Analysis of Downlink Coverage and Capacity for 3D Mobile UAV Networks

Since traditional cellular network analysis does not consider the random distribution and irregular movement of unmanned aerial vehicles (UAV s) in three-dimensional (3-D) space, it is not suitable for high-density urban areas. Therefore, this paper follows the random geometry theory and mobile ad hoc network (MANET) to construct a 3-D Poisson point process (PPP) mobile UAV network model that allows UAVs to move freely in 3-D space. In this model, we consider that the ground user equipment (GUE) uses the nearest neighbor association strategy and the random association strategy to select the UAV as the serving base station (SBS), and the rest are the interfering base stations (IBS). Then, through the Laplace transform of the distance distribution between the UAV and the user and the interference of other base stations, it is derived that the downlink network coverage under the two associated strategies is proportional to the channel capacity. Finally, through simulation and theoretical analysis, we find that the nearest neighbor association strategy is significantly better than the random association strategy, and as the path loss exponents increases, the coverage and channel capacity are increasing.