  In this paper, we jointly design the power control and position dispatch for
Multi-unmanned aerial vehicle (UAV)-enabled communication in device-to-device
(D2D) networks. Our objective is to maximize the total transmission rate of
downlink users (DUs). Meanwhile, the quality of service (QoS) of all D2D users
must be satisfied. We comprehensively considered the interference among D2D
communications and downlink transmissions. The original problem is strongly
non-convex, which requires high computational complexity for traditional
optimization methods. And to make matters worse, the results are not
necessarily globally optimal. In this paper, we propose a novel graph neural
networks (GNN) based approach that can map the considered system into a
specific graph structure and achieve the optimal solution in a low complexity
manner. Particularly, we first construct a GNN-based model for the proposed
network, in which the transmission links and interference links are formulated
as vertexes and edges, respectively. Then, by taking the channel state
information and the coordinates of ground users as the inputs, as well as the
location of UAVs and the transmission power of all transmitters as outputs, we
obtain the mapping from inputs to outputs through training the parameters of
GNN. Simulation results verified that the way to maximize the total
transmission rate of DUs can be extracted effectively via the training on
samples. Moreover, it also shows that the performance of proposed GNN-based
method is better than that of traditional means.
