Structured sparsity learning-based pruned retraining volterra equalization for data-center interconnects

Govind Sharan Yadav, Chun Yen Chuang, Kai Ming Feng*, Jyehong Chen, Young Kai Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We propose a structured sparsity learning-based pruned retraining Volterra equalization for inter-dadta-center interconnects. Compared with conventional VE, we achieve 95% and 90.5% complexity reduction without signal degradation for B2B and 40-km at 80-Gb/s PAM4, respectively.

Original languageEnglish
Title of host publicationOptical Fiber Communication Conference, OFC 2021
PublisherOptica Publishing Group (formerly OSA)
ISBN (Electronic)9781557528209
StatePublished - 2021
EventOptical Fiber Communication Conference, OFC 2021 - Virtual, Online, United States
Duration: 6 Jun 202111 Jun 2021

Publication series

NameOptics InfoBase Conference Papers

Conference

ConferenceOptical Fiber Communication Conference, OFC 2021
Country/TerritoryUnited States
CityVirtual, Online
Period6/06/2111/06/21

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