Multiple-input, multiple-output communication system with reduced feedback

In MIMO systems, two or more transmit signals are transmitted from different antenna clusters having one or more transmit antennas each. A precoding circuit weight the transmit signals transmitted from each transmit antenna using a common set of frequency independent antenna weights for all antenna clusters. The antenna weights are computed based on correlations between transmit antennas in the same antenna cluster.

BACKGROUND

The present invention relates to multiple-input, multiple output (MIMO) communication systems, and more particularly, to a MIMO system that uses knowledge of the statistics of the communication channel to prefilter the transmit signal(s).

In recent years, there has been much interest in multiple input, multiple output (MIMO) systems for enhancing data rates in mobile communication systems. MIMO systems employ multiple antennas at the transmitter and receiver to transmit and receive information. The receiver can exploit the spatial dimensions of the signal at the receiver to achieve higher spectral efficiency and higher data rates without increasing bandwidth.

The best performance in a MIMO system is obtained when the channel response is known to the transmitter. In this case, the transmitter can use knowledge of the channel response to compute antenna weights for each antenna so as to compensate for the channel conditions between the transmitter and the receiver. The amount of channel feedback from the receiver in such systems increases with the number of antennas at the transmitter and the receiver. The channel feedback from the receiver to the transmitter consumes valuable reverse link resources. Therefore, it is desirable to reduce the amount of feedback required to be sent on the reverse link while maintaining good performance on the forward link.

SUMMARY

The present invention relates to a MIMO system that reduces the amount of channel feedback required to prefilter the transmit signals while maintaining good performance. The transmit antennas at the transmitter are grouped into clusters. There is a one-to-one correspondence between antenna clusters at the transmitter and receive antennas at the receiver. A different transmit signal is transmitted by each antenna cluster. Each transmit antenna in a given antenna cluster transmits a weighted version of the same transmit signal. A common set of frequency independent antenna weights are used for all antenna clusters. Thus, the antenna weights for the first transmit antenna in the first cluster is the same as the antenna weights for the first transmit antenna in the second, third fourth, etc, antenna cluster. By using the same set of antenna weights for all antenna clusters, the amount of channel feedback required to prefilter the transit signal is significantly reduced.

DETAILED DESCRIPTION

FIG. 1illustrates a multiple input/multiple output (MIMO) wireless communication system10including a first station12and a second station14. The first station12includes a transmitter100for transmitting signals to the second station14over a communication channel16, while the second station includes a receiver200for receiving signals transmitted by the first station12. Those skilled in the art will appreciate that the first station12and second station14may each include both a transmitter100and receiver200for bi-directional communications. In one exemplary embodiment, the first station12is a base station in a wireless communication network, and the second station14is mobile station. The present invention is particularly useful in Orthogonal Frequency Division Multiplexing (OFDM) systems.

An information signal I(n) in the form of a binary data stream is input to the transmitter100at the first station12. The transmitter includes a controller102to control the overall operation of the transmitter100and a transmit signal processing circuit104. The transmit signal processing circuit104performs error coding, maps the input bits to complex modulation symbols, and generates transmit signals for each transmit antenna150. After upward frequency conversion, filtering, and amplification, transmitter100transmits the transmit signals from respective transmit antennas150through the communication channel16to the second station14.

The receiver200at the second station14demodulates and decodes the signals received at each antenna250. Receiver200includes a controller202to control operation of the receiver200and a receive signal processing circuit204. The receive signal processing circuit204demodulates and decodes the signal transmitted from the first station12. The output signal from the receiver200comprises an estimate Î(n) of the original information signal. In the absence of errors, the estimate Î(n) will be the same as the original information signal input I(n) at the transmitter100.

Because multiple data streams are transmitted in parallel from different antennas150, there is a linear increase in throughput with every pair of antennas150,250added to the system without an increase in the bandwidth requirement. MIMO systems have been the subject of extensive research activity worldwide for use in wireless communication networks because of their potential to achieve high spectral efficiencies, and therefore high data rates.

