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| United States Patent Application |
20090239486
|
| Kind Code
|
A1
|
|
Sugar; Gary L.
;   et al.
|
September 24, 2009
|
APPARATUS FOR ANTENNA DIVERSITY USING JOINT MAXIMAL RATIO COMBINING
Abstract
A method for improving performance of radio frequency (RF) communication
of a station (STA) having an access point (AP) is disclosed. The method
includes using an arbitrary set of transmit antenna weights, calculating
a set of receive antenna weights, and updating the transmit antenna
weights based on the receive antenna weights.
| Inventors: |
Sugar; Gary L.; (Rockville, MD)
; Vaidyanathan; Chandra; (Bethesda, MD)
; Tesfai; Yohannes; (Falls Church, VA)
|
| Correspondence Address:
|
VOLPE AND KOENIG, P.C.;DEPT. ICC
UNITED PLAZA, SUITE 1600, 30 SOUTH 17TH STREET
PHILADELPHIA
PA
19103
US
|
| Assignee: |
IPR LICENSING, INC.
Wilmington
DE
|
| Serial No.:
|
481385 |
| Series Code:
|
12
|
| Filed:
|
June 9, 2009 |
| Current U.S. Class: |
455/101 |
| Class at Publication: |
455/101 |
| International Class: |
H04B 1/02 20060101 H04B001/02 |
Claims
1. A method for improving performance of radio frequency (RF)
communication of a station (STA) having an access point (AP), the method
comprising:transmitting a transmit antenna weight vector using a complex
transmit antenna weight vector for each of a plurality of N antennas,
wherein each complex transmit antenna weight has a magnitude and a phase
whose values may vary with frequency;calculating a receive antenna weight
vector comprising a plurality of complex receive antenna weights for the
N plurality of antennas; andupdating the transmit antenna weight vector
for the plurality of N antennas based on a computed conjugate of the
received antenna weight vector and a norm of the receive antenna weight
vector.
2. The method as in claim 1, wherein the transmit weight vector and the
receive antenna weight vector converge to values that optimize the
signal-to noise-ratio (SNR) of the STA.
3. The method as in claim 1, wherein the receive antenna weights are
computed from a matrix multiplication of an arbitrary set of transmit
antenna weights and a channel response matrix.
4. The method as in claim 2, further comprising storing in a memory the
optimized SNR value.
5. The method as in claim 4, wherein the optimized SNR value is stored in
a look-up-table.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001]This application is a continuation of U.S. application Ser. No.
11/231,161, filed Sep. 20, 2005, which is a continuation of U.S.
application Ser. No. 10/695,229, filed Oct. 28, 2003, which in turn is a
continuation of U.S. application Ser. No. 10/174,728, filed Jun. 19,
2002, which issued on Feb. 3, 2004 as U.S. Pat. No. 6,687,492, which in
turn claims priority to U.S. Provisional Application No. 60/365,797,
filed Mar. 21, 2002 and to U.S. Provisional Application No. 60/361,055
filed Mar. 1, 2002, which are incorporated by reference as if fully set
forth.
FIELD OF THE INVENTION
[0002]The present application is directed to antenna (spatial) signal
processing useful in wireless communication applications, such as
short-range wireless applications.
[0003]Antenna diversity schemes are well known techniques to improve the
performance of radio frequency (RF) communication between two RF devices.
Types of antenna diversity schemes include antenna selection diversity
and maximal ratio combining. An antenna selection diversity scheme
selects one of two antennas for transmission to a particular
communication device based on which of the two antennas best received a
signal from the particular communication device. On the other hand,
maximal ratio combining schemes involve beamforming a signal to be
transmitted by two or more antennas by scaling the signal with an antenna
weight associated with each antenna. A signal received by a plurality of
antennas can also be weighted by a plurality of receive antenna weights.
Selection of the antenna weights to optimize communication between two
communication devices is critical to the performance of maximal ratio
combining schemes.
[0004]There is room for improving the maximal ratio combining antenna
processing schemes to optimize the link margin between two RF
communication devices.
SUMMARY
[0005]An antenna signal processing scheme, hereinafter called composite
beamforming (CBF), is provided to optimize the range and performance RF
communication between two communication devices. Composite beamforming
(CBF) is a multiple-input multiple-output (MIMO) antenna scheme that uses
antenna signal processing at both ends of the communication link to
maximize the signal-to-noise (SNR) and/or
signal-to-noise-plus-interference (SNIR), thereby improving the link
margin between two communication devices, as well as to provide for other
advantages described herein.
[0006]Generally, a first communication device has a plurality of antennas
and the second communication has a plurality of antennas. The first
communication device transmits to the second communication device using a
transmit weight vector for transmission by each the plurality of antennas
and the transmit signals are received by the plurality of antennas at the
second communication device. The second communication device determines
the receive weight vector for its antennas, and from that vector, derives
a suitable transmit weight vector for transmission on the plurality of
antennas back to the first communication device. Several techniques are
provided to determine the optimum frequency dependent transmit weight
vector and receive weight vector across the bandwidth of a baseband
signal transmitted between the first and second communication devices so
that there is effectively joint or composite beamforming between the
communication devices. The link margin between communication devices is
greatly improved using the techniques described herein.
[0007]With the same antenna configuration, 2-antenna CBF (2-CBF) provides
an SNR improvement of up to 10 dB over transmit/selection diversity when
it is used at both ends of the link. A system design using 4 antennas at
a first communication device and 2 antennas at a second communication
device (hereinafter referred to as 4.times.2 CBF) provides nearly 14 dB
of SNR improvement. In general, for a fixed number of antennas, CBF
outperforms the well-known space-time block codes by up to 4 dB.
Moreover, unlike space-time coding, CBF does not require a change to an
existing wireless standard.
[0008]The above and other objects and advantages will become more readily
apparent when reference is made to the following description taken in
conjunction with the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0009]FIG. 1 is a block diagram of two communication devices performing an
antenna diversity scheme using composite beamforming.
[0010]FIG. 2 is a block diagram of a communication device that may be used
at either end of a composite beamforming communication link.
[0011]FIG. 3 is a flow chart illustrating an adaptive method to obtain
antenna beamforming weights for communication between first and second
communication devices.
[0012]FIGS. 4 and 5 are graphical diagrams illustrating convergence
properties of the adaptive method shown in FIG. 3.
[0013]FIG. 6 is a diagram showing application of beamforming weights to a
baseband signal for transmission in a frequency dependent communication
channel.
