Title :
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
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;
Conference_Titel :
Circuits and Systems, 1997. ISCAS '97., Proceedings of 1997 IEEE International Symposium on
Print_ISBN :
0-7803-3583-X
DOI :
10.1109/ISCAS.1997.608825
