Learning-Based User Association in Multi-UAV Emergency Networks with Ground D2D

In this paper, we consider the user association for a dual-UAV enabled wireless network with the help of D2D connections in disasters. To achieve better performance, we maximize the weighted sum rate of the UAV-served users and total number of the D2D-connected users by optimizing the user association. The formulated problem is a combinatorial optimization problem involving binary variables, which is extremely difficult to solve. Accordingly, we propose two algorithms to solve it approximately. Simulation results demonstrate that these two algorithms can achieve excellent suboptimal performance, and the computational complexity of the learning-based clustering algorithm is much lower.