• DocumentCode
    2784652
  • Title

    Low-complexity joint beamforming and power control for SINR balancing and number of antenna considerations in cognitive radio

  • Author

    Yang, Yang ; Wang, Jin-long ; Wu, Qi-hui

  • Author_Institution
    Inst. of Commun. Eng., PLA Univ. of Sci. & Technol., Nanjing, China
  • fYear
    2009
  • fDate
    23-25 Oct. 2009
  • Firstpage
    306
  • Lastpage
    312
  • Abstract
    The SINR balancing problem involving joint beamforming and power control is considered in the cognitive radio network, wherein the single-input multi-output multiple access channels are assumed. Subject to two sets of constraints: the interference temperature constraints of primary users and the peak transmission power constraints of cognitive users, a low-complexity joint beamforming and power control algorithm called semi-decoupled multi-constraint power allocation with constraints preselection (SDMCPA-CP) for SINR balancing is proposed. Compared with the existing algorithm, the proposed SDMCPA-CP can reduce the number of matrix inversions and matrix eigenvalue decompositions significantly, while still provide the optimal balanced SINR level for all the cognitive users. In addition, based on SDMCPA-CP, a two-phase search (TPS) algorithm for the number of antenna is further presented. With TPS algorithm, the minimal number of antenna which satisfies the above two sets of constraints as well as the QoS requirements of all the CUs could be found fast.
  • Keywords
    antennas; array signal processing; cognitive radio; power control; telecommunication control; QoS; SDMCPA-CP; SINR balancing; antenna; cognitive radio network; cognitive users; constraints preselection; low-complexity joint beamforming; matrix eigenvalue decompositions; matrix inversions; power control algorithm; semidecoupled multi-constraint power allocation; single-input multi-output multiple access channels; two-phase search algorithm; Array signal processing; Chromium; Cognitive radio; Eigenvalues and eigenfunctions; Interference constraints; Matrix decomposition; Power control; Quality of service; Signal to noise ratio; Temperature; Beamforming; SINR balancing; cognitive radio; number of antenna; power control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Apperceiving Computing and Intelligence Analysis, 2009. ICACIA 2009. International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-5204-0
  • Electronic_ISBN
    978-1-4244-5206-4
  • Type

    conf

  • DOI
    10.1109/ICACIA.2009.5361094
  • Filename
    5361094