Abstract
As an enhancement of IEEE 802.16e, IEEE 802.16m can save more energy. Considering the digital nature of the networks and regarding the initial sleep window as one half of the subsequent sleep window, in this chapter, we build a discrete-time queueing model with multiple heterogeneous vacations to analyze communication networks using the IEEE 802.16m protocol. We first describe the working principle of this system model, and then present an analytical approach to analyze the sleep mode in the steady state. By using a discrete-time embedded Markov chain, we derive performance measures of the system in terms of the average response time of data packets and the energy saving rate of the system, respectively. Finally, we present numerical results to investigate the influence of the sleep cycle and the arrival rate of data packets on the performance of the system using the sleep mode in IEEE 802.16m.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Baek, S., Choi, B.: Performance of an efficient sleep mode operation for IEEE 802.16m. J. Ind. Manag. Optim. 7(3), 623–639 (2011)
Hwang, E., Kim, K., Son, J., Choi, B.: The power saving mechanism with periodic traffic indications in the IEEE 802.16e/m. IEEE Trans. Veh. Technol. 59(1), 319–334 (2009)
IEEE Computer Society and the IEEE Microwave Theory and Techniques Society: IEEE Std 802.16m-2011, Part 16: Air Interface for Broadband Wireless Access Systems-Amendment 3 for Advanced Air Interface (2011)
Jin, S., Yue, W.: Performance analysis and evaluation for power saving class type III in IEEE 802.16e network. J. Ind. Manag. Optim. 6(3), 691–708 (2010)
Jin, S., Chen, X., Qiao, D., Choi, S.: Adaptive sleep mode management in IEEE 802.16m wireless metropolitan area networks. Computer Networks 55(16), 3774–3783 (2011)
Kong, L., Tsang, D.: Performance study of power saving classes of types I and II in IEEE 802.16e. In: Proceedings of the 31st IEEE Conference on Local Computer Networks, pp. 20–27 (2006)
Xue, J., Watada, J.: Short-term power load forecasting method by radial-basis-function neural network with support vector machine model. ICIC Express Lett. 5(5), 1523–1528 (2011)
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Jin, S., Yue, W. (2021). Bernoulli Arrival-Based Sleep Mode in WiMAX 2. In: Resource Management and Performance Analysis of Wireless Communication Networks. Springer, Singapore. https://doi.org/10.1007/978-981-15-7756-7_5
Download citation
DOI: https://doi.org/10.1007/978-981-15-7756-7_5
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-7755-0
Online ISBN: 978-981-15-7756-7
eBook Packages: Computer ScienceComputer Science (R0)