USOO7742546B2
`
`(12) United States Patent
`US 7,742,546 B2
`Ketchum et a].
`(45) Date of Patent:
`Jun. 22, 2010
`
`(10) Patent N0.:
`
`(54) RECEIVER SPATIAL PROCESSING FOR
`EIGENMODE TRANSMISSION IN A MINIO
`SYSTEM
`
`(75)
`
`Inventors: John W'. Ketchum, Harvard, MA (US);
`Mark S. \Vallace, Bedford, MA (US); J.
`Rodney Walton, Carlisle, MA (US);
`Steven J. Howard, Ashland, MA (US)
`
`(73) Assignee: QUALCOMM Incorporated, San
`Diego, CA (US)
`
`( * ) Notice:
`
`Subject to any disclaimer, the term of this
`patent is extended or adjusted under 35
`U.S.C. 154(b) by 643 days.
`
`(21) Appl. N0.: 10/682,160
`
`(22) Filed:
`
`Oct. 8, 2003
`
`(65)
`
`Prior Publication Data
`
`US 2005/0078762 A1
`
`Apr. 14, 2005
`
`(51)
`
`Int. Cl.
`(2006.01)
`H04L 23/02
`(2006.01)
`H03H 7/30
`(2006.01)
`H04N 7/12
`(2006.01)
`H04J 13/00
`(2006.01)
`H04] 1/00
`(52) US. Cl.
`....................... 375/341; 375/229; 375/265;
`375/262; 370/480; 370/497; 370/498; 370/529
`(58) Field of Classification Search ................. 375/260,
`375/267, 295,296,335, 346, 349, 1487149,
`375/152, 1367137, 262, 265, 316, 341, 343,
`375/344, 350, 370/208, 319, 210, 295, 344,
`370/436; 455/63, 92, 101, 296, 702, 701,
`455/703, 73, 91, 150.1
`See application file for complete search history.
`
`(56)
`
`EP
`
`References Cited
`U.S. PATENT DOCUMENTS
`8/1969 Rosinski et a1,
`............... 502/65
`
`3,459,679 A *
`
`(Continued)
`FOREIGN PATENT DOCUMENTS
`1786118 Al *
`5/2007
`
`(Continued)
`OTHER PUBLICATIONS
`
`Edfors et al, “An introduction to orthogonal frequency division mul-
`tiplexing”, Sep. 1996, pp. l-58."‘
`
`(Continued)
`
`Primary ExamineriDavid C Payne
`Assistant ExamineriLinda Wong
`(74) Attorney, Agent, or FirmiThien T. Nguyen; Ross L.
`Franks
`
`(57)
`
`ABSTRACT
`
`For eigenmode transmission with minimum mean square
`error (MMSE) receiver spatial processing, a transmitter per-
`forms spatial processing on N5 data symbol streams with
`steering vectors to transmit the streams onNS spatial channels
`of a MIMO channel. The steering vectors are estimates of
`transmitter steering vectors required to orthogonalize the spa-
`tial channels. A receiver derives a spatial filter based on an
`MMSE criterion and with an estimate of the MIMO channel
`
`response and the steering vectors. The receiver (1 ) obtains NR
`received symbol streams from NR receive antemias, (2) per-
`forms spatial processing on the received symbol streams with
`the spatial filter to obtain NS filtered symbol streams, (3)
`pcrforms signal scaling on the filtcrcd symbol streams With a
`scaling matrix to obtain NSrecovered symbol streams, and (4)
`processes the N5 recovered symbol streams to obtain NS
`decoded data streams for the N5 data streams sent by the
`transmitter.
`
`31 Claims, 6 Drawing Sheets
`
`
`TX Data]
`FlX Spatiav
`Data
`
`Processor
`Spatial
`Processor
`
`Recelved
`
`Feedback
`Pilot
`
`
`Into
`Codlng and
`
`Modulation
`
`
`
`Controls
`
`
`
`Data Rate
`Controls
`
` Received
`
`Spatial
`Steering
`Pilul
`Filter
`
`1 12
`170
`
`132
`120 Pi|01130 “a“
`Symbols
`154 Matrices
`Status
`Fomrard
`RX Data
`FlXSpaliel
`
`
`MIMO
`Processor
`Channel
`a HCVR a Processor a
`
`
`
`
`NE
`NF
`NS
`N,
`N,
`Reoelved
`Recovered
`Recelved
`Transmit Modulated
`Signals
`Symbol
`Symbol
`Symbol
`Signals
`Streams
`Streams
`Streams
`
`I 4
`
`,N
`
`Data
`Source
`
`
`
`
`
`
`
`Processor
`Processor
`TX Date I TX Spatial
`
`N3
`Data
`Symbol
`Streams
`
`3
`Data
`Strean-a
`
`.
`
`
`
`NS
`Decoded
`Data
`Streams
`
`Page 1 of 17
`
`SAMSUNG EXHIBIT 1017
`
`Page 1 of 17
`
`SAMSUNG EXHIBIT 1017
`
`

