DocumentCode :
1535844
Title :
Blind estimation of multipath channel parameters: a modal analysis approach
Author :
Kang, Insung ; Fitz, Michael P. ; Gelfand, Saul B.
Author_Institution :
Network Solution Sectors, Motorola Inc., Arlington Heights, IL, USA
Volume :
47
Issue :
8
fYear :
1999
fDate :
8/1/1999 12:00:00 AM
Firstpage :
1140
Lastpage :
1150
Abstract :
We propose a novel approach to efficiently estimate multipath channel parameters, which is particularly useful in sparse multipath channels. Conventional methods do not fully exploit the inherent structure present in the combined channel response; the excess number of parameters to be estimated by conventional methods makes the identification difficult. By utilizing a priori knowledge of the transmission data pulse, the channel identification problem is transformed into the mode estimation problem. Then, the parameters directly related to the multipath propagation are extracted in the the modal analysis framework, and hence, the number of estimation parameters are significantly reduced. Finally, the multipath channel parameters are obtained by inverse-transforming the mode parameters. Simulation results show significant improvement in the normalized mean square error over existing approaches
Keywords :
blind equalisers; data communication; modal analysis; multipath channels; parameter estimation; HDTV channel; blind estimation; channel identification problem; combined channel response; estimation parameters; high-speed wireless digital communications; modal analysis; mode estimation problem; multipath channel parameters; multipath propagation; normalized mean square error; simulation results; transmission data pulse; Adaptive equalizers; Communication systems; Data communication; Data mining; Frequency domain analysis; HDTV; Mean square error methods; Modal analysis; Multipath channels; Parameter estimation;
fLanguage :
English
Journal_Title :
Communications, IEEE Transactions on
Publisher :
ieee
ISSN :
0090-6778
Type :
jour
DOI :
10.1109/26.780450
Filename :
780450
Link To Document :
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