# Location-Aware Node Management Solution for Multi-Radio Dual Connectivity Scenarios
## 5 Evaluation
This decision enables a compromise between the most reliable decisions possible and the minimum memory and computing cost, since the difference between the MAPE obtained for 20 and 30 m of square side size is relatively small. Moreover, this allows for a larger error in tracking the UE location. In addition, the importance of each metric in the QoE estimation must be analyzed. In this way, the weight of each metric for each service in all scenarios is represented in a box plot in Figure 5. These values are obtained after normalizing the weight of each metric in each estimation model generated for areas of 30 m of square side size. Figure 5a shows that RSRP is the least important metric for QoE estimation, except for the RTV service since RSRP is correlated with the distance between the nodes and the user, which may have an impact on the service latency and, therefore, on the QoE perceived. On the other hand, RSRQ and available PRBs have similar weights for less resource demanding services, i.e., FD and WB. On the contrary, available PRBs are more important for video services, especially for the most resource and throughput demanding service, i.e., VS. In addition, the relevance of available resources will increase in Scenario 2 for all services, as shows in Figure 5b, since the higher density of video users in two different areas will lead to overload these regions. Moreover, resource availability will be more important for WB users which do not demand as much throughput as FD users, which will also rely heavily on RSRQ. Furthermore, RSRQ is also very relevant for video users to perceive a good QoE. On the other hand, the decrease in user density does not affect the weights much, as the values represented in Figure 5c are similar to those obtained in Scenario 1. Conversely, the increase in propagation losses does affect the RTV service, which is more dependent on RSRP, as depicted in Figure 5d. These additional propagation losses could indicate a longer distance between nodes and users, which is relevant for RTV with strict delay requirements. Finally, Figure 5e shows that available PRBs are considerably more important than the others metrics when there are heavily loaded areas in the scenario, as in Scenario 2. After resource availability, RSRQ is the most important metric. It should also be noted that the relevance of RSRP for RTV users is low in this scenario because there are no additional propagation losses in the area where this service predominates. Therefore, this set of subfigures shows that RSRP, which is the only metric used in the 3 GPP solution, is the indicator that has the lowest weight for estimating QoE. This implies that RSRQ and available resources should be used to decide the nodes that will serve an user if MOS is to be maximized. Last but not least, the variance of the values indicates that the weights change throughout the scenario, verifying the requirement of multiple estimation models. Figure 4: MAPE for different square side sizes, services and scenarios. (**a**) MAPE in Scenario 1. (**b**) MAPE in Scenario 2. (**c**) MAPE in Scenario 3. (**d**) MAPE in Scenario 4. (**e**) MAPE in Scenario 5. Figure 5: _Cont._  
The previously stored estimation models are now used to select the eNB and gNB that provide the maximum estimated QoE in these tests. The resulting performance is compared with that obtained in the same scenarios but selecting the nodes based solely on RSRP, as indicated by 3 GPP. Results show that the proposed solution increases the average MOS obtained by the 3 GPP approach for all the services introduced in every scenario, as depicted in Figure 6. Nevertheless, the average MOS achieved varies depending on the scenario configuration. Figure 6b shows how the average MOS of least demanding services increases in the areas where they are predominant with respect to that obtained in the uniform scenario shown in Figure 6a. On the contrary, the MOS of video services decreases due to the high struggle for radio resources in regions where video services are predominant.