Joint UAV Trajectory, IRS Beamforming, and Power Allocation Optimization for Secure Communication in IRS-Assisted Cognitive Networks - Liu, Xiaoyan (Informatica, 2025)
Based on the challenges faced by unmanned aerial vehicle communication in urban environments, such as signal blockage caused by building obstruction, limited spectrum resources, and dynamic security threats, this article aims to improve the safety communication performance of unmanned aerial vehicles through intelligent reflective surface (IRS) technology, and solve the problems of signal obstruction and cognitive radio interference. Moreover, this paper proposes an innovative multi-parameter collaborative optimization method, constructs a three-dimensional channel model including Rayleigh/Rice fading, designs an IRS-trajectory-power three-dimensional coordination algorithm based on alternating optimization, and solves the IRS phase shift matrix through semi-steady relaxation (SDR), optimizes the UAV trajectory through continuous convex approximation (SCA), and allocates power through Lagrangian dual decomposition to achieve iterative updates of the three modules. Numerical simulation verification: 1) The safe capacity reaches 1.85 ± 0.12 bit/s/Hz, which is 30.3% higher than the optimal control group; 2) The interference suppression rate is 94.3 ± 2.1%, and the NFZ (No fly zones) avoidance success rate is 100%; 3) The energy efficiency is 1.58 ± 0.11 bit/Joule, which is 30.6% higher than the SOTA model. The conclusion shows that the three-dimensional collaborative mechanism of IRS trajectory power can break through the bottleneck of traditional optimization, and its core contribution lies in: 1) solving the shortcomings of existing research in dynamic security response, multi device interference suppression, and energy consumption balance; 2) providing robust solutions for high mobility urban scenarios.