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研究生:張傑堯
研究生(外文):Cheih-Yao Chang
論文名稱:最小均方誤差演算法使用模糊步階在正交分頻多工系統之通道預測的應用
論文名稱(外文):Application of LMS Algorithm with Fuzzy Updated Step Size on Channel Prediction for OFDM Systems
指導教授:溫志宏溫志宏引用關係
指導教授(外文):Jyh-Horng Wen
學位類別:碩士
校院名稱:國立中正大學
系所名稱:電機工程所
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:2006
畢業學年度:94
語文別:英文
論文頁數:40
中文關鍵詞:正交分頻多工通道預測最小均方誤差模糊控制
外文關鍵詞:OFDMchannel predictionLMSfuzzy logic control
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本論文主要是探討模糊控制器(Fuzzy Logic Controller)在正交分頻多工系統下的通道預測器上的應用。在本論文中在正交分頻多工系統下的通道預測器應用不同的適應性濾波器演算法,如NLMS 以及RLS演算法。通道預測可以運作在時域和頻域。我們提出以最小均方誤差演算法(Least Mean Square)為基礎並使用模糊控制器週期性調整步階參數進行通道預測。此外,我們也使用多個模糊控制器來調整在不同路徑上所需要的步階參數。模擬結果顯示在時變的通道變化下,我們所提出的演算法有較NLMS還要快的通道追蹤能力,但是只需花費比NLMS還要低的運算複雜度。因此,運用模糊步階的最小均方誤差演算法在正交分頻多攻下的通道預測是有效的應用。
The adaptive filter applied to channel predictor for orthogonal frequency division multiplexing (OFDM) systems is investigated. Different algorithms of adaptive filter, such as normalized least mean square (NLMS) and recursive least square (RLS), are applied to predict the channel response. We proposed the algorithm which is based on the least mean square (LMS) and periodically updates the step size by a fuzzy logic controller. The computation load of proposed algorithm is smaller than both NLMS and RLS algorithms. The simulation results show that the tracking ability of proposed algorithm is slightly better than the NLMS algorithm. Therefore, the proposed algorithm is an efficient method which can be applied to channel prediction.
Chapter 1 Introduction…………………………………………………1
Chapter 2 System Description………………………………………….3
2.1 OFDM System Description………………………………….……….....3
2.2 Fuzzy Logic Controller………………………………………….………6
2.2.1 Fuzzy Set & Fuzzy Logic…………………………………...…….7
2.2.2 Fuzzification…………………………………………………..…10
2.2.3 The Inference Mechanism………………………………………..10
2.2.4 Defuzzification…………………………………………………...11
Chapter 3 Frequency Domain Channel Prediction for OFDM Systems……………………………………………………..12
3.1 Channel Prediction Using Adaptive Filter…………………….……….12
3.2 Combining FLC with LMS Algorithm………………………….……..15
3.3 Computation Complexity Analysis……………………………….……19
3.4 Simulation Results……………………………………………….…….21
Chapter 4 Time Domain Channel Prediction for OFDM Systems………………………………………..……………24
4.1 Structure of channel predictor on Time Domain……….………………24
4.2 NLMS, RLS, and FLC-LMS algorithms…………….….……………..26
4.3 Tracking on Each Grouped Branches……………….….………...……28
4.4 Computation Complexity Analysis………….……….………..….……30
4.5 Simulation Results……………………………………..…………..….32
Chapter 5 Conclusions……………………………………..………….37
References…………………………………………………...…...…….39
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[11] I. C. Wong, Antonio Forenza, Robert W. Heath, Brian L. Evans, "Long range channel prediction for adaptive OFDM systems", Signals, Systems and Computers, vol.1, 2004.
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