Parametrization and Validation of the Geometry-Based Stochastic Channel Model for Train-to-Train Communication

Abstract

The future of railway transport aims at more flexible train composition with virtually coupled train sets (VCTSs), automatic train operation, and autonomously driving trains. The train-to-train (T2T) communication is one major technology which is enabling those future railway concepts. Hence, the development of the next generation of communication standards takes into account railway communication. The development of standards and equipment for wireless communication requires a profound knowledge of the propagation conditions in railway environments and for moving trains. For safety critical applications the time-variant behavior of the propagation channel has to be considered. Therefore, we propose a geometry-based stochastic channel model (GSCM) and show the parametrization for an open field environment. The proposed and parametrized GSCM enables the development and testing of communication standards for T2T communication.