## 4 Experiments and Results  
The experimental circumstance provides the WUGSN design using Network Simulator 3.0 (NS 3.0). In this experiment, wireless sensor network patches are installed and WUGSN parameters are configured as illustrated in Tables 2 and 3. The NS 3.0 sensor network package provides the configuration features related to noise, interference, amplitude, and underground channel constraints. Additionally, the proposed network model consists of electromagnetic signal characteristics and acoustic characteristics. Consequently, the proposed techniques are developed using C++ and Python 3.8 languages in the modelled network base. Figure 4: System design of proposed DMCAP phases. The configured WUGSN has the proposed techniques under Medium Access Control (MAC) policies as inbuilt patches. The network works under 3.5 GHz band around 500 m\({}^{2}\) area. The built-up network area contains the sensor nodes with underground channel characteristics and open surface characteristics. Table 2 shows the WUGSN characteristics of surface sensor nodes and Table 3 illustrates the configurations of underground channel parameters. The dual-type channel quality configurations ensure close real-time WUGSN channel assumptions [43]. As provided in Figure 3, the knowledge base maintains channel parameter attributes and malicious event attributes (Knowledge Discovery in Databases (KDD'99)). Figure 5 shows the variations in major channel quality parameters such as channel interference rate, channel data transfer rate, and overall channel uncertainty rate. Moreover, Figure 5 denotes the distortion rates at probability scale measurement. The observed measurements present the reduction in data transfer rate as uncertainty and interference rates are increasing over time. The experiment confirms that underground and surface level channel distortions severely affect sensor node's data communication efforts [44]. The test bed of WUGSN initially observes the wireless channel quality metrics and channel distortions as provided in Figures 5 and 6. Figure 6 relates the quantity of data retransmission rate and channel noise production rate. Generally, noise is defined as unwanted signals that disturb the original data communication. \begin{table}
\begin{tabular}{l l} \hline
**Test Bed Features** & **Features** \\ \hline Tool & NS-3.0 \\ MAC & CSMA/CA \\ Channel Assessment Model & DMCAP \\ Routing Protocol & AOMDV \\ Number of Sensor Nodes & 40, 80, 100 \\ Attack Dataset & KDD’99 \\ Transmitter Power (W) & 0.56 \\ Receiver Power (W) & 0.31 \\ Channel Throughput (Kbps) & Variable \\ Coverage (meters) & 50 (maximum) \\ Channel & Surface (Air) \\ Mobility & Surface-Random Way Point \\ Propagation & Two Ray Ground \\ \hline \end{tabular}
\end{table} 
Table 2: WUGSN-surface channel configuration parameters. \begin{table}
\begin{tabular}{l l} \hline
**Test Bed Features** & **Features** \\ \hline Tool & NS-3.0 \\ MAC & CSMA/CA \\ Channel Assessment Model & DMCAP \\ Routing Protocol & AOMDV \\ Number of Sensor Nodes & 40, 80, 100 \\ Attack Dataset & KDD’99 \\ Transmitter Power (W) & Variable \\ Coverage (meters) & 50 (maximum) \\ Channel & Surface (Air) \\ Mobility & Surface-Random Way Point \\ Propagation & Two Ray Ground \\ \hline \end{tabular}
\end{table} 
Table 3: WUGSN configuration parameters. Figure 5: Channel quality measurements. Figure 6: Channel distortion rate. \[\text{Channel Interference Rate}=\frac{\text{S}^{\text{I}}}{\text{S}^{\text{O}}}*100 \tag{24}\]
* \(\text{S}^{\text{I}}\)-Signal from communicating parties;
* \(\text{S}^{\text{O}}\)-Signals from other nodes. \[\text{Channel Data Rate}=\frac{\text{TH}}{\text{SD}} \tag{25}\]
* \(\text{TH}^{\text{T}}\)Data Transfer Rate between nodes in bits per second;
* \(\text{SD}^{\text{S}}\)Session Duration in seconds.