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研究生:林尹泰
研究生(外文):Yin-Tai Lin
論文名稱:極化碼基於不同解碼方式 之效能分析比較
論文名稱(外文):Polar Code Over Different Decoding Method For Performance Analysis Comparison
指導教授:曾德峰曾德峰引用關係
指導教授(外文):Der-Feng Tseng
口試委員:賴坤財張立中曾恕銘陳永芳曾德峰
口試委員(外文):Lay,Kuen-TsairLi-Chung ChangShu-Ming TsengYang-Fang ChenDer-Feng Tseng
口試日期:2019-07-30
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:電機工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2019
畢業學年度:107
語文別:中文
論文頁數:78
中文關鍵詞:極化碼脈衝雜訊通道極化通道可靠性估測巴氏參數凍結位元系統性編碼接續消去解碼信仰傳送解碼剪裁器
外文關鍵詞:Polar codeImpulse channelPolarization channels reliability estimationBhattacharyya parameterFrozen bitssystematic encodingBelief Propogation decodingSuccessive Cancellation decodingclipper
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2008年在國際資訊理論ISIT會議上,土耳其畢爾肯大學教授Arikan首次提出了通道極化的概念,基於該理論,他給出了已知的第一種能夠被嚴格證明達到通道容量的通道編碼方法,並命名為極化碼(Polar code)。極化碼具有明確而簡單的編碼及解碼演算法,而在2016年,極化碼成為5GeMBB情況的控制通道編碼方案。對於有線通訊或無線通訊,脈衝雜訊是很嚴重的問題,瞬間的強力干擾不僅會破壞傳送的訊號,還會使系統在資料的解讀上產生大量的錯誤。常見的脈衝雜訊模型可分為有記憶型態的Markov-Gaussian通道模型以及無記憶型態的Bernoulli-Gaussian和Additive White Class A Noise通道模型。本篇論文將利用巴氏參數對極化通道進行2種可靠度估測方式來編制凍結位元(frozen bits)以及利用系統性編碼(systematic encoding)、系統性接續消去解碼(systematic Successive Cancellation decoding)和系統性信仰傳送解碼(systematic Belief Propogation decoding)並加入剪裁器所造出的極化碼在無記憶型態的脈衝雜訊模型中的性能表現。
In 2008, at the meeting of International Information Theory ISIT, Professor Erdal Arikan of Bilkent University in Turkey first proposed the concept of channel polarization , and named it Polar Code. Based on this concept, polar codes, the first channel coding method that can be rigorously proved to achieve the capacity of the channel appeared. Polar code has a clear and simple encoding and decoding algorithm. In 2016, the polar code became the control channel coding scheme for the 5G eMBB scene.Impulse noise becomes one of the problems in the wired and wireless communication systems. As the impulse noise is different from the general AWGN noise, the energy of impulse noise is often hundreds of times that of the AWGN noise. Common impulse noise models can be divided into memory noise channels, Markov-Gaussian channel models, and memoryless noise channels, Bernoulli-Gaussian and Additive White Class A Noise channel. This paper will explore the performance of using 2 different polarization channels reliability estimation methods under Bhattacharyya Parameter to create frozen bits under memoryless noise channels, add clipper, and the performance of the polar codes generated by systematic encoding, systematic Successive Cancellation decoding and systematic Belief Propogation decoding.
第 1 章 緒論
1.1 研究背景
1.2 研究目的
1.3 章節概述
第 2 章 脈衝雜訊通道以及極化碼概述
2.1 簡介
2.2 脈衝雜訊模型環境建立
2.2.1 Bernoulli-Gaussian (BG) 脈衝雜訊模型
2.2.2 Additive White Class A Noise脈衝雜訊模型創建
2.2.3 AWAN脈衝雜訊和BG脈衝雜訊比較
2.3 極化碼(Polar code)概述
2.3.1 極化碼概述
2.3.2 通道極化
2.3.3 編碼
2.3.4 系統編碼(systematic encoding)
2.3.5 解碼
2.3.6 解碼器設計
2.3.7 BP解碼使用Early Stopping Criteria
第 3 章 通道可靠度設計以及剪裁器的使用
3.1 極化通道可靠度估測
3.1.1 極化通道脈衝雜訊位置可靠度估測
3.1.2 極化通道脈衝雜訊統計特徵可靠度估測
3.2 裁剪器的使用
3.2.1 裁剪器臨界值選取
第 4 章 模擬結果
4.1 在AWGN下模擬結果
4.2 在脈衝雜訊下模擬結果
4.2.1 在Bernoulli-Gaussian通道上的模擬結果
4.2.2 在Additive White Class A Noise通道上的模擬結果
4.3 在脈衝環境下使用裁剪器掃描臨界值模擬結果
4.3.1 BP在BG脈衝雜訊背景下之裁剪器掃描臨界值分析
4.3.2 BP在AWAN脈衝雜訊背景下之裁剪器掃描臨界值分析
4.3.3 SC在BG雜訊背景下之裁剪器掃描臨界值分析
4.3.4 SC在AWAN雜訊背景下之裁剪器掃描臨界值分析
4.4 在脈衝環境下加入剪裁器情境之模擬結果比較
4.4.1 BG脈衝雜訊通道下加入裁剪器之模擬比較
4.4.2 AWAN脈衝雜訊通道下加入裁剪器之模擬比較
4.5 BP解碼使用Early Stopping Criteria之模擬結果
4.5.1 使用Early Stopping Criteria在BG脈衝下之模擬結果
4.5.2 使用Early Stopping Criteria在AWAN脈衝下之模擬結果
4.5.3 使用Early Stopping Criteria在BG脈衝下clip之結果
4.5.4 使用Early Stopping Criteria在AWAN脈衝下clip之結果
4.6 結論
4.7 未來研究方向
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