Nash Equilibrium Cognitive Radio Secondary User Cognitive Radio Network Radio Spectrum 
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  1. S. Haykin, “Cognitive dynamic systems,” Proc. IEEE, vol. 94, pp. 1910–1911, Nov. 2006.Google Scholar
  2. 2.
    S. Haykin, “Cognitive radio: Brain-empowered wireless communications,” IEEE J. Select. Areas Commun., vol. 23, no. 2, pp. 201–220, Feb. 2005.CrossRefGoogle Scholar
  3. 3.
    R. Pfeifer and C. Scheier, Understanding intelligence, pp. 5–6. MIT Press, 1999.Google Scholar
  4. 4.
    S. Haykin, Neural networks: A comprehensive foundation, 2nd ed. Prentice-Hall, 1999.Google Scholar
  5. 5.
    P. N. Johnson-Laird, The Computer and the mind: An introduction to cognitive science. Harvard University Press, 1988.Google Scholar
  6. 6.
    J. Mitola, “Cognitive radio: An integrated agent architecture for software defined radio,” Dissertation, Doctor of Technology, Royal Institute of Technology (KTH), Sweden, May 8, 2000.Google Scholar
  7. 7.
    J. Mitola, Cognitive radio architecture: The engineering foundations of radio XML.Wiley, 2006.Google Scholar
  8. 8.
    Federal Communications Commission, “Spectrum Policy Task Force,” Report ET Docket No. 02,135, Nov. 2002.Google Scholar
  9. 9.
    “Wolfram Research.” Scholar
  10. 10.
    B. Bale et al., “Noise in wireless systems produced by solar radio bursts,” Radio Sci., vol. 37, 2002.Google Scholar
  11. 11.
    L. J. Lanzerotti et al., “Engineering issues in space weather,” in M. A. Stucthly, editor, Modern Radio Science, pp. 25–50, Oxford University Press, 1999.Google Scholar
  12. 12.
    S. Haykin and M. Moher, Introduction to analog and digital communications.Wiley, 2001.Google Scholar
  13. 13.
    S. Haykin, Communication systems, 4th ed., p. 61. Wiley, 2001.Google Scholar
  14. 14.
    M. Lo‘eve, “Fonctions alatoires de second ordre,” Rev. Sci., Paris, vol. 84, pp. 195–206, 1946.MathSciNetGoogle Scholar
  15. 15.
    M. Lo‘eve, Probability theory. Van Nostrand, 1963.Google Scholar
  16. 16.
    L. Cohen, Time–frequency analysis. Prentice-Hall, 1995.Google Scholar
  17. 17.
    Lord Rayleigh, “On the spectrum of an irregular disturbance,” Philos. Mag., vol. 41, pp. 238–243, 1903. (Note: This paper is reproduced in the Scientific Papers by Lord Rayleigh, Volume V, Article 285, pp. 98–102, Dover Publications, 1964.)Google Scholar
  18. 18.
    D. J. Thomson, “Spectrum estimation and harmonic analysis,” Proc. IEEE, vol. 20, pp. 1055–1096, Sept. 1982.CrossRefGoogle Scholar
  19. 19.
    P. D. Welch, “The use of fast Fourier transform for the estimation of power spectra: A method based on time-averaging over short, modified periodograms,” IEEE Trans. Audio Electroacoust., vol. AU-15, pp. 70–73, 1967.CrossRefMathSciNetGoogle Scholar
  20. 20.
    D. B. Percival and A. T. Walden, Spectral analysis for physical applications. Cambridge University Press, 1993.Google Scholar
  21. 21.
    D. Slepian, “Prolate spheroidal wave functions, Fourier analysis and uncertainty”, Bell Syst. Tech. J., vol. 57, pp. 1371–1430, 1978.Google Scholar
  22. 22.
    A. Drosopoulos and S. Haykin,“Angle-of-arrival estimation in the presence of multipath,” in S. Haykin, editor, Adaptive Radar Signal Processing, pp. 11–89, Wiley, 2007.Google Scholar
  23. 23.
    D. J. Thomson and A. D. Chave, “Jackknifed error estimates for spectra, coherences, and transfer functions,” in S. Haykin, editor, Advances in Spectrum Analysis and Array Processing, vol. 1, pp. 58–113, Prentice-Hall, 1991.Google Scholar
  24. 24.
