Abstract
Multiple unmanned aerial vehicles (UAVs) can function as aerial base stations to provide flexible and reliable communication services for massive ground devices (GDs). It is quite a challenging task to analyze such multi-UAV networks when considering practical mutually exclusive relationships among UAVs. Based on the tools of stochastic geometry, we develop in this paper a theoretical framework for modeling and analyzing the coverage probability and average rate in a 3D air-ground network with UAVs following Matérn Hard-Core Point Process (MHCPP) distribution. As the tractable probability generating functional (PGFL) for such repulsive point processes is unavailable, we employ the approximate signal to interference ratio (SIR) analysis based on the Poisson point process (ASPPP) to obtain the Laplace transform approximation expression of an arbitrary GD’s cumulative interference in the network by considering both line-of-sight (LoS) and none-line-of-sight (NLoS) communications. Finally, extensive simulation results are presented to validate the effective and accuracy of our proposed framework.
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