`

`US 7,742,546 B2
`
`Page 2
`
`US. PATENT DOCUMENTS
`
`W0
`
`W00341300 A1 *
`
`5/2003
`
`OTHER PUBLICATIONS
`Joonsuk Kim et al., “Transmission Optimization withaSpace—Time
`Filter at Low SNRWireless Environment,” Globecom 1999, vol. 1B,
`Dec 5, 1993139389393
`_
`_
`_
`_
`7,
`Burr A‘Gu AdflPtWe Space-Time Signal frocessmg and Codlng,
`IEEE200°aVOL LEM 22, 2000,1313. 710_"14'
`fiwlan “I: 6‘ €11"
`fperi‘gnfiagcfdfiflfls 0f MlbgéMMasllgpFE
`.“ffluser ecewer.“
`01: We.“ W1
`Pa“
`we“
`Slty, VTC 2001 Spr1ng.IEEEVTS 53 .Vehlcular Technology Con-
`_
`.
`_
`felence. Rhodes, Greece. May 6-9. 2001, IEEE Vehlculal Technol-
`ogyConference, NeWYork, NY: IEEE. US, V01. 1 of4. Conf. 53, May
`
`6 2001 pp 142446
`’
`’
`'
`‘
`-International
`International Search Report PCT/USO4/032106
`Search AuthorityiEuropean Patent Office NOV. 1, 2005.
`Written Opinion PCT/US04/032106-ISA-European Patent Office
`Apr. 8, 2006.
`International Preliminary Examination Report PCT/USO4/032106,
`IPEA US, Jan. 30, 2006.
`
`* Cited by examiner
`
`..
`
`
`
`4/2002 Raleigh ...................... 375/299
`6.377,631 B1
`8/2003 Crillyet a1.
`. 342/378
`6,611,231 B2*
`3/2005 Temple et a1.
`. 507/119
`6,861,393 B2 *
`5/2006 Thoumy et a1.
`. 375/275
`7039,120 B1 '1
`9/2002 Khatri
`........................ 455/103
`2002/0127978 A1 *
`
`2002/0191703 A1* 12/2002 Ling et 31.
`...........
`375/267
`2003/0003880 A1*
`1/2003 Ling et 31.
`455/92
`
`..
`.375/295
`2003/0108117 A1*
`6/2003 Kctchum ct al.
`,,
`*
`.370/208
`2003/0125381 A1
`7/2003 Zhuangetal.
`
`37q/259
`2003/0185310 A1* 10/2003 Ketchum et al
`“
`”
`
`
`2004/0042556 A1
`375/260
`.. 375/267
`2004/0179627 A1*
`
`'
`3/2004 Medvedev etal.
`9/2004 Ketchum et a1.
`
`FOREIGN PATENT DOCUMENTS
`
`JP
`JP
`WO
`
`2002204193
`7/2002
`2003 209 5 34
`7/2003
`W00278211 A2 * 10/2002
`
`Page 2 of 17
`
`Page 2 of 17
`
`

`

`US. Patent
`
`Jun. 22, 2010
`
`Sheet 1 0f 6
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`

`

`US. Patent
`
`Jun. 22, 2010
`
`Sheet 2 of6
`
`US 7,742,546 B2
`
`NS
`Data
`Streams
`a
`
`E
`E
`
`11120
`TX Data Processor
`214a
`
`212a
`
`216a
`
`NS
`Data
`Symbol
`Streams
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`8
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`:
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`:
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`
`
`Coding
`Controls
`
`Modulation
`Controls
`
`FIG. 2
`
`Page 4 of 17
`
`Page 4 of 17
`
`

`

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`Page 5 of 17
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`Page 5 of 17
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`
`
`

`

`US. Patent
`
`Jun. 22, 2010
`
`Sheet 4 0f 6
`
`us 7,742,546 B2
`
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`Page 6 of 17
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`Page 6 of 17
`
`
`
`

`

`US. Patent
`
`Jun. 22, 2010
`
`Sheet 5 of6
`
`US 7,742,546 B2
`
`NS
`Recovered
`Symbol
`Streams
`& E
`i
`
`L70
`RX Data Processor
`514a
`
`512a
`
`516a
`
`NS
`Decoded
`Data
`Streams
`E 6
`E
`
`
`
`:
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`:
`
`:
`C
`
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`
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`
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`
`
`
`Demodulation
`Controls
`
`Decoding
`Controls
`
`FIG. 5
`
`Page 7 of 17
`
`Page 7 of 17
`
`

