Spectrum Sharing Based Cognitive UAV Networks via Optimal Beamwidth Allocation

Yue Ling Che, Sheng Luo, Kaishun Wu

Abstract: This paper investigates a spectrum sharing based cognitive unmanned aerial vehicle (UAV) network. To protect the primary users (PUs) from harmful co-channel interference from the UAVs' transmissions, and at the same time, to control the resultant downlink interference at the secondary users (SUs), each UAV is equipped with a directional antenna of adjustable beamwidth. We adopt a probability-based air-to-ground (AtG) channel model to reflect both line-of-sight (LoS) and non-line-of-sight (NLoS) effects from the UAVs' transmissions to the users on ground. By studying the interference distributions in both primary network and cognitive UAV network, we successfully characterize the coverage probabilities for both PUs and SUs. We then optimally design the UAV density and the UAV beamwidth, so as to maximize the UAV coverage probability under a PU coverage probability constraint. Despite of the complicated network performance characterizations that make this problem non-convex, we find an efficient method to solve this problem. Finally, numerical results are provided to validate the theoretical analysis, and show the performance of our proposed spectrum sharing method via UAV beamwidth over the benchmark scheme.