A capacity-based RAU selection scheme for downlink transmission in distributed antenna system
Proceedings of the 2006 international conference on Wireless communications and mobile computing
Random matrix theory and wireless communications
Communications and Information Theory
Limits of multi-user MIMO systems using scheduling and rate feedback
Signal Processing
Optimal STBC precoding with channel covariance feedback for minimum error probability
EURASIP Journal on Applied Signal Processing
IEEE Transactions on Communications
On rate-optimal MIMO signalling with mean and covariance feedback
IEEE Transactions on Wireless Communications
Capacity of a multiple-antenna fading channel with a quantized precoding matrix
IEEE Transactions on Information Theory
Optimizing training-based transmission for correlated MIMO systems with hybrid feedback
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
On queueing and multilayer coding
IEEE Transactions on Information Theory
Why does the Kronecker model result in misleading capacity estimates?
IEEE Transactions on Information Theory
Optimization of training and feedback overhead for beamforming over block fading channels
IEEE Transactions on Information Theory
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We consider a narrowband point-to-point communication system with nT transmitters and nR receivers. We assume the receiver has perfect knowledge of the channel, while the transmitter has no channel knowledge. We consider the case where the receiving antenna array has uncorrelated elements, while the elements of the transmitting array are arbitrarily correlated. Focusing on the case where nT=2, we derive simple analytic expressions for the ergodic average and the cumulative distribution function of the mutual information for arbitrary input (transmission) signal covariance. We then determine the ergodic and outage capacities and the associated optimal input signal covariances. We thus show how a transmitter with covariance knowledge should correlate its transmissions to maximize throughput. These results allow us to derive an exact condition (both necessary and sufficient) that determines when beamforming is optimal for systems with arbitrary number of transmitters and receivers.