Liu, Z and Doucet, A and Singh, SS (2004) The cross-entropy method for blind multiuser detection. IEEE International Symposium on Information Theory - Proceedings. 510-.Full text not available from this repository.
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.
|Divisions:||Div F > Signal Processing and Communications|
|Depositing User:||Unnamed user with email email@example.com|
|Date Deposited:||09 Dec 2016 17:32|
|Last Modified:||24 Mar 2017 23:56|