Title :
Adaptive channel estimation for OFDM systems in time-varying non-stationary wireless channels
Author :
Zeng, Jianqiang ; Minn, Hlaing
Author_Institution :
Dept. of Electr. Eng., Univ. of Texas at Dallas, Dallas, TX
fDate :
April 30 2007-May 2 2007
Abstract :
This paper addresses adaptive channel estimation for time-varying mobile wireless channels with nonstationary statistics. We presents a reduced complexity adaptive channel estimator based on a set membership filtering approach known as the Optimal Bounding Ellipsoid (OBE) algorithm. To exploit time and frequency domain correlation properties of the channel in an efficient low-complexity way, we allow only a certain number of most significant channel impulse response taps to pass through time-domain adaptive filters while nulling the remaining taps. We obtain further complexity reduction by means of selective updating of the adaptive filters. Our proposed method overcomes the existing methodspsila drawbacks namely slow convergence, high sensitivity to channel statistics mismatch, and very high complexity. Comparisons with the existing methods (Robust MMSE estimator, adaptive NLMS and RLS estimators) corroborate advantages of our method in non-stationary time-varying wireless channels.
Keywords :
OFDM modulation; adaptive filters; channel estimation; least mean squares methods; mobile radio; time-varying channels; transient response; wireless channels; MMSE estimator; OFDM systems; RLS estimators; adaptive NLMS; adaptive channel estimation; channel impulse response; channel statistics mismatch; mobile wireless channels; nonstationary statistics; optimal bounding ellipsoid algorithm; set membership filtering approach; time-domain adaptive filters; time-varying nonstationary wireless channels; Adaptive filters; Channel estimation; Convergence; Ellipsoids; Filtering algorithms; Frequency domain analysis; OFDM; Statistics; Time domain analysis; Time varying systems;
Conference_Titel :
Sarnoff Symposium, 2007 IEEE
Conference_Location :
Nassau Inn, Princeton, NJ
Print_ISBN :
978-1-4244-2483-2
DOI :
10.1109/SARNOF.2007.4567346