How To Dimension Radio Resources When Users Are Distributed on Roads Modeled by Poisson Line Process

TL;DR

This paper introduces a novel radio resource dimensioning method for road-based user distributions modeled by Poisson Line Processes, focusing on congestion probability as a key QoS metric, with analytical derivations and numerical validations.

Contribution

It provides a new analytical framework for radio resource dimensioning considering road-based user distributions and congestion probability, extending beyond traditional spatial models.

Findings

Analytical expression for congestion probability derived.

Resource dimensioning relation established based on congestion probability.

Numerical results validate the proposed dimensioning approach.

Abstract

Resources dimensioning aims at finding the number of radio resources required to carry a forecast data traffic at a target users Quality of Services (QoS). The present paper attempts to provide a new approach of radio resources dimensioning considering the congestion probability, qualified as a relevant metric for QoS evaluation. Users are assumed to be distributed according to a linear Poisson Point Process (PPP) in a random system of roads modeled by Poisson Line Process (PLP) instead of the widely-used spatial PPP. We derive the analytical expression of the congestion probability for analyzing its behavior as a function of network parameters. Finally we show how to dimension radio resources by setting a value of the congestion probability, often targeted by the operator, in order to find the relation between the necessary resources and the forecast data traffic expressed in terms of cell throughput. Different numerical results are presented to justify this dimensioning approach.