Repository logo

Queueing models for capacity changes in cellular networks

dc.contributor.advisorSrinivasan, Rajen_US
dc.contributor.committeeMemberMartin, Johnen_US
dc.contributor.committeeMemberBickis, Miken_US
dc.contributor.committeeMemberSoteros, Chrisen_US
dc.contributor.committeeMemberSparks, Gordon A.en_US
dc.contributor.committeeMemberHlynka, Myronen_US
dc.creatorYan, Qingxiangen_US 2013en_US
dc.description.abstractWith the rapid development of cellular communication techniques, many recent studies have focused on improving the quality of service (QoS) in cellular networks. One characteristic of the systems in cellular networks, which can have direct impact on the system QoS, is the fluctuation of the system capacity. In this thesis, the QoS of systems with capacity fluctuations is studied from two perspectives: (1) priority queueing systems with preemption, and (2) the M/M/~C/~C system. In the first part, we propose two models with controlled preemption and analyze their performance in the context of a single reference cell that supports two kinds of traffic (new calls and handoff calls). The formulae for calculating the performance measures of interest (i.e., handoff call blocking probability, new call blocking and dropping probabilities) are developed, and the procedures for solving optimization problems for the optimal number of channels required for each proposed model are established. The proposed controlled preemption models are then compared to existing non-preemption and full preemption models from the following three perspectives: (i) channel utilization, (ii) low priority call (i.e., new calls) performance, and (iii) flexibility to meet various constraints. The results showed that the proposed controlled preemption models are the best models overall. In the second part, the loss system with stochastic capacity, denoted by M/M/~C/~C, is analyzed using the Markov regenerative process (MRGP) method. Three different distributions of capacity interchange times (exponential, gamma, and Pareto) and three different capacity variation patterns (skip-free, distance-based, and uniform-based) are considered. Analytic expressions are derived to calculate call blocking and dropping probabilities and are verified by call level simulations. Finally, numerical examples are provided to determine the impact of different distributions of capacity interchange times and different capacity variation patterns on system performance.en_US
dc.subjectcellular networks, stochastic capacity, M/M/C/C, QoS, preemptive queue, MRGPen_US
dc.titleQueueing models for capacity changes in cellular networksen_US
dc.type.materialtexten_US and Statisticsen_US of Saskatchewanen_US of Philosophy (Ph.D.)en_US


Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
2.77 MB
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
1006 B
Plain Text