Spectrum Sensing in 3D Wireless Networks

This article explores three-dimensional (3D) spectrum sensing in a UAV network to detect spectrum holes for enabling spectrum sharing. The UAVs are randomly deployed within a large-scale cellular network, modeled as a 3D homogeneous Poisson point process. In this setup, small base stations (SBSs) on the ground function as sensing devices, utilizing an energy detection scheme to identify spectrum holes in the sky. We determine the average spectrum sensing range for a given environment and employ stochastic geometry to analyze sensing performance in terms of false alarm probability, missed detection probability, and total error probability. Additionally, we derive approximate error probabilities and compare them with exact results. The mathematical expressions are further simplified for a special case where the environment is obstructed by buildings. Finally, the theoretical findings are validated through numerical simulations.