• DocumentCode
    2020247
  • Title

    Compressive broadcast in MIMO systems with receive antenna heterogeneity

  • Author

    Liu, Xiao Lin ; Luo, Chong ; Hu, Wenjun ; Wu, Feng

  • Author_Institution
    Univ. of Sci. & Technol. of China, Hefei, China
  • fYear
    2012
  • fDate
    25-30 March 2012
  • Firstpage
    3011
  • Lastpage
    3015
  • Abstract
    The key challenge in a broadcast system is receiver heterogeneity, where the weakest receiver typically constrains the entire system performance. Traditionally, this arises from heterogeneous channel SNRs at different receivers. In Multiple-Input Multiple-Output (MIMO) systems, a further heterogeneity is caused by different antenna numbers across receivers. We propose a compressive broadcast framework to address both types of heterogeneity. By layering compressive sensing (CS) over MIMO transmissions, our framework ensures a received source quality commensurate with the channel SNR and the MIMO channel dimension. Compared with a conventional framework, our framework achieves more smooth rate increase with channel SNR and much higher performance for multi-antenna receivers.
  • Keywords
    MIMO communication; antenna arrays; compressed sensing; data compression; receiving antennas; wireless channels; MIMO channel dimension; MIMO systems; MIMO transmissions; antenna numbers; compressive broadcast framework; compressive sensing; heterogeneous channel SNR; multiantenna receivers; multiple-input multiple-output systems; receive antenna heterogeneity; Antenna measurements; MIMO; Noise measurement; Receiving antennas; Signal to noise ratio; Transmitting antennas;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    INFOCOM, 2012 Proceedings IEEE
  • Conference_Location
    Orlando, FL
  • ISSN
    0743-166X
  • Print_ISBN
    978-1-4673-0773-4
  • Type

    conf

  • DOI
    10.1109/INFCOM.2012.6195749
  • Filename
    6195749