A MIMO system with M transmit antennas and N receive antennas is typically described by the following matrix representation:
y(f)=G(f)x(f)+z(f),  Eq. (1)
where y(f) is the N×1 received signal vector, G(f) is the N×M MIMO channel response, z(f) is the independent and identically distributed (i.i.d.) AWGN at the receiver with individual variance of 2, and x(f) is the M×1 transmitted signal vector with a certain power constraint. In general, the best performance in a MIMO system is achieved when the channel response is known to the transmitter100so that the transmit signals can be weighted accordingly by the transmitter100prior to transmission.

One MIMO approach that is attracting significant attention is Per Antenna Rate Control (PARC). In PARC systems, information to be transmitted is divided into multiple streams. Each stream is independently encoded and modulated, and then transmitted from a respective transmit antenna150. The coding rates depend on the signal to interference plus noise ratio (SINR). In conventional PARC systems, the number of transmit antennas150is fixed and all transmit antennas150are used all the time to transmit data to mobile stations.

Another MIMO approach attracting attention is known as the Eigen Beamforming (EBF). In EBF systems, the transmit signals transmitted by each transmit antenna150are pre-filtered prior to transmission. For MIMO systems using Eigen Beamforming (EBF), a precoding circuit applies an M×N coding matrix and outputs N transmit signals; one for each receive antenna250. The rows of the precoding matrix are the N eigen vectors, corresponding to the largest eigen values of the matrix:

H_=1Nf⁢∑k=1Nf⁢GH⁡(fk)⁢G⁡(fk),Eq.⁢(2)
where Nfis the number of averaging sub-carriers. In the EBF approach, M×N complex elements of the precoding matrix must be fed back from the receiver200to the transmitter100on the reverse link. For purposes of this application, the term reverse link is used to refer to the channel used to feedback information from the receiver to the transmitter. The reverse link channel may be an uplink channel (mobile terminal to base station) or a downlink channel (base station to mobile terminal).

Different antenna geometries can be used with either the PARC approach or the EBF approach.FIGS. 2 and 3illustrate two exemplary antenna geometries for a MIMO transmitter100. The antenna geometry shown inFIG. 2, referred to herein as the clustered geometry, groups the transmit antennas150into two or more antenna clusters152. The antenna clusters152are separated by a large distance (e.g., 10λ) so that the antennas150in different antenna clusters152can be considered to be essentially independent from each other. The transmit antennas150within each antenna cluster152are closely spaced (e.g., 0.5λ) so that the transmit antennas150within the same antenna cluster152are highly correlated. The geometry shown inFIG. 3, referred to as the distributed geometry, places the transmit antennas150far apart (e.g., 10λ) so that all of the transmit antennas150can be considered mutually independent.

FIGS. 4 and 5illustrate the relative performance of the PARC and EBF approaches for the clustered and the distributed antenna geometries.FIG. 4shows the average data rate as a function of the average SNR for the PARC approach.FIG. 4shows that the PARC approach is best when the distributed geometry (Geometry2) is used.FIG. 5shows the average data rate as a function of the average SNR for the EBF approach.FIG. 5shows that the EBF approach is best when the clustered geometry (Geometry1) is used.

FIG. 6compares the performance of the PARC approach using a distributed geometry with the EBF approach using the clustered geometry.FIG. 6shows that the EBF approach with the clustered geometry is best when the SNR is below 12 dB. In a typical mobile communication system with a 1/1 reuse factor, the overwhelming majority of users (e.g. approximately 90%) will have an SNR less than 12 dB. Thus, the EBF approach with a clustered geometry will be the best approach for the majority of users.

