# Rapid Deployment Method for Multi-Scene UAV Base Stations for Disaster Emergency Communications
## 4 Simulation Results and Discussion
### Small Area UAV Deployment Simulation  
Eight UAVs are randomly deployed within a rectangular area of 500 m \(\times\) 500 m. Additionally, eight target deployment points are set for UAV redeployment, while 200 users in need of rescue are distributed within the area. The fitness function for redeployment is calculated using three algorithms: SABFGS, LAESGA, and SGA. The coordinates of the target deployment points are denoted as \(C_{\text{target}}=(x_{\text{target}},y_{\text{target}})\), and the final deployment coordinates calculated with the three algorithms are denoted as \(C_{final}=(x_{final},y_{final})\). The number of users in need of rescue within the coverage range of the UAVs is denoted as \(M_{i}\), and the user coverage ratio is calculated using the following formula:  
\[M_{\text{$COV$}}=\frac{M_{i}}{M}\times 100\% \tag{17}\]  
We evaluate the accuracy of deployment by normalizing the error between the final coordinates of the UAV deployment and the coordinates of the target deployment point:  
\[\mathbb{S}=(100-\frac{1}{2\times N}\sum_{i=1}^{N}\sqrt{(x_{\text{target}}-x_{ final})^{2}+(y_{\text{target}}-y_{final})^{2}})\times 100\% \tag{18}\]  
We configure the maximum number of iterations \(\gamma_{1}\) for the three algorithms as 1500. To ensure user QoS in the small-scale UAV deployment scenario, we establish a UAV communication radius of 100 m.  
As depicted in Figure 6, the pink circle represents UAV communication radius. And demonstrated by Tables 3 and 4, all targets are encompassed within the UAV's coverage area. This indicates that all three algorithms are capable of achieving redeployment of the unmanned aerial vehicles within a limited range. In terms of connectivity and coverage,  
Figure 5: Comparison of average computing time.  
all three algorithms are capable of achieving 100% connectivity. The SAIBFGS algorithm yields a user coverage rate of 91%, while the LAESGA algorithm achieves a user coverage rate of 92%, and the SGA algorithm achieves a user coverage rate of 88.5%. Regarding deployment accuracy, the SAIBFGS algorithm boasts a deployment accuracy of 89.85%, the LAESGA algorithm exhibits a deployment accuracy of 90.85%, and the SGA algorithm demonstrates a deployment accuracy of 90.83%.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Coordinate** & **SAIBFGS** & **LAESGA** & **SGA** \\ \hline (444, 326) & (444.17, 326.74) & (460.60, 321.16) & (426.14, 355.8) \\ (88, 286) & (88.65, 286.77) & (83.91, 283.83) & (85.16, 289.06) \\ (94, 331) & (94.68, 331.65) & (82.27, 313.19) & (76.08, 334.73) \\ (370, 296) & (328.45, 275.85) & (334.97, 290.48) & (391.88, 284.28) \\ (386, 81) & (386.72, 81.39) & (388.15, 62.04) & (382.45, 72.84) \\ (89, 38) & (89.47, 38.46) & (110.57, 48.95) & (69.59, 60.12) \\ (57, 41) & (158.88, 85.38) & (54.15, 48.96) & (56.75, 29.28) \\ (236, 146) & (236.42, 146.79) & (251.43, 150.47) & (250.42, 148.75) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Small-area deployment coordinate parameters.  
Figure 6: A simulated representation of the deployment of small area UAVs. (**a**) UAVs initial deployment of small area; (**b**) UAVs final deployment results under the small area LAESGA algorithm; (**c**) UAVs final deployment results under the small area SAIBFGS algorithm; (**d**) UAVs final deployment results under the small area SGA algorithm.