[0014]FIG. 7 is a flow chart illustrating an adaptive algorithm to obtain
antenna beamforming weights in a frequency dependent communication
channel.
[0015]FIG. 8 is a block diagram of a composite beamforming transmission
process for a multi-carrier baseband modulation scheme.
[0016]FIG. 9 is a block diagram of a composite beamforming reception
process for a multi-carrier baseband modulation scheme.
[0017]FIG. 10 is a block diagram of a composite beamforming transmission
process for a single carrier baseband modulation scheme.
[0018]FIG. 11 is a block diagram of a composite beamforming reception
process for a single carrier baseband modulation scheme.
[0019]FIG. 12 is a flow chart of a beamforming training method where one
communication device of a communication link uses antenna selection
diversity.
[0020]FIG. 13 is a flow chart illustrating a collaborative method to
obtain antenna processing parameters for communication between first and
second communication devices.
DETAILED DESCRIPTION
[0021]Referring first to FIG. 1, a system 10 is shown in which a first
communication device 100 and a second communication device 200
communicate with each other using radio frequency (RF) communication
techniques. The techniques described herein are useful in any radio
frequency (RF) communication application, such as short-range wireless
applications. A wireless local area network (WLAN) is only an example of
an application. For example, device 100 may be an access point (AP) in a
WLAN, and device 200 may be a station (STA).
[0022]Generally, the device 100 has Nap antennas 110 and the device 200
has Nsta antennas 210. FIG. 1 shows an example where the device 100 has
three antennas 110 and the device 200 has two antennas 210. A complex
transmit symbol at device 100 is scaled (multiplied) using a set of
complex transmit antenna weights w.sub.tx,ap=[w.sub.0 . . .
w.sub.Nap-1].sup.T before being transmitted through respective ones of
the antennas 110 (.sup.T denotes the transpose operator). The received
vector at device 200 is r.sub.sta=sH w.sub.tx,ap+n, where H is an Nsta by
Nap channel matrix of unity variance, complex Gaussian random variables
(to represent flat Rayleigh fading between each antenna), and n
represents noise and interference. At device 200, a combiner
C=(w.sub.rx,sta).sup.Hr is applied, C is passed to a detection circuit
(e.g., soft-decision QAM detector, etc.). If H is known at both the
transmitter and the receiver, w.sub.tx,ap and w.sub.rx,sta may be
selected to maximize the signal-to-noise ratio (SNR) at the output of the
combiner subject to a transmit power constraint, i.e.,
(w.sub.tx,ap).sup.H w.sub.tx,ap=1.
[0023]The SNR for C is maximized over w.sub.tx,ap and w.sub.rx,sta when
w.sub.tx,ap is equal to e.sub.max, the unit norm eigenvector for the
maximum eigenvalue .lamda..sub.max of the matrix H.sup.HH, and
w.sub.rx,sta is a matched filter for He.sub.max, i.e., w.sub.rx,sta=k
He.sub.max for some nonzero constant k. Under these conditions, the SNR
for C is equal to .lamda..sub.max. Since H is a random matrix,
.lamda..sub.max is a random variable. The distribution on .lamda..sub.max
is well known, and can be found in M. Wennstrom, M. Helin, A. Rydberg, T.
Oberg, "On the Optimality and Performance of Transmit and Receive Space
Diversity in MIMO Channels", IEEE Technical Seminar on MIMO Systems,
London, December, 2001, which is incorporated herein by reference.
[0024]The transmit device and the receive device communicate using
time-division-duplexing at the same frequency. The channel matrix for the
reverse link is H.sub.r=H.sup.T, and the optimum transmit weight vector
w.sub.tx,ap is equal to the eigenvector for the maximum eigenvalue of
H.sub.r.sup.HH.sub.r=H*H.sup.T (* denotes the conjugate operator). The
maximum SNR at either end of the link is the same (since it is a well
known result that the nonzero eigenvalues for both H*H.sup.T and H.sup.HH
are the same). The beamforming technique that results from this analysis
is hereinafter referred to as composite beamforming (CBF).
[0025]The communication devices at both ends of the link, i.e., devices
100 and 200 may have any known suitable architecture to transmit, receive
and process signals. An example of a communication device block diagram
is shown in FIG. 2. The communication device 300 comprises an RF section
310, a baseband section 320 and optionally a host 330. There are a
plurality of antennas, e.g., four antennas 302, 304, 306, 308 coupled to
the RF section 310 that are used for transmission and reception. The RF
section 310 has a transmitter (Tx) 312 that upconverts baseband signals
for transmission, and a receiver (Rx) 314 that downconverts received RF
signals for baseband processing. In the context of the composite
beamforming techniques described herein, the Tx 312 upconverts and
supplies separately weighted signals to corresponding ones of each of the
plurality of antennas via separate power amplifiers. Similarly, the Rx
314 downconverts and supplies received signals from each of the plurality
of antennas to the baseband section 320. The baseband section 320
performs processing of baseband signals to recover the information from a
received signal, and to convert information in preparation for
transmission. The baseband section 320 may implement any of a variety of
communication formats or standards, such as WLAN standards IEEE 802.11x,
Bluetooth.TM., as well as other protocol standards, not necessarily used
in a WLAN.
[0026]The intelligence to execute the computations for the composite
beamforming techniques described herein may be implemented in a variety
of ways. For example, a processor 322 in the baseband section 320 may
execute instructions encoded on a processor readable memory 324 (RAM,
ROM, EEPROM, etc.) that cause the processor 322 to perform the composite
beamforming steps described herein. Alternatively, an application
specific integrated circuit (ASIC) configured with the appropriate
firmware, e.g., field programmable gates that implement digital signal
processing instructions to perform the composite beamforming steps. This
ASIC may be part of, or the entirety of, the baseband section 320. Still
another alternative is for the beamforming computations to be performed
by a host processor 332 (in the host 330) by executing instructions
stored in (or encoded on) a processor readable memory 334. The RF section
310 may be embodied by one integrated circuit, and the baseband section
320 may be embodied by another integrated circuit. The communication
device on each end of the communication link need not have the same
device architecture or implementation.
