Impact of UAV Mobility and Wobble on Temporal Correlation of Air-to-Ground Channels

In this paper, an air-to-ground (A2G) channel model, based on the geometry-based stochastic model (GBSM), is proposed, jointly considering the effects of high-speed motion and three-dimensional (3D) wobbles of fixed-wing unmanned aerial vehicles (UAVs). It is found that the UAV's internal vibration is periodic and narrowband, while wobbles caused by atmospheric flow are bounded and uniformly random, as verified by measurements. Accordingly, the wobbles are modeled by sinusoidal and uniform random processes, respectively, and the effect of high-speed motion is modeled by a moving factor, determined by flight altitude and radius. The channel temporal correlation function (CF) is derived based on the proposed model. Numerical results show that both the UAV's high-speed motion and 3D wobbles accelerate the decay of the CF, with the high-speed motion contributing over 80–90% of the reduction in coherence time, making it the dominant impairment in high dynamic A2G scenarios. In addition, the coherence time at lower carrier frequencies, such as L-band and S-band, is significantly longer. In addition, by comparing with existing low-altitude rotor UAV models, the effectiveness of the proposed model in such scenarios are verified.