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16QAM Blind Equalization via Maximum Entropy Density Approximation Technique and Nonlinear Lagrange Multipliers

机译:通过最大熵密度近似技术和非线性拉格朗日乘数的16QAM盲均衡

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摘要

Recently a new blind equalization method was proposed for the 16QAM constellation input inspired by the maximum entropy density approximation technique with improved equalization performance compared to the maximum entropy approach, Godard's algorithm, and others. In addition, an approximated expression for the minimum mean square error (MSE) was obtained. The idea was to find those Lagrange multipliers that bring the approximated MSE to minimum. Since the derivation of the obtained MSE with respect to the Lagrange multipliers leads to a nonlinear equation for the Lagrange multipliers, the part in the MSE expression that caused the nonlinearity in the equation for the Lagrange multipliers was ignored. Thus, the obtained Lagrange multipliers were not those Lagrange multipliers that bring the approximated MSE to minimum. In this paper, we derive a new set of Lagrange multipliers based on the nonlinear expression for the Lagrange multipliers obtained from minimizing the approximated MSE with respect to the Lagrange multipliers. Simulation results indicate that for the high signal to noise ratio (SNR) case, a faster convergence rate is obtained for a channel causing a high initial intersymbol interference (ISI) while the same equalization performance is obtained for an easy channel (initial ISI low).
机译:最近,在最大熵密度近似技术的启发下,针对16QAM星座输入提出了一种新的盲均衡方法,与最大熵方法,Godard算法等相比,均衡性能得到了改善。另外,获得了最小均方误差(MSE)的近似表达式。想法是找到那些拉格朗日乘数,使近似的MSE最小。由于获得的MSE相对于Lagrange乘子的推导导致了Lagrange乘子的非线性方程,因此忽略了MSE表达式中导致Lagrange乘子方程非线性的部分。因此,获得的拉格朗日乘数不是那些使近似MSE达到最小值的拉格朗日乘数。在本文中,我们基于拉格朗日乘子的非线性表达式导出了一组新的拉格朗日乘子,该表达式是通过将相对于拉格朗日乘子的近似MSE最小化而获得的。仿真结果表明,对于高信噪比(SNR)的情况,对于引起高初始符号间干扰(ISI)的信道,可以获得更快的收敛速度,而对于简单信道(初始ISI低)可以获得相同的均衡性能。 。

著录项

  • 期刊名称 other
  • 作者

    R. Mauda; M. Pinchas;

  • 作者单位
  • 年(卷),期 -1(2014),-1
  • 年度 -1
  • 页码 548714
  • 总页数 5
  • 原文格式 PDF
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  • 中图分类
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  • 入库时间 2022-08-21 11:19:32

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