Open AccessDynamic backhaul resource allocation in wireless networks using artificial neural networks
Author(s) -
Loumiotis I.,
Stamatiadi T.,
Adamopoulou E.,
Demestichas K.,
Sykas E.
Publication year - 2013
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2013.0454
Subject(s) - backhaul (telecommunications) , base station , computer network , computer science , software deployment , wireless , wireless network , quality of service , commit , artificial neural network , bandwidth (computing) , bandwidth allocation , distributed computing , telecommunications , artificial intelligence , database , operating system
The increasing bandwidth demand of end‐users renders the need for efficient resource management more compelling in next generation wireless networks. In the present work, a novel scheme incorporating the deployment of an intelligent agent capable of monitoring, storing, and predicting the forthcoming needs for resources of a base station (BS) is proposed. In this way, the BS can in advance commit the necessary resources for its backhaul connection, guaranteeing the end‐user's quality of service. The prediction process is performed using machine learning techniques.