Learning and Perturbation Based Multi-Stage Nonlinear Pre-Compensation Algorithm in Coherent Optical Systems

A learning and perturbation based multi-stage pre-compensation method is proposed. The nonlinear compensation performance is enhanced by introducing amplitude and phase factors in each stage of pre-compensation, which are obtained by the gradient descent algorithm.

Authors

Institutions

Publication Details

Published
2024-11-02
DOI
https://doi.org/10.1109/acp/ipoc63121.2024.10809737
Primary Topic
Optical Network Technologies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Learning and Perturbation Based Multi-Stage Nonlinear Pre-Compensation Algorithm in Coherent Optical Systems

Junhe Zhou, Yuheng Wang, Tengyuan Liu
Optical Network Technologies
article

Learning and Perturbation Based Multi-Stage Nonlinear Pre-Compensation Algorithm in Coherent Optical Systems

Junhe Zhou, Yuheng Wang, Tengyuan Liu
article en

Abstract

A learning and perturbation based multi-stage pre-compensation method is proposed. The nonlinear compensation performance is enhanced by introducing amplitude and phase factors in each stage of pre-compensation, which are obtained by the gradient descent algorithm.

Tongji University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Climate action
Openalex Percentile: Top 77%
Optical Network Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.