Skip to main content

Monotone Games for Cognitive Radio Systems

  • Chapter
Distributed Decision Making and Control

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 417))

Abstract

Noncooperative game theory is a branch of game theory for the resolution of conflicts among interacting decision makers (called players), each behaving selfishly to optimize his own well-being. In this chapter, we present a mathematical treatment of (generalized) Nash equilibrium problems based on the variational inequality and complementarity approach, covering the topics of existence and uniqueness of an equilibrium, and the design of distributed algorithms using best-response iterations along with their convergence properties.We then apply the developed machinery to the distributed design of cognitive radio systems. The proposed equilibrium models and resulting algorithms differ in performance of the secondary users, level of protection of the primary users, computational effort and signaling among primary and secondary users, convergence analysis, and convergence speed; which makes them suitable for many different CR systems.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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. Altman, E., Boulogne, T., Azouzi, R.E., Jimenez, T., Wynter, L.: A survey on networking games. Computers and Operations Research 33, 286–311 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  2. Aubin, J.P.: Mathematical Method for Game and Economic Theory. Dover Publications (2007)

    Google Scholar 

  3. Bapat, R.B., Raghavan, T.E.S.: Nonnegative Matrices and Applications. Cambridge University Press (1997)

    Google Scholar 

  4. Berman, A., Plemmons, R.J.: Nonnegative Matrices in the Mathematical Sciences. Society for Industrial Mathematics, SIAM (1987)

    Google Scholar 

  5. Bertsekas, D.P., Tsitsiklis, J.N.: Parallel and Distributed Computation: Numerical Methods, 2nd edn. Athena Scientific Press, Belmont (1989)

    MATH  Google Scholar 

  6. Cendrillon, R., Huang, J., Chiang, M., Moonen, M.: Autonomous spectrum balancing for digital subscriber lines. IEEE Trans. Signal Processing 55(8), 4241–4257 (2007)

    Article  MathSciNet  Google Scholar 

  7. Cottle, R.W., Pang, J.S., Stone, R.E.: The Linear Complementarity Problem. Academic Press, San Diego (1992)

    MATH  Google Scholar 

  8. Etkin, R., Parekh, A., Tse, D.: Spectrum sharing for unlicensed bands. IEEE J. Selected Areas in Communications 25(3), 517–528 (2007)

    Article  Google Scholar 

  9. Facchinei, F., Fischer, A., Piccialli, V.: On generalized Nash games and variational inequalities. Operations Research Letters 35, 159–164 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  10. Facchinei, F., Kanzow, C.: Generalized Nash equilibrium problems. A Quarterly Journal of Operations Research (4OR) 5(3), 173–210 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  11. Facchinei, F., Pang, J.S.: Finite-Dimensional Variational Inequalities and Complementarity Problem. Springer, New York (2003)

    Google Scholar 

  12. Facchinei, F., Sagratella, S.: On the computation of all solutions of jointly convex generalized Nash equilibrium problems. Optimization Letters 4(3) (2010)

    Google Scholar 

  13. Facchinei, F., Pang, J.S.: Nash equilibria: The variational approach. In: Palomar, D.P., Eldar, Y.C. (eds.) Convex Optimization in Signal Processing and Communications, ch. 12, pp. 443–493. Cambridge University Press, London (2009)

    Google Scholar 

  14. Goldsmith, A., Jafar, S.A., Maric, I., Srinivasa, S.: Breaking spectrum gridlock with cognitive radios: An information theoretic perspective. Proc. IEEE 97(5), 894–914 (2009)

    Article  Google Scholar 

  15. Haykin, S.: Cognitive radio: Brain-empowered wireless communications. IEEE J. Selected Areas in Communications 23(2), 201–220 (2005)

    Article  Google Scholar 

  16. Hong, M., Garcia, A.: Dynamic pricing of interference in cognitive radio networks. IEEE Trans. Signal Processing (2010) (submitted)

    Google Scholar 

  17. Huang, J., Palomar, D.P., Mandayam, N., Walrand, J., Wicker, S.B., Basar, T.: Special Issue on Game Theory in Communication Systems. IEEE J. Selected Areas in Communications 26(7) (2008)

    Google Scholar 

  18. Jorswieck, E.A., Larsson, E.G., Luise, M., Poor, H.V.: Special Issue on Game Theory in Signal Proc. and Comm. IEEE Signal Processing Magazine 26(5) (2009)

    Google Scholar 

  19. Konnov, I.V.: Equilibrium Models and Variational Inequalities. Elsevier B.V., Amsterdam (2007)

    MATH  Google Scholar 

  20. Luo, Z.Q., Pang, J.S.: Analysis of iterative waterfilling algorithm for multiuser power control in digital subscriber lines. EURASIP J. Applied Signal Processing 2006, 1–10 (2006)

    Article  Google Scholar 

  21. Mitola, J.: Cognitive radio for flexible mobile multimedia communication. In: Proc. IEEE 1999 Int. Workshop on Mobile Multimedia Communications (MoMuC 1999), San Diego, CA, pp. 3–10 (1999)

