Investigative optimization of nonlinear ion-ion interactions in thulium–erbium doped cascaded fiber amplifier for S + C band
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Krishna Sarma
Abstract
A combination of a thulium-doped fiber amplifier (TDFA) and an erbium-doped fiber amplifier (EDFA) in a sequential configuration has been identified to design a hybrid amplifier. The proposed amplifier module delivers a flat and high gain. This method is potentially an effective strategy to fully utilize the S + C band (1,460 nm–1,565 nm) for amplifying fiber optic signals. The proposed TDF-EDF hybrid amplifier has an optimum average flat-band gain of 24.27 dB from 1,460 nm to 1,516 nm with a maximum gain of 47.07 dB at 1,528 nm. The parametric optimization has been performed considering the optical pumping configuration with corresponding power, input-signal power, amplifier length, ion density with its radius, and the hybrid amplifier’s numerical aperture (NA). The nonlinear clustering-ion effects known as the ion-ion interaction mechanism (IM) have been aimed to distort the signal gain with broadband flat-gain profile minimally. Apparently, the optimized parameter reduced the gain deterioration by the IM effect to 1.12 % with homogeneous up-conversion (HUC) and 8.14 % with the combined effect of HUC and pair-induced quenching (PIQ) corresponding to the maximum gain. In the flat-band region, the HUC and HUC + PIQ combination have the respective gain deteriorating contributions of 0.67 % and 5.24 %. For the input signal power of −40 dBm, the gain flatness of the hybrid amplifier is obtained as 3.27 dB for 1,460 nm–1,516 nm regions without IM effects. However, with HUC and HUC + PIQ, gain flatness has been reduced to 3.08 dB and 2.19 dB, respectively. Furthermore, the gain variation ratio (GVR) of 0.05 (preferably GVR
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: The raw data can be obtained on request from the corresponding author.
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