(3.238.173.209) 您好!臺灣時間:2021/05/16 20:12
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:李建忠
研究生(外文):Chien-Chung Li
論文名稱:多輸入多輸出正交分頻多工系統中以錯誤補償方法執行訊號偵測
論文名稱(外文):An Error Compensation Approach for Signal Detection of MIMO-OFDM Systems
指導教授:郝敏忠
指導教授(外文):Miin-Jong Hao
學位類別:碩士
校院名稱:國立高雄第一科技大學
系所名稱:電腦與通訊工程所
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:2009
畢業學年度:97
語文別:英文
論文頁數:78
中文關鍵詞:錯誤補償多輸出多輸入系統正交分頻多工
外文關鍵詞:MIMOError CompensationOFDM
相關次數:
  • 被引用被引用:0
  • 點閱點閱:114
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
  傳統的V-BLAST信號偵測演算法,如最小均方誤差(MMSE)和迫零法(Zero Forcing, ZF)在接收端可有效的偵測信號,但需耗費大量的計算量,我們可以使用QR與SVD分解演算法來降低逆運算所造成的運算複雜度。在論文中我們在系統前端實行ZF、QR、SVD和enhanced [5]等方法,並且我們提出一種近似卡曼修正(Kalman-Alike)的方法與遞迴式錯誤補償(IDD)[5]方法作比較,兩者主要適用於減輕因錯誤延伸(error propagation)所導致的判斷錯誤,Kalman-Alike是找到使誤差交相關函數(error covariance)為最小的Kalman-Alike gain,進而調整更新方程式使其達到更準確的 ,來達到降低錯誤率的目的。我們模擬接收信號經過ZF,MMSE,QR,SVD等偵測方式的解調後,再組合IDD或Kalman-Alike方法來補償錯誤延伸導致的判斷錯誤。由模擬可觀察出使用Kalman-Alike方式可以有效改善系統特性,與IDD相比也只消耗較少的運算複雜度。
  The conventional V-BLAST have Minimum Mean Square Error (MMSE) and Zero Forcing (ZF) schemes for detecting signals in the receiver of MIMO-OFDM system, which consume generally a large number of computations. We can use QR and SVD schemes to decrease the computations due to inversion matrix. In the thesis, we employ the QR, ZF, SVD and enhanced [5] V-BLAST as a front-end receiver for MIMO-OFDM systems. We then propose a Kalman-Alike scheme in comparison with the Iterative Detect and Decoding (IDD) for mitigate the signal decision error due to error propagation effect. The Kalman-Alike scheme applied the gain for minimizing the error covariance. Which is used for adjusting linear equation to find the more accurate decision signal , and achieve the goal of reducing the bit error rate (BER) performance effectively. We simulate the receiver signal after the detection of ZF, MMSE, QR and SVD methods, which are compensated for error propagation by IDD and the Kalman-Alike approach. From the simulation, we can observe that the Kalman-Alike can improve the system performance, which also consumes less computation in comparison with the IDD approach.
Abstract in Chinese . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i
Abstract in English . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
Acknowledgment in Chinese . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
List of Figures and Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi
Chapter 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1
Chapter 2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1
2.1 MIMO System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1
2.2 Spatial Multiplexing . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 2-4
2.2.1 Spatial Multiplexing without Channel Feedback (Open-Loop). . . . . 2-4
2.2.1.1 Optimal Decoding : Maximum-Likelihood Detection . . . . . . 2-5
2.2.1.2 Linear Detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-5
2.2.1.3 Interference cancellation : BLAST . . . . . . . . . . . . . . . . . . . . . 2-6
2.2.2 The Advantage of Channel Knowledge . . . . . . . . . . . . . . . . . . . . . . . 2-8
2.2.2.1 Precoding and Postcoding with SVD. . . . . . . . . . . . . . . . . . . . 2-8
2.3 Spatial Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-10
2.3.1 Receive Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2-10
2.3.1.1 Selection Combining. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-11
2.3.1.2 Maximal Ratio Combining. . . . . . . . . . . . . . . . . . . . . . . . . . . 2-12
2.3.2 Transmit Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-13
2.3.2.1 Open-Loop Transmit Diversity. . . . . . . . . . . . . . . . . . . . . . . . 2-14
2.3.2.1.1 Space-Time Block Codes (Alamouti Code) . . . . . . . . 2-15
2.3.2.2 Closed-Loop Transmit Diversity. . . . . . . . . . . . . . . . . . . . . . .2-17
2.3.2.2.1 Transmit Selection Diversity . . . . . . . . . . . . . . . . . . . .2-18
2.3.2.2.2 Linear Diversity Precoder. . . . . . . . . . . . . . . . . . . . . . 2-19
Chapter 3 Error Propagation and Signal Detection Improvement in MIMO-OFDM
System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . 3-1
3.1 System Model of MIMO-OFDM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2
3.2 Signal Detection with QR Decomposition. . . . . . . . . . . . . . . . . . . . . . . . . .3-5
3.3 Signal Detection with Singular Value Decomposition (SVD) . . . . . . . . . . .3-7
3.4 Improving Error Propagation of V-BLAST with Error Compensation . . . 3-11
3.4.1 Enhanced V-BLAST . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-11
3.4.2 Iterative Detection and Decoding Process (IDD) . . . . . . . . . . . . . . . 3-21
3.4.3 Kalman-Alike Aproach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-25
Chapter 4 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1
4.1 Simulation Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1
4.2 Performance of different Detection Algorithms in MIMO-OFDM system.4-1

4.3 Performance of the Detection Algorithms for IDD and Kalman-Alike in
MIMO-OFDM system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-5
Chapter 5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-1
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R-1
[1].G. J. Foschini, “Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas,” Bell Labs. Tech. J., vol. 1, pp. 41–59, 1996.
