Title of Invention

METHOD AND APPARATUS FOR CHANNEL ESTIMATION AND SPATIAL PROCESSING FOR TDD MIMO SYSTEM

Abstract Channel estimation and spatial processing for a TDD MIMO system. Calibration may be performed to account for differences in the responses of transmit/ receive chains at the access point and user terminal . During normal operation, a MIMO pilot is transmitted on a first link and used to derive an estimate of the first link channel response , which is decomposed to obtain a diagonal matrix of singular values and a first unitary matrix containing both left eigenvectors of the first link and right eigenvectors of a second link . A steered reference is transmitted on the second link using the eigenvectors in the first unitary matrix , and is processed to obtain the diagonal matrix and a second unitary matrix containing both left eigenvectors of the second link and right eigenvectors of the first link . Each unitary matrix may be used to perform spatial processing for data transmission/reception via both links
Full Text

CHANNEL ESTIMATION AND SPATIAL PROCESSING FOR TDD
MIMO SYSTEMS
Claim of Priority under 35 U.S.C §119
[0001] This application claims the benefit of provisional U.S. Application Serial No.
60/421,428, entitled "Channel Estimation and Spatial Processing for TDD MIMO Systems," provisional U.S. Application Serial No. 60/421,462, entitled "Channel Calibration for a Time Division Duplexed Communication System," and provisional U.S. Application Serial No. 60/421,309, entitled "MIMO WLAN System," all of which are filed on October 25, 2002, assigned to the assignee of the present application, and incorporated herein by reference.
BACKGROUND Field
[0002] The present invention relates generally to data communication, and more
specifically to techniques to perform channel estimation and spatial processing in time-division duplexed (TDD) multiple-input multiple-output (MIMO) communication systems. -
Background
[0003] A MIMO system employs multiple (NT) transmit antennas and multiple (NR)
receive antennas for data transmission. A MIMO channel formed by the NT transmit and Nr receive antennas may be decomposed into Ns independent channels, with
Ns subchannel or an eigenmode of the MIMO channel and corresponds to a dimension.
The MIMO system can provide improved performance (e.g., increased transmission
capacity) if the additional dimensionalities created by the multiple transmit and receive
antennas are utilized.
[0004] In order to transmit data on one or more of the Ns eigenmodes of the MIMO
channel, it is necessary to perform spatial processing at the receiver and typically also at the transmitter. The data streams transmitted from the NT transmit antennas interfere

with each other at the receive antennas. The spatial processing attempts to separate out
the data streams at the receiver so that they can be individually recovered.
[0005] To perform spatial processing, an accurate estimate of the channel response
between the transmitter and receiver is typically required. For a TDD system, the downlink (i.e., forward link) and uplink (i.e., reverse link) between an access point and a user terminal both share the same frequency band. In this case, the downlink and uplink channel responses may be assumed to be reciprocal of one another, after calibration has been performed (as described below) to account for differences in the transmit and receive chains at the access point and user terminal. That is, if H represents the channel response matrix from antenna array A to antenna array B, then a reciprocal channel implies that the coupling from array B to array A is given by H ,
where M denotes the transpose of M.
[0006] The channel estimation and spatial processing for a MIMO system typically
consume a large portion of the system resources. There is therefore a need in the art for techniques to efficiently perform channel estimation and spatial processing in a TDD MIMO system.
SUMMARY
[0007] Techniques are provided herein to perform channel estimation and spatial
processing in an efficient manner in a TDD MIMO system. For the TDD MIMO
system, the reciprocal channel characteristics can be exploited to simplify the channel
estimation and spatial processing at both the transmitter and receiver. Initially, an
access point and a user terminal in the system may perform calibration to determine
differences in the responses of their transmit and receive chains and to obtain correction
factors used to account for the differences. Calibration may be performed to ensure that
the "calibrated" channel, with the correction factors applied, is reciprocal. In this way, a
more accurate estimate of a second link may be obtained based on an estimate derived
for a first link.
* [0008] During normal operation, a MIMO pilot is transmitted (e.g., by the access point)
on the first link (e.g., the downlink) and used to derive an estimate of the channel response for the first link. The channel response estimate may then be decomposed (e.g., by the user terminal, using singular value decomposition) to obtain a diagonal

matrix of singular values and a first unitary matrix containing both the left eigenvectors of the first link and the right eigenvectors of the second link (e.g., the uplink). The first unitary matrix may thus be used to perform spatial processing for data transmission received on the first link as well as for data transmission to be sent on the second link.
[0009] A steered reference may be transmitted on the second link using the eigenvectors
in the first unitary matrix. A steered reference (or steered pilot) is a pilot transmitted on specific eigenmodes using the eigenvectors used for data transmission. This steered reference may then be processed (e.g., by the access point) to obtain the diagonal matrix and a second unitary matrix containing both the left eigenvectors of the second link and the right eigenvectors of the first link. The second unitary matrix may thus be used to perform spatial processing for data transmission received on the second link as well as for data transmission to be sent on the first link.
[0010] Various aspects and embodiments of the invention are described in further detail
below.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] The various aspects and features-of the present invention are described below in
conjunction with the following drawings, in which:
[0012] FIG. 1 is a block diagram of an access point and a user terminal in a TDD
MDMO system, in accordance with one embodiment of the invention;
[0013] FIG. 2A shows a block diagram of the transmit and receive chains at the access
point and user terminal, in accordance with one embodiment of the invention;
[0014] FIG.-2B shows application of correction matrices to account for differences in
the transmit/receive chains at the access point and user terminal, in accordance with one
embodiment of the invention;
[0015] FIG. 3 shows the spatial processing for the downlink and uplink for a spatial
multiplexing mode, in accordance with one embodiment of the invention;
[0016] FIG. 4 shows the spatial processing for the downlink and uplink for a beam-
steering mode, in accordance with one embodiment of the invention; and
[0017] FIG. 5 shows a process for performing channel estimation and spatial processing
at the access point and user terminal, in accordance with one embodiment of the
invention.

DETAILED DESCRIPTION
[0018] FIG. 1 is a block diagram of an embodiment of an access point 110 and a user
terminal 150 in a TDD MIMO system 100. Access point 110 is equipped with Nap
transmit/receive antennas for data transmission/reception, and user terminal 150 is equipped with Nut transmit/receive antennas.
[0019] On the downlink, at access point 110, a transmit (TX) data processor 114
receives traffic data (i.e., information bits) from a data source 112 and signaling and other data from a controller 130. TX data processor 114 formats, codes, interleaves, and modulates (i.e., symbol maps) the data to provide modulation symbols. A TX spatial processor 120 receives the modulation symbols from TX data processor 114 and performs spatial processing to provide Nap streams of transmit symbols, one stream for
each antenna. TX spatial processor 120 also multiplexes in pilot symbols as appropriate
(e.g., for calibration and normal operation).
[0020] Each modulator (MOD) 122 (which includes a transmit chain) receives and
processes a respective transmit symbol stream to provide a corresponding downlink modulated signal. The Nap downlink modulated signals from modulators 122a through
122ap are then transmitted from Nttp antennas 124a through 124ap, respectively.
[0021] At user terminal 150, Nut antennas 152a through I52ut receive the transmitted
downlink modulated signals, and each antenna provides a received signal to a respective
demodulator (DEMOD) 154. Each demodulator 154 (which includes a receive chain)
performs processing complementary to that performed at modulator 122 and provides
received symbols. A receive (RX) spatial processor 160 then performs spatial
processing on the received symbols from all demodulators 154a through 154ut to
provide recovered symbols, which are estimates of the modulation symbols sent by the
access point. An RX data processor 170 further processes (e.g., symbol demaps,
deinterleaves, and decodes) the recovered symbols to provide decoded data. The
decoded data may include recovered traffic data, signaling, and so on, which may be
provided to a data sink 172 for storage and/or a controller 180 for further processing.
[0022] The processing for the uplink may be the same or different from the processing
for the downlink. Data and signaling are processed (e.g., coded, interleaved, and modulated) by a TX data processor 188 and further spatially processed by a TX spatial

