CDMA multiuser detection, neural networks, and statistical mechanics

Toshiyuki Tanaka, A. J. Han Vinck (Editor)

    Research output: Contribution to conferencePaper

    Abstract

    A novel approach, based on statistical mechanics, to analyze typical performance of optimum code-division multiple-access (CDMA) multiuser detectors is reviewed. A `black-box' view ot the basic CDMA channel is introduced, based on which the CDMA multiuser detection problem is regarded as a `learning-from-examples' problem of the `binary linear perceptron' in the neural network literature. Adopting Bayes framework, analysis of the performance of the optimum CDMA multiuser detectors is reduced to evaluation of the average of the cumulant generating function of a relevant posterior distribution. The evaluation of the average cumulant generating function is done, based on formal analogy with a similar calculation appearing in the spin glass theory in statistical mechanics, by making use of the replica method, a method developed in the spin glass theory.
    Original languageEnglish
    Pages94-97
    Number of pages4
    Publication statusPublished - Jun 2002
    EventProceedings of workshop on concepts in information theory, Breisach, Germany, June, 2002 -
    Duration: 1 Jun 20021 Jun 2002

    Workshop

    WorkshopProceedings of workshop on concepts in information theory, Breisach, Germany, June, 2002
    Period1/06/021/06/02

    Keywords

    • code-division multiple-access
    • multiuser detection problem
    • `learning-from-examples' problem
    • Bayes framework
    • posterior distribution

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