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一种不受信道阶数估计影响的SIMO直接盲均衡算法 被引量:2

Direct SIMO Blind Equalization Algorithm Independent of Channel Order Estimation
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摘要 针对单输入多输出(Single-Input-Multiple-Output,SIMO)模型提出一种不需要信道阶数估计的直接盲均衡算法。文章利用接收数据的截短协方差矩阵和信号子空间的关系设计一种零延迟均衡器,并通过信道矩阵和均衡器系数的合响应特性克服了算法相位偏转的问题,最后得到一种对信道阶数估计鲁棒并且没有相位偏转的盲均衡算法。该算法不同于一般子空间类算法,不需要直接对接收信号的协方差矩阵进行信号子空间和噪声子空间的分解,因此对信道阶数估计具有很强的鲁棒性。文章给出了算法的Batch实现过程,同时为更好适应一般时变信道环境和实现实时处理的要求,通过递归迭代得到算法的自适应实现过程。仿真实验表明该算法几乎不受信道阶数过估计或欠估计的影响,同时该算法具有良好的均方误差(Mean Square Error,MSE)和误符号率SER(Symbol Error Rate,SER)性能,并且具有很快的收敛速度。 Direct blind equalization algorithm for Single-Input-Multiple-Output(SIMO) model is proposed.The algorithm is independent of channel order estimation.Through the relationship between signal subspace and truncated data covariance,zero-delay equalizer which has random phase rotation problem is investigated.The combined impulse response of the channels matrix and equalizer filter impulse coefficients is used to deal with phase rotation problem of the proposed equalizer,so that a novel blind equalization algorithm is presented in this paper.Unlike many known subspace methods,the algorithm proposed in this paper do not rely on signal and noise subspace separation of received data covariance,and is robust to channel order estimation.The batch processing program of the proposed equalization algorithm is introduced in this paper.Based on recursion and iteration methods,the adaptive processing program of the proposed algorithm is also presented in this paper.Consequently the algorithm can be used in time-varying environment and can be applied to on-line processing.Simulation results illustrate that the performance of the proposed algorithm is also well in the condition of overestimation or underestimation of channel order.Besides that,good Mean Square Error(MSE),Symbol Error Rate(SER) and convergence performance are also presented through the simulation.
出处 《信号处理》 CSCD 北大核心 2012年第4期519-525,共7页 Journal of Signal Processing
基金 国家自然科学基金(61072046)
关键词 盲均衡 单输入多输出 二阶统计量 信道阶数 blind equalization Single-Input-Multiple-Output Second Order Statistics channel order
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参考文献14

  • 1Tong L. , Xu G. and Kailath T. Blind identification and equalization based on second-order statistics: a time domain approach [ J ]. IEEE Transactions on Information Theory, 1994, 41(1) :308-311.
  • 2Gazzah H.. SOS-based blind channel equalization with quadratic complexity [ J ]. IEEE Transactions on Signal Processing, 2011, 59(2): 837-841.
  • 3Li X. , Fan H.. Direct Estimation of Blind zero-forcing equalizers based on second-oder Statistics [ J ]. IEEE Transactions on Signal Processing, 2000, 48 ( 8 ) : 2211-2218.
  • 4Seung Kyung, Cho Juphil, and KiBaik Heung. Blind adaptive channel equalization using muhichannel linear prediction-based cross-correlation[J]. IEEE Transactions on Consumer Electronics, 2004, 50(4) :1026-1032.
  • 5田营,葛临东,王彬,王露.一种改进的稀疏多径信道盲辨识算法[J].信号处理,2011,27(7):1009-1015. 被引量:2
  • 6Liu S. 1. , Zhu F. , Hu J. h.. Research on blind equalization algorithm of modified RLS based on canonical correlation analysis [ C ] // IEEE 2009 International Conference on Communications and Mobile Computing. Yunnan: 2009: 377-380.
  • 7Gazzab H.. Optimum blind muhichannel equalization using the linear prediction algorithm [ J ]. IEEE Transactions on Signal Processing, August 2006, 54 (08) : 32423247.
  • 8Kaeha I, Meraim K A and Belouehrani A. A low-cost adaptive algorithm for blind equalization without channel order estimation [ C]//ISCCSP 2008. Malta: 12-14 March 2008.
  • 9Chen S. , Wolfgang A. and Shi Y.. Space-time decision feedback equalization using a hainimum bit error rate design for single-input Multi-Output Channels [ J ]. lET Communications, 2007, 1 (4) : 671-678.
  • 10Chen F.j. , Kwong S. , Kok C.w.. Blind MMSE equalization of FIR/IIR channels using oversampling and muhicbannel linear prediction[J]. ETRI Journal, 2009, 31(2).

