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Compressive spectrum sensing based on spectral shape feature detection
Lagunas, Eva; Nájar Martón, Montserrat
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions
In this paper, we address sparsity-based spectrum sensing for Cognitive Radio (CR) applications. Motivated by the sparsity described by the low spectral occupancy of the licensed radios, the proposed approach utilizes the novel Compressive Sensing (CS) technique to alleviate the sampling burden in CR when processing very wide bandwidth. Instead of detecting underutilized subbands of the radio spectrum, this paper propose a feature-based strategy to detect the licensed holder activity from compressive measurements. The procedure follows the framework of correlation matching, changing the traditional single frequency scan to a spectral scan with the a priori known spectral shape of the licensed holder. In addition to the frequencylocation estimate, the proposed technique is able to provide a power-level estimate and an estimation of the angle-of-arrival (AoA) of the primary users by circumventing the complex nonlinear CS reconstruction.
Peer Reviewed
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica
Wireless communication systems
Cognitive radio networks
Comunicació sense fil, Sistemes de
Ràdio cognitiva
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
Institute of Electrical and Electronics Engineers (IEEE)
         

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