Wobbling and Impairments-Aware Channel Model and its Implications on High-Frequency UAV Links

This paper provides an impairments-aware unified channel model for the link between an unmanned aerial vehicle (UAV) and a ground user equipment (UE). In particular, we consider both physical and hardware impairments, where the former is unique to UAVs and refers to random physical vibrations of the UAV platform, also known as wobbling. The latter pertains to both the UAV and the UE and refers to intrinsic radio frequency (RF) impairments, such as power amplifier (PA) nonlinearity, phase noise, and in-phase/quadrature (I/Q) imbalance. We model the fluctuations of the UAV platform pitch angle (caused by wobbling) by a sinusoidal stochastic process. On the other hand, the combined effect of all hardware impairments is modeled by two wide-sense stationary (WSS) additive and multiplicative distortion noise processes, which is a well-accepted approach in the literature. Using this unified model, we characterize the autocorrelation function (ACF) of the impairments-aware channel impulse response, which further provides the coherence time of the channel. We also derive the power spectral density (PSD) of the distortion-plus-noise process of our unified channel model. To obtain useful insights from the joint impact of physical and hardware impairments on the air-to-ground wireless channel, we evaluate both of these metrics with reasonable impairment models and parameters. One key implication of our results is that the channel coherence time degrades noticeably at high frequencies even for small wobbling, which renders channel estimation of UAV links extremely challenging at these frequencies.