• DocumentCode
    3768556
  • Title

    Artificial Intelligence-based 5G network capacity planning and operation

  • Author

    J. P?rez-Romero;O. Sallent;R. Ferr?s;R. Agust?

  • Author_Institution
    Dept. of Signal Theory and Communications, Universitat Polit?cnica de Catalunya (UPC), Barcelona, Spain
  • fYear
    2015
  • Firstpage
    246
  • Lastpage
    250
  • Abstract
    The highly demanding requirements envisaged for future 5G networks together with the required support of new customers from vertical industries (e.g. e-health, automotive, energy) pose a big challenge for operators in 5G on how to balance investments, user experience and profitability. There will be the need to revisit the actual methodologies of network planning and operation, fully exploiting cognitive capabilities that embrace knowledge and intelligence to achieve a proper understanding of the network usage in multiple dimensions. In this respect, this paper presents a vision on how these planning and operation processes can rely on the inclusion of Artificial Intelligence (AI) concepts that will allow devising models to characterize the impact of many correlated inputs on specific operator objectives and to drive decisions for different processes.
  • Keywords
    "5G mobile communication","Planning","Training","Capacity planning","Artificial intelligence","Mobile computing"
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communication Systems (ISWCS), 2015 International Symposium on
  • Electronic_ISBN
    2154-0225
  • Type

    conf

  • DOI
    10.1109/ISWCS.2015.7454338
  • Filename
    7454338