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研究生:廖偉吉
研究生(外文):Liao, Wei-Ji
論文名稱:考慮多輸入多輸出正交分頻調變系統在快速時變的多通道下藉由模糊濾波器方法做強健性通道估測和等化器
論文名稱(外文):Robust Fast Time-Varying Multipath Fading Channel Estimation and Equalization for MIMO-OFDM System via Fuzzy Filter Method
指導教授:陳博現
指導教授(外文):Chen, Bor-Sen
學位類別:碩士
校院名稱:國立清華大學
系所名稱:電機工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2010
畢業學年度:98
語文別:英文
論文頁數:56
中文關鍵詞:多入多出正交分頻多工自回歸隨機程序直接估測通道追蹤設計模糊線性系統等化器
外文關鍵詞:Multi-input multi-outputrthogonal frequency division multiplexing (OFDM) systemautoregressive (AR) random processdecision-directed channel tracking designTakagi-Sugeno (T-S) fuzzy linear modelequalization
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  通道估測在無線通訊系統中一直是個很重要的議題。基於對通道增益的了解,我們可處理許多無線通訊上的問題,例如:信號偵測和傳輸功率控制。這篇論文提出了一個在多入多出正交分頻多工調變(MIMO-OFDM)系統中藉由(Takagi-Sugeno)TS模糊(Fuzzy)卡曼濾波器(Kalman filter) 的方法對一個速度隨時變的通道做估測。我們考慮一個由自回歸(autoregressive)隨機程序來做通道模型的正交空時區碼(OSTBC)多入多出系統。所提出的TS卡曼濾波器在多輸入多輸出正交分頻多工調變系統中可藉由內插許多根據不同移動端速度的線性參數系統來逼近非線性系統近而同時估測自回歸程序的參數和通道增益達到強健性的非線性參數估測和預測。在快速衰減的通道下直接偵測通道追蹤設計是個有效的方法,而直接偵測方法本質上的延遲問題可藉由模糊卡曼濾波器的預測方法來補償。而且,強健性的最小均方誤差等化器設計可藉由考慮通道預測誤差的協方差來改善信號的偵測。為了確立所提出的方法的效果,在模擬的部分會與其他方法做比較。由於在多入多出正交分頻多工系統中考慮移動端的隨時變速度,藉由TS卡曼濾波器強化後的等化器跟傳統的等化器相比有較低的信號偵測誤差。
Channel estimation is an important issue for wireless communication system.
A Channel estimation scheme using Takagi-Sugeno (T-S) fuzzy-based Kalman filter under the time-varying velocity of mobile station in a multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) system is proposed in this paper.
We consider the orthogonal space time block coding (OSTBC) scheme of MIMO system where the mobile radio channel is modeled as an autoregressive (AR) random process.
The parameters of the AR process and the channel gain are simultaneously estimated by the proposed T-S fuzzy-based Kalman filter to achieve robust nonlinear parameter estimation and prediction by interpolating several linear parameter systems at different mobile speeds to approximate the nonlinear parameter systems in MIMO-OFDM communication.
It is useful for the decision-directed channel tracking design, especially in fast fading channel due to time-varying velocity of mobile station.
The inherent delay problem of decision-directed scheme can also be compensated by a fuzzy Kalman-based channel prediction method.
Further, the robust MMSE equalization design can be achieved by the consideration of channel prediction error to improve the performance of symbol detection.
To confirm the performance of proposed method, several simulation results are given in comparison with other methods.
With consideration of time-varying velocity of the mobile station communicated in the MIMO-OFDM system, the enhanced equalizer based on the T-S fuzzy-based Kalman filter performs better than those based on the conventional channel estimators in symbol error rate.
1 Introduction 8
2 System Models of MIMO-OFDM Systems 15
2.1 Model of Transmitter . . . . . . . . . . . . . . . . . . . . . . . 15
2.2 Model of Receiver . . . . . . . . . . . . . . . . . . . . . . . . . 17
3 Fuzzy-Based Channel Tracking 20
3.1 Subcarrier Channel Estimation . . . . . . . . . . . . . . . . . 20
3.2 Fuzzy-based Kalman Filter for Time-Varying Channel Estimation
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
4 Robust Fuzzy Decision-Directed Algorithm in the Tracking
Mode 29
4.1 Decision-Directed Algorithm . . . . . . . . . . . . . . . . . . . 29
4.2 The Robust MMSE Equalizer . . . . . . . . . . . . . . . . . . 32
4.3 Performance Analysis . . . . . . . . . . . . . . . . . . . . . . . 35
5 Computer Simulation 38
5.1 Parameters of MIMO-OFDM Systems . . . . . . . . . . . . . . 38
5.2 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . 39
6 Conclusion 46
A Proof of Theorem 1 49
Bibliography 49
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