Fully-blind Neural Network Based Equalization for Severe Nonlinear Distortions in 112 Gbit/s Passive Optical Networks-Reference-Cited by-同舟云学术

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Fully-blind Neural Network Based Equalization for Severe Nonlinear Distortions in 112 Gbit/s Passive Optical Networks

Published:2024 Issue: Volume: Page:
ISSN:
Container-title:Optical Fiber Communication Conference (OFC) 2024
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Author:

Lauinger Vincent,Matalla Patrick,Ney Jonas,Wehn Norbert,Randel Sebastian,Schmalen Laurent

Abstract

We demonstrate and evaluate a fully-blind digital signal processing (DSP) chain for 100G passive optical networks (PONs), and analyze different equalizer topologies based on neural networks with low hardware complexity.

Publisher

Optica Publishing Group

Reference8 articles.

1. 50G-PON: The First ITU-T Higher-Speed PON System

2. Perspectives on and the road towards 100 Gb/s TDM PON with intensity-modulation and direct-detection

3. High Dynamic Range 100G PON Enabled by SOA Preamplifier and Recurrent Neural Networks

4. 92 and 50 Gbps TDM-PON using neural network enabled receiver equalization specialized for PON;Houtsma,2019

5. Machine Learning for 100 Gb/s/λ Passive Optical Network

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Optical Nonlinearity Mitigation Using Reservoir Computing with Tapped-Delay Lines;IEICE Communications Express;2024-09

2. Real-Time FPGA Demonstrator of ANN-Based Equalization for Optical Communications;2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN);2024-05-05

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