BGD-based Adam algorithm for time-domain equalizer in PAM-based optical interconnects

Haide Wang, Ji Zhou, Weiping Liu, Jianping Li, Xincheng Huang, Long Liu, Weixian Liang, Changyuan Yu, Fan Li, Zhaohui Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

To the best of our knowledge, for the first time, we propose an adaptive moment estimation (Adam) algorithm based on batch gradient descent (BGD) to design a time-domain equalizer (TDE) for pulse-amplitude modulation (PAM)-based optical interconnects. The Adam algorithm has been applied widely in the fields of artificial intelligence. For TDE, the BGD-based Adam algorithm can obtain globally optimal tap coefficients without being trapped in locally optimal tap coefficients. Therefore, fast and stable convergence can be achieved by the BGD-based Adam algorithm with low mean square error. Meanwhile, the BGD-based Adam algorithm is implemented by parallel processing, which is more efficient than conventional serial algorithms, such as least mean square and recursive least square algorithms. The experimental results demonstrate that the BGD-based Adam feed-forward equalizer works well in 120-Gbit/s PAM8 optical interconnects. In conclusion, the BGD-based Adam algorithm shows great potential for converging the tap coefficients of TDE in future optical interconnects.

Original languageEnglish
Pages (from-to)141-144
Number of pages4
JournalOptics Letters
Volume45
Issue number1
DOIs
Publication statusPublished - 1 Jan 2020

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

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