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Minimum Eigenvalue Detection for Spectrum Sensing in Cognitive Radio

Authors: Syed Sajjad Ali; Chang Liu; Minglu Jin;

Minimum Eigenvalue Detection for Spectrum Sensing in Cognitive Radio

Abstract

Spectrum sensing is a key task for cognitive radio. Our motivation is to increase the probability of detection for spectrum sensing in cognitive radio. In this paper, we proposed a new semi blind method which is based on minimum Eigenvalue of a covariance matrix. The ratio of the minimum eigenvalue to noise power is used as the test statistic. The method does not need channel and signal information as prior knowledge. Eigenvalue based algorithm perform better than energy detection for correlated signal. Our proposed method is better than the maximum eigenvalue and energy detection for correlated signal. We perform Simulation which is based on digital TV signal. In all tests, our method performs better than maximum eigenvalue detection and energy detection. DOI: http://dx.doi.org/10.11591/ijece.v4i4.6226

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Top 10%
Average
gold