首页> 外文会议>Neural Information Processing pt.2; Lecture Notes in Computer Science; 4233 >An Intelligent PSO-Based Control Algorithm for Adaptive Compensation Polarization Mode Dispersion in Optical Fiber Communication Systems
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An Intelligent PSO-Based Control Algorithm for Adaptive Compensation Polarization Mode Dispersion in Optical Fiber Communication Systems

机译:基于PSO的智能控制算法在光纤通信系统中的自适应补偿偏振模色散

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In high bit rate optical fiber communication systems, Polarization mode dispersion (PMD) is one of the main factors to signal distortion and needs to be compensated. Because PMD possesses the time-varying and the statistical properties, to establish an effective control algorithm for adaptive or automatic PMD compensation is a challenging task. Widely used control algorithms are the gradient-based peak search methods, whose main drawbacks are easy being locked into local sub-optima for compensation and no ability to resist noise. In this paper, we introduce particle swarm optimization (PSO), which is an evolutionary approach, into automatic PMD compensation as feedback control algorithm. The experiment results showed that PSO-based control algorithm has unique features of rapid convergence to the global optimum without being trapped in local sub-optima and good robustness to noise in the transmission line that had never been achieved in PMD compensation before.
机译:在高比特率光纤通信系统中,偏振模色散(PMD)是造成信号失真的主要因素之一,需要进行补偿。由于PMD具有时变和统计特性,因此建立有效的自适应或自动PMD补偿控制算法是一项艰巨的任务。广泛使用的控制算法是基于梯度的峰值搜索方法,其主要缺点是很容易将其锁定在局部次优中进行补偿,并且无法抵抗噪声。在本文中,我们将粒子群优化(PSO)作为一种进化方法,引入到自动PMD补偿中作为反馈控制算法。实验结果表明,基于PSO的控制算法具有独特的特点,可以快速收敛到全局最优,而不会陷入局部次优状态,并且对传输线中的噪声具有良好的鲁棒性,这是以前的PMD补偿所没有的。

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