Relevance Vector Machines for Enhanced BER Probability in DMT-Based Systems
Joint Authors
Tahat, Ashraf A.
Galatsanos, Nikolaos P.
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2010, Issue 2010 (31 Dec. 2010), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2010-06-29
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Engineering Sciences and Information Technology
Information Technology and Computer Science
Abstract EN
A new channel estimation method for discrete multitone (DMT) communication system based on sparse Bayesian learning relevance vector machine (RVM) method is presented.
The Bayesian frame work is used to obtain sparse solutions for regression tasks with linear models.
By exploiting a probabilistic Bayesian learning framework, sparse Bayesian learning provides accurate models for estimation and consequently equalization.
We consider frequency domain equalization (FEQ) using the proposed channel estimate at both the transmitter (preequalization) and receiver (postequalization) and compare the resulting bit error rate (BER) performance curves for both approaches and various channel estimation techniques.
Simulation results show that the proposed RVM-based method is superior to the traditional least squares technique.
American Psychological Association (APA)
Tahat, Ashraf A.& Galatsanos, Nikolaos P.. 2010. Relevance Vector Machines for Enhanced BER Probability in DMT-Based Systems. Journal of Electrical and Computer Engineering،Vol. 2010, no. 2010, pp.1-8.
https://search.emarefa.net/detail/BIM-453262
Modern Language Association (MLA)
Tahat, Ashraf A.& Galatsanos, Nikolaos P.. Relevance Vector Machines for Enhanced BER Probability in DMT-Based Systems. Journal of Electrical and Computer Engineering No. 2010 (2010), pp.1-8.
https://search.emarefa.net/detail/BIM-453262
American Medical Association (AMA)
Tahat, Ashraf A.& Galatsanos, Nikolaos P.. Relevance Vector Machines for Enhanced BER Probability in DMT-Based Systems. Journal of Electrical and Computer Engineering. 2010. Vol. 2010, no. 2010, pp.1-8.
https://search.emarefa.net/detail/BIM-453262
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-453262