Joint Optimization of UAV Deployment and Ground Users Clustering in Air-Ground Networks: A Hierarchical Coalition-Formation Game Approach

With the development of communication technology, unmanned aerial vehicles (UAVs) have been widely used to enhance ground communication services. However, the limited number of UAVs and the massive data requirements of ground users (GUs) restrict information transmission in air-ground networks. To satisfy the requirements of more GUs and reduce the communication overhead of GUs, this paper investigates a joint deployment of UAVs and GUs clustering optimization for collective data acquisition in air-ground networks. In light of the problem’s complexity, this paper builds a hierarchical game, where the outer game is modeled as a UAV deployment game and the inner game is modeled as a coalition formation game. A Pareto order under resource constraints is proposed in the inner game to enable more GUs to join the coalition set. The outer game is proven to have at least one Nash equilibrium (NE), and the inner game is proven to have at least one stable coalition partition. To obtain the stable solution of the hierarchical game, a joint optimization algorithm for UAV deployment and GUs clustering based on the partial space adaptive play and best response algorithm is proposed. Specially, in light of the impact of data requirements among GUs, a GU processing sequence is designed, and the coalition merging and exchange mechanism is improved in the coalition formation algorithm. Simulation results show that the proposed algorithm performs better than traditional methods, with a performance improvement of around 10% in scenarios involving around fifty GUs.