Geometry-Based Stochastic Line-of-Sight Probability Model for A2G Channels Under Urban Scenarios

Line-of-sight (LoS) path is essential for the reliability of air-to-ground (A2G) communications, but the existence of the LoS path is difficult to predict due to random obstacles on the ground. Based on the statistical geographic information and Fresnel clearance zone, a general stochastic LoS probability model for 3-D A2G channels under urban scenarios is developed. By considering the factors, that is, building height distribution, building width, building space, carrier frequency, and transceiver’s heights, the proposed model is suitable for different frequencies and altitudes. Moreover, in order to get a closed-form expression and reduce the computational complexity, an approximate parametric model is also built with the machine-learning (ML) method to estimate the model parameters. The simulation results show that the proposed model has good consistency with existing models at low altitude. When the altitude increases, it has a better performance by comparing with that of the ray-tracing (RT) Monte-Carlo simulation data. The analytical results of the proposed model are helpful for the channel modeling and performance analyses such as cell coverage, outage probability, and bit error rate in A2G communications.