Compressive Spectrum Sensing Front-ends for Cognitive Radios Conference Paper

abstract

• We propose a novel parallel mixed-signal compressive spectrum sensing architecture for Cognitive Radios (CRs) with a detailed study of the signal modeling. The mixed-signal compressive sensing is realized with a parallel segmented compressive sensing (PSCS) architecture, which not only can filter out all the harmonic spurs that leak from the local random generator, but also provides a tradeoff between the sampling rate and the system complexity such that a practical hardware implementation is possible. We consider application of the architecture to do spectrum estimation, which is the first step for spectrum sensing in CRs. The benefit of prior knowledge about the input signal's structure is explored and it is shown that this can be exploited in the PSCS architecture to greatly reduce the sampling rate. 2009 IEEE.

name of conference

• 2009 IEEE International Conference on Systems, Man and Cybernetics

authors

• Hoyos, Sebastian

published proceedings

• 2009 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2009), VOLS 1-9

author list (cited authors)

• Yu, Z., & Hoyos, S.

citation count

• 9

complete list of authors

• Yu, Zhuizhuan||Hoyos, Sebastian

publication date

• October 2009

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• Conference proceedings / IEEE International Conference on Systems, Man, and Cybernetics. IEEE International Conference on Systems, Man, and Cybernetics  Journal

keywords

• Cognitive Radio
• Compact Signal Modeling
• Compressive Sensing
• Mixed-signal
• Spectrum Sensing

Digital Object Identifier (DOI)

• 10.1109/ICSMC.2009.5346164

International Standard Book Number (ISBN) 13

• 978-1-4244-2793-2

start page

• 1899

end page

• 1904

URL

• http%3A%2F%2Fdx.doi.org%2F10.1109%2Ficsmc.2009.5346164