The EBF approach requires that M×N complex coefficients be fed back from the receiver200to the transmitter100to compute the prefilter matrix.FIG. 7illustrates a transmit signal processing circuit104for a transmitter100using a technique referred to herein as Clustered Eigen Beamforming (CEBF). This technique allows a reduction in the amount of channel feedback required while achieving performance levels that are very close to that obtained using the EBF approach with a clustered geometry. In this approach, the transmit antennas150are grouped into N antenna clusters152, where N equals the number of receive antennas250at the receiver200. In one embodiment, there are M/N transmit antennas150in each antenna cluster152. For example, consider a MIMO system with six transmit antennas150and two receive antennas250. The six transmit antennas150may be divided into two antenna clusters152with three transmit antennas150each. The transmit antennas150in each antenna cluster152are closely spaced (e.g., 0.5λ) so that the transmit antennas150in the same antenna cluster152are highly correlated. The antenna clusters152are spaced far apart (e.g., 10λ) so that the transmit antennas150in different antenna clusters152may be considered independent.

The transmit signal processing circuit104for the CEBF approach comprises a demultiplexer106, a channel coding circuit107, a precoding circuit120, a plurality of transmitter front end circuits122, and a feedback processor124. An information bitstream I(n) is divided by demultiplxer1067into N substreams {I1(n), . . . IN(n)}, where equals the number of antenna clusters152. Each substream Ii(n) for i=1, . . . N is input to a corresponding channel coding circuit107including an encoder108, a modulator110, an Inverse Fast Fourier Transform (IFFT) circuit112. Encoder108comprises an error correction encoder, such as a Turbo encoder or convolutional encoder. The modulator110may comprise, for example a QPSK or QAM modulator. The modulation symbol streams {s1(n), . . . sN(n)} output by the respective modulators110are input to an IFFT circuit112(FIG. 8).

The IFFT circuit112includes a serial-to-parallel (S/P) converter114to divide the stream of modulation symbols si(n) from the modulator110into Ncsubstreams, where Ncequals the number of subcarriers, an IFFT filter116to apply an Inverse Fast Fourier transform as is known in the art, and a parallel-to-serial (P/S) converter118to generate a transmit signal {tilde over (s)}i(n).

The transmit signals {{tilde over (s)}i(n), . . . {tilde over (s)}N(n)} output from each channel coding circuit107is input to the precoding circuit120. The precoding circuit120weights the transmit signals using antenna weights denoted by the weight vector W of size M/N×1 provided by the feedback processor124. It should be noted that a common set of frequency independent antenna weights is used for each antenna cluster152. The generation of the weighted transmit signals fed to each transmit antenna150from the transmit signals {{tilde over (s)}i(n), . . . {tilde over (s)}N(n)} is described below.

Referring toFIG. 9, the precoding circuit120takes {{tilde over (s)}i(n), . . . {tilde over (s)}N(n)} as its input and generates weighted transmit signals {x1(n), . . . xM(n)} at its output, where xk(n) represents the signal fed to the front end122of the kth transmit antenna150. The transmit antennas150are grouped into N antenna clusters152, where each antenna cluster152comprises M/N transmit antennas150. As shown inFIG. 9, {tilde over (s)}i(n) is fed to the transmit antennas150in the ith antenna cluster152. For each transmit antenna150in the antenna cluster152, the transmit signal {tilde over (s)}i(n) is weighted by a corresponding antenna weight wj, where j denotes the jth transmit antenna152in an antenna cluster152. Thus, the first transmit antenna150in the ith antenna cluster152transmits {tilde over (s)}i(n)·w1, the second transmit antenna152in the it antenna cluster152transmits {tilde over (s)}i(n)·w2, etc. More generally, the jth transmit antenna in the ith antenna cluster152transmits {tilde over (s)}i(n)·wj.

In one exemplary embodiment, the same set of frequency independent antenna weights

{wj}j=1MN
are used by each antenna cluster152. The common set of antenna weights

{wj}j=1MN
is represented by the weight vector

w=[w1,…⁢⁢wMN]T.
The antenna weights may be computed as follows. Let Gi(f) represent the N×M/N channel response matrix for the channel between the transmit antennas in the ithcluster152and the N receive antennas at the receiver. The weight vector W may be computed as the eigen vector corresponding to the largest eigen value of the transmit correlation matrix

D_=1Nf⁢1N⁢∑k=iNf⁢∑i=1N⁢GiT⁡(fk)⁢Gi⁡(fk)Eq.⁢(3)
The antenna weights may be computed by the receiver200and fed back to the transmitter100by the receiver200or, alternatively, computed by the feedback processor124based on feedback of antenna correlations from the receiver200as hereinafter described.

