# A Review of Unmanned Aerial Vehicle Based Antenna and Propagation Measurements
## 3 UAV-Based Propagation Measurements
### UAV-Based Large-Scale Propagation Measurements
To understand the influence of LOS and non-line-of-sight (NLOS) conditions on the path loss calculations in [67], the path loss was measured in an area of 500 m \(\times\) 500 m. As part of this experiment, propagation measurements were performed in an urban area in Greece, which consists of buildings and trees. Measurements were conducted at 2.12 GHz for both LOS and NLOS scenarios, with the UAVs operating at an altitude of 6 to 200 m above ground level. The attenuation caused by reflections and diffractions from buildings and obstacles was also considered for the path loss calculations using the log-distance path loss model. The calculations were based on the uniform theory of diffraction (UTD) and geometric optics (GO). The path loss calculations varied for the LOS and NLOS conditions. The UAV flew at 100 m above the ground; for the LOS condition, \(\alpha\) was as low as 2.6; however, at the same altitude, for the NLOS condition, \(\alpha\) was 7.2, indicating that the path loss values differed depending on the test conditions. The polarization mismatch of the antenna mounted on the UAV also affects the accuracy of the path loss measurements. In [68], a DJI Phantom 4 UAV with a vertically polarized dipole working in the 3.1-4.8 GHz range was used for propagation measurements in three different scenarios. Initial measurements were performed between the UAV and receiver, assuming that no obstacles were present between the UAV and receiver. During this experiment, the receiver antenna at ground level was vertically polarized in one case and horizontally polarized in the other. By always leaving the transmitter located on the UAV vertically polarized, the VV and VH cases were produced. For the VV condition, a path loss of 72 dB and a path loss of 80 dB were observed for the VH condition. This indicates that there was an additional path loss resulting from the polarization mismatch. For ATG propagation measurements, EM waves are attenuated by multipath components, such as reflections, diffractions, and scattering. To estimate these losses, using the FSPL, two-ray [69], and log-distance path loss models may not be accurate in certain scenarios. Alternatively, empirical models, such as multi-slope log-distance path loss models [70], height-dependent two-ray models [71], and excess path loss models [72], are more reliable. The models that have been addressed so far are all deterministic. These models do not consider the dielectric properties of obstacles that attenuate the signals. In such instances, statistical models such as log-normal shadowing are used to calculate the attenuation of signals due to random variations. There are two crucial variables in a log-normal shadowing expression, \(\mu_{\phi B}\): the mean of the random variable, and \(\sigma_{\phi B}\): its standard deviation. A DJI N3 UAV, in combination with a \(\lambda/4\) monopole, was used in [73] to measure path loss while the UAV moved from 0 to 24 m in height. In the context of path loss measurements, [73] proposed an altitude-dependent propagation loss model based on a zero-mean-behavior random variable. Under NLOS conditions, after performing  
Figure 14: Scattering effect in a semi–urban area simulated in CST. propagation measurements at 1 GHz and 4 GHz, the \(\sigma_{\psi B}\)[74] value increased with the frequency and distance of the UAV from the receiver. The typical range of \(\sigma_{\psi B}\) is 5-12 dB for terrestrial macrocells and 4-13 dB for terrestrial microcells. For aerial wireless channels, \(\sigma_{\psi B}\) ranges from 1.2 to 5.24 dB, and it is observed that when UAVs fly at high altitudes, \(\sigma_{\psi B}\) can be as low as 1.2 dB [75].