Network slicing for vehicular communication

AbstractAbstractUltra‐reliable vehicle‐to‐everything (V2X) communication is essential for enabling the next generation of intelligent vehicles. V2X communication is a growing area of communication that connects vehicles to neighboring vehicles (V2V), infrastructure (V2I), and pedestrians (V2P). Network slicing is one of the promising technologies for connectivity of the next generation devices, creating several logical networks on a common and programmable physical infrastructure. Network slicing offers an efficient way to satisfy the diverse use case requirements by exploiting the benefits of shared physical infrastructure. In this regard, we propose a network slicing‐based communication solution for vehicular networks. In this work, we model a highway scenario with vehicles having heterogeneous traffic demands. The autonomous driving slice (safety messages) and the infotainment slice (video stream) are the two logical slices created on a common infrastructure. We formulated a network clustering and slicing algorithm to partition the vehicles into different clusters and allocate slice leaders (SLs) to each cluster. SLs serve its clustered vehicles with high‐quality V2V links and forwards safety information with low latency. On the other hand, road side unit provides infotainment service using high‐quality V2I links. An extensive Long Term Evolution Advanced system‐level simulator with enhancement of cellular V2X standard is used to evaluate the performance of the proposed method, in which it is shown that the proposed network slicing technique achieves low latency and high‐reliability communication. View Figure We have studied the performance of network slicing based vehicular communication network with heterogeneous traffic demands. Ultra reliable low latency (URLLC) requirements are satisfied with the autonomous driving sub‐slice and the enhanced mobile broadband (eMBB) services are provided with the infotainment sub‐slice. The network clustering algorithm is formulated to partition the vehicular user equipment's (VUE's) into different clusters and the slicing algorithm is responsible for assigning virtual access points. The performance of the proposed network slicing framework is analyzed through extensive simulations.