Communications à multi-saut dans un réseau cellulaire : État de l’art & Analyse

La partie accès des réseaux cellulaires génère des problèmes communs liés aux points morts (parties qui ne sont pas couvertes par le réseau) et aux points chauds (parties où le nombre d'utilisateurs est important par rapport aux ressources du réseau). Au cours des quinze dernières années, de nombreuses propositions de recherche ont tenté de résoudre les problèmes cellulaires grâce aux architectures MCN (Multi-hope Cellular Networks), un nouveau paradigme permettant l'extension de la partie accès cellulaire via des réseaux ad hoc. Dans cet article, nous proposons une étude de différentes architectures MCN. Nous identifions les principaux facteurs de classification MCN, nous comparons les architectures proposées avec les avantages et les inconvénients de chacune, puis nous présentons certaines questions ouvertes liées à ce sujet

Power-efficient resource allocation in a heterogeneous network with cellular and D2D capabilities

This paper focuses on a heterogeneous scenario in which cellular and wireless local area technologies coexist and in which mobile devices are enabled with device-to-device communication capabilities. In this context, this paper assumes a network architecture in which a given user equipment (UE) can receive mobile service either by connecting directly to a cellular base station or by connecting through another UE that acts as an access point and relays the traffic from a cellular base station. The paper investigates the optimization of the connectivity of different UEs with the target to minimize the total transmission power. An optimization framework is presented, and a distributed strategy based on Q-learning and softmax decision making is proposed as a means to solve the considered problem with reduced complexity. The proposed strategy is evaluated under different conditions, and it is shown that the strategy achieves a performance very close to the optimum. Moreover, significant transmission power reductions of approximately 40% are obtained with respect to the classical approach, in which all UEs are connected to the cellular infrastructure. For multi-cell scenarios, in which the optimum solution cannot be easily known a priori, the proposed approach is compared against a centralized genetic algorithm. The proposed approach achieves similar performance in terms of total transmitted power, while exhibiting much lower computational requirements.Peer ReviewedPostprint (author's final draft