Rician fading multiple-input multiple-output (MIMO) channels with Kronecker-decomposable covariance structure are considered in this study to derive information measures characterizing their achievable rate. Analytic results are obtained in the asymptotic setting corresponding to infinitely many transmit and receive antennas, whose numbers approach a finite limiting ratio. More specifically, the asymptotic mean and variance of the mutual information are derived in this asymptotic regime, and it is shown that the corresponding probability distribution converges to a Gaussian distribution. All these results are based on the replica method, whose mathematical principles are discussed in this study. The ergodic capacity is also addressed by deriving an iterative water-filling algorithm yielding the capacity-achieving input covariance matrix (under an average power constraint). Resorting to the asymptotic Gaussianity of the mutual information distribution, an analytic expression of the outage capacity is derived based on the mean and variance of the mutual information. Finally, numerical results are reported to assess the level of approximation of the analytic results in comparison with those obtained by Monte Carlo simulation.

Further Results on the Asymptotic Mutual Information of Rician Fading MIMO Channels / Taricco, Giorgio. - In: IEEE TRANSACTIONS ON INFORMATION THEORY. - ISSN 0018-9448. - 59:2(2013), pp. 894-915. [10.1109/TIT.2012.2223195]

Further Results on the Asymptotic Mutual Information of Rician Fading MIMO Channels

TARICCO, GIORGIO
2013

Abstract

Rician fading multiple-input multiple-output (MIMO) channels with Kronecker-decomposable covariance structure are considered in this study to derive information measures characterizing their achievable rate. Analytic results are obtained in the asymptotic setting corresponding to infinitely many transmit and receive antennas, whose numbers approach a finite limiting ratio. More specifically, the asymptotic mean and variance of the mutual information are derived in this asymptotic regime, and it is shown that the corresponding probability distribution converges to a Gaussian distribution. All these results are based on the replica method, whose mathematical principles are discussed in this study. The ergodic capacity is also addressed by deriving an iterative water-filling algorithm yielding the capacity-achieving input covariance matrix (under an average power constraint). Resorting to the asymptotic Gaussianity of the mutual information distribution, an analytic expression of the outage capacity is derived based on the mean and variance of the mutual information. Finally, numerical results are reported to assess the level of approximation of the analytic results in comparison with those obtained by Monte Carlo simulation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2505582
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