# Flying Ad Hoc Networks: A New Domain for Network Communications
## 1 Introduction  
Unmanned aerial vehicles (UAVs), also known as drones, have been adopted in many sectors such as agriculture, wildfire monitoring, border surveillance, or telecommunications, to name a few [1, 2]. Simple taxonomies can be used to categorize UAVs, for instance, in terms of the type of flight (autonomous or remotely controlled), their size (large or small), the type of wings, or their communication capabilities. Regarding the types of wings, there are two main categories: fixed-wing UAVs (FW-UAVs) and rotary-wing UAVs (RW-UAVs). Whereas FW-UAVs present longer flight times, higher flight speeds, and a more aerodynamic design, RW-UAVs are able to perform vertical take-off and landing (VTOL), exhibit greater stability (can control yaw, pitch, roll, and throttle), and have the capacity to hover over static points. A brief comparison between FW-UAVs and RW-UAVs is presented in Table 1. Regarding the communication capabilities, we differentiate between single UAVs, which usually employ star topologies to communicate with a base station (BS) or a satellite [3], and multi-UAV systems [4]. Nowadays, most civil and military applications are implemented using multi-UAV systems that consist of a swarm or formation of small UAVs. This approach brings several advantages, such as lower times to complete tasks, cost reduction, higher scalability, and more reliability, among others [5, 6, 7], and is known under the term flying ad hoc network (FANET). FANETs can be seen as a subset of the well-known concept of mobile ad hoc networks (MANETs). MANETs are networks composed of mobile devices such as laptops, cellular phones, sensors, etc. Similarly to vehicle ad hoc networks (VANETs), whose components are cars, buses, ambulances, etc., incorporating embedded communication devices, in FANETs, UAVs are wirelessly interconnected, either directly or using intermediate nodes. Thus, only a small set of nodes need to be connected to the BS/satellite. Even though it is clear that FANETs share common features with MANETs and VANETs, there are several unique characteristics that makes them different, namely, mobility, topology changes, radio propagation, and energy constraints. The mobility of the nodes in a FANET is usually greater than in VANETs and MANETs. The speed of FANETs nodes is highly variable, from being static in aerial coverage or in relaying network-nodes to flying at full speed in search and rescue tasks. More importantly, these nodes have the peculiarity of being able to move in the three spatial dimensions (3-D) with total freedom of movement and RW-UAVs can rotate independently on the three axes (roll, pitch, and yaw). This high mobility of the nodes in FANETs is very different from that presented by the nodes in MANETs and VANETs. In MANETs, nodes usually have very low mobility (e.g., people walking at 6 km/h [8]) and limited speed changes. In VANETs, nodes correspond to vehicles circulating in the streets, presenting medium speed changes (around 100 km/h on highways and around 50 km/h on urban roads [9]) in a 2-D mobility plane (horizontal plane). Nevertheless, speed in VANETs could be higher than in FANETs in some particular cases [10]. These differences have a direct impact on the proposed mobility models. Since these models are employed to simulate the network in more realistic scenarios, it is expected to resemble the way the nodes move. For instance, the random walk mobility model is used in MANETs when the direction and the speed of the nodes are chosen randomly. As another example, the street random walk model or the Manhattan mobility model are used in VANETs because nodes are only allowed to move through streets or highways. Most of these models for MANETs and VANETs are close to reality since the movements of the nodes are very predictable and are also limited by the layout of roads. However, mobility models adopted in MANETs and VANETs cannot be applied directly in FANETs. It is necessary to propose more adequate models that represent the behavior of UAVs considering their high 3-D mobility.