505 research outputs found
Space Division Multiple Access with a Sum Feedback Rate Constraint
On a multi-antenna broadcast channel, simultaneous transmission to multiple
users by joint beamforming and scheduling is capable of achieving high
throughput, which grows double logarithmically with the number of users. The
sum rate for channel state information (CSI) feedback, however, increases
linearly with the number of users, reducing the effective uplink capacity. To
address this problem, a novel space division multiple access (SDMA) design is
proposed, where the sum feedback rate is upper-bounded by a constant. This
design consists of algorithms for CSI quantization, threshold based CSI
feedback, and joint beamforming and scheduling. The key feature of the proposed
approach is the use of feedback thresholds to select feedback users with large
channel gains and small CSI quantization errors such that the sum feedback rate
constraint is satisfied. Despite this constraint, the proposed SDMA design is
shown to achieve a sum capacity growth rate close to the optimal one. Moreover,
the feedback overflow probability for this design is found to decrease
exponentially with the difference between the allowable and the average sum
feedback rates. Numerical results show that the proposed SDMA design is capable
of attaining higher sum capacities than existing ones, even though the sum
feedback rate is bounded.Comment: 29 pages; submitted to IEEE Transactions on Signal Processin
Fundamental Limits in Correlated Fading MIMO Broadcast Channels: Benefits of Transmit Correlation Diversity
We investigate asymptotic capacity limits of the Gaussian MIMO broadcast
channel (BC) with spatially correlated fading to understand when and how much
transmit correlation helps the capacity. By imposing a structure on channel
covariances (equivalently, transmit correlations at the transmitter side) of
users, also referred to as \emph{transmit correlation diversity}, the impact of
transmit correlation on the power gain of MIMO BCs is characterized in several
regimes of system parameters, with a particular interest in the large-scale
array (or massive MIMO) regime. Taking the cost for downlink training into
account, we provide asymptotic capacity bounds of multiuser MIMO downlink
systems to see how transmit correlation diversity affects the system
multiplexing gain. We make use of the notion of joint spatial division and
multiplexing (JSDM) to derive the capacity bounds. It is advocated in this
paper that transmit correlation diversity may be of use to significantly
increase multiplexing gain as well as power gain in multiuser MIMO systems. In
particular, the new type of diversity in wireless communications is shown to
improve the system multiplexing gain up to by a factor of the number of degrees
of such diversity. Finally, performance limits of conventional large-scale MIMO
systems not exploiting transmit correlation are also characterized.Comment: 29 pages, 8 figure
Compressive Sensing for Feedback Reduction in MIMO Broadcast Channels
We propose a generalized feedback model and compressive sensing based
opportunistic feedback schemes for feedback resource reduction in MIMO
Broadcast Channels under the assumption that both uplink and downlink channels
undergo block Rayleigh fading. Feedback resources are shared and are
opportunistically accessed by users who are strong, i.e. users whose channel
quality information is above a certain fixed threshold. Strong users send same
feedback information on all shared channels. They are identified by the base
station via compressive sensing. Both analog and digital feedbacks are
considered. The proposed analog & digital opportunistic feedback schemes are
shown to achieve the same sum-rate throughput as that achieved by dedicated
feedback schemes, but with feedback channels growing only logarithmically with
number of users. Moreover, there is also a reduction in the feedback load. In
the analog feedback case, we show that the propose scheme reduces the feedback
noise which eventually results in better throughput, whereas in the digital
feedback case the proposed scheme in a noisy scenario achieves almost the
throughput obtained in a noiseless dedicated feedback scenario. We also show
that for a fixed given budget of feedback bits, there exist a trade-off between
the number of shared channels and thresholds accuracy of the feedback SINR.Comment: Submitted to IEEE Transactions on Wireless Communications, April 200
Opportunistic Scheduling and Beamforming for MIMO-OFDMA Downlink Systems with Reduced Feedback
Opportunistic scheduling and beamforming schemes with reduced feedback are
proposed for MIMO-OFDMA downlink systems. Unlike the conventional beamforming
schemes in which beamforming is implemented solely by the base station (BS) in
a per-subcarrier fashion, the proposed schemes take advantages of a novel
channel decomposition technique to perform beamforming jointly by the BS and
the mobile terminal (MT). The resulting beamforming schemes allow the BS to
employ only {\em one} beamforming matrix (BFM) to form beams for {\em all}
subcarriers while each MT completes the beamforming task for each subcarrier
locally. Consequently, for a MIMO-OFDMA system with subcarriers, the
proposed opportunistic scheduling and beamforming schemes require only one BFM
index and supportable throughputs to be returned from each MT to the BS, in
contrast to BFM indices and supportable throughputs required by the
conventional schemes. The advantage of the proposed schemes becomes more
evident when a further feedback reduction is achieved by grouping adjacent
subcarriers into exclusive clusters and returning only cluster information from
each MT. Theoretical analysis and computer simulation confirm the effectiveness
of the proposed reduced-feedback schemes.Comment: Proceedings of the 2008 IEEE International Conference on
Communications, Beijing, May 19-23, 200
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