全像光資訊儲存系統的編解碼;Coding for Holographic Data Storage System

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Title:	全像光資訊儲存系統的編解碼;Coding for Holographic Data Storage System
Authors:	劉宜鈞;Liu, Yi-Chun
Contributors:	通訊工程學系
Keywords:	全像光資訊儲存系統;低密度奇偶檢查碼;稀疏碼;Holographic Data Storage System;LDPC code;Sparse code
Date:	2024-07-24
Issue Date:	2024-10-09 16:40:48 (UTC+8)
Publisher:	國立中央大學
Abstract:	在本論文中，我們設計出一套應用於全像光資訊儲存系統的編解碼。我們建立了不同點亮個數與刪除易錯圖形的稀疏碼編碼表，資料位元能經由此編碼表選擇光亮暗樣式。對於每個四乘四畫素，我們讓原本九位元的資料量提升到最高十三位元，並降低擴散造成的影響。本論文可分為兩部分，第一部分只考慮擴散的影響，此時使用稀疏碼，而解碼有事先不知道或事先知道擴散影響的兩種方式。第二部分考慮擴散和雜訊的影響，我們使用稀疏碼和低密度奇偶檢查碼，而解碼有事先不知道或事先知道擴散影響的硬決策或軟決策六種方式，其中事先知道擴散影響的軟決策在所有方法中，具有最低的位元錯誤率。;In this paper, we design a coding scheme for holographic data storage system. We establish sparse code tables with varying numbers of illuminated pixels and deletion of error-prone patterns, enabling data bits to be selected for light and dark patterns using these tables. For each four-by-four pixel block, we increase the original data bits from nine bits to a maximum of thirteen bits, while reducing the impact of blur. This paper can be divided into two parts: the first part considers only the impact of blur, using sparse code, with decoding methods that either do or do not have prior knowledge of the blur impact. The second part considers both blur and noise, using sparse code and low-density parity check code, with six decoding methods: hard and soft decisions, each with or without prior knowledge of the blur impact. Among these, the soft decision method with prior knowledge of the blur impact has the lowest bit error rate.
Appears in Collections:	[Graduate Institute of Communication Engineering] Electronic Thesis & Dissertation

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