[0027]Regardless of the specific implementation chosen, the composite
beamforming process is generally performed as follows. A transmit weight
vector (comprising a plurality of complex transmit antenna weights
corresponding to the number of transmit antennas) is applied to, i.e.,
multiplied by, a baseband signal to be transmitted, and each resulting
weighted signal is coupled to a transmitter where it is upconverted,
amplified and coupled to a corresponding one of the transmit antennas for
simultaneous transmission. At the communication device on the other end
of the link, the transmit signals are detected at each of the plurality
of antennas and downconverted to a baseband signal. Each baseband signal
is multiplied by a corresponding one of the complex receive antenna
weights and combined to form a resulting receive signal. The architecture
of the RF section necessary to accommodate the beamforming techniques
described herein may vary with a particular RF design, and many are known
in the art and thus is not described herein.
[0028]Turning to FIG. 3, a process 400 is shown for achieving optimum CBF
between two communication devices. To restate the results from the
previous discussion, the optimum receive and transmit weights at the AP
are given by w.sub.rx,ap=e.sub.max(of H.sup.HH),
w.sub.tx,ap=w.sub.rx,ap*. The optimum receive and transmit weights at the
STA are given by w.sub.rx,sta=e.sub.max(of H*H.sup.T),
w.sub.tx,sta=w.sub.rx,sta*. Additionally, w.sub.rx,sta=H w.sub.tx,ap,
w.sub.rx,ap=H.sup.T w.sub.tx,ap. These properties can be utilized to
design an adaptive/iterative algorithm that converges to the optimum
eigenvector as follows.
[0029]Initially, in step 410, the AP uses an arbitrary set of transmit
antenna weights to transmit a signal to the STA. When the STA receives
the signal, the receive antenna weights at the STA are matched to the
receive signal such that w.sub.rx,sta(0)=H w.sub.tx,ap(0). That is, the
STA receive antenna weights are computed from the received signals at
each of the antennas by matching to the received signals. In step 420,
the STA computes the conjugate of the receive weight vector made up of
the receive antenna weights for use as the transmit antenna weight vector
for transmitting on the STA's antennas back to the AP. The AP receives
the signal transmitted by the plurality of antennas of the STA and
matches the receive antenna weights to the received signal.
[0030]In step 430, the AP updates the new transmit antenna weights by
computing the conjugate of the receive weight vector (comprised of the AP
receive antenna weights) divided by the norm of the AP receive weight
vector. This process repeats in steps 440 through 460, ad infinitum. It
can be shown that the weights converge to the eigenvector corresponding
to the maximum eigenvalue. See G. Golub, C. V. Loan, "Matrix
Computations", 2nd edition, pp. 351.
[0031]Within a few iterations, the transmit weight vector and receive
antenna weight vector of both devices will converge to values that
optimize the SNR at each of the devices. At such point, the first
communication device may store in a memory (in the baseband section or
host processor section) the current optimum transmit antenna weights for
a particular destination communication device indexed against an
identifier for that communication device. The first communication device,
such as an AP, may store in a look-up-table optimum transmit antenna
weights indexed against corresponding identifiers (such as MAC addresses)
for a plurality of other communication devices it communicates with.
[0032]The adaptive process of FIG. 3 will converge to optimum antenna
weights even if one device has multiple antennas and can weight signals
supplied thereto, and the other device is a merely a single antenna
device. The device on the link with the multiple antennas and combining
capability can still converge to its optimum transmit and receive weights
for a single antenna device it communicates with.
[0033]With reference to FIGS. 4 and 5, the convergence properties of the
adaptive algorithm were studied over 1000 randomly generated channels.
The average SNR at each receive antenna was set to 10 dB. The normalized
antenna array gain at the output of the receive antenna array,
|Hw.sub.tx|.sup.2/.lamda..sub.max(H.sup.HH) is used to study the
performance. In FIG. 4, (Nap=2, Nsta=2), it is shown that the adaptive
algorithm loss is less than a 1 dB at the 3rd iteration with 95%
probability. When the number of antenna elements is increased to four,
only one additional iteration was required for the algorithm converge to
less than 1 dB loss with 95% probability.
[0034]An advantage of adaptive composite beamforming is that no special
training sequence is required for adaptation. In addition, no changes to
existing protocols are necessary, and there is no impact on throughput.
The antenna weights are updated when real information or data is
transmitted between devices. Transmit and receive weight adaptation is
the same regardless of whether CBF is implemented at both ends of the
link. However, if the destination device uses selection diversity the
performance can be improved by estimating the channel response.
[0035]The indoor wireless channel is a frequency dependent channel. Due to
multi-path propagation the signal arrives at the receiver with different
delays. The different delays cause the channel transfer function to be
frequency selective. Therefore, to account for these delays, the antenna
weights need to be adjusted according to the frequency dependent
characteristics of the channel transfer function between the transmitting
device and the receiving device.
[0036]Solutions for optimum antenna processing in a frequency selective
channel are described hereinafter. Between any two communication devices,
the communication channel will have a frequency response depending on
frequency selective fading conditions, etc. The channel transfer function
H(f) describes the frequency response and is used to select the optimum
antenna transmit and receive weights for communication between those
terminals.
[0037]To understand the frequency selective situation, reference is again
made to FIG. 1, where the frequency dependent Nsta by Nap transfer
function between the first and communication device and the second
communication devices is denoted by the H(f). The Nap by Nsta transfer
function between the second communication device and the first
communication device is H.sup.T(f). The transmit weights at the first and
second communication devices are denoted by the Nap.times.1 vector
w.sub.tx,ap(f) and the Nsta.times.1 vector w.sub.tx,sta(f), respectively.
w.sub.tx,ap(f)=[w.sub.tx,ap,1(f), w.sub.tx,ap,2(f), . . .
w.sub.tx,ap,Nap(f)].sup.T
w.sub.tx,sta(f)[w.sub.tx,sta,1(f), w.sub.tx,sta,2(f), . . .
w.sub.tx,sta,Nsta(f)].sup.T
[0038]The receive weights at the first and second communication devices
are denoted by the Nap.times.1 vector w.sub.rx,ap(f) and the Nsta.times.1
vector w.sub.rx,sta(f), respectively
w.sub.rx,ap(f)=[w.sub.rx,ap,1(f), w.sub.rx,ap,2(f), . . .
w.sub.rx,ap,Nap(f)].sup.T
w.sub.rx,sta(f)=[w.sub.rx,sta,1(f), w.sub.rx,sta,2(f), . . .
w.sub.rx,sta,Nsta(f)].sup.T
[0039]The transmit and receive weights (only the first communication
device-second communication device link is described below but the
results apply in the reverse direction with appropriate change in
notation) are computed by optimizing a cost function, C, with a
constraint on the maximum transmit power. In a communication system, the
ultimate goal is to reduce bit-error rate (BER).
