Title :
Multiuser interference mitigation in multipath fading channels using a neural network based blind receiver
Author :
Fantacci, Romano ; Mancini, Leonardo ; Tarchi, Daniele
Author_Institution :
Dipt. di Elettronica e Telecomunicazioni, Univ. di Firenze, Italy
Abstract :
In order to enhance the bandwidth utilization, new advanced receivers for next generation mobile communications are developed. Adaptive blind multiuser detection has been widely proposed for applications in CDMA (code division multiple access) wireless communication systems for its principal advantage of eliminating training sequence to set-up receiver filter coefficients. 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 environments. 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 (1988) neural network, based on the Hopfield (1984) model. Numerical results are given to demonstrate the effectiveness of the proposed approach in different time-varying application scenarios.
Keywords :
3G mobile communication; Hopfield neural nets; adaptive signal detection; code division multiple access; fading channels; multipath channels; multiuser detection; radio receivers; spread spectrum communication; telecommunication computing; time-varying channels; CDMA wireless communication systems; DS-CDMA communication system; Hopfield model; adaptive blind multiuser detection; bandwidth utilization enhancement; code division multiple access; mobile communications; modified Kennedy-Chun neural network; multipath fading channels; multiuser interference mitigation; neural network approach; neural network based blind receiver; optimum behavior; receiver filter coefficients; third generation mobile communication systems; time-varying environments; Adaptive filters; Bandwidth; Fading; Hopfield neural networks; Interference; Mobile communication; Multiaccess communication; Multiuser detection; Neural networks; Wireless communication;
Conference_Titel :
Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE
Print_ISBN :
0-7803-7632-3
DOI :
10.1109/GLOCOM.2002.1188127