On Real-Time Communication Systems with Noisy Feedback

TL;DR

This paper develops a systematic method to find optimal encoding, decoding, and memory update strategies for real-time communication systems with noisy feedback, aiming to minimize total expected distortion over a finite horizon.

Contribution

It introduces a sequential decomposition and nested optimality equations to determine globally optimal strategies in noisy feedback communication systems.

Findings

Provides a set of nested optimality equations for strategy optimization.

Offers a systematic methodology for joint source-channel encoding and decoding.

Achieves minimized expected distortion in real-time noisy feedback communication.

Abstract

We consider a real-time communication system with noisy feedback consisting of a Markov source, a forward and a backward discrete memoryless channels, and a receiver with finite memory. The objective is to design an optimal communication strategy (that is, encoding, decoding, and memory update strategies) to minimize the total expected distortion over a finite horizon. We present a sequential decomposition for the problem, which results in a set of nested optimality equations to determine optimal communication strategies. This provides a systematic methodology to determine globally optimal joint source-channel encoding and decoding strategies for real-time communication systems with noisy feedback.