臺灣博碩士論文加值系統

摘 要
近年來，由於傳輸資料量的暴增，且在頻寬尚未大幅增加的情形下，新ㄧ代的行動通訊技術必須擁有更高的頻寬效益，並能同時提供較低的錯誤率，才能夠符合新的需求。正交分頻多工傳輸系統(orthogonal frequency division multiplexing，OFDM)在無線通訊系統上佔有相當重要的地位，因為OFDM系統採用快速傅立葉變換(fast Fourier transform，fft)做為調變技術，降低了製作上的複雜度，OFDM同時也插入保護區間，有效的解決了多重路徑下造成的符碼間干擾(inter-symbol interference，ISI)，使得近幾年來OFDM技術逐漸受到重視並且也因此快速發展。
由於可以在不需要增加頻寬或總發射功率的情況下，大幅增加系統的資料量及傳送距離，多重輸入多重輸出(multiple-input multiple-output，MIMO)為無線通訊上一項重要的應用技術。
空時區塊碼則(space time block code，STBC)可以架構在多輸入多輸出系統上，為一種優越的傳送分集塊狀編碼。在本論文之中，我們結合時空碼與正交分頻多工，並考慮在多輸入多輸出系統下，探討通道的估測，在已知及未知的情況下對整體通訊效能的影響。我們利用STBC本身的編碼方式，在本論文中提出新型STBC訓練序列，並加以比較。
論文中，除了對未知通道補償下和通道已知的情況做出分析，而我們使用的方法是先傳輸我們的新型訓練序列，利用STBC的特性解碼估測出通道響應，再使用內插法估測出中間缺的響應值，用來補償下一個訊號，做出修正。
本論文所提出的新型STBC訓練序列擁有和一般Alamouti Code 不相同的週期性以及對稱性，解碼方式能同時兼顧解碼的低複雜度以及用於通到估測時的效能表現良好。

Abstract
In recent years, due to the increase of transmission material quantity and on the basis of narrow in bandwidth , new motion mechanics of communication must have more bandwidth efficiency and provide less wrong rate in order to meet recent requirement. Orthogonal frequency division multiplexing(OFDM) plays an important role in wireless communication systems because it utilizes the Fast Fourier Transform as modulation technique to reduce production complex and uses guard interval to combat the inter-symbol interference in the transmit symbols. These make OFDM important.
Duo to the abilities to provide high data rate and transmission distant without increasing bandwidth or total power, the multiple-input multiple-output (MIMO) is a promising technology in the wireless communication systems.
Space-time block code (STBC) is a great transmit diversity technique, which can set up in MIMO system. In this paper, we combine STBC with OFDM and take the influence of communication efficiency under MIMO system into consideration. We use STBC coding in training sequence which is mentioned in this paper. We also use STBC construction, the method is as follow.
In this paper, in addition to making analysis on the condition of unknown channel and known channel, we put training sequences and utilize the STBC to predict channel response, and then we use interpolation to predict absent channel response in order to compensate next message and correct them.
The new type of STBC training sequences in this paper equips with periodicity
and symmetry which is different from the normal Alamouti Code, and decode method can achieve low decoding complexity and great efficiency in channel estimation at the same time.

指導教授推薦書
口試委員會審定書
授權書.................iii
誌謝..........iv
摘要......................v
Abstract........... .........vi
第一章 簡介....................1
1.1 引言............................1
1.2 研究動機與目的...............3
1.3 論文架構.................3
第二章 正交分頻多工原理與模型介紹.............4
2.1 正交分頻多工系統發展史和應用..........4
2.2 正交分頻多工 訊號模型................5
2.2.1 正交分頻多工的正交性..............9
2.2.2 循環字首(Cyclic Prefix)...........12
2.2.3 正交分頻多工系統上遇到的問題........13
第三章 STBC MIMO-OFDM 系統....................17
3.1 多重輸入多重輸出(MIMO)的歷史............17
3.2 多重輸入多重輸出(MIMO)訊號模型........19
3.3 無線傳輸通道介紹......................20
3.3.1通道容量..........................20
3.3.2通道環境.......................21
3.4 Alamouti 所提出的編碼...............23
3.5多重輸入多重輸出結合正交分頻多工系統和空時區塊碼.......27
第四章 MIMO-OFDM的通道估測技術.........29
4.1 正交分頻多工通道估測.................29
4.2領航訊號..............................32
4.3內插法..................35
第五章 以新型訓練序列為基礎的通道估測演算法.........38
5.1 傳統的STBC通道估測方法................38
5.2 所提出的新式STBC訓練序列架構..........41
5.3所提出的新型STBC通道估測演算法.........48
第六章 模擬結果與討論..................49
6.1所提出新型空時區塊碼的模擬通道環境..........49
6.2 所提出訓練序列的解碼模擬結果...............52
6.3通道估計演算法在AWGN與多重路徑通道下的模擬結果......54
6.3.1模擬環境為通道變化............54
6.3.2模擬環境為通道固定..........57
6.3.3模擬結果討論...........59
第七章 結論..............60
參考文獻.............61

