U.S. patent application number 11/210946 was filed with the patent office on 2005-12-22 for multi-user detection using an adaptive combination of joint detection and successive interference cancellation.
This patent application is currently assigned to InterDigital Technology Corporation. Invention is credited to Misra, Raj Mani, Pan, Jung-Lin, Zeira, Ariela.
Application Number | 20050281214 11/210946 |
Document ID | / |
Family ID | 26885406 |
Filed Date | 2005-12-22 |
United States Patent
Application |
20050281214 |
Kind Code |
A1 |
Misra, Raj Mani ; et
al. |
December 22, 2005 |
Multi-user detection using an adaptive combination of joint
detection and successive interference cancellation
Abstract
A time division duplex communication system using code division
multiple access transmits a plurality of data signals over a shared
spectrum in a time slot. A combined signal is received over the
shared spectrum in the time slot. The plurality of data signals are
grouped into a plurality of groups. The combined signal is matched
filtered based on in part symbol responses associated with the data
signals of one of the groups. Data from each data signal in the one
group is jointly detected. An interference signal is constructed
based on in part the one group detected data. The constructed
interference signal is subtracted from the combined signal. Data
from the other groups is detected by processing the subtracted
signal.
Inventors: |
Misra, Raj Mani; (Fremont,
CA) ; Zeira, Ariela; (Huntington, NY) ; Pan,
Jung-Lin; (Selden, NY) |
Correspondence
Address: |
VOLPE AND KOENIG, P.C.
DEPT. ICC
UNITED PLAZA, SUITE 1600
30 SOUTH 17TH STREET
PHILADELPHIA
PA
19103
US
|
Assignee: |
InterDigital Technology
Corporation
Wilmington
DE
|
Family ID: |
26885406 |
Appl. No.: |
11/210946 |
Filed: |
August 24, 2005 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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11210946 |
Aug 24, 2005 |
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09783792 |
Feb 15, 2001 |
|
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6963546 |
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60189680 |
Mar 15, 2000 |
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60207700 |
May 26, 2000 |
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Current U.S.
Class: |
370/321 ;
375/E1.025; 375/E1.03 |
Current CPC
Class: |
H04L 25/03331 20130101;
H04B 1/7105 20130101; H04L 25/03305 20130101; H04B 1/71072
20130101 |
Class at
Publication: |
370/321 |
International
Class: |
H04B 007/212 |
Claims
What is claimed is:
1. A method for use in a receiver for receiving a plurality of data
signals transmitted over a shared spectrum in a time slot in a time
division duplex communication system using code division multiple
access, the method comprising: receiving a combined signal over the
shared spectrum in the time slot; estimating a received power level
for each data signal; selectively grouping data signals of the
plurality of data signals based on in part the received power level
of the data signals into at least one group; and separately
detecting data within each group for that group's data signals; and
wherein the estimating the received power level for each data
signal is based on in part a power level of a training sequence
associated with each data signal.
2. A method for use in a receiver for receiving a plurality of data
signals transmitted over a shared spectrum in a time slot in a time
division duplex communication system using code division multiple
access, the method comprising: receiving a combined signal over the
shared spectrum in the time slot; estimating a received power level
for each data signal; selectively grouping data signals of the
plurality of data signals based on in part the received power level
of the data signals into at least one group; and separately
detecting data within each group for that group's data signals;
wherein the estimating the received power level for each data
signal is based on in part apriori knowledge at the receiver.
3. The method of claim 1 wherein the selectively grouping data
signals groups data signals within a certain threshold power level
into a group.
4. The method of claim 3 wherein the certain threshold power level
is one decibel.
5. A method for use in a receiver for receiving a plurality of data
signals transmitted over a shared spectrum in a time slot in a time
division duplex communication system using code division multiple
access, the method comprising: receiving a combined signal over the
shared spectrum in the time slot; estimating a received power level
for each data signal; selectively grouping data signals of the
plurality of data signals based on in part the received power level
of the data signals into at least one group; and separately
detecting data within each group for that group's data signals;
wherein the selectively grouping data signals groups data signals
within a certain threshold power level into a group and the certain
threshold is adjusted to achieve a desired bit error rate at the
receiver.
