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研究生:鄭勝韓
研究生(外文):Shen-Han Cheng
論文名稱:智慧型天線應用於多重使用者直序展頻分碼多工伴隨多重路徑衰減通道
論文名稱(外文):Smart Antennas for Multiuser DS/CDMA Communications in Mutipaht Fading Channels
指導教授:翁芳標翁芳標引用關係
指導教授(外文):Fang-Biau Ueng
學位類別:碩士
校院名稱:國立中興大學
系所名稱:電機工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2004
畢業學年度:92
語文別:英文
論文頁數:50
中文關鍵詞:分碼多工智慧型天線最小均方誤差遞回最小均方誤差
外文關鍵詞:CDMASmart AntennaLMSRLS
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在多重使用者分碼多工(Code division multiple access)通訊系統中,使用智慧型天線可增加範圍、可靠度及系統容量。此外,適應性波束合成技術可從接收到的訊號中移除不想要的雜訊及干擾。在本論文中,我門提出四個應用於多重使用者直序展頻分碼多工(Direct-sequence CDMA)環境伴隨多重路徑衰減通道的適應性天線接收架構。本論文同時考慮窄頻及寬頻適應性陣列接收架構。窄頻及寬頻適應性陣列接收機架構均使用最小均方誤差(Least mean square)及遞回最小均方誤差(Recursive least square)演算法來調整展頻碼係數。我們稱此架構為Wiener解碼濾波器。因為適應性波束合成器的權重和展頻碼是每訊符間更新一次,所以計算的複雜度非常低。比較新架構表現的模擬範例會被提出來。這些架構的分析也會被提出來。

Smart antennas, with spatial processing, used in code division multiple access (CDMA) multiuser communications can enhance range, reliability and capacity. Moreover, the adaptive beamforming technologies can remove unwanted noise and interference from the received signal. In this paper, we propose four adaptive antenna receiver structures for direct-sequence (DS) CDMA multiuser environment with multipath fading channels. Narrowband and wideband adaptive array receiver structures are considered in this paper. LMS and RLS algorithms are employed in both narrowband and wideband receiver structures to adjust the spreading code coefficients. We call these new schemes as Wiener code filters. The weights of the adaptive beamformer and the spreading code are updated every symbol interval, so the computational complexity is very low. Simulation examples are given to compare the performances of the proposed receiver structures. Analyses are also given for these structures.

Chinese Abstract i
English Abstract ii
Acknowledgments iii
Contents iv
List of Figures vi
Chapter 1:Introduction 1
Chapter 2:Introduction to Smart Antennas 5
2.1 Types of Smart antennas 5
2.2 Beamforming Schemes 7
2.3 Direction-Of-Arrival (DOA) Estimation 13
2.4 Adaptive Beamforming Algorithm 14
Chapter 3:System Model 16
Chapter 4:LMS-Based Algorithms 18
4.1 Narrowband Adaptive Antennas 18
4.2 Mean Square Error (MSE) Analysis 21
4.3 Narrowband Adaptive Antenna with Code Adjustment 22
4.4 MSE Analysis with Code Adjustment 24
4.5 Wideband Adaptive Antenna with Code Adjustment 25
Chapter 5:RLS-Based Algorithms 28
5.1 Weight Update Equations 28
5.2 Analysis of RLS Weight Update Equation 31
5.3 Code Update Equations 34
5.4 Analysis of RLS Code Update Equation 36
Chapter 6:Simulation Results 39
Chapter 7:Conclusions 47
Bibliography 48

Bibliography
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[4] Y. Ichikawa, K. Tomitsuka, S. OBOTE, and K. Kagoshima, " A Computation Reduced MMSE Adaptive Array Antenna Using Space-Temporal Simultaneous Processing Equalizer," IEICE Trans. Commun., vol. E85-B, no. 12, Dec. 2002.
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[6] L. M. Tuan, J. D. Park, G. W. Yoon, and J. W. Kim, "Projection-based LMS and MMSE algorithms for adaptive antennas," Proceedings ICII 2001 - Beijing, vol. 2, pp. 429-432, 2001.
[7] M. Chryssomallis, "Smart antennas," IEEE Antennas and Propagation Magazine, vol. 42, Issue 3, pp. 129-136, June 2000.
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[14] S.U. Pillai and B.H. Kwon, "Forward/backward spatial smoothing techniques for coherent signal identification," IEEE Trans. on Acoustics, Speech, and Signal Processing, vol. 37, Issue 1, pp. 8-15, Jan. 1989.
[15] S. Haykin, Adaptive Filter Theory, Prentice Hall, NJ, 2001.

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