Trajectory estimation based on mobile network operator data for cellular network simulations

Abstract

In this paper, we present a framework for estimating trajectories of cellular networks users based on mobile network operator data. We use handover and location area update events of both speech and packet data users captured in the core network of the Austrian MNO A1 to estimate the subscribers' mobility behavior. By utilizing publicly available data, i.e., environmental information, road infrastructure data, transmitter power ranges and antenna characteristics, our approach allows the estimation of subscriber trajectories for both urban and semi-rural environments with a good accordance to the actual trajectories. Additionally, we present a method to estimate a particular subscriber's movement velocity, on the basis of mentioned data. Furthermore, we propose a methodology to estimate when a particular user started or ended a speech or packet data session during his journey, based on mobility-related network events. With this, our framework enables the creation of reproducible mobility situations for cellular network simulations at system level.

Big data and data analytics in 5G mobile networks

“…A mobile network operator (MNO) records many incidents on its primary network interfaces by installing network detectors. Each incident recorded on the primary network has the following characteristics [49].…”

“…The first event describes a call installation, followed by three HO events and a call termination event. Using the position of the base station involved in conjunction with the configuration of their antenna (i.e., the angles of electrical vision), an approximate part of the subscriber at the time of the event can be determined [49].…”