臺灣博碩士論文加值系統

在區塊渦輪碼(Block Turbo Codes，稱BTC)解碼演算法中，對於解碼參數權重因子α及可靠因子β值隨著疊代的次數增加，有其靜態設定限制，在通道環境不良時難以解碼;由於傳輸時通道具有時變性，這種以預先設定α、β值來參與解碼的方式，造成系統不易控制，並非是一種有效的估測，而本文提出隨著解碼輸入與解碼輸出值的相對變化 ，動態地來估測α、β值。
區塊渦輪碼解碼演算法是一種利用反覆疊代解碼來改善解碼的效能，對於解碼運算時，大多設定八次為其所需解碼的半疊代次數。然而，在實際的訊息解碼中解碼疊代的次數是與傳輸通道環境有關， 疊代次數不確定性來自訊息干擾的高低程度，當雜訊源較大的環境中即需較多的解碼疊代才能解出正確的訊息，而雜訊源較輕微的環境則僅需較少次的解碼疊代即可更正為正確的訊息。因此本文在傳統的區塊渦輪解碼器中，實際測量解碼器的輸入訊息量和輸出訊息量，建立熵和互消息的觀念，使得能順利進行解碼。

In a general decoding algorithm of block turbo codes(BTCs), the weighting factor α and reliability factor β are fixed in each static decoding iteration with increasing times. It’s difficult to decode codes under poor channel environment. However, the time-variant channels predefined α and β are not appropriate in BTC decoding because they are not easily being controlled. The thesis proposes a method to set the values of α and β dynamically based on input and output values of the decoder.
BTC decoding algorithms use an iterative decoding procedure to achieve low bit error rate performance typically with eight half decoding iterations. However, the requirement for the number of decoding iterations is related to the channel; i.e. , the larger the noise is, the more the number of iterations is required. So in the traditional BTC decoders, we practically measure the input and output values of decoders, then establish entropy and mutual information concepts to make the decoding process work smoothly.

目 錄

明志科技大學碩士學位論文指導教授推薦書 ..i
明志科技大學碩士學位論文口試委員審定書 ..ii
明志科技大學學位論文授權書 ..iii
誌謝 ..iv
中文摘要 ..v
英文摘要 ....vi
目錄 vii
表目錄 ..x
圖目錄 ..xi

第一章 緒論…………………………………………………………1
1.1研究背景………………………………………………………1
1.2研究目的………………………………………………………2
1.3結果概述………………………………………………………3
1.4論文架構………………………………………………………3

第二章文獻探討……………………………………………5
2.1 夏農(Shannon) 熵的衡量……………………………………....6
2.2 熵(平均消息含量)……………………………………………....7
2.3 區塊與條件熵函數………………………………………...….12
2.4 通道相互消息(Mutual Information, MI)……………………...15
2.5 通道容量……………………………………………………….18

第三章 硬式與軟式解碼演算法簡介…………………………………19
3.1高斯雜訊………………………………………………………..21
3.2 硬式判斷……………………………………………………….22
3.2.1 最大事後機率法則……………………………………..22
3.2.2 最大概似機率法則……………………………………..23
3.3 軟式判斷………………………………………………………...24
3.4 硬式與軟式解碼演算法………………………………………...25
3.4.1 硬式解碼演算法………………………………………...26
3.4.2 軟式解碼演算法………………………………………...26
3.5 硬式與軟式解碼效能之比較………………………………...…27

第四章 區塊渦輪碼……………………………………………………29
4.1 乘積碼與基本線性代數……………………………………...30
4.2 線性區塊碼…………………………………………………33
4.2.1 生成矩陣……………………………………………...35
4.3 區塊渦輪碼…………………………………………………….38
4.4 區塊渦輪碼之解碼效能…………………………………….....45
4.5 互消息量之推導…………………………………………….....47
4.6 模擬結果……………………………………………………….49

第五章 結論與未來展望………………………………………………52
5.1結論……………………………………………………………52 5.2 未來展望………………………………………………………53

參考文獻………………………………………………………………54


表目錄
表1. (7,3) 線性區塊碼………………………………………….........37
表2. 在不同SNR下，I(x , r)的值……………………………….......49
表3. 相同下，位元錯誤率(BER)之比較………………………49


圖目錄
圖1. 二進位源之熵函數……………………………………………….10
圖2. 離散無記憶通道模型………………………………………….…15
圖2. 數位通訊系統架構……………………………………………….19
圖3. 高斯雜訊之機率密度函數…………………………….…21
圖4. 接收訊號之機率密度函數…………………………….…21
圖5. (7,4)漢明碼之硬式與軟式解碼演算法之效能比較……28
圖6. 乘積碼之架構圖 ……………………………………30
圖7. 為MLD之碼字； 為競爭碼； 表接收序列； 為用ChaseII
找出之碼字子空間…………………………….………………….42
圖8. 區塊渦輪碼之區塊圖………………………………….…………42
圖9. 渦輪區塊碼解碼流程圖………………………………………….44
圖10. BTC(32, 26, 4)2區塊渦輪碼在高斯通道環境下之解碼效能…..45
圖11. BTC(64, 57, 4)2區塊渦輪碼在高斯通道環境下之解碼效能…..46
圖12. BER解碼增益比較………………………………………….......50

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