Performance Analysis of Hierarchical Cellular Networks With Generally Distributed Call Holding Times and Dwell Times

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.

User behavior modeling of voice communications: an empirical study

Büyükçorak

Kurt

Toprakkiran

2014

Performance evaluation of wireless cellular networks under more realistic assumptions

Fang

2005

In wireless cellular networks, performance evaluation is an important part in modeling and designing effective schemes to utilize the limited resource. In the past, performance evaluation was carried out either under restricted assumption on some time variables such as exponential assumption or via simulations. In this paper, we present a survey on a new analytical approach we have developed in the last few years to evaluate the performance of wireless cellular networks under more realistic assumptions. In particular, we apply this approach to the analysis of call connection performance and mobility management under assumptions that many time variables such as call holding time, cell residence time, channel holding time, registration area (RA) residence time, and inter‐service time are assumed to be generally distributed and show how we can obtain more general analytical results. Copyright © 2005 John Wiley & Sons, Ltd.

An approximation and its applications in wireless networks performance analysis

Zhang

Fujise²

2006

In the literature, there are two common assumptions for the tele-traffic parameter in analyzing the wireless network performance, that is, the tele-parameter follows a specific probability density function (pdf) and additionally the pdf exists closed-form Laplace Transform (LT). However, taking into account the cell irregular shape, the specific pdf may be unavailable while only the measured statistical moments are available. Moreover, the pdf function may not exist a closed-form LT, for example, lognormal distribution function. In this paper, based on the Central Limit Theorem and hyper-Erlang universal approximation property, we propose an approximation method applicable in the situations when only the statistical moments are available or LT of pdf does not exist. We then employ the technique in diverse applications, including the performance analysis of wireless network and the cost evaluation of mobility management. Extensive numerical examples demonstrate the good approximation capability to the exact formula and the simulation results.can be a good approximation for the cell residence time with random movement. By taking into account both the effect of shadowing and mobility characteristics as well as other parameters such as cell radius, Kourtis and Tafazolli [4] proposed the weighted summation of exponential and generalized Gamma distribution model for cell residence time. Based upon the probability and complex theory, reference [5] proposed a technique to study the call performance with the general call holding time and cell residence time in personal communications system (PCS) network. By modeling the call holding time as hyper-Erlang distribution [6], the WIRELESS NETWORKS PERFORMANCE ANALYSIS 115 Handoff Counting and Handoff RateThe handoff counting, defined as the number of experienced handoff per call, is of great significance for wireless network signaling traffic and performance analysis. We denote H as the handoff counting. For k ≥ 1, its probability mass function is expressed as Pr(H = k) = (1 − P n )Pr(T k < t c ≤ T k+1 )(1 − P h ) k +(1 − P n )Pr(t c ≥ T k+1 )(1 − P h ) k−1 P h