  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.
