UAV Placement and Resource Allocation for Intelligent Reflecting Surface Assisted UAV-Based Wireless Networks

Abstract

We design an unmanned aerial vehicle (UAV) based wireless network with wireless access and backhaul links leveraging an intelligent reflecting surface (IRS). This design aims to maximize the sum rate achieved by ground users (GUs) through optimizing the UAV placement, IRS phase shifts, and sub-channel assignments considering the wireless backhaul capacity constraint. To tackle the underlying mixed integer non-linear optimization problem (MINLP), we first derive the closed-form IRS phase shift solution; we then optimize the sub-channel assignment and UAV placement by using the alternating optimization method. Specifically, we propose an iterative sub-channel assignment method to efficiently utilize the bandwidth and balance bandwidth allocation for wireless access and backhaul links while maintaining the backhaul capacity constraint. Moreover, we employ the successive convex approximation (SCA) method to solve the UAV placement optimization sub-problem. We show the effectiveness of our proposed design via extensive numerical studies.