A Simulation Study on the Impact of IoT Traffic in a Smart-city LTE Network

Richard Samoilenko

Simulation scenario image using Google Maps API .

Simulation scenario image using Google Maps API.

Undergraduate Student Project


Have you ever wondered what it would be like to live in a smart city: a city where all devices are interconnected and information about the location of your bus or the time left on your parking meter could be available right from your own smartphone.  My name is Richard Samoilenko, and my partner's name is Nicholas Accurso. We are both Electrical Engineering majors, and we've worked alongside Dr. Filippo Malandra in his research on the Internet of Things (IoT) and network performance analysis and simulation.  For the past year, we have carried out a case study of a neighborhood in Montreal to understand the impact of IoT traffic in a smart city. Montreal was named the most intelligent community in 2016, so we decided to perform our simulations in this city using real geographical data to achieve the most accurate results possible. It is common knowledge that we'd need a sophisticated network to support a completely connected and "smart" city.  Current cellular networks, such as LTE, may not be enough to support such a system. In this study, we showed that current LTE networks can fall victim to network congestion when IoT traffic is introduced, which may suggest the demand for more robust networking technology to support the implementation of smart cities.


The massive introduction of traffic from the Internet of Things (IoT), particularly in smart-city scenarios, needs to be supported by a steady, pervasive and reliable communication infrastructure. Cellular networks (such as LTE and 5G) are considered a popular solution to support the increasing amount of traffic from the Internet of Things (IoT), especially in smart cities. However, a massive deployment of IoT devices in existing cellular infrastructures can jeopardize the communication of human users and the overall network performance. In this study, the coexistence of IoT traffic and human users in a smart-city LTE infrastructure was studied through simulation using the SimuLTE software. Real geographical data were employed on the position of LTE base stations and IoT devices, retrieved from publicly available sources. Key network indicators, such as user throughput and cell utilization, were adopted to analyze both network and user performance. Simulation results showed a considerable performance degradation when IoT traffic is introduced into the network.

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