Optimal Spectrum Sensing and Resource Allocation in Cognitive Radio

  • Author / Creator
    Fan, Rongfei
  • Cognitive radio is an emerging spectrum-agile technology to alleviate the upcoming spectrum shortage problem. In a cognitive radio network, unlicensed users (secondary users) can access the licensed spectrum if there is no transmission/reception activity of licensed users (primary users) in an overlay mode, or the interference of secondary users to primary users is below a threshold in an underlay mode. Spectrum sensing is essential in an overlay mode, while resource allocation is challenging in both modes due to the lower priority of secondary channel access. The focus of this thesis is on optimal spectrum sensing and resource allocation in cognitive radio networks, to provide necessary protection for primary users and achieve resource efficiency for secondary users. Firstly, optimal sensing time allocation in multichannel cognitive radio network is studied, to maximize the average throughput of secondary users while protecting primary activities. The initially formulated optimization problems are non-convex, which are very hard to be solved optimally. By finding special properties of the problems, the problems are decomposed into bi-level convex optimization problems, which can be solved optimally. Secondly, channel sensing order setting in a two-user multichannel cognitive radio network is investigated. Two sub-optimal algorithms are proposed and numerically verified to have comparable performances to optimal solutions. When adaptive modulation is adopted, it is shown that the stopping rule should be designed jointly with sensing order setting strategy of the two users. Thirdly, joint sensing time setting and resource allocation in a multichannel cognitive radio network is studied. An optimization problem is formulated to maximize the weighted average throughput of secondary users. The problem is non-convex. With the aid of monotonic optimization and bi-level optimization, the non-convex problem is solved optimally. The research is also extended to cases maximizing the proportional or max-min fairness level of the users. Last but not least, optimal resource allocation in an underlay mode is investigated. The average rate of secondary users is maximized while limiting the interference to primary users. Convex problems are formulated. By deriving special properties of the optimal solutions, simple online algorithms are given, with closed-form solutions.

  • Subjects / Keywords
  • Graduation date
  • Type of Item
  • Degree
    Doctor of Philosophy
  • DOI
  • 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
  • Institution
    University of Alberta
  • Degree level
  • Department
    • Department of Electrical and Computer Engineering
  • Supervisor / co-supervisor and their department(s)
    • Hai Jiang (Department of Electrical and Computer Engineering)
  • Examining committee members and their departments
    • Xinwei Yu (Department of Mathematical and Statistical Sciences)
    • Hai Jiang (Department of Electrical and Computer Engineering)
    • Chintha Tellambura (Department of Electrical and Computer Engineering)
    • F. Richard Yu (Department of Systems and Computer Engineering, Carleton University)
    • H. Vicky Zhao (Department of Electrical and Computer Engineering)