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Iterative Narrowband Interference Suppression for DS-CDMA Systems Using Feed-Forward Neural Network

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4 Author(s)
Zan Yang ; State Key Lab. of Adv. Opt. Commun. Syst. & Networks, Peking Univ., Beijing, China ; Tingting Zhao ; Yuping Zhao ; Jianli Yu

This paper proposes a feed-forward neural network predictor to adaptively estimate and suppress the narrowband interference (NBI) in the Direct Sequence-Code Division Multiple Access (DS-CDMA) signal. The iterative code-aided estimation is used to further improve the system performance. Simulation results reveal that the proposed algorithm outperforms conventional linear prediction filtering and recurrent neural networks (RNN) based NBI rejection methods, in different interference models.

Published in:

Vehicular Technology Conference (VTC 2010-Spring), 2010 IEEE 71st

Date of Conference:

16-19 May 2010