# Trajectories and Resource Management of Flying Base Stations for C-V2X
## 1 Introduction  
The transport system is one of the fields expecting the greatest changes in the next decades. Human-driven cars and trucks will be progressively replaced by connected and autonomous vehicles (CAVs), promising safer mobility, more efficient traffic management, significant pollution reduction, and the availability of new services for passengers. Focusing on connectivity, for several years IEEE 802.11p and the related standards had been the main solution for the vehicular environment [1]. Starting from 2016, however, 3 GPP has introduced the concept of cellular-vehicle-to-anything (C-V2X), which specifically addresses this sector within long term evolution (LTE), 5G, and beyond [2; 3; 4]. In C-V2X, long and short-range communications are parts of the same framework, with the promise of a single chip-set, a native involvement of vulnerable users, and a long term support from the entire cellular ecosystem. Regarding the applications envisaged for the vehicular scenarios, often denoted as use cases, a large list has been presented for what are called the Day-1 or Day-1.5, which are in principle supported by both IEEE 802.11p and the first versions of C-V2X and are based on the unidirectional distribution of information to improve context awareness; emergency vehicle warning, stationary vehicle warning, and roadworks warning are just a few examples [5; 6; 7]. Recently, 3 GPP has started a discussion about advanced use cases, where vehicles do not only share basic information about their status throughsmall packets, but also exchange large messages and interact in order to coordinate their actions. Such applications have challenging requirements in terms of wireless capabilities that are hardly guaranteed by current standards [8]. One relevant example is extended sensing [9]; by allowing a collective perception of the environment, it implies the need for data rates that range between 10 Mbps to 1 Gbps within a limited range [8]. Although connected vehicles are often associated with the capability of short-range wireless communications, it is clear that it will take time before all cars are equipped and that the long-range connection guaranteed by cellular base stations must be viewed as a valuable option at least during this transitory. However, providing an ubiquitous and reliable coverage to vehicles is particularly challenging with terrestrial base stations (TBSs), since the density and distribution of vehicles is significantly variable in both time and space, in ways that are not always easy to predict. In a scenario where the penetration of cars equipped with wireless communication devices is far from 100% and the requirements tend to be challenging for a cellular network not specifically planned for the vehicular scenario, the use of an unmmaned aerial vehicle (UAV), carrying a mobile base station, could be helpful to fill the gap of short-range connections and address unpredictable traffic distribution in space and time. In fact, UAVs might be an efficient complement to traditional TBSs [10; 11], because they can: (1) fly where TBSs cannot offer good coverage and capacity; (2) satisfy traffic demand when needed, if a proper trajectory is planned; and (3) easily achieve line of sight (LOS) conditions toward vehicles on the ground. In this work we consider a scenario where C-V2X users are moving in an urban area and request to be served by base stations. A number of TBSs are deployed in the area with limited amount of radio resources (RRs) and one UAV is launched in the area to support the TBSs in the service provision. A joint RR scheduling strategy, between the UAV and the TBSs, is applied and a UAV trajectory is defined according to a heuristic algorithm. The latter is inspired by the cluster-based algorithm defined in [12], where, however, a different weighting cost function was defined to select the trajectory. Results show the improvement of performance in terms of the percentage of successfully served vehicles when using the UAV in addition to TBSs. The article is organized as follows.