    P. Stoica and T. Sundin, “On nonparametric spectral estimation,” Circuits Syst. Signal Process., vol. 16, pp. 169–181, 1999.CrossRefGoogle Scholar
  25. 25.
    D. J. Thomson and S. Haykin, “Time-frequency analysis of sea clutter,” in S. Haykin, editor, Adaptive Radar Signal Processing, pp. 91–115, Wiley, 2007.Google Scholar
  26. 26.
    M. E. Mann and J. Park, “Oscillatory spatiotemporal signal detection in climate studies: A multiple-taper spectral domain approach,” in R. Dnowska and B. Saltzman, editors, Advances in Geophysics, vol. 41, pp. 1–131, Academic Press, 1999.Google Scholar
  27. 27.
    G. H. Golub and C. F. VanLoan, Matrix computations, 3rd ed. Johns Hopkins University Press, 1996.Google Scholar
  28. 28.
    G. J. Foschini and M. J. Gans, “On limits of wireless communications in a fading environment when using multiple antennas,”jtyWireless Pers. Commun., vol. 6, pp. 311–335, 1998.Google Scholar
  29. 29.
    S. Haykin, K. Huber, and Z. Chen, “Bayesian sequential state estimation for MIMO wireless communications,” Proc IEEE, Special Issue on Sequential State Estimation, vol. 92, pp. 439–454, 2004.Google Scholar
  30. 30.
    I. Arasarathnam and S. Haykin, “Improved channel tracking for wireless PAT,” submitted to IEEE Trans. Commun.Google Scholar
  31. 31.
    A. Ephirenides and T. Truong, “Schedule broadcasts in multihop radio networks,” IEEE Trans. Commun., vol. 38, pp. 456–460, 1990.CrossRefGoogle Scholar
  32. 32.
    K. Scott and N. Bambos, “Formation and maintenance of self-organizing wireless networks,” Conference Record 3rd Asilomar Conference on Signals, Systems, and Computers, vol. 1, pp. 31–35, Nov. 1997.Google Scholar
  33. 33.
    C. E. Perkins, Ad hoc networking. Addison-Wesley, 2001.Google Scholar
  34. 34.
    O. K. Tonguz and G. Ferrari, Ad hoc wireless networks.Wiley, 2006.Google Scholar
  35. 35.
    M. A. Arbib, The handbook of brain theory and neural networks, 2nd ed. MIT Press, 2003.Google Scholar
  36. 36.
    T. J. Shepard, “Decentralized channel management in scalable multihop spread-spectrum packet radio networks,” PhD Thesis, MIT, July 1995.Google Scholar
  37. 37.
    P. Gupta and P. R. Kumar, “The capacity of wireless networks,” IEEE Trans. Inf. Theory, vol. 46, no. 2, pp. 388–404, 2000.MATHCrossRefMathSciNetGoogle Scholar
  38. 38.
    P. Gupta and P. R. Kumer, “Internets in the sky: The capacity of three-dimensional wireless networks,” Commun. Inf. Syst., vol. 1, pp. 39–49, 2001.Google Scholar
  39. 39.
    S. Haykin and M. Moher, Modern wireless communications.Prentice-Hall, 2003.Google Scholar
  40. 40.
    L. Hanzo and T. Keller, OFDM and MC-CDMA.Wiley, 2006.Google Scholar
  41. 41.
    J. A. C. Bingham, ADSL, VDSL, and multicarrier modulation.Wiley, 2000.Google Scholar
  42. 42.
    C. Berrou, “The ten-year old turbo codes are entering into service,” IEEE Commun. Mag., vol. 42, pp. 110–116, Aug. 2003.CrossRefGoogle Scholar
  43. 43.
    V. Tarokh, H. Jafarkhni, and A. R. Calderbank, “Space–time block coding for wireless communication: Performance results,” IEEE J. Select. Areas Commun., vol. 17, pp. 451– 460, May 1999.CrossRefGoogle Scholar
  44. 44.
    P. Moose, “A technique for orthogonal frequency division multiplexing frequency offset correction,” IEEE Trans. Commun., vol. 42, pp. 2908–2914, 1994.CrossRefGoogle Scholar
  45. 45.
