Multi-User ISAC with Heterogeneous Unknown Parameters: Optimal Beamforming based on Distribution Information

TL;DR

This paper develops an optimal beamforming strategy for multi-user ISAC systems with unknown parameters, leveraging distribution information to enhance sensing and communication performance.

Contribution

It introduces a novel beamforming optimization framework that accounts for heterogeneous unknown parameters and derives the optimal solution using SDR and duality.

Findings

Optimal beamforming minimizes periodic PCRB for angle sensing.

At most one dedicated sensing beam is needed for optimal performance.

Numerical results confirm the effectiveness of the proposed design.

Abstract

This paper studies an integrated sensing and communication (ISAC) system where a multi-antenna base station (BS) communicates with multiple single-antenna users in the downlink and senses the unknown and random angle information of a target based on its prior distribution information and the received echo signals. We focus on a challenging scenario with heterogeneous unknown parameters where the target's reflection coefficient is also unknown with no prior information. We consider a general transmit beamforming structure with both communication beams and dedicated sensing beams, where the communication users can cancel the interference caused by the pre-determined sensing signals. By adopting the periodic posterior Cramer-Rao bound (PCRB) to quantify a lower bound of the mean-cyclic error (MCE) for sensing the periodic angle parameter, we optimize the transmit beamforming to minimize the periodic PCRB, subject to individual communication user rate constraints, which is a non-convex problem. By leveraging the semi-definite relaxation (SDR) technique and Lagrange duality theory, we derive the optimal solution and prove that at most one dedicated sensing beam is needed. Numerical results validate our analysis and effectiveness of the proposed beamforming design.