Secure Beamforming with IRS-Enhanced Phase Shifting for ISAC Systems

• Published in: IEEE transactions on vehicular technology pp. 1 - 10
• Main Authors: Wang, Zhiyi, Xiao, Yaoqiang, Wang, Jun, Li, Yuqing, Zeng, Yonghong, Sun, Sumei
• Format: Journal Article
• Language: English
• Published: IEEE 2025
• Subjects: Array signal processing; beamforming; Information leakage; Integrated sensing and communication; integrated sensing and communication (ISAC); intelligent reflecting surface (IRS); Interference; Optimization; Physical layer security; Quality of service; Radar; Signal to noise ratio; Wireless communication
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2025.3584330

In this paper, we investigate secure transmission schemes at the physical layer of an intelligent reflecting surface (IRS)-aided integrated sensing and communication (ISAC) system, where a base station (BS) simultaneously communicates with multiple legitimate users and senses multiple malicious eavesdroppers using a multi-user multi-eavesdropper multi-input single-output (MU-ME-MISO) configuration. A key challenge in designing secure ISAC systems arises from balancing effective communication, precise target sensing, and robust security measures simultaneously under practical resource constraints. To address these issues, the IRS is leveraged not only to enhance communication performance but also to prevent confidential information from being intercepted by malicious targets. Furthermore, A dedicated sensing signal is transmitted together with the communication signal from the BS to enhance sensing performance and prevent information leakage. A joint optimization problem of IRS phase shifts and the communication and radar beamformers is formulated to maximize the minimum beampattern gain of all targets, subject to constraints on the minimum signal-to-interference-plus-noise ratio (SINR) requirements for users and the maximum information leakage tolerance for the malicious targets. To solve this challenging problem, an alternating optimization (AO) algorithm based on semi-definite relaxation (SDR) and Gaussian randomization is proposed. Simulation results demonstrate the proposed scheme can effectively enhance quality of service for legitimate users and simultaneously suppress the SINR of eavesdroppers.