Simple and Accurate Closed-Form Approximation of the Standard Condition Number Distribution with Application in Spectrum Sensing

Hussein Kobeissi 1 Amor Nafkha 1 Youssef Nasser 2 Oussama Bazzi 3 Yves Louët 1
1 IETR - Institut d'Electronique et de Télécommunications de Rennes
2 ECE Department
3 Department of Physics and Electronics
Abstract : "Standard condition number (SCN) detector is a promising detector that can work e ectively in uncertain environments. In this paper, an accurate and simple closed form approximation of the con- dition number distribution is provided using the generalized extreme value (GEV) distribution. The approximation framework is based on the moment-matching method and used to perform spectrum sensing for asymptotic matrix dimension. The expressions of the moments are approximated using bi-variate Taylor expansion and results from random matrix theory. Through intensive simulations, it is shown that the derived approximation is tightly matched to the condition number distribution."
Type de document :
Communication dans un congrès
11th EAI International Conference on Cognitive Radio Oriented Wireless Networks, Jun 2016, Grenoble, France. 2016
Liste complète des métadonnées
https://hal-centralesupelec.archives-ouvertes.fr/hal-01318207
Contributeur : Myriam Andrieux <>
Soumis le : jeudi 19 mai 2016 - 13:27:35
Dernière modification le : mercredi 16 mai 2018 - 11:23:50

Identifiants

  • HAL Id : hal-01318207, version 1

Collections

IETR | IETR_SCEE | UNIV-NANTES | SUP_IETR | CENTRALESUPELEC | SUP_SCEE | UR1-UFR-ISTIC | UNIV-RENNES

Citation

Hussein Kobeissi, Amor Nafkha, Youssef Nasser, Oussama Bazzi, Yves Louët. Simple and Accurate Closed-Form Approximation of the Standard Condition Number Distribution with Application in Spectrum Sensing . 11th EAI International Conference on Cognitive Radio Oriented Wireless Networks, Jun 2016, Grenoble, France. 2016. 〈hal-01318207〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

850

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD