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Nonparameter Nonlinear Phase Noise Mitigation by Using M-ary Support Vector Machine for Coherent Optical Systems

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6 Author(s)
Minliang Li ; State Key Lab. of Inf. Photonics & Opt. Commun., Beijing Univ. of Posts & Telecommun., Beijing, China ; Song Yu ; Jie Yang ; Zhixiao Chen
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The M-ary support vector machine (SVM) is introduced as a nonparameter nonlinear phase noise (NLPN) mitigation approach for the coherent optical systems. The NLPN tolerance of the system can be improved by using the M-ary SVM to conduct nonlinear detection. In this scheme, SVMs with different classification strategies are utilized to execute binary classification for signals impaired by fiber NLPN. Since the separating hyperplane of each SVM is constructed by training data, this scheme is independent from the knowledge of the transmission link. In numerical simulation, the M-ary SVM performs better than the method of amplitude-dependent phase rotation at the transmitter and receiver, as well as the maximum likelihood detection with back rotation.

M-ary SVM detection example for 16-QAM signal dominated by nonlinear phase noise (NLPN) with 1600 km transmission link and 0 dBm launch power. (a) classification result by SVM1; (b) classification result by SVM2; (c) classification result by SVM3; (d) classification result by SVM4. M-ary SVM detection example for 16-QAM signal dominated by nonlinear phase noise (NLPN) with 1600 km transmission link and 0 dBm launch power. (a) classification result by SVM1; (b) classification result by SVM2; (c) classification result by SVM3; (d) classification result by SVM4.

Published in:

Photonics Journal, IEEE  (Volume:5 ,  Issue: 6 )