Models for Wireless Data Communications in Indoor Train Environment

The provisioning of wireless data services in the railway environment will become increasingly important for train operators and train constructors in the upcoming years. In this paper, we present models to predict train-to-wayside wireless data communications characteristics in terms of throughput, jitter, and packet loss predictions for 2G/3G networks. To this end, an extensive measurement campaign is carried out along a Belgian Intercity railway track. Based on these measurements, we apply a multiple regression, window mean, and autoregressive model. We find that the window mean model is recommended for the prediction of throughput and jitter, while the multiple regression model is more favorable for the prediction of packet loss. The implementation of these predictions in train-to-wayside communication systems can enhance the provisioning of seamless network connection necessary for a wide variety of data services.