estimation values are calculated with the pilot blocks of
from the (n-l)th pilot block to the (n+l)th pilot block
for the data symbol segments (1) , (2), and (3). Likewise,
the channel estimation values are calculated with the pilot
blocks of from the nth pilot block to the (n+2)th pilot
block for the data symbol segments (4), (5), and (6). The
channel estimation values may be calculated with the same
weighting factor for the data symbol segments (1), (2),
and (3). Alternatively, these values may be calculated
with different weighting factors. This is also true for
64 -
CA 02727686 2011-01-12
the data symbol segments (4), (5), and (6).
In Fig. 7, the same pilot symbol is selected for the
calculation of the channel estimation value for the data
symbols in the last data symbol segment (1) in the (n-
1)th slot and the calculation of the channel estimation
value for the data symbols in the first data symbol segment
(2) in the nth slot. The average of these pilot symbols
are taken with the weighting factor to obtain the channel
estimation value for the data symbols in each data symbol
segment.
Figs. 8 through 10 are views illustrating
calculations of the channel estimation values for the
respective data symbol segments that are obtained by means
of separating the data symbols in a single slot. In Figs.
8 through 10, two symbols before and two symbols after the
current symbol in the slot on the control channel serve
as the pilot symbols. Upon the estimation of the channel,
an average value for a certain number of pilot symbols is
calculated while shifting the symbol position successively.
In Figs. 8 through.10, no average value for the pilot
symbols for each pilot block is obtained. Instead, the
pilot symbols are directly averaged with the weighting
factor.
In Fig. 8, four pilot symbols are used to take the
weighting average. The data symbol in a single slot is
separated into three segments. In Fig. 9, four pilot
symbols are used to take the weighting average. The data
65 -
CA 02727686 2011-01-12
symbol in a single slot is thus separated into four segments.
In Fig. 10, eight pilot symbols are used to take the
weighting average. The data symbol in a single slot is
separated into three segments.
In Figs. 8 through 10, the same pilot symbol is
selected for the calculation of the channel estimation
value for the data symbols in the last data symbol segment
in the ith slot, where i is an integer, and the calculation
of the channel estimation value for the data symbols in
the first data symbol segment in the (i+1)th slot. The
average of these pilot symbols are taken with the weighting
factor to obtain the channel estimation value for the data
symbols in each data symbol segment.
In this embodiment, the weighting factors used for
taking the weighting average are varied depending on the
fading frequency. The fading frequency decision unit 150
decides the fading frequency based on the average value
for the pilot symbols. The weighting factor controller
138 varies the weighting factor according to the decision
result.
The fading frequency decision unit 150 normalizes the
average values for the pilot symbols in each of the two
slots on the control channel to calculate an inner product
value.
Figs. 11A and 11B are views for use in describing a
concept of the fading frequency decision. As shown in Fig.
11A, the channel estimation values in the slots correlates
66 -
CA 02727686 2011-01-12
with each other to a larger degree with the slower
fluctuation of the fading, indicated by a smaller fading
frequency. This provides a larger inner product value.
On the contrary, as shown in Fig. 11B, the channel
estimation values in the slots correlates with each other
to a smaller degree with the faster fluctuation of the
fading, indicated by a larger fading frequency. This
provides a smaller inner product value.
Fig. 12 is a graphical representation of a simulated
result obtained through a computer, in which the abscissa
represents a measurement time and the ordinate represents
a measured value with the fading frequency (fDTslot) being
used as a parameter. In Fig. 12, a threshold value is set
to, for example, 0.3 for the measured value in order to
decide whether the fading frequency is a fast fading of
0.3 or larger. The fading frequency of. 0.3 or larger is
decided when the measured value is smaller than the
threshold value.
The normalization unit 152 in the fading frequency
decision unit 150 normalizes the average values for the
pilot symbols in two pilot blocks, that is, two slots on
the control channel. The inner product calculator 154
calculates an inner product value of the average values
for the two normalized pilot symbols.
The demodulation device according to the present
embodiment is a demodulation device which performs the RAKE
combining and it performs the normalization and inner
67 -
CA 02727686 2011-01-12
product calculation for each of the multiple paths used
for the RAKE combining as described above. The inner
product values obtained from the multiple paths are
averaged by the first averaging unit 156. If such
averaging is not to be performed among the multiple paths,
the first averaging unit 156 is not required.
The average value calculated by the first averaging
unit 156 is further averaged among the plurality of slots
by the second averaging unit 158 (for example, the inner
product values (1), (2), and (3) are averaged in Fig.11A) .
This may reduce possible influence of thermal noise. If
such averaging is not to be performed among the plurality
of slots, the second averaging unit 158 is not required.
The threshold decision unit 160 compares the average
value calculated by the second averaging unit 158 with the
threshold to perform a fading frequency decision.
Specifically, it is decided which of the plurality of
regions the fading frequency belongs to, by performing a
threshold decision with a preset threshold by several steps.
The fading frequency decision is performed with the
threshold in the present embodiment and however, it may
be performed, for example, through calculations.
According to the present embodiment, the fading
frequency decision is performed by calculating an inner
product of the average value obtained from the pilot
symbols of two pilot blocks. These two pilot blocks may
be, for example, those for adjacent slots (for example,
-68-
CA 02727686 2011-01-12
the pilot blocks (1) and (2) in Fig. 11A) or those for every
other slot (for example, the pilot blocks (1) and (3) in
Fig.11A). Alternatively, the fading frequency decision
may be performed by calculating an-inner product of one
pilot symbol and another pilot symbol without any pilot
block.
If an inner produce (its average value) of pilot
symbols (their average value) (for example, an output of
the second averaging section 158 in Fig. 5) is larger than
a predetermined value, an average value calculated from
the pilot symbols of two slots at a longer interval in the
control channel may be subjected to the normalization, the
inner product calculation, the inner product averaging
among the multiple paths, and the inner product averaging
among the plurality of slots as described above and then
the averaged inner product value may be compared with a
threshold corresponding to such a longer interval to
perform the fading frequency decision.
As seen from a graph in Fig. 12 for the inner product
value with a fading frequency as a parameter, for higher
fading frequencies, it is possible to easily perform the
fading frequency decision with a threshold because a
difference in frequency results in a relatively large
difference in inner products (that is, a higher resolution).
