Joint Optimization of UAV Trajectory and User Scheduling Based on NOMA Technology

Unmanned aerial vehicles (UAVs) have been widely used in the past few decades due to their high maneuverability. This paper studies a downlink UAV air-ground wireless network based on non-orthogonal multiple access (NOMA) technology, where a UAV is deployed as an aerial base station to provide periodic service for a group of users. With the purpose of maximizing the minimum sum rate of system in the limited time, an iterative algorithm for jointly optimizing user scheduling and UAV trajectory is proposed. In order to find the optimal users to communicate with, we present a method of user partitioning based on k-Means clustering algorithm and a strategy for selecting subset to schedule on the basis of NOMA technology. The maximum sum rate of edge users in the NOMA-based UAV communication system is also considered. The simulation results are provided to show the optimal UAV trajectories with different objective functions, and to indicate that the NOMA-based UAV system provides the benefits of achieving a better air-ground communication compared to OMA scheme and other benchmark schemes.