In order to enhance data rate for multimedia services, new advanced receivers for next generation mobile com-munications are developed. Adaptive blind multiuser detection has been widely proposed for applications in CDMA (Code Division Multiple Access) wireless com-munication systems for its principal advantage of elim-inating training sequence to set-up receiver filter coeffi-cients. Main drawback of this technique is that it reaches the optimum behavior after a certain number of bit times, which precludes its use in typical time-varying environ-ments. In this paper, a new neural network approach is proposed in order to solve this drawback. In particular, this paper considers the use of a modified Kennedy-Chua neural network, based on the Hopfield model. Simulation results are given to demonstrate the effectiveness of the proposed approach in different time-varying application scenarios.
A Neural Network Approach For Blind Multiuser Detection in DS-CDMA Communication Systems
D. Tarchi;
2002
Abstract
In order to enhance data rate for multimedia services, new advanced receivers for next generation mobile com-munications are developed. Adaptive blind multiuser detection has been widely proposed for applications in CDMA (Code Division Multiple Access) wireless com-munication systems for its principal advantage of elim-inating training sequence to set-up receiver filter coeffi-cients. Main drawback of this technique is that it reaches the optimum behavior after a certain number of bit times, which precludes its use in typical time-varying environ-ments. In this paper, a new neural network approach is proposed in order to solve this drawback. In particular, this paper considers the use of a modified Kennedy-Chua neural network, based on the Hopfield model. Simulation results are given to demonstrate the effectiveness of the proposed approach in different time-varying application scenarios.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
