DocumentCode :
8076
Title :
Unveiling the Hidden Assumptions of Energy Detector Based Spectrum Sensing for Cognitive Radios
Author :
Umar, Raza ; Sheikh, A.U.H. ; Deriche, M.
Author_Institution :
King Fahd Univ. of Pet. & Miner., Dhahran, Saudi Arabia
Volume :
16
Issue :
2
fYear :
2014
fDate :
Second Quarter 2014
Firstpage :
713
Lastpage :
728
Abstract :
Cognitive radio is a promising solution to current problem of spectrum scarcity. It relies on efficient spectrum sensing. Energy detection is the most dominantly used spectrum sensing approach owing to its low computational complexity and ability to identify spectrum holes without requiring a priori knowledge of primary transmission characteristics. This paper offers a comprehensive tutorial on energy detection based spectrum sensing and presents an in depth analysis of the test statistic for energy detector. General structure of the test statistic and corresponding threshold are presented to address existing ambiguities in the literature. The derivation of exact distribution of the test statistic, reported in the literature, is revisited and hidden assumptions on the primary user signal model are unveiled. In addition, the scope of detection probability results is discussed for identifying various classes of random primary transmissions. Gaussian approximations of the test statistic are investigated. Specifically, the roles of signal to noise ratio and performance constraint in terms of probability of detection or false alarm are highlighted when Normal approximations are used in place of exact expressions.
Keywords :
Gaussian processes; approximation theory; cognitive radio; computational complexity; radio spectrum management; signal detection; telecommunication power management; Gaussian approximations; cognitive radios; computational complexity; depth analysis; detection probability; energy detector; hidden assumptions; normal approximations; signal model; spectrum scarcity; spectrum sensing; test statistic; transmission characteristics; Detectors; Fading; Measurement; Noise; Uncertainty; Cognitive radio; Gaussian approximations; cooperative sensing; energy detector; hidden assumptions; noise uncertainty; probability of detection; probability of false alarm; spectrum sensing; test statistics;
fLanguage :
English
Journal_Title :
Communications Surveys & Tutorials, IEEE
Publisher :
ieee
ISSN :
1553-877X
Type :
jour
DOI :
10.1109/SURV.2013.081313.00054
Filename :
6599063
Link To Document :
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