# Rapid Deployment Method for Multi-Scene UAV Base Stations for Disaster Emergency Communications
## 2 System Model
### Channel Model  
For the recovery of UAV communications in the disaster area, we assume that the people who survived in the disaster area can still use their smartphones, but because the ground base stations in the disaster area are overloaded or damaged, it makes it impossible for smartphones to communicate with the outside world. At this time, UAV can be used as a mobile node in the communication network to provide emergency communications for disaster areas. We hypothesized two scenarios that would require UAVs deployment. One scenario would be a large event space, where the large number of user communications requests exceed the load of the ground base station, and the UAVs would overcome geographic barriers that limit communication at the event horizon, providing temporary emergency communications to the region. In the other scenario, where ground base stations are damaged by a disaster such as an earthquake or mudslide [5], UAVs are deployed immediately to provide a temporary emergency communications network in open areas. The Hata-Okumura model [38] is employed to evaluate path loss and signal enhancement. This model enables the assessment of path loss in urban, suburban, and rural environments, and can be represented as follows:  
\[P_{loss} =69.55+26.16 lg(f_{o})-13.82 lg(h_{sta})-\mathbb{Z}(h_{msta})+(44.9 -6.55 lg(h_{sta}))\times lg(D)+\Bbbk \tag{1}\]  
\[\mathbb{Z}(h_{msta})=\left\{ \begin{array}{ll}3.2\times(lg(11.75 \leavevmode\
obreak\ \times h_{msta}))^{2}-4.97\leavevmode\
obreak\ f_{0}>300 MHz\\ 8.29\times(lg(1.54\leavevmode\
obreak\ \times h_{msta}))^{2}-1.1f_{0}\leq 300 MHz\\ (1.11\leavevmode\
obreak\ \textit{lgf}_{0}-0.7)h_{msta}-1.56 lg\leavevmode\
obreak\ \textit{f}_{0}+0.8\leavevmode\
obreak\ \textit{others}\end{array} \right. \tag{2}\]  
\[\Bbbk=\left\{ \begin{array}{ll}0&\textit{urban}\\ -2\times(lg(f_{0}\leavevmode\
obreak\ /28))^{2}-5.4&\textit{suburban}\\ -4.78\times(lg(f_{0}))^{2}+18.33\times lg(f_{0})-40.98&\textit{ rural}\end{array} \right. \tag{3}\] \begin{table}
\begin{tabular}{c c} \hline \hline
**Notations** & **Description** \\ \hline \(h_{msta}\) & The effective height of the user equipment antenna on the rescue surface \\ \(h_{sta}\) & The effective height of the UAVs station antenna \\ \(\omega\) & The number of chromosomes \\ \(C_{i}\) & The offspring chromosome \\ \(F_{i}\) & The parent chromosome \\ \(\lhd\) & The crossover probability \\ \(>\) & The mutation probability \\ \(\gamma_{1},\gamma_{2}\) & Number of iterations \\ \(P_{t}\) & UAVs launch power \\ \(P_{r}\) & Power received by ground users to be rescued \\ \(C_{target}\) & The coordinates of the target deployment points \\ \(C_{final}\) & The final deployment coordinates \\ \(M_{i}\) & The number of users in need of rescue within the coverage range of the UAVs \\ \(M_{COV}\) & The user coverage ratio \\ \(\underline{S}\) & The accuracy of deployment \\ \(F_{BW}\) & Bandwidth frequency \\ \(\mathfrak{M}\) & Data transmission rate \\ \(SINR\) & The signal-to-noise ratio of the communication. \\ \(\sigma,\tau\) & Random variable \\ \(erf\) & Error function \\ \(U\) & A random number uniformly distributed over an interval (0,1) \\ \(C_{D}\) & The discrete coefficient of user distribution on the ground to be rescued \\ \(Z_{person}\) & The coordinates of the ground users to be rescued \\ \(P_{extra}\) & A power loss function \\ \hline \hline \end{tabular}
\end{table} 
Table 1: \(Cont.\)In the equation, \(h_{msta}\) represents the effective height of the user equipment antenna on the rescue surface, \(h_{sta}\) represents the effective height of the UAVs station antenna, \(D\) represents the horizontal distance between the users equipment antenna on the rescue surface and the UAVs station antenna, \(\mathbb{Z}(h_{msta})\) is the antenna parameter calibration factor, \(\mathbb{k}\) is the scenario type calibration factor, and \(f_{0}\) is the carrier frequency of the U2U channel.