## 4 Results and Analysis  
This section presents the results of the proposed channel model. Unless otherwise stated, the basic parameters are chosen as follows: \(D=50\) m, \(h_{t}=h_{r}=25\) m, \(G_{t}=G_{r}=5\) dBi [47], \(\gamma=2\), \(\eta=3\)[48], \(\sigma_{h}=0.02\) m [49], \(\alpha_{R}=1\)[22], \(\delta_{t}=\delta_{r}=\lambda/2\), \(\xi_{t}=\xi_{r}=\pi/2\), \(N=1000\), \(\sigma_{x}=5.93\) m, \(\sigma_{y}=4.81\) m, \(v_{t}=v_{r}=10\) m/s, and \(\alpha_{t}=\alpha_{r}=0\). Additionally, the maximum vibration amplitude is \(a_{tm}=a_{m}=0.01\) m, the vibration frequency is set as \(f_{t}=f_{r}=24\) Hz (120 ppm/V, 12 V) [50], and the vibration directions are defined by the azimuth angles, \(\xi_{t}^{A}=\xi_{r}^{A}=\pi/6\), and elevation angles, \(\xi_{t}^{E}=\xi_{r}^{E}=\pi/10\). Furthermore, vertical polarization antennas are assumed in the simulation. Note that the parameters, including the carrier frequency, UAV altitudes, Tx-Rx separation, and antenna gain, are established in accordance with the measurement campaign in [47]. Only a limited set of parameters, such as \(\sigma_{x}\) and \(\sigma_{y}\), which distinguish the proposed model from conventional ones, are derived through the fitting of the statistical properties of the model to the measurement data. Figure 6 shows the PDF of the attenuation of small-scale fading of the proposed model and the measurement results in [47]. The A2A measurements were conducted at 2.4 GHz using Wistron DNMA92 and TP-Link WN821N adapters, following [51]. Two AscTec Firefly UAVs equipped with omnidirectional antennas with a 5 dBi gain were used, and the transmission power was set at 20 dBm. During the measurements, the UAVs maintained a horizontal separation of 50 m and operated at an altitude of 25 m. The received signal strength values were recorded and analyzed. In the simulation, model parameters such as the carrier frequency, Tx-Rx separation, antenna gain, and UAV height were set according to the measurement campaign in [47]. The scatterer density parameters, i.e., \(\sigma_{x}\) and \(\sigma_{y}\), were obtained by fitting the statistics to the measurement results. Due to the impacts of the LoS and ground reflection paths, the proposed model illustrates typical Rice fading [47]. The agreement between the simulation and measurement results demonstrates the practicability of the model. Figure 7 illustrates the spatial CCFs of the proposed model with different UAV heights and scattering-lobe widths. It is found that a large \(\alpha_{R}\), which results in narrower scattering lobes, increases the spatial CCFs of the model. This implies that an environment with  
Figure 6: PDF of attenuation of small-scale fading of the proposed model and measurement results in [47] (\(f_{c}=2.4\) GHz, \(D=50\) m, \(h_{t}=h_{r}=25\) m, \(\sigma_{x}=5.93\) m, \(\sigma_{y}=4.81\) m). less scattering can increase the spatial correlation of the channel, thereby decreasing the spatial diversity of a MIMO system. Additionally, as the UAV height increases, the spatial correlation becomes higher due to the smaller angular spread. With the same horizontal distance between the Tx and Rx, a greater UAV height of 100 m results in increased path loss for the diffuse rays. Consequently, the A2A channel is primarily dominated by the LoS ray. As a result, the influence of the scattering-lobe widths on the spatial CCF becomes negligible. Figure 8 shows the temporal ACFs of the proposed A2A channel model with different vibration amplitudes, vibration frequencies, and carrier frequencies. It can be observed that an increasing vibration amplitude or vibration frequency results in a lower temporal correlation of the channel, implying a faster time variation in the channel over time. A noteworthy insight observed from the results is that the temporal ACF demonstrates a high sensitivity to UAV vibrations when the system operates at high-frequency bands. A higher carrier frequency makes the channel decorrelate over time more rapidly.