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ZHU Zhengyu, YANG Chenyi, LI Zheng, HAO Wanming, YANG Jing, SUN Gangcan. Resource Allocation Algorithm for Intelligent Reflecting Surface-assisted Secure Integrated Sensing And Communications System[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240083
Citation: ZHU Zhengyu, YANG Chenyi, LI Zheng, HAO Wanming, YANG Jing, SUN Gangcan. Resource Allocation Algorithm for Intelligent Reflecting Surface-assisted Secure Integrated Sensing And Communications System[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240083

Resource Allocation Algorithm for Intelligent Reflecting Surface-assisted Secure Integrated Sensing And Communications System

doi: 10.11999/JEIT240083
Funds:  The National Key R&D Program of China (2022YFD2001200), The National Natural Science Foundation of China (61922072), China Postdoctoral Science Foundation (2023T160596), The Natural Science Foundation of Henan Province (232300421097), The Program for Science & Technology Innovation Talents in Universities of Henan Province (23HASTIT019), Henan Postdoctoral Foundation (202001015), The Open Research Fund of National Mobile Communications Research Laboratory, Southeast University (2023D11)
  • Received Date: 2024-02-04
  • Rev Recd Date: 2024-05-04
  • Available Online: 2024-05-17
  • In order to solve the problems of information security, and spectrum limitation in Integrated Sensing And Communications (ISAC) systems, a secure resource allocation scheme in Intelligent Reflecting Surface (IRS)-assisted ISAC systems is investigated in this paper. To start with, in this IRS-ISAC system, where the user is being maliciously attacked by eavesdroppers, the security of the system is ensured by incorporating a jammer and deploying an IRS that utilizes its intelligent regulation of the wireless environment. Then, a secrecy rate maximization problem that subjects to the maximum transmit power constraints of the base station and the jammer, the IRS reflecting phase shift constraints, and the radar’s signal-to-noise ratio constraints is formulated by jointly designing the transmit beamforming of base station, jammer precoding vectors, and IRS phase shifts. Next, utilizing techniques such as alternating optimization and Semi-Definite Relaxation (SDR) algorithm, the original non-convex optimization problem is reformulated into a convex optimization problem, capable of determining a definitive solution. Finally, simulation results verify the security and effectiveness of the proposed algorithm and the superiority of the IRS-ISAC system.
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