Optimizing TDMA Schedule and SIC-Capable UAV Position via Gibbs Sampling

This letter considers a novel problem that aims to derive the shortest possible Time Division Multiple Access (TDMA) schedule for use by ground nodes to upload their data to an Unmanned Aerial Vehicle (UAV) over random channel gains. Its key novelties include equipping the UAV with a Successive Interference Cancellation (SIC) radio and applying a Gibbs sampling based approach to optimize the UAV's position. Our results show that the UAV is able to learn the optimal location whereby the average schedule length at the optimal position is up to 17% shorter as compared to other locations.