A model for teletraffic performance and channel holding time characterization in wireless cellular communication with general session and dwell time distributions

Orlik, Philip V.; Rappaport, S.S.

doi:10.1109/49.700913

Cited by 173 publications

(103 citation statements)

References 10 publications

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“…Zonoozi et al [6] used the Gamma distribution to model the cell residence time. Other researchers, Orlik et al [3], suggested using the Sum of Hyperexponential distribution for the cell residence time. The characterization of the cell residence time as a nonexponential distribution proved to be timely.…”

Section: Introductionmentioning

confidence: 99%

A Coxian model for channel holding time distribution for teletraffic mobility modeling

Soong

Barria

2000

IEEE Commun. Lett.

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Abstract-In this letter, we derive an algebraic set of equations that examines the relationships between the cell residence times and the handoff call's channel holding time. When the cell residence times have an Erlang or Hyper-Erlang distribution, the channel holding times can be represented by a Coxian model. An algorithm is presented to compute the parameters of the equivalent Coxian model. The analytical models proposed in this letter provide a flexible framework for further studies into the optimization and performance evaluation aspects of teletraffic mobile systems.

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Section: Introductionmentioning

confidence: 99%

A Coxian model for channel holding time distribution for teletraffic mobility modeling

Soong

Barria

2000

IEEE Commun. Lett.

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“…Thus, the one-dimensional Markov chain model for some guard channel CAC schemes assuming that the new calls and handoff calls are identically distributed may not be appropriate; the multidimensional Markov chain may be needed. Rappaport and his colleagues noticed such an observation and started a series of research works (e.g., [9], [20], and [18]). In [20], Rappaport used the generalized Erlang distribution to model some random variable (such as dwell time).…”

Section: ) Guard Channel (Gc) Schemesmentioning

confidence: 99%

“…In [20], Rappaport used the generalized Erlang distribution to model some random variable (such as dwell time). In [18], Orlik and Rappaport proposed the sum of hyperexponential distribution to model the dwell time. The multidimensional Markovian chain theory has been extensively used in their research.…”

Section: ) Guard Channel (Gc) Schemesmentioning

confidence: 99%

Call admission control schemes and performance analysis in wireless mobile networks

Fang

Zhang²

2002

IEEE Trans. Veh. Technol.

335

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Abstract-Call admission control (CAC) plays a significant role in providing the desired quality of service in wireless networks. Many CAC schemes have been proposed. Analytical results for some performance metrics such as call blocking probabilities are obtained under some specific assumptions. It is observed, however, that due to the mobility, some assumptions may not be valid, which is the case when the average values of channel holding times for new calls and handoff calls are not equal. In this paper, we reexamine some of the analytical results for call blocking probabilities for some call admission control schemes under more general assumptions and provide some easier-to-compute approximate formulas.

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“…A large number of studies have been made on the performance of cellular mobile systems [4,5,[11][12][13][14][15][16]. Hong et al studied prioritized handoff procedures in cellular systems [4].…”

Section: Introductionmentioning

confidence: 99%

“…These studies assumed the calls to arrive according to a Poisson process and the dwell time and unencumbered-session time to be exponentially distributed. Orlik et al [12] studied cellular systems in terms of non-exponential dwell-time and session-time distributions. They also considered the analysis based on MMPP for the handoff arrival process [13].…”

Section: Introductionmentioning

confidence: 99%

A Finite Population Model and Product-Form Approximation for Cellular Mobile Systems with Traveling Users

Ohtsuka

Shioda

Machihara³

2007

IEEE GLOBECOM 2007-2007 IEEE Global Telecommunications Conference

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We propose a new finite population model for cellular mobile systems with traveling users. In this model, mobile users arrive according to a Poisson process from outside the system, independently travel in the system, and leave the system in due time. A mobile user is either in call (active) or out of call (inactive). We find that if two minor modifications are made to the model, the joint distribution of the number of calls in progress in each cell has the product form. Making the two modifications is referred to as product-form approximation in this paper. Under the product-form approximation, the probability that channels are fully occupied in a cell is given by the Erlangloss formula. We evaluate the accuracy of the product-form approximation through several simulation experiments, and find that the Erlang-loss formula remains applicable to the performance evaluation and channel provisioning of cellular mobile systems.Keywords: Telecommunication, mathematical modeling, cellular mobile systems, Erlang-loss formula, insensitivity IntroductionInvestigating the performance characteristics of cellular mobile networks has been the focus of considerable research reported in literature. The performance of cellular mobile systems is often described in terms of the probability of call blocking or that of hand-off blocking. Thus, it is crucial to find a simple method to evaluate these performance indices in order to design cellular mobile networks.In traditional wired telephone networks, the Erlang-loss formula has been used to evaluate the call blocking probability. The Erlang-loss formula holds when new calls are generated according to a Poisson process. In wired telephone networks, calls are generated by users, the number of which is much larger than the number of available channels, and thus the call arrival rate does not depend on the number of calls in progress. Under such infinite population models, the use of the Poisson-arrival assumption is appropriate. However, the infinite population model may not be applicable to cellular mobile systems because the number of mobile users (mobile units) in a small cell cannot be regarded as "infinite" compared with that of available channels. In this sense, the finite population model would suite cellular mobile systems. Note that, due to user mobility, the number of mobile users within a cell should fluctuate over time. Most existing formulas based on finite population models like the Engset formula, however, do not take the fluctuation of the population over time into account.Recently, Machihara proposed a finite population model for cellular mobile systems [7]. In Machihara's model, mobile users arrive according to a Poisson process from outside the system, travel independently within the system, and leave the system in due time. He found that, in this model with a certain modification, the call blocking or hand-off blocking probability is given by the Erlang-loss formula. In addition, he showed that an insensitive property holds; the stationary

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A model for teletraffic performance and channel holding time characterization in wireless cellular communication with general session and dwell time distributions

Cited by 173 publications

References 10 publications

A Coxian model for channel holding time distribution for teletraffic mobility modeling

A Coxian model for channel holding time distribution for teletraffic mobility modeling

Call admission control schemes and performance analysis in wireless mobile networks

A Finite Population Model and Product-Form Approximation for Cellular Mobile Systems with Traveling Users

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