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Spectral feature detection with Sub-Nyquist sampling for wideband spectrum sensing

Autor
Lagunas, E.; Najar, M.
Tipus d'activitat
Article en revista
Revista
IEEE transactions on wireless communications
Data de publicació
2015-07-01
Volum
14
Número
7
Pàgina inicial
3978
Pàgina final
3990
DOI
https://doi.org/10.1109/TWC.2015.2415774 Obrir en finestra nova
Projecte finançador
GRE3N-LINK-MAC. Conceptos radio generales para comunicaciones móviles eficientes energéticamente: aspectos de las capas de enlace y de acceso al medio
Repositori
http://hdl.handle.net/2117/103450 Obrir en finestra nova
URL
http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7065302 Obrir en finestra nova
Resum
Compressive sensing (CS) has been successfully applied to alleviate the sampling bottleneck in wideband spectrum sensing leveraging the sparsity described by the low spectral occupancy of the licensed radios. However, the existence of interferences emanating from low-regulated transmissions, which cannot be taken into account in the CS model because of their non-regulated nature, greatly degrade the identification of licensed activity. This paper presents a feature-based technique for primary us...
Citació
Lagunas, E., Najar, M. Spectral feature detection with Sub-Nyquist sampling for wideband spectrum sensing. "IEEE transactions on wireless communications", 1 Juliol 2015, vol. 14, núm. 7, p. 3978-3990.
Paraules clau
Algorithms, Cognitive radio, Cognitive radio networks, Compressive sensing, Energy detection, Information, Pursuit, Reconstruction, Signal recovery, Spectrum sensing, Sub-Nyquist sampling
Grup de recerca
SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions

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