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Nonlinear Dynamics

, Volume 78, Issue 1, pp 703–711 | Cite as

CDKF approach for estimating a static parameter of carrier frequency offset based on nonlinear measurement equations in OFDM systems

  • Jaechan Lim
Original Paper

Abstract

“Central difference Kalman filtering (CDKF)” is proposed as a new state of the art approach for carrier frequency offset estimation in orthogonal frequency division multiplexing systems. The parameter of interest to be estimated in this problem is a static value rather than a dynamically varying parameter. Therefore, classical approaches (e.g., maximum likelihood method or best linear unbiased estimator) might be more pertinent than Bayesian approaches if it is assumed to be a deterministic value. Nonetheless, it is shown and justified that a recently developed extended Kalman variant, i.e., CDKF, outperforms previously proposed methods in terms of mean squared error with efficient processing speed. Particularly, it is shown that CDKF outperforms recently proposed Gaussian particle filter for this one-dimensional static parameter estimation problem.

Keywords

Carrier frequency offset Central difference Kalman filter Dynamic state system Extended Kalman filter Nonlinear model OFDM Particle filter 

Notes

Acknowledgments

This research was supported by “Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education (NRF-2011-0009255)” and “the Ministry of Science, ICT and Future Planning, Korea, under the ‘IT Consilience Creative Program’ (NIPA-2014-H0201-14-1001) supervised by the National IT Industry Promotion Agency.”

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Department of Future IT Innovation LaboratoryPohang University of Science and TechnologyPohangSouth Korea

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