    T. M. Cover and J. A. Thomas, Elements of information theory.Wiley, 1991.Google Scholar
  46. 46.
    J. von Neumann and O. Morgenstein, Theory of games and economic behavior.Princeton University Press, 1947.Google Scholar
  47. 47.
    D. Fudenberg and D. K. Levine, The theory of learning in games.MIT Press, 1999.Google Scholar
  48. 48.
    T. Basar and G. J. Olsder, Dynamic noncooperative game theory, 2nd ed. SIAM, 1999.Google Scholar
  49. 49.
    M. J. Osborne and A. Rubinstein, A course in game theory.MIT Press, 1994.Google Scholar
  50. 50.
    G. Gordon, “No-regret algorithms for structured prediction problems,” Technical report 112, Carnegie-Mellon University, Center for Automated Learning and Discovery, 2005.Google Scholar
  51. 51.
    P. W. Glimcher, Decisions, uncertainty, and the brain: The science of neuroeconomics. MIT Press, 2003.Google Scholar
  52. 52.
    A. B. McKenzie, L. Dasilva, andW. Tranter, Game theory for wireless engineers.Morgan and Claypool Publishers, 2006.Google Scholar
  53. 53.
    J. F. Nash, “Non-cooperative games,” Ann. Math., vol. 54, pp. 286–295, 1951.CrossRefMathSciNetGoogle Scholar
  54. 54.
    J. F. Nash, “Equilibrium points in n-person games,” in Proc. Natl Acad. Sci., vol. 36, pp. 48–49, 1950.MATHCrossRefMathSciNetGoogle Scholar
  55. 55.
    M. Felegyhazi and J. P. Hubaux, “Game theory in wireless networks: A tutorial,” EPFL Technical report, LCA-REPORT-2006-002, EPFL, Switzerland.Google Scholar
  56. 56.
    W. Yu, “Competition and cooperation in multi-user communication environments,” Doctoral Dissertation, Stanford University, 2002.Google Scholar
  57. 57.
    W. Yu, G. Ginis, and J. M. Cioffi, “Distributed multiuser power control for digital subscriber lines,” IEEE J. Select. Areas Commun., vol. 20, pp. 1105–1115, June 2002.CrossRefGoogle Scholar
  58. 58.
    S. T. Chung, “Transmission schemes for frequency selective Gaussian interference channels,” Dissertation, Doctor of Philosophy, Stanford University, CA, Nov. 2003.Google Scholar
  59. 59.
    T. Starr, J. M. Cioffi, and P. J. Silverman, Understanding digital subcarrier line technology. Prentice-Hall, 1999.Google Scholar
  60. 60.
    A. Boyd and L. Vandenbarghe, Convex optimization.Cambridge University Press, 2004.Google Scholar
  61. 61.
    H. K. Khalil, Nonlinear systems. Prentice-Hall, 1992.Google Scholar
  62. 62.
    J. Maynard Smith, “The theory or games and the evolution of animal conflicts,” J. Theor. Biol., vol. 47, pp. 209–221, 1974.CrossRefMathSciNetGoogle Scholar
  63. 63.
    J. Maynard Smith, Evolution and the theory of games.Cambridge University Press, 1982.Google Scholar
  64. 64.
    H. G. Schuster, Complex adaptive systems: An introduction.Springer-Verlag, 2001.Google Scholar
  65. 65.
    D. L. Stein, editor, Lectures in the Sciences of Complexity.Addison-Wesley, 1989.Google Scholar
  66. 66.
    E. Jen, editor, 1989 Lectures in Complex Systems.Addison-Wesley, 1990.Google Scholar
  67. 67.
    G. G. Weisbunch, Complex system dynamics.Addison-Wesley, 1991.Google Scholar
  68. 68.
    G. Nicolis and I. Progogine, Exploring complexity: An introduction.W. H. Freeman and Company, 1989.Google Scholar
  69. 69.
    S. Haykin, editor, Adaptive Radar Signal Processing, pp. 153–155. Wiley, 2007.Google Scholar
  70. 70.
    J. Zhao, H. Zheng, and G. H. Yang, “Distributed coordination in dynamic spectrum allocation networks,” in IEEE Workshop(Baltimore, MA), pp. 259–268, 2005.Google Scholar

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© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Simon Haykin
    • 1
  1. 1.McMaster UniversityCanada

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