## 8 Network Setup, Results, and Discussion  
### Simulation Setup and Limitations  
Table 2 shows the simulation parameters for the considered system model. The choice of network parameters facilitates the fact that most of the outcomes of the analysis are quantified in terms of coverage and SE. The network parameters are set by following the specific method given in [11; 16]. The simulation results are obtained on MATLAB ([[https://www.mathworks.com/products/matlab.html](https://www.mathworks.com/products/matlab.html)]([https://www.mathworks.com/products/matlab.html](https://www.mathworks.com/products/matlab.html)), accessed on 16 May 2025) software using 100,000 Monte Carlo runs by considering hardware, i.e., Intel (R) Core (TM) i7-12700 (20 CPUs), 2.1 GHz, with 16 GB RAM. Our analytical work is validated by simulations. The analytical results and simulation results are shown with legends \(Ana-\) and \(Sim-\)  
respectively. The V2V connection is represented by pink color, the V2M connection is represented by cyan color, the V2L connection is represented by purple color, and the V2N connection is represented by brown color. The V2X connection is represented by the black color, showing the combined results of direct mode transmission and shared mode transmission. The standard deviation of the fluctuations of the beam width is represented by the filled circle with zero-degree variation, the filled hat with three-degree variation, and the filled hexagon with six-degree variation. The solid line and dashed-dotted line represent the network's performance without including jamming and with including jamming, respectively. Monte Carlo simulations are obtained to validate the analysis. For each of the Monte Carlo independent trials, the MBSs are allocated in the given 2D space based on a 2D PPP with an average value of MBSs given as \(\lambda_{M}\), while the V-Ns are allocated on each of the roads based on a PLP. The average number of roads is given as \(\lambda_{R}\), and the average number of V-Ns on each road, based on a 3D PPP, with an average value of LAPs given as \(\lambda_{U}\). The jammers are distributed using an MCP such that the number of clusters in the given region is a 2D PPP with an average number of clusters given in the region as \(\lambda_{I}\). For each of the clusters, the number of jammers is a Poisson random variable with a mean number of jammers in each cluster given as \(J\). The jammers are distributed around each cluster center with a circular radius given as \(r_{J}\). For UAV-assisted C-V2X communications, the performance of the V-N is computed in terms of coverage and SE by assuming that for each of the Monte Carlo trials, a transmitting typical V-N wants to communicate with the recipient V-N located at the origin either by utilizing infrastructure such as multiple UAVs (e.g., LOS-LAPs or NLOS-LAPs) and MBSs or without utilizing the infrastructure (such as in V-N to V-N communications). In V2X communications, the transmitting V-N (also known as the conventional typical V-N) wishes to connect with the nearby V-N (also known as the one that receives data). The receiving V-N is located at the origin, \(o\). The most adjacent V-N to the recipient V-N is known as the typical node or the traditional node. Following choosing the typical V-N, it determines when to opt for the transmission in direct mode or the transmission in the shared mode according to the average power of the V-N from its origin or the average power of the V-N at the nearest MBS, at the nearest LOS-LAP, or at the nearest NLOS-LAP. The possibility of a conventional V-N to maintain a LOS interaction is determined using Equation (1), and its complementary function may be utilized for the NLOS connection.