# Location-Aware Node Management Solution for Multi-Radio Dual Connectivity Scenarios
## 5 Evaluation  
First of all, the optimal square size must be defined. This will indicate the number of estimation models to be stored, as well as the required accuracy in locating the users. With this purpose, the MAPE obtained for each service with different square sizes is computed for all the scenario setups introduced in the previous section. Figure 4 shows that the MAPE decreases for all services as the square side size decreases in every scenario, i.e., the scenario is characterized with more estimation models. However, the values are different for each scenario configuration. The lowest overall MAPE values are obtained in scenarios 2 and 5, as can be seen in the Figure 4b,e. This indicates that the MAPE tends to be lower in small regions where there is a predominant service whose performance is well \begin{table}
\begin{tabular}{c c} \hline \hline
**Scenario 1** & Uniform distribution of users and services \\  & (60 UEs per site and 300 UEs per service on average) \\ \hline
**Scenario 2** & Uneven distribution of services \\  & 4 squares: 70\% of total UEs use the same service in each square \\  & The remaining 30\% use the other 3 services \\  & Predominant service as indicated in Figure 3a \\ \hline
**Scenario 3** & Uneven distribution of users \\  & 4 squares: Users density decreases by 15\% in each square \\  & as indicated in Figure 3b \\ \hline
**Scenario 4** & Different radio conditions \\  & 4 squares: Propagation losses increase in each square \\  & as indicated in Figure 3c \\ \hline
**Scenario 5** & 4 squares with completely different characteristics \\  & Scenarios 2, 3 and 4 are combined \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Configuration of the scenario for each test. \begin{table}
\begin{tabular}{c c} \hline \hline
**Environment** & Dense urban scenario with 20 sites, \\  & 1 eNB and 1 gNB per site, 3 sectors/site \\ \hline
**Carrier** & eNB: 10 MHz carrier bandwidth at 2.4 GHz \\  & gNB: 10 MHz carrier bandwidth at 4 GHz \\ \hline
**Channel model** & Urban micro (UMi) [36] \\ \hline
**PHY numerology** & 15 kHz sub-carrier spacing \\  & 12 subcarriers/PRB (180 kHz) \\ \hline
**Data channel MCS** & QPSK to 64 QAM \\  & with same encoding rates as specified for LTE \\ \hline
**Antenna configuration** & 2 \(\times\) 2 MIMO \\ \hline
**Scheduler** & Classical exponential/proportional fair [37] \\ \hline
**Link adaptation** & CQI-based \\ \hline
**Mobility model** & 50\% chance of the user being static or moving at 0.83 m/s \\ \hline
**FD traffic model** & File size: log-normal distribution (avg. 2 MB) \\ \hline
**WB traffic model** & Web page size: log-normal distribution (avg. 3 MB) \\  & No. pages per session: log-normal distribution (avg. 4) \\  & Reading time: exponential distribution (avg. 30 s) \\ \hline
**RTV traffic model** & Video codec: H.264, Resolution: 720 p \\  & Video bitrate range: 1.5-2 Mbps \\  & Video duration: uniform distribution [0, 540] s \\ \hline
**VS traffic model** & Video codec: H.264, Resolution: 1080 p \\  & Video bitrate range: 3–4 Mbps \\  & Video duration: uniform distribution [0, 540] s \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation assumptions. known. However, the MAPE of the RTV service is higher in these scenarios because the increase in user density causes an increase in the overall delay that negatively affects the QoE perceived by users and is not directly measured by the proposed approach. On the other hand, the MAPE obtained for the other services is similar in each scenario, as they are more dependent on the throughput, which can be better estimated in small regions where local radio conditions and typical resource availability are more accurately known. In conclusion, the lowest MAPE values are obtained for areas with 20 m of square side size. Nonetheless, 30 m of square side size is proposed to generate the estimation models used in the next tests.