Asymptotic Rate-Distortion Analysis of Symmetric Remote Gaussian Source Coding: Centralized Encoding vs. Distributed Encoding

Consider a symmetric multivariate Gaussian source with ℓ 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 er...

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Vydané v:Entropy (Basel, Switzerland) Ročník 21; číslo 2; s. 213
Hlavní autori: Wang, Yizhong, Xie, Li, Zhou, Siyao, Wang, Mengzhen, Chen, Jun
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 23.02.2019
MDPI
Predmet:
CEO problem
Codes
Distortion
Error analysis
mean squared error
multiterminal source coding
Noise
rate-distortion
remote source coding
ISSN:1099-4300, 1099-4300
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Popis
Shrnutí:Consider a symmetric multivariate Gaussian source with ℓ 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 ℓ limit.
Bibliografia:ObjectType-Article-1
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ISSN:1099-4300
1099-4300
DOI:10.3390/e21020213