Joint Trajectory and Link Scheduling Optimization in UAV Networks

This paper considers data upload from multiple devices to a rotary-wing Unmanned Aerial Vehicle (UAV) equipped with a Successive Interference Cancellation (SIC) radio. The problem at hand is to optimize the UAV's data collection points, and the set of transmitting devices at each point. We outline three contributions. The first is an Integer Linear Program (ILP), which can be used to compute the optimal trajectory and data transmission schedule. Second, we propose a novel heuristic called Iteratively Construct Link Schedule and Trajectory (ICLST) that includes a link set/schedule selection policy called Highest Sum-Rate Selection (HSRS). Third, we propose a novel learning-based protocol that enables a UAV to independently learn the optimal trajectory with the highest energy efficiency. Our results show that a SIC radio helps double the amount of data collected by the UAV. Placing devices at different heights helps the UAV collect more data. Moreover, ICLST with HSRS is capable of producing a schedule that is near optimal. Additionally, our learning protocol yields a schedule with the highest energy-efficiency.