On the contrary, for lower fading frequencies, it tends
to be difficult to perform the fading frequency decision
because such a difference in inner products is relatively
69 -
CA 02727686 2011-01-12
small (that is, a lower resolution).
The resolution for lower fading frequencies can be
enhanced by increasing an interval between slots which
include pilot symbols used for inner product calculation
(inner product measurement interval). For this purpose,
if an inner product value with a lower resolution is
initially obtained (from pilot symbols of slots at a
shorter interval) and the inner product value is larger
than a predetermined value (that is, the inner product
value is a frequency lower than a predetermined fading
frequency), much more accurate decision can be made with
respect to a wider range of frequencies from higher fading
frequencies to lower fading frequencies by using an inner
product value with a higher resolution (from pilot symbols
of slots at a longer interval) for the fading frequency
decision.
For example, if an inner product value (its average
value) of pilot symbols (their average value) of adjacent
slots (inner product measurement interval = one-slot
interval) (for example, an output of the second averaging
unit 158 in Fig. 5) is a value corresponding to a fading
frequency equal to or lower than a predetermined frequency,
the fading frequency decision can be made with a much higher
resolution by performing the threshold decision on another
inner product value of pilot symbols at a two-slot interval
which is longer than the previous interval by one slot.
If the inner product value for a two-slot interval
70 -
CA 02727686 2011-01-12
is a value corresponding to a fading frequency equal to
or lower than a predetermined lower frequency, the fading
frequency decision can be made more accurately by using
an inner product value of pilot symbols at a three-slot
interval which is longer than the previous interval by one
slot. Accordingly, the resolution can be enhanced by
increasing the inner product measurement interval
gradually. (The reason why the inner product measurement
interval is varied from a smaller value to a larger value
in this way is that the frequency which can'be decided for
a given inner product measurement interval may become lower
as the interval increases.)
It should be appreciated that several inner product
calculations with different inner product measurement
intervals can be performed in parallel and an appropriate
result can be obtained from even such a step-by-step
decision as described above for a short time by doing so.
It should be further appreciated that two or more
inner product values can be calculated with different inner
product measurement intervals to perform the fading
frequency decision.
Figs.13A and 13B are block diagrams showing another
configuration of the fading frequency decision unit 150
according to the present embodiment. The fading frequency
decision unit shown in Figs. 13A and 13B comprises a
normalization unit 162, delay units 163-1 and 163-2, inner
product calculators 164-1 and 164-2, first averaging units
71 -
CA 02727686 2011-01-12
166-1 and 166-2, second averaging units 168-1 and 168-
2, a difference operation unit 169, and a decision unit
170.
In the configuration example of Figs. 13A and 13B,
the inner product calculator 164-1 calculates an inner
product value for an inner product measurement interval
of one slot and the inner product calculator 164-2
calculates an inner product value for that of two slots
(that is, every other slot).
After the inner product values for these different
inner product measurement intervals are averaged among the
multiple paths by the first averaging units 166-1 and 166-2
and further averaged among the plurality of slots by the
second averaging units 168-1 and 168-2, the difference
operation unit 169 calculates a difference between the
inner product values for two different inner product
measurement intervals (a difference between the inner
product value for a one-slot interval and that for a
two-slot interval). Then the decision unit 170 performs
the fading frequency decision by using the inner product
value for a one-slot interval, that for a two-slot interval,
and a difference between them.
It should be appreciated that in the example of Figs.
13A and 13B, both the averaging among the multiple paths
and the averaging among the plurality of slots are
performed but either one or neither of them may be
performed.
- 72 -
CA 02727686 2011-01-12
Fig. 14 is a schematic diagram for explaining an
example of the fading frequency decision. In the example
of Fig. 14, the fading frequency decision is made by using
a point P1 (a point where the inner product value for a
two-slot interval coincides with the difference (absolute
value) first) , a point P 2 (a point where the inner product
value for a one-slot interval coincides with the difference
first) , and P 3 (a point where the inner product value for
a one-slot interval coincides with that for a two-slot
interval first). That is, as the result of such fading
frequency decision, any frequency will be decided to be
lower than the fading frequency at the point P 1, to be equal
to or higher than the fading frequency at the point P 1 and
lower than the fading frequency at the point P 2, to be equal
to or higher than the fading frequency at the point P2 and
lower than the fading frequency at the point P 3, or to be
higher than the fading frequency at the point P3.
It should be appreciated that such decision may
eliminate the need for threshold establishment. It should
be further appreciated that it can provide more thorough.
decision than the case where only one inner product value
is calculated for an inner product measurement interval.
Therefore, still more inner product values calculated with
more different intervals could provide much more thorough
decision.
In addition, the fading frequency decision can be
made by using only several inner product values without
73 -
CA 02727686 2011-01-12
any difference calculation. In that case, only the point
P3 in the example of Fig. 14 will be used for decision
Based on thus decided fading frequency, the weighting
factor controller 138 varies the weighting factor.
Considering the example of Fig. 6, if the fading frequency
is higher, a larger weighting factor is used for pilot
blocks close (in time) to the data symbols for which channel
estimation values are to be calculated, as compared with
that for a lower fading frequency. That is because, for
a higher fading frequency, channel fluctuation for data
symbols for which channel estimation values are to be
calculated is quite different from channel fluctuation for
pilot blocks distant (in time) from these data symbols.
For example, suppose that the weighting factor ratio for
a lower fading frequency is a -1: a 0: a 1=0.2:1. 0:0.6 and the
weighting factor ratio for a higher fading frequency is
1 = 0 . 0 5 : (on the assumption that the pilot
blocks in the nth slot, those in the (n+1) th slot, and those
in the (n-l)th slot are close, in this order, to data
symbols for which channel estimation values are
calculated).
It should be appreciated that, in the present
embodiment, the weighting factor used for calculating a
weighted average varies according to the fading frequency
but a fixed weighting factor may be used.
The channel estimation values (the output of the
adder 140) calculated as described above are used to
74 -
CA 02727686 2011-01-12
compensate for channel fluctuation (fading fluctuation)
of despread data symbols timed by the delay unit 104.
Specifically, the despread data symbols are multiplied by
the complex conjugates of the channel estimation values
to compensate for such channel fluctuation. Then the RAKE
combiner 110 carries out coherent combining of the
compensated signals.
It should be appreciated that, in the present
embodiment, the data channel has the same transmission rate
as that of the control channel but these two channels may
have different transmission rates.
