Switching cost minimization in the IEEE 802.16e mobile WiMAX sleep mode operation

ABSTRACT

To prolong the battery lifetime, it is important to continue designing a better energy efficient mechanism for different mobile technologies. Most of the existing works on the IEEE 802.16e sleep mode operation focus on the decision making before a mobile station switching to sleep mode state. The correlation of the decision is mainly on when and how to sleep based on the traffic demands. After the mobile station is switched to sleep mode, the deactivation of it mainly depends on new incoming traffic regardless of the actual amount. Truly, frequent switching can increase the energy cost on the mobile station, which can significantly reduce the battery lifetime. To minimize the switching frequency, we propose a novel approach to resolve this issue by making a heuristic decision during the listening interval. With this aim, we propose a real-time heuristic algorithm, WAKSLP_DECISION, to accommodate our target. Three main decision criteria are analyzed and designed, namely the probability of buffer overflow, expected delay violation, and battery lifetime expiry, to achieve our goal. We verify the energy consumption performance with simulation experiments to validate our proposed scheme. The result shows that our scheme performs 25% to 30% better compared with the original standard in terms of energy consumption. We believe this algorithm is practical and implementable without changing the original standard, which can contribute both in the research community and industrial development.

REFERENCES

• 1: IEEE 802.16-2004, "Part 16: Air Interface for Fixed Broadband Wireless Access Systems, Standard for Local and Metropolitan Area Networks", Octorber 2004.
• 2: IEEE 802.16e-2006, "Part 16: Air Interface for Fixed and Mobile Broadband Wireless Access Systems-Amendment for Physical and Medium Access Control Layers for Combined Fixed and Mobile Operation in Licensed Bands", February 2006.
• 3: Yang Xiao, "Energy Saving Mechanism in the IEEE 802.16e Wireless MAN", IEEE Communication Letters, vol. 9, no. 7, pp. 595--597, July, 2005.
• 4: Yang Xiao, "Performance Analysis of an Energy Saving Mechanism in the IEEE 802.16e Wireless MAN", Proceedings of IEEE CCNC 2006, Janurary, 2006.
• 5: Lei Kong and Danny H. K. Tsang, "Performance Study of Power Saving Classes of Type I and II in IEEE 802.16e", Proc. of of the 31st IEEE Conference on Local Computer Networks, Tampa, Florida, US, November. 2006.
• 6: Lei Kong and Danny H. K. Tsang, "Optimal Selection of Power Saving Classes in IEEE 802.16e", Proc. of IEEE Wireless Communications and Networking Conference (WCNC 2007), Hong Kong, March, 2006.
• 7: Yin Ge and G. S. Kuo, textquotedblleft An Efficient Sleep Mode Management Scheme in IEEE 802.16e Networks," in Proc of IEEE ICC'07, Glasgow, Scotland, 2007.
• 8: M. Kim, M. Kang, and J. Choi, "Remaining Energy-Aware Power Management Mechanism in the 802.16e MAC," in Proc. IEEE CCNC 2008.
• 9: Henk C. Tijms, A First course in Stochastic Models, John Wiley and Sons, Inc., New York, 2003.
• 10: "Matlab," http://www.mathworks.com/
• 11: Sequans Communications, "Datasheet: SQN1130 System-on-Chip (SOC) for WiMAX Mobile Stations"

INDEX TERMS

Primary Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.1 Network Architecture and Design
          Subjects: Network communications

Additional Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.1 Network Architecture and Design
          Subjects: Wireless communication; Distributed networks

General Terms:
Algorithms, Design, Performance

Keywords:
802.16e, energy-efficiency wireless, power management, sleep mode