[1]孙钢灿,党满满,徐雪菲..改进的基于循环平稳分析的OFDM关键参数估计方法[J].郑州大学学报(工学版),2012,33(02):5-9.[doi:10.3969/j.issn.1671-6833.2012.02.002]
　SUN Gangcan,DANG Manman,XU Xuefei.Improved Blnd Estimation of OFDM Parameters Based onCyclostationarity Analysis Method[J].Journal of Zhengzhou University (Engineering Science),2012,33(02):5-9.[doi:10.3969/j.issn.1671-6833.2012.02.002]
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改进的基于循环平稳分析的OFDM关键参数估计方法()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
33卷
期数:
2012年02期
页码:
5-9
栏目:
出版日期:
2012-03-10

文章信息/Info

Title:
Improved Blnd Estimation of OFDM Parameters Based onCyclostationarity Analysis Method
作者:
孙钢灿; 党满满; 徐雪菲.
郑州大学信息工程学院,河南郑州,450001, 郑州大学信息工程学院,河南郑州,450001, 郑州大学信息工程学院,河南郑州,450001
Author(s):
SUN Gangcan; DANG Manman; XU Xuefei
School of Information Engineering, Zhengzhou University, Zhengzhou 450001,China
关键词:
多径信道;  OFDM;  参数盲估计;  自相关;  循环平稳
Keywords:
multipath channel;  OFDM ;  blind parameters estimation;  autocorrelation;  cyclostationarity
分类号:
TN914
DOI:
10.3969/j.issn.1671-6833.2012.02.002
摘要:
摘要:提出了一种利用OFDM信号自相关特性和循环平稳特性进行多径信道下关键参数盲估计的算法.该算法首先利用OFDM信号的自相关特性估计信号的有效符号长度,接着利用多径信道下的OFDM信号具有二阶循环平稳特性来估计符号长度,并且在此过程中引入平均的思想,通过对信号的一组循环频率求均值的方法得到最终估计值.信号的二阶循环平稳特性使得该算法可抑制多径干扰,平均的处理方法提高了算法的抑制高斯噪声能力.计算机仿真结果表明:该算法在设定的多径信道下,当信噪比SNR=-2 dB时参数盲估计的正确率可以达到90％以上,在信噪比SNR=2 dB时正确率可以达到100％.
Abstract:
This paper proposes a new algorithm for blind estimation of parameters of OFDM signals under mul.tipath channel based on the autocorrelation properties and the cyclostationarity of OFDM signals. The autocor.relation of the OFDM signal is firstly applied to estimate the useful data period, then we introduce average ideawhen estimate symbol period based on the second-order cyclostationarity character of OFDM signals in mul.tipath channel, and get more accurate OFDM symbol period by getting the average value of the cyclic frequencies, so the proposed algorithm has better performance. The simulation results show that the blind parametersestimation accuracy rate of this algorithm can reach more than 90% with SNR equals to -2 dB, as well as al-most 100% when SNR equals to 2 dB.
更新日期/Last Update: 1900-01-01