Approximation of DAC Codeword Distribution for Equiprobable Binary Sources along Proper Decoding Paths

TL;DR

This paper introduces three approximation methods—numeric, polynomial, and Gaussian—for analyzing DAC codeword distribution in equiprobable binary sources, enhancing understanding of its properties across different rates.

Contribution

It proposes novel approximation techniques for DAC codeword distribution along proper decoding paths, addressing the difficulty of deriving closed-form solutions in general cases.

Findings

Numeric approximation effectively estimates DAC codeword distribution.

Polynomial approximation is accurate at rates below 0.5.

Gaussian approximation is suitable at very low rates, with a proposed variance estimation.

Abstract

Distributed Arithmetic Coding (DAC) is an effective implementation of Slepian-Wolf coding, especially for short data blocks. To research its properties, the concept of DAC codeword distribution along proper and wrong decoding paths has been introduced. For DAC codeword distribution of equiprobable binary sources along proper decoding paths, the problem was formatted as solving a system of functional equations. However, up to now, only one closed form was obtained at rate 0.5, while in general cases, to find the closed form of DAC codeword distribution still remains a very difficult task. This paper proposes three kinds of approximation methods for DAC codeword distribution of equiprobable binary sources along proper decoding paths: numeric approximation, polynomial approximation, and Gaussian approximation. Firstly, as a general approach, a numeric method is iterated to find the approximation to DAC codeword distribution. Secondly, at rates lower than 0.5, DAC codeword distribution can be well approximated by a polynomial. Thirdly, at very low rates, a Gaussian function centered at 0.5 is proved to be a good and simple approximation to DAC codeword distribution. A simple way to estimate the variance of Gaussian function is also proposed. Plenty of simulation results are given to verify theoretical analyses.