• DocumentCode
    2164725
  • Title

    Energy efficiency optimization for MIMO cognitive radio network

  • Author

    Zhang, Xiaohui ; Li, Hongxiang

  • Author_Institution
    Department of Electrical and Computer Engineering, University of Louisville, Kentucky 40292, United States
  • fYear
    2015
  • fDate
    8-12 June 2015
  • Firstpage
    7713
  • Lastpage
    7718
  • Abstract
    Cognitive radio and MIMO have drawn significant attention to achieve high spectrum utilization efficiency. On the other hand, increasing energy demand and soaring energy related operating cost call for new design of energy efficient communication networks. In this paper, we study the energy efficiency optimization in a cognitive radio MIMO network. Specifically, we propose both distributed and centralized energy efficiency optimization algorithms. Since the original fractional problems are nonconvex, we use Dinkelbach´s method to transform them into parametric problem and solve the optimal solution iteratively. Simulation results show that, while the centralized algorithm outperforms the distributed algorithm in terms of network-wise energy efficiency, it may lose fairness among all CR links in high interference scenario.
  • Keywords
    Convergence; Energy efficiency; Interference; Message systems; Optimization; Radio frequency; Resource management; MIMO; cognitive radio; energy efficiency; fractional programming; transmission beamforming;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications (ICC), 2015 IEEE International Conference on
  • Conference_Location
    London, United Kingdom
  • Type

    conf

  • DOI
    10.1109/ICC.2015.7249560
  • Filename
    7249560