• DocumentCode
    31797
  • Title

    Improving Small-Cell Performance Through Switched Multielement Antenna Systems in Heterogeneous Networks

  • Author

    Razavi, Rouzbeh ; Ho, Lester ; Claussen, Holger ; Lopez-Perez, David

  • Author_Institution
    Bell Labs., Alcatel-Lucent, Dublin, Ireland
  • Volume
    64
  • Issue
    7
  • fYear
    2015
  • fDate
    Jul-15
  • Firstpage
    3140
  • Lastpage
    3151
  • Abstract
    This paper introduces an effective yet simple and practical solution to improve small-cell performance in heterogeneous networks (HetNets). The proposed solution is based on deploying a switched multielement antenna (MEA) system capable of generating a variety of antenna patterns at small-cell base stations (BSs). Then, antenna patterns are assigned to user equipment (UE) in a dynamic basis. The antenna pattern selection for each UE is considered to be a supervised machine learning classification problem, in which the small-cell BS seek to find the optimal antenna pattern to serve each UE according to its measurement reports (i.e., UE radio-frequency fingerprint). Simulation results confirm the feasibility of the proposed approach, despite potential inaccuracies in UE measurement reports. Compared with the existing solutions comprising a single omnidirectional antenna (ODA), the proposed approach results in a 68% additional network-wide capacity increase. In addition, a technoeconomic analysis is presented in this paper, indicating the economic advantages of deploying the proposed scheme.
  • Keywords
    antenna arrays; antenna radiation patterns; cellular radio; learning (artificial intelligence); telecommunication computing; HetNet; antenna pattern selection; heterogeneous network; small-cell base station; small-cell performance improvement; supervised machine learning classification problem; switched multielement antenna system; user equipment; Antenna measurements; Directive antennas; Interference; Radio frequency; Switches; Training; Classification; heterogeneous networks (HetNets); interference management; machine learning; multielement antenna (MEA); picocells; radio frequency (RF) fingerprint; small cells;
  • fLanguage
    English
  • Journal_Title
    Vehicular Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9545
  • Type

    jour

  • DOI
    10.1109/TVT.2014.2348319
  • Filename
    6879477