• DocumentCode
    743993
  • Title

    Adaptive Energy-Efficient Power Allocation in Green Interference-Alignment-Based Wireless Networks

  • Author

    Zhao, Nan ; Yu, F. Richard ; Sun, Hongjian

  • Volume
    64
  • Issue
    9
  • fYear
    2015
  • Firstpage
    4268
  • Lastpage
    4281
  • Abstract
    Interference alignment (IA) is a promising technique for interference management in wireless networks. However, the sum rate may fall short of the theoretical maximum, particularly at low signal-to-noise ratio (SNR) levels since IA mainly concentrates on mitigating the interference, instead of improving the quality of desired signal. Moreover, most of the previous works focused on improving spectrum efficiency, but the energy efficiency (EE) aspect is largely ignored. In this paper, an adaptive energy-efficient IA algorithm is proposed through power allocation (PA) and transmission-mode adaptation for green IA-based wireless networks. The PA problem for IA is first analyzed; then, we propose a PA scheme that optimizes the EE of IA-based wireless networks. When the SNR is low, the transmitted power of some users may become zero. Thus, the users with low transmitted power are turned into the sleep mode in our scheme to save energy. The transmitted power and transmission mode of the remaining active users are adapted again to further improve the EE of the network. To guarantee the interests of all the users, fairness among users is also considered in the proposed scheme. Simulation results are presented to show the effectiveness of the proposed algorithm in improving the EE of IA-based wireless networks.
  • Keywords
    Algorithm design and analysis; Interference; Optimization; Receivers; Resource management; Signal to noise ratio; Wireless networks; Energy efficiency (EE); Interference alignment; energy efficiency; fairness; interference alignment (IA); power allocation; power allocation (PA); transmission-mode adaptation;
  • fLanguage
    English
  • Journal_Title
    Vehicular Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9545
  • Type

    jour

  • DOI
    10.1109/TVT.2014.2362005
  • Filename
    6918468