Doctoral research project

Person in charge of the project:
LAUWEREINS RUDY, member of research team Associated Section of ESAT - INSYS, Integrated Systems
Dynamic Resource Allocation and Self-Organizing Signalling Optimisation in LTE-A Downlink
Project summary:
This doctoral work has been focused on the management of a vast, dynamic and distributed cellular network. The main ideas verge on the fact that a complex system, to be managed properly, has to distribute resources The main objective of this doctoral work is to find a good, practical solution for the radio resource management problem of a future heterogeneous network serving a massive number of mobile users. This entails making sure that the network allocates its resources in a way that is satisfactory to all users. This dissertation finds solutions for the two following questions:(1) Can a practical and implementable distributed solution be found to allow a heterogeneous network to maximise overall performance by minimising overall interference? (2) Can the total amount of control information necessary to allocate resources to the user be reduced without sacrificing payload performance?An equilibrium between these two objectives requires a careful characterization of the network's properties and the design of methods able to manage small parts of the network, with only local information, but with global consequences.In this work, the interference management problem is first considered, as by reducing interference, the capacity of the network is increased. In fact, by applying the distributed inter-cell interference coordination method proposed in this work an improvement of about 50% can be seen for the previously interfered users.Afterwards, machine learning solutions are provided to reduce the amount of control information necessary to manage the network both in the frequency and in the time domains. It is shown that it is possible to reduce the amount of control information in frequency and gain 20% of performance. It is also shown that it is possible to predict the link quality of a user, with respect to its mobility and estimate its behaviour in time. By doing so, the system is able to operate with a factor 16 less control information while losing only 5% in performance.
ph.D student :
Faculty of Engineering Science
Doctoral Programme in Engineering Science (Leuven)

ph.D defence : 09.10.2015
Full text ph.D