Improved Finite Blocklength Converses for Slepian-Wolf Coding via Linear Programming
Abstract
A new finite blocklength converse for the Slepian- Wolf coding problem is presented which significantly improves on the best known converse for this problem, due to Miyake and Kanaya [2]. To obtain this converse, an extension of the linear programming (LP) based framework for finite blocklength point- to-point coding problems from [3] is employed. However, a direct application of this framework demands a complicated analysis for the Slepian-Wolf problem. An analytically simpler approach is presented wherein LP-based finite blocklength converses for this problem are synthesized from point-to-point lossless source coding problems with perfect side-information at the decoder. New finite blocklength metaconverses for these point-to-point problems are derived by employing the LP-based framework, and the new converse for Slepian-Wolf coding is obtained by an appropriate combination of these converses.
Keywords
Cite
@article{arxiv.1801.08693,
title = {Improved Finite Blocklength Converses for Slepian-Wolf Coding via Linear Programming},
author = {Sharu Theresa Jose and Ankur A. Kulkarni},
journal= {arXiv preprint arXiv:1801.08693},
year = {2018}
}
Comments
under review with the IEEE Transactions on Information Theory