Analysis of a Spatially Correlated Vehicular Network Assisted by Cox-Distributed Vehicle Relays

In vehicle-to-everything (V2X) communications, roadside units (RSUs) play an essential role in connecting various network devices. In some cases, users may not be well-served by RSUs due to congestion, attenuation, or interference. In these cases, vehicular relays associated with RSUs can be used to serve those users. This paper uses stochastic geometry to model and analyze a spatially correlated heterogeneous vehicular network where both RSUs and vehicular relays serve network users such as pedestrians or other vehicles. We present an analytical model where the spatial correlation between roads, RSUs, relays, and users is systematically modeled via Cox point processes. Assuming users are associated with either RSUs or relays, we derive the association probability and the coverage probability of the typical user. Then, we derive the user throughput by considering interactions of links unique to the proposed network. This paper gives practical insights into designing spatially correlated vehicular networks assisted by vehicle relays. For instance, we express network performance such as user association, signal-to-interference (SIR) coverage probability, and network throughput as the functions of network key geometric parameters. In practice, this helps one to optimize the network so as to achieve ultra reliability or maximum user throughput of the vehicular networks by varying key aspects such as the relay density or the bandwidth for relays.