TY - GEN
T1 - Structured sparsity learning-based pruned retraining volterra equalization for data-center interconnects
AU - Yadav, Govind Sharan
AU - Chuang, Chun Yen
AU - Feng, Kai Ming
AU - Chen, Jyehong
AU - Chen, Young Kai
N1 - Publisher Copyright:
© OSA 2021, © 2021 The Author(s)
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85133738425&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85133738425
T3 - Optics InfoBase Conference Papers
BT - Optical Fiber Communication Conference, OFC 2021
PB - Optica Publishing Group (formerly OSA)
T2 - Optical Fiber Communication Conference, OFC 2021
Y2 - 6 June 2021 through 11 June 2021
ER -