# Path Loss Model for Outdoor Parking Environments at 28 GHz and 38 GHz for 5G Wireless Networks
## 6 Results and Discussions
### Path Loss Models Results
The parameters of the proposed path loss models are listed in Table 3. Hence, it can be concluded that the proposed model was a physical-based model (accurate model) and a simple model: only one parameter needs to be estimated, which is the parking lot loss factor \(k_{f}\). The \(k_{f}\) factor provided the effect of parking lot using a PLE of 2 (FSPL exponent) for different frequencies. Figure 3.0 The proposed PLM at 38 GHz. Figure 3.1 The proposed parking lot path loss model (PLM) at 28 GHz. In addition to the FI path loss model, the ABG models were proposed as multi-frequency path loss model with three main parameters. As shown in Table 4, the three-parameter ABG model had the lowest standard deviation in DPL compared to the SPL by 1 dB. The distance dependent factor \(\alpha\) values in DPL and SPL were 0.6 and 2.9, respectively. The frequency dependent factor \(\gamma\) values were 3.8 and 0.9 for SPL and DPL, respectively. This significant difference in value of slope indicates that more constructive reflections that in DPL as compared to SPL case study. Even though the DPL showed higher performance than the SPL, it was at the expense of an additional optimization factor by roughly 120 dB as compared to the SPL. The reason behind the optimization factor difference can be expected, since some path loss values for the DPL had a high difference compared to mean DPL path loss values as shown in Figure 3.2 The three-parameter ABG model can typically obtain an additional accuracy comparing with other models at the  
To show scalability of the proposed framework, some additional numerical results are provided in this section. Figures 10 and 11 show the predicted received power at 28 and 38 GHz, respectively. This was calculated based on proposed path loss models in this work at Tx power of 25 dBm. The received power values were calculated at the Tx-Rx separation distance beyond the measurement distance. The received power presents ratio of the transmitted power to the path loss. The predicted received power at different Tx-Rx separation distance is presented in Table 5 at 28 GHz and 38 GHz bands for SPL and DPL scenarios. The complexity for the path loss models was evaluated based on the number of estimated parameters using MMSE approach [2]. The PLM proposed model and CI model outperformed the FI and ABG models in terms of computation complexity. For the PLM and CI models, only one parameter for each one was required to be estimated by the MMSE approach, which were \(n\) and \(\mathrm{k}_{\mathrm{f}}\), for CI and PLM respectively. The FI path loss model has two parameters (\(\alpha\) and \(\beta\)) which were estimated by MMSE. The computation complexity of ABG model was the highest one, where three parameters (\(\alpha\), \(\beta\) and Y) needed to be estimated using MMSE. In conclusion, the complexity of FI and ABG models are two and three times more than the complexity of PLM and CI models, respectively. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Scenario** & **Model** & \(n\) & \(\alpha\) & \(b\) & \(\gamma\) & _Kf_ & \(\sigma\)**[dB]** \\ \hline SPL & \multirow{2}{*}{ABG} & - & 2.9 & 2.4 & 3.8 & - & 2.9 \\ DPL & & - & 0.6 & 120.8 & 0.9 & - & 1.9 \\ \hline SPL & \multirow{2}{*}{CI} & 2.8 & - & - & - & - & 3.2 \\ DPL & & 3.3 & - & - & - & - & 3.4 \\ \hline SPL & \multirow{2}{*}{PLM} & 2 & - & - & - & 11.8 dB & 3.0 \\ DPL & & 2 & - & - & - & 21.1 dB & 3.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Multi-frequency path loss model for 28 GHz and 38 GHz. Figure 10: Predicted received power at 28 GHz.