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Design of Optimal Frameworks for Wideband/Multichannel Spectrum Sensing in Cognitive Radio Networks

  • Author / Creator
    Paysarvi Hoseini, Pedram
  • Several optimal detection frameworks for wideband/multichannel spectrum sensing in cognitive radio networks are proposed. All frameworks search for multiple secondary transmission opportunities over a number of narrowband channels, enhancing the secondary network performance while respecting the primary network integrity and keeping the interference limited. Considering a periodic sensing scheme with either uniform or non-uniform channel sensing durations, the detection problems are formulated as joint optimization of the sensing duration(s) and individual detector parameters to maximize the aggregate achievable secondary throughput capacity given some bounds/limits on the overall interference imposed on the primary network. It is demonstrated that all the formulated optimization problems can be solved using “convex” optimization if certain practical constraints are applied. Simulation results attest that the proposed frameworks achieve superior performance compared to contemporary frameworks. To realize efficient implementation, an iterative low-complexity algorithm which solves one of the optimization problems with much lower complexity compared to other numerical methods is presented. It is established that the iteration-complexity and the complexity-per-iteration of the proposed algorithm increases linearly with the number of optimization variables (i.e. the number of narrowband channels).

  • Subjects / Keywords
  • Graduation date
    2011-06
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R3Q36P
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Master's
  • Department
    • Department of Electrical and Computer Engineering
  • Supervisor / co-supervisor and their department(s)
    • Beaulieu, Norman C. (Electrical and Computer Engineering)
  • Examining committee members and their departments
    • Iyer, Ashwin K. (Electrical and Computer Engineering)
    • Nikolaidis, Iaonis (Computing Science)