Narrowband interference suppression using RKF-based recurrent neural network in spread spectrum system

Ding Jie Xu; Pi Jie Zhao; Feng Shen; Hong Zhao

doi:10.1109/WiCom.2008.433

Narrowband interference suppression using RKF-based recurrent neural network in spread spectrum system

Ding Jie Xu^*
, Pi Jie Zhao
, Feng Shen
, Hong Zhao

^*Corresponding author for this work

Harbin Engineering University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

A new adaptive neural network predictor to eradicate the narrowband interference in the spread spectrum system is proposed in this paper. The effectively robust Kalman filter (RKF) algorithm is adopted to adjust the synaptic weights in the nonlinear recurrent architecture and thereby estimate the narrowband interference. The main characteristics of the proposed RKF-based canceller are its rapid convergence rate and precise prediction. Simulation results reveal that the RNINP based on RKF algorithm has large improvement on the interference suppression capability compared with conventional LMS, ACM and RTRL-based canceller in CWI and ARI environments, respectively.

Original language	English
Title of host publication	2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008
DOIs	https://doi.org/10.1109/WiCom.2008.433
State	Published - 2008
Externally published	Yes
Event	2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008 - Dalian, China Duration: 12 Oct 2008 → 14 Oct 2008

Publication series

Name	2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008

Conference

Conference	2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008
Country/Territory	China
City	Dalian
Period	12/10/08 → 14/10/08

Keywords

Narrowband interference
Recurrent neural network
Robust Kalman filter
Spread spectrum system

Access to Document

10.1109/WiCom.2008.433

Cite this

Xu, D. J., Zhao, P. J., Shen, F., & Zhao, H. (2008). Narrowband interference suppression using RKF-based recurrent neural network in spread spectrum system. In 2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008 Article 4678342 (2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008). https://doi.org/10.1109/WiCom.2008.433

@inproceedings{b624d292bc0b47e492176ca0259dbe6f,

title = "Narrowband interference suppression using RKF-based recurrent neural network in spread spectrum system",

abstract = "A new adaptive neural network predictor to eradicate the narrowband interference in the spread spectrum system is proposed in this paper. The effectively robust Kalman filter (RKF) algorithm is adopted to adjust the synaptic weights in the nonlinear recurrent architecture and thereby estimate the narrowband interference. The main characteristics of the proposed RKF-based canceller are its rapid convergence rate and precise prediction. Simulation results reveal that the RNINP based on RKF algorithm has large improvement on the interference suppression capability compared with conventional LMS, ACM and RTRL-based canceller in CWI and ARI environments, respectively.",

keywords = "Narrowband interference, Recurrent neural network, Robust Kalman filter, Spread spectrum system",

author = "Xu, \{Ding Jie\} and Zhao, \{Pi Jie\} and Feng Shen and Hong Zhao",

year = "2008",

doi = "10.1109/WiCom.2008.433",

language = "英语",

isbn = "9781424421084",

series = "2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008",

booktitle = "2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008",

note = "2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008 ; Conference date: 12-10-2008 Through 14-10-2008",

}

Xu, DJ, Zhao, PJ, Shen, F & Zhao, H 2008, Narrowband interference suppression using RKF-based recurrent neural network in spread spectrum system. in 2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008., 4678342, 2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008, 2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008, Dalian, China, 12/10/08. https://doi.org/10.1109/WiCom.2008.433

Narrowband interference suppression using RKF-based recurrent neural network in spread spectrum system. / Xu, Ding Jie; Zhao, Pi Jie; Shen, Feng et al.
2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008. 2008. 4678342 (2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Narrowband interference suppression using RKF-based recurrent neural network in spread spectrum system

AU - Xu, Ding Jie

AU - Zhao, Pi Jie

AU - Shen, Feng

AU - Zhao, Hong

PY - 2008

Y1 - 2008

N2 - A new adaptive neural network predictor to eradicate the narrowband interference in the spread spectrum system is proposed in this paper. The effectively robust Kalman filter (RKF) algorithm is adopted to adjust the synaptic weights in the nonlinear recurrent architecture and thereby estimate the narrowband interference. The main characteristics of the proposed RKF-based canceller are its rapid convergence rate and precise prediction. Simulation results reveal that the RNINP based on RKF algorithm has large improvement on the interference suppression capability compared with conventional LMS, ACM and RTRL-based canceller in CWI and ARI environments, respectively.

AB - A new adaptive neural network predictor to eradicate the narrowband interference in the spread spectrum system is proposed in this paper. The effectively robust Kalman filter (RKF) algorithm is adopted to adjust the synaptic weights in the nonlinear recurrent architecture and thereby estimate the narrowband interference. The main characteristics of the proposed RKF-based canceller are its rapid convergence rate and precise prediction. Simulation results reveal that the RNINP based on RKF algorithm has large improvement on the interference suppression capability compared with conventional LMS, ACM and RTRL-based canceller in CWI and ARI environments, respectively.

KW - Narrowband interference

KW - Recurrent neural network

KW - Robust Kalman filter

KW - Spread spectrum system

UR - https://www.scopus.com/pages/publications/58049095492

U2 - 10.1109/WiCom.2008.433

DO - 10.1109/WiCom.2008.433

M3 - 会议稿件

AN - SCOPUS:58049095492

SN - 9781424421084

T3 - 2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008

BT - 2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008

T2 - 2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008

Y2 - 12 October 2008 through 14 October 2008

ER -

Xu DJ, Zhao PJ, Shen F, Zhao H. Narrowband interference suppression using RKF-based recurrent neural network in spread spectrum system. In 2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008. 2008. 4678342. (2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008). doi: 10.1109/WiCom.2008.433

Narrowband interference suppression using RKF-based recurrent neural network in spread spectrum system

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this