圖片目錄
圖2.1 為FDM(a)與OFDM(b)的頻寬使用率............6
圖2.2 早期OFDM傳送端示意圖..................6
圖2.3 OFDM系統傳送與接收的架構圖............8
圖2.4 (a)為QPSK調變(b)為16QAM調變............8
圖2.5 保護區間為零的情況下ICI產生.............9
圖2.6 OFDM(a)頻率正交圖(b)時域正交圖.........10
圖2.7 具有循環字首的正交分頻多工符元........12
圖2.8 循環字首的方式架構.............13
圖2.9 多重路徑干擾....................14
圖3.1 MIMO系統架構圖...................19
圖3.2 通道種類，(a)訊號之符號週期，(b)傳送訊號之頻寬......22
圖3.3 為Alamouti編碼架構圖.............24
圖3.4 兩根傳送天線與一根接收天線示意圖..........25
圖3.5 (a)STBC的傳送端系統(b)MIMO-OFDM結合STBC架構........27
圖4.1 領航訊號的排列，黑色為領航訊號，白色為資料.......33
圖4.2 (a)Block type (b)Comb type ，顏色的為領航訊號，白色為資料...34
圖4.3 使用領航訊號於通道估測示意圖...........35
圖4.4 ㄧ階線性內插..........................36
圖4.5 二階線性內差.....................37
圖5.1 2ISO的架構圖......................38
圖5.2 時間上週期的特性.................39
圖5.3 新型空時編碼在頻率上的編排方式...........41
圖5.4 時域上的正交分頻多工符元示意圖...........43
圖5.5 調整過後新型的空時區塊編碼架構.........44
圖5.6 調整過後新型態時域上的正交分頻多工符元示意圖....45
圖5.7 接收天線一收到的正交分頻多工訊號示意圖........45
圖6.1 QPSK MIMO-OFDM...........53
圖6.2 16-QAM MIMO-OFDM.........54
圖6.3 在reduced typical urban通道下的錯誤率..........55
圖6.4 在 typical urban通道下的錯誤率................55
圖6.5 在 reduced bad urban通道下的錯誤率.............56
圖6.6 在bad urban通道下的錯誤率.................56
圖6.7 在reduced typical urban通道變化下的錯誤率........58
圖6.8 在bad urban通道變化下的錯誤率...........58

表目錄

表3.1 MIMO標準以及它們相應的技術........19
表6.1 Reduced Typical Urban參數表.......50
表6.2 Typical Urban參數表..............50
表6.3 Reduced Bad Urban參數表..........51
表6.4 Bad Urban參數表...............51

