分簇认知网络中能量有效的协作频谱感知算法

An Energy-efficient Cooperative Spectrum Sensing Algorithm in Cluster-based Cognitive Radio Networks

针对认知网络中用户节点能量受限问题,提出了一种基于分簇网络的能量有效协作频谱感知算法。该频谱感知算法通过对用户节点分簇,缩短感知结果的传输距离。根据对授权用户信号的本地感知和簇内融合的判决结果,设计两次报告审查规则,减少传输感知结果的认知用户数量。以最小化协作频谱感知能耗为目标,建立多变量非线性优化问题模型,并通过逐一变量优化方法求得次优解。仿真结果表明,在保证检测性能的前提下,该算法能明显降低协作频谱感知的能量消耗和传输时延。

To solve the problem of energy-constrained in cognitive network nodes,a cluster-based energy-efficient cooperative spectrum sensing algorithm was proposed. The algorithm reduces the transmission distance of sensing by clustering,and according to the decision results made by local sensing and cluster fusing,the two-step censoring policy is designed to decrease the number of cognitive users involved in transmitting. In order to minimize the energy consumption of cooperative spectrum sensing,the multivariable nonlinear optimization model is established,and the sub-optimal solutions are obtained by the method of variable optimization. The simulation results show that,under the premise of ensuring the detecting performance,the proposed algorithm has a significant decrease in the energy consumption and transmission delay.