A Novel Time-varying Channel Estimation Based on Wavelet

被引：0
|
作者：
Xu R. [1 ]
Yuan W. [1 ]
Wang J. [1 ]
机构：
[1] School of Information Science and Engineering, East China University of Science and Technology, Shanghai
来源：
Tiedao Xuebao/Journal of the China Railway Society | 2018年 / 40卷 / 05期
关键词：
Basis function; BEM; Channel estimation; OFDM; Scale function;
D O I：
10.3969/j.issn.1001-8360.2018.05.013
中图分类号：
学科分类号：
摘要：
Basis expansion model is one of the most commonly used modeling methods for rapidly time-varying channels, and the choice of basis functions determines the accuracy of the modeling. Based on multiresolution analysis and Mallat algorithm, this paper proposed a basis function constructing method using wavelet scaling functions, which used Daubechies, Symlet, Coiflet wavelet scaling functions for rapidly time-varying channel fitting. Theoretical analysis and simulation results show that, using the proposed basis functions to fit time-varying channels, the performance of channel estimation is better than that of traditional CE-BEM, GCE-BEM, P-BEM, DCT-BEM models, while the complexity is lower than that of DKL-BEM, DPS-BEM models. Compared with other basis functions constructed by wavelet scaling function, the performance of basis function constructed by Sym2 wavelet scaling function is optimal. © 2018, Department of Journal of the China Railway Society. All right reserved.
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页码：90 / 96
页数：6
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