6. The method of claim 1 further comprising forcing all of the data
signals into a single group to override the step of selectively
grouping.
7. The method of claim 1 further comprising forcibly grouping each
data signal into its own group to override the step of selectively
grouping.
Description
[0001] This application is a continuation of U.S. patent
application Ser. No. 09/783,792, filed Feb. 15, 2001, which claims
priority to U.S. Provisional Patent Application No. 60/189,680,
filed on Mar. 15, 2000 and U.S. Provisional Patent Application No.
60/207,700, filed on May 26, 2000 which are incorporated by
reference as if fully set forth.
BACKGROUND
[0002] The invention generally relates to wireless communication
systems. In particular, the invention relates to joint detection of
multiple user signals in a wireless communication system.
[0003] FIG. 1 is an illustration of a wireless communication system
10. The communication system 10 has base stations 12.sub.1 to
12.sub.5 which communicate with user equipments (UEs) 14.sub.1 to
14.sub.3. Each base station 12.sub.1 has an associated operational
area where it communicates with UEs 14.sub.1 to 14.sub.3 in its
operational area.
[0004] In some communication systems, such as code division
multiple access (CDMA) and time division duplex using code division
multiple access (TDD/CDMA), multiple communications are sent over
the same frequency spectrum. These communications are typically
differentiated by their chip code sequences. To more efficiently
use the frequency spectrum, TDD/CDMA communication systems use
repeating frames divided into time slots for communication. A
communication sent in such a system will have one or multiple
associated chip codes and time slots assigned to it based on the
communication's bandwidth.
[0005] Since multiple communications may be sent in the same
frequency spectrum and at the same time, a receiver in such a
system must distinguish between the multiple communications. One
approach to detecting such signals is matched filtering. In matched
filtering, a communication sent with a single code is detected.
Other communications are treated as interference. To detect
multiple codes, a respective number of matched filters are used.
Another approach is successive interference cancellation (SIC). In
SIC, one communication is detected and the contribution of that
communication is subtracted from the received signal for use in
detecting the next communication.
[0006] In some situations, it is desirable to be able to detect
multiple communications simultaneously in order to improve
performance. Detecting multiple communications simultaneously is
referred to as joint detection. Some joint detectors use Cholesky
decomposition to perform a minimum mean square error (MMSE)
detection and zero-forcing block equalizers (ZF-BLEs). These
detectors have a high complexity requiring extensive receiver
resources.
[0007] Accordingly, it is desirable to have alternate approaches to
multi-user detection.
SUMMARY
[0008] A time division duplex communication system using code
division multiple access transmits a plurality of data signals over
a shared spectrum in a time slot. A combined signal is received
over the shared spectrum in the time slot. The plurality of data
signals are grouped into a plurality of groups. The combined signal
is matched filtered based on in part symbol responses associated
with the data signals of one of the groups. Data from each data
signal in the one group is jointly detected. An interference signal
is constructed based on in part the one group detected data. The
constructed interference signal is subtracted from the combined
signal. Data from the other groups is detected by processing the
subtracted signal.
BRIEF DESCRIPTION OF THE DRAWINGS
[0009] FIG. 1 is a wireless communication system.
[0010] FIG. 2 is a simplified transmitter and a receiver using
joint detection.
[0011] FIG. 3 is an illustration of a communication burst.
[0012] FIG. 4 is a flow chart of adaptive combination of joint
detection and successive interference cancellation.
[0013] FIG. 5 is an illustration of an adaptive combination of
joint detection and successive interference cancellation
device.
