AAV Air-to-Air Channel: Statistical Properties and Experimental Verification

Abstract

Unmanned aerial vehicle (UAV) air-to-air (A2A) communications are emerging as a vital component of future low-attitude wireless networks. This paper introduces a novel A2A channel model and evaluates its statistical properties through analysis and experimental validation. The proposed model adopts a quasi-deterministic approach that incorporates rooftop specular reflection (RSR), distinguishing it from traditional ground reflection. Airframe occlusion (AO) is represented using a diffraction-based segmented function to accurately characterize its impact on the line-of-sight path. Key statistical indicators are derived based on the proposed model, and numerical results show that the presence of RSR reduces both the level crossing rate and average fade duration. Enhanced Rician factor improves spatial-temporal correlation, while higher transmission power and lower UAV mobility reduce outage probability. Compared to standardized models, the proposed model demonstrates improved capability in capturing the effects of RSR and AO while maintaining compatibility. Additionally, an A2A channel measurement platform leveraging the high autocorrelation properties of Zadoff-Chu sequences is developed to extract channel impulse response. Experimental measurements of channel capacity, outage probability, and root mean square delay spread closely align with simulated results, validating the model’s accuracy and reliability.