Optimization of MIMO Systems Capacity Using Large Random Matrix Methods
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 approxim...
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doaj-0070990c173f403a9bebca912b3086112020-11-24T22:39:37ZengMDPI AGEntropy1099-43002012-11-0114112122214210.3390/e14112122Optimization of MIMO Systems Capacity Using Large Random Matrix MethodsPhilippe LoubatonFlorian DupuyThis 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.http://www.mdpi.com/1099-4300/14/11/2122large random matricesMIMO systemsaverage mutual informationoptimization of the input covariance matrixiterative water-filling |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Philippe Loubaton Florian Dupuy |
spellingShingle |
Philippe Loubaton Florian Dupuy Optimization of MIMO Systems Capacity Using Large Random Matrix Methods Entropy large random matrices MIMO systems average mutual information optimization of the input covariance matrix iterative water-filling |
author_facet |
Philippe Loubaton Florian Dupuy |
author_sort |
Philippe Loubaton |
title |
Optimization of MIMO Systems Capacity Using Large Random Matrix Methods |
title_short |
Optimization of MIMO Systems Capacity Using Large Random Matrix Methods |
title_full |
Optimization of MIMO Systems Capacity Using Large Random Matrix Methods |
title_fullStr |
Optimization of MIMO Systems Capacity Using Large Random Matrix Methods |
title_full_unstemmed |
Optimization of MIMO Systems Capacity Using Large Random Matrix Methods |
title_sort |
optimization of mimo systems capacity using large random matrix methods |
publisher |
MDPI AG |
series |
Entropy |
issn |
1099-4300 |
publishDate |
2012-11-01 |
description |
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. |
topic |
large random matrices MIMO systems average mutual information optimization of the input covariance matrix iterative water-filling |
url |
http://www.mdpi.com/1099-4300/14/11/2122 |
work_keys_str_mv |
AT philippeloubaton optimizationofmimosystemscapacityusinglargerandommatrixmethods AT floriandupuy optimizationofmimosystemscapacityusinglargerandommatrixmethods |
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1725707975679541248 |