Abstract

ASTAIZA HOYOS, Evelio; BERMUDEZ OROZCO, Héctor Fabio  and  MUNOZ, Luis Freddy. Compressive sensing applied to efficient broadband spectrum sensing on cognitive radio systems. Tecnura [online]. 2017, vol.21, n.51, pp.42-56. ISSN 0123-921X.  https://doi.org/10.14483/udistrital.jour.tecnura.2017.1.a03.

Abstract Contex: Spectrum polling is universally known as the main Cognitive Radio (CR) enabler, since it provides the CR device with the ability to know the radio environment. Objetive: This article presents an algorithm design to perform the broadband spectrum probing in Cognitive Radio systems. Method: Spectrum polling is based on Compressive Sensing (CS), by which cognitive users minimize the amount of samples to be processed, without the need for a priori knowledge of signal characteristics in the radio environment. In this way, it is possible to proportionally reduce detection times, power consumption and processing capacity required in cognitive radio devices (CRD). Results: The performance of the proposed algorithm is evaluated by obtaining the probability of detection, the probability of non-detection, the probability of false alarm, and the Receiver Operating Characteristics (ROC), and comparing it with other algorithms proposed in the state of the art. Conclusion: The simulation results demonstrate that the proposed method allows the efficient sampling of the spectrum. This improves the probe performance based on the probability of detection and the Receiver Operating Characteristic ROC, and it is better than the other proposed algorithms based on sub-Nyquist sampling.

Keywords : Convex relaxation; Compressive sensing; Random demodulator; Sampling; Spectrum sensing.

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