AI 中文总结
本文针对ISAC系统，研究STAR-RIS辅助的安全感知与通信，构建联合优化问题，提出混合BCD算法优化波束成形和STAR-RIS相移，以CRB和保密速率评估性能。
AI 中文摘要
集成感知与通信（ISAC）是一项快速发展的技术，为未来无线网络实现安全通信和智能感知提供了新方法。本文研究由同时传输与反射可重构智能表面（STAR-RIS）赋能的ISAC框架，其中配备多天线的基站在检测点目标的同时，建立与各单天线用户的无线链路；该点目标被视为窃听者，试图拦截用户信息。本文采用克拉美罗界（CRB）评估点窃听者的感知精度，用保密速率衡量通信链路的安全等级，构建优化感知-通信权衡的联合优化问题。为求解该问题，提出一种基于混合块坐标下降（BCD）的算法，交替更新传输波束成形和STAR-RIS相移，采用 successive convex approximation（SCA）技术、penalty dual decomposition（PDD）框架和 projected gradient method（PGM）。
英文摘要
Integrated sensing and communication(ISAC), as a rapidly advancing technique, introduces a fresh approach for achieving secure communication and intelligent sensing for future wireless networks. An ISAC framework empowered by simultaneously transmitting and reflecting reconfigurable intelligent surfaces(STAR-RIS) is explored in this paper, where a base station equipped with multiple antennas establishes wireless links to users each with a single antenna during the detection of a point target. The point target, regarded as an eavesdropper, trying to intercept users' information. Cramer-Rao bound(CRB) serves as evaluation criterion to assess sensing accuracy of point eavesdropper, whereas the secrecy rate is employed to quantify the security level of the communication link. To optimize sensing-communication tradeoff, a joint optimization problem is constructed. To approach the formulated problem, a hybrid Block Coordinate Descent(BCD)-based algorithm is developed, which alternately updates the transmission beamforming and STAR-RIS phase shifts, using successive convex approximation(SCA) technique, penalty dual decomposition (PDD) framework and projected gradient method(PGM).
Journal refH. Zhang, S. Wu, X. Zhang, Z. Wu, X. Ma and Y. Ren, IEEE Journal on Selected Areas in Communications, 2026, 44: 4037-4050
