| 研究生: |
王志祺 Chih-Chi Wang |
|---|---|
| 論文名稱: |
適用於非對稱數位用戶迴路系統之有效率的時域等化器演算法 Cost-effective TEQ Algorithm for ADSL System |
| 指導教授: |
吳安宇
An-Yeu Wu |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
資訊電機學院 - 電機工程學系 Department of Electrical Engineering |
| 畢業學年度: | 88 |
| 語文別: | 中文 |
| 論文頁數: | 51 |
| 中文關鍵詞: | 離散多頻 、非對稱數位用戶迴路 、時域等化器 、頻域等化器 |
| 外文關鍵詞: | DMT, ADSL, TEQ, FEQ |
| 相關次數: | 點閱:21 下載:0 |
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離散多頻(DMT)調變/解調方法是非對稱數位用戶迴路(ADSL)系統中標準的實體層傳輸技術。在散散多
頻的傳收機中,通道的等化是經由兩個步驟所完成的,稱為時域等化器(TEQ)及頻域等化器(FEQ)。時域等
化器的目的是用來縮短通道響應長度。而頻域等化器則是被用來補償信號經過通道時所造成的大小及相位的失真
。
有許多訓練時域等化器的演算法被提出,而這些演算法可以被分為上線(on-line)及下線(off-line)的方法。
下線的方法通常非常複雜以致於無法實際的實現。而現有的上線的方法則仍然有複雜度太高的缺點。在本論文中
,我們提出了一個具有經濟效益的上線演算法。我們利用MATLAB完整的模擬所提出的演算法並驗證其正確性。
模擬的結果顯示我們所提出的演算法可以得到和其他上線演算法差不多的縮短訊號雜訊比(SSNR)。我們也比較
了上線演算法之間的運算複雜度,結果顯示我們所提出的演算法可以達到最低的運算複雜度。另外,我們也是出
了一個可以結合時域等化器及頻域等化器的訓練方法。如此我們可以利用這個演算法同時得到時域等化器及頻域
等化器的參數。
Discrete multiton (DMT) modulation/demodulation scheme is the standard physical-layer transmission technology in Asymmetric
digital subscriber line (ADSL) system. In DMT transceiver, channel equalization is complete through 2-step way, called Time-domain
equalizer (TEQ) and Frequency domain equalizer (FEQ). TEQ is introduced to shorten the channel response to a pre-defined length.
On the con-trary, FEQ is used to compensate the magnitude and phase distortion caused by chan-nel.
There are many TEQ training algorithms have been proposed and these algo-rithms can be categorized as on-line and off-line
approaches. The off-line ap-proaches are generally too complicated for practical implementations. On the other hand, the existing
on-line approaches still have the disadvantage of high complexity. In this thesis, a cost-effective on-line TEQ training algorithm is
proposed. We verify the proposed algorithm by completed simulation on MATLAB environment. Simu-lation results show that the
proposed algorithm has the similar Shortened signal to noise ratio (SSNR) compared with other on-line algorithms. Complexity
comparison is also made, and it shows that our algorithm can achieve the lowest computational complexity between the on-line
algorithms. Moreover, an algorithm of combining TEQ and FEQ training is proposed, too. Consequently, the coefficients of TEQ and
FEQ are obtained simultaneously through the co-training algorithm.
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