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一种基于二阶统计量的盲信道辨识与均衡 被引量：3

A algorithm for blind identification and equalization based on second-order statistics
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摘要 本文提出了一种新的基于二阶统计量的盲信道辨识与均衡方法。通过对接收信号过采样,等效的信道矩阵有特殊的结构可以提供足够的信道信息给我们来估计信道矩阵。根据Tong等人的观点,本文给出了另外一种证明的方法,并由此得到了一种新的基于二阶统计量的盲信道辨识与均衡方法。仿真结果表明此方法和Tong的方法具有同样的均衡效果。 This paper presented a new approach to blind channel estimation and equalization based on Second Order Statistics （SOS） .Due to over-sampling,the equivalent channel matrix possesses a particular structure which making estimating the channel possible.According to Tong＇s point,this text gave another kind of proving method and got a kind of approaches to blind channel estimation and equalization based on Second Order Statistics.Simulation example was provided to demonstrate the algorithm as good as Tong＇s techniques.
作者 陈洪 舒勤 孟川杰 王韬 王凤兰
机构地区 四川大学电气信息学院 眉山科学技术学校
出处 《中国测试技术》 CAS 2006年第3期100-102,共3页 CHINA MEASUREMENT & TESTING TECHNOLOGY
关键词 二阶统计量 盲信道辨识 均衡 过采样 SOS Blind channel estimation Equslization Oversampling
分类号 TN915.06 [电子电信—通信与信息系统]
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参考文献5

  • 1Godard D N.Self-recovering equalization and carrier tracking in two-dimensional data communication systems[J].IEEE Trans.Communication,1980,28 (11):1867-1875.
  • 2Hatzinakos D,Nikias CL.Blind equalization using a tricepstrum based algorithm[J].IEEE Trans Communication,1991,39(5):669-681.
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  • 4Tong L,Xu G,Kailath T.Blind channel identification and equalization using second-order statistics:a time domain approach[J].IEEE Trans Information theory,1994,40(10):340-349.
  • 5S.Prakriya.Eigenanalysis based blind methods for identification,equalization and inversion of linear time invariant channels[J].IEEE Trans Signal Processing,2002,50(3):1525-1532.

同被引文献23

  • 1王丹,蒋铃鸽,何晨.一种逆迭代互关系子空间SIMO信道盲辨识方法[J].电子学报,2006,34(7):1226-1230. 被引量：2
  • 2李静,王华奎,赵菊敏.基于二阶循环统计量的直接盲MMSE均衡算法[J].太原理工大学学报,2007,38(1):38-41. 被引量：2
  • 3J Shen, Z Ding. Direct blind MMSE channel equalization based on second-order statistics[ J]. IEEE Transactions on Signal Processing,2000,48(4) : 1015 - 1022.
  • 4K S Alm,J Cho,H K Balk. Blind adaptive channel equalization using multi-channel linear prediction-based cross-correlation vector estimation [ J ]. IEEE Transactions on Consumer Electronics, 2004,5(4) : 1024 - 1032.
  • 5I Kacha, K A Memim, A Relouchrani. A low-cost adaptive algorithm for blind equalization without channel order estimation [ A ]. Proceedings of the Third International Symposium on Communications, Control and Signal Processing [ C ]. Malta: IEEE,2008. 1384- 1388.
  • 6J Shen,Z Ding. Zero-forcing blind equalization based on subspace estimation for multiuser systems[ J]. IEEE Transactions on Communication, 2001,49 (2) : 262 - 271.
  • 7D G Manolalds, V K Ingle,S M Kogon. Statistical and Adaptive Signal Processing[ M]. Beijing: Publishing House of Electronics Industry, 2003. 709 - 710.
  • 8E Moulines,P Duhamel, et al. Subspace methods for the bfind identification of multi-channel FIR filters [J]. IEEE Transactions on Signal Processing, 1995,43(2):516- 525.
  • 9A P Liavas, P A Regalia, J P Delmas. Robustness of leastsquares and subspace methods for blind channel idenfificationlequalization with respect to effective channel undermodeling/ overmodeling[ J]. IEEE Transactions on Signal Processing, 1999,47(6) : 1636 - 1645.
  • 10Kacha I,Meraim K A,Relouchrani A.A Low-cost Adaptive Algorithm for Blind Equalization Without Channel OrderEstimation. ISCCSP 2008 . 2008

引证文献3

二级引证文献1

中国测试技术
2006年 第3期

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