Adaptive configuration of LoRa networks for dense IoT deployments

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


Original languageEnglish
Title of host publicationIEEE/IFIP Network Operations and Management Symposium
Subtitle of host publicationCognitive Management in a Cyber World, NOMS 2018
Publication statusPublished - 2018
MoE publication typeA4 Article in a conference publication
EventIEEE/IFIP Network Operations and Management Symposium - Taipei, Taiwan, Republic of China
Duration: 23 May 201827 May 2018

Publication series

NameIEEE/IFIP Network Operations and Management Symposium
ISSN (Electronic)2374-9709


ConferenceIEEE/IFIP Network Operations and Management Symposium
Abbreviated titleNOMS
CountryTaiwan, Republic of China
Internet address


Research units


Large-scale Internet of Things (IoT) deployments demand long-range wireless communications, especially in urban and metropolitan areas. LoRa is one of the most promising technologies in this context due to its simplicity and flexibility. Indeed, deploying LoRa networks in dense IoT scenarios must achieve two main goals: efficient communications among a large number of devices and resilience against dynamic channel conditions due to demanding environmental settings (e.g., the presence of many buildings). This work investigates adaptive mechanisms to configure the communication parameters of LoRa networks in dense IoT scenarios. To this end, we develop FLoRa, an open-source framework for end-to-end LoRa simulations in OMNeT++. We then implement and evaluate the Adaptive Data Rate (ADR) mechanism built into LoRa to dynamically manage link parameters for scalable and efficient network operations. Extensive simulations show that ADR is effective in increasing the network delivery ratio under stable channel conditions, while keeping the energy consumption low. Our results also show that the performance of ADR is severely affected by a highly-varying wireless channel. We thereby propose an improved version of the original ADR mechanism to cope with variable channel conditions. Our proposed solution significantly increases both the reliability and the energy efficiency of communications over a noisy channel, almost irrespective of the network size. Finally, we show that the delivery ratio of very dense networks can be further improved by using a network-aware approach, wherein the link parameters are configured based on the global knowledge of the network.

    Research areas

  • Adaptive data rate, Configuration management, Energy efficiency, LoRa, Performance evaluation, Reliability

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