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Unmanned aerial vehicle (UAV) aided millimeter wave (mmWave) technologies have a promising prospect in the future wireless communication networks. By considering the factors of three-dimensional (3D) scattering space, 3D trajectory, and 3D antenna array, a non-stationary ray-based channel model for UAV-to-vehicle (U2V) mmWave communications is proposed. The computation and generation methods of channel parameters including inter-path and intra-path are developed and illustrated in detail. The inter-path parameters are calculated in a deterministic way based on the given geometric information. The parameters of intra-path rays are generated in a stochastic way based on the statistical properties, which can be obtained in advance by applying a Gaussian mixture model (GMM) on the massive ray tracing (RT) data of different typical scenarios. Meanwhile, a modified method of equal areas (MMEA) is developed to generate the random intra-path variables. To speed up the RT algorithm, the 3D propagation scenario is reconstructed based on the user-defined digital map. Moreover, the theoretical statistical properties of the proposed channel model, i.e., power delay profile (PDP), autocorrelation function (ACF), Doppler power spectrum density (DPSD), cumulative distribution function (CDF), and level crossing rate (LCR) are derived. Finally, a typical U2V channel under urban scenario at 28 GHz is generated and validated. Simulation results demonstrate that the PDP and DPSD of the proposed channel model are accorded well with the theoretical ones, and the ACF, CDF, and LCR are consistent with the measured ones as well.

Map-Based Channel Modeling and Generation for U2V mmWave Communication