Entropy 2012, 14(11), 2122-2142; doi:10.3390/e14112122

Optimization of MIMO Systems Capacity Using Large Random Matrix Methods

1,* email and 2,* email
Received: 12 September 2012; in revised form: 19 October 2012 / Accepted: 24 October 2012 / Published: 1 November 2012
(This article belongs to the Special Issue Information Theory Applied to Communications and Networking)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: This paper provides a comprehensive introduction of large random matrix methods for input covariance matrix optimization of mutual information of MIMO systems. It is first recalled informally how large system approximations of mutual information can be derived. Then, the optimization of the approximations is discussed, and important methodological points that are not necessarily covered by the existing literature are addressed, including the strict concavity of the approximation, the structure of the argument of its maximum, the accuracy of the large system approach with regard to the number of antennas, or the justification of iterative water-filling optimization algorithms. While the existing papers have developed methods adapted to a specific model, this contribution tries to provide a unified view of the large system approximation approach.
Keywords: large random matrices; MIMO systems; average mutual information; optimization of the input covariance matrix; iterative water-filling
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MDPI and ACS Style

Dupuy, F.; Loubaton, P. Optimization of MIMO Systems Capacity Using Large Random Matrix Methods. Entropy 2012, 14, 2122-2142.

AMA Style

Dupuy F, Loubaton P. Optimization of MIMO Systems Capacity Using Large Random Matrix Methods. Entropy. 2012; 14(11):2122-2142.

Chicago/Turabian Style

Dupuy, Florian; Loubaton, Philippe. 2012. "Optimization of MIMO Systems Capacity Using Large Random Matrix Methods." Entropy 14, no. 11: 2122-2142.

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