In this article, we propose a three-dimensional (3D) multi-input multi-output (MIMO) channel model for air-to-ground (A2G) communications in unmanned aerial vehicles (UAV) environments, where the UAV transmitter and ground receiver are in motion in the air and on the ground, respectively. A novel angular estimation algorithm is proposed to estimate the real-time azimuth angle of departure (AAoD), elevation angle of departure (EAoD), azimuth angle of arrival (AAoA), and elevation angle of arrival (EAoA) based on the non-stationary nature of the channel model. In the model, we investigate the time-varying spatial cross-correlation functions (CCFs) and temporal auto-correlation functions (ACFs) with respect to the different moving directions and velocities of the UAV transmitter and ground receiver. Furthermore, we derive and study the Doppler power spectral densities (PSDs) and power delay profiles (PDPs) of the proposed channel model. Numerical results show that characteristics of the proposed channel model are very close to those of practical measurements, which provide a new and practical approach to evaluate the performance of next generation UAV-MIMO communication systems.

中文翻译：

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使用 AoD 和 AoA 估计算法的 A2G 通信环境的新型 3D 无人机信道模型

在本文中，我们提出了一种用于无人机 (UAV) 环境中空对地 (A2G) 通信的三维 (3D) 多输入多输出 (MIMO) 信道模型，其中 UAV 发射机和地面接收机分别在空中和地面上运动。提出了一种新的角度估计算法来估计实时方位角(AAoD)、离去仰角(EAoD)、方位角(AAoA)和到达仰角(EAoA)。通道模型的平稳性。在模型中，我们针对无人机发射机和地面接收机的不同移动方向和速度研究了时变空间互相关函数 (CCF) 和时间自相关函数 (ACF)。此外，我们推导出并研究了所提出的信道模型的多普勒功率谱密度 (PSD) 和功率延迟分布 (PDP)。数值结果表明，所提出的信道模型的特性与实际测量的特性非常接近，为评估下一代 UAV-MIMO 通信系统的性能提供了一种新的实用方法。