Startseite Performance analysis of a hybrid DWDM-FSO system for 6G
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Performance analysis of a hybrid DWDM-FSO system for 6G

  • Hanane Djellab EMAIL logo , Oumaima Allaoua ORCID logo , Fouzia Mammri , Saidi Riad , Farouk Boumehrez und Abdelhakim Sahour
Veröffentlicht/Copyright: 1. Januar 2025
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Abstract

The increasing demand for higher bandwidth and reliable communication networks driven by next-generation mobile technologies (5G/6G) and the Internet of Things (IoT) poses challenges for existing communication infrastructures. Free Space Optics (FSO) offers high-speed wireless data transmission comparable to fiber optics but suffers from significant performance degradation due to environmental factors such as rain, fog, and atmospheric turbulence. This study investigates the potential of a hybrid Dense Wavelength Division Multiplexing (DWDM)-FSO system to overcome these challenges. By combining DWDM’s high capacity with the flexibility of FSO links, the system achieves a data rate of 5.4 Tbps across 90 users. Simulations conducted using OptiSystem software evaluate the impact of different weather conditions – clear skies, heavy rain, and dense fog – on performance. Key metrics, including bit error rate (BER), quality factor (Q-factor), and eye diagrams, are analyzed to assess signal integrity and reliability. A comparative study of Single Input Single Output (SISO) and MIMO configurations (2 × 2 and 3 × 3) shows that the 3 × 3 MIMO-FSO setup significantly enhances performance, maintaining signal quality and extending range under adverse weather. These findings highlight the hybrid DWDM-FSO system’s potential to deliver high-speed, resilient communication, ensuring seamless connectivity in dynamic environments.


Corresponding author: Hanane Djellab, Department of Electrical Engineering, LTI Laboratory of Guelma, Laboratory of Signals and Smart Systems, Echahid Larbi Tebessi University, Tebessa, Algeria, E-mail:

Acknowledgments

The authors are grateful to the anonymous referees for their valuable and helpful comments. The authors thank the staff of LAMIS laboratory for helpful comments and suggestions.

  1. Research ethics: This study adheres to ethical guidelines, ensuring informed consent from all participants and the responsible use of AI and machine learning tools. All research was conducted in compliance with relevant legal and ethical standards.

  2. Informed consent: Not applicable.

  3. Author contributions: Oumaima Allaoua: original draft preparation. Hanene Djellab: paper revision and validation. Fouzia Mammri: reviewing and editing. Saidi Riad: software. Abdelhakim Sahour: methodology. Farouk Boumehrez: conceptualization.

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

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

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Received: 2024-10-15
Accepted: 2024-12-11
Published Online: 2025-01-01

© 2024 Walter de Gruyter GmbH, Berlin/Boston

Heruntergeladen am 19.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/joc-2024-0259/html
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