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Proceedings Paper

Improvement of the linear blind channel identification algorithms based on second-order statistics
Author(s): Yiling Xu; Qicong Peng; Yubai Li
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Paper Abstract

The main blind channel identification methods based on second order statistics include linear prediction algorithm (LPA), outer product decomposition algorithm (OPDA), multi-step linear prediction algorithm (MSLP), least square smoothing algorithm (LSS), and constrained minimum output energy algorithm (CMOE). But the simulations show that the channel couldn't be identified. This paper will analyze these algorithms and point out the reason. The problem happens at the second step. The method based on second order statistics induces an unidentified sign and an indeterminable scale that result in the failure of channel identification. This problem can be resolved in the digital communication system.

Paper Details

Date Published: 28 April 2004
PDF: 4 pages
Proc. SPIE 5284, Wireless Communications and Networks, (28 April 2004); doi: 10.1117/12.514691
Show Author Affiliations
Yiling Xu, Univ. of Electronic Science and Technology of China (China)
Qicong Peng, Univ. of Electronic Science and Technology of China (China)
Yubai Li, Univ. of Electronic Science and Technology of China (China)

Published in SPIE Proceedings Vol. 5284:
Wireless Communications and Networks
Chih-Lin I; Jiann-An Tsai; Hequan Wu, Editor(s)

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