Online Trajectory Optimization for Rotary-Wing UAVs in Wireless Networks

This paper studies the trajectory optimization problem in an online setting for a single rotary-wing UAV acting as the source of data for random downlink transmission requests by two ground nodes (GNs) in a wireless network. The goal is to optimize the UAV trajectory in order to minimize the expected average communication delay of requests to transmit a fixed payload to the GNs. It is shown that the problem can be cast as a semi-Markov decision process (SMDP), and the resulting minimization problem is solved via multi-chain policy iteration. It is proved that the optimal trajectory in the communication phase greedily minimizes the communication delay of the current request while moving between target start and end positions, with the end positions selected to minimize the expected average long-term delay in the SMDP. Numerical simulations show that the expected average delay is minimized when the UAV moves towards the geometric center of the GNs during phases in which it is not actively servicing transmission requests, and demonstrate significant improvements over sensible heuristics. Finally, it is revealed that the optimal end positions of communication phases become increasingly independent of the payload, for large payload values.