MIMO system with multiple spatial multiplexing modes

Information

  • Patent Grant
  • 9031097
  • Patent Number
    9,031,097
  • Date Filed
    Tuesday, December 29, 2009
    14 years ago
  • Date Issued
    Tuesday, May 12, 2015
    9 years ago
Abstract
A MIMO system supports multiple spatial multiplexing modes for improved performance and greater flexibility. These modes may include (1) a single-user steered mode that transmits multiple data streams on orthogonal spatial channels to a single receiver, (2) a single-user non-steered mode that transmits multiple data streams from multiple antennas to a single receiver without spatial processing at a transmitter, (3) a multi-user steered mode that transmits multiple data streams simultaneously to multiple receivers with spatial processing at a transmitter, and (4) a multi-user non-steered mode that transmits multiple data streams from multiple antennas (co-located or non co-located) without spatial processing at the transmitter(s) to receiver(s) having multiple antennas. For each set of user terminal(s) selected for data transmission on the downlink and/or uplink, a spatial multiplexing mode is selected for the user terminal set from among the multiple spatial multiplexing modes supported by the system.
Description
BACKGROUND

1. Field


The present invention relates generally to communication, and more specifically to a multiple-input multiple-output (MIMO) communication system with multiple transmission modes.


2. 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 decomposed into NS spatial channels, where NS≦min {NT, NR}. The NS spatial channels may be used to transmit NS independent data streams to achieve greater overall throughput. In general, spatial processing may or may not be performed at a transmitter and is normally performed at a receiver to simultaneously transmit and recover multiple data streams.


A conventional MIMO system typically uses a specific transmission scheme to simultaneously transmit multiple data streams. This transmission scheme may be selected based on a trade-off of various factors such as the requirements of the system, the amount of feedback from the receiver to the transmitter, the capabilities of the transmitter and receiver, and so on. The transmitter, receiver, and system are then designed to support and operate in accordance with the selected transmission scheme. This transmission scheme typically has favorable features as well as unfavorable ones, which can impact system performance.


There is therefore a need in the art for a MIMO system capable of achieving improved performance.


SUMMARY

A MIMO system that supports multiple spatial multiplexing modes for improved performance and greater flexibility is described herein. Spatial multiplexing refers to the transmission of multiple data streams simultaneously via multiple spatial channels of a MIMO channel. The multiple spatial multiplexing modes may include (1) a single-user steered mode that transmits multiple data streams on orthogonal spatial channels to a single receiver, (2) a single-user non-steered mode that transmits multiple data streams from multiple antennas to a single receiver without spatial processing at a transmitter, (3) a multi-user steered mode that transmits multiple data streams simultaneously to multiple receivers with spatial processing at a transmitter, and (4) a multi-user non-steered mode that transmits multiple data streams from multiple antennas (co-located or non co-located) without spatial processing at the transmitter(s) to receiver(s) having multiple antennas.


A set of at least one user terminal is selected for data transmission on the downlink and/or uplink. A spatial multiplexing mode is selected for the user terminal set from among the multiple spatial multiplexing modes supported by the system. Multiple rates are also selected for multiple data streams to be transmitted via multiple spatial channels of a MIMO channel for the user terminal set. The user terminal set is scheduled for data transmission on the downlink and/or uplink with the selected rates and the selected spatial multiplexing mode. Thereafter, multiple data streams are processed (e.g., coded, interleaved, and modulated) in accordance with the selected rates and further spatially processed in accordance with the selected spatial multiplexing mode for transmission via multiple spatial channels.


Various aspects and embodiments of the invention are described in further detail below.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 shows a multiple-access MIMO system;



FIG. 2 shows a frame and channel structure for the MIMO system;



FIG. 3 shows an access point and two user terminals in the MIMO system;



FIG. 4 shows a transmit (TX) data processor at the access point;



FIG. 5 shows a TX spatial processor and modulators at the access point;



FIG. 6 shows demodulators and a receive (RX) spatial processor at a multi-antenna user terminal;



FIG. 7 shows an RX data processor at the multi-antenna user terminal;



FIG. 8 shows an RX spatial processor and an RX data processor that implement a successive interference cancellation (SIC) technique;



FIG. 9 shows the transmit/receive chains at the access point and user terminal;



FIG. 10 shows a closed-loop rate control mechanism;



FIG. 11 shows a controller and a scheduler for scheduling user terminals;



FIG. 12 shows a process for scheduling user terminals for data transmission;



FIG. 13 shows a process for transmitting data on the downlink; and



FIG. 14 shows a process for receiving data on the uplink.





DETAILED DESCRIPTION

The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.


A MIMO system may utilize a single carrier or multiple carriers for data transmission. 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 system bandwidth into multiple (NF) orthogonal subbands, which are also commonly referred to as tones, bins, carriers, and frequency channels. With OFDM, each subband is associated with a respective carrier that may be modulated with data. The following description is for a MIMO system that utilizes OFDM. However, the concepts described herein are equally applicable for a single carrier MIMO system.


The MIMO system supports multiple spatial multiplexing modes for improved performance and greater flexibility. Table 1 lists the supported spatial multiplexing modes and their short descriptions.










TABLE 1





Spatial



Multiplexing Mode
Description







Single-User
Multiple data streams are transmitted on orthogonal spatial


Steered
channels to a single receiver.


Single-User
Multiple data streams are transmitted from multiple antennas to


Non-Steered
a single receiver without spatial processing at a transmitter.


Multi-User
Multiple data streams are transmitted simultaneously (1) from a


Steered
single transmitter to multiple receivers or (2) from multiple



transmitters to a single receiver, both with spatial processing



at the transmitter(s).


Multi-User
Multiple data streams are transmitted simultaneously (1) from


Non-Steered
multiple transmitters to a single receiver or (2) from a single



transmitter to multiple receivers, both without spatial



processing at the transmitter(s).










The MIMO system may also support other and/or different spatial multiplexing modes, and this is within the scope of the invention.


Each spatial multiplexing mode has different capabilities and requirements. The steered spatial multiplexing modes can typically achieve better performance but can only be used if the transmitter has sufficient channel state information to orthogonalize the spatial channels via decomposition or some other technique, as described below. The non-steered spatial multiplexing modes require very little information to simultaneously transmit multiple data streams, but performance may not be quite as good as the steered spatial multiplexing modes. A suitable spatial multiplexing mode may be selected for use depending on the available channel state information, the capabilities of the transmitter and receiver, system requirements, and so on. Each of these spatial multiplexing modes is described below.


Single-User Steered Spatial Multiplexing Mode


A frequency-selective MIMO channel formed by 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 NR×NT. The channel response matrix for each subband may be expressed as:












H
_



(
k
)


=

[





h

1
,
1




(
k
)






h

1
,
2




(
k
)









h

1
,

N
T





(
k
)








h

2
,
1




(
k
)






h

2
,
2




(
k
)









h

2
,

N
T





(
k
)






















h


N
R

,
1




(
k
)






h


N
R

,
2




(
k
)









h


N
R

,

N
T





(
k
)





]


,




Eq
.





(
1
)








  • where entry hi,j(k), for i=1 . . . NR, j=1 . . . NT, and k=1 . . . NF, is the coupling (i.e., complex gain) between transmit antenna j and receive antenna i for subband k.



The channel response matrix H(k) for each subband may be “diagonalized” to obtain NS eigenmodes for that subband. This diagonalization may be achieved by performing either singular value decomposition of the channel response matrix H(k) or eigenvalue decomposition of a correlation matrix of H(k), which is R(k)=HH(k)H(k), where “H” denotes the conjugate transpose.


The singular value decomposition of the channel response matrix H(k) for each subband may be expressed as:

H(k)=U(k)Σ(k)VH(k),  Eq. (2)

where



U(k) is an (NR×NR) unitary matrix of left eigenvectors of H(k);



Σ(k) is an (NR×NT) diagonal matrix of singular values of H(k); and



V(k) is an (NT×NT) unitary matrix of right eigenvectors of H(k).


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) for each subband may be expressed as:

R(k)=HH(k)H(k)=V(k)Λ(k)VH(k),  Eq. (3)

  • where Λ(k) is an (NT×NT) diagonal matrix of eigenvalues of R(k). As shown in equations (2) and (3), the columns of V(k) are eigenvectors of R(k) as well as right eigenvectors of H(k).


Singular value decomposition and eigenvalue decomposition are described by Gilbert Strang in a book entitled “Linear Algebra and Its Applications,” Second Edition, Academic Press, 1980. The single-user steered spatial multiplexing mode may be implemented with either singular value decomposition or eigenvalue decomposition. For clarity, singular value decomposition is used for the following description.


The right eigenvectors of H(k) are also referred to as “steering” vectors and may be used for spatial processing by a transmitter to transmit data on the NS eigenmodes of H(k). The left eigenvectors of H(k) may be used for spatial processing by a receiver to recover the data transmitted on the NS eigenmodes. The eigenmodes may be viewed as orthogonal spatial channels obtained through decomposition. The diagonal matrix Σ(k) contains non-negative real values along the diagonal and zeros elsewhere. These diagonal entries are referred to as the singular values of H(k) and represent the channel gains for the NS eigenmodes of H(k). The singular values of H(k), {σ1(k) σ2(k) . . . σNS(k)}, are also the square roots of the eigenvalues of R(k), {λ1(k) λ2(k) . . . λNS(k)}, where σi(k)=√{square root over (λi(k))}. Singular value decomposition may be performed independently on the channel response matrix H(k) for each of the NF subbands to determine the NS eigenmodes for that subband.


For each subband, the singular values in the matrix Σ(k) may be ordered from largest to smallest, and the eigenvectors in the matrices V(k) and U(k) may be ordered correspondingly. A “wideband” eigenmode may be defined as the set of same-order eigenmodes of all NF subbands after the ordering (i.e., wideband eigenmode m includes eigenmode m of all subbands). In general, all or fewer than NF subbands may be used for transmission, with the unused subbands being filled with signal values of zero. For simplicity, the following description assumes that all NF subbands are used for transmission.


The single-user steered spatial multiplexing mode (or simply, the “single-user steered mode”) transmits NS data symbol streams on the NS eigenmodes of the MIMO channel. This requires spatial processing by both the transmitter and the receiver.


The spatial processing at the transmitter for each subband for the single-user steered mode may be expressed as:

xsu-s(k)=V(k)s(k),  Eq. (4)

where

    • s(k) is an (NT×1) vector with NS non-zero entries for NS data symbols to be transmitted on the NS eigenmodes for subband k; and
    • xsu-s(k) is an (NT×1) vector with NT entries for NT transmit symbols to be sent from the NT transmit antennas for subband k.


      The NS entries of s(k) can represent NS data symbol streams and the remaining entries of s(k), if any, are filled with zeros.


The received symbols obtained by the receiver for each subband may be expressed as:

rsu-s(k)=H(k)xsu-s(k)+n(k)=H(k)V(k)s(k)+n(k),  Eq. (5)

where

    • rsu-s(k) is an (NR×1) 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 at the receiver to recover the data vector s(k) for each subband may be expressed as:

















s
^

_


su
-
s




(
k
)


=






Σ
_


-
1




(
k
)






U
_

H



(
k
)






r
_


su
-
s




(
k
)




,







=






Σ
_


-
1




(
k
)






U
_

H



(
k
)




(




H
_



(
k
)





V
_



(
k
)





s
_



(
k
)



+


n
_



(
k
)



)



,







=






Σ
_


-
1




(
k
)






U
_

H



(
k
)




(




U
_



(
k
)





Σ
_



(
k
)






V
_

H



(
k
)





V
_



(
k
)





s
_



(
k
)



+


n
_



(
k
)



)



,







=





s
_



(
k
)


+



n
_


su
-
s




(
k
)




,







Eq
.





(
6
)









or

{tilde over (s)}su-s(k)=UH(k)rsu-s(k) and ŝsu-s(k)=Σ−1(k){tilde over (s)}su-s(k),

where

    • {tilde over (s)}su-s(k) is an (NT×1) vector with NS detected data symbols for subband k;
    • ŝsu-s(k) is an (N1) vector with NS recovered data symbols for subband k; and
    • nsu-s(k) is a vector of post-processed noise for subband k.


      The vector {tilde over (s)}su-s(k) is an unnormalized estimate of the data vector s(k), and the vector ŝsu-s(k) is a normalized estimate of s(k). The multiplication by Σ−1(k) in equation (6) accounts for the (possibly different) gains of the NS spatial channels and normalizes the output of the receiver spatial processing so that recovered data symbols with the proper magnitude are provided to a subsequent processing unit.


For the single-user steered mode, the matrix Fsu-s (k) of steering vectors used by the transmitter for each subband may be expressed as:

Fsu-s(k)=V(k).  Eq. (7)

The spatial filter matrix used by the receiver for each subband may be expressed as:

Msu-s(k)=UH(k).  Eq. (8)


The single-user steered mode may be used if the transmitter has channel state information for either the channel response matrix H(k) or the matrix V(k) of right eigenvectors of H(k), for k=1 . . . NF. The transmitter can estimate H(k) or V(k) for each subband based on a pilot transmitted by the receiver, as described below, or may be provided with this information by the receiver via a feedback channel. The receiver can typically obtain H(k) or UH(k) for each subband based on a pilot transmitted by the transmitter. Equation (6) indicates that the NS data symbol streams s(k), distorted only by post-processed channel noise nsu-s (k), may be obtained for the single-user steered mode with the proper spatial processing at both the transmitter and the receiver.


The signal-to-noise-and-interference ratio (SNR) for the single-user steered mode may be expressed as:












γ


su
-
s

,
m




(
k
)


=




P
m



(
k
)





λ
m



(
k
)




σ
2



,

m
=

1












N
S



,




Eq
.





(
9
)









where

    • Pm (k) is the transmit power used for the data symbol transmitted on subband k of wideband eigenmode m;
    • λm(k) is the eigenvalue for subband k of wideband eigenmode m, which is the m-th diagonal element of Λ(k); and
    • γsu-s,m(k) is the SNR for subband k of wideband eigenmode m.


      Single-User Non-Steered Spatial Multiplexing Mode


The single-user non-steered spatial multiplexing mode (or simply, the “single-user non-steered mode”) may be used if the transmitter does have not sufficient channel state information or if the single-user steered mode cannot be supported for any reasons. The single-user non-steered mode transmits NS data symbol streams from NT transmit antennas without any spatial processing at the transmitter.


For the single-user non-steered mode, the matrix Fns(k) of steering vectors used by the transmitter for each subband may be expressed as:

Fns(k)=I.  Eq. (10)

The spatial processing at the transmitter for each subband may be expressed as:

xns(k)=s(k),  Eq. (11)

  • where xs(k) is the transmit symbol vector for the single-user non-steered mode. A “wideband” spatial channel for this mode may be defined as the spatial channel corresponding to a given transmit antenna (i.e., wideband spatial channel m for the single-user non-steered mode includes all subbands of transmit antenna m).


The received symbols obtained by the receiver for each subband may be expressed as:

rns(k)=H(k)xns(k)+n(k)=H(k)s(k)+n(k).  Eq. (12)

The receiver can recover the data vector s(k) using various receiver processing techniques such as a channel correlation matrix inversion (CCMI) technique (which is also commonly referred to as a zero-forcing technique), a minimum mean square error (MMSE) technique, a decision feedback equalizer (DFE), a successive interference cancellation (SIC) technique, and so on.


CCMI Spatial Processing


The receiver can use the CCMI technique to separate out the data symbol streams. A CCMI receiver utilizes a spatial filter having a response of Mccmi(k), for k=1 . . . NF, which can be expressed as:

Mccmi(k)=[HH(k)H(k)]−1HH(k)=R−1(k)H(k).  Eq. (13)


The spatial processing by the CCMI receiver for the single-user non-steered mode may be expressed as:

















s
_

^

ccmi



(
k
)


=






M
_

ccmi



(
k
)






r
_


n





s




(
k
)




,







=






R
_


-
1




(
k
)






H
_

H



(
k
)




(




H
_



(
k
)





s
_



(
k
)



+


n
_



(
k
)



)



,







=





s
_



(
k
)


+



n
_

ccmi



(
k
)




,







Eq
.





(
14
)









where

    • ŝccmi(k) is an (NT×1) vector with NS recovered data symbols for subband k; and
    • nccmi(k)=Mccmi(k)n(k) is the CCMI filtered noise for subband k.


An autocovariance matrix φccmi(k) of the CCMI filtered noise for each subband may be expressed as:
















φ
_

ccmi



(
k
)


=



E


[




n
_

ccmi



(
k
)






n
_

ccmi
H



(
k
)



]



,







=






M
_

ccmi



(
k
)






φ
_

nn



(
k
)






M
_

ccmi
H



(
k
)




,







=




σ
2





R
_


-
1




(
k
)




,







Eq
.





(
15
)








  • where E[x] is the expected value of x. The last equality in equation (15) assumes that the noise n(k) is additive white Gaussian noise (AWGN) with zero mean, a variance of σ2, and an autocovariance matrix of φnn(k)=E[n(k)nH(k)]=σ2I. In this case, the SNR for the CCMI receiver may be expressed as:













γ

ccmi
,
m




(
k
)


=



P
m



(
k
)





r
mm



(
k
)




σ
2




,

m
=

1












N
S



,




Eq
.





(
16
)









where

    • Pm(k) is the transmit power used for the data symbol transmitted on subband k of wideband spatial channel m;
    • rmm(k) is the m-th diagonal element of R(k) for subband k; and
    • γccmi,m(k) is the SNR for subband k of wideband spatial channel m.


      Due to the structure of R(k), the CCMI technique may amplify the noise.


MMSE Spatial Processing


The receiver can use the MMSE technique to suppress crosstalk between the data symbol streams and maximize the SNRs of the recovered data symbol streams. An MMSE receiver utilizes a spatial filter having a response of Mmmse(k), for k=1 . . . NF, which is derived such that the mean square error between the estimated data vector from the spatial filter and the data vector s(k) is minimized. This MMSE criterion may be expressed as:










min

(



M
_


m





m





s





e




(
k
)


)





E


[



(





M
_


m





m





s





e




(
k
)






r
_


n





s




(
k
)



-


s
_



(
k
)



)

H



(





M
_


m





m





s





e




(
k
)






r
_


n





s




(
k
)



-


s
_



(
k
)



)


]


.