Fig. 15 shows an example of different transmission
rates for the data and control channels. In the example
of Fig. 15, the control channel has half the transmission
rate of the data channel. Even if such different
transmission rates are used for these channels, channel
estimation values can be obtained from pilot symbols.
(Second Embodiment)
Fig. 16 is a drawing showing a frame configuration
example of a signal received by the demodulation device
in accordance with the second embodiment of the present
invention. The demodulation device in accordance with the
present embodiment receives and demodulates a signal of
a channel in which data symbols and pilot symbols are time
multiplexed (time multiplexing system). A signal
received by this pilot symbol section (phase, amplitude)
75 -
CA 02727686 2011-01-12
is used as a reference signal to estimate channel
fluctuations of data symbols. Pilot symbols are inserted
into data symbols at fixed intervals. The channel
estimation method in the demodulation device in accordance
with the present embodiment is the same as the channel
estimation method in the demodulation device in accordance
with the first embodiment of the present invention.
Fig. 17 is a block diagram showing a configuration
example of the demodulation device in accordance with the
present embodiment. The demodulation device in
accordance with the present embodiment comprises a matched
filter 202, a delay unit 204, a channel estimation unit
220, a multiplication unit 208 and a RAKE combiner 210.
Although the demodulation device in the present embodiment
is also compliant with a CDMA system, it is. also possible
to apply the present invention to demodulation devices
compliant with other systems (for example, TDMA system and
FDMA system). The demodulation device in the present
embodiment carries out multiple access transmission by
spreading a signal into a wideband signal using a spreading
code faster than an information rate.
The configuration example of the channel estimation
unit 220 in accordance with the present embodiment is the
same as the configuration example of the channel estimation
unit 120 in accordance with the first embodiment of the
present invention shown in Fig. 4. Slot synchronization
detector 122 detects pilot symbol locations in a channel
76 -
CA 02727686 2011-01-12
in which data symbols and pilot symbols are time
multiplexed. The configuration example of the fading
frequency decision unit of the present embodiment is also
the same as the configuration example of the fading
frequency decision unit 150 of the first embodiment of the
present invention shown in Fig. 5 (it can also be configured
as shown in Fig. 13A and Fig. 13B).
The operation of the demodulation device of the
present embodiment is also the same as the operation of
the demodulation device of the first embodiment of the
present invention.
Fig. 18 is a drawing showing a case where data symbols
in one slot are divided into a plurality of data symbol
intervals and a channel estimation value is calculated for
every data symbol interval. In the example of Fig. 18,
for data symbol intervals (1), and (2), a channel estimation
value is calculated using the (n-1) th pilot block to the
(n+l) th pilot block, and for data symbol intervals (3) and
(4), a channel estimation value is calculated using the
nth pilot block to the (n+2) th pilot block . The channel
estimation values for data symbol intervals (1) and (2)
can be calculated using a same weighting factor or using
different weighting factors. The same applies to data
symbol intervals (3) and (4).
Moreover, in the example of Fig. 18, in calculating
a channel estimation value of data symbols in the last data
symbol interval (1) of the (n-1)th slot and calculating
77 -
CA 02727686 2011-01-12
a channel estimation value of data symbols in the first
data symbol interval (2) of the nth slot, a same pilot
symbol is selected and the pilot symbol is weighted and
averaged to calculate a channel estimation value of data
symbols during each data symbol interval.
Fig. 19 to Fig. 21 also show cases where data symbols
in one slot are divided into a plurality of data symbol
intervals and a channel estimation value is calculated for
every data symbol interval. In the examples of Fig. 19
to Fig. 21, two symbols before and two symbols after a
control channel slot are pilot symbols. Furthermore, in
channel estimation, an average value for a certain number
of pilot symbols is calculated while moving the symbol
position successively. In the examples of Fig. 19 to Fig.
21, pilot symbols are directly weighted and averaged
without calculating an average value of pilot symbols for
each pilot block.
In the example of Fig. 19, four pilot symbols are used
for weighting and averaging and data symbols in one slot
are divided into three intervals. In the example of Fig.
20, four pilot symbols are used for weighting and averaging
and data symbols in one slot are divided into five intervals.
In the example of Fig.. 21, eight pilot symbols are used
for weighting and averaging and data symbols in one slot
are divided into three intervals.
In the examples of Fig. 19 to Fig. 21, in calculating
a channel estimation value of data symbols during the last
78 -
CA 02727686 2011-01-12
data symbol interval of the ith (i: an integer) slot and
calculating a channel estimation value of data symbols
during the first data symbol interval of the (i+l) th slot,
a same pilot symbol is selected and the pilot symbol is
weighted and averaged to calculate a channel estimation
value of data symbols during each data symbol interval.
In the present embodiment, weighting factors used for
weighting and averaging are changed according to the fading
frequency. However, it is also possible to use a fixed
weighting factor.
Data symbol channel fluctuations (fading
fluctuations) after despreading whose timing is determined
by the delay section 204 are compensated using the channel
estimation value obtained by the channel estimation
section 220. More specifically, channel fluctuations are
compensated by multiplying the despread data symbols by
a complex conjugate of the channel estimation value. Then,
the compensated signals are combined in-phase by the RAKE
combiner 210.
In the present embodiment, data symbols and pilot
symbols in a channel have a same transmission rate, but
data symbols and pilot symbols in the channel can also have
different transmission rates.
(Third Embodiment)
The above concept can also be applied to a parallel
system.
- 79 -
CA 02727686 2011-01-12
Fig. 22 is a drawing showing a frame configuration
example of a signal received by the demodulation device
in accordance with the third embodiment of the present
invention. The demodulation device in accordance with the
present embodiment receives and demodulates signals of a
data channel and a pilot channel, which is parallel
multiplexed with the data channel (parallel system). A
received signal (phase, amplitude) of the pilot symbol of
this pilot channel is used as a reference signal to estimate
channel fluctuations of data symbols in the data channel.
In the parallel system, unlike the parallel time
multiplexing system or time multiplexing system that
transmit/receive pilot symbols using some slots, pilot
symbols are transmitted/received consecutively, and
therefore the concept of a 'slot' is not so Important. For
this reason, slots are not indicated in Fig. 22.
The channel estimation method in the demodulation
device in accordance with the present embodiment is
basically the same as the channel estimation method by the
demodulation device in accordance with the first and second
embodiments, but specific examples will be explained
below.
