## 1 Introduction
### Related Works  
UAV-assisted C-V2X communications can support both UAVs and base stations to exploit vehicular communications. This is achieved via vehicle-to-vehicle (V2V) direct-mode communications using PC5 or side-link interface and vehicle-to-infrastructure (V2I) shared-mode communications using the Uu interface. In [12], various propagation models are presented for the direct-mode connectivity that typically considers V-N to V-N transmissions, e.g., the transmission of a vehicle to nearby RSUs, the transmission of a vehicle to nearby pedestrians, or V2V transmissions, as well as for the shared-mode connectivity that considers V-N to cellular base station transmissions or the transmission of V-N to LOS UAV or NLOS UAV. However, the presence of jamming devices in UAV-assisted C-V2X communications can disrupt the safety-based services as well as the autonomous driving services by introducing jamming signals that degrade the network's performance. Thus, the characterization of jamming devices is crucially important to improve the V-N's performance in a UAV-assisted C-V2X network.  
Jamming signals compromise the UAV-assisted networks' efficiency in terms of user coverage. In [13], the coverage efficiency of a UAV-assisted system is exploited. The authors considered stochastic geometry for base station modeling and considered the location of MBSs as a two-dimensional (2D) Poisson point process (PPP), whereas UAVs are modeled as a 3D PPP. Their work modeled aerial jammers' performance and showed that the network's performance is degraded with aerial jamming in terms of coverage. Moreover, the authors in [14] modeled the location of MBSs and jamming devices using a 2D PPP. The authors demonstrated a decrease in coverage of the user device due to the jamming interference in the network.  
C-V2X networks are conventionally modeled by exploiting the stochastic geometry approach in [1; 11; 15]. The location of base stations is traditionally modeled by exploiting a 2D PPP, whereas the position of V-Ns is represented as a Poisson line process, and the networks' performance is evaluated relative to coverage efficiency and SE. The authors in [1] modeled the jamming devices using MCP and showed that 2D ground-based jamming devices can deteriorate the coverage as well as the SE of the C-V2X network. Moreover, U-V2X communication is modeled using stochastic geometry in several research studies [8; 9; 16; 17; 18; 19]. The authors modeled the LOS-LAPs and NLOS-LAPs using a 3D PPP, whereas the V-Ns are modeled using a Poisson line process. Additionally, the authors in [19] modeled the jamming devices as a 2D PPP and showed that jamming devices decrease the U-V2X networks' performance.  
Recently, UAV-assisted networks' efficiency has been investigated by considering millimeter waves along with the antenna beam-width variations [20; 21; 22; 23]. Higher wind, atmospheric pressure, and UAV controlling motors' noise are the main causes of variations in the beam width. The authors modeled UAVs as a 3D PPP, whereas 3D beam width is represented by a normal distribution, and showed that the characterization of the UAV antenna beam-with variations considering millimeter waves for UAV-assisted systems is desirable. Thus, it is important to model the beam-width variations for vehicular systems. Moreover, the authors in [24; 25] modeled the beam-width variations for UAV-assisted systems by including the influence of jamming devices in the network. The research demonstrated that the interference of jamming devices compromised the networks' performance; however, the work does not exploit the influence of jamming in a UAV-assisted C-V2X network.