DocumentCode :
3535531
Title :
Eigenvalue-based signal detectors performance comparison
Author :
Omar, M.H. ; Hassan, Shoaib ; Nor, S.A.
Author_Institution :
InterNetWorks Res. Group, Univ. Utara Malaysia, Sintok, Malaysia
fYear :
2011
fDate :
2-5 Oct. 2011
Firstpage :
1
Lastpage :
6
Abstract :
The purpose of this paper is to compare the performance of eigenvalue-based signal detectors designed for IEEE 802.22Wireless Regional Area Network (WRAN). Two eigenvalue techniques were studied, which are the eigenvalue decomposition (EVD) and singular value decomposition (SVD). Both techniques were implemented on Matlab as detection algorithms. Using Monte Carlo simulations, we tested the algorithms to compare their performance. We also adopted the maximum-minimum eigenvalue threshold method as the decision statistic for detecting signals. The tests were done for their ability to detect signal, receiver operating characteristics, expected performance, robustness and computational complexity. Empirically, the performance of SVD technique found to be better compared to the EVD technique.
Keywords :
computational complexity; decision theory; eigenvalues and eigenfunctions; radio networks; signal detection; singular value decomposition; EVD technique; IEEE 802.22 wireless regional area network; Matlab detection algorithms; SVD technique; WRAN; computational complexity; decision statistic; eigenvalue decomposition techniques; eigenvalue-based signal detector technique; maximum-minimum eigenvalue threshold method; receiver operating characteristics; singular value decomposition techniques; Cognitive radio; Covariance matrix; Detectors; Eigenvalues and eigenfunctions; Signal to noise ratio; Cognitive radio; performance evaluation; signal detection; singular value decomposition(SVD);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications (APCC), 2011 17th Asia-Pacific Conference on
Conference_Location :
Sabah
Print_ISBN :
978-1-4577-0389-8
Type :
conf
DOI :
10.1109/APCC.2011.6477853
Filename :
6477853
Link To Document :
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