Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Digital Pre-Distortion Coefficients Identification Using Gauss-Newton Based Direct Learning Architecture

Not Accessible

Your library or personal account may give you access

Abstract

We propose to identify the coefficients of a digital pre-distortion equalizer based on direct learning architecture (DLA) using the Gauss-Newton method. Experimental results show that DLA outperforms indirect learning architecture by 0.5dB.

© 2023 The Author(s)

PDF Article  |   Presentation Video
More Like This
Efficient Training of Volterra Series-Based Pre-distortion Filter Using Neural Networks

Vinod Bajaj, Mathieu Chagnon, Sander Wahls, and Vahid Aref
M1H.3 Optical Fiber Communication Conference (OFC) 2022

Experimental Demonstration of Nonlinear Equalizer for Self-Homodyne Detection Using Indirect Learning Digital Pre-Distorter and Neural Networks

Shuo Zheng, Min Yang, Guofeng Yan, Yanjun Zhu, Hua Zhang, Chaonan Yao, Yuchen Shao, and Jian Wang
SpTu1J.6 Signal Processing in Photonic Communications (SPPCom) 2022

Net 100 Gb/s/λ VCSEL+MMF nonlinear Digital Pre-Distortion using Convolutional Neural Networks

Leonardo Minelli, Fabrizio Forghieri, Tong Shao, Ali Shahpari, and Roberto Gaudino
Tu3I.4 Optical Fiber Communication Conference (OFC) 2023

Presentation Video

Presentation video access is available to:

  1. Optica Publishing Group subscribers
  2. Technical meeting attendees
  3. Optica members who wish to use one of their free downloads. Please download the article first. After downloading, please refresh this page.

Contact your librarian or system administrator
or
Log in to access Optica Member Subscription or free downloads


More Like This
Efficient Training of Volterra Series-Based Pre-distortion Filter Using Neural Networks

Vinod Bajaj, Mathieu Chagnon, Sander Wahls, and Vahid Aref
M1H.3 Optical Fiber Communication Conference (OFC) 2022

Experimental Demonstration of Nonlinear Equalizer for Self-Homodyne Detection Using Indirect Learning Digital Pre-Distorter and Neural Networks

Shuo Zheng, Min Yang, Guofeng Yan, Yanjun Zhu, Hua Zhang, Chaonan Yao, Yuchen Shao, and Jian Wang
SpTu1J.6 Signal Processing in Photonic Communications (SPPCom) 2022

Net 100 Gb/s/λ VCSEL+MMF nonlinear Digital Pre-Distortion using Convolutional Neural Networks

Leonardo Minelli, Fabrizio Forghieri, Tong Shao, Ali Shahpari, and Roberto Gaudino
Tu3I.4 Optical Fiber Communication Conference (OFC) 2023

Nonlinear Pre-Distortion Based on Indirect Learning Architecture and Cross-Correlation-Enabled Behavioral Modeling for 120-Gbps Multimode Optical Interconnects

Chenyu Liang, Wenjia Zhang, Ling Ge, Jiangbing Du, and Zuyuan He
W2A.31 Optical Fiber Communication Conference (OFC) 2020

Nonlinear Pre-distortion through a Multi-rate End-to-end Learning Approach over VCSEL-MMF IM-DD Optical Links

Leonardo Minelli, Fabrizio Forghieri, and Roberto Gaudino
Tu3C.3 European Conference and Exhibition on Optical Communication (ECOC) 2022

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.