Integrated Sensing and Communications With Reconfigurable Intelligent Surfaces: From signal modeling to processing

被引:44
作者
Chepuri S.P. [1 ]
Shlezinger N. [2 ]
Liu F. [3 ]
Alexandropoulos G.C. [4 ]
Buzzi S. [5 ]
Eldar Y.C. [6 ]
机构
[1] Indian Institute of Science, Department of Electrical and Computer Engineering, Bengaluru
[2] Ben-Gurion University of the Negev, School of Electrical and Computer Engineering, Be'er Sheva
[3] Southern University of Science and Technology, Shenzhen
[4] School of Sciences, National and Kapodistrian University of Athens, Department of Informatics and Telecommunications, Athens
[5] University of Cassino and Lazio Meridionale, Cassino
[6] Weizmann Institute of Science, Department of Mathematics and Computer Science, Rehovot
关键词
Compilation and indexing terms; Copyright 2025 Elsevier Inc;
D O I
10.1109/MSP.2023.3279986
中图分类号
学科分类号
摘要
Integrated sensing and communications (ISAC) are envisioned to be an integral part of future wireless networks, especially when operating at the millimeter-wave (mm-wave) and terahertz (THz) frequency bands. However, establishing wireless connections at these high frequencies is quite challenging, mainly due to the penetrating path loss that prevents reliable communication and sensing. Another emerging technology for next-generation wireless systems is reconfigurable intelligent surface (RIS), which refers to hardware-efficient planar structures capable of modifying harsh propagation environments. In this article, we provide a tutorial-style overview of the applications and benefits of RISs for sensing functionalities in general, and for ISAC systems in particular. We highlight the potential advantages when fusing these two emerging technologies, and identify for the first time that 1) joint sensing and communications (S&C) designs are most beneficial when the channels referring to these operations are coupled, and that 2) RISs offer the means for controlling this beneficial coupling. The usefulness of RIS-aided ISAC goes beyond the obvious individual gains of each of these technologies in both performance and power efficiency. We also discuss the main signal processing challenges and future research directions that arise from the fusion of these two emerging technologies. © 1991-2012 IEEE.
引用
收藏
页码:41 / 62
页数:21
相关论文
共 48 条
[41]  
Chiriyath A.R., Paul B., Bliss D.W., Radar-communications convergence: Coexistence, cooperation, and co-design, IEEE Trans. Cogn. Commun. Netw., 3, 1, pp. 1-12, (2017)
[42]  
Abeywickrama S., Zhang R., Wu Q., Yue C., Intelligent reflecting surface: Practical phase shift model and beamforming optimization, IEEE Trans. Commun., 68, 9, pp. 5849-5863, (2020)
[43]  
Van Trees H.L., Optimum Array Processing: Part IV of Detection, Estimation, and Modulation Theory, (2004)
[44]  
Liu F., Liu Y.-F., Li A., Masouros C., Eldar Y.C., Cramér-Rao bound optimization for joint radar-communication beamforming, IEEE Trans. Signal Process., 70, pp. 240-253, (2022)
[45]  
Meng X., Liu F., Lu S., Chepuri S.P., Masouros C., RIS-assisted integrated sensing and communications: A subspace rotation approach, Proc. IEEE Radar Conf. (RadarConf23), pp. 1-6, (2023)
[46]  
Alexandropoulos G.C., Shlezinger N., Del Hougne P., Reconfigurable intelligent surfaces for rich scattering wireless communications: Recent experiments, challenges, and opportunities, IEEE Commun. Mag., 59, 6, pp. 28-34, (2021)
[47]  
Ma D., Shlezinger N., Huang T., Liu Y., Eldar Y.C., FRaC: FMCW-based joint radar-communications system via index modulation, IEEE J. Sel. Topics Signal Process., 15, 6, pp. 1348-1364, (2021)
[48]  
Jing X., Liu F., Masouros C., Zeng Y., ISAC from the sky: UAV trajectory design for joint communication and target localization, (2022)