A New Look at UAV Channel Modeling: A Long Tail of LoS Probability

Abstract

Accurate channel modelling is crucial for network performance analysis, particularly when considering unmanned aerial vehicles (UAVs). Measurement campaigns involving UAVs have shown that the path loss between UAVs and terrestrial base stations (BSs) is highly dependent on the UAV height, rendering previous line-of-sight (LoS) probability models inaccurate. In this paper, the coverage probability, average ergodic rate and area spectral efficiency are theoretically investigated based on a more realistic channel model, with height dependent LoS probabilities. Our results show that the long tail of the LoS probability function in UAV networks has an important performance impact on sparse networks where the BS density is low. Our new findings also show that the coverage of UAV-enabled networks may continuously decrease with the UAV density, since the LoS probability slowly declines with the link range.