臺灣博碩士論文加值系統

傳統的V-BLAST信號偵測，如迫零法(zero forcing)，可有效的偵測信號。若使用QR演算法可以減低系統上的運算量，但已估測的信號無法完全消除接收信號的干擾項導致信號偵測錯誤延伸的效應，因此我們導入一個接收端上使用偵測信號的遞迴式錯誤補償的方法來補償QR演算法所產生的錯誤延伸之效應。我們藉著估測和未估測信號之前的差異找出最小平方誤差，並且以遞迴式的方法來補償錯誤延伸所產生的誤差。透過數值模擬的分析結果，可以證實此系統可有效的補償錯誤延伸所產生的錯誤，而達到QR演算法更高的效益。

The conventional V-BLAST with Zero Forcing (ZF) used to detect signal available in MIMO OFDM systems. When performing QR algorithm, the consumption computation of systems can be reduced. But the drawback of QR algorithm is the effect of error propagation due to the back cancellation detector can not cancel entire interference in the received signal. Hence, we try to derive an iterative detect and decoding systems to mitigate the effect of error propagation by iterative compensation. By using the undetected and detected signals to find the minimum mean square error (MMSE) and perform the iterative error compensation to mitigate the interference of error propagation. Finally, we can obvious the performance of QR algorithm with iterative compensation better than original system.

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 Structure of Multiple-Input Multiple-Output System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1
2.1.1 MIMO System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1
2.2 Basic Principle of Space-Time Block Codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-3
2.2.1 Space-Time Block Codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-4
2.3 Receiver Detection for MIMO. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-6
2.3.1 Layered Space-Time Codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-6
2.3.2 Signal Detection Process for V-BLAST . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-7
2.3.3 Turbo-MIMO for Wireless Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-11
2.4 Orthogonal Frequency Division Multiplexing (OFDM) . . . . . . . . . . . . . . . . . . . . . . . . . . 2-13
Chapter 3 Algorithm for Error Propagation and Reduction and Data Detection Improvement in MIMO-OFDM System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-1
3.1 System Model of MIMO-OFDM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2
3.2 Improving V-BLAST with Error Compensation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-5
3.2.1 Enhanced V-BLAST . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-5
3.2.2 Data Detection with QR Decomposition. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-11
3.3 Data Detection with Precoding QR Decomposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-12
3.4 Iterative Detection and Decoding Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-15
Chapter 4 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1
4.1 Simulation Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1
4.2 Performance Simulation of the Detection Algorithms for MIMO . . . . . . . . . . . . . . . . . . . 4-1
4.3 Performance Simulation of the Detection Algorithms for IDD . . . . . . . . . . . . . . . . . . . . . 4-5
Chapter 5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-1
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R-1

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