• DocumentCode
    2132974
  • Title

    Traffic-aware ACB scheme for massive access in machine-to-machine networks

  • Author

    He, Hongliang ; Du, Qinghe ; Song, Houbing ; Li, Wanyu ; Wang, Yichen ; Ren, Pinyi

  • Author_Institution
    School of Electronic and Information Engineering, Xi´an Jiaotong University, China
  • fYear
    2015
  • fDate
    8-12 June 2015
  • Firstpage
    617
  • Lastpage
    622
  • Abstract
    Supporting massive access of machine-type devices in a short period is a critical challenge in machine-to-machine (M2M) communications. We in this paper propose a traffic-aware Access Class Barring (ACB) scheme to improve the scalability of M2M networks. Unlike traditional ACB scheme, our proposed scheme aim at dynamically regulating the parameter of access probability, called barring factor, based on network load, thus accommodating much more M2M devices as well as lowering the access delay. To achieve this goal, we first develop a Markov-Chain based traffic-load estimation scheme according to the collision status. Then, we propose a spectrum of functions to control the barring factor varying with the estimated traffic load. Also provided is a set of simulations results, demonstrating that our proposed traffic-aware scheme significantly outperforms the traditional ACB scheme in terms of not only access success probability, but also average access delay.
  • Keywords
    Delays; Estimation; Internet of things; Markov processes; Mathematical model; Radio access networks; Simulation; IoT; LTE; M2M communications; Markov-Chain; barring factor; random access; traffic-aware ACB;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications (ICC), 2015 IEEE International Conference on
  • Conference_Location
    London, United Kingdom
  • Type

    conf

  • DOI
    10.1109/ICC.2015.7248390
  • Filename
    7248390