• DocumentCode
    1754834
  • Title

    Optimal power allocation for green cognitive radio: fractional programming approach

  • Author

    Naeem, M. ; Illanko, K. ; Karmokar, A. ; Anpalagan, Alagan ; Jaseemuddin, M.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Ryerson Univ., Toronto, ON, Canada
  • Volume
    7
  • Issue
    12
  • fYear
    2013
  • fDate
    Aug. 13 2013
  • Firstpage
    1279
  • Lastpage
    1286
  • Abstract
    In this study, the problem of determining the power allocation that maximises the energy efficiency of cognitive radio network is investigated as a constrained fractional programming problem. The energy-efficient fractional objective is defined in terms of bits per Joule per Hertz. The proposed constrained fractional programming problem is a non-linear non-convex optimisation problem. The authors first transform the energy-efficient maximisation problem into a parametric optimisation problem and then propose an iterative power allocation algorithm that guarantees ε-optimal solution. A proof of convergence is also given for the ε-optimal algorithm. The proposed ε-optimal algorithm provide a practical solution for power allocation in energy-efficient cognitive radio networks. In simulation results, the effect of different system parameters (interference threshold level, number of primary users and number of secondary users) on the performance of the proposed algorithms are investigated.
  • Keywords
    cognitive radio; concave programming; environmental factors; iterative methods; nonlinear programming; ε-optimal solution; constrained fractional programming problem; energy-efficient cognitive radio networks; energy-efficient fractional objective; energy-efficient maximisation problem; green cognitive radio; interference threshold level; iterative power allocation algorithm; nonlinear nonconvex optimisation problem; optimal power allocation; parametric optimisation problem; primary users; secondary users;
  • fLanguage
    English
  • Journal_Title
    Communications, IET
  • Publisher
    iet
  • ISSN
    1751-8628
  • Type

    jour

  • DOI
    10.1049/iet-com.2012.0604
  • Filename
    6583146