# An Intelligent Cluster-Based Routing Scheme in 5G Flying Ad Hoc Networks
## 2 Related Work
\(E_{elect}\) is the energy consumed by the transmitter and receiver circuitry, \(E_{amp}\) is the energy consumed by transmit amplifier, \(L\) is the number of bits transmitted, and \(d\) is the distance between transmitting and receiving nodes. \begin{table}
\begin{tabular}{l l l} \hline \hline
**Parameters** & **RL** & **DQN** \\ \hline Batch size & - & 32 \\ Episodes \(z\) & 1001 & 1001 \\ Transmission Range (m) & 500 & 500 \\ Grid size (km\({}^{3}\)) & 1 & 1 \\ Energy for transmission & 2 & 2 \\ (_joule_) & 1 & 1 \\ Energy for reception (\(joule\)) & 10–100 & 10–100 \\ Speed (m/s) & 100–1000 & 100–1000 \\ Network density & 100–1000 & 100–1000 \\ Replay memory size & - & 2000 \\ Discount factor \(\gamma\) & 0.95 & 0.95 \\ Learning rate \(\alpha\) & 0.1–1.0 & 0.0001–0.001 \\ Exploration rate \(\varepsilon\) & 1.0 & 1.0 \\ Minimum exploration rate & - & 0.001 \\ Maximum exploration rate & - & 1.0 \\ Decaying variable \(\varepsilon_{decay}\) & - & 0.995 \\ Data lifetime threshold \(\tau\) & \(z\) & \(z\) \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Simulation parameters for the RL and DQN agent. ### Performance Measures

There are three performance measures. _Energy consumption_ represents the average number of energy units (i.e., joule) consumed for a successful transmission of a data packet from a source node to a destination node. Lower energy consumption improves the energy efficiency of a network. _Rate of link breakages_ represents the average percentage of link breakages (out of all link breakages) caused by the drainage of residual energy and UAV movements. Lower number of link breakages indicates a lower route maintenance and a higher cluster stability, leading to lower packet loss and delay. _Network lifetime_ represents the average network failure time when \(\frac{5}{4}\) of the UAVs in the network run out of residual energy. Higher network lifetime improves throughput. Our simulation is investigated with respect to two aspects: _Network density_ represents the number of nodes in a fixed-size area. _Node mobility_ represents the speed of a node (m/s) ranging from 10 m/s to 100 m/s. In the experiments, the lower limit of 10 m/s is fixed, while the upper limit of 100 m/s may be changed. Our proposed scheme selects routes across different network planes (or network cells) to enable inter- and intra-plane communications while improving network lifetime, as well as reducing energy consumption and link breakages. Our proposed scheme focuses on route selection, rather than signaling protocol and message structure, in 5G access networks. Similar to the investigations in [55,56], packet-based network performance, such as end-to-end packet delivery ratio, are not selected. Our proposed scheme aims to (a) reduce energy consumption which increases the availability of residual energy and (b) reduce the rate of link breakages which reduces the packet drop ratio. Improving these performance measures has shown to increase the end-to-end packet delivery ratio [55,57]. There is a correlation between the performance measures. As node mobility increases, the rate of link breakages increases exponentially as shown in Section 5.7.5. This increases network lifetime as shown in Section 5.7.6 due to the lack of data transmission when new routes are being established and stored in DCs. In general, DQN provides _the best_ results as compared to the traditional RL and random approaches. Our proposed scheme focuses on route selection choosing the most favorable route with a higher residual energy and a lower mobility, rather than signaling protocols and message structures, in 5G access networks. Therefore, we have chosen to improve performance metrics, including energy consumption, rate of link breakages, and network lifetime. Enhancing these performance metrics improves QoS, such as packet loss rate, throughput, and end-to-end delay as shown in [58,59].