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RIS-Assisted Physical Layer Security in Emerging RF and Optical Wireless Communications Systems: A Comprehensive Survey


Abstract:

Security and latency are crucial aspects in the design of future wireless networks. Physical layer security (PLS) has received a growing interest from the research commun...Show More

Abstract:

Security and latency are crucial aspects in the design of future wireless networks. Physical layer security (PLS) has received a growing interest from the research community in recent years for its ability to safeguard data confidentiality without relying on key distribution or encryption/decryption, and for its latency advantage over bit-level cryptographic techniques. However, the evolution towards the fifth generation wireless technology and beyond poses new security challenges that must be addressed in order to fulfill the unprecedented performance requirements of future wireless communications networks. Among the potential key-enabling technologies, reconfigurable intelligent surface (RIS) has attracted extensive attention due to its ability to proactively and intelligently reconfigure the wireless propagation environment to combat dynamic channel impairments. Consequently, the RIS technology can be adopted to improve the information-theoretic security of both radio frequency (RF) and optical wireless communications (OWC) systems. It is worth noting that the configuration of RIS in RF communications is different from that in optical systems at many levels (e.g., RIS materials, signal characteristics, and functionalities). This survey article provides a comprehensive overview of the information-theoretic security of RIS-based RF and optical systems. The article first discusses the fundamental concepts of PLS and RIS technologies, followed by their combination in both RF and OWC systems. Subsequently, some optimization techniques are presented in the context of the underlying system model, followed by an assessment of the impact of RIS-assisted PLS through a comprehensive performance analysis. Given that the computational complexity of future communications systems that adopt RIS-assisted PLS is likely to increase rapidly as the number of interactions between the users and infrastructure grows, machine learning (ML) is seen as a promising approach to address this...
Published in: IEEE Communications Surveys & Tutorials ( Volume: 27, Issue: 4, August 2025)
Page(s): 2156 - 2203
Date of Publication: 28 October 2024

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I. Introduction

Despite the enormous potential of the fifth generation (5G) technology as a key enabler for the Internet-of-Everything (IoE), it is anticipated that the rapid emergence of fully intelligent and automated systems such as tactile Internet, industrial automation, augmented reality (AR), mixed reality (MR), virtual reality (VR), telemedicine, haptics, flying vehicles, brain-computer interfaces, and connected autonomous systems, will overburden the capacity and limit the performance of 5G mobile networks in supporting the stringent requirements of next-generation networks such as extremely high-spectrum- and energy-efficiency, ultra-low latency, ultra-massive and ubiquitous wireless connectivity, full dimensional network coverage, as well as connected intelligence [1], [2], [3]. As a result, there have been intensive research efforts from both industry and academia devoted to the sixth generation (6G) wireless technology to meet such technical requirements and demands as it is expected to provide much improved key performance indicators (KPIs) [4], [5]. Fig. 1 shows a comparison between the 5G and 6G technologies in terms of some important KPIs, including peak data rate, maximum bandwidth, energy efficiency, mobility, reliability, latency, connection density, and spectral efficiency.

Comparison of some KPIs between 5G and 6G communications systems [5, Table IV].

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