DocumentCode :
639883
Title :
Network compression: Worst-case analysis
Author :
Asnani, Himanshu ; Shomorony, Ilan ; Avestimehr, Amir Salman ; Weissman, Tsachy
Author_Institution :
Stanford Univ., Stanford, CA, USA
fYear :
2013
fDate :
7-12 July 2013
Firstpage :
196
Lastpage :
200
Abstract :
We consider the problem of communicating a distributed correlated memoryless source over a memoryless network, from source nodes to destination nodes, under quadratic distortion constraints. We show the following two complementary results: (a) for an arbitrary memoryless network, among all distributed memoryless sources with a particular correlation, Gaussian sources are the worst compressible, that is, they admit the smallest set of achievable distortion tuples, and (b) for any arbitrarily distributed memoryless source to be communicated over a memoryless additive noise network, among all noise processes with a fixed correlation, Gaussian noise admits the smallest achievable set of distortion tuples. In each case, given a coding scheme for the corresponding Gaussian problem, we provide a technique for the construction of a new coding scheme that achieves the same distortion at the destination nodes in a non-Gaussian scenario with the same correlation structure.
Keywords :
Gaussian noise; distortion; encoding; memoryless systems; Gaussian noise; Gaussian sources; arbitrarily distributed memoryless source; arbitrary memoryless network; coding scheme; correlation structure; distortion tuples; distributed correlated memoryless source; distributed memoryless sources; memoryless additive noise network; network compression; nonGaussian scenario; quadratic distortion constraints; worst-case analysis; Additive noise; Covariance matrices; Decoding; Encoding; 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.2013.6620215
Filename :
6620215
Link To Document :
بازگشت