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

被引：5

作者：

Yuminaka, Yasushi ^{[1
]}

Taya, Keigo ^{[1
]}

Iijima, Yosuke ^{[2
]}

机构：

[1] Gunma Univ, Grad Sch Sci & Technol, 1-5-1 Tenjin Cho, Kiryu, Gunma 3768515, Japan

[2] Oyama Coll, Natl Inst Technol KOSEN, 771 Nakakuki, Oyama 3230806, Japan

来源：

IEICE COMMUNICATIONS EXPRESS | 2020年 / 9卷 / 10期

关键词：

multi-valued logic; PAM-4; eye monitoring; Gaussian mixture model; TRANSMITTER;

D O I：

10.1587/comex.2020XBL0086

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：464 / 469

页数：6

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