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A Probabilistic Framework for Estimating Call Holding Time Distributions (bibtex)
A Probabilistic Framework for Estimating Call Holding Time Distributions (bibtex)
by Saliha Büyükçorak, Güneş Karabulut Kurt, Okan Cengaver
Abstract:
Call holding time (CHT) is a statistical indicator in a cellular network, directly affecting network performance and providing critical insight for the network service provider. CHT distribution estimation literature relies on the classical estimation theory that targets to determine parameters of a function. Hence related work can be considered as making use of parametric approaches. However, the required assumptions for these approaches may not be correct in order to obtain an accurate model. In this paper, we introduce a probabilistic framework for CHT distribution estimation, which makes use of Dirichlet process mixture of lognormal distributions. The purpose of this work is to provide a practical Bayesian inference framework to enable the extraction and identification of user behaviors, which are not available through traditional estimation techniques. The performance of the proposed framework is tested on a large dataset that is obtained from a mobile switching center of a cellular network service provider composed of calls from GSM and HSPA networks. Accuracy of the obtained CHT distributions are verified through several performance tests, showing that all distribution estimates have significance levels of 0.99.
Reference:
Saliha Büyükçorak, Güneş Karabulut Kurt, Okan Cengaver, "A Probabilistic Framework for Estimating Call Holding Time Distributions", IEEE Transactions on Vehicular Technology, vol. 63, no. 99, pp. 811- 821, 2014, February. ([paperpdf])
Bibtex Entry:
@ARTICLE{buyukcorakkurtcengaver2013, 
author={Saliha Büyükçorak and Güneş Karabulut Kurt and Okan Cengaver}, 
journal={IEEE Transactions on Vehicular Technology}, 
title={A Probabilistic Framework for Estimating Call Holding Time Distributions}, 
year={2014}, 
month = {february},
volume={63},
issue={2}, 
number={99}, 
pages={811 - 821}, 
abstract={Call holding time (CHT) is a statistical indicator in a cellular network, directly affecting network performance and providing critical insight for the network service provider. CHT distribution estimation literature relies on the classical estimation theory that targets to determine parameters of a function. Hence related work can be considered as making use of parametric approaches. However, the required assumptions for these approaches may not be correct in order to obtain an accurate model. In this paper, we introduce a probabilistic framework for CHT distribution estimation, which makes use of Dirichlet process mixture of lognormal distributions. The purpose of this work is to provide a practical Bayesian inference framework to enable the extraction and identification of user behaviors, which are not available through traditional estimation techniques. The performance of the proposed framework is tested on a large dataset that is obtained from a mobile switching center of a cellular network service provider composed of calls from GSM and HSPA networks. Accuracy of the obtained CHT distributions are verified through several performance tests, showing that all distribution estimates have significance levels of 0.99.}, 
keywords={Call holding time distribution;Dirichlet process mixture model;cellular radio;mixture of lognormal distributions}, 
doi={10.1109/TVT.2013.2275081}, 
url={http://dx.doi.org/10.1109/TVT.2013.2275081},
comment={<a href="http://akademi.itu.edu.tr/gkurt/DosyaGetir/90566/06570525.pdf">[paperpdf]</a>},
ISSN={0018-9545},
}
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