Multi-Functional RIS Integrated Sensing and Communications for 6G Networks

作     者：Han, Dongsheng Wang, Peng Ni, Wanli Wang, Wen Zheng, Ailing Niyato, Dusit Al-Dhahir, Naofal 

作者机构：The School of Electrical and Electronic Engineering North China Electric Power University Beijing102206 China Hebei Key Laboratory of Power Internet of Things Technology North China Electric Power University Baoding071003 China The Department of Electronic Engineering Tsinghua University Beijing100084 China The Pervasive Communications Center Purple Mountain Laboratories Nanjing211111 China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China The School of Computer Science and Engineering Nanyang Technological University 639798 Singapore The Department of Electrical and Computer Engineering The University of Texas Dallas United States 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2024年

核心收录：

主　　题：Budget control 

摘      要：In this paper, we propose a novel multi-functional reconfigurable intelligent surface (MF-RIS) that supports signal reflection, refraction, amplification, and target sensing simultaneously. Our MF-RIS aims to enhance integrated communication and sensing (ISAC) systems, particularly in multi-user and multi-target scenarios. Equipped with reflection and refraction components (i.e., amplifiers and phase shifters), MF-RIS is able to adjust the amplitude and phase shift of both communication and sensing signals on demand. Additionally, with the assistance of sensing elements, MF-RIS is capable of capturing the echo signals from multiple targets, thereby mitigating the signal attenuation typically associated with multi-hop links. We propose a MF-RIS-enabled multi-user and multi-target ISAC system, and formulate an optimization problem to maximize the signal-to-interference-plus-noise ratio (SINR) of sensing targets. This problem involves jointly optimizing the transmit beamforming and MF-RIS configurations, subject to constraints on the communication rate, total power budget, and MF-RIS coefficients. We decompose the formulated non-convex problem into three sub-problems, and then solve them via an efficient iterative algorithm. Simulation results demonstrate that: 1) The performance of MF-RIS varies under different operating protocols, and energy splitting (ES) exhibits the best performance in the considered MF-RIS-enabled multi-user multi-target ISAC system;2) Under the same total power budget, the proposed MF-RIS with ES protocol attains 52.2%, 73.5%, and 60.86% sensing SINR gains over active RIS, passive RIS, and simultaneously transmitting and reflecting RIS (STAR-RIS), respectively;3) The number of sensing elements will no longer improve sensing performance after exceeding a certain number. © 2024, CC BY.