[1]WiMAX Forum, “Mobile WiMAX—Part 1: A technical
overview and performance evaluation,” June 2006.
[2]S. M. Alamouti, “A simple transmitter diversity
scheme for wireless communications,” IEEE J. Sel.
Areas Commun., vol. 16, no. 8, pp. 1451-1458,
Oct. 1998.
[3]B. Lu and X. Wang, “Space-time code design in OFDM
systems”, IEEE Global Telecommu. Conference, vol. 2,
pp. 1000-1004, Dec. 2000.
[4]Weistein. S and Ebert. T, ”Data Transmission by
Frequency-Division Multiplexing Using the Discrete
Fourier Transform,” IEEE Trans. Commun. Vol. 19,
pp.628-634, Oct. 1971.
[5]R. Knopp and H. Leib, “M-ary coding for the
noncoherent AWGN channel,” IEEE Trans. Inform.
Theory, vol. 40, pp. 1968-1984, Nov. 1994.
[6]A. Stamoulis, S. N. Diggavi, N. Al
Dhahir, “Intercarrier interference in MIMO
OFDM,” IEEE Trans. Signal Processing, vol. 50,
no. 10, October 2002.
[7]J. Heiskala and J. Terry, OFDM Wireless LANs: A
Theoretical and Practical Guide Indianapolis,
IN: Sams Publishing, 2002.
[8]H. Qiu, Y. Ariura, H. Qzaki, ”Optimal circular
interpolation for plane curve
contours” , IEEE International Conference,
page 1279-1284, vol. 2, October 1995.
[9]H.-K. Song, Y.-h. You, J.-H. Paik, and Y.-S.
Cho, “Frequency-Offset Synchronization and
Channel Estimation for OFDM-Based Transmission,”
IEEE Commun. Lett, vol. 4, pp. 95-97, Mar. 2000.
[10]X. Li and L. J. Cimini, Jr., “Effects of Clipping
and Filtering on the
Performance of OFDM,” IEEE Communication Letter,
Vol. 2, pp. 131-133,May 1998.
[11]R. van Nee, “OFDM Codes for Peak-to-Average Power
Reduction and Error Correction,”
IEEE Global Telecommunication Conference,
Vol. 1, pp. 740-744,
Nov. 1996.
[12]S.-Y. Ramin and K. Tadenusz “Challenges in the
Design of Next Generation WLAN Terminals,” in
Proc. of Canadian Conference on Electrical and
Computer Engineering (CCECE 2007), pp.1483-1486,
April 2007.
[13]T.S. Rappaport, “Wireless Communications”,
Prentice-Hall, 1999.
[14]H. Yang, “A road to future broadband wireless
access: MIMO-OFDM-based air interface,”
Bell Labs Syst. Tech. J., vol. 1, pp. 41-59,
Autumn 1996.
[15]J. G. Proakis, Digital Communications, 3rd ed.,
McGrawHill, New York, 1995
[16]B. Sklar and E. Okamoto, “Rayleigh fading
channels in mobile digital communication systems
.I. Characterization,” IEEE Communications
Magazine, vol. 35, pp. 90-100, July 1997.
[17]J. Yue, K. J. Kim, J. D. Gilbson and R. A.
Iltis, ”Channel estimation and data
detection for MIMO-OFDM systems,” in Proc. IEEE
GLOBECOM, vol. 2, 2003, pp. 581-585.
[18]V. Tarokh, H. Jafarkhani, and A. R. Calderbank,
“Space-time block codes from orthogonal designs,”
IEEE Trans. Inform. Theory, vol. 45,
pp. 1456–1467, July 1999.
[19]A. F. Naguib and R. Calderbank, “Space-time
coding and signal processing for high data rate
wireless communications,” Wirel. Commun.
Mob. Comput., pp.13-34, 2001.
[20]A. J. Paulraj and C. B. Papadias, “Space-time
processing for wireless communications,”
IEEE Signal Processing Magazine, vol. 14,
pp. 49-83, Nov. 1997.
[21]Yi Gong and Khaled Ben Letaief, Fellow, “Low
Complexity Channel Estimation for Space–Time
Coded Wideband OFDM Systems.” IEEE Trans. on
Wireless Commun.vol. 2, no. 5, pp. 876-882 Sep.
2003.
[22]S. Boumard, ”Novel noise variance and SNR
estimation algorithm for wireless MIMO OFDM
systems,” in Proc. IEEE GLOBECOM, vol. 4, 2003,
pp.1330-1334.
[23]D. Wang, G. Zhu and Z. Hu, ”Optimal pilots in
frequency domain for channel estimation in
MIMO-OFDM systems in mobile wireless channels,”
in Proc. IEEE Veh. Technol. Conf., May 2004, pp.
608-612.
[24]Y. Qiao, S. Yu, P. Su and L. Zhang, ”Research
on an iterative algorithm of LS channel
estimation in MIMO OFDM systems,” IEEE
Trans. Broadcasting, vol.51, no. 1, pp. 149-153,
Mar. 2005.
[25]S. Balasubramanian, B. B. Farhang, and V. J.
Mathews, ”Pilot embedding for channel estimation
and tracking in OFDM systems,” in Proc. IEEE
Global Telecommunications Conf, 2004, pp.
1244 - 1248.
[26]D. R. Pauluzzi and N. C. Beaulieu, ”A Comparison
of SNR Estimation Techniques for the AWGN Channel,
”IEEE Trans. Commun., vol. 48, pp.1681-1691, Oct.
2000
[27]C. Y. Wong, R. S. Cheng, K. B. Lataief, R. D.
Murch, “Multiuser OFDM with Adaptive Subcarrier,
Bit, and Power Allocation,” Selected Areas in
Communications, IEEE Journal on vol. 17,issue 10,
pp.1747-1758, October 1999.
[28]Simon Haykin, communication system, 4th edition,
John Wiley & Sons INC, 2000.