Improving User Environment Detection Using Context-aware Multi-Task Deep Learning in Mobile Networks - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Article Dans Une Revue IEEE Transactions on Cognitive Communications and Networking Année : 2022

Improving User Environment Detection Using Context-aware Multi-Task Deep Learning in Mobile Networks

Résumé

Cognition of user behavior can make future mobile networks more intelligent and flexible. Knowledge about users' habits can be used to personalize services and intelligently manage network resources. However, inferring this key information with a low-cost signaling implementation, and avoiding constant user interaction, is crucial for Mobile Network Operators (MNOs). With this motivation, this paper investigates the detection of the real-life mobile user environment using contextaware detection via multi-task learning (MTL). We propose models that are able to automatically detect up to eight distinct real-life user environments. We also improve the detection accuracy with the assistance of the mobility state profiling task. We associate both environment and mobility tasks because they correspond to the main attributes of user behavior and, additionally, both of them are correlated. Using MTL, the task of detecting environment corresponds to simultaneously answering the questions: "how and where mobile user consumes mobile services?". We build models using real-life radio data which is already available in network. This data has been massively gathered from multiple diversified situations of mobile users. Simulation results support our claim to detect several environment classes in network infrastructure with improved UED accuracy.
Fichier principal
Vignette du fichier
IEEE_TCCN_Journal_Final.pdf (3.54 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03781983 , version 1 (20-09-2022)

Identifiants

Citer

Marie Line Alberi Morel, Illyyne Saffar, Kamal Singh, Sid Ali Hamideche, César Viho. Improving User Environment Detection Using Context-aware Multi-Task Deep Learning in Mobile Networks. IEEE Transactions on Cognitive Communications and Networking, 2022, pp.1-11. ⟨10.1109/TCCN.2022.3205696⟩. ⟨hal-03781983⟩
57 Consultations
92 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More