U.S. patent application number 14/112540 was filed with the patent office on 2015-10-01 for method and system for blind interference cancellation in a wireless communication systems.
The applicant listed for this patent is SHANGHAI MOBILEPEAK SEMICONDUCTOR CO., LTD.. Invention is credited to Yuan Li, Feng Wan, Liang Xu, Weiping Xu, Qiuzhen Zou.
Application Number | 20150280775 14/112540 |
Document ID | / |
Family ID | 49230590 |
Filed Date | 2015-10-01 |
United States Patent
Application |
20150280775 |
Kind Code |
A1 |
Xu; Weiping ; et
al. |
October 1, 2015 |
METHOD AND SYSTEM FOR BLIND INTERFERENCE CANCELLATION IN A WIRELESS
COMMUNICATION SYSTEMS
Abstract
Aspects of the present invention include methods, systems, and
computer-readable medium for canceling interference in wireless
communication. The method includes receiving wireless CDMA
communication signals using one or more antennas at least from a
first entity via a first communication channel and a second entity
via a second communication channel, determining a set of known
characteristics associated with the first entity, the first set of
characteristics comprising a first signal strength, a first
synchronization information, and an first channel identification
information, and determining an aggregate signal matrix based on
signals received from at least the first entity and the second
entity. The method further includes determining a covariance matrix
associated with the aggregate signal value, determining a reference
signal matrix based on the set of known characteristics,
calculating an interference matrix by subtracting the reference
signal matrix from the covariance matrix, and removing the
interference estimation from the communication signals.
Inventors: |
Xu; Weiping; (Shanghai,
CN) ; Wan; Feng; (Shanghai, CN) ; Xu;
Liang; (Shanghai, CN) ; Li; Yuan; (Shanghai,
CN) ; Zou; Qiuzhen; (Shanghai, CN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
SHANGHAI MOBILEPEAK SEMICONDUCTOR CO., LTD. |
Shanghai |
|
CN |
|
|
Family ID: |
49230590 |
Appl. No.: |
14/112540 |
Filed: |
November 13, 2012 |
PCT Filed: |
November 13, 2012 |
PCT NO: |
PCT/CN2012/084511 |
371 Date: |
October 17, 2013 |
Current U.S.
Class: |
375/148 |
Current CPC
Class: |
H04B 1/711 20130101;
H04B 1/712 20130101; H04B 1/7103 20130101 |
International
Class: |
H04B 1/7103 20060101
H04B001/7103; H04B 1/711 20060101 H04B001/711 |
Claims
1. A method for canceling interference in wireless communication,
the method comprising: receiving wireless code division multiple
access (CDMA) communication signals using one or more antennas via
a first communication channel via a second communication channel;
determining a set of known characteristics associated with
communication signals from the first communication channel, the
first set of characteristics comprising a first signal strength, a
first synchronization information, and an first channel
identification information; determining an aggregate signal matrix
based on noise and communication signals received from the
communication channel and the second communication channel;
determining a covariance matrix associated with the aggregate
signal value; determining a reference signal matrix based on the
set of known characteristics; calculating an interference matrix by
subtracting the reference signal matrix from the covariance matrix;
determining a maximum eigenvalue and an eigenvector corresponding
to the maximum eigenvalue for with the interference matrix;
generating an interference estimation using the maximum eigenvalue
and the eigenvector; and removing the interference estimation from
the communication signals.
2. The method of claim 1, further comprising receiving
communication signals via a third communication channel.
3. The method of claim 2, wherein the aggregate signal matrix is
further based on the communication signals via the third
communication channel.
4. The method of claim 1, further comprising performing recursive
calculations with a threshold condition to determine the maximum
eigenvalue.
5. The method of claim 2, wherein the threshold is determined based
on a desired signal-to-noise ratio and the correlation feature of
the designed signature code.
6. The method of claim 1, wherein the channel identification
information comprises a signature (spreading) code, scrambling
code, in orthogonal code, or non-orthogonal.
7. The method of claim 1, wherein the reference signal matrix is
associated with covariance values of the set of known
characteristics.
8. The method of claim 1, wherein the wireless communication CDMA
signals includes interference signals.
9. A system for canceling interference in wireless communication,
the system comprising: a storage device; and a processor in
communication with the storage device, wherein the storage device
has sets of instructions stored thereon which, when executed by the
processor, cause the processor to: receive wireless code division
multiple access (CDMA) communication signals using one or more
antennas via a first communication channel via a second
communication channel, determine a set of known characteristics
associated with communication signals from the first communication
channel, the first set of characteristics comprising a first signal
strength, a first synchronization information, and an first channel
identification information, determine an aggregate signal matrix
based on noise and communication signals received from the
communication channel acid the second communication channel,
determine a covariance matrix associated with the aggregate signal
value, determine a reference signal matrix based on the set of
known characteristics, calculate an interference matrix by
subtracting the reference signal matrix from the covariance matrix,
determine a maximum eigenvalue and an eigenvector corresponding to
the maximum eigenvalue for with the interference matrix, generate
an interference estimation using the maximum eigenvalue and the
eigenvector, and remove the interference estimation from the
communication signals.
10. The system of claims 9, wherein the sets of instruction when
further executed by the processor, cause the processor to perform
recursive calculations with a threshold condition to determine the
maximum eigenvalue.
11. The system of claim 10, wherein the threshold is determined
based on a desired signal-to-noise ratio and the correlation
feature of the designed signature code.
12. The system of claim 9, wherein the channel identification
information comprises a signature (spreading) code, scrambling
code, in orthogonal code, or non-orthogonal.
13. The system of claim 9, wherein the reference signal matrix is
associated with covariance values of the set of known
characteristics.
14. The system of claim 9, wherein the wireless communication CDMA
signals includes interference signals.
