DocumentCode :
1675689
Title :
Low-complexity Kalman filter-based carrier frequency offset estimation and tracking for OFDM systems
Author :
Ashour, Mohamed ; El-Keyi, Amr ; Sultan, Ahmed
Author_Institution :
Wireless Intell. Networks Center, Nile Univ., Cairo, Egypt
fYear :
2013
Firstpage :
4923
Lastpage :
4927
Abstract :
In this paper, an iterative blind estimator for fractional carrier frequency offset (CFO) in orthogonal frequency division multiplexing (OFDM) systems is proposed. The estimator utilizes the null subcarriers transmitted at the edge of the spectrum and does not require any training. In addition, the proposed estimator does not require any prior knowledge of the frequency response of the channel. The problem is formulated using a state-space model, and an extended Kalman filter (EKF) is employed to estimate the CFO iteratively. Simulation results illustrate the enhanced ability of the proposed algorithm, relative to the existing approaches, to estimate and track the CFO even in the presence of high Doppler.
Keywords :
Kalman filters; OFDM modulation; frequency response; iterative methods; nonlinear filters; CFO; EKF; OFDM systems; carrier frequency offset estimation; carrier frequency offset tracking; extended Kalman filter; fractional carrier frequency offset; frequency response; high Doppler; iterative blind estimator; iterative estimation; low-complexity Kalman filter; null subcarriers; orthogonal frequency division multiplexing; state-space model; Discrete Fourier transforms; Estimation; Indexes; Kalman filters; OFDM; Time-domain analysis; Vectors; Kalman filter; Orthogonal frequency division multiplexing; carrier frequency offset;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
ISSN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2013.6638597
Filename :
6638597
Link To Document :
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