全像光資訊儲存系統的讀取和解碼方法;Reading and Decoding Methods for Holographic Data Storage Systems

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题名:	全像光資訊儲存系統的讀取和解碼方法;Reading and Decoding Methods for Holographic Data Storage Systems
作者:	史育銓;Shi, Yu-Quan
贡献者:	通訊工程學系
关键词:	全像光資訊儲存系統;低密度奇偶檢查碼;HDS;LDPC
日期:	2025-09-22
上传时间:	2025-10-17 12:27:27 (UTC+8)
出版者:	國立中央大學
摘要:	本論文基於理論模型的設計，整合繞射影像輸出與多頁資料編碼，並充分考量讀取過程中因光學擴散（Blur）與雜訊所造成的影響，在資料編碼端，我們利用以前論文所建立的不同點亮個數並排除高錯誤率圖樣的稀疏碼表，使每個四乘四稀疏碼區塊的資訊容量由原本九位元提升至最多十三位元，同時降低光學擴散導致的錯誤。本研究可分為兩部分：第一部分針對已知光學擴散資訊，分別設計對應的解碼法，分析模糊與雜訊的聯合作用，並結合低密度奇偶檢查碼(Low-density parity-check code，LDPC )進行編解碼。此外，我們提出邊界感知解碼法，利用已解碼區塊的擴散邊界畫素作為先驗資訊，顯著提升模糊資訊的精度。第二部分則進一步將LDPC解碼過程中的迭代機率更新機制，應用於稀疏碼與無稀疏碼的情況，並於無稀疏碼情況下搭配編碼端間隔儲存策略，有效抑制光學擴散對系統性能的影響。實驗結果顯示，所提方法在多種模糊與雜訊條件下皆能顯著降低位元錯誤率，提升全像光儲存系統的可靠性與容錯能力。 ;This thesis is based on a theoretical model design that integrates diffraction image output with multi-page data encoding, while fully accounting for the effects of optical blur and noise during the reading process. On the encoding side, we adopt previously developed sparse code tables with different numbers of activated pixels, excluding high-error patterns. This increases the information capacity of each 4×4 sparse code block from 9 bits to as many as 13 bits, while simultaneously reducing errors caused by optical blur. The study is divided into two parts. In the first part, decoding methods are designed for known blur conditions to analyze the joint impact of blur and noise, combined with low-density parity-check (LDPC) coding and decoding. In addition, we propose a boundary-aware decoding method that leverages the blurred boundary pixels of previously decoded blocks as prior information, thereby significantly enhancing the accuracy of blur compensation. In the second part, we further incorporate an iterative probability update mechanism within the LDPC decoding process, applying it to both sparse-coded and non-sparse-coded cases. For the non-sparse-coded case, we also adopt an interleaving storage strategy at the encoding stage to effectively suppress the impact of optical blur on system performance. Experimental results demonstrate that the proposed methods can substantially reduce the bit error rate under various blur and noise conditions, thereby improving the reliability and fault tolerance of holographic data storage systems.
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