Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
Conferences > OFC > 2022 > W3I > W3I.2

Implementation of Machine Learning-based Emergency Communication Using RoFSO-VLC/RF Convergence link

Song Song, Xiangyu Liu, Yejun Liu, Junxian Wu, Tingwei Wu, and Lei Guo

Not Accessible

Your library or personal account may give you access

Abstract

This paper firstly experimentally demonstrates an ease of deployment integrated system to provide communication services for emergency responders, which employs machine-learning-based Radio-over-FSO system for outdoor fronthaul network and hybrid VLC/RF system for indoor access network.

© 2022 The Author(s)

PDF Article  |   Presentation Video
More Like This
Demonstration of Channel-Predictable Free Space Optical Communication System Using Machine Learning

Song Song, Yejun Liu, Tianming Xu, Shasha Liao, and Lei Guo
Th1A.36 Optical Fiber Communication Conference (OFC) 2021

Noise-Resistant Crowd Equalisation for Optical Communication Systems Based on Machine Learning

Karina Nurlybayeva, Diego Argüello Ron, Morteza Kamalian-Kopae, Elena Turitsyna, and Sergei Turitsyn
FM3D.2 Frontiers in Optics (FiO) 2022

10 Gbps Laser Communication for Low Earth Orbit Satellites with Volterra and Machine Learning Nonlinear Compensation Providing Link Budget up to 74 dB

Yi-Jun Cai, Shao-Hung Yu, Zheng-Wei Huang, Yu-Wei Wang, Pin-Hsuan Ting, Yu-Pin Lan, Chen-Joe Fang, Hsin-Chia Lin, Bor-Chwan Chen, and Chun-Ting Lin
M1C.2 Optical Fiber Communication Conference (OFC) 2022

View More...

Presentation Video

Presentation video access is available to:

  1. Optica Publishing Group subscribers
  2. Technical meeting attendees
  3. Optica members who wish to use one of their free downloads. Please download the article first. After downloading, please refresh this page.

Contact your librarian or system administrator
or
Log in to access Optica Member Subscription or free downloads

More Like This
Demonstration of Channel-Predictable Free Space Optical Communication System Using Machine Learning

Song Song, Yejun Liu, Tianming Xu, Shasha Liao, and Lei Guo
Th1A.36 Optical Fiber Communication Conference (OFC) 2021

Noise-Resistant Crowd Equalisation for Optical Communication Systems Based on Machine Learning

Karina Nurlybayeva, Diego Argüello Ron, Morteza Kamalian-Kopae, Elena Turitsyna, and Sergei Turitsyn
FM3D.2 Frontiers in Optics (FiO) 2022

10 Gbps Laser Communication for Low Earth Orbit Satellites with Volterra and Machine Learning Nonlinear Compensation Providing Link Budget up to 74 dB

Yi-Jun Cai, Shao-Hung Yu, Zheng-Wei Huang, Yu-Wei Wang, Pin-Hsuan Ting, Yu-Pin Lan, Chen-Joe Fang, Hsin-Chia Lin, Bor-Chwan Chen, and Chun-Ting Lin
M1C.2 Optical Fiber Communication Conference (OFC) 2022

View More...
Machine Learning-Based Underwater Communication System Using Light Carrying Orbital Angular Momentum

William A. Jarrett, Svetlana Avramov-Zamurovic, Joel M. Esposito, and Charles Nelson
JW3B.108 CLEO: Applications and Technology (CLEO:A&T) 2022

An Indoor Visible Light Communication and Positioning System Based on Machine Learning and Alamouti STBC

Shencheng Ni, Feng Wang, Shuying Han, Xiang Li, Wu Liu, Cai Li, and Shanhong You
SW4L.1 CLEO: Science and Innovations (CLEO:S&I) 2020

Select as filters
Select Topics Cancel
Top
       
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.
Privacy | Terms of Use