Butterfly neural equalizer applied to optical communication systems with two-dimensional digital modulation
| Autor: | Marcelo A. C. Fernandes, Tiago F. B. de Sousa |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Optical amplifier
Artificial neural network business.industry Computer science Computer Science::Neural and Evolutionary Computation Optical communication Equalizer 02 engineering and technology Perceptron Interference (wave propagation) 01 natural sciences Atomic and Molecular Physics and Optics 010309 optics Nonlinear system Noise 020210 optoelectronics & photonics Optics Polarization mode dispersion Modulation 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Electronic engineering business Quadrature amplitude modulation Communication channel |
| Zdroj: | Optics Express. 26:30837 |
| ISSN: | 1094-4087 |
| DOI: | 10.1364/oe.26.030837 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|