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Wireless Personal Communications

, Volume 103, Issue 3, pp 2137–2154 | Cite as

Energy and Latency-Aware Scheduling Under Channel Uncertainties in LTE Networks for Massive IoT

  • Mohammad Reza Mardani
  • Salman MohebiEmail author
  • Mohammad Ghanbari
Article
  • 97 Downloads

Abstract

The machine-to-machine (M2M) communication is an enabler technology for internet of things (IoT) that provides communication between machines and devices without human intervention. One of the main challenges in IoT is managing a large number of machine-type communications co-existing with the human to human (H2H) or human type communications. Long term evolution (LTE) and LTE-advanced (LTE-A) technologies due to their inherent characteristics like high capacity and flexibility in data access management are appropriate choices for M2M/IoT systems. In this paper, a two-phase intelligent scheduling mechanism based on interval type-2 fuzzy logic to (1) satisfy QoS requirements, (2) ensure fair resource allocation and (3) control energy level of devices for coexistence of M2M/H2H traffics in LTE-A networks, is presented. The proposed interval type-2 fuzzy Logic mechanism enhances data traffic efficiency by predicting and handling the network uncertainties. The performance of the proposed algorithm is evaluated in terms of various metrics such as delay, throughput, and bandwidth utilization.

Keywords

M2M communication LTE network Resource allocation Internet of things Fuzzy logic 

Notes

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of ECE, College of EngineeringUniversity of TehranTehranIran
  2. 2.Faculty of New Sciences and TechnologiesUniversity of TehranTehranIran
  3. 3.School of Computer Science and Electronic EngineeringUniversity of EssexColchesterUK

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