processor 190, which also multiplexes in pilot symbols as appropriate (e.g., for calibration and normal operation). The pilot and transmit symbols from TX spatial processor 190 are further processed by modulators 154a through 154ut to generate Nut
uplink modulated signals, which are then transmitted via antennas 152a through 152ut to the access point.
[0023] At access point 110, the uplink modulated signals are received by antennas 124a
through 124ap, demodulated by demodulators 122a through 122ap, and processed by an RX spatial processor 140 and an RX data processor 142 in a complementary manner to that performed at the user terminal. The decoded data for the uplink may be provided to a data sink 144 for storage and/or controller 130 for further processing.
[0024] Controllers 130 and 180 control the operation of various processing units at the
access point and user terminal, respectively. Memory units 132 and 182 store data and program codes used by controllers 130 and 180, respectively.
1. Calibration
[0025] For a TDD system, since the downlink and uplink share the same frequency
band, a high degree of correlation normally exists between the downlink and uplink channel responses. Thus, the downlink and uplink channel response matrices may be assumed to be reciprocal (i.e., transpose) of each other. However, the responses of the transmit/receive chains at the access point are typically not equal to the responses of the transmit/receive chains at the user terminal. For improved performance, the differences may be determined and accounted for via calibration.
[0026] FIG. 2A shows a block diagram of the transmit and receive chains at access
point 110 and user terminal 150, in accordance with one embodiment of the invention. For the downlink, at access point 110, symbols (denoted by a "transmit" vector xdn) are
processed by a transmit chain 214 and transmitted from Nap antennas 124 over the
MIMO channel. At user terminal 150, the downlink signals are received by NM
antennas 152 and processed by a receive chain 254 to provide received symbols (denoted by a "receive" vector rdn). For the uplink, at user terminal 150, symbols
(denoted by a transmit vector xup) are processed by a transmit chain 264 and transmitted from Nut antennas 152 over the MIMO channel. At access point 110, the

uplink signals are received by Nap antennas 124 and processed by a receive chain 224
to provide received symbols (denoted by a receive vector rup ).
[0027] For the downlink, the receive vector rdn at the user terminal (in the absence of
noise) may be expressed as:
Edn=RutHTapXdn , Eq(l)
where xdn is the transmit vector with Nap entries for the downlink; rdn is the receive vector with Nut entries; Tap is an /VflpxiVflp diagonal matrix with entries for the complex gains associated
with the transmit chain for the Nop antennas at the access point; Rut is an Nut xNM "diagonal matrix with entries for the complex gains associated
with the receive chain for the Nut antennas at the user terminal; and
H is an Nut XNap channel response matrix for the downlink.
The responses of the transmit/receive chains and the MIMO channel are typically a
function of frequency. For simplicity, a flat-fading channel (i.e., with a flat frequency
response) is assumed for the following derivation.
[0028] For the uplink, the receive vector rup at the access point (in the absence of
noise) may be expressed as:
rup=EapHrTulxup , Eq(2)
where xup is the transmit vector with Nut entries for the uplink; rup is the receive vector with Nap entries; Tut is an Nut XNut diagonal matrix with entries for the complex gains associated
with the transmit chain for the Nut antennas at the user terminal; Rap is an Nap XNap diagonal matrix with entries for the complex gains associated with the receive chain for the Nap antennas at the access point; and
H is an Nnp x Nut channel response matrix for the uplink.
[0029J From equations (1) and (2), the "effective" downlink and uplink channel
responses, Hdn and Hup, which include the responses of the applicable transmit and
receive chains, may be expressed as:


As shown in equation (3), if the responses of the transmit/receive chains at the access point are not equal to the responses of the transmit/receive chains at the user terminal, then the effective downlink and uplink channel responses are not reciprocal of one
another, i.e., RmHTap (RapH7Tut)7.
[0030] Combining the two equations in equation set (3), the following relationship may
be obtained:
Eq(4)
Rearranging equation (4), the following is obtained:
Hup = iutiiuiiidn J-apJiap = ikui Mdniiap
or
Eq(5)
where Rap are diagonal
matrices, Kap and KUI are also diagonal matrices. Equation (5) may also be expressed as:
Eq (6)
[0031] The matrices Kap and Kut may be viewed as including "correction factors" that
can account for differences in the transmit/receive chains at the access point and user terminal. This would then allow the channel response for one link to be expressed by the channel response for the other link, as shown in equation (5).
[0032] Calibration may be performed to determine the matrices Kap and Kut.
Typically, the true channel response H and the transmit/receive chain responses are not known nor can they be exactly or easily ascertained. Instead, the effective downlink and uplink channel responses, Hdn and Hup, may be estimated based on MIMO pilots
sent on the downlink and uplink, respectively. The generation and use of MIMO pilot are described in detail in the aforementioned U.S. Patent Application Serial No. 60/421,309.

[0033] Estimates of the matrices Kap and Kut, which are referred to as correction
matrices, Kap and Kut , may be derived based on the downlink and uplink channel
response estimates, Hdn and Hup, in various manners, including by a matrix-ratio
computation and a minimum mean square error (MMSE) computation. For the matrix-ratio computation, an (Nul xNap) matrix C is first computed as a ratio of the uplink
and downlink channel response estimates, as follows:
Eq(7) where the ratio is taken element-by-element. Each element of C may thus be computed as:

where hnpij and hdni.l are the (/,y)-th (row, column) element of Htup and Hdn, respectively, and c. . is the (/,; )-th element of C.
[0034] A correction vector for the access point, kap, which includes only the Nap
diagonal elements of Kap, may be defined to be equal to the mean of the normalized rows of C. Each row of C, c,, is first normalized by dividing each element of the row with the first element of the row to obtain a corresponding normalized row, c,. Thus, if c(K) = [c, ... ciN ] is the i-th row of C, then the normalized row c may be
expressed as:
A
The correction vector kap(k) is then set equal to the mean of the Nut normalized rows of C and may be expressed as:
Eq (8)
/» Because of the normalization, the first element of kap(k) is unity.
A A
[0035] A correction vector kul(k) for the user terminal, kul(k), which includes only
the Nul diagonal elements of Km(k), may be defined to be equal to the mean of the

inverses of the normalized columns of C. Each column of C, c , is first normalized
by scaling each element in the column with the;-th element of the vector k^ap, which is - -denoted as K9pJJy to obtain a corresponding normalized column, c;. Thus, if
cj(k)=[ci.j....cnm j]t is the j-th column of C, then the normalized column c . may be expressed as:
The correction vector kap is then set equal to the mean of the inverses of the Nap normalized columns of C and may be expressed as:
Eq(9)
where the inversion of the normalized columns, c j(k), is performed element-wise.
The calibration provides the correction vectors, kap and kut, or the corresponding
^ ^ ....
correction matrices Kap and Kut, for the access point and user terminal, respectively.
[0036] The MMSE computation for the correction matrices Kap and Kut is described
in detail in aforementioned U.S. Patent Application Serial No. 60/421,462.
[0037] FIG. 2B illustrates the application of the correction matrices to account for
differences in the transmit/receive chains at the access point and user terminal, in accordance with one embodiment of the invention. On the downlink, the transmit
vector xdn is first multiplied with the matrix Kap by a unit 212. The subsequent
processing by transmit chain 214 and receive chain 254 for the downlink is the same as shown in FIG. 2A. Similarly, on the uplink, the transmit vector xup is first multiplied
with the matrix Kut by a unit 262. Again, the subsequent processing by transmit chain
264 and receive chain 224 for the uplink is the same as shown in FIG. 2A.
[0038] The "calibrated" downlink and uplink channel responses observed by the user
terminal and access point, respectively, may be expressed as:
Hcdn =HdnKap and HCup = HupKut , Eq(10)
where Htcdn and Hcup are estimates of the "true" calibrated channel response expressions in equation (6). From equations (6) and (10), it can be seen

