Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
561710 | Signal Processing | 2009 | 13 Pages |
Abstract
This paper presents two blind identification methods for nonlinear memoryless channels in multiuser communication systems. These methods are based on the parallel factor (PARAFAC) decomposition of a tensor composed of channel output covariances. Such a decomposition is possible owing to a new precoding scheme developed for phase-shift keying (PSK) signals modeled as Markov chains. Some conditions on the transition probability matrices (TPM) of the Markov chains are established to introduce temporal correlation and satisfy statistical correlation constraints inducing the PARAFAC decomposition of the considered tensor. The proposed blind channel estimation algorithms are evaluated by means of computer simulations.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Carlos Alexandre Fernandes, Gérard Favier, João Cesar M. Mota,