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21 May 2015 New cognitive detection techniques for multimedia signals
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In this paper we are address two issues regarding cognitive radio spectrum sensing. Spectrum sensing for cognitive radio has been extensively studied in recent past and multiple techniques have been proposed. One such technique is entropy based detection. In entropy based detection we measure the entropy of the received signal after converting it to frequency domain. The logic is that in frequency domain, the entropy of noise (assuming its AWGN) is higher than the signal, thereby enabling us to segment noise from signal by using entropy based threshold. This approach however makes some assumptions which may not be valid. It assumes at a time only one of the two( signal / noise) is present. It further assumes that a given test segment is either a signal or a noise segment. The length of the segment in such a scenario would be fixed /known. These assumptions may be too constraining and we propose alternate method to address the above issues. We use a filtering technique in form of Independent Component Analysis to segment the signal and further use additional techniques like energy weight-age to weigh the components to estimate the signal strength. We test our proposed method for a variety of signals include image, audio and sinusoidal signals. Results show the improvement in performance as well as the availability of new measures as generated from our proposed technique.
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Yixuan Sun and Sumit Chakravarty "New cognitive detection techniques for multimedia signals", Proc. SPIE 9497, Mobile Multimedia/Image Processing, Security, and Applications 2015, 94970R (21 May 2015);


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