IRS-Aided Non-Orthogonal ISAC Systems: Performance Analysis and Beamforming Design
Zhouyuan Yu, Xiaoling Hu, Chenxi Liu, Mugen Peng
Abstract
The fundamental performance of IRS-aided communication/sensing has been extensively studied, demonstrating the benefits of IRS in improving communication rate or sensing accuracy, while that of IRS-aided integrated sensing and communication (ISAC) and the impacts of IRS on the communication-sensing tradeoff are far from being well understood. In this paper, we investigate the fundamental performance of an IRS-aided non-orthogonal ISAC (NO-ISAC) system, where a distributed IRS is deployed to assist concurrent communication and location sensing, occupying non-orthogonal time-frequency resources. We use the modified Cramer-Rao lower bound (CRLB) to characterize the joint communication-sensing performance in a unified manner, and derive its closed-form expression, revealing that IRS affects the communication-sensing tradeoff by allocating its additional spatial resources. By exploiting the modified CRLB, we propose a joint active and passive beamforming algorithm that achieves a good communication-sensing tradeoff. Numerical results demonstrate the advantage of using the unified performance metric (i.e., modified CRLB) for IRS beamforming design over using the SNR metric, and the benefits of applying more IRS elements in enlarging the communication-sensing tradeoff region. Also, we demonstrate the superiority of IRS-aided NO-ISAC systems over IRS-aided time-division ISAC systems, and show IRS-aided NO-ISAC systems can achieve comparable localization performance to IRS-aided localization systems.