Sequential Chaotic Annealing Neural Network for Cdma Multiuser Detection

The optimum Multiuser Detection Problem in the presence of noise is a quadratic integer programming problem which has been shown to be NP-complete. In this paper, we propose a novel neural network based Multiuser Detector for Direct-Sequence Code Division Multiple Access system. The proposed detector combines the paradigms of chaotic neural networks and methods from Sequential Unconstrained Minimization Techniques. The proposed network is adaptive in the sense that the network "learns" the energy function to minimize. We show that the proposed network outperforms traditional methods such as the Hopfield Net as well as as recent methods such as the Transiently Chaotic Neural Network.