[0040]However, optimization using the BER as a cost function is not always
analytically feasible. Therefore, cost functions that implicitly reduce
the BER are usually selected. The cost function also depends on the
receiver structure. Selection of the cost function for different
modulation schemes and receiver structures is discussed.
min w tx , ap w rx , sta .intg. - 1 / 2 T 1
/ 2 T C ( H ( f ) , w tx , ap ( f ) , w
rx , sta ( f ) ) f , subject to
.intg. - 1 / 2 T 1 / 2 T | w tx , ap ( f ) |
2 f .ltoreq. P 0 ##EQU00001##
[0041]For a code division multiple access (CDMA) communication system,
such as IEEE 802.11b, the receiver is assumed to be a RAKE receiver and
the BER is a function of the SNIR (signal to noise+interference ratio) at
the output of the RAKE receiver. Maximizing the SNIR at the output of the
RAKE receiver minimizes the BER.
max w tx , ap w rx , sta .intg. - 1 / 2 T 1
/ 2 T SNIR ( H ( f ) , w tx , ap ( f ) , w
rx , sta ( f ) ) f , subject to
.intg. - 1 / 2 T 1 / 2 T | w tx , ap ( f ) |
2 f .ltoreq. P 0 ##EQU00002##
[0042]For an orthogonal frequency division multiplex (OFDM) system, such
as IEEE 802.11a, the receiver is a linear equalizer followed by a Viterbi
decoder. Since the Viterbi decoder is a non-linear operator, optimizing
the coded BER is very challenging. An alternative is to minimize the mean
square error (MSE) at the output of the linear equalizer (note another
possible approach is to minimize the uncoded BER).
min w tx , ap w rx , sta .intg. - 1 / 2 T 1
/ 2 T MSE ( H ( f ) , w tx , ap ( f ) , w
rx , sta ( f ) ) f , subject to
.intg. - 1 / 2 T 1 / 2 T | w tx , ap ( f ) |
2 f .ltoreq. P 0 ##EQU00003##
[0043]A single carrier modulation scheme, such as IEEE 802.11b, uses a
decision feedback equalizer (DFE) at the receiver. The receiver is a
non-linear receiver. The transmit, receive and feedback weights are
computed jointly. This can be achieved by minimizing the MSE at the
output of the DFE.
min w tx , ap w rx , sta B .intg. - 1 / 2 T
1 / 2 T MSE ( H ( f ) , w tx , ap ( f ) ,
w rx , sta ( f ) ) f , subject to
.intg. - 1 / 2 T 1 / 2 T | w tx , ap ( f )
| 2 f .ltoreq. P 0 ##EQU00004##
[0044]For all cases considered, the optimum transmit weights are given by
w.sub.tx.sub.--.sub.ap(f)=p(f)e.sub.max(H.sup.H(f)H(f))
where e.sub.max is the eigenvector corresponding to the maximum eigenvalue
of the matrix H.sup.H(f) H(f), where p (f) is a weighting function that
weights each individual frequency bin and is based on the cost function.
Typically, the solution to p(f) follows a waterpouring distribution.
[0045]For the linear equalizer case, the solution is given by
p 2 ( f ) = 1 .mu. .sigma. s 2 .sigma. n 2
.lamda. ma x ( f ) - 1 .sigma. s 2 .sigma. n 2
.lamda. ma x ( f ) ##EQU00005## SNR = .sigma. s
2 .sigma. n 2 ##EQU00005.2##
[0046]For the DFE case, the solution is
p 2 ( f ) = 1 .mu. - 1 .sigma. s 2 .sigma. n 2
.lamda. max ( f ) ##EQU00006##
where .mu. is selected to satisfy the power constraint
.intg. 1 / 2 T 1 / 2 T p 2 ( f ) f = P
0 ##EQU00007##
[0047]An optimal solution for p(f) requires knowledge of the channel and
SNR at the receiver. A suboptimal solution is obtained by setting p(f) to
a constant, p, across frequency.
w.sub.tx.sub.--.sub.ap(f)=pe.sub.max(H.sup.H(f)H(f))
[0048]This is referred to herein as a frequency shaping constraint. To
explain further, the frequency shaping constraint requires that at each
frequency of the baseband signal to be transmitted (e.g., frequency
sub-band or frequency sub-carrier k), the sum of the power of signals
across all of the transmit antennas is equal to a constant value,
P.sub.tx/K. This constraint is useful to ensure that, in an iterative
process between two communication devices, the transmit weights of the
two devices will converge to optimal values. An additional benefit of
this constraint is that the transmitting device can easily satisfy
spectral mask requirements of a communication standard, such as IEEE
802.11x.
[0049]This solution does not require knowledge of the receiver SNR and
simulations have shown that the loss in performance over the optimal
solution is negligible. However, this solution requires knowledge of the
channel response at the transmitter.
[0050]For the cost functions maximizing the SNIR or minimizing the MSE for
a linear equalizer, the optimum receive weights are given by
w.sub.rx,sta(f)=R.sub.ss.sup.-1(f)v.sub.mf,sta(f)
[0051]where v.sub.mf,sta(f) is matched to the received signal
v.sub.mf,sta(f)=H(f)w.sub.tx,ap(f)
and R.sub.ss(f) is the correlation matrix defined as
R ss ( f ) = .sigma. s 2 H ( f ) w tx , ap
( f ) w tx , ap H H H ( f ) + .sigma. n 2 I
= .sigma. s 2 v mf , sta ( f ) v mf , sta
H ( f ) + .sigma. n 2 I ##EQU00008##
[0052]When the MSE of the DFE is the minimized, the optimum receive
weights are given by
w.sub.rx,sta(f)=R.sub.ss.sup.-1(f)v.sub.mf,sta(f)(1+B(f))
where B(f) is the feedback filter.