15. A computer-readable medium for updating user assistance
content, having sets of instructions stored thereon which, when
executed by a computer, cause the computer to: receive wireless
code division multiple access (CDMA) communication signals using
one or more antennas via a first communication channel via a second
communication channel; determine a set of known characteristics
associated with communication signals from the first communication
channel, the first set of characteristics comprising a first signal
strength, a first synchronization information, and an first channel
identification information; determine an aggregate signal matrix
based on noise and communication signals received from the
communication channel and the second communication channel;
determine a covariance matrix associated with the aggregate signal
value; determine a reference signal matrix based on the set of
known characteristics; calculate an interference matrix by
subtracting the reference signal matrix from the covariance matrix;
determine a maximum eigenvalue and an eigenvector corresponding to
the maximum eigenvalue for with the interference matrix; generate
an interference estimation using the maximum eigenvalue and the
eigenvector; and remove the interference estimation from the
communication signals.
16. The computer-readable medium of claim 15, wherein the sets of
instruction when further executed by the computer, cause the
computer to perform recursive calculations with a threshold
condition to determine the maximum eigenvalue.
17. The computer-readable medium of claim 16, wherein the threshold
is determined based on a desired signal-to-noise ratio and the
correlation feature of the designed signature code.
18. The computer-readable medium of claim 15, wherein the channel
identification information comprises a signature (spreading) code,
scrambling code, in orthogonal code, or non-orthogonal.
19. The computer-readable medium of claim 15, wherein the reference
signal matrix is associated with covariance values of the set of
known characteristics.
20. The computer-readable medium of claim 15, wherein the wireless
communication CDMA signals includes interference signals.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] The present application claims priority to PCT application
No. PCT/CN2012/084511, filed on Nov. 13, 2012, and entitled "Method
and System for Blind Interference Cancellation in a wireless
communication systems", the entire disclosure of which is
incorporated herein by reference.
BACKGROUND
[0002] Currently, there are two main types of interference
cancellation receivers. Namely, linear minimal mean square error
(LMMSE) based interference cancellation receivers and non-linear
interference cancellation (NLIC) receivers. LMMSE based
interference cancellation receivers estimate the covariance matrix
and find the coefficient which is used to achieve the MMSE by
solving the large matrix inversion. The minimal required
pre-knowledge to use this algorithm in CDMA based communication
systems is the desired signal's scrambling and spread code. The NIX
based interference cancellation receivers estimate interference
items and subtract such items from the received signal in parallel
or successively.
[0003] These techniques reconstruct the interference items by
estimating each interference's amplitude, timing, channel response,
and information bit and then remove them from the received signal,
based on the pre-knowledge of the desired signal and interference's
scrambling and spread codes. Specifically, in wide-band code
division multiple access (CDMA) (WCDMA) downlink, the knowledge of
variable spreading factors and spread codes of intra-channel and
inter-channel interferences is very limited, and an additional
algorithm is needed to detect the presence of the
interferences.
[0004] A significant drawback of these existing interference
cancellation techniques is that they require computational
complexity and have high requirement for the accuracy of the
estimated interference signal in the NLIC receivers. Hence, for
these and other reasons, improvements are needed in the art.
BRIEF DESCRIPTION OF THE DRAWINGS
[0005] A further understanding of the nature and advantages of the
present invention may be realized by reference to the remaining
portions of the specification and the drawings wherein like
reference numerals are used throughout the several drawings to
refer to similar components. In some instances, a sub-label is
associated with a reference numeral to denote one of multiple
similar components. When reference is made to a reference numeral
without specification to an existing sub-label, it is intended to
refer to all such multiple similar components.
[0006] FIG. 1 illustrates a block diagram of a receiver with blind
interference cancellation, according to one embodiment of the
present invention.
[0007] FIG. 2 illustrates a block diagram of intra-interference and
inter-interference cancellation and channel equalization, according
to one embodiment of the present invention.
[0008] FIG. 3 illustrates a block diagram of blind interference
cancellation on each channel, according to one embodiment of the
present invention.
[0009] FIG. 4 illustrates a block diagram of
multi-channel/multi-stage blind interference cancellation,
according to one embodiment of the present invention.
[0010] FIGS. 5A and 5B illustrates flow diagrams for implementing
blind interference cancellation, according to one embodiment of the
present invention.
[0011] FIG. 6 illustrates a block diagram of a receiver with an
interference cancellation and equalizer according to one embodiment
of the present invention.
[0012] FIG. 7 illustrates a block diagram of multi-channel
interference cancellation and equalizer, according to one
embodiment of the present invention.
[0013] FIG. 8 illustrates a block diagram of self-tracking multi
channel equalizer based on a pilot channel, according to one
embodiment of the present invention.
[0014] FIG. 9 illustrates a flow diagram for combining symbol level
interference cancellation and chip level channel equalizer,
according to one embodiment of the present invention.
[0015] FIG. 10 illustrates a flow diagram for dynamically selecting
the interference cancellation and channel equalizer, according to
one embodiment of the present invention.
[0016] FIG. 11 is a generalized schematic diagram illustrating a
computer system, in accordance with various embodiments of the
invention.
[0017] FIG. 12 is a block diagram illustrating a networked system
of computers, which can be used in accordance with various
embodiments of the invention.
SUMMARY OF THE INVENTION
[0018] The present invention is related to a method for canceling
interference in wireless communication. The method includes
receiving wireless code division multiple access (CDMA)
communication signals using one or more antennas at least from a
first entity via a first communication channel and a second entity
via a second communication channel, determining a set of known
characteristics associated with the first entity, the first set of
characteristics comprising a first signal strength, a first
synchronization information, and an first channel identification
information, and determining aggregate signal matrix based on
signals received from at least the first entity and the second
entity. The method further includes determining a covariance matrix
associated with the aggregate signal value, determining a reference
signal matrix based on the set of known characteristics, and
calculating an interference matrix by subtracting the reference
signal matrix from the covariance matrix. Furthermore, the method
includes determining a maximum eigenvalue and an eigenvector
corresponding to the maximum eigenvalue for with the interference
matrix, generating an interference estimation using the maximum
eigenvalue and the eigenvector, and removing the interference
estimation from the communication signals.
