研究生: |
林峻毅 Jyun-Yi Lin |
---|---|
論文名稱: |
使用有限域建構準循環低密度同位檢查碼在馬可夫高斯雜訊通道之研究 A study of Finite Field -based Quasi-cyclic LDPC Codes over Markov Gaussian Channels |
指導教授: |
曾德峰
Der-Feng Tseng |
口試委員: |
曾恕銘
Shu-Ming Tseng 賴坤財 Kuen-Tsair Lay 張立中 Li-Chung Chang |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 電機工程系 Department of Electrical Engineering |
論文出版年: | 2018 |
畢業學年度: | 106 |
語文別: | 中文 |
論文頁數: | 74 |
中文關鍵詞: | 低密度同位檢查碼 、馬可夫高斯 、有限域 、準循環 、和積演算法 、MAP估測器 |
外文關鍵詞: | Low-Density Parity Check Codes, Markov-Gaussian, Finite Field, Quasi-cyclic, Sum-Product Algorithm, MAP Estimation |
相關次數: | 點閱:427 下載:5 |
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本篇論文探討在馬可夫高斯通道下不同碼率低密度同位檢查碼(LDPC)的表現
。我們是基於有限域的加法組(Additive Group)來建構同位檢查矩陣的,其矩陣為一個準循環的形式。並分別在不同通道環境中模擬。建立在有限域的低密度同位檢查碼,其在可加性高斯白雜訊(AWGN)通道下擁有很好的表現,更重要的是,這種有限域低密度同位檢查碼被證明具有低的錯誤層次(error floor),此種特性對於通訊或資料儲存系統相當重要。而大部分建立在有限域的低密度同位檢查碼是準循環的,因此能夠利用簡單的位移暫存器[1]進行編碼且具有低的線性複雜度[2]。在對於有線或無線通訊中,脈衝雜訊是一個重要的議題。由於常見的脈衝雜訊通道模型,屬於無記憶性型,其發生雜訊的時機具有隨機性,無法去描述真實通道的特性,故發展出基於馬可夫鏈特性的雜訊碼可夫高斯通道模型(Markov-Gaussian Channel)。
為了解決脈衝雜訊,在本論文中使用了基於有限域的QC¬-LDPC結合了最大後驗機率(MAP)來進行通道估測並且利用和使用積演算法(SPA)進行解碼以降低位元錯誤率。
In this paper, we study the performance of LDPC code which have different Coding rate over Markov-Gaussian channels. We construct parity check matrices base on subgroups of a finite field, and its matrix is a quasi-cyclic form. And simulation in different channel environment. LDPC code which based on finite fields perform well over the binary-input AWGN channel. Most importantly, these finite-field LDPC codes were shown to have low error floors, which is important for communication and data-storage systems. Most of the LDPC code constructions base on finite fields are quasi-cyclic and hence they can be efficiently encoded using simple shift-registers[1] with linear complexity[2]. In the wired and wireless communication systems Impulse noise is a important issue . The common impulse noise models. they are memoryless, which mean that their occurrences are random. However, they can’t describe the characteristics of the real channel. A memory channel such as Markov-Gaussian is introduced to address the characteristics of the real channel.
To address the impulsive noise, QC-LDPC base on finite field is used in this paper to combine the maximum a posteriori (MAP) Estimation for channel estimation and use the SPA algorithm to reduce the bit error rate.
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