Advertisement

Wireless Networks

, Volume 17, Issue 1, pp 199–212 | Cite as

Selfish users in energy constrained ALOHA systems with power capture

  • Johan Hultell
  • Ömer Ileri
  • Jens Zander
Article

Abstract

We consider a slotted ALOHA setting where backlogged, energy-constrained users selfishly select the probability with which they transmit packets. Packets are successfully received, even in case of collision, if the signal to interference plus noise ratio at the access point exceeds some threshold (power capture). The user problem of finding appropriate transmission probabilities is formulated as a static non-cooperative game and the performance limits for stationary and mobile scenarios are determined. The equilibrium analyses show that for stationary scenarios, users with high pathgains share the channel fairly while others never transmit. In the mobile case users utilize a binary strategy where they try to monopolize the channel when their pathgain exceeds some threshold that depends on system parameters (number of users, transmission costs, etc.). Otherwise they shut their transmitters off. Compared to traditional nondiscriminatory distributed multiaccess protocols the operating points achieved by selfish users generally increase sum-utility although this comes at the expense of larger user performance variations.

Keywords

ALOHA systems Non-cooperative games Power capture 

References

  1. 1.
    Mitola, J., & Maguire, G. Q. Jr. (1999). Cognitive radio: Making software radios more personal. IEEE Personal Communications, 6(4), 13–18.CrossRefGoogle Scholar
  2. 2.
    Saraydar, C. U., Mandayam, N. B., & Goodman, D. J. (2001). Pricing and power control in multi-cell wireless data networks. IEEE Journal on Selected Areas in Communications, 19(10), 1883–1892.CrossRefGoogle Scholar
  3. 3.
    Felegyhazi, M., Buttyn, L., & Hubaux J.-P. (2003). Equilibrium analysis of packet forwarding strategies in wireless ad hoc networks—the static case. Technical Report IC/2003/03, Laboratory of Computer Communications and Applications, Swiss Federal Institute of Technology, Lausanne.Google Scholar
  4. 4.
    Nie, N., & Comaniciu, C. (2006). Adaptive channel allocation spectrum etiquette for cognitive radio networks. Mobile networks and applications, 100, 779–797.CrossRefGoogle Scholar
  5. 5.
    Levorato, M., Casari, P., & Zorzi, M. (2006). On the performance of access strategies for MIMO ad hoc networks. In Proceedings of IEEE globecom.Google Scholar
  6. 6.
    Mathur, S., Sankar, L., & Mandayam, N. B. (2008). Coalitions in cooperative wireless networks. IEEE Journal on Selected Areas in Communications, 26(7), 1104–1115.CrossRefGoogle Scholar
  7. 7.
    MacKenzie, A. B., & Wicker, S. B. (2001). Selfish users in ALOHA: A game-theoretic approach. In Proceedings of the 54th vehicular technology conference (Vol. 3, pp. 1354–1357). Atlantic City, USA, October 2001.Google Scholar
  8. 8.
    Inaltekin, H., & Wicker, S. (2005). A one-shot random access game for wireless networks. In Proceedings of the international conference on wireless networks, communication and mobile computing (Vol. 2, pp. 940–945).Google Scholar
  9. 9.
    Inaltekin, H., & Wicker, S. (2006). The analysis of game theoretic MAC protocol for wireless networks. In Proceedings of the annual IEEE communication society on sensor and ad hoc communications and networks (Vol. 1, pp. 296–305).Google Scholar
  10. 10.
    Cagalj, M., Ganeriwal, S., Aad, I., & Hubaux, J.-P. (2005). On selfish behavior in CSMA/CA networks. In Proceedings of the 24th annual joint conference of the IEEE computer and communication societies (INFOCOM) (Vol. 4, pp. 2513–2524). Miami, USA, March 2005.Google Scholar
  11. 11.
    Cho, Y., Hwang, C. S., & Tobagi, F. A. (2008) Design of robust random access protocols for wireless networks using game theoretic models. IEEE INFOCOM. Phoenix, April 2008.Google Scholar
  12. 12.
    Sagaduyu, Y. E., & Ephremides, A. (2006). A game-theoretic look at throughput and stability in random access. In Proceedings of the military communications conference (MILCOM) (pp. 1–7).Google Scholar
  13. 13.
    MacKenzie, A. B., & Wicker, S. B. (2003). Stability of multipacket slotted ALOHA with selfish users and perfect information. In Proceedings of twenty-second annual joint conference of the IEEE computer and communication societies (INFOCOM) (Vol. 3, pp. 1580–1590).Google Scholar
  14. 14.
    Cho, Y., & Tobagi, F. A. (2008). Cooperative and non-cooperative aloha games with channel capture. In Proceedings of IEEE Globecom. December.Google Scholar
  15. 15.
    Krishnamurthy, V., & Ngo, M. H. (2005). A game theoratical approach for transmission strategies in slotted aloha networks with multi-packet reception. In IEEE international conference on acoustics, speech, and signal processing (ICASSP). Philadelphia, March 2005.Google Scholar
  16. 16.
    Ngo, M. H., & Krishnamurthy, V. (2007). Game theoretic cross-layer transmission policies in multipacket reception wireless networks. IEEE Transactions on Signal Processing, 55(5), 1911–1926 May 2007.CrossRefMathSciNetGoogle Scholar
  17. 17.
    Lee, H., Kwon, H., Motskin, A., & Guibas, L. (2009). Interference-aware MAC protocols for wireless networks by a game-theoretic approach. In Proceedings of the IEEE infocom. April 2009.Google Scholar
  18. 18.
    Fudenberg, D., & Tirole, J. (1991). Game theory. Cambridge: MIT Press.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Wireless@KTH, Royal Institute of TechnologyKistaSweden

Personalised recommendations