# Non-Terrestrial Networks with UAVs: A Projection on Flying Ad-Hoc Networks
## 1 Introduction
### Background of FANET  
FANET is a sub-type of mobile ad hoc network (MANET) or vehicular ad hoc network (VANET) [17; 18; 19; 20] as shown in Figure 2. However, while both MANET and VANET are mainly explored for ground-based devices on a 2-dimensional (2D) basis, aerial nodes may move freely and flexibly with a higher speed and a lower density in three dimensions (3D), posing new issues for network administration and operation. Besides, clear LoS propagation and environment-resilient communication are key enablers to establish highly efficient network topologies in FANETs [21]. We note that there are two main kinds of UAVs: fixed-wing drones and rotator-wing drones (either single- or multi-rotor) capable of vertical takeoff and landing [22]. The rotator-wing UAVs are more advantageous in terms of their high stability and flexible movements. In [23], a comprehensive characterization of distinctive UAVs was given in more detail. It is noteworthy that the greater mobility of UAVs allows the network topology in FANET to quickly form a kind of fast time-varying networks [24]. Therefore, node mobility is one of the most critical challenges in designing FANETs, which is important for UAVs cooperation and collaboration [25]. Some mobility models have a predefined flight path and the map is updated after each modification [24; 26], whilst others have no specific pattern [22; 27; 28]. Furthermore, when compared to MANET and VANET, the mobility of UAVs plays a vital role since their mobility, direction, and speed can change in considerably shorter time intervals, which might generate communication issues amongst UAVs [29]. This is perhaps FANET's most defining feature, enabling it to be suitable for trajectory control and optimization. Besides, power consumption [30; 31], loca  
Figure 2: MANET, VANET, and FANET relationships. A detailed comparison can be found in [17; 18; 23]. radio propagation models [34; 35] have been found as other critical factors with a huge impact on the performance of FANETs. _Data packet routing_ in such intermittent connected networks is another important topic where a huge corpus of research in FANETs is devoted to it. In [36; 37; 38], different routing protocols for FANETs are discussed and evaluated. Each protocol has distinct strengths and disadvantages, as well as suitability for specific situations, which makes it impossible to find one ideal routing protocol for all scenarios [39]. Hence, [19] classified the routing protocols in FANETs into five main categories as follows: (i) topology-based, (ii) position-based, (iii) clustering/hierarchical, (iv) swarm-based, and (v) _delay tolerant networks (DTN)_. The first four categories, i.e., (i) to (iv), function well when the deployment area is not too large and most of the UAVs are in an LoS transmission range with each other, and the density of the UAVs is also relatively high. Within such a high density of nodes, communication from one UAV to another is reliable. However, we note that the sparsity of UAVs in FANETs is another intrinsic feature that has been identified for the intermittent connectivity problem. Therefore, the true issue arises when there is intermittent connections in a low density of UAVs. Indeed, [40] showed that in a social environment, such as a large urban region where various sites are separated by enormous geographical distances, there is a trade-off between UAV density and the cumulative energy consumption of the FANET. Therefore, [22] showed the first four categories of (i) to (iv) are relatively compromised. Moreover, [41; 42] also explained that the the rise in the total number of UAVs in the network would be disadvantageous in terms of cost, message overhead, buffer overflow, and cumulative energy consumption. It was shown that in low UAV densities, **DTN routing protocols** are the only models that can send data packets with good performance like a high delivery ratio, despite the fact that the network is only sometimes linked [22].