Blind feedforward cyclostationarity-based timing estimation for linear modulations

Yan Wang, Erchin Serpedin, Philippe Ciblat

Research output: Contribution to journalArticle

19 Citations (Scopus)


By exploiting a general cyclostationary (CS) statistics-based framework, this letter develops a rigorous and unified asymptotic (large sample) performance analysis setup for a class of blind feedforward timing epoch estimators for linear modulations transmitted through time nonselective flat-fading channels. Within the proposed CS framework, it is shown that several estimators proposed in the literature can be asymptotically interpreted as maximum likelihood (ML) estimators applied on a (sub)set of the second- (and/or higher) order statistics of the received signal. The asymptotic variance of these ML estimators is established in closed-form expression and compared with the modified Cramér-Rao bound. It is shown that the timing estimator proposed by Oerder and Meyr achieves asymptotically the best performance in the class of estimators which exploit all the second-order statistics of the received signal, and its performance is insensitive to oversampling rates P as long as P ≥ 3. Further, an asymptotically best consistent estimator, which achieves the lowest asymptotic variance among all the possible estimators that can be derived by exploiting jointly the second- and fourth-order statistics of the received signal, is also proposed.

Original languageEnglish
Pages (from-to)709-715
Number of pages7
JournalIEEE Transactions on Wireless Communications
Issue number3
Publication statusPublished - May 2004
Externally publishedYes



  • Cramér-Rao bound (CRB)
  • Cyclostationarity
  • Maximum likelihood (ML)
  • Synchronization
  • Timing estimation

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Networks and Communications

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