# AoI Analysis of Satellite-UAV Synergy Real-Time Remote Sensing System
## 4 Numerical Results
Such algorithms are particularly important in dense urban or disaster scenarios where interference is more likely to degrade communication quality. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter of SAT**[45] & **Value** \\ \hline Orbital height (LEO) & \(H_{s}=600\) km (LEO) \\
3 dB beamwidth & \(\theta_{s,3\mathrm{dB}}=8.8320^{\circ}\) \\ Beam diameter & \(r_{s}=45\) km \\ Downlink carrier frequency & \(f_{c}=2\) GHz (\(\mathrm{S}\)-band) \\ Satellite maximum antenna gain & \(G_{s,\mathrm{max}}=24\) dBi \\ \hline
**Parameter of UAV** & **Value** \\ \hline Altitude of UAV & \(H_{u}=5\) km \\ Half beamwidth of UAV & \(\phi_{u}=80^{\circ}\)[39] \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Simulation Parameters. In the following content, define the relative performance advantage of AAoI\({}_{PW}^{FF}\) over AAoI\({}_{PW}^{FD}\) as AAoI\({}_{adban}=-(\)AAoI\({}_{PW}^{FF}-\)AAoI\({}_{PW}^{FD})\), which quantifies the advantage of the FFR strategy over the FDMA strategy in terms of AAoI\({}_{PW}\). Moreover, the metric energy advantage (EA) is defined to evaluate AAoI\({}_{adban}\) per unit transmit power in this paper. The EA with respect to \(p_{u}\) and \(p_{s}\) is calculated as  
\[\text{EA}(p_{u},p_{s},B)=\frac{\text{AAoI}_{adban}}{10^{(p_{s}-30)/10}+10^{(p_{ u}-30)/10}}. \tag{22}\]  
To clearly illustrate the numerical differences in energy advantage under various parameter settings, we converted the units of \(p_{s}\) and \(p_{u}\) from dBm to Watts through \(10^{(p_{s}-30)/10}\) and \(10^{(p_{u}-30)/10}\). Similarly, define the metric spectrum advantage (SA) to evaluate AAoI\({}_{adban}\) per unit spectrum resource in this paper. The SA with respect to \(B\) is calculated as  
\[\text{SA}(p_{u},p_{s},B)=\frac{\text{AAoI}_{adban}}{B} \tag{23}\]  
In Figure 8, EA > 0 indicates that under the current settings of \(p_{u}\) and \(p_{s}\), the FFR strategy outperforms FDMA in AAoI\({}_{adban}\) per unit transmit power. This indicates that under these settings, the FFR strategy exhibits superior energy efficiency compared to FDMA. It verifies that FFR can be a preferable strategy in scenarios where energy resources are constrained, such as in battery-operated UAVs or power-limited satellites. As \(p_{s}\) increases, more energy is consumed, leading to a decrease in EA. This is due to the fact that it is inefficient to reduce the AoI by increasing the rate of only one Poisson process. However, when more \(p_{s}\) is spent, EA is still above 0, especially when \(p_{u}\) < 15 dBm. This is mainly due to two reasons. On the one hand, the FFR strategy can improve the spectrum efficiency and network throughput in SAGIN, which improves the AoI performance. On the other hand, appropriately increasing \(p_{s}\) can improve the SINR of the SAT-GU channel, which mitigates the effects of interference from the UAV-GU channel to the SAT-GU channel and then enhances the resistance of the satellite signal. This improves the communication  
Figure 7: AAoI\({}_{PW}\) in dBi. rate of the SAT-UAV channel and, to some extent, improves the AoI performance of the fused information at GU under the FFR strategy. This insight suggests that power control strategies should be an integral part of network design. In practice, the AoI of fused remote sensing information in the SAGIN network can be improved by deploying the power control mechanism to adjust the satellite power output according to the real-time interference level. Additionally, as \(p_{u}\) increases, the interference from the UAV-GU channel to the SAT-GU channel increases, thereby reducing EA. For example, as shown by the blue line in Figure 8, when \(p_{s}=45\) dBm and \(p_{u}>21\) dBm, EA becomes less than 0. The reduced EA at high \(p_{u}\) highlights the significance of interference management in SAGIN. Techniques such as interference cancellation, beamforming, and advanced modulation schemes could be employed to reduce the impact interference, thereby further improving the AoI performance of fused information in SAGIN.