• DocumentCode
    110990
  • Title

    Fronthaul Compression for Cloud Radio Access Networks: Signal processing advances inspired by network information theory

  • Author

    Seok-Hwan Park ; Simeone, Osvaldo ; Sahin, Ozge ; Shamai Shitz, Shlomo

  • Author_Institution
    Dept. of Electr. Eng., New Jersey Inst. of Technol., Newark, NJ, USA
  • Volume
    31
  • Issue
    6
  • fYear
    2014
  • fDate
    Nov. 2014
  • Firstpage
    69
  • Lastpage
    79
  • Abstract
    Cloud radio access networks (C-RANs) provide a novel architecture for next-generation wireless cellular systems whereby the baseband processing is migrated from the base stations (BSs) to a control unit (CU) in the "cloud." The BSs, which operate as radio units (RUs), are connected via fronthaul links to the managing CU. The fronthaul links carry information about the baseband signals-in the uplink from the RUs to the CU and vice versa in the downlink-in the form of quantized in-phase and quadrature (IQ) samples. Due to the large bit rate produced by the quantized IQ signals, compression prior to transmission on the fronthaul links is deemed to be of critical importance and is receiving considerable attention. This article provides a survey of the work in this area with emphasis on advanced signal processing solutions based on network information theoretic concepts. Analysis and numerical results illustrate the considerable performance gains to be expected for standard cellular models.
  • Keywords
    cloud computing; next generation networks; radio access networks; signal processing; C-RAN; base stations; baseband processing; cloud radio access networks; control unit; fronthaul compression; fronthaul links; next-generation wireless cellular systems; quadrature samples; quantized in-phase; radio units; signal processing advances; 5G mobile communication; Base stations; Baseband; Cellular networks; Cloud computing; Next generation networking; Process control; Radio access networks; Uplink; Wireless cellular networks; Wireless communication;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2014.2330031
  • Filename
    6924850