直接序列 (DS) 分碼多重存取 (CDMA) 的技術已經是倍受矚目的. 在本篇論文中, 我們討論在直接序列-分碼多重存取系統中抑制窄頻干擾 (NBI)的問題. 我們可以使用非線性濾波器的方法, 稱之為直接-決策卡門 (DDK) 濾波器, 來消除存在分碼多重存取系統中的單一窄頻雜訊干擾, 如此其系統性能已被證實優於使用線性濾波器的方法. 由於本篇論文主要是在討論消除多重窄頻該擾的問題, 這樣的情形有可能發生在一些實際的用途上, 如使用在2.4GHz頻帶的分碼多重存取系統中, 存在著藍牙 (bluetooth) 及無線區域迴路 (wireless LAN)兩種技術, 如此在同一頻帶下有可能會發生信號功率大小不同之現象.
在本篇論文裡, 一個快速收斂最小平方演算法 (LS), viz., 修正的反向QR分解-遞迴式最小平方 (IQRD-RLS) 演算法及內點 (IP) 最小平方 (IP LS) 演算法被設計出, 以用來消除在多用戶分碼多重存取的系統中之多重窄頻的干擾. 事實上, 在遞迴式最小平方 (RLS) 家族裡, 反向QR分解-遞迴式最小平方演算法及內點最小平方演算法已經知道有比較好的數值穩定性及收斂速度. 因此我們使用非線性濾波器 (多用戶直接-決策卡門 (MDK) 濾波器) 配合修正的反向QR分解-遞迴式最小平方演算法的方式來解決多重窄頻干擾的問題, 其與傳統的反向QR分解-遞迴式最小平方演算法差別在於將估測誤差εk,k-1 以 ρ(εk,k-1) 來替代. 我們可由電腦模擬結果得知所提出的方法有較好的性能, 並以收斂特性及訊雜比增益 (SNRI) 來驗證所提出之演算法之性能優於傳統的非線性濾波器配合最小均方值 (LMS) 演算法

The technique of direct-sequence (DS) code division multiple access (CDMA) cellular systems has been the focus of increased attention. In this thesis, the problem of narrow-band interference (NBI) cancellation for the DS-CDMA communication systems is considered. It has been shown that the performance of single NBI cancellation for CDMA systems by using the non-linear filtering approach, the so-called DDK filter or the MDK filter, is superior to the one using the linear filtering approach. The main concern of this thesis is to deal with the multiple NBI cancellation. This may occur in some practical application, for instance, in the 2.4GHz CDMA system, the bluetooth and wireless LAN may exist in the same frequency band with different power ratio.
In this thesis, the nonlinear filtering with fast convergence least square (LS) algorithms, viz., the modified inverse QRD-RLS (IQRD-RLS) and the interior point (IP) LS algorithms, are devised for multiple NBI cancellation in the multi-user CDMA system. In fact, the IQRD-RLS and the IP LS algorithms are known to have better numerical stability and convergence property in the RLS family. Since in the non-linear MDK filter with the IQRD-RLS algorithm, the prediction error εk,k-1 used in the conventional IQRD-RLS is replaced by the nonlinear function of ρ(εk,k-1), and is defined to as the modified IQRD-RLS algorithm. The merits of the proposed algorithms are verified via computer simulation. We showed that the performance of our proposed algorithms outperformed the one using the conventional nonlinear filtering approach with LMS algorithm, in terms of convergence property and the signal-to-noise ratio improvement (SNRI).

Contents
Acknowledgement i
Abstract ii
Contents iii
List of Figures and Tables v
Chapter 1 Introduction 1
Chapter 2 Nonlinear NBI Cancellation Filtering for DS-CDMA System
2.1 Introduction 3
2.2 Conventional Nonlinear Filters for Single User DS-CDMA System 4
2.2.1 Approximate Conditional Mean (ACM) Filter 6
2.2.2 Decision-Directed Kalman (DDK) Filter 9
2.3 Nonlinear Multi-user DDK (MDK) filter for Multi-user DS-CDMA
System 12
2.3.1 Multi-user ACM Filter 13
2.3.2 MDK Filter 14
2.4 Computer Simulation Results 16
Chapter 3 Nonlinear Multiple NBI cancellation Filtering with Modified IQRD-RLS
Algorithm for Multi-user DS-CDMA System
3.1 Introduction 18
3.2 Signal Model of K-user with Multiple NBI for DS-CDMA System 20
3.3 Adaptive Nonlinear Filtering Based on the LMS Algorithm 22
3.4 Adaptive Nonlinear Filtering Based on the IP LS Algorithm 24
3.5 Adaptive Nonlinear Filtering Based on the Modified IQRD-RLS
Algorithm 28
3.6 Computer Simulation Results 37
Chapter 4 Conclusions 44
References 45

