PAM-4 eye-opening monitoring techniques based on Gaussian mixture model fitting

Yasushi Yuminaka; Keigo Taya; Yosuke Iijima

doi:10.1587/comex.2020XBL0086

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PAM-4 eye-opening monitoring techniques based on Gaussian mixture model fitting

Yasushi Yuminaka, Keigo Taya, Yosuke Iijima

著者情報

キーワード: Multi-valued logic, PAM-4, Eye monitoring, Gaussian mixture model

ジャーナルフリー早期公開

論文ID: 2020XBL0086

DOI https://doi.org/10.1587/comex.2020XBL0086

この記事には本公開記事があります。

The final version of this article is now available: Vol. 9 (2020), No. 10 pp. 464-469

詳細

抄録

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.

責任著者(Corresponding author)

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