{"title":"A Survey on Reconfigurable Intelligent Surface for Physical Layer Security of Next-Generation Wireless Communications","authors":"Ravneet Kaur;Bajrang Bansal;Sudhan Majhi;Sandesh Jain;Chongwen Huang;Chau Yuen","doi":"10.1109/OJVT.2023.3348658","DOIUrl":null,"url":null,"abstract":"Unprecedented growth in wireless data traffic, and ever-increasing demand for highly secured, and low-latency wireless communication has motivated the research community to move towards sixth-generation (6G) technology, where networks can cater to the rising need for ubiquitous secure wireless connectivity. One of the promising technologies for 6G wireless communication is the reconfigurable intelligent surface (RIS) concept that is proposed to successfully deal with increasing security threats by smartly controlling the wireless channel conditions. This survey paper presents a detailed literature review on RIS-assisted physical layer security (PLS) for next-generation wireless communications. Firstly, we briefly discuss the PLS concept, its importance, the PLS performance metrics, and its applicability in different wireless networks. Next, we discuss the applications of RIS in the 6G scenario. Then, a detailed and systematic classification of the various RIS-assisted wireless system topologies exhibiting multiple scenarios, system models, channel fading models, performance metrics and objectives is done. The existing state-of-art approaches for PLS such as secret key generation (SKG), optimization algorithms, namely semidefinite relaxation-successive convex approximation (SDR-SCA) to optimize RIS coefficients, and optimal placement of RIS units are discussed for single-input single-output (SISO) case. For multiple-input single-output (MISO) case, PLS strategies such as inducing artificial noise (AN), optimization algorithms, alternating optimization (AO), machine learning (ML) and deep learning (DL), and reflect matrices are discussed. Similarly, for multiple-input multiple-output (MIMO) setup, block coordinate descent (BCD) and AN induction are some of the PLS methods used to analyze the secrecy. Lastly, we present some of the technical challenges and future directions based on the survey.","PeriodicalId":34270,"journal":{"name":"IEEE Open Journal of Vehicular Technology","volume":"5 ","pages":"172-199"},"PeriodicalIF":5.3000,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10409564","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Journal of Vehicular Technology","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10409564/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Unprecedented growth in wireless data traffic, and ever-increasing demand for highly secured, and low-latency wireless communication has motivated the research community to move towards sixth-generation (6G) technology, where networks can cater to the rising need for ubiquitous secure wireless connectivity. One of the promising technologies for 6G wireless communication is the reconfigurable intelligent surface (RIS) concept that is proposed to successfully deal with increasing security threats by smartly controlling the wireless channel conditions. This survey paper presents a detailed literature review on RIS-assisted physical layer security (PLS) for next-generation wireless communications. Firstly, we briefly discuss the PLS concept, its importance, the PLS performance metrics, and its applicability in different wireless networks. Next, we discuss the applications of RIS in the 6G scenario. Then, a detailed and systematic classification of the various RIS-assisted wireless system topologies exhibiting multiple scenarios, system models, channel fading models, performance metrics and objectives is done. The existing state-of-art approaches for PLS such as secret key generation (SKG), optimization algorithms, namely semidefinite relaxation-successive convex approximation (SDR-SCA) to optimize RIS coefficients, and optimal placement of RIS units are discussed for single-input single-output (SISO) case. For multiple-input single-output (MISO) case, PLS strategies such as inducing artificial noise (AN), optimization algorithms, alternating optimization (AO), machine learning (ML) and deep learning (DL), and reflect matrices are discussed. Similarly, for multiple-input multiple-output (MIMO) setup, block coordinate descent (BCD) and AN induction are some of the PLS methods used to analyze the secrecy. Lastly, we present some of the technical challenges and future directions based on the survey.