• DocumentCode
    1208151
  • Title

    Convergence analysis of the constant modulus algorithm

  • Author

    Dabeer, Onkar ; Masry, Elias

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of California, Santa Barbara, CA, USA
  • Volume
    49
  • Issue
    6
  • fYear
    2003
  • fDate
    6/1/2003 12:00:00 AM
  • Firstpage
    1447
  • Lastpage
    1464
  • Abstract
    We study the global convergence of the stochastic gradient constant modulus algorithm (CMA) in the absence of channel noise as well as in the presence of channel noise. The case of fractionally spaced equalizer and/or multiple antenna at the receiver is considered. For the noiseless case, we show that with proper initialization, and with small step size, the algorithm converges to a zero-forcing filter with probability close to one. In the presence of channel noise such as additive Gaussian noise, we prove that the algorithm diverges almost surely on the infinite-time horizon. However, under suitable conditions, the algorithm visits a small neighborhood of the Wiener filters a large number of times before ultimately diverging.
  • Keywords
    Gaussian noise; Wiener filters; antenna arrays; convergence of numerical methods; equalisers; gradient methods; probability; receiving antennas; stochastic processes; CMA; Wiener filters; additive Gaussian noise; channel noise; convergence analysis; fractionally spaced equalizer; global convergence; high data rate communication systems; infinite-time horizon; intersymbol interference cancellation; multiple receiver antenna; probability; step size initialization; stochastic gradient constant modulus algorithm; zero-forcing filter; Additive noise; Algorithm design and analysis; Blind equalizers; Convergence; Cost function; Gaussian noise; Receiving antennas; Stochastic resonance; Vectors; Wiener filter;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2003.811903
  • Filename
    1201068