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Paper:SPCOM-P9.6
Session:(Semi)blind Techniques II
Time:Thursday, May 20, 15:30 - 17:30
Presentation: Poster
Topic: Signal Processing for Communications: (Blind/Semiblind) Channel Estimation
Title: AN INFORMATION GEOMETRIC APPROACH TO CHANNEL IDENTIFICATION
Authors: Amin Zia; McMaster University 
 James P. Reilly; McMaster University 
 Shahram Shirani; McMaster University 
Abstract: In this paper, the semi-blind MIMO channel identification problem is modelled as a \emph{stochastic} maximum likelihood estimation problem and an iterative method, called information geometric identification (IGID), for channel identification and tracking is presented. The method is developed based on the results from information geometry; specifically, the alternatingprojections theorem first proved by Csiszar. It is demonstrated that the proposed method has similar performance compared to a recently reported method based on the expectation maximization (EM) algorithm. Since the IGID method has an analytical solution, the proposed algorithm can be implemented much faster while while having a similar performance. The method can be considered as a generalization of all the methods developed based on the EM algorithm.
 
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