Spectrum Sensing in UAV-Enabled Cellular Networks

This article presents a novel framework for analyzing spatial spectrum sensing to detect spectrum holes for sharing licensed band spectrum. A large-scale ground-based station (GBS) network using licensed band spectrum is considered, and another subnetwork of unmanned aerial vehicles (UAVs) senses the licensed band spectrum to detect spectrum holes. We assume that the GBSs are randomly deployed following a Poisson point process (PPP) and that the spectrum-sensing UAVs are distributed randomly at a fixed altitude. Each UAV employs an energy detection scheme to identify spectrum holes on the ground. To assess the performance of spectrum sensing, we analyze the distribution of received signal energy, followed by calculating the probabilities of false alarm and missed detection. We then derive the total error probability for the spectrum sensing scheme. The analytical results are validated through numerical simulations.