Finite-Length Bounds for Joint Source-Channel Coding with Markovian Source and Additive Channel Noise to Achieve Large and Moderate Deviation Bounds
Information Theory
2017-05-03 v2 math.IT
Abstract
We derive novel upper and lower finite-length bounds of the error probability in joint source-channel coding when the source obeys an ergodic Markov process and the channel is a Markovian additive channel or a Markovian conditional additive channel. These bounds are tight in the large and moderate deviation regimes.
Keywords
Cite
@article{arxiv.1701.03305,
title = {Finite-Length Bounds for Joint Source-Channel Coding with Markovian Source and Additive Channel Noise to Achieve Large and Moderate Deviation Bounds},
author = {Ryo Yaguchi and Masahito Hayashi},
journal= {arXiv preprint arXiv:1701.03305},
year = {2017}
}
Comments
This paper and arXiv:1701.03290 address joint source-channel coding with markovian source. While arXiv:1701.03290 discusses the second order analysis, this paper discusses finite-length bounds as well as large and moderate deviation bounds. Hence, there is no overlap between these two papers