Analysis of underwater communication systems based on hybrid Li-Fi technology
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Main Article Content
Authors
a.urazgaliyeva@satbayev.university
Abstract
When humanity reaches a new phase in exploring the ocean floor, one of the most persistent technical challenges will still be maintaining dependable communication beneath the surface. The underwater environment introduces obstacles such as delayed signal transmission, fluctuating water conditions, significant signal loss, and the limited effectiveness of traditional communication methods. To address these issues, this work proposes a combined system that integrates both optical and acoustic channels, leveraging the strengths of each: the extensive range typical of acoustic links, and the fast, low-latency performance made possible by Li-Fi technology. The study compares existing approaches – acoustic, optical, and electromagnetic – with attention to the physical constraints imposed by the marine environment, including energy absorption, light scattering, refraction effects, and multipath propagation. It also considers the role of adaptive, intelligent signal-processing methods designed to maintain link stability as conditions change. From an engineering perspective, the discussion extends to laser wavelength choice, photodetector tuning, and the design of a network framework capable of enabling real-time data exchange between autonomous underwater vehicles and surface-level monitoring systems. The results suggest the potential for building a high-speed, large-scale underwater communication network with substantial capacity. This advancement could significantly accelerate deep-sea research, representing a major step forward in the evolution of marine communications.
Keywords:
Sustainable Development Goals (SDG)
- 9 - Industry, Innovation, Technology and Infrastructure
- 11 - Sustainable cities and communities
- 14 - Life below water
References
[1] Abdykadyrov, A., Smailov, N., Sabibolda, A., Tolen, G., Dosbayev, Z., Ualiyev, Z., & Kadyrova, R. (2024). Optimization of distributed acoustic sensors based on fiber optic technologies. Eastern-European Journal of Enterprise Technologies, 5(5 (131)), 50–59. https://doi.org/10.15587/1729-4061.2024.313455
[2] Abdykadyrov, A., Yerishova, M., Kuttybayeva, A., Yermekbayev, M., & Amanzholov, A. (2025). Mechanisms of signal loss and reflection in optical fibers and their impact on radio direction finding efficiency in bent cable routes. International Journal of Innovative Research and Scientific Studies, 8(3), 5056–5069. https://doi.org/10.53894/ijirss.v8i3.7706
[3] Ahmed, M., Alam, Md. M., & Arefin, M. S. (2023). An Experimental Study to Operate Underwater Vehicle Using Li-Fi: Advantages and Challenges. 2023 1st International Conference on Circuits, Power and Intelligent Systems (CCPIS), 1–4. https://doi.org/10.1109/CCPIS59145.2023.10291476
[4] Ali, A. A., Kumar, R. H., R. Dheenathalayan, N. Prasanth, V. Parthasaradi, S. Senthilkumar, & Kumar, T. S. (2023). Audio Streaming Using Li-FI Communication. Irish Interdisciplinary Journal of Science & Research, 07(01), 01–07. https://doi.org/10.46759/IIJSR.2023.7101
[5] Ali, M. F., Jayakody, D. N. K., & Li, Y. (2022). Recent Trends in Underwater Visible Light Communication (UVLC) Systems. IEEE Access, 10, 22169–22225. https://doi.org/10.1109/ACCESS.2022.3150093
[6] Al-Zhrani, S., Bedaiwi, N. M., El-Ramli, I. F., Barasheed, A. Z., Abduldaiem, A., Al-Hadeethi, Y., & Umar, A. (2021). Underwater Optical Communications: A Brief Overview and Recent Developments. Engineered Science, 16, 146–186. https://doi.org/10.30919/es8d574
[7] Apoorva, N., Pragati, R. M., Impana, B., Anusha, K., & Siddalingappagouda, B. (2024). Underwater audio and data transmission system using Li-Fi technology. International Research Journal of Modernization in Engineering Technology and Science, 6(5), 5713–5722. https://doi.org/10.56726/IRJMETS57039
[8] Campagnaro, F., Favaro, F., Casari, P., & Zorzi, M. (2014). On the feasibility of fully wireless remote control for underwater vehicles. 2014 48th Asilomar Conference on Signals, Systems and Computers, 33–38. https://doi.org/10.1109/ACSSC.2014.7094391
[9] Chen, Y., Zhang, L., & Ling, Y. (2022). New approach for designing an underwater free-space optical communication system. Frontiers in Marine Science, 9, 971559. https://doi.org/10.3389/fmars.2022.971559
[10] Codd-Downey, R., & Jenkin, M. (2018). Wireless Teleoperation of an Underwater Robot using Li-Fi. 2018 IEEE International Conference on Information and Automation (ICIA), 859–864. https://doi.org/10.1109/ICInfA.2018.8812544
[11] He, J., Li, J., Zhu, X., Xiong, S., & Chen, F. (2022). Design and Analysis of an Optical–Acoustic Cooperative Communication System for an Underwater Remote-Operated Vehicle. Applied Sciences, 12(11), 5533. https://doi.org/10.3390/app12115533
[12] Intaniawati, L. S. J., Pantjawati, A. B., Saripudin, A., & Nurhidayatulloh. (2022). Underwater Wireless Optical Communication Using Li-Fi Technology In Data Transmission. 2022 5th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), 430–433. https://doi.org/10.1109/ISRITI56927.2022.10053033
