臺灣博碩士論文加值系統

水下通訊環境中多重路徑效應和都卜勒效應一直是障礙所在,若想要快速的傳送資料，更是增加問題的複雜度,必須在接收端使用精密的通道等化及信號處理技術來克服。
為能得到正確且高通訊容量的需求,改善傳統適應等化器需要訓練序列,本論文引入軟決策盲蔽適應性決策迴授等化器架構,其結合了傳統決策迴授等化器、適應性等化器及一般盲蔽式等化器的優點,
同時再加入軟決策的概念,不須訓練序列即可適應時變的通道變化,
同時具有較快的收斂速度和更低的位元錯誤率。應用Matlab程式語言模擬等化器在穩態和非穩態通道中的適應及追蹤能力,由結果可知本文所改良之架構在惡劣通道中以及低SNR時都有不錯性能。

Because of multi-path and Doppler effect, the development of the underwater acoustic communication system is a challenging task. The optimum equalization and appropriate signal processing technique are needed to improve the quality of communications.

In this thesis, the implementation algorithms based on the blind adaptive decision feedback equalization (BADFE), whose function can be automatically adjusted according to variations of channel, are investigated. The soft decision is combined with the BADFE to get a modified equalization scheme. The proposed method combines decision feedback, blind adaptive scheme, and the soft decision method at the same time. Therefore it can combat the distortion occurred
in underwater communication channels without the need of the training sequence. The bit error rates and the transmission efficiency are improved. Computer simulation results indicate that the performances of the proposed method always has better convergence speed and lower bit error rate even in the bad channel and low SNR.

1 序論 1
1.1 研究動機與目的..................................1
1.2 各章節內容概述..................................2
2 常見等化器簡介 4
2.1 等化器簡介......................................4
2.2 等化器架構及型別................................5
2.3 決策迴授等化器..................................6
2.4 軟決策裝置的最佳化..............................7
2.5 傳統的適應性演算法..............................12
2.5.1 最小均方演算法 (LMS).......................13
2.5.2 遞迴最小平方演算法 (RLS)...................14
2.6 盲蔽式等化器....................................16
3 盲蔽適應性決策迴授等化器之改良 18
3.1 簡介............................................18
3.2 盲蔽適應性決策迴授等化器演算法則................19
3.2.1 起始模式 (R在T之前)........................19
3.2.2 追蹤模式 (T在R之前)........................22
3.2.3 追蹤模式的適應性演算法.....................24
3.3 改良盲蔽適應性決策迴授等化器....................25
3.3.1 結合BADFE的起始模式和追蹤模式..............25
3.3.2 加入軟決策概念.............................28
3.3.3 在DFE中引入抹除概念來降低錯誤傳遞..........30
4 等化器模擬結果與分析 32
4.1 模擬系統結構與通道描述..........................32
4.2 Matlab模擬結果與分析............................39
5 結論與未來發展 51

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