Non-data-aided joint bit-rate and modulation format identification for next-generation heterogeneous optical networks

Faisal Nadeem Khan, Yudi Zhou, Qi Sui, Pak Tao Lau

Research output: Journal article publicationJournal articleAcademic researchpeer-review

34 Citations (Scopus)

Abstract

A novel and cost-effective technique for simultaneous bit-rate and modulation format identification (BR-MFI) in next-generation heterogeneous optical networks is proposed. This technique utilizes an artificial neural network (ANN) in conjunction with asynchronous delay-tap plots (ADTPs) to enable low-cost joint BR-MFI at the receivers as well as at the intermediate network nodes without requiring any prior information from the transmitters. The results of numerical simulations demonstrate successful identification of several commonly-used bit-rates and modulation formats with estimation accuracies in excess of 99.7%. The effectiveness of proposed technique under different channel conditions i.e. optical signal-to-noise ratio (OSNR) in the range of 14-28 dB, chromatic dispersion (CD) in the range of -500 to 500 ps/nm and differential group delay (DGD) in the range of 0-10 ps, is investigated and it has been shown that the proposed technique is robust against all these impairments.
Original languageEnglish
Pages (from-to)68-74
Number of pages7
JournalOptical Fiber Technology
Volume20
Issue number2
DOIs
Publication statusPublished - 1 Mar 2014

Keywords

  • Artificial neural networks
  • Bit-rate and modulation format identification
  • Fiber-optic communication
  • Heterogeneous fiber-optic networks
  • Optical performance monitoring

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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