[0014] FIGS. 6-12 are graphs comparing the performance of adaptive
combination of joint detection and successive interference
cancellation, full joint detection and a RAKE receiver.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0015] FIG. 2 illustrates a simplified transmitter 26 and receiver
28 using an adaptive combination of joint detection (JD) and
successive interference cancellation (SIC), "SIC-JD", in a TDD/CDMA
communication system. In a typical system, a transmitter 26 is in
each UE 14.sub.1 to 14.sub.3 and multiple transmitting circuits 26
sending multiple communications are in each base station 12.sub.1
to 12.sub.5. A base station 12.sub.1 will typically require at
least one transmitting circuit 26 for each actively communicating
UE 14.sub.1 to 14.sub.3. The SIC-JD receiver 28 may be at a base
station 12.sub.1, UEs 14.sub.1 to 14.sub.3 or both. The SIC-JD
receiver 28 receives communications from multiple transmitters 26
or transmitting circuits 26.
[0016] Each transmitter 26 sends data over a wireless radio channel
30. A data generator 32 in the transmitter 26 generates data to be
communicated over a reference channel to a receiver 28. Reference
data is assigned to one or multiple codes and/or time slots based
on the communications bandwidth requirements. A modulation and
spreading device 34 spreads the reference data and makes the spread
reference data time-multiplexed with a training sequence in the
appropriate assigned time slots and codes. The resulting sequence
is referred to as a communication burst. The communication burst is
modulated by a modulator 36 to radio frequency. An antenna 38
radiates the RF signal through the wireless radio channel 30 to an
antenna 40 of the receiver 28. The type of modulation used for the
transmitted communication can be any of those known to those
skilled in the art, such as direct phase shift keying (DPSK) or
quadrature phase shift keying (QPSK).
[0017] A typical communication burst 16 has a midamble 20, a guard
period 18 and two data bursts 22, 24, as shown in FIG. 3. The
midamble 20 separates the two data bursts 22, 24 and the guard
period 18 separates the communication bursts to allow for the
difference in arrival times of bursts transmitted from different
transmitters. The two data bursts 22, 24 contain the communication
burst's data and are typically the same symbol length. The midamble
contains a training sequence.
[0018] The antenna 40 of the receiver 28 receives various radio
frequency signals. The received signals are demodulated by a
demodulator 42 to produce a baseband signal. The baseband signal is
processed, such as by a channel estimation device 44 and a SIC-JD
device 46, in the time slots and with the appropriate codes
assigned to the communication bursts of the corresponding
transmitters 26. The channel estimation device 44 uses the training
sequence component in the baseband signal to provide channel
information, such as channel impulse responses. The channel
information is used by the SIC-JD device 46 to estimate the
transmitted data of the received communication bursts as hard
symbols.
[0019] The SIC-JD device 46 uses the channel information provided
by the channel estimation device 44 and the known spreading codes
used by the transmitters 26 to estimate the data of the various
received communication bursts. Although SIC-JD is described in
conjunction with a TDD/CDMA communication system, the same approach
is applicable to other communication systems, such as CDMA.
[0020] One approach to SIC-JD in a particular time slot in a
TDD/CDMA communication system is illustrated in FIG. 4. A number of
communication bursts are superimposed on each other in the
particular time slot, such as K communication bursts. The K bursts
may be from K different transmitters. If certain transmitters are
using multiple codes in the particular time slot, the K bursts may
be from less than K transmitters.
[0021] Each data burst 22, 24 of the communication burst 16 has a
predefined number of transmitted symbols, such as Ns. Each symbol
is transmitted using a predetermined number of chips of the
spreading code, which is the spreading factor (SF). In a typical
TDD communication system, each base station 12.sub.1 to 12.sub.5
has an associated scrambling code mixed with its communicated data.
