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LoRa Parameter Choice for Minimal Energy Usage

Published: 04 November 2018 Publication History

Abstract

LoRa (Long Range) is a radio technology that facilitates low power communications over a large distance. The long range of communication means that a simple single hop transmission to a centralised gateway is sufficient for most applications. To supply this performance the LoRa physical layer offers a range of transmission parameters to tailor the capabilities for different applications. With over 6000 parameter combinations it is difficult to select the most efficient combination. Using experimental measurements and simulations we show how to find a parameter set with minimal energy usage for a given situation. Using data from real world deployments we also show that using payload replication with data-aware compression can improve data delivery ratios by 16 to 25% at no or minimal extra energy cost. For energy-sensitive applications low energy LoRa settings and forward error correction give better results than settings that maximise the packet reception ratio.

References

[1]
Aloÿs Augustin, Jiazi Yi, Thomas Clausen, and William Townsley. 2016. A Study of LoRa: Long Range and Low Power Networks for the Internet of Things. Sensors 16, 12 (sep 2016), 1466.
[2]
Martin Bor and Utz Roedig. 2017. LoRa Transmission Parameter Selection. In Proceedings of the 13th IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS), Ottawa, ON, Canada. 5--7.
[3]
Martin Bor, Utz Roedig, Thiemo Voigt, and Juan Alonso. 2016. Do LoRa lowpower wide-area networks scale?. In The 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems.
[4]
R. Cardell-Oliver, S. Boettcher, and C. Huebner. 2013. Data-aware, resource-aware, lossless compression for sensor networks. In EWSN, Vol. 7772 LNCS.
[5]
R. Cardell-Oliver, A. Willig, C. Huebner, T. Buehring, and A. Monsalve. 2012. Error control strategies for transmit-only sensor networks: A case study. In IEEE International Conference on Networks, ICON.
[6]
Marco Cattani, Carlo Boano, and Kay Römer. 2017. An Experimental Evaluation of the Reliability of LoRa Long-Range Low-Power Wireless Communication. Journal of Sensor and Actuator Networks 6, 2 (jun 2017), 7.
[7]
Oana Iova, Amy L Murphy, L Ghiro, D Molteni, F Ossi, and F Cagnacci. 2017. LoRa from the city to the mountains: Exploration of hardware and environmental factors. In Proceedings of the 2nd International Workshop on New Wireless Communication Paradigms for the Internet of Things (MadCom), Uppsala, Sweden. 20--22.
[8]
LoRa Alliance 2017. LoRaWAN™ Specification. LoRa Alliance. https://www.lora-alliance.org/resource-hub/lorawantm-specification-v11
[9]
P. J. Marcelis, V. Rao, and R. V. Prasad. 2017. DaRe: Data Recovery through Application Layer Coding for LoRaWAN. In Proceedings of the Second International Conference on Internet-of-Things Design and Implementation - IoTDI '17. 97--108.
[10]
Juha Petäjäjärvi, Konstantin Mikhaylov, Antti Roivainen, Tuomo Hanninen, and Marko Pettissalo. 2015. On the coverage of LPWANs: range evaluation and channel attenuation model for LoRa technology. In ITS Telecommunications (ITST), 2015 14th International Conference on. IEEE, 55--59.
[11]
Juha Petäjäjärvi, Konstantin Mikhaylov, Rumana Yasmin, Matti Hämäläinen, and Jari Iinatti. 2017. Evaluation of LoRa LPWAN technology for indoor remote health and wellbeing monitoring. International Journal of Wireless Information Networks 24, 2 (2017), 153--165.
[12]
Simon R. Saunders and Alejandro Aragon Zavala. 2008. Antennas and propagation for wireless communication systems. John Wiley & Sons.
[13]
Semtech 2017. LoRa 860 MHz to 1020 MHz Low Power Long Range Transceiver. Semtech. Rev.3.1.
[14]
Marco Zimmerling, Federico Ferrari, Luca Mottola, Thiemo Voigt, and Lothar Thiele. 2012. pTunes: Runtime Parameter Adaptation for Low-power MAC Protocols. In IPSN'12, April 16ÃćÂĂÂŞ20, 2012, Beijing, China. 36--38.

Cited By

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  • (2023)Multi-Hop and Mesh for LoRa Networks: Recent Advancements, Issues, and Recommended ApplicationsACM Computing Surveys10.1145/363824156:6(1-43)Online publication date: 20-Dec-2023
  • (2022)Adaptive Wireless Network Management with Multi-Agent Reinforcement LearningSensors10.3390/s2203101922:3(1019)Online publication date: 28-Jan-2022
  • (2022)Application-aware adaptive parameter control for LoRaWANJournal of Parallel and Distributed Computing10.1016/j.jpdc.2022.04.023166:C(166-177)Online publication date: 1-Aug-2022
  • Show More Cited By

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cover image ACM Conferences
RealWSN'18: Proceedings of the 7th International Workshop on Real-World Embedded Wireless Systems and Networks
November 2018
61 pages
ISBN:9781450360487
DOI:10.1145/3277883
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 November 2018

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Author Tags

  1. Adaptive Protocol
  2. Low Power
  3. Sensor Networks

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Overall Acceptance Rate 6 of 7 submissions, 86%

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Cited By

View all
  • (2023)Multi-Hop and Mesh for LoRa Networks: Recent Advancements, Issues, and Recommended ApplicationsACM Computing Surveys10.1145/363824156:6(1-43)Online publication date: 20-Dec-2023
  • (2022)Adaptive Wireless Network Management with Multi-Agent Reinforcement LearningSensors10.3390/s2203101922:3(1019)Online publication date: 28-Jan-2022
  • (2022)Application-aware adaptive parameter control for LoRaWANJournal of Parallel and Distributed Computing10.1016/j.jpdc.2022.04.023166:C(166-177)Online publication date: 1-Aug-2022
  • (2021)Data-driven Adaptive Network Management with Deep Reinforcement Learning2021 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)10.1109/DASC-PICom-CBDCom-CyberSciTech52372.2021.00037(153-160)Online publication date: Oct-2021
  • (2021)Experiments on LoRa Communication Used in a Relay Station Network for Disaster ManagementComputational Intelligence in Information Systems10.1007/978-3-030-68133-3_22(225-232)Online publication date: 19-Jan-2021
  • (2019)DatasetProceedings of the 2nd Workshop on Data Acquisition To Analysis10.1145/3359427.3361912(26-28)Online publication date: 10-Nov-2019

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