Compressive wideband spectrum sensing with spectral prior information

Daniel Romero, Roberto Lopez-Valcarce, Geert Leus

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Wideband spectrum sensing provides a means to determine the occupancy of channels spanning a broad range of frequencies. Practical limitations impose that the acquisition should be accomplished at a low rate, much below the Nyquist lower bound. Dramatic rate reductions can be obtained by the observation that only a few parameters need to be estimated in typical spectrum sensing applications. This paper discusses the joint estimation of the power of a number of channels, whose power spectral density (PSD) is known up to a scale factor, using compressive measurements. First, relying on a Gaussian assumption, an efficient approximate maximum likelihood (ML) technique is presented. Next, a least-squares estimator is applied for the general non-Gaussian case.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages4469-4473
Number of pages5
DOIs
StatePublished - Oct 18 2013
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: May 26 2013May 31 2013

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
CountryCanada
CityVancouver, BC
Period5/26/135/31/13

Keywords

  • Analog-to-Information Conversion
  • Maximum Likelihood Estimation
  • Spectrum Sensing

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    Romero, D., Lopez-Valcarce, R., & Leus, G. (2013). Compressive wideband spectrum sensing with spectral prior information. In 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings (pp. 4469-4473). [6638505] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2013.6638505