Allocation de ressources et association utilisateur/cellule optimisées pour les futurs réseaux denses

par Duc thang Ha

Projet de thèse en Réseaux, information et communications

Sous la direction de Lila Boukhatem et de Steven Martin.

Thèses en préparation à Paris Saclay , dans le cadre de Sciences et Technologies de l'Information et de la Communication , en partenariat avec LRI - Laboratoire de Recherche en Informatique (laboratoire) , ROCS - Réseaux & Optimisation Combinatoire et Stochastique (equipe de recherche) et de Université Paris-Sud (établissement de préparation de la thèse) depuis le 01-10-2015 .


  • Résumé

    L'objectif de la thèse est de trouver des allocations optimaux pour le communication D2D dans les réseaux denses. Nous projetons de développer des solutions algorithmiques que nous modélisons ou analysons avec des outils théoriques telles que la théorie des jeux, théorie des couplages.

  • Titre traduit

    Optimized resource allocation and user / cell association for future dense networks


  • Résumé

    The goal of this PhD thesis is to conduct a comprehensive study on the context-aware joint resource allocation and user to cell association problem in future D2D (Device to Device)-enabled dense small cells networks under spectral and energy efficiency constraints. Besides the capacity increase, one of the main key design requirements of future wireless networks (5G) is the massive densification of the network and the minimization of the energy consumption. In this context, we aim to develop optimized and original joint resource allocation and user to cell association solutions which will take into account users' context information (such as user application profile: proximity applications, QoS/QoE (Quality of Service/Quality of Experience) constraints; user mobility, etc.) under the joint constraints imposed by the maximization of spectral and energy efficiencies (SE and EE). More specifically, under D2D-enabled dense small cells deployments, optimal user to cell association decisions as well as D2D links establishments will be developed together with dynamic cell range expansion (CRE) adaptations for an optimal system performance (in terms of SE and EE). To achieve these goals, the problem will be formalized and resolved using tools from the optimization theory (linear and dynamic programming), the matching theory and/or the game theory. Moreover, to avoid optimal approaches complexity, heuristic solutions and algorithms with reasonable complexity will be proposed. The developed solutions have to be validated on a theoretical basis along with a series of simulations taking into account different realistic scenarios.