Stochastic Geometry Analysis of Asymmetric Uplink Interference for Urban UAV-RC Networks

Abstract

Uncrewed aerial vehicles (UAVs) have emerged as a flexible platform for providing coverage over challenging environments, particularly for public safety and surveillance missions in urban areas. However, deploying the UAVs in dense urban areas introduces unique challenges, most notably asymmetric uplink (UL, remote controller to UAV) interference due to a higher chance of line-of-sight (LoS) interference at the UAV. In this letter, we propose a stochastic geometry framework to tractably analyze the large-scale asymmetric interference in urban areas. We incorporate a log-Gaussian Cox process (LGCP) model to capture the spatial correlation of the interference field in both UL and downlink (DL) as a function of the UAV altitude and the two-dimensional (2-D) distance between the remote controller and UAV. To quantify the UL and the DL interference asymmetry, we also define the interference asymmetry ratio characterizing the interference disparity between the UL and the DL. Our numerical results demonstrate that the interference asymmetry ratio increases as the UAV altitude and 2-D distance increase, highlighting that the UL interference worsens.