以群眾外包進行頻譜感測之研究

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姓名	蔡宗宏(Tsung-Hung Tsai) 查詢紙本館藏	畢業系所	通訊工程學系
論文名稱	以群眾外包進行頻譜感測之研究
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摘要(中)	群眾外包模式(Crowdsourcing model) 應用於合作式頻譜感測(Cooperative spectrum sensing) 環境，對於頻譜資訊的獲取上，是一項新穎的感測技術。近年來，在頻譜共享(Spectrum sharing) 的模式中，共享使用者(Secoundary users)，將其所檢測到既有使用者頻譜資訊分享至頻譜資訊彙整中心(Fusion center)，即群眾外包及合作式頻譜檢測結合應用的案例之一。但實際上，這樣的技術中存在著許多不安定的因素，譬如: 檢測頻譜的誤差、惡意使用者的存在等，都會干擾共享使用者們自頻譜彙整中心來獲取正確的頻譜資訊。因此，本論文中提出，合作式頻譜檢測的架構下，新穎的群眾外包演算法。其中引進在群眾外包模式下重要參數，使用者所回覆資訊的同意比率(Agreement ratio)。此演算法不但可以精準的找出本次檢測頻譜的任務中，所存在的惡意使用者，同時提升頻譜檢測的正確率，最後，在模擬的結果中可以發現，本論文所提的演算法，比其他方法會有較好的偵測頻譜及惡意使用者精準度。
摘要(英)	Cooperative spectrum sensing with the crowdsourcing model has become an innovative and efficient technique for obtaining the spectrum state information (SSI) under the cognitive radio networks. Specifically, the secondary users sense the licensed spectrum then send the SSI back to the fusion center according to the crowdsourcing model. In practice, the users with malicious or erroneous behavior are always existing among those secondary users. Thus the accuracy of spectrum sensing would be influenced by those users. In this paper, a novel crowdsourcing algorithm for cooperative spectrum sensing is proposed to detect the malicious users and further improve the accuracy of spectrum sensing. The agreement ratio is introduced in the proposed scheme, which is an important information under the crowdsourcing framework. Simulation results show that the proposed algorithm possesses better performance than the existing approaches.
關鍵字(中)	★ 群眾外包 ★ 頻譜感測 ★ 惡意使用者	關鍵字(英)	★ Crowdsourcing ★ Spectrum sensing ★ Malicious users
論文目次	中文摘要 i 英文摘要 ii 目錄 i 圖目錄 ii 表目錄 iii 第1 章序論 1 1.1 頻譜資源短缺與頻譜共享技術 1 1.1.1 行動裝置的普及 1 1.1.2 頻譜資源有限 1 1.1.3 頻譜共享 2 1.2 現行頻譜感測技術 3 1.2.1 電波監測系統 3 1.2.2 群眾外包模式的頻譜感測系統 4 1.3 研究動機 6 1.4 章節架構 6 第2 章Background 7 2.1 頻譜共享 7 2.1.1 License Shared Access 7 2.1.2 Spectrum Access System 9 2.1.3 LSA 與SAS 的異同 11 2.2 頻譜感測技術 12 2.2.1 技術架構 12 2.2.2 群眾外包結合頻譜感測 14 2.3 群眾外包模式下的頻譜感測的問題 16 第3 章The Novel Crowdsourcing Algorithm 19 3.1 序論 19 3.2 系統架構 19 3.3 群眾外包頻譜檢測演算法 24 3.3.1 The degrees of Data Agreement 24 3.3.2 Joint Verification for Location and Reputation 25 3.3.3 Statistic of Reputation 27 3.3.4 The Novel Crowdsourcing Algorithm 28 第4 章系統模擬與結果分析 30 4.1 單一既有使用者 33 4.2 多位既有使用者 37 第5 章結論 44 參考文獻 45
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指導教授	鍾偉和張大中(Wei-ho Chung Dah-Chung Chang)	審核日期	2018-8-1
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博碩士論文 105523018 詳細資訊