鐘嘉德臺灣大學:電信工程學研究所陳重亨Chen, Chong-HengChong-HengChen2010-07-012018-07-052010-07-012018-07-052009U0001-1808200900534600http://ntur.lib.ntu.edu.tw//handle/246246/188363因為合作通訊可以提供空間分集以及增加無線通訊傳輸上的可靠性，可說是一個非常有潛力的技術。在多數關於中繼系統的研究分析中，都是假設在接收端對通道的資訊是完美已知的，很少研究著手於通道估計的議題上，然而通道估計在中繼系統中是一個非常重要的技術。在此篇論文中，我們考慮了一個以正交分頻多工為基礎的放大與前傳的中繼系統。此篇論文中，分成三個主題。在第一個主題中，我們考慮一個具有緩慢衰減通道的多數中繼器系統，符合最小平方及最小均方誤差的最佳訓練序列準則分別被提出來，透過模擬，所提出的最佳訓練序列表現的比其他訓練序列都要來的理想。在第二個主題中，我們考慮一個具有快速衰減通道的單一中繼器系統，我們提出了三個時域虛擬領航信號的演算法，所有提出的方法不僅可以大大地改善通道估計的效能，且表現的比張教授所提出的方法還要更加理想。在最後一個主題中，一個具有快速衰減通道的單一中繼器系統仍然是被我們所考慮的，我們提出了一個適應性虛擬領航信號共軛梯度的演算法，此演算法既不需要反矩陣的運算也具有更低的計算複雜度，更重要的是此演算法的性能比其他傳統通道估計的方法有著更好的表現。Cooperative communication is a promising technologyhich can provide the space diversity and increase the reliability in wireless communication. Most existing analyses of relay systems assume that the perfect channel state information is known at the receiver, and pay less attention to the channel estimation. However, channel estimation is an indispensable technique in relay systems. In this thesis, we consider orthogonal frequency division multiplexing (OFDM)- based amplify-and-forward (AF) relay systems. We divide this thesis into three topics. In the first topic, multiple relay systems over slow fading channels are considered. The optimal training sequences for least squares (LS) and linear minimum mean squared error (LMMSE) are proposed. Through simulations, it is shown that the optimal training sequences proposed in this thesis significantly outperform the other training sequences. In the second topic, single relay systems over fast fading channels are considered. We propose three time-domain pseudo-pilot algorithms. All of the proposed algorithms can improve the performance of channel estimation and achieve better performance than Chang''s method. In the final topic, we still focus on the single relay systems over fast fading channels. We propose the adaptive pseudo-pilot conjugate gradient (APPCG) algorithm which does not need to perform the inverse matrix operation and has lower computational complexity. Moreover, it has better performance than other channel estimation methods.1 Introduction 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Relay-Based Cooperative Communication Systems . . . . . . . . . . . 2.2.1 Cooperative Communication . . . . . . . . . . . . . . . . . . . 2.2.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.3 Relaying Protocols . . . . . . . . . . . . . . . . . . . . . . . . 3.2.4 Relaying Algorithms . . . . . . . . . . . . . . . . . . . . . . . 5.2.5 Signal Models in AF Relay Systems . . . . . . . . . . . . . . . 5.2.6 Signal Models in DF Relay Systems . . . . . . . . . . . . . . . 7.2.7 Discussion for Signal Models . . . . . . . . . . . . . . . . . . . 7.3 OFDM Channel Estimation . . . . . . . . . . . . . . . . . . . . . . . 8.3.1 Overview of OFDM Channel Estimation . . . . . . . . . . . . 8.3.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.3.3 Pilot Arrangement . . . . . . . . . . . . . . . . . . . . . . . . 15.3.4 Pilot-Based Frequency Domain Channel Estimation . . . . . . 18.3.5 Pilot-Based Time Domain Channel Estimation . . . . . . . . . 26.4 Motivations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Optimal Training Sequences for OFDM in Multiple Relay Systems 32.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33.3 Least Squares (LS) Channel Estimator . . . . . . . . . . . . . . . . . 37.4 LS Optimal Training Criterion . . . . . . . . . . . . . . . . . . . . . . 38.5 Linear Minimum-Mean-Squared-Error (LMMSE) Channel Estimator . 43.6 LMMSE Optimal Training Criterion . . . . . . . . . . . . . . . . . . 44.7 Frequency Domain Optimal Training Sequences . . . . . . . . . . . . 49.8 Time Domain Optimal Training Sequences . . . . . . . . . . . . . . . 55.9 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Pseudo-Pilot Algorithms for OFDM in Single Relay Systems 65.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66.3 Frequency Domain Pseudo-Pilot Algorithm . . . . . . . . . . . . . . . 68.4 Time Domain Pseudo-Pilot Algorithm . . . . . . . . . . . . . . . . . 71.4.1 Time Domain Pseudo-Pilot Algorithm (1) . . . . . . . . . . . 71.4.2 Time Domain Pseudo-Pilot Algorithm (2) . . . . . . . . . . . 73.4.3 Time Domain Pseudo-Pilot Algorithm (3) . . . . . . . . . . . 74.5 Complexity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 76.6 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 Adaptive Pseudo-Pilot Conjugate Gradient Algorithm for OFDMn Single Relay Systems 84.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.2 The Conjugate Gradient Algorithm . . . . . . . . . . . . . . . . . . . 85.3 Adaptive Pseudo-Pilot Conjugate Gradient Algorithm . . . . . . . . . 87.4 Complexity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 92.5 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100ibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . .101873045 bytesapplication/pdfen-US合作通訊正交分頻多工系統放大與前傳中繼器通道估計最佳訓練序列虛擬領航信號演算法共扼梯度演算法cooperative communicationorthogonal frequency division multiplexing (OFDM)amplify-and-forward (AF) relaychannel estimationoptimal trainingpseudo-pilot algorithmconjugate gradient algorithmthesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/188363/1/ntu-98-R96942129-1.pdf