Eq
.





(
17
)








The solution to the optimization problem posed in equation (17) may be obtained in various manners. In one exemplary method, the MMSE spatial filter matrix Mmmse(k) for each subband may be expressed as:
















M
_


m





m





s





e




(
k
)


=







H
_

H



(
k
)




[




H
_



(
k
)






H
_

H



(
k
)



+



φ
_

nn



(
k
)



]



-
1



,






=








H
_

H



(
k
)




[




H
_



(
k
)






H
_

H



(
k
)



+


σ
2



I
_



]



-
1


.








Eq
.





(
18
)









The second equality in equation (18) assumes that the noise vector n(k) is AWGN with zero mean and variance of σ2.


The spatial processing by the MMSE receiver for the single-user non-steered mode is composed of two steps. In the first step, the MMSE receiver multiplies the vector rns(k) for the NR received symbol streams with the MMSE spatial filter matrix Mmmse(k) to obtain a vector {tilde over (s)}mmse(k) for NS detected symbol streams, as follows:

















s
_

~


m





m





s





e




(
k
)


=






M
_


m





m





s





e




(
k
)






r
_


n





s




(
k
)




,







=






M
_


m





m





s





e




(
k
)




(




H
_



(
k
)





s
_



(
k
)



+


n
_



(
k
)



)



,







=






Q
_



(
k
)





s
_



(
k
)



+



n
_


m





m





s





e




(
k
)




,







Eq
.





(
19
)








  • where nmmse(k)=Mmmse(k)n(k) is the MMSE filtered noise and Q(k)=Mmmse(k)H(k).


    The NS detected symbol streams are unnormalized estimates of the NS data symbol streams.



In the second step, the MMSE receiver multiplies the vector {tilde over (s)}mmse(k) with a scaling matrix Dmmse−1(k) to obtain a vector ŝmmse(k) for the NS recovered data symbol streams, as follows:

ŝmmse(k)Dmmse−1(k){tilde over (s)}mmse(k)  Eq. (20)

  • where Dmmse(k) is a diagonal matrix whose diagonal elements are the diagonal elements of Q(k), i.e., Dmmse(k)=diag [Q(k)]. The NS recovered data symbol streams are normalized estimates of the NS data symbol streams.


Using the matrix inverse identity, the matrix Q(k) can be rewritten as:















Q
_



(
k
)


=






H
_

H



(
k
)






φ
_

nn

-
1




(
k
)







H
_



(
k
)




[





H
_

H



(
k
)






φ
_

nn

-
1




(
k
)





H
_



(
k
)



+

I
_


]



-
1




,






=






H
_

H



(
k
)








H
_



(
k
)




[





H
_

H



(
k
)





H
_



(
k
)



+


σ
2



I
_



]



-
1


.









Eq
.





(
21
)









The second equality in equation (21) assumes that the noise is AWGN with zero mean and variance of σ2.


The SNR for the MMSE receiver may be expressed as:












γ


m





m





s





e

,
m




(
k
)


=




q
mm



(
k
)



1
-


q
mm



(
k
)







P
m



(
k
)




,

m
=

1












N
S



,




Eq
.





(
22
)









where qmm(k) is the m-th diagonal element of Q(k) for subband k; and


γmmse,m(k) is the SNR for subband k of wideband spatial channel m.


Successive Interference Cancellation Receiver Processing


The receiver can process the NR received symbol streams using the SIC technique to recover the NS data symbol streams. For the SIC technique, the receiver initially performs spatial processing on the NR received symbol streams (e.g., using CCMI, MMSE, or some other technique) and obtains one recovered data symbol stream. The receiver further processes (e.g., demodulates, deinterleaves, and decodes) this recovered data symbol stream to obtain a decoded data stream. The receiver then estimates the interference this stream causes to the other NS−1 data symbol streams and cancels the estimated interference from the NR received symbol streams to obtain NR modified symbol streams. The receiver then repeats the same processing on the NR modified symbol streams to recover another data symbol stream.


For a SIC receiver, the input (i.e., received or modified) symbol streams for stage custom character, where custom character=1 . . . NS, may be expressed as:

custom character(k)=custom character(k)custom character(k)+n(k)=custom character(k)custom character(k)+n(k),  Eq. (23)

where

    • custom character(k) is a vector of NR modified symbols for subband k in stage custom character, and rsic1(k)=rns(k) for the first stage;
    • custom character(k) is a vector of (NTcustom character+1) data symbols not yet recovered for subband k in stage custom character; and
    • custom character(k) is an NR×(NTcustom character+1) reduced channel response matrix for subband k in stage custom character.


Equation (23) assumes that the data symbol streams recovered in the (custom character−1) prior stages are canceled. The dimensionality of the channel response matrix H(k) successively reduces by one column for each stage as a data symbol stream is recovered and canceled. For stage custom character, the reduced channel response matrix custom character(k) is obtained by removing (custom character−1) columns in the original matrix H(k) corresponding to the (custom character−1) data symbol streams previously recovered, i.e., custom character(k)=[custom character(k)custom character(k) . . . hjNT(k)], where hjn(k) is an NR×1 vector for the channel response between transmit antenna jn and the NR receive antennas. For stage custom character, the (custom character−1) data symbol streams recovered in the prior stages are given indices of {j1 j2 . . . custom character}, and the (NTcustom character+1) data symbol streams not yet recovered are given indices of {custom character . . . jNT}.


For stage custom character, the SIC receiver derives a spatial filter matrix custom character(k), for k=1 . . . NF, based on the reduced channel response matrix custom character(k) (instead of the original matrix H(k)) using the CCMI technique as shown in equation (13), the MMSE technique as shown in equation (18), or some other technique. The matrix custom character(k) has dimensionality of (NTcustom character+1)×NR. Since custom character(k) is different for each stage, the spatial filter matrix custom character(k) is also different for each stage.


The SIC receiver multiplies the vector custom character(k) for the NR modified symbol streams with the spatial filter matrix custom character(k) to obtain a vector custom character(k) for (NTcustom character+1) detected symbol streams, as follows:

















s
_

~

sic
l



(
k
)


=






M
_

sic
l



(
k
)






r
_

sic
l



(
k
)




,







=






M
_

sic
l



(
k
)




(





H
_

l



(
k
)






s
_

l



(
k
)



+



n
_

l



(
k
)



)



,







=







Q
_

sic
l



(
k
)






s
_

l



(
k
)



+



n
_

sic
l



(
k
)




,







Eq
.





(
24
)








  • where custom character(k)=custom character is the filtered noise for subband k of stage custom character(k) is a reduced vector of n(k), and custom character(k)=custom character(k).


    The SIC receiver then selects one of the detected symbol streams for recovery. Since only one data symbol stream is recovered in each stage, the SIC receiver can simply derive one (1×NR) spatial filter row vector custom character(k) for the data symbol stream custom character to be recovered in stage custom character. The row vector custom character(k) is one row of the matrix custom character(k). In this case, the spatial processing for stage custom character to recover the data symbol stream custom character may be expressed as:

    custom character(k)=custom character(k)=custom character(k)+custom character(k)n(k),  Eq. (25)

    where custom character is the row of custom character(k) corresponding to data symbol stream custom character.



In any case, the receiver scales the detected symbol stream custom character to obtain a recovered data symbol stream custom character and further processes (e.g., demodulates, deinterleaves, and decodes) the stream custom character to obtain a decoded data stream custom character. The receiver also forms an estimate of the interference this stream causes to the other data symbol streams not yet recovered. To estimate the interference, the receiver re-encodes, interleaves, and symbol maps the decoded data stream custom character in the same manner as performed at the transmitter and obtains a stream of “remodulated” symbols custom character, which is an estimate of the data symbol stream just recovered. The receiver then convolves the remodulated symbol stream with each of NR elements in the channel response vector custom character(k) for stream custom character to obtain NR interference components custom character caused by this stream. The NR interference components are then subtracted from the NR modified symbol streams custom character for stage custom character to obtain NR modified symbol streams custom character(k) for the next stage custom character+1, i.e., custom character(k)=custom character(k)−custom character(k). The modified symbol streams custom character(k) represent the streams that would have been received if the data symbol stream custom character had not been transmitted (i.e., assuming that the interference cancellation was effectively performed).


The SIC receiver processes the NR received symbol streams in NS successive stages. For each stage, the SIC receiver (1) performs spatial processing on either the NR received symbol streams or the NR modified symbol streams from the preceding stage to obtain one recovered data symbol stream, (2) decodes this recovered data symbol stream to obtain a corresponding decoded data stream, (3) estimates and cancels the interference due to this stream, and (4) obtains NR modified symbol streams for the next stage. If the interference due to each data stream can be accurately estimated and canceled, then later recovered data streams experience less interference and may be able to achieve higher SNRs.


For the SIC technique, the SNR of each recovered data symbol stream is dependent on (1) the spatial processing technique (e.g., CCMI or MMSE) used for each stage, (2) the specific stage in which the data symbol stream is recovered, and (3) the amount of interference due to data symbol streams recovered in later stages. The SNR for the SIC receiver with CCMI may be expressed as:












γ


sic
-
ccmi

,
m




(
k
)


=



P
m



(
k
)





r
mm
l



(
k
)




σ
2




,

m
=

1












N
S



,




Eq
.





(
26
)








  • where custom character(k) is the m-th diagonal element of [custom character(k)]−1 for subband k, where custom character(k)=custom character(k).



The SNR for the SIC receiver with MMSE may be expressed as:












γ


sic
-

m





m





s





e


,
m




(
k
)


=




q
mm
l



(
k
)



1
-


q
mm
l



(
k
)







P
m



(
k
)




,

m
=

1












N
S



,




Eq
.





(
27
)








  • where custom character(k) is the m-th diagonal element of custom character(k) for subband k, where custom character(k) is derived as shown in equation (21) but based on the reduced channel response matrix custom character(k) instead of the original matrix H(k).



In general, the SNR progressively improves for data symbol streams recovered in later stages because the interference from data symbol streams recovered in prior stages is canceled. This then allows higher rates to be used for data symbol streams recovered later.


Multi-User Steered Spatial Multiplexing Mode


The multi-user steered spatial multiplexing mode (or simply, the “multi-user steered mode”) supports data transmission from a single transmitter to multiple receivers simultaneously based on “spatial signatures” of the receivers. The spatial signature for a receiver is given by a channel response vector (for each subband) between the NT transmit antennas and each receive antenna at the receiver. The transmitter may obtain the spatial signatures for the receivers as described below. The transmitter may then (1) select a set of receivers for simultaneous data transmission and (2) derive steering vectors for the data symbol streams to be transmitted to the selected receivers such that transmit stream crosstalk is adequately suppressed at the receivers.


The steering vectors for the multi-user steered mode may be derived in various manners. Two exemplary schemes are described below. For simplicity, the following description is for one subband and assumes that each receiver is equipped with one antenna.


In a channel inversion scheme, the transmitter obtains the steering vectors for multiple receivers using channel inversion. The transmitter initially selects NT single-antenna receivers for simultaneous transmission. The transmitter obtains a 1×NT channel response row vector hi (k) for each selected receiver and forms an NT×NT channel response matrix Hsu-s(k) with the NT row vectors for the NT receivers. The transmitter then uses channel inversion to obtain a matrix Fmu-s(k) of NT steering vectors for the NT selected receivers, as follows:

Fmu-s(k)=Hmu-s−1(k).  Eq. (28)


The spatial processing at the transmitter for each subband for the multi-user steered mode may be expressed as:

xmu-s(k)=Fmu-s(k)s(k).  Eq. (29)

where xmu-s(k) is the transmit symbol vector for the multi-user steered mode.


The received symbols at the NT selected receivers for each subband may be expressed as:
















r
_


mu
-
s




(
k
)


=







H
_


mu
-
s




(
k
)






x
_


mu
-
s




(
k
)



+


n
_



(
k
)




,







=







H
_


mu
-
s




(
k
)






F
_


mu
-
s




(
k
)





s
_



(
k
)



+


n
_



(
k
)




,







=





s
_



(
k
)


+


i
_



(
k
)


+


n
_



(
k
)




,







Eq
.





(
30
)








  • where rmu-s(k) is an (NT×1) received symbol vector for subband k at the NT selected receivers, and i(k) represents the crosstalk interference due to imperfect estimation of Fmu-s(k) at the transmitter.


    Each selected receiver would obtain only one entry of the vector rmu-s(k) for each receive antenna. If the spatial processing at the transmitter is effective, then the power in i(k) is small, and each recovered data symbol stream experiences little crosstalk from the (NT−1) other data symbol streams sent to the other receivers.



The transmitter can also transmit a steered pilot to each selected receiver, as described below. Each receiver would then process its steered pilot to estimate the channel gain and phase and coherently demodulate the received symbols from its single antenna with the channel gain and phase estimates to obtain recovered data symbols.


The SNRs achieved for the multi-user steered mode are a function of the autocovariance of the channel response matrix Hmu-s(k). Higher SNRs can be achieved by selecting “compatible” user terminals. Different sets and/or combinations of user terminals may be evaluated, and the set/combination with the highest SNRs may be selected for data transmission.


While the channel inversion scheme is appealing in its simplicity, in general, it will provide poor performance, because preconditioning the data symbol streams with the inverse channel response matrix in equation (29) forces the transmitter to put the majority of its power in the worst eigenmodes of the MIMO channel. Also, in some channels, particularly those with large correlations among the elements of Hmu-s (k), the channel response matrix is less than full rank, and calculating an inverse will not be possible.


In a precoding scheme, the transmitter precodes NT data symbol streams to be sent to the NT selected receivers such that these data symbol streams experience little crosstalk at the receivers. The transmitter can form the channel response matrix Hmu(k) for the NT selected receivers. The transmitter then performs QR factorization on Hmu(k) such that Hmu(k)=Ftri(k)Qmu(k), where Ftri(k) is a lower left triangular matrix and Qmu(k) is a unitary matrix.


The transmitter performs a precoding operation on the data symbol vector to be transmitted, s(k)=[s1(k) s2(k) . . . sNT(k)]T, to obtain a precoded symbol vector a(k)=[a1 (k) a2(k) . . . aNT(k)]T, as follows:












a
l



(
k
)


=


1


f
ll



(
k
)





(



s
l



(
k
)


-




i
=
1


l
-
1






f
li



(
k
)





a
i



(
k
)





)



mod


(

M
/
2

)




,






for





l

=

1












N
T



,




Eq
.





(
31
)









where

    • M is the number of levels, spaced at unit intervals, in the in-phase or quadrature dimension of a square QAM signal constellation; and
    • custom character(k) is the element of Ftri(k) in row i and column j.


      The modulo (mod) operation adds a sufficient number of integer multiples of M to the argument so that the result satisfies custom character(k)ε[−M/2, M/2). After this precoding operation, the transmit symbols are computed by processing the precoded symbol vector a(k) with the unitary steering matrix Qmu(k) to generate the transmit symbol vector xmu-pc(k)=QmuH(k)a(k).


The receive symbol vector for the precoding scheme can be expressed as:

rmu-pc(k)=Hmu(k)QmuH(k)a(k)+n(k)=Ftri(k)a(k)+n(k).  Eq. (32)

It can be shown that Ftri(k)a(k)mod(M/2)=s(k). Thus, the data symbol vector can be estimated as ŝmu-pc(k)=rmu-pc(k)mod(M/2). Each of the NT selected receivers only obtains one of the NT elements of rmu-pc(k) and can estimate the data symbols sent to it by performing the mod(M/2) operation on its received symbols.


The transmitter can also transmit multiple data symbol streams to a multi-antenna receiver in the multi-user steered mode. The channel response matrix Hmu(k) would then include one row vector for each receive antenna of the multi-antenna receiver.


The multi-user steered mode also supports data transmission from multiple multi-antenna transmitters to a single receiver. Each multi-antenna transmitter performs spatial processing on its data symbol stream to steer the stream toward the receiver. Each transmitter also transmits a steered pilot to the receiver. To the receiver, each transmitter appears as a single transmission. The receiver performs spatial processing (e.g., CCMI, MMSE, and so on) to recover the steered data symbol streams from all transmitters.


Multi-User Non-Steered Spatial Multiplexing Mode


The multi-user non-steered spatial multiplexing mode (or simply, the “multi-user non-steered mode”) supports simultaneous data transmission by (1) a single transmitter to multiple receivers (e.g., for the downlink) and (2) multiple transmitters to a single receiver (e.g., for the uplink).


For non-steered transmission from a single transmitter to multiple receivers, the transmitter transmits one data symbol stream from each transmit antenna for a recipient receiver. One or multiple data symbol streams may be transmitted for each recipient receiver. Each recipient receiver includes at least NT receive antennas and can perform spatial processing to isolate and recover its data symbol stream(s). Each receiver desiring data transmission estimates the SNR for each of the NT transmit antennas and sends the NT SNR estimates to the transmitter. The transmitter selects a set of receivers for data transmission based on the SNR estimates from all receivers desiring data transmission (e.g., to maximize the overall throughput).


For non-steered transmission from multiple transmitters to a single receiver, the transmitters transmit data symbol streams from their antennas (i.e., without spatial processing) such that these streams arrive approximately time-aligned at the receiver. The receiver can estimate the channel response matrix for all of the transmitters as if they were one transmitter. The receiver can recover multiple data symbol streams transmitted by these multiple transmitters using any of the techniques described above for the single-user non-steered mode (e.g., CCMI, MMSE, and SIC techniques).


Spatial Processing


Table 2 summarizes the spatial processing at the transmitter and the receiver for the four spatial multiplexing modes described above. For the non-steered modes, receiver processing techniques other than CCMI and MMSE may also be used. The last column in Table 2 indicates whether or not the SIC technique may be used at the receiver.













