Traffic evaluation is very important for wireless network planning. We should provide enough resources (channels) for conveying the traffic load. Next generation wireless networks are all based on IP. In this path, voice is also handled as VoIP. In this paper considering Eb/No, data rates, source activity factor and other cells interferences in a multi-user system, we first calculate the number of subscribers in a cell, then based on the Markov Model we introduce a queuing model with capacity K and m servers (K>m) suitable for Internet user handling, then we pay attention to traffic calculations for that users and introduce an approach to the IP traffic planning.

background

Queueing Systems - Vol. 1: Theory

An Approach to Mobile IP Traffic Planning

A mean value analysis of the Ethernet throughput

It is frequently the case in communications systems that transmission facilities are shared among a number of different sources. In Chapter 5, for example, time-division multiplexing is used to distribute transmission capacity among the sources sharing the same line. The allocation of resources in this case is fixed and is therefore unresponsive to the instantaneous needs of users. In this and in subsequent chapters we shall be examining techniques for sharing resources that respond to variations in instantaneous traffic levels. In this chapter sharing will be effected by granting priority to one class of users over another. As we shall see presently, this mechanism does not necessarily mean inequitable service.

Intermittently Available Server, Priority Queues

Most of the real queuing systems include special properties and constraints, which can not be analyzed directly by using the results of solved classical queuing models. Lack of Markov chains features, unexponential patterns and service constraints, are the mentioned conditions. This paper represents an applied general algorithm for analysis and optimizing the queuing systems. The algorithm stages are described through a real case study. It is consisted of an almost completed non-Markov system with limited number of customers and capacities as well as lots of common exception of real queuing networks. Simulation is used for optimizing this system. So introduced stages over the following article include primary modeling, determining queuing system kinds, index defining, statistical analysis and goodness of fit test, validation of model and optimizing methods of system with simulation. Keywords—Estimation, queuing system, simulation model, probability distribution, non-Markov chain

methods

/pdf/a-new-heuristic-statistical-methodology-for-optimizing-1gfbx1znqs.pdf

A New Heuristic Statistical Methodology for Optimizing Queuing Networks Using Discreet Event Simulation

/pdf/performance-evaluation-of-qos-1p7hc13f4n.pdf

Queueing Systems - Vol. 1: Theory

Citations

An Approach to Mobile IP Traffic Planning

A mean value analysis of the Ethernet throughput

Intermittently Available Server, Priority Queues

A New Heuristic Statistical Methodology for Optimizing Queuing Networks Using Discreet Event Simulation

Performance evaluation of qos

Related Papers (5)

Theory, Volume 1, Queueing Systems

Queueing systems, Vol. I: Theory

Fundamentals of queueing theory

Introduction to matrix analytic methods in stochastic modeling

Queueing Systems, Vol. II: Computer Applications.