DocumentCode
818449
Title
An Extremal Inequality Motivated by Multiterminal Information-Theoretic Problems
Author
Liu, Tie ; Viswanath, Pramod
Author_Institution
Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX
Volume
53
Issue
5
fYear
2007
fDate
5/1/2007 12:00:00 AM
Firstpage
1839
Lastpage
1851
Abstract
We prove a new extremal inequality, motivated by the vector Gaussian broadcast channel and the distributed source coding with a single quadratic distortion constraint problems. As a corollary, this inequality yields a generalization of the classical entropy-power inequality (EPI). As another corollary, this inequality sheds insight into maximizing the differential entropy of the sum of two dependent random variables
Keywords
Gaussian channels; broadcast channels; entropy codes; source coding; EPI; distributed source coding; entropy-power inequality; extremal inequality motivation; multiterminal information-theoretic problem; single quadratic distortion constraint problem; vector Gaussian broadcast channel; Additive noise; Broadcasting; Channel coding; Covariance matrix; Entropy; Information theory; Random variables; Source coding; Differential entropy; Fisher information; distributed source coding; entropy- power inequality (EPI); vector Gaussian broadcast channel;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/TIT.2007.894680
Filename
4167742
Link To Document