Perturbation-based Frequency Domain Linear and Nonlinear Noise Estimation

In this paper, a new method for the separation of noise categories based on Four-Wave Mixing is presented. The theoretical analysis is grounded in the Gaussian Noise model and verified by split step simulations. The noise categories react differently to the introduced perturbations, by performing a...

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Published in:arXiv.org 2021-05
Main Authors: Vaquero-Caballero, F J, Ives, D J, Savory, S J
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Language:English
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Four-wave mixing
Noise
Perturbation
Power spectral density
Random noise
Spectrum analysers
Transceivers
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Savory, S J
description In this paper, a new method for the separation of noise categories based on Four-Wave Mixing is presented. The theoretical analysis is grounded in the Gaussian Noise model and verified by split step simulations. The noise categories react differently to the introduced perturbations, by performing a set of perturbations the behaviour of the different categories can be separated by means of a least-square fitting. Given ASE is independent of the induced perturbations, it is possible to separate noise contributions. The analysis includes constant and variable power perturbations. The estimation of the noise categories is discussed from two points of view: NSR evolution post-DSP processing, and over the power spectral density in a notched region. The NSR estimation can only be performed at reception, whereas the power spectral density approach can be performed along the optical link if a high resolution Optical Spectrum Analyzer is available. Additionally, we perform a simple experimental verification considering of two WaveLogic 3 transceivers for the NSR, successfully estimating the noise contributions.
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subjects Categories
Four-wave mixing
Noise
Perturbation
Power spectral density
Random noise
Spectrum analysers
Transceivers
title Perturbation-based Frequency Domain Linear and Nonlinear Noise Estimation
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