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A frequency-calibrated SCINet (FC-SCINet) equalizer is proposed for down-stream 100G PON with 28.7 dB path loss. At 5 km, FC-SCINet improves the BER by 88.87% compared to FFE and a 3-layer DNN with 10.57% lower complexity.
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@article{shao2024novel,
title = {A Novel Machine Learning-based Equalizer for a Downstream 100G PAM-4 PON},
author = {Chen Shao and Elias Giacoumidis and Shi Li and Jialei Li and Michael Faerber and Tobias Kaefer and Andre Richter},
year = {2024},
eprint = {2405.00720},
archivePrefix = {arXiv},
url = {http://arxiv.org/abs/2405.00720v1}
}Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/2405.00720)