The scrambling code distinguishes the base stations from one
another. Typically, the scrambling code does not affect the
spreading factor. Although the terms spreading code and factor are
used hereafter, for systems using scrambling codes, the spreading
code for the following is the combined scrambling and spreading
codes. As a result, each data burst 22, 24 has N.sub.S.times.SF
chips. After passing through a channel having an impulse response
of W chips, each received burst has a length of
SF.times.N.sub.s+W-1, which is also represented as N.sub.c chips.
The code for a k.sup.th burst of the K bursts is represented by
C.sup.(k).
[0022] Each k.sup.th burst is received at the receiver and can be
represented by Equation 1.
r.sup.(k)=A.sup.(k)d.sup.(k), k=1. . . K Equation 1
[0023] r.sup.(k) is the received contribution of the k.sup.th
burst. A.sup.(k) is the combined channel response, being an
N.sub.c.times.N.sub.s matrix. Each j.sup.th column in A.sup.(k) is
a zero-padded version of the symbol response s.sup.(k) of the
j.sup.th element of d.sup.(k). The symbol response s.sup.(k) is the
convolution of the estimated response h.sup.(k) and spreading code
C.sup.(k) for the burst. d.sup.(k) is the unknown data symbols
transmitted in the burst. The estimated response for each k.sup.th
burst, h.sup.(k), has a length W chips and can be represent by
Equation 2.
h.sup.(k)=.gamma..sup.(k).multidot.{tilde over (h)}.sup.(k)
Equation 2
[0024] (.sup.(k) reflects the transmitter gain and/or path loss.
{tilde over (h)}.sup.(k) represents the burst-specific fading
channel response or for a group of bursts experiencing a similarly
channel, {tilde over (h)}.sup.(g) represents the group-specific
channel response. For uplink communications, each h.sup.(k) as well
as each (.sup.(k) and {tilde over (h)}.sup.(k) are distinct. For
the downlink, all of the bursts have the same {tilde over
(h)}.sup.(k) but each (.sup.(k) is different. If transmit diversity
is used in the downlink, each (.sup.(k) and {tilde over
(h)}.sup.(k) are distinct.
[0025] The overall received vector from all K bursts sent over the
wireless channel is per Equation 3. 1 r _ = i = 1 K r _ ( k ) + n _
Equation 3
[0026] n is a zero-mean noise vector.
[0027] By combining the A.sup.(k) for all data bursts into matrix A
and all the unknown data for each burst d.sup.(k) into matrix d,
Equation 1 becomes Equation 4.
r=Ad+n Equation 4
[0028] SIC-JD determines the received power of each k.sup.th burst.
This determination may be based on apriori knowledge at the
receiver 28, burst-specific channel estimation from a
burst-specific training sequence, or a bank of matched filters. The
K bursts are arranged in descending order based on the determined
received power.
[0029] Bursts having roughly the same power level, such as within a
certain threshold, are grouped together and are arranged into G
groups, 48. The G groups are arranged into descending order by
their power, such as from group 1 to G with group 1 having the
highest received power. FIG. 5 is an illustration of a SIC-JD
device 46 performing SIC-JD based on the G groups.
[0030] For the group with the highest received power, group 1, the
symbol response matrix for only the bursts in group 1,
A.sub.g.sup.(1), is determined. A.sub.g.sup.(1) contains only the
symbol responses of the bursts in group 1. The received vector, r,
is modeled for group 1 as x.sub.g.sup.(1). As a result, Equation 4
becomes Equation 5 for group 1.
x.sub.g.sup.(1)=A.sub.g.sup.(1)d.sub.g.sup.(1)+n Equation 5
[0031] d.sub.g.sup.(1) is the data in the bursts of group 1.
Equation 5 addresses both the effects of inter symbol interference
(ISI) and multiple access interference (MAI). As a result, the
effects of the other groups, groups 2 to G, are ignored.
[0032] The received vector, x.sub.g.sup.(1), is matched filtered to
the symbol responses of the bursts in group 1 by a group 1 matched
filter 66.sub.1, such as per Equation 6, 50.
y.sub.g.sup.(1)=A.sub.g.sup.(1).sup..sup.Hx.sub.g.sup.(1) Equation
6
[0033] y.sub.g.sup.(1) is the matched filtered result.