thatHcup =Hcdn. The accuracy of the relationship Hcup = H[dn is dependent on the
accuracy of the estimates Kap and Kut, which in turn is dependent on the quality of the
downlink and uplink channel response estimates, Hdn and Hup. As shown above, once the transmit/receive chains have been calibrated, a calibrated channel response estimate obtained for one link (e.g., Hcdn) may be used as an estimate of the calibrated channel
response for the other link (e.g., Hcup ).
[0039] The calibration for TDD MIMO systems is described in detail in the
aforementioned U.S. Patent Application Serial No. 60/421,309 and U.S. Patent Application Serial No. 60/421,462.
2. Spatial Processine
[00401 For a MIMO system, data may be transmitted on one or more eigenmodes of the
MIMO channel. A spatial multiplexing mode may be defined to cover data transmission on multiple eigenmodes, and a beam-steering mode may be defined to cover data transmission on a single eigenmode. Both operating modes require spatial processing at the transmitter and receiver.
[0041] The channel estimation and spatial processing techniques described herein may
be used for MIMO systems with and without OFDM. OFDM effectively partitions the overall system bandwidth into a number of (NF) orthogonal subbands, which are also referred to as frequency bins or subchannels. With OFDM, each subband is associated with a respective subcarrier upon which data may be modulated. For a MIMO system that utilizes OFDM (i.e., a MIMO-OFDM system), each eigenmode of each subband may be viewed as an independent transmission channel. For clarity, the channel estimation and spatial processing techniques are described below for a TDD MIMO-OFDM system. For this system, each subband of the wireless channel may be assumed to be reciprocal.
[0042] The correlation between the downlink and uplink channel responses may be
exploited to simplify the channel estimation and spatial processing at the access point and user terminal for a TDD system. This simplification is effective after calibration has been performed to account for differences in the transmit/receive chains. The calibrated channel responses may be expressed as a function of frequency, as follows:


where K represents a set of all subbands that may be used for data transmission (i.e., the "data subbands"). The calibration may be performed such that the matrices Kap(k) and
Kul(k) are obtained for each of the data subbands. Alternatively, the calibration may be performed for only a subset of all data subbands, in which case the matrices Kap(k)
and Kut(k) for the "uncalibrated" subbands may be obtained by interpolating the
matrices for the "calibrated" subbands, as described in the aforementioned U.S. Patent
Application Serial No. 60/421,462.
[0043] The channel response matrix U(k) for each subband may be "diagonalized" to
obtain the Ns eigenmodes for that subband. This may be achieved by performing either singular value decomposition on the channel response matrix H(k) or eigenvalue
decomposition on the correlation matrix of H(k), which is R(k) = HH(k)H(k). For
clarity, singular value decomposition is used for the following description.
[0044] The singular value decomposition of the calibrated uplink channel response
matrix, Hcup(k), may be expressed as:

where Uap(A:) is an (Nap x Nap) unitary matrix of left eigenvectors of Hcup(k); Σ(k) is an (NapXNut) diagonal matrix of singular values of Hcup(k); and
Vut(k) is an (NutXNut) unitary matrix of right eigenvectors of Hcup(k).
A unitary matrix is characterized by the property M M = 1, where I is the identity
matrix.
[0045] Correspondingly, the singular value decomposition of the calibrated downlink
channel response matrix, Hcdn(k), may be expressed as:

where the matrices Vut(k) and Uap(k) are unitary matrices of left and right eigenvectors, respectively, of Hcdp(k). As shown in equations (12) and (13) and based

on the above description, the matrices of left and right eigenvectors for one link are the complex conjugate of the matrices of right and left eigenvectors, respectively, for the
other link. The matrices Vut(k), Vut(k), Vut(k), and Vut(k) are different forms of
the matrix Vut(k:), and the matrices Uap(k), Uap(k), Uap(k), and UaHp(k) are also
different forms of the matrix Uap(k). For simplicity, reference to the onatrices Uap(k) and Vul(k) in the following description may also refer to their various other forms. The matrices Uap(k) and VUt(k) are used by the access point and user terminal,
respectively, for spatial processing and are denoted as such by their subscripts. The
eigenvectors are also often referred to as "steering" vectors.
[0046] Singular value decomposition is described in further detail by Gilbert Strang in a
book entitled "Linear Algebra and Its Applications," Second Edition, Academic Press,
1980.
[0047] The user terminal can estimate the calibrated downlink channel response based
on a MIMO pilot sent by the access point. The user terminal may then perform singular
value decomposition for the calibrated downlink channel response estimate Hcdn (k), for
k E K , to obtain the diagonal matrix Σ(k) and the matrix Vut(k) of left eigenvectors
of Hcdn(k) This singular value decomposition may be given as
Hcdn(k) = Vut (k)Σ(k)UaP(k), where the hat (" A ") above each matrix indicates that it is
an estimate of the actual matrix.
[0048] Similarly, the access point can estimate the calibrated uplink channel response
based on a MIMO pilot sent by the user terminal. The access point may then perform singular value decomposition for the calibrated uplink channel response estimate
Hcup(k), for k € K , to obtain the diagonal matrix Σ(k) and the matrix Uap(k) of left eigenvectors of Hcup(k). This singular value decomposition may be given as
[0049] However, because of the reciprocal channel and the calibration, the singular
value decomposition only needs to be performed by either the user terminal or the
access point. If performed by the user terminal, then the matrix Vul(k), for k e K . are

used for spatial processing at the user terminal and the matrix Uap(k) ,forkeK, may be provided to the access point in either a direct form (i.e., by sending entries of the matrices Uap (k)) or an indirect form (e.g., via a steered reference, as described below).
[0050] The singular values in each matrix Σ(k) ,forkEK, may be ordered such that
the first column contains the largest singular value, the second column contains the next largest singular value, and so on (i.e., σi>σl>..-> σNs , where σx is the eigenvalue in
the i-th column of Σ(k) after the ordering). When the singular values for each matrix Σ(k) are ordered, the eigenvectors (or columns) of the associated unitary matrices
VuI(k) and Uap(k) for that subband are also ordered correspondingly. A "wideband"
eigenmode may be defined as the set of same-order eigenmode of all subbands after the ordering (i.e., the 772-th wideband eigenmode includes the m-th eigenmode of all subbands). Each wideband eigenmode is associated with a respective set of eigenvectors for all of the subbands. The principle wideband eigenmode is the one
associated with the largest singular value in'each matrix 2(k) after the ordering.
A. Uplink Spatial Processing
[0051] The spatial processing by the user terminal for an uplink transmission may be
expressed as:
xup,(k) = Kut(K)Vut(k)sup(k) , for k E K , Eq (14)
where xup(k) is the transmit vector for the uplink for the k-th subband; and
svp(k) is a "data" vector with up to Nsnon-zero entries for the modulation
symbols to be transmitted on the Ns eigenmodes of the k-th subband.
[0052] The received uplink transmission at the access point may be expressed as:


where rup(k) is the received vector for the uplink for the k-th subband; and
nup(k) is additive white Gaussian noise (AWGN) for the k-th subband.
Equation (15) uses the following relationships.

[0053] A weighted matched filter matrix Map(k) for the uplink transmission from the
user terminal may be expressed as:

The spatial processing (or matched filtering) at the access point for the received uplink transmission may be expressed as:

where §up(k) is an estimate of the data vector sup(k) transmitted by the user terminal on the uplink, and nup(k) is the post-processed noise.
B. Downlink Spatial Processing
[0054] The spatial processing by the access point for a downlink transmission may be
expressed as:

where xdn(k) is the transmit vector and sdft(k) is the data vector for the downlink.
[0055] The received downlink transmission at the user terminal may be expressed as:


[0056] A weighted matched filter matrix Mul(k) for the downlink transmission from
the access point may be expressed as:

The spatial processing (or matched filtering) at the user terminal for the received downlink transmission may be expressed as:

[0057] Table 1 summarizes the spatial processing at the access point and user terminal
for data transmission and reception.
Table 1

