Algorithms for Blind Separation and Estimation of Transmitter and Receiver IQ Imbalances

Qun Zhang, Yanfu Yang, Changjian Guo, Xian Zhou, Yong Yao, Alan Pak Tao Lau, Chao Lu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

57 Citations (Scopus)

Abstract

We propose a blind transmitter (Tx) and receiver (Rx) in-phase/quadrature (IQ) amplitude and phase imbalances estimation scheme based on a combination of analytical modeling and clustering algorithms. The proposed scheme can isolate and separately estimate Tx and Rx phase and amplitude imbalances, applicable to high-order multi-modulus signals, and hence, is a great physical-layer-monitoring tool for network disaggregation. We first estimate the Rx imbalances by identifying the fact that the received signal distribution in presence of laser frequency offset (FO), phase noise (PN), and Rx imbalance forms concentric ellipses. A convex hull assisted ellipse correction algorithm is used to determine the Rx IQ imbalance parameters that best match the ellipses. Standard laser FO compensation algorithm follows. A k-means clustering assisted blind phase search algorithm is then employed to mitigate the PN in presence of Tx imbalances. Finally, another iterative k-means clustering procedure is used to estimate the Tx IQ imbalances. The proposed scheme is evaluated experimentally for 34 Gbaud QPSK and 16-quadratic-amplitude modulation signals. The accurate estimation for a wide range of Tx and Rx IQ imbalances and good robustness to amplified spontaneous emission noise is demonstrated.

Original languageEnglish
Article number8643374
Pages (from-to)2201-2208
Number of pages8
JournalJournal of Lightwave Technology
Volume37
Issue number10
DOIs
Publication statusPublished - 15 May 2019

Keywords

  • Digital signal processing
  • machine learning
  • optical fiber communication
  • parameter estimation

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

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