## 5 Comparison of Experimental and Numerical Results and Discussions
### Direct Experiment and Coverage Measurement  
The results of the direct experiment are shown in Figure 19. The graphs show that both the measured and simulated throughputs are saturated up to 45 m, after which they decay. The difference between the measured and simulated values after the saturated throughput is because the numerical evaluation shows a continuous throughput, but the actual throughput is discrete due to the selection of MCS and other factors. A summary of the coding rates, etc. for each MCS in IEEE802.11 ad is shown in Appendix B. In addition, we believe that this is because the numerical evaluation was able to take modulation, etc. into account in the MCS in the saturated throughput state due to \(\alpha\) in Equation (12), but not in the other MCS states. Figure 19: Comparative results of direct experiment. A comparison of the numerical evaluation and empirical results of the coverage experiment is shown in Figure 20. There is a similar performance trend between the theoretical and experimental results, although there is a close agreement when the horizontal distance is short and a slight error when it is long. As in the previous case, here too, we believe that the difference between the measured and simulated values is due to the difference in MCS, which is different from the \(\alpha\) at saturation. In addition, the distributions at saturated throughput in Figures 19 and 20 are almost identical, indicating that the attenuation at saturation can be taken into account with \(\alpha\) utilized in Equation (12). As the horizontal distance increases, the error is not only due to the choice of MCS, but in fact may be due to the position error caused by the wind of the UAV and the deterioration of antenna directivity due to its tilted angle. In addition, when the received power is high, a high MCS also results in a high throughput. Therefore, the throughput is close to the Shannon capacity at high MCS values. In this case, \(\alpha\) is set at high MCS at saturation, which means that the simulated value is larger than the measured value, because when the attenuation is high and MCS is low, the \(\alpha\) must be even smaller than the set value. In addition, the drone's position was affected by the pilot's operation, wind, and GPS corrections. Therefore, positional error must be taken into account. The drone's flight performance in this experiment had an error accuracy of \(\pm 1.5\) m for horizontal distance and \(\pm 0.5\) m for vertical distance [60]. Figures 21 and 22 show the results of numerical analysis of the maximum and minimum throughput values when the drone is positioned within this error range in the direct experiment and coverage measurement. The solid line is the average value, and the dashed lines are the maximum and minimum values. From the numerical results of the direct experiment with positioning errors in Figure 21, it can be seen that the difference between the theoretical and numerical results is relatively large at lower altitudes due to the deteriorating antenna directivity when there are misalignments caused by positioning errors. It can also be seen that the maximum and minimum values gradually converge as the positioning error becomes relatively smaller at higher altitudes. Figure 22 shows the graph of coverage measurement considering the positioning error. When the horizontal distance is small, the effect of the positioning error is small because the altitude is 30 m, and both the maximum and minimum values show saturated throughput values. When the horizontal distance increases to some extent, the measured throughput was within the range of the maximum and minimum numerical throughput, which validated the fact that drone's positioning errors contributed to the discrepancy of the measured throughput against the numerical one. Also, the gap between the maximum and minimum  
Figure 20: Comparative results of coverage measurement.