臺灣博碩士論文加值系統

本論文研製了一個可對抗時變之頻率選擇性快速衰減通道的可適性等化器。IEEE 802.11n 無線網路標準被用作為設計時的參考平台，2對2以及4對4的多重輸入多重輸出正交分頻多工系統皆被納入考慮。此平台工作在2.4GHz頻段，使用20MHz的頻寬。
模擬平台引入了兩種時變通道模型，其中之一為傑克斯模型，而另一個自定義的模型是基於通道效應會隨機變化的概念所產生。
本論文提出的可適性等化器包含兩個步驟。時空區塊碼經解碼後，經由本論文所提出的可適性通道估計演算法做處理，以估計出包含雜訊的時變通道，再由頻域上的維納濾波器濾去大部分的雜訊，以降低演算法對訊噪比的需求。
此可適性等化器在2對2的多輸入多輸出系統下，可在傑克斯模型120km/hr、訊噪比24dB的條件下達到104Mbps的資料傳輸速率，在250km/hr、訊噪比20dB的條件下達到78Mbps的資料傳輸速率。在4對4的多輸入多輸出系統中、傑克斯模型120km/hr、29.5dB訊噪比的環境下可達到208Mbps的資料傳輸速率。
在硬體實作階段，維納濾波器將被省略，因為其運算複雜度過高。4對4的可適性等化器是一個管線化的設計，其總邏輯閘數為190萬，使用UMC 0.13um^2 製程。

This thesis presents a decision-feedback adaptive channel-estimation scheme for Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems under time-variant frequency-selective fast-fading channels. IEEE 802.11n standard of TGn Sync Proposal is targeted. It operates at 2.4GHz band with 20MHz bandwidth. Both 2 2 and 4 4 transceiver allocations with corresponded Space-Time Block Coding (STBC) are considered.
Two time-variant channel models are applied to the simulation platform. One is the well-known Jakes’ model, and the other is a custom model defined on the concept of randomly changed channels.
The adaptive equalization contains two parts. First, the proposed adaptive channel estimation scheme is applied to the STBC-decoded symbols in order to estimate the noisy time-variant channels. The second and the last, a frequency domain Wiener filter is applied to each estimated noisy time-variant channel to decrease the Signal-to-Noise Ratio (SNR) requirements that adaptive equalization needed.
The proposed algorithm achieves 104Mbps data rate under 120km/hr Jakes’ model at 24dB SNR and 78Mbps for 250km/hr at 20dB SNR for 2 2 MIMO-OFDM systems, and 208Mbps for 4 4 MIMO-OFDM systems under 120km/hr Jakes’ model at 29.5dB SNR.
In hardware implementation phase, the frequency domain Wiener filter is omitted since its computational complexity is too high to fit in regular area constrains. The proposed adaptive equalizer for 4 4 MIMO-OFDM systems is a pipelined design and is implemented using UMC 0.13um^2 process. The total gate count of the 4 4 adaptive equalizer is 1.9 million.

摘要 i
Abstract iii
Acknowledgement v
Table of Contents vii
List of Figures ix
List of Tables xi
Chapter 1 Introduction 1
1.1 Doppler Shift 1
1.2 Time-Variant Channel Effect 2
Chapter 2 System Platform 5
2.1 IEEE 802.11n PHY Specification 5
2.1.1 Transmitter 5
2.1.2 Receiver 6
2.1.3 Packet Format 7
2.2 Space-Time Block Coding 7
2.2.1 2 2 STBC 7
2.2.2 4 4 STBC 8
2.3 Channel Models 10
2.3.1 Jakes’ Model 10
2.3.2 Custom Model 11
Chapter 3 The Proposed Algorithm 15
3.1 Adaptive Equalizer Overview 15
3.2 Decision Feedback Adaptive Channel Estimation 18
3.2.1 Adaptive Channel Estimation for 2 2 STBC 18
3.2.2 Adaptive Channel Estimation for 4 4 STBC 20
3.3 Wiener Filtering 23
3.3.1 Wiener Estimator 24
3.3.2 Frequency Domain Wiener Filtering 25
Chapter 4 Performance Analysis 31
Chapter 5 Hardware Implementation 37
5.1 Architecture of the 4 4 Adaptive Equalizer 37
5.1.1 Architecture of 4 4 Matrix Inverter 38
5.1.2 Architecture of 4 4 Matrix Multiplier 41
5.2 Data Path of the 4 4 Adaptive Equalizer 42
5.3 Summary 45
Chapter 6 Conclusion and Future Work 47
6.1 Conclusion 47
6.2 Future Work 49
Bibliography 51

[1] Theodore S. Rappaport, “Wireless Communications – Principles and Practice, 2nd edition”, chapter 5, Prentice-Hall, 2002
[2] P. Dent, G. Bottomley and T. Croft, “Jakes Fading Model Revisited”, IEE Electronics Letters, p.1162~p.1163, June 1993
[3] 802.11n standard, ”TGn Sync Proposal Technical Specification”, IEEE 802.11-04/0889r7, July 2005
[4] S.M. Alamouti, “A simple transmit diversity technique for wireless communications”, IEEE Journal on Selected Areas in Communications, Oct. 1998
[5] Ta-Yang Juan, “The Study of Pilot-based Adaptive Equalization for Wireless MIMO-OFDM Baseband Designs”, NCTU thesis, 2006
[6] Branka Vucetic and Jinhong Yuan, “Space-Time Coding”, chapter 3, WILEY, 2003
[7] W. C. Jakes, Ed., “Microwave Mobile Communications”, IEEE Press, Piscataway, NJ, 1974
[8] Henrik Schulze and Christian Luders, “Theory and Applications of OFDM and CDMA - Wideband Wireless Communications”, p.183~p.192, WILEY, Sep. 2005
[9] Steven J. Leon, “Linear Algebra with Applications”, 5th edition, Prentice Hall
[10] Ming-Yeh Wu, “Design of Pilot-based Adaptive Equalization for Wireless OFDM Baseband Applications”, NCTU thesis, 2004
[11] Jos Akhtman and Lajos Hanzo, “Advanced Channel Estimation for MIMO-OFDM in Realistic Channel Conditions”, IEEE Transactions, Mar. 2007
[12] Tsung-Han Tsai, “Interference Cancellation in OFDM Systems over Time-Varying Channels”, NCTU thesis, 2006
[13] Gabriele Dona and Witold A. Krzymien, “MMSE Channel Estimation Using Two-Dimensional Filtering in Rapid Time-Variant Environments”, IEEE, 2005
[14] Chia-Chun Hung, “On the Detection of Coded MIMO-OFDM Signals in Time-Varying Channels”, NCTU thesis, 2005
[15] Chin-Jung Tsai, “Design of Channel Estimation and Data Detection for OFDM Systems in Time-Varying and Multipath Fading Channels”, NCTU thesis, 2006
[16] Jie Wu and Gary J.Saulnier, “Orthogonal Space-Time Block Code over Time-Varying Flat-Fading Channels: Channel Estimation, Detection, and Performance Analysis”, IEEE Transactions on Communications, May. 2007
[17] Jingming Wang and Babak Daneshard, “An 8 8 RLS based MIMO Detection ASIC for Broadband MIMO-OFDM Wireless Transmissions”, EUSIP Conference, 2006