User behavior modeling of voice communications: an empirical study

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.

The short-term prediction of the mobile communication traffic based on the product seasonal model

“…With the widespread use of mobile devices, a large number of high-resolution spatial and temporal data are collected. Scientists use different methods to analyze mobile communication data to study human behavior [1,2], predict trends in mobile communication data [3], establish the traffic signal advisory system [4] and analyze the future development of mobile services [5,6]. With the rapid development of mobile network and the universality of network services, the storage of traffic increases.…”