# VLC Network Design for High Mobility Users in Urban Tunnels
## 7 Conclusions  
In this paper, we have explored an encouraging VLC network solution to support communication in vehicular tunnels. The performance of the proposed solution has been studied through a system-level simulator that validates the functionality of an operating  
Figure 24: The data rate per vehicular node for different number of vehicular nodes operating in the network.  
VLC network instead of peer-to-peer communication. As a result, this study provides a better understanding of the challenges VLC networks face to support the implementation of vehicular communication. These early findings, though promising, will need further development to assist vehicular communications with high mobility.  
The method is exemplified in a vehicular VLC network that operates over a tunnel. This specific scenario is employed to examine the proposed solution consisting of a network topology and a handover mechanism that achieve lower handover latencies. When the vehicle goes through a tunnel, the communication service is barely interrupted under a controlled environment. In the worst-case scenario, the interruptions do not span more than 20 milliseconds. Additionally, the quality of service is not affected during the vehicle trajectory where the communication link remains under a steady data rate and FER below \(10^{-3}\). These results demonstrate that the system can provide trusted services to deliver emergency notifications, crucial for Automated Guided Vehicles. Furthermore, the proposed solution also applies to urban scenarios, where the number of vehicular nodes per area is high. This factor does not impact the system performance considerably.  
As mentioned previously, the VLC network design for vehicular communication is still in the early stage of its development. Future works include studies of more complex scenarios, for example, considering interferences from vehicles in different lanes and changing their speed dynamically. Also, it is necessary to explore other cases when the vehicles can cause an obstruction. For example, in a road tunnel with more lanes, the uplink of a vehicle transiting in the central lane can be blocked by other vehicles. However, we would require to extend the simulator capabilities to evaluate these scenarios. Moreover, the propagating optical channel can suffer from some degradation effects that need incorporating in the simulations, such as car fume, dust, and turbulence effects. The handover estimation can be more reliable by adding supplementary tracking mechanisms to deal with erratic movement patterns. Eventually, it will be necessary to enhance the system design and perform practical trials to validate the solutions.  
The contributions of the authors in this paper are the following: conceptualization and methodology J.R., M.L.-R. and E.T.-Z; writing, edition, software, and validation E.T.-Z., M.L.-R. and V.G.; project administration R.P.-J. All authors have read and agreed to the published version of the manuscript.  
This project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 764461.  
Not applicable.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.