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Recent Patents on Computer Science

Editor-in-Chief

ISSN (Print): 2213-2759
ISSN (Online): 1874-4796

General Research Article

Research on Optimal CDMA Multiuser Detection Based on Stochastic Hopfield Neural Network

Author(s): Tongke Fan*

Volume 12, Issue 3, 2019

Page: [233 - 240] Pages: 8

DOI: 10.2174/2213275912666181210103742

Price: $65

Abstract

Background: Most of the common multi-user detection techniques have the shortcomings of large computation and slow operation. For Hopfield neural networks, there are some problems such as high-speed searching ability and parallel processing, but there are local convergence problems.

Objective: The stochastic Hopfield neural network avoids local convergence by introducing noise into the state variables and then achieves the optimal detection.

Methods: Based on the study of CDMA communication model, this paper presents and models the problem of multi-user detection. Then a new stochastic Hopfield neural network is obtained by introducing a stochastic disturbance into the traditional Hopfield neural network. Finally, the problem of CDMA multi-user detection is simulated.

Conclusion: The results show that the introduction of stochastic disturbance into Hopfield neural network can help the neural network to jump out of the local minimum, thus achieving the minimum and improving the performance of the neural network.

Keywords: CDMA, multiuser detector, stochastic Hopfield network, BER, optimal detection, state variables.

Graphical Abstract

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