基于常交叉算法的盲均衡新方案

Shunlan Liu, Jian-Hong Hu, M. Dai
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引用次数: 0

摘要

在这项工作中,我们提出了两种新的适用于传输交叉交叉qam信号的盲均衡方案。在恒交叉算法(CXA)框架的基础上,通过在CXA的代价函数中加入星座匹配误差(CME)项,得到了修正的CXA (MCXA)。对于MCXA, CXA项提供全局收敛,CME项有助于减少残差,加速收敛。此外,我们提出了一个决策导向版本的MCXA,称为DD-MCXA,它可以提高MCXA的性能。保持CXA良好的初始收敛特性,当均衡器接近收敛时,DD-MCXA自动降低CXA误差的影响。仿真和分析均证明了所提方案的良好性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New blind equalization schemes based on constant cross algorithm
In this work, we present two new blind equalization schemes suitable for transmitting cross cross-QAM signals. Based on the framework of constant cross algorithm (CXA), a modified CXA (MCXA) is obtained by adding a constellation-matched error (CME) term to the cost function of the CXA. For the MCXA, the CXA term provides global convergence and the CME term helps to decrease the residual error and accelerate convergence. Furthermore, we propose a decision-directed version of the MCXA, called DD-MCXA, which can improves the performance of the MCXA. Preserving the good initial convergence characteristics of the CXA, the DD-MCXA automatically decreases the effect of the CXA errors when the equalizer is near convergence. Both simulation and analysis demonstrate the good performance of the proposed schemes.
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