It may be noted that the transmit correlation matrixDis approximately equal to the expected value of the channel correlation matrix E{GiT(f)Gi(f)} for each antenna cluster152. It has been observed that with the clustered geometry, the correlations between transmit antennas150in an antenna cluster152will be the same for each antenna cluster152assuming that the antennas150in each antenna cluster152have the same relative spacing. Consequently, the expected value of the channel correlation matrix E{GiT(f)Gi(f)} for the antennas150in all antenna clusters152are the same.

FIG. 10illustrates the receive signal processing circuit204for a MIMO receiver200using the CEBF approach. The receiver comprises N receive antennas250. As previously noted, the number of receive antennas250equals the number of antenna clusters152at the transmitter100. A receiver front end circuit206downconverts the received signals {r1(t), . . . rN(t)} at each receive antenna250to baseband frequency and converts the baseband signals into digital form for processing by the receive signal processing circuit204. The digitized received signals {r1(n), . . . rN(n)} are input to a combiner208that combines the received signals {r1(n), . . . rN(n)} and outputs estimates {{circumflex over (x)}1(n), . . . {circumflex over (x)}N(n)} of the transmitted signal {x1(n), . . . xN(n)}. The estimates {{circumflex over (x)}1(n), . . . {circumflex over (x)}N(n)} are input to corresponding IFFT circuits210which apply a Fast Fourier transform and output estimates {ŝ1(n), . . . ŝN(n)} of the modulation symbol streams {s1(n), . . . sN(n)}. The symbol stream estimates {ŝ1(n), . . . ŝN(n)} are demodulated by corresponding demodulators212using channel estimates provided by a channel estimator218. The channel estimator218computes the channel estimates based on the received signal as known in the art. Demodulators212output estimates {ĉ1(n), . . . ĉN(n)} of the coded bit streams. These estimates are input to a parallel to serial converter214and converted into a parallel bitstream, which is an estimate ĉ(n) of the coded bitstream c(n) input at the transmitter100. A decoder216decodes the estimate ĉ(n) to produce an estimate Î(n) of the original information signal I(n).

The channel estimates computed by the channel estimator218are also input to a feedback processor220to generate channel feedback for use by the transmitter100. The channel feedback processor220may compute antenna weights as described above, and transmit the antenna weights to the transmitter100. This approach requires the receiver200to feed back M×N antenna weights. Instead of computing antenna weights, the feedback processor220may instead compute the transmit correlations that comprise the transmit correlation matrixD. In this case, the feedback processor124at the transmitter100can compute the antenna weights from the transmit correlations.

Those skilled in the art may recognize that it is not necessary to feed back the entire transmit correlation matrixD. As previously noted, the transmit correlations in the transmit correlation matrixDrepresent the correlations between the transmit antennas150in a given antenna cluster152, which is the same for all antenna clusters152. It has been observed that the transmit correlation matrixDis a Toeplitz Hermitian matrix. Therefore, the receiver200only needs to feed back the transmit correlations corresponding to a single row in the transmit correlation matrixD. With a single row of the transmit correlations, the transmitter100can reconstruct the transmit correlation matrixDand compute the combining weights.

FIG. 11is a graph comparing the performance of the CEBF transmitter shown inFIG. 7with a more conventional EBF transmitter using a clustered antenna geometry. As shown inFIG. 11, the CEBF approach achieves a performance level very close to the EBF approach using different antenna weights for each antenna cluster152. Given that the CEBF approach significantly reduces the amount of channel feedback required, the CEBF approach provides an attractive alternative.

A transmitter100using the CEBF approach requires the computation of M/N antenna weights. In contrast, the more conventional EBF approach described above requires M×N antenna weights to be computed. Thus, the present invention reduces the number of antenna weights needed for operation by a factor of N2as compared to conventional practice.