TBS Joint Optimization to Serve mmWave High Altitude UAVs: A Counterfactual MAB Approach

High-altitude uncrewed aerial vehicles (UAVs) with millimeter wave communication are well-suited for fifth-generation (5G) and beyond applications. UAVs may cause significant interference to ground user equipment (GUE). We consider using a moving tethered aerial base station (TBS) as an alternative to a terrestrial base station. We consider, the UAV and GUE locations as contexts to perform joint TBS location, UAV and GUE power allocation optimization in a three-dimensional environment. We propose a contextual multi-armed bandit framework using a novel counterfactual Thompson sampling (CTS) algorithm. We compare its performance against a joint optimization using vanilla Thompson sampling (TS) and single optimization TS (SOTS) approaches. Our results show that the CTS approach converges faster. We conclude that the CTS-based approach achieves better interference mitigation for both aerial and ground users.