Identifiability of data-aided carrier-frequency offset estimation over frequency selective channels

Feifei Gao*, A. Nallanathan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

Carrier-frequency offset (CFO) must be compensated before channel estimation and coherent detection. Several data-aided CFO estimation algorithms have been proposed recently. However, an improper selection of training sequences may cause the identifiability problem which results in failure of CFO estimation. In this correspondence, we present a detailed study on identifiability issue and derive two new theorems for data-aided CFO estimation. The first theorem is suitable for all training sequences. The second one mainly deals with a popular set of training sequences that is deemed as optimal for channel estimation. Simulation results are provided to validate the proposed study.

Original languageEnglish
Pages (from-to)3653-3657
Number of pages5
JournalIEEE Transactions on Signal Processing
Volume54
Issue number9
DOIs
Publication statusPublished - Sept 2006

Keywords

  • carrier-frequency offset (CFO)
  • channel estimation
  • identifiability
  • orthogonal frequency-division multiplexing (OFDM)
  • preamble
  • OFDM
  • TRANSMISSIONS

Fingerprint

Dive into the research topics of 'Identifiability of data-aided carrier-frequency offset estimation over frequency selective channels'. Together they form a unique fingerprint.

Cite this