Optical Performance Monitoring through signal processing in current and future optical communication systems

2012 ◽  
Author(s):  
Alan Pak Tao Lau ◽  
Fabian N. Hauske ◽  
Trevor B. Anderson ◽  
Chao Lu
Keyword(s):  
Signal Processing ◽  
Optical Communication ◽  
Communication Systems ◽  
Performance Monitoring ◽  
Optical Performance ◽  
Optical Performance Monitoring ◽  
Optical Communication Systems

scholarly journals Assessment of Linearity Improvement in Optical Communication Systems with Machine Learning Methods

2019 ◽  
Author(s):  
Muhammad Usman Hadi
Keyword(s):  
Machine Learning ◽  
Optical Communication ◽  
Communication Systems ◽  
Performance Monitoring ◽  
Optical Communication System ◽  
Optical Performance Monitoring ◽  
Fiber Nonlinearities ◽  
Machine Learning Methods ◽  
Optical Communication Systems ◽  
Linearity Improvement

Use of Machine Learning (ML) methodologies in optical communications has paved a new pathway. In this paper, firstly, we discuss the use of ML methodologies for reducing optical fiber nonlinearities, nonlinearity compensation, fault detection and optical performance monitoring. Then we present our recent work where we compare RL-SARSA and SVM based method with conventional method. The results show that RL-SARSA and SVM methods are successful candidates in mitigating the nonlinearities in proposed system as compared to conventional optical communication system.

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