A Novel Machine Learning-based Equalizer for a Downstream 100G PAM-4 PON
<|reference_start|>A Novel Machine Learning-based Equalizer for a Downstream 100G PAM-4 PON: 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.<|reference_end|>
@article{shao2024a,
    title={A Novel Machine Learning-based Equalizer for a Downstream 100G PAM-4 PON},
    author={Chen Shao, Elias Giacoumidis, Shi Li, Jialei Li, Michael Faerber,
  Tobias Kaefer, and Andre Richter},
    journal={arXiv preprint arXiv:2405.00720},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.00720},
    primaryClass={eess.SP cs.LG}
}