Allocation de ressource opportuniste dans les réseaux sans fil multicellulaires

Mahdi Ezzaouia 1, 2
2 ADOPNET - Advanced technologies for operated networks
UR1 - Université de Rennes 1, IMT Atlantique - IMT Atlantique Bretagne-Pays de la Loire, IRISA-D2 - RÉSEAUX, TÉLÉCOMMUNICATION ET SERVICES
Abstract : The exponential growth of traffic in mobile networks is accompanied by an increase in its heterogeneity, both in space and over time. This thesis deals with scheduling algorithms adapted to highly concentrated and time-varying traffic zones. We propose a spectrum borrowing mechanism from an under-loaded cell to an overloaded one combined with a reactive intra-cellular scheduling algorithm. We are also interested in the Cloud Radio Access Network architecture that separates the Radio Head(RRH) from the Baseband Unit (BBU). The BBU is connected to the RRU according to two modes. The first one is called a one-to-one association and consists in allocating the resource units of the BBU radio frame to a single RRH. In the second mode which is called multiple association, a BBU can handle multiple RRHs. We propose a hybrid association mode in which the resource units of each frame are divided into two slices. The first one constitutes an unshared slice and is allocated to central users according to the one-to-one association in order to increase the throughput, especially at high traffic load. The second slice contains a quantity of resource units that are shared by a group of RRHs belonging to the same BBU. This common slice is configured according to the multiple association mode and is allocated to the edge and mobile users. We show that the hybrid mode reduces the inter-cell interferences, decreases the number of inter-BBU handovers and improves the energy consumption.
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  • HAL Id : tel-02118466, version 1


Mahdi Ezzaouia. Allocation de ressource opportuniste dans les réseaux sans fil multicellulaires. Réseaux et télécommunications [cs.NI]. Ecole nationale supérieure Mines-Télécom Atlantique; Université de Tunis El Manar, 2018. Français. ⟨NNT : 2018IMTA0098⟩. ⟨tel-02118466⟩



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