NDLI: Cyclostationarity-Based Narrowband Interference Suppression for Heterogeneous Networks Using Neural Network

Content Provider	Springer Nature Link
Author	Yang, Zan Zhang, Xiaoxin Zhao, Yuping
Copyright Year	2011
Abstract	This paper proposes a narrowband interference (NBI) suppression algorithm for Direct Sequence-Code Division Multiple Access systems. The NBI is considered from heterogeneous networks, and predicted based on its cyclostationary characteristic using a nonlinear feed-forward neural network predictor which eliminates the nonlinearity of the spread spectrum (SS) signal in the NBI prediction. To further improve the suppression performance, this paper exploits the structure of the spreading code, and proposes an iterative code-aided algorithm to jointly estimate the NBI and the SS signal. Simulation results reveal that the proposed algorithm largely outperforms the conventional linear prediction filtering and linear-conjugate linear polyperiodically time-varying filtering methods in both the signal to interference plus noise ratio improvement and the bit error rates, when it operates in NBI-contaminated environments.
Starting Page	993
Ending Page	1012
Page Count	20
File Format	PDF
ISSN	09296212
Journal	Wireless Personal Communications
Volume Number	68
Issue Number	3
e-ISSN	1572834X
Language	English
Publisher	Springer US
Publisher Date	2011-12-24
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Cyclostationarity Neural network Narrowband interference suppression DS-CDMA Communications Engineering, Networks Signal, Image and Speech Processing Computer Communication Networks
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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