DocumentCode
639966
Title
A new extremal entropy inequality with applications
Author
Hon-Fah Chong ; Ying-Chang Liang
Author_Institution
Inst. for Infocomm Res., Singapore, Singapore
fYear
2013
fDate
7-12 July 2013
Firstpage
609
Lastpage
613
Abstract
Liu et al. proved an extremal entropy inequality using a vector generalization of the Costa entropy-power inequality (EPI). The generalized Costa EPI was proved, in turn, using a perturbation approach via a fundamental relationship between the derivative of mutual information and the minimum mean-square error (MMSE) estimate in linear vector Gaussian channels. In this paper, we consider two new variations of the (Liu et al.) extremal entropy inequality. Instead of employing perturbation approaches, we employ a new method recently introduced by Geng and Nair, which was used to resolve the capacity region of the Gaussian MIMO broadcast channel (BC) with common and private messages. As an application, we use one of the extremal entropy inequalities to prove the capacity region of a class of reversely degraded Gaussian MIMO BC with three users and three-degraded message sets.
Keywords
Gaussian channels; MIMO communication; broadcast channels; channel capacity; entropy; least mean squares methods; perturbation techniques; vectors; Gaussian MIMO broadcast channel capacity; MMSE; entropy power inequality; extremal entropy inequality; generalized Costa EPI; linear vector Gaussian channel; message sets; minimum mean square error; mutual information; perturbation approach; reversely degraded Gaussian MIMO BC; vector generalization; Additives; Covariance matrices; Entropy; Information theory; MIMO; Receivers; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory Proceedings (ISIT), 2013 IEEE International Symposium on
Conference_Location
Istanbul
ISSN
2157-8095
Type
conf
DOI
10.1109/ISIT.2013.6620298
Filename
6620298
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