Modulation recognition for MIMO relaying ...
Document type :
Compte-rendu et recension critique d'ouvrage
Title :
Modulation recognition for MIMO relaying broadcast channels with direct link
Author(s) :
Ben Chikha, Wassim [Auteur]
Dayoub, Iyad [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Hamouda, Walaa [Auteur]
Concordia University [Montreal]
Attia, Rabah [Auteur]
Dayoub, Iyad [Auteur]

Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Hamouda, Walaa [Auteur]
Concordia University [Montreal]
Attia, Rabah [Auteur]
Journal title :
IEEE Wireless Communications Letters
Pages :
50-53
Publisher :
IEEE comsoc
Publication date :
2014
ISSN :
2162-2337
English keyword(s) :
higher order statistics
multiple-input multiple-output relaying broadcast channels
modulation identification
multilayer perceptron
decision tree
spatial multiplexing
multiple-input multiple-output relaying broadcast channels
modulation identification
multilayer perceptron
decision tree
spatial multiplexing
English abstract : [en]
In this letter, we investigate the performance of modulation identification based on pattern recognition approach using the decision tree (J48) classifier, for multiple-inputmultipleoutput (MIMO) relaying broadcast channels ...
Show more >In this letter, we investigate the performance of modulation identification based on pattern recognition approach using the decision tree (J48) classifier, for multiple-inputmultipleoutput (MIMO) relaying broadcast channels with direct link (source-to-destination). The proposed system identifies the modulation type and order among different M-ary shift-keying linear modulations used by broadband technologies such as long term evolution-advanced (LTE-A) and worldwide interoperability for microwave access (WiMAX). The system under study employs features extraction based on higher order statistics (HOS) of the received signal. Based on receiver operating characteristic (ROC) curves, our study shows that J48 classifier is more efficient than the multilayer perceptron (MLP) classifier trained with resilient backpropagation training algorithm (RPROP) where it achieves close to perfect detection rate (over 99%) with reasonable training time in acceptable signal-to-noise ratio (SNR) range. We also show that the performance of the MIMO relaying broadcast network is remarkably better than the traditional MIMO one.Show less >
Show more >In this letter, we investigate the performance of modulation identification based on pattern recognition approach using the decision tree (J48) classifier, for multiple-inputmultipleoutput (MIMO) relaying broadcast channels with direct link (source-to-destination). The proposed system identifies the modulation type and order among different M-ary shift-keying linear modulations used by broadband technologies such as long term evolution-advanced (LTE-A) and worldwide interoperability for microwave access (WiMAX). The system under study employs features extraction based on higher order statistics (HOS) of the received signal. Based on receiver operating characteristic (ROC) curves, our study shows that J48 classifier is more efficient than the multilayer perceptron (MLP) classifier trained with resilient backpropagation training algorithm (RPROP) where it achieves close to perfect detection rate (over 99%) with reasonable training time in acceptable signal-to-noise ratio (SNR) range. We also show that the performance of the MIMO relaying broadcast network is remarkably better than the traditional MIMO one.Show less >
Language :
Anglais
Popular science :
Non
Source :