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。;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.
