Mono-Static Background Channel Modeling for UAV Applications in Urban Macrocell Scenario

This paper proposes a statistical mono-static background channel modeling method for unmanned aerial vehicle (UAV) communications in urban macrocell (UMa) environments. The approach introduces virtual reference points (RPs) uniformly distributed around the UAV transmitter, where each link is assumed to be non-line-of-sight. Without requiring receiver-side information, the method reuses the standardized channel generation procedures defined in 3GPP TR 38.901 to simulate large-scale multipath characteristics. For each RP, cluster-level parameters such as path loss, shadow fading, delay spread, and angular spreads are generated. The overall background channel is constructed by summing the contributions from all RPs. To evaluate the proposed model, ray tracing simulations of mono-static channels are conducted in a typical UMa scenario across the height of the UAV, ranging from 20 to 300 m. The model parameters at different heights are extracted by fitting the simulation results, and their relationship with the height of the UAV is further characterized by functional fitting. The results demonstrate that the proposed model closely matches the ray tracing data in terms of delay, angular, and path loss distributions, effectively capturing the dominant background channel characteristics in the UMa scenario.