# Survey on Q-Learning-Based Position-Aware Routing Protocols in Flying Ad Hoc Networks
### Related Studies
So far, the comprehensive review articles on position-based routing protocols in FANETs discuss the different relay UAV selection mechanisms by considering the path selection strategy, bio-inspired swarming, and topology-based routing [37; 38]. The QL-based routing protocols incorporated with position-based forwarding techniques are new research trends for FANETs, which are not covered by the existing survey works. Motivated by this, we surveyed all the recently proposed QL-based position-aware routing protocols in FANETs, most of which are published in reputed journals. In our earlier study [40], the relationship between QL and routing was reviewed, and seven QL-based routing protocols for FANETs were discussed and compared qualitatively, primarily focusing on key features and performance challenges. However, in this review article, we define the FANETs, their components with functionalities, and dynamic FANET topology. Then, we extensively study the realistic mobility models in FANETs according to their applications and define the QL and its relationship with dynamic FANETs. Additionally, we comprehensively review each protocol with its advantages and limitations, and then perform a comparative study considering important performance metrics for FANETs. According to our comparative study, we find key open issues and discuss their potential research directions. According to the above discussion, related review articles on FANET routing protocols are summarized in Table 1 to indicate our key contributions. The limitations of topology-based proactive, reactive, and hybrid routing protocols are summarized in Table 2. \begin{table}
\begin{tabular}{c c c} \hline
**Ref.** & **Year** & **Key Focused Points** \\ \hline
[32] & 2019 &
\begin{tabular}{c} Reviewed the routing protocols in FANETs by classifying them as topology-based, \\ position-based, and hierarchical routing. \\ \end{tabular} \\ \hline
[30] & 2019 &
\begin{tabular}{c} Reviewed UAV types, mobility models, and routing protocols in FANETs by classifying them as topology-based, position-based, and delay-tolerant-based categories. \\ \end{tabular} \\ \hline
[31] & 2020 &
\begin{tabular}{c} Reviewed UAV mobility models, application scenarios of UAV networks, and routing protocols by classifying them as topology-based, position-based, hybrid, and bio-inspired routing. \\ \end{tabular} \\ \hline
[37] & 2018 &
\begin{tabular}{c} Reviewed the only position-based routing protocols in FANETs by classifying them based on the path selection strategy. \\ \end{tabular} \\ \hline
[38] & 2017 & \begin{tabular}{c} Reviewed the only position-based routing protocols in FANETs based on the three categories of topology-based, position-based, and swarm-based routing. \\ \end{tabular} \\ \hline This survey & 2022 & \
\begin{tabular}{c} \(\bullet\) \\ \(\bullet\) \\ \(\bullet\) \\ \(\bullet\) \\ \(\bullet\) \\ \(\bullet\) \\ \(\bullet\) \\ \end{tabular} &
\begin{tabular}{c} Reviews the mobility model of the UAV swarm networks based on the realistic application scenarios in FANETs \\ \(\bullet\) \\ \(\bullet\) \\ \(\bullet\) \\ \(\bullet\) \\ \end{tabular} \\ \hline \end{tabular}
\end{table} 
Table 1: Comparative summary of survey works and their focused points on routing in FANETs. According to the above discussion, the features supported by QL-based position-aware routing protocols are listed in Table 4 compared with only position-based forwarding techniques.