Content area

Abstract

In this paper, we propose a low-complexity fiber nonlinearity impairments compensation scheme based on nonlinear step size and modified adaptive digital back propagation. To verify the feasibility of the proposed algorithm, we construct a simulation system of single channel 12.5 GBaud polarization division multiplexing 16-ary quadrature amplitude modulation (PDM-16QAM) optical transmission system. Comprehensive numerical simulation results demonstrate that the proposed scheme can not only search for the fiber nonlinear coefficient adaptively, but also has the characteristics of high performance and low complexity.

Details

Title
Fiber nonlinear impairments compensation based on nonlinear step size and modified adaptive digital back propagation
Author
Jian-Yu, Meng 1 ; Hong-Bo, Zhang 1 ; Zhang, Min 1 ; Cai, Ju 1 ; Qian-Wu, Zhang 2 ; Hong-Lin, Zhu 1 ; Qing-Bin, Yi 1 ; Yong-Zhi, Zhang 3 ; Yun-Han, Xiao 3 

 College of Communication Engineering, Chengdu University of Information Technology, Chengdu, 610225, China 
 Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University, Shanghai, 200072, China 
 Production and Application of Plastic Optical Fiber National and Local Engineering Laboratory, Chengdu, 611230, China 
Publication title
Volume
45
Issue
3
Pages
523-528
Publication year
2024
Publication date
2024
Publisher
Walter de Gruyter GmbH
Place of publication
Berlin
Country of publication
Germany
Publication subject
ISSN
01734911
e-ISSN
21916322
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2022-03-21
Milestone dates
2021-12-20 (Received); 2022-01-21 (Rev-recd); 2022-01-28 (Accepted)
Publication history
 
 
   First posting date
21 Mar 2022
ProQuest document ID
3090033991
Document URL
https://www.proquest.com/scholarly-journals/fiber-nonlinear-impairments-compensation-based-on/docview/3090033991/se-2?accountid=208611
Copyright
© 2022 Walter de Gruyter GmbH, Berlin/Boston
Last updated
2024-08-19
Database
ProQuest One Academic