Fig. 23 is a block diagram showing a configuration
example of the demodulation device in accordance with the
present embodiment. The demodulation device in
accordance with the present embodiment comprises a data
channel matched filter 302, a delay unit 304, a pilot
-80-
CA 02727686 2011-01-12
channel matched filter 306, a channel estimation unit 320,
a multiplication unit 308 and a RAKE combiner 310.
Although the demodulation device in the present embodiment
is also compliant with a CDMA system, it is also possible
to apply the present invention to demodulation devices
compliant with other systems (for example, TDMA system and
FDMA system).
Fig. 24 is a block diagram showing a configuration
example of a channel estimation section in accordance with
the present embodiment. The channel estimation unit 320
of the present embodiment comprises a pilot symbol
averaging unit 324, delay units 326, 328, 330, etc.,
multiplication units 332, 334, 336, etc., a weighting
factor controller 338, an adder 340 and a fading frequency
decision unit 350. The configuration example of the
fading frequency decision unit (fading frequency decision
unit 350) of the present embodiment is the same as the
configuration example of the fading frequency decision
unit 150 of the first embodiment of the present invention
shown in Fig. 5 (can also be configured as shown, in Fig.
13A and Fig. 13B).
The operation of the demodulation device of the
present embodiment is also basically the same as the
operation of the demodulation device of the first and
second embodiments.
Fig. 25 is a drawing showing a case where data symbols
in a data channel are divided into a plurality of data
81 -
CA 02727686 2011-01-12
symbol intervals and a channel estimation value is
calculated for every data symbol interval. In the example
of Fig. 25, data symbols are divided into intervals, with
each interval containing 3 symbols, and a channel
estimation value is calculated using the corresponding
pilot symbol interval (3-symbol configuration) on the time
scale and pilot symbol intervals before and after. More
specifically, channel estimation value ~" is calculated
by weighting channel estimation value ' (0) obtained from
averaging the 3 symbols in the pilot symbol interval
corresponding on the time scale, channel estimation values
' (-1) and s ' (1) obtained from averaging during the pilot
symbol intervals before and after, with a o, a _1 and a 1,
respectively and averaging them.
Fig. 26 and Fig. 27 are also drawings showing cases
where data symbols in a data channel are divided into a
plurality of data symbol intervals (one interval for one
symbol) and a channel estimation value is calculated for
every data symbol interval. In channel estimation, an
average value for a certain number of pilot symbols is
calculated while moving the symbol position successively.
In the examples of Fig. 26 and Fig. 27, pilot symbols are
directly weighted and averaged without weighting and
averaging after obtaining an average value of pilot symbols
as in the example of Fig. 25.
In the example of Fig. 26, four pilot symbols are used
for weighting and averaging and a pilot symbol used for
82 -
CA 02727686 2011-01-12
weighting and averaging is changed for every one data
symbol. In the example of Fig. 27, four pilot symbols are
used for weighting and averaging and a pilot symbol used
for weighting and averaging is changed for every two data
symbols.
In the present embodiment, the weighting factor used
for weighting and averaging is changed according to a
fading frequency. However, it is also possible to use a
fixed weighting factor.
Fig. 28A and Fig. 28B are drawings to explain the
concept of determining a fading frequency. The fading
frequency determining method of the present embodiment is
basically the same as the fading frequency determining
method of the first and second embodiments. In the first
and second embodiments, an average value of pilot symbols
of each of two slots is used. In the present embodiment,
an average value of pilot symbols of each of two pilot
channel intervals is used. The two intervals can be
discontinuous or continuous (discontinuous in the case of
Fig. 28). The number of pilot symbols included in. one
interval can be one or two or more.
In the present embodiment, as in the case of the first
and second embodiments, if a calculated inner product value
is larger than a predetermined value, it is possible to
calculate the inner product value by increasing the
interval (inner product measurement interval) at which a
pilot symbol used for calculation of the inner product
83 -
CA 02727686 2011-01-12
value is inserted. It is also possible to calculate two
or more inner products by changing the inner product
measurement interval and decides the fading frequency
using those inner product values.
Channel fluctuations (fading fluctuations) after
despreading whose timing is determined by the delay unit
304 are compensated using the channel estimation value
obtained from the channel estimation unit 320. More
specifically, channel. fluctuations are compensated by
multiplying the despread data symbols by a complex
conjugate of the channel estimation value. Then, the
compensated signals are combined in-phase by the RAKE
combiner 310.
In the present embodiment, as in the case of the first
embodiment, data channels and pilot channels can also have
different transmission rates.
(Fourth Embodiment)
At first, an averaging method of a pilot signal in
channel estimation to be used in the fourth to tenth
embodiment of the present invention will be described with
reference to Fig. 29. As shown in Fig. 29, from a
communication counterpart station, a known pilot symbol
of a transmission pattern (phase when a primary modulation
is phase modulation) is transmitted together with an
information data symbol. At this time, the pilot symbol
is not transmitted continuously as shown in Fig. 29 but
84 -
CA 02727686 2011-01-12
also intermittently. Namely, an insertion method of the
pilot symbol may be a parallel time multiplexing system
(Fig. 1) , time multiplexing system (Fig. 16) and a parallel
system (Fig. 22).
In order to perform estimation of phase fluctuation
of a propagation path to perform compensation (phase
correction) of a communication channel, a channel
estimation value is derived by averaging the pilot signal
of preceding and following zone of a reception data to be
corrected the phase. In the example of Fig. 29, in order
to derive a channel vector of N(th) symbol of the
communication channel, preceding and following pilot
signals are averaged using a weighting sequences a (here
a = {a(k)Ik = ... -1, 0, 1, ...)
It should be noted that when averaging is performed
using the weighting sequences, averaging is performed
using the weighting sequences after simple averaging per
arbitrary block greater than or equal to a chip unit.
In the fourth to tenth embodiment which will be
described hereinafter in detail, in a demodulation device
according to the direct sequence CDMA system, the channel
estimation value is derived by weighted averaging of the
pilot signal using a plurality of predetermined weighting
sequences. Then, using the derived channel estimation
value, the reception data is demodulated. By making
judgment for credibility of a plurality of demodulation
data, data of the highest quality is selected.
CA 02727686 2011-01-12
On the other hand, it is also possible to select some
of weighting sequences on the basis of result of judgment
of credibility of the demodulated data sequence in terms
of a certain given period. In this case, demodulation is
performed only by the weighting sequences selected,
subsequently.
