Main > Photonics Research >  Volume 9 >  Issue 1 >  Page 010000B1 > Article
  • Abstract
  • Abstract
  • Figures (8)
  • Tables (3)
  • Equations (5)
  • References (50)
  • Get PDF
  • View Full Text
  • Paper Information
  • Received: Sep. 9, 2020

    Accepted: Nov. 13, 2020

    Posted: Nov. 18, 2020

    Published Online: Dec. 25, 2020

    The Author Email: Pu Li (lipu8603@126.com)

    DOI: 10.1364/PRJ.409114

  • Get Citation
  • Copy Citation Text

    Qiang Cai, Ya Guo, Pu Li, Adonis Bogris, K. Alan Shore, Yamei Zhang, Yuncai Wang. Modulation format identification in fiber communications using single dynamical node-based photonic reservoir computing[J]. Photonics Research, 2021, 9(1): 010000B1

    Download Citation

  • Special Issue
  • DEEP LEARNING IN PHOTONICS
  • Share
Photonics Research, Vol. 9, Issue 1, 010000B1 (2021)

Modulation format identification in fiber communications using single dynamical node-based photonic reservoir computing

Qiang Cai1,†, Ya Guo1,2,†, Pu Li1,3,4,*, Adonis Bogris5, K. Alan Shore6, Yamei Zhang7, and Yuncai Wang3

Author Affiliations

  • 1Key Laboratory of Advanced Transducers and Intelligent Control System, Ministry of Education, Taiyuan University of Technology, Taiyuan 030024, China
  • 2School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China
  • 3School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China
  • 4Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University, Shanghai 200444, China
  • 5Department of Informatics and Computer Engineering, University of West Attica, Athens 12243, Greece
  • 6School of Electronic Engineering, Bangor University, Wales LL57 1UT, UK
  • 7Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Abstract

We present a simple approach based on photonic reservoir computing (P-RC) for modulation format identification (MFI) in optical fiber communications. Here an optically injected semiconductor laser with self-delay feedback is trained with the representative features from the asynchronous amplitude histograms of modulation signals. Numerical simulations are conducted for three widely used modulation formats (on–off keying, differential phase-shift keying, and quadrature amplitude modulation) for various transmission situations where the optical signal-to-noise ratio varies from 12 to 26 dB, the chromatic dispersion varies from -500 to 500 ps/nm, and the differential group delay varies from 0 to 20 ps. Under these situations, final simulation results demonstrate that this technique can efficiently identify all those modulation formats with an accuracy of >95% after optimizing the control parameters of the P-RC layer such as the injection strength, feedback strength, bias current, and frequency detuning. The proposed technique utilizes very simple devices and thus offers a resource-efficient alternative approach to MFI.

Please Enter Your Email: