On the Generalized Gaussian CEO Problem

This paper considers a distributed source coding (DSC) problem where L encoders observe noisy linear combinations of K correlated remote Gaussian sources, and separately transmit the compressed observations to the decoder to reconstruct the remote sources subject to a sum-distortion constraint. This...

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Bibliographic Details
Published in:IEEE transactions on information theory Vol. 58; no. 6; pp. 3350 - 3372
Main Authors: Yang, Yang, Xiong, Zixiang
Format: Journal Article
Language:English
Published: New York IEEE 01.06.2012
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Coding theory
Compressed
Covariance matrix
Decoding
Differential scanning calorimetry
Distributed source coding (DSC)
Encoders
Entropy
Equivalence
Gaussian
Gaussian CEO problem
Inequalities
Joints
multiterminal source coding
Noise measurement
Normal distribution
Optimization
rate region
remote sources
Source coding
sum rate
Transforms
Upper bound
ISSN:0018-9448, 1557-9654
Online Access:Get full text
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Summary:This paper considers a distributed source coding (DSC) problem where L encoders observe noisy linear combinations of K correlated remote Gaussian sources, and separately transmit the compressed observations to the decoder to reconstruct the remote sources subject to a sum-distortion constraint. This DSC problem is referred to as the generalized Gaussian CEO problem since it can be viewed as a generalization of the quadratic Gaussian CEO problem where the number of remote source K =1. First, we provide a new outer region obtained using the entropy power inequality and an equivalent argument (in the sense of having the same rate-distortion region and Berger-Tung inner region) among a certain class of generalized Gaussian CEO problems. We then give two sufficient conditions for our new outer region to match the inner region achieved by Berger-Tung schemes, where the second matching condition implies that in the low-distortion regime, the Berger-Tung inner rate region is always tight, while in the high-distortion regime, the same region is tight if a certain condition holds. The sum-rate part of the outer region is also studied and shown to meet the Berger-Tung sum-rate upper bound under a certain condition, which is obtained using the Karush-Kuhn-Tucker conditions of the underlying convex semidefinite optimization problem, and is in general weaker than the aforesaid two for rate region tightness.
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ISSN:0018-9448
1557-9654
DOI:10.1109/TIT.2012.2184667