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
Link To Document :
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