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Article

High-Speed Underwater Optical Wireless Communication with Advanced Signal Processing Methods Survey

1
School of Engineering, Royal Melbourne Institute of Technology (RMIT) University, Melbourne, VIC 3000, Australia
2
School of Architecture and Urban Design, Royal Melbourne Institute of Technology (RMIT) University, Melbourne, VIC 3000, Australia
*
Author to whom correspondence should be addressed.
Photonics 2023, 10(7), 811; https://doi.org/10.3390/photonics10070811
Submission received: 31 May 2023 / Revised: 4 July 2023 / Accepted: 10 July 2023 / Published: 12 July 2023
(This article belongs to the Special Issue Advances in Visible Light Communication)

Abstract

Underwater wireless communication (UWC) technology has attracted widespread attention in the past few years. Compared with conventional acoustic underwater wireless communication technology, underwater optical wireless communication (UOWC) technology has promising potential to provide high data rate wireless connections due to the large license-free bandwidth. Building a high-performance and reliable UOWC system has become the target of researchers and various advanced and innovative technologies have been proposed and investigated. Among them, better hardware such as transmitters and receivers, as well as more advanced modulation and signal processing techniques, are key factors in improving UOWC system performance. In this paper, we review the recent development in UOWC systems. In particular, we provide a brief introduction to different types of UOWC systems based on channel configuration, and we focus on various recent studies on advanced signal processing methods in UOWC systems, including both traditional non-machine learning (NML) equalizers and machine learning (ML) schemes based on neural networks. In addition, we also discuss the key challenges in UOWC systems for future applications.
Keywords: underwater optical wireless communication (UOWC); digital signal; linear equalizer; nonlinear equalizer; supervised machine learning; reinforcement machine learning underwater optical wireless communication (UOWC); digital signal; linear equalizer; nonlinear equalizer; supervised machine learning; reinforcement machine learning

Share and Cite

MDPI and ACS Style

Fang, C.; Li, S.; Wang, Y.; Wang, K. High-Speed Underwater Optical Wireless Communication with Advanced Signal Processing Methods Survey. Photonics 2023, 10, 811. https://doi.org/10.3390/photonics10070811

AMA Style

Fang C, Li S, Wang Y, Wang K. High-Speed Underwater Optical Wireless Communication with Advanced Signal Processing Methods Survey. Photonics. 2023; 10(7):811. https://doi.org/10.3390/photonics10070811

Chicago/Turabian Style

Fang, Chengwei, Shuo Li, Yinong Wang, and Ke Wang. 2023. "High-Speed Underwater Optical Wireless Communication with Advanced Signal Processing Methods Survey" Photonics 10, no. 7: 811. https://doi.org/10.3390/photonics10070811

APA Style

Fang, C., Li, S., Wang, Y., & Wang, K. (2023). High-Speed Underwater Optical Wireless Communication with Advanced Signal Processing Methods Survey. Photonics, 10(7), 811. https://doi.org/10.3390/photonics10070811

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