Analysis of Energy Detection in Cognitive Radio Networks

  • Author / Creator
    Atapattu, Saman U. B.
  • Cognitive radio is one of the most promising technologies to address the spectrum scarcity problem. Cognitive radio requires spectrum sensing, which is used by unlicensed users to opportunistically access the licensed spectrum. Spectrum sensing using energy detection offers low-cost and low-complexity. In this thesis, a comprehensive performance analysis of energy detection based spectrum sensing is developed. Detection performance over composite (fading and shadowing) channels is first investigated using the K and K_G channel models. To further facilitate analysis of energy detection over different wireless channels, a unified channel model based on a mixture gamma distribution is developed. The unified model can accurately represent most existing channel models. A single-value performance metric, the area under the receiver operating characteristic curve, is proposed to measure the overall detection capability, and is investigated over various wireless fading channels. The energy detection based cooperative spectrum sensing is also studied, which can largely improve the detection performance. Since spectrum sensing is required to identify activities of licensed users at a very low signal-to-noise ratio (SNR), performance of energy detection with low SNR is also analyzed in this thesis.

  • 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
  • Specialization
    • Communications
  • Supervisor / co-supervisor and their department(s)
    • Tellambura, Chintha (Electrical and Computer Engineering)
    • Jiang, Hai (Electrical and Computer Engineering)
  • Examining committee members and their departments
    • Tellambura, Chintha (Electrical and Computer Engineering)
    • Krzymie, Witold (Electrical and Computer Engineering)
    • Dong, Xiaodai (Electrical and Computer Engineering, University of Victoria)
    • Khabbazian, Majid (Electrical and Computer Engineering)
    • Jiang, Hai (Electrical and Computer Engineering)