Secure UAV Random Networks With Minimum Safety Distance

In this correspondence, we study the physical layer security in a stochastic unmanned aerial vehicles (UAVs) network from network-wide perspective, where locations of UAVs are modeled as Mat$\acute{\text{e}}$rn hard-core point process (MHCPP) to characterize minimum safety distance between UAVs, and users eavesdroppers Poisson cluster process, respectively. adopt zero-forcing precoding serve multiple ground emit artificial noise combat eavesdropping. We derive approximations for coverage probability secrecy typical user, with which throughput whole network. Numerical results show analytical can well approximate simulation results. Impacts parameters on performance shown.