本論文中，針對應用於感知無線電網路的合作式感測之傳統AND/OR方法進行改善，我們提出了新的次要使用者的決策方式。並讓次要使用者們根據自身的感測狀況來決定自己是否參與合作決策。此新決策方法將可大量的節省次要使用者的傳輸功率消耗且強化合作式決策的效能。而我們也會針對根據K-means分群法之決策方式中次要使用者的消耗功率進行限制，並在同樣的限制條件下和我們的新方法進行比較。

In this thesis, we improve the performance of traditional cooperative sensing methods used in cognitive radio (CR) networks by proposing new local decision rules at Secondary Users (SUs). And let each SU decide whether to participate in the cooperative sensing process based on the decision method and the samples received in the past period of time. After proving the new decision-making methods enable to save total SU power consumption while improving decision-making efficiency. We regard the total transmit power of SUs as a constraint and we also let our new decision-making method and the method of using machine learning technology be compared under fair conditions.

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