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The problem of multiple antenna spectrum sensing in cognitive radio (CR) networks is studied in this paper. We propose two new invariant constant false-alarm rate eigenvalue-based (EVB) detectors, using the higher order moments of the sample covariance matrix eigenvalues, by exploiting the separating function estimation test framework. We find closed-form expressions for the false-alarm and detection...
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 order to improve the detection probability of weak signals, a new eigenvalue-based detection scheme is used in cognitive radio system and attracts more attention. The limited distribution of the largest and the smallest eigenvalues is studied in the same framework based on Random Matrix Theory, and used to set the decision thresholds accordingly. A spectrum sensing scheme based on receiver nodes...
One of the key problems in cognitive radio (CR) is the detection of primary activity in order to determine which parts of the spectrum are available for opportunistic access. In this work, we present a new multiantenna detector which fully exploits the spatial and temporal structure of the signals. In particular, we derive the generalized likelihood ratio test (GLRT) for the problem of detecting a...
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