UAV communications based on non-orthogonal multiple access

Abstract

This article proposes a novel framework for UAV networks with massive access capability supported by NOMA. In order to better understand NOMA-enabled UAV networks, three case studies are carried out. We first provide performance evaluation of NOMA-enabled UAV networks by adopting stochastic geometry to model the positions of UAVs and ground users. Then we investigate the joint trajectory design and power allocation for static NOMA users based on a simplified 2D model of UAV flying around at fixed height. As a further advance, we demonstrate the UAV placement issue with the aid of machine learning techniques when the ground users are roaming and the UAVs are capable of adjusting their positions in three dimensions accordingly. With these case studies, we can comprehensively understand the UAV systems from fundamental theory to practical implementation.