Collision Resolution Protocol for Delay and Energy Efficient LoRa Networks

Future 5G and Internet of Things (IoT) applications will heavily rely on long-range communication technologies such as low-power wide area networks. In particular, LoRaWAN built on LoRa physical layer is gathering increasing interest, both from academia and industries, for enabling low-cost energy e...

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Published in:IEEE transactions on green communications and networking Vol. 3; no. 2; pp. 535 - 551
Main Authors: El Rachkidy, Nancy, Guitton, Alexandre, Kaneko, Megumi
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.06.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:2473-2400, 2473-2400
Online Access:Get full text
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Summary:Future 5G and Internet of Things (IoT) applications will heavily rely on long-range communication technologies such as low-power wide area networks. In particular, LoRaWAN built on LoRa physical layer is gathering increasing interest, both from academia and industries, for enabling low-cost energy efficient IoT wireless sensor networks for, e.g., environmental monitoring over wide areas. While its communication range may go up to 20 km, the achievable bit rates in LoRaWAN are limited to a few kilobits per second. In the event of collisions, the perceived rate is further reduced due to packet loss and retransmissions. First, to alleviate the harmful impacts of collisions, we propose a decoding algorithm that enables to resolve several superposed LoRa signals. Our proposed method exploits the slight desynchronization of superposed signals and specific features of LoRa physical layer. Secondly, we design a full MAC protocol enabling collision resolution. The simulation results demonstrate that the proposed method outperforms conventional LoRaWAN jointly in terms of system throughput, energy efficiency as well as delay. These results show that our scheme is well suited for 5G and IoT systems, as one of their major goals is to provide the best trade-off among these performance objectives.
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ISSN:2473-2400
2473-2400
DOI:10.1109/TGCN.2019.2908409