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UBC Theses and Dissertations

Channel resource managemant strategies for low earth orbit mobile satellite systems Wang, Zhipeng


Low Earth Orbit Mobile Satellite Systems (LEO-MSS) are promising solutions for global-coverage mobile communications systems, which are expected to provide users with advanced telecommunication services, including multi-party and multimedia services, anytime and anywhere. For these systems, one of the major difficulties in providing such advanced telecommunication services on a global scale is efficient channel resource management. The very high speed of LEO satellites and their relatively small spotbeams make channel resource management for LEO-MSS a very challenging technical issue. With this problem as our main motivation, we propose several novel and efficient resource management strategies in this thesis and provide a combined analytical and computer simulation framework through which the performance and limitations of conventional and newly proposed resource management strategies can be better understood and evaluated. First, we develop a more accurate analytical method to evaluate Fixed Channel Reservation (FCR) with First Input First Output Queuing of Handover requests (FIFO-QH). In order to improve the performance of FCR, we propose an efficient Traffic-Dependent Dynamic Channel Reservation (TDDCR) scheme that exploits the high-speed deterministic movement property of LEO satellites and reserves channels according to the estimated number of handover requests and the positions of the Mobile Terminals (MTs). Second, motivated by the fact that the exact analysis of Dynamic Channel Allocation (DCA) with FIFO-QH is highly complex due to the dynamic nature of channel allocation to different cells, we develop an approximate but accurate analytical method to evaluate the performance of DCA in conjunction with FIFO-QH in LEO-MSS. Based on our previous study of DCA, we optimize channel reservations through both handover estimation and DCA and propose a novel Traffic-Dependent Dynamic Channel Allocation and Reservation (TDDCAR) technique that improves the efficiency of channel reservation and the handover performance of DCA. Third, we develop an analytical method for evaluating the performance of channel resource management strategies for LEO-MSS supporting multi-party traffic. To improve the overall performance, we propose and analyze the performance of an efficient Adaptive Channel Reservation (ACR) scheme that allows priority to be given to handover requests generated by multi-party traffic. When ACR is used in conjunction with a New Call Queuing (NCQ) policy, extremely low blocking and handover failure probabilities can be achieved for multi-party traffic. Finally, we generalize our research to include multi-class traffic in LEO-MSS. We develop an analytical methodology to evaluate the performance of two channel resource partitioning schemes, namely Complete Partitioning (CP) and Complete Sharing (CS), with and without FCR. Using multi-dimensional Markov chain techniques, we solve the analytical models and derive explicit expressions for Quality of Service (QoS) parameters such as call blocking and dropping probabilities. In addition, we introduce a more efficient Threshold Call Admission (TCA) scheme. This scheme ensures fair access to channel resources by setting proper call admission thresholds for incoming traffic and achieves better efficiency of channel utilization with its multiplexing gain.

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