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 無線通訊網路已在這十年中蓬勃發展,越來越多的數位內容也快速地增加中，透過無線通訊網路而能夠輕易地傳送。由於多媒體技術的快速提升，無線通訊網路必須能夠安全地傳送更大的封包。在3GPP的規格當中,最大的通訊編碼封包被制定為5,114個位元,由於渦輪碼的性能優越,因此在3GPP的規格中廣為使用。 渦輪碼的解碼器部分使用BCJR演算法作為其主要解碼的部分，由於BCJR演算法在反向部分的解碼必須等待最後的位元，因此，在記憶體的使用上有著其先天上的缺點。為了改善這個問題，滑窗演算法因應而生。藉由滑窗演算法，BCJR演算法在反向部分的解碼即不需要等待最後的位元，也因此可以有效的解決BCJR先天上的缺點。 由於滑窗演算法運作時必須儲存整個視窗的狀態(state metrics)，因此，我們提出可進一步降低記憶體的雙向滑窗法。而滑窗法以及雙向滑窗法將會在此論文中作深入之探討與比較。
 Wireless communication network has been greatly prospered in the last decade. More and more digital contents are rapidly invented and can be easily transferred via the communication network. Because the related multimedia tech. is rapidly grown up, wireless communication transmission is expected for dealing with the larger frame. In 3GPP spec, the maximum code block size is defined as 5,114. Generally, the most powerful CODEC algorithm- turbo code is adopted in 3GPP spec. In the decoding part of turbo code, it involves BCJR algorithm. BCJR algorithm is composed of two parts: forward and backward. Actually, because backward part should operate initially from the last symbol, it has its inherent drawback in its memory costs. To deal with this problem, sliding window method is proposed. Sliding window, which based on the property of dual-maximum and Viterbi algorithm, can deal with the drawback of backward part in BCJR algorithm. In a fact, when sliding window adopted, it still need to store full state metric in each window. In this paper, we proposed a new method which named as bi-sliding which can further required memory size.
 摘要...….……………………………………………………………………………….I Abstract..………………………………………………………………………………II 誌謝..…..…….……………………………………….…………………..…………..III Table of Contents………………………………………..…..……....……………….IV List of Tables…………………………………………………………………………VI List of Figures……………………………………………………………………….VII Chapter 1 INTRODUCTION 1.1 Digital Communication Systems……………………………………………..1 1.2 Motivations and Related Work……………………………………………….2 1.3 Thesis Organization…………………………………………………………..2 Chapter 2 INTRODUCTION OF TURBO CODES 2.1 Introduction....………………………………………………………………..4 2.2 Shannon’s Limitation....……………………………………..……………….4 2.3 Convolutional Code....………………………………………………………..5 2.3.1 Encoder…………………………………………………………………5 2.3.2 Transfer Functions of Convolutional Codes……….…….……………..7 2.3.3 Decoder………………………………………………………………..11 2.4 Turbo Code………………………………………………………………….15 2.4.1 Turbo Encoder………………………………………………………...16 2.4.2 Turbo Decoder………………………………………………………...16 2.4.3 Flow Chart of Turbo Decodin……………….………………………..18 Chapter 3 Dual-Maximum and Sliding Window 3.1 Introduction…………………………………………………………………20 3.2 Max-Log-MAP algorithm and Dual-maximum………………….…………21 3.3 Sliding Window Method...………………………………………………….26 Chapter 4 Bi-sliding Window Algorithm 4.1 Introduction…………………………………………………………………30 4.2 Bi-sliding Window………………………………………………………….31 4.3 Memory Requirement Analysis……………………………………………..38 Chapter 5 Experimental Results 5.1 Introduction…………………………………………………………………39 5.2 Experiments…………………………………………………………………39 5.2.1 Optimal Window Size………………………………………………...40 5.2.2 Comparison for Bi-sliding Window and Sliding Window……………46 Chapter 6 Conclusions and Future Work…………………………………………48 Reference……………………………………………………………………………..49 作者簡介……………………………………………………………………………..52 授權書………………………………………………………….…………………….53
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