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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Altman, E., Boulogne, T., Azouzi, R.E., Jimenez, T., Wynter, L.: A survey on networking games. Computers and Operations Research 33, 286–311 (2006)
Aubin, J.P.: Mathematical Method for Game and Economic Theory. Dover Publications (2007)
Bapat, R.B., Raghavan, T.E.S.: Nonnegative Matrices and Applications. Cambridge University Press (1997)
Berman, A., Plemmons, R.J.: Nonnegative Matrices in the Mathematical Sciences. Society for Industrial Mathematics, SIAM (1987)
Bertsekas, D.P., Tsitsiklis, J.N.: Parallel and Distributed Computation: Numerical Methods, 2nd edn. Athena Scientific Press, Belmont (1989)
Cendrillon, R., Huang, J., Chiang, M., Moonen, M.: Autonomous spectrum balancing for digital subscriber lines. IEEE Trans. Signal Processing 55(8), 4241–4257 (2007)
Cottle, R.W., Pang, J.S., Stone, R.E.: The Linear Complementarity Problem. Academic Press, San Diego (1992)
Etkin, R., Parekh, A., Tse, D.: Spectrum sharing for unlicensed bands. IEEE J. Selected Areas in Communications 25(3), 517–528 (2007)
Facchinei, F., Fischer, A., Piccialli, V.: On generalized Nash games and variational inequalities. Operations Research Letters 35, 159–164 (2007)
Facchinei, F., Kanzow, C.: Generalized Nash equilibrium problems. A Quarterly Journal of Operations Research (4OR) 5(3), 173–210 (2007)
Facchinei, F., Pang, J.S.: Finite-Dimensional Variational Inequalities and Complementarity Problem. Springer, New York (2003)
Facchinei, F., Sagratella, S.: On the computation of all solutions of jointly convex generalized Nash equilibrium problems. Optimization Letters 4(3) (2010)
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)
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)
Haykin, S.: Cognitive radio: Brain-empowered wireless communications. IEEE J. Selected Areas in Communications 23(2), 201–220 (2005)
Hong, M., Garcia, A.: Dynamic pricing of interference in cognitive radio networks. IEEE Trans. Signal Processing (2010) (submitted)
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)
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)
Konnov, I.V.: Equilibrium Models and Variational Inequalities. Elsevier B.V., Amsterdam (2007)
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)
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)
Nash, J.: Equilibrium points in n-person game. National Academy of Science 36, 48–49 (1950)
Olfati-Saber, R., Fax, J.A., Murray, R.M.: Consensus and cooperation in networked multi- agent systems. Proc. IEEE 95(1), 215–223 (2007)
Ortega, J.M., Rheinboldt, W.C.: Iterative Solution of Nonlinear Equations in Several Variables. Society for Industrial Mathematics (SIAM), Philadelphia (1987)
Pang, J.S., Chan, D.: Iterative methods for variational and complementarity problems. Mathematical Programming 24(1), 284–313 (1982)
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)
Pang, J.S.: Asymmetric variational inequality problems over product sets: Applications and iterative methods. Mathematical Programming 31(2), 206–219 (1985)
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)
Rosen, J.: Existence and uniqueness of equilibrium points for concave n-person games. Econometrica 33(3), 520–534 (1965)
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)
Scutari, G., Palomar, D.P.: MIMO cognitive radio: A game theoretical approach. IEEE Trans. Signal Processing 58(2), 761–780 (2010)
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)
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)
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)
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)
Scutari, G., Palomar, D.P., Barbarossa, S.: The MIMO iterative waterfilling algorithm. IEEE Trans. Signal Processing 57(5), 1917–1935 (2009)
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)
Scutari, G., Facchinei, F., Pang, J.S., Palomar, D.P.: Monotone communication games: Theory, algorithms, and models. IEEE Trans. Information Theory (2010) (submitted)
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)
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)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights 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)