(Construction of the Fourth Embodiment)
Figs. 30A and 30B are block diagrams showing the
fourth embodiment. In these drawings, 1 denotes a
io despreading unit, 2(including 2-1 to 2-N) denote channel
estimation units, 3 (including 3-i to 3-N) denotes
multipli ers, 4 (including 4-1 to 4-N) denote RAKE combiners,
5(including 5-i to 5-N) denote FEC decoders, 6 (including
6-1 to 6-N) denote CRC decoders, 7 (including 7-1 to 7-N)
denote frame error number counters, 8A denotes_a
reliability comparator, 9 denotes a reliability judgment
unit and 10 denotes a first switch.
(Operation of Fourth Embodiment)
Next, operation of the fourth embodiment of the CDMA
demodulation device shown in Figs. 30A and 30B will be
explained.
At first, a received spread signal is input to the
despreader 1. The input reception spread data sequence
is despread using a spread code replica depending upon a
timing of multiple path.
In the channel estimation units 2, N (N a' 2) in number
of the weighting sequences for performing averaging of the
86 -
CA 02727686 2011-01-12
pilot signals are provided. The pilot signals are
averaged with respective weighting sequences in parallel
to derive the channel estimation values.
In the multiplier 3, phase correction is performed
by multiplying the despread data sequence of the
communication channel with complex conjugate of respective
channel estimation values.
Next, in the RAKE combiners 4, the signals after phase
correction is coherent combined in all of RAKE fingers and
1o input to the reliability judgment unit 9.
In the reliability judgment unit 9, at first,
decoding of the error correction code is performed in the
FEC decoders 5 to output N in number of decoded data of
the weighting coefficient from #1 to W.
In the CRC decoder 6, decoding of CRC is performed
using the extracted CRC bit among decoded data sequence
to make judgment whether frame error is present or not to
input the result of judgment to the frame error number
counter 7.
In the frame error number counter 7, counting of the
frame error number present during a period of predetermined
number of frames is performed to input the counted number
to the reliability comparator 8.
In the reliability comparing and judgment unit 8A,
the data sequence having the least frame error number is
selected from the frame error information of N sequence
to output the foregoing data by switching the first switch
-87-
CA 02727686 2011-01-12
to the desired sequence.
(Effect of Fourth Embodiment)
As explained above, by the fourth embodiment, channel
estimation using a plurality of weighting coefficients is
5 constantly performed and weighting coefficients
corresponding to various motion speeds are used
simultaneously by selecting data having high reliability
through reliability judgment using the reception data
sequence to permit channel estimation at high precision.
10 On the other hand, using the result of CRC decoding,
judgment to lower of the frame error ratio can be performed
by selecting the weighting sequences having frame error.
(Modification of Fourth Embodiment)
In the explanation set forth above, while channel
estimation to CRC decoding is performed constantly using
N in number of weighting sequences, load of the system can
be reduced by the following modification.
A modification of the fourth embodiment is shown in
Figs. 31A and 31B.
In Figs. 31A and 31B, the same portions to those in
the fourth embodiment shown in Figs. 30A and 30B are
identified by the same reference numerals. 11 denote
second switches.
At every given period, concerning data sequence of
the predetermined number of frames, all of the second
switches 11 are turned ON to perform operation of the
foregoing fourth embodiment is performed in N sequences.
88 -
CA 02727686 2011-01-12
Also, in the reliability judgment unit 9, N' (here N':
natural number, 1 N' < N) in number of weighting sequences
having high reliability in the foregoing frame number are
selected. After judgment of reliability, concerning
remaining data sequence until performing reliability
judgment again in the foregoing time interval, only second
switches 11 of the selected weighting sequences are turned
ON, and other weighting sequences are turned OFF. Thus,
similar operation to the foregoing fourth embodiment is
performed in N' sequences using selected N' in number of
weighting sequences.
It should be noted that Figs. 31A and 31B show example
in which two sequences of weighting sequences #1 and #2
are selected (N' = 2) and only two sequences are in
operating condition.
(Fifth Embodiment)
(Construction of Fifth Embodiment)
Fig. 32 is a block diagram showing the reliability
judgment unit of this fifth embodiment. Other functional
blocks correspond to the fourth embodiment and will be
omitted from disclosure. The same portions to the fourth
embodiment shown in Figs. 30A and 30B are identified by
the same reference numerals. 12 (12-1 to 12-N) denote
likelihood averaging units.
(Operation of Fifth Embodiment)
Next, operation of the fifth embodiment of the
89 -
CA 02727686 2011-01-12
reliability judgment unit will be explained. Operation
of other functional block corresponds to those of the
fourth embodiment and explanation thereof is omitted.
The RAKE combined signal is input to the FEC decoder
5. In the FEC decoder 5, decoding of the error correction
code is performed to output decoding data from the
weighting sequence #1 to #N, and in conjunction therewith,
likelihood information calculated upon error correction
is input to the likelihood averaging unit 12.
In the likelihood averaging unit 12, input likelihood
is averaged over the predetermined number of frames, Y
frames (here, Y: natural number, Y Z 1) to input to the
reliability comparator 8. In the reliability comparator
8, from the likelihood information of the N sequences, the
data sequence having the highest reliability is selected
as information output.
(Effect of Fifth Embodiment)
As explained above, according to the fifth embodiment,
by using the likelihood information calculated upon error
correction decoding, judgment reflecting communication
quality (bit error ratio or the like) can be performed.
(Modification 1 of Fifth Embodiment)
In the foregoing explanation, while channel
estimation to CRC decoding is performed constantly using
N in number of weighting sequences, load of the system can
be reduced*by the following modification.
The modification of the fifth embodiment can be
90 -
CA 02727686 2011-01-12
constructed by replacing the reliability judgment unit of
the modification of the fourth embodiment shown in Figs.
31A and 31B with the fifth embodiment shown in Fig. 32.
At every given period, concerning data sequence of
the predetermined number of frames, all of the second
switches 11 are turned ON to perform operation of the
foregoing fourth embodiment is performed in N sequences.
Also, in the reliability judgment unit, N' (here N':
natural number, V5 N' < N) in number of weighting sequences
having high reliability in the foregoing frame number are
selected. After judgment of reliability, concerning
remaining data sequence until performing reliability
judgment again in the foregoing time interval, only second
switches 11 of the selected weighting sequences are turned
ON, and other weighting sequences are turned OFF. Thus,
similar operation to the foregoing fourth embodiment is
performed in N' sequences using selected N' in number of
weighting sequences.
