面向下一代无线通信物理层安全的可重构智能表面概览

IF 5.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Open Journal of Vehicular Technology Pub Date : 2024-01-19 DOI:10.1109/OJVT.2023.3348658
Ravneet Kaur;Bajrang Bansal;Sudhan Majhi;Sandesh Jain;Chongwen Huang;Chau Yuen
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引用次数: 0

摘要

无线数据流量的空前增长,以及对高度安全、低延迟无线通信不断增长的需求,促使研究界向第六代(6G)技术迈进,使网络能够满足日益增长的对无处不在的安全无线连接的需求。可重构智能表面(RIS)概念是 6G 无线通信领域前景广阔的技术之一,它通过智能控制无线信道条件,成功地应对了日益增长的安全威胁。本调查论文详细综述了下一代无线通信中 RIS 辅助物理层安全(PLS)的文献。首先,我们简要讨论了 PLS 概念、其重要性、PLS 性能指标及其在不同无线网络中的适用性。接着,我们讨论了 RIS 在 6G 场景中的应用。然后,我们对各种 RIS 辅助无线系统拓扑进行了详细、系统的分类,包括多种场景、系统模型、信道衰落模型、性能指标和目标。针对单输入单输出(SISO)情况,讨论了现有的 PLS 先进方法,如密钥生成(SKG)、优化算法(即半无限松弛-后继凸近似(SDR-SCA))以优化 RIS 系数,以及 RIS 单元的最佳位置。对于多输入单输出(MISO)情况,讨论了诱导人工噪音(AN)、优化算法、交替优化(AO)、机器学习(ML)和深度学习(DL)以及反射矩阵等 PLS 策略。同样,对于多输入多输出(MIMO)设置,块坐标下降(BCD)和AN诱导是用于分析保密性的一些 PLS 方法。最后,我们在调查的基础上提出了一些技术挑战和未来发展方向。
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A Survey on Reconfigurable Intelligent Surface for Physical Layer Security of Next-Generation Wireless Communications
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.
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来源期刊
CiteScore
9.60
自引率
0.00%
发文量
25
审稿时长
10 weeks
期刊最新文献
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