Title :
A neural network approach to MMSE receivers in a DS-CDMA multipath fading environment
Author :
Fantacci, Romano ; Tarchi, Daniele ; Marini, Mauro ; Rabbini, Alessandro
Author_Institution :
Dept. of Electron. & Telecommun., Univ. of Florence, Italy
fDate :
5/1/2006 12:00:00 AM
Abstract :
This letter deals with an advanced minimum mean-squared error receiver for applications to uplink transmissions in a multiuser code-division multiple-access system. The receiver is implemented by means of a suitable neural network in order to enhance the receiver convergence speed in the case of fast fading. Performance comparisons with classical approaches highlights a better behavior for the proposed scheme.
Keywords :
code division multiple access; fading channels; least mean squares methods; multipath channels; multiuser channels; neural nets; radio links; radio receivers; spread spectrum communication; telecommunication computing; DS-CDMA; MMSE receivers; minimum mean-squared error receiver; multipath fading environment; multiuser code-division multiple-access system; neural network approach; uplink transmissions; AWGN; Convergence; Fading; Filters; Intelligent networks; Multiaccess communication; Multiple access interference; Multiuser detection; Neural networks; Support vector machines; Code-division multiple access (CDMA); least-mean square (LMS) methods; multiuser channels; multiuser detection (MUD); neural networks;
Journal_Title :
Communications, IEEE Transactions on
DOI :
10.1109/TCOMM.2006.874011
