Title
Asymptotic Rate-Distortion Analysis of Symmetric Remote Gaussian Source Coding: Centralized Encoding vs. Distributed Encoding.
Abstract
Consider a symmetric multivariate Gaussian source with components, which are corrupted by independent and identically distributed Gaussian noises; these noisy components are compressed at a certain rate, and the compressed version is leveraged to reconstruct the source subject to a mean squared error distortion constraint. The rate-distortion analysis is performed for two scenarios: centralized encoding (where the noisy source components are jointly compressed) and distributed encoding (where the noisy source components are separately compressed). It is shown, among other things, that the gap between the rate-distortion functions associated with these two scenarios admits a simple characterization in the large limit.
Year
DOI
Venue
2019
10.3390/e21020213
ENTROPY
Keywords
Field
DocType
CEO problem,mean squared error,multiterminal source coding,rate-distortion,remote source coding
Mean squared error distortion,Rate distortion,Mathematical optimization,Source code,Algorithm,Mean squared error,Multivariate normal distribution,Gaussian,Independent and identically distributed random variables,Mathematics,Encoding (memory)
Journal
Volume
Issue
ISSN
21
2
1099-4300
Citations 
PageRank 
References 
0
0.34
9
Authors
5
Name
Order
Citations
PageRank
Yizhong Wang110.69
Li Xie216921.63
Siyao Zhou300.34
Mengzhen Wang400.34
Jun Chen573094.14