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This paper presents a generalized channel preemption model (GCPM) for multiclass traffic in mobile wireless networks. In the proposed model, a mobile call is identified by four parameters--call type, traffic class, channel requirement, and preemption ratioi--in which different classes of traffic can have different priority levels. To effectively reduce dropping probability, high-priority handoff calls are allowed to fully or partially preempt low-priority ongoing calls when the mobile network becomes congested. A fully preempted call can be completely disconnected, whereas a partially preempted call can still communicate with certain degree of quality-of-service degradation. We introduce an analytical model with multidimensional Markov chains. In the model, a cost function, which is expressed as a weighted sum of the ongoing calls to be preempted and the bandwidth reduction rate in the preempted calls, is defined to select candidate calls from a certain traffic class. The statistical result from the model allows us to tune the parameters of the GCPM to support high-priority handoff calls and therefore offers new insights in understanding the tradeoffs in supporting multiclass traffic. Index Terms--Channel preemption, handoff calls, Markov chains, mobile wireless networks.

In this paper, we construct mathematical models to analyze the probabilities of new call blocking and handoff call (HC) dropping for a sectorized cellular network with fractional frequency reuse (FFR). Because a sectorized FFR network (SFN) consists of two areas, the super group (SG) and the regular group (or sectors), three different types of HCs may happen when a mobile station (MS) moves from the SG to a sector, from a sector to the SG, or from one sector to another sector. To characterize three types of HCs, we first derive the area transition probability, which is defined as the reciprocal of MS's average residence time in an area (i.e., sector or SG). Moreover, we construct the model of Markov chains and derive the state transition rates. Then on the basis of the stationary probabilities of Markovian states, we derive the three types of blocking probabilities of new calls and two types of dropping probabilities of HCs. Finally, we conduct extensive numerical simulations. From the results of numerical simulations, we reveal two important rules for choosing the optimal radius of the SG, with which the system blocking and dropping probability can be effectively minimized. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]