Dual-Function Radar-Communication Beamforming with Outage Probability Metric

TL;DR

This paper proposes a beamforming method for dual-function radar-communication systems that balances radar and communication performance under imperfect CSI, using outage probability metrics and convex relaxations.

Contribution

It introduces a novel joint beamforming design framework for radar-communication systems considering outage probability, with solutions based on stochastic optimization and semidefinite programming relaxations.

Findings

Effective beamforming strategies for dual radar-communication systems.

Balanced radar and communication performance under imperfect CSI.

Numerical results validate the proposed optimization approach.

Abstract

The integrated design of communication and sensing may offer a potential solution to address spectrum congestion. In this work, we develop a beamforming method for a dual-function radar-communication system, where the transmit signal is used for both radar surveillance and communication with multiple downlink users, despite imperfect channel state information (CSI). We focus on two scenarios of interest: radar-centric and communication-centric. In the radar-centric scenario, the primary goal is to optimize radar performance while attaining acceptable communication performance. To this end, we minimize a weighted sum of the mean-squared error in achieving a desired beampattern and a mean-squared cross correlation of the radar returns from directions of interest (DOI). We also seek to ensure that the probability of outage for the communication users remains below a desired threshold. In the communication-centric scenario, our main objective is to minimize the maximum probability of outage among the communication users while keeping the aforementioned radar metrics below a desired threshold. Both optimization problems are stochastic and untractable. We first take advantage of central limit theorem to obtain deterministic non-convex problems and then consider relaxations of these problems in the form of semidefinite programs with rank-1 constraints. We provide numerical experiments demonstrating the effectiveness of the proposed designs.