[0019] The method also includes performing recursive calculations
with a threshold condition to determine the maximum eigenvalue. The
threshold is determined based on a desired signal-to-noise ratio
and the correlation feature of the designed signature code. Also,
the channel identification information comprises a signature
(spreading) code, scrambling code, in orthogonal code, or
non-orthogonal. The reference signal matrix is associated with
covariance values of the set of known characteristics, and the
wireless communication CDMA signals includes interference
signals.
[0020] In a further embodiment, a system for canceling interference
in wireless communication, is described. The system includes a
storage device, a common reference timing, and a processor in
communication with the storage device. There are two types of
storage devices: instruction memory block and data memory block.
The former storage device has sets of instructions stored thereon
which, when executed by the processor, cause the processor to:
receive wireless code division multiple access (CDMA) communication
signals using one or more antennas at least from a first entity via
a first communication channel and a second entity via a second
communication channel, called reference channel,and other entities
via all other available communication channels and save to the data
storage device at a preset time. The processor will process these
saved data offline to: determine a set of known characteristics
associated with the first entity, the first set of characteristics
comprising a first signal strength, a first synchronization
information, and an first channel identification information, and
determine an aggregate signal matrix based on signals received from
at least the first entity and the other related entities.
[0021] The sets of instructions further cause the processor to
determine a covariance matrix associated with the aggregate signal
value, determine a reference signal matrix based on the set of
known characteristics, calculate an interference matrix by
subtracting the reference signal matrix from the covariance matrix,
determine a maximum eigenvalue and an eigenvector corresponding to
the maximum eigenvalue for with the interference matrix, generate
an interference estimation using the maximum eigenvalue and the
eigenvector, and remove the interference estimation from the
communication signals.
[0022] Further, another embodiment describes a hardware processing
accelerator to complete all the above interference estimation and
cancellation process. Further, another embodiment describes a
computer-readable medium for updating user assistance content. The
computer-readable medium has sets of instructions stored thereon
which, when executed by a computer, cause the computer to: receive
wireless code division multiple access (CDMA) communication signals
using one or more antennas at least from a first entity via a first
communication channel, a second entity via a second communication
channel and so on, determine a set of known characteristics
associated with the first entity, the first set of characteristics
comprising a first signal strength, a first synchronization
information, and an first channel identification information,
determine an aggregate signal matrix based on signals received from
at least the first entity and the second entity, determine a
covariance matrix associated with the aggregate signal value,
determine a reference signal matrix based on the set of known
characteristics, calculate an interference matrix by subtracting
the reference signal matrix from the covariance matrix, determine a
maximum eigenvalue and an eigenvector corresponding to the maximum
eigenvalue for with the interference matrix, generate an
interference estimation using the maximum eigenvalue and the
eigenvector, and remove the interference estimation from the
communication signals.
DETAILED DESCRIPTION OF THE INVENTION
[0023] While various aspects of embodiments of the invention have
been summarized above, the following detailed description
illustrates exemplary embodiments in further detail to enable one
of skill in the art to practice the invention. In the following
description, for the purposes of explanation, numerous specific
details are set forth in order to provide a thorough understanding
of the present invention. It will be apparent, however, to one
skilled in the art that the present invention may be practiced
without some of these specific details. In other instances,
well-known structures and devices are shown in block diagram form.
Several embodiments of the invention are described below and, while
various features are ascribed to different embodiments, it should
be appreciated that the features described respect to one
embodiment may be incorporated with another embodiment as well. By
the same token, however, no single feature or features of any
described embodiment should be considered essential to the
invention, as other embodiments of the invention may omit such
features.
[0024] Aspects of the present invention relate to inter symbol
interference cancellation and channel equalizer. Removing
interferences includes symbol level inter-interference and
intra-interference cancellation (e.g., blind interference
cancellation). Aspects of the invention further includes chip level
inter symbol interference cancellation and channel equalization,
time tracking on the reference channel by analyzing the equalizer
channel profile, estimate the equalizer coefficient on the
reference channel, applying the equalizer coefficient on all
channels associated with the desired user, and dynamically
selecting the combination of the symbol level inter-interference
and intra-interference cancellation and chip level equalizer based
on the interference detection and the output signal-to-noise
ratio.
[0025] Further aspects of the present invention relate to
interference cancellation of wireless communication systems, and
specifically to CDMA based mobile communication systems (i.e.,
WCDMA) which are particularly applied in a universal mobile
telecommunications system (UMTS) terrestrial radio access-frequency
division duplexing (UTRA-FDD) downlink receiver to cancel the
intra-cell interference, and inter-cell interference, and mitigate
inter symbol interference (ISI) interference.
[0026] Instead of estimating an interference signal, the present
invention blindly cancels interferences in succession based on
second order statistics to avoid the computational complexity. The
most dominant interference contribution to the received covariance
matrix is first estimated and then removed from the receiving
vector. Then, the weaker interferences are removed in succession by
repeating this process. The desired signal will be detected after
each of the significant interference items are removed. The
estimation of the interference contribution to the received
covariance matrix can be implemented by using subspace technique to
project the interference on the maximum eigenvalue and its
corresponding maximum eigenvector.