    Google Scholar 

  22. Nash, J.: Equilibrium points in n-person game. National Academy of Science 36, 48–49 (1950)

    Article  MathSciNet  MATH  Google Scholar 

  23. Olfati-Saber, R., Fax, J.A., Murray, R.M.: Consensus and cooperation in networked multi- agent systems. Proc. IEEE 95(1), 215–223 (2007)

    Article  Google Scholar 

  24. Ortega, J.M., Rheinboldt, W.C.: Iterative Solution of Nonlinear Equations in Several Variables. Society for Industrial Mathematics (SIAM), Philadelphia (1987)

    Google Scholar 

  25. Pang, J.S., Chan, D.: Iterative methods for variational and complementarity problems. Mathematical Programming 24(1), 284–313 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  26. Pang, J.S., Scutari, G., Palomar, D.P., Facchinei, F.: Design of cognitive radio systems under temperature-interference constraints: A variational inequality approach. IEEE Trans. Signal Processing 58(6), 3251–3271 (2010)

    Article  MathSciNet  Google Scholar 

  27. Pang, J.S.: Asymmetric variational inequality problems over product sets: Applications and iterative methods. Mathematical Programming 31(2), 206–219 (1985)

    Article  MathSciNet  MATH  Google Scholar 

  28. Pang, J.S., Scutari, G., Facchinei, F., Wang, C.: Distributed power allocation with rate constraints in Gaussian parallel interference channels. IEEE Trans. Information Theory 54(8), 3471–3489 (2008)

    Article  MathSciNet  Google Scholar 

  29. Rosen, J.: Existence and uniqueness of equilibrium points for concave n-person games. Econometrica 33(3), 520–534 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  30. Scutari, G., Barbarossa, S., Pescosolido, L.: Distributed decision through self-synchronizing sensor networks in the presence of propagation delays and asymmetric channels. IEEE Trans. Signal Processing 56(4), 1667–1684 (2008)

    Article  MathSciNet  Google Scholar 

  31. Scutari, G., Palomar, D.P.: MIMO cognitive radio: A game theoretical approach. IEEE Trans. Signal Processing 58(2), 761–780 (2010)

    Article  MathSciNet  Google Scholar 

  32. Scutari, G., Palomar, D.P., Barbarossa, S.: Asynchronous iterative water-filling for Gaussian frequency-selective interference channels. IEEE Trans. Information Theory 54(7), 2868–2878 (2008)

    Article  MathSciNet  Google Scholar 

  33. Scutari, G., Palomar, D.P., Barbarossa, S.: Competitive design of multiuser MIMO systems based on game theory: A unified view. IEEE J. Selected Areas in Communications 26(7), 1089–1103 (2008)

    Article  MathSciNet  Google Scholar 

  34. Scutari, G., Palomar, D.P., Barbarossa, S.: Optimal linear precoding strategies for wideband noncooperative systems based on game theory—Part I & II: Nash equilibria & Algorithms. IEEE Trans. Signal Processing 56(3), 1230–1249 & 1250–1267 (2008)

    Google Scholar 

  35. Scutari, G., Palomar, D.P., Barbarossa, S.: Competitive optimization of cognitive radio MIMO systems via game theory. In: Palomar, D.P., Eldar, Y.C. (eds.) Convex Optimization in Signal Processing and Communications, ch. 11, pp. 387–442. Cambridge University Press, London (2009)

    Google Scholar 

  36. Scutari, G., Palomar, D.P., Barbarossa, S.: The MIMO iterative waterfilling algorithm. IEEE Trans. Signal Processing 57(5), 1917–1935 (2009)

    Article  Google Scholar 

  37. Scutari, G., Palomar, D.P., Facchinei, F., Pang, J.S.: Convex optimization, game theory, and variational inequality theory in multiuser communication systems. IEEE Signal Processing Magazine 27(4), 35–49 (2010)

    Article  Google Scholar 

  38. Scutari, G., Facchinei, F., Pang, J.S., Palomar, D.P.: Monotone communication games: Theory, algorithms, and models. IEEE Trans. Information Theory (2010) (submitted)

    Google Scholar 

  39. Yin, H., Shanbhag, U.V., Mehta, P.G.: Nash equilibrium problems with congestion costs and shared constraints. IEEE Trans. Automatic Control 56(7), 1702–1708 (2010)

    Article  Google Scholar 

  40. Yu, W., Ginis, G., Cioffi, J.M.: Distributed multiuser power control for digital subscriber lines. IEEE J. Selected Areas in Communications 20(5), 1105–1115 (2002)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer London

About this chapter

Cite this chapter

Scutari, G., Palomar, D.P., Facchinei, F., Pang, JS. (2012). Monotone Games for Cognitive Radio Systems. In: Johansson, R., Rantzer, A. (eds) Distributed Decision Making and Control. Lecture Notes in Control and Information Sciences, vol 417. Springer, London. https://doi.org/10.1007/978-1-4471-2265-4_4

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-2265-4_4

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-2264-7

  • Online ISBN: 978-1-4471-2265-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics