Scalability Analysis of Large-Scale LoRaWAN Networks in ns-3
Top Cited Papers
- 31 October 2017
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Internet of Things Journal
- Vol. 4 (6), 2186-2198
- https://doi.org/10.1109/jiot.2017.2768498
Abstract
As LoRaWAN networks are actively being deployed in the field, it is important to comprehend the limitations of this low power wide area network technology. Previous work has raised questions in terms of the scalability and capacity of LoRaWAN networks as the number of end devices grows to hundreds or thousands per gateway. Some works have modeled LoRaWAN networks as pure ALOHA networks, which fails to capture important characteristics such as the capture effect and the effects of interference. Other works provide a more comprehensive model by relying on empirical and stochastic techniques. This paper uses a different approach where a LoRa error model is constructed from extensive complex baseband bit error rate simulations and used as an interference model. The error model is combined with the LoRaWAN MAC protocol in an ns-3 module that enables to study multichannel, multispreading factor, multigateway, bi-directional LoRaWAN networks with thousands of end devices. Using the LoRaWAN ns-3 module, a scalability analysis of LoRaWAN shows the detrimental impact downstream traffic has on the delivery ratio of confirmed upstream traffic. The analysis shows that increasing gateway density can ameliorate but not eliminate this effect, as stringent duty cycle requirements for gateways continue to limit downstream opportunities.Keywords
Funding Information
- MoniCow Project realized in collaboration with imec
- DeLaval, Metagam, Multicap, NXP Semiconductors N.V., and snapTonic through VLAIO (Flanders Innovation and Entrepreneurship)
- Fund for Scientific Research-Flanders through the “Intelligent Dense and Long Range IoT Networks” (IDEAL-IoT) project (S004017N)
- Processing Visual Sensor Data in Low-Power Wide Area Networks project (G084177N)
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