NDLI: Robust spectrum sensing based on spectral flatness measure

Content Provider	IET Digital Library
Author	Gurugopinath, S. Muralishankar, R. Shankar, H. N.
Abstract	The authors investigate the spectral flatness measure (SFM)-based spectrum sensing technique for cognitive radios. This scheme exploits the fact that under Gaussian noise, the noise-only observations have flattened spectrum, i.e. more white, when compared with that of the observations containing the incumbent or primary signal; hence, an increased SFM under the null hypothesis. Under the null hypothesis, the authors derive the asymptotic distribution of the test statistic, and the asymptotically optimal detection threshold, with a constraint on the probability of false-alarm. Furthermore, the authors show that this test is robust to the noise variance uncertainty (NVU) and is related to a test based on the entropy in the observed sequence. Through extensive Monte-Carlo simulations, the authors show that the test based on SFM performs better than the existing energy detector and the blind detector, under realistic signal and fading models, all in the presence of NVU. The authors also highlight the practical utility of this technique based on experimental results.
Starting Page	890
Ending Page	892
Page Count	3
ISSN	00135194
Volume Number	53
e-ISSN	1350911X
Issue Number	Issue 13, Jun (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/53/13
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2016.4712
Journal	Electronics Letters
Publisher Date	2017-05-15
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Asymptotic Distribution Asymptotically Optimal Detection Threshold Blind Detector Cognitive Radio Cognitive Radios Energy Detector Entropy Fading Model False-alarm Probability Gaussian Noise Monte Carlo Method Monte Carlo Simulation Method Noise Variance Uncertainty Null Hypothesis NVC Probability Radio Link And Equipment Radio Spectrum Management Robust Spectrum Sensing SFM Signal Detection Spectral Flatness Measure Statistical Distribution Statistical Testing
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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