Article

# Random Beamforming over Correlated Fading Channels

05/2011;
Source: arXiv

ABSTRACT We study a multiple-input multiple-output (MIMO) multiple access channel
(MAC) from several multi-antenna transmitters to a multi-antenna receiver. The
fading channels between the transmitters and the receiver are modeled by random
matrices, composed of independent column vectors with zero mean and different
covariance matrices. Each transmitter is assumed to send multiple data streams
with a random precoding matrix extracted from a Haar-distributed matrix. For
this general channel model, we derive deterministic approximations of the
normalized mutual information, the normalized sum-rate with
minimum-mean-square-error (MMSE) detection and the
signal-to-interference-plus-noise-ratio (SINR) of the MMSE decoder, which
become arbitrarily tight as all system parameters grow infinitely large at the
same speed. In addition, we derive the asymptotically optimal power allocation
under individual or sum-power constraints. Our results allow us to tackle the
problem of optimal stream control in interference channels which would be
intractable in any finite setting. Numerical results corroborate our analysis
and verify its accuracy for realistic system dimensions. Moreover, the
techniques applied in this paper constitute a novel contribution to the field
of large random matrix theory and could be used to study even more involved
channel models.

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05/2011;

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### Keywords

asymptotically optimal power allocation

channel models

general channel model

independent column vectors

infinitely large

interference channels

large random matrix theory

MMSE decoder

multi-antenna transmitters

multiple data streams

multiple-input multiple-output

normalized sum-rate

novel contribution

Numerical results

optimal stream control

random precoding matrix

realistic system dimensions

system parameters

transmitter