부산대학교 도서관

As one of the most promising new technologies in the upcoming 6G communication, intelligent reflecting surface (IRS) can significantly improve the reliability of wireless transmission and deal with the security threat in the presence of eavesdroppers by smartly reconfiguring the wireless propagation environment. However, existing research mainly focuses on terrestrial communication networks. In contrast, there is not much research on IRS-aided secure unmanned aerial vehicle (UAV) communication problems, especially for ground-to-air (G2A) communication scenarios with air eavesdroppers that will bring greater security threats. In this article, we consider an IRS-assisted G2A communication network with an altitude-dependent Rician fading channel, where the ground base station (BS) transmits legitimate information to the UAV user in the presence of air eavesdroppers. The transmission power, active and passive beamforming, and UAV 3-D trajectory are jointly optimized to maximize the average secrecy rate. Due to the nonconvexity of the optimization problem, the block coordinate descent method is used to solve it. Specifically, the overall optimization problem is divided into four subproblems, and nonconvex subproblems are solved by successive convex approximation and semidefinite relaxation algorithms. Simulation results show that the proposed alternating optimization algorithm has a good convergence performance and can increase the average secrecy rate by 28% compared with the scenario without IRS assistance.