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Enhancement of underwater visible light communications transmission by using optical IPS-MSK modulation

  • Salama Touré , Khadija Amadou Tidiane Ly and Leila Graini ORCID logo EMAIL logo
Published/Copyright: December 30, 2025
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Abstract

This paper introduces a novel underwater visible light optical communications (UVLC) system architecture employing optical Minimum Shift Keying modulation with independent pulse shaping (IPS-MSK). The system under consideration is configured with a non-line- of-sight (NLOS) channel, and its performance is evaluated numerically under various aquatic conditions, such as different water types (pure seawater, clear ocean, and coastal ocean), depths, link ranges and turbulence strengths, considering different data rates. The effect of transmitter optical power and receiver aperture diameter has also been investigated. The key parameters used are bit error rate (BER), quality factor (Q), eye diagram and signal to noise ratio (SNR). Results shown that, when combined with IPS-MSK modulator, UVLC system demonstrates enhanced capacity, extended transmission range, and improved performance, particularly, in clear water. At data rate up to 40 Gbps, an underwater distance of 102 m and 100 m is achieved in the pure seawater and clear ocean, respectively, with a target Q-factor of 6. Coastal water demonstrated shorter transmission distance of 1 m while maintaining similar Q-factor. The findings confirm that the proposed system could be advantageous choice for higher data rate UVLC system over long-range in clear water, and for short-range applications in turbid water.


Corresponding author: Leila Graini, Telecommunications Laboratory, Telecommunications Institute, 8 Mai 1945-Guelma University, Guelma 24000, Algeria, E-mail:

Acknowledgments

This work was supported by the Directorate General for Scientific Research and Technological Development (DG-RSDT) of Algeria.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

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Received: 2025-09-12
Accepted: 2025-12-10
Published Online: 2025-12-30

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