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Generalized Gaussian Multiterminal Source Coding: The Symmetric Case.

Authors :
Chen, Jun
Xie, Li
Chang, Yameng
Wang, Jia
Wang, Yizhong
Source :
IEEE Transactions on Information Theory; Apr2020, Vol. 66 Issue 4, p2115-2128, 14p
Publication Year :
2020

Abstract

Consider a generalized multiterminal source coding system, where $\binom{\ell }{ m}$ encoders, each observing a distinct size- $m$ subset of $\ell $ ($\ell \geq 2$) zero-mean unit-variance exchangeable Gaussian sources with correlation coefficient $\rho $ , compress their observations in such a way that a joint decoder can reconstruct the sources within a prescribed mean squared error distortion based on the compressed data. The optimal rate-distortion performance of this system was previously known only for the two extreme cases $m=\ell $ (the centralized case) and $m=1$ (the distributed case), and except when $\rho =0$ , the centralized system can achieve strictly lower compression rates than the distributed system under all non-trivial distortion constraints. Somewhat surprisingly, it is established in the present paper that the optimal rate-distortion performance of the afore-described generalized multiterminal source coding system with $m\geq 2$ coincides with that of the centralized system for all distortions when $\rho \leq 0$ and for distortions below an explicit positive threshold (depending on $m$) when $\rho > 0$. Moreover, when $\rho > 0$ , the minimum achievable rate of generalized multiterminal source coding subject to an arbitrary positive distortion constraint $d$ is shown to be within a finite gap (depending on $m$ and $d$) from its centralized counterpart in the large $\ell $ limit except for possibly the critical distortion $d=1-\rho $. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00189448
Volume :
66
Issue :
4
Database :
Complementary Index
Journal :
IEEE Transactions on Information Theory
Publication Type :
Academic Journal
Accession number :
143315410
Full Text :
https://doi.org/10.1109/TIT.2020.2971474