[0034] A joint detection is performed on group 1 by a group 1 joint
detection device 68.sub.1 to make a soft decision estimate of 2 d ^
_ g , soft ( 1 ) ,
[0035] using the matched filtered result y.sub.g.sup.(1). One JD
approach is to compute the least-squares, zero-forcing, solution of
Equation 7. 3 d ^ _ g , soft ( 1 ) = ( A g ( 1 ) H A g ( 1 ) ) - 1
y _ g ( 1 ) Equation 7
[0036] A.sub.g.sup.(1).sup..sup.H is the hermetian of
A.sub.g.sup.(1). Another JD approach is to compute the minimum mean
square error solution (MMSE) as per Equation 8. 4 d ^ _ g , soft (
1 ) = ( A g ( 1 ) H A g ( 1 ) + 2 I ) - 1 y _ g ( 1 ) Equation
8
[0037] I is the Identity matrix and F.sup.2 is the standard
deviation.
[0038] One advantage to performing joint detection on only a group
of bursts is that the complexity of analyzing a single group versus
all the signals is reduced. Since A.sub.g.sup.(1).sup..sup.H and
A.sub.g.sup.(1) are banded block Toeplitz matrices, the complexity
in solving either Equation 7 or 8 is reduced. Additionally,
Cholesky decomposition may be employed with a negligible loss in
performance. Cholesky decomposition performed on a large number of
bursts is extremely complex. However, on a smaller group of users,
Cholesky decomposition can be performed at a more reasonable
complexity.
[0039] The soft decisions, 5 d ^ _ g , soft ( 1 ) ,
[0040] are converted into hard decisions, 6 d ^ _ g , hard ( 1 )
,
[0041] by soft to hard decision block 70.sub.1 as the received data
for group 1, 54. To process the other weaker groups, the multiple
access interference caused by group 1 onto the weaker groups is
estimated by a group 1 interference construction block 72.sub.1
using Equation 9, 56.
{circumflex over (r)}.sup.(1)=A.sub.g.sup.(1){circumflex over
(d)}.sub.g,hard.sup.(1) Equation 9
[0042] {circumflex over (r)}.sup.(1) is the estimated contribution
of group 1 to r.
[0043] For the next group 2, the estimated contribution of group 1
is removed from the received vector, x.sub.g.sup.(1), to produce
x.sub.g.sup.(2), such as by a subtractor 74.sub.1, as per Equation
10, 58.
x.sub.g.sup.(2)=x.sub.g.sup.(1)-{circumflex over (r)}.sup.(1)
Equation 10
[0044] As a result, multiple access interference from group 1 is
effectively canceled from the received signal. The next strongest
group, group 2, is processed similarly using x.sub.g.sup.(2), with
group 2 matched filter 66.sub.2, group 2 JD block 68.sub.2, soft to
hard decision block 70.sub.2 and group 2 interference construction
block 72.sub.2, 60. The constructed group 2 interference,
{circumflex over (r)}.sup.(2), is subtracted, such as by subtractor
24.sub.2, from the interference cancelled signal for group 2,
x.sub.g.sup.(2)-{circumflex over (r)}.sup.(2)=x.sub.g.sup.(3), 62.
Using this procedure, each group is successively processed until
the final group G. Since group G is the last group, the
interference construction does not need to be performed.
Accordingly, group G is only processed with group G matched filter
66.sub.G, group G JD block 68.sub.G and soft to hard decisions
block 70.sub.G to recovery the hard symbols, 64.
[0045] When SIC-JD is performed at a UE 14.sub.1, it may not be
necessary to process all of the groups. If all of the bursts that
the UE 14.sub.1 is intended to receive are in the highest received
power group or in higher received power groups, the UE 14.sub.1
will only have to process the groups having its bursts. As a
result, the processing required at the UE 14.sub.1 can be further
reduced. Reduced processing at the UE 14.sub.1 results in reduced
power consumption and extended battery life.
