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In cognitive radio spectrum sensing is a fundamental problem. Under the case of uncorrelated noise different methods are used for spectrum sensing. In this paper we compare the performance of MP and eigenvalue based methods. In eigenvalue based method we find the threshold using random matrix theory (RMT). Marchenko-Pastur (MP) method use standard condition number (SCN) to find the threshold. Here...
In cognitive radio, the spectrum sensing plays a key role in determining the performance of both the primary and the secondary networks. The eigenvalue based detection (EbD) algorithm has received broad attentions, since it shows significant robustness to the noise uncertainty problem. However, in EbD algorithm, it is quite difficult to obtain the distribution for the eigenvalues of the statistic...
Spectrum sensing is a fundamental component in a cognitive radio. In this paper, we propose new sensing methods based on the eigenvalues of the covariance matrix of signals received at the secondary users. In particular, two sensing algorithms are suggested, one is based on the ratio of the maximum eigenvalue to minimum eigenvalue; the other is based on the ratio of the average eigenvalue to minimum...
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