[0053]The weights for the reverse link are similar to the forward link and
is summarized below. The optimum transmit weights at the second
communication are given by
w.sub.tx.sub.--.sub.sta(f)=p(f)e.sub.max(H*(f)H.sup.T(f))
and the suboptimal transmit weights are
w.sub.tx.sub.--.sub.sta(f)=pe.sub.max(H*(f)H.sup.T(f))
[0054]Similarly, the receive weights at the first communication device are
given by
w.sub.rx,ap(f)=R.sub.aa.sup.-1(f)v.sub.mf,ap(f)
where
v.sub.mf,ap(f)=H.sup.T(f)w.sub.tx,sta(f)
[0055]and for DFE case
R.sub.aa(f)=.sigma..sub.s.sup.2v.sub.mf,ap(f)+.sigma..sub.n.sup.2I
w.sub.rx,ap(f)=R.sub.xx.sup.-1(f)(1+B(f))
[0056]In the presence of co-channel interference R.sub.ss(f) is given by
R ss ( f ) = .sigma. s 2 H ( f ) w tx , ap
( f ) w tx , ap H ( f ) H H ( f ) + k
.noteq. 0 .sigma. k 2 H k ( f ) w k ( f )
w k H ( f ) H k H ( f ) + .sigma. n 2 I
##EQU00009##
where the terms in the summation are the contribution due to the
interferes. In this case, the optimum receive antenna weights minimize
the contribution of the interferes and the noise. Therefore, in addition
to diversity gain, optimum antenna combining at the receiver also
provides interference suppression capability.
[0057]FIG. 6 illustrates how frequency selective beamforming weights are
applied to a baseband signal. The baseband signal may be a single carrier
signal or a multi-carrier signal. In either case, the baseband signal
will have a bandwidth or spectrum. According to the composite beamforming
(CBF) technique described herein, when communication device 100 transmits
a signal to communication device 200, it applies (i.e., multiplies or
scales) a baseband signal s to be transmitted by a transmit weight vector
associated with a particular destination device, e.g., communication
device 200, denoted w.sub.tx,1. Similarly, when communication device 200
transmits a baseband signal s to communication device 100, it multiplies
the baseband signal s by a transmit weight vector w.sub.tx,2, associated
with destination communication device 100. The (M.times.N) frequency
dependent channel matrix from the N plurality of antennas of the first
communication device 100 to M plurality of antennas of the second
communication device 200 is H(k), and the frequency dependent
communication channel (N.times.M) matrix between the M plurality of
antennas of the second communication device and the N plurality of
antennas of the first communication device is H.sup.T(k). The variable k
denotes the frequency dependent characteristic as explained further
hereinafter.
[0058]The transmit weight vectors w.sub.tx,1 and w.sub.tx,2 each comprises
a plurality of transmit weights corresponding to each of the N and M
antennas, respectively. Each transmit weight is a complex quantity.
Moreover, each transmit weight vector is frequency dependent; it varies
across the bandwidth of the baseband signal s to be transmitted. For
example, if the baseband signal s is a multi-carrier signal of K
sub-carriers, each transmit weight for a corresponding antenna varies
across the K sub-carriers. Similarly, if the baseband signal s is a
single-carrier signal (that can be divided into K frequency sub-bands),
each transmit weight for a corresponding antenna varies across the
bandwidth of the baseband signal. Therefore, the transmit weight vector
is dependent on frequency, or frequency sub-band/sub-carrier k, such that
w.sub.tx becomes w.sub.tx(f), or more commonly referred to as
w.sub.tx(k), where k is the frequency sub-band/sub-carrier index.
[0059]While the terms frequency sub-band/sub-carrier are used herein in
connection with beamforming in a frequency dependent channel, it should
be understood that the term "sub-band" is meant to include a narrow
bandwidth of spectrum forming a part of a baseband signal. The sub-band
may be a single discrete frequency (within a suitable frequency
resolution that a device can process) or a narrow bandwidth of several
frequencies.
[0060]The receiving communication device also weights the signals received
at its antennas with a frequency dependent receive antenna weight vector
w.sub.rx(k). Communication device 100 uses a receive antenna weight
vector w.sub.rx,1(k) when receiving a transmission from communication
device 200, and communication device 200 uses a receive antenna weight
vector w.sub.rx,2(k) when receiving a transmission from communication
device 100. The receive antenna weights of each vector are matched to the
received signals by the receiving communication device.
[0061]Generally, transmit weight vector w.sub.tx,1 comprises a plurality
of transmit antenna weights
w.sub.tx,1,i=.beta..sub.1,i(k)e.sup.j.phi.1,i,(k), where
.beta..sub.1,i(k) is the magnitude of the antenna weight, .phi.1,i,(k) is
the phase of the antenna weight, i is the antenna index (up to N), and k
is the frequency sub-band or sub-carrier index (up to K frequency
sub-bands/sub-carriers). The subscripts tx,1 denote that it is a vector
that communication device 100 uses to transmit to communication device
200. Similarly, the subscripts tx,2 denote that it is a vector that
communication device 200 uses to transmit to communication device 100.
[0062]The frequency shaping constraint described above may be imposed on
the transmit weights for each antenna. As mentioned above, the constraint
requires that at each frequency of the baseband signal to be transmitted
(e.g., frequency sub-band or frequency sub-carrier k), the sum of the
power of signals across all of the transmit antennas
(|w.sub.tx,i(k)|.sup.2 for i=1 to N) is equal to a constant value,
P.sub.tx/K.
[0063]The relationship between transmit and receive weights are summarized
below: The optimum receive and transmit weights at the first
communication device are related as follows.
w.sub.tx,ap(f)=emax(H.sup.H(f)H(f)),v.sub.mf,sta(f)=H(f)w.sub.tx,ap(f)
[0064]Similarly at the second communication device, the optimum receive
and transmit weights are related as follows.
