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Permanent link (DOI): https://doi.org/10.7939/R3Q36P

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

Descriptions

Other title
Subject/Keyword
Multiband sensing-time-adaptive joint detection
Wideband spectrum sensing in cognitive radio
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Paysarvi Hoseini, Pedram
Supervisor and department
Beaulieu, Norman C. (Electrical and Computer Engineering)
Examining committee member and department
Nikolaidis, Iaonis (Computing Science)
Iyer, Ashwin K. (Electrical and Computer Engineering)
Department
Department of Electrical and Computer Engineering
Specialization

Date accepted
2010-12-23T17:37:22Z
Graduation date
2011-06
Degree
Master of Science
Degree level
Master's
Abstract
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).
Language
English
DOI
doi:10.7939/R3Q36P
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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