“k秩”融合协作频谱感知算法中最优k值的判定

The Decision of the Optimal K Value in K-rank Fusion Collaborative Spectrum Sensing Algorithm

在认知无线网络中,"k秩"融合是协作频谱检测中一种十分具有概括性的检测方法。认知节点数M一定,k值取值不同时,融合中心的融合效果也不同。而当认知节点数量较大时,通过实验的方法逐一比较找出最优的情况会浪费很多时间和资源,并不适合延时敏感型网络。本文在已知认知节点数M的情况下,给出了最优的融合效果下对应的k值的简单方法,此方法可以节约k值寻找时间,降低融合判决复杂度。

As a kind of collaborative spectrum sensing algorithm in cognitive radio networks,the K-rank fusion spectrum sensing algorithm is a very recapitulative algorithm. When the number M of cognitive users is settled,if the k value is changed,the results of spectrum sensing will be different. And if there is a large sum of cognitive users,it will be difficult tofind out the best k value through experiments. It will cost a lot of time and resources,which will not be applied to delay-sensitive networks. In this paper,a simple method to determine the optimal K value is proposed under the best fusion effect when M is given. This method can save the time for searching K value and reduce the complexity of fusion decision.