Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik
Doi
Abstract
Stochastic geometry models are used to study wireless networks,
particularly cellular phone networks, but most of the research focuses on the
typical user, often ignoring atypical events, which can be highly disruptive
and of interest to network operators. We examine atypical events when a
unexpected large proportion of users are disconnected or connected by
proposing a hybrid approach based on ray launching simulation and point
process theory. This work is motivated by recent results [12] using large
deviations theory applied to the signal-to-interference ratio. This theory
provides a tool for the stochastic analysis of atypical but disruptive
events, particularly when the density of transmitters is high. For a section
of a European city, we introduce a new stochastic model of a single network
cell that uses ray launching data generated with the open source RaLaNS
package, giving deterministic path loss values. We collect statistics on the
fraction of (dis)connected users in the uplink, and observe that the
probability of an unexpected large proportion of disconnected users decreases
exponentially when the transmitter density increases. This observation
implies that denser networks become more stable in the sense that the
probability of the fraction of (dis)connected users deviating from its mean,
is exponentially small. We also empirically obtain and illustrate the density
of users for network configurations in the disruptive event, which highlights
the fact that such bottleneck behaviour not only stems from too many users at
the cell boundary, but also from the near-far effect of many users in the
immediate vicinity of the base station. We discuss the implications of these
findings and outline possible future research directions