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10 - Cognitive radio networks

from Part II - CS-Based Wireless Communication

Published online by Cambridge University Press:  05 June 2013

Zhu Han
Affiliation:
University of Houston
Husheng Li
Affiliation:
University of Tennessee, Knoxville
Wotao Yin
Affiliation:
Rice University, Houston
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Summary

Introduction

Ever since the 1920s, every wireless system has been required to have an exclusive license from the government in order not to interfere with other users of the radio spectrum. Today, with the emergence of new technologies that enable new wireless services, virtually all usable radio frequencies are already licensed to commercial operators and government entities. According to former U.S. Federal Communications Commission (FCC) chair William Kennard we are facing a “spectrum drought” [356]. On the other hand, not every channel in every band is in use all the time; even for premium frequencies below 3 GHz in dense, revenue-rich urban areas, most bands are quiet most of the time. The FCC in the United States and the Ofcom in the United Kingdom, as well as regulatory bodies in other countries, have found that most of the precious, licensed radio-frequency spectrum resources are inefficiently utilized [37, 357].

In order to increase the efficiency of spectrum utilization, diverse types of technologies have been deployed. Cognitive radio is one of those that leads to the greatest technological gain in wireless capacity. Through the detection and utilization of the spectra that are assigned to the licensed users but standing idle at certain times, cognitive radio acts as a key enabler for spectrum sharing. Spectrum sensing, aiming at detecting spectrum holes (i.e., channels not used by any primary users), is the precondition for the implementation of cognitive radio.

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Publisher: Cambridge University Press
Print publication year: 2013

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  • Cognitive radio networks
  • Zhu Han, University of Houston, Husheng Li, University of Tennessee, Knoxville, Wotao Yin, Rice University, Houston
  • Book: Compressive Sensing for Wireless Networks
  • Online publication: 05 June 2013
  • Chapter DOI: https://doi.org/10.1017/CBO9781139088497.011
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  • Cognitive radio networks
  • Zhu Han, University of Houston, Husheng Li, University of Tennessee, Knoxville, Wotao Yin, Rice University, Houston
  • Book: Compressive Sensing for Wireless Networks
  • Online publication: 05 June 2013
  • Chapter DOI: https://doi.org/10.1017/CBO9781139088497.011
Available formats
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Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Cognitive radio networks
  • Zhu Han, University of Houston, Husheng Li, University of Tennessee, Knoxville, Wotao Yin, Rice University, Houston
  • Book: Compressive Sensing for Wireless Networks
  • Online publication: 05 June 2013
  • Chapter DOI: https://doi.org/10.1017/CBO9781139088497.011
Available formats
×