喻雨微,王彦.OFDM系统中基于基扩展模型的快时变信道估计算法[J].南华大学学报(自然科学版),2019,33(4):55~59.[YU Yuwei,WANG Yan.Fast Time-varying Channel Estimation Algorithm Based on Base Extension Model in OFDM Systems[J].Journal of University of South China(Science and Technology),2019,33(4):55~59.]
OFDM系统中基于基扩展模型的快时变信道估计算法
Fast Time-varying Channel Estimation Algorithm Based on Base Extension Model in OFDM Systems
投稿时间:2019-02-22  
DOI:
中文关键词:  正交频分复用  信道估计  快时变信道  基扩展模型
英文关键词:orthogonal frequency division multiplexing  channel estimation  fast time-varying channel  basis expansion model
基金项目:湖南省教育厅重点项目(16A181);南华大学研究生科学基金项目(2018KYY008)
作者单位E-mail
喻雨微 南华大学 电气工程学院,湖南 衡阳 421001 yu_yu_wei@126.com 
王彦 南华大学 电气工程学院,湖南 衡阳 421001  
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中文摘要:
      信道估计是正交频分复用(orthogonal frequency division multiplexing,OFDM)的关键技术。随着移动端速度的提高,信道会发生快速变化产生频率选择性衰落,针对此种情况,通过对传统信道估计算法搭建OFDM系统级仿真链路的基础上对不同的基扩展模型(basis expansion model,BEM)研究,针对复指数基扩展模型(complex exponential-BEM,CE-BEM)的部分基函数频率过高会产生较大误差的缺点,提出一种修正基函数系数的方法有效地去除了频率过高的基函数,通过仿真对信噪比和多普勒频移对模型均方误差性能的影响进行分析,结果表明提出算法能在不增加复杂度的前提下均方误差性能较CE-BEM低4~5 dB,有效地提高了拟合性能。
英文摘要:
      Channel estimation is a key technique for orthogonal frequency division multiplexing (OFDM).As the speed of the mobile terminal increases,the channel will change rapidly to produce frequency selective fading.For this situation,this paper studied different basis expansion models (BEM) based on building an OFDM system-level simulation link by using the traditional channel estimation algorithm.Aiming at that partial frequency of basis functions of complex exponential-BEM (CE-BEM) are too high,which will cause a large error,it proposed a modified basis function correcting the basis function coefficient which can effectively removes its excessive frequency.The effect of signal-to-noise ratio and Doppler shift on the mean square error performance of different models are analyzed by simulation.The results show that the mean square error performance of the proposed algorithm is 4~5 dB lower than CE-BEM without increasing complexity,which effectively improves the fitting performance.
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