`

`US. Patent
`
`Jun. 22, 2010
`
`Sheet 6 of6
`
`US 7,742,546 B2
`
`Obtain estimate, Ear), of channel
`response matrix for each subband
`
`Decompose estimAated channel
`response matrix flUr) foreach
`subband to obtain matrix 1(k) of
`steering vectors that orthogonalize
`NS spatial channels for the subband
`
`Process NS data streams to
`obtain NS data symbol streams
`for transmission on the Ns spatial
`channels of the MIMO channel
`
`
`
`For each subband. perform spatial
`processing on vector §(k) for N5
`data symbol streams with the
`steering vectors to obtain vector
`x(k) for NT transmit symbol streams
`
`Transmit NT transmit symbol
`streams from NT transmit antennas
`
`FIG. 6
`
`m
`r/
`
`712
`
`Obtain estimate, flUr}, of channel
`response matrix for each subband
`
`714
`
`
`Decompose estimated channel
`response matrix fiUr) for each
`subband to obtain matrix
`
`
`1(k) for the subband
`
`716
`
`For each subband, derive
`
`
`
`spatial filter matrix _V_V(k) and
`diagonal matrix flank) based on
`MMSE criterion and with matrices
`fi(k) and 1(k) for the subband
`
`718
`
`
`
`Obtain NR received symbol
`
`
`streams from NH receive antenna
`for N5 data symbol streams
`
`
`transmitted via NS spatial
`
`channels of the MIMO channel
`
`720
`
`
`For each subband, perform
`
`
`spatial processing on vector [(k)
`for the NH received symbol
`
`
`streams with the spatial filter matrix
`fl(k) to obtain vector §(k)
`
`
`for N8 filtered symbol streams
`722
`
`
`For each subband, perform signal
`
`scaling on vector §(k) with diagonal
`matrix 123(k) to obtain vector $(k) for
`N5 recovered symbol streams
`724
`
`
`
`
`
`
`
`
`
`Process the NS recovered
`symbol streams to obtain
`N5 decoded data streams
`
`
`
`
`
`End
`
`FIG. 7
`
`Page 8 of 17
`
`Page 8 of 17
`
`