(Modification 2 of Fifth Embodiment)
In the foregoing explanation, in the likelihood
averaging unit 12, in addition to a method of simple
averaging of the likelihood to predetermined number of
frames, Y frames (here, Y : natural number, Y Z 1) , weighted
averaging, method for selecting the minimum value and
method for selecting the maximum value may be taken.
(Sixth Embodiment)
91 -
CA 02727686 2011-01-12
(Construction of Sixth Embodiment)
Fig. 33 is a block diagram showing the reliability
judgment unit of this sixth embodiment. Other functional
blocks correspond to the fourth embodiment and will be
omitted from disclosure. The same portions to the fourth
embodiment shown in Figs. 30A and 30B are identified by
the same reference numerals. 13 (including 13-1 to 13-
N) denote power calculators.
(Operation of Sixth Embodiment)
Next, operation of the sixth embodiment of the
reliability judgment unit will be explained.
Operation of other functional block corresponds to those
of the fourth embodiment and explanation thereof is
omitted.
The RAKE combined signals are input to the power
calculators 13. In the power calculators 13, powers of
the signals after RAKE combination in N sequences are
calculated and averaged over the predetermined period.
The averaged power calculated values are input to the
reliability comparator. In the reliability comparing and
judgment unit 8, the data sequence having the highest
reliability is selected from the power calculated values
in N sequences to input to the FEC decoder 5. In the error
correction decoding is performed in the FEC decoder 5 and
is output as information output.
(Effect of Sixth Embodiment)
As explained above, in the shown sixth embodiment,
92 -
CA 02727686 2011-01-12
by using the reception power after RAKE combination in
reliability judgment, judgment to make the reception power
greater can be performed. Thus, communication quality
(frame error ratio or the like) can be improved, and also,
since judgment of reliability can be made by performing
FEC decoding, reduction of the load of the system becomes
possible.
(Modification of Sixth Embodiment)
In the foregoing explanation, channel estimation and
power calculation is performed constantly using N in number
of weighting sequences, load of the system can be reduced
by the following modification.
The modification of the sixth embodiment can be
constructed by replacing the reliability judgment unit of
the modification of the fourth embodiment shown in Figs.
31A and 31B with the sixth embodiment shown in Fig. 33.
At every given period, concerning data sequence of
the predetermined number of frames, all of the second
switches 11 are turned ON to perform operation of the
foregoing fourth embodiment is performed in N sequences.
Also, in the reliability judgment unit, N' (here N':
natural number, 1;5 N' < N) in number of weighting sequences
having high reliability in the foregoing frame number are
selected. After judgment of reliability, concerning
remaining data sequence until performing reliability
judgment again in the foregoing time interval, only second
switches 11 of the selected weighting sequences are turned
93 -
CA 02727686 2011-01-12
ON, and other weighting sequences are turned OFF. Thus,
similar operation to the foregoing fourth embodiment is
performed in N' sequences using selected N' in number of
weighting sequences.
(Seventh Embodiment)
(Construction of Seventh Embodiment)
Fig. 34 is a block diagram showing the reliability
judgment unit of this seventh embodiment. Other.
functional blocks correspond to the fourth embodiment and
will be omitted from disclosure. The same portions to the
fourth embodiment shown in Figs. 30A and 30B are identified
by the same reference numerals. 14 (including 14 -1 to 14 -N)
denote SN ratio calculators.
(Operation of Seventh Embodiment)
Next, operation of the seventh embodiment of the
reliability judgment unit will be explained. Operation
of other functional block corresponds to those of the
fourth embodiment and explanation thereof is omitted.
The RAKE combined signals are input to the SN ratio
calculators 12. In the SN ratio calculators 14, SN ratios
of the signals after RAKE combination in N sequences are
calculated and are averaged over the predetermined period.
The averaged SN radio calculated values are input to the
reliability comparator 8.
In the reliability comparator 8, the data sequence
having highest reliability is selected among SN ratio
94 -
CA 02727686 2011-01-12
calculated values in N sequences to be input to the FEC
decoder 5. Error correction decoding is performed in the
FEC decoder 5 to output as the information output.
(Effect of Seventh Embodiment)
As explained above, in the shown seventh embodiment,
by using the SN ratio after RAKE combination in reliability
judgment, judgment to make the SN ratio greater can be
performed. Thus, communication quality (frame error
ratio or the like) can be improved, and also, since judgment
of reliability can be made by performing FEC decoding,
reduction of the load of the system becomes possible.
(Modification of Seventh Embodiment)
In the foregoing explanation, channel estimation and
SN ratio calculation is performed constantly using N in
number of weighting sequences, load of the system can be
reduced by the following modification.
The modification of the seventh embodiment can be
constructed by replacing the reliability judgment unit of
the modification of the fourth embodiment shown in Figs.
31A and 31B with the seventh embodiment shown in Fig. 34.
At every given period, concerning data sequence of
the predetermined number of frames, all of the second
switches 11 are turned ON to perform operation of the
foregoing fourth embodiment is performed in N sequences.
Also, in the reliability judgment unit, N' (here N':
natural number, 15 N' < N) in number of weighting sequences
having high reliability in the foregoing frame number are
95 -
CA 02727686 2011-01-12
selected. After judgment of reliability, concerning
remaining data sequence until performing reliability
judgment again in the foregoing time interval, only second
switches 11 of the selected weighting sequences are turned
ON, and other weighting sequences are turned OFF. Thus,
similar operation to the foregoing fourth embodiment is
performed in N' sequences using selected N' in number of
weighting sequences.
(Eighth Embodiment)
(Construction of Eighth Embodiment)
Figs. 35A and 35B are block diagrams showing the
reliability judgment unit of this Eighth embodiment. The
functional blocks other than the reliability judgment unit
correspond to the fourth embodiment and will be omitted
from disclosure. The same portions to the fourth
embodiment shown in Figs. 30A and 30B are identified by
the same reference numerals.
(Operation of Eighth Embodiment)
Next, operation of the eighth embodiment of the
reliability judgment unit will be explained. Operation
of other functional block corresponds to those of the
fourth embodiment and explanation thereof is omitted.
