Anti-Jamming Design for Integrated Sensing and Communication via Aerial IRS

被引:4
|
作者
Xu, Jinlei [1 ]
Li, Dongdong [2 ]
Zhu, Zhengyu [3 ]
Yang, Zhutian [2 ]
Zhao, Nan [1 ]
Niyato, Dusit [4 ]
机构
[1] Dalian Univ Technol, Sch Informat & Commun Engn, Dalian 116024, Peoples R China
[2] Harbin Inst Technol, Sch Elect & Informat Engn, Harbin 150001, Peoples R China
[3] Zhengzhou Univ, Sch Elect & Informat Engn, Zhengzhou 450001, Peoples R China
[4] Nanyang Technol Univ, Coll Comp & Data Sci, Singapore 639798, Singapore
基金
中国国家自然科学基金;
关键词
Jamming; Array signal processing; Sensors; Signal to noise ratio; Wireless communication; Receivers; Interference; Integrated sensing and communication; aerial intelligent reflecting surface; anti-jamming; deployment optimization; RESOURCE-ALLOCATION; OPTIMIZATION; SYSTEMS; ROBUST;
D O I
10.1109/TCOMM.2024.3375809
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Integrated sensing and communication (ISAC) systems can suffer from malicious jamming attacks due to the open nature of wireless channels. Deploying aerial intelligent reflecting surface (AIRS) can flexibly configure the propagation environment of ISAC to address this threat. In this paper, we propose an anti-jamming scheme for ISAC via AIRS. Our goal is to maximize the achievable sum rate by jointly optimizing the transmitting beamforming at the dual-function base station, as well as the phase shift matrix and deployment of AIRS, while satisfying the echo signal-to-interference-plus-noise ratio requirement of target sensing. To handle this non-convex problem with multiple coupled variables, we decompose it into three sub-problems and solve them via the alternate optimization. We first introduce auxiliary variables to convert the transmit beamforming sub-problem into a convex counterpart and solve it via semi-definite relaxation. Then, the IRS phase-shift design is transformed into an equivalent rank-constrained problem, and the penalty-based method and the first-order Taylor expansion are leveraged to calculate the passive beamforming. Finally, with the optimized active and passive beamformings, we resort to successive convex approximation to optimize the AIRS deployment. Simulation results are presented to verify the feasibility and effectiveness of the proposed scheme.
引用
收藏
页码:4607 / 4619
页数:13
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