w.sub.tx,sta(f)=emax(H*(f)H.sup.T(f)),v.sub.mf,ap(f)=H.sup.T(f)w.sub.tx,st-
a(f)
Additionally,
v.sub.mf,ap(f)=w.sub.tx,ap*(f),v.sub.mf,sta(f)=w.sub.tx,ap*(f)
[0065]The properties outlined above can be utilized in an
adaptive/iterative process 480 shown in FIG. 7 that is similar to the
process shown in FIG. 3. The antenna weight parameters in FIG. 4 are
written with indexes to reflect communication between an AP and a STA,
but without loss of generality, it should be understood that this process
is not limited to a WLAN application, and is useful in any wireless
application, such as a short-range application. The AP has Nap antennas
and the STA has Nsta antennas. Assuming the AP begins with the first
transmission to the STA, the initial AP transmit weight vector
w.sub.T,AP,0(k) is [1, 1, . . . 1], normalized by 1/(Nap).sup.1/2 for all
antennas and all frequency sub-bands/sub-carriers k. Phase for the
transmit antenna weights are also initially set to zero. The index T
indicates it is a transmit weight vector, index AP indicates it is an AP
vector, index 0 is the iteration of the vector, and (k) indicates that it
is frequency sub-band/sub-carrier dependent. In step 482, a baseband
signal is scaled by the initial AP transmit weight vector
w.sub.T,AP,0(k), upconverted and transmitted to the STA by the Nap
antennas. The transmitted signal is effectively altered by the frequency
selective channel matrix H(k) from AP-STA. The STA receives the signal
and matches its initial receive weight vector w.sub.R,STA,0(k) to the
signals received at its antennas. In step 484, the STA normalizes the
receive weight vector w.sub.R,STA,0(k) and computes the conjugate of
normalized receive weight vector to generate the STA's initial transmit
weights for transmitting a signal back to the AP. In step 486, the STA
processes the signal to be transmitted to the AP by the initial transmit
weight vector, upconverts that signal and transmits it to the AP. The
transmitted signal is effectively altered by the frequency selective
channel matrix H.sup.T(k). At the AP, the receive weight vector is
matched to the signals received at its antennas. The AP then computes the
conjugate of the gain-normalized receive weight vector as the next
transmit weight vector w.sub.T,AP,1(k) and transmits a signal to the STA
with that transmit weight vector. The STA receives the signal transmitted
from the AP with this next transmit weight vector and matches to the
received signals to compute a next receive weight vector
w.sub.R,STA,1(k). Again, the STA computes the conjugate of the
gain-normalized receive weight vector w.sub.R,STA,1(k) as its next
transmit weight vector w.sub.T,STA,1(k) for transmitting a signal back to
the AP. This process repeats for several iterations as shown by steps 488
and 490, ultimately converging to transmit weight vectors that achieve
nearly the same performance as non-equal gain composite beamforming. This
adaptive process works even if one of the devices, such as a STA, has a
single antenna for transmission and reception.
[0066]When storing the transmit weights of a frequency transmit weight
vector, in order to conserve memory space in the communication device,
the device may store, for each antenna, weights for a subset or a portion
of the total number of weights that span the bandwidth of the baseband
signal. For example, if there are K weights for K frequency sub-bands or
sub-carrier frequencies, only a sampling of those weights are actually
stored, such as weights for every other, every third, every fourth, etc.,
k sub-band or sub-carrier. Then, the stored subset of transmit weights
are retrieved from storage when a device is to commence transmission of a
signal, and the remaining weights are generated by interpolation from the
stored subset of weights. Any suitable interpolation can be used, such as
linear interpolation, to obtain the complete set of weights across the K
sub-bands or sub-carriers for each antenna.
[0067]With reference to FIG. 8, a beamforming transmission process 500 is
shown for a multi-carrier baseband modulation scheme. For an orthogonal
frequency division multiplexed (OFDM) system used, for example, by the
IEEE 802.11a standard, the data symbols are in the frequency domain. K
symbols are assigned to K sub-carriers (K=52 for 802.11a). For
convenience, each of the transmit antenna weights are described as a
function of (k), the sub-carrier frequency. Each of the N antennas has a
transmit antenna weight w.sub.tx that is a function of k, i.e.,
w.sub.tx(k) over k=1 to K. The transmit antenna weights are computed by
any of the processes described above at each of the sub-carrier
frequencies. There is a signal processing path for each of the N
antennas. In each signal processing path, a multiplier 510 multiplies the
frequency domain symbol s(k) by the corresponding transmit antenna weight
w.sub.tx(k) and because w.sub.tx(k) has K values, there are K results
from the multiplication process. The results are stored in a buffer 520
for k=1 to K. An inverse Fast Fourier Transform (IFFT) 530 is coupled to
the buffer to convert the frequency domain results stored in buffer 520
to a digital time domain signal for each of the K sub-carriers. There is
some adjustment made for cyclic prefixes caused by the OFDM process. A
filter 540 provides lowpass filtering of the result of the IFFT process.
The digital results of the filtering process are converted to analog
signals by a D/A 550. The outputs of the D/A 550 are coupled to RF
circuitry 560 that upconverts the analog signals to the appropriate RF
signal which is coupled via a power amplifier (PA) 570 to one of the N
antennas 580. In this manner, for each antenna 580, the signal s(k) is
multiplied by respective transmit antenna weights whose values may vary
as a function of the sub-carrier frequency k. The frequency shaping
constraint described above can also be applied to the antenna weights.
[0068]FIG. 9 shows a beamforming reception process 600 that is essentially
the inverse of the transmission process shown in FIG. 8. There is a
signal processing channel for each of the antennas 580. RF circuitry 610
downconverts the RF signals detected at each antenna 580 for each of the
sub-carriers. An A/D 620 converts the analog signal to a digital signal.
A lowpass filter 630 filters the digital signal. There is some adjustment
made for cyclic prefixes caused by the OFDM process. A buffer 640 stores
the time domain digital signal in slots associated with each sub-carrier
frequency k. An FFT 650 converts the time domain digital signal in buffer
640 to a frequency domain signal corresponding to each sub-carrier
frequency k. The output of the FFT 650 is coupled to a multiplier 660
that multiplies the digital signal for each sub-carrier k by a
corresponding receive antenna weight w.sub.rx(k) for the corresponding
one of the N antennas. The outputs of each of the multipliers 660 are
combined by an adder 670 to recover the digital frequency domain symbol
s(k). The signal s(k) is then mapped back to symbol b(k).
[0069]FIGS. 10 and 11 show transmission and reception processes,
respectively, for frequency dependent beamforming applied to a single
carrier baseband modulation scheme, such as that used by the IEEE 802.11b
standard. The data symbols in such a system are in the time domain. FIG.
10 shows a beamforming transmission process 700 suitable for a single
carrier modulation scheme. Since in a frequency dependent channel, the
transmit antenna weights are frequency dependent, the passband of the
baseband signal is synthesized into frequency bins (K bins) and transmit
beamforming weights are computed for each frequency bin using any of the
processes described above. There are processing channels for each
antenna. In each processing channel, transmit filters 710 are synthesized
with the frequency response specified by the beamforming weights. Thus,
each transmit filter 710 has a frequency response defined by the transmit
antenna weight w.sub.tx(f) associated with that antenna. The data symbol
s(n) is passed through the transmit filter 710 which in effect applies
the frequency selective antenna weight to the data symbol s(n). The D/A
720 converts the digital output of the transmit filter 710 to an analog
signal. The RF circuitry 730 upconverts the analog signal and couples the
upconverted analog signal to an antenna 750 via a power amplifier 740.
