## 4 Numerical Results  
In this section, the analytical study is verified by numerical results that were obtained using MATLAB and the Wolfram Mathematica program. The numerical expressions were produced by Wolfram Mathematica 13. The values of the parameters used to calculate the findings are shown in Table 2.  
Figure 2 shows the achievable rate (bits/sec/Hz) versus bandwidth (GHz). Increasing the bandwidth provides an increase in the achievable rate. In addition to power consumption, one of the main objectives in designing a communication system is maximizing the achievable rate. However, as bandwidth increases, the achievable rate decreases according to the law of diminishing returns. In fact, the rate of growth in the attainable rate of a wideband-coherent communications system changes as a function of the bandwidth, B. As a result, the possible rate per unit of power often depends on the bandwidth that is available without rising. Figure 3 provides the required transmission power as a function of bandwidth. As available bandwidth increases, the transmission power optimization value will increase. Also, a wider bandwidth prevents transmission power reduction, especially when the bandwidth is greater than 5 GHz. Figure 4 shows the average capacity versus the SNR. We can obtain the values of the two distinct frequencies of the various fading channels based on mathematical analysis. The average capacitance rises with increasing frequency. The capacity of the 5 THz system with a Nakagami-m (\(m=2\)) channel fading is better than others. Figure 5 shows the outage probability (\(P_{out}\)) versus the transmission distance for different fading channel types. From farther away, the \(P_{out}\) increases. The Nakagami-m fading channel has the shortest \(P_{out}\) when the distance is short, whereas the Weibull fading channel (\(\beta=2\)) has a larger \(P_{out}\) than the Rician fading channel (\(K=2\)). The \(P_{out}\) of Rician fading is higher than that of the log-normal fading channel. The \(P_{out}\) of log-normal fading is greater than that of the Rayleigh fading channel. When distance is far--more than 300 m--the Nakagami-m fading channel obtains the highest \(P_{out}\), whereas the Weibull fading channel (\(\beta=2\)) achieves a slightly lower \(P_{out}\) than the Nakagami-m fading channel. The order of outage probabilities from best to worst is Nakagami-m > Weibull > Rician > log-normal > Rayleigh. The \(P_{out}\) versus SNR values for several fading channels are shown in Figure 6. Increasing the SNR reduces the likelihood of an outage for all fading channel types. Since the SNR rises with signal strength, the probability of an outage decreases. The findings unmistakably demonstrate that the Nakagami-m fading channel's performance has the best performance with the lowest outage probability. \begin{table}
\begin{tabular}{l l} \hline \hline
**Parameters** & **Values** \\ \hline \(f\) & 1–5 THz \\ \hline G\({}_{\text{T}}\), G\({}_{\text{R}}\) & 1, 1 \\ \hline \(d\) & 0–500 m \\ \hline \(\sigma_{R}\), \(\sigma_{Noise}\), \(\gamma_{th}\) (dB) & 10, \(-\)50, 5 \\ \hline \(\alpha\) & 2 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Value of parameters utilized in the numerical results [5; 8; 12]. In Figure 7, the number of UAVs is shown versus the likelihood of an outage. The \(P_{out}\) grows as the UAV fleet expands. The network architecture rapidly changes as the number of UAVs increases, making communication unstable and increasing the probability of outages. The highest \(P_{out}\) is experienced by the model using a Rayleigh fading channel, whereas the model using a Nakagami-m fading channel achieves the smallest amount (\(m=2\)). Figure 8 displays the BER versus SNR values for modulation types under different fading channels. The performance of the system improves as the SNR becomes higher. As a result, the BER goes down. The BER versus SNR value is 2-QAM < BPSK. When compared with the performance of other fading channels, the Nakagami-m fading channel provides superior results for the system.