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.
|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||Proceedings of workshop on concepts in information theory, Breisach, Germany, June, 2002|
|Period||1/06/02 → 1/06/02|
- code-division multiple-access
- multiuser detection problem
- `learning-from-examples' problem
- Bayes framework
- posterior distribution
Tanaka, T., & Vinck, A. J. H. (Ed.) (2002). 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, .