TABLE 2





Spatial
Transmit
Receive




Multiplexing Mode
F(k)
M(k)
Scaling
SIC







Single-User Steered
V(k)
UH(k)
Σ−1(k)
no


Single-User
I
Mccmi(k)

yes


Non-Steered

Mmmse(k)
Dmmse−1(k)


Multi-User Steered
Hmu-s−1(k)


no


(single transmitter to


multiple receivers)


Multi-User
I
Mccmi(k)

yes


Non-Steered

Mmmse(k)
Dmmse−1(k)


(multiple transmitters


to single receiver)










For simplicity, the spatial processing for the multi-user steered mode from multiple transmitters to a single receiver and the multi-user non-steered mode from a single transmitter to multiple receivers are not shown in Table 2.


In the following description, a wideband spatial channel can correspond to (1) a wideband eigenmode, for a steered spatial multiplexing mode, (2) a transmit antenna, for a non-steered spatial multiplexing mode, or (3) a combination of one or more spatial channels of one or more subbands. A wideband spatial channel can be used to transmit one independent data stream.


MIMO System



FIG. 1 shows a multiple-access MIMO system 100 with a number of access points (APs) 110 providing communication for a number of user terminals (UTs) 120. For simplicity, only two access points 110a and 110b are shown in FIG. 1. An access point is generally a fixed station that communicates with the user terminals and may also be referred to as a base station or some other terminology. A user terminal may be fixed or mobile and may also be referred to as a mobile station, a wireless device, or some other terminology. A system controller 130 couples to and provides coordination and control for access points 110.


MIMO system 100 may be a time division duplex (TDD) system or a frequency division duplex (FDD) system. The downlink and uplink (1) share the same frequency band for a TDD system and (2) use different frequency bands for an FDD system. The following description assumes that MIMO system 100 is a TDD system.


MIMO system 100 utilizes a set of transport channels to transmit different types of data. The transport channels may be implemented in various manners.



FIG. 2 shows an exemplary frame and channel structure 200 that may be used for MIMO system 100. Data transmission occurs in TDD frames. Each TDD frame spans a predetermined time duration (e.g., 2 msec) and is partitioned into a downlink phase and an uplink phase. Each phase is further partitioned into multiple segments 210, 220, 230, 240, and 250 for multiple transport channels.


In the downlink phase, a broadcast channel (BCH) carries a beacon pilot 214, a MIMO pilot 216, and a BCH message 218. The beacon pilot is used for timing and frequency acquisition. The MIMO pilot is used for channel estimation. The BCH message carries system parameters for the user terminals. A forward control channel (FCCH) carries scheduling information for assignments of downlink and uplink resources and other signaling for the user terminals. A forward channel (FCH) carries FCH protocol data units (PDUs) on the downlink. An FCH PDU 232a includes a pilot 234a and a data packet 236a, and an FCH PDU 232b includes only a data packet 236b. In the uplink phase, a reverse channel (RCH) carries RCH PDUs on the uplink. An RCH PDU 242a includes only a data packet 246a, and an RCH PDU 242b includes a pilot 244b and a data packet 246b. A random access channel (RACH) is used by the user terminals to gain access to the system and to send short messages on the uplink. An RACH PDU 252 sent on the RACH includes a pilot 254 and a message 256.



FIG. 3 shows a block diagram of an access point 110x and two user terminals 120x and 120y in MIMO system 100. Access point 110x is one of the access points in FIG. 1 and is equipped with multiple (Nap) antennas 324a through 324ap. User terminal 120x is equipped with a single antenna 352x, and user terminal 120y is equipped with multiple (Nut) antennas 352a through 352ut.


On the downlink, at access point 110x, a TX data processor 310 receives traffic data for one or more user terminals from a data source 308, control data from a controller 330, and possibly other data from a scheduler 334. The various types of data may be sent on different transport channels. TX data processor 310 processes (e.g., encodes, interleaves, and symbol maps) the different types of data based on one or more coding and modulation schemes to obtain NS streams of data symbols. As used herein, a “data symbol” refers to a modulation symbol for data, and a “pilot symbol” refers to a modulation symbol for pilot. A TX spatial processor 320 receives the NS data symbol streams from TX data processor 310, performs spatial processing on the data symbols with matrices Fap(k), for k=1 . . . NF, multiplexes in pilot symbols, and provides Nap streams of transmit symbols for the Nap antennas. The matrices Fap(k) are derived in accordance with the spatial multiplexing mode selected for use. The processing by TX data processor 310 and TX spatial processor 320 is described below.


Each modulator (MOD) 322 receives and processes a respective transmit symbol stream to obtain a stream of OFDM symbols, and further conditions (e.g., amplifies, filters, and frequency upconverts) the OFDM symbol stream to generate a downlink signal. Nap modulators 322a through 322ap provide Nap downlink signals for transmission from Nap antennas 324a through 324ap, respectively, to the user terminals.


At each user terminal 120, one or multiple antennas 352 receive the Nap downlink signals, and each antenna provides a received signal to a respective demodulator (DEMOD) 354. Each demodulator 354 performs processing complementary to that performed by modulator 322 and provides a stream of received symbols. For single-antenna user terminal 120x, an RX spatial processor 360x performs coherent demodulation of the received symbol stream from a single demodulator 354x and provides one stream of recovered data symbols. For multi-antenna user terminal 120y, RX spatial processor 360y performs spatial processing on Nut received symbol streams from Nut demodulators 354 with spatial filter matrices Mut(k), for k=1 . . . NF, and provides Nut streams of recovered data symbols. In any case, each recovered data symbol stream {ŝm} is an estimate of a data symbol stream {Sm} transmitted by access point 110x to that user terminal 120. An RX data processor 370 receives and demultiplexes the recovered data symbols to the proper transport channels. The recovered data symbols for each transport channel are then processed (e.g., demapped, deinterleaved, and decoded) to obtain decoded data for that transport channel. The decoded data for each transport channel may include recovered traffic data, control data, and so on, which may be provided to a data sink 372 for storage and/or a controller 380 for further processing.


At each user terminal 120, a channel estimator 378 estimates the downlink channel response and provides channel estimates, which may include channel gain estimates, SNR estimates, and so on. Controller 380 receives the channel estimates, derives the vectors and/or coefficients used for spatial processing on the transmit and receive paths, and determines a suitable rate for each data symbol stream on the downlink. For example, controller 380y for multi-antenna user terminal 120y may derive the spatial filter matrices Mut(k) for the downlink and the matrices Fut(k) of steering vectors for the uplink based on downlink channel response matrices Hdn(k), for k=1 . . . NF. Controller 380 may also receive the status of each packet/frame received on the downlink and assemble feedback information for access point 110x. The feedback information and uplink data are processed by a TX data processor 390, spatially processed by a TX spatial processor 392 (if present at user terminal 120), multiplexed with pilot symbols, conditioned by one or more modulators 354, and transmitted via one or more antennas 352 to access point 110x.


At access point 110x, the transmitted uplink signals are received by antennas 324, demodulated by demodulators 322, and processed by an RX spatial processor 340 and an RX data processor 342 in a complementary manner to that performed at user terminals 120. The recovered feedback information is provided to controller 330 and scheduler 334. Scheduler 334 may use the feedback information to perform a number of functions such as (1) scheduling a set of user terminals for data transmission on the downlink and uplink and (2) assigning the available downlink and uplink resources to the scheduled terminals.


Controllers 330 and 380 control the operation of various processing units at access point 110x and user terminal 120, respectively. For example, controller 380 may determine the highest rates supported by the spatial channels on the downlink for user terminal 120. Controller 330 may select the rate, payload size, and OFDM symbol size for each spatial channel of each scheduled user terminal.


The processing at access point 110x and user terminals 120x and 120y for the uplink may be the same or different from the processing for the downlink. For clarity, the processing for the downlink is described in detail below.



FIG. 4 shows a block diagram of an embodiment of TX data processor 310 at access point 110x. For this embodiment, TX data processor 310 includes one set of encoder 412, channel interleaver 414, and symbol mapping unit 416 for each of the NS data streams. For each data stream {dm}, where m=1 . . . NS, an encoder 412 receives and codes the data stream based on a coding scheme selected for that stream and provides code bits. The coding scheme may include CRC, convolutional, Turbo, low density parity check (LDPC), block, and other coding, or a combination thereof. A channel interleaver 414 interleaves (i.e., reorders) the code bits based on an interleaving scheme. A symbol mapping unit 416 maps the interleaved bits based on a modulation scheme selected for that stream and provides a stream of data symbols {sm}. Unit 416 groups each set of B interleaved bits to form a B-bit binary value, where B≧1, and further maps each B-bit binary value to a specific data symbol based on the selected modulation scheme (e.g., QPSK, M-PSK, or M-QAM, where M=2B). The coding and modulation for each data stream are performed in accordance with coding and modulation controls provided by controller 330.



FIG. 5 shows a block diagram of an embodiment of TX spatial processor 320 and modulators 322a through 322ap at access point 110x. For this embodiment, TX spatial processor 320 includes NS demultiplexers (Demux) 510a through 510s, NF TX subband spatial processors 520a through 520f, and Nap multiplexers (Mux) 530a through 530ap. Each demultiplexer 510 receives a respective data symbol stream {sm} from TX spatial processor 320, demultiplexes the stream into NF data symbol substreams for the NF subbands, and provides the NF substreams to NF spatial processors 520a through 520f. Each spatial processor 520 receives NS data symbol substreams for its subband from NS demultiplexers 510a through 510s, performs transmitter spatial processing on these substreams, and provides Nap transmit symbol substreams for the Nap access point antennas. Each spatial processor 520 multiplies a data vector sdn(k) with a matrix Fap(k) to obtain a transmit vector xdn(k). The matrix Fap(k) is equal to (1) a matrix Vdn(k) of right eigenvectors of Hdn(k) for the single-user steered mode, (2) the matrix Fmu(k) for the multi-user steered mode, or (3) the identity matrix I for the single-user non-steered mode.


Each multiplexer 530 receives NF transmit symbol substreams for its transmit antenna from NF spatial processors 520a through 520f, multiplexes these substreams and pilot symbols, and provides a transmit symbol stream {xj} for its transmit antenna. The pilot symbols may be multiplexed in frequency (i.e., on some subbands), in time (i.e., in some symbol periods), and/or in code space (i.e., with an orthogonal code). Nap multiplexers 530a through 530ap provide Nap transmit symbol streams {xj}, for j=1 . . . Nap, for Nap antennas 324a through 324ap.


For the embodiment shown in FIG. 5, each modulator 322 includes an inverse fast Fourier transform (IFFT) unit 542, a cyclic prefix generator 544, and a TX RF unit 546. IFFT unit 542 and cyclic prefix generator 544 form an OFDM modulator. Each modulator 322 receives a respective transmit symbol stream {xj} from TX spatial processor 320 and groups each set of NF transmit symbols for the NF subbands. IFFT unit 542 transforms each set of NF transmit symbols to the time domain using an NF-point inverse fast Fourier transform and provides a corresponding transformed symbol that contains NF chips. Cyclic prefix generator 544 repeats a portion of each transformed symbol to obtain a corresponding OFDM symbol that contains NF+Ncp chips. The repeated portion (i.e., the cyclic prefix) ensures that the OFDM symbol retains its orthogonal properties in the presence of multipath delay spread caused by frequency selective fading. TX RF unit 546 receives and conditions the OFDM symbol stream from generator 544 to generate a downlink modulated signal. Nap downlink modulated signals are transmitted from Nap antennas 324a through 324ap, respectively.



FIG. 6 shows a block diagram of an embodiment of demodulators 354a through 354ut and RX spatial processor 360y for multi-antenna user terminal 120y. At user terminal 120y, Nut antennas 352a through 352ut receive the Nap modulated signals transmitted by access point 110x and provide Nut received signals to Nut demodulators 354a through 354ut, respectively. Each demodulator 354 includes an RX RF unit 612, a cyclic prefix removal unit 614, and a fast Fourier transform (FFT) unit 616. Units 614 and 616 form an OFDM demodulator. Within each demodulator 354, RX RF unit 612 receives, conditions, and digitizes a respective received signal and provides a stream of chips. Cyclic prefix removal unit 614 removes the cyclic prefix in each received OFDM symbol to obtain a received transformed symbol. FFT unit 616 then transforms each received transformed symbol to the frequency domain with an NF-point fast Fourier transform to obtain NF received symbols for the NF subbands. FFT unit 616 provides a stream of received symbols to RX spatial processor 360y and received pilot symbols to channel estimator 378y.


For the embodiment shown in FIG. 6, RX spatial processor 360y includes Nat demultiplexers 630a through 630ut for the Nut antennas at user terminal 120y, NF RX subband spatial processors 640a through 640f and NF scaling units 642a through 642f for the NF subbands, and NS multiplexers 650a through 650s for the NS data streams. RX spatial processor 360y obtains Nut received symbol streams {ri}, for i=1 . . . Nut, from demodulators 354a through 354ut. Each demultiplexer 630 receives a respective received symbol stream {ri}, demultiplexes the stream into NF received symbol substreams for the NF subbands, and provides the NF substreams to NF spatial processors 640a through 640f. Each spatial processor 640 obtains Nut received symbol substreams for its subband from Nut demultiplexers 630a through 630ut, performs receiver spatial processing on these substreams, and provides NS detected symbol substreams for its subband. Each spatial processor 640 multiplies a received vector rdn(k) with a matrix Mut(k) to obtain a detected symbol vector {tilde over (s)}dn(k). The matrix Mut(k) is equal to (1) a matrix UdnH(k) of left eigenvectors of Hdn(k) for the single-user steered mode or (2) the matrix Mccmi(k), Mmmse(k), or some other matrix for the single-user non-steered mode.


Each scaling unit 642 receives NS detected symbol substreams for its subband, scales these substreams, and provides NS recovered data symbol substreams for its subband. Each scaling unit 642 performs the signal scaling of the detected symbol vector {tilde over (s)}dn(k) with a diagonal matrix Dut−1(k) and provides the recovered data symbol vector ŝdn(k). Each multiplexer 650 receives and multiplexes NF recovered data symbol substreams for its data stream from NF scaling units 642a through 642f and provides a recovered data symbol stream. NS multiplexers 650a through 650s provide NS recovered data symbol streams {ŝm}, for m=1 . . . NS.



FIG. 7 shows a block diagram of an embodiment of RX data processor 370y at user terminal 120y. RX data processor 370y includes one set of symbol demapping unit 712, channel deinterleaver 714, and decoder 716 for each of the NS data streams. For each recovered data symbol stream {ŝm}, where m=1 . . . NS, a symbol demapping unit 712 demodulates the recovered data symbols in accordance with the modulation scheme used for that stream and provides demodulated data. A channel deinterleaver 714 deinterleaves the demodulated data in a manner complementary to the interleaving performed on that stream by access point 110x. A decoder 716 then decodes the deinterleaved data in a manner complementary to the encoding performed by access point 110x on that stream. For example, a Turbo decoder or a Viterbi decoder may be used for decoder 716 if Turbo or convolutional coding, respectively, is performed at access point 110x. Decoder 716 provides a decoded packet for each received data packet. Decoder 716 further checks each decoded packet to determine whether the packet is decoded correctly or in error and provides the status of the decoded packet. The demodulation and decoding for each recovered data symbol stream are performed in accordance with demodulation and decoding controls provided by controller 380y.



FIG. 8 shows a block diagram of an RX spatial processor 360z and an RX data processor 370z, which implement the SIC technique. RX spatial processor 360z and RX data processor 370z implement NS successive (i.e., cascaded) receiver processing stages for NS data symbol streams. Each of stages 1 to NS−1 includes a spatial processor 810, an interference canceller 820, an RX data stream processor 830, and a TX data stream processor 840. The last stage includes only a spatial processor 810s and an RX data stream processor 830s. Each RX data stream processor 830 includes a symbol demapping unit 712, a channel deinterleaver 714, and a decoder 716, as shown in FIG. 7. Each TX data stream processor 840 includes an encoder 412, a channel interleaver 414, and a symbol mapping unit 416, as shown in FIG. 4.


For stage 1, spatial processor 810a performs receiver spatial processing on the Nut received symbol streams and provides one recovered data symbol stream {ŝj1}, where the subscript j1 denotes the access point antenna used to transmit the data symbol stream {sj1}. RX data stream processor 830a demodulates, deinterleaves, and decodes the recovered data symbol stream {ŝj1} and provides a corresponding decoded data stream {{circumflex over (d)}J1}. TX data stream processor 840a encodes, interleaves, and modulates the decoded data stream {{circumflex over (d)}j1} in the same manner performed by access point 110x for that stream and provides a remodulated symbol stream {{hacek over (s)}j1}. Interference canceller 820a performs spatial processing on the remodulated symbol stream {{hacek over (s)}j1} in the same manner (if any) performed by access point 110x and further processes the result with the channel response matrix Hdn(k) to obtain Nut interference components due to the data symbol stream {sj1}. The Nut interference components are subtracted from the Nut received symbol streams to obtain Nut modified symbol streams, which are provided to stage 2.


Each of stages 2 through NS−1 performs the same processing as stage 1, albeit on the Nut modified symbol streams from the preceding stage instead of the Nut received symbol streams. The last stage performs spatial processing and decoding on the Nut modified symbol streams from stage NS−1 and does not perform interference estimation and cancellation.


Spatial processors 810a through 810s may each implement the CCMI, MMSE, or some other receiver processing technique. Each spatial processor 810 multiplies an input (received or modified) symbol vector custom character(k) with a matrix custom character(k) to obtain a detected symbol vector custom character(k), selects and scales one of the detected symbol streams, and provides the scaled symbol stream as the recovered data symbol stream for that stage. The matrix custom character(k) is derived based on a reduced channel response matrix custom character(k) for the stage.


