在本論文中，我們使用修正型高斯小波為基底之多載波 (MC) 分碼多重存取 (CDMA) 系統經由結合程序 (combining process) 在瑞雷衰退通道中探討消除多重存取干擾 (MAI) 之問題。本論文的主要目的是提出一個新方法，運用以線性限制性常模 (LCCM) 結合強健性反向QR分解 (IQRD) 遞迴最小平方和(RLS)演算法，進一步提升以小波為基底之多載波多重存取系統與結合程序的系統效能。為了證明新演算法的優勢，將於不完美通道參數估測和近遠效應下作為探討。在通道不匹配環境下，我們提出的強健性線性限制性常模結合反向QR分解遞迴最小平方和演算法在輸出的干擾雜訊比和抑制MAI上都比線性限制性常模梯度演算法有較突出的表現。同樣地，在修正型高斯小波為基底之多載波分碼多重存取系統上也會比傳統的小波為基底之多載波分碼多重存取系統上會得較佳的效能。在通道不匹配和近遠效應環境下具有一定的強韌性。此外，強健性線性限制性常模結合反向QR分解遞迴最小平方和演算法比其他傳統演算法，如：線性限制性常模梯度演算法、最大比例組合 (MRC) 和盲目式適應性演算法，在MAI的抑制能力與位元錯誤率上獲得較佳的效能。

In this thesis, the problem of multiple access interference (MAI) suppression for the multi-carrier (MC) code division multiple access (CDMA) system, based on the multi-carrier modulation with modified Gaussian wavelet, associated with the combining process is investigated for Rayleigh fading channel. The main concern of this thesis is to derive a new scheme, based on the linearly constrained constant modulus (LCCM) criterion with the robust inverse QR decomposition (IQRD) recursive least squares (RLS) algorithm to improve the performance of the wavelet-based MC-CDMA system with combining process. To verify the merits of the new algorithm, the effect due to imperfect channel parameters estimation and near-far effect are investigated. We show that the proposed robust LCCM IQRD-RLS algorithm outperforms the conventional LCCM-gradient algorithm, in terms of output SINR, for MAI suppression under channel mismatch environment. Also, the performance of the modified Gaussian wavelet-based MC-CDMA system is superior to the one with wavelet-based MC-CDMA system. It is more robust to the channel mismatch and near-far effect. Moreover, the modified Gaussian wavelet-based MC-CDMA system with robust LCCM IQRD-RLS algorithm does have better performance over other conventional approaches, such as the LCCM-gradient algorithm, maximum ratio combining (MRC), and blind adaptation algorithm, in terms of the capability of MAI suppression and bit error rate (BER).

Acknowledgement i
Abstract ii
Content iii
List of Figures iv
Chapter 1 Introduction 1
Chapter 2 Wavelets and Filter Banks
2.1 Introduction 5
2.2 Discrete Wavelet with Two-Band Filter 6
2.2.1 Formulation of Discrete Wavelet Transform 6
2.2.2 Two-Channel Filter Bank 7
2.3 Wavelet Packet Division Multiplexer 10
Chapter 3 Linearly Constrained Constant Modulus(LCCM) Inverse QR Decomposition-RLS Algorithm for Modified Gaussian Wavelet-Based MC-CDMA Receiver
3.1 Introduction 17
3.2 Conventional MC-CDMA System with Combining Process 18
3.3 Modified Gaussian Wavelet Based MC-CDMA System with Combining Process 25
3.3.1 Modified Gaussian Wavelet 25
3.3.2 Wavelet Based MC-CDMA with Receiver with Modified Gaussian Wavele 28
3.4 Modified Gaussian Wavelet-Based MC-CDMA Receiver with Linearly Constrained Constant Modulus IQRD-RLS Algorithm 32
3.4.1 Direct Linearly Constrained Constant Modulus with IQRD-RLS algorithm 33
3.4.2 Robust LCCM IQRD-RLS algorithm 33
3.5 Computer Simulation Results 40
3.5.1 Perfect Channel Estimation Case 40
3.5.2 Channel Mismatch Case 41
Chapter 4 Conclusions 43
Appendix A 45
Appendix B 47
Appendix C 49
References 50

