## 6 Propagation Models Versus Measurements  
To find the best propagation model that matches the measurement results, we consider the following five well-known propagation models: (i) Free Space; (ii) Shadowing Path Loss; (iii) Egli; (iv) Hata; and (v) COST 23. These propagation models and their implications when deploying Wi-Fi-based VANETs in a large shopping mall are discussed next. This section also highlights the superior performance of the \"Free Space\" and Hata models in Scenario 1, the close agreement of the Egli model with measurement data in Scenario 2, the slight advantage of the Egli model in Scenario 3, and the good agreement of the \"Free Space\" model in Scenario 5. For the path loss calculation, factors such as transmitter power, receiver sensitivity, cables, antennas, free space loss, and other losses are considered. All the models used are suitable for their intended purposes, but they all operate in the \"Far field region\". Table 7 provides an overview of the parameters used in the five empirical propagation models. Figures 15-18 show the accumulated path losses for the five selected propagation models. The received signal strength versus the distance plot is also presented, revealing the performance of the five models. Upon comparing the practical measurement path losses with the theoretical model values, a difference is observed. It is important to note that the theoretical data may not precisely match real-world applications due to environmental \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Frequency (f) & 2.4 GHz \\ Speed of light (c) & \(3\times 10^{8}\) m/s \\ Wavelength (a) & 0.125 m \\ Linear size of the antenna (D) & 0.25 m \\ Reference distance (d\({}_{0}\)) & 1 m \\ Power of radio wave on the transmitting antenna (P\({}_{t}\)) & 0.03162 W \\ Power of radio wave on the reference distance (P\({}_{r}=d_{0}\)) & 3.93 \(\times\)\(10^{-5}\) W \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Parameters used in the propagation models. factors and operating conditions. However, it is evident that higher frequencies generally result in greater losses. Figure 15 compares different propagation models' path losses in Scenario 1, with the \"Free Space\" and \"Hata\" models displaying the lowest predictions. The RSSI values decrease as the distance increases. The \"Free Space\" model has the superior path loss prediction, while the \"COST 231\", \"Egli\", and \"Shadowing Path Loss\" models overestimate path loss. The \"Hata\" and \"Free Space\" models closely match the measured data and are recommended for evaluating signal propagation under non-line-of-sight conditions. Figure 16 compares the path loss models in Scenario 2. The \"Egli\" model has the lowest path loss prediction, while the \"Hata\" model exhibits the highest. The \"Hata\" model slightly distorts the power-distance relationship under NLOS conditions but agrees well  
Figure 16: Scenario 2—RSSI versus distance for NLOS conditions: Comparison between the measurement and five models. Figure 15: Scenario 1—RSSI versus distance for NLOS conditions: comparison between the measurement and five models. with the measured data. Other models overestimate path loss. Therefore, the \"Hata\" model is recommended for accurate signal propagation evaluation in Scenario 2. Figure 17 compares path loss predictions of the different propagation models in Scenario 3. The \"Egli\" model shows the lowest path loss, ranging from \(-71.64\) dBm to \(-74.54\) dBm, for distances of \(8\) m to \(9.43\) m. Under non-line-of-sight conditions, the \"Egli\" model slightly distorts the power-distance curve but aligns well with the measured data. The \"Shadowing Path Loss\", \"Free Space\", \"Hata\", and \"COST 231\" models yield higher path loss predictions, which are considered unrealistic and disregarded under NLOS conditions. Based on the measured and model results, the \"Egli\" model is the closest match and demonstrates good agreement with the data.