The processing units at access point 110x and user terminal 120y for the uplink may be implemented as described above for the downlink. TX data processor 390y and TX spatial processor 392y may be implemented with TX data processor 310 in FIG. 4 and TX spatial processor 320 in FIG. 5, respectively. RX spatial processor 340 may be implemented with RX spatial processor 360y or 360z, and RX data processor 342 may be implemented with data processor 370y or 370z.


For single-antenna user terminal 120x, RX spatial processor 360x performs coherent demodulation of one received symbol stream with channel estimates to obtain one recovered data symbol stream.


Channel Estimation


The channel response of the downlink and uplink may be estimated in various manners such as with a MIMO pilot or a steered pilot. For a TDD MIMO system, certain techniques may be used to simplify the channel estimation.


For the downlink, access point 110x can transmit a MIMO pilot to user terminals 120. The MIMO pilot comprises Nap pilot transmissions from Nap access point antennas, with the pilot transmission from each antenna being “covered” with a different orthogonal sequence (e.g., a Walsh sequence). Covering is a process whereby a given modulation symbol (or a set of L modulation symbols with the same value) to be transmitted is multiplied by all L chips of an L-chip orthogonal sequence to obtain L covered symbols, which are then transmitted. The covering achieves orthogonality among the Nap pilot transmissions sent from the Nap access point antennas and allows the user terminals to distinguish the pilot transmission from each antenna.


At each user terminal 120, channel estimator 378 “decovers” the received pilot symbols for each user terminal antenna i with the same Nap orthogonal sequences used by access point 110x for the Nap antennas to obtain estimates of the complex channel gain between user terminal antenna i and each of the Nap access point antennas. Decovering is complementary to covering and is a process whereby received (pilot) symbols are multiplied by the L chips of the L-chip orthogonal sequence to obtain L decovered symbols, which are then accumulated to obtain an estimate of the transmitted (pilot) symbol. Channel estimator 378 performs the same pilot processing for each subband used for pilot transmission. If pilot symbols are transmitted on only a subset of the NF subbands, then channel estimator 378 can perform interpolation on the channel response estimates for subbands with pilot transmission to obtain channel response estimates for subbands without pilot transmission. For single-antenna user terminal 120x, channel estimator 378x provides estimated downlink channel response vectors ĥdn(k), for k=1 . . . NF, for the single antenna 352. For multi-antenna user terminal 120y, channel estimator 378y performs the same pilot processing for all Nut antennas 352a through 352ut and provides estimated downlink channel response matrices Ĥdn(k), for k=1 . . . NF. Each user terminal 120 can also estimate the noise variance for the downlink based on the received pilot symbols and provides the downlink noise estimate, {circumflex over (σ)}dn2.


For the uplink, multi-antenna user terminal 120y can transmit a MIMO pilot that can be used by access point 110x to estimate the uplink channel response Ĥup(k) for user terminal 120y. Single-antenna user terminal 120x can transmit a pilot from its single antenna. Multiple single-antenna user terminals 120 can transmit orthogonal pilots simultaneously on the uplink, where orthogonality may be achieved in time and/or frequency. Time orthogonality can be obtained by having each user terminal cover its uplink pilot with a different orthogonal sequence assigned to the user terminal Frequency orthogonality can be obtained by having each user terminal transmit its uplink pilot on a different set of subbands. The simultaneous uplink pilot transmissions from multiple user terminals should be approximately time-aligned at access point 120x (e.g., time-aligned to within the cyclic prefix).


For a TDD MIMO system, a high degree of correlation normally exists between the channel responses for the downlink and uplink since these links share the same frequency band. However, the responses of the transmit/receive chains at the access point are typically not the same as the responses of the transmit/receive chains at the user terminal. If the differences are determined and accounted for via calibration, then the overall downlink and uplink channel responses may be assumed to be reciprocal (i.e., transpose) of each other.



FIG. 9 shows the transmit/receive chains at access point 110x and user terminal 120y. At access point 110x, the transmit path is modeled by an Nap×Nap matrix Tap(k) and the receive path is modeled by an Nap×Nap matrix Rap(k). At user terminal 120y, the receive path is modeled by an Nut×Nut matrix Rut(k) and the transmit path is modeled by an Nut×Nut matrix Tut(k). The received symbol vectors for the downlink and uplink for each subband may be expressed as:

rdn(k)=Rut(k)H(k)Tap(k)xdn(k), and
rup(k)=Rap(k)HT(k)Tat(k)xap(k),  Eq. (33)

  • where “T” denotes the transpose. Equation (34) assumes that the downlink and uplink are transpose of one another. The “effective” downlink and uplink channel responses, Hedn(k) and Heup(k), for each subband include the responses of the transmit and receive chains and may be expressed as:

    Hedn(k)=Rut(k)H(k)Tap(k) and Heup(k)=Rap(k)HT(k)Tut(k).  Eq. (34)

    The effective downlink and uplink channel responses are not reciprocal of one other (i.e., Hedn(k)≠HeupT(k)) if the responses of the downlink and uplink transmit/receive chains are not equal to each other.


Access point 110x and user terminal 120y can perform calibration to obtain correction matrices Kap(k) and Kut(k) for each subband, which may be expressed as:

Kap(k)=Tap−1(k)Rap(k) and Kut(k)=Tut−1(k)Rut(k).  Eq. (35)

The correction matrices may be obtained by transmitting MIMO pilots on both the downlink and uplink and deriving the correction matrices using MMSE criterion or some other techniques. The correction matrices Kap(k) and Kut(k) are applied at access point 110x and user terminal 120y, respectively, as shown in FIG. 9. The “calibrated” downlink and uplink channel responses, Hcdn(k) and Hcup(k), are then reciprocal of one another and may be expressed as:

Hcup(k)=Hup(k)Kut(k)=(Hdn(k)Kap(k))T=HcdnT(k).  Eq. (36)


The singular value decomposition of the calibrated uplink and downlink channel response matrices, Hcup(k) and Hcdn(k), for each subband may be expressed as:

Hcup(k)=Uap(k)Σ(k)VutH(k), and
Hcda(k)=Vut*(k)Σ(k)UapH(k).  Eq. (37)

As shown in equation set (38), the matrices Vut*(k) and Uap*(k) of left and right eigenvectors of Hcdn(k) are the complex conjugate of the matrices Vut(k) and Uap(k) of right and left eigenvectors of Hcup(k). The matrix Uap(k) can be used by access point 110x for both transmit and receive spatial processing. The matrix Vut(k) can be used by user terminal 120y for both transmit and receive spatial processing.


Because of the reciprocal nature of the MIMO channel for the TDD MIMO system, and after calibration has been performed to account for the differences in the transmit/receive chains, the singular value decomposition only needs to be performed by either user terminal 120y or access point 110x. If performed by user terminal 120y, then the matrices Vut(k), for k=1 . . . NF, are used for spatial processing at the user terminal and the matrix Uap(k), for k=1 . . . NF, may be provided to the access point in either a direct form (e.g., by sending entries of the matrices Uap(k)) or an indirect form (e.g., via a steered pilot). In actuality, user terminal 120y can only obtain Ĥcdn(k), which is an estimate of Hcdn(k), and can only derive {circumflex over (V)}ut(k), {circumflex over (Σ)}(k) and Ûap(k), which are estimates of Vut(k), Σ(k) and Uap(k), respectively. For simplicity, the description herein assumes channel estimation without errors.


An uplink steered pilot sent by user terminal 120y may be expressed as:

xup,m(k)=Kut(k)vut,m(k)p(k),  Eq. (38)

  • where vup,m(k) is the m-th column of Vut(k) and p(k) is the pilot symbol. The received uplink steered pilot at access point 110x may be expressed as:

    rup,m(k)=uap,m(kmp(k)+nup(k).  Eq. (39)

    Equation (40) indicates that access point 110x can obtain the matrix Uap(k), one vector at a time, based on the uplink steered pilot from user terminal 120y.


A complementary process may also be performed whereby user terminal 120y transmits a MIMO pilot on the uplink, and access point 110x performs singular value decomposition and transmits a steered pilot on the downlink. Channel estimation for the downlink and uplink may also be performed in other manners.


At each user terminal 120, channel estimator 378 can estimate the downlink channel response (e.g., based on a MIMO pilot or a steered pilot sent by access point 110x) and provide downlink channel estimates to controller 380. For single-antenna user terminal 120x, controller 380x can derive the complex channel gains used for coherent demodulation. For multi-antenna user terminal 120y, controller 380y can derive the matrix Mut(k) used for receive spatial processing and the matrix Fut(k) used for transmit spatial processing based on the downlink channel estimates. At access point 110x, channel estimator 328 can estimate the uplink channel response (e.g., based on a steered pilot or a MIMO pilot sent by user terminal 120) and provide uplink channel estimates to controller 380. Controller 380 can derive the matrix Fap(k) used for transmit spatial processing and the matrix Map(k) used for receive spatial processing based on the uplink channel estimates.



FIG. 9 shows the spatial processing at access point 110x and user terminal 120y for the downlink and uplink for one subband k. For the downlink, within TX spatial processor 320 at access point 110x, the data vector sdn(k) is first multiplied with the matrix Fap(k) by a unit 910 and further multiplied with the correction matrix Kap(k) by a unit 912 to obtain the transmit vector xdn(k). The vector xdn(k) is processed by a transmit chain 914 within modulators 322 and transmitted over the MIMO channel to user terminal 120y. Units 910 and 912 perform the transmit spatial processing for the downlink and may be implemented within TX subband spatial processor 520 in FIG. 5.


At user terminal 120y, the downlink signals are processed by a receive chain 954 within demodulators 354 to obtain the receive vector rdn(k). Within RX spatial processor 360y, the receive vector rdn(k) is first multiplied with the matrix Mut(k) by a unit 956 and further scaled with the inverse diagonal matrix Dut−1(k) by a unit 958 to obtain the vector ŝdn(k), which is an estimate of the data vector sdn(k). Units 956 and 958 perform the receive spatial processing for the downlink and may be implemented within RX subband spatial processor 640 in FIG. 6.


For the uplink, within TX spatial processor 392y at user terminal 120y, the data vector sup(k) is first multiplied with the matrix Fut(k) by a unit 960 and further multiplied with the correction matrix Kut(k) by a unit 962 to obtain the transmit vector xup(k). The vector xup(k) is processed by a transmit chain 964 within modulators 354 and transmitted over the MIMO channel to access point 110x. Units 960 and 962 perform the transmit spatial processing for the uplink.


At access point 110x, the uplink signals are processed by a receive chain 924 within demodulators 322 to obtain the receive vector rup(k). Within RX spatial processor 340, the receive vector rup(k) is first multiplied with the matrix Map(k) by a unit 926 and further scaled with the inverse diagonal matrix Dap−1(k) by a unit 928 to obtain the vector ŝup(k), which is an estimate of the data vector sup(k). Units 926 and 928 perform the receive spatial processing for the uplink.


Spatial Processing for TDD MIMO System


Table 3 summarizes exemplary pilot transmission and spatial processing performed by the access point and the user terminals for data transmission on the downlink and uplink for various spatial multiplexing modes in the TDD MIMO system. For the single-user steered mode, the access point transmits a MIMO pilot to allow the user terminal to estimate the downlink channel response. The user terminal transmits a steered pilot to allow the access point to estimate the uplink channel response. The access point performs transmit and receive spatial processing with Uap(k). The user terminal performs transmit and receive spatial processing with Vut(k).


For the single-user non-steered mode, for downlink data transmission, the access point transmits a MIMO pilot from all antennas and a data symbol stream from each antenna. The user terminal estimates the downlink channel response with the MIMO pilot and performs receiver spatial processing using the downlink channel estimates. The complementary processing occurs for uplink data transmission.











TABLE 3





Spatial
Downlink Data
Uplink Data


Multiplexing Mode
Transmission
Transmission







Single-User
AP transmits MIMO pilot
AP transmits MIMO pilot


Steered
UT transmits steered pilot
UT transmits steered pilot



AP transmits data with Uap(k)
UT transmits data with Vut(k)



UT receives data with Vut(k)
AP receives data with Uap(k)


Single-User
AP transmits MIMO pilot
UT transmits MIMO pilot


Non-Steered
AP transmits data from each antenna
UT transmits data from each antenna



UT uses CCMI, MMSE, etc.
AP uses CCMI, MMSE, etc.


Multi-User
UTs transmit orthogonal pilot
AP transmits MIMO pilot


Steered
AP transmits steered data
UTs transmit steered pilot



AP transmits steered pilot
UTs transmit steered data



UTs receive with steered pilot
AP uses CCMI, MMSE, etc.


Multi-User
AP transmits MIMO pilot
UTs transmit orthogonal pilot


Non-Steered
UTs send rate for each AP antenna
AP selects compatible UTs



AP transmits data from each antenna
UTs transmits data from each



UTs use CCMI, MMSE, etc.
antenna AP uses CCMI, MMSE, etc.









For the multi-user steered mode, for downlink data transmission to single-antenna and/or multi-antenna user terminals, the user terminals transmit orthogonal pilots on the uplink to allow the access point to estimate the downlink channel response. A single-antenna user terminal transmits an unsteered pilot, and a multi-antenna user terminal transmits a steered pilot. The access point derives downlink steering vectors based on the orthogonal uplink pilots, and uses the steering vectors to transmit steered pilots and steered data symbol streams to the selected user terminals. Each user terminal uses the steered pilot to receive the steered data symbol stream sent to the user terminal. For uplink data transmission from multi-antenna user terminals, the access point transmits a MIMO pilot. Each multi-antenna user terminal transmits a steered pilot and a steered data symbol stream on the uplink. The access point performs receiver spatial processing (e.g., CCMI, MMSE, and so on) to recover the data symbol streams.


For the multi-user non-steered mode, for downlink data transmission to multi-antenna user terminals, the access point transmits a MIMO pilot on the downlink. Each user terminal determines and sends back the rate it can receive from each access point antenna. The access point selects a set of user terminals and transmits data symbol streams for the selected user terminals from the access point antennas. Each multi-antenna user terminal performs receiver spatial processing (e.g., CCMI, MMSE, and so on) to recover its data symbol stream. For uplink data transmission from single-antenna and/or multi-antenna user terminals, the user terminals transmit orthogonal (unsteered) pilots on the uplink. The access point estimates the uplink channel response based on the uplink pilots and selects a set of compatible user terminals. Each selected user terminal transmits a data symbol stream from a user terminal antenna. The access point performs receiver spatial processing (e.g., CCMI, MMSE, and so on) to recover the data symbol streams.


Rate Selection


Each data stream for the downlink and uplink is transmitted on a wideband spatial channel m using one of the spatial multiplexing modes. Each data stream is also transmitted at a rate that is selected such that the target level of performance (e.g., 1 percent packet error rate (PER)) can be achieved for that stream. The rate for each data stream can be determined based on the SNR achieved at the receiver for that stream (i.e., the received SNR), where the SNR is dependent on the spatial processing performed at the transmitter and receiver, as described above.


In an exemplary rate selection scheme, the determine the rate for wideband spatial channel m, an SNR estimate, γm(k), (e.g., in units of dB) for each subband k of the wideband spatial channel is first obtained, as described above. An average SNR, γavg, is then computed for wideband spatial channel m, as follows:










γ

avg
,
m


=


1

N
F







k
=
1


N
F






γ
m



(
k
)


.







Eq
.





(
40
)









The variance of the SNR estimates, σγm2, is also computed as follows:










σ

γ
m

2

=


1


N
F

-
1







k
=
1


N
F






(



γ
m



(
k
)


-

γ

avg
,
m



)

2

.







Eq
.





(
41
)









An SNR back-off factor, γbo,m, is determined based on a function F(γavg,mγm2) of the average SNR and the SNR variance. For example, the function F(γavg,mγm2)=Kb·σγm2 may be used, where Kb is a scaling factor that may be selected based on one or more characteristics of the MIMO system such as the interleaving, packet size, and/or coding scheme used for the data stream. The SNR back-off factor accounts for variation in SNRs across the wideband spatial channel. An operating SNR, γop,m, for wideband spatial channel m is next computed, as follows:

γop,mavg,m−γbo.m.  Eq. (42)

The rate for the data stream is then determined based on the operating SNR. For example, a look-up table (LUT) may store a set of rates supported by the MIMO system and their required SNRs. The required SNR for each rate may be determined by computer simulation, empirical measurement, and so on, and based on an assumption of an AWGN channel. The highest rate in the look-up table with a required SNR that is equal to or lower than the operating SNR is selected as the rate for the data stream sent on wideband spatial channel m.


Various other rate selection schemes may also be used.


Closed-Loop Rate Control


Closed-loop rate control may be used for each of the data streams transmitted on multiple wideband spatial channels. Closed-loop rate control may be achieved with one or multiple loops.



FIG. 10 shows a block diagram of an embodiment of a closed-loop rate control mechanism 1000, which comprises an inner loop 1010 that operates in conjunction with an outer loop 1020. Inner loop 1010 estimates the channel conditions and determines the rate supported by each wideband spatial channel. Outer loop 1020 estimates the quality of the data transmission received on each wideband spatial channel and adjusts the operation of the inner loop accordingly. For simplicity, the operation of loops 1010 and 1020 for one downlink wideband spatial channel m is shown in FIG. 10 and described below.


For inner loop 1010, channel estimator 378 at user terminal 120 estimates wideband spatial channel m and provides channel estimates (e.g., channel gain estimates and noise variance estimate). A rate selector 1030 within controller 380 determines the rate supported by wideband spatial channel m based on (1) the channel estimates from channel estimator 378, (2) an SNR back-off factor and/or a rate adjustment for wideband spatial channel m from a quality estimator 1032, and (3) a look-up table (LUT) 1036 of rates supported by the MIMO system and their required SNRs. The supported rate for wideband spatial channel m is sent by controller 380 to access point 110. At access point 110, controller 330 receives the supported rate for wideband spatial channel m and determines the data rate, coding, and modulation controls for the data stream to be sent on this spatial channel. The data stream is then processed in accordance with these controls by TX data processor 310, spatially processed and multiplexed with pilot symbols by TX spatial processor 320, conditioned by modulators 322, and transmitted to user terminal 120.


