Branch Identification in Passive Optical Networks using Machine Learning-Reference-Cited by-同舟云学术

Branch Identification in Passive Optical Networks using Machine Learning

Published:2023 Issue: Volume: Page:
ISSN:
Container-title:Optical Fiber Communication Conference (OFC) 2023
language:
Short-container-title:

Author:

Abdelli Khouloud,Tropschug Carsten,Grießer Helmut,Jansen Sander,Pachnicke Stephan

Abstract

A machine learning approach for improving monitoring in passive optical networks with almost equidistant branches is proposed and experimentally validated. It achieves a high diagnostic accuracy of 98.7% and an event localization error of 0.5m.

Publisher

Optica Publishing Group

Reference3 articles.

1. Physical Layer Monitoring Techniques for TDM-Passive Optical Networks: A Survey

2. Passive optical network monitoring: challenges and requirements

3. A Machine Learning-Based Framework for Predictive Maintenance of Semiconductor Laser for Optical Communication

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. ML approaches for OTDR diagnoses in passive optical networks—event detection and classification: ways for ODN branch assignment;Journal of Optical Communications and Networking;2024-04-12

2. Optimizing Optical Fiber Faults Detection: A Comparative Analysis of Advanced Machine Learning Approaches;Computers, Materials & Continua;2024

3. Correlation-Based OTDR for High-Resolution Monitoring in Passive Optical Networks;Optical Fiber Communication Conference (OFC) 2024;2024

4. PON Monitoring Based on Dual-FBG Periodic Encoders and Sequence Correlation;2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings (ACP/POEM);2023-11-04