A phase-type based Markov chain model for IEEE 802.16e sleep mode and its performance analysis

Authors:
Zhisheng Niu;Yanfeng Zhu;Vilius Benetis
Affiliations:
Department of Electronic Engineering, Tsinghua University Beijing P.R. China;Department of Electronic Engineering, Tsinghua University Beijing P.R. China;Research Center COM Technical University of Denmark
Venue:
ITC20'07 Proceedings of the 20th international teletraffic conference on Managing traffic performance in converged networks
Year:
2007

Citing 0
Cited 6

Modeling and analysis of the type I power saving class in IEEE 802.16 with general traffic

Proceedings of the 4th Annual International Conference on Wireless Internet
The power saving mechanism with binary exponential traffic indications in the IEEE 802.16e/m

Queueing Systems: Theory and Applications
Performance evaluation for the power saving class type III with a sleep-delay in IEEE 802.16e

Proceedings of the 4th International Conference on Queueing Theory and Network Applications
An optimized energy saving mechanism in IEEE 802.16e Mobile WiMAX systems

Journal of High Speed Networks
Performance analysis and evaluation of an enhanced power saving class type III in IEEE 802.16 with self-similar traffic

Journal of Global Optimization
An Adaptive QoS Power Saving Scheme for Mobile WiMAX

Wireless Personal Communications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

To support battery powered mobile broadband wireless access devices efficiently, IEEE 802.16e defines a sleep mode operation for conserving the power of mobile terminals. In this paper we propose a theoretical Phase-type (PH) based Markov chain model to analyze the performance of IEEE 802.16e sleep mode operation. The model describes the behavior of the mobile stations working in sleep mode. In particular, the service process is designed as a discrete PH model. By means of the mathematic tools of PH theory we then derive the closed-form expressions of the mean sojourn time of packets and power consumption. Comparison with simulation results shows that the model provides an accurate prediction of the system performance. Furthermore, we propose a simple utility function to quantify the efficiency of sleep mode operation which takes the joint effect of sojourn time and power saving into account. This function allows mobile stations to decide when to enable sleep mode operation for power saving.