[0027] Furthermore, the present invention provides improved
performance by adding the interference cancellation and thus
increasing the data rate. Further, the effect of signal covariance
matrix estimation errors are mitigated. The computational
complexity is decreased by removing the block to detect unknown
interferences. Processing delay is reduced by removing the
interference reconstruction from the decision feedback. As such,
the present invention increases calculation speed without
sacrificing accuracy in order to solve inter-cellular and
intra-cellular interferences.
[0028] Referring now to FIG. 1 which a system 100 of a receiver
with blind interference cancellation, according to one embodiment
of the present invention. In one embodiment, the system 100
includes a radio frequency block 101 in communication with a
digital front end block 102. Radio frequency block 101 includes an
RF block A 103 and RF block B 104, which receive radio frequencies
Rx1 and Rxi, respectively.
[0029] Digital front end block 102 includes a digital sampling
block A 105 which receives input from RF block A 103 and a digital
sampling block B 106 which receives input from RF block B 104.
Further, digital front end block 102 includes a storage block A
107, a channel estimation block A 109, a storage block B 108, and a
channel estimation block B 110. Storage block A 107, channel
estimation block A 109 receive inputs from digital sampling block A
105, and storage block B 108, channel estimation block B 110
receive inputs from digital sampling block B 106. Accordingly,
storage block A 107 and storage block B 108 store the received
signals, and channel estimation block A 109 and channel estimation
block B 110 perform channel estimation based on the received
signals.
[0030] A scrambling spreading code generator 111 is in
communication with channel estimation block A 109 and channel
estimation block B 110. Then, a blind interference cancellation
block A 112 receives {r1} from storage block A 107, {h1} from
channel estimation block A 109, and an input from scrambling
spreading code generator 111. Further, a blind interference
cancellation block B 113 receives {ri} from storage block B 108,
{hi} from channel estimation block B 110, and an input from
scrambling spreading code generator 111. Furthermore, a RF block
114 receives input from blind interference cancellation block A
112, blind interference cancellation block B 113, and {sci} from
scrambling spreading code generator 111.
[0031] Turning now to FIG. 2, which is block diagram illustrating a
system 200 for implementing intra-interference and
inter-interference cancellation and channel equalization, according
to one embodiment of the present invention. In one embodiment,
system 200 includes a m-stage intra-CHk blind interference
cancellation (BIC)1 201, an m-stage intra-CH1 BIC1 202, and a
m-stage CPICH BIC1 203, each of which receive input from r.sup.(1).
Furthermore, m-stage intra-CHk BIC2 206, an m-stage intra-CH1 BIC2
205, and a m-stage CPICH BIC2 204, each of which receive input from
r.sup.(2).
[0032] In a further embodiment, system 200 includes an equalizer
211 which includes a channel equalizer (CE)1 207 in communication
with an equation (EQU)1 coefficient (COEFF) 209, and a CE2 208 in
communication with an EQU2 COEFF 210. Further, CE1 207 receives
input r.sub.m,pi.sup.(1) from m-stage CPICH BIC1 203, and CE2 208
receives input r.sub.m,pi.sup.(2) from m-stage CPICH BIC1 204.
[0033] System 200 further includes an apply EQU coefficients and
combiner 212 which receives input r.sub.m,chk.sup.(1) from m-stage
intra-CHk BIC1 201, input r.sub.m,ch1.sup.(1) from m-stage
intra-CH1 BIC1 202, input r.sub.m,ch1.sup.(2) from m-stage
intra-CH1 BIC2 205, and input r.sub.m,chk.sup.(2) from m-stage
intra-CHk BIC2 206. apply EQU coefficients and combiner 212 also
received input from EQU1 COEFF 209 and EQU2 COEFF 210. apply EQU
coefficients and combiner 212 then processes the inputs and outputs
r.sub.pi, r.sub.ch1, and r.sub.chk to CPICH demod 213, intra-CH1
demod 214, and inta-CHk demod 215, respectively.
[0034] In one embodiment, in system 200 the received high-speed
downlink packet access (HSDAP) signal of the serving cell includes
the synchronous intra-cell channels and the asynchronous inter-cell
interferences. The HSDAP received signal on the p.sup.th branch on
symbol level is simplified as:
r ( p ) = k = 0 K - 1 ch = 0 CH - 1 l = 0 L - 1 h k , ch , l ( p )
d k , ch , l n = 0 N k , ch - 1 SC ch , n + l Equation 1
##EQU00001##
where SC is the equivalent spreading code combined by the
scrambling code and the orthogonal spreading code. The scrambling
codes are used to identify cells, indexed by k, and in each cell
the intra-cell channels are identified by orthogonal spreading
code, indexed by ch. FIG. 2 demonstrates a single input, multiple
outputs (SIMO) system where there are two receiving branches. The
received signal on each branch is modeled first as passing to a
multi-path channel and the channel h is assumed not changing for
the duration of a symbol l is used to index the multi-path. Then
ISI will be removed by the equalizer after the multi-stage blind
interference cancellation. The equalizer coefficients will be
obtained from common pilot channel (CPICH) and applied on all
intra-channels.
[0035] Turning next to FIG. 3 which illustrates a block diagram of
a system 300 for implementing blind interference cancellation on
each channel, according to one embodiment of the present invention.
In one embodiment, system 300 includes a BIC state 1 301, which
includes a covariance matrix estimator R.sub.r 302, a desired
multipath signal matrix estimator R.sub.ch 303, a max interference
vector and matrix on subspace estimator 304, an interference on
signal space reconstructor 305, and an excessive cancellation
detector 306.
