## 2 System Model  
This article considers an AG-HetNet before and after a disaster, as shown in Figure 2. In particular, Figure 2a shows a typical public safety network with most of the geographical area under broadband coverage before a disaster. In a disaster, the public safety network infrastructure is destroyed and the first responders and victim users experience an SE outage, as illustrated by the white areas in Figure 2b. Furthermore, Figure 2b also illustrates that GUEs are clustered at locations irrespective of the cellular coverage and infrastructure. To simulate the public safety scenario, a two-tier AG-HetNet is modeled, with 3D locations of MBS and UABS captured in matrices \(\mathbf{L}_{\text{mBS}}^{\text{3D}}\in\mathbb{R}^{N_{\text{mBS}}\times 3}\) and \(\mathbf{L}_{\text{uabs}}^{\text{3D}}\in\mathbb{R}^{N_{\text{uabs}}\times 3}\), respectively, with \(N_{\text{mBS}}\) and \(N_{\text{uabs}}\) denoting the number of MBSs and UABSs within the simulation area (ARsim). Similarly, the 3D distribution of GUEs is captured in matrices \(\mathbf{L}_{\text{gue}}\) with a density of \(\Lambda_{\text{gue}}\) and modeled using the Matern cluster process (MCP) and Thomas \begin{table}
\begin{tabular}{c c} \hline \hline
**Symbol** & **Description** \\ \hline \(f_{\text{c}}^{\text{B14}}\) & Carrier frequency in PSC band 14 \\ \(h_{\text{bs}}\) & Altitude of the base station in Okumura–Hata model \\ \(h_{\text{mBS}},h_{\text{uabs}}\) & Altitude of MBS and UABS \\ \(h_{\text{gue}}\) & Altitude of a UE in Okumura–Hata model \\ \(d_{\text{mBS}},d_{\text{mBS}}\) & UE distance from MOI and MOI \\ \(\text{Pow}_{\text{mBS}}^{\prime}(\text{d}_{\text{on}})\) & RSRP from MOI \\ \(\text{Pow}_{\text{uabs}}^{\prime}(\text{d}_{\text{un}})\) & RSRP from UOI \\ \(\text{Iagg}\) & Aggregate interference at GUE from all base stations, except MOI/UOI \\ \(\Gamma_{\text{usf}}^{\text{mBS}},\Gamma_{\text{uabs}}^{\text{uabs}}\) & SIR from MOI and UOI in USF subframes \\ \(\Gamma_{\text{usf}}^{\text{mBS}},\Gamma_{\text{uas}}^{\text{uas}}\) & SIR from MOI and UOI in CSF subframes \\ \(\alpha_{\text{mBS}}\) & MBS Power reduction factor during CSF transmission \\ \(\beta_{\text{mBS}}\) & Duty cycle for USF transmission \\ \(T_{\text{uabs}}\) & Cell range expansion bias \\ \(\rho_{\text{mbs}}\)\(\rho_{\text{uabs}}\) & Scheduling threshold for MUE and UUE \\ \(N_{\text{uas}}^{\text{mBS}},N_{\text{uas}}^{\text{uas}}\) & Number of USF-MUEs and CSF-MUEs \\ \(N_{\text{uas}}^{\text{uas}},N_{\text{uas}}^{\text{uas}}\) & Number of USF-UUEs and CSF-UUEs \\ \(\text{Cmbs}_{\text{uas}},C_{\text{csf}}^{\text{mbs}}\) & Aggregate SEs for USF-MUEs and CSF-MUEs \\ \(\text{Cusus}_{\text{uas}}^{\text{uas}}\) & Aggregate SEs for USF-UUEs and CSF-UUEs \\ \(\Gamma_{\text{uabs}}^{\text{uas}}\) & Fixed hexagonal locations of deployed UABS \\ \(\text{SICIC}\) & Matrix representation of ICIC parameters for MBSs \\ \(\text{Pob}_{\text{uabs}}^{\text{SIC}}\) & Matrix representation of ICIC parameters for UABSs \\ \(\mathbf{rad}\) & Radius of the Matern Cluster Process \\ ARsim & Simulation area \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._  
Figure 2: Illustration of Typical PSC AG-HetNet and SE coverage before/after a disaster. cluster process (TCP). Wherein MCP and TCP are the special cases of the Neyman-Scott process [37],
* MCP: To simulate the MCP distribution, we assume a homogeneous Poisson point process with an intensity \(\Lambda_{\text{gue}}\) within the \(\text{AR}_{\text{sim}}\). For each point of the underlying point process, a Poisson number of points is simulated with mean \(\mu>0\) and distributed uniformly on a disk with a constant radius \(\mathbf{rad}>0\). The considered underlying point process is also called the parent (point) process and its points are the centers of the cluster disks. The subsequent point process on all the disks is called the daughter (point) process and is responsible for forming the clusters.