DocumentCode
1243052
Title
Adaptive power techniques for blind channel estimation in CDMA systems
Author
Doukopoulos, Xenofon G. ; Moustakides, George V.
Author_Institution
IRISA-INRIA, Univ. of Rennes, France
Volume
53
Issue
3
fYear
2005
fDate
3/1/2005 12:00:00 AM
Firstpage
1110
Lastpage
1120
Abstract
The problem of blind adaptive channel estimation in code-division multiple access (CDMA) systems is considered. Motivated by the iterative power method, which is used in numerical analysis for estimating singular values and singular vectors, we develop recursive least squares (RLS) and least mean squares (LMS) subspace-based adaptive algorithms in order to identify the impulse response of the multipath channel. The schemes proposed in this paper use only the spreading code of the user of interest and the received data and are therefore blind. Both versions (RLS and LMS) exhibit rapid convergence combined with low computational complexity. With the help of simulations, we demonstrate the improved performance of our methods as compared with the already-existing techniques in the literature.
Keywords
channel estimation; code division multiple access; computational complexity; convergence; iterative methods; least mean squares methods; multipath channels; recursive estimation; transient response; AWGN channel; CDMA system; adaptive power technique; blind channel estimation; code-division multiple access; computational complexity; convergence; impulse response; iterative power method; least mean squares method; multipath channel; recursive least squares method; singular vector estimation; spreading code; Adaptive algorithm; Blind equalizers; Channel estimation; Iterative methods; Least squares approximation; Multiaccess communication; Multipath channels; Numerical analysis; Recursive estimation; Resonance light scattering; Blind adaptive algorithms; CDMA; LMS; RLS; channel estimation;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/TSP.2004.842187
Filename
1396440
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