[00581 In the above description and as shown in Table 1, the correction matrices
Kap(k) anc Kut(k) are aPPlied on the transmit side at the access point and user
terminal, respectively. The correction matrices Kap(k) and Kut(k) may also be combined with other diagonal matrices (e.g., such as weight matrices Wdn(k) and Wup(k) used to achieve channel inversion). However, the correction matrices may also

be applied on the receive side, instead of the transmit side, and this is within the scope
of the invention.
[0059] FIG. 3 is a block diagram of the spatial processing for the downlink and uplink
for the spatial multiplexing mode, in accordance with one embodiment of the invention.
[0060] For the downlink, within a TX spatial processor 120x at access point HOx, the
data vector sdn (k), for k e K , is first multiplied with the matrix Uap(k) by a unit 310
and then further multiplied with the correction matrix Kap(k) by a unit 312 to obtain
the transmit vector xdnik). The vector xdn(k), for k E K , is then processed by a
transmit chain 314 within modulator 122x and transmitted over the MIMO channel to
user terminal 150x. Unit 310 performs the spatial processing for the downlink data
transmission.
[0061] At user terminal 150x, the downlink signals are processed by a receive chain 354
within demodulator 154x to obtain the receive vector rdn(k), for k e K . Within an RX
spatial processor 160x, the receive vector rdn(k), for k e K , is first multiplied with the
* r * -t
matrix Vu((fc) by a unit 356 and further scaled by the inverse diagonal matrix £ (k)
by a unit 358 to obtain the vector sdn (k), which is an estimate of the data vector sdn (k).
Units 356 and 358 perform the spatial processing for the downlink matched filtering.
[0062] For the uplink, within a TX spatial processor 190x at user terminal 150x, the
data vector sup(k), for k e K , is first multiplied with the matrix Vul(k) by a unit 360
and then further multiplied with the correction matrix Kul(k) by a unit 362 to obtain
the transmit vector xup(k). The vector Xup(k), for Jt€ K , is then processed by a
transmit chain 364 within modulator 154x and transmitted over the MIMO channel to
access point 1 lOx. Unit 360 performs the spatial processing for the uplink data
transmission.
[0063] At access point HOx, the uplink signals are processed by a receive chain 324
within demodulator 122x to obtain the receive vector rup(k), for k e K . Within an RX
spatial processor 140x, the receive vector rup(k), for k e K , is first multiplied with the
* H * -I
matrix Uap(k) by a unit 326 and further scaled by the inverse diagonal matrix £ {k)

by a unit 328 to obtain the vector sup(k), which is an estimate of the data vector sup(k). Units 326 and 328 perform the spatial processing for the uplink matched filtering.
3. Beam-Steering
[0064] For certain channel conditions, it is better to transmit data on only one wideband
eigenmode - typically the best or principal wideband eigenmode. This may be the case if the received signal-to-noise ratios (SNRs) for all other wideband eigenmodes are sufficiently poor so that improved performance is achieved by using all of the available transmit power on the principal wideband eigenmode.
[0065] Data transmission on one wideband eigenmode may be achieved using either
beam-forming or beam-steering. For beam-forming, the modulation symbols are spatially processed with the eigenvectors yuI](k) or uapl(k), for ke K , for the
principal wideband eigenmode (i.e., the first column of Vut(k) or Uap(k), after the
ordering). For beam-steering, the modulation symbols are spatially processed with a set of "normalized" (or "saturated") eigenvectors vuI(k) or Uap(K), for k Ee K , for the
principal wideband eigenmode. For clarity, beam-steering is described below for the
uplink.
[0066] For the uplink, the elements of each eigenvector vul,(Jfc), for ke K , for the
principal wideband eigenmode may have different magnitudes. Thus, the preconditioned symbols for each subband, which are obtained by multiplying the modulation symbol for subband k with the elements of the eigenvector ywl(k) for
subband ky may then have different magnitudes. Consequently, the per-antenna transmit
vectors, each of which includes the preconditioned symbols for all data subbands for a
given transmit antenna, may have different magnitudes. If the transmit power for each ,
transmit antenna is limited (e.g.. because of limitations of power amplifiers), then beam-
forming may not fully use the total power available for each antenna.
[0067] Beam-steering uses onl> the phase information from the eigenvectors yu(1(k),
for k 6 K , for the principal wideband eigenmode and normalizes each eigenvector such that all elements in the eigenvector have equal magnitudes. The normalized eigenvector Vut (k) for k- the subband may be expressed as:


where A is a constant (e.g., A = 1); and
θt{k) is the phase for the k-th subband of the i-th transmit antenna, which is
given as:
Eq (23)
As shown in equation (23), the phase of each element in the vector Vm(k) is obtained from the corresponding element of the eigenvector Vut, (k) (i.e., θt(k) is obtained from

A. Uplink Beam-Steering
[0068] The spatial processing by the user terminal for beam-steering on the uplink may
be expressed as:

where sup(k) is the modulation symbol to be transmitted on the k-th subband; and
x up (k) is the transmit vector for the k-th subband for beam-steering.
As shown in equation (22), the Nut elements of the normalized steering vector Vu( (k)
for each subband have equal magnitude but possibly different phases. The beam-steering thus generates one transmit vector xup(k) for each subband, with the Nut
elements of xup(k) having the same magnitude but possibly different phases.
[0069] The received uplink transmission at the access point for beam-steering may be
expressed as:

where rup(k) is the received vector for the uplink for the k-th subband for beam-steering.

[0070] A matched filter row vector map(k) for the uplink transmission using beam-

The matched filter vector mapk) may be obtained as described below. The spatial
processing (or matched filtering) at the access point for the received uplink transmission with beam-steering may be expressed as:

where (i.e., λup(k) is the inner product of
Map(k) and its conjugate transpose),
Sup(k) is estimate of the modulation symbol sup(k) transmitted by the user
terminal on the uplink, and ~Nup (k) is the post-processed noise.
B. Downlink Beam-Steering
[0071] The spatial processing by the access point for beam-steering on the downlink
may be expressed aS:
Eq (28)
where uap(k) is the normalized eigenvector for the k-th subband, which is generated
based on the eigenvector uapA(k), for the principal wideband eigenmode, as described
above.
[0072] A matched filter row vector rnui(k) for the downlink transmission using beam-
steering may be expressed as:
Eq (29)
The spatial processing (or matched filtering) at the user terminal for the received downlink transmission may be expressed as:


where λdn(k) = (Hcdn(k)uap(k))H (Hcdn(k)U)) (i.e., λdn(k) is the inner product of
Mut (k) anc its conjugate transpose).
[0073] Beam-steering may be viewed as a special case of spatial processing in which
only one eigenvector for one eigenmode is used for data transmission and this
eigenvector is normalized to have equal magnitudes.
[0074] FIG- 4 is a block diagram of the spatial processing for the downlink and uplink
for the beam-steering mode, in accordance with one embodiment of the invention.
[0075] For the downlink, within a TX spatial processor 120y at access point 11Oy, the
modulation symbol sdn(k), for kEK, is first multiplied with the normalized eigenvector Uap(k) by a unit 410 and then further multiplied with the correction matrix
Kap(k) by a unit 412 to obtain the transmit vector xdn(k). The vector Xdn(k), for
k E K, is then processed by a transmit chain 414 within modulator 122y and
transmitted over the MIMO channel to user terminal 150y. Unit 410 performs spatial
processing for the downlink data transmission for the beam-steering mode.
[0076] At user terminal 150y, the downlink signals are processed by a receive chain 454
within demodulator 154y to obtain the receive vector Rdn (k), for k E K. Within an RX spatial processor 160y, a unit 456 performs an inner product of the receive vector Rdn(k)yforkEK, with the matched filter vector mul(k). The inner product result is then scaled by λ-dn(k) by a unit 458 to obtain the symbol sdn(k), which is an estimate of the modulation symbol sdn (k). Units 456 and 458 perform spatial processing for the
downlink matched filtering for the beam-steering mode.
[0077] For the uplink, within a TX spatial processor 190y at user terminal 150y, the
modulation symbol sup(k), for kEK, is first multiplied with the normalized
eigenvector vul (k) by a unit 460 and then further multiplied with the correction matrix
Kut(k) by a unit 462 to obtain the transmit vector x (k). The vector xup(k), for k e K, is then processed by a transmit chain 464 within modulator 154y and

