蘇炫榮臺灣大學：電信工程學研究所黃家毅Huang, Chia-YiChia-YiHuang2007-11-272018-07-052007-11-272018-07-052007http://ntur.lib.ntu.edu.tw//handle/246246/58648傳送與接收波束技術是充分發揮多通道系統多樣性的一種便易技術，然而要達到最佳波束的效能就必須讓傳送端知道完整的通道資訊或是波束向量資訊，而兩者都難以實現，因此，從接收端必須將通道資訊回傳給傳送端，但是此回傳的通道頻寬是有限的，所以量化通道資訊就變得不可或缺，這篇論文討論了量化的技術。 有了波束技術，原本的矩陣通道可以被轉換成數個平行的子通道，由於量化，回傳到傳送端的通道資訊就變得不完美，也因此在平行通道間會出現對彼此的干擾，使用一種將此干擾加入考量的能量配置來增加所有子通道的平均干擾噪聲比。 可適性調變編碼應用在每個子通道中，每個子通道中的調變編碼方案是根據各子通道的干擾噪聲比來決定，而不同方案之間的分界點會適應性地根據混合自動重複請求而調整來增加傳輸量，因此藉由較好的量化、更貼近實際的能量配置、以及搭配調整分界點的可適性調變編碼來使多通道系統的總傳輸量達到最大。Transmit beamforming and receive combining are simple methods for exploiting the significant diversity that is available in multiple-input multiple-output (MIMO) wireless systems. Unfortunately, optimal performance requires either complete channel state information (CSI) or knowledge of the optimal beamforming vector; both are hard to realize. Thus, the feedback of CSI from the receiver to the transmitter is needed. Nevertheless, the feedback bandwidth is limited, and the quantization of feedback CSI is necessary. The quantization methods are studied in the thesis. With beamforming, the matrix channel can be transformed into several parallel subchannels. Because of the quantization, the CSI at transmitter is imperfect, and there exists some interference between different parallel channels. A power allocation that takes the interference into consideration besides the noise is used to increase the mean signal-to-interference-plusnoise-ratio (SINR) of all subchannels. Adaptive modulation and coding (AMC) is applied to each parallel subchannel. The modulation and coding scheme (MCS) in each parallel channel is decided by its SINR, and the thresholds of different MCSs are adaptively adjust by hybrid automatic repeat-request (HARQ) to maximize the throughput. Thus, by better quantization, more practical power allocation, and AMC with threshold adjustment, the total throughput of the MIMO channel is maximized.1 Introduction 6 1.1 Background..................................... 6 1.2 Motivation......................................7 1.3 Outline.........................................8 2 Multiple-input Multiple-output (MIMO) channel 9 2.1 System Model ...................................9 2.2 Beamforming ....................................9 3 Beamforming 12 3.1 Singular Value Decomposition...................12 3.2 Quantization ..................................13 3.3 Random Vector Quantization (RVQ)...............13 3.4 Grassmannian Beamforming.......................15 3.5 Random Unitary Matrix Quantization (RUMQ)......17 3.6 Dispersive Unitary Matrix Quantization (DUMQ)..19 3.7 Quantization Feedback with Nonzero Delay.......21 4 Power Allocation 23 4.1 Regular Waterfilling...........................23 4.1.1 Capacity of AWGN Channel...................23 4.1.2 Multi-channel transmission system..........24 4.2 The Power Allocation...........................27 4.3 Comparison.....................................31 4.4 Quantization of power allocation...............33 5 Adaptive Modulation and Coding (AMC) System 37 5.1 AMC System.....................................37 5.2 Hybrid Auto Repeat Request (HARQ)..............41 5.3 Thresholds Adjustment of AMC System by HARQ....42 5.4 MIMO Channel with AMC System...................46 6 Conclusion 52en-US多天線通道動態調變編碼波束MIMOAMCbeamformingthesis