No abstract

LoRaWAN simulations are a flexible way to analyse the behaviour of this LPWAN technology in scenarios that are unfeasible to deploy due to their scale and the number of devices required. Parallel to this, there is also a continued lack of largerscale LoRaWAN deployments in current literature. Crucially, none of these studies involves comparison with any theoretical model, such as discrete-time simulation or mathematical analysis, for validation. In this paper we deploy a 20 nodes LoRaWAN network around the University of Glasgow's campus, analyse the results and then proceed to develop an NS-3 simulation to recreate and match as faithfully as possible the behaviour and topology of the physical deployment. The performance of both the deployment and the simulation is then compared, and the results show that while the complexity of the simulation is kept relatively low, it is possible to get simulation results within about 20% of the deployment results.

The large-scale behaviour of LoRaWAN networks has been studied through mathematical analysis and discrete-time simulations to understand their limitations. However, current literature is not always coherent in its assumptions and network setups. This paper proposes a comprehensive analysis of the known causes of packet loss in an uplink-only LoRaWAN network: duty cycle limitations, packet collision, insufficient coverage, and saturation of a receiver’s demodulation paths. Their impact on the overall Quality of Service (QoS) for a two-gateway network is also studied. The analysis is carried out with the discrete-event network simulator NS-3 and is set up to best fit the real behaviour of devices. This approach shows that increasing gateway density is only effective as the gateways are placed at a distance. Moreover, the trade-off between different outage conditions due to the uneven distribution of spreading factors is not always beneficial, diminishing returns as networks grow denser and wider. In particular, networks operating similarly to the one analysed in this paper should specifically avoid SF11 and 12, which decrease the average overall PDR by about 7% at 10% nodes increment across all configurations. The results of this work intend to homogenise behavioural assumptions and setups of future research investigating the capability of LoRaWAN networks and provide insight on the weight of each outage condition in a varying two-gateway network.

In a LoRaWAN network one of the main reasons of packet outage is the destructive interference that is caused by colliding packets. As the network operates with an ALOHA-like channel access setup, there is no easy way of preventing two or more devices transmitting at the same time, possibly generating interference to each other. Different methods are proposed in literature that can be used to decrease this chance. However, most of them require extensive use of downlink messages coupled with involved algorithms at the network side, often for only a marginal improvement in performance. In this paper we analyse some ways to optimise the Packet Delivery Ratio (PDR) of a LoRaWAN network that can be used when setting up a node or a group of nodes, do not involve downlink and can operate without knowledge of other devices in the same network. These are shown to provide a small boost in performance of maximum 10%, which is akin to that of more complex, downlink-dependant schemes, while decreasing the set up complexity considerably.

Both stochastic geometry and discrete-time simulations are useful ways to analyse otherwise unfeasible largescale LoRaWAN networks. Currently, very limited research has been performed on assessing how the two methods compare in terms of their results when modelling the same scenario. In this study, such a comparison is performed by replicating via discrete time simulations performed with NS-3 a common result from stochastic analysis of a single gateway network. Results of the comparison show how the two methods are for the most part equivalent and thus they are both equally employable in future research. However, attention needs to be paid to the subtle differences that are characteristic of the two different methods and can give rise to discrepancies in results.