A Simple formulation for the Distribution of the Scaled Largest Eigenvalue and application to 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 : "Scaled largest eigenvalue (SLE) detector stands out as the best single-primary-user detector in uncertain noisy environments. In this paper, we consider a multi-antenna cognitive radio system in which we aim at detecting the presence/absence of a primary user (PU) using the SLE detector. We study the distribution of the SLE as a large num- ber of samples are used in detection without constraint on the number of antennas. By the exploitation of the distributions of the largest eigen- value and the trace of the receiver sample covariance matrix, we show that the SLE could be modeled as a normal random variable. Moreover, we derive the distribution of the SLE and deduce a simple yet accurate form of the probability of false alarm. Hence, this derivation yields a very simple form of the detection threshold. The analytical derivations are validated through extensive Monte Carlo simulations."
Document type :
Conference papers
Complete list of metadatas
https://hal-centralesupelec.archives-ouvertes.fr/hal-01318205
Contributor : Myriam Andrieux <>
Submitted on : Thursday, May 19, 2016 - 1:21:46 PM
Last modification on : Monday, April 8, 2019 - 11:50:04 AM

Identifiers

  • HAL Id : hal-01318205, version 1

Collections

IETR | IETR_SCEE | UNIV-NANTES | UNIV-RENNES1 | SUP_IETR | CENTRALESUPELEC | SUP_SCEE | UR1-UFR-ISTIC | UNIV-RENNES | INSA-GROUPE

Citation

Hussein Kobeissi, Amor Nafkha, Youssef Nasser, Oussama Bazzi, Yves Louët. A Simple formulation for the Distribution of the Scaled Largest Eigenvalue and application to Spectrum Sensing . 11th EAI International Conference on Cognitive Radio Oriented Wireless Networks, Jun 2016, Grenoble, France. ⟨hal-01318205⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

1331

Contact

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