光偏振复用正交频分复用系统中基于联合近似特征矩阵对角化-独立分量分析的盲均衡算法

摘要

该文提出一种在光偏振复用正交频分复用(PDM-OOFDM)系统中基于联合近似特征矩阵对角化-独立分量分析(JADE-ICA)的盲解偏振复用算法.在传统的偏振复用系统中,恒模算法(CMA)被用于解偏振复用信号.然而,该方法需要多次对CMA滤波器系数更新,CMA收敛时间较长,并且CMA算法解偏振复用可能导致奇异性问题.该文结合对经典ICA算法及其模型的分析,提出将JADE-ICA算法用于PMD-OOFDM系统中进行解偏振复用信号.利用该方法,可以分离在发送端和接收端混有高斯白噪声的偏振信号成分,并且提高了系统中偏振信号的分离性能;同时,避免了传统CMA在解偏振复用中的奇异性问题.仿真结果表明,该文方法可以有效分离PMD-OOFDM系统中的偏振信号.%In this study, a complex-valued Joint Approximate Diagonalization of Eigen-matrices (JADE)- Independent Component Analysis (JADE-ICA) algorithm is proposed for the Polarization Division Multiplexed in Optical Orthogonal Frequency Division Multiplexing (PDM-OOFDM) systems. Generally, the Constant Modulus Algorithm (CMA) method is used to devise polarization signals in PDM-OOFDM systems. However, this method requires multiple filter coefficients update on CMA, needs more time to converge, and lead it to the polarization multiplexing singularity problem. In this paper, a method based on JADE-ICA algorithm is applied to the PDM-OOFDM systems. With this method, the signals can be separated at the sending and the receiving, which mixed with white Gaussian noise polarization components. Moreover, it improves the separation performance of the system with respect to the polarization signal, while avoiding the traditional CMA polarization multiplexing in the solution of the singularity. Simulations demonstrate the effectiveness of the proposed method to devise signals of polarization in PDM-OOFDM systems.