Optical communication systems represent the backbone of modern communication
networks. Since their deployment, different fiber technologies have been used to deal with …

We introduce low complexity machine learning method method (based on lasso regression,
which promotes sparsity, to identify the interaction between symbols in different time slots …

Dual polarization quadrature phase-shifting keying (DP-QPSK) wavelength division
multiplexing (WDM) systems are currently acting as the backbone of long-haul optical …

In this paper, a novel deep learning architecture, Fourier neural operator (FNO), has been
introduced to ap-proximate the nonlinear Schrodinger equation which characterizes fiber …

A fast Newton-based support vector machine (N-SVM) nonlinear equalizer (NLE) is
experimentally demonstrated, for the first time, in 40 Gb/s 16-quadrature amplitude …

Communication using the optical fibre channel can be challenging due to nonlinear effects
that arise in the optical propagation. These effects represent physical processes that …

The first-order (FO) perturbation theory-based nonlinearity compensation (PB-NLC)
technique has been widely investigated to combat the detrimental effects of the intra …

Based on a developed analytical model, we demonstrate the feasibility of intensity-
modulation direct-detection (IM/DD) optical orthogonal frequency division multiplexing …

In this survey, we analyze the newest machine learning (ML) techniques applied in modern
optical orthogonal frequency division multiplexing (O‐OFDM) systems for access, core …

The regular perturbation (RP) series used to analytically approximate the solution of the
nonlinear Schrodinger equation has a serious energy-divergence problem when truncated …