Perturbation Analysis of Nonlinear Propagation in a Strongly Dispersive Optical Communication System
By Pontus Johannisson, Magnus Karlsson. Journal of Lightwave Technology, 2012
136 citations recorded by the source corpus.
We discuss an analytical model that predicts the impact of the Kerr nonlinearity in optical communication systems when the signal spectrum is wide and the accumulated dispersion during propagation is large. A detailed derivation of this model is given for a generalized system by means of a perturbation analysis of the Manakov equation with attenuation, gain, and third order dispersion included. As in the case with previous studies, three simplifying assumptions are necessary. These are that (i) the nonlinearity is weak, (ii) the input signal is of a given specific form, and (iii) the signal-noise interaction can be neglected. Under these assumptions, the result is found exactly. We also discuss the accuracy of the analytical result and show that third order dispersion has a small impact in practice.
Subfields: Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/a29005de22f0319fe5e18a617c32e9cd3a7c8d0b
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In Atomic and Molecular Physics, and Optics
In Electrical and Electronic Engineering
- Pontus Johannisson
- Pierluigi Poggiolini
- Erik Agrell
- Vittorio Curri
- Fabrizio Forghieri
- Andrea Carena
- Gabriella Bosco
- Yanchao Jiang
Citations in the corpus
- The GN-Model of Fiber Non-Linear Propagation and its Applications (2014, methodology): “Two further papers, devoted specifically to detailed rederivations of the GN-model, were also recently published (2011–2013) [35]–[36].”
- Modeling of Nonlinear Signal Distortion in Fiber-Optic Networks (2013, methodology): “The derivation is started from the GN model as stated in [20], where the model equation, [20, Eq.”
- The Gaussian Noise Model in the Presence of Inter-Channel Stimulated Raman Scattering (2017, result): “Similar results were independently derived by other groups and the model became widely known as the Gaussian noise (GN) model [14]–[16], [22], [24].”