Rate-Splitting Multiple Access for Transmissive Reconfigurable Intelligent Surface Transceiver Empowered ISAC Systems

被引:2
|
作者
Liu, Ziwei [1 ]
Chen, Wen [1 ]
Wu, Qingqing [1 ]
Yuan, Jinhong [2 ]
Zhang, Shanshan [1 ]
Li, Zhendong [3 ]
Li, Jun [4 ]
机构
[1] Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200240, Peoples R China
[2] Univ New South Wales, Sch Elect Engn & Telecommun, Sydney, NSW 2052, Australia
[3] Xi An Jiao Tong Univ, Sch Informat & Commun Engn, Xian 710049, Peoples R China
[4] Nanjing Univ Sci & Technol, Sch Elect & Opt Engn, Nanjing 210094, Peoples R China
来源
IEEE INTERNET OF THINGS JOURNAL | 2024年 / 11卷 / 16期
基金
澳大利亚研究理事会;
关键词
Difference-of-convex (DC); integrated sensing and communication (ISAC); rate-splitting multiple access (RSMA); sensing quality of service (QoS); transmissive reconfigurable intelligent surface (TRIS); CHANNEL ESTIMATION; COMMUNICATION; DESIGN; RADAR;
D O I
10.1109/JIOT.2024.3397736
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this article, a novel transmissive reconfigurable intelligent surface (TRIS) transceiver empowered integrated sensing and communications (ISAC) system is proposed for future multidemand terminals. To address interference management, we implement rate-splitting multiple access (RSMA), where the common stream is independently designed for the sensing service. We introduce the sensing Quality of Service (QoS) criteria based on this structure and construct an optimization problem with the sensing QoS criteria as the objective function to optimize the sensing stream precoding matrix and the communication stream precoding matrix. Due to the coupling of optimization variables, the formulated problem is a nonconvex optimization problem that cannot be solved directly. To tackle the above-mentioned challenging problem, alternating optimization (AO) is utilized to decouple the optimization variables. Specifically, the problem is decoupled into three subproblems about the sensing stream precoding matrix, the communication stream precoding matrix, and the auxiliary variables, which is solved alternatively through AO until the convergence is reached. For solving the problem, successive convex approximation (SCA) is applied to deal with the sum-rate threshold constraints on communications, and difference-of-convex (DC) programming is utilized to solve rank-one nonconvex constraints. Numerical simulation results verify the superiority of the proposed scheme in terms of improving the communication and sensing QoS.
引用
收藏
页码:27245 / 27259
页数:15
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