Distributed Arithmetic Coding for the Asymmetric Slepian-Wolf problem

TL;DR

This paper introduces distributed arithmetic coding for the Slepian-Wolf problem, leveraging arithmetic codes' dual role as source and channel codes, offering improved performance at small block lengths and flexible source modeling.

Contribution

It proposes a novel distributed arithmetic coding scheme with a soft joint decoder for Slepian-Wolf coding, enhancing performance and model flexibility over existing methods.

Findings

Competitive performance compared to turbo and LDPC codes

Effective at small block lengths

Supports arbitrary source models

Abstract

Distributed source coding schemes are typically based on the use of channels codes as source codes. In this paper we propose a new paradigm, termed "distributed arithmetic coding", which exploits the fact that arithmetic codes are good source as well as channel codes. In particular, we propose a distributed binary arithmetic coder for Slepian-Wolf coding with decoder side information, along with a soft joint decoder. The proposed scheme provides several advantages over existing Slepian-Wolf coders, especially its good performance at small block lengths, and the ability to incorporate arbitrary source models in the encoding process, e.g. context-based statistical models. We have compared the performance of distributed arithmetic coding with turbo codes and low-density parity-check codes, and found that the proposed approach has very competitive performance.