Zhang Junfeng, Chen Wei, Gao Mingyi, Shen Gangxiang
Opt Express. 2017 Oct 30;25(22):27570-27580. doi: 10.1364/OE.25.027570.
In this work, we proposed two k-means-clustering-based algorithms to mitigate the fiber nonlinearity for 64-quadrature amplitude modulation (64-QAM) signal, the training-sequence assisted k-means algorithm and the blind k-means algorithm. We experimentally demonstrated the proposed k-means-clustering-based fiber nonlinearity mitigation techniques in 75-Gb/s 64-QAM coherent optical communication system. The proposed algorithms have reduced clustering complexity and low data redundancy and they are able to quickly find appropriate initial centroids and select correctly the centroids of the clusters to obtain the global optimal solutions for large k value. We measured the bit-error-ratio (BER) performance of 64-QAM signal with different launched powers into the 50-km single mode fiber and the proposed techniques can greatly mitigate the signal impairments caused by the amplified spontaneous emission noise and the fiber Kerr nonlinearity and improve the BER performance.
在这项工作中，我们提出了两种基于k均值聚类的算法，用于减轻64正交幅度调制（64-QAM）信号的光纤非线性，即训练序列辅助k均值算法和盲k均值算法。我们在75-Gb/s 64-QAM相干光通信系统中通过实验验证了所提出的基于k均值聚类的光纤非线性减轻技术。所提出的算法具有降低的聚类复杂度和低数据冗余度，并且能够快速找到合适的初始质心并正确选择聚类的质心，以获得大k值时的全局最优解。我们测量了在50公里单模光纤中以不同发射功率输入的64-QAM信号的误码率（BER）性能，所提出的技术能够极大地减轻由放大自发辐射噪声和光纤克尔非线性引起的信号损伤，并提高BER性能。
