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High speed optical modulation fiber systems for ultra high spectral efficiency improvement through the digital shift keying techniques employment

  • Ramachandran Thandaiah Prabu EMAIL logo , Govindanaidu Damodaran Vignesh , Manimaraboopathy Maruthu Pandian , Arulanantham Dhandapani , Ata Kishore Kumar , Binu Sukumar and Yossif Khaled Ali EMAIL logo
Published/Copyright: April 14, 2025
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Abstract

This paper simulates the high speed optical modulation fiber systems for ultra high spectral efficiency improvement through the digital shift keying techniques employment. The electrooptic modulators are used with compensated fiber communication system. The optical fiber system is composed of three hybrid fibers that are namely single mode/highly nonlinear/dispersion shifted fibers. The Raman amplification system is demonstrated with 10 km dispersion compensated fiber (DCF) for ultra high speed long distance transmission can be achieved up to 450 km. The digital shift keying techniques are used through this work that are namely ASK (amplitude shift keying), PSK (phase shift keying) and FSK (frequency shift keying). The signal per noise ratio/BER and optical/electrical power are measured to detect the high system spectral efficiency. The distributed bidirectional Raman amplification is used for the efficient power transferred through the optical fiber system. The hybrid fiber system with distributed Raman amplification have achieved the optimum optical modulated fiber systems.


Corresponding authors: Ramachandran Thandaiah Prabu, Department of ECE, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, SIMATS, Saveetha University, Chennai, Tamilnadu, India, E-mail: ; and Yossif Khaled Ali, Alexabdria Academy of Science Technology, Alexandria, Egypt, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  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: Not applicable.

  7. Data availability: Not applicable.

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Received: 2025-02-20
Accepted: 2025-03-22
Published Online: 2025-04-14

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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