  Line-of-sight (LoS) path is essential for the reliability of air-to-ground
(A2G) communications, but the existence of 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 three-dimensional (3D) A2G channels under urban scenarios is
developed. By considering the factors, i.e., 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 model parameters. The simulation
results show that the proposed model has good consistency with existing models
at the low altitude. When the altitude increases, it has better performance by
comparing with that of the ray-tracing Monte-Carlo simulation data. The
analytical results of proposed model are helpful for the channel modeling and
performance analysis such as cell coverage, outage probability, and bit error
rate in A2G communications.
