• DocumentCode
    2456085
  • Title

    Low Complexity Multiuser MIMO Scheduling with Channel Decomposition

  • Author

    Zhang, Xiaojie ; Lee, Jungwoo

  • Author_Institution
    Telecommun. R&D Center, Samsung Electron., Suwon
  • fYear
    2006
  • fDate
    Oct. 29 2006-Nov. 1 2006
  • Firstpage
    641
  • Lastpage
    645
  • Abstract
    In multiuser MIMO systems, the base station schedules transmissions to a group of users simultaneously. In order to avoid the inter-user interference, a transmit preprocessing technique which decomposes the multiuser MIMO downlink channel into multiple parallel independent single-user MIMO channels can be used. When the number of users is larger than the maximum that the system can support simultaneously, the base station selects a subset of users who have the best instantaneous channel quality to maximize the system throughput. Since the exhaustive search for the optimal user set is computationally prohibitive, a low complexity scheduling algorithm which aims to maximize the capacity upper bound is proposed in this paper. Simulation results show that the proposed scheduling algorithm achieves similar total throughput as the optimal algorithm but with much lower complexity.
  • Keywords
    MIMO communication; channel capacity; computational complexity; multiuser channels; scheduling; wireless channels; base station; channel capacity; channel decomposition; inter-user interference; low complexity multiuser MIMO scheduling; transmit preprocessing technique; Base stations; Channel capacity; Downlink; Interference cancellation; MIMO; Matrix decomposition; Receiving antennas; Scheduling algorithm; Throughput; Upper bound;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers, 2006. ACSSC '06. Fortieth Asilomar Conference on
  • Conference_Location
    Pacific Grove, CA
  • ISSN
    1058-6393
  • Print_ISBN
    1-4244-0784-2
  • Electronic_ISBN
    1058-6393
  • Type

    conf

  • DOI
    10.1109/ACSSC.2006.354827
  • Filename
    4176637