A Novel Non-stationary 5G-R Channel Model for High-speed Railway Wireless Communications

5G for railway (5G-R) technology is regarded as a promising solution for next-generation railway wireless communication systems. However, modeling 5G-R channels in high-mobility scenarios presents significant challenges due to their non-stationary characteristics and stringent reliability demands. In this paper, we propose a novel non-stationary 5G-R channel model tailored for high-speed railway (HSR) train-ground communication, incorporating three-dimensional scattering clusters and time-varying parameters. Furthermore, by partitioning the receiver’s trajectory into segments and incorporating overlapping regions between adjacent ones, we effectively capture the temporal evolution of parameters to address the channel nonstationarity. To explore the properties of the proposed channel model, some key statistical properties are derived and simulated, including the Rician K-factor, root mean square delay spread, spatial cross-correlation function, and quasi-stationary distance. Simulation results, validated against empirical measurements, confirm the model’s accuracy in representing HSR channel characteristics, thereby providing a robust framework for the design and performance evaluation of 5G-R systems.