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研究生:甯君正
研究生(外文):Jiun-Cheng Ning
論文名稱:適用於雙時變通道之多輸入多輸出正交分頻分碼多重存取通訊之等化技術
論文名稱(外文):Equalizations for MIMO OFDM-CDMA Communication Over Doubly Selective Channel
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:通訊工程研究所
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:2010
畢業學年度:98
語文別:英文
論文頁數:57
中文關鍵詞:雙選擇性通道多輸入多輸出正交分頻多工分碼多重進接(MIMO OFDM-CDMA)頻率域每一頻道等化器(frequency per-tone equalizer)
外文關鍵詞:Doubly selective channelMIMO OFDM-CDMAfrequency-domain per-tone equalizer
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正交分頻多工分碼多重進接系統(OFDM-CDMA)因為實現容易和對頻率選擇性衰減通道有強力的抵抗力,以及CDMA適合多使用者系統的種種優點,所以近年來被受矚目。
而多輸入多輸出(MIMO)技術能在沒有增加額外的傳輸頻寬和發射端功率的前提下,顯著地提高資料的吞吐量和聯結的範圍。我們打算在本計劃將上述兩項技術結合,但由於參考傳統的線性區塊等化器(BLE)之後發現要降低它的設計和實現複雜度是非常困難的,因此在本論文中,我們打算提出在MIMO OFDM-CDMA系統中,以雙選擇性衰減通道為傳輸媒介的一個時間域等化器(TEQ)和一個頻率域等化 (PTEQ)。在設計等化器時,為了提昇頻寬效益,將考慮最普遍的情況也就是通道的延遲範圍(delay spread)大於所加的循環字首(cyclic prefix),如此一來將導致區塊間干擾(IBI)而隨之發生的都普勒效應接著造成載波間干擾(ICI)。本論文預計使用基本指數模型(BEM)來設計時間域等化器,其原因是能簡化等化器運算使得系統效能和實現與設計複雜度之間能做更有彈性的取捨。由於TEQ的作法是將所有載波上的信號結合一併做處理和最佳化,所以無法獲得使人滿意地表現。因此透過參考文獻,若能將TEQ轉換到頻率域中操作,即可獲得一個理想的PTEQ,近而得到較佳的系統效能。


Orthogonal frequency division multiplexing-code division multiple access (OFDM-CDMA) has arrested a lot of attention, owing to the simple implementation and powerful resistance to frequency-selective channels and the CDMA with the suitability for multiuser systems. The multi-input multi-output technique offers significant increases in data throughput and link range without additional bandwidth or transmit power. We intend to combine the above mentioned in this project. Due to the conventional block linear equalizer (BLE) reference at extremely low complexity of design as well as implementation is difficult. Therefore, we propose a time-domain and frequency-domain per-tone equalizers for MIMO OFDM-CDMA over doubly selective channels. We consider the most general case, where the cyclic prefix (CP) is smaller than channel delay spread which leads to inter-block interference (IBI). IBI in concurrent with the Doppler Effect spoils the orthogonality between subcarriers and, hence, leads to severe inter-carrier interference (ICI). We intend to develop a time-domain equalizer using the basis expansion model which allows us to turn a complicated equalization problem into an equivalent simpler equalization problem, containing only the BEM coefficients of both the doubly selective channel and the TEQ. Owing to the fact, TEQ optimizes the performance over all subcarriers in a joint mode; it doesn’t have a satisfied performance. An ideal frequency-domain per-tone equalizer (PTEQ) is then obtained by changing the TEQ operation to the frequency domain. Through record of references, we expect to obtain a better performance of the proposed equalization techniques in this project.

