## 3 Modeling of City Environment  
The building's layout and characteristics significantly impact the radio frequency (RF) model in an urban setting. These factors include building heights, materials, spacing between buildings, and obstacles such as trees and other structures. Understanding these conditions and constraints is essential for accurately developing an RF model to account for signal propagation and coverage in urban areas effectively. The statistical ITU-R recommendation P.1410-5 [36] model allows for us to create the build-up area for an urban environment without specific information about building shapes and distribution. As per [34], only three parameters are needed to model the area: \(\alpha\), which is the ratio of build-up area to the total land area (dimensionless); \(\beta\), the mean number of buildings per unit area (buildings/km\({}^{2}\)); \(\gamma\), a scale parameter that describes the distribution of building heights according to a Rayleigh probability density function.  
\[p(h_{b})=\frac{h_{b}}{\gamma^{2}}\ \exp(\frac{-{h_{b}}^{2}}{\gamma^{2}}) \tag{1}\]  
where \(p(h_{b})\) is the probability distribution of the building with height \(h_{b}\).  
The statistical ITU-R model parameters are utilized to create four different environments that can be used to map the area of an Indian metropolitan city. Table 1 summarizes the above-mentioned statistical parameters based on ITU-R recommendation P.1410-5 [36]. These parameters are utilized to create four distinct environments that can be correlated with urban areas. The distribution of buildings is generated using the Rayleigh distribution to ensure a realistic approach when analyzing shadowing effects.  
\begin{table}
\begin{tabular}{l l l l} \hline
**Environment** & \(\alpha\) & \(\beta\) & \(\Gamma\) \\ \hline Suburban & 0.1 & 750 & 8 \\ \hline Urban & 0.3 & 500 & 15 \\ \hline Dense urban & 0.5 & 300 & 20 \\ \hline High-rise urban & 0.5 & 300 & 50 \\ \hline \end{tabular}
\end{table}
Table 1: ITU-R P.1410-5 model parameters.  
Designing a geometric model that meets these criteria to represent an acceptable city layout is a significant challenge. This paper utilizes a mathematical approximation proposed by [PERSON] [27] to shape the city environment, as shown in Figure 1. The simulation considers a square plot with an area of one square kilometer, where the total number of buildings is Ns, the side length is denoted as Ds, the building width is Ws, and the interbuilding space is Ss, all measured in meters. As per [27], the ITU-R statistical parameters can be linked with Ds, Ws, and Ss with the relationship \(W_{s}=1000\sqrt{\frac{\pi}{\beta}}\), with interbuilding spacing \(S_{s}=\frac{1000}{\sqrt{\beta}}-W_{s}\) and side length \(D_{s}=\frac{W_{s}+S_{s}}{1000}\sqrt{N_{s}}\).  
The city layout can be easily generated using MATLAB 2023. In the real-world environment, buildings do not have a regular structure. To mitigate that in simulation, the UAV's position is determined by the elevation and azimuthal angles at each point along the street. Calculations are carried out for specific elevation angles using the median value obtained from the azimuthal angle. This approach ensures that the results are not dependent on the azimuthal angle, accounting for the uneven spacing of buildings in the real world.