@inproceedings{c6f561f63c494da0aea072355aceccd7,
title = "3D non-stationary GBSMs for high-speed train tunnel channels",
abstract = "This paper proposes 3D non-stationary multipleinput multiple-output (MIMO) geometry-based stochastic models (GBSMs) for high-speed train (HST) tunnel channels. Considering the line-of-sight (LoS), single-bounced (SB), and double-bounced (DB) components from the geometrical tunnel scattering model, a reference HST tunnel channel model under the assumption that scatterers are uniformly distributed on the tunnel walls is first derived. Then, by using the modified method of equal areas (MMEA), the corresponding simulation model is developed. Based on the proposed tunnel channel models, the correlation properties in time and space domains are investigated. A good agreement of statistical properties between the reference model and simulation model can be obtained. Furthermore, the simulation results show that the proposed model can be applied to mimic the nonstationarity of HST tunnel channels.",
keywords = "channel model, High-speed train, statistical properties, tunnel scenario",
author = "Yu Liu and Liu Feng and Jian Sun and Wensheng Zhang and Cheng-Xiang Wang and Pingzhi Fan",
year = "2018",
month = jul,
day = "26",
doi = "10.1109/VTCSpring.2018.8417802",
language = "English",
series = "IEEE Vehicular Technology Conference",
publisher = "IEEE",
pages = "1--5",
booktitle = "2018 IEEE 87th Vehicular Technology Conference (VTC Spring)",
address = "United States",
}