A Geometry-Based Beamforming Channel Model for UAV mmWave Communications
Kai Mao,
Qiuming Zhu,
Maozhong Song,
Boyu Hua,
Weizhi Zhong,
Xijuan Ye
Affiliations
Kai Mao
The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Qiuming Zhu
The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Maozhong Song
The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Boyu Hua
The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Weizhi Zhong
The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Xijuan Ye
The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Considering the three-dimensional (3D) trajectory, 3D antenna array, and 3D beamforming of unmanned aerial vehicle (UAV), a novel non-stationary millimeter wave (mmWave) geometry-based stochastic model for UAV to vehicle communication channels is proposed. Based on the analysis results of measured and ray tracing simulation data of UAV mmWave communication links, the proposed parametric channel model is constructed by a line-of-sight path, a ground specular path, and two strongest single-bounce paths. Meanwhile, a new parameter computation method is also developed, which is divided into the deterministic (or geometry-based) part and the random (or empirical) part. The simulated power delay profile and power angle profile demonstrate that the statistical properties of proposed channel model are time-variant with respect to the scattering scenarios, positions and beam direction. Moreover, the simulation results of autocorrelation functions fit well with the theoretical ones as well as the measured ones.
