Open AccessK-means-clustering-based fiber nonlinearity equalization techniques for 64-QAM coherent optical communication system
Author(s) -
Junfeng Zhang,
Wei Chen,
Mingyi Gao,
Gangxiang Shen
Publication year - 2017
Publication title -
optics express
Language(s) - Danish
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.25.027570
Subject(s) - quadrature amplitude modulation , qam , centroid , cluster analysis , computer science , multi mode optical fiber , nonlinear system , optical communication , redundancy (engineering) , algorithm , optics , electronic engineering , bit error rate , optical fiber , physics , telecommunications , artificial intelligence , engineering , decoding methods , quantum mechanics , operating system
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.