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首页> 外文会议>EUSIPCO 2007;European signal processing conference >PERFORMANCE COMPARISON OF THE BLIND MULTI CHANNEL FREQUENCYDOMAIN NORMALIZED LMS AND VARIABLE STEP-SIZE LMS WITH NOISE
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PERFORMANCE COMPARISON OF THE BLIND MULTI CHANNEL FREQUENCYDOMAIN NORMALIZED LMS AND VARIABLE STEP-SIZE LMS WITH NOISE

机译：盲多通道频率归一化LMS和可变步长LMS的性能比较

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摘要

The paper provides a comparative performance analysisrnof the normalized multichannel frequency-domain leastmean-rnsquares (MCFLMS) and variable step size MCFLMSrn(VSS-MCFLMS) algorithms used in blind channel identification.rnBoth the algorithms eliminate the need of a priorirnestimation of the step size parameter for rapid convergencernto the desired solution. We perform the convergence analysisrnof the normalized MCFLMS (NMCFLMS) and show thatrneven for a moderate SNR, the algorithm fails to converge tornthe eigenvector corresponding to the minimum eigenvalue ofrnthe data correlation matrix and hence misconverge to a fictitiousrnsolution. On the other hand, we show that the VSSMCFLMSrnalgorithm converges, both in noise-free and noisyrnconditions, to the eigenvector corresponding to the minimumrneigenvalue and therefore more noise robust as compared tornthe NMCFLMS. The enhanced noise robustness of the VSSMCFLMSrnalgorithm over the NMCFLMS algorithm was verifiedrnusing computer simulation results for a wide range ofrnSNRs.
机译：本文针对用于盲信道识别的归一化多通道频域最小均方（MCFLMS）算法和可变步长MCFLMSrn（VSS-MCFLMS）算法提供了比较性能分析。这两种算法都无需先验估计步长参数快速收敛到所需的解决方案。我们在归一化的MCFLMS（NMCFLMS）上进行了收敛分析，结果表明即使对于中等SNR，该算法也无法收敛到与数据相关矩阵的最小特征值相对应的特征向量，从而失收敛为一个虚拟解。另一方面，我们表明，在无噪声和有噪声的条件下，VSSMCFLMS算法均收敛于与最小特征值相对应的特征向量，因此与NMCFLMS相比，噪声鲁棒性更高。利用计算机仿真结果对宽信噪比（SNR）进行了验证，验证了VSSMCFLMSrn算法在NMCFLMS算法上具有更高的噪声鲁棒性。

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  • 来源
  • 会议地点 Poznan(PL);Poznan(PL)
  • 作者

    Mohammad Ariful Haque; Kamrul Hasan;

  • 作者单位

    Department of Electrical and Electronic EngineeringrnBangladesh University of Engineering and Technology, Dhaka, Bangladesh Email: arifulhoque@eee.buet.ac.bd;

    rnDepartment of Electrical and Electronic EngineeringrnBangladesh University of Engineering and Technology, Dhaka, Bangladesh Email: khasan@eee.buet.ac.bd;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 通信理论;
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