Dynamic extended access barring for improved M2M communication in LTE-A networks

Hyundong Kim, Seung Seob Lee, Sukyoung Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Machine-to-machine (M2M) communication is an up-and-coming technology for Internet of Things. However, current wireless cellular network such as LTE-A that is originally designed for human-to-human (H2H) communication falls short in supporting massive number of bursty random access (RA) requests from machine type communication (MTC) devices. Specifically, random access network (RAN) overload due to the huge amount of MTC devices is a critical issue. In this paper, we propose a Dynamic Extended Access Barring (DEAB) scheme to regulate the number of RA requests to mitigate the RAN overload. By utilizing the direct communication between MTC devices in M2M, we exploit RA success rates of neighbour devices in choosing the optimal Extended Access Barring (EAB) parameters. The DEAB scheme is evaluated against EAB scheme and the simulation results show that the proposed scheme significantly outperforms the EAB.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2742-2747
Number of pages6
ISBN (Electronic)9781538616451
DOIs
Publication statusPublished - 2017 Nov 27
Event2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 - Banff, Canada
Duration: 2017 Oct 52017 Oct 8

Publication series

Name2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
Volume2017-January

Other

Other2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
Country/TerritoryCanada
CityBanff
Period17/10/517/10/8

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Control and Optimization

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