High bandwidth performance of multimode graded-index microstructured polymer optical fibers
Savović S. Simović A. Drljača B. Kovačević M.S. Kuzmanović L. Ivanović M. Djordjevich A. Aidinis K. Tosi D. Min R.
July 2023Elsevier B.V.
Results in Physics
2023#50
The investigation of the bandwidth in multimode graded-index microstructured polymer optical fiber (GI mPOF) with a solid core is proposed using a modal diffusion approach. For a variety of launch radial offsets of multimode GI mPOF, bandwidth is reported by numerically solving the time-dependent power flow equation (TD PFE) using the explicit finite difference method (EFDM) and physics-informed neural networks (PINN). The decline in bandwidth with fiber length becomes slower at fiber lengths close to the coupling length Lc at which an equilibrium mode distribution (EMD) is attained, showing that mode coupling enhances bandwidth at longer fiber lengths. As fiber length is increased, bandwidth approaches complete independence from radial offset, suggesting the steady-state distribution (SSD) has been reached. We compare multimode GI mPOF performance in terms of bandwidth with that of traditional multimode GI POFs made of the same material. Higher bandwidth performance and quicker bandwidth improvement are displayed by the GI mPOF. To enhance fiber performance in GI mPOF links, such a fiber characterization can be used.
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Faculty of Science, University of Kragujevac, R. Domanovića 12, Kragujevac, 34000, Serbia
Department of Mechanical Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Hong Kong
Faculty of Sciences, University of Priština in Kosovska Mitrovica, Lole Ribara 29, Kosovska Mitrovica, 38220, Serbia
Department of Electrical Engineering, Ajman University, P.O. Box 346, Ajman, United Arab Emirates
Center of Medical and Bio-allied Health Sciences Research, Ajman University, Ajman P.O. Box 346, United Arab Emirates
School of Engineering, Nazarbayev University, Astana, Kazakhstan
Center for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University at Zhuhai, Zhuhai, 519087, China
Faculty of Science
Department of Mechanical Engineering
Faculty of Sciences
Department of Electrical Engineering
Center of Medical and Bio-allied Health Sciences Research
School of Engineering
Center for Cognition and Neuroergonomics
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