A Non-Stationary 6G V2V Channel Model With Continuously Arbitrary Trajectory

In this article, a novel three-dimensional (3D) massive multiple-input multiple-output (MIMO) millimeter wave (mmWave) geometry-based stochastic model (GBSM) is proposed for sixth-generation (6G) vehicle-to-vehicle (V2V) channels. In the proposed GBSM, clusters in the environment are divided into static clusters and dynamic clusters. Furthermore, the time-variant acceleration together with the integration of time during the transmission distance update are exploited. As a result, the continuously arbitrary trajectory of the transceiver and dynamic clusters is successfully captured. To jointly model space-time-frequency (S-T-F) non-stationarity of 6G V2V channels, a new method, which properly integrates the frequency-dependent factor, birth-death (BD) process, and selective evolution of static and dynamic clusters, is developed. Key channel statistics, including the space-time-frequency correlation function (STF-CF), time stationary interval, and Doppler power spectral density (DPSD) are obtained. Simulation results demonstrate that S-T-F non-stationarity is modeled and the impacts of vehicular traffic density (VTD) and vehicular movement trajectory (VMT) on channel statistics are further analyzed thoroughly. Finally, the generality and accuracy of the proposed GBSM are validated through the comparison of simulation results and available measurement data.