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Effect of beam divergence angle and waterbodies on 16 QAM signal transmission in underwater communication

  • Rajat Paliwal ORCID logo EMAIL logo , Piyush Patel and Ahmad Atieh
Published/Copyright: July 28, 2025
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Abstract

Spectrally efficient 16 QAM system for underwater communication using commercial high-power LEDs is proposed in this letter. The transmitted beam divergence (BD) angle and the effect of 10 different types of waters are investigated to enable reliable communication. The results show that a BD angle of 0.029° is needed to achieve a maximum transmission distance of 6.9 m and 4.9 m when using Osram and Luminus LEDs, respectively. The effect of transmitted data rate on distance for the optimized BD angle show that at data rate of 0.5 Gbps Osram LED supported 6.6 m link distance, which reduced to 3.7 m for the Luminus LED in pure water. The proposed system is evaluated for 10 different types of waters at fixed data rate of 0.5 Gbps while using Luminus LED. The results show that waters with lower attenuation, such as Pure Water (PW), Jerlov I, Jerlov IA, and Clear Ocean (CL), enabled longer transmission distances of 3.7 m, 3.7 m, 3.6 m, and 3.4 m, respectively. Conversely, higher attenuation in Harbor I, Jerlov III, and Harbor II waters achieved shorter distances of 2.1 m, 1.6 m, and 1.5 m, respectively. The % Error Vector Magnitude (% EVM), Symbol Error Rate (SER), and Bit Error Rate (BER) metrics are used to evaluate the proposed system performance.


Corresponding author: Rajat Paliwal, University of Mumbai, Thadomal Shahani Engineering College, Bandra (W), Mumbai, Maharashtra, 400 050, India, E-mail:

Acknowledgments

I acknowledge my guide, Dr Piyush Patel, for guiding me and Dr Ahmad Atieh for providing resources and technical support.

  1. Research ethics: I cited all the references which I have used in my paper.

  2. Informed consent: Not applicable.

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

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

  5. Conflict of interests: The authors declare no conflicts of interest regarding this article.

  6. Research funding: None declared.

  7. Data availability: Not available.

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Received: 2025-04-20
Accepted: 2025-06-19
Published Online: 2025-07-28

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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