[0046] SIC-JD is less complex than a single-step JD due to the
dimension N.sub.c.times.K@N.sub.s matrix being replaced with G JD
stages of dimension N.sub.c.times.n.sub.i@N.sub.s, where i=1 to G.
n.sub.i is the number of bursts in the i.sup.th group. The
complexity of JD is proportional to the square to cube of the
number of bursts being jointly detected.
[0047] An advantage of this approach is that a trade-off between
computational complexity and performance can be achieved. If all of
the bursts are placed in a single group, the solution reduces to a
JD problem. The single grouping can be achieved by either forcing
all the bursts into one group or using a broad threshold.
Alternately, if the groups contain only one signal or only one
signal is received, the solution reduces to a SIC-LSE problem. Such
a situation could result using a narrow threshold or forcing each
burst into its own group, by hard limiting the group size. By
selecting the thresholds, an optional tradeoff between performance
and complexity can be achieved.
[0048] FIGS. 6 to 12 are simulation results that compare the bit
error rate (BER) performance of SIC-JD to full JD and RAKE-like
receivers under various multi-path fading channel conditions. The
parameters chosen are those of the 3G UTRA TDD CDMA system: SF=61
and W=57. Each TDD burst/time-slot is 2560 chips or 667
microseconds long. The bursts carry two data fields with N.sub.S
QPSK symbols each, a midamble field and a guard period. Each
simulation is run over 1000 timeslots. In all cases the number of
bursts, K is chosen to be 8. All receivers are assumed to have
exact knowledge of the channel response of each burst, which is
used to perfectly rank and group the bursts. The channel response
is assumed to be time-invariant over a time-slot, but successive
time-slots experience uncorrelated channel responses. No channel
coding was applied in the simulation. The JD algorithm jointly
detects all K bursts. The RAKE-like receiver was a bank of matched
filters, {circumflex over
(d)}.sup.(i)=A.sup.(i).sup..sup.Hr.sup.(i), for an i.sup.th burst's
code. The maximal ratio combiner (MRC) stage is implicit in these
filters because they are matched to the entire symbol-response.
[0049] The performance was simulated under fading channels with
multi-path profiles defined by the ITU channel models, such as the
Indoor A, Pedestrian A, Vehicular A models, and the 3GPP UTRA TDD
Working Group 4 Case 1, Case 2 and Case 3 models. In Vehicular A
and Case 2 channels, the SIC-JD suffered a degradation of up to 1
decibel (dB) as compared to the full JD in the 1% to 10% BER range.
For all other channels, the SIC-JD performance was within 0.5 dB of
that of the full JD. Since Vehicular A and Case 2 represent the
worst-case amongst all cases studied, only the performance plots
are shown. Amongst all channels simulated, Vehicular A and Case 2
have the largest delay spread. Vehicular A is a six tap model with
relative delays of 0, 310, 710, 1090, 1730 and 2510 nanoseconds and
relative average powers of 0, -1, -9, -10, -15 and -20 decibels
(dB). Case 2 is a 3 tap model, all with the same average power and
with relative delays of 0, 976 and 1200 nanoseconds.
[0050] FIGS. 6 and 7 compare the bit error rate (BER) vs. the
chip-level signal to noise ratio (SNR) performance of the SIC-LSE
receiver with the full JD and RAKE-like receivers under two
multi-path fading channel conditions. The group size is forced to
be 1, to form K groups, both, at the transmitter and receiver. The
theoretical binary phase shift keying (BPSK) BER in an additive
white gaussian noise (AWGN) channel that provides a lower bound to
the BER is also shown. The BER is averaged over all bursts. FIG. 6
represents the distinct channel case wherein each burst is assumed
to pass through an independently fading channel but all channels
have the same average power leading to the same average SNR. Thus,
in this case, {tilde over (h)}.sup.(i), i=1 . . . K are distinct
while .gamma..sup.(i), i=1 . . . K are all equal. Such a situation
exists in the uplink where the power control compensates for
long-term fading and/or path-loss but not for short-term fading. At
each time-slot, the bursts were arranged in power based upon the
associated h.sup.(i), i=1 . . . K. FIG. 7 shows similar plots for
the common channel case. All bursts are assumed to pass through the
same multi-path channel, i.e., {tilde over (h)}.sup.(i), i=1 . . .
