The unmanned aerial vehicle (UAV) channel models are very important and useful for the design and evaluation of UAV communications. In existing works, the terrestrial scatterers are widely stationary or moving all the time, and the UAV is assumed to move at a constant speed. However, these modeling assumptions may not be appropriate in realistic scenarios. In this work, we propose a new 3-dimensional (3-D) dynamic non-wide-sense stationary (non-WSS) cluster-based geometric model for UAV multiple-input multiple-output (MIMO) channels. We assume that a few non-isotropic scatterers are distributed around the terrestrial receiver and have a probabilistic movement behavior. Meanwhile, we consider that the UAV flies at a varying speed, and we design a non-stationary mobility model with acceleration. The proposed channel model performs the birth-death evolutionary process of clusters based on a Markov model, and the time-variant multipath component (MPC) parameters (e.g., angle of arrival/departure (AoA/AoD), power, and delay) are obtained. In addition, we derive the space-time correlation function, mean Doppler spread, and root-mean-square doppler shift spread of the UAV MIMO channels, and provide the quasi-stationary interval. We also investigate the impact of some key model factors on the statistical properties by numerical simulations. Finally, we compare the space-time correlation functions and the second-order statistical properties between the proposed model and the UAV channel measurement results. The close agreements between the numerical simulations and field measurements have validated the proposed model.

中文翻译：

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无人机 MIMO 信道的 3D 动态非 WSS 集群基于几何的随机模型


无人机（UAV）信道模型对于无人机通信的设计和评估非常重要和有用。在现有的工作中，地面散射体大范围静止或一直移动，并且假设无人机以恒定速度移动。然而，这些建模假设可能不适合现实场景。在这项工作中，我们为无人机多输入多输出（MIMO）信道提出了一种新的基于集群的3维（3-D）动态非广义固定（非WSS）几何模型。我们假设一些非各向同性散射体分布在地面接收器周围并具有概率运动行为。同时，考虑到无人机的飞行速度是变化的，我们设计了具有加速度的非平稳移动模型。所提出的信道模型基于马尔可夫模型执行簇的生灭演化过程，时变多径分量（MPC）参数（例如，到达/离开角度（AoA/AoD）、功率和延迟）为获得。此外，我们推导了无人机MIMO信道的时空相关函数、平均多普勒扩展和均方根多普勒频移扩展，并提供了准平稳间隔。我们还通过数值模拟研究了一些关键模型因素对统计特性的影响。最后，我们比较了所提出的模型和无人机信道测量结果之间的时空相关函数和二阶统计特性。数值模拟和现场测量之间的密切一致性验证了所提出的模型。