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研究生: 劉芳伶
Fang-Ling Liu
論文名稱: 基於瞬時時域特徵值的自動調變識別系統之研究
Research on Automatic Modulation Classification System Based on Instantaneous Time Domain Features
指導教授: 張立中
Li-Chung Chang
口試委員: 曾恕銘
Shu-Ming Tseng
曾德峰
Der-Feng Tseng
劉馨勤
Hsin-Chin Liu
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: 76
中文關鍵詞: 自動調變識別瞬時時域特徵決策樹辨識率複雜度
外文關鍵詞: Automatic Modulation Classification, Instantaneous Time Domain Feature, Decision Tree, Probability of the Correct Classification, Complexity
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在通訊系統中其調變方式為此系統重要的特徵之一,每個領域例如軟體無線電、感知無線電、軍事通訊等均有不同調變環境之設置,需在環境與雜訊干擾下確定系統的調變方式,才能進一步分析與處理系統的通訊訊號。自動調變識別系統(Automatic Modulation Classification System, AMC System)之目的為在沒有任何先驗知識的情況下,只對接收訊號進行計算分析並判斷出該訊號的調變方式。隨著通訊技術的發展,調變方式種類日益增加,其複雜度也逐漸上升,AMC系統的設計也在接收端中扮演重要的角色。
AMC系統之基本架構為特徵擷取與分類器,兩者皆有數種不同方法,可互相組合成多種AMC系統,對應於不同的環境通道。本篇論文將文獻上在特徵擷取中絕大部分使用瞬時時域(ITD)特徵值與在分類器中使用決策樹(DT)分類器的論文加以探討並比較。
在絕大部分使用ITD特徵值的條件下,比較不同DT分類器之做法並觀察其調變識別結果,本論文由此比較結果提出兩個新的AMC系統,其一為在比較對象的DT分類器中,提升平均正確調變辨識率之系統;其二為在比較對象的DT分類器中,降低平均計算複雜度之系統。


The modulation type is one of the important properties in the communication system. Each field has different complicated environment settings. It is necessary to determine the modulation type under the complicated environment and noise interference so that the system could receive and analyze the transmitted signal. The purpose of the Automatic Modulation Classification(AMC) system is to analyze the received signal and determine the modulation type of the signal without any prior knowledge. With the development of the communication technology, the variety of the modulation type is increasing, and its complexity is also gradually increasing. So, the design of the AMC system plays an important role in the receiver.
The basic architecture of the AMC system is feature extraction and classifier. Both have several different methods, which can be combined into different AMC system, corresponding to different environment. This paper selected the literature using ITD features in feature extraction and DT classifier in classifier.
Under the condition that the ITD features are used, compare the different DT classifiers and observe the probability of correct classification of each DT classifier. This paper proposed two new AMC systems based on the comparison of the probability of correct classification of each DT classifier. The first system improves the average of the probability of correct classification over the DT classifiers. The second system reduces the average of complexity over the DT classifiers.

摘要 I Abstract II 致謝 III 目錄 IV 圖目錄 VI 表目錄 VIII 第1章 序論 1 1.1 研究動機與目的 1 1.2 論文架構 2 第2章 相關理論介紹與文獻回顧 3 2.1 自動調變識別系統 3 2.1.1 發展概況 3 2.1.2 基本架構 4 2.2 特徵擷取 5 2.2.1 調變訊號數學模型 5 2.2.2 瞬時時域特徵值 7 2.2.3 非瞬時時域特徵值 11 2.3 分類器作法 13 2.3.1 人工神經網路分類器 13 2.3.2 支援向量機分類器 15 2.3.3 決策樹分類器 16 第3章 提出方法與系統架構 26 3.1 提升平均正確辨識率的方法 26 3.1.1 五個已擴充後的決策樹方法之平均辨識率 26 3.1.2 基於同族群調變之平均正確辨識率最高的路徑選取 30 3.1.3 路徑結合之系統架構 31 3.2 降低平均複雜度的方法 33 3.2.1 五個已擴充後的決策樹方法之平均計算複雜度 34 3.2.2 基於同族群調變之平均計算複雜度最低的路徑選取 35 3.2.3 路徑結合之系統架構 37 第4章 模擬結果與討論 39 4.1 辨識率效能分析 39 4.1.1 辨識單載波與多載波系統之效能 39 4.1.2 基於5種原始決策樹共有之調變效能比較 40 4.1.3 基於5種已擴充後的決策樹效能比較 43 4.1.4 提升平均正確辨識率的方法與5種原始決策樹效能比較 49 4.1.5 提出之兩個方法與5種擴充後決策樹效能比較 53 4.1.6 傳送不同取樣數之效能比較 56 4.1.7 傳送不同載波頻率之效能比較 57 4.2 複雜度分析 59 4.2.1 降低平均複雜度的方法與5種擴充後決策樹複雜度比較 59 4.2.2 降低平均複雜度的方法與5種原始決策樹複雜度比較 59 第5章 結論與未來方向 61 參考文獻 63

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