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Eigenvalue decomposition based estimators of carrier frequency offset in multicarrier underwater acoustic communication

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

Abstract

We propose computationally efficient carrier frequency offset estimators for multicarrier underwater acoustic communication using identical pilot tones equi-spaced in the frequency domain. The first estimator uses the phase of the maximal eigenvector of a channel-dependent correlation matrix. Next, the phase of the minimal eigenvector of a channel-independent correlation matrix is combined with the first estimation using a weighted linear least squares principle. The third estimator solves a generalized eigenvalue decomposition problem by jointly considering the two correlation matrices, and then performs a similar second step as the previous estimator. Simulations and pool trials show that the proposed estimators achieve similar performance as common estimation techniques while surpassing them in severe environments.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
Pages3534-3538
Number of pages5
ISBN (Electronic)9781509041176
DOIs
StatePublished - 16 Jun 2017
Event2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - New Orleans, United States
Duration: 5 Mar 20179 Mar 2017

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Conference

Conference2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
Country/TerritoryUnited States
CityNew Orleans
Period5/03/179/03/17

Keywords

  • carrier frequency offset
  • multicarrier communication
  • underwater acoustic communication

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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