By Topic

Blind channel identification using robust subspace estimation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
S. Visuri ; Signal Process. Lab., Helsinki Univ. of Technol., Finland ; H. Oja ; V. Koivunen

The paper introduces a robust approach to subspace based blind channel identification. The technique is based on estimating the noise subspace from the sample sign covariance matrix. The theoretical motivation for the technique is shown under the white Gaussian noise assumption. A simulation study is performed to demonstrate the robust performance of the algorithm both in Gaussian and non-Gaussian noise. The results indicate that when the noise is Gaussian, the proposed method has similar good performance as the standard subspace method. When the noise is heavy-tailed, the proposed method outperforms the conventional subspace technique

Published in:

Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on

Date of Conference: