Performance of a Link in a Field of Vehicular Interferers with Hardcore Headway Distance

TL;DR

This paper models vehicle locations with a hardcore distance to better predict interference and outage probability in vehicular networks, improving accuracy over traditional Poisson models especially in urban and highway scenarios.

Contribution

It introduces a new vehicle distribution model incorporating a hardcore distance and develops approximation methods for interference analysis, surpassing Poisson process limitations.

Findings

Approximations accurately predict interference in various scenarios.

Poisson model's predictions are less accurate with high interference variability.

Model performs well with multi-antenna receivers and retransmission schemes.

Abstract

The Poisson point process (PPP) is not always a realistic model for the locations of vehicles along a road, because it does not account for the safety distance a driver maintains from the vehicle ahead. In this paper, we model the inter-vehicle distance equal to the sum of a constant hardcore distance and a random distance following the exponential distribution. Unfortunately, the probability generating functional of this point process is unknown. To approximate the Laplace transform of interference at the origin, we devise simple approximations for the variance and skewness of interference, and we select suitable probability functions to model the interference distribution. When the coefficient-of-variation and the skewness of interference distribution are high, the PPP (of equal intensity) approximation of the outage probability becomes loose in the upper tail. Relevant scenarios are associated with urban microcells and highway macrocells with a low density of vehicles. The predictions of PPP deteriorate with a multi-antenna maximum ratio combining receiver and temporal indicators related to the performance of retransmission schemes. Our approximations generate good predictions in all considered cases.