To meet the increasing demand for high-speed communication in VLSI (very large-scale integration) systems, next-generation high-speed data transmission standards (e.g., IEEE 802.3bs and PCIe 6.0) will adopt four-level pulse amplitude modulation (PAM-4) for data coding. Although PAM-4 is spectrally efficient to mitigate inter-symbol interference caused by bandwidth-limited wired channels, it is more sensitive than conventional non-return-to-zero line coding. To evaluate the received signal quality when using adaptive coefficient settings for a PAM-4 equalizer during data transmission, we propose an eye-opening monitor technique based on machine learning. The proposed technique uses a Gaussian mixture model to classify the received PAM-4 symbols. Simulation and experimental results demonstrate the feasibility of adaptive equalization for PAM-4 coding.
Yosuke IIJIMA
Oyama College
Keigo TAYA
Gunma University
Yasushi YUMINAKA
Gunma University
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Yosuke IIJIMA, Keigo TAYA, Yasushi YUMINAKA, "PAM-4 Eye-Opening Monitor Technique Using Gaussian Mixture Model for Adaptive Equalization" in IEICE TRANSACTIONS on Information,
vol. E104-D, no. 8, pp. 1138-1145, August 2021, doi: 10.1587/transinf.2020LOP0007.
Abstract: To meet the increasing demand for high-speed communication in VLSI (very large-scale integration) systems, next-generation high-speed data transmission standards (e.g., IEEE 802.3bs and PCIe 6.0) will adopt four-level pulse amplitude modulation (PAM-4) for data coding. Although PAM-4 is spectrally efficient to mitigate inter-symbol interference caused by bandwidth-limited wired channels, it is more sensitive than conventional non-return-to-zero line coding. To evaluate the received signal quality when using adaptive coefficient settings for a PAM-4 equalizer during data transmission, we propose an eye-opening monitor technique based on machine learning. The proposed technique uses a Gaussian mixture model to classify the received PAM-4 symbols. Simulation and experimental results demonstrate the feasibility of adaptive equalization for PAM-4 coding.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2020LOP0007/_p
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@ARTICLE{e104-d_8_1138,
author={Yosuke IIJIMA, Keigo TAYA, Yasushi YUMINAKA, },
journal={IEICE TRANSACTIONS on Information},
title={PAM-4 Eye-Opening Monitor Technique Using Gaussian Mixture Model for Adaptive Equalization},
year={2021},
volume={E104-D},
number={8},
pages={1138-1145},
abstract={To meet the increasing demand for high-speed communication in VLSI (very large-scale integration) systems, next-generation high-speed data transmission standards (e.g., IEEE 802.3bs and PCIe 6.0) will adopt four-level pulse amplitude modulation (PAM-4) for data coding. Although PAM-4 is spectrally efficient to mitigate inter-symbol interference caused by bandwidth-limited wired channels, it is more sensitive than conventional non-return-to-zero line coding. To evaluate the received signal quality when using adaptive coefficient settings for a PAM-4 equalizer during data transmission, we propose an eye-opening monitor technique based on machine learning. The proposed technique uses a Gaussian mixture model to classify the received PAM-4 symbols. Simulation and experimental results demonstrate the feasibility of adaptive equalization for PAM-4 coding.},
keywords={},
doi={10.1587/transinf.2020LOP0007},
ISSN={1745-1361},
month={August},}
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TY - JOUR
TI - PAM-4 Eye-Opening Monitor Technique Using Gaussian Mixture Model for Adaptive Equalization
T2 - IEICE TRANSACTIONS on Information
SP - 1138
EP - 1145
AU - Yosuke IIJIMA
AU - Keigo TAYA
AU - Yasushi YUMINAKA
PY - 2021
DO - 10.1587/transinf.2020LOP0007
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E104-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2021
AB - To meet the increasing demand for high-speed communication in VLSI (very large-scale integration) systems, next-generation high-speed data transmission standards (e.g., IEEE 802.3bs and PCIe 6.0) will adopt four-level pulse amplitude modulation (PAM-4) for data coding. Although PAM-4 is spectrally efficient to mitigate inter-symbol interference caused by bandwidth-limited wired channels, it is more sensitive than conventional non-return-to-zero line coding. To evaluate the received signal quality when using adaptive coefficient settings for a PAM-4 equalizer during data transmission, we propose an eye-opening monitor technique based on machine learning. The proposed technique uses a Gaussian mixture model to classify the received PAM-4 symbols. Simulation and experimental results demonstrate the feasibility of adaptive equalization for PAM-4 coding.
ER -