Steady-state performance of multimodulus blind equalizers

  • Ali W. Azim
  • , Shafayat Abrar*
  • , Azzedine Zerguine
  • , Asoke K. Nandi
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Multimodulus algorithms (MMA) based adaptive blind equalizers mitigate inter-symbol interference in a digital communication system by minimizing dispersion in the quadrature components of the equalized sequence in a decoupled manner, i.e., the in-phase and quadrature components of the equalized sequence are used to minimize dispersion in the respective components of the received signal. These unsupervised equalizers are mostly incorporated in bandwidth-efficient digital receivers (wired, wireless or optical) which rely on quadrature amplitude modulation based signaling. These equalizers are equipped with nonlinear error-functions in their update expressions which makes it a challenging task to evaluate analytically their steady-state performance. However, exploiting variance relation theorem, researchers have recently been able to report approximate expressions for steady-state excess mean square error (EMSE) of such equalizers for noiseless but interfering environment. In this work, in contrast to existing results, we present exact steady-state tracking analysis of two multimodulus equalizers in a non-stationary environment. Specifically, we evaluate expressions for steady-state EMSE of two equalizers, namely the MMA2-2 and the βMMA. The accuracy of the derived analytical results is validated using different set experiments and found in close agreement.

Original languageEnglish
Pages (from-to)509-520
Number of pages12
JournalSignal Processing
Volume108
DOIs
StatePublished - Mar 2015

Bibliographical note

Publisher Copyright:
© 2014 Elsevier Inc. All rights reserved.

Keywords

  • Blind equalization
  • Energy conservation theorem
  • Mean square error
  • Multimodulus algorithm
  • Quadrature amplitude modulation
  • Steady-state analysis
  • Tracking performance
  • Variance relation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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