An Energy Approximation Model Based on Restricted Isometry Property in Compressive Spectrum Sensing for Cognitive Radio

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Provided by: Journal of Communications
Topic: Mobility
Format: PDF
Compressive Sensing (CS) has proved to be an effective technique in terms of spectrum sensing of Cognitive Radio (CR). However the signal reconstruction is costly and unnecessary. Through analysis of Restricted Isometry Property (RIP) of CS, it is feasible to detect the primary user directly through the compressed signal. In this paper, a novel Energy Approximation model based on Compressive Spectrum Sensing (EA-CSS) in cognitive radios is proposed. In contrast with the traditional compressive spectrum sensing scheme, this method does not need to reconstruct the original signal and has lower complexity algorithms at the same time.
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