DocumentCode :
2565311
Title :
Spectrum sensing with multiple antennas
Author :
Ruttik, Kalle ; Koufos, Konstantinos ; Jäntti, Riku
Author_Institution :
Commun. & Networking Dept., Helsinki Univ. of Technol., Espoo, Finland
fYear :
2009
fDate :
11-14 Oct. 2009
Firstpage :
2281
Lastpage :
2286
Abstract :
The primary signal detection is an essential operation for the secondary spectrum usage. In this paper we extend the covariance based detection for multiple-antenna receiver. The proposed method uses the noise power estimation and does not suffer from the noise level uncertainty. We analyze the detection algorithm and compute the distribution of the decision variable not only for the pure noise case but also for the jointly presence of primary signal and noise. By deriving the distribution of the primary signal in noise we are able to use the detection probability as the detector design constraint. Our analysis takes advantage of the high amount of samples available at the detector. The proposed method sets the foundation for the analysis of any detector that involves cross correlation, summing and squaring operations of samples.
Keywords :
antenna arrays; cognitive radio; correlation methods; covariance analysis; decision theory; frequency allocation; probability; radio receivers; signal detection; cognitive radio; covariance-based detection; crosscorrelation method; decision variable distribution; detection probability; multiple-antenna receiver; noise level uncertainty; noise power estimation; primary signal detection; primary signal distribution; secondary spectrum usage; spectrum sensing; squaring operation; summing operation; Covariance matrix; Detectors; Distributed computing; Noise level; Signal analysis; Signal detection; Statistical analysis; Statistical distributions; Testing; Uncertainty; Signal detection; covariance analysis; probability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
Conference_Location :
San Antonio, TX
ISSN :
1062-922X
Print_ISBN :
978-1-4244-2793-2
Electronic_ISBN :
1062-922X
Type :
conf
DOI :
10.1109/ICSMC.2009.5345966
Filename :
5345966
Link To Document :
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