`

`US 7,742,546 B2
`
`2
`ditions and transmits the NTtransmit symbol streams from the
`N Ttransmit antennas to the receiver.
`The receiver derives a spatial filter based on a minimum
`mean square error (MMSE) criterion and with the channel
`response estimate and the steering vectors. The receiver also
`derives a scaling matrix. The receiver obtains NR received
`symbol streams from NR receive antennas for the NS data
`symbol streams transmitted on the N5 spatial Channels. The
`receiver performs spatial processing on the NR received sym-
`bol streams with the spatial filter and obtains NS filtered
`symbol streams. The receiver further performs signal scaling
`on the filtered symbol streams with the scaling matrix to
`obtain NS recovered symbol streams, which are estimates of
`the NS data symbol streams sent by the transmitter. The
`receiver then processes (e.g., demodulates, deinterleaves, and
`decodes) the NS recovered symbol streams to obtain NS
`decoded data streams, which are estimates of the NS data
`streams sent by the transmitter.
`The receiver spatial processing techniques described
`herein may be used for single—carrier and multi—carrier
`MIMO systems. For a multi-can‘ier MIMO system, the spa-
`tial processing at the transmitter and receiver may be per-
`formed for each of multiple subbands.
`Various aspects and embodiments of the invention are
`described in further detail below.
`
`
`
`BRIEF D: LIISCRIPTION OF THE DRAWINGS
`
`1
`RECEIVER SPATIAL PROCESSING FOR
`EIGEN MODE TRANSMISSION IN A MLVIO
`SYSTEM
`
`BACKGROUND
`
`I. Field
`
`The present invention relates generally to data communi—
`cation, and more specifically to techniques for perfonning
`receiver spatial processing in a multiple-input multiple-out-
`put (MIMO) communication system.
`II. Background
`A MIMO system employs multiple (NT) transmit antennas
`and multiple (NR) receive antennas for data transmission and
`is denoted as an (NT, NR) system. A MIMO channel formed
`by the NT transmit and NR receive antennas may be decom-
`posed into N5 spatial channels, where NSE min {N 13 NR}).
`The NS spatial channels may be used to transmit up to NS
`independent data streams to achieve greater overall through-
`put. Spatial processing may or may not he performed by a
`transmitter and is performed by a receiver in order to transmit
`multiple data streams on the NS spatial channels.
`The NS spatial channels may or may not be orthogonal to
`one another. Orthogonal spatial channels can only be
`obtained when both (I) the transmitter performs spatial pro-
`cessing with the proper steering vectors and (2) the receiver
`performs spatial processing with the proper spatial filter. The
`orthogonality of the spatial channels thus depends on (1)
`whether or not spatial processing was performed at the trans-
`mitter and (2) whether or not the spatial processing at both the
`transmitter and the receiver was successful in orthogonalizing
`the spatial channels. Each spatial chamiel is referred to as an
`“eigenmode” of the MIMO chamiel ifthe N5 spatial channels
`are orthogonal to one another, In this case, NS data streams
`may be transmitted orthogonally on the Nb eigenmodes. Per-
`formance is better when the spatial channels are orthogonal.
`However, in a practical system, the N5 spatial channels are
`usually not completely orthogonal to one another due to vari—
`ous reasons. For example, the spatial channels would not be
`orthogonal if (1) the transmitter has no knowledge of the
`MIMO channel or (2) the transmitter and/or the receiver have
`an imperfect estimate of the MIMO channel. If the spatial
`channels are not orthogonal, then each data stream will expe-
`rience cross-talk from the other data streams at the receiver.
`The cross-talk acts as additive noise that degrades perfor-
`mance.
`
`There is therefore a need in the art for techniques to miti-
`gate the deleterious effects of cross—talk when transmitting
`data 011 multiple spatial channels in a MIMO system.
`
`SUMMARY
`
`Techniques for performing receiver spatial processing in a
`manner to mitigate cross-talk and achieve better performance
`are provided herein. Initially, a transmitter and/or a receiver
`estimates the response of a MIMO Channel and decomposes
`the channel response estimate to obtain steering vectors,
`which are estimates ofthe transmitter steering vectors needed
`to orthogonalize the NS spatial channels of the MIMO chan-
`nel. The transmitter is provided with the steering vectors if
`they are derived by the receiver. The transmitter processes
`(e. g., encodes, interleaves, and modulates) NS data streams to
`obtain NS data symbol streams for transmission on the NS
`spatial channels. The transmitter performs spatial processing
`on the NS data symbol streams with the steering vectors to
`obtain NT transmit symbol streams. The transmitter then con-
`
`10
`
`15
`
`20
`
`30
`
`35
`
`40
`
`45
`
`60
`
`65
`
`Page 9 of 17
`
`The features and nature of the present invention will
`become more apparent from the detailed description set forth
`below when taken in conjunction with the drawings in which
`like reference characters identify correspondingly through-
`out and wherein:
`FIG. 1 shows a transmitter and a receiver in a MIMO
`system;
`FIG. 2 shows a transmit (TX) data processor at the trans—
`mitter;
`FIG. 3 shows a TX spatial processor and a transmitter unit
`at the transmitter;
`FIG. 4 shows a receiver unit and a receive (RX) spatial
`processor at the receiver;
`FIG. 5 shows an RX data processor at the receiver; and
`FIGS. 6 and 7 s 10w processes performed by the transmitter
`and the receiver, respectively, for eigenmode transmission
`with MMSE receiver spatial processing.
`
`DETAILED DESCRIPTION
`
`The word “exemplary” is used herein to mean “serving as
`an example, instance, or illustration.” Any embodiment or
`design described 1erein as “exemplary” is not necessarily to
`be construed as preferred or advantageous over other embodi-
`ments or designs.
`The receiver spatial processing techniques described
`herein may be used in a single-carrier MIMO system as well
`as a multi-carrier MIMO system. Multiple carriers may be
`provided by orthogonal frequency division multiplexing
`(OFDM), other multi-carrier modulation techniques, or some
`other constructs. OFDM effectively partitions the overall sys-
`tem bandwidth into multiple (NF) orthogonal subbands,
`which are also commonly referred to as tones, bins, or fre—
`quency channels. With OFDM, each subband is associated
`with a respective carrier that may be modulated with data. For
`clarity, the receiver spatial processing techniques are specifi-
`cally described below for a MIMO system that implements
`OFDM (i.e., a MIMO-OFDM system).
`
`
`
`Page 9 of 17
`
`

