臺灣博碩士論文加值系統

先前在正交分頻多工調變(OFDM)系統上，循環字首是不可少的一種被應用於通道估測以及抵抗多路徑通道的一種方法。在之前的論文中，有利用子空間(SS)盲目通道估測技術來估測通道來應用於不加循環字首的OFDM系統，其原理乃利用等效通道向量正交於接收訊號的雜訊子空間的特性，即可形成一齊次方程式，並利用最小平方法(least square)來計算出在有雜訊誤差下的最佳解，也有利用線性平滑運算(LS)來做盲目通道估測的方法應用於單傳多收(SIMO) OFDM的系統上。因為我們的OFDM系統不需要使用循環字首，因此比一般的OFDM系統擁有更高的頻寬效益。LS的方法運算量會比用SS的方法還少，但SS的方法效能卻會優於LS。我們在這篇論文中，提出一種利用區塊矩陣(Block matrix scheme)的方法分別對LS以及SS去做改善。區塊矩陣的方法不但使得LS和SS的效能變好，還使得它們的收斂速度變得更快。不僅如此，由於區塊矩陣使用比較小的接收訊號的自相關矩陣，因此區塊矩陣的運算量也會低於傳統的LS和SS方法。
我們還加上了空時碼(STBC)在OFDM系統中，使得天線多工的效能更加的明顯。由於加上STBC之後，我們依然使用不加循環字首的OFDM系統，因此我們依然保有更高的頻寬效益。我們利用STBC的特性使用forward-backward平均法，提出增加取樣資料的有效方法，以提高系統的效能。並且使用區塊矩陣的方法去改善STBC-OFDM系統，這兩個效能加強的方法可以同時使用並且增加效能。經由改善方法後的STBC-OFDM系統在位元錯誤率(BER)的效能表現上甚至優於傳統的OFDM以及補零的OFDM系統。

In practical orthogonal frequency-division multiplexing (OFDM) systems, cyclic prefix insertion and channel estimation are indispensable to achieve coherent demodulation. In previously, there have subspace (SS) and linear smoothing (LS) based blind channel estimation methods for single input multiple output(SIMO) OFDM systems over a time-dispersive channel are investigated. SS method has better performance than LS method, but LS method has lower computation than SS method. The two proposed methods do not require a cyclic prefix and thus leading to higher spectral efficiency. In this paper, we propose a performance enhance measure by block matrix scheme to improve SS and LS methods. Because we are to cope with smaller autocorrelation matrix than SS and LS, we obtain such that computational cost is reduced. Besides, the performance enhances measure by block matrix scheme convergence faster than conventions SS and LS.
In this paper, we also utilize the Alamonti’s Space-time block code (STBC) scheme and subspace (SS) channel estimation on the OFDM system without cyclic prefix. The STBC-OFDM system without cyclic prefix has higher diversity order than SIMO-OFDM system without cyclic prefix. We also propose two performances enhance methods, forward-backward averaging technique and block matrix scheme method, to improve SS channel estimation. The forward-backward technique doubles the data information without increasing computation. The block matrix scheme method not only makes convergence faster also has lower complex of operation by using smaller autocorrelation matrix than traditions (SS) channel estimation. After we are enhance the performance in STBC-OFDM system without CP, the performance even better than STBC-CP-OFDM and STBC-ZP-OFDM system. We will see it clearly in computer simulations.

Abstract(in Chinese)………………………………………………………………...….i
Abstract……………………………………………...…………………………….…..ii
Contents………………………………………………………………………….…...iii
List of Figures……………………………………………………………..…………..v
1 Introduction…………………………………...……………….……1
1.1. Overview of OFDM………………………………………………..……..3
1.2. Cyclic Prefix………………………………………………………………...4
1.3. Space-Time Block Coded…………………………………………………...5
1.4. Forward-Backward Averaging Technique…………………………………..7
1.5. Outline of this Thesis……………………………………………………….8
2 Basic Function……………………………………..……………….10
2.1. Single-Input Multiple-Output (SIMO) OFDM systems………….………..10
2.2. Blind Channel Estimation………………………………………...…….…13
2.3. Space-Time Block Coding (STBC) OFDM systems………………………15
3 Blind Channel Estimation for SIMO-OFDM Systems without
Cyclic Prefix…………...…………………………………………...18
3.1. System Model……………………...……..………………………………..18
3.2. Blind Channel Estimators………………….………………………………21
3.2.1 Linear Smoothing (LS) Method……………………………….……..21
3.2.2 Subspace (SS) Method………..……………..……………….……...23
3.3. Performance enhancement…….……...…………………………..……….25
3.3.1 Block matrix scheme for LS method………………………….…...25
3.3.2 Block matrix scheme for SS method………………………………30
3.4. Symbols Detection……………………………………………………….33
3.5. Simulations………………………………………………………………...34
4 Blind Channel Estimation for STBC-OFDM Systems without
Cyclic Prefix…………………………….………………………....48
4.1. System Model…………………………………………………….………..48
4.2. Subspace Blind Channel Estimation…………….………………………...50
4.3. Performance enhance………………………….………………..…………54
4.3.1 Forward-Backward averaging technique………………..…….…...54
4.3.2 Block matrix scheme for SS method………………………………54
4.4. Symbols Detection……………………………………………………...…56
4.5. Simulations………………………………………………………………...57
5 Conclusion…………………………………………………………68
References...…………………………………………………………….69
Appendix A………………..…………………………………………....75

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