Resumo

LOPEZ-PARRADO, Alexander  e  VELASCO-MEDINA, Jaime. Algorithm for wideband spectrum sensing based on sparse Fourier transform. Dyna rev.fac.nac.minas [online]. 2016, vol.83, n.198, pp.79-86. ISSN 0012-7353.  https://doi.org/10.15446/dyna.v83n198.48654.

In this paper we present a novel sub-Nyquist algorithm to perform Wideband Spectrum Sensing (WSS) for Cognitive Radios (CRs) by using the recently developed Sparse Fast Fourier Transform (sFFT) algorithms. In this case, we developed a noise-robust sub-Nyquist WSS algorithm with reduced sampling cost, by modifying the Nearly Optimal sFFT algorithm; this was accomplished by using Gaussian windows with small support. Simulation results show that the proposed algorithm is suitable for hardware implementation of WSS systems for sparse spectrums composed of highly-noisy multiband-signals.

Palavras-chave : Cognitive Radio; Compressed Sensing; Sparse Fourier Transform; Spectrum Sensing.

        · resumo em Espanhol     · texto em Inglês     · Inglês ( pdf )