Outer loop 1020 estimates the quality of the decoded data steam received on wideband spatial channel m and adjusts the operation of inner loop 1010. The received symbols for wideband spatial channel m are spatially processed by RX spatial processor 360 and further processed by RX data processor 370. RX data processor 370 provides the status of each packet received on wideband spatial channel m and/or decoder metrics to quality estimator 1032. Outer loop 1020 can provide different types of information (e.g., SNR back-off factor, a rate adjustment, and so on) used to control the operation of inner loop 1010.


Closed-loop rate control described above may thus be performed independently for each downlink and uplink wideband spatial channel, which can correspond to (1) a wideband eigenmode, for the single-user steered mode, or (2) a transmit antenna, for the single-user and multi-user non-steered modes.


Scheduling User Terminals



FIG. 11 shows a block diagram of an embodiment of controller 330 and scheduler 334 for scheduling user terminals for data transmission on the downlink and uplink. Within controller 330, a request processor 1110 receives access requests transmitted by user terminal 120 on the RACH and possibly access requests from other sources. These access requests are for data transmission on the downlink and/or uplink. Request processor 1110 processes the received access requests and provides the identities (IDs) and the status of all requesting user terminals. The status for a user terminal may indicate the number of antennas available at the terminal, whether the terminal is calibrated, and so on.


A rate selector 1120 receives channel estimates from channel estimator 328 and determines the rates supported by the downlink and/or uplink wideband spatial channels for the requesting user terminals, as described above. For the downlink, each user terminal 120 can determine the rate supported by each of its wideband spatial channels, as described above. The supported rate is the maximum rate that may be used for data transmission on the wideband spatial channel to achieve the target level of performance. Each user terminal 120 can send the supported rates for all of its downlink wideband spatial channels to access point 110, e.g., via the RACH. Alternatively, access point 110 can determine the supported rates for the downlink wideband spatial channels if (1) the downlink and uplink are reciprocal and (2) access point 110 is provided with the noise variance or noise floor at user terminal 120. For the uplink, access point 110 can determine the supported rate for each wideband spatial channel for each requesting user terminal 120.


A user selector 1140 selects different sets of one or more user terminals, from among all of the requesting user terminals, for possible data transmission on the downlink and/or uplink. The user terminals may be selected based on various criteria such as system requirements, user terminal capabilities and supported rates, user priority, the amount of data to send, and so on. For the multi-user spatial multiplexing modes, the user terminals for each set may also be selected based on their channel response vectors.


A mode selector 1130 selects the particular spatial multiplexing mode to use for each set of user terminals based on the operating state and capabilities of the user terminals in the set and possibly other factors. For example, the single-user steered mode may be used for a “calibrated” multi-antenna user terminal that has performed calibration so that the channel response for one link (e.g., downlink) can be estimated based on a (e.g., steered) pilot received via the other link (e.g., uplink). The single-user non-steered mode may be used for an “uncalibrated” multi-antenna user terminal that has not performed calibration or cannot support the single-user steered mode for any reason. The multi-user steered mode may be used for downlink transmission to multiple user terminals, each of which is equipped with one or more antennas. The multi-user non-steered mode may be used for uplink transmission by multiple user terminals.


Scheduler 334 receives the sets of user terminals from user selector 1140, the selected spatial multiplexing mode for each user terminal set from mode selector 1130, and the selected rates for each user terminal set from rate selector 1120. Scheduler 334 schedules the user terminals for data transmission on the downlink and/or uplink. Scheduler 334 selects one or more sets of user terminals for data transmission on the downlink and one or more sets of user terminals for data transmission on the uplink for each TDD frame. Each set includes one or more user terminals and is scheduled for data transmission concurrently in a designated transmission interval within the TDD frame.


Scheduler 334 forms an information element (IE) for each user terminal scheduled for data transmission on the downlink and/or uplink. Each information element includes (1) the spatial multiplexing mode to use for data transmission, (2) the rate to use for the data stream sent on each wideband spatial channel, (3) the start and the duration of the data transmission, and (4) possibly other information (e.g., the type of pilot being transmitted along with the data transmission). Scheduler 334 sends the information elements for all scheduled user terminals via the FCCH. Each user terminal processes the FCCH to recover its information element, and thereafter receives a downlink transmission and/or sends an uplink transmission in accordance with the received scheduling information.



FIG. 11 shows an embodiment of the scheduling of user terminals for data transmission when multiple spatial multiplexing modes are supported. The scheduling may be performed in other manners, and this is within the scope of the invention.



FIG. 12 shows a flow diagram of a process 1200 for scheduling user terminals for data transmission in MIMO system 100. A set of least one user terminal is selected for data transmission on the downlink and/or uplink (block 1212). A spatial multiplexing mode is selected for the user terminal set from among multiple spatial multiplexing modes supported by the system (block 1214). Multiple rates are also selected for multiple data streams to be transmitted via multiple spatial channels for the user terminal set (block 1216). The user terminal set is scheduled for data transmission on the downlink and/or uplink with the selected rates and the selected spatial multiplexing mode (block 1218).



FIG. 13 shows a flow diagram of a process 1300 for transmitting data on the downlink in MIMO system 100. Process 1300 may be performed by access point 110x. A first plurality of data streams are coded and modulated in accordance with a first plurality of rates to obtain a first plurality of data symbol streams (block 1312). For the single-user steered mode, the first plurality of data symbol streams are spatially processed with a first plurality of steering vectors to obtain a first plurality of transmit symbol streams for transmission from multiple antennas to a first user terminal in a first transmission interval (block 1314). The first plurality of steering vectors are derived such that the first plurality of data streams are transmitted on orthogonal spatial channels to the first user terminal. A second plurality of data streams are coded and modulated in accordance with a second plurality of rates to obtain a second plurality of data symbol streams (block 1316). For the single-user non-steered mode, the second plurality of data symbol streams are provided as a second plurality of transmit symbol streams for transmission from the multiple antennas to a second user terminal in a second transmission interval (block 1318). A third plurality of data streams are coded and modulated to obtain a third plurality of data symbol streams (block 1320). For the multi-user steered mode, the third plurality of data symbol streams are spatially processed with a second plurality of steering vectors to obtain a third plurality of transmit symbol streams for transmission from the multiple antennas to multiple user terminals in a third transmission interval (block 1322). The second plurality of steering vectors are derived such that the third plurality of data symbol streams are received with suppressed crosstalk at the multiple user terminals.



FIG. 14 shows a flow diagram of a process 1400 for receiving data on the uplink in MIMO system 100. Process 1400 may also be performed by access point 110x. Receiver spatial processing is performed on a first plurality of received symbol streams in accordance with a first spatial multiplexing mode (e.g., the single-user steered mode) to obtain a first plurality of recovered data symbol streams (block 1412). The first plurality of recovered data symbol streams are demodulated and decoded in accordance with a first plurality of rates to obtain a first plurality of decoded data streams (block 1414). Receiver spatial processing is performed on a second plurality of received symbol streams in accordance with a second spatial multiplexing mode (e.g., a non-steered mode) to obtain a second plurality of recovered data symbol streams (block 1416). The second plurality of recovered data symbol streams are demodulated and decoded in accordance with a second plurality of rates to obtain a second plurality of decoded data streams, which are estimates of data streams transmitted by one or multiple user terminals (block 1418).


Each user terminal performs corresponding processes to transmit data on one or multiple uplink wideband spatial channels and to receive data on one or multiple downlink wideband spatial channels.


Data transmission with multiple spatial multiplexing modes, as described herein, may be implemented by various means. For example, the processing may be implemented in hardware, software, or a combination thereof. For a hardware implementation, the processing units used to perform data processing, spatial processing, and scheduling at the access point 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. The processing units at a user terminal may also be implemented on one or more ASICs, DSPs, and so on.


For a software implementation, the processing at the access point and user terminal for data transmission with multiple spatial multiplexing modes 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 unit 332 or 382 in FIG. 3) and executed by a processor (e.g., controller 330 or 380). The memory unit may be implemented within the processor or external to the processor.


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.


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.

Claims
  • 1. A method of transmitting data in a wireless multiple-input multiple-output (MIMO) communication system, comprising: selecting a spatial multiplexing mode to use for data transmission from among a plurality of spatial multiplexing modes supported by the system based on whether a user terminal has performed calibration so that the user terminal can estimate a channel response for a downlink based on a pilot received via an uplink, the plurality of spatial multiplexing modes comprising at least one steered spatial multiplexing mode and a non-steered spatial multiplexing mode, wherein the steered spatial multiplexing mode includes spatial processing using eigenvectors of a channel response matrix for at least one subband;coding and modulating a plurality of data streams in accordance with a plurality of rates to obtain a plurality of data symbol streams; andusing the spatial multiplexing mode, processing the plurality of data symbol streams to obtain a plurality of transmit symbol streams for transmission from a plurality of antennas.
  • 2. The method of claim 1, wherein the selected spatial multiplexing mode is a steered spatial multiplexing mode, and wherein the plurality of data symbol streams are spatially processed with a plurality of steering vectors to transmit the plurality of data symbol streams on a plurality of orthogonal spatial channels of a MIMO channel.
  • 3. The method of claim 2, further comprising: transmitting a steered pilot on each of the plurality of orthogonal spatial channels.
  • 4. The method of claim 1, wherein the plurality of data symbol streams are provided as the plurality of transmit symbol streams.
  • 5. The method of claim 1, further comprising: performing calibration so that uplink channel response is reciprocal of downlink channel response.
  • 6. The method of claim 1, wherein: each of the plurality of rates is selected from among a set of rates supported by the system.
  • 7. An apparatus in a wireless multiple-input multiple-output (MIMO) communication system, comprising: a controller operative to select a spatial multiplexing mode to use for data transmission from among a plurality of spatial multiplexing modes supported by the system based on whether a user terminal has performed calibration so that the user terminal can estimate a channel response for a downlink based on a pilot received via an uplink, the plurality of spatial multiplexing modes comprising at least one steered spatial multiplexing mode and a non-steered spatial multiplexing mode, wherein the steered spatial multiplexing mode includes spatial processing using eigenvectors of a channel response matrix for at least one subband;a transmit data processor operative to code and modulate a plurality of data streams in accordance with a plurality of rates to obtain a plurality of data symbol streams; anda transmit spatial processor operative to, using the spatial multiplexing mode, process the plurality of data symbol streams to obtain a plurality of transmit symbol streams for transmission from a plurality of antennas.
  • 8. The apparatus of claim 7, wherein the selected spatial multiplexing mode is a steered spatial multiplexing mode, and wherein the plurality of data symbol streams are spatially processed with a plurality of steering vectors to transmit the plurality of data symbol streams on a plurality of orthogonal spatial channels of a MIMO channel.
  • 9. The apparatus of claim 8, further comprising: a transmitter operative to transmit a steered pilot on each of the plurality of orthogonal spatial channels.
  • 10. The apparatus of claim 7, wherein the plurality of data symbol streams are provided as the plurality of transmit symbol streams.
  • 11. The apparatus of claim 7, further comprising: a calibrator operative to perform calibration so that uplink channel response is reciprocal of downlink channel response.
  • 12. The apparatus of claim 7, wherein: each of the plurality of rates is selected from among a set of rates supported by the system.
  • 13. An apparatus of transmitting data in a wireless multiple-input multiple-output (MIMO) communication system, comprising: means for selecting a spatial multiplexing mode to use for data transmission from among a plurality of spatial multiplexing modes supported by the system based on whether a user terminal has performed calibration so that the user terminal can estimate a channel response for a downlink based on a pilot received via an uplink, the plurality of spatial multiplexing modes comprising at least one steered spatial multiplexing mode and a non-steered spatial multiplexing mode, wherein the steered spatial multiplexing mode includes spatial processing using eigenvectors of a channel response matrix for at least one subband;means for coding and modulating a plurality of data streams in accordance with a plurality of rates to obtain a plurality of data symbol streams; andmeans for processing, using the spatial multiplexing mode, the plurality of data symbol streams to obtain a plurality of transmit symbol streams for transmission from a plurality of antennas.
  • 14. The apparatus of claim 13, wherein the selected spatial multiplexing mode is a steered spatial multiplexing mode, and wherein the plurality of data symbol streams are spatially processed with a plurality of steering vectors to transmit the plurality of data symbol streams on a plurality of orthogonal spatial channels of a MIMO channel.
  • 15. The apparatus of claim 14, further comprising: means for transmitting a steered pilot on each of the plurality of orthogonal spatial channels.
  • 16. The apparatus of claim 13, wherein the plurality of data symbol streams are provided as the plurality of transmit symbol streams.
  • 17. The apparatus of claim 13, further comprising: means for performing calibration so that uplink channel response is reciprocal of downlink channel response.
  • 18. The apparatus of claim 13, wherein: each of the plurality of rates is selected from among a set of rates supported by the system.
  • 19. A non-transitory computer-readable medium for transmitting data in a wireless multiple-input multiple-output (MIMO) communication system, the computer-readable medium having a set of instructions stored thereon, the set of instructions being executable by one or more processors and the set of instructions comprising: instructions for selecting a spatial multiplexing mode to use for data transmission from among a plurality of spatial multiplexing modes supported by the system based on whether a user terminal has performed calibration so that the user terminal can estimate a channel response for a downlink based on a pilot received via an uplink, the plurality of spatial multiplexing modes comprising at least one steered spatial multiplexing mode and a non-steered spatial multiplexing mode, wherein the steered spatial multiplexing mode includes spatial processing using eigenvectors of a channel response matrix for at least one subband;instructions for coding and modulating a plurality of data streams in accordance with a plurality of rates to obtain a plurality of data symbol streams; andinstructions for processing, using the spatial multiplexing mode, the plurality of data symbol streams to obtain a plurality of transmit symbol streams for transmission from a plurality of antennas.
  • 20. The computer-readable medium of claim 19, wherein the selected spatial multiplexing mode is a steered spatial multiplexing mode, and wherein the plurality of data symbol streams are spatially processed with a plurality of steering vectors to transmit the plurality of data symbol streams on a plurality of orthogonal spatial channels of a MIMO channel.
  • 21. The computer-readable medium of claim 20, further comprising: instructions for transmitting a steered pilot on each of the plurality of orthogonal spatial channels.
  • 22. The computer-readable medium of claim 19, wherein the plurality of data symbol streams are provided as the plurality of transmit symbol streams.
  • 23. The computer-readable medium of claim 19, further comprising: instructions for performing calibration so that uplink channel response is reciprocal of downlink channel response.
  • 24. The computer-readable medium of claim 19, wherein: each of the plurality of rates is selected from among a set of rates supported by the system.
  • 25. A method of receiving data in a wireless multiple-input multiple-output (MIMO) communication system, comprising: receiving information indicating a spatial multiplexing mode to use for data transmission selected from among a plurality of spatial multiplexing modes supported by the system based on whether a user terminal has performed calibration so that the user terminal can estimate a channel response for a downlink based on a pilot received via an uplink, the plurality of spatial multiplexing modes comprising at least one steered spatial multiplexing mode and a non-steered spatial multiplexing mode, wherein the steered spatial multiplexing mode includes spatial processing using eigenvectors of a channel response matrix for at least one subband;using the spatial multiplexing mode, processing at least one received symbol stream to obtain at least one recovered data symbol stream; anddemodulating and decoding the at least one recovered data symbol stream in accordance with at least one rate to obtain at least one decoded data stream.
  • 26. The method of claim 25, wherein the selected spatial multiplexing mode is a steered spatial multiplexing mode, and wherein a plurality of received symbol streams are spatially processed with a plurality of eigenvectors for a plurality of spatial channels of a MIMO channel to obtain a plurality of recovered data symbol streams.
  • 27. The method of claim 25, wherein a plurality of received symbol streams are spatially processed based on a channel correlation matrix inversion (CCMI) technique, a minimum mean square error (MMSE) technique, or a successive interference cancellation (SIC) technique to obtain a plurality of recovered data symbol streams.
  • 28. The method of claim 25, wherein one received symbol stream is processed with channel gain estimates to obtain one recovered data symbol stream.
  • 29. The method of claim 25, wherein: each of the at least one rate is selected from among a set of rates supported by the system.
  • 30. An apparatus in a wireless multiple-input multiple-output (MIMO) communication system, comprising: a controller operative to receive information indicating a spatial multiplexing mode to use for data transmission selected from among a plurality of spatial multiplexing modes supported by the system based on whether a user terminal has performed calibration so that the user terminal can estimate a channel response for a downlink based on a pilot received via an uplink, the plurality of spatial multiplexing modes comprising at least one steered spatial multiplexing mode and a non-steered spatial multiplexing mode, wherein the steered spatial multiplexing mode includes spatial processing using eigenvectors of a channel response matrix for at least one subband;a receive spatial processor operative to, using the spatial multiplexing mode, process at least one received symbol stream to obtain at least one recovered data symbol stream; anda receive data processor operative to demodulate and decode the at least one recovered data symbol stream in accordance with at least one rate to obtain at least one decoded data stream.
  • 31. The apparatus of claim 30, wherein the selected spatial multiplexing mode is a steered spatial multiplexing mode, and wherein a plurality of received symbol streams are spatially processed with a plurality of eigenvectors for a plurality of spatial channels of a MIMO channel to obtain a plurality of recovered data symbol streams.
  • 32. The apparatus of claim 30, wherein a plurality of received symbol streams are spatially processed based on a channel correlation matrix inversion (CCMI) technique, a minimum mean square error (MMSE) technique, or a successive interference cancellation (SIC) technique to obtain a plurality of recovered data symbol streams.
  • 33. The apparatus of claim 30, wherein one received symbol stream is processed with channel gain estimates to obtain one recovered data symbol stream.
  • 34. The apparatus of claim 30, wherein: each of the at least one rate is selected from among a set of rates supported by the system.
  • 35. An apparatus of receiving data in a wireless multiple-input multiple-output (MIMO) communication system, comprising: means for receiving information indicating a spatial multiplexing mode to use for data transmission selected from among a plurality of spatial multiplexing modes supported by the system based on whether a user terminal has performed calibration so that the user terminal can estimate a channel response for a downlink based on a pilot received via an uplink, the plurality of spatial multiplexing modes comprising at least one steered spatial multiplexing mode and a non-steered spatial multiplexing mode, wherein the steered spatial multiplexing mode includes spatial processing using eigenvectors of a channel response matrix for at least one subband;means for processing, using the spatial multiplexing mode, at least one received symbol stream to obtain at least one recovered data symbol stream; andmeans for demodulating and decoding the at least one recovered data symbol stream in accordance with at least one rate to obtain at least one decoded data stream.
  • 36. The apparatus of claim 35, wherein the selected spatial multiplexing mode is a steered spatial multiplexing mode, and wherein a plurality of received symbol streams are spatially processed with a plurality of eigenvectors for a plurality of spatial channels of a MIMO channel to obtain a plurality of recovered data symbol streams.
  • 37. The apparatus of claim 35, wherein a plurality of received symbol streams are spatially processed based on a channel correlation matrix inversion (CCMI) technique, a minimum mean square error (MMSE) technique, or a successive interference cancellation (SIC) technique to obtain a plurality of recovered data symbol streams.
  • 38. The apparatus of claim 35, wherein one received symbol stream is processed with channel gain estimates to obtain one recovered data symbol stream.
  • 39. The apparatus of claim 35, wherein: each of the at least one rate is selected from among a set of rates supported by the system.
  • 40. A non-transitory computer-readable medium for receiving data in a wireless multiple-input multiple-output (MIMO) communication system, the computer-readable medium having a set of instructions stored thereon, the set of instructions being executable by one or more processors and the set of instructions comprising: instructions for receiving information indicating a spatial multiplexing mode to use for data transmission selected from among a plurality of spatial multiplexing modes supported by the system based on whether a user terminal has performed calibration so that the user terminal can estimate a channel response for a downlink based on a pilot received via an uplink, the plurality of spatial multiplexing modes comprising at least one steered spatial multiplexing mode and a non-steered spatial multiplexing mode, wherein the steered spatial multiplexing mode includes spatial processing using eigenvectors of a channel response matrix for at least one subband;instructions for processing, using the spatial multiplexing mode, at least one received symbol stream to obtain at least one recovered data symbol stream; andinstructions for demodulating and decoding the at least one recovered data symbol stream in accordance with at least one rate to obtain at least one decoded data stream.
  • 41. The computer-readable medium of claim 40, wherein the selected spatial multiplexing mode is a steered spatial multiplexing mode, and wherein a plurality of received symbol streams are spatially processed with a plurality of eigenvectors for a plurality of spatial channels of a MIMO channel to obtain a plurality of recovered data symbol streams.
  • 42. The computer-readable medium of claim 40, wherein a plurality of received symbol streams are spatially processed based on a channel correlation matrix inversion (CCMI) technique, a minimum mean square error (MMSE) technique, or a successive interference cancellation (SIC) technique to obtain a plurality of recovered data symbol streams.
  • 43. The computer-readable medium of claim 40, wherein one received symbol stream is processed with channel gain estimates to obtain one recovered data symbol stream.
  • 44. The computer-readable medium of claim 40, wherein: each of the at least one rate is selected from among a set of rates supported by the system.
CLAIM OF PRIORITY

