光学学报, 2013, 33 (5): 0506002, 网络出版: 2013-04-16   

基于电域反馈神经网络的自适应盲均衡方法

Adaptive Blind Equalization Using Electrical Recurrent Neural Networks
作者单位
1 温州大学物理与电子信息工程学院, 浙江 温州 325035
2 温州大学激光与光电子技术研究所, 浙江 温州 325035
摘要
为解决无线分集相干光接收机的电域自适应盲均衡的特定问题,根据动力学驱动反馈神经网络(DDRNN)的特点,提出一种基于同相部分与正交部分振幅激励的DDRNN盲均衡方法。设计了一种结构简单、灵活性强的连续多阈值的正弦函数型激励函数形式,详细分析了该激励函数的参数选择方法并提出了该问题接近点和远离点的新概念;进而从激励函数角度分析了DDRNN电域自适应盲均衡问题的放大因子取值。论述了高阶正交振幅调制(QAM)的激励函数用于低阶QAM系统盲均衡时的适用性。设计了多阈值激励函数和DDRNN新的能量函数并给出相关证明,该激励函数和能量函数的设计和分析不仅可适用于无线相干光接收机的自适应盲均衡,也可推广至其他相关领域。
Abstract
To solve the special issue of electrical adaptive blind equalization for wireless spatial diversity optical coherent receivers, a novel electrical adaptive blind equalization method based on dynamically driven recurrent neural networks (DDRNNs) with in-phase/quadrature amplitude component continuous activation is proposed. A multi-threshold continuous amplitude sinusoidal type activation function is designed. This activation function is simple and flexible. How to select the parameters of the activation function is analyzed in detail and the new concepts of the approach point and leaving point are proposed. Amplification factor selection range of blind equalization is analyzed using DDRNN about electrical adaptive blind equalization from the perspective of activation function. Then, the applicability of detecting low-order quadrature amplitude modulation (QAM) signals using higher order QAM activation function is discoursed. Furthermore, the new energy function with the condition of the multi-threshold continuous activation function is proposed and proven. The design and analysis of the activation function and energy function are not only suitable for the blind equalization issues, but also can be extended to other fields.

阮秀凯, 李昌, 谈燕花, 张耀举. 基于电域反馈神经网络的自适应盲均衡方法[J]. 光学学报, 2013, 33(5): 0506002. Ruan Xiukai, Li Chang, Tan Yanhua, Zhang Yaoju. Adaptive Blind Equalization Using Electrical Recurrent Neural Networks[J]. Acta Optica Sinica, 2013, 33(5): 0506002.

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