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arXiv · 2104.03540

Map-based Channel Modeling and Generation for U2V mmWave Communication

Qiuming Zhu·Kai Mao·Maozhong Song·Xiaomin Chen·Boyu Hua·Weizhi Zhong·Xijuan Ye
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Abstract

Unmanned aerial vehicle (UAV) aided millimeter wave (mmWave) technologies have a promising prospect in the future communication networks. By considering the factors of three-dimensional (3D) scattering space, 3D trajectory, and 3D antenna array, a non-stationary channel model for UAV-to-vehicle (U2V) mmWave communications is proposed. The computation and generation methods of channel parameters including interpath and intra-path are analyzed in detail. The inter-path parameters are calculated in a deterministic way, while the parameters of intra-path rays are generated in a stochastic way. The statistical properties are obtained by using a Gaussian mixture model (GMM) on the massive ray tracing (RT) data. Then, a modified method of equal areas (MMEA) is developed to generate the random intra-path variables. Meanwhile, to reduce the complexity of RT method, the 3D propagation space is reconstructed based on the user-defined digital map. The simulated and analyzed results show that the proposed model and generation method can reproduce non-stationary U2V channels in accord with U2V scenarios. The generated statistical properties are consistent with the theoretical and measured ones as well.

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Qiuming Zhu, Kai Mao, Maozhong Song, Xiaomin Chen, Boyu Hua, Weizhi Zhong, Xijuan Ye. 2021-04-08. Map-based Channel Modeling and Generation for U2V mmWave Communication. https://doi.org/10.1109/tvt.2022.3174404

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