3D Non-Stationary Wideband Tunnel Channel Models for 5G High-Speed Train Wireless Communications

Yu Liu, Cheng-Xiang Wang, Carlos F. Lopez, George Goussetis, Yang Yang, George K. Karagiannidis

Research output: Contribution to journalArticle

Abstract

High-speed train (HST) communications in tunnels have attracted more and more research interests recently, especially within the framework of the fifth generation (5G) wireless networks. In this paper, based on cuboid-shape, three-dimensional (3D) non-stationary wideband geometry-based stochastic models (GBSMs) for HST tunnel scenarios are proposed. By considering the influence of the tunnel walls, a theoretical channel model is first established, which assumes clusters with an infinite number of scatterers randomly distributed on the tunnel walls. The corresponding simulation model is then developed and the method of equal areas is employed to obtain the discrete parameters, such as the azimuth and elevation angles. We derive and investigate the most important channel statistical properties of the proposed 3D GBSMs, including the time-variant autocorrelation function, spatial cross-correlation function, and Doppler power spectrum density. It is indicated that all statistical properties of the simulation model, verified by simulation results, can match very well with those of the theoretical model. Furthermore, a validation is presented by comparing the stationary regions of our proposed tunnel channel model to those of relevant measurement data.

Original languageEnglish
Pages (from-to)259-272
Number of pages14
JournalIEEE Transactions on Intelligent Transportation Systems
Volume21
Issue number1
Early online date13 Feb 2019
DOIs
Publication statusPublished - Jan 2020

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Keywords

  • HST tunnel channels
  • measurement data
  • Non-stationary GBSM
  • statistical properties
  • time-variant parameters

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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