Y. Jiang

TL;DR: This paper tries to gather the recent results regarding the Gaussian-noise 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.

TL;DR: This paper analyzes in detail the GN-model errors and derives a complete set of formulas accounting for all single, cross, and multi-channel effects that constitute the enhanced GN- model (EGN-model), which is found to be very good when assessing detailed span-by-span NLI accumulation and excellent when estimating realistic system maximum reach.

TL;DR: In this paper, the authors investigated the reach increase obtained through nonlinearity mitigation by means of transmission symbol rate optimization (SRO), and showed that the EGN model that properly accounts for the phenomenon is the four-wave mixing.

TL;DR: In this paper, the question of when and whether more sophisticated models are truly needed in any given system/network scenario, for a given set of accuracy and computational complexity constraints, then naturally arises.

TL;DR: In this paper, an extended and more detailed version of the GN-model derivation is reported, providing deeper insight into the model and some straightforward generalizations of the model are also proposed.