IDEAS home Printed from https://ideas.repec.org/a/spr/joptap/v168y2016i1d10.1007_s10957-014-0656-x.html
   My bibliography  Save this article

Energy-Efficient Sensing for Delay-Constrained Cognitive Radio Systems Via Convex Optimization

Author

Listed:
  • Hang Hu

    (PLA University of Science and Technology)

  • Hang Zhang

    (PLA University of Science and Technology)

  • Hong Yu

    (PLA University of Science and Technology)

Abstract

Spectrum sensing is a critical issue in cognitive radio (CR) systems. When the energy of the CR system is constrained, using the energy efficiently is an important problem, which must be considered. In this paper, the energy efficiency is defined as the ratio of average spectrum efficiency of the CR system over average power consumed by the CR system. We consider a joint optimization of sensing time and power allocation to maximize the energy efficiency under the condition of sufficient protection to primary user and the delay constraint. It is demonstrated that convex optimization plays an essential role in solving the problem. An efficient iterative algorithm is proposed to obtain the optimal values. Then, we propose a block sensing scheme in which several adjacent frames are bundled as a block. Our results show that significant improvement in the energy efficiency is obtained via joint optimization of sensing time and power allocation. The energy efficiency and the delay performance can be further improved by using the proposed block sensing scheme.

Suggested Citation

  • Hang Hu & Hang Zhang & Hong Yu, 2016. "Energy-Efficient Sensing for Delay-Constrained Cognitive Radio Systems Via Convex Optimization," Journal of Optimization Theory and Applications, Springer, vol. 168(1), pages 310-331, January.
    • Handle: RePEc:spr:joptap:v:168:y:2016:i:1:d:10.1007_s10957-014-0656-x
    DOI: 10.1007/s10957-014-0656-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10957-014-0656-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10957-014-0656-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:joptap:v:168:y:2016:i:1:d:10.1007_s10957-014-0656-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.