A 3D UAV-Assisted Cellular Network Model with Inter-Tier Dependence

In UAV-assisted cellular networks (UACNs), the UAV tier should be flexibly adjusted to the terrestrial tier, which causes location dependence between UAVs and ground base stations (GBSs). To capture it, this paper proposes a 3D UACN model with inter-tier dependence and analyzes the performance of such UAV-assisted network via stochastic geometry. Specifically, UAVs with random altitudes are deployed outside the exclusion regions of GBSs to avoid the strong inter-tier interference, and accordingly, the locations of GBSs and UAVs follow a PPP and a marked Poisson hole process (MPHP), respectively. Under this setup, we propose a division region-based user association scheme, and provide analytical results for the association probability, link distance distribution, and success probability which are verified through simulations. Numerical results unveil that: 1) the exclusion region should be carefully designed to achieve the optimal access probability and 2) significant gains (especially for cell edge users) can be obtained if UAVs are introduced and deployed agilely.