DocumentCode
2943980
Title
An Extremal Inequality Motivated by Multiterminal Information Theoretic Problems
Author
Liu, Tie ; Viswanath, Pramod
Author_Institution
Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL
fYear
2006
fDate
9-14 July 2006
Firstpage
1016
Lastpage
1020
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 problem. As a corollary, this inequality yields a generalization of the classical vector entropy-power inequality (EPI). As another corollary, this inequality sheds insight into maximizing differential entropy of a sum of jointly distributed random variables, generalizing a classical result of Cover and Zhang
Keywords
Gaussian channels; broadcast channels; combined source-channel coding; entropy; differential entropy; distributed source coding; extremal inequality; multiterminal information theoretic problems; quadratic distortion constraint; vector Gaussian broadcast channel; vector entropy-power inequality; Additive noise; Broadcasting; Channel capacity; Constraint theory; Covariance matrix; Distributed computing; Entropy; Random variables; Source coding; Symmetric matrices;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 2006 IEEE International Symposium on
Conference_Location
Seattle, WA
Print_ISBN
1-4244-0505-X
Electronic_ISBN
1-4244-0504-1
Type
conf
DOI
10.1109/ISIT.2006.261881
Filename
4036118
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