transmitted over the MIMO channel to access point HOy. Unit 460 performs spatial
processing for the uplink data transmission for the beam-steering mode.
[0078] At,access point HOy, the uplink signals are processed by a receive chain 424
within demodulator 124y to obtain the receive vector Fup (k), for k e K . Within an RX
spatial processor 140y, a unit 426 performs an inner product of the receive vector rup (k), for k e K , with the matched filter vector map(k). The inner product result is
then is scaled by Xup{k) by a unit 428 to obtain the symbol sup(k), which is an estimate of the modulation symbol sup (k). Units 426 and 428 perform spatial processing for the uplink matched filtering for the beam-steering mode.
4. Steered Reference
[0079] As shown in equation (15), at the access point, the received uplink vector
rup(k)' f°r keK, in the absence of noise is equal to the data vector sup(k)
transformed by Uap(k)Σ(k), which is the matrix Vap(k) of left eigenvectors of Hcup(k)
scaled by the diagonal matrix Σ(k) of singular values. As shown in equations (17) and
(18), because of the reciprocal channel and the calibration, the matrix Uap(k) and its
transpose are used for spatial processing of the downlink transmission and spatial
processing (matched filtering) of the received uplink transmission, respectively.
[0080] A steered reference (or steered pilot) may be transmitted by the user terminal
A A
and used by the access point to obtain estimates of both Uap(k) and Σ(k), for k E K ,
without having to estimate the MIMO channel or perform the singular value decomposition. Similarly, a steered reference may be transmitted by the access point
A A
and used by the user terminal to obtain estimates of both Vul (k) and Σ(k).
[0081] A steered reference comprises a specific OFDM symbol (which is referred to as
a pilot or "P" OFDM symbol) that is transmitted from all of the Nul antennas at the user
terminal (for the uplink) or the N'np antennas at the access point (for the downlink). The
P OFDM symbol is transmitted on only one wideband eigenmode by performing spatial processing with the set of eigenvectors for that wideband eigenmode.

A. Uplink Steered Reference
[0082] An uplink steered reference transmitted by the user terminal may be expressed
as:

where x (k) is the transmit vector for the k-th subband of the m-th wideband
eigenmode; Vui,m(k) is the eigenvector for the k-th subband of the m-th wideband
eigenmode; and p(k) is a pilot modulation symbol to be transmitted on the k-th subband.
The eigenvector Vwm(k) is the m-th column of the matrix Vut(k), where

[0083] The received uplink steered reference at the access point may be expressed as:

where r m (it) is the received vector for the uplink steered reference for the k-th
subband of the m-th wideband eigenmode; and crm(k) is the singular value for the k-th subband of the m-th wideband
eigenmode.
[0084] Techniques to estimate the channel response based on the steered reference are
described in further detail below.
B. Downlink Steered Reference
[0085] A downlink steered reference transmitted by the access point may be expressed
as:


where xdnm(k) is the transmit vector for the k-th subband of the m-th wideband
eigenmode; and
* U[pm(k) is the eigenvector for the k-th subband of the m-th wideband
eigenmode. The steering vector uapffi(k) is the m-th column of the matrix Uap(k), where

[0086] The downlink steered reference may be used by the user terminal for various
purposes. For example, the downlink steered reference allows the user terminal to determine what kind of estimate the access point has for the MIMO channel (since the access point has an estimate of an estimate of the channel). The downlink steered reference may also be used by the user terminal to estimate the received SNR of downlink transmission.
C. Steered Reference For Beam-Steerirrg
[0087] For the beam-steering mode, the spatial processing on the transmit side is
performed using a set of normalized eigenvectors for the principal wideband eigenmode. The overall transfer function with a normalized eigenvector is different from the overall transfer function with an unnormalized eigenvector (i.e., Hcup(k)Vur1(k)≠HcuP(k)Vut(k)). A steered reference generated using the set of
normalized eigenvectors for all subbands may then be sent by the transmitter and used
by the receiver to derive the matched filter vectors for these subbands for the beam-
steering mode.
[0088] For the uplink, the steered reference for the beam-steering mode may be
expressed as:

At the access point, the receive uplink steered reference for the beam-steering mode may be expressed as:


[0089] To obtain the matched filter row vector map(k) for the uplink transmission with
beam-steering, the received vector rup>sr(k) for the steered reference is first multiplied
with p'k). The result is then integrated over multiple received steered reference
symbols to form an estimate of Hcup(k)Vul(k). The vector map(k) is then the
conjugate transpose of this estimate.
[0090] While operating in the beam-steering mode, the user terminal may transmit
multiple symbols of steered reference, for example, one or more symbols using the normalized eigenvector V_ul(k)» one or more symbols using the eigenvector Vul i(k) for
the principal eigenmode, and possibly one or more symbols using the eigenvectors for the other eigenmodes. The steered reference symbols generated with yut(k) may be
used by the access point to derive the matched filter vector m (k). The steered reference symbols generated with vutI(k) may be used to obtain u ,(k), which may then be used to derive the normalized eigenvector uap (k) used for beam-steering on the downlink. The steered reference symbols generated with the..eigenvectors Vul2(k) through vul „ (k) for the other eigenmodes may be used by the access point to obtain uap2(k) through uapNs(k) and the singular values for these other eigenmodes. This
information may then be used by the access point to determine whether to use the
spatial multiplexing mode or the beam-steering mode for data transmission.
[0091] For the downlink, the user terminal may derive the matched filter vector mut (k)
for the beam-steering mode based on the calibrated downlink channel response estimate Hcdn(k). In particular, the user terminal has uapI(k) from the singular value
decomposition of Hcdn (k) and can derive the normalized eigenvector uap(k). The user
terminal can then multiply uup(k) with Hcdn(k) to obtain Hcdn(k)uap(k), and may then
derive mut (k) based on Hcdn(k)uap(k). Alternatively, a steered reference may be sent
» by the access point using the normalized eigenvector uap(k), and this steered reference
may be processed by the user terminal in the manner described above to obtain mul (k).

D. Channel Estimation Based on Steered Reference
[0092] As shown in equation (32), at the access point, the received uplink steered
reference (in the absence of noise) is approximatelyUpm(k)σm(k)p(k). The access
point can thus obtain an estimate of the uplink channel response based on the steered
reference sent by the user terminal. Various estimation techniques may be used to
obtain the channel response estimate.
[0093] In one embodiment, to obtain an estimate of uapm(k), the received vector
r (it) for the steered reference for the m-th wideband eigenmode is first multiplied
with the complex conjugate of the pilot modulation symbol, p'(k), used for the steered reference. The result is then integrated over multiple received steered reference symbols for each wideband eigenmode to obtain an estimate of uap.m (k)σm{k), which is
a scaled left eigenvector of HCttp(k) for the m-th wideband eigenmode. Each of the Nap entries of u (k) is obtained based on a corresponding one of the Nap entries for r (it), where the Nnp entries of rupm(k) are the received symbols obtained from the Nap antennas at the access point. Since eigenvectors have unit power, the singular
value σm{k) may be estimated based on the received power of the steered reference,
which can be measured for each subband of each wideband eigenmode.
[0094] In another embodiment, a minimum mean square error (MMSE) technique is
used to obtain an estimate of uap>IB(k) based on the received vector rup,m (k) for the
steered reference. Since the pilot modulation symbols p(k) are known, the access point
can derive the estimate of uap,m (k) such that the mean square error between the received
pilot symbols (obtained after performing the matched filtering on the received vector rup.m. (k)) and the transmitted pilot symbols is minimized. The use of the MMSE
technique for spatial processing at the receiver is described in detail in commonly
assigned U.S. Patent Application Serial No. 09/993,087, entitled "Multiple-Access
Multiple-Input Multiple-Output (MIMO) Communication System," filed November 6,
2001.
[0095] The steered reference is sent for one wideband eigenmode in any given symbol
period, and may in turn be used to obtain an estimate of one eigenvector for each

