Distributed Source Coding, Multiple Description Coding, and Source Coding with Side Information at Decoders Using Constrained-Random Number Generators

TL;DR

This paper unifies various source coding paradigms, characterizes their rate-distortion regions using entropy functions, and proposes a code construction based on constrained-random number generators to achieve these bounds.

Contribution

It clarifies the equivalence between distributed source coding and multiple description coding with side information and provides a new code construction approach.

Findings

Established the equivalence between two coding paradigms.

Characterized the multi-letter rate-distortion region for general sources.

Proposed a code construction based on constrained-random number generators.

Abstract

This paper investigates a unification of distributed source coding, multiple description coding, and source coding with side information at decoders. The equivalence between the multiple-decoder extension of distributed source coding with decoder side information and the multiple-source extension of multiple description coding with decoder side information is clarified. Their multi-letter rate-distortion region for arbitrary general correlated sources is characterized in terms of entropy functions. We construct a code based on constrained-random number generators and show its achievability.