基于频谱感知的认知Ad hoc网络分簇算法

为了提高认知Ad hoc网络频谱感知效率，解决认知Ad hoc网络分簇问题，本文提出一种基于频谱感知的认知Ad hoc网络分簇算法。通过引入检测因子，综合考虑多个主用户信号交叠与阴影衰落的情况，将认知Ad hoc网络中的次用户节点与需要检测的主用户信道建模为二部图模型，使得分簇问题简化为最大权边二部图（Constraint maximum-weight edge biclique, C-MWEB）分解问题，并设计一种贪婪算法对其求解。仿真结果表明，在多个主用户信号交叠与阴影衰落并存的情况下，相较于传统算法，本文算法分簇更为合理，具有更好的有效性与可靠性。

Clustering Scheme Based on Spectrum Sensing in Cognitive Radio Ad hoc Networks

To improve the spectrum sensing efficiency of cognitive radio Ad hoc networks and to solve the problem of cognitive radio Ad hoc networks clustering, a clustering scheme based on spectrum sensing for cognitive radio Ad hoc networks clustering is proposed. By introducing the detection factor, considering multiple primary user signals overlapping and shadow fading effect, the clustering problem of secondary users and primary user channels is mapped to bipartitie model. Then the clustering problem can be simplified to constraint maximum-weight edge biclique(C-MWEB) decomposition problem and solved by greedy algorithm. Simulation result shows that the proposed clustering scheme is more effective and reliable than the traditional one in the case of multiple primary user signals overlapping and shadow fading effect.