Asymptotically optimal blind fractionally spaced channel estimation and performance analysis

Georgios B. Giannakis, Steven D. Haiford

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

When the received data are fractionally sampled, the magnitude and phase of most linear time-invariant FIR communications channels can be estimated from second-order output-only statistics. We present a general cyclic correlation matching algorithm for known order FIR blind channel identification that has closed-form expressions for calculating the asymptotic variance of the channel estimates. We show that for a particular choice of weights, the weighted matching estimator yields (at least for large samples) the minimum variance channel estimator among all unbiased estimators based on second-order statistics. Furthermore, the matching approach, unlike existing methods, provides a useful estimate even when the channel is not uniquely identifiable from second-order statistics.

Original languageEnglish (US)
Pages (from-to)1815-1830
Number of pages16
JournalIEEE Transactions on Signal Processing
Volume45
Issue number7
DOIs
StatePublished - 1997

Bibliographical note

Funding Information:
Manuscript received October 16, 1995, revised December 9, 1996. This work was supported by ONR Grant N00014-93-0485. Part of the work in this paper was presented at the Conference of Information Science and Systems, Princeton, NJ, March 1994 and at Milcom ‘94, Ft. Monmouth, NJ, October 1994. The associate editor coordinating the review of this paper and approving it for publication was Dr. Zhi Ding.

Keywords

  • Cyclostationarity
  • Fractional sampling
  • System identification

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