### Abstract

Original language | English |
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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 |
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Period | 1/06/02 → 1/06/02 |

### Fingerprint

### Keywords

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

### Cite this

*CDMA multiuser detection, neural networks, and statistical mechanics*. 94-97. Paper presented at Proceedings of workshop on concepts in information theory, Breisach, Germany, June, 2002, .

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**CDMA multiuser detection, neural networks, and statistical mechanics.** / Tanaka, Toshiyuki; Vinck, A. J. Han (Editor).

Research output: Contribution to conference › Paper

TY - CONF

T1 - CDMA multiuser detection, neural networks, and statistical mechanics

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

SP - 94

EP - 97

ER -