Several approximate non-linear fiber propagation models have been proposed over the years. Recent reconsideration and extension of earlier modeling efforts has led to the formalization of the so-called Gaussian-noise (GN) model. The evidence collected so far hints at the GN-model as being a relatively simple and, at the same time, sufficiently reliable tool for performance prediction of uncompensated coherent systems, characterized by a favorable accuracy versus complexity trade-off. This paper tries to gather the recent results regarding the GN-model definition, understanding, relations versus other models, validation, limitations, closed form solutions, approximations and, in general, its applications and implications in link analysis and optimization, also within a network environment.

The GN-Model of Fiber Non-Linear Propagation and its Applications / Poggiolini, Pierluigi; Bosco, Gabriella; Carena, Andrea; Curri, Vittorio; Jiang, Yanchao; F., Forghieri. - In: JOURNAL OF LIGHTWAVE TECHNOLOGY. - ISSN 0733-8724. - STAMPA. - 32:4(2014), pp. 694-721. [10.1109/JLT.2013.2295208]

The GN-Model of Fiber Non-Linear Propagation and its Applications

POGGIOLINI, PIERLUIGI;BOSCO, GABRIELLA;CARENA, Andrea;CURRI, Vittorio;JIANG, YANCHAO;
2014

Abstract

Several approximate non-linear fiber propagation models have been proposed over the years. Recent reconsideration and extension of earlier modeling efforts has led to the formalization of the so-called Gaussian-noise (GN) model. The evidence collected so far hints at the GN-model as being a relatively simple and, at the same time, sufficiently reliable tool for performance prediction of uncompensated coherent systems, characterized by a favorable accuracy versus complexity trade-off. This paper tries to gather the recent results regarding the GN-model definition, understanding, relations versus other models, validation, limitations, closed form solutions, approximations and, in general, its applications and implications in link analysis and optimization, also within a network environment.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2542088
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