Effect of Random Sampling on Spectrum Sensing for Cognitive Radio Networks

Cognitive radio is a system with the potential to overcome the scarcity of available radio spectrum by allowing dynamic access to channels on this spectrum. Since its beginnings, researchers have been working on using this inventive technology to control and manage the spectrum resources. Consequently, this research field has been progressing rapidly and important advances have been made. Spectrum sensing is a key function of cognitive radios that helps prevent the harmful interference with licensed users, as well as identifies the available spectrum to improve its utilization. Several spectrum sensing techniques are found in scientific literature. In this paper, we investigate the effect of the random sampling in spectrum sensing. We propose a spectrum sensing approach based on the Energy Detection and on the Maximum Eigenvalue Detection combined with random sampling. The performance of the proposed approach is evaluated in terms of the Receiver Operating Characteristics curves and in terms of the detection probability for different values of Signal to Noise Ratio. The obtained results are compared to the uniform sampling case to show the added value of random sampling.