The frequency shaping constraint described above can also be applied to
the antenna weights.
[0070]FIG. 11 shows a reception process 800 suitable for a single carrier
modulation scheme. There is a processing channel for each antenna 750. In
each processing channel, RF circuitry 810 downconverts the received RF
signal. An A/D 820 converts the downconverted analog signal to a digital
signal. Like the frequency dependent transmit antenna weights, the
receive antenna weights are computed for several frequency sub-bands.
Receive filters 830 are synthesized with the frequency response specified
by the receive beamforming weights w.sub.rx(f) and the received digital
signal is passed through filters 830 for each antenna, effectively
applying a frequency dependent antenna weight to the received signal for
each antenna. The results of the filters 830 are combined in an adder
850, and then passed to a demodulator 860 for demodulation.
[0071]Referring next to FIG. 12, a procedure is shown for use when only
one of the two devices supports beamforming. For example, N-CBF is
supported at a first communication device (an AP) but not at a second
communication device (a STA). In this case, the STA is likely to support
2-antenna Tx/Rx selection diversity as discussed previously. If this is
the case, it is possible for the AP to achieve 3 dB better performance
than Nth order maximal ratio combining (MRC) at both ends of the link.
[0072]When the STA associates or whenever a significant change in channel
response is detected, the AP sends a special training sequence to help
the STA select the best of its two antennas. The training sequence uses
messages entirely supported by the applicable media access control
protocol, which in the following example is IEEE 802.11x.
[0073]The sequence consists of 2 data units (such as an IEEE 802.11 MSDU
ideally containing data that is actually meant for the STA so as not to
incur a loss in throughput). In step 900, the first communication device
sends the first data unit using the Tx weight vector [1 0 . . . 0].sup.T.
That is, the first communication device sends the first data unit
exclusively by one of its N antennas. In step 910, the second
communication device responds by transmitting a message using one of its'
two antennas. The first device decodes the message from the second
device, and obtains one row of the H matrix (such as the first row
h.sub.r1). In step 920, the first device sends the second MSDU using a
weight vector which is orthogonal to the first row of H (determined in
step 910). When the second device receives the second MSDU, in step 930,
standard selection diversity logic forces it to transmit a response
message in step 930 using the other antenna, allowing the first device to
see the second row of the H matrix, h.sub.r2. Now the first device knows
the entire H matrix. The first device then decides which row of the H
matrix will provide "better" MRC at the second device by computing a norm
of each row, h.sub.r1 and h.sub.r2, of the H matrix and, and selecting
the row that has the greater norm as the transmit weight vector for
further transmissions to that device until another change is detected in
the channel.
[0074]For the frequency sensitive case, the process shown in FIG. 11 is
repeated at each of a plurality of frequency sub-bands that span the
bandwidth of a single carrier baseband signal to be communicated between
the devices, or at each of the sub-carrier frequencies of a multi-carrier
baseband signal to be communication between the devices.
[0075]Turning to FIG. 13 with continued reference to FIG. 1, a method is
described for a collaborative approach for maintaining channel response
information at one communication device for transmission with another
communication device. Initially, in step 1000, one communication device
determines which other communication devices are CBF-capable using a
special CBF-capability request message. For example, this message is sent
by an AP whenever a new STA associates with the AP. Non-CBF-capable
devices will not respond to the message since they will not recognize it
without CBF capability. Once it has confirmed CBF capability, whenever a
CBF-capable device (AP or STA) sends information to the other device, in
step 1010, a CBF training sequence is generated and appended to a data
unit. For example, in the context of IEEE 802.11x, when a directed media
access control (MAC) Protocol Data Unit (MPDU) to another CBF-capable
terminal, it appends a small (2*N orthogonal frequency division
multiplexed (OFDM) symbols, N=the number of antennas of the transmitting
device) CBF training sequence containing channel response information at
the end of the MPDU data segment. For example, the CBF training sequence
may comprise N consecutive 2-symbol long preamble sequences as defined in
802.11a. These N sequences are multiplied by respective ones of N
linearly independent vectors that span the column matrix of the channel
response matrix. Such N linearly independent vectors may be, for example,
the transmitted using the transmit weight vectors [1 0 . . . 0].sup.T, [0
1 0 . . . 0].sup.T, . . . , [0 0 . . . 1].sup.T. These vectors
essentially cause individual sequences to be transmitted exclusively on
separate ones of the antennas, and nevertheless produce a column vector
of the channel response matrix H at the receiving terminal. The CBF
training sequence is appended to the MPDU and transmitted to the
destination communication device in step 1020. The transmitting terminal
uses the optimum transmit weight vector when transmitting all other
portions of the MPDU.
[0076]In step 1030, the destination device receives and decodes the normal
portion of the incoming MPDU using a matched filter derived using the
long preamble at the beginning of the incoming burst to determine the
optimum phase and gain relationships on each receive antenna. Also, in
step 1040, the destination device updates the transmit weight vector to
use when transmitting to the source device (including the ACK to the
incoming MPDU, for example) using the channel response matrix H derived
from the CBF training sequence.
[0077]For example, suppose there are three antennas at the AP and two
antennas at the STA. The CBF training sequence that the AP sends to the
STA is transmitted using the transmit weight vectors [1 0 0].sup.T, [0 1
0].sup.T and [0 0 1].sup.T. The channel response H vector between these
two devices is a 2.times.3 matrix defined as [h.sub.11 h.sub.12].sup.T,
[h.sub.21 h.sub.22].sup.T and [h.sub.31 h.sub.32].sup.T. When these
transmit weight vectors are applied to the symbol s and transmitted, the
result is s[h.sub.11 h.sub.12].sup.T, s[h.sub.21 h.sub.22].sup.T and
s[h.sub.31 h.sub.32].sup.T. Therefore, the column vectors [h.sub.11
h.sub.12].sup.T, [h.sub.21 h.sub.22].sup.T and [h.sub.31 h.sub.32].sup.T
of the H matrix can be computed by dividing each receive vector
([r.sub.11 r.sub.12].sup.T, [r.sub.21 r.sub.22].sup.T and [r.sub.31
r.sub.32].sup.T, the receive output of the antennas at the STA) by s
since the transmit symbol s is known at the STA because the STA will know
the symbols used by the AP for the training sequence.
