Joint Source-Channel Coding for the Multiple-Access Channel with Correlated Sources

TL;DR

This paper analyzes the error exponents in joint source-channel coding for multiple-access channels with correlated sources, introducing message-dependent input distributions and optimal thresholds to improve performance over independent source models.

Contribution

It introduces a new approach using message-dependent input distributions and threshold optimization to enhance error exponents in correlated source MAC coding.

Findings

Achievable exponent is larger with message-dependent distributions.

Optimal thresholds significantly improve the error exponent.

Comparison shows benefits over independent source models.

Abstract

This paper studies the random-coding exponent of joint source-channel coding for the multiple-access channel with correlated sources. For each user, by defining a threshold, the messages of each source are partitioned into two classes. The achievable exponent for correlated sources with two message-dependent input distributions for each user is determined and shown to be larger than that achieved using only one input distribution for each user. A system of equations is presented to determine the optimal thresholds maximizing the achievable exponent. The obtained exponent is compared with the one derived for the MAC with independent sources.