正交分頻多工系統之聯合同步與通道估測技術

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研究生：	王鴻欽 Wang, Hung-Chin
論文名稱：	正交分頻多工系統之聯合同步與通道估測技術 Joint Synchronization and Channel Estimation for OFDM Systems
指導教授：	王晉良 Wang, Chin-Liang
口試委員:
學位類別：	博士 Doctor
系所名稱：	電機資訊學院 - 通訊工程研究所 Communications Engineering
論文出版年：	2010
畢業學年度：	98
語文別：	英文
論文頁數：	88
中文關鍵詞：	多輸入多輸出、正交分頻多工、同步、通道估測
相關次數：	點閱：2 下載：0
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正交分頻多工（OFDM, orthogonal frequency-division multiplexing）因其高頻譜使用效率以及對於頻率選擇性通道的高抵抗性，廣泛被採納於眾多無線通訊協定之中。期間，透過多天線傳送與接收訊號的多輸入多輸出（MIMO, multiple-input multiple-output）技術已被證實能有效提升系統之效能與傳輸速率。進一步將OFDM與MIMO傳輸技術相結合，即衍生名為MIMO OFDM之嶄新系統。MIMO OFDM系統雖擁有眾多優勢，其同步與通道估測技術之良莠，對於載波間正交性之維持與訊號之解調具有關鍵性之影響。然而，多數針對傳統OFDM系統所發展之同步與通道估測演算法卻難以直接推廣至MIMO OFDM系統。此外，同步與通道估測雖息息相關，至今關於同步與通道估測之聯合設計仍顯不足。
在此論文中，我們針對OFDM與MIMO OFDM系統發展聯合同步與通道估測演算法。我們首先基於特殊的訓練序列架構為OFDM系統發展聯合同步與通道估測演算法，並透過理論分析導出演算法所需之最佳與次佳門檻值。我們導出之最佳門檻值明確顯示其與通道統計特性、訊雜比以及相關系統參數之對應關係。此外，我們導出之次佳門檻值無須仰賴通道資訊或系統模擬便可求得，並經證實可於實際應用中有效取代最佳門檻值。我們提出之聯合演算法因具備最佳化門檻值，在多重路徑通道之首路徑能量與訊雜比相對低時，明顯優於仰賴系統模擬產生門檻值之傳統設計。另一方面，在不改變原始訓練序列架構的前提下，我們提出兼備理想週期性自相關函數與部份幾何特性之特殊序列，並發展可與聯合演算法整合之大範圍載波頻率偏移估測演算法。
針對MIMO OFDM系統，我們巧妙安排經不同天線同時傳送的多個訓練序列，使整體之MIMO訓練序列架構免於訓練序列間之交互干擾。接著，基於此MIMO訓練序列之獨特性，我們將原本為OFDM系統設計之聯合同步與通道估測演算法推廣至MIMO OFDM系統，並提出多數決優化（MVR, majority vote refinement）的概念以充分運用MIMO傳輸架構下之多樣性，進一步改善同步與通道估測之效能。電腦模擬結果顯示MVR可提升聯合演算法之穩定度，並在訊雜比相對低時提供可觀的效能改善。在理論分析方面，我們針對門檻值選擇與MVR對聯合演算法的影響進行深入探討，相關結果與電腦模擬結果極為一致。此外，我們亦基於最大長度序列（maximal length sequence）發展適用於OFDM與MIMO OFDM系統之低複雜度聯合同步與通道估測演算法。

Orthogonal frequency-division multiplexing (OFDM) has been adopted in various wireless communication standards due to its high spectrum efficiency and robustness against frequency selective fading channels. Meanwhile, multiple-input multiple-output (MIMO) transmission that utilizes multiple antennas at both the transmitter and receiver sides has been shown effective to enhance the system performance and/or throughput. Combining OFDM with MIMO transmission results in a new system called MIMO OFDM. Despite the inviting features, MIMO OFDM requires superior synchronization as well as channel estimation to restore the orthogonality among subcarriers and to support MIMO detection. Challengingly, most of the conventional synchronization and channel estimation methods for OFDM cannot be directly applied to MIMO OFDM without major modifications. Furthermore, synchronization and channel estimation depend on each other, yet they are mostly investigated separately.
In this dissertation, we develop joint synchronization and channel estimation schemes for both OFDM and MIMO OFDM systems. For OFDM systems, we first develop a joint scheme based on a special training sequence structure. To ensure superior performance, we derive an optimal threshold and a suboptimal threshold for the proposed joint scheme. The optimal threshold clearly reveals how the threshold should react to the channel statistics, the signal-to-noise ratio (SNR), and other design parameters. On the other hand, the suboptimal threshold that can be calculated without pre-simulation or prior information on the channel statistics is shown a practical substitute for the optimal threshold. The proposed joint scheme with optimized thresholds improves both synchronization and channel estimation performance as compared with a related work with pre-simulated thresholds, especially when the channel’s first tap is rather insignificant and/or the SNR is relatively low. To integrate a carrier frequency offset (CFO) acquisition scheme with the proposed joint scheme, while preserving the original training sequence structure, we construct a partially geometric sequence that has an ideal periodic auto-correlation function. Accordingly, we develop an acquisition scheme that exploits the partially geometric feature to extend the CFO estimation range.
For MIMO OFDM systems, we first develop a novel arrangement of the training sequences, which skillfully eliminates the mutual interference among the simultaneously transmitted training signals of the active antennas. Based on the training sequence arrangement, we generalize our joint scheme for OFDM into MIMO scenario and further present a majority vote refinement (MVR) of the timing estimates for different transmit-receive links. The proposed MVR fully exploits the features of our training sequence arrangement and the MIMO diversity to improve synchronization as well as channel estimation. It is shown that MVR not only enhances the robustness of the proposed joint scheme but also contributes significant performance gain at lower SNRs. The performance of the proposed joint approach is also analyzed with respect to MVR and threshold selection, and the theoretical results agree well with the simulation results over several channel models. To provide a trade-off between performance and complexity, we also develop low-complexity joint schemes for both OFDM and MIMO OFDM systems using maximal length sequence based training structures.

