skip to main content
10.1145/2093256.2093260acmotherconferencesArticle/Chapter ViewAbstractPublication PagescogartConference Proceedingsconference-collections
research-article

Modeling and simulation of joint time-frequency properties of spectrum usage in cognitive radio

Published:26 October 2011Publication History

ABSTRACT

The development of the Dynamic Spectrum Access/Cognitive Radio (DSA/CR) technology can significantly benefit from the availability of realistic models able to accurately capture and reproduce the statistical properties of spectrum usage in real wireless communication systems. Relying on field measurements of real systems, this paper analyzes the joint time-frequency statistical properties of spectrum usage and develops adequate models describing the observed characteristics. Based on such models, a sophisticated method is also proposed to generate artificial spectrum data for simulation or other purposes. The proposed method is able to accurately reproduce the statistical time-frequency characteristics of spectrum usage in real systems.

References

  1. I. F. Akyildiz, W.-Y. Lee, M. C. Vuran, and S. Mohanty. NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey. Comp. Networks, 50(13):2127--2159, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. M. C. Jones. Kumaraswamy's distribution: A beta-type distribution with some tractability advantages. Statistical Methodology, 6(1):70--81, Jan. 2009.Google ScholarGoogle ScholarCross RefCross Ref
  3. P. Kumaraswamy. A generalized probability density function for double-bounded random processes. Journal of Hydrology, 46(1--2):79--88, Mar. 1980.Google ScholarGoogle ScholarCross RefCross Ref
  4. M. López-Benítez and F. Casadevall. Methodological aspects of spectrum occupancy evaluation in the context of cognitive radio. European Trans. on Telecomms., 21(8):680--693, 2010.Google ScholarGoogle ScholarCross RefCross Ref
  5. M. López-Benítez and F. Casadevall. Discrete-time spectrum occupancy model based on markov chain and duty cycle models. In Proc. IEEE 5th Int'l. Symp. on Dynamic Spectrum Access Networks (DySPAN 2011), pages 1--10, May 2011.Google ScholarGoogle ScholarCross RefCross Ref
  6. M. López-Benítez and F. Casadevall. Modeling and simulation of time-correlation properties of spectrum use in cognitive radio. In Proc. 6th Int'l. ICST Conf. on Cognitive Radio Oriented Wireless Networks (CrownCom 2011), June 2011.Google ScholarGoogle ScholarCross RefCross Ref
  7. M. López-Benítez and F. Casadevall. A radio spectrum measurement platform for spectrum surveying in cognitive radio. In Proc. 7th Int'l. ICST Conf. on Testbeds and Research Infrastructures for the Development of Networks and Communities (TridentCom 2011), pages 1--16, Apr. 2011.Google ScholarGoogle Scholar
  8. M. A. McHenry et al. Spectrum occupancy measurements. Technical report, Shared Spectrum Company, 2004--2005.Google ScholarGoogle Scholar
  9. A. Papoulis and S. U. Pillai. Probability, random variables, and stochastic processes. McGraw-Hill, Boston, 4 edition, 2002.Google ScholarGoogle Scholar
  10. H. Urkowitz. Energy detection of unknown deterministic signals. Proceedings of the IEEE, 55(4):523--531, Apr. 1967.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Modeling and simulation of joint time-frequency properties of spectrum usage in cognitive radio

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Other conferences
        CogART '11: Proceedings of the 4th International Conference on Cognitive Radio and Advanced Spectrum Management
        October 2011
        372 pages
        ISBN:9781450309127
        DOI:10.1145/2093256

        Copyright © 2011 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 26 October 2011

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader