Nonlinear phase noise tolerance for coherent optical systems using soft-decision-aided ML carrier phase estimation enhanced with constellation partitioning

Yan Li, Mingwei Wu, Xinwei Du, Zhuoran Xu, Mohan Gurusamy, Changyuan Yu, Pooi Yuen Kam

Research output: Journal article publicationJournal articleAcademic researchpeer-review


A novel soft-decision-aided maximum likelihood (SDA-ML) carrier phase estimation method and its simplified version, the decision-aided and soft-decision-aided maximum likelihood (DA-SDA-ML) methods are tested in a nonlinear phase noise-dominant channel. The numerical performance results show that both the SDA-ML and DA-SDA-ML methods outperform the conventional DA-ML in systems with constant-amplitude modulation formats. In addition, modified algorithms based on constellation partitioning are proposed. With partitioning, the modified SDA-ML and DA-SDA-ML are shown to be useful for compensating the nonlinear phase noise in multi-level modulation systems.
Original languageEnglish
Pages (from-to)45-51
Number of pages7
JournalOptics Communications
Publication statusPublished - 15 Feb 2018


  • Coherent optical systems
  • Constellation partitioning
  • Nonlinear phase noise
  • SDA-ML

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Physical and Theoretical Chemistry
  • Electrical and Electronic Engineering

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