References
[1] C. J. Masreliez, “Approximate non-Gaussian filtering with linear state and observation relations,” IEEE Transactions on Automatic control, pp. 107-110, Feb. 1975.
[2] R. Vijayan and H. V. Poor, “Nonlinear technique for interference suppression in spread-spectrum systems,” IEEE Trans. Commun., vol. COM-38, pp. 1060-1065, July 1990.
[3] S. T. Alexander and A. L. Ghirnikar, ”a Method for Recursive Least Squares Filtering Based Upon an Inverse QR Decomposition,” IEEE Trans. on signal processing, vol. 41, No. 1, pp. 20-30, Jan. 1993.
[4] L. A. Rusch and H. V. Poor, “ Narrowband intereference suppression in CDMA spread spectrum communications,” IEEE Trans. Commun., vol. COM-42, pp. 1969-1979, Apr. 1994.
[5] W. R. Wu and F.-F. Yu, “New Nonlinear algorithms for estimating and suppressing narrowband interference in DS spread-spectrum systems,” IEEE Trans. Commun., vol. 44, pp. 508-515, Apr.1996.
[6] K. J. Wang and Y. Yao, “New Nonlinear Algorithms for Narrowband Interference Suppression in CDMA Spread-Spectrum Systems,” IEEE Journal on selected areas in commun., vol. 17, No. 12, pp. 2148-2153, Dec. 1999.
[7] K. H. Afkhamie, Z. O. Luo and K. M. Wong, “Adaptive Linear Filtering Using Interior Point Optimization Techniques,” TEEE Trans. on Signal Processing, vol. 48, No. 6, pp. 1637-1647, June 2000.
[8] S. Haykin, Adaptive Filter Theory, 3rd Ed. Prentice Hall, Prentice Hall, Englewood Cliffs, New Jersey, U.S.A. 1996.
[9] Y. Nesterov and A. Nemirovskii, Interior Point Polynomial Algorithms in Convex Programming. Philadelphia, PA: SIAM, 1993.
[10] G. R. Cooper and C. D. McGillem, Modern Communications and Spread Spectrum. New York: McGraw-Hill, 1986.
[11] S. J. Chern and C. C. Hung, “The QRD-Based Recursive Least-Squares Nonlinear Equalizer,” Kaohsiung Taiwan, 1997.
[12] S. J. Chern and C. Y. Sung, “The Performance of Hybrid Adaptive Beamforming Algorithm for Jammers Suppression,” IEEE Trans. on Antennas and Propagation, VOL. 42, NO. 9, pp. 1223-1232, Ste. 1994.
[13] S. A. Alshebeili*, A. M. Al-Qurainy, A. S. Al-Ruwais, “Nonlinear approaches for narrowband interference suppression in DS spread spectrum systems” Signal Processing 77, pp. 11-20, Jan. 1999.
[14] L. Garth and H. V. Poor, “ Narrowband interference suppression in implusive channels,” TEEE Trans. Aerosp. Electron. Syst., vol. 28, pp. 15-34, Jan. 1992.
[15] F. M. Hsu and A. A. Giordano, “Digital whitening techniques for improving spread-spectrum communications performance in the presence of narrow-band jamming and interference,” IEEE Trans. Commun., vol. COM-26, pp. 209-216, Feb. 1978.
[16] J. W. Keltchum and J. G. Proakis, ”Adaptive algorithms for estimating and suppressing narrow-band interference in PN spread-spectrum systems,” IEEE Trans. Commun., vol. COM-30, pp. 913-924, May 1982.
[17] L. M. Li and L. B. Milsten, “ Rejection of narrow-band interference in PN spread-spectrum systems using transversal filters,” IEEE Trans. Commun., vol. COM-30, pp. 925-928, May 1982.
[18] R. A. Iltis and L. B. Milsten, “Performance analysis of narrow-band interference rejection techniques in DS spread-spectrum systems,” IEEE Trans. Commun., vol. COM-32, pp. 1169-1177, Nov. 1984.