低密度偶校碼(low-density parity-check codes, LDPC codes)已被證實當運用疊代訊號傳遞解碼(iterative message passing decoding)並配合極長的碼長時，會有接近薛農極限(Shannon limit)的表現。類循環低密度偶校碼(quasi-cyclic low-density parity-check codes, QC-LDPC codes)是一種具代數結構的低密度偶校碼，而低密度偶校迴旋碼(low-density parity-check convolutional codes, LDPC-CCs)可以由類循環低密度偶校碼構造，彼此具有對應關係，且兩者的偶校矩陣都是低密度的。受益於坦納圖(Tanner graph)與偶校矩陣的相似性，將適用於低密度偶校碼的疊代訊號傳遞解碼調整為管線狀(pipeline)架構，即可應用在低密度偶校迴旋碼上，在編碼器與解碼器兩端皆可以連續輸出並編碼成任意長度。

　　在此篇論文中，我們藉由屏蔽法(masking)將非均等錯誤保護(unequal error protection, UEP)性質由類循環低密度偶校碼推廣到低密度偶校迴旋碼，這些建構出來的碼由模擬結果顯示具有非均等錯誤保護的效果存在，錯誤更正能力也優於所對應到的類循環低密度偶校碼。儘管低密度偶校迴旋碼在錯誤更正能力以及連續解碼方面具有優勢，但是它有個缺點是解碼過程中會有滑動視窗(sliding window)及初始延遲(initial delay)。初始延遲以及解碼過程中的滑動視窗的大小與解碼器中的記憶體個數(syndrome former memory)有關，隨著記憶體個數降低，初始延遲以及解碼過程的滑動視窗也會跟著變小。因此我們提出了三種可以降低記憶體個數的方法，並以電腦模擬驗證這些方法是否對其錯誤保護能力造成影響。從模擬結果可以觀察到，雖然這三種方式會不同幅度造成錯誤更正能力衰減，但是仍然維持相當優異的表現。

Low-density parity-check (LDPC) convolutional codes, which can be constructed from quasi-cyclic LDPC (QC-LDPC) codes, have been shown to achieve excellent performance with pipeline message-passing decoding. Moreover, LDPC convolutional codes (LDPC-CCs) can be decoded continuously and are desirable in continuous transimission and block transmission in frames of arbitrary size. In this thesis, we extend the masking technique of constructing unequal error protection (UEP) QC-LDPC codes to build UEP LDPC-CCs. Some specific construction structures of UEP LDPC-CCs are also provided.

In spite of the advantages in error performance and continuous decoding, one weakness of LDPC-CCs is the initial delay and large window size during decoding. We propose three approaches to decrease the syndrome former memory. Simulation results verify the UEP property of the constructed LDPC-CCs and the superiority over their QC-LDPC counterparts. Furthermore, the proposed approaches can also maintain competitive error performance while reducing the syndrome former memory.

Abstract
Contents
Chapter 1 Introduction-------------------------------------------- 1
Chapter 2 Low-Density Parity-Check Convolutional Codes------------ 3
Chapter 3 UEP LDPC Convolutional Codes----------------------------15
Chapter 4 Simulation Results--------------------------------------40
Chapter 5 Conclusion----------------------------------------------60
Bibliography------------------------------------------------------61

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