# Review of Communication Technologies for Electric Vehicle Charging Management and Coordination
## 8 Conclusions  
Large-scale adoption of electric vehicles is expected to reduce environmental pollution, yet is hindered by the range anxiety of EV drivers due to the limited driving range, long recharging time, and low penetration of fast recharging facilities in addition to the high purchase prices of commercial EVs. Wireless EV charging solutions offer convenient and reliable charging with no physical connectivity between the EV and the charging points, thereby enabling dynamic on-the-road EV charging with minimal charging downtime and reduced range anxiety. Nevertheless, in order to achieve efficient charging, information on traffic conditions, battery level, waiting time, and charging system state must be exchanged between the EVs and the charging infrastructure. Therefore, reliable communication links between EVs and the charging systems are necessary to exchange information, monitor system states, and coordinate charging decisions. High throughput, low latency, and high security are other desirable characteristics of the vehicular communication links to guarantee the desired QoS. This paper reviewed the existing literature on vehicular communication technologies and their utilization for static and dynamic EV charging coordination and management. The radio access technologies for vehicular communication were presented and the communication requirements for EV charging services were highlighted. Different physical layer security techniques were also surveyed to address the security requirements of vehicular communications. The role of vehicular communication technologies in EV charging management and coordination was then discussed in detail. Among the different radio access technologies for vehicular communications surveyed in this work, LTE cellular networks offer the advantages of ubiquitous coverage, high QoS, and infrastructure readiness in comparison with the DSRC networks proposed for VANETs. Nevertheless, LTE networks are not optimized for vehicular communications and, hence, suffer from inefficient operation in high density scenarios. The same issue persists with LTE C-V2X networks despite their improved mobility support, which accordingly impacts EV charging coordination in locations with high traffic density and high EV charging demands. In contrast, 5G NR-V2X communication networks offer improved performance in high dense networks while providing ultra-low latency, high reliability, and high mobility support. Nevertheless, in order to satisfy the requirements of different EV charging modes in different traffic density levels and network congestion scenarios, heterogeneous vehicular communication networks need to be deployed to utilize technologies such as massive MIMO, mmWave, and SDNs to enable effective EV charging coordination. Furthermore, with this massive information exchange between different entities at high vehicular mobility levels, advanced physical layer security techniques need to be implemented to protect the communication channels from illegitimate attacks. Collectively, the evolution of different vehicular RATs and different PLS strategies is expected to offer more efficient mobility-aware coordination and scheduling and better energy management. Nevertheless, most of the published literature on EV charging coordination assumes the existence of an underlying effective vehicular communication infrastructure, without studying the specific requirements of the communication network for effective EV charging management in an IoEV. Hence, further studies are required to develop the end-to-end architecture of the IoEV, by defining the roles of the different RATs and PLS techniques for effective EV charging coordination. Conceptualization, E.E., I.A., M.H. and A.O. ; methodology, I.A. and E.E. ; software, I.A. ; validation, M.H. and A.O. ; formal analysis, E.E. and I.A. ; investigation, I.A. and E.E. ; resources, M.H. and A.O. ; data curation, I.A. ; writing--original draft preparation, E.E. ; writing--review and editing, M.H. and A.O. ; visualization, E.E., I.A., M.H. and A.O.