ML blind channel estimation in OFDM using cyclostationarity and spectral factorization

A. A. Quadeer, Tareq Al-Naffouri

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

3 Scopus citations

Abstract

Channel estimation is vital in OFDM systems for efficient data recovery. In this paper, we propose a blind algorithm for channel estimation that is based on the assumption that the transmitted data in an OFDM system is Gaussian (by central limit arguments). The channel estimate can then be obtained by maximizing the output likelihood function. Unfortunately, the likelihood function turns out to be multi-modal and thus finding the global maxima is challenging. We rely on spectral factorization and the cyclostationarity of the output to obtain the correct channel zeros. The Genetic algorithm is then used to fine tune the obtained solution.

Original languageEnglish (US)
Title of host publication2010 IEEE 11th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2010
DOIs
StatePublished - Dec 1 2010
Event2010 IEEE 11th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2010 - Marrakech, Morocco
Duration: Jun 20 2010Jun 23 2010

Publication series

NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC

Other

Other2010 IEEE 11th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2010
CountryMorocco
CityMarrakech
Period06/20/1006/23/10

Keywords

  • Blind channel estimation
  • Genetic algorithm
  • Maximum likelihood estimation
  • Spectral factorization

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Information Systems

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