# LoRaWAN Behaviour Analysis through Dataset Traffic Investigation
###### Abstract  
The large development of Internet of Things technologies is increasing the use of smart-devices to solve and support several real-life issues. In many cases, the aim is to move toward systems that, even if significant demands are not required in terms of quantity of exchanged data, they should be very reliable in terms of battery life and signal coverage. Networks that have these characteristics are the Low Power WAN (LPWAN). One of the most interesting LPWAN is LoRaWAN. LoRaWAN is a network with four principal components: end-devices, gateways, network servers, and application servers. It uses a LoRa physical layer to exchange messages between end-devices and gateways that forward these messages, through classic TCP/IP protocol, to the network server. In this work, we analyse LoRa and LoRaWAN by looking at its transmission characteristics and network behaviour, respectively, explaining the role of its components and showing the message exchange. This analysis is performed through the exploration of a dataset taken from the literature collecting real LoRaWAN packets. The goal of the work is twofold: (1) to investigate, under different perspectives, how a LoRaWAN works and (2) to provide software tools that can be used in several other LoraWAN datasets to measure the network behaviour. We carry out six different analyses to look at the most important features of LoRaWAN. For each analysis we present the adopted measurement strategy as well as the obtained results in the specific use case.  
LPWAN; LoRa; LoRaWAN; performance analysis 2022222470.  
31 January 202215 March 202223 March 20  
out of 3 GPP standards, which operate on the industrial, scientific, and medical (ISM) radio bands are available, such as Sig-Fox and LoRaWAN (Low Power Wide Area Network). LoRaWAN is one of the most interesting since with a powerful and robust physical layer, named LoRa, it is possible to set up long range communication links.  
The contributions of the paper can be summarized in three main points. These are the following:  
1. We aim at defining and using some performance metrics useful to evaluate LoRaWAN, as a network. As far as we know the contribution is new since few works have provided a way to process real LoRaWAN datasets to derive performance indicators. The most of the proposals in the literature are based on simulations while we have developed software tools to apply the metrics on any dataset;
2. We designed and presented the procedures implemented in our software tool that can be used to analyse real-world LoRaWAN data;
3. We tested these procedures on a large and heterogeneous dataset that contain data collected from a big LoRaWAN ecosystem with 9 gateways and used for several distinct IoT applications.  
The rest of the paper is organized as following. We provide a quick overview of LoRa and LoRaWAN in Section 2. Then in Section 3 we presented the LoRaWAN at the Edge Dataset (LoED) that contains a rich collection of LoRaWAN packets gathered from a real LoRaWAN in London [2]. We use LoED as a study case to perform some data analyses. We present our six analyses in Section 4, for each analysis we introduce the type of measures we target to, the adopted strategy and we discuss the obtained results.