# VLC Network Design for High Mobility Users in Urban Tunnels
## 6 Results and Discussion
### Multiple Vehicles  
One of the goals of a handover algorithm is to prevent a handover failure due to insufficient resources in the target cell. To measure this influence, we evaluate the performance of the network considering a scenario with multiple vehicles as described in Section 5.2. For these evaluations, we compare only for configuration 3 the service availability, PFER, and EFER, as the number of vehicular nodes increases.  
Moreover, due to the limited cell coverage, the individual user performance is not impacted deeply by scaling the network with more users. It means that we do not have to scale up the simulation with a large number of vehicular nodes to determine the perfor  
Figure 19: Physical layer Frame Error Rate (logarithmic scale).  
Figure 20: Average User’s data rate during the entire simulation.  
mance limit. Furthermore, the coverage area of each AP helps to delimit to a maximum of 3 vehicles per cell, minimizing the need of serving a large number of vehicles.  
From Figure 21, it is evident how the service availability decreases with the number of vehicular nodes. For this scenario, the service time is affected because multiple vehicles join the same AP. Therefore, the AP does not transmit any information to a new vehicle until the previous frames in the buffer of the AP have been delivered. Thus, the service is more likely to be interrupted during the handovers. As expected, the results depicted in Figure 21 corroborate how the service time is reduced on average. Moreover, the operation of multiple vehicles in a close area makes the blackout time increase up to 20 ms when the AP separation distance is less than 13 m. Furthermore, when the separation of the APs is shorter, the handover occurs much more frequently.  
Figure 22 plots the comparison of the EFER for a different number of vehicular nodes. The results exhibit a considerable drawback when more than one user is associated with an AP. We observe that the EFER converges to \(3\times 10^{-2}\) at distances under 13 m, which is a substantial rise in comparison with \(5\times 10^{-4}\) from the single-vehicle scenario. On the other hand, Figure 23 shows that the PFER performance has a similar tendency to EFER. As expected, a single-vehicle crossing the tunnel achieves superior performance with an error rate of 12% when the distances between lamps are less than 12 m, which is regulatory. However, PFER does not exceed a maximum value of 19% regardless of the number of vehicles in the same scenario. Indeed, the PFER performance value for three or more vehicles does not change notably.  
Figure 21: The complement of the service availability for different number of vehicular nodes operating in the network (Outage ratio).  
Finally, Figure 24 depicts the measured data rate with respect to the separation of the AP and the number of active vehicular nodes. Here, the data rate is reduced to 420 Kbps with \(m=3,5\), and 7 vehicular nodes in the network. More interesting, it is worth noting how quickly the data rate of convergence is obtained when the separation between APs is under 14 m. It means that the solution is scalable without significant penalties.  
Figure 23: The PFER for different number of vehicular nodes operating in the network.  
Figure 22: The EFER for different number of vehicular nodes operating in the network.