A Novel A2A Channel Model Incorporating Rooftop Specular Reflection and Airframe Occlusion

In the increasingly critical field of aerial communication, unmanned aerial vehicles (UAVs) have gained significant attention as prominent representatives, and accurate air-to-air (A2A) channel modeling plays a pivotal role in the design and evaluation of reliable communication systems. This paper presents a A2A channel model for UAV communications. It introduces a quasi-deterministic approach to address limitations in existing modeling frameworks. The proposed model uses a truncated ellipsoid to capture the distribution of scatterers in A2A scenarios and, for the first time, incorporates rooftop specular reflection (RSR). Power correction factors, based on the UAV’s airframe structure, position, and posture, are introduced to provide a comprehensive and realistic depiction of the A2A communication channel. The performance of proposed model is assessed by simulating key statistical channel characteristics and comparing with other alternatives. The simulations illustrate how channel behavior is influenced by factors such as flight level, flight trajectory, and UAV posture. The results show that RSR leads to the channel hardening effect, while airframe occlusion causes the received signal power to vary gradually with changes in UAV’s position and posture. The validity of the model is confirmed through comparison with measurement data and ray-tracing results, proving its accuracy and practical application.