This application for patent is a continuation of, and claims the benefit of priority from, U.S. patent application Ser. No. 10/693,429, entitled “MIMO System with Multiple Spatial Multiplexing Modes” and filed on Oct. 23, 2003, which claims the benefit of priority from U.S. Provisional Patent Application Ser. No. 60/421,309, entitled “MIMO WLAN System” and filed Oct. 25, 2002, both of which are assigned to the assignee of this application for patent and are fully incorporated herein by reference for all purposes.

US Referenced Citations (488)
Number Name Date Kind
4736371 Tejima et al. Apr 1988 A
4750198 Harper Jun 1988 A
4797879 Habbab et al. Jan 1989 A
5239677 Jasinski Aug 1993 A
5241544 Jasper et al. Aug 1993 A
5295159 Kerpez Mar 1994 A
5404355 Raith Apr 1995 A
5422733 Merchant et al. Jun 1995 A
5471647 Gerlach et al. Nov 1995 A
5479447 Chow et al. Dec 1995 A
5491837 Haartsen Feb 1996 A
5493712 Ramesh et al. Feb 1996 A
5506861 Bottomley Apr 1996 A
5509003 Snijders et al. Apr 1996 A
5528581 De Bot Jun 1996 A
5606729 D'Amico et al. Feb 1997 A
5638369 Ayerst et al. Jun 1997 A
5677909 Heide Oct 1997 A
5729542 Dupont Mar 1998 A
5790550 Peeters et al. Aug 1998 A
5799005 Soliman Aug 1998 A
5818813 Saito et al. Oct 1998 A
5822374 Levin Oct 1998 A
5832387 Bae et al. Nov 1998 A
5859875 Kato et al. Jan 1999 A
5867478 Baum et al. Feb 1999 A
5867539 Koslov Feb 1999 A
5883887 Take et al. Mar 1999 A
5886988 Yun et al. Mar 1999 A
5929810 Koutsoudis et al. Jul 1999 A
5959965 Ohkubo et al. Sep 1999 A
5963589 Nagano et al. Oct 1999 A
5973638 Robbins et al. Oct 1999 A
5982327 Vook et al. Nov 1999 A
6005876 Cimini, Jr. et al. Dec 1999 A
6011963 Ogoro Jan 2000 A
6049548 Bruno et al. Apr 2000 A
6067290 Paulraj et al. May 2000 A
6072779 Tzannes et al. Jun 2000 A
6084915 Williams Jul 2000 A
6097771 Foschini Aug 2000 A
6115354 Weck Sep 2000 A
6122247 Levin et al. Sep 2000 A
6131016 Greenstein et al. Oct 2000 A
6141388 Servais et al. Oct 2000 A
6141542 Kotzin et al. Oct 2000 A
6141555 Sato Oct 2000 A
6141567 Youssefmir et al. Oct 2000 A
6144711 Raleigh et al. Nov 2000 A
6154661 Goldburg Nov 2000 A
6163296 Lier et al. Dec 2000 A
6167031 Olofsson et al. Dec 2000 A
6175588 Visotsky et al. Jan 2001 B1
6178196 Naguib et al. Jan 2001 B1
6192256 Whinnett Feb 2001 B1
6205410 Cai Mar 2001 B1
6222888 Kao et al. Apr 2001 B1
6232918 Wax et al. May 2001 B1
6266528 Farzaneh Jul 2001 B1
6272354 Saario Aug 2001 B1
6275543 Petrus et al. Aug 2001 B1
6278726 Mesecher et al. Aug 2001 B1
6292917 Sinha et al. Sep 2001 B1
6298035 Heiskala Oct 2001 B1
6298092 Heath, Jr. et al. Oct 2001 B1
6308080 Burt et al. Oct 2001 B1
6310704 Dogan et al. Oct 2001 B1
6314113 Guemas Nov 2001 B1
6314289 Eberlein et al. Nov 2001 B1
6317467 Cox et al. Nov 2001 B1
6317612 Farsakh Nov 2001 B1
6330277 Gelblum et al. Dec 2001 B1
6330293 Klank et al. Dec 2001 B1
6330462 Chen Dec 2001 B1
6333953 Bottomley et al. Dec 2001 B1
6339399 Andersson et al. Jan 2002 B1
6345036 Sudo et al. Feb 2002 B1
6346910 Ito Feb 2002 B1
6347217 Bengtsson et al. Feb 2002 B1
6347234 Scherzer Feb 2002 B1
6348036 Looney et al. Feb 2002 B1
6351499 Paulraj et al. Feb 2002 B1
6363267 Lindskog et al. Mar 2002 B1
6369758 Zhang Apr 2002 B1
6377812 Rashid-Farrokhi et al. Apr 2002 B1
6385264 Terasawa et al. May 2002 B1
6389056 Kanterakis et al. May 2002 B1
6426971 Wu et al. Jul 2002 B1
6452981 Raleigh et al. Sep 2002 B1
6463290 Stilp et al. Oct 2002 B1
6473467 Wallace et al. Oct 2002 B1
6478422 Hansen Nov 2002 B1
6492942 Kezys Dec 2002 B1
6510184 Okamura Jan 2003 B1
6512737 Agee Jan 2003 B1
6515617 Demers et al. Feb 2003 B1
6532225 Chang et al. Mar 2003 B1
6532255 Gunzelmann et al. Mar 2003 B1
6532562 Chou et al. Mar 2003 B1
6545997 Bohnke et al. Apr 2003 B1
6574211 Padovani et al. Jun 2003 B2
6574267 Kanterakis et al. Jun 2003 B1
6574271 Mesecher et al. Jun 2003 B2
6590883 Kitade et al. Jul 2003 B1
6594473 Dabak et al. Jul 2003 B1
6594798 Chou et al. Jul 2003 B1
6597682 Kari Jul 2003 B1
6608874 Beidas et al. Aug 2003 B1
6611231 Crilly, Jr. et al. Aug 2003 B2
6615024 Boros et al. Sep 2003 B1
6631121 Yoon Oct 2003 B1
6636496 Cho et al. Oct 2003 B1
6636568 Kadous Oct 2003 B2
6654590 Boros et al. Nov 2003 B2
6654613 Maeng et al. Nov 2003 B1
6668161 Boros et al. Dec 2003 B2
6683916 Sartori et al. Jan 2004 B1
6690660 Kim et al. Feb 2004 B2
6693992 Jones et al. Feb 2004 B2
6694155 Chin et al. Feb 2004 B1
6697346 Halton et al. Feb 2004 B1
6711121 Gerakoulis et al. Mar 2004 B1
6728233 Park et al. Apr 2004 B1
6731668 Ketchum May 2004 B2
6735188 Becker et al. May 2004 B1
6738020 Lindskog et al. May 2004 B1
6744811 Kantschuk Jun 2004 B1
6751187 Walton et al. Jun 2004 B2
6751444 Meiyappan Jun 2004 B1
6751480 Kogiantis et al. Jun 2004 B2
6757263 Olds Jun 2004 B1
6760313 Sindhushayana et al. Jul 2004 B1
6760388 Ketchum et al. Jul 2004 B2
6760882 Gesbert et al. Jul 2004 B1
6763244 Chen et al. Jul 2004 B2
6768727 Sourour et al. Jul 2004 B1
6771706 Ling et al. Aug 2004 B2
6785341 Walton et al. Aug 2004 B2
6785513 Sivaprakasam Aug 2004 B1
6788948 Lindskog et al. Sep 2004 B2
6792041 Kim et al. Sep 2004 B1
6795424 Kapoor et al. Sep 2004 B1
6798738 Do et al. Sep 2004 B1
6801790 Rudrapatna Oct 2004 B2
6802035 Catreux et al. Oct 2004 B2
6804191 Richardson Oct 2004 B2
6821535 Nurmi et al. Nov 2004 B2
6842460 Olkkonen et al. Jan 2005 B1
6847828 Miyoshi et al. Jan 2005 B2
6850252 Hoffberg Feb 2005 B1
6850498 Heath et al. Feb 2005 B2
6859503 Pautler et al. Feb 2005 B2
6862271 Medvedev et al. Mar 2005 B2
6862440 Sampath Mar 2005 B2
6868079 Hunt Mar 2005 B1
6873651 Tesfai et al. Mar 2005 B2
6879578 Pan et al. Apr 2005 B2
6879579 Myles et al. Apr 2005 B1
6882868 Shattil Apr 2005 B1
6885708 Thomas et al. Apr 2005 B2
6888809 Foschini et al. May 2005 B1
6888899 Raleigh et al. May 2005 B2
6891858 Mahesh et al. May 2005 B1
6920192 Laroia et al. Jul 2005 B1
6920194 Stopler et al. Jul 2005 B2
6927728 Vook et al. Aug 2005 B2
6937592 Heath, Jr. et al. Aug 2005 B1
6940917 Menon et al. Sep 2005 B2
6950632 Yun et al. Sep 2005 B1
6952426 Wu et al. Oct 2005 B2
6952454 Jalali et al. Oct 2005 B1
6956813 Fukuda Oct 2005 B2
6956897 Honig Oct 2005 B1
6956906 Tager et al. Oct 2005 B2
6959171 Tsien et al. Oct 2005 B2
6963741 Johansson et al. Nov 2005 B2
6963742 Boros et al. Nov 2005 B2
6965762 Sugar et al. Nov 2005 B2
6970722 Lewis Nov 2005 B1
6980601 Jones Dec 2005 B2
6980800 Noerpel et al. Dec 2005 B2
6985434 Wu et al. Jan 2006 B2
6985534 Meister Jan 2006 B1
6987819 Thomas et al. Jan 2006 B2
6990059 Anikhindi et al. Jan 2006 B1
6992972 Van Nee Jan 2006 B2
6996380 Dent Feb 2006 B2
7002900 Walton et al. Feb 2006 B2
7003044 Subramanian et al. Feb 2006 B2
7006464 Gopalakrishnan et al. Feb 2006 B1
7006483 Nelson, Jr. et al. Feb 2006 B2
7006848 Ling et al. Feb 2006 B2
7009931 Ma et al. Mar 2006 B2
7012978 Talwar Mar 2006 B2
7020110 Walton et al. Mar 2006 B2
7020482 Medvedev et al. Mar 2006 B2
7020490 Khatri Mar 2006 B2
7023826 Sjoberg et al. Apr 2006 B2
7024163 Barratt et al. Apr 2006 B1
7031671 Mottier Apr 2006 B2
7035359 Molnar Apr 2006 B2
7039125 Friedman May 2006 B2
7039363 Kasapi et al. May 2006 B1
7042858 Ma et al. May 2006 B1
7043259 Trott May 2006 B1
7054378 Walton et al. May 2006 B2
7058367 Luo et al. Jun 2006 B1
7062294 Rogard et al. Jun 2006 B1
7068628 Li et al. Jun 2006 B2
7072381 Atarashi et al. Jul 2006 B2
7072410 Monsen Jul 2006 B1
7072413 Walton et al. Jul 2006 B2
7088671 Monsen Aug 2006 B1
7095709 Walton et al. Aug 2006 B2
7095722 Walke et al. Aug 2006 B1
7099377 Berens et al. Aug 2006 B2
7103325 Jia et al. Sep 2006 B1
7110378 Onggosanusi et al. Sep 2006 B2
7110463 Wallace et al. Sep 2006 B2
7113499 Nafie et al. Sep 2006 B2
7116652 Lozano Oct 2006 B2
7120199 Thielecke et al. Oct 2006 B2
7120657 Ricks et al. Oct 2006 B2
7127009 Berthet et al. Oct 2006 B2
7130362 Girardeau et al. Oct 2006 B2
7133459 Onggosanusi et al. Nov 2006 B2
7137047 Mitlin et al. Nov 2006 B2
7149190 Li et al. Dec 2006 B1
7149239 Hudson Dec 2006 B2
7149254 Sampath Dec 2006 B2
7155171 Ebert et al. Dec 2006 B2
7158563 Ginis et al. Jan 2007 B2
7164649 Walton et al. Jan 2007 B2
7164669 Li et al. Jan 2007 B2
7184713 Kadous et al. Feb 2007 B2
7187646 Schramm Mar 2007 B2
7190749 Levin et al. Mar 2007 B2
7191381 Gesbert et al. Mar 2007 B2
7194237 Sugar et al. Mar 2007 B2
7197084 Ketchum et al. Mar 2007 B2
7200404 Panasik et al. Apr 2007 B2
7206354 Wallace et al. Apr 2007 B2
7218684 Bolourchi et al. May 2007 B2
7221956 Medvedev et al. May 2007 B2
7224704 Lu et al. May 2007 B2
7231184 Eilts et al. Jun 2007 B2
7233625 Ma et al. Jun 2007 B2
7238508 Lin et al. Jul 2007 B2
7242727 Liu et al. Jul 2007 B2
7248638 Banister Jul 2007 B1
7248841 Agee et al. Jul 2007 B2
7254171 Hudson Aug 2007 B2
7260153 Nissani Aug 2007 B2
7260366 Lee et al. Aug 2007 B2
7263119 Hsu et al. Aug 2007 B1
7274734 Tsatsanis Sep 2007 B2
7277679 Barratt et al. Oct 2007 B1
7280467 Smee et al. Oct 2007 B2
7280625 Ketchum et al. Oct 2007 B2
7283508 Choi et al. Oct 2007 B2
7289570 Schmidl et al. Oct 2007 B2
7292854 Das et al. Nov 2007 B2
7298778 Visoz et al. Nov 2007 B2
7298805 Walton et al. Nov 2007 B2
7308035 Rouquette et al. Dec 2007 B2
7317750 Shattil Jan 2008 B2
7324429 Walton et al. Jan 2008 B2
7327800 Oprea et al. Feb 2008 B2
7333556 Maltsev et al. Feb 2008 B2
7342912 Kerr et al. Mar 2008 B1
7356004 Yano et al. Apr 2008 B2
7356089 Jia et al. Apr 2008 B2
7379492 Hwang May 2008 B2
7386076 Onggosanusi et al. Jun 2008 B2
7392014 Baker et al. Jun 2008 B2
7403748 Keskitalo et al. Jul 2008 B1
7421039 Malaender et al. Sep 2008 B2
7453844 Lee et al. Nov 2008 B1
7466749 Medvedev et al. Dec 2008 B2
7480278 Pedersen et al. Jan 2009 B2
7492737 Fong et al. Feb 2009 B1
7508748 Kadous Mar 2009 B2
7548506 Ma et al. Jun 2009 B2
7551546 Ma et al. Jun 2009 B2
7551580 Du Crest et al. Jun 2009 B2
7573805 Zhuang et al. Aug 2009 B2
7599443 Ionescu et al. Oct 2009 B2
7603141 Dravida Oct 2009 B2
7606296 Hsu et al. Oct 2009 B1
7606319 Zhang et al. Oct 2009 B2
7616698 Sun et al. Nov 2009 B2
7623871 Sheynblat Nov 2009 B2
7636573 Walton et al. Dec 2009 B2
7646747 Atarashi et al. Jan 2010 B2
7653142 Ketchum et al. Jan 2010 B2
7653415 Van Rooyen Jan 2010 B2
7656967 Tiirola et al. Feb 2010 B2
7778337 Tong et al. Aug 2010 B2
7822140 Catreux et al. Oct 2010 B2
7843972 Nakahara et al. Nov 2010 B2
7885228 Walton et al. Feb 2011 B2
8145179 Walton et al. Mar 2012 B2
8170513 Walton et al. May 2012 B2
8203978 Walton et al. Jun 2012 B2
8218609 Walton et al. Jul 2012 B2
8254246 Ma et al. Aug 2012 B2
8260210 Esteve Asensio et al. Sep 2012 B2
8325836 Tong et al. Dec 2012 B2
8355313 Walton et al. Jan 2013 B2
8358714 Walton et al. Jan 2013 B2
8406118 Ma et al. Mar 2013 B2
8462643 Walton et al. Jun 2013 B2
8483188 Walton et al. Jul 2013 B2
20010017881 Bhatoolaul et al. Aug 2001 A1
20010031621 Schmutz Oct 2001 A1
20010033623 Hosur Oct 2001 A1
20010046205 Easton et al. Nov 2001 A1
20020003774 Wang et al. Jan 2002 A1
20020004920 Cho et al. Jan 2002 A1
20020018310 Hung Feb 2002 A1
20020018453 Yu et al. Feb 2002 A1
20020027951 Gormley et al. Mar 2002 A1
20020041632 Sato et al. Apr 2002 A1
20020044591 Lee et al. Apr 2002 A1
20020044610 Jones Apr 2002 A1
20020057659 Ozluturk et al. May 2002 A1
20020062472 Medlock et al. May 2002 A1
20020064214 Hattori et al. May 2002 A1
20020072336 Mottier Jun 2002 A1
20020075830 Hartman, Jr. Jun 2002 A1
20020080735 Heath et al. Jun 2002 A1
20020085620 Mesecher Jul 2002 A1
20020085641 Baum Jul 2002 A1
20020098872 Judson Jul 2002 A1
20020105928 Kapoor et al. Aug 2002 A1
20020115467 Hamabe Aug 2002 A1
20020115473 Hwang et al. Aug 2002 A1
20020118781 Thomas et al. Aug 2002 A1
20020122381 Wu et al. Sep 2002 A1
20020122393 Caldwell et al. Sep 2002 A1
20020127978 Khatri Sep 2002 A1
20020136271 Hiramatsu et al. Sep 2002 A1
20020147032 Yoon et al. Oct 2002 A1
20020147953 Catreux et al. Oct 2002 A1
20020150182 Dogan et al. Oct 2002 A1
20020152253 Ricks et al. Oct 2002 A1
20020154705 Walton et al. Oct 2002 A1
20020177447 Walton et al. Nov 2002 A1
20020181390 Mody et al. Dec 2002 A1
20020183010 Catreux et al. Dec 2002 A1
20020184453 Hughes et al. Dec 2002 A1
20020191535 Sugiyama et al. Dec 2002 A1
20020193146 Wallace et al. Dec 2002 A1
20020196842 Onggosanusi et al. Dec 2002 A1
20030002450 Jalali et al. Jan 2003 A1
20030003863 Thielecke et al. Jan 2003 A1
