Average Communication Rate Maximization for IRS-Aided Hybrid Near- and Far-Field UAV Communication Under Jamming

Near-field communication has become very common in the next generation communication systems, especially under the wide deployment of extremely large-scale intelligent reflecting surfaces (XL-IRS). This paper investigates an XL-IRS-assisted hybrid near- and far-field unmanned aerial vehicle (UAV) communication system with multiple users and an energy-constrained UAV under jamming. First, based on different electromagnetic radiation characteristics of the hybrid near- and far-field channels, average communication rate (ACR) is derived. Subsequently, by considering the effect of user association, XL-IRS phase shift, and UAV 3D trajectory, we formulate a penalty-based alternate optimization (AO) ACR maximization problem, which consists of inner and outer loops. Herein, the penalty factor and auxiliary penalty variable are introduced to transform the binary variable representing the user association into a continuous variable. In the outer loop, the penalty factor can be updated by a linear function, enabling the continuous variable to approximate 0 or 1. In the inner loop, the user association subproblem is optimized first, the XL-IRS phase shift subproblem is optimized by the semidefinite relaxation (SDR) method, and then the UAV trajectory subproblem is optimized by successive convex approximation (SCA) method. Based on the outcomes of the above subproblems, the closed solution of the penalty variable is obtained. Finally, extensive simulation results show that the proposed scheme outperforms the benchmark schemes in terms of ACR.