## 4 Simulation Verification
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \begin{tabular}{c} **Base** \\ **Station 3** \\ \end{tabular} & \begin{tabular}{c} **Base** \\ **Station 4** \\ \end{tabular} & \begin{tabular}{c} **Satellite 5** \\ \end{tabular} & \begin{tabular}{c} **Satellite 6** \\ \end{tabular} & \
\begin{tabular}{c} **Satellite 7** \\ \end{tabular} &
\begin{tabular}{c} **Satellite 8** \\ \end{tabular} \\ \hline GNSS & / & / & S15 & S16 & S17 & S18 \\
4G & S23 & S24 & / & / & / & / \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Statistical table of all the S-parameters that need to be solved. Figure 12: Arrangement of the transmission and receiving antennas within the model. describes the signal transmission capability from satellite 5 to the vehicle-mounted GNSS antenna. The remaining S-parameters follow this pattern accordingly. During the design phase, we comprehensively considered channel characteristics, antenna configuration, and environmental factors to ensure that the listed parameters accurately represent the actual performance of the system. Furthermore, these data can be utilized to evaluate the overall performance of the communication system, including signal quality and stability, thereby providing a scientific basis for optimizing the design scheme. After simulating and solving the three-dimensional electromagnetic model, we obtained all of the relevant parameters listed in Table 1, as shown in Figure 13. These parameters underwent in-depth statistical data analysis, ultimately leading to the summary of all S-parameters between the transmitting and receiving antennas, as shown in Table 2.  
Specifically, Table 2 summarizes the transmission coefficients of the S-parameters at frequencies ranging from 1 to 1.6 GHz; these parameters are crucial indicators for assessing the coupling effect between the transmitting and receiving antennas, as well as the signal transmission performance. By analyzing these S-parameters, we can clearly understand the \begin{table}
\begin{tabular}{l c c c c c} \hline \hline  & \multicolumn{2}{c}{**GNSS (dB)**} & \multicolumn{3}{c}{**4G (dB)**} \\ \hline
3 & & / & / & S23 & \(-\)44.491 & \(-\)65.345 \\
4 & & / & / & S24 & \(-\)42.272 & \(-\)78.402 \\
5 & S15 & \(-\)71.4798 & \(-\)91.0719 & / & / & / \\
6 & S16 & \(-\)80.0948 & \(-\)102.386 & / & / & / \\
7 & S17 & \(-\)69.4918 & \(-\)90.929 & / & / & / \\
8 & S18 & \(-\)81.0894 & \(-\)101.43 & / & / & / \\ \hline \hline \end{tabular}
\end{table} 
Table 2: S-parameters between the transmitting and receiving antennas. Figure 13: Simulation results of the S \(-\) parameters in the frequency range of 1 to 1.6 GHz. changes in signals during transmission and reception, thereby revealing the interactions among various antennas. From Table 2, we can observe that the maximum absolute value of the S-parameters between the satellite and the vehicle's GNSS antenna was 102.386, while the maximum absolute value of the S-parameters between the base station and the vehicle's 4G antenna was 78.402. These values indicate that larger absolute S-parameter values signify a more severe coupling loss between the transmitting and receiving antennas. Such coupling loss directly affects signal transmission efficiency. Table 3 illustrates that, according to the 3 GPP standard specifications [11], the MCL is defined as a critical metric for evaluating the coverage range of wireless access technologies. Theoretically, the MCL can be interpreted as the maximum loss of transmitted power that the system can withstand while still functioning properly; it serves as the critical threshold for achieving normal data transmission. In other words, exceeding this loss level may render the system unable to maintain stable signal transmission. From the data presented in Tables 2 and 3, it is evident that although the S-parameter values obtained from the simulation are relatively high, they still fall short of meeting the MCL parameter specified in industry standards.