Author(s)

ZhenHan Xu, Lei Guo, XiangYu Liu^*

Affiliation(s)

School of Information Science and Engineering, Shenyang Ligong University, Shenyang 110159, Liaoning, China.

Corresponding Author

XiangYu Liu

ABSTRACT

With the increasing demand for marine development and intelligent monitoring, underwater information transmission technologies characterized by high bandwidth, low latency, and strong anti-interference capabilities are becoming increasingly important. Underwater visible light communication (UVLC), with its advantages of high bandwidth, strong directionality, low power consumption, and absence of electromagnetic interference, is considered a highly promising underwater communication method. However, it still faces many challenges in real marine environments, such as signal absorption and scattering, fluctuations caused by turbulence and particle disturbances, and link mismatch due to environmental changes. Therefore, achieving intelligent communication and monitoring early warning in complex and dynamic waters has become a key issue. This paper, targeting dynamic underwater monitoring environments prone to link degradation, designs and implements an integrated intelligent underwater visible light communication monitoring system and path selection scheme. The core innovation lies in introducing chaotic systems and multi-physics coupling into channel modeling and path optimization, significantly improving the system's robustness and adaptability under multi-disturbance monitoring conditions, and enhancing path reliability in harsh environments. Experimental results demonstrate that the proposed monitoring channel model exhibits significantly superior performance to traditional models in predicting power attenuation and pulse broadening. Under the condition of a specific bit error rate (BER), the system can stably maintain a high link switching success rate with the aid of the chaotic optimization mechanism, while keeping the response time below the set threshold. This fully verifies that the system possesses excellent reliability and stability in complex underwater monitoring environments.

KEYWORDS

Chaotic systems; Multiphysics coupling; Channel modeling; Path selection

CITE THIS PAPER

ZhenHan Xu, Lei Guo, XiangYu Liu. Underwater visible light communication and path selection algorithm design. Journal of Computer Science and Electrical Engineering. 2026, 8(1): 18-24. DOI: https://doi.org/10.61784/jcsee3113.

REFERENCES

[1] Zhang Y, Tan S, Li X, et al. Marine ecological environment monitoring and management system based on sensor technology. 2024 International Conference on Integrated Circuits and Communication Systems (ICICACS), Raichur, India. 2024, 1-6. DOI: 10.1109/ICICACS60521.2024.10498570.

[2] Jayaweera V L, Peiris C, Darshani D, et al. Visible Light Communication for Underwater Applications: Principles, Challenges, and Future Prospects. Photonics, 2025, 12(6): 593.

[3] Singh D P, Batham D. A review of underwater communication systems. International Journal of Engineering Development and Research, 2022, 10(2): 100-104.

[4] Al-Tameemi H M, Idris A, Sarnin S S, et al. Underwater acoustic communication systems: An overview. AIP Conference Proceedings. AIP Publishing LLC, 2023, 2977(1): 020008.

[5] Zhilin I V, Bushnaq O M, De Masi G, et al. A universal multimode (acoustic, magnetic induction, optical, RF) software defined radio architecture for underwater communication. IEEE Transactions on Wireless Communications, 2021, 22(12): 9105-9116. DOI: 10.1109/TWC.2023.3268418.

[6] Zhang L, Liu X, Wu S. Intelligent Architecture for Multi-Domain Aerial-Surface-Underwater Networks with Hybrid Radio-Acoustic-Optical Communications. 2024 IEEE Smart World Congress (SWC)Nadi, Fiji. 2024, 503-510. DOI: 10.1109/SWC62898.2024.00100.

[7] Rehman A U, Galluccio L, Morabito G. AI-Driven Adaptive Communications for Energy-Efficient Underwater Acoustic Sensor Networks. Sensors, 2025, 25(12): 3729.

[8] Luo X, Yang L, Alexandropoulos G C, et al. Performance Analysis of Underwater RSMA-Assisted Covert Wireless Communications. IEEE Transactions on Communications, 2025, 73(12): 13863-13875. DOI: 10.1109/TCOMM.2025.3618170.

[9] Gonchenko S, Kazakov A, Turaev D, et al. Leonid Shilnikov and mathematical theory of dynamical chaos. Chaos: An Interdisciplinary Journal of Nonlinear Science, 2022, 32(1).

[10] Zheng C, Sun K, Gu Y, et al. Multimodal transport path selection of cold chain logistics based on improved particle swarm optimization algorithm. Journal of advanced transportation, 2022, 2022(1): 5458760.