基于DD-LMS和MCMA的盲判决反馈均衡算法研究

    Study On Blind Decision Feedback Equalization Algorithm Based on DD-LMS and MCMA

    • 摘要: 文章对具有DFE结构的盲均衡算法作了研究,在一种修正常模算法(MCMA)代价函数中引入泄漏因子,并将常模算法(CMA)和直接判决-最小均方误差算法(DD-LMS)同时应用到盲判决反馈均衡器的抽头更新中,得到一种适用范围广?均衡特性好?变步长的DD-LLMS MCMBDFE算法。该算法在均衡的同时能自动补偿由信道引起的相位误差,收敛速度快,收敛后剩余误差小,同时还能克服当均衡器长期没有持续输入激励时,LMS算法产生的抽头系数漂移问题。仿真结果表明DD-LLMS MCMBDFE算法是一种有效的盲判决反馈均衡算法。

       

      Abstract: This paper studied on blind equalization algorithm based on Decision Feedback Equalizer and applied the idea of combining CMA with DD-LMS to update the coefficient of blind decision feedback equalizer based on a modified constant modulus cost-function in which a leaking gene was brought,then an variable step size algorithm combing DD-LLMS with MCMBDFE was derived which has an extensive applicability and a goodish equalization property.This algorithm which has a fast convergence rate and a lower residual error when converged recovers the channel phase error automatically while equalizing,it also solves the problem of coefficient excursion which was produced by LMS algorithm when the equalizer has no continuous input.Computer simulation validates that the algorithm of blind decision feedback equalization combing DD-LLMS with MCMBDFE is effective.

       

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