• DocumentCode
    1474692
  • Title

    Optimal Channel Training in Uplink Network MIMO Systems

  • Author

    Hoydis, Jakob ; Kobayashi, Mari ; Debbah, Mérouane

  • Author_Institution
    Dept. of Telecommun., Supelec, Gif-sur-Yvette, France
  • Volume
    59
  • Issue
    6
  • fYear
    2011
  • fDate
    6/1/2011 12:00:00 AM
  • Firstpage
    2824
  • Lastpage
    2833
  • Abstract
    We consider a multicell frequency-selective fading uplink channel (network MIMO) from K single-antenna user terminals (UTs) to B cooperative base stations (BSs) with M antennas each. The BSs, assumed to be oblivious of the applied codebooks, forward compressed versions of their observations to a central station (CS) via capacity limited backhaul links. The CS jointly decodes the messages from all UTs. Since the BSs and the CS are assumed to have no prior channel state information (CSI), the channel needs to be estimated during its coherence time. Based on a lower bound of the ergodic mutual information, we determine the optimal fraction of the coherence time used for channel training, taking different path losses between the UTs and the BSs into account. We then study how the optimal training length is impacted by the backhaul capacity. Although our analytical results are based on a large system limit, we show by simulations that they provide very accurate approximations for even small system dimensions.
  • Keywords
    MIMO communication; antennas; cellular radio; fading channels; BS; CS; CSI; UT; backhaul capacity; capacity-limited backhaul links; central station; channel state information; cooperative base stations; multicell frequency-selective fading uplink channel; optimal channel training; optimal training length; single-antenna user terminals; uplink network MIMO systems; Antennas; Bandwidth; Channel estimation; Coherence; Downlink; MIMO; Training; Channel estimation; coordinated multi-point (CoMP); imperfect channel state information (CSI); multicell processing; network MIMO; random matrix theory;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2011.2129513
  • Filename
    5733435