## 5 Results  
After filtering the received signal, the linear regression method was used in the fading samples to estimate the path loss. Figure 6 shows the path loss for flights over the lake (scenario 1). For higher altitude flights, the signal presented a positive exponent (gain) and negative exponent for the route of lower altitudes. This effect is related to the first partially cleared Fresnel zone [5], as also observed in [12]. In flights at greater heights, the path loss decreases as distance increases, as observed in [22; 47]. In [47], an experimental path loss study was carried out with the UAV flying at an altitude of 1 km. The work showed that the power received at the base station increases as the aircraft moves away from the base station, until it reaches its maximum value and then begins its decline, that is, the intensity of power received at the base station decreases as the aircraft moves away. This result of gain with increasing distance was observed in this work for all environments, except for flights at 8 m of altitude, as observed in Figure 6. In [48], the work analyzed the path loss of a mobile communication system in a forest, and the results showed that the values varied in a range between 1.6 and 4.4. The same result was observed in this work, as shown in Table 6. The exceptions were for the low altitude flight environment over the lake, which presented a high exponent modulus of path loss. Figure 5: Mixed scenario. (**a**) Mixed scenario photo taken by the UAV at 80 m. (**b**) Full view of the mixed scenario. Figure 6: Path loss of flights over the lake. Figure 7 shows the path loss to the Caatinga scenario with the flight at an 80-m height and speeds of 1 and 3 km/h. The same behavior of Figure 6 is observed considering the flight at a height of 80 m, with higher received power levels as distance increases. The scenario tangent to the lake presented the same trend, as shown in Figure 8. Therefore, the communication between the UAV and the BS at the moment the aircraft flies over the BS may be hampered due to the use of dipole antennas. Appendix A illustrates the dipole antenna radiation pattern, showing the decreasing antenna gain for upper directions (Figure A2). However, when the UAV starts to move away from the base station, the antenna gain starts to increase due to the change in the main Fresnel zone. Equation (2) was used to estimate the path loss exponent, as shown in Table 6. As expected, path loss exponents for low-altitude flights have a negative exponent. For the purpose of comparison, reference values for path loss exponents are 2 for free space and 4 to 6 for channels obstructed by buildings. Thus, low-altitude flights have a more severe path loss. Figure 8: Path loss of flights over the mixed region. Figure 7: Path loss of flights over the Caatinga. We use the maximum likelihood method to estimate the parameters of the Nakagami, Rice, Rayleigh, and Weibull distributions, as shown in Table 8. These results display the parameters of distributions from the measured samples. The Kolmogorov-Smirnov (KS) test was used to compute the similarity of the empirical CDF (from measurements) and theoretical CDFs of all distributions at a significance rate of 95%. The KS test indicates Weibull as the best-fit distribution for the collected data. Using the estimated parameters \(\beta\) of the Weibull distribution (Table 8), the theoretical CDFs were computed and plotted to compare with the empirical CDFs, as shown in Figures 9-11. We can notice the good curve-fitting of empirical and estimated CDFs. Figure 9 presents the results for the Lake region for a height and different speeds in the same plot. We observe a higher small-scale fading variation at a lower speed (Figure 9a). We can deduce that the lower the speed of the aircraft, the worse the flight stabilization, which causes a higher variation in the small-scale fading. Additionally, we can also observe that the results of flights at 80 m do not show significant differences, regardless of the speed (Figure 9b).