# Machine Learning-Assisted Adaptive Modulation for Optimized Drone-User Communication in B5G
## 5 Numerical Results  
We carried out Monte Carlo simulations for a drone-user communication system over the Rician channel. First, we analyze performance with atmospheric disturbances, and in the later phase, the application of ML to optimize the performance is shown. The drones considered are located at the height of 18 km above the ground. Therefore, the performance analysis of atmospheric disturbances is performed in two phases. In the first phase, the effect of the Rician factor (\(\kappa\)) on drone communication over the clear sky is studied, while we analyze the impact of rain on the capacity and error performance in the second phase. Finally, we analyze the performance of the communication system with Adaptive Modulation. During the first phase, a QPSK modulation is performed over the symbols transmitted. Figure 3 shows the capacity of the drone-user communication system over different Rician factors. We note that capacity above \(\kappa=-10\) dB is better than the Rayleigh channel due to the limited presence of the LoS channel along with the NLoS channel. The presence of a stronger LoS component (i.e., \(\kappa=10\) dB) improves capacity, which is very useful in urban areas [1]. It is important to note that the advantage in data rate is possible if antennas are sufficiently separated to produce a full rank channel matrix. Overall, from Figure 3, we can observe that the data rate with \(\kappa=10\) dB is better than \(\kappa=0\) dB, which is again better than \(\kappa=-10\) dB. Hence, the data rate provided for drone-user communication differs for different values of the Rician factor, which again depends on the geographical locations [1]. Next, we consider the effect of rain on the performance of the system considered. Figure 4 reports the data rate in \(bits/sec/Hz\) for different scenarios, and the corresponding effect is observed. The rainfall rates of 1, 16, and 100 mm/h correspond to light, medium, and heavy tropical. It can be noted that the data rate is degraded heavily as the rainfall rate increases. While light rain can still support data transmission, transmission in heavy rain is nearly impossible. Results show that at \(\text{SNR}=15\) dB, as rainfall rate varies from 1 to 16 mm/h, the system with \(\kappa=10\) dB experiences a data rate drop of 83.18% and on the other hand, the system with \(\kappa=-10\) dB experiences a data rate drop of 94.47%. It is because the signal at the receiver is heavily degraded due to the rain. Figure 3: CDF with different Rician factor. In Figure 5, we analyze the effect of SNR on the data rate of the system. In other words, the signal power in the receiver has a considerable effect on the data rate. It can be observed that at higher SNR, the data rate is high, and the data rate is dropping with decreasing SNR. Furthermore, a higher rainfall rate restricts the sum rate, which is also observed in Figure 4. At a higher rainfall rate, the data rate is near to zero \(bps/Hz\). In Figure 6, BER vs. SNR characteristics are plotted for various modulation schemes. We can easily understand that it is possible to retain the BER performance at the data rate cost. During rain fall, it is possible to adapt to another modulation scheme that offers lesser spectral efficiency. However, the SNR at which the switching is to be carried out vary with the rainfall rate. It can be observed that, to achieve a BER threshold of \(10^{-2}\), the transition from QPSK to BPSK occurs at 18 dB for a rainfall rate of 1 mm/h. Meanwhile, a similar transition occurs at 33 dB for 10 mm/h. Intelligent switching between modulation schemes depending on rain is the key to retaining the required BER. An ML-assisted switching is analyzed in the next phase. Figure 4: Data rate under different rain rates. Figure 5: CDF vs. bps/Hz for drone–user communication. Finally, in Figure 7, we apply a k-means algorithm with K = 2 in a drone-user communication system with atmospheric disturbances. Two modulations schemes are considered for simplicity.