# Performance Evaluation of UAV-Enabled LoRa Networks for Disaster Management Applications
###### Abstract  
In hostile and remote environments, such as mountains, forests or suburban areas, traditional communications may not be available, especially after a disaster, such as a flood, a forest fire or an earthquake. In these situations, the wireless networks may become congested or completely disrupted and may not be adequate to support the traffic generated by rescuers. It is also considered as the key tool in Corona Virus (COVID-19) battle. Moreover, the conventional approaches with fixed gateways may not work either, and this might lead to decoding errors due to the large distance between mobile nodes and the gateway. To avoid the decoding errors and improve the reliability of the messages, we propose to use intermediate Unmanned Aerial Vehicles (UAVs) to transfer messages from ground-based Long Range (LoRa) nodes to the remote base station (BS). Specifically, this UAV-enabled LoRa architecture is based on the ad hoc WiFi network, wherein, UAVs act as relays for the traffic generated between LoRa nodes and BS. To make the architecture more efficient, a distributed topology control algorithm is also proposed for UAVs. The algorithm is based on virtual spring forces and movement prediction technique that periodically updates the UAV topology to adapt to the movement of the ground-based LoRa nodes that move on the surface. The simulation results show the feasibility of the proposed approach for packet reception rate and average delay quality of service (QoS) metrics. It is observed that the mechanisms implemented in a UAV-enabled LoRa network effectively help to improve the packet reception rate with nominal buffer delays. LoRa; packet reception rate; UAV; topology control +
Footnote †: journal: Computer Science and Technology  
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Long Range (LoRa) Wide Area Network (WAN) is one of the most promising technologies enabling LPWANs [4; 5]. LoRaWAN takes advantage of Spread Spectrum (SS), chirp orthogonality and the good propagation characteristics of the sub-GHz spectrum to provide reliable communication over long distances. This comes at the expense of the bit rate and of the maximum time interval between consecutive transmissions due to duty cycle limitations in the bands used by the protocol. Unmanned Aerial Vehicles (UAV), commonly called drones, are flying vehicles that can operate without the need of a remote pilot. Exclusive prerogative of the military for many years, UAVs are now commercially available and their relatively low price makes them appealing for a wide variety of applications in a diverse range of scenarios [6; 7; 8; 9]. The price range can vary between 205-300$ for small battery-powered Radio Frequency (RF) drones such as the Parrot Bebop 2, to more than 3000$ for professional drones with advanced control systems and sensors such as the DJI Spreading Wings S1000. In the consumer market segment, drones are mainly used for taking aerial pictures and videos, while in the commercial segment the range of applications is more diverse: mapping of geographical areas, product delivery, and logistics, data collection, crop monitoring, and surveillance [10; 11; 12]. Drones are increasingly being used also in applications such as crime prevention, weather and meteorology, search and rescue operations, border and maritime patrol and forest fire monitoring. In case of a disaster, such as an earthquake, a flood or a wildfire [13], UAVs can be used to support the operations of the rescuers, to localize the victims and to create a backhaul network in case of absence or disruption of the communication facilities [14]. In this last circumstance, the relay network formed by UAVs can support the data generated by isolated IoT devices that have been deployed in advance or during the rescue operations. During the ongoing pandemic circumstances, the UAVs can be deployed against the Corona Virus (COVID-19) battle.