Markov Chain Based Channel Characterization for High Speed Railway in Viaduct Scenarios

The non-stationary properties based on Markov chains are proposed to describe the wireless propagation mechanism of High Speed Railway (HSR) under viaduct scenarios. This Markov modeling method reveals the statistical behaviors of the persistence process corresponding to a resolvable multipath component. Based upon the channel measurement on Beijing-Tianjin HSR at 2.35 GHz, the transition probability matrix and the steady-state probability matrix of Markov chains are specified. These proposed model parameters are informative for link-level simulation and prototype verification for HSR communication systems. In addition, the non-stationary properties are first investigated by medium-scale fading entropy and run length to evaluate the degrees of activity and persistence, respectively. Finally, our Markov models are compared with the experimental results by the Kullback-Leibler (KL) distance to obtain the degree of approximation, which show that the second order model provides a good match to the measured data.