Novel 3D Non-Stationary mmWave Massive MIMO Channel Models for 5G High-Speed Train Wireless Communications

Yu Liu, Cheng-Xiang Wang, Jie Huang, Jian Sun, Wensheng Zhang

Research output: Contribution to journalArticle

Abstract

In fifth generation (5G) wireless communications, high-speed train (HST) communications is one of the most challenging scenarios. By adopting massive multiple-input multiple-output (MIMO) and millimeter wave (mmWave) technologies into HST communications, the underlying communication system design becomes more challenging and some new channel characteristics have to be studied, such as the non-stationarities in space, time, and frequency domains. This paper proposes a novel three-dimensional (3D) space-time-frequency non-stationary mmWave massive MIMO theoretical model, as well as a corresponding simulation model, for 5G HST wireless channels based on WINNER~II and Saleh-Valenzuela (SV) channel models. Cluster evolutions in space, time, and frequency domains are proposed and analyzed to ensure the models' non-stationarities in three domains. Moreover, based on the proposed channel models, important time-variant channel statistical properties are investigated, such as the time autocorrelation function (ACF), space cross-correlation function (CCF), delay power spectrum density (PSD), and angular PSD. Results indicate that the statistical properties of the simulation model, verified by simulation results, can match well with those of the theoretical model.

Original languageEnglish
JournalIEEE Transactions on Vehicular Technology
Early online date21 Aug 2018
DOIs
Publication statusE-pub ahead of print - 21 Aug 2018

Fingerprint

Millimeter waves
Communication
Power spectrum
Autocorrelation
Communication systems
Systems analysis

Keywords

  • 5G
  • HST channels
  • massive MIMO
  • mmWave
  • space-time-frequency non-stationarity

ASJC Scopus subject areas

  • Automotive Engineering
  • Aerospace Engineering
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Cite this

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title = "Novel 3D Non-Stationary mmWave Massive MIMO Channel Models for 5G High-Speed Train Wireless Communications",
abstract = "In fifth generation (5G) wireless communications, high-speed train (HST) communications is one of the most challenging scenarios. By adopting massive multiple-input multiple-output (MIMO) and millimeter wave (mmWave) technologies into HST communications, the underlying communication system design becomes more challenging and some new channel characteristics have to be studied, such as the non-stationarities in space, time, and frequency domains. This paper proposes a novel three-dimensional (3D) space-time-frequency non-stationary mmWave massive MIMO theoretical model, as well as a corresponding simulation model, for 5G HST wireless channels based on WINNER~II and Saleh-Valenzuela (SV) channel models. Cluster evolutions in space, time, and frequency domains are proposed and analyzed to ensure the models' non-stationarities in three domains. Moreover, based on the proposed channel models, important time-variant channel statistical properties are investigated, such as the time autocorrelation function (ACF), space cross-correlation function (CCF), delay power spectrum density (PSD), and angular PSD. Results indicate that the statistical properties of the simulation model, verified by simulation results, can match well with those of the theoretical model.",
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Novel 3D Non-Stationary mmWave Massive MIMO Channel Models for 5G High-Speed Train Wireless Communications. / Liu, Yu; Wang, Cheng-Xiang; Huang, Jie; Sun, Jian; Zhang, Wensheng.

In: IEEE Transactions on Vehicular Technology, 21.08.2018.

Research output: Contribution to journalArticle

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