Evaluation of an Adaptive Resource Allocation for LoRaWAN

Jean Moraes, Helder Oliveira, Eduardo Cerqueira, Cristiano Both, Sherali Zeadally, Denis Rosário

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Long Range Wide Area Network (LoRaWAN) emerges to connect devices that require long-range and low-cost (bandwidth and power) communication services. In this context, the adoption of this technology brings new challenges due to the densification of IoT devices, which causes signal interference and affects the QoS directly. On the other hand, the LoRaWAN transmission configurations’ flexibility allows higher management to use end-device parameters, allowing better resource utilization and improve network scalability. We evaluate an adaptive solution that defines the best LoRaWAN parameter settings to reduce the channel utilization and, consequently, maximize the number of packets delivered. Additionally, to validate the method, we used a mixed-integer linear programming solution and compared the results obtained with those given by the heuristics. The results achieved by the heuristics were very close to those provided by the optimal result, demonstrating the effectiveness of the heuristics.

Original languageEnglish
Pages (from-to)65-79
Number of pages15
JournalJournal of Signal Processing Systems
Volume94
Issue number1
DOIs
StatePublished - Jan 2022

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Keywords

  • IoT
  • LoRaWAN
  • MILP
  • Resource allocation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Signal Processing
  • Information Systems
  • Modeling and Simulation
  • Hardware and Architecture

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