Design and performance evaluation of a hybrid FSO-FTTx communication link utilizing UD-WDMA 1.28 Tbps data rates transmission under various weather conditions
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Ashenafi Paulos Forsido
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Ram Sewak Singh
Abstract
The rapid growth of high-data-rate applications necessitates the development of new communication frameworks since bandwidth constraints for data-intensive applications hinder traditional networks and conventional microwave/radio frequency (RF) communications. This study explores a hybrid communication link that combines fiber-to-the-x (FTTx) and free-space optical (FSO) technologies, utilizing ultra-dense wavelength-division multiple access (UD-WDMA) with a channel spacing of 0.2 nm/25 GHz, under various weather conditions. Based on bit error rate (BER), optical signal-to-noise ratio (OSNR), and quality factor (QF), the performance of the suggested FSO-FTTx system was examined. The system performed well in diverse weather conditions, achieving a minimum BER of ≤10−5, QF values of 4 or higher, and OSNR levels between 10 and 20 dB. The proposed system successfully transmitted a data rate of 1.28 Tbps over 35 km in single-mode fiber (SMF), accommodating different FSO link ranges despite varying weather conditions. However, performance fluctuations were observed under adverse conditions, with attenuation ranging from 0.91 dB/km in extremely light mist to 273.39 dB/km in dense fog, impacting the FSO link range. The findings underscore the proposed hybrid system’s potential to enhance optical wireless communication for high data rates, making it promising for beyond 5G and early 6G applications.
Acknowledgments
The authors would like to acknowledge Adama Science and Technology University for creating good environment for research work.
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Research ethics: In writing this manuscript, the authors follows to the ethics of research.
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Informed consent: Not applicable.
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Author contributions: Each author has made significant contributions to the research and manuscript preparation.
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Use of Large Language Models, AI and Machine Learning Tools: The authors declare that we have not use of Large Language Models, AI and Machine Learning Tools to write this manuscript.
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Conflict of interest: We have no conflicts of interest to disclose. Therefore, the authors declare no conflicts of interest related to this study.
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Research funding: There is no any research fund in this study.
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Data availability: The data supporting the findings of this study are available from the corresponding author upon reasonable request.
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