DocumentCode :
69632
Title :
Nonparameter Nonlinear Phase Noise Mitigation by Using M-ary Support Vector Machine for Coherent Optical Systems
Author :
Minliang Li ; Song Yu ; Jie Yang ; Zhixiao Chen ; Yi Han ; Wanyi Gu
Author_Institution :
State Key Lab. of Inf. Photonics & Opt. Commun., Beijing Univ. of Posts & Telecommun., Beijing, China
Volume :
5
Issue :
6
fYear :
2013
fDate :
Dec. 2013
Firstpage :
7800312
Lastpage :
7800312
Abstract :
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.
Keywords :
light coherence; maximum likelihood detection; numerical analysis; phase noise; support vector machines; M-ary SVM; M-ary support vector machine; NLPN tolerance; amplitude-dependent phase rotation; binary classification; coherent optical systems; maximum likelihood detection; nonlinear detection; nonparameter nonlinear phase noise mitigation; numerical simulation; training data; transmission link; Nonlinear optics; Optical noise; Phase noise; Support vector machines; Training; Training data; Vectors; M-ary SVM; Nonlinear phase noise; quadratic amplitude modulation (QAM); support vector machine (SVM);
fLanguage :
English
Journal_Title :
Photonics Journal, IEEE
Publisher :
ieee
ISSN :
1943-0655
Type :
jour
DOI :
10.1109/JPHOT.2013.2287565
Filename :
6648652
Link To Document :
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