• DocumentCode
    3604722
  • Title

    On Big Data Analytics for Greener and Softer RAN

  • Author

    Chih-Lin I ; Yunlu Liu ; Shuangfeng Han ; Sihai Wang ; Guangyi Liu

  • Author_Institution
    China Mobile Res. Inst., Beijing, China
  • Volume
    3
  • fYear
    2015
  • fDate
    7/7/1905 12:00:00 AM
  • Firstpage
    3068
  • Lastpage
    3075
  • Abstract
    Big data analytics applied to signaling, traffic, and wireless environment data in mobile communication networks can help realize autonomous network optimization and build big data-based network operation. In this paper, a signaling-based intelligent network optimization scheme is introduced and applied to the current mobile communication networks, such as 4G Long Term Evolution. In 5G era, big data analytics can help mine user and service requirements from the radio access network level, thus allowing a more efficient 5G design and operation. This paper illustrates how it would significantly facilitate local content provision, dynamical network and functionality deployment, user behavior awareness, fine-tuned network operation, and globally optimized energy saving solutions. It is anticipated that the big data-based 5G network design, and the operation will be greener and softer, and better meet the ever increasing user-centric requirements of mobile communication.
  • Keywords
    4G mobile communication; 5G mobile communication; Big Data; Long Term Evolution; data analysis; environmental factors; telecommunication computing; 4G long term evolution; 5G era; autonomous network optimization; big data analytics; big data-based 5G network design; big data-based network operation; dynamical network; fine-tuned network operation; functionality deployment; globally optimized energy saving solutions; greener RAN; local content provision; mobile communication; mobile communication networks; radio access network level; signaling-based intelligent network optimization scheme; softer RAN; user behavior awareness; user-centric requirements; wireless environment data; 5G mobile communication; Behavioral science; Big data; Data analysis; Green design; Mobile communication; Wireless communication; 5G; Big data; big data; network operation; user behavior sensing; user-centric;
  • fLanguage
    English
  • Journal_Title
    Access, IEEE
  • Publisher
    ieee
  • ISSN
    2169-3536
  • Type

    jour

  • DOI
    10.1109/ACCESS.2015.2469737
  • Filename
    7210136