• DocumentCode
    266445
  • Title

    Energy- and spectrum-efficiency tradeoff in OFDM-based cognitive radio systems

  • Author

    Weijia Shi ; Shaowei Wang ; Dageng Chen

  • Author_Institution
    Sch. of Electron. Sci. & Eng., Nanjing Univ., Nanjing, China
  • fYear
    2014
  • fDate
    8-12 Dec. 2014
  • Firstpage
    3092
  • Lastpage
    3097
  • Abstract
    In this paper, we investigate the Energy Efficiency (EE) - Spectrum Efficiency (SE) tradeoff issue in an OFDM-based cognitive radio (CR) network. A multi-objective resource allocation problem is formulated, where we try to maximize the EE and the SE simultaneously. The Pareto optimal set of the formulated problem is characterized by analyzing the relationship between the EE and the SE. To find a unique globally optimal solution, we proposed a unified EE-SE tradeoff metric, based on which the original optimization task is transformed into a single-objective problem that has a D.C. (Difference of two Convex functions/sets) structure. Then an efficient barrier method is developed, where we speeds up the time-consuming computation of Newton step by exploiting the structure of the D.C. programming problem. Simulation results validate the effectiveness and efficiency of the proposed algorithm. Our general problem formulation sheds some insights on how to design an energy- and spectrum-efficient CR system.
  • Keywords
    OFDM modulation; Pareto optimisation; cognitive radio; convex programming; energy conservation; radio networks; radio spectrum management; D.C. programming problem; EE-SE tradeoff metric; Newton step; OFDM-based cognitive radio network; Pareto optimal set; convex functions structure; convex sets structure; energy-efficiency tradeoff; multiobjective resource allocation problem; single-objective problem; spectrum-efficiency tradeoff; Convex functions; Interference; Measurement; OFDM; Pareto optimization; Resource management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Communications Conference (GLOBECOM), 2014 IEEE
  • Conference_Location
    Austin, TX
  • Type

    conf

  • DOI
    10.1109/GLOCOM.2014.7037280
  • Filename
    7037280