Joint Active and Passive Beamforming Design for IRS-aided MIMO ISAC Based on Sensing Mutual Information

TL;DR

This paper develops joint active and passive beamforming algorithms for IRS-assisted MIMO ISAC systems to maximize sensing mutual information while satisfying communication QoS, considering both ideal and realistic channel conditions.

Contribution

It introduces novel algorithms for joint beamforming optimization in IRS-aided ISAC, addressing both simplified and general channel scenarios with interference considerations.

Findings

Proposed algorithms outperform benchmarks in sensing MI enhancement.

Joint optimization effectively balances sensing and communication requirements.

Algorithms are validated through numerical simulations under various conditions.

Abstract

In this paper, we investigate the intelligent reflecting surface (IRS)/reconfigurable intelligent surface (RIS)-aided integrated sensing and communication (ISAC) system based on sensing mutual information (MI). Specifically, the base station (BS) perceives the sensing target via the reflected sensing signal by the IRS, while communicating with the users simultaneously. Our aim is to maximize the sensing MI, subject to the quality of service (QoS) constraints for all communication users, the transmit power constraint at the BS, and the unit-modulus constraint on the IRS's passive reflection. We solve this problem under two cases: one simplified case assuming a line-of-sight (LoS) channel between the BS and IRS and no clutter interference to sensing, and the other generalized case considering the Rician fading channel of the BS-IRS link and the presence of clutter interference to sensing. For the first case, we prove that the dedicated sensing beamformer is unnecessary for improving sensing MI and develop a low-complexity iterative algorithm to jointly optimize the BS and IRS active/passive beamformers. Then, for the second case, we propose an alternative iterative algorithm, which can also be applied to the first case, to solve the beamforming design problem under the general setup. Numerical results are provided to validate the performance of the proposed algorithms, as compared to various benchmark schemes.