[0036] The outputs R.sub.r,1 and r.sub.1 from BIC state 1 301 are
received by a BIC stage 2 308 and then outputs R.sub.r,2 to
R.sub.r,m-1 and r.sub.2 to r.sub.m-1 are received by BIC stage m
309. Then, BIC stage m 309 outputs r.sub.m.
[0037] In one embodiment, the following the multi stage blind
interference cancellation block may be implemented using system 300
in FIG. 3. The received signal vector with a length of N.sub.ch
chips at symbol i is noted as r(i), where N.sub.ch usually is the
spreading factor of the channel. Note that the maximum number of
interference components may be detected and cancelled usually meets
the following relations: N.sub.ch.gtoreq.2K.sub.a+K.sub.s+1, where
K.sub.a is the total number of asynchronous interference items and
K.sub.s is the total number of synchronous interference items. The
receiving signal covariance matrix can be estimated directly from
the received signal sample or channel estimation. Equation 2 is a
typical sample estimation with the estimation window size of N:
R r ( i ) = 1 N j = i * N ch - N + 1 i * N ch r ( j ) r H ( j )
Equation 2 ##EQU00002##
The desired multipath signal matrix is estimated as:
R ^ ch ( i ) = l = 0 L - 1 h ^ l ( i ) 2 SC ch ( iN ch - l ) SC ch
H ( iN ch - l ) Equation 3 ##EQU00003##
where H is Hermitian conjugation operation, the channel estimation
on symbol level h can simply use the finger output of RAKE receiver
and is not the key focus of this invention. Dropping the symbol
index i for simplification, the interference covariance matrix can
be obtained by removing the desired signal as:
{circumflex over (R)}.sub.r,0={circumflex over
(R)}.sub.r-{circumflex over (R)}.sub.ch Equation 4
[0038] The mean energy (ME) of the received signal r on the
N.sub.ch-dimensional vector space u is defined as
ME(u)=E{(r.sup.Hu).sup.2}, where u.sup.Hu=1. According to linear
algebra theory, the eigenvalue .lamda. and the corresponding
eigenvector v is the necessary condition to maximize ME(v) as
R.sub.rv=.lamda.v. For a set of eigenvalue and the corresponding
eigenvector of R.sub.r, ME(V)=V.sup.HR.sub.rV=D , where
D=diag{.lamda..sub.n}, n=0 . . . N.sub.ch-1 and V is the
Eigen-matrix consist of N.sub.ch orthogonal Eigenvectors. Therefore
the eigenvector corresponding to the maximum eigenvalue is the
vector that maximizes the mean energy on it. The next step is to
remove the maximum interference contribution in the interference
covariance matrix in stage m by applying this subspace theory
as:
{circumflex over (R)}.sub.r,m={circumflex over
(R)}.sub.r,m-1-.lamda..sub.max.sup.(m)v.sub.max.sup.(m)v.sup.H.sup.(m).su-
p.max Equation 5
[0039] To find the maximum eigenvalue .lamda..sub.max and the
corresponding Eigenvector v.sub.max. The Eigen-decomposition in
full is not needed. Instead an iterative solution like power method
(PM) can be used. The iteration algorithm to obtain the maximum
eigenvalue .lamda..sub.max and the corresponding Eigenvector
v.sub.max is not the key topic in this invention. The excessive
cancellation detector in stage m can be implemented by a threshold,
which is associated with the signal-to-noise ratio and the
correlation feature of the combined spreading code, check as:
w.sub.m=(SC.sub.ch.sup.Hv.sub.max.sup.(m)>Threshold)?0:1
Equation 6
The cleaner signal will feed to the next stage when w.sub.m=1 else
stop.
{circumflex over
(r)}.sub.m=r.sub.m-1-w(r.sub.m-1.sup.Hv.sub.max.sup.(m))v.sub.max.sup.(m)
Equation 7
where r.sub.0=r.
[0040] In UTRA-FDD downlink, the CPICH can be used to calculate the
channel equalizer coefficients and the coefficients will apply on
each channel after performing multi-stage blind interference
cancellation on each channel to remove ISI. The equalizer can be
implemented in time domain or frequency domain based on the signal
covariance matrix estimation and is not the main focus in this
invention.
[0041] Referring next to FIG. 4 which illustrates a system 400 for
implementing multi-channel/multi-stage blind interference
cancellation, according to one embodiment of the present invention.
In one embodiment, system 400 includes a J.sup.th Channel
Multi-Stage Blind Interference Cancellation A 401, a 1.sup.st
Channel Multi-Stage Blind Interference Cancellation A 402, and a
channel estimation block A 405, which each receive input {r1}.
Further, a J.sup.th Channel Multi-Stage Blind Interference
Cancellation B 404, a 1.sup.st Channel Multi-Stage Blind
Interference Cancellation B 403, and a channel estimation block B
406, each receive input {ri},
[0042] Channel estimation block A 405 provides input {h11} to
1.sup.st Channel Multi-Stage Blind Interference Cancellation A 402
and input {h1} to J.sup.th Channel Multi-Stage Blind Interference
Cancellation A 401. Further, channel estimation block B 406
provides input {hi1} to 1.sup.st Channel Multi-Stage Blind
Interference Cancellation B 403 and input {hij} to J.sup.th Channel
Multi-Stage Blind Interference Cancellation B 404.
[0043] System 400 further includes a scrambling spreading code
generator 407 which provides input {sc11} to 1.sup.st Channel
Multi-Stage Blind Interference Cancellation A 402 and input {sc1j}
to J.sup.th Channel Multi-Stage Blind Interference Cancellation A
401, as well as input {sci1} to 1.sup.st Channel Multi-Stage Blind
Interference Cancellation B 403 and input {scij} to J.sup.th
Channel Multi-Stage Blind Interference Cancellation B 404,
scrambling spreading code generator 407 also provides input to a
demod block 408, and demod block 408 outputs {d1 to dj}.
