Soutenance de thèse
13/06/2018 – 10:00
This thesis focuses on the study of noise and interference exhibiting an impulsive behavior, an attribute that can be found in many contexts such as wireless communications or molecular communications. This interference is characterized by the presence of high amplitudes during short durations, an effect that is not well represented by the classical Gaussian model. In fact, these undesirable features lead to heavier tails in the distributions and can be modeled by the alpha-stable distribution. In particular, we study the impulsive behavior that occurs in large-scale communication networks that forms the basis for our model of dynamic interference. More precisely, such interference can be encountered in heterogeneous networks with short packets to be transmitted, as in the Internet of Things, when the set of active interferers varies rapidly.
The first part of this work is to study the capacity of alpha-stable additive noise channels, which is not well understood at present. We derive lower and upper bounds for the capacity with an absolute moment (amplitude) constraint. The second part consists in analyzing the impact of our bounds in practical contexts.
Jury members :
Philippe Ciblat, Professeur, Telecom ParisTech
Marco Di Renzo : Chargé de recherche CNRS, L2S, Centrale Supélec, France
Mérouane Debbah, Directeur laboratoire R&D en mathématiques etcalgorithmes, Huawei Technologies ;
Gareth W. Peters Prof. Chair, Statistics for Risk and Insurance, Heriot-Watt University,
Michèle Wigger Maître de Conférence, Telecom ParisTech, France
Atika Rivenq Professeur, Université de Valenciennes et du Hainaut-Cambrésis, France
Laurent Clavier Professeur, IMT, Télécom Lille, France
Malcolm Egan, Associate Professor, INSA de Lyon, France