An Information-Theoretic Approach to Joint Sensing and Communication

TL;DR

This paper develops an information-theoretic framework for joint sensing and communication, characterizing the capacity-distortion tradeoff and proposing optimal co-design schemes for shared spectrum systems.

Contribution

It provides a complete characterization of the capacity-distortion tradeoff for single receiver and degraded broadcast channels, introducing numerical methods and bounds for general cases.

Findings

Optimal co-design schemes outperform resource-splitting methods

Capacity-distortion tradeoff characterized for single receiver channels

Inner and outer bounds for general broadcast channels

Abstract

A communication setup is considered where a transmitter wishes to convey a message to a receiver and simultaneously estimates the state of that receiver through a common waveform. The state is estimated at the transmitter by means of generalized feedback, i.e., a strictly causal channel output, and the known waveform. The scenario at hand is motivated by joint radar and communication, which aims to co-design radar sensing and communication over a shared spectrum and hardware. For the case of memoryless single receiver channels with i.i.d. time-varying state sequences, we fully characterize the capacity-distortion tradeoff, defined as the largest achievable rate below which a message can be conveyed reliably while satisfying some distortion constraints on state sensing. We propose a numerical method to compute the optimal input that achieves the capacity-distortion tradeoff. Then, we address memoryless state-dependent broadcast channels (BCs). For physically degraded BCs with i.i.d. time-varying state sequences, we characterize the capacity-distortion tradeoff region as a rather straightforward extension of single receiver channels. For general BCs, we provide inner and outer bounds on the capacity-distortion region, as well as a sufficient condition when this capacity-distortion region is equal to the product of the capacity region and the set of achievable distortions. A number of illustrative examples demonstrate that the optimal co-design schemes outperform conventional schemes that split the resources between sensing and communication.