[0044] Furthermore, J.sup.th Channel Multi-Stage Blind Interference
Cancellation A 401 outputs {r1j} to a J.sup.th Channel Combiner 410
and J.sup.th Channel Multi-Stage Blind Interference Cancellation B
404 also outputs {rij} to J.sup.th Channel Combiner 410. 1.sup.st
Channel Multi-Stage Blind Interference Cancellation A 402 outputs
{r11} to 1.sup.st Channel Combiner 409 and 1.sup.st Channel
Multi-Stage Blind Interference Cancellation B 403 outputs {ri1} to
1.sup.st Channel Combiner 409. Further, 1.sup.st Channel Combiner
409 and J.sup.th Channel Combiner 410 provide output to demod block
408.
[0045] FIGS. 5A and 5B illustrates a method 500 for implementing
blind interference cancellation, according to one embodiment of the
present invention. In one embodiment, method 500 may be implemented
using any one of systems 100, 200, 300, or 400. At process block
501, a signal vector is received and saved. The signal vector is
then input into a 1st stage blind interference cancellation module.
At process block 502, a covariance matrix is received and
processed.
[0046] At process block 503, a channel estimation for a desired
signal is performed and a covariance matrix for the desired signal
is processed (process block 504). At process block 505, an
interference matrix is processed by subtracting the output of the
processing of the covariance matrix for the desired signal. Then,
the maximum eigenvalue and its eigenvector of the interference
matrix is determined (process block 506).
[0047] At process block 507, the strongest interference based on
the determined eigenvector is generated to rebuild the 2.sup.nd
item in Equation 7. The strongest interference covariance matrix is
determined based on the eigenvalue and its eigenvector for the
2.sup.nd item in Equation 5 (process block 508). Then, at process
block 509, a threshold is checked against the correlation between
the desired signal and the eigenvector results.
[0048] If the threshold is not exceeded, then the process moves to
point `A`, otherwise the process moves to point `B` and on to
process block 515. Turning now to FIG. 5B from point `A`, at
process block 511, a cleaner signal vector is obtained by
subtracting the results of process block 507 from the input to the
stage vector.
[0049] A determination is made whether the number of stages has
reached the number of the covariance matrix dimension (decision
block 512). If the number of stages has not reached the number of
the covariance matrix dimensions, then at process block 513, the
remaining interference covariance matrix is processed by removing
the results from process block 508. At process block 514, the next
stage BIC is stared with two inputs from process blocks 511 and
513. Then, the process returns to process block 506 via point `C`.
Otherwise, the process proceeds to point `B` and process block 515.
At process block 515, the outputs from process block 511 from each
antenna for each channel are combined. At process block 516, the
outputs of process block 515 for each channel are dispread.
[0050] One implementation of the method 500 includes calculating
(2.times.2) covariance matrix (it should be noted that the larger
the dimension of the covariance matrix, the more interference items
can be detected and further cancelled, and usually the size of the
covariance matrix is equivalent to the length of each CDMA
channel's spreading code).
[0051] In one embodiment, the desired signal's signature code in
one symbol for the desired user is:
s.sub.0=[1 1].sup.T, [0052] the interference's item is:
[0052] s.sub.1=[1 -1].sup.T [0053] the covariance matrix for the
received signal is:
[0053] R = [ 2.1 0 0 0.1 ] , ##EQU00004## [0054] with a variance of
normal additive noise is estimated at 0.1. [0055] the covariance
matrix for the desired user is estimated perfectly as:
[0055] R 0 = [ 0.5 0.5 0.5 0.5 ] ##EQU00005## [0056] the covariance
matrix after being removed, the desired user's contribution
(interference and noise) will be:
[0056] R r 0 = [ 1.6 - 0.5 - 0.5 - 0.4 ] . ##EQU00006## [0057] the
max Eigenvalue and corresponding Eigenvector will be:
[0057] .lamda..sub.max=1.718 and .nu..sub.max=[-0.9732
0.2298].sup.T.
[0058] The rebuild interference s.sub.1=[1.9337 0.4565] and the
cleaner signal after interference remove will be s.sub.0=[0.0915
0.3875].sup.T and the estimated symbol will be detected as 1 as
expected,
[0059] Turning now to FIG. 6 which illustrates a system 600 of a
receiver with an interference cancellation and equalizer, according
to one embodiment of the present invention. In one embodiment,
system 600 includes similar elements of FIG. 1 with the
Interference and Cancellation Equalizer Block A 601, Interference
and Cancellation Equalizer Block B 602, and Combine and Demod Block
603, which replace Blind Interference Cancellation Block A 112,
Blind Interference Cancellation Block B 113, and RF block 114,
[0060] Turning next to FIG. 7 which illustrates a system 700 for
implementing multi-channel interference cancellation and equalizer,
according to one embodiment of the present invention. In one
embodiment, system 700 includes the elements of FIG. 4 with a
Reference Channel Equalizer Coefficient Estimation 701, a finite
impulse response (FIR) Filter Bank 702, and Demod Block 703, which
replace Demod Block 408, 1st Channel Combiner 409, and J.sup.th
Channel Combiner 410.
[0061] FIG. 8 illustrates a system 800 for implementing a
self-tracking multi-channel equalizer based on a pilot channel,
according to one embodiment of the present invention. In one
embodiment, system 800 includes a storage block A 801 which
receives input {r1} or {r11}. System 800 further includes a storage
block B 802 which receives input or {ri} or {ri1}. System 800
further includes a Channel Estimation with Fraction Chip Level
Resolution A 803 and Channel Estimation with Fraction Chip Level
Resolution B 804, which receives input from storage block A 801 and
storage block B 802, respectively.
