Learning strategies for adaptive equalizers using the constant modulus error criterion

Robert A. Soni, Tracie A. Schirtzinger, William Kenneth Jenkins

    Research output: Contribution to journalArticle

    1 Scopus citations

    Abstract

    In communication systems, data are often corrupted during transmission due to imperfect communication channels. Since channel characteristics may be time varying or unknown prior to data transmission, adaptive equalizers are typically incorporated into the receiver to reduce the ill effects of the imperfect channel. Conventional equalizers utilize a training signal to achieve the proper correction. Blind equalization schemes do not require the use of a training signal, but instead attempt restoration based upon some known property of the transmitted signal. The constant modulus algorithm (CMA) is a blind equalization technique that may be used to equalize certain communication signals (e.g. BPSK, QPSK, and FM). This paper investigates three new techniques for adaptive equalization based on the constant modulus error criterion: (i) the fast quasi-Newton CMA, (ii) the conjugate gradient quasi-Newton CMA, (iii) the conjugate gradient CMA. These three methods are formulated analytically and evaluated experimentally on several typical communication channel models.

    Original languageEnglish (US)
    Pages (from-to)97-116
    Number of pages20
    JournalInternational Journal of Adaptive Control and Signal Processing
    Volume12
    Issue number2
    DOIs
    StatePublished - Jan 1 1998

    All Science Journal Classification (ASJC) codes

    • Control and Systems Engineering
    • Signal Processing
    • Electrical and Electronic Engineering

    Fingerprint Dive into the research topics of 'Learning strategies for adaptive equalizers using the constant modulus error criterion'. Together they form a unique fingerprint.

  • Cite this