`

`US 7,742,546 B2
`
`3
`A frequency-selective MIMO channel with NT transmit
`antennas and NR receive antennas may be characterized by NF
`frequency-domain channel response matrices H(k), for k:
`1
`.
`.
`. NF, each with dimensions of NRxNT. These channel
`response matrices may be expressed as:
`
`111,1“:|
`km (’0
`_
`
`[112(k)
`hulk)
`_
`
`H(k) =
`
`firm-(k)
`thvT (k)
`.
`
`Eq (1)
`
`hNRJ (k)
`
`hNR,2(/<)
`
`hNR,(V7-(kl
`
`for/(=1
`
`Np,
`
`. .NF,
`. .NR,j:l ...NI, andk:l .
`where entry hl’](k), fori:l .
`is the coupling (i.e., complex gain) between transmit antemia
`j and receive antenna i for subband k.
`The channel response matrix H(k) for each subband may
`be “diagonalized” to obtain the NS eigenmodes for that sub-
`band. This diagonalization may be achieved by performing
`either singular value decomposition of the channel response
`matrix H(k) or eigenvalue decomposition of the correlation
`matrix of H(k), which is R(k):HH(k)H(k).
`The singular value decomposition of the channel response
`matrix H(k) may be expressed as:
`H(k):U(k)2(k) VH(k), for k:1 _
`_
`. NF,
`
`Eq (2)
`
`where U(k) is a (NR><NR) unitary matrix ofleft eigenvectors of
`H(k);
`2(k) is an (NRXNT) diagonal matrix of singular values of
`H(k); and
`V(k) is a (NIxNT) unitary matrix of right eigenvectors of
`H(k).
`
`4
`Eigenmode transmission refers to transmission of data on
`the NS eigenmodes of the MIMO channel. Eigenmode trans-
`mission requires spatial processing by both the transmitter
`and the receiver, as described below.
`The spatial processing at the transmitter for eigenmode
`transmission on subband k may be expressed as:
`Xidwflk): VUUSUCL
`
`HQ 1.4)
`
`where s(k) is an (NTxl) data vector with N5 non-zero entries
`for NS modulation symbols to be transmitted on the NS eigen-
`modes for subband k; and
`deeal(k) is a (Nle) transmit vector with NT entries for NT
`transmit symbols to be sent from the NT transmit anten-
`nas for subband k.
`
`NS entries of s(k) can represent N5 data streams and the
`remaining entries of s(k), if any, are filled with zeros.
`The received symbols obtained by the receiver for subband
`k may be expressed as:
`rzdeal(k):H(k)xzdeal(k)+n (M4106) V(k)S(k)+H(k)s
`
`Eq (5)
`
`where r1.deal(k) is an (NRxl) received vector with NR entries
`for NR received symbols obtained via the NR receive antennas
`for subband k; and
`n(k) is a noise vector for subband k.
`The spatial processing or matched filtering at the receiver
`to recover the data vector s(k) may be expressed as:
`
`314ml") = A71(k)VH(I‘)HH(k)rideal‘:k)a
`
`= A’l(k)VW)Warm/owes“) + mm
`= 500 + fiideallk)a
`
`where gaming) is an (Nle) estimated data vector with up to
`NS recovered data symbols for subband k; and
`f1,dm(k) is a vector of post-processed noise for subband k.
`The matched filter used by the receiver for subband k may
`be expressed as:
`
`Mdea:(k):VHtk)HH(k)-
`
`Eq (7)
`
`The multiplication by A'1(k) in equation (6) accounts for the
`(possibly different) gains of the NS spatial channels and nor-