The RAKE combined signals are input to the FEC
decoders 5. Decoding of the error correction code is
performed in the FEC decoders 5 to output decoded data with
the weighting coefficients #1 to #N, and also, likelihood
96 -
CA 02727686 2011-01-12
information calculated upon error correction is input to
the likelihood averaging unit 12.
In the likelihood averaging unit 12, input likelihood
is averaged over the predetermined number of frames, Y
frames (here, Y: natural number, Y Z 1) to input to the
reliability comparator 8.
On the other hand, in the CRC decoder 6, decoding of
CRC is performed using CRC bit extracted from the data
sequences decoded by the FEC decoder 5 to make judgment
whether the frame error is present or not to input the
result of judgment to the frame error number calculator
7.
In the frame error number calculator 7, counting of
the frame error number present in the predetermined Y2
frame (here Y2: natural number, Y2 Z 1) is performed to
input the counted number to the reliability comparator 8.
In the reliability comparator 8, the data sequence
having the highest reliability is selected as the
information output based on the likelihood information
input from-the likelihood averaging unit 12, among the
sequences having the lest frame error number based on the
frame error information of N sequences output from the
frame error number calculator 7.
(Effect of Eighth Embodiment)
As explained above, in the shown Eighth embodiment,
by using likelihood information calculated upon error
correction decoding in addition to the counted frame error
97 -
CA 02727686 2011-01-12
number from the result of CRC decoding, in reliability
judgment, the judgment factors are mutually combined to
permit strict reliability judgment.
(Modification 1 of Eighth Embodiment)
In the foregoing explanation, channel estimation and
CRC decoding is performed constantly using N in number of
weighting sequences, load of the system can be reduced by
the following modification.
The modification of the Eighth embodiment can be
constructed by replacing the reliability judgment unit of
the modification of the fourth embodiment shown in Figs.
31A and 31B with the eighth embodiment shown in Figs. 35A
and 35B.
At every given period, concerning data sequence of
the predetermined number of frames, all of the second
switches 11 are turned ON to perform operation of the
foregoing fourth embodiment is performed in N sequences.
Also, in the reliability judgment unit, N' (here N':
natural number, 1 S N' < N) in number of weighting sequences
having high reliability in the foregoing frame number are
selected. After judgment of reliability, concerning
remaining data sequence until performing reliability
judgment again in the foregoing time interval, only second
switches 11 of the selected weighting sequences are turned
ON, and other weighting sequences are turned OFF. Thus,
similar operation to the foregoing fourth embodiment is
performed in N' sequences using selected N' in number of
98 -
CA 02727686 2011-01-12
weighting sequences.
(Modification 2 of Eighth Embodiment)
In the foregoing explanation, in the likelihood
averaging unit 12, in addition to a method of simple
averaging of the likelihood to predetermined number of
frames, Y frames (here, Y1: natural number, Y1 Z1),
weighted averaging, method for selecting the minimum value
and method for selecting the maximum value may be taken.
(Ninth Embodiment)
(Construction of Ninth Embodiment)
Figs. 36A and 36B are block diagrams showing the
reliability judgment unit of this ninth embodiment. The
functional blocks other than the reliability judgment unit
correspond to the fourth embodiment and will be omitted
from disclosure. The same portions to the fourth
embodiment shown in Figs. 31A and 31B are identified by
the same reference numerals.
(Operation of Ninth Embodiment)
Next, operation of the ninth embodiment of the
reliability judgment unit will be explained. Operation
of other functional block corresponds to those of the
fourth embodiment and explanation thereof is omitted.
The RAKE combined signals are input to the power
calculator 13. In the power calculator 13, the power of
the signals after RAKE combination in N sequences are
calculated. After averaging over the predetermined
99 -
CA 02727686 2011-01-12
period, the calculated value is input to the reliability
comparator 8.
On the other hand, in the FEC decoders 5, decoding
of the error correction code is performed to output decoded
data with the weighting coefficients #1 to #N, and, in the
CRC decoder 6, decoding of CRC is performed using CRC bit
extracted from the data sequences decoded by the FEC
decoder 5 to make judgment whether the frame error is
present or not to input the result of judgment to the frame
error number calculator 7.
In the frame error number calculator 7, counting of
the frame error number present in the predetermined Y frame
(here Y2: natural number, Y 2t 1) is performed to input the
counted number to the reliability comparator 8.
In the reliability comparator 8, the data sequence
having the highest reliability is selected as the
information output based on the power calculated value,
among the sequences having the lest frame error number
based on the frame error information of N sequences output
from the frame error number calculator 7.
(Effect of Ninth Embodiment)
As explained above, in the shown ninth embodiment,
by using the received power after RAKE combination in
addition to the counted frame error number from the result
of CRC decoding, in reliability judgment, the judgment
factors are mutually combined to permit strict reliability
judgment.
- 100 -
CA 02727686 2011-01-12
(Modification 1 of Ninth Embodiment)
In the foregoing explanation, channel estimation and
CRC decoding is performed constantly using N in number of
weighting sequences, load of the system can be reduced by
the following modification.
The modification of the ninth embodiment can be
constructed by replacing the reliability judgment unit of
the modification of the fourth embodiment shown in Figs.
31A and 31B with the ninth embodiment shown in Figs. 36A
and 36B.
At every given period, concerning data sequence of
the predetermined number of frames, all of the second
switches 11 are turned ON to perform operation of the
foregoing fourth embodiment is performed in N sequences.
Also, in the reliability judgment unit, N' (here N':
natural number, 1;5 N' < N) in number of weighting sequences
having high reliability in the foregoing frame number are
selected. After judgment of reliability, concerning
remaining data sequence until performing reliability
judgment again in the foregoing time interval, only second
switches 11 of the selected weighting sequences are turned
ON, and other weighting sequences are turned OFF. Thus,
similar operation to the foregoing fourth embodiment is
performed in N' sequences using selected N' in number of
weighting sequences.
(Tenth Embodiment)
- 101 -
CA 02727686 2011-01-12
(Construction of Tenth Embodiment)
Figs. 37A and 37B are block diagrams showing the
reliability judgment unit of this tenth embodiment. The
functional blocks other than the reliability judgment unit
correspond to the fourth embodiment and will be omitted
from disclosure. The same portions to the fourth
embodiment shown in Figs. 31A and 31B are identified by
the same reference numerals.
