Performance analysis of underwater optical wireless communication system under clear oceanic environment
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Dip Sarkar
und
Bobby Barua
Abstract
Underwater wireless communication is the use of wireless carriers, such as radio-frequency waves, acoustic waves, and optical waves, to transmit data in an unguided aquatic environment. This study focuses on underwater optical wireless communication (UOWC), leveraging the high bandwidth of optical waves for enhanced data rates. While orthogonal frequency division multiplexing (OFDM) and space-time block coding (STBC) are well-established in radio frequency (RF) and free-space optical systems, their application in UOWC introduces unique challenges due to underwater attenuation, scattering, and multipath effects. UOWC holds significant potential in military, offshore exploration, environmental monitoring, and disaster response, yet is constrained by severe absorption and scattering in underwater channels. This work examines coding, modulation, and channel characteristics in UOWC systems. It analyzes outage performance in terms of bandwidth, bit error rate (BER), and carrier-to-noise ratio (CNR) to optimize communication links. Power penalties over varying distances are examined, showing increasing degradation with longer transmission ranges. From the analysis it is found that at a short distance of 10 m, power penalties range from approximately 11–16 dB for received optical power levels between 10−2 and 10−12. At 120 m, the power penalty increases to 28–31 dB with corresponding BER values from 10−2 to 10−12. These findings underscore the need for advanced signal processing and adaptive modulation to minimize power loss and enhance UOWC system efficiency in practical scenarios.
Acknowledgments
We would like to express our sincere gratitude to Department of Electrical and Electronics Engineering of Ahsanullah University of Science and Technology for providing the necessary resources and a conducive environment for this research.
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Research ethics: This research paper has been implemented by myself with taking my supervisor’s support and instruction.
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Author contributions: The study has been conceived by myself and my supervisor. I have developed the theoretical framework and performed the experiments and also analyzed of the systems. Then, my supervisor supervised the project. The results and contributed to the final manuscript have been discussed by myself and my supervisor.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interests: There is no conflict of interest.
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Research funding: There is no funding.
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Data availability: This research has been implemented by simulation work. All kinds of data has been taken from implementation and simulation. For some important information which have been taken from other research paper, references have been used.
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