subband of that wideband eigenmode. Thus, the receiver is able to obtain an estimate of one eigenvector in a unitary matrix for any given symbol period. Since estimates of multiple eigenvectors for the unitary matrix are obtained over different symbol periods, and due to noise and other sources of degradation in the transmission path, the estimated eigenvectors for the unitary matrix are not likely be orthogonal. If the estimated eigenvectors are thereafter used for spatial processing of data transmission on the other link, then any errors in orthogonality in these estimated eigenvectors would result in cross-talk among the eigenmodes, which may degrade performance.
[0096] In an embodiment, the estimated eigenvectors for each unitary matrix are forced
to be orthogonal to each other. The orthogonalization of the eigenvectors may be achieved using the Gram-Schmidt technique, which is described in detail in the aforementioned reference from Gilbert Strang, or some other technique.
[0097] Other techniques to estimate the channel response based on the steered reference
may also be used, and this is within the scope of the invention.
[0098] The access point can thus estimate both Uap(k) and Σ(k) based on the steered
reference sent by the user terminal, without having to estimate the uplink channel
response or perform singular value decomposition on Hcup(k). Since only Nu
wideband eigenmodes have any power, the matrix Uap(k) of left eigenvectors of
Hcup(k) is effectively (NapxNul), and the matrix Σ(k) may be considered to be
(NmxNm).
[0099] The processing at the user terminal to estimate the matrices Vul(&) and Z(Jfc),
for ke K, based on the downlink steered reference may be performed similar to that described above for the uplink steered reference.
5. Channel Estimation and Spatial Processing
[00100] FIG- 5 is a flow diagram of a specific embodiment of a process 500 for
performing channel estimation and spatial processing at the access point and user terminal, in accordance with one embodiment of the invention. Process 500 includes two parts - calibration (block 510) and normal operation (block 520).
[00101] Initially, the access point and user terminal perform calibration to determine the
differences in the responses of their transmit and receive chains and to obtain correction

matrices Kap(k) and Kul(k), for ke K (at block 512). The calibration only needs to
be performed once (e.g., at the start of a communication session, or the very first time
the user terminal is powered up). The correction matrices Kap(k) and Kut(k) are
thereafter used by the access point and user terminal, respectively, on the transmit side as described above.
[00102] During normal operation, the access point transmits a MIMO pilot on the
calibrated downlink channel (at block 522). The user terminal receives and processes the MIMO pilot, estimates the calibrated downlink channel response based on the received MIMO pilot, and maintains an estimate of the calibrated downlink channel response (at block 524). It can be shown that performance is better (i.e., less degradation) when the channel response estimate is accurate. An accurate channel response estimate may be obtained by averaging the estimates derived from multiple received MIMO pilot transmissions.
[00103] The user terminal then decomposes the calibrated downlink channel response
estimate; Hcdn(k), for keK, to obtain the diagonal matrix Σ(k) and the unitary matrix Vut(;t) (at block 526). The matrix Vul(£) contains the left eigenvectors of
Hcd»(*) and Yut(*) contains the right eigenvectors of Hcup(&). The matrix VttI(*)
can thus be used by the user terminal to perform spatial processing for data transmission
received on the downlink as well as for data transmission to be sent on the uplink.
[00104] The user terminal then transmits a steered reference on the uplink to the access
point using the eigenvectors in the matrix Vol(k), as shown in equation (31) (at block
530). The access point receives and processes the uplink steered reference to obtain the
diagonal matrix Σ(k) and the unitary matrix Uap(k), fox kE K (at block 532). The matrix Uap(k) contains the left eigenvectors of Hcup(k) and Uap(k) contains the right
eigenvectors of Hcdn(k). The matrix Ua (k) can thus be used by the access point to
perform spatial processing for data transmission received on the uplink as well as for data transmission to be sent on the downlink.

[00105] The matrix Uap(k), for k e K , is obtained based on an estimate of the uplink
steered reference, which in turn is generated with the eigenvector that is obtained based
on an estimate of the calibrated downlink channel response. Thus, the matrix Uap(k) is effectively an estimate of an estimate. The access point may average the uplink steered reference transmissions to obtain more accurate estimate of the actual matrix Uap (k).
[00106] Once the user terminal and access point obtain the matrices Vul (k) and Uap(k),
respectively, data transmission can commence on the downlink and/or uplink. For downlink data transmission, the access point performs spatial processing on symbols
with the matrix Uap(k)of right eigenvectors of Hcdn(k) and transmits to the user terminal (at block 540). The user terminal would then receive and spatially process the
* T
downlink data transmission with the matrix Vut(k), which is the conjugate transpose of
the matrix Vul(k) of left eigenvectors of Hcdn(k) (at block 542). For uplink data transmission, the user terminal performs spatial processing on symbols with the matrix Vut(k) of right eigenvectors of Hcup(k), and transmits to the access point (at block 550). The access point would then receive and spatially process the uplink data
- H
transmission with the matrix IJ (k), which is the conjugate transpose of the matrix
Uap(k) of left eigenvectors of H(k) (at block 552).
[00107] The downlink and/or uplink data transmission can continue until terminated by
either the access point or user terminal. While the user terminal is idle (i.e., with no
data to transmit or receive), the MIMO pilot and/or steered reference may still be sent to
allow the access point and user terminal to maintain up-to-date estimates of the
downlink and uplink channel responses, respectively. This would then allow data
transmission to commence quickly, if and when resumed.
[00108] For clarity, the channel estimation and spatial processing techniques have been
* described for a specific embodiment in which the user terminal estimates the calibrated
downlink channel response based on a downlink MIMO pilot and performs the singular
value decomposition. The channel estimation and singular value decomposition may
also be performed by the access point, and this is within the scope of the invention. In

general, because of the reciprocal channel for a TDD system, the channel estimation needs only be performed at one end of the link.
[00109] The techniques described herein may be used with or without calibration.
Calibration may be performed to improve the channel estimates, which may then improve system performance.
[00110] The techniques described herein may also be used in conjunction with other
spatial processing techniques, such as water-filling for transmit power allocation among the wideband eigenmodes and channel inversion for transmit power allocation among the subbands of each wideband eigenmode. Channel inversion and water-filling are described in the aforementioned U.S. Patent Application Serial No. 60/421,309.
[00111] The channel estimation and spatial processing techniques described herein may
be implemented by various means. For example, these techniques may be implemented in hardware, software, or a combination thereof. For a hardware implementation, the elements used to implement the techniques described herein may be implemented within one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described herein, or a combination thereof.
[00112] For a software implementation, the channel estimation and spatial processing
techniques may be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein. The software codes may be stored in a memory unit (e.g., memory units 132 and 182 in FIG. 1) and executed by a processor (e.g., controllers 130 and 180). The memory unit may be implemented within the processor or external to the processor, in which case it can be communicatively coupled to the processor via various means as is known in the art.
[00113] Headings are included herein for reference and to aid in locating certain
sections. These headings are not intended to limit the scope of the concepts described therein under, and these concepts may have applicability in other sections throughout the entire specification.
[00114] The previous description of the disclosed embodiments is provided to enable any
person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic

principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
WHAT IS CLAIMED IS:




CLAIMS
1. A method of performing spatial processing in a wireless time division
duplexed (TDD) multiple-input multiple-output (MIMO) communication system,
comprising:
processing a first transmission received via a first link to obtain at least one eigenvector usable for spatial processing for both data transmission received via the first link and data transmission sent via a second link; and
performing spatial processing for a second transmission with the at least one eigenvector prior to transmission over the second link.
2. The method of claim 1, further comprising:
performing spatial processing on a third transmission received via the first link with the at least one eigenvector to recover data symbols for the third transmission.
3. The method of claim 1, wherein the first transmission is a steered pilot received on at least one eigenmode of a MIMO channel for the first link.
4. The method of claim 1, wherein the first transmission is a MIMO pilot comprised of a plurality of pilot transmissions sent from a plurality of transmit antennas, and wherein the pilot transmission from each transmit antenna is identifiable by a receiver of the MIMO pilot.
5. The method of claim 4, wherein the processing a first transmission includes
obtaining a channel response estimate for the first link based on the MIMO pilot, and
decomposing the channel response estimate to obtain a plurality of eigenvectors usable for spatial processing for the first and second links.
6. The method of claim 5, wherein the channel response estimate for the
first link is decomposed using singular value decomposition.

