Steering Mobile Users in LTE Networks Based on Their Mobility Behaviour

Date: 21 June 2017

Venue: Campus Middelheim, G0.10 - Middelheimlaan 1 - 2020 Antwerpen (route: UAntwerpen, Campus Middelheim)

Time: 4:00 PM

PhD candidate: Bart Sas

Principal investigator: Chris Blondia

Short description: PhD defence Bart Sas - Faculty of Science, Dept. of Mathematics & Computer Science



Abstract

In cellular networks, in case of a dense deployment of cells and/or when user velocities are high, frequent handovers will occur.

These frequent handovers will have a negative impact of the performance of certain applications, especially real-time applications.

In this thesis a SON (Self-Organising Network) function is developed that deals with this problem.

The SON function classifies users according to their mobility behaviour and, based on this classification, steers them in an intelligent way such that the number of short stays are reduced while the QoS (Quality of Service) is maintained or possibly even improved.

By assuming that events that occur to one user will also occur to another user that follows a similar trajectory through a cell, the SON function can decide whether it is beneficial to hand over the user to another cell or to keep it in the current cell.

In order to do this, the SON function will match currently active with users that were active in the past and assume that the future behaviour of the currently active user in the will be similar to the behaviour of the user that was active in the past.

Based on this information the SON algorithm makes a decision on how to steer the user.

The developed SON function consists of three components, namely the Trajectory Classifier, the Trajectory Identifier and the Traffic Steerer.

The Trajectory Classifier is responsible for classifying users according to the trajectory they follow through the cell.

It does this by comparing measurement traces that are made by currently active users (active traces) to measurement traces that were made by users that were active in the past (reference traces), and as such identifying matching traces of measurements.

For the matching, an algorithm that is based on the well known Dynamic Time Warping (DTW) algorithm is used.

The Trajectory Identifier is responsible for identifying the traces that will serve as reference traces.

This means selecting new reference traces as well as removing old, obsolete reference traces.

The Traffic Steerer is responsible for making a traffic steering decision once a sufficiently reliable match of the trajectory of a currently active user with a reference trace has been made by the Trajectory Classifier.

Results show that the SON function is able to reduce the amount of short stays significantly in scenarios where there are frequent handovers.

 



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