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Security Performance Analysis of Active Intelligent Reflective Surface Assisted Wireless Communication

Yiming Li¹, Xitao Liang¹, Wenwu Xie¹ and Juan Zhu²

1. Hunan Institute of Science and Technology, Department of Information and Communication Engineering Hunan Province, China
2. School of Physics & Electronic Engineering, Hubei University of Arts and Science, Xiang Yang, Hubei Province, China
   journey1022@126.com

Abstract

As a new communication technology, Intelligent Reflecting Surface (IRS) can intelligently reconfigure the wireless propagation environment by integrating many passive/active reflective elements on the plane. According to the characteristics that IRS can adjust the propagation channel intelligently, this paper applies IRS to wireless security communication, and studies how to make the security rate reach the optimal security capacity from the perspective of optimization technology. In this paper, two schemes of passive/active IRS are considered, and the corresponding safety rate maximization algorithm is proposed. In view of the nonconvexity of the objective function, on the one hand, in the passive IRS scheme, the Dinkelbach method is used to transform the objective function into a form that is easy to handle, and the original problem is transformed into a convex problem through the continuous convex approximation method; On the other hand, under the active IRS scheme, aiming at the complexity of the original problem, the first order Taylor expansion is used to obtain the lower bound of the optimization problem, and a minimax optimization algorithm is proposed. Finally, the performance of the proposed algorithm is verified by simulation. The simulation results show that the algorithm designed with active IRS has better security rate than the algorithm designed with passive IRS under the same parameter settings.

Key words

IRS, Physical layer Secrecy, Convex optimization

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS220712011L

Publication information

Volume 20, Issue 2 (April 2023)
Special Issue on Machine Learning-based Decision Support Systems in IoT systems
Year of Publication: 2023
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Li, Y., Liang, X., Xie, W., Zhu, J.: Security Performance Analysis of Active Intelligent Reflective Surface Assisted Wireless Communication. Computer Science and Information Systems, Vol. 20, No. 2, 595–607. (2023), https://doi.org/10.2298/CSIS220712011L