CDMA multiuser detection, neural networks, and statistical mechanics

Toshiyuki Tanaka; A. J. Han Vinck

CDMA multiuser detection, neural networks, and statistical mechanics

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

Research output: Contribution to conference › Paper

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 language	English
Pages	94-97
Number of pages	4
Publication status	Published - Jun 2002
Event	Proceedings of workshop on concepts in information theory, Breisach, Germany, June, 2002 - Duration: 1 Jun 2002 → 1 Jun 2002

Workshop

Workshop	Proceedings of workshop on concepts in information theory, Breisach, Germany, June, 2002
Period	1/06/02 → 1/06/02

Keywords

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

Access to Document

NCRG_2002_011.pdf

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Cite this

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title = "CDMA multiuser detection, neural networks, and statistical mechanics",

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.",

keywords = "code-division multiple-access, multiuser detection problem, `learning-from-examples' problem, Bayes framework, posterior distribution",

author = "Toshiyuki Tanaka and Vinck, {A. J. Han}",

year = "2002",

month = jun,

language = "English",

pages = "94--97",

note = "Proceedings of workshop on concepts in information theory, Breisach, Germany, June, 2002 ; Conference date: 01-06-2002 Through 01-06-2002",

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AU - Tanaka, Toshiyuki

A2 - Vinck, A. J. Han

PY - 2002/6

Y1 - 2002/6

N2 - 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.

AB - 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.

KW - code-division multiple-access

KW - multiuser detection problem

KW - `learning-from-examples' problem

KW - Bayes framework

KW - posterior distribution

M3 - Paper

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EP - 97

T2 - Proceedings of workshop on concepts in information theory, Breisach, Germany, June, 2002

Y2 - 1 June 2002 through 1 June 2002

ER -