Hysteretic HNN MAI-Cancellation for CDMA Signals in Multipath Fading Channels

Authors:
Ebrahim Soujeri
Affiliations:
Department of Electrical and Electronic Engineering, European University of Lefke, Gemikonagi, Turkish Republic of Northern Cyprus
Venue:
Neural Processing Letters
Year:
2010

Citing 4
Cited 0

Minimum probability of error for asynchronous Gaussian multiple-access channels

IEEE Transactions on Information Theory
Multiuser Detection of Synchronous MC-CDMA in Multipath Fading Channels Using Hopfield Neural Networks

Neural Processing Letters
Hopfield neural network implementation of the optimal CDMA multiuser detector

IEEE Transactions on Neural Networks
The hysteretic Hopfield neural network

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.01

Visualization

Abstract

Multiple-access interference cancellation using hysteretic Hopfield neural network receiver for direct sequence code-division multiple access (DS-CDMA) in multipath fading channels is investigated. It has been shown that by applying the phenomenon of "hysteresis" to the Hopfield neural network (HNN) detector, performance of this detector may be enhanced in all near-far situations for different number of multipath rays. Introducing the concept of Hysteresis into HNN has made this suboptimum CDMA detector even closer to the optimum multiuser CDMA detector. As shown by simulation results, the bit-error rate performance achieved by the Hysteretic Hopfield Neural Network detector outperforms the classical HNN detector with a good margin and is promising.