[13] Jayaweera, V. L., Peiris, C., Darshani, D., Edirisinghe, S., Dharmaweera, N., & Wijewardhana, U. (2025). Visible Light Communication for Underwater Applications: Principles, Challenges, and Future Prospects. Photonics, 12(6), 593. https://doi.org/10.3390/photonics12060593
[14] Johnson, L. J., Green, R. J., & Leeson, M. S. (2013). Underwater optical wireless communications: Depth dependent variations in attenuation. Applied Optics, 52(33), 7867. https://doi.org/10.1364/AO.52.007867
[15] Kaushal, H., & Kaddoum, G. (2016). Underwater Optical Wireless Communication. IEEE Access, 4, 1518–1547. https://doi.org/10.1109/ACCESS.2016.2552538
[16] Kiesewetter, D., Krivosheev, S., Magazinov, S., Malyugin, V., Koshkinbayev, S., & Smailov, N. (2022). Measurement of High-Speed Deformations Using Fiber Bragg Gratings. 2022 International Conference on Electrical Engineering and Photonics (EExPolytech), 324–327. https://doi.org/10.1109/EExPolytech56308.2022.9950795
[17] Kuttybayeva, A., Sabibolda, A., Kengesbayeva, S., Baigulbayeva, M., Amir, A., & Sekenov, B. (2024). Investigation of a Fiber Optic Laser Sensor with Grating Resonator Using Mirrors. 2024 Conference of Young Researchers in Electrical and Electronic Engineering (ElCon), 709–711. https://doi.org/10.1109/ElCon61730.2024.10468264
[18] Oubei, H. M., Shen, C., Kammoun, A., Zedini, E., Park, K.-H., Sun, X., Liu, G., Kang, C. H., Ng, T. K., Alouini, M.-S., & Ooi, B. S. (2018). Light based underwater wireless communications. Japanese Journal of Applied Physics, 57(8S2), 08PA06. https://doi.org/10.7567/JJAP.57.08PA06
[19] Pal, A., Campagnaro, F., Ashraf, K., Rahman, M. R., Ashok, A., & Guo, H. (2023). Communication for Underwater Sensor Networks: A Comprehensive Summary. ACM Transactions on Sensor Networks, 19(1), 1–44. https://doi.org/10.1145/3546827
[20] Qu, Z., & Lai, M. (2024). A Review on Electromagnetic, Acoustic, and New Emerging Technologies for Submarine Communication. IEEE Access, 12, 12110–12125. https://doi.org/10.1109/ACCESS.2024.3353623
[21] Rajan, S., C, Nagaraj., B.S, V. Murthy., Srivastava, A., M R, V., & Karadi, D. S. (2024). Development of Underwater Communication System Using Li-Fi Technology. 2024 5th International Conference on Circuits, Control, Communication and Computing (I4C), 509–514. https://doi.org/10.1109/I4C62240.2024.10748501
[22] Saeed, N., Celik, A., Al-Naffouri, T. Y., & Alouini, M.-S. (2019). Underwater optical wireless communications, networking, and localization: A survey. Ad Hoc Networks, 94, 101935. https://doi.org/10.1016/j.adhoc.2019.101935
[23] Smailov, N., Koshkinbayev, S., Yssyraiyl, K., Kuttybayeva, A., Yussupova, G., Batyrgaliyev, A., & Sabibolda, A. (2026). Fiber Bragg Grating-Based Deformation Monitoring in Space Infrastructure: A Comprehensive Review. Journal of Sensor and Actuator Networks, 15(3), 38. https://doi.org/10.3390/jsan15030038
[24] Smailov, N., Tsyporenko, V., Ualiyev, Z., Issova, А., Dosbayev, Z., Tashtay, Y., Zhekambayeva, M., Alimbekov, T., Kadyrova, R., & Sabibolda, A. (2025). Improving accuracy of the spectral-correlation direction finding and delay estimation using machine learning. Eastern-European Journal of Enterprise Technologies, 2(5 (134)), 15–24. https://doi.org/10.15587/1729-4061.2025.327021
[25] Smailov, N., Zhadiger, T., Tashtay, Y., Abdykadyrov, A., & Amir, A. (2024). Fiber laser-based two-wavelength sensors for detecting temperature and strain on concrete structures. International Journal of Innovative Research and Scientific Studies, 7(4), 1693–1710. https://doi.org/10.53894/ijirss.v7i4.3481
[26] Taissariyeva, K., Abdykadyrov, A., Mussilimov, K., Jobalayeva, G., & Marxuly, S. (2025). Analysis and Modeling of Environmental Monitoring Using Multicopters. International Journal of Innovative Research and Scientific Studies, 8(3), 2947–2960. https://doi.org/10.53894/ijirss.v8i3.7119
[27] Zeng, Z., Fu, S., Zhang, H., Dong, Y., & Cheng, J. (2017). A Survey of Underwater Optical Wireless Communications. IEEE Communications Surveys & Tutorials, 19(1), 204–238. https://doi.org/10.1109/COMST.2016.2618841
[28] Zhang, H., Liu, L., Yang, C., Yang, Z., Wang, Q., Yao, B., Zhang, Z., Wang, X., Shi, X., Liu, D., & Xue, C. (2023). Cooperative Control of Multiple Underwater Robots Based on Brief Binary Optical-Acoustic Dual Signals. IEEE Access, 11, 136924–136933. https://doi.org/10.1109/ACCESS.2023.3338630
[29] Zhu, S., Chen, X., Liu, X., Zhang, G., & Tian, P. (2020). Recent progress in and perspectives of underwater wireless optical communication. Progress in Quantum Electronics, 73, 100274. https://doi.org/10.1016/j.pquantelec.2020.100274
[30] Zilgarayeva, A., Smailov, N., Pavlov, S., Mirzakulova, S., Alimova, M., Kulambayev, B., & Nurpeissova, D. (2024). Optical sensor to improve the accuracy of non-invasive blood sugar monitoring. Indonesian Journal of Electrical Engineering and Computer Science, 34(3), 1489. https://doi.org/10.11591/ijeecs.v34.i3.pp1489-1498
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