On the Accuracy of the GN-Model and on Analytical Correction Terms to Improve It

TL;DR

This paper critically analyzes the GN-model for optical system performance prediction, identifies its limitations, and introduces the enhanced EGN-model with comprehensive formulas that significantly improve accuracy in NLI estimation.

Contribution

It derives a complete set of formulas for the EGN-model, addressing previous neglect of certain NLI contributions, and validates its superior accuracy through extensive simulations.

Findings

EGN-model provides very good accuracy for span-by-span NLI

EGN-model estimates maximum system reach with high precision

Proposed formulas outperform previous correction methods

Abstract

The GN-model has been proposed as an approximate but sufficiently accurate tool for predicting uncompensated optical coherent transmission system performance, in realistic scenarios. For this specific use, the GN-model has enjoyed substantial validation, both simulative and experimental. Recently, however, it has been pointed out that its predictions, when used to obtain a detailed picture of non-linear interference (NLI) noise accumulation along a link, may be affected by a substantial NLI overestimation error, especially in the first spans of the link. In this paper we analyze in detail the GN-model errors. We discuss recently proposed formulas for correcting such errors and show that they neglect several contributions to NLI, so that they may substantially underestimate NLI in specific situations, especially over low-dispersion fibers. We derive a complete set of formulas accounting for all single, cross, and multi-channel effects, this set constitutes what we have called the enhanced GN-model (EGN-model). We extensively validate the EGN model by comparison with accurate simulations in several different system scenarios. The overall EGN model accuracy is found to be very good when assessing detailed span-by-span NLI accumulation and excellent when estimating realistic system maximum reach. The computational complexity vs. accuracy trade-offs of the various versions of the GN and EGN models are extensively discussed.