Deterministic Annealing-Based Optimization for Zero-Delay Source-Channel Coding in Networks

This paper studies the problem of global optimization of zero-delay source-channel codes that map between the source space and the channel space, under a given transmission power constraint and for the mean-square-error distortion. Particularly, we focus on two well-known network settings: the Wyner...

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Vydáno v:IEEE transactions on communications Ročník 63; číslo 12; s. 5089 - 5100
Hlavní autoři: Mehmetoglu, Mustafa Said, Akyol, Emrah, Rose, Kenneth
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.12.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Annealing
Channel coding
Channels
Coders
Codes
Computational modeling
Decoders
Decoding
deterministic annealing
distributed coding
Encoders
Entropy
estimation
Joint source channel coding
Mathematical model
Mathematical models
Networks
Optimization
estimation
deterministic annealing
distributed coding
Joint source channel coding
ISSN:0090-6778, 1558-0857
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Shrnutí:This paper studies the problem of global optimization of zero-delay source-channel codes that map between the source space and the channel space, under a given transmission power constraint and for the mean-square-error distortion. Particularly, we focus on two well-known network settings: the Wyner-Ziv setting where only a decoder has access to side information and the distributed setting where independent encoders transmit over independent channels to a central decoder. Prior work derived the necessary conditions for optimality of the encoder and decoder mappings, along with a greedy optimization algorithm that imposes these conditions iteratively, in conjunction with the heuristic noisy channel relaxation method to mitigate poor local minima. While noisy channel relaxation is arguably effective in simple settings, it fails to provide accurate global optimization in more complicated settings considered in this paper. We propose a powerful nonconvex optimization method based on the concept of deterministic annealing-which is derived from information theoretic principles and was successfully employed in several problems including vector quantization, classification, and regression. We present comparative numerical results that show strict superiority of the proposed method over greedy optimization methods as well as prior approaches in literature.
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ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2015.2494004