Substituting the cumulants in the super-exponential blind equalization algorithm

Arie Yeredor*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

The Shalvi-Weinstein super-exponential algorithm for blind channel equalization employs empirical high-order cross-cumulants between the equalizer's input and output for iterative updates of the equalizer. When the source signal has (nearly) null cumulants of the required order, the algorithm's performance may be severely degraded. Rather than resort to even higher-order cumulants in such cases, we propose to employ an alternative statistic, based on second-order derivatives (Hessians, evaluated away from the origin) of the joint log-characteristic function of the equalizer's input and output. These Hessians admit straightforward empirical estimates, maintain the "philosophy of operation" of the algorithm, and, as we demonstrate in simulation, can significantly improve its performance in such (and in other) cases.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages3477-3480
Number of pages4
DOIs
StatePublished - 2008
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: 31 Mar 20084 Apr 2008

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Country/TerritoryUnited States
CityLas Vegas, NV
Period31/03/084/04/08

Keywords

  • Blind equalization
  • Characteristic function
  • Charrelation matrix
  • Hessian
  • Super-exponential

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