Annealed neural network based multiuser detector in code division multiple access communications
- 1 January 2000
- journal article
- Published by Institution of Engineering and Technology (IET) in IEE Proceedings - Communications
- Vol. 147 (1) , 57-62
- https://doi.org/10.1049/ip-com:20000228
Abstract
An annealed neural network based multiuser detector in code division multiple access (CDMA) communications is presented. This detector combines features of the Hopfield neural network and simulated annealing. Unlike existing neural network based detectors, this detector does not need good initial estimates or optimal selection of network parameters. The BER performance of the proposed detector is close to the theoretical lower bound of the BER peformance, especially in ‘near–far’ situations. Extensive numerical evaluation of the proposed technique as well as various suboptimal multiuser detectors is conducted using Monte-Carlo simulation.Keywords
This publication has 11 references indexed in Scilit:
- Optimal solutions for cellular neural networks by paralleled hardware annealingIEEE Transactions on Neural Networks, 1996
- Hopfield neural network implementation of the optimal CDMA multiuser detectorIEEE Transactions on Neural Networks, 1996
- A neural network for detection of signals in communicationIEEE Transactions on Circuits and Systems I: Regular Papers, 1996
- Blind adaptive multiuser detectionIEEE Transactions on Information Theory, 1995
- Neural network techniques for adaptive multiuser demodulationIEEE Journal on Selected Areas in Communications, 1994
- Neural networks for multiuser detection in code-division multiple-access communicationsIEEE Transactions on Communications, 1992
- Near-optimum detection in synchronous code-division multiple-access systemsIEEE Transactions on Communications, 1991
- Graph partitioning using annealed neural networksIEEE Transactions on Neural Networks, 1990
- Linear multiuser detectors for synchronous code-division multiple-access channelsIEEE Transactions on Information Theory, 1989
- Cellular neural networks: theoryIEEE Transactions on Circuits and Systems, 1988