Blind primary user identification in MIMO ...
Document type :
Communication dans un congrès avec actes
DOI :
Title :
Blind primary user identification in MIMO cognitive networks
Author(s) :
Ghosh, A. [Auteur]
Electrical and Computer Engineering Department [Concordia] [ECE]
Hamouda, W. [Auteur]
Electrical and Computer Engineering Department [Concordia] [ECE]
Dayoub, Iyad [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Electrical and Computer Engineering Department [Concordia] [ECE]
Hamouda, W. [Auteur]
Electrical and Computer Engineering Department [Concordia] [ECE]
Dayoub, Iyad [Auteur]

Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Conference title :
IEEE International Conference on Communications, IEEE ICC 2013
City :
Budapest
Country :
Hongrie
Start date of the conference :
2013
Book title :
Proceedings of IEEE International Conference on Communications, IEEE ICC 2013, Session SPC-01 : Estimation and Detection I
Publication date :
2013
English keyword(s) :
Cognitive networks
MIMO
blind identification
artificial neural networks
MIMO
blind identification
artificial neural networks
English abstract : [en]
Early detection of primary users presence is one of the most important tasks for cognitive communication. Also, in cognitive settings cognitive nodes may receive signals from primary users and from other cognitive users ...
Show more >Early detection of primary users presence is one of the most important tasks for cognitive communication. Also, in cognitive settings cognitive nodes may receive signals from primary users and from other cognitive users simultaneously. For such scenario, we propose primary user signal detection using modulation class identification method. We consider multiple transmit and multiple receive antennas for cognitive nodes. We employ Artificial Neural Network (ANN) for the modulation identification purpose. The proposed algorithm works as higher order moments and cumulants are calculated from the received signal samples at each of the receiving branches of cognitive nodes. After this step, these features are fed to the ANN to determine the presence of primary users. Final identification decision is drawn using the decision from all receiving branches. We also present numerical results of our algorithm and compare these results with the theoretical results of the energy detection algorithm.Show less >
Show more >Early detection of primary users presence is one of the most important tasks for cognitive communication. Also, in cognitive settings cognitive nodes may receive signals from primary users and from other cognitive users simultaneously. For such scenario, we propose primary user signal detection using modulation class identification method. We consider multiple transmit and multiple receive antennas for cognitive nodes. We employ Artificial Neural Network (ANN) for the modulation identification purpose. The proposed algorithm works as higher order moments and cumulants are calculated from the received signal samples at each of the receiving branches of cognitive nodes. After this step, these features are fed to the ANN to determine the presence of primary users. Final identification decision is drawn using the decision from all receiving branches. We also present numerical results of our algorithm and compare these results with the theoretical results of the energy detection algorithm.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Source :