# Trajectories and Resource Management of Flying Base Stations for C-V2X
## 2 Related Work  
Equipping vehicles with wireless communication devices to implement advanced services on the road has been studied for decades and standards today appear mature for large scale deployment [13]. However, given their critical impact on road safety and the need that the various car-manufacturers agree to common technologies, still a small percentage of vehicles is presently connected, normally relying on long-range cellular coverage and providing services that are limited to entertainment [14; 15] or vehicle tracking [16]. It is anyway generally believed that CAVs will come to market in the next few years and this represents an enormous opportunity for all companies directly or indirectly involved. In this context, the cellular ecosystem started to think about protocols and services for LTE and 5G specifically devoted to the vehicular environment. Beginning even before first definitions inside the standards in 2016, much effort has thusfar being devoted to C-V2X [17; 18]. Most work does actually focus on short-range communications [19; 20], which is expected to minimize the delay and guarantee a high spatial reuse, but it is clear that long-range communications will always play a relevant role, especially until the percentage of equipped vehicles will be limited [21; 22]. When dealing with long-range communications, however, it appears very challenging to combine a fixed deployment of base stations with stringent requirements of a significantly variable and possibly huge data traffic, which is presumable for vehicles that might be sparse or very dense in different parts of a city or at different times of day [23]. At the same time, UAVs are studied from a number of perspectives and different applications. For example, they are considered in many works as flying base stations. The works [10; 11] discuss the integration of drones and aerial platforms in the next generation of networks. They analyze aspects such as coverage, radio access, and backhaul links introduced by multiple drone-cells. The works related to UAVs started by focusing on optimal deployments and moved to trajectory considerations in [24]. In particular, a clusterization algorithm is used with one UAV per cluster. The objective is to study the optimal trajectory and deployment in the internet of things (IoT) uplink communications to minimize the power transmitted by machine nodes and the energy consumed by the UAV. In [25], multiple UAVs are used as relays and they are deployed based on appropriate density and cost functions. These functions determine areas with higher user demand. In [26], how radio-maps can drive UAVs is studied, in order to exploit the environment-dependent path loss in a specific area and take advantage of a better coverage. In our previous works [27; 28] we considered issues related to a joint radio resource management (RRM) between the terrestrial base stations and a UAV. However, we had a uniform scenario with a large number of active users; different applications with different demands may require algorithm adaptation and simpler and more practical considerations. The use of UAVs to support vehicular communications has recently raised significant attention as an efficient, flexible, and limited cost solution when the deployed infrastructure is not sufficient or in case of particular events. The majority of papers investigate the use of UAVs to improve routing in vehicular networks. For example, in [29] a novel reactive algorithm exploiting UAVs as relays is suggested when the capacity or coverage becomes insufficient. In [30], drones are used with store and carry capabilities when disconnections occur due to a low density of vehicles. Also in [31], routing is addressed, with the use of game theory to predict disconnected segments where UAVs should be moved. In [32], some vehicles are assumed to be equipped with drones that can fly within a given control range and act as a relay of a multi-hop route or might carry the data directly to the intended receiver.