7. The method of claim 4, further comprising:
performing spatial processing on pilot symbols with the at least one eigenvector to generate a steered pilot for transmission on at least one eigenmode of a MIMO channel for the second link.
8. The method of claim 1, wherein the second transmission is spatially processed with one eigenvector for transmission on one eigenmode of a MIMO channel for the second link.
9. The method of claim 1, wherein the second transmission is spatially processed with a normalized eigenvector for transmission on one eigenmode of a MIMO channel for the second link, the normalized eigenvector including a plurality of elements having same magnitude.
10. The method of claim 1, wherein the first transmission is a steered pilot generated with a normalized eigenvector for one eigenmode of a MIMO channel for the first link, the normalized eigenvector including a plurality of elements having same magnitude, and wherein one eigenvector usable for spatial processing for the first and second links is obtained.
11. The method of claim 1, further comprising:
calibrating the first and second links such that a channel response estimate for the first link is reciprocal of a channel response estimate for the second link.
12. The method of claim 11, wherein the calibrating includes
obtaining correction factors for the first link based on the channel response estimates for the first and second links, and
obtaining correction factors for the second link based on the channel response estimates for the first and second links.
13. The method of claim 1, wherein the TDD MIMO communication system
utilizes orthogonal frequency division multiplexing (OFDM), and wherein the

processing for the First transmission and the spatial processing for the second transmission are performed for each of a plurality of subbands.
14. An apparatus in a wireless time division duplexed (TDD) multiple-input
multiple-output (M1MO) communication system, comprising:
means for processing a first transmission received via a first link to obtain at least one eigenvector usable for spatial processing for both data transmission received via the first link and data transmission sent via a second link; and
means for performing spatial processing for a second transmission with the at least one eigenvector prior to transmission over the second link.
15. The apparatus of claim 14, further comprising:
means for performing spatial processing on a third transmission received via the first link with the at least one eigenvector to recover data symbols for the third transmission.
16. The apparatus of claim 14, wherein the first transmission is a steered pilot received on at least one eigenmode of a MIMO channel for the first link.
17. The apparatus of claim 14, wherein the first transmission is a MIMO pilot comprised of a plurality of pilot transmissions sent from a plurality of transmit antennas, and wherein the pilot transmission from each transmit antenna is identifiable by a receiver of the MIMO pilot.
18. The apparatus of claim 17, further comprising:
means for obtaining a channel response estimate for the first link based on the MIMO pilot; and
means for decomposing the channel response estimate to obtain a plurality of eigenvectors usable for spatial processing for the first and second links.
19. An apparatus in a wireless time division duplexed (TDD) multiple-input
multiple-output (MIMO) communication system, comprising:

a controller operative to process a first transmission received via a first link to obtain at least one eigenvector usable for spatial processing for both data transmission received via the first link and data transmission sent via a second link; and
a transmit spatial processor operative to perform spatial processing for a second transmission with the at least one eigenvector prior to transmission over the second link.
20. The apparatus of claim 19, further comprising:
a receive spatial processor operative to perform spatial processing on a third transmission received via the first link with the at least one eigenvector to recover data symbols for the third transmission.
21. The apparatus of claim 19, wherein the first transmission is a steered pilot received on at least one eigenmode of a MIMO channel for the first link.
22. The apparatus, of claim 19, wherein the first transmission is a MIMO pilot comprised of a plurality of pilot transmissions sent from a plurality of transmit antennas, and wherein the pilot transmission from each transmit antenna is identifiable by a receiver of the MIMO pilot.
23. The apparatus of claim 22, wherein the controller is further operative to obtain a channel response estimate for the first link based on the MEMO pilot and to decompose the channel response estimate to obtain a plurality of eigenvectors usable for spatial processing for the first and second links.
24. A method of performing spatial processing in a wireless time division duplexed (TDD) multiple-input multiple-output (MIMO) communication system, comprising:
processing a MIMO pilot received via a first link to obtain a plurality of eigenvectors usable "for spatial processing for both data transmission received via the first link and data transmission sent via a second link, wherein the MIMO pilot comprises a plurality of pilot transmissions sent from a plurality of transmit antennas,

and wherein the pilot transmission from each transmit antenna is identifiable by a receiver of the MIMO pilot;
performing spatial processing on a first data transmission received via the first link with the plurality of eigenvectors to recover data symbols for the first data transmission; and
performing spatial processing for a second data transmission with the plurality of eigenvectors prior to transmission over the second link.
25. The method of claim 24, further comprising:
performing spatial processing on pilot symbols with at least one of the eigenvectors to generate a steered pilot for transmission on at least one eigenmode of a MIMO channel for the second link.
26. The method of claim 24, further comprising:
performing calibration to obtain correction factors; and
scaling the second data transmission with the correction factors prior to transmission over the second link.
27. The method of claim 24, wherein the TDD MIMO communication system utilizes orthogonal frequency division multiplexing (OFDM), and wherein the spatial processing is performed for each of a plurality of subbands.
28. An apparatus in a wireless time division duplexed (TDD) multiple-input multiple-output (MIMO) communication system, comprising:
means for processing a MEMO pilot received via a first link to obtain a plurality of eigenvectors usable for spatial processing for both data transmission received via the first link and data transmission sent via a second link, wherein the MIMO pilot comprises a plurality of pilot transmissions sent from a plurality of transmit antennas, and wherein the pilot transmission from each transmit antenna is identifiable by a receiver of the MIMO pilot;

means for performing spatial processing on a first data transmission received via the first link with the plurality of eigenvectors to recover data symbols for the first data transmission; and
means for performing spatial processing for a second data transmission with the plurality of eigenvectors prior to transmission over the second link.
29. The apparatus of claim 28, further comprising:
means for performing spatial processing on pilot symbols with at least one of the eigenvectors to generate a steered pilot for transmission on at least one eigenmode of a MIMO channel for the second link.
30. The apparatus of claim 28, further comprising:
means for performing calibration to obtain correction factors; and means for scaling the second data transmission with the correction factors prior to transmission over the second link.
31. An apparatus in a wireless time division duplexed (TDD) multiple-input
multiple-output (MIMO) communication system, comprising:
a controller operative to process a MIMO pilot received via a first link to obtain a plurality of eigenvectors usable for spatial processing for both data transmission received via the first link and data transmission sent via a second link, wherein the MIMO pilot comprises a plurality of pilot transmissions sent from a plurality of transmit antennas, and wherein the pilot transmission from each transmit antenna is identifiable by a receiver of the MIMO pilot;
a receive spatial processing operative to perform spatial processing on a first data transmission received via the first link with the plurality of eigenvectors to recover data symbols for the first data transmission; and
a transmit spatial processor operative to perform spatial processing for a second data transmission with the plurality of eigenvectors prior to transmission over the second link

32. The apparatus of claim 31, wherein the transmit spatial processor is further operative to perform spatial processing on pilot symbols with at .least one of the eigenvectors to generate a steered pilot for transmission on at least one eigenmode of a MIMO channel for the second link.
33. The apparatus of claim 31, wherein the controller is further operative to perform calibration to obtain correction factors, and wherein the transmit spatial processor is further operative to scale the second data transmission with the correction factors prior to transmission over the second link.
34. A method of performing spatial processing in a wireless time division duplexed (TDD) multiple-input multiple-output (MIMO) communication system, comprising:
processing a steered pilot received via at least one eigenmode of a MIMO channel for a first link to obtain at least one eigenvector usable for spatial processing for both data transmission received via the first link and data transmission sent via a second link;
performing spatial processing on a first data transmission received via the first link with the at least one eigenvector; and
performing spatial processing for a second data transmission with the at least one eigenvector prior to transmission over the second link.
35. The method of claim 34, further comprising:
generating a MIMO pilot for transmission over the second link, wherein the MIMO pilot comprises a plurality of pilot transmissions sent from a plurality of transmit antennas, and wherein the pilot transmission from each transmit antenna is identifiable by a receiver of the MIMO pilot.
36. An apparatus in a wireless time division duplexed (TDD) multiple-input
multiple-output (MIMO) communication system, comprising:
means for processing a steered pilot received via at least one eigenmode of a MIMO channel for a first link to obtain at least one eigenvector usable for spatial