Abstract i
Contents iii
List of Figures vii
List of Tables ix
Chapter 1 Orthogonal Frequency-Division Multiplexing 1
1 Introduction 1
2 OFDM Basics and System Overview 1
3 Outline of the Dissertation 2
Chapter 2 Synchronization and Channel Estimation for OFDM Systems 5
1 Introduction 5
2 An Overview of Synchronization Methods for OFDM 6
3 An Overview of Channel Estimation Methods for OFDM    6
4 Joint Synchronization and Channel Estimation for OFDM 7
5 Synchronization and Channel Estimation for MIMO OFDM 8
Chapter 3 Optimized Joint Synchronization and Channel Estimation for OFDM Systems    11
1 Introduction 11
2 The Proposed Joint Fine Timing Synchronization and Channel Esimation Scheme with Optimal and Suboptimal Thresholds 12
2.1 The Proposed Training Sequence Structure with Ideal PACF Properties 12
2.2 Coarse Timing and Frequency Synchronization 13
2.3 Analysis of the CCF Output 14
2.4 The Proposed Joint Fine Timing Synchronization and Channel Estimation Scheme 15
2.5 Analysis of the PDFs of the CCF Output 16
2.6 Derivation of the Optimal and Suboptimal Thresholds over Rayleigh Channels 17
2.7 Theoretical Performance Analysis of the Proposed Joint Scheme 19
3 The Proposed CFO Acquisition Scheme 19
3.1 A Conventional CFO Acquisition Scheme based on Geometric Sequences 20
3.2 The Development of a Partially Geometric MOS 21
3.3 The Proposed CFO Acquisition Scheme based on a Partially Geometric MOS 22
4 The Proposed Low-Complexity Joint Fine Timing Synchronization and Channel Estimation Scheme    22
4.1 A Conventional m-Sequence based Training Structure 23
4.2 Analysis of the CCF Output 23
4.3 Analysis of the PDFs of the CCF Output 24
4.4 Derivation of the Optimal and Suboptimal Thresholds over Rayleigh Channels 24
5 Simulation Results 25
5.1 Evaluation of the Proposed Joint Scheme    26
5.2 Evaluation of the Proposed CFO Acquisition Scheme 28
5.3 Evaluation of the Proposed Low-Complexity Joint Scheme 28
6 Summary 29
Chapter 4 Optimized Joint Timing Synchronization and Channel Estimation for MIMO OFDM Systems 41
1 Introduction 41
2 The Proposed Joint Fine Timing Synchronization and Channel Estimation Scheme with MVR 42
2.1 System Model and the Proposed MIMO Training Sequence Arrangement 42
2.2 Coarse Timing and Frequency Synchronization 43
2.3 Analysis of the CCF Output 44
2.4 The First Channel Tap Selection Scheme for Each Transmit-Receive Link 45
2.5 The Proposed MVR of the Timing Estimates and the Resultant CIR Estimate 46
2.6 The Computational Complexity of the Proposed Joint Scheme 47
2.7 Analysis of the PDFs of the CCF Output 48
2.8 Derivation of the Optimal and Suboptimal Thresholds for the Proposed First Channel Tap Selection Scheme to Operate over Rayleigh Channels 49
2.9 The Threshold Selection for the Proposed First Channel Tap Selection Scheme to Operate over Rician Channels 50
3 Theoretical Performance Analysis of the Proposed Joint Scheme 51
3.1 The Probability of Perfect Timing Synchronization for Each Transmit-Receive Link 51
3.2 The Probability of Perfect Timing Synchronization after MVR     52
4 The Proposed Low-Complexity Joint Fine Timing Synchronization and Channel Estimation Scheme    54
4.1 The Proposed m-Sequence Based MIMO Training Sequence Arrangement 54
4.2 Analysis of the CCF Output 55
4.3 Analysis of the PDFs of the CCF Output 55
4.4 Derivation of the Optimal and Suboptimal Thresholds 56
5 Simulation Results 57
5.1 Evaluation of the Proposed Joint Scheme    57
5.2 Evaluation of the Proposed Low-Complexity Joint Scheme 59
6 Summary 60
Chapter 5 Conclusions 71
Appendix A The Proof of the Inexistence of a Geometric Sequence with an Ideal PACF 73
Appendix B The Derivation of the Optimal Threshold 75
Bibliography 77
Publication List 87

                                

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