Skip to main content

A Relevant Equilibrium in Open Spectrum Sharing: Lorenz Equilibrium in Discrete Games

  • Conference paper
Internet of Things, Smart Spaces, and Next Generation Networks and Systems (NEW2AN 2014)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 8638))

Included in the following conference series:

Abstract

A new game theoretical solution concept for open spectrum sharing in cognitive radio (CR) environments is highlighted – the Lorenz equilibrium (LE). Both Nash and Pareto solution concepts have limitations when applied to real world problems. Nash equilibrium (NE) rarely ensures maximal payoff and it is frequently Pareto inefficient. The Pareto set is usually a large set of solutions, often too hard to process. The Lorenz equilibrium is a subset of Pareto efficient solutions that are equitable for all players and ensures a higher payoff than the Nash equilibrium. LE induces a selection criterion of NE, when several are present in a game (e.g. many-player discrete games) and when fairness is an issue. Besides being an effective NE selection criterion, the LE is an interesting game theoretical situation per se, useful for CR interaction analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Nagy, R., Suciu, M., Dumitrescu, D.: Lorenz Equilibrium: Evolutionary Detection. In: GECCO 2012, pp. 489–496 (2012)

    Google Scholar 

  2. Fudenberg, D., Tirole, J.: Multiple Nash Equilibria, Focal Points, and Pareto Optimality. In: Game Theory. MIT Press (1983)

    Google Scholar 

  3. Akyildiz, I., Lee, W., Vuran, M., Mohanty, S.: NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey. Computer Networks: Int. J. of Comput. Telecomm. Netw. 50(13), 2127–2159 (2006)

    Article  MATH  Google Scholar 

  4. Wang, B., Wu, Y., Liu, K.J.R.: Game theory for cognitive radio networks: An overview. Computer Networks, Int. J. of Omput. Telecomm. Netw. 54(14), 2537–2561 (2010)

    MATH  Google Scholar 

  5. Osborne, M.J.: An Introduction to Game Theory, Oxford, U.P.(2004)

    Google Scholar 

  6. Neel, J.O.: Analysis and Design of Cognitive Radio Networks and Distributed Radio Resource Management Algorithms. PhD Thesis (2006)

    Google Scholar 

  7. MacKenzie, A., Wicker, S.: Game Theory in Communications: Motivation, Explanation, and Application to Power Control. In: GLOBECOM 2001, pp. 821–825 (2001)

    Google Scholar 

  8. Huang, J.W., Krishnamurthy, V.: Game Theoretic Issues in Cognitive Radio Systems. J. of Comm. 4(10), 790–802 (2009)

    Google Scholar 

  9. Niyato, D., Hossain, E.: Microeconomic models for dynamic spectrum management in cognitive radio networks. In: Hossain, E., Bhargava, V.K. (eds.) Cognitive Wireless Communication Networks, pp. 391–423. Springer, NY (2007)

    Chapter  Google Scholar 

  10. Cordeiro, C., Challapali, K., Birru, D.: IEEE 802.22: An Introduction to the first wireless standard based on cognitive radios. J. of Comm. 1(1), 38–47 (2006)

    Article  Google Scholar 

  11. da Costa, G.W.O., Cattoni, A.F., Kovacs, I.Z., Mogensen, P.E.: A scalable spectrum-sharing mechanism for local area network deployment. IEEE T. Veh. Technol. 59(4) (May 2010)

    Google Scholar 

  12. Nie, N., Comaniciu, C.: Adaptive channel allocation spectrum etiquette for cognitive radio networks. Mobile Netw. App. 11(6), 779–797 (2006)

    Article  Google Scholar 

  13. Cremene, L.C., Dumitrescu, D., Nagy, R., Cremene, M.: Game theoretic modelling for dynamic spectrum access in TV whitespace. In: CROWNCOM 2011, Osaka, pp. 336–340 (2011)

    Google Scholar 

  14. Kostreva, M.M., Ogryczak, W.: Linear Optimiation with multiple equitable criteria. RAIRO Op. Research 33, 275–297 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  15. Dumitrescu, D., Lung, R.I., Mihoc, T.D.: Generative relations for evolutionary equilibria detection. In: GECCO 2009, pp. 1507–1512 (2009)

    Google Scholar 

  16. Lung, R.I., Dumitrescu, D.: Computing Nash Equilibria by Means of Evolutionary Computation. IJCCC 3, 364–368 (2008)

    Google Scholar 

  17. Cremene, L.C., Dumitrescu, D., Nagy, R., Gasko, N.: Cognitive Radio Simultaneous Spectrum Access/ One-shot Game Modelling. In: IEEE, IET CSNDSP 2012, Poznan, pp. 1–6 (2012)

    Google Scholar 

  18. Storn, R., Price, K.: Differential evolution – simple and efficient heuristic for global optimization over continuous spaces. J. of Global Optimization 11, 341–359 (1997)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Cremene, L.C., Dumitrescu, D. (2014). A Relevant Equilibrium in Open Spectrum Sharing: Lorenz Equilibrium in Discrete Games. In: Balandin, S., Andreev, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN 2014. Lecture Notes in Computer Science, vol 8638. Springer, Cham. https://doi.org/10.1007/978-3-319-10353-2_31

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-10353-2_31

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10352-5

  • Online ISBN: 978-3-319-10353-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics