Network planning tool based on network classification and load prediction

Real Call Detail Records (CDR) are analyzed and classified based on Support Vector Machine (SVM) algorithm. The daily classification results in three traffic classes. We use two different algorithms, K-means and SVM to check the classification efficiency. A second support vector regression (SVR) bas...

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Bibliographic Details
Published in:arXiv.org 2016-02
Main Authors: Hammami, Seif eddine, Afifi, Hossam, Marot, Michel, Gauthier, Vincent
Format: Article
Language:English
Subjects:
Algorithms
Classification
Regression analysis
Support vector machines
Online Access:Get full text
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Summary:Real Call Detail Records (CDR) are analyzed and classified based on Support Vector Machine (SVM) algorithm. The daily classification results in three traffic classes. We use two different algorithms, K-means and SVM to check the classification efficiency. A second support vector regression (SVR) based algorithm is built to make an online prediction of traffic load using the history of CDRs. Then, these algorithms will be integrated to a network planning tool which will help cellular operators on planning optimally their access network.
ISSN:2331-8422