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Blind equalization based on a cascade of a new algorithm and multi-step prediction error filter

机译:基于级联的新算法和多步预测误差滤波器的盲均衡

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Adaptive channel equalization accomplished without a training sequence is known as blind equalization. Blind equalizers may be implemented with linear prediction error filters (LPEF) but the delay (D) cannot be controlled with one-step predictors to minimize the mean square error (MSE). Consequently, multi-step prediction error filters (MSPEF) has been suggested as a solution to the problem. But the slowness of the convergence process will remain a problem, so we propose a new technique to fast the convergence rate. In this paper, a blind equalizer composed of a modified algorithm (MA) cascaded with MSPEF is proposed (MAMSPEF). Simulation results show comparable improvements of the proposed equalizer relative to the LPEF or the MSPEF equalizers and compared also with CMAMSPEF for symmetric constellation QAM.
机译:无需训练序列即可完成的自适应信道均衡称为盲均衡。盲均衡器可以用线性预测误差滤波器(LPEF)来实现,但是延迟(D)不能用单步预测器来控制,以使均方误差(MSE)最小。因此,已经提出了多步预测误差滤波器(MSPEF)作为该问题的解决方案。但是收敛过程的缓慢性仍然是一个问题,因此我们提出了一种加快收敛速度​​的新技术。本文提出了一种由MSPEF级联的改进算法(MA)组成的盲均衡器(MAMSPEF)。仿真结果表明,相对于LPEF或MSPEF均衡器,所提出的均衡器具有可比的改进,并且与CMAMSPEF相比,它还可以改善对称星座QAM。

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