# A Study on the Maximum Reliability of Multi-UAV Cooperation Relay Systems
## 4 Simulations and Discussions  
In this section, simulations and analysis are conducted. Set time slot \(T=1000\), and the maximum moving distance of UAV in each time slot is \(v=0.1\) m, \(V=10\) m/s, \(\eta_{\text{LOS}}\in[0.1\), \(1.6]\) dB, \(\eta_{\text{NLOS}}\in[21,23]\) dB, \(\alpha\in[0.1,0.3]\), \(\beta\in[500,750]\), \(\gamma\in[8,15]\), \(a\in[0.1139\), \(0.4290]\), \(b\in[4.8800\), \(12.0810]\), \(\Omega=25\) mW, \(\sigma^{2}=-96\) dBm, \(\gamma_{th}=0\) dB, \(\epsilon=-10^{-2}\), \(P_{max}=26\) dBm \(r_{max}=4000\) m, \(PL_{\max}=113\) dB, and \(\delta=-10^{-2}\). Figure 4 shows LoS probability and path loss under different environmental models. For the suburban and urban environment models, the LoS probability of the suburbanenvironment increases more rapidly than that of the urban environment and then tends toward 1 with t increasing elevation angle, while the path loss of the suburban environment model decreases more rapidly than that of the urban environment model and then tends toward stability in the AtG model, and the path loss attenuation of the AtG model is faster than that of the AtG model. That is to say, AtA path loss is lower than AtG path loss, and the AtG path loss in suburban environments is lower than that in urban environments. When \(\theta^{\star}\), the corresponding path loss is minimized. Within the maximum coverage radius, the closer the ground user is to the geometric center of the ground, the smaller the radius, and the lower the path loss. Figure 5 shows the effect of different \(PL_{\text{max}}\) values and environment models on \(h^{\star}\). Figure 5 shows the change in unit radius relative to UAV height in the case of different \(PL_{\text{max}}\) values. The point on the radius-height curve in the figure that changes its direction; specifically, the top of the curve is the optimal height solution: \(h^{\star}\). It can be seen from Figure 5 that the angle between the horizontal axis and the line generated by connecting the top of each radius-height curve to the origin represents the optimal elevation \(\theta^{\star}\) which always meets the constant ratio \(\frac{h^{\star}}{r}\). The larger the \(PL_{\text{max}}\) value, the larger the \(h^{\star}\) value. Due to the main consideration of low-altitude airspace in this work, the LAP will be subject to physically constraints when reaching the optimal altitude. Therefore, there is \(h^{\star}\), and the corresponding path loss is at its minimum. Figure 5 shows the effect of suburban and urban environment models on \(h^{\star}\). It can be seen that \(h^{\star}\) is a function of the maximum allowable path loss and environmental statistical parameters, which largely depend on the environmental conditions in specific regions. Figure 4: LoS probability and path loss for different environments model. Figure 5: The effect of different \(PL_{\text{max}}\) values and environments models on \(h^{\star}\): (**a**) radius vs. altitude curve for different \(PL_{\text{max}}\) values; (**b**) radius vs. altitude curve for different environment models. Figure 6 describes the relationship between the distance between UAVs and the BER of AtA communication links. When the distance between UAVs decreases, the BER decreases. That is to say, the shorter distance leads to lower outage because when the distance decreases, AtA communication link loss decreases. Figure 7 describes the BER of the downlink communication links of static and mobile UAVs under a suburban environment model. When the UAV height increases, the BER first decreases to the minimum value and then increases slowly. The AtG communication link loss decreases to the minimum value and then increases slowly with the increase in UAV height. The path loss of the AtA communication link increases with the increase in UAV height, and its change is very small, with the path loss difference within 0.1 dB. It can be seen from Figure 7 that the BER of a mobile UAV is slightly lower than that of a static UAV. The bottom of the curve is \(h^{\star}\), corresponding to the minimum BER.