By Topic

Channel identification and tracking using alternating projections

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
$31 $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)
Zia, Amin ; Dept. of ECE, McMaster Univ., Hamilton, Ont., Canada ; Reilly, J.P. ; Shirani, S.

In this paper an iterative method for semi-blind MIMO channel identification and tracking is presented. The method is based on results from information geometry; specifically, the alternating projections theorem first proved by Csiszar, which provides a rigorous iterative method for stochastic maximum likelihood estimation. It is demonstrated that the proposed method has similar performance compared to a recently reported method based on the expectation maximization (EM) algorithm. In addition to having a complete analytical solution, the proposed algorithm avoids the complex multidimensional integrations usually found necessary in similar EM-type methods. The result is a much faster implementation.

Published in:

Statistical Signal Processing, 2003 IEEE Workshop on

Date of Conference:

28 Sept.-1 Oct. 2003