Perturbation-based Frequency Domain Linear and Nonlinear Noise Estimation

TL;DR

This paper introduces a perturbation-based method using Four-Wave Mixing to distinguish and estimate different noise types in optical communication systems, validated through simulations and experiments.

Contribution

It presents a novel frequency domain technique for separating noise categories based on perturbation responses, applicable in real-time optical signal processing.

Findings

Effective separation of noise categories using perturbation responses.

Successful estimation of noise contributions in experimental setup.

Applicable for in-situ noise analysis along optical links.

Abstract

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.