Channel Power Control for Full C-band Generalized Signal-to-Noise Ratio Optimization Based on Deep Reinforcement Learning

A model-free method based on deep reinforcement learning is implemented to control channel power for GSNR optimization. Flat GSNR covering entire C-band is achieved across 1440 km transmission with uneven gain profile of EDFA.

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Published
2024-11-02
DOI
https://doi.org/10.1109/acp/ipoc63121.2024.10809907
Primary Topic
Advanced Adaptive Filtering Techniques
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article
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article

Channel Power Control for Full C-band Generalized Signal-to-Noise Ratio Optimization Based on Deep Reinforcement Learning

Minghui Shi, Lilin Yi, Weisheng Hu, Zekun Niu et al.
Advanced Adaptive Filtering Techniques
article

Channel Power Control for Full C-band Generalized Signal-to-Noise Ratio Optimization Based on Deep Reinforcement Learning

Minghui Shi, Lilin Yi, Weisheng Hu, Zekun Niu, Xiao Jin, Lyu Li
article en

Abstract

A model-free method based on deep reinforcement learning is implemented to control channel power for GSNR optimization. Flat GSNR covering entire C-band is achieved across 1440 km transmission with uneven gain profile of EDFA.

Shanghai Jiao Tong University (CN)
Openalex Percentile: Top 73%
Advanced Adaptive Filtering Techniques
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Channel Power Control for Full C-band Generalized Signal-to-Noise Ratio Optimization Based on Deep Reinforcement Learning — Minghui Shi, Lilin Yi, et al. · (2024) | TGRS Research Map | TGRS