Search for: [Description = "Vacant frequency bands are used in cognitive radio \(CR\) by incorporating the spectrum sensing \(SS\) technique. Spectrum sharing plays a central role in ensuring the effectiveness of CR applications. Therefore, a new multi\-stage detector for robust signal and spectrum sensing applications is introduced here. Initially, the sampled signal is subjected to SNR estimation by using a convolutional neural network \(CNN\). Next, the detection strategy is selected in accordance with the predicted SNR levels of the received signal. Energy detector \(ED\) and singular value\-based detector \(SVD\) are the solutions utilized in the event of high SNR, whilst refined non\-negative matrix factorization \(MNMF\) is employed in the case of low SNR. CNN weights are chosen via the Levy updated sea lion optimization \(LU\-SLNO\) algorithm inspired by the traditional sea lion optimization \(SLNO\) approach. Finally, the outcomes of the selected detectors are added, offering a precise decision on spectrum tenancy and existence of the signal."]

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