Spatial Models for Networks on Roads: Bridging the Gap Between Industry and Academia

Cellular vehicle-to-everything (C-V2X) communication is one of the most important features of the fifth generation new radio (5G-NR) standard. The design and deployment of efficient networks that meet the demanding performance requirements of such features necessitates a thorough understanding of the system-level performance. However, vehicular network studies in the industry have mostly relied on fairly simplistic spatial models where the roads are modeled by a deterministic grid and wireless nodes are stochastically placed on them. Meanwhile, more sophisticated doubly stochastic models, such as the Poisson line Cox process (PLCP), have been developed in academia that capture the randomness in both the road layouts and the position of vehicles. In this article, we bridge this gap by providing an accessible introduction to the PLCP and demonstrating its relevance in the study of various performance metrics of interest to the industry. Further, the versatility of this model enables the study of path distance characteristics, which have useful applications in transportation networks and the Industrial Internet of Things. Some promising future research directions are also discussed.