论文标题
无人机通信的渠道建模，具有姿势变化和机身散射效果
Channel Modeling for UAV-to-Ground Communications with Posture Variation and Fuselage Scattering Effect
论文作者
论文摘要
无人驾驶飞机（UAV）至地面（U2G）频道模型起着无人机和地面终端之间可靠通信的关键作用。本文提出了一个三维（3D）非平稳的混合模型，包括用于U2G多输入 - 元素输出（MIMO）通道的大规模和小规模褪色。 UAV，机身散射效果（FSE）和姿势变化褪色（PVF）下的U2G场景下的独特信道特性（即3D轨迹和姿势）被纳入所提出的模型中。通道参数，即路径损耗（PL），阴影褪色（SF），路径延迟和路径角度，是生成结合机器学习（ML）和射线跟踪（RT）技术，以捕获与结构相关的特征。为了确保通道参数的物理连续性，例如多普勒相和路径功率，提出了间隔间隔和固定间隔的时间演化方法。关键的统计属性，即时间自动校正函数（ACF），功率延迟曲线（PDP），水平交叉率（LCR），平均褪色持续时间（AFD）和固定间隔（SI），并分析了机身和姿势变化的变化的影响。证明姿势变化和机身散射对通道特征都有至关重要的影响。通过将仿真结果与测量结果进行比较，可以验证所提出模型的有效性和实用性。
Unmanned aerial vehicle (UAV)-to-ground (U2G) channel models play a pivotal role for reliable communications between UAV and ground terminal. This paper proposes a three-dimensional (3D) non-stationary hybrid model including both large-scale and small-scale fading for U2G multiple-input-multiple-output (MIMO) channels. Distinctive channel characteristics under U2G scenarios, i.e., 3D trajectory and posture of UAV, fuselage scattering effect (FSE), and posture variation fading (PVF), are incorporated into the proposed model. The channel parameters, i.e., path loss (PL), shadow fading (SF), path delay, and path angle, are generated incorporating machine learning (ML) and ray tracing (RT) techniques to capture the structure-related characteristics. In order to guarantee the physical continuity of channel parameters such as Doppler phase and path power, the time evolution methods of inter- and intra- stationary intervals are proposed. Key statistical properties , i.e., temporal autocorrection function (ACF), power delay profile (PDP), level crossing rate (LCR), average fading duration (AFD), and stationary interval (SI) are given, and the impact of the change of fuselage and posture variation is analyzed. It is demonstrated that both posture variation and fuselage scattering have crucial effects on channel characteristics. The validity and practicability of the proposed model are verified by comparing the simulation results with the measured ones.
