Position optimization and resource allocation for cooperative heterogeneous aerial networks

Unmanned aerial vehicle (UAV) has great potential in the future wireless networks. In this paper, we investigate the system optimization algorithms for the heterogeneous aerial networks. Specifically, we propose a cooperative heterogeneous aerial network, where several low-altitude aerial base stations (LABSs) with high frequency are dynamically deployed to enhance the coverage of a high-altitude aerial base station (HABS) with low frequency. For this network, we formulate a joint position optimization, channel allocation, and power allocation problem with the objective to maximize the total data rate of all users under the constraint of the minimum rate requirement of each user. To tackle this hard problem, we first adopt the particle-and-fish swarm algorithm to optimize the positions of the LABSs. Then, the channel-and-power allocation algorithms are designed based on the matching theory and the Lagrangian dual decomposition technique. Simulation results indicate that our proposed algorithms can greatly improve the network performance.