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A flexible polarization demultiplexing method based on an adaptive Kalman filter(AKF) is proposed in which the process noise covariance has been estimated adaptively. The proposed method may significantly improve the adaptive capability of an extended Kalman filter(EKF) by adaptively estimating the unknown process noise covariance. Compared to the conventional EKF, the proposed method can avoid the tedious and time consuming parameter-by-parameter tuning operations. The effectiveness of this method is confirmed experimentally in 128 Gb/s 16 QAM polarization-division-multiplexing(PDM) coherent optical transmission systems. The results illustrate that our proposed AKF has a better tracking accuracy and a faster convergence(about 4 times quicker)compared to a conventional algorithm with optimal process noise covariance. 相似文献
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针对偏振复用16阶正交幅度调制(16QAM)传输系统(PDM-16QAM),基于线型卡尔曼滤波器,提出了一种计算复杂度更低、线宽容忍度更高的双偏振并行载波相位恢复算法,使用两个偏振态内环和外环的符号信息对两个偏振态同时进行相位噪声估计。仿真结果表明,在传输速率为224Gb/s传输速率下,本文算法相比于单偏振卡尔曼滤波器算法的线宽容忍度提高了7倍,由原来的400kHz提高至2800kHz。此外,相比于单偏振卡尔曼滤波器载波相位恢复算法,本文算法并行处理符号个数提升了4倍左右,有效提高了算法的实时性,但是复杂度有所降低。最后,在传输速率为224Gb/s的PDM-16QAM传输实验中对本文算法进行了验证。 相似文献
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