Neural network interference canceller in DS/SSMA communications with impulse noise

Author

Leung, S.H. ; Weng, J.F. ; Bi, G.G.

Author_Institution

Dept. of Electron. Eng., City Univ. of Hong Kong, Hong Kong

Volume

1

fYear

1997

fDate

9-12 Jun 1997

Firstpage

585

Abstract

A new neural network interference canceller for the receptions of DS/SSMA communications with impulse noise is presented. In this canceller, a nonlinearity is used to limit the large impulse noise and an Armijo gradient algorithm applied in estimating and subtracting the interfering signal. It is shown that without knowing the signals´ amplitudes and the data bits a priori, the neural network interference canceller can jointly suppress the multiple-access interference and the impulse noise and provide a near single-user performance

Keywords

interference suppression; multi-access systems; radiofrequency interference; recurrent neural nets; spread spectrum communication; telecommunication computing; Armijo gradient algorithm; DS/SSMA communications; RFI; direct sequence SSMA; impulse noise; multiple-access interference; neural network interference canceller; nonlinearity; spread spectrum multiple access; Detectors; Intelligent networks; Interference cancellation; Interference suppression; Multiple access interference; Neural networks; Noise cancellation; Noise level; Noise robustness; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1997. ISCAS '97., Proceedings of 1997 IEEE International Symposium on

Print_ISBN

0-7803-3583-X

Type

conf

DOI

10.1109/ISCAS.1997.608825

Filename

608825