# An Intelligent Cluster-Based Routing Scheme in 5G Flying Ad Hoc Networks
### Fanet  
In FANETs, a large number of unmanned aerial vehicles (UAVs), which are autonomous, small-sized, and lightweight flying nodes, move at high speed at low or high altitudes in a three-dimensional space. Communication in FANETs is characterized by (a) a large transmission range due to the elevated look angle of UAVs, providing long-range connectivity with UAVs and base stations (BSs), and (b) frequent link disconnections and network partitions due to the high-speed and three-dimensional movement [3]. We consider that all nodes in FANETs are UAVs with different characteristics and different roles, namely, cluster member (CM), cluster head (CH), cluster gateway (CG), and vertical cluster gateway (VCG). UAVs have become increasingly important to support resource starving applications of FANETs in 5G and beyond 5G mobile networks [4]. Examples of use cases are advanced mapping and aerial photography, in which UAVs must satisfy the ever-increasing demands for mobile data communication and ubiquitous connectivity to different kinds of wireless devices [4]. As UAVs are battery-powered with limited residual energy, frequent link disconnections and network partitions cannot be addressed by further increasing the transmission range, which can drain out residual energy. Consequently, network performance degrades, including higher overheads (e.g., clustering and routing overheads, and handover) and lower quality of service (QoS) (e.g., lower throughput and higher end-to-end delay). Therefore, efficient vertical routing is performed over a clustered network to increase network stability. One of the most critical issues of UAVs is how to consume the limited residual energy efficiently. The lifetime of the whole UAV network is highly dependent on the energy consumption of UAVs, which is related to their mobility patterns and data transmission. Although UAVs can be equipped with rechargeable batteries powered by solar energy, fuels, and other sources of energy, UAVs should not frequently return to ground stations to charge their batteries frequently, which can reduce their hovering time considerably. \begin{table}
\begin{tabular}{l l} \hline \hline
**Notation** & **Description** \\ \hline \(n_{i}\) & Node \(i\in N\). \\ \(\theta_{i}\) & Direction of node \(n_{i}\) where, \(i\in N\). \\ \(v_{i}\) & Velocity of node \(n_{i}\) where, \(i\in N\). \\ \(T\) & Transmission range. \\ \(t_{p}\) & Data lifetime. \\ \(\tau\) & Data lifetime threshold. \\ \(x_{i},y_{i},z_{i}\) & Coordinates of node \(n_{i}\) in three dimensions, where \(i\in N\). \\ \(t\) & Time \\ \(D_{i,j}\) & Distance between two nodes \(n_{i}\) and \(n_{j}\), where \(i\,j\in N\). \\ \hline \hline \end{tabular}
\end{table} 
Table 1: General notations. Therefore, efficient routing should be performed to enhance network lifetime [5]. In [6], the challenges of data transmission in FANETs, especially reducing its energy consumption, have been addressed. Nevertheless, the proposed approach focuses on increasing network lifetime, reducing energy consumption, and reducing the rate of link breakages for 5G or beyond. In FANETs, multiple UAVs cooperate and establish an ad hoc network in a multi-UAV scenario. The presence of a large swarm of UAVs is called a multi-UAV swarm. Using 5G to support a multi-UAV swarm provides three main advantages: network scalability, network stability, and load distribution, for achieving improved QoS. As an example, device-to-device (D2D) communication allows neighboring UAVs to communicate with each other without passing through a BS, which can reduce control message exchange and enable traffic offload from the BS, leading to an increased bandwidth availability at BS [7]. As another example, small cells (SCs) are deployed to cater for local traffic in order to reduce energy consumption [8; 9]. The BSs provide backhaul access, and they have the privilege to interact with central controllers (CCs).