Application of decision feedback equalisers based on multilayer neural network structures to compensate for optical fibre dispersion and nonlinearity

被引：0
|
作者：
Yunxi, L. [1 ]
机构：
[1] UCL, Dept Elect & Elect Engn, London WC1E 7JE, England
来源：
IET OPTOELECTRONICS | 2007年 / 1卷 / 04期
关键词：
D O I：
10.1049/iet-opt:20060097
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Decision feedback equalisers (DFE) based on multilayer neural networks (MNNs) structure are simulated in a 10 Gbit/s optical channel of standard single mode fibre of 300 km. Simulation results show that the DFE based on the MNN structure significantly outperforms the traditional DFE in the equalisation of chromatic dispersion in medium to long haul optical communications (> 220 km).
引用
收藏
页码：169 / 174
页数：6
相关论文
共 50 条
  • [31] Design of Planar Multilayer Devices for Optical Filtering Using Surrogate Model Based on Artificial Neural Network
    Rego, Davi F.
    Silva, Fabricio G. S.
    Gusmao, Rodrigo C.
    Rodriguez-Esquerre, Vitaly F.
    OPTICS, 2024, 5 (01): : 121 - 132
  • [32] Neural Network-based Fiber Nonlinearity Mitigation in High-speed Coherent Optical Transmission Systems
    Zhang, Fan
    Fang, Xiansong
    Chen, Xinyu
    2022 OPTICAL FIBER COMMUNICATIONS CONFERENCE AND EXHIBITION (OFC), 2022,
  • [33] Towards FPGA Implementation of Neural Network-Based Nonlinearity Mitigation Equalizers in Coherent Optical Transmission Systems
    Freire, Pedro J.
    Anderson, Michael
    Spinnler, Bernhard
    Bex, Thomas
    Prilepsky, Jaroslaw E.
    Eriksson, Tobias A.
    Costa, Nelson
    Schairer, Wolfgang
    Blott, Michaela
    Napoli, Antonio
    Turitsy, Sergei K.
    2022 EUROPEAN CONFERENCE ON OPTICAL COMMUNICATION (ECOC), 2022,
  • [34] A Novel Underwater Wireless Optical Communication Optical Receiver Decision Unit Strategy Based on a Convolutional Neural Network
    El Ramley, Intesar F.
    Bedaiwi, Nada M.
    Al-Hadeethi, Yas
    Barasheed, Abeer Z.
    Al-Zhrani, Saleha
    Chen, Mingguang
    MATHEMATICS, 2024, 12 (18)
  • [35] Feedback recurrent neural network-based embedded vector and its application in topic model
    Li, Lian-sheng
    Gan, Sheng-jiang
    Yin, Xiang-dong
    EURASIP JOURNAL ON EMBEDDED SYSTEMS, 2016,
  • [36] Research on application of water conservancy project bidding decision model based on BP neural network
    Liu, Ling
    Ji, Huiran
    Guo, Xiaoying
    Sun, Shuhong
    ENGINEERING TECHNOLOGY AND APPLICATIONS, 2014, : 25 - 30
  • [37] An optical fibre sensor for in situ measurement of external species in fluids based on artificial neural network pattern recognition
    Lyons, WB
    Ewald, H
    Flanagan, C
    Lewis, E
    PHYSIOLOGICAL MEASUREMENT, 2001, 22 (03) : 635 - 646
  • [38] OPTICAL IMPLEMENTATION OF A FEATURE-BASED NEURAL NETWORK WITH APPLICATION TO AUTOMATIC TARGET RECOGNITION
    CHAO, TH
    STONER, WW
    APPLIED OPTICS, 1993, 32 (08): : 1359 - 1369
  • [39] RETRACTION: Efficient and economical smart healthcare application based on quantum optical neural network
    Zhou, Tianyi
    Anuradha, T.
    Mahendra, S. J.
    Webber, Julian L.
    Mehbodniya, Abolfazl
    Wang, Jinsong
    Subrahmanyam, Kodukula
    OPTICAL AND QUANTUM ELECTRONICS, 2024, 56 (09)
  • [40] Intra-Channel Nonlinearity Mitigation in Optical Fiber Transmission Systems Using Perturbation-Based Neural Network
    Ding, Jiazheng
    Liu, Tiegen
    Xu, Tongyang
    Hu, Wenxiu
    Popov, Sergei
    Leeson, Mark S.
    Zhao, Jian
    Xu, Tianhua
    JOURNAL OF LIGHTWAVE TECHNOLOGY, 2022, 40 (21) : 7106 - 7116
12345