Harnessing machine learning for fiber-induced nonlinearity mitigation in long-haul coherent optical OFDM
Coherent optical orthogonal frequency division multiplexing (CO-OFDM) has attracted a lot
of interest in optical fiber communications due to its simplified digital signal processing …
of interest in optical fiber communications due to its simplified digital signal processing …
A survey on machine learning for optical communication [machine learning view]
MA Amirabadi - arXiv preprint arXiv:1909.05148, 2019 - arxiv.org
Machine Learning (ML) for Optical Communication (OC) is certainly a hot topic emerged
recently and will continue to raise interest at least for the next few years. The rate of research …
recently and will continue to raise interest at least for the next few years. The rate of research …
Reduction of nonlinear intersubcarrier intermixing in coherent optical OFDM by a fast newton-based support vector machine nonlinear equalizer
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 …
experimentally demonstrated, for the first time, in 40 Gb/s 16-quadrature amplitude …
[HTML][HTML] Mitigation of nonlinearities in analog radio over fiber links using machine learning approach
MU Hadi - ICT Express, 2021 - Elsevier
Abstract Machine learning (ML) techniques are looked upon as an innovative and realistic
direction to cope up with nonlinearity issues in fiber optics communication. In this paper, a …
direction to cope up with nonlinearity issues in fiber optics communication. In this paper, a …
QAM classification methods by SVM machine learning for improved optical interconnection
High-order quadrature amplitude modulation (QAM) formats are very effective for increasing
the transmission capacity due to the highly increased spectral efficiency. However, the …
the transmission capacity due to the highly increased spectral efficiency. However, the …
A blind nonlinearity compensator using DBSCAN clustering for coherent optical transmission systems
Coherent fiber-optic communication systems are limited by the Kerr-induced nonlinearity.
Benchmark optical and digital nonlinearity compensation techniques are typically complex …
Benchmark optical and digital nonlinearity compensation techniques are typically complex …
The modulation classification methods in PPM–VLC systems
TT Ağır, M Sönmez - Optical and Quantum Electronics, 2023 - Springer
Intelligent methods have been applied to many fields for a long time. Recently, Visible Light
Communication (VLC) systems widely include learning and classification models to improve …
Communication (VLC) systems widely include learning and classification models to improve …
A novel support vector machine robust model based electrical equaliser for coherent optical orthogonal frequency division multiplexing systems
Classifiers, such as artificial neural networks non‐linear equaliser (ANN‐NLE), Wiener–
Hammerstein non‐linear equaliser, Volterra non‐linear equaliser (Volterra‐NLE) and …
Hammerstein non‐linear equaliser, Volterra non‐linear equaliser (Volterra‐NLE) and …
A Survey on Machine and Deep Learning for Optical Communications
MA Amirabadi, SA Nezamalhosseini… - arXiv preprint arXiv …, 2024 - arxiv.org
The ever-growing complexity of optical communication systems and networks demands
sophisticated methodologies to extract meaningful insights from vast amounts of …
sophisticated methodologies to extract meaningful insights from vast amounts of …
Extensive simulation of fibre non‐linearity mitigation in a CO‐OFDM‐WDM long‐haul communication system
In this study, a performance comparison of fibre non‐linearity mitigation is performed in the
context of 10 and 20 Gb/s coherent optical orthogonal frequency‐division multiplexing and …
context of 10 and 20 Gb/s coherent optical orthogonal frequency‐division multiplexing and …