# Impact of Weather Factors on Unmanned Aerial Vehicles' Wireless Communications
## 2 Methodology
### Simulation Parameters for Mobility, Doppler Shift, and SNR Degradation  
The impact of mobility and resultant Doppler shift on SNR degradation was assessed through the variation of a set of key parameters as expressed in Equation (20). Assuming the maximum permissible value of BER (\(P_{b}\)) at 0.01, for 4, 16, 32, 64, and 256-QAM modulation schemes, we computed the corresponding values of \(\overline{\gamma_{b}}\) using Equation (22):  
\[\overline{\gamma_{b}}=10 log_{10}\frac{\Big{(}Q^{-1}\Big{(}\frac{P_{b}\log_{2}M }{4}\Big{)}\Big{)}^{2}(M-1)}{3\log_{2}M} \tag{22}\]  
where \(Q^{-1}\) is the inverse error function.  
The computed values of \(\overline{\gamma_{b}}\) thus serve as the minimum SNR thresholds for corresponding modulation schemes to maintain a BER \(\leq\) 0.01. We set the reference SNR at 20 dB. At this level of SNR, \(P_{b}\) \(<\) 0.01 is satisfied for all assumed modulation schemes. Degradation resulting from Doppler shift was applied to this reference SNR. The carrier frequency \(f_{c}\) was set to 2.4 GHz. The sub-carrier frequencies and corresponding symbol rate \(R_{s}\) were selected according to the fifth generation (5G) numerology [34], which is backward compatible with the fourth generation (4G) cellular communications. The number of sub-carriers were selected for quantities of 4, 16, 32, 64, and 256. SNR degradation was evaluated against the symbol rates of 15, 30, 60, and 120 Kbd/s. The relative speed to generate a Doppler shift was set in the range of 0 to 200 km/h, with 1 km/h increment. Table 3 presents the parameters utilized in this study, along with their corresponding values.  
\begin{table}
\begin{tabular}{l l l} \hline
**Parameters** & **Values/Range of Values** & **Units** \\ \hline Temperature (\(T_{a}\)) & \(-\)40, \(-\)25, 25, 40 & \({}^{\circ}\)C \\ Standard pressure (\(p_{a}\)) & 1013.25 & hPa \\  & For gas attenuation: \\ Liquid water density (\(lwd\)) & 0.23, 5.75, 17.26, 23.01 & \\  & For fog attenuation: & g/m\({}^{3}\) \\  & 0.05, 0.5, 5.0, 10 & \\ Rain-rate (\(R_{r}\)) & 1, 10, 50, 120 & mm/h \\ GCS to UAV distance (\(d\)) & 500, 1000, 1500, 2000 & m \\ GCS to UAV height (\(h\)) & 100, 200, 300, 400 & m \\ Frequency (\(f\)) & 1 to 100 & GHz \\ Isotropic Transmitter power (\(P_{tx}\)) & 0.25, 0.75 & mW \\ All white gaussian noise (AWGN) (\(N_{0}\)) & \(-\)142 to \(-\)144 & dB \\ \hline \end{tabular}
\end{table}
Table 2: Weather simulation parameters.  
Figure 7 illustrates the methodology employed for conducting simulations, analyzing the results, and deriving pertinent recommendations within the context of UAV operations.  
The simulations conducted include computation of 1 path loss, 2 weather attenuation, 3 SNR, 4 BER, and 5 Doppler shift caused SNR degradation. The results were used to analyze their effects on UAV operations in terms of 6 bandwidth suboptimization and 7 Doppler shift impact analysis. The analysis resulted in a set of 8 recommendations, which can be utilized to formulate suitable algorithms to enhance UAV operational reliability.  
The path loss computation block takes the power transmission, carrier frequency, and other model-dependent parameters as inputs to compute the expected path loss at the receiver. The weather attenuation computation is carried out based on operating frequency and applicable weather parameters. The total received power is computed based on the path loss and the weather influenced attenuation. Based on the operating bandwidth and temperature, AWGN noise is computed. Subsequently, the SNR is computed as the ratio of the received power to the noise power. BER computation is performed based on the computed SNR. We apply a Doppler shift-based degradation to the SNR to evaluate the impact of mobility across different modulation schemes, symbol rates, and sub-carrier spacing.