李學智臺灣大學：電信工程學研究所曾建榮Tzeng, Jian-RongJian-RongTzeng2007-11-272018-07-052007-11-272018-07-052006http://ntur.lib.ntu.edu.tw//handle/246246/58925一般多天線輸入輸出系統的天線擺放方式，通常是在傳送與接收兩端皆採用垂直極化。因為正交極化具有好的隔離效果，在有直接波的環境下，鏈結兩端採用對稱的正交極化方式，通道容量會比傳統上的極化方式來得高。然而在沒有直接波的環境下，因為功率增益的減少，我們會得到相反的結果。 對多天線輸入輸出系統來說，雖然VBLAST是一個很有效率的偵測演算法，它的系統效能還是比最佳的ML演算法差得多。許多改進的演算法因此被提出，而我們實現並比較它們的表現。最後，我們提出了一個稱為『半軟性判斷VBLAST』(semi-soft decision VBLAST) 的新演算法。模擬結果證明，這個演算法的效能不僅比傳統的VBLAST好上許多，它也能輕易地和各種VBLAST還有其相關的演算法結合，以尋求更高的系統效能。 VBLAST-OFDM 可以把一般的頻率選擇衰落 (frequency-selective fading) 通道，轉變成適合使用VBLAST的雷利衰落 (Rayleigh fading) 通道。我們使用下一世代無線網路的規格—802.11n的通道模型作為模擬的通道，同時也考慮了通道估測的演算法。當傳輸天線的數量增加，不同天線間互相干擾的情況會變嚴重；此外在相關性通道內，歸零 (nulling) 動作沒辦法表現良好。雖然在獨立一致分佈 (independent and identical distribution) 通道內，增加天線數量可以提升系統效能，在相關性通道內卻不盡然。For a general MIMO system, we usually use the vertically co-polarized antenna arrays at both transmitter and receive ends. If we use cross polarization antenna scheme symmetrically in both ends, the capacity is higher than conventional antenna polarization scheme under the LOS condition due to the high isolation between orthogonal polarizations. However, in NLOS condition, the result is contrary because of the loss of power gain. VBLAST is an efficient detection algorithm for MIMO system, the performance, however, is still far from optimal ML algorithm. Therefore, several modified algorithm has been proposed and we implement them to compare their performance. Finally, we propose a new modified algorithm called semi-soft decision VBLAST. Simulation results show that our proposed algorithm not only outperform than conventional VBLAST considerably but also can be easily combined with any kind of VBLAST algorithms and their modified version to achieve more tremendous performance. VBLAST-OFDM is introduced to convert common frequency-selective fading channel into Rayleigh fading channel which is suitable for VBLAST. Channel model adopted by next-generation WLAN standard, 802.11n, is used in our simulation. Channel estimation algorithm is also considered. There is more interference when more antennas are used and the nulling operation cannot work well in the correlated channel. Consequently, in the correlated channel, using more antennas cannot guarantee the higher performance as what we can see in i.i.d. channel.Contents Abstract Ⅰ Contents Ⅲ List of Figures Ⅶ List of Tables ⅩⅡ Chapter 1 Introduction 1 Chapter 2 Correlation Properties and Capacity for MIMO Radio Channel 3 2.1 Introduction 3 2.2 Basic Concept of MIMO System 4 2.2.1 Channel Model 4 2.2.2 Capacity 5 2.2.3 Correlation Matrix 8 2.3 Experiment Description 10 2.3.1 MIMO Measurement System 10 2.3.2 MIMO Measurement Environment 11 2.4 Experiment Result and Analysis 15 2.4.1 Experiment for Different Polarization 15 2.4.2 Experiment for Different Antenna Spacing 30 Chapter 3 Performance Analysis of VBLAST Detection Algorithm under Rayleigh Fading Environment 35 3.1 Introduction 35 3.2 Space Time Block Code 36 3.3 Singular Value Decomposition 37 3.4 VBLAST 38 3.4.1 Introduction 38 3.4.2 System Description 39 3.4.3 ZF-VBLAST Detection Algorithm 40 3.4.4 MMSE-VBLAST Detection Algorithm 42 3.5 Performance Enhancement for VBLAST System 43 3.5.1 Introduction 43 3.5.2 PD-OSIC VBLAST 43 3.5.3 STBC-VBLAST 46 3.5.4 Proposed Semi-Soft Decision VBLAST 51 3.6 Simulation Result and Analysis 61 3.6.1 Simulation Setup 61 3.6.2 Sorted QR Decomposition 61 3.6.3 SISO System with Viterbi Soft Decision 62 3.6.4 PD-OSIC VBLAST 63 3.6.5 STBC-VBLAST 63 3.6.6 Proposed Semi-Soft Decision VBALST 64 Chapter 4 Performance Analysis of VBLAST-OFDM System 69 4.1 Introduction 69 4.2 Wireless Channel Characteristics and Channel Models 70 4.2.1 Introduction 70 4.2.2 Doppler Effect for Indoor Channel Model 71 4.2.3 Simulator of Narrowband and Wideband Fading Channel 73 4.3 Orthogonal Frequency Division Multiplexing 75 4.3.1 Introduction 75 4.3.2 System Description 76 4.4 VBLAST-OFDM System 80 4.4.1 System Description 80 4.4.2 Channel Estimation for VBLAST-OFDM System 82 4.4.2.1 Introduction 82 4.4.2.2 System Model 83 4.4.2.3 Channel Estimation 84 4.4.2.4 Performance Analysis of Channel Estimation 86 4.5 Simulation Result and Analysis 88 4.5.1 Simulation Setup 88 4.5.2 Simulation With Model A and Model B (Perfect CSI) 91 4.5.3 Simulation With Model C (Perfect CSI) 93 4.5.4 Simulation With Model B (Considering Channel Estimation) 94 Chapter 5 Conclusion 99 Reference 1012500921 bytesapplication/pdfen-US空間多工偵測多天線傳輸VBLASTMIMOspatial multiplexingdetectionthesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/58925/1/ntu-95-R93942115-1.pdf