Joint Beamforming for Multi-target Detection and Multi-user Communication in ISAC Systems

TL;DR

This paper proposes a joint beamforming method for ISAC systems that enhances weak target detection while maintaining multi-user communication quality, addressing the sensing-communication trade-off.

Contribution

It introduces a max-min optimization framework and an AO algorithm for robust multi-target detection in ISAC systems, a novel approach compared to traditional methods.

Findings

Significantly improves detection probability of weak targets.

Ensures multi-user communication performance is maintained.

Outperforms baseline approaches in numerical simulations.

Abstract

Detecting weak targets is one of the main challenges for integrated sensing and communication (ISAC) systems. Sensing and communication suffer from a performance trade-off in ISAC systems. As the communication demand increases, sensing ability, especially weak target detection performance, will inevitably reduce. Traditional approaches fail to address this issue. In this paper, we develop a joint beamforming scheme and formulate it as a max-min problem to maximize the detection probability of the weakest target under the constraint of the signal-to-interference-plus-noise ratio (SINR) of multi-user communication. An alternating optimization (AO) algorithm is developed for solving the complicated non-convex problem to obtain the joint beamformer. The proposed scheme can direct the transmit energy toward the multiple targets properly to ensure robust multi-target detection performance. Numerical results show that the proposed beamforming scheme can effectively increase the detection probability of the weakest target compared to baseline approaches while ensuring communication performance.