Water-to-Air PAM4 Optical Camera Communication Using Long Short Term Memory Neural Network (LSTM-NN)

Yun Han Chang, Shang Yen Tsai, Ming Chieh Tsai, Jia Fu Li, Yin He Jian, Chi Wai Chow*, Chien Hung Yeh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

We demonstrate a wide field-of-view (FOV) water-to-air transmission using rolling-shutter-based optical-camera-communication (OCC). Long-short-term-memory-neural-network (LSTM-NN) is utilized to mitigate the wavy water-surface induced link outage and to decode 4-level pulse-amplitude-modulation (PAM4) rolling-shutter pattern.

Original languageEnglish
Title of host publication2024 Optical Fiber Communications Conference and Exhibition, OFC 2024 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781957171326
StatePublished - 2024
Event2024 Optical Fiber Communications Conference and Exhibition, OFC 2024 - San Diego, United States
Duration: 24 Mar 202428 Mar 2024

Publication series

Name2024 Optical Fiber Communications Conference and Exhibition, OFC 2024 - Proceedings

Conference

Conference2024 Optical Fiber Communications Conference and Exhibition, OFC 2024
Country/TerritoryUnited States
CitySan Diego
Period24/03/2428/03/24

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