Performance Determinants in LoRa Networks: A Literature Review

The LoRa radio technology is one of the most prominent choices in the Internet of Things Low-Power Wide Area Networks (LPWANs) industry due to its versatile and robust technical characteristics along with its ability to achieve long communication ranges combined with low energy consumption and reduc...

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Bibliographic Details
Published in:IEEE Communications surveys and tutorials 2021-01, Vol.23 (3), p.1721-1758
Main Authors: Gkotsiopoulos, Panagiotis, Zorbas, Dimitrios, Douligeris, Christos
Format: Article
Language:English
Subjects:
access protocols
communication networks
Energy consumption
Frequency shift keying
Interference
Internet of Things
Literature reviews
Logic gates
Performance evaluation
Synchronization
Throughput
Tutorials
Wide area networks
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Summary:The LoRa radio technology is one of the most prominent choices in the Internet of Things Low-Power Wide Area Networks (LPWANs) industry due to its versatile and robust technical characteristics along with its ability to achieve long communication ranges combined with low energy consumption and reduced cost. One of the main issues in LoRa networks is how many end-devices can be reporting efficiently while meeting the requirements set by the application they support. This is known as the capacity metric and it is affected by many network parameters and various factors. A literature overview is presented in this work, studying works on LoRa-based networks, outlining their behavior and categorizing them based on their technological breakthroughs. Throughout this survey, a number of performance determinants that stand out are highlighted. These factors span five main categories that encompass physical layer characteristics, deployment and hardware features, end device transmission settings, LoRa MAC protocols, and application requirements. Discussion follows the presentation of each of the factors pinpointing the relevant research, and describing the impact of each one of them on the achieved network efficiency focusing especially on the capacity metric. Open issues and research directions are also highlighted for each of the five identified categories.
ISSN:1553-877X
1553-877X
2373-745X
DOI:10.1109/COMST.2021.3090409