# An Unsupervised Machine Learning Approach for UAV-Aided Offloading of 5G Cellular Networks
## 4 Performance Evaluation
### Comparative Evaluation of UDP in Terms of Offloading Percentage  
In this section, we examine the percentage of the UEs offloaded from the MBSs. More specifically, comparisons between the proposed and the compared methods are presented in terms of percentage offload. Furthermore, constraints regarding the maximum number of UEs that a single UAV-BS or PBS can serve, are considered. First, we determine the best weighting factor \(a\) concerning the UDP method. Figure 2 illustrates the offloading percentage achieved by the UDP, depending on the available number of UAV-BSs and the weighing factor \(a\). The red line represents the best values of \(a\), depending on the available number of UAV-BSs, where the offloading percentage is maximized. More specifically, we observe that for 1 to 5 UAV-BSs, we obtain the maximum offloading rates for \(a=0.5\). When the number of UAV-BSs is equal to 6, then the maximum offloading rate is reached for \(a=0.6\). Morevoer, when the number of UAV-BS is greater \begin{table}
\begin{tabular}{l l} \hline \hline
**Parameters** & **Values** \\ \hline Simulated frames & 100,000 \\ Number of MBSs \(M\) & 3 \\ Number of UEs \(N\) & 150 \\ Number of UAV-BSs/PBSs & 1–10 \\ Number of UE hotspots \(H\) & 1–10 \\ MBS downlink operating frequency \(f_{m}\) & 2 GHz \\ UAV-BS downlink operating frequency \(f_{d}\) & 1.8 GHz \\ MBS Transmit power \(P_{m}\) & 43 dBm \\ UAV-BS Transmit power \(P_{d}\) & 23 dBm \\ Area of interest \(W\) & 4.5 km \(\times\) 4.5 km \\ MBS Cell Radius \(R_{MBS}\) & 1.27 km \\ MBS Path loss model (NLOS) & 128.1 \(\times\) 37.6 \(\log_{10}(r)\) dB \\ Path loss model (NLOS) for PBS & 145.4 \(+\) 37.5 \(\log_{10}(r)\) dB \\ Path loss model (LOS) for PBS & 38 \(+\) 30 \(\log_{10}(r)\) dB \\ Path loss model (LOS/NLOS) for UAV-BS & Elevation Angle-Based Model [26] \\ Terrestrial Environment & Urban \\ UE receive antenna gain \(G_{r}\) & 0 dBi \\ MBS transmit antenna gain \(G_{t}^{m}\) & 15 dBi \\ UAV-BS transmit antenna gain \(G_{t}^{d}\) & 0 dBi \\ PBS transmit antenna gain \(G_{t}^{p}\) & 0 dBi \\ Terrestrial Environment & Urban \\ Log-Normal Shadowing & 6 dB \\ Bandwidth \(B_{g}\) with \(g=\{\)MBS, PBS, UAV-BS\} & 5 MHz \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Simulation parameters. than 6, the maximum offloading rates are achieved for \(a=0.7\). Based on this observation, we have set these values in our simulations for the UDP method. Regarding the KDP method, we have considered fixed value of \(a=0.5\), as in [23]. From Figure 2, we can easily conclude that as the number of available UAV-BSs increases, it is more important to consider the number of users in each cluster \(n_{norm}^{k}\) for CSP process instead of the distance \(d_{norm}^{k}\) from the MBSs (\(a>0.5\)), in order to achieve the maximum possible offloading. In Figure 3, the percentage of UEs offloaded from the MBSs for different number of UAV-BSs/PBSs is presented, utilizing the proposed scheme, as well as the compared ones. As it can be observed, the UDP process outperforms all the compared methods for all configurations. Furthermore, when the number of the available UAV-BSs or PBSs is less than two, the offloading rate for the KDP and PDPP with LOS channel conditions remains the same. However, when the availability of UAV-BSs/PBSs increases, the methods that utilize ML techniques for the UAV-BSs placement outperform the traditional PDPP and PDPR methods, respectively. The maximum percentage of the UEs offloaded from the MBSs through the PDPP and PDPR is 44% and 3%, respectively. PDPR has quite small offloading percentage since the placement of PBSs is random, and practically, it can not be ensured that the formed hotspots of UEs will be covered. In addition, the maximum offloading percentage achieved by the KDP and UDP methods is 49% and 59%, respectively.