A Measurement-Based Stochastic Model for High-Speed Railway Channels

The high-speed railway (HSR) propagation channel has a significant impact on the design and performance analysis of wireless railway control systems. This paper derives a stochastic model for the HSR wireless channel at 930 MHz. The model is based on a large number of measurements in 100 cells using a practically deployed and operative communication system. We use the Akaike information criterion to select the distribution of the parameter distributions, including the variations from cell to cell. The model incorporates the impact of directional base station (BS) antennas, includes several previously investigated HSR deployment scenarios as special cases, and is parameterized for practical HSR cell sizes, which can be several kilometers. The proposed model provides a consistent prediction of the propagation in HSR environments and allows a straightforward and time-saving implementation for simulation.