[0078]Using the method described above, a communication device may store
the optimum transmit weight vectors for each of the other communication
devices it communicates with. For example, an AP maintains a table
mapping the MAC address for each STA to the optimum Tx weight vector for
that STA. CBF-capable STAs may also store a table of such information
when supporting communication in a peer-peer or ad-hoc network. All
transmit weight vectors may be initially set to [1 0 . . . 0].sup.T.
[0079]For a 4-CBF scheme (4 antennas at the AP) using 1500 byte packets at
54 Mbps, the loss in throughput for the above approach is approximately
8%. The loss in throughput could be made smaller using the following
enhancements: one symbol long preambles instead of 2 in the training
sequence; use the channel response training sequence only when it is
needed; and/or transmitting the training sequence during the IEEE 802.11
SIFS interval.
[0080]The training sequence scheme described above can be applied to
generate frequency dependent antenna weights. Steps 1010 through 1030 are
repeated for each of a plurality of frequencies. For example, in the
multi-carrier signal case, steps 1010 through 1040 are repeated K times,
for each sub-carrier frequency. Similarly, for a single carrier
modulation scheme, the training sequence would be applied for each of a
plurality of frequency sub-bands that span the bandwidth of the baseband
signal to be transmitted. In addition, the transmit weights can be
frequency shaped so that the sum of the power across all of the antennas
at a given frequency is constant.
[0081]The antenna processing techniques described herein can be
incorporated into devices in a variety of ways. For example, an RF chip
can be built that supports 2 Tx/Rx antenna ports, and one baseband chip
that supports 2.times. to 4.times.CBF. One RF chip together with one
baseband chip can be used in a network interface card, and two RF chips
together with one baseband chip can be used in an AP for a system that
supports 4-CBF at an AP, and 2-CBF in a STA. This system will perform up
to 12 dB better than current state-of-the-art system.
[0082]From simulations for 2-antenna selection diversity in an indoor
office environment w/50 ns RMS delay spread, 8 dB (4 dB) SNR is required
for 802.11a (802.11b) at the lowest data rate. Including 6 dB of
additional path loss for 802.11a at 5 GHz, a total of 6+8-4=10 dB of
additional received signal power is required for 802.11a. For a path loss
coefficient of 3.3 (indoor environment), 10 dB of additional signal power
corresponds to 1/2 the range.
[0083]In addition, the antenna processing schemes described herein help
reduce the performance degradation caused by interference. It has been
shown through simulations that the interference immunity for a
CBF-enhanced 802.11b network is approximately 2.2 times that of a non-CBF
network. In other words, a CBF enhanced communication between two devices
permits an interference source to be 2.2 times close to a receiving
device without degrading reception performance at that device.
[0084]To again summarize, the antenna processing techniques described
above provide up to a 14 dB (25.times.) SNR improvement over existing
802.11a/b implementations without requiring a change to the communication
protocol or standard. Moreover, compared to current 2-antenna
implementations, these techniques provide nearly three times more range
per AP; 7.3 times more coverage area; four times less infrastructure cost
at a fixed throughput per user; 7-10 times less infrastructure cost when
optimized for coverage; 5 times more throughput per user at a fixed
infrastructure cost; normalized and improved range for dual-mode
802.11a/b networks; and better interference immunity and higher data
rates. As much as 10 times fewer APs are required to support a similar
coverage area when CBF-enhanced APs are used.
[0085]To summarize, a method is provided that accomplishes communication
between a first communication device and a second communication device
using radio frequency (RF) communication techniques, comprising steps of
applying a transmit antenna vector to a baseband signal to be transmitted
from the first communication device to the second communication device,
the transmit antenna weight vector comprising a complex transmit antenna
weight for each of the N plurality of antennas, wherein each complex
transmit antenna weight has a magnitude and a phase whose values may vary
with frequency across a bandwidth of the baseband signal, thereby
generating N transmit signals each of which is weighted across the
bandwidth of the baseband signal; receiving at the N plurality of
antennas of the first communication device a signal that was transmitted
by the second communication device; determining a receive weight vector
comprising a plurality of complex receive antenna weights for the N
plurality of antennas of the first communication device from one or more
signals received by the N plurality of antennas from the second
communication device, wherein each receive antenna weight has a magnitude
and a phase whose values may vary with frequency; and updating the
transmit weight vector for the plurality of antennas of the first
communication device for transmitting signals to the second communication
device by computing a conjugate of the receive weight vector of the first
communication device divided by a norm of the conjugate of the receive
weight vector. This same method may be embodied in the form of
instructions encoded on a medium or in a communication device.
[0086]Also provided is a method that accomplishes communication between a
first communication device and a second communication device, comprising
steps of transmitting a first signal by one of N plurality of antennas of
the first communication device; receiving a first response signal at the
plurality of antennas of the first communication device transmitted from
a first of two antennas of the second communication device; deriving a
first row of a channel response matrix that describes the channel
response between the first communication device and the second
communication device; transmitting a second signal by the plurality of
antennas of the first communication device using a transmit weight vector
that is orthogonal to the first row of the channel response matrix;
receiving a second response signal transmitted by a second of the two
antennas of the second communication device and deriving therefrom a
second row of the channel response matrix; and selecting one of the first
and second rows of the channel response matrix that provides better
signal-to-noise at the second communication device as the transmit weight
vector for further transmission of signals to the second communication
device. This same method may be embodied in the form of instructions
encoded on a medium or in a communication device.
[0087]Still further provided is a method that accomplishes communication
between first and second communication devices comprising steps of
generating a training sequence comprising a sequence of N consecutive
symbols, where N is a number of antennas of the first communication
device, and the N symbols are multiplied by respective ones of N linearly
independent vectors that span columns of a channel response matrix
between the plurality of antennas of the first communication device and a
plurality of antennas of the second communication device, thereby
producing N transmit signals; transmitting the N transmit signals from
the plurality of antennas of the first communication device; receiving
the N transmit signals at each of a plurality of antennas at the second
communication device; at the second communication device, deriving from
signals received by the plurality of antennas the channel response matrix
between the first communication device and the second communication
device; and at the second communication device, generating a transmit
weight vector from the channel response matrix for transmitting a signal
from the second communication device to the first communication device
using the plurality of antennas of the second communication device. This
same method may be embodied in the form of instructions encoded on a
medium or in a communication device.
[0088]The above description is intended by way of example only.
* * * * *