Soutenance de thèse de doctorat le 19 Décembre 2019, 10h00 à CentraleSupelec (Gif-sur-Yvette) Amphi F3-06
| M. Marco Di Renzo | Directeur de recherche CNRS | Directeur de Thèse |
| Mme Maryline Helard | Professeur – IETR | Président |
| M. Jalel Ben-Othman | Professeur-CNRS-CentraleSupélec-Université Paris-Saclay-Université Paris 13 | Examinateur |
| M. Jean-Marie Gorce | Professeur – INSA-Lyon | Examinateur |
| Mme Valeria Loscri | Chargé de recherche – Inria Lille-Nord Europe | Examinateur |
| Mme Lina Mroueh | Maître de conférences – ISEP | Examinateur |
| M. Mustapha Benjillali | Maître de conférences – INPT – Maroc | Rapporteur |
| M. Laurent Clavier | Professeur – Institut Mines-Telecom | Rapporteur |
The main focus of this thesis is on modeling, performance evaluation and system-level optimization of next-generation cellular networks by using stochastic geometry. In addition, the emerging technology of Reconfigurable Intelligent Surfaces (RISs) is investigated for application to future wireless networks. In particular, relying on a Poisson-based abstraction model for the spatial distribution of nodes and access points, this thesis develops a set of new analytical frameworks for the computation of important performance metrics, such as the coverage probability and potential spectral efficiency, which can be used for system-level analysis and optimization. More specifically, a new analytical methodology for the analysis of three-dimensional cellular networks is introduced and employed for system optimization. A novel resource allocation problem is formulated and solved by jointly combining for the first time stochastic geometry and mixed-integer non-linear programming. The impact of deploying intelligent reflecting surfaces throughout a wireless network is quantified with the aid of line point processes, and the potential benefits of RISs against relaying are investigated with the aid of numerical simulations.
This PhD thesis is supported by the European Commission through the H2020-ETN-5Gaura project under grant 675806.
