Resource configuration for throughput maximization in UAV-WPCN with IRS-assisted NOMA

Abstract

Abstract Unmanned aerial Vehicle (UAV) enabled wireless powered communication network (WPCN) often experience poor energy delivery on the downlink and restricted data rates on the uplink. We tackle these issues by deploying an intelligent reflecting surface (IRS) and a clustered non-orthogonal multiple access (NOMA) scheme within a UAV-assisted WPCN. A sum-throughput maximization is posed that simultaneously determines the UAV’s flight trajectory, IRS phase configuration, user transmit powers, and slot-time division. The resulting non-convex program is split into three manageable blocks and addressed through an alternating framework that leverages semidefinite relaxation and successive convex approximation. Simulations demonstrate sizable throughput improvements over conventional designs.