Blind adaptive stochastic neural network for multiuser detection

Author

Jeney, Gábor ; Levendovszky, János ; Kovács, Lóránt

Author_Institution

Dept. of Telecommun., Budapest Univ. of Tecnology & Econ., Hungary

Volume

3

fYear

2001

fDate

2001

Firstpage

1868

Abstract

In this paper some blind adaptive methods are introduced for multiuser detection (MUD). The detector architecture contains a channel identifier followed by a stochastic Hopfield (1985) net. Blind channel identification is proposed to be carried out by either the Kohonen (see Self-Organizing Maps, Springer, 2000) algorithm or by a novel adaptive decorrelation technique. Based on the estimated channel parameters the stochastic Hopfield net implements a near optimal decision. Besides describing the related algorithms, the paper contains extensive simulations to evaluate the performance of the proposed detector structures

Keywords

Hopfield neural nets; adaptive signal detection; code division multiple access; decorrelation; multipath channels; multiuser channels; self-organising feature maps; spread spectrum communication; stochastic processes; telecommunication computing; DS-CDMA systems; Kohonen algorithm; adaptive decorrelation; blind adaptive methods; blind adaptive stochastic neural network; blind channel identification; detector architecture; direct sequence code division multiple access; estimated channel parameters; multipath propagation model; multiuser detection; performance evaluation; simulations; stochastic Hopfield net; Adaptive systems; Decorrelation; Detectors; Hopfield neural networks; Multiaccess communication; Multiuser detection; Neural networks; Parameter estimation; Recurrent neural networks; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Vehicular Technology Conference, 2001. VTC 2001 Spring. IEEE VTS 53rd

Conference_Location

Rhodes

ISSN

1090-3038

Print_ISBN

0-7803-6728-6

Type

conf

DOI

10.1109/VETECS.2001.945018

Filename

945018