Operators are pressured to maximize the achieved capacity over deployed links. This can be
obtained by operating in the weakly nonlinear regime, requiring a precise understanding of …

The optical signal-to-noise ratio (OSNR) and fiber nonlinearity are critical factors in
evaluating the performance of high-speed optical fiber communication systems. Recently …

Joint Estimation of Linear and Non-linear Signal-to-Noise Ratio based on Neural Networks
Page 1 M2F.4.pdf OFC 2018 © OSA 2018 Joint Estimation of Linear and Non-linear Signal-to-Noise …

For high symbol rate fiber optic networks, the estimation and monitoring of time varying link
performance parameters are critical for delivering optimal network performance. In this …

Template for Papers ECOC 2015 Page 1 Fiber Nonlinear Noise-to-Signal Ratio Monitoring
Using Artificial Neural Networks AS Kashi(1,2), Q. Zhuge(1), JC Cartledge(1,2), A. Borowiec(1) …

By associating machine learning and an analytical model (ie, the Gaussian noise model),
we reduce uncertainties on the output power profile and the noise figure of each amplifier in …

Nonlinearity compensation is considered as a key enabler to increase channel transmission
rates in the installed optical communication systems. Recently, data-driven approaches …

To address the open and diverse situation of future optical networks, it is necessary to find a
methodology to accurately estimate the value of a target quantity in an optical performance …

Fiber nonlinearity is one of the major limitations to the achievable capacity in long distance
fiber optic transmission systems. Nonlinear impairments are determined by the signal …

An effective machine learning algorithm, the support vector machine (SVM), is presented in
the context of a coherent optical transmission system. As a classifier, the SVM can create …