Open AccessButterfly neural equalizer applied to optical communication systems with two-dimensional digital modulation
Author(s) -
Tiago Sousa,
Marcelo A. C. Fernandes
Publication year - 2018
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.26.030837
Subject(s) - computer science , modulation (music) , artificial neural network , nonlinear system , interference (communication) , butterfly , multilayer perceptron , noise (video) , perceptron , optical communication , channel (broadcasting) , electronic engineering , optics , telecommunications , artificial intelligence , acoustics , physics , engineering , finance , quantum mechanics , economics , image (mathematics)
This article aims to present, analyze and evaluate a new equalizer architecture, inspired by the butterfly equalizer used in optical communication, based on Artificial Neural Networks (ANN) of the Multi-Layer Perceptron (MLP) type for nonlinear systems with two-dimensional modulation named the Butterfly Neural Equalizer (NE-Butterfly). The NE-Butterfly is intended to equalize any channel that has real or complex taps, whether linear or nonlinear. Simulation results are presented for different types of nonlinear fiber optic channels with complex and real taps, also containing inter symbolic interference and additive noise. The results are compared with other neural equalizers in the literature with the objective of validating the performance of the NE-Butterfly, which stands out as having the overall best performance against the ones it was compared to.