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author:

Lai, Xinlin (Lai, Xinlin.) [1] | Chen, Zhonghui (Chen, Zhonghui.) [2] (Scholars:陈忠辉) | Zhao, Yisheng (Zhao, Yisheng.) [3] (Scholars:赵宜升)

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EI Scopus

Abstract:

In order to provide the users with reliable wireless communication service in high-speed mobility scenarios, we need to obtain channel state information by channel estimation. However, the wireless channel presents a characteristic of dynamic change in high-speed mobility environments. It will bring great challenge to channel estimation. Aiming at the high-speed railway communication system, the issue of the fast time-varying channel estimation is investigated in this paper. The impulse response of the fast time-varying channel is modeled as the product of the basis functions and the coefficients by introducing a basis expansion model (BEM). Meanwhile, the comb pilot clusters are inserted in frequency domain. The coefficients of basis functions are derived by the least-square estimation criterion so as to realize the estimation of the channel impulse response. Simulation results show that optimization generalized complex exponential BEM (OGCE-BEM) has the smallest normalized mean square error among the various types of BEMs. © 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Keyword:

Boundary element method Channel estimation Channel state information Expansion Frequency domain analysis Functions Impulse response Mean square error Railroad plant and structures Railroad transportation Time varying networks

Community:

  • [ 1 ] [Lai, Xinlin]College of Physics and Information Engineering, Fuzhou University, Fuzhou, China
  • [ 2 ] [Chen, Zhonghui]College of Physics and Information Engineering, Fuzhou University, Fuzhou, China
  • [ 3 ] [Zhao, Yisheng]College of Physics and Information Engineering, Fuzhou University, Fuzhou, China

Reprint 's Address:

  • 陈忠辉

    [chen, zhonghui]college of physics and information engineering, fuzhou university, fuzhou, china

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ISSN: 1867-8211

Year: 2018

Volume: 209

Page: 489-501

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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