Spectral feature detection with Sub-Nyquist sampling for wideband spectrum sensing
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 c...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/103450 |
| Acceso en línea: | https://hdl.handle.net/2117/103450 https://dx.doi.org/10.1109/TWC.2015.2415774 |
| Access Level: | acceso abierto |
| Palabra clave: | Mobile communication systems Radio frequency Sub-Nyquist sampling Spectrum sensing Cognitive radio Compressive sensing Cognitive radio networks Energy detection Signal recovery Pursuit Reconstruction Information Algorithms Comunicacions mòbils, Sistemes de Radiofreqüència Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal |
| Sumario: | 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 user's spectrum identification with interference immunity which works with a reduced amount of data. The proposed method not only detects which frequencies are occupied by primary users' but also identifies the primary users' transmitted power. The basic strategy is to compare the a priori known spectral shape of the primary user with the power spectral density of the received signal. This comparison ismade in terms of autocorrelation by means of a correlation matching, thus avoiding the computation of the power spectral density of the received signal. The essence of the novel interference rejection mechanism lies in preserving the positive semidefinite character of the residual correlation, which is inserted by means of a weighted formulation of the l(1)-minimization. Simulation results show the effectiveness of the technique for interference suppression and primary user detection. |
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