• DocumentCode
    3255765
  • Title

    Joint signal and channel state information compression for uplink network MIMO systems

  • Author

    Jin-Kyu Kang ; Simeone, Osvaldo ; Joonhyuk Kang ; Shamai, Shlomo

  • Author_Institution
    Dept. of Electr. Eng., KAIST, Daejeon, South Korea
  • fYear
    2013
  • fDate
    3-5 Dec. 2013
  • Firstpage
    875
  • Lastpage
    878
  • Abstract
    In the uplink of network MIMO systems, in order to cope with backhaul capacity limitations, base stations (BSs) must compress the received baseband data signal and the channel state information (CSI) for communication to the central unit (CU). Assuming ergodic fading, an Estimate-Compress-Forward (ECF) approach is investigated, whereby the BSs perform CSI estimation and forward a compressed version of the CSI to the CU. This approach contrasts with the previously studied Compress-Forward-Estimate (CFE) strategy, whereby CSI estimation is performed at the CU, and is motivated by the information-theoretic optimality of separate estimation and compression. Various ECF schemes are proposed that perform either separate or joint compression of estimated CSI and received baseband signal. Via numerical results, it is shown that a proper design of ECF strategies leads to substantial performance gains compared to the CFE approach.
  • Keywords
    MIMO systems; channel estimation; data compression; fading channels; CFE; CSI estimation; ECF; base stations; baseband data signal; channel state information compression; compress-forward-estimate strategy; ergodic fading; estimate-compress-forward strategy; information-theoretic optimality; joint signal compression; uplink network MIMO systems; Channel estimation; Coherence; Covariance matrices; Joints; Niobium; Noise; Uplink; Uplink network MIMO; compress and forward; distributed compression; imperfect CSI; limited backhaul;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Conference on Signal and Information Processing (GlobalSIP), 2013 IEEE
  • Conference_Location
    Austin, TX
  • Type

    conf

  • DOI
    10.1109/GlobalSIP.2013.6737031
  • Filename
    6737031