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MLP and RBF symbol tracking with 16 QAM modulation over multipath distorted channel

机译:在多径失真信道上采用16 QAM调制的MLP和RBF符号跟踪

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摘要

Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were proposed in this paper as two models of non-linear ANN based equalization techniques in order to optimize processing performance, tracking, and minimize error of the channel effects and the ascending noise with 16 QAM Modulation, this work will be referenced with one of the most used linear adaptive equalization; Recursive least squares (RLS), as an evaluation. The two models will be compared in terms of efficiency and robustness facing noisy channel.
机译:本文提出了多层感知器(MLP)和径向基函数(RBF)作为基于非线性ANN的均衡技术的两个模型,以优化处理性能,跟踪并最小化通道效应和上升噪声的误差(16)。 QAM调制,这项工作将以最常用的线性自适应均衡之一为参考;递归最小二乘(RLS)作为评估。两种模型将在面对噪声信道的效率和鲁棒性方面进行比较。

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