K and are all equal, but with different .gamma..sup.(i), i=1 . . .
K. The .delta..sup.(i) are chosen such that neighboring bursts have
a power separation of 2 dB when arranged by power level. Such
difference in power can exist, for instance, in the downlink where
the base station 12.sub.1 applies different transmit gains to
bursts targeted for different UEs 14.sub.1 to 14.sub.3. FIGS. 6 and
7 show that in the range of 1% to 10% bit error rate (BER), the
SIC-LSE suffers a degradation of less than 1 dB as compared to the
JD. This is often the range of interest for the uncoded BER (raw
BER). The RAKE receiver exhibits significant degradation, since it
does not optimally handle the ISI. As the power differential
between bursts increases, the performance of SIC-LSE improves.
Depending upon the channel, a power separation of 1 to 2 dB is
sufficient to achieve a performance comparable to that of the full
JD.
[0051] FIGS. 8, 9, 10 and 11 compare the BER vs. SNR performance of
the SIC-JD receiver with the full JD and RAKE-like receivers under
two multi-path fading channels. The 8 codes are divided into 4
groups of 2 codes each at the transmitter and receiver. The BER is
averaged over all bursts. FIGS. 8 and 9 represent the distinct
channel case wherein different groups are assumed to pass through
independently fading channels. However, all channels have the same
average power leading to the same average SNR. All bursts within
the same group are subjected to an identical channel response. In
this case, {tilde over (h)}.sub.g.sup.(g), g=1 . . . G are all
distinct, but the channel responses, h.sub.g.sup.(i), i=1 . . .
n.sub.g, for each burst in the group are equal. n.sub.g is the
number of bursts in the g.sup.th group. This potentially represents
a multi-code scenario on the uplink, where each UE 14.sub.1
transmits two codes. The SIC-JD receiver 28 groups the multi-codes
associated with a single UE 14.sub.1 into the same group, thus
forming 4 groups. FIGS. 10 and 11 represent the common channel
case. All groups are assumed to pass through the same multi-path
channel, i.e., {tilde over (h)}.sub.g.sup.(i), g=1 . . . n.sub.g
are all equal, but with different .gamma..sub.g, g=1 . . . G. The
.gamma..sub.g are chosen such that, when arranged according to
power, neighboring groups have a power separation of 2 dB. This
potentially represents a multi-code scenario on the downlink where
the base station 12.sub.1 transmits 2 codes per UE 14.sub.1. FIGS.
10 and 11 show a trend similar to that observed for the SIC-LSE
shown in FIGS. 8 and 9. SIC-JD has a performance comparable (within
a dB) to the JD in the region of 1% to 10% BER, which is the
operating region of interest for the uncoded BER. Depending upon
the channel, a power separation of 1 to 2 dB is sufficient to
achieve a performance of SIC-LSE comparable to that of the full JD.
As shown, performance improves as the power separation between
bursts increases.
[0052] FIG. 12 is similar to FIG. 10, except that there are only
two groups with 4 bursts each. As shown in FIG. 12, SIC-JD has a
performance comparable (within a dB) to JD in the region of 1% to
10% BER.
[0053] The complexity of SIC-JD is less than full JD. The reduced
complexity stems from the replacement of a single-step JD which is
a dimension N.sub.c.times.K.multidot.N.sub.s with G JD stages of
dimension N.sub.c.times.n.sub.i.multidot.N.sub.s, i=1 . . . G.
