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  • Research Article
  • Open Access

The Extended-Window Channel Estimator for Iterative Channel-and-Symbol Estimation

EURASIP Journal on Wireless Communications and Networking20052005:349390

  • Received: 29 April 2004
  • Published:


The application of the expectation-maximization (EM) algorithm to channel estimation results in a well-known iterative channel-and-symbol estimator (ICSE). The EM-ICSE iterates between a symbol estimator based on the forward-backward recursion (BCJR equalizer) and a channel estimator, and may provide approximate maximum-likelihood blind or semiblind channel estimates. Nevertheless, the EM-ICSE has high complexity, and it is prone to misconvergence. In this paper, we propose the extended-window (EW) estimator, a novel channel estimator for ICSE that can be used with any soft-output symbol estimator. Therefore, the symbol estimator may be chosen according to performance or complexity specifications. We show that the EW-ICSE, an ICSE that uses the EW estimator and the BCJR equalizer, is less complex and less susceptible to misconvergence than the EM-ICSE. Simulation results reveal that the EW-ICSE may converge faster than the EM-ICSE.


  • blind channel estimation
  • EM algorithm
  • maximum-likelihood estimation
  • iterative systems

Authors’ Affiliations

DSPCom, DECOM, FEEC, University of Campinas (UNICAMP), 400 Albert Einstein Avenue, Sao Paulo, 13083-970 Campinas, Brazil
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0250, USA


© Lopes and Barry 2005

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.