Scalar Lattices and Probabilistic Shaping for Dithered Wyner-Ziv Quantization

TL;DR

This paper introduces a novel scalar lattice quantization method with dithering and probabilistic shaping for the Wyner-Ziv problem, achieving optimal rate-distortion pairs for Gaussian sources and extending to vector sources.

Contribution

It develops a new scalar lattice quantization approach with probabilistic shaping for Wyner-Ziv coding, including analysis and simulation results.

Findings

Achieves Wyner-Ziv rate-distortion pairs for Gaussian sources

Extends to vector sources using reverse waterfilling

Demonstrates improved performance over traditional scalar quantizers

Abstract

Scalar lattice quantization with a modulo operator, dithering, and probabilistic shaping is applied to the Wyner-Ziv (WZ) problem with a Gaussian source and mean square error distortion. The method achieves the WZ rate-distortion pairs. The analysis is similar to that for dirty paper coding but requires additional steps to bound the distortion because the modulo shift is correlated with the source noise. The results extend to vector sources by reverse waterfilling on the spectrum of the covariance matrix of the source noise. Simulations with short polar codes illustrate the performance and compare with scalar quantizers and polar coded quantization without dithering.