# LoRa Technology Propagation Models for IoT Network Planning in the Amazon Regions
## 5 Results
### Path Loss
#### 5.2.2 Path Loss for Uplink Channels for Spreading Factors 7, 8, and 9  
We present graphs depicting data collected in SF7, SF8, and SF9 along the route. We modeled the data by adjusting the CI and FI models and comparing them with the Okumura-Hata model for suburban environments. The anchoring value of the CI model for the frequency of 915 MHz is 31.67 dB, and this value will be used to model the three SFs under study. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & \(RSSI_{mean}\) (dBm) & \(SNR_{mean}\) (dB) & \(RRP\) (\%) \\ \hline
**SF7** & \(-84.62\) & \(7.54\) & \(75.78\) \\ \hline
**SF8** & \(-85.71\) & \(8.71\) & \(86.29\) \\ \hline
**SF9** & \(-87.76\) & \(8.76\) & \(92\) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Average values of RSSI and SNR and rate of received packets in SF7, SF8, and SF9. Figure 11: Box plot of the distribution of path loss variation of data measured, with 106 dB, 106 dB, and 108.5 dB for the median (in red) of the data in SF7, SF8, and SF9. As mentioned before in Section 4, the \(n,\alpha\), and \(\beta\) parameters are adjusted through the MMSE method, resulting in \(n=2.69\), \(\alpha=29.70\), and \(\beta=2.76\), for SF7. Notably, in Figure 12, the two adjusted models present similar behavior, as the values of \(\beta\) and \(n\) are very close. The uplink channel experiences a more significant loss with distance in the measurement path, and the \(n\) value obtained is greater than the free space conditions due to the high density of trees on the route. The precision of the models is evaluated with a root mean square error (RMSE) between the data and models, yielding values of 6.17 dB, 6.17 dB, and 6.91 dB for CI, FI, and Okumura-Hata, respectively. As the values of \(n\) and \(\beta\) are close, the values of \(RMSE\) for the CI and FI models are also close. For SF8, as shown in Figure 13, the values are \(n=2.73\), \(\alpha=26.19\), and \(\beta=2.93\). Due to the sensitivity of the signal in SF8, its average loss value is greater than the average signal loss value in SF7, resulting in regressions in CI and FI with different slopes, as observed in the graphic. Since there is no significant difference in the slope values of the CI and FI models, it can be concluded that the difference between the \(RMSE\) values will be negligible. In SF8, the \(RMSE\) values for the CI, FI, and Okumura-Hata models are 6.57 dB, 6.55 dB, and 7.53 dB, respectively. Figure 12: Path loss data and the modeling with CI, FI, and Okumura–Hata models for SF7. Figure 13: Path loss data and the modeling with CI, FI, and Okumura–Hata models for SF8. Figure 14 shows that the SF9 has values of \(n=2.78\), \(\alpha=19.16\), and \(\beta=3.23\). Due to the higher average path loss value compared to SF7 and SF8, SF9 presents a significant difference in modeling with CI and FI. This is because SF9 has greater sensitivity to the RSSI and SNR values. In contrast to the observations made in the modeling with SF7 and SF8, the modeling with SF9 revealed slope values with significant differences, which will be reflected in the \(RMSE\) values. For SF9, the \(RMSE\) values are 6.68 dB, 6.57 dB, and 7.87 dB, respectively, for the CI, FI, and Okumura-Hata models. Our study found that the FI model had the best RMSE values among all SFs. The CI model had the second-best RMSE value, and the Okumura-Hata model had the highest RMSE value. Several articles in the literature focus on determining the maximum range distance of LoRa technology for links, presenting values of 6 km for urban and suburban environments, 18 km for rural environments [27; 29; 30; 31; 51; 52], and between 0.4 and 30 km for environments over water [9; 17; 18; 19; 27]. Our experiment was conducted on a route located 50 m away from the riverbank in an environment different from the environments studied in the literature. Our aim is not to determine the coverage or range of LoRa technology across a river, but, rather, to characterize the signal on the banks of the river.