A Constrained Channel Coding Approach to Joint Communication and Channel Estimation

TL;DR

This paper investigates the fundamental limits of joint communication and channel estimation by formulating it as a constrained channel coding problem, balancing information rate and estimation accuracy.

Contribution

It introduces a capacity-distortion function that characterizes the tradeoff between data transmission and channel estimation fidelity.

Findings

Derived the capacity-distortion function for joint communication and estimation

Illustrated results through case studies

Discussed extensions like multiple constraints and channel uncertainty

Abstract

A joint communication and channel state estimation problem is investigated, in which reliable information transmission over a noisy channel, and high-fidelity estimation of the channel state, are simultaneously sought. The tradeoff between the achievable information rate and the estimation distortion is quantified by formulating the problem as a constrained channel coding problem, and the resulting capacity-distortion function characterizes the fundamental limit of the joint communication and channel estimation problem. The analytical results are illustrated through case studies, and further issues such as multiple cost constraints, channel uncertainty, and capacity per unit distortion are also briefly discussed.