(Operation of Tenth Embodiment)
Next, operation of the tenth embodiment of the
reliability judgment unit will be explained. Operation
of other functional block corresponds to those of the
fourth embodiment and explanation thereof is omitted.
The RAKE combined signals are input to the SN ratio
calculators 12. In the SN ratio calculators 14, SN ratios
of the signals after RAKE combination in N sequences are
calculated and are averaged over the predetermined period.
The averaged SN radio calculated values are input to the
reliability comparator 8.
On the other hand, in the FEC decoders 5, decoding
of the error correction code is performed to output decoded
data with the weighting coefficients #1 to #N, and, in the
CRC decoder 6, decoding of CRC is performed using CRC bit
extracted from the data sequences decoded by the FEC
decoder 5 to make judgment whether the frame error is
present or not to input the result of judgment to the frame
error number calculator 7.
-102-
CA 02727686 2011-01-12
In the frame error number calculator 7, counting of
the frame error number present in the predetermined Y frame
(here Y2: natural number, Y Z 1) is performed to input the
counted number to the reliability comparator 8.
In the reliability comparator 8, the data sequence
having the highest reliability is selected as the
information output based on the SN ratio calculated value,
among the sequences having the least frame error number
based on the frame error information of N sequences output
from the frame error number calculator 7.
(Effect of Tenth Embodiment)
As explained above, in the shown tenth embodiment,
by using the SN ratio after RAKE combination in addition
to the counted frame error number from the result of CRC
decoding, in reliability judgment, the judgment factors
are mutually combined to permit strict reliability
judgment.
(Modification 1 of Tenth Embodiment)
In the foregoing explanation, channel estimation. and
CRC decoding is performed constantly using N in number of
weighting sequences, load of the system can be reduced by
the following modification.
The modification of the tenth embodiment can be
constructed by replacing the reliability judgment unit of
the modification of the fourth embodiment shown in Figs.
31A and 31B with the tenth embodiment shown in Figs. 37A
103 -
CA 02727686 2011-01-12
and 37B.
At every given period, concerning data sequence of
the predetermined number of frames, all of the second
switches 11 are turned ON to perform operation of the
foregoing fourth embodiment is performed in N sequences.
Also, in the reliability judgment unit, N' (here N':
natural number, 1;5 N' < N) in number of weighting sequences
having high reliability in the foregoing frame number are
selected. After judgment of reliability, concerning
remaining data sequence until performing reliability
judgment again in the foregoing time interval, only second
switches 11 of the selected weighting sequences are turned
ON, and other weighting sequences are turned OFF. Thus,
similar operation to the foregoing fourth embodiment is
performed in N' sequences using selected N' in number of
weighting sequences.
(Summarization of Fourth to Tenth Embodiments)
Fig. 38 is an illustration showing a dominant
conception in the fourth to tenth embodiments explained
above. In Fig. 38, 30 denotes despreader, 40 (including
40-1 to 40-N) denote receiving unit, 50 (including 50-1
to 50-N) denote quality measuring units, 60 denotes a
quality comparing and judging unit, and 70 denotes an
output switch.
Namely, in the demodulation device according to the
direct sequence CDNA system, weighted averaging of the
pilot signal using predetermined plurality of weighting
104 -
CA 02727686 2011-01-12
sequences is performed to derive the channel estimation
values. Then, using the derived channel estimation values,
the received data is demodulated (40) to make judgment of
reliability of a plurality of demodulation data to select
one of output data of the best quality (50, 60, 70).
On the other hand, concerning a certain given period,
it is possible to select some of the weighting sequences
on the basis of the result of judgment of the reliability
of the demodulated data sequences. In this case,
subsequently, demodulation is performed only by the
selected weighting sequences.
It should be noted that, as the channel estimation
unit 2 of the fourth to the tenth embodiments, the channel
estimation units 120, 220 and 320 in the first to third
embodiments may also be used.
As described above, according to the present
invention, accurate channel estimation can be carried out
in the parallel time multiplexing method by subjecting
pilot symbols to weighted averaging to calculate a channel
estimated value for data symbols in a data channel.
In addition, accurate channel estimation can be
carried out by dividing data symbols within a slot into
a plurality of data symbol sections, selecting pilot
symbols appropriate for calculation of a channel estimated
value for data symbols within each of the data symbol
sections, and subjecting the pilot symbols to weighted
105 -
CA 02727686 2011-01-12
averaging to calculate the channel estimated value for the
data symbols in each data symbol section.
Further, a fading frequency can be decided based on
an inner product value of the pilot symbols. In addition,
channel estimation optimal for the fading frequency can
be.realized using a simpler configuration.
Once accurate channel estimation has been achieved,
the absolute synchronous detection method can be used to
reduce the SNIR required to obtain a required reception
quality (reception error rate). As a result, the required
transmission power can be diminished to increase the
capacity for system subscribers.
The results of decision obtained by the fading
frequency decision unit can be used not only for setting
the weight factor for channel estimation but also for
operation switching or parameter setting for various
individual techniques the performance (transmission
characteristic) of which is affected by the movement speed
of a mobile terminal (portable terminal), for example,
switching between an operative and inoperative states for
transmission power control or for transmission diversity.
In addition, according to the present invention, a
weight sequence effective on a movement speed is directly
determined from reception quality for use, thereby
enabling improvement of communication quality, a reduction
in transmission power required, and an increase in
communication capacity achieved. More specifically, the
106 -
CA 02727686 2011-01-12
present invention can provide the following effects:
(1) Since weight sequences suitable for various
movement speeds can be sequentially selected, accurate
channel estimation is possible. This enables a reduction
in transmission power required, improvement of reception
quality, and an increase in communication capacity
achieved.
(2) Except for a fixed period of time, a selected one
of the weight sequences alone can be used to simplify the
system.
(3) By using the CRC to determine the reliability of
data, accurate reliability determination can be achieved.
(4) By using the likelihood obtained during recovery
of the FEC to determine the reliability of data, accurate
reliability determination can be accomplished.
(5) By using the power or SN ratio of the data sequence
during data reliability determination, the reliability can
be determined faster and more simply, thereby restraining
an increase in hardware scale.
The present invention has been described in detail
with respect to various embodiments, and it will now be
apparent from the foregoing to those skilled in the art
that changes and modifications may be made without
departing from the invention in its broader aspects, and
it is the intention, therefore, in the appended claims to
cover all such changes and modifications as fall within
the true spirit of the invention.
- 10 7 -
