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20122026
most citedFast and Accurate Optical Fiber Channel Modeling Using Generative Adversarial Network

113 citations · 425 across the 25 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

eess.SP2024

Low Complexity Joint Chromatic Dispersion and Time/Frequency Offset Estimation Based on Fractional Fourier Transform

Guozhi Xu, Zekun Niu, Lyu Li +2

We propose and experimentally validate a joint estimation method for chromatic dispersion and time-frequency offset based on the fractional Fourier transform, which reduces computa…

eess.SP2024

Improve the Fitting Accuracy of Deep Learning for the Nonlinear Schrödinger Equation Using Linear Feature Decoupling Method

Yunfan Zhang, Zekun Niu, Minghui Shi +2

We utilize the Feature Decoupling Distributed (FDD) method to enhance the capability of deep learning to fit the Nonlinear Schrodinger Equation (NLSE), significantly reducing the N…

eess.SY2024★ 1 cited

First Field Trial of LLM-Powered AI Agent for Lifecycle Management of Autonomous Driving Optical Networks

Xiaomin Liu, Qizhi Qiu, Yihao Zhang +4

We design and demonstrate the first field trial of LLM-powered AI Agent for ADON. Three operation modes of the Agent are proposed for network lifecycle management. The Agent effici…

eess.SP2024

Preamble Design for Joint Frame Synchronization, Frequency Offset Estimation, and Channel Estimation in Upstream Burst-mode Detection of Coherent PONs

Yongxin Sun, Hexun Jiang, Yicheng Xu +5

Coherent optics has demonstrated significant potential as a viable solution for achieving 100 Gb/s and higher speeds in single-wavelength passive optical networks (PON). However, u…

eess.SY2024

Heuristic Optimization of Amplifier Reconfiguration Process for Autonomous Driving Optical Networks

Qizhi Qiu, Xiaomin Liu, Yihao Zhang +3

We propose a heuristic-based optimization scheme for reliable optical amplifier reconfiguration process in ADON. In the experiment on a commercial testbed, the scheme prevents a 1.…

physics.optics2024★ 1 cited

Improved Physics-based Raman Amplifier Model in C+L Networks through Input Parameter Refinement

Yihao Zhang, Xiaomin Liu, Qizhi Qiu +4

We propose a n input parameter refinement scheme for the physics-based Raman amplifier model. Experiments over C+L band are conducted. Results show the scheme can lower the physica…