On Distributed Lossy Coding of Symmetrically Correlated Gaussian Sources

A distributed lossy compression network with L encoders and a decoder is considered. Each encoder observes a source and sends a compressed version to the decoder. The decoder produces a joint reconstruction of target signals with the mean squared error distortion below a given threshold. It is assum...

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Bibliographic Details
Published in:IEEE transactions on communications Vol. 70; no. 12; p. 1
Main Authors: Zhou, Siyao, Salehkalaibar, Sadaf, Qian, Jingjing, Chen, Jun, Shi, Wuxian, Ge, Yiqun, Tong, Wen
Format: Journal Article
Language:English
Published: New York IEEE 01.12.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Asymptotic analysis
Coders
Decoding
Distortion
distributed source coding
Eigenvalues and eigenfunctions
Lower bounds
Minimization
Rate-distortion
rate-distortion function
Source coding
Upper bound
Upper bounds
vector Gaussian source
ISSN:0090-6778, 1558-0857
Online Access:Get full text
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Summary:A distributed lossy compression network with L encoders and a decoder is considered. Each encoder observes a source and sends a compressed version to the decoder. The decoder produces a joint reconstruction of target signals with the mean squared error distortion below a given threshold. It is assumed that the observed sources can be expressed as the sum of target signals and corruptive noises which are independently generated from two symmetric multivariate Gaussian distributions. The minimum compression rate of this network versus the distortion threshold is referred to as the rate-distortion function, for which an explicit lower bound is established by solving a minimization problem. Our lower bound matches the well-known Berger-Tung upper bound for some values of the distortion threshold. The asymptotic gap between the upper and lower bounds is characterized in the large L limit.
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ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2022.3218822