Content
摘 要 iv
Abstract v
Content vii
LIST OF FIGURES ix
Chapter 1 10
Introduction 10
Chapter 2 13
System Model 13
2.1 MIMO SYSTEM 15
2.2 OFDM-CDMA 18
2.3 MIMO OFDM-CDMA 20
Chapter 3 22
Channel Estimation and Basis Expansion Model 22
3.1 Channel Model 22
3.1.1 Basis expansion channel model 23
3.2 Channel estimation 26
3.2.1 MMSE channel estimation 27
3.2.2 BEM channel estimation 28
Chapter 4 31
Block Linear Equalizers 31
4.1 Block Data Model 31
4.2 Whitening Matched Filter 32
4.3 Zero-Forcing Block Linear Equalizer 34
4.4 Minimum Mean-Square-Error Block Linear Equalizer 36
Chapter 5 39
Time-domain Equalization 39
5.1 TV-FIR TEQ 40
5.2 Design of TIR and TEQ 43
Chapter 6 49
Frequency-Domain Per-tone Equalization 49
Chapter 7 54
Analysis of Complexity 54
Chapter 8 57
Simulation Results 57
Chapter 9 63
Conclusions 63
BIBLIOGRAPHY 65



BIBLIOGRAPHY
[1] Imad Barhumi and Marc Moonen., “Time-Varying FIR Equalization for MIMO Transmission over Doubly Selective Channels,” Global Telecommunications Conference, 2008, IEEE GLOBECOM 2008.IEEE, Nov.30 2008-Dec.4 2008.
[2] S. Hara and R. Prasad., “Overview of Multicarrier CDMA,” in Proc. IEEE Commun. Mag., pp. 126-133, Dec. 1997.
[3] I. Barhumi, G. Leus, and M. Moonen, “Time-domain and frequency-domain per-tone equalization for OFDM over doubly selective channels,” in Signal Process. (Special Section Signal Processing in Communications) vol. 84/11, pp. 2055-2066, 2004.
[4]. I. Barhumi, G. Leus, and M. Moonen, “Time-Varying FIR Equalization of Doubly Selective Channels,” IEEE Trans. Wireless Commun., vol. 4, pp. 202–214, Jan. 2005
[5]. Imad Barhumi, Geert Leus, and Marc Moonen., “Equalization for OFDM Over Doubly Selective Channels,” IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 54, NO. 4, APRIL 2006 1445
[6] Imad Barhumi, Geert Leus, and Marc Moonen, “Estimation and Direct Equalization of Doubly Selective Channels,” Hindawi Publish Corporation EURASIP Journal on Applied Signal Processing Volume 2006, Article ID 62831, Page 1-15.
[7] Xiaoli Ma, Georgios B. Giannakis, and Shuichi Ohno, “Optimal Training for Block Transmissions Over Doubly Selective Wireless Fading Channels,” IEEE Transactions on Signal Processing, VOL. 51, No. 5, MAY 2003.
[8] A. Klein, G. K. Kaleh, and P. W. Baier, “Zero forcing and minimum mean-square-error equalization for multiuser detection in code-division multiple-access channels,” IEEE Trans. Veh. Technol., vol. 45, pp. 276–287, May 1996.
[9] G. Ysebaert, K. V. Acker, M. Moonen, and B. D. Moor, “Constraints in channel shortening equalizer design for DMT-based systems,” Elsevier Signal Process., vol. 83, pp. 641–648, Mar. 2003.
[10] Naofal AI-Dhahir, and John M. Cioffi, “Efficiently Computed Reduced-Parameter Input-Aided MMSE Equalizers for ML Detection: A Unified Approach,” IEEE TRANS. ON INFORMATION THEORY, VOL. 42, NO. 3, MAY 1996
[11] A. Klein and P. W. Baier, “Linear unbiased data estimation in mobile radio systems applying CDMA,” ZEEE J. Select. Areas Commun., vol. 11, pp. 1058-1066, Sept. 1993.
[12] A. D. Whalen, “Detection of signals in noise”. New York Academic, 1971.
[13] G.Leus, I.Barhumi, and M.Moonen, “Low-complexity serial equalization of doubly selective channels,” in Proceedings of 6th Baiona Workshop on Signal Processing in Commumications, pp. 69-74, Baiona, Spain, September 2003.


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