• DocumentCode
    22458
  • Title

    Mode Selection and Power Optimization for Energy Efficiency in Uplink Virtual MIMO Systems

  • Author

    Yun Rui ; Zhang, Q.T. ; Lei Deng ; Peng Cheng ; Mingqi Li

  • Author_Institution
    State Key Lab. of Integrated Services Networks (ISN), Shanghai Adv. Res. Inst., Shanghai, China
  • Volume
    31
  • Issue
    5
  • fYear
    2013
  • fDate
    May-13
  • Firstpage
    926
  • Lastpage
    936
  • Abstract
    Driven by green communications, energy-efficient transmission is becoming an important design criterion for wireless systems, aiming to extend the life cycle of batteries in mobile devices. In this paper, we tackle the energy efficiency (EE) issue in uplink virtual multiple-input multiple-output (MIMO) systems, which requires the optimization of two interlaced parameters: the number of constituent mobile users in the virtual MIMO and their corresponding power allocation. The former parameter is a structural parameter defining the size of the virtual MIMO (usually known as the transmission mode) and its optimization relies on the method of enumeration. The difficulty is further aggravated by the fact that the EE is a non-convex function of power, even for a given transmission mode. By exploiting the fact that increasing the number of active users can increase the number of contributors to the total EE on one hand but reducing the diversity order for each single user on the other, we can show the existence of an optimal transmission mode and find a simple way for its search. Through in-depth analysis, we show the existence of a unique globally optimal power allocator for the case without power constraints under the assumption of zero-forcing receivers, and further reveal the impact of power constraints upon power allocation, as compared to its global counterpart, aiming to provide a powerful means for power-constrained EE optimization. Finally, we establish theories, for isometric networks, to narrow down the search range for possible transmission modes, leading to a significant reduction of computational complexity in optimization. Simulation results are presented to substantiate the proposed schemes and the corresponding theories.
  • Keywords
    MIMO communication; computational complexity; convex programming; EE; computational complexity; energy efficient transmission; green communications; interlaced parameters; mobile devices; mode selection; multiple-input multiple-output systems; nonconvex function; optimal power allocator; power allocation; power constraints; power optimization; structural parameter; transmission mode; uplink virtual MIMO systems; wireless systems; zero forcing receivers; Energy Efficiency; Mode Selection; Power Allocation; Virtual MIMO;
  • fLanguage
    English
  • Journal_Title
    Selected Areas in Communications, IEEE Journal on
  • Publisher
    ieee
  • ISSN
    0733-8716
  • Type

    jour

  • DOI
    10.1109/JSAC.2013.130511
  • Filename
    6502487