ris辅助通信系统中的物理层安全:保密性能分析

IF 2.9 3区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Mustafa Namdar , Arif Basgumus , Serdar Ozgur Ata , Sultan Aldirmaz-Colak
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引用次数: 0

摘要

在这项工作中,研究了一种新的可重构智能表面(RIS)辅助无线通信系统在窃听者存在下的保密性能。本研究旨在表征城市无线网络中存在单天线窃听者的情况下,单天线基站(BS)通过RIS向单天线合法用户发送机密信息的隐私性能。特别推导了新的平均保密能力和近似保密能力表达式。进一步研究了合法用户接收机和单天线窃听器的保密中断概率(SOP)场景。最后,我们还进行了渐近SOP分析,以获得所考虑的系统模型的见解。此外,还考虑了信道状态信息不完善对可实现保密性能的影响,这是实际ris辅助系统中的一个关键因素。分析结果与仿真结果吻合较好,证实了所推导的闭型方程的准确性。从大量的仿真结果可以看出,增加RIS元素的数量可以提高平均保密能力和SOP性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Physical layer security in RIS-aided communication systems: Secrecy performance analyses
In this work, the secrecy performance of a novel reconfigurable intelligent surface (RIS)-assisted wireless communication system is investigated in the presence of an eavesdropper. This study is realized to characterize the privacy performance for the case where a single antenna base station (BS) sends confidential information to a single antenna legitimate user via RIS with the existence of a single antenna eavesdropper in urban wireless networks. In particular, new average secrecy capacity and approximate secrecy capacity expressions are derived. The secrecy outage probability (SOP) scenario for a legitimate user receiver and single antenna eavesdropper is further examined. Finally, the asymptotic SOP analysis is also conducted to obtain insights for the considered system model. Additionally, the impact of imperfect channel state information, a crucial factor in practical RIS-aided systems, on the achievable secrecy performance is also considered. It is verified that the analytical results are consistent with the simulations, which confirm the accuracy of the derived closed-form equations. It can be observed from the extensive simulation results that increasing the number of RIS elements improves both the average secrecy capacity and the SOP performance.
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来源期刊
Digital Signal Processing
Digital Signal Processing 工程技术-工程:电子与电气
CiteScore
5.30
自引率
17.20%
发文量
435
审稿时长
66 days
期刊介绍: Digital Signal Processing: A Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative. The Journal invites top quality research articles at the frontiers of research in all aspects of signal processing. Our objective is to provide a platform for the publication of ground-breaking research in signal processing with both academic and industrial appeal. The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging applications of signal processing such as: • big data• machine learning• internet of things• information security• systems biology and computational biology,• financial time series analysis,• autonomous vehicles,• quantum computing,• neuromorphic engineering,• human-computer interaction and intelligent user interfaces,• environmental signal processing,• geophysical signal processing including seismic signal processing,• chemioinformatics and bioinformatics,• audio, visual and performance arts,• disaster management and prevention,• renewable energy,
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