`malizes the output of the matched filter so that recovered data
`symbols with the proper magnitude are provided to the sub-
`sequent processing unit. The normalization (i.e., signal scal-
`ing) is based on the following observation:
`VH(k)11H(k)II(k) mik):2H(k)2(k):A(k).
`
`Eq (8)
`
`Equation (8) indicates that the eigenvalues of HH(k)H(k) in
`the diagonal matrix A(k) are also the squares of the singular
`values of H(k) in the diagonal matrix 2(k).
`Equation (6) indicates that the N5 data symbol streams s(k),
`distorted only by post—processed channel noise fiidgal(k), may
`be obtained with the proper spatial processing at both the
`transmitter and the receiver. However, the result shown in
`equation (6) is ideal in that both the transmitter and the
`receiver are assumed to have perfect information about the
`MIMO channel. In a practical system, both the transmitter
`and the receiver will have noisy estimates of the MIMO
`channel and/or noisy estimates ofthe eigenvectors and eigen-
`values. In this case, the recovered data symbols for each
`stream will be corrupted by cross-talk from the other streams.
`
`10
`
`15
`
`20
`
`30
`
`35
`
`40
`
`45
`
`60
`
`65
`
`A unitary matrix M is characterized by the property MHM:I,
`where I is the identity matrix. The columns of a unitary matrix
`are orthogonal to one another.
`The eigenvalue decomposition of the correlation matrix of
`H(k) may be expressed as:
`H(k):HH(k)H(k):I/(k)A(k) VH(k), for k:1 .
`
`.
`
`. NF,
`
`Hq (3)
`
`where A(k) is a (NRXNT) diagonal matrix of eigenvalues of
`R(k). As shown in equations (2) and (3), the columns ofV(k)
`are eigenvectors ofR(k) as well as right eigenvectors ofH(k).
`Singular value decomposition and eigenvalue decomposi-
`tion are described by Gilbert Strang in a book entitled “Linear
`Algebra and Its Applications,” Second Edition, Academic
`Press, 1980. The receiver spatial processing techniques
`described herein may be used in conjunction with either sin-
`gular value decomposition or eigenvalue decomposition. For
`clarity, singular value decomposition is used for the following
`description.
`The right eigenvectors ofH(k) are also referred to as “steer-
`ing” vectors and may be used for spatial processing by a
`transmitter in order to transmit data 011 the NS eigenmodes of
`H(k). The left eigenvectors of H(k) may be used for spatial
`processing by a receiver in order to recover the data transmit-
`ted on the NS eigenmodes. The diagonal matrix 2(k) contains
`non-negative real values along the diagonal and zeros every-
`where else. These diagonal entries are referred to as the sin—
`gular values ofI I(k) and represent the channel gains for the NS
`eigenmodes of H(k). Singular value decomposition may be
`performed independently on the channel response matrix
`H(k) for each of the NF subbands to determine the N5 eigen—
`modes for that subband.
`
`Page 10 of 17
`
`Page 10 of 17
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`

