Congestion control for machine-type communications in LTE-A Networks

Chia Wei Chang, Yi Hao Lin, Yi Ren, Jyh-Cheng Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

Collecting data from a tremendous amount of Internet-of-Things (IoT) devices for next generation networks is a big challenge. A large number of devices may lead to severe congestion in Radio Access Network (RAN) and Core Network (CN). 3GPP has specified several mechanisms to handle the congestion caused by massive amounts of devices. However, detailed settings and strategies of them are not defined in the standards and are left for operators. In this paper, we propose two congestion control algorithms which efficiently reduce the congestion. Simulation results demonstrate that the proposed algorithms can achieve 20∼40% improvement regarding accept ratio, overload degree and waiting time compared with those in LTE-A.

Original languageEnglish
Title of host publication2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509013289
DOIs
StatePublished - 1 Jan 2016
Event59th IEEE Global Communications Conference, GLOBECOM 2016 - Washington, United States
Duration: 4 Dec 20168 Dec 2016

Publication series

Name2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings

Conference

Conference59th IEEE Global Communications Conference, GLOBECOM 2016
CountryUnited States
CityWashington
Period4/12/168/12/16

Keywords

  • Congestion control
  • IoT
  • LTE-A
  • M2M

Fingerprint Dive into the research topics of 'Congestion control for machine-type communications in LTE-A Networks'. Together they form a unique fingerprint.

Cite this