20030007463 Li et al. Jan 2003 A1
20030012308 Sampath et al. Jan 2003 A1
20030039217 Seo et al. Feb 2003 A1
20030039317 Taylor et al. Feb 2003 A1
20030045288 Luschi et al. Mar 2003 A1
20030045318 Subrahmanya Mar 2003 A1
20030048856 Ketchum et al. Mar 2003 A1
20030050069 Kogiantis et al. Mar 2003 A1
20030072382 Raleigh et al. Apr 2003 A1
20030072395 Jia et al. Apr 2003 A1
20030073409 Nobukiyo et al. Apr 2003 A1
20030076812 Benedittis Apr 2003 A1
20030078024 Magee et al. Apr 2003 A1
20030095197 Wheeler et al. May 2003 A1
20030099306 Nilsson et al. May 2003 A1
20030103584 Bjerke et al. Jun 2003 A1
20030112745 Zhuang et al. Jun 2003 A1
20030117989 Kim Jun 2003 A1
20030119452 Kim et al. Jun 2003 A1
20030123389 Russell et al. Jul 2003 A1
20030125040 Walton et al. Jul 2003 A1
20030128656 Scarpa Jul 2003 A1
20030128658 Walton et al. Jul 2003 A1
20030139194 Onggosanusi et al. Jul 2003 A1
20030142732 Moshavi et al. Jul 2003 A1
20030153345 Cramer, III Aug 2003 A1
20030153360 Burke et al. Aug 2003 A1
20030157954 Medvedev et al. Aug 2003 A1
20030162519 Smith et al. Aug 2003 A1
20030174676 Willenegger et al. Sep 2003 A1
20030174686 Willenegger et al. Sep 2003 A1
20030185310 Ketchum et al. Oct 2003 A1
20030185311 Kim Oct 2003 A1
20030186650 Liu Oct 2003 A1
20030190897 Lei et al. Oct 2003 A1
20030202492 Akella et al. Oct 2003 A1
20030202612 Halder et al. Oct 2003 A1
20030206558 Parkkinen et al. Nov 2003 A1
20030210668 Malladi et al. Nov 2003 A1
20030235147 Walton et al. Dec 2003 A1
20030235149 Chan et al. Dec 2003 A1
20030235255 Ketchum et al. Dec 2003 A1
20040005887 Bahrenburg et al. Jan 2004 A1
20040013103 Zhang et al. Jan 2004 A1
20040017785 Zelst Jan 2004 A1
20040037257 Ngo Feb 2004 A1
20040042439 Menon et al. Mar 2004 A1
20040042556 Medvedev et al. Mar 2004 A1
20040047284 Eidson Mar 2004 A1
20040047292 Du Crest et al. Mar 2004 A1
20040052228 Tellado et al. Mar 2004 A1
20040062192 Liu et al. Apr 2004 A1
20040071104 Boesel et al. Apr 2004 A1
20040071107 Kats et al. Apr 2004 A1
20040076224 Onggosanusi et al. Apr 2004 A1
20040081131 Walton et al. Apr 2004 A1
20040082356 Walton et al. Apr 2004 A1
20040085939 Wallace et al. May 2004 A1
20040087324 Ketchum et al. May 2004 A1
20040095907 Agee et al. May 2004 A1
20040121730 Kadous et al. Jun 2004 A1
20040136349 Walton et al. Jul 2004 A1
20040151108 Blasco Claret et al. Aug 2004 A1
20040151122 Lau et al. Aug 2004 A1
20040156328 Walton et al. Aug 2004 A1
20040160921 Kaipainen et al. Aug 2004 A1
20040160987 Sudo et al. Aug 2004 A1
20040176097 Wilson et al. Sep 2004 A1
20040179627 Ketchum et al. Sep 2004 A1
20040198276 Tellado et al. Oct 2004 A1
20040252632 Bourdoux et al. Dec 2004 A1
20050002326 Ling et al. Jan 2005 A1
20050047384 Wax et al. Mar 2005 A1
20050047515 Walton et al. Mar 2005 A1
20050099974 Kats et al. May 2005 A1
20050111599 Walton et al. May 2005 A1
20050120097 Walton et al. Jun 2005 A1
20050128953 Wallace et al. Jun 2005 A1
20050135284 Nanda et al. Jun 2005 A1
20050135295 Walton et al. Jun 2005 A1
20050135308 Vijayan et al. Jun 2005 A1
20050135318 Walton et al. Jun 2005 A1
20050147177 Seo et al. Jul 2005 A1
20050174981 Heath et al. Aug 2005 A1
20050185575 Hansen et al. Aug 2005 A1
20050195915 Raleigh et al. Sep 2005 A1
20050208959 Chen et al. Sep 2005 A1
20050220211 Shim et al. Oct 2005 A1
20050227628 Inanoglu Oct 2005 A1
20050245264 Laroia et al. Nov 2005 A1
20050276343 Jones Dec 2005 A1
20060018247 Driesen et al. Jan 2006 A1
20060018395 Tzannes Jan 2006 A1
20060039275 Walton et al. Feb 2006 A1
20060067417 Park et al. Mar 2006 A1
20060072649 Chang et al. Apr 2006 A1
20060077935 Hamalainen et al. Apr 2006 A1
20060104196 Wu et al. May 2006 A1
20060104340 Walton et al. May 2006 A1
20060114858 Walton et al. Jun 2006 A1
20060153237 Hwang et al. Jul 2006 A1
20060159120 Kim Jul 2006 A1
20060176968 Keaney et al. Aug 2006 A1
20060183497 Paranchych et al. Aug 2006 A1
20060209894 Tzannes et al. Sep 2006 A1
20060209937 Tanaka et al. Sep 2006 A1
20070086536 Ketchum et al. Apr 2007 A1
20070177681 Choi et al. Aug 2007 A1
20070274278 Choi et al. Nov 2007 A1
20080267138 Walton et al. Oct 2008 A1
20080285488 Walton et al. Nov 2008 A1
20080285669 Walton et al. Nov 2008 A1
20080285670 Walton et al. Nov 2008 A1
20090129454 Medvedev et al. May 2009 A1
20090161613 Kent et al. Jun 2009 A1
20090291642 Cozzo et al. Nov 2009 A1
20100067401 Medvedev et al. Mar 2010 A1
20100142636 Heath, Jr. et al. Jun 2010 A1
20100183088 Inanoglu Jul 2010 A1
20100208841 Walton et al. Aug 2010 A1
20100220825 Dubuc et al. Sep 2010 A1
20100260060 Abraham et al. Oct 2010 A1
20100271930 Tong et al. Oct 2010 A1
20110096751 Ma et al. Apr 2011 A1
20110235744 Ketchum et al. Sep 2011 A1
20120140664 Walton et al. Jun 2012 A1
20120176928 Wallace et al. Jul 2012 A1
20120219093 Jia et al. Aug 2012 A1
20130040682 Chang et al. Feb 2013 A1
20130235825 Walton et al. Sep 2013 A1
20130279614 Walton et al. Oct 2013 A1
20140036823 Ma et al. Feb 2014 A1
Foreign Referenced Citations (195)
Number Date Country
2002259221 Nov 2002 AU
2690245 Oct 2001 CA
2690247 Oct 2001 CA
1086061 Apr 1994 CN
1234661 Nov 1999 CN
1298266 Jun 2001 CN
1308794 Aug 2001 CN
1314037 Sep 2001 CN
1325198 Dec 2001 CN
1325243 Dec 2001 CN
1339885 Mar 2002 CN
1347609 May 2002 CN
1469662 Jan 2004 CN
1489836 Apr 2004 CN
1537371 Oct 2004 CN
19951525 Jun 2001 DE
0755090 Jan 1997 EP
0762701 Mar 1997 EP
0772329 May 1997 EP
0805568 Nov 1997 EP
0869647 Oct 1998 EP
0895387 Feb 1999 EP
0929172 Jul 1999 EP
0951091 Oct 1999 EP
0991221 Apr 2000 EP
0993211 Apr 2000 EP
1061446 Dec 2000 EP
1075093 Feb 2001 EP
1087545 Mar 2001 EP
1117197 Jul 2001 EP
1126673 Aug 2001 EP
1133070 Sep 2001 EP
1137217 Sep 2001 EP
1143754 Oct 2001 EP
1170879 Jan 2002 EP
1175022 Jan 2002 EP
1182799 Feb 2002 EP
1185001 Mar 2002 EP
1185015 Mar 2002 EP
1185048 Mar 2002 EP
1207635 May 2002 EP
1207645 May 2002 EP
1223702 Jul 2002 EP
1241824 Sep 2002 EP
1265411 Dec 2002 EP
1315311 May 2003 EP
1379020 Jan 2004 EP
1387545 Feb 2004 EP
1416688 May 2004 EP
1447934 Aug 2004 EP
1556984 Jul 2005 EP
2300337 Oct 1996 GB
2373973 Oct 2002 GB
1132027 May 1989 JP
03104430 May 1991 JP
06003956 Jan 1994 JP
6501139 Jan 1994 JP
8274756 Oct 1996 JP
9135230 May 1997 JP
9266466 Oct 1997 JP
9307526 Nov 1997 JP
09327073 Dec 1997 JP
9512156 Dec 1997 JP
10028077 Jan 1998 JP
10051402 Feb 1998 JP
10084324 Mar 1998 JP
10209956 Aug 1998 JP
10303794 Nov 1998 JP
10327126 Dec 1998 JP
1141159 Feb 1999 JP
2991167 Mar 1999 JP
11069431 Mar 1999 JP
11074863 Mar 1999 JP
11163823 Jun 1999 JP
11205273 Jul 1999 JP
11252037 Sep 1999 JP
11317723 Nov 1999 JP
2000068975 Mar 2000 JP
2000078105 Mar 2000 JP
2000092009 Mar 2000 JP
2001044930 Feb 2001 JP
200186045 Mar 2001 JP
2001103034 Apr 2001 JP
2001186051 Jul 2001 JP
2001510668 Jul 2001 JP
2001217896 Aug 2001 JP
2001231074 Aug 2001 JP
2001237751 Aug 2001 JP
200264879 Feb 2002 JP
2002504283 Feb 2002 JP
200277098 Mar 2002 JP
200277104 Mar 2002 JP
2002111627 Apr 2002 JP
2002118534 Apr 2002 JP
2002510932 Apr 2002 JP
2002514033 May 2002 JP
2002164814 Jun 2002 JP
2002176379 Jun 2002 JP
2002204217 Jul 2002 JP
2002232943 Aug 2002 JP
2003504941 Feb 2003 JP
2003198442 Jul 2003 JP
2003530010 Oct 2003 JP
2004266586 Sep 2004 JP
2004297172 Oct 2004 JP
2006504336 Feb 2006 JP
200011799 Feb 2000 KR
20010098861 Nov 2001 KR
1020020003370 Jan 2002 KR
20060095576 Aug 2006 KR
2015281 Jun 1994 RU
2111619 May 1998 RU
2134489 Aug 1999 RU
2141168 Nov 1999 RU
2149509 May 2000 RU
2152132 Jun 2000 RU
2157592 Oct 2000 RU
2158479 Oct 2000 RU
2168277 May 2001 RU
2168278 May 2001 RU
2197781 Jan 2003 RU
2201034 Mar 2003 RU
2335852 Oct 2008 RU
419912 Jan 2001 TW
496620 Jul 2002 TW
503347 Sep 2002 TW
545006 Aug 2003 TW
567689 Dec 2003 TW
567701 Dec 2003 TW
583842 Apr 2004 TW
I263449 Oct 2006 TW
I267251 Nov 2006 TW
86007223 Dec 1986 WO
9307684 Apr 1993 WO
WO-9516319 Jun 1995 WO
9521501 Aug 1995 WO
WO9530316 Nov 1995 WO
WO9532567 Nov 1995 WO
WO9622662 Jul 1996 WO
WO9635268 Nov 1996 WO
9702667 Jan 1997 WO
WO9719525 May 1997 WO
9736377 Oct 1997 WO
WO9809381 Mar 1998 WO
WO9809395 Mar 1998 WO
WO9824192 Jun 1998 WO
WO9826523 Jun 1998 WO
WO9830047 Jul 1998 WO
9857472 Dec 1998 WO
WO9903224 Jan 1999 WO
9914878 Mar 1999 WO
WO99016214 Apr 1999 WO
9929049 Jun 1999 WO
WO9944379 Sep 1999 WO
9952224 Oct 1999 WO
WO9957820 Nov 1999 WO
WO0011823 Mar 2000 WO
WO0036764 Jun 2000 WO
WO0062456 Oct 2000 WO
WO0105067 Jan 2001 WO
WO0126269 Apr 2001 WO
0163775 Aug 2001 WO
WO0169801 Sep 2001 WO
WO0171928 Sep 2001 WO
WO0176110 Oct 2001 WO
WO0180510 Oct 2001 WO
WO0182521 Nov 2001 WO
0195531 Dec 2001 WO
WO0197400 Dec 2001 WO
WO0201732 Jan 2002 WO
WO0203557 Jan 2002 WO
WO-0205506 Jan 2002 WO
0251433 Feb 2002 WO
WO0215433 Feb 2002 WO
WO0225853 Mar 2002 WO
WO02060138 Aug 2002 WO
WO02062002 Aug 2002 WO
WO02065664 Aug 2002 WO
WO02069523 Sep 2002 WO
WO02069590 Sep 2002 WO
WO02073869 Sep 2002 WO
WO02078211 Oct 2002 WO
WO02082689 Oct 2002 WO
WO02088656 Nov 2002 WO
WO02099992 Dec 2002 WO
03010994 Feb 2003 WO
WO03010984 Feb 2003 WO
WO03019984 Mar 2003 WO
WO03028153 Apr 2003 WO
WO03034646 Apr 2003 WO
WO03047140 Jun 2003 WO
WO04002011 Dec 2003 WO
WO04002047 Dec 2003 WO
WO2004039011 May 2004 WO
WO2004039022 May 2004 WO
Non-Patent Literature Citations (74)
Entry
G. Bauch, J. Hagenauer, “Smart Versus Dumb Antennas—Capacities and FEC Performance,” IEEE Communications Letters, vol. 6, No. 2, pp. 55-57, Feb. 2002.
European Search Report—EP10173988—Search Authority—Munich—Mar. 15, 2011.
Translation of Office Action in Canadian Application 2501634 corresponding to U.S. Appl. No. 10/610,446, citing CA2690247 dated Feb. 25, 2011.
Translation of Office Action in Japanese Application 2005-501686 corresponding to U.S. Appl. No. 10/375,162 , citing JP09135230 dated Feb. 15, 2011.
Chung, J. et al: “Multiple antenna systems for 802.16 systems.” IEEE 802.16 Broadband Wireless Access Working Group <http://ieee802.org/I6>, IEEE 802.16abc-01/31, Sep. 7, 2001.
Gore D. A., et al: “Selecting an optimal set of transmit antennas for a low rank matrix channel,” 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. (ICASSP). Istanbul, Turkey, Jun. 5-9, 2000, New York, NY; IEEE, US, vol. 5 of 6, Jun. 5, 2000, pp. 2785-2788, XP001035763, abstract.
Diggavi, S. et al., “Intercarrier interference in MIMO OFDM,” IEEE International Conference on Communications, (Aug. 2002), vol. 1, pp. 485-489, doi: 10.1109/ICC.2002.996901.
European Search Report—EP08012143.7, Search Authority—Munich Patent Office, Jan. 19. 2011.
Lebrun G., et al., “MIMO transmission over a time varying TDD channel using SVD,” Electronics Letters, 2001, vol. 37, pp. 1363-1364.
Li, Ye et. al., “Simplified Channel Estimation for OFDM Systems with Multiple Transmit Antennas,” IEEE Transactions on Wireless Communications, Jan. 2002, vol. 1, No. 1, pp. 67-75.
Iserte, P., et al.,“Joint beamforming strategies in OFDM-MIMO systems,” Acoustics, Speech, and Signal Processing, 1993. ICASSP-93., 1993 IEEE International Conference on , vol. 3, sections 2-3, Apr. 27-30, 1993, doi: 10.1109/ICASSP.2002.1005279.
Sampath, H., et al., “Joint transmit and receive optimization for high data rate wireless communication using multiple antennas,” Signals, Systems, and Computers, 1999. Conference Record of the Thirty-Third Asilomar Conference, Oct. 24, 1999, XP010373976, pp. 215-219, IEEE, Piscataway, NJ, US.
The Authoritative Dictionary of IEEE Standards Terms, Seventh Edition, IEEE Press: New York (Dec. 2000), p. 902.
Wong, Cheong. et al., “Multiuser OFDM with Adaptive Subcarrier, Bit and Power Allocation,” Oct. 1999, IEEE Journal on Selected Areas in Communications, vol. 17, No. 10, pp. 1747-1758.
Wong K. K., et al., “Optimizing time and space MIMO antenna system for frequency selective fading channels,” IEEE Journal on Selected Areas in Communications, vol. 19, No. 7, Jul. 2001, Sections II and III and V, 1396, pp. 1395-1406.
International Search Report, PCT/US03/034519—International Search Authority—European Patent Office—Jul. 8, 2004.
International Preliminary Examination Report—PCT/US03/034519, IPEA/US—Aug. 31, 2004.
3GPP2 TIA/EIA/IS-2000-2-A, “Physical Layer Standard for cdma2000 Spread Spectrum Systems”, (Nov. 19, 1999).
Alamouti, S.M., “A Simple Transmit Diversity Technique for Wireless Communications,” IEEE Journal on Select Areas in Communications, vol. 16, No. 8, Oct. 1998, pp. 1451-1458.
