Enhancing Performance and Quality of Transmission Through Knowledge-Driven Machine Learning-Based FWM Mitigation

Enhancing Performance and Quality of Transmission Through Knowledge-Driven Machine Learning-Based FWM Mitigation

This article proposes a knowledge-driven four-wave mixing (FWM) mitigation using supervised learning approaches and a multilevel regression-based dense wavelength division multiplexing (SMR-DWDM) system design. The evolution of 5G and the Internet of Things (IoT) results in an immense data rate cons...

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Bibliographic Details
Main Authors: Sudha Sakthivel, Muhammad Mansoor Alam, Aznida Abu Bakar Sajak, Mazliham Mohd Su'ud, Mohammad Riyaz Belgaum
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
FWM
machine learning
knowledge-driven DWDM
multilevel regression
quality of transmission
Online Access:https://ieeexplore.ieee.org/document/10776958/
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