Information-Theoretic Limits of Bistatic Integrated Sensing and Communication

TL;DR

This paper explores the fundamental limits of bistatic integrated sensing and communication systems using information theory, deriving capacity-distortion bounds and demonstrating benefits over separate systems.

Contribution

It provides the first information-theoretic analysis of bistatic ISAC, deriving capacity-distortion functions and bounds for general and degraded channels, including broadcast scenarios.

Findings

Bistatic ISAC can outperform separate communication and sensing systems.

Single-letter bounds and exact characterizations are established for degraded channels.

Numerical results show the advantages of joint sensing and communication in bistatic setups.

Abstract

Bistatic sensing refers to scenarios where the transmitter (illuminating the target) and the sensing receiver (estimating the target state) are physically separated, in contrast to monostatic sensing, where both functions are co-located. In practical settings, bistatic sensing may be required either due to inherent system constraints or as a means to mitigate the strong self-interference encountered in monostatic configurations. A key practical challenge in bistatic radio-frequency radar systems is the synchronization and calibration of the separate transmitter and sensing receiver. In this paper, we are not concerned with these signal processing aspects and take a complementary information-theoretic perspective on bistatic integrated sensing and communication (ISAC). Namely, we aim to characterize the capacity-distortion function-the fundamental tradeoff between communication capacity and sensing accuracy. We consider a general discrete channel model for a bistatic ISAC system and derive a multi-letter representation of its capacity-distortion function. Then, we establish single-letter upper and lower bounds and provide exact single-letter characterizations for degraded bistatic ISAC channels. Furthermore, we extend our analysis to a bistatic ISAC broadcast channel and derive the capacity-distortion region with a single-letter characterization in the degraded case. Numerical examples illustrate the theoretical results, highlighting the benefits of ISAC over separate communication and sensing, as well as the role of leveraging communication to assist sensing in bistatic systems.