Treffer: Mobile Terminal Session SIR Prediction Method Based on Clustering and Classification Algorithms

Title:
Mobile Terminal Session SIR Prediction Method Based on Clustering and Classification Algorithms
Authors:
Jose F. Monserrat, Daniel Calabuig, David Martin-Sacristan, Narcis Cardona
Source:
2010 IEEE Wireless Communication and Networking Conference. :1-5
Publisher Information:
IEEE, 2010.
Publication Year:
2010
Subject Terms:
0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 0101 mathematics, 01 natural sciences
Document Type:
Fachzeitschrift Article
DOI:
10.1109/wcnc.2010.5506222
Access URL:
https://ieeexplore.ieee.org/document/5506222/
https://dblp.uni-trier.de/db/conf/wcnc/wcnc2010.html#Martin-SacristanMCC10
http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000005506222
http://ieeexplore.ieee.org/document/5506222/
Accession Number:
edsair.doi.dedup.....9a72db8e18ab4d8a845aa7c40f3f2d62
Database:
OpenAIRE

Weitere Informationen

In this paper, a novel method for mobile terminal session signal to interference ratio (SIR) prediction is presented. The method is based on clustering and classification algorithms configuring a fully-automatic process, highly adaptable to the deployment scenario. It is focused on the prediction of the session SIR probability density function (pdf) of each user whose knowledge will allow for the application of advanced radio resource management (RRM) techniques. The proposed method has been applied in simulated and real scenarios showing its validity in both cases.