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

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

doi:10.1109/VTCSpring.2016.7504490

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 proceeding › Conference 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 language	English
Title of host publication	2016 IEEE 83rd Vehicular Technology Conference (VTC Spring)
Publisher	IEEE
ISBN (Electronic)	9781509016983
DOIs	https://doi.org/10.1109/VTCSpring.2016.7504490
Publication status	Published - 7 Jul 2016
Event	83rd IEEE Vehicular Technology Conference 2016 - Nanjing, China Duration: 15 May 2016 → 18 May 2016

Conference

Conference	83rd IEEE Vehicular Technology Conference 2016
Abbreviated title	VTC Spring 2016
Country/Territory	China
City	Nanjing
Period	15/05/16 → 18/05/16

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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10.1109/VTCSpring.2016.7504490

Cite this

@inproceedings{7003bb1bb28a430eb9c42071dbdbf86c,

title = "Statistical properties of high-speed train wireless channels in different scenarios",

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.",

keywords = "High-speed train wireless channels, HST scenarios, Statistical properties",

author = "Yu Liu and Yapei Zhang and Ammar Ghazal and Cheng-Xiang Wang and Yang Yang",

year = "2016",

month = jul,

day = "7",

doi = "10.1109/VTCSpring.2016.7504490",

language = "English",

booktitle = "2016 IEEE 83rd Vehicular Technology Conference (VTC Spring)",

publisher = "IEEE",

address = "United States",

note = "83rd IEEE Vehicular Technology Conference 2016, VTC Spring 2016 ; Conference date: 15-05-2016 Through 18-05-2016",

}

TY - GEN

T1 - Statistical properties of high-speed train wireless channels in different scenarios

AU - Liu, Yu

AU - Zhang, Yapei

AU - Ghazal, Ammar

AU - Wang, Cheng-Xiang

AU - Yang, Yang

PY - 2016/7/7

Y1 - 2016/7/7

N2 - 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.

AB - 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.

KW - High-speed train wireless channels

KW - HST scenarios

KW - Statistical properties

UR - http://www.scopus.com/inward/record.url?scp=84979765583&partnerID=8YFLogxK

U2 - 10.1109/VTCSpring.2016.7504490

DO - 10.1109/VTCSpring.2016.7504490

M3 - Conference contribution

AN - SCOPUS:84979765583

BT - 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring)

PB - IEEE

T2 - 83rd IEEE Vehicular Technology Conference 2016

Y2 - 15 May 2016 through 18 May 2016

ER -

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

Abstract

Conference

Keywords

ASJC Scopus subject areas

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