• DocumentCode
    66473
  • Title

    An SVM-Based Detection for Coherent Optical APSK Systems With Nonlinear Phase Noise

  • Author

    Yi Han ; Song Yu ; Minliang Li ; Jie Yang ; Wanyi Gu

  • Author_Institution
    State Key Lab. of Inf. Photonics & Opt. Commun., Beijing Univ. of Posts & Telecommun., Beijing, China
  • Volume
    6
  • Issue
    5
  • fYear
    2014
  • fDate
    Oct. 2014
  • Firstpage
    1
  • Lastpage
    10
  • Abstract
    A support vector machine (SVM)-based data detection is proposed for coherent optical fiber amplitude phase-shift keying (APSK) communication systems where the nonlinear phase noise is the main system impairment. The performances of the detection with SVMs are investigated for three different 16-APSK modulation formats. In addition, three transmission scenarios with dispersion being considered or not are adopted to simulate and analyze the performances. Compared with the traditional two-stage maximum-likelihood detection, the SVM conducts detection without the need to know the information of transmission link, and it gains a relatively large improvement in the nonlinear system tolerance, particularly in the high nonlinear regime. Compared with quadrature amplitude modulation (QAM), the 16-APSK system can increase the nonlinear system tolerance by 4.88 dB at BER 1/4 1E - 3.
  • Keywords
    optical fibre communication; phase noise; phase shift keying; support vector machines; SVM-based detection; coherent optical APSK systems; coherent optical fiber amplitude phase-shift keying communication systems; nonlinear phase noise; nonlinear system tolerance; support vector machine based data detection; Detectors; Dispersion; Nonlinear optics; Optical noise; Phase noise; Quadrature amplitude modulation; Support vector machines; Support vector machine (SVM); amplitude phase-shift keying (APSK); nonlinear phase noise (NLPN);
  • fLanguage
    English
  • Journal_Title
    Photonics Journal, IEEE
  • Publisher
    ieee
  • ISSN
    1943-0655
  • Type

    jour

  • DOI
    10.1109/JPHOT.2014.2357424
  • Filename
    6897918