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http://dx.doi.org/10.3837/tiis.2018.11.012

Scaled-Energy Based Spectrum Sensing for Multiple Antennas Cognitive Radio  

Azage, Michael Dejene (Department of Electrical and Computer Engineering, Ajou University)
Lee, Chaewoo (Department of Electrical and Computer Engineering, Ajou University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.12, no.11, 2018 , pp. 5382-5403 More about this Journal
Abstract
In this paper, for a spectrum sensing purpose, we heuristically established a test statistic (TS) from a sample covariance matrix (SCM) for multiple antennas based cognitive radio. The TS is formulated as a scaled-energy which is calculated as a sum of scaled diagonal entries of a SCM; each of the diagonal entries of a SCM scaled by corresponding row's Euclidean norm. On the top of that, by combining theoretical results together with simulation observations, we have approximated a decision threshold of the TS which does not need prior knowledge of noise power and primary user signal. Furthermore, simulation results - which are obtained in a fading environment and in a spatially correlating channel model - show that the proposed method stands effect of noise power mismatch (non-uniform noise power) and has significant performance improvement compared with state-of-the-art test statistics.
Keywords
Cognitive radio; noise power mismatch; sample covariance matrix; scaled energy; spectrum sensing;
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