標題: New nonlinear algorithms for estimating and suppressing narrowband interference in DS spread spectrum systems
作者: Wu, WR
Yu, FF
交大名義發表
電信工程研究所
National Chiao Tung University
Institute of Communications Engineering
公開日期: 1-四月-1996
摘要: It has been shown that the narrow-band (NB) interference suppression capability of a direct-sequence (DS) spread spectrum system can be enhanced considerably by processing the received signal via a prediction error filter, The conventional approach to this problem makes use of a linear filter. However, the binary DS signal, that acts as noise in the prediction process, is highly non-Gaussian, Thus, linear filtering is not optimal, Vijayan and Poor [11] first proposed using a nonlinear approximate conditional mean (ACM) filter of the Masreliez type and obtained significant results, This paper proposes a number of new nonlinear algorithms, Our work consists of three parts, 1) We develop a decision-directed Kalman (DDK) filter, that has the same performance as the ACM filter but a simpler structure, 2) Using the nonlinear function in the ACM and the DDK filters, we develop other nonlinear least mean square (LR IS) filters with improved performance, 3) We further use the nonlinear functions to develop nonlinear recursive least squares (RLS) filters that can be used independently as predictors or as interference identifiers so that the ACM or the DDK filter can be applied, Simulations show that our nonlinear algorithms outperform conventional ones.
URI: http://dx.doi.org/10.1109/26.489097
http://hdl.handle.net/11536/1356
ISSN: 0090-6778
DOI: 10.1109/26.489097
期刊: IEEE TRANSACTIONS ON COMMUNICATIONS
Volume: 44
Issue: 4
起始頁: 508
結束頁: 515
顯示於類別:期刊論文


文件中的檔案:

  1. A1996UE72300016.pdf