[2].Siavash M. Alamouti, “A Simple Transmit Diversity Technique for Wireless Communications,” IEEE J. Select. Areas Commun., pp. 1451-1458, Oct. 1998
[3].Qi Ling, Tongtong Li, “Efficiency Improvement for Alamiuti Codes,” IEEE Trans. Information Sciences and Systems., pp. 569-572, Mar. 2006.
[4].P.W Wolniansky, G.J. Foschini, G.D. Golden, R.A. Valenzuela, “V-BLAST: an architecture for realizing very data rates over the rich-scattering wireless channel,” in Proc. URSI Int. Symp. Signals, Systems, Electronics., pp. 295-300, Oct. 1998.
[5].Henuchul Lee, Byeongsi Lee, Inkyu Lee, “Iterative detection and decoding with an improved V-BLAST for MIMO-OFDM systems,” IEEE. Selected Area in Communications., Vol. 24, Issue 3, pp. 504-513, Mar. 2006.
[6].Jeffrey G. Andrews, Arunabha Ghosh, Rias Muhamed, “Fundamentals of WiMAX Understanding Broadband Wireless Networking”, PRENTICE-Hill, 2007.
[7].Branka Vucetic and Jinhong Yuan, “Space-Time Coding,” 1st ed, England: Wiley, 2003.
[8].Henuchul Lee, Inkyu Lee, “New Approach for Error Compensation in Coded V-BLAST OFDM Systems,” IEEE Trans. Communications., Vol. 55, Issue 2, pp. 345-355, Feb. 2007.
[9].X. Li, H. Huang, G.J. Foschini, R.A. Valenzuela, “Effects of iterative detection and decoding on the performance of BLAST,” IEEE. Global Telecommunications Conference., Vol. 2, pp. 1061-1066, Dec. 2000.
[10].H. Lee and I. Lee, “New Approach for Coded Layered Space-Time Architecture for MIMO-OFDM systems, ” in Proc. of ICC, pp. 608, 612, May 2005.
[11].A. M. Tonello, “Space-time bit-interleaved coded modulation with an iterative decoding strategy, ” in Proc. of IEEE VTC, pp. 473-478, September 2000.
[12].X. Wang and H. V. Poor, “Iterative (turbo) soft interference cancellation and decoding for coded CDMA,” IEEE Transactions on Communications, pp. 1046-1061, July 1999.
[13].X. Li, H. Huang, G. Foschini, and R. A. Valenzuela, “Effects of Iterative Detection and Decoding on the Performance of BLAST,” in Proc. IEEE GLOBECOM, pp. 1061-1066, December 2000.
[14].J. G. Proakis, Digital Communications. Fourth Edition, McGraw-Hill Series in Electrical and Computer Engineering, 2001.
[15].T.M.Schmidl, D.C.Cox, "Robust Frequency and Timing Synchronization for OFDM, IEEE Tran. Commun. , pp. 1613-1621, Dec. 1997.
[16].S.M.Kay, Fundamentals of Statistical Signal Processing: Estimation theory, Prentice-Hall, Englewood Cliffs, New Jersey,1993.
[17].Jenn-Kaie Lain, OFDM課程講義, Dept. of Eletronic National Yunlin University of Science & Technology,2004.
[18].M. Morelli and U. Mengali,”An Improved Frequency Offset Estimator for OFDM Applications”, IEEE Commun. Letter ,1999.
[19].Simon Haykin , COMMUNICATION SYSTEM, 2001.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