# On the Use of LoRaWAN for Mobile Internet of Things: The Impact of Mobility
###### Abstract  
A long-range wide-area network (LoRaWAN) targets both mobile and static Internet of Things (IoT) applications; it is suited to IoT applications, which require a large coverage area while consuming less power at a low data rate; it provides a solution for transferring data between IoT devices with a minimum cost in terms of power, at the expense of higher latency. LoRaWAN was designed for static low-power long-range networks. However, several IoT solution applications involve the use of mobility. Therefore, this study investigates the usage of LoRaWAN in the field of mobile Internet of Things applications such as bike rentals, fleet monitoring, and wildlife and animal tracking applications. Using the OMNeT++ simulator, two different well-known mobility models are used to investigate the influence of mobility on the performance of mobile LoRaWAN. The results show that intense LoRaWAN networks can operate under a high velocity and varying traffic load. It can be observed that the random waypoint model combination yields a better performance, but at the cost of higher collisions and energy consumption. As a consequence, the results suggest the reconsideration of mobile IoT solutions over LoRaWAN. LoRa; LoRaWAN; mobility; IoTs +
Footnote †: journal: Applied system  
modulation. Tuning these parameters results in a trade-off between power consumption and communication coverage, as well as the amount of transferred data. The parameters are the bandwidth, spreading factor (SF), coding rate (CR), and transmission power. The bandwidth can be set to 500, 250, or 125 kHz. The spreading factor is the ratio between the symbol rate and the chip rate; it signifies the number of encoded bits per symbol, and ranges from 7 to 12. With larger SF, the time on air for a packet is increased, resulting in an increase in power consumption and a decrease in data rate. The CR can be used by the receiving LoRa device to perform forward error correction to overcome the effect of noise on the received packets; it takes one of the following values: 4/5, 4/6, 4/7, or 4/8. The overall growth in recent years in the number of connected smart devices has led to a rise in the number of studies related to the IoT, with topics such as big data, number of devices per cell, energy consumption, security [11], and mobility of connected devices. Today, there are a wide range of deployed IoT applications that involve or require mobility. Examples of these applications can be seen in smart cities, smart vehicles, like rental applications, smart health care, solutions for coping with an aging society, fleet monitoring, and wildlife and animal tracking applications. Therefore, LoRaWAN performance should be investigated while taking into consideration different types of mobility models. The main goal of this article is to investigate the effects of mobility on the performance of mobile IoT devices. The consideration of mobility in the field of LoRaWAN is not quite new. However, a search of the literature revealed that only a few mobility models with a limited speed or number of end devices have been considered. Moreover, some of the existing works focused on mobility in terms of roaming between different networks, or partial mobility--where only a few devices are mobile. Consequently, there is still a lack of investigations on the effect of mobility on the performance of LoRaWAN. Therefore, the contributions of this paper are as follows:  
* Integrating the Framework for LoRa (FloRa) with different mobility models in the OMNeT++ simulator;
* Evaluating the performance of LoRaWAN over different mobility models--namely, random waypoint (RWP), Gauss-Markov (GM), and stationary models;
* Performing a comprehensive evaluation over three mobility models while considering a network consisting of up to 5000 end devices moving at different speeds of up to 25 m/s while using varying numbers of gateways;
* Evaluating the effects of the amount of payload on the performance of mobile LoRaWAN.