二级参考文献9

  • 1Moulines E., Duhamel P., Cardoso J.-F. and Mayrargue S. Subspace methods for the blind identification of multichannel FIR Filters [ J ]. IEEE Trans. on Signal Processing, 1995, 43(2): 516-525.
  • 2Karim A. -M. , Moulines E. and Loubaton P., Prediction error method for second-order blind identification [ J ]. IEEE Trans. Signal Processing, 1997, 45(3) : 694-705.
  • 3Zhi Ding, Matrix outer product decomposition method for blind multiple channel identification [ J ]. IEEE Trans. Signal Processing, 1997, 45 (2) : 3053-3061.
  • 4Liavas A. P., Regalia P. A. and Delmas J. -P. Blind channel approximation: Effective channel order determination [J]. IEEE Trans. Signal Processing, 1999, 47 (12) : 3336-3344.
  • 5Liavas A.P., Regalia P. A. and Delmas J. -P. Robustness of least-squares and subspace methods for blind channel identification/equalization with respect to effective channel undermodeling/overmodeling[ J]. IEEE Trans. Signal Processing, 1999, 47(6): 1636-1645.
  • 6Liavas A. P., Regalia P.A. and Delmas J. -P. On the robustness of the linear prediction method for blind channel identification with respect to effective channel undermodeling/overmodeling, IEEE Trans. Signal Processing, 2000, 48(5) : 1477-1481.
  • 7Javier Vfa, Ignacio Santamaria and Jestus Perez. Effective channel order estimation based on combined identification/equalization[ J ]. IEEE Trans. on Signal Processing, 2006, 54(9) : 3518-3526.
  • 8Rice university. Signal Processing Information Base [ DB/ OL]. http :////spib. rice. edu/spib/microwave, html.
  • 9王彬,葛临东,刘媛涛.一种基于矩阵外积分解的信道盲辨识与盲均衡算法[J].信号处理,2008,24(5):839-844. 被引量:1

共引文献1

同被引文献11

  • 1Tong L,Xu G,Kailath T. Blind identification and equalization based on second-order statistics:a time domain approach[J].{H}IEEE Transactions on Information Theory,1994.340-349.
  • 2Xu G,Liu H,Tong L. A least squares approach to blind channel identification[J].{H}IEEE Transactions on Signal Processing,1995,(12):2982-2993.
  • 3Aissa-El-Bey A,Grebici M,Abed-Meraim K. Blind system identification using cross-relation methods:further results and developments[A].2003.649-652.
  • 4Hua Y,Wax M. Strict identifiability of multiple FIR channels driven by an unknown arbitrary sequence[J].{H}IEEE Transactions on Signal Processing,2006,(03):756-759.
  • 5Wang S,Manton J,Devlin J. An FFT-based method for bind identification of FIR SIMO channels[J].{H}IEEE Signal Processing Letters,2009,(07):437-440.
  • 6Karakutuk S,Tuncer T E. Channel matrix recursion for blind effective channel order estimation[J].{H}IEEE Transactions on Signal Processing,2011,(04):1642-1653.
  • 7Shi M,Yi Q M. An efficient blind SIMO channel identification algorithm via eigenvalue decomposition[J].{H}LECTURE NOTES IN CONTROL AND INFORMATION SCIENCES,2010,(01):41-47.
  • 8He Z S,Cichocki A. Robust channel identification using FOCUSS method[J].Advance in Neural Network Research and Application,2011,(01):471-477.
  • 9Schimid D,Enzner G. Cross-relation-based blind SIMO identifiability in the presence of near-common zeros and noise[J].{H}IEEE Transactions on Signal Processing,2012,(01):60-72.
  • 10Gabet J D,Bojanczyk A W. Effective channel order estimation based on nullspace structure and exponential fit[J].{H}IEEE Transactions on Signal Processing,2010,(10):5425-5430.

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