Equalização Cega com Realimentação de Decisões Baseada em Redes Imunológicas Artificiais

Diogo C. Soriano, Everton Z. Nadalin, C. Wada, Rafael Ferrari, R. Suyama, Romis Attux
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Abstract

— This work proposes a blind strategy for adapting the parameters of a decision-feedback equalizer (DFE). The approach, which is based on the constant modulus (CM) criterion and on an artificial immune system, was tested under scenarios characterized by channels representative of a number of aspects relevant from a practical standpoint. In all cases, it was possible to find the global optimum of the CM criterion with a number of iterations considered by us to be quite reasonable in view of, inter alia , the complexity of the employed search tool.
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基于人工免疫网络的决策反馈盲均衡
这项工作提出了一种适应决策反馈均衡器(DFE)参数的盲策略。该方法基于恒定模量(CM)标准和人工免疫系统,在具有代表从实际角度来看相关的许多方面的通道特征的场景下进行了测试。在所有情况下,有可能找到CM标准的全局最优,我们认为,考虑到所使用的搜索工具的复杂性,许多迭代是相当合理的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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