Blahut-Arimoto Algorithm and Code Design for Action-Dependent Source Coding Problems

TL;DR

This paper introduces an efficient algorithm for the action-dependent source coding problem, providing a practical two-stage code design that approaches theoretical limits in resource-constrained data acquisition scenarios.

Contribution

It presents a novel numerical algorithm with convergence proof and a multiplexing-based code design for action-dependent source coding problems.

Findings

The algorithm accurately computes the rate-distortion-cost function.

The proposed code design achieves near-optimal performance.

Numerical examples validate the effectiveness of the approach.

Abstract

The source coding problem with action-dependent side information at the decoder has recently been introduced to model data acquisition in resource-constrained systems. In this paper, an efficient algorithm for numerical computation of the rate-distortion-cost function for this problem is proposed, and a convergence proof is provided. Moreover, a two-stage code design based on multiplexing is put forth, whereby the first stage encodes the actions and the second stage is composed of an array of classical Wyner-Ziv codes, one for each action. Specific coding/decoding strategies are designed based on LDGM codes and message passing. Through numerical examples, the proposed code design is shown to achieve performance close to the lower bound dictated by the rate-distortion-cost function.