processing for both data transmission received via the first link and data transmission sent via a second link;
means for performing spatial processing on a first data transmission received via the first link with the at least one eigenvector; and
means for performing spatial processing for a second data transmission with the at least one eigenvector prior to transmission over the second link.
37. The apparatus of claim 36, further comprising:
means for generating a MIMO pilot for transmission over the second link, wherein the MEMO pilot comprises a plurality of pilot transmissions sent from a plurality of transmit antennas, and wherein the pilot transmission from each transmit antenna is identifiable by a receiver of the MIMO pilot.
38. An apparatus in a wireless time division duplexed (TDD) multiple-input
multiple-output (MIMO) communication system, comprising:
a controller operative to process a steered pilot received via at least one eigenmode of a MIMO channel for a first link to obtain at least one eigenvector usable for spatial processing for both data transmission received via the first link and data transmission sent via a second link;
a receive spatial processor operative to perform spatial processing on a first data transmission received via the first link with the at least one eigenvector; and
a transmit spatial processor operative to perform spatial processing for a second data transmission with the at least one eigenvector prior to transmission over the second link.
39. The apparatus of claim 38, wherein the transmit spatial processor is
further operative to generate a MIMO pilot for transmission over the second link,
wherein the MIMO pilot comprises a plurality of pilot transmissions sent from a
plurality of transmit antennas, and wherein the pilot transmission from each transmit
antenna is identifiable by a receiver of the MIMO pilot.

40. A method of performing spatial processing in a wireless time division
duplexed (TDD) multiple-input multiple-output (MIMO) communication system,
comprising:
performing spatial processing on pilot symbols with a normalized eigenvector for one eigenmode of a MIMO channel to generate a first steered pilot for transmission via the one eigenmode of the MIMO channel, the normalized eigenvector including a plurality of elements having same magnitude; and
performing spatial processing on data symbols with the normalized eigenvector prior to transmission on the one eigenmode of the MIMO channel.
41. The method of claim 40, further comprising:
performing spatial processing on pilot symbols with an unnormalized eigenvector for the one eigenmode to generate a second steered pilot for transmission via the one eigenmode of the MIMO channel.
42. A method of performing spatial processing in a wireless time division
duplexed (TDD) multiple-input multiple-output (MIMO) orthogonal frequency division
multiplexing (OFDM) communication system, comprising:
processing a first transmission received via a first link to obtain a matrix of eigenvectors for each of a plurality of subbands, wherein a plurality of matrices of eigenvectors are obtained for the plurality of subbands and are usable for spatial processing for both data transmission received via the first link and data transmission sent via a second link; and
performing spatial processing for a second transmission with the plurality of matrices of eigenvectors prior to transmission over the second link.
43. The method of claim 42, further comprising:
ordering the eigenvectors in each matrix based on channel gains associated with the eigenvectors.

44. The method of claim 43, wherein the second transmission is sent on at least one wideband eigenmode, each wideband eigenmode associated with a set of eigenvectors in the plurality of matrices having same order after the ordering.
45. A method of estimating a wireless channel in a time division duplexed (TDD) multiple-input multiple-output (MIMO) communication system, comprising:
processing a pilot transmission received via a first link to obtain a channel response estimate for the first link; and
decomposing the channel response estimate to obtain a matrix of eigenvectors usable for spatial processing for both data transmission received via the first link and data transmission sent via a second link.
46. A method of estimating a wireless channel in a time division duplexed
(TDD) multiple-input multiple-output (MIMO) communication system, comprising:
receiving a steered pilot on at least one eigenmode of a MIMO channel for a first link; and
processing the received steered pilot to obtain at least one eigenvector usable for spatial processing for both data transmission received via the first link and data transmission sent via a second link.
47. The method of claim 46, wherein the processing includes
demodulating the received steered pilot to remove modulation due to pilot
symbols used to generate the steered pilot, and
processing the demodulated steered pilot to obtain the at least one eigenvector.
48. The method of claim 46, wherein the at least one eigenvector is obtained based on a minimum mean square error (MMSE) technique.
49. The method of claim 46, wherein a plurality of eigenvectors are obtained and are forced to be orthogonal to one another.

50. A method for performing data processing in a wireless communication
system including an access point and a user terminal, the method comprising:
calibrating one or more communication links including a first link and a second link between the access point and the user terminal to form a calibrated first link and a calibrated second link;
obtaining a channel response estimate for the calibrated first link based on one or more pilots transmitted on the calibrated first link; and
decomposing the channel response estimate to obtain one or more eigenvectors usable for spatial processing of the one or more communication links.
51. The method of claim 50 wherein calibrating comprises:
determining one or more sets of correction factors based on estimates of channel responses for the one or more communication links; and
applying the one or more sets of correction factors to the first and second links to form the calibrated first and second links.
52. The method of claim 50 further comprising:
performing spatial processing for data transmissions on the first and second links . using the one or more eigenvectors obtained from decomposing the channel response estimate for the calibrated first link.
53. The method of claim 52 wherein performing spatial processing
comprises:
transmitting a steered reference on the second link using the one or more eigenvectors.
54. The method of claim 53 further comprising:
performing spatial processing on or more pilot symbols with the one or more eigenvectors to generate the steered reference.

55. An apparatus for performing data processing in a wireless
communication system including an access point and a user terminal, the apparatus
comprising:
means for calibrating one or more communication links including a first link and a second link between the access point and the user terminal to form a calibrated first link and a calibrated second link;
means for obtaining a channel response estimate for the calibrated first link based on one or more pilots transmitted on the calibrated first link; and
means for decomposing the channel response estimate to obtain one or more eigenvectors usable for spatial processing of the one or more communication links.
56. The apparatus of claim 55 wherein calibrating comprises:
means for determining one or more sets of correction factors based on estimates of channel responses for the one or more communication links; and
means for applying the one or more sets of correction factors to the first and second links to form the calibrated first and second links.
57. The apparatus of claim 55 further comprising:
performing spatial processing for data transmissions on the first and second links using the one or more eigenvectors obtained from decomposing the channel response estimate for the calibrated first link.
58. The apparatus of claim 57 wherein performing spatial processing
comprises:
transmitting a steered reference on the second link using the one or more eigenvectors.
59. The apparatus of claim 58 further comprising:
performing spatial processing on or more pilot symbols with the one or more
eigenvectors to generate the steered reference. (\ J

Documents:

0719-chenp-2005-abstract.pdf

0719-chenp-2005-assignement.pdf

0719-chenp-2005-claims.pdf

0719-chenp-2005-correspondnece-others.pdf

0719-chenp-2005-correspondnece-po.pdf

0719-chenp-2005-description(complete).pdf

0719-chenp-2005-drawings.pdf

0719-chenp-2005-form 1.pdf

0719-chenp-2005-form 3.pdf

0719-chenp-2005-form 5.pdf

0719-chenp-2005-form18.pdf

0719-chenp-2005-pct.pdf

719-chenp-2005 abstract-duplicate.pdf

719-chenp-2005 claims-duplicate.pdf

719-chenp-2005 description (complete)-duplicate.pdf


Patent Number 222537
Indian Patent Application Number 719/CHENP/2005
PG Journal Number 47/2008
Publication Date 21-Nov-2008
Grant Date 14-Aug-2008
Date of Filing 25-Apr-2005
Name of Patentee QUALCOMM INCORPORATED
Applicant Address 5775 Morehouse Drive, San Diego, California 92121,
Inventors:
# Inventor's Name Inventor's Address
1 KETCHUM, John, W 37 Candleberry Lane, Harvard, MA 01451,
2 WALTON, J, Rodney 7 Ledgewood Drive, Westford, MA 01886,
3 WALLACE, Mark, S 4 Madel Lane, Bedford, MA 01730,
4 HOWARD, Steven, J 75 Heritage Avenue, Ashland, MA 01721,
PCT International Classification Number H04B7/08
PCT International Application Number PCT/US03/34567
PCT International Filing date 2003-10-24
PCT Conventions:
# PCT Application Number Date of Convention Priority Country
1 10/693,171 2003-10-23 U.S.A.
2 60/421,309 2002-10-25 U.S.A.
3 60/421,428 2002-10-25 U.S.A.
4 60/421,462 2002-10-25 U.S.A.