## 3 Verification and Analysis
### Typical Scenario Analysis
Additionally, detailed information is displayed in the red team's jamming power and the red team's signal-to-noise ratio (SNR). \begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline \multirow{2}{*}{**Device Name**} & \multirow{2}{*}{ \begin{tabular}{c} **Frequency to** \\ **Be Selected** \\ **(MHz)** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Power and** \\ **Antenna Gain** \\ **(Hz/P/P_D),** \\ **rfc/b/c,** \\ **rfc/b/c,** \\ **rfc/b/c,** \\ **rfc/b/c,** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Longitude and** \\ **Latitude** \\ **(Hz/P/P_D),** \\ **rfc/b/c,** \\ **rfc/b/c,** \\ **rfc/b/c,** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Modulation** \\ **Scheme** \\ **(m)** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Coding Scheme** \\ **(m)** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Altitude** \\ **Priority** \\ **Antenna Type** \\ \end{tabular}  } & \multirow{2}{*}{\ \begin{tabular}{c} **Frequency** \\ **Priority** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Antenna Type** \\ **(m)** \\ \end{tabular}  } \\ \hline Communication & & & [116.5372, 39.7563] & & & & & 26 \\ \cline{1-1} Agent 1 & & & [116.6348, 39.8921] & & & & & 23 \\ \cline{1-1} \cline{3-10} Communication & & & [116.2436, 39.9314] & The simulation is configured for 6 (supporting & & & & 22 \\ \cline{1-1} \cline{3-10} \cline{3-1 mation about both teams' agents is shown in the expanded panel on the left side of the interface, as illustrated in Figure 5.  
To avoid the stochastic noise introduced by Monte Carlo simulations, we conducted 100 simulation rounds. We verified by calculating the total interference and the sum of interferences for agents of the red team and blue team over the 100 rounds. Figure 6 shows the comparison of interference counts for red team defensive agents based on the MCCFR and MC strategies. From the figure, it can be observed that in 100 rounds of simulation, the interference counts for agents based on the MCCFR algorithm are consistently lower than those based on the MC algorithm. Among the eight agents employing the two algorithms, the MCCFR-based agents experienced an average reduction of 11 interference instances compared to the MC-based agents. Notably, Agent 6 exhibited the greatest reduction in interference counts, with a decrease of 20 instances. Figure 7 compares jamming failures for blue team attacking agents based on the MCCFR and MC strategies. The figure shows that in 100 rounds of simulation, the number of successful jamming attempts by agents based on the MCCFR algorithm is consistently higher than that of agents based on the MC algorithm. Among the eight agents employing the two algorithms, the MCCFR-based agents achieved an average increase of 14 successful jamming attempts compared to the MC-based agents. Notably, Agent 5 exhibited the most significant improvement in jamming success, increasing 27 instances. Figure 8 illustrates the frequency selection counts and the interference counts for the chosen frequency bands by the red team agent. It is evident from the figure that the red team agent selected 40 MHz as the central frequency for communication the most frequently, with a total of 228 selections, accounting for 28.50% of all frequency selections. This frequency band experiences interference only 64 times, resulting in an interference percentage of just 28.07%. The red team agent selects 80 MHz as the central frequency for communication the least frequently, with only 80 selections, representing 10.00% of all frequency selections. This frequency band experiences interference 42 times, resulting in an interference percentage of 52.50%. In contrast, the selection of 2700 MHz as the central frequency by the red team is the second most frequent after 40 MHz, with a total of 220 selections, accounting for 27.5% of the total frequency choices.