CUED Publications database

The cross-entropy method for blind multiuser detection

Liu, Z and Doucet, A and Singh, SS (2004) The cross-entropy method for blind multiuser detection. IEEE International Symposium on Information Theory - Proceedings. p. 510.

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We consider the problem of blind multiuser detection. We adopt a Bayesian approach where unknown parameters are considered random and integrated out. Computing the maximum a posteriori estimate of the input data sequence requires solving a combinatorial optimization problem. We propose here to apply the Cross-Entropy method recently introduced by Rubinstein. The performance of cross-entropy is compared to Markov chain Monte Carlo. For similar Bit Error Rate performance, we demonstrate that Cross-Entropy outperforms a generic Markov chain Monte Carlo method in terms of operation time.

Item Type: Article
Divisions: Div F > Signal Processing and Communications
Depositing User: Cron job
Date Deposited: 04 Feb 2015 22:31
Last Modified: 05 Feb 2015 08:28