Accéder directement au contenu Accéder directement à la navigation
Nouvelle interface
Communication dans un congrès

DNN Based Beam Selection in mmW Heterogeneous Networks

Abstract : We consider a heterogeneous cellular network wherein multiple small cell millimeter wave (mmW) base stations (BSs) coexist with legacy sub-6GHz macro BSs. In the mmW band, small cells use multiple narrow beams to ensure sufficient coverage and User Equipments (UEs) have to select the best small cell and the best beam in order to access the network. This process usually based on exhaustive search may introduce unacceptable latency. In order to address this issue, we rely on the sub-6GHz macro BS support and propose a deep neural network (DNN) architecture that utilizes basic components from the Channel State Information (CSI) of sub-6GHz network as input features. The output of the DNN is the mmW BS and beam selection that can provide the best communication performance. In the set of features, we avoid using the UE location, which may not be readily available for every device. We formulate a mmW BS selection and beam selection problem as a classification and regression problem respectively and propose a joint solution using a branched neural network. The numerical comparison with the conventional exhaustive search results shows that the proposed design demonstrate better performance than exhaustive search in terms of la-tency with at least 85% accuracy.
Type de document :
Communication dans un congrès
Liste complète des métadonnées

Littérature citée [15 références]  Voir  Masquer  Télécharger
Contributeur : Marceau Coupechoux Connectez-vous pour contacter le contributeur
Soumis le : vendredi 10 juillet 2020 - 09:37:51
Dernière modification le : vendredi 3 décembre 2021 - 11:43:00
Archivage à long terme le : : lundi 30 novembre 2020 - 19:01:54


Fichiers produits par l'(les) auteur(s)


  • HAL Id : hal-02895732, version 1


Deepa Jagyasi, Marceau Coupechoux. DNN Based Beam Selection in mmW Heterogeneous Networks. International Conference on Network Games, Control and Optimisation (Netgcoop), 2020, Cargèse, France. ⟨hal-02895732⟩



Consultations de la notice


Téléchargements de fichiers