Statistical properties of high-speed train wireless channels in different scenarios

Yu Liu, Yapei Zhang, Ammar Ghazal, Cheng-Xiang Wang, Yang Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, we compare the statistical properties of high-speed train (HST) wireless channels in different scenarios using a generic non-stationary HST channel model that has been verified by channel measurements [1]. We mainly focus our comparison and analysis on the three most common HST scenarios, i.e., the rural area, cutting, and viaduct scenarios. Several channel statistical properties such as the temporal autocorrelation function (ACF), space cross-correlation function (CCF), and space- Doppler (SD) power spectrum density (PSD) are investigated. The impacts of different scenario- specific parameters on the channel statistical properties are also studied via numerical analysis.

Original languageEnglish
Title of host publication2016 IEEE 83rd Vehicular Technology Conference (VTC Spring)
PublisherIEEE
ISBN (Electronic)9781509016983
DOIs
Publication statusPublished - 7 Jul 2016
Event83rd IEEE Vehicular Technology Conference 2016 - Nanjing, China
Duration: 15 May 201618 May 2016

Conference

Conference83rd IEEE Vehicular Technology Conference 2016
Abbreviated titleVTC Spring 2016
CountryChina
CityNanjing
Period15/05/1618/05/16

Keywords

  • High-speed train wireless channels
  • HST scenarios
  • Statistical properties

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Applied Mathematics

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