IEICE Communications Express
Online ISSN : 2187-0136
ISSN-L : 2187-0136
PAM-4 eye-opening monitoring techniques based on Gaussian mixture model fitting
Yasushi YuminakaKeigo TayaYosuke Iijima
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JOURNALS FREE ACCESS Advance online publication

Article ID: 2020XBL0086

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Abstract

Four-level pulse amplitude modulation (PAM-4) data formats are adopted to achieve next-generation high-speed data transmission standards. In this letter, a novel eye-opening monitoring technique based on machine learning is proposed to evaluate the received signal quality for the adaptive coefficients setting of a transmitter feed-forward equalizer for PAM-4 signaling. The monitoring technique employs a Gaussian mixture model (GMM) to classify the received PAM-4 symbols. Simulation and measured results of the coefficient adjustment using the GMM method are presented.

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© 2020 The Institute of Electronics, Information and Communication Engineers
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