[0062] System 800 further includes a Scrambling Spreading Code
Generator 805 which sends output {sc1} to Channel Estimation with
Fraction Chip Level Resolution A 803 and output {cs1} to Channel
Estimation with Fraction Chip Level Resolution B 804. Furthermore,
Channel Estimation with Fraction Chip Level Resolution A 803
receives input {t11} from an Equalizer Control Engine 806 and
Channel Estimation with Fraction Chip Level Resolution B 804
receives an input {ti1} from Equalizer Control Engine 806.
[0063] System 800 further includes an Equalizer Coefficient
Estimator 807 which receives input {hlk} from Channel Estimation
with Fraction Chip Level Resolution A 803 and input {hik} from
Channel Estimation with Fraction Chip Level Resolution B 804.
Further, Equalizer Coefficient Estimator 807 outputs c1 to cn.
[0064] Referring now to FIG. 9 which illustrates a method 900 for
combining symbol level interference cancellation and chip level
channel equalizer, according to one embodiment of the present
invention. At process block 901, the signal vectors are saved on
the reference channel after interference cancellation or with the
resolution of the fraction chip. A covariance matrix is then
received and processed (process block 902).
[0065] At process block 903, the received and processed Covariance
matrix is used, and the equalizer tap coefficient and tap energy
are calculated and saved (process block 904). At decision block
905, a determination is made whether additional start time
positions are in start window. If there are additional start time
positions in the start window, then the process returns to process
block 902. Otherwise the process continues to process block 906,
which analyzes the channel characters and the output
signal-to-noise ratio (SNR) in the control engine to decide the
time position in the fraction chip.
[0066] At process block 907, the input signal vector window time
position may be changed based on results of process block 906.
Then, the channel estimation start time position is changed based
on results of process block 906 (process block 908). At process
block 909, the demodulation time position is determined based on
process block 906. Then, a determination for a set of time
positions the equalizer tap coefficients is made (process block
910). At process block 911, the equalizer tap coefficients are
applied on each channel signal vector for a desired user.
[0067] Referring next to FIG. 10 which illustrates a method 1000
for dynamically selecting the interference cancellation and channel
equalizer, according to one embodiment of the present invention. At
decision block 1001, a determination is made whether valid
interference components are detected on the reference channel. If
valid interference components are detected on the reference
channel, then the process moves to process block 1004, otherwise
the process continues to process block 1002.
[0068] At process block 1002, blind interference cancellation on
each channel is processed. At process block 1003, the output SNR of
the BIC on each channel are estimated. Then, the channel equalizer
coefficients on the reference channel are estimated. At process
block 1005, the timing position in response to the output of
process block 1003 is adjusted.
[0069] At process block 1006, the equalizer coefficients on all
channels are applied and the output SNR of equalizer on each
channel are estimated (process block 1007). At decision block 1008,
a determination of whether the SNR equalization output is improved.
If the SNR equalization output is improved, then the output of
equalizer to the demodulation is connected. Otherwise, the output
of interference to the demodulation is connected.
[0070] FIG. 11 is a block diagram illustrating an exemplary system
1100 in which embodiments of the present invention may be
implemented. For example, the system 1100 can be a wireless
communication device, a portable computer with wireless
communication interface, abase station, and/or others. The system
1100 is shown comprising hardware elements that may be electrically
coupled via a bus 1190. The hardware elements may include one or
more central processing units 1110, one or more input device(s)
1120 (e.g., keypad, etc.), and one or more output device(s) 1130
(e.g., a display device, a printer, etc.). The system 1100 may also
include one or more storage device(s) 1140. By way of example,
storage device(s) 1140 may be disk drives, optical storage devices,
a solid-state storage device such as a random access memory ("RAM")
and/or a read-only memory ("ROM"), which can be programmable,
flash-updateable, and/or the like. The system 1100 is adapted to
performed interference cancellation in real time. For example, the
interference cancellation is performed with a latency of less than
2 ms.
[0071] The system 1100 may additionally include a computer-readable
storage media reader 1150. The system 1100 includes a communication
system 1160 (e.g., a modem, a network card (wireless or wired), an
infra-red communication device, Bluetooth.TM. device, cellular
communication device, etc.), and working memory 1180, which may
include RAM and ROM devices as described above. For example, the
communication system 1160 comprises a wireless communication
interface compatible with CDMA standard. In some embodiments, the
computer system 1100 may also include a processing acceleration
unit 1170, which can include a digital signal processor, a
special-purpose processor, and/or the like.
[0072] The computer-readable storage media reader 1150 can further
be connected to a computer-readable storage medium, together (and,
optionally, in combination with storage device(s) 1140)
comprehensively representing remote, local, fixed, and/or removable
storage devices plus storage media for temporarily and/or more
permanently containing computer-readable information. The
communication system 1160 may permit data to be exchanged with a
wireless network, system, computer, and/or other component
described above.
[0073] The system 1100 may also comprise software elements, shown
as being currently located within a working memory 1180, including
an operating system 1188 and/or other code 1184. It should be
appreciated that alternate embodiments of a computer system 1100
may have numerous variations from that described above. For
example, customized hardware might also be used and/or particular
elements might be implemented in hardware, software (including
portable software, such as applets), or both. Furthermore,
connection to other computing devices such as network input/output
and data acquisition devices may also occur.
[0074] Software of system 1100 may include code 1184 for
implementing any or all of the functions of the various elements of
the architecture as described herein. For example, software, stored
on and/or executed by a computer system such as system 1100, can
provide the functionality and/or other components of the invention
such as those discussed above. Methods implementable by software on
some of these components have been discussed above in more
detail.
[0075] Merely by way of example, FIG. 12 illustrates a schematic
diagram of a system 1200 that can be used in accordance with one
set of embodiments. The system 1200 can include one or more user
devices 1205. The user devices 1205 can be general purpose personal
computers (including, merely by way of example, laptop computers
running any appropriate flavor of Microsoft Corp.'s Windows.TM.
and/or Apple Corp.'s Macintosh.TM. operating systems) and/or
workstation computers running any of a variety of commercially
available UNIX.TM. or UNIX-like operating systems. These user
computers 1205 can also have any of a variety of applications,
including one or more applications configured to perform methods of
the invention, as well as one or more office applications, database
client and/or server applications, and web browser applications.
