User behavior modeling of voice communications: an empirical study. Issue 1 (12th June 2014)

• Record Type: Journal Article
• Authors: Büyükçorak, Saliha; Karabulut Kurt, Gunes; Toprakkiran, Guven
• Is Part Of: Wireless communications and mobile computing. Volume 16:Issue 1(2016)
• Page Start: 29
• Page End: 46
• Publication Date: 2014-06-12
• Subjects: cellular networks -- data acquisition system -- android operating system -- hurst parameter -- modified Allan variance (MAVAR) -- wavelet log‐scale diagram -- autocorrelation function -- incoming and outgoing calls -- poisson random process -- call holding time (CHT) distribution -- mixture of lognormal distributions -- maximum likelihood estimation (MLE) -- expectation maximization (EM); Wireless communication systems -- Periodicals; Mobile communication systems -- Periodicals; 621.38205
• DOI: 10.1002/wcm.2491
• Languages: English
• ISSNs: 1530-8669

Abstract

Abstract: In this study, analysis and modeling of arrival and service processes are presented in a comprehensive fashion in order to determine statistical properties of voice traffic from end‐user perspective in accordance with the queueing theory. For the first time in the literature, we introduce a user centric approach and examine these services considering both flow directions of voice traffic, the uplink and the downlink as opposed to existing studies with the network centric approach. In our study, we use experimental data composed of actual phone calls collected from 2G/3G networks. To achieve this, we designed and implemented a data collection system for mobile users and compared the results by using data from an operational cellular network. In order to determine the time correlation of voice calls, Hurst parameter estimation methods are used. On the basis of the outcomes, independency of call arrivals is shown. Additionally, it is shown that calls acquired from user and network centric approaches are both Poisson distributed. Next, looking at the problem from service process perspective, thorough analyses are performed to determine mathematical models that can best characterize call holding times. Maximum likelihood estimation and expectation maximization algorithm are used, and it is shown that the optimum mathematical model for the characterization of call holding times is the lognormal distribution family. Copyright © 2014 John Wiley & Sons, Ltd. Abstract : In this study, analysis and modeling of arrival and service processes are presented in a comprehensive fashion in order to determine statistical properties of voice traffic from end‐user perspective in accordance with the queueing theory. We introduce a user centric approach and examine these services considering both flow directions of voice traffic, the uplink, and the downlink as opposed to existing studies with the network centric approach.