A novel method for analysing the performance of power saving class of Type III in IEEE 802.16e is proposed, which is applicable to design, maintenance and management for mobile wireless metropolitan area network. Cons...A novel method for analysing the performance of power saving class of Type III in IEEE 802.16e is proposed, which is applicable to design, maintenance and management for mobile wireless metropolitan area network. Considering the memoryless nature of user initiated packet arrival, a Geom/G/1 queue model with multiple vacations and setup period is built to capture the principle for the power saving class of Type III. By using an embedded Markov chain method and the boundary state variable theory, we obtain the queueing measures such as queueing length, waiting time and busy cycle in steady state. Correspondingly, we derive explicitly the performance measures for the power saving class of Type III in terms of handover ratio, energy saving ratio, and average packet response time. Based on numerical results, we develop a cost function to determine numerically the optimal length of sleep window and the minimal cost with different offered loads.展开更多
基金Supported by the National Natural Science Foundation of China (No.10671170,60773100)the Natural Science Foundation of Hebei Province,China (No.2009000475)
文摘A novel method for analysing the performance of power saving class of Type III in IEEE 802.16e is proposed, which is applicable to design, maintenance and management for mobile wireless metropolitan area network. Considering the memoryless nature of user initiated packet arrival, a Geom/G/1 queue model with multiple vacations and setup period is built to capture the principle for the power saving class of Type III. By using an embedded Markov chain method and the boundary state variable theory, we obtain the queueing measures such as queueing length, waiting time and busy cycle in steady state. Correspondingly, we derive explicitly the performance measures for the power saving class of Type III in terms of handover ratio, energy saving ratio, and average packet response time. Based on numerical results, we develop a cost function to determine numerically the optimal length of sleep window and the minimal cost with different offered loads.
