DocumentCode :
302926
Title :
Performance comparison of three methods for blind channel identification
Author :
Qiu, Wanzhi ; Hua, Yingbo
Author_Institution :
Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia
Volume :
5
fYear :
1996
fDate :
7-10 May 1996
Firstpage :
2423
Abstract :
We study the performance of the subspace (SS), cross-relation (CR) and two-step maximum likelihood (TSML) methods for estimating the impulse responses of multiple FIR channels driven by an unknown input sequence. Assuming a large data size or/and a high SNR, the estimation variances of the SS and CR methods are derived. The performances of the three methods are studied and compared against the Cramer-Rao bound (CRB). It is shown that the TSML method significantly outperforms the SS and CR methods and attains the CRB over a wide range of SNR. It is also shown that the SS method is more robust to ill channel conditions than the CR method, while the two methods show nearly identical performances for well-conditioned channels
Keywords :
FIR filters; equalisers; filtering theory; maximum likelihood estimation; signal processing; telecommunication channels; CRB; Cramer-Rao bound; blind channel identification; channel conditions; cross-relation method; estimation variances; high SNR; ill conditioned channels; impulse response estimation; input sequence; large data size; multiple FIR channels; performance comparison; signal processing; subspace methods; two-step maximum likelihood method; well conditioned channels; Chromium; Finite impulse response filter; Image analysis; Image sequence analysis; Maximum likelihood estimation; Mobile communication; Robustness; Signal analysis; Signal processing; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on
Conference_Location :
Atlanta, GA
ISSN :
1520-6149
Print_ISBN :
0-7803-3192-3
Type :
conf
DOI :
10.1109/ICASSP.1996.547952
Filename :
547952
Link To Document :
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