Geometry-Based Stochastic Channel Model for Train-to-Train Communication in Open Field Environment

Future railway applications, e.g., wireless train bus or virtual coupled trains, will rely on train-to-train (T2T) communication. Those future applications require an exchange of safety critical data between trains within one train-set based on wireless communication. Hence, the investigation of the propagation effects and the influence on the wireless communication is tremendously important. Future developments of communication standards and systems demand a detailed characterization and modeling. We investigated the propagation mechanisms based on channel sounding measurements and derived statistics for the propagation effects. Based on the environment, geometry and the propagation statistics we derive channel models for T2T communication. To cope with the movement of the trains, the changing environment and resulting temporal correlation effects we present a geometry-based stochastic channel model (GSCM) for T2T communication in open field environment.