Alternatively, the user computers 1205 can be any other electronic
device, such as a thin-client computer, Internet-enabled mobile
telephone, and/or personal digital assistant (PDA), capable of
communicating via a wireless network (e.g., the network 1210
described below) and/or displaying and navigating web pages or
other types of electronic documents. Although the exemplary system
1200 is shown with three user devices 1205, any number of user
computers can be supported. For example, the user device 1205a is a
wireless phone, which can be configured to performed interference
cancellation described above.
[0076] Certain embodiments of the invention operate in a networked
environment, which can include a network 1210. The network 1210 can
be any type of network familiar to those skilled in the art that
can support data communications using any of a variety of
commercially available protocols, including without limitation
TCP/IP, SNA, IPX, AppleTalk, and the like. Merely by way of
example, the network 1210 can be a local area network ("LAN"),
including without limitation an Ethernet network, a Token-Ring
network, and/or the like; a wide-area network (WAN); a virtual
network, including without limitation a virtual private network
("VPN"); the Internet; an intranet; an extranet; a public switched
telephone network ("PSTN"); an infrared network; a wireless
network, including without limitation a network operating under any
of the IEEE 802.11 suite of protocols, the Bluetooth.TM. protocol
known in the art, and/or any other wireless protocol; and/or any
combination of these and/or other networks. In various embodiments,
the network 1210 is a wireless communication network. For example,
the network 1210 is configured to communicate using wireless
communication protocols such as CDMA, GSM, and/or others.
[0077] Embodiments of the invention can include one or more server
computers 1215. Each of the server computers 1215 may be configured
with an operating system, including without limitation any of those
discussed above, as well as any commercially (or freely) available
server operating systems. Each of the servers 1215 may also be
running one or more applications, which can be configured to
provide services to one or more user devices 1205 and/or other
server computers 1215.
[0078] Merely by way of example, one of the server computers 1215
may be a web server, which can be used, merely by way of example,
to process requests for web pages or other electronic documents
from user computers 1205. The web server can also run a variety of
server applications, including HTTP servers, FTP servers, CGI
servers, database servers, Java.TM. servers, and the like. In some
embodiments of the invention, the web server may be configured to
serve web pages that can be operated within a web browser on one or
more of the user computers 1205 to perform methods of the
invention.
[0079] The server computers 1215, in some embodiments, might
include one or more application servers, which can include one or
more applications accessible by a client running on one or more of
the user computers 1205 and/or other server computers 1215. Merely
by way of example, the server computers 1215 can be one or more
general purpose computers capable of executing programs or scripts
in response to the user computers 1205 and/or other server
computers 1215, including without limitation web applications
(which might, in some cases, be configured to perform methods of
the invention). Merely by way of example, a web application can be
implemented as one or more scripts or programs written in any
suitable programming language, such as Java.TM., C, C#.TM. or C++,
and/or any scripting language, such as Perl, Python, or TCL, as
well as combinations of any programming/scripting languages. The
application server(s) can also include database servers, including
without limitation those commercially available from Oracle.TM.,
Microsoft.TM.. Sybase.TM., IBM.TM. and the like, which can process
requests from clients (including, depending on the configuration,
database clients, API clients, web browsers, etc.) running on a
user computer 1205 and/or another server computer 1215. In some
embodiments, an application server can create web pages dynamically
for displaying the information in accordance with embodiments of
the invention. Data provided by an application server may be
formatted as web pages (comprising HTML, Javascript, etc., for
example) and/or may be forwarded to a user computer 1205 via a web
server (as described above, for example). Similarly, a web server
might receive web page requests and/or input data from a user
computer 1205 and/or forward the web page requests and/or input
data to an application server. In some cases, a web server may be
integrated with an application server.
[0080] In accordance with further embodiments, one or more server
computers 1215 can function as a file server and/or can include one
or more of the files (e.g., application code, data files, etc.)
necessary to implement methods of the invention incorporated by an
application running on a user computer 1205 and/or another server
computer 1215. Alternatively, as those skilled in the art will
appreciate, a file server can include all necessary files, allowing
such an application to be invoked remotely by a user computer 1205
and/or server computer 1215. It should be noted that the functions
described with respect to various servers herein (e.g., application
server, database server, web server, file server, etc.) can be
performed by a single server and/or a plurality of specialized
servers, depending on implementation-specific needs and
parameters.
[0081] In certain embodiments, the system can include one or more
database(s) 1220. The location of the database(s) 1220 is
discretionary. Merely by way of example, a database 1220a might
reside on a storage medium local to (and/or resident in) a server
computer 1215a (and/or a user computer 1205). Alternatively, a
database 1220b can be remote from any or all of the computers 1205,
1215, so long as the database can be in communication via the
network 1210) with one or more of these. In a particular set of
embodiments, a database 1220 can reside in a storage-area network
("SAN") familiar to those skilled in the art. (Likewise, any
necessary files for performing the functions attributed to the
computers 1205, 1215 can be stored locally on the respective
computer and/or remotely, as appropriate.) In one set of
embodiments, the database 1220 can be a relational database, such
as an Oracle.TM. database, that is adapted to store, update, and
retrieve data in response to SQL-formatted commands. The database
might be controlled and/or maintained by a database server, as
described above, for example.
[0082] The invention has now been described in detail for the
purposes of clarity and understanding. However, it will be
appreciated that certain changes and modifications may be practiced
within the scope of the appended claims.
* * * * *