http://iet.metastore.ingenta.com
1887

Adaptive online power control scheme based on the evolutionary game theory

Adaptive online power control scheme based on the evolutionary game theory

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Communications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

In view of the remarkable growth in the number of users and the limited network resource, an efficient network management is very important and has been an active area of research over the years. Especially, during wireless network operations, adaptive power control is an effective way to enhance the network performance. In this study, a new online power control scheme is proposed based on the evolutionary game theory. To converge a desirable network equilibrium, the proposed scheme adaptively adjusts a transmit power level in a distributed online manner. For the efficient network management, the online approach is dynamic and flexible that can adaptively respond to current network conditions. With a simulation study, the author demonstrates that the proposed scheme improves the network performance under widely diverse network environments.

References

    1. 1)
      • S. Kim , P.K. Varshney . An integrated adaptive bandwidth management framework for QoS sensitive multimedia cellular networks. IEEE Trans. Veh. Technol. , 835 - 846
    2. 2)
      • F. Meshkati , H.V. Poor , S.C. Schwartz , R.V. Balan . Energy-efficient power and rate control with QoS constraints: a game-theoretic approach’. IWCMC , 1435 - 1440
    3. 3)
      • N. Feng , S.-C. Mau , N.B. Mandayam . Pricing and power control for joint network-centric and user-centric radio resource management. IEEE Trans. Commun. , 9 , 1547 - 1557
    4. 4)
      • Holliday, T., Goldsmith, A.J., Glynn, P., Bambos, N.: `Distributed power and admission control for time varying wireless networks', IEEE GLOBECOM, December 2004, p. 768–774.
    5. 5)
      • Leino, J.: `Applications of game theory in ad hoc networks', 2003, Master's, Helisnki University of Technology.
    6. 6)
      • Dirani, M., Chahed, T.: `Framework for resource allocation in heterogeneous wireless networks using game theory', EuroNGI Workshop, 2006, p. 144–154.
    7. 7)
      • V. Srivastava . Using game theory to analyze wireless ad hoc networks. IEEE Commun. Sur. Tutorials , 4 , 46 - 56
    8. 8)
      • Y. Xiao , X. Shan , Y. Ren . Game theory models for IEEE 802.11 DCF in wireless ad hoc networks. IEEE Commun. Mag. , 3 , 22 - 26
    9. 9)
      • J. Hofbauer , K. Sigmund . Evolutionary game dynamics. J. Bull. Am. Math , 479 - 519
    10. 10)
      • Y. Tao , Z. Wang . Effect of time delay and evolutionarily stable strategy. J. Theor. Biol. , 111 - 116
    11. 11)
      • D.S. Menasche , D.R. Figueiredo , E. de Souzae Silva . An evolutionary game-theoretic approach to congestion control. Perform. Eval. , 295 - 312
    12. 12)
      • Ginde, S., Neel, J., Buehrer, R.M.: `A game-theoretic analysis of joint link adaptation and distributed power control in GPRS', IEEE Vehicular Technology Conf., October 2003, p. 732–736.
    13. 13)
      • C. Long , Q. Zhang , B. Li , H. Yang , X. Guan . Non-cooperative power control for wireless ad hoc networks with repeated games. IEEE J. Select. Areas Commun. , 6 , 1101 - 1112
    14. 14)
      • Kim, S.: `Online energy efficient routing approach for QoS-sensitive wireless sensor networks', IEEE Int. Conf. on Information Networking (ICOIN 2009), January 2009, p. 1–3.
    15. 15)
      • A. Rogers , E. David , N.R. Jennings . Self-organized routing for wireless microsensor networks. IEEE Trans. Syst., Man Cybernet. , 3 , 349 - 359
    16. 16)
      • Yang, C.-G., Li, J.-D., Li, W.-Y.: `Joint rate and power control based on game theory in cognitive radio networks', Fourth Int. Conf. on Communications and Networking, 2009, p. 1–5.
    17. 17)
      • Liu, Y., Peng, Q.-C., Shao, H.-Z., Chen, X.-F., Wang, L.: `Power control algorithm based on game theory in cognitive radio networks', Int. Conf. on Apperceiving Computing and Intelligence Analysis (ICACIA), 2010, p. 164–168.
    18. 18)
      • A. Zappone , S. Buzzi , E. Jorswieck . Energy-efficient power control and receiver design in relay-assisted DS/CDMA wireless networks via game theory. IEEE Commun. Lett. , 1 - 3
    19. 19)
      • Zhanjun, L., Chengchao, L., Yun, C., Huan, D., Cong, R.: `An interference avoidance power control algorithm based on game theory', Second Pacific-Asia Conf. on Circuits, Communications and System (PACCS), 2010, p. 414–416.
    20. 20)
      • Hou, Y., Wang, Y., Hu, B.: `Research on power control algorithm based on game theory in cognitive radio system', Int. Conf. on Signal Processing Systems (ICSPS), 2010, p. 614–618.
    21. 21)
      • C.K. Tan , M.L. Sim , T.C. Chuah . Fair power control for wireless ad hoc networks using game theory with pricing scheme. IET Commun. , 3 , 322 - 333
    22. 22)
      • Chenglin, Z., Yan, G.: `A novel distributed power control algorithm based on game theory', Int. Conf. on Wireless Communications, Networking and Mobile Computing, 2009, p. 1–4.
    23. 23)
      • Li, J., He, J., Zhang, Q., Huang, S.: `A game theory based WiMAX uplink power control algorithm', Int. Conf. on Wireless Communications, Networking and Mobile Computing (WiCom'09), 2009, p. 1–4.
    24. 24)
      • E. Altman , E.-A. Rachidh , Y. Hayel , H. Tembine . An evolutionary game approach for the design of congestion control protocols in wireless networks’. Physicomnet workshop , 1 - 6
    25. 25)
      • Byde, A.: `Applying evolutionary game theory to auction mechanism design', IEEE Int. Conf. on E-Commerce, June 2003, p. 347–354.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-com.2011.0093
Loading

Related content

content/journals/10.1049/iet-com.2011.0093
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address