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Secrecy Efficiency Maximization in Intelligent Reflective Surfaces Assisted UAV Communications

Hui Wei, Leibing Yan*

School of Electronic Information Engineering, Henan Institute of Technology, Xinxiang, 453003, China

* Corresponding Author: Leibing Yan. Email: email

(This article belongs to this Special Issue: Recent Advances in Backscatter and Intelligent Reflecting Surface Communications for 6G-enabled Internet of Things Networks)

Computer Modeling in Engineering & Sciences 2023, 137(2), 1805-1824. https://doi.org/10.32604/cmes.2023.028072

Abstract

This paper focuses on the secrecy efficiency maximization in intelligent reflecting surface (IRS) assisted unmanned aerial vehicle (UAV) communication. With the popularization of UAV technology, more and more communication scenarios need UAV support. We consider using IRS to improve the secrecy efficiency. Specifically, IRS and UAV trajectories work together to counter potential eavesdroppers, while balancing the secrecy rate and energy consumption. The original problem is difficult to solve due to the coupling of optimization variables. We first introduce secrecy efficiency as an auxiliary variable and propose relaxation optimization problem, and then prove the equivalence between relaxation problem and the original problem. Then an iterative algorithm is proposed by applying the block coordinate descent (BCD) method and the inner approximation method. The simulation results show that the proposed algorithm converges fast and is superior to the existing schemes. In addition, in order to improve the robustness of the algorithm, we also pay attention to the case of obtaining imperfect channel state information (CSI).

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Cite This Article

Wei, H., Yan, L. (2023). Secrecy Efficiency Maximization in Intelligent Reflective Surfaces Assisted UAV Communications. CMES-Computer Modeling in Engineering & Sciences, 137(2), 1805–1824.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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