Location-Aware Resource Allocation for Multi-UAV Aided Multi-Cell NOMA Networks

In this paper, we consider multiple tethered UAVs assisted downlink NOMA networks, where UAVs are deployed as flying base stations (FBSs), and investigate the joint UAVs’ locations, user pairing and power allocation optimization problem. Firstly, we derive the optimal user pairing and power allocation strategies for multi-cell scenario with given fixed UAVs’ locations. Then, from the perspective of air-ground collaboration, we formulate the UAVs’ location optimization problem as a local altruistic game, which is proved to be an exact potential game admitting at least one pure strategy Nash equilibrium (PNE). Finally, A centralized-distributed learning algorithm based on spatial adaptive play is designed to quickly achieve the optimal PNE, which can maximize the defined network utility metric. Simulation results show that the proposed algorithm outperforms the existing schemes and significantly improves the network utility.