Compressive multispectral model for spectrum sensing in cognitive radio networks

Jeison A. Marín, Jose I.T. Martinez, Leonardo Betancur, Henry Arguello

    Research output: Chapter in Book/Report/Conference proceedingConference and proceedingspeer-review

    Abstract

    Cognitive Radio (CR) is one of the most promising techniques for optimizing the spectrum usage. However, the large amount of data of spectral information that must be processed to identify and assign spectral resources increases the channel assignment times, therefore worsening the quality of service for the devices using the spectrum. Compressive Sensing (CS) is a digital processing technique that allows the reconstruction of sparse or compressible signals using fewer samples than those required traditionally. This paper presents a model that addresses the Spectral Sensing problem in Cognitive Radio using Compressive Sensing as an effective way of decreasing the number of samples required in the sensing process. This model is based on Compressive Spectral Imaging (CSI) architectures where a centralized spectrum manager selects what power data must be delivered by the different wireless devices using binary patterns, and builds a multispectral data cube image with the geographical and spectral data power information. The results show that this multispectral data cube can be built with only a 50% of the samples generated by the devices and, therefore reducing the data traffic dramatically.

    Original languageEnglish
    Title of host publication25th European Signal Processing Conference, EUSIPCO 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages2571-2575
    Number of pages5
    ISBN (Electronic)9780992862671
    DOIs
    StatePublished - 23 Oct 2017
    Event25th European Signal Processing Conference, EUSIPCO 2017 - Kos, Greece
    Duration: 28 Aug 20172 Sep 2017

    Publication series

    Name25th European Signal Processing Conference, EUSIPCO 2017
    Volume2017-January

    Conference

    Conference25th European Signal Processing Conference, EUSIPCO 2017
    Country/TerritoryGreece
    CityKos
    Period28/08/172/09/17

    Bibliographical note

    Publisher Copyright:
    © EURASIP 2017.

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