# Flying Ad Hoc Networks: A New Domain for Network Communications
## 2 State of the Art
### Propagation Models
* Semi-empirical models: The semi-empirical models are initiated as theoretical models and then varied according to a set of measures to match reality. In Reference [59], the authors started with a series of measurements of the RSS (received signal strength) of the U2G channel in an urban area, and then selected the propagation model that most resembled the collected measurements. It was Rice + Log-Normal ([PERSON]'s model [60]). Finally, they modified the chosen model such that the results with that model corresponded to the obtained measures. [PERSON] et al. [13] assessed another semi-empirical model, but in this case for the U2U channel. To do this, the authors extended the Rice channel model in the U2U link to take into account the multipath effect of the signals produced by an UAV flying at a fixed altitude. In this study, the antennas of the UAV were placed in a vertical position, which makes the reflections with the ground less frequent and have a lower power. In addition, the impact of the UAV on the transmitted power was not known, since only the horizontal plane of the complete RP was studied. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Ref.** & **Type** & **Channel** & **Frequency (GHz)** \\ \hline
[16] & Theoretical & UAV–Ground & 2.4 \\
[54] & Theoretical & UAV–Ground & 2–6 \\
[55] & Empirical & UAV–Ground & 1.8–5.76 \\
[56] & Empirical & UAV–Ground & 0.8 \\
[57] & Empirical & UAV–Ground & 0.96–0.977 \\
[58] & Empirical & UAV–Ground & 5.030–5.091 \\
[59] & Empirical & UAV–Ground & 3.1–5.3 \\
[59] & Semi-Empirical & UAV–Ground & 2 \\
[13] & Semi-Empirical & UAV–UAV & 2.4 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparative of channel models in literature. * Well-known models: There are other works in the related literature that focus on verifying the adequacy of already-known propagation models in FANET scenarios. For example, in Reference [61], [PERSON] et al. proposed a method to select the environment or areas (urban, sub-urban, rural, mountainous, near the sea, etc.) where the air network is going to be deployed in order to choose the U2G channel propagation model that more adapts to reality. The results showed that their method worked for a wide variety of environments. [PERSON] et al. [62] analyzed the applicability of traditional propagation models to FANETs. For this, the authors made a comparison of different propagation models used for conventional mobile systems (e.g., Cost 231-Hata, Walfish-Ikegami, Erceg, Har, WINNER II B1, C1, C2, and D2) with the ray tracing model. They found out that the WINNER II C1 and Walfish-Ikegami models are suitable options when the air node is below 30 m, otherwise the free space model predicted propagation losses quite well. As it can be seen, and to the best of the authors' knowledge, most works addressing the study of propagation models in the state of the art have not considered the influence that the UAV can have on the radiation pattern of the integrated communication device. This can lead to erroneous results in mobility, in positioning, and generally in performance, since either loss due to the UAV chassis/vibrations/etc. are not being considered in the theoretical models, or these losses are being mistakenly included in another factor such as noise in uncontrolled environments. As we will demonstrate later, these losses can suppose a power drop of up to 10 dB in some angles for the U2G link. Therefore, a factor that takes into account the position/orientation of the UAVs and the nodes on the ground should be incorporated in the propagation models to include the losses due to the UAV chassis/vibrations/etc. To assist on this matter, the next section presents a study on the influence of a UAV on the radiation pattern of an embedded communication device. As a result, a representation of the expected losses will be obtained for the different links (U2U and U2G) in all the spatial planes. **3. Case Study: Understanding the Impact of Embedded Devices on the Radiation Pattern of UAVs**  
This case study has three goals.