Second Order Analysis for Joint Source-Channel Coding With General Channel and Markovian Source

We derive the optimal second-order rates in joint source-channel coding when the channel is a general discrete memoryless channel and the source is an irreducible and ergodic Markov process. In contrast, previous studies solved it only when the channel satisfies a certain unique-variance condition a...

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Published in:IEEE transactions on information theory Vol. 65; no. 9; pp. 5750 - 5770
Main Authors: Yaguchi, Ryo, Hayashi, Masahito
Format: Journal Article
Language:English
Published: New York IEEE 01.09.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Channel coding
Coding
Convolution
Decoding
Distribution functions
Gaussian distribution
joint source-channel coding
Markov chain
Markov processes
Normal distribution
second order
separation scheme
Switches
ISSN:0018-9448, 1557-9654
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Abstract We derive the optimal second-order rates in joint source-channel coding when the channel is a general discrete memoryless channel and the source is an irreducible and ergodic Markov process. In contrast, previous studies solved it only when the channel satisfies a certain unique-variance condition and the source is subject to an independent and identical distribution. We also compare the joint source-channel scheme with the separation scheme in the second-order regime, while a previous study made a notable comparison with numerical calculation. To discuss these two topics, we introduce two kinds of new distribution families, switched Gaussian convolution distribution and *-product distribution, which are defined by modifying the Gaussian distribution.
AbstractList We derive the optimal second-order rates in joint source-channel coding when the channel is a general discrete memoryless channel and the source is an irreducible and ergodic Markov process. In contrast, previous studies solved it only when the channel satisfies a certain unique-variance condition and the source is subject to an independent and identical distribution. We also compare the joint source-channel scheme with the separation scheme in the second-order regime, while a previous study made a notable comparison with numerical calculation. To discuss these two topics, we introduce two kinds of new distribution families, switched Gaussian convolution distribution and *-product distribution, which are defined by modifying the Gaussian distribution.
Author Yaguchi, Ryo
Hayashi, Masahito
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  surname: Hayashi
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  email: masahito@math.nagoya-u.ac.jp
  organization: Graduate School of Mathematics, Nagoya University, Nagoya, Japan
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SubjectTerms Channel coding
Coding
Convolution
Decoding
Distribution functions
Gaussian distribution
joint source-channel coding
Markov chain
Markov processes
Normal distribution
second order
separation scheme
Switches
Title Second Order Analysis for Joint Source-Channel Coding With General Channel and Markovian Source
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