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Ultra-wideband amplification utilizing O-shape hybrid fiber amplifier

  • Thamer Fahad Al-Mashhadani ORCID logo EMAIL logo , Mohammed Kamil Salh Al-Mashhadani ORCID logo , Ali Yaseen Ali , Mohammed K. Awsaj , Hayder G. Fahad , Mudhafar Hussein Ali and Norhana Arsad
Published/Copyright: December 16, 2025
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Abstract

An ultra-wideband amplification utilizing a proposed O shape-hybrid fiber amplifier (OS-HFA) is experimentally demonstrated. Raman fiber amplifier (RFA) is combined with erbium doped fiber amplifier (EDFA) within a simple design. Low power of 50 mW with standard 1,480 nm pump unit that achieves gain in conventional (C)-band is used with EDFA while 750 and 500 mW of pump power units of 1,410 and 1,495 nm, respectively, are used for RFA. These two pump unit wavelengths are used to achieve peak gain at S and L band regions. A 103 nm flatness gain bandwidth from 1,515 to 1,618 nm and average gain of 27 dB is obtained at −30 dBm input power. While wider flatness gain bandwidth of 107 nm from 1,515 to 1,622 nm and an average gain of 17 dB are achieved at large input signal of −5 dBm.


Corresponding author: Thamer Fahad Al-Mashhadani, Department of Electrical Engineering Techniques, College of Technical Engineering, University of Kut, Wasit, 52001, Iraq, E-mail:

Funding source: Daw Alfada Company, Baghdad, Iraq

Acknowledgments

This work was conducted with the support of the Daw Alfada Company, Baghdad, Iraq.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: Thamer Fahad Al-Mashhadani: Conceptualization, Methodology, Experimental work. Mohammed Kamil Salh Al-Mashhadani: Experimental work, Data curation, analysis, Writing – original draft. Mudhafar Hussein Ali: Investigation, Resources, Validation. Ali Yaseen Ali: Software, Visualization, Writing – review & editing. Mohammed K. Awsaj: Data collection, Experimental work. Hayder G. Fahad: Data curation, Statistical analysis. Norhana Arsad Visualization, Writing – review & editing. 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: None declared.

  7. Data availability: Not applicable.

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Received: 2025-10-24
Accepted: 2025-11-26
Published Online: 2025-12-16

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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