[1] Yee, N., J-P. Linnartz and G. Fettweis, “Multi-carrier CDMA in Indoor Wireless Radio Networks,” Proc. of IEEE PIMRC’93, Sept. 1993, Page(s): 109-113.
[2] Hara, S.,T-H. Lee and R.Prasad, “BER comparison of DS-CDMA and MC-CDMA for frequency Selective Fading Channels ”, Proc. of 7th Tyrrhenian International Workshop on Digital Communications, Sept.1995. Page(s): 3 –14.
[3] S. Hara and R. Prasad, “Overview of Multicarrier CDMA,” IEEE Commun. Mag., Dec. 1997, Page(s): 126–133.
[4] Richard van Nee and Ramjee Prasad, “OFDM Wireless Multimedia Communications”, Artce House, 2000.
[5] Suzuki, N.; Fujimoto, M.; Shibata, T.; Itoh, N.; Nishikawa, K. “Maximum likelihood decoding for wavelet packet modulation” Vehicular Technology Conference, 1999. VTC 1999 Fall. IEEE VTS 50th , Volume: 5 , 19-22 Sept. 1999 Pages:2895 - 2898 vol.5
[6] Kon Max Wong; Jiangfeng Wu; Davidson, T.N.; Qu Jin “Wavelet packet division multiplexing and wavelet packet design under timing error effects” Signal Processing, IEEE Transactions on, Volume: 45 , Issue: 12 , Dec. 1997
Pages:2877 - 2890
[7] Okamoto, E.; Iwanami, Y.; Ikegami, T. “Multimode transmission using wavelet packet modulation and OFDM” Vehicular Technology Conference, 2003. VTC 2003-Fall. 2003 IEEE 58th , Volume: 3 , 6-9 Oct. 2003
Pages:1458 - 1462
[8] Nikookar, H.; Prasad, R., “Multicarrier transmission with nonuniform carriers in a multipath channel”, Universal Personal Communications, 1996. Record., 1996 5th IEEE International Conference on , Volume: 2 , 1996 ,Page(s): 628 -632 vol.2
[9] Martin Vetterli and Jelena Kovacevic “Wavelet and Subband Coding”, (Prentice Hall PTR, Englewood Cliffs, New Jersey, 1995)
[10] PP. Vaidyanathan , ’’ Multirate Systems and Filter Banks”,( Prentice-Hall 1993 )
[11] 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, Jan. 1993, Page(s): 20-30.
[12] L. S. Resende, J. T. Romano, and M. G. Bellanger, “ A Fast Least-Squares Algorithm for Linearly Constrained Adaptive Filtering,” IEEE Trans. on Signal Processing, vol. 44, No. 5, May 1996.
[13] Jaquin Miguez and Luis Castedo, “ A Linearly Constrained Constant Modulus Approach to Blind Adaptive Multiuser Interference Suppression,” IEEE Communications Letters, Vol.2, No.8, August 1998.
[14] J.R. Treichler and B.G. Agee, “A New Approach to Mulitpath Correction of Constant Modulus Signals,” IEEE Transactions on Acoustics, Speech, and SignalProcessing, Vol. ASSP-31, April 1983, Page(s): 459-472.
[15] Tai-Yin Liao, “Multiuser Interference Cancellation in Multicarrier CDMA System with Constrained Adaptive Inverse QRD-RLS Algorithm”, Master thesis, NSYSU, Kaohsiung, ROC, 2001.
[16] J. Miguez, and L. Castedo, “A Linearly Constrained Constant Modulus Approach to Blind Adaptive Multiuser Interference Suppression,” IEEE Commun. Letters, vol.2, No. 8, Aug. 1998
[17] C. Y. Chang and S. J. Chern, “Adaptive Linearly Constrained Inverse QRD-RLS Beamformer for Multiple Jammers Suppression,” The Third IEEE Signal Processing Workshop on Signal Processing Advances in Wireless Communications, Westin Resort, March 20-23, 2001, Page(s): 294-297.
[18] Daubeciesh, I. “Ten lectures on wavelets”, CBMS series. Philadelphia: SIAM, 1992.
[19] Mallat S.G., “A Theory for Multiresolution Signal Decomposition: The Wavelet Representation” Pattern Analysis and Machine Intelligence, IEEE Transactions, VOL: 11 NO. 7. July 1989
[20] Davidson, T.N.; Schott, A.-J.; Wong, K.M. “Branch-hopped wavelet packet division multiplexing” Acoustics, Speech, and Signal Processing, 1998. ICASSP '98. Proceedings of the 1998 IEEE International Conference on ,Volume: 6 , 12-15 May 1998 Pages:3233 - 3236 vol.6 Pages:674 – 693
[21] Wong, K.M.; Jiangfeng Wu; Davidson, T.N.; Qu Jin; Ching, P.-C. “Performance of wavelet packet-division multiplexing in impulsive and Gaussian noise” Communications, IEEE Transactions on, Volume: 48, Issue: 7, July 2000 Pages:1083 - 1086
[22] R. R. Coifman, Y. Meyer, and M. V. Wickerhauser. “ Wavelet analysis and signal processing“ In M. B. Ruskai et al, editor, Wavelets and their Applications, page 153-178. Jones and Barlett, Boston, 1992.
[23] Weimin Yang; Guangguo Bi; Yum, T.-S.P.; “A multirate wireless transmission system using wavelet packet modulation” Vehicular Technology Conference, 1997 IEEE 47th , Volume: 1 , 4-7 May 1997 Pages:368 - 372 vol.1
[24] Yu, X.; Zhang, X.; Bi, G. “Performance of an MC-CDMA system based on the complex wavelet packet and pre-equalisation technique “Communications, IEE Proceedings , Volume: 151 , Issue: 2 , April 2004 Pages:152 - 156
[25] Madhukumar, A.S.; Chin, F.; Premkumar, A.B. “Performance enhancement of a wavelet based multicarrier DS-CDMA system through multistage interference cancellation” Signals, Systems and Computers, 2000. Conference Record of the Thirty-Fourth Asilomar Conference on , Volume: 2 , 29 Oct.-1 Nov. 2000
Pages:1421 - 1425 vol.2
[26] K. Fazel, “Performance of CDMA/OFDM for mobile communication system” in IEEE, 2nd ICUPC, Proc. October 1993.
[27] Tat M. Lok, Tan F. Wong and James S. Lehnert, “Blind Adaptive Signal Reception for MC-CDMA Systems in Rayleigh Fading Channels” IEEE Trans. on Commun., vol. 47, No. 3, March 1999 ,Page(s): 464-471.
[28] Dovis, F.; Mondin, M.; Daneshgaran, F. “The modified Gaussian: a novel wavelet with low sidelobes with applications to digital communications” Communications Letters, IEEE , Volume: 2 , Issue: 8 , Aug. 1998 Pages:208 - 210
[29] Haykin, “Adaptive Filter Theory”, 3rd, Englewood Cliffs, NJ: Prentice Hall, 1996.
[30] S. J. Chern, C. Y. Chang and T. Y. Liao, “Adaptive Multiuser Interference Cancellation with Robust Constrained IQRD-RLS Algorithm for MC-CDMA System,” IEEE ISPACS2001