The SINR Meta Distributions in Cellular-Connected UAV Networks

Jingkai Hou, Hongguang Sun, Chong Zhang, Hongming Zhang, Shuqin Li

Abstract: In this work, we develop a systematic framework based on the tools from stochastic geometry to characterize the meta distributions of the downlink signal-tointerference-plus-noise ratio (SINR) of the typical aerial user (AU) in a cellular-connected unmanned aerial vehicle (UAV) network. We utilize a practical channel model that accounts for both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions to characterize the air-to-ground (A2G) channel. Assuming that the A2G transmissions experience Nakagami-m small-scale fading channels, and the adoption of strongest average received signal strength (RSS)-based cell association scheme, we drive the exact analytical expressions for the conditional success probability (CSP) and its b th moment, which is then utilized to obtain the meta distribution. A moment matching approach is further adopted to approximate the meta distribution to a beta distribution, where the accuracy is validated by simulations. The analysis concludes that compared to the Rayleigh fading channel, more AUs have higher link reliability in the Nakagami-m fading channel. As the Nakagami-m parameter increases, the proportion of AUs with higher reliability also increases. Our framework can provide guidance for the setting of related parameters in the deployment strategy for cellular-connected UAV.