B. Hassibi, et al. “High-Rate Codes that are Linear in Space and Time,” Lucent Technologies, Murray Hill, NY (USA), Aug. 22, 2000, (pp. 1-54).
Chen, K.C. et al., “Novel Space-Time Processing of DS/CDMA Multipath Signal,” IEEE 49th, Vehicular Technology Conference, Houston, Texas, May 16-20, 1999, pp. 1809-1813.
Choi, R. et al., “MIMO Transmit Optimization for Wireless Communication Systems,” Proceedings of the First IEEE International workshops on Electronic Design, pp. 1-6, Piscataway, New Jersey, Jan. 29-31, 2002.
ETSI TS 101 761-1 v1.3.1, “Broadband Radio Access Networks (BRAN); Hiperlan Type 2; Data Link Control (DLC) Layer; Part 1: Basic Data Transport Functions,” ETSI Standards, European Telecommunications Standards Institute BR (V131), pp. 1-88 (Dec. 2001).
Fujii, M.: “Pseudo-Orthogonal Multibeam-Time Transmit Diversity for OFDM-CDMA” pp. 222-226 (2002).
Gao, et al. “On implementation of Bit-Loading Algorithms for OFDM Systems with Multiple-Input Multiple Output,” VTC 2002-Fall. 2002 IEEE 56th. Vehicular Technology Conference Proceedings. Vancouver, Canada, Sep. 24-28, 2002, IEEE Vehicular Technology Con.
Haustein, T. et al.: “Performance of MIMO Systems with Channel Inversion,” IEEE 55th Vehicular Technology Conference, Birmingham, Alabama, May 6-9, 2002, pp. 35-39.
Hayashi, K, A New Spatio-Temporal Equalization Method Based on Estimated Channel Response, Sep. 2001, IEEE Transaction on Vehicular Technology, vol. 50, Issue 5, pp. 1250-1259.
Hong, D. K. et al.: “Robust Frequency Offset Estimation for Pilot Symbol Assisted Packet CDMA with MIMO Antenna Systems,” IEEE Communications Letters, vol. 6, No. 6, pp. 262-264 (Jun. 2002).
IEEE Std 802.11a-1999 (Supplement to IEEE Std 801.11-1999) “Part 11: Wireless LAN Medium Access Control (MAC) and Phyiscal Layer (PHY) specifications: High-Speed physical Layer in the 5GHZ Band”, pp. 1-90, Sep. 1999.
Joham, M. et al.: “Symbol Rate Processing for the Downlink of DS-CDMA Systems”, IEEE Journal on Selected Areas in Communications, vol. 19, No. 1, paragraphs 1, 2; IEEE Service Center, Piscataway, US, (Jan. 1, 2001), XP011055296, ISSN: 0733-8716.
John A.C. Bingham, “Multicarrier Modulation for Data Transmission: An Idea Whose Time Has Come,” IEEE Communications Magazines, May 1990 (pp. 5-13).
Jongren et al., “Utilizing Quantized Feedback Information in Orthogonal Space-Time Block Coding,” 2000 IEEE Global Telecommunications Conference, 2(4): 995-999, Nov. 27, 2000.
Kiessling, et al., “Short-Term and Long Term Diagonalization of Correlated MIMO Channels with Adaptive Modulation,” IEEE Conference, vol. 2, (Sep. 15, 2002), pp. 593-597.
L. Deneire, et al. “A Low Complexity ML Channel Estimator for OFDM,” Proc IEEE ICC Jun. 2001 pp. 1461-1465.
Li Lihua, et al., “A Practical Space-Frequency Block Coded OFDM Scheme for Fast Fading Broadband Channels” 13th IEEE International Symposium on Personal Indoor and Mobile Radio Communications. PIMRC 2002. Sep. 15-18, 2002, pp. 212-216, vol. 1, XP002280831.
M.A. Kousa, et al., “Multichannel adaptive system,” IEE Proceedings—I, vol. 140, No. 5, Oct. 1993, rages 357-364.
Miyashita, et al., “High Data-Rate Transmission with Eigenbeam-Space Division Multiplexing (E-SDM) in a MIMO Channel,” VTC 2002-Fall. 2002 IEEE 56th. Vehicular Technology Conference Proceedings. Vancouver, Canada, Sep. 24-28, 2002, IEEE Vehicular Technology.
P.W. Wolniansky, et al. “V-BLAST: An Architecture for Realizing Very High Data Rates Over the Rich-Scattering Wireless Channel,” Lucent Technologies, Holmdel, NJ.
Pautler, J. et al.: “On Application of Multiple-Input Multiple-Output Antennas to CDMA Cellular Systems,” IEEE 54th Vehicular Technology Conference Proceedings, Atlantic City, New Jersey, Oct. 7-11, 2001, pp. 1508-1512.
Tarighat, A. et al. “Performance Analysis of Different Algorithms for cdma2000 Antenna Array System and a New Multi User Beamforming (MUB) Algorithm”, Wireless Communications and Networking Conference, vol. 1, pp. 409-414, Sep. 23, 2000.
Theon, S. et al.: “Improved Adaptive Downlink for OFDM/SDMA-Based Wireless Networks,” IEEE VTS 53rd Vehicular Technology Conference, pp. 707-711, Rhodes, Greece, May 6-9, 2001.
Tujkovic, D.: “High bandwidth efficiency space-time turbo coded modulation”, Institute of Electrical and Electronics Engineers, ICC 2001. 2001 IEEE International Conference on Communications, Conference Record, pp. 1104-1109, Helsinky, Finland, Jun. 11-14, 2001.
Van Zelst, A. et al.: “Space Division Multiplexing (SDM) for OFDM Systems,” IEEE 51st Vehicular Technology Conference Proceedings, pp. 1070-1074, Tokyo, Japan, May 15-18, 2000.
Warner, W. et al.: “OFDM/FM Frame Synchronization for Mobile Radio Data Communication”, IEEE Transactions on Vehicular Technology, vol. 42, No. 3, pp. 302-313.
Yoshiki, T., et al., “A Study on Subcarrier Adaptive Demodulation System using Multilevel Transmission Power Control for OFDM/FDD System,” The Institute of Electronics, Information and Communications Engineers general meeting, lecture collection, Japan, Mar. 7, 2000, Communication 1, p. 400.
Dae-Ko Hong, Young-Jo Lee, Daesik Hong, and Chang-Eon Kang. “Robust frequency offset estimation for pilot symbol assisted packet CDMA with MIMO antenna systems.” Communications Letters. IEEE. Jun. 2002.
S.W. Wales, A MIMO technique within the UTRA TDD standard Jun. 22, 2005.
3 rd Generation Partnership Project (3GPP); Technical Specification Group (TSG); Radio Access Network (RAN); RF requirements f o r 1.28Mcps UTRA TDD option, 3GPP Standard; 3G TR 25.945, 3rd Generation Partnership Project (3GPP), Mobile Competence Centre ; 650, Route Des Lucioles ; F-06921 Sophia-Antipolis Cedex; France, No. V2.0.0, Dec. 20, 2000, pp. 1-144, XP050400193, [retreived on Dec. 20, 2000], p. 126.
3rd Generation Parthership Project ; Technical Specification Group Radio Access Network; Radio Resource Control (RRC); Protocol Specifiation (Release 5 ) , 3GPP Standard; 3GPP TS 25.331, 3rd Generation Partnership Project (3GPP), Mobile Competence Centre ; 650, Route Des Lucioles ; F-06921 Sophia-Antipolis Cedex; France, No. V5.2.0, Sep. 1, 2002, pp. 1-938, XP050367950, pp. 124, 358-p. 370.
“3rd Generation Partnership Project ; Technical Specification Group Radio Access 6-18, Network; Physical channels and mapping of 21-24 transport channels onto physical channels (TDD) (Release 5 )”, 3GPP Standard; 3GPP TS 25.221, 3rd Generation Partnership Project (3GPP), Mobile Competence Centre ; 650, Route Des Lucioles ; F-06921 Sophia-Antipolis Cedex ; France, No. V5.2.0, Sep. 1, 2002, pp. 1-97, XP050366967.
Catreux S., et al., “Simulation results for an interference-limited multiple input multiple output cellular system”., Global Telecommmunications letters . IEEE: U.S.A. Nov. 2000. vol. 4(11), pp. 334-336.
Coleri, S. et al: “Channel Estimation Techniques Based on Pilot Arrangement in OFDM Systems,” IEEE Transactions on Broadcasting, Sep. 1, 2002, pp. 223-229, vol. 48, No. 3, IEEE Service Center, XP011070267, ISSN: 0018-9316.
Co-pending U.S. Appl. No. 07/624,118, filed Dec. 7, 1990.
Co-pending U.S. Appl. No. 08/118,473, filed Sep. 8, 1993.
Editor: 3GPP Draft; 3rd Generation Partnership Project (3GPP), Technical Specification Group (TSG) Radio Access Network (RAN); Working Group 4(WG4); base Station conformance and testing“, TS 25.141 V0.1.1 (May 1999)”, R4-99349, Mobile Competence Centre; 650, Route Des Lucioles; F-06921 Sophia-Antipolis Cedex; France, vol. RAN WG4, no.Miami; 20011024, Oct. 24, 2001, XP050166323.
EPO Communication pursuant to Article 94(3) EPC issued by the European Patent Orifice for Application No. 10174926.5 dated Aug. 1, 2013.
EPO Communication pursuant to Article 94(3) EPC issued by the European Patent Orifice for Application No. 10174932.3 dated Jul. 30, 2013.
European Search Report—EP10174919—Search Authority—Munich—Apr. 11, 2012.
Grunheid, R. et al., “Adaptive Modulation and Multiple Access for the OFDM Transmission Technique,” Wireless Personal Communications 13: May 13, 2000, 2000 Kluwer Academic Publishers, pp. 4-13, XP000894156.
Harada H., et al., “An OFDM-Based Wireless ATM Transmission System Assisted by a Cyclically ExtendedPN Sequence for Future Broad-BandMobile Multimedia Communications”, IEEE Transactions on Vehicular Technology, IEEE Service Center, Piscataway, NJ, US, vol. 50, No. 6, Nov. 1, 2001, XP011064321, ISSN: 0018-9545.
Heath et al., “Multiuser diversity for MIMO wireless systems with linear receivers”, Conference Record of the 35th Asilomar Conference on Signals, Systems, & Computers, Nov. 4, 2001, pp. 1194-1199, vol. 2, IEEE, XP010582229, DOI: 10.1109/ACSSC.2001.987680, ISBN: 9780-7803-7147-7.
Lal D et al: “A novel MAC layer protocol for space division multiple access in wireless ad hoc networks”, Computer Communications and Networks, 2002 Proceedings, Eleventh International Conference on Oct. 14, 2002, pp. 614-619.
Le Goff, S. et al: “Turbo-codes and high spectral efficiency modulation,” IEEE International Conference on Communications, 1994. ICC “94, SUPERCOMM/ICC” 94, Conference Record, ‘Serving Humanity Through Communications.’ pp. 645-649, vol. 2, May 1-5, 1994, XP010126658, doi: 10.1109/ICC.1994.368804.
Louvigne J.C., et al., “Experimental study of a real-time calibration procedure of a CDMA/TDD multiple antenna terminal,” IEEE Antennas and Propagation Society International Symposium, 2002 Digest.APS.San Antonio, TX, Jun. 16-21, 2002,vol. 2, Jun. 16, 2002, pp. 644-647, XP010591780, DOI: 10.1109/APS.2002.1016729, ISBN: 978-0-7803-7330-3.
Nogueroles R., et al., “Performance of a random OFDMA system for mobile communications”, Broadband Communications, 1998. Accessing, Transmission, Networking. Proceedings. 1998 International Zurich Seminar on Zurich, Switzerland Feb. 17-19, 1998, New York , NY, USA , IEEE, US, Feb. 17, 1998, pp. 37-43, XP010277032 , DOI : 10.1109/IZSBC.1998.670242 ISBN: 978-0-7803-3893-7, p. 1-p. 2.
Sakaguchi et al, “Comprehensive Calibration for MIMO System”, International Symposium on Wireless Personal Multimedia Communications, IEEE, vol. 2, Oct. 27, 2002, pp. 440-443.
Sampath et al., “A Fourth-Generation MIMO-OFDM Broadband Wireless System: Design, Performance and Field Trial Results”, IEEE Communications Magazine, Sep. 1, 2002, pp. 143-149, vol. 40, No. 9, IEEE Service Center, XP011092922, ISSN: 0163-6804, DOI: 10.1109/MCOM.2002.1031841.
Song, Bong-Gee et al., “Prefilter design using the singular value decomposition for MIMO equalization,” 1996 Conference Record of the Thirtieth Asilomar Conference on Signals, Systems and Computers, vol. 1, pp. 34-38, Nov. 3-6, 1996, XP010231388, DOI : 10.1109/ACSSC.1996.600812, p. 35, col. 2, paragraph 4 through p. 36, col. 1.
Technical Search Report issued by the Taiwan Patent Office for TW Application No. 098143050, dated Aug. 2, 2013.
Varanasi M.K, et al., “Optimum decision feedback multiuser equalization with successive decoding achieves the total capacity of the Gaussian multiple-access channel”, Signals, Systems & Computers, 1997. Conference Record of the Thirty-First Asilomar Conference on Pacific Grove, CA, USA Nov. 2-5, 1997, Los Alamitos, CA, USA,IEEE Comput. SOC, US, vol. 2, Nov. 2, 1997, pp. 1405-1409 , XP010280667, DOI: 10.1109/ACSSC.1997 . 679134 ISBN : 978-0-8186-8316-9 pp. 1,3,5; figures 1,3.
Vook, F. W. et al., “Adaptive antennas for OFDM”, Vehicular Technology Conference, vol. 1, May 18-21, 1998, pp. 606-610, XP010287858, New York, NY, USA, IEEE, US DOI: 10.1109/VETEC.1998.686646 ISBN: 978-0-7803-4320-7.
Wyglinski, Alexander. “Physical Layer Loading Algorithms for Indoor Wireless Multicarrier Systems,” Thesis Paper, McGill University, Montreal, Canada, Nov. 2004, p. 109.
Yamamura, T et al., “High Mobility OFDM transmission system by a new channel estimation and ISI cancellation scheme using characteristics of pilot symbol inserted OFDM signal”., Vehicular Technology Conference, vol. 1, Sep. 19, 1999-Sep. 22, 1999, pp. 319-323, XP010352958 IEEE, Piscataway, NJ, USA, ISBN: 0-7803-5435-4.
Taiwan Search Report—TW099105740—TIPO—Apr. 22, 2014.
Related Publications (1)
Number Date Country
20100119001 A1 May 2010 US
Provisional Applications (1)
Number Date Country
60421309 Oct 2002 US
Continuations (1)
Number Date Country
Parent 10693429 Oct 2003 US
Child 12649040 US