`

`5
`The spatial processing at the transmitter in a practical sys-
`tem for subband k may be expressed as:
`
`6
`and the data vector s(k) is minimized. This MMSE criterion
`may be expressed as:
`
`US 7,742,546 B2
`
`X(k):Vtik)S(k)s
`
`Eq (9)
`
`Where V(k) is a matrix of steering vectors used by the trans-
`mitter for subband k; and
`
`x(k) is a transmit vector obtained with V(k).
`
`The matrix V(k) is an estimate ofV(k) and may be obtained,
`for example, by performing singular value decomposition of
`H(k), which is an estimate of H(k).
`The received symbols obtained by the receiver for subband
`k may be expressed as:
`
`r(k):H(k) f’(k)s(k)+n (k).
`
`Eq (10)
`
`The matched filter M(k) for the received symbols may be
`expressed as:
`
`M(_k,):f’H(k)HH(k).
`
`Hq r1 1)
`
`10
`
`15
`
`20
`
`Similar to the transmitter, the receiver in the practical system
`only has an estimate of this matched filter.
`The spatial processing at the receiver in the practical sys-
`tem for subband k may be expressed as:
`
`SmuI/O = A’1<k)n‘4<k)rtk),
`
`Eq “2)
`
`30
`
`= N1<k)Wk)H(kJV(k)s(k> Mme).
`= s(k) + c(k) + fipmctk),
`
`Where M(k) is an estimate of M(k) for subband k;
`[\(k):diag [M(k)H(k)v(k)] for subband k; and
`C(k) is a vector of cross-talk terms for subband k.
`In equation (12), [\(k) is a diagonal matrix whose diagonal
`elements are the diagonal elements of M(k)H(k)V(k). The
`cross-talk terms in C(k) are generated by the off-diagonal
`terms of M(k)H(k)VA’(k), which result from (1) the use of an
`imperfect estimate of V(k) by the transmitter and (2) the use
`of an imperfect estimate of M(k) by the receiver. The cross-
`talk terms act as additive noise that degrades the quality ofthe
`estimated data vector épm(k).
`The power in the cross-talk vector c(k) may be small rela-
`tive to the signal power in the data vector s(k) ifthe transmitter
`has a good estimate of V(k) and the receiver has a good
`estimate of M(k), both of which require a good estimate of
`H(k). Good estimates of both V(k) and M(k) are needed to
`orthogonalize the NS spatial channels and to minimize deg—
`radation due to cross-talk. If the transmitter has a good esti-
`mate of V(k), then a good estimate of M(k) is needed to
`mimmize the off-diagonal terms of M(k)H(k)V(k). However,
`if the transmitter has a poor estimate of V(k), then the cross-
`talk terms may have significant amounts of power even if the
`receiver has a perfect estimate of M(k).
`The receiver can use MMSE spatial processing to suppress
`the cross-talk terms and maximize the signal-to-noise-and-
`interference ratio (SNR) of the estimated data vector. The
`MMSE receiver spatial processing can provide improvedper-
`formance when he transmitter has an imperfect estimate of
`
`V(k). An MMSE receiver utilizes a spatial filter having a
`response ofW(k), which is derived such that the mean square
`error between the estimated data vector from the spatial filter
`
`35
`
`40
`
`45
`
`60
`
`65
`
`min E[(W(k)r(lc) 7 5(k))’H (W(k)r(k,) 7 sum],
`tW(/<))
`
`Eq (13)
`
`where E[x] is the expected value of x.
`The solution to the optimization problem posed in equation
`(13) may be obtained in various manners. One exemplary
`method for deriving the MMSE spatial filter matrix W(k) is
`described below. For this method, the matrix W (k) may be
`cxprcsscd as:
`
`W<_k>:f””<k>HH<k> [H00 m) W:k>HH<_k)+¢...<kJr£
`
`Eq (14)
`
`Where (pm (k) is an autocovariance matrix of the receive noise
`process for subband k, Which is ¢"n(k):E[n(k)nH(k)].
`The spatial processing by the MMSE receiver for subband
`k may then bc cxprcsscd as:
`
`s(k) = D§1<k)W<k)r<k>,
`= D? <k>W<k)H<k)V<k)s(/a + m),
`= D§1(k)Q(/<)s(k) + fi(k),
`
`where 71th = 051 (k)w (kmug).
`
`Eq (15)
`
`Q(k) = W(k)H<kJV<k),
`
`Eq (16)
`
`= VH(k)H”(I<)[H(k)\7(ky)VH(k)H"(ky) + go,,,,(k)]il
`mot/(k).
`
`= VH(k)H”(k)[H(/<)H”tk) + som<k>rlH<W<m
`
`and 09th = diag [W(kJHUth/CJ].
`
`Eq (17)
`
`DQ(k) is a diagonal matrix whose diagonal elements are the
`diagonal elements of Q(k). Using the matrix inverse identity,
`equation (16) can be rewritten as:
`
`Q(kliW(k)H”tk)q>..: Romef/(kn
`V”(k)H”(k)¢.;l(kwrk)V(k)+I]".
`
`Eqas)
`
`If the noise vector 11(k) is additive white Gaussian noise
`(AWGN) with zero mean and an autocovariance matrix of
`(1),," (k):ozl, Where 02 is the variance of the noise, then equa-
`tions (14) and (18) may be simplified as:
`
`W(k):f“"(_k)HH(_k) [H(_k) Wk) f/Hijk)HH(k)+02U 1. and
`
`Eq (19)
`
`Q(kjr 13H(k)HH(/:)H(k) f/(k) [W(IQHHQQHUC)
`f/(k)+021]".
`
`The MMSE receiver spatial processing in equation (15) is
`composed oftwo steps. In the first step, the vector r(k) for the
`NR received symbol streams is multiplied With the MMSE
`spatial filter matrix W(k) to obtain a vector s(k) for NS filtered
`symbol streams, as follows:
`
`S‘tk):Wtk)rtk)-
`
`Eq (20)
`
`The NS filtered symbol streams are unnormalized estimates of
`the NS data symbol streams. In the second step, the vector s(k)
`is multiplied with the scaling matrix DQ'](k) to obtain the
`vector s(k) for the N5 recovered symbol streams, as follows:
`
`§(k):DQ’l(k)§(kj.
`
`Eq (21)
`
`Page 11 of17
`
`Page 11 of 17
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`

