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Optimal primary-user mobility aware parameters design of spectrum sensing in cognitive radio networks

  • Harbin Institute of Technology

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

Abstract

An important issue of the spectrum sensing functionality in Cognitive Radio (CR) networks is the ability of tuning the parameters according to the time, i.g., the capacity of the Cognitive Radio Users in the network and the transmission time, which become more challenging in presence of Primary User (PU) mobility. In this paper, an optimal spectrum sensing is depicted to achieve the feature: I)to determine the value of the capacity of the Cognitive Radio Users in the network; II) to determine the optimal transmission time of each CR user. First, closed-form expressions for the capacity of the Cognitive Radio users and the optimal transmission time of each CR user are derived for a general PU mobility model. Then, the expressions are applied to a widely used model, i.e., the Random Walk mobility model. Finally, the analytical results are verified through simulations.

Original languageEnglish
Title of host publicationInternational Conference on ICT Convergence 2015
Subtitle of host publicationInnovations Toward the IoT, 5G, and Smart Media Era, ICTC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1237-1239
Number of pages3
ISBN (Electronic)9781467371155
DOIs
StatePublished - 11 Dec 2015
Event6th International Conference on Information and Communication Technology Convergence, ICTC 2015 - Jeju Island, Korea, Republic of
Duration: 28 Oct 201530 Oct 2015

Publication series

NameInternational Conference on ICT Convergence 2015: Innovations Toward the IoT, 5G, and Smart Media Era, ICTC 2015

Conference

Conference6th International Conference on Information and Communication Technology Convergence, ICTC 2015
Country/TerritoryKorea, Republic of
CityJeju Island
Period28/10/1530/10/15

Keywords

  • Cognitive radio users' capacity
  • Primary-User mobility
  • Random Walk Model
  • Spectrum sensing

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