Since, typically, JD involves a matrix inversion, whose complexity
varies as the cube of the number of bursts, the overall complexity
of the multi-stage JD can be significantly lower than that of the
single-stage full JD. Furthermore, the complexity of the SIC part
varies only linearly with the number of bursts, hence it does not
offset this complexity advantage significantly. For instance, the
complexity of the G-1 stages of interference cancellation can be
derived as follows. Since successive column blocks of
A.sub.g.sup.(i) are shifted versions of the first block and
assuming that elements of 7 d ^ _ g , hard ( i ) ,
[0054] belong to 1 of 4 QPSK constellation points, the
4.multidot.n.sub.i possible vectors can be computed that are needed
in computing the product 8 A g ( i ) d ^ _ g , hard ( i ) .
[0055] This step requires 9 4 ( SF + W - 1 ) Rate 10 6 i = 1 G - 1
n i
[0056] million real operations per sec (MROPS). .alpha.=4 is the
number of real operations per complex multiplication or multiply
and accumulate (MAC). Rate is the number of times the SIC-JD is
performed per second With these 4.multidot.n.sub.i vectors already
computed, the computation of x.sub.g.sup.(i+1) requires 10 2 N s (
SF + W - 1 ) Rate 10 6 i = 1 G - 1 n i MROPS .
[0057] The factor of 11 2
[0058] comes from the fact that only complex additions are
involved. Hence, only 2 real operations are required for each
complex operation. It then follows that the complexity of G-1
stages of interference cancellation can be expressed by Equation
11. 12 Z = ( SF + W - 1 ) ( 4 + N s 2 ) Rate 10 6 i = 1 G - 1 n i
Equation 11
[0059] The complexity of converting soft to hard decisions is
negligible.
[0060] There are several well-known techniques to solve the matrix
inversion of JD. To illustrate the complexity, an approach using a
very efficient approximate Cholesky factor algorithm with
negligible loss in performance as compared to the exact Cholesky
factor algorithm was used. The same algorithm can be employed to
solve group-wise JD. The complexity of the full JD and the SIC-JD
for the 3GPP UTRA TDD system is shown in Table 1. Table 1 compares
their complexity for various group sizes. It can be seen that as K
increases or as the group size decreases the complexity advantage
of the SIC-JD over the full JD increases. The complexity for group
size 1, of the SIC-LSE, varies linearly with K and is 33% that of
the full JD for K=16. Note that maximum number of bursts in the
UTRA TDD system is 16. The complexity advantage of the SIC-JD over
full JD will be even more pronounced when the exact Cholesky
decomposition is employed. Exact Cholesky decomposition's
complexity exhibits a stronger dependence on K, leading to more
savings as the dimension of the JD is reduced via SIC-JD.
1 TABLE 1 Complexity of the SIC-JD expressed as a percentage of the
complexity of the single-step JD of all K bursts K groups of K/2
K/4 K/8 Total number size 1 each groups of groups of groups of of
bursts (SIC-LSE) size 2 each size 4 each size 8 each 8 63% 67% 76%
100% 16 33% 36% 41% 57%
[0061] As shown in Table 1, when the number and size of codes is
made completely adaptive on an observation interval-by-observation
interval basis, the SIC-JD provides savings, on average, over full
JD. Since, on average, all bursts do not arrive at the receiver
with equal power, depending upon the grouping threshold, the size
of the groups will be less then the total number of arriving
bursts. In addition, a reduction in peak complexity is also
possible if the maximum allowed group size is hard-limited to be
less than the maximum possible number of bursts. Such a scheme
leads to some degradation in performance when the number of bursts
arriving at the receiver with the roughly the same power exceeds
the maximum allowed group size. Accordingly, SIC-JD provides a
mechanism to trade-off performance with peak complexity or required
peak processing power.
* * * * *