Unmanned aerial base stations for NB-IoT:trajectory design and performance analysis

Abstract In this paper, we consider a NarrowBand-Internet of Things (NB-IoT) network where an Unmanned Aerial Vehicle (UAV) is employed to gather data from IoT devices deployed in a given area. It is well known that UAVs may fly over the terrestrial plane, where and when needed, acting as Unmanned Aerial Base Stations (UABs). In order to serve as many ground IoT devices as possible, a proper trajectory design is fundamental. As we show in the paper, the optimization of the UAV speed and the radio parameters are also essential. Specifically, this paper studies a cluster-based scenario, where IoT devices are deployed according to a Thomas process, and applies a Traveling Salesman Problem approach to design the UAB trajectory. Notably, our model considers the protocol constraints on the number of resource units available on the UAB’s NPUSCH, and the data rate that it can provide to IoT devices. Our results reveal the impact of different design parameters, such as UAB speed and NPRACH periodicity on the network throughput and the number of requests served

Data collection from LoRaWAN sensor network by UAV gateway:design, empirical results and dataset

Abstract Collecting data from Internet-of-Things (IoT) devices, especially the variety of sensors dispersed in the environment, is an increasingly important and difficult task. Several long-range radio-access technologies, such as low-power wide-area networks (LPWAN) and specifically LoRaWAN, have been proposed to address this challenge. However, until now, the key focus of the related studies has been on static terrestrial LPWAN deployments. In this study, we depart from this vision and investigate the practical feasibility and performance of a LoRaWAN gateway (GW) on a flying platform, specifically — an unmanned aerial vehicle (UAV). The key contributions of this study are (i) the design and field-testing of a packet-sniffer-based mobile LoRaWAN GW prototype, allowing collection of the data from LoRaWAN networks, including the already deployed ones; (ii) the open-publication of the data collected during our experimental campaign in the 426 LoRaWAN sensor node network of the University of Oulu illustrating the performance of different drone trajectories; (iii) the initial results of the system’s performance analysis, revealing some interesting trends and setting goals for further studies, and pinpointing the lessons learned during the experimental campaign. Our empirical findings suggest that the Travelling Salesman Problem (TSP) trajectory is the most effective moving trajectory for the number of packets collected and the average energy consumed per packet collected