`

`US 7,742,546 B2
`
`7
`The NS recovered symbol streams are normalized estimates
`of the N5 data symbol streams.
`As noted above, the receiver spatial processing techniques
`described herein may also be used for a single-canier MIMO
`system. In this case, the description above applies, albeit
`without the subband index k. The spatial processing at the
`transmitter can be expressed as:
`1': Vs.
`
`Eq (22)
`
`The MMSE spatial processing at
`expressed as:
`
`the receiver can be
`
`§:DQ’1Wr,
`
`Eq (23)
`
`or §:Wr and §:DQ'1§.
`The MMSE spatial filter response W can be expressed as:
`W: f/HHH [HVVH+¢nn 4-
`Eq (24)
`
`If the noise is AWGN with an autocovariance matrix of
`
`¢,,M:OZI, then the MMSE spatial filter response simplifies to:
`Eq (2 5)
`W: f/HHHmf’f’HHH+GZI]"
`
`
`
`The MMSE spatial filter matrices W and W(k) may also be
`derived using other methods. For example, these matrices
`may be derived using time recursive methods such as a recur-
`sive least square method, a least mean square method, and so
`on, which are known in the art.
`FIG. 1 shows a block diagram of a transmitter 110 and a
`receiver 150 in a MIMO system 100.At transmitter 110, a TX
`data processor 120 receives NS data streams from a data
`source 112. TX data processor 120 processes (e.g., encodes,
`interleaves, and modulates) each data stream in accordance
`with a rate selected for that data stream to obtain a corre—
`sponding data symbol stream. The selected rate for each data
`stream may indicate the data rate, coding scheme or code rate,
`modulation scheme, and so on, to use for that data stream, all
`of which are indicated by the various controls provided by a
`controller 140. A TX spatial processor 130 receives NS data
`symbol streams from TX data processor 120, performs spatial
`processing on these streams with the matrices V(k), for k:
`l
`.
`.
`. NF, multiplexes in pilot symbols, and provides NT
`transmit symbol streams to a transmitter unit (TMTR) 132.
`The pilot symbols are modulation symbols known a priori and
`may be used by receiver 150 for channel estimation.
`Transmitter unit 132 performs OFDM modulation on the
`NT transmit symbol streams to obtain NT OFDM symbol
`streams. Transmitter unit 132 further conditions (e.g., con—
`verts to analog, frequency upconverts, filters, and amplifies)
`the OFDM symbol streams to obtain NT modulated signals.
`Each modulated signal is transmitted from a respective trans-
`mit antenna (not shown in FIG. 1) and via a forward MIMO
`channel to receiver 150. The MIMO channel distorts the NT
`transmitted signals with the channel response H(k), for k:
`l
`.
`.
`. NF, and further degrades the transmitted signals with
`noise and possibly interference from other transmitters.
`At receiver 150, the NT transmitted signals are received by
`each ofNR receive antennas (not shown in FIG. 1), and the NR
`received signals from the NR receive antennas are provided to
`a receiver unit (RCVR) 154. Receiver unit 154 conditions,
`digitizes, and pre-processes each receive signal to obtain a
`corresponding received chip stream. Receiver unit 154 fur—
`ther performs OFDM demodulation on each received chip
`stream to obtain a corresponding received symbol stream.
`Receiver unit 154 provides NR received symbol streams (for
`data) to an RX spatial processor 160 and received pilot sym—
`bols (for pilot) to a channel estimator 172.
`
`Page 12 of 17
`
`8
`RX spatial processor 160 performs spatial processing on
`the NR received symbol streams to obtain NS recovered sym-
`bol streams, which are estimates of the NS data symbol
`streams sent by transmitter 110. An RX data processor 170
`further processes (e.g., demodulates, deinterleaves, and
`decodes) the NS recovered symbol streams to obtain NS
`decoded data streams, which are estimates of the NS data
`streams sent by transmitter 110. RX data processor 170 also
`provides the status of each decoded packet, which indicates
`whether the packet is decoded correctly or in error.
`Channel estimator 172 processes the received pilot sym-
`bols to obtain channel estimates forthe forward MIMO chan-
`nel (e.g., estimated channel response matrices H(k), for k:
`1 .
`.
`. NF, noise variance estimate, 01, and so on). A matrix
`computation unit 174 receives the channel estimates, com-
`putes the MMSE spatial filter matrices W(k) and the scaling
`matrices DQ'1(k), for k:l .
`.
`. NF, and provides these matrices
`to RX spatial processor 160. Matrix computation unit 174
`may also compute the matrices V(k), for k:l .
`.
`. NF, of
`steering vectors for transmitter 110.
`A controller 180 receives the channel estimates from chan—
`nel estimator 172 and the packet status from RX data proces-
`sor 170, selects the rates for the NS data streams, and
`assembles feedback information for transmitter 110. The
`
`feedback information may include the N5 selected rates,
`acknowledgments (ACKs) and negative acknowledgments
`(NAKs) forthe decoded packets, the matrices VA’(k), and so on.
`The feedback information andpilot symbols are processed by
`a TX data/spatial processor 190, conditioned by a transmitter
`unit 192, and transmitted via a reverse MIMO channel to
`transmitter 110.
`
`At transmitter 110, the NR signals transmitted by receiver
`150 are received and conditioned by a receiver unit 146 and
`further processed by an RX spatial/data processor 148 to
`obtain the feedback information sent by receiver 150. Con-
`troller 140 receives the feedback information, uses theACKs/
`NAKs to control the transmission of data packets to receiver
`150, and uses the NS selected rates to process new packets for
`the N5 data streams.
`Controllers 140 and 180 direct the operation at transmitter
`110 and receiver 150, respectively. Memory units 142 and
`182 provide storage for program codes and data used by
`controllers 140 and 180, respectively. Memory units 142 and
`182 may be internal to controllers 140 and 180, as shown in
`FIG. 1, or external to these controllers. Some of the process-
`ing units shown in FIG. 1 are described in detail below.
`Transmitter 110 may be an access point and receiver 150
`may be a user terminal in the MIMO system, in which case the
`forward and reverse MIMO channels are the downlink and
`uplink, respectively. Altematively, transmitter 110 may be a
`user terminal and receiver 150