一种低复杂度的最大化资源效用的最优感知节点数目优化算法

协作频谱感知技术是认知无线电中的重要技术.首先定义了认知网络的效用函数,该函数考虑了协作频谱感知中的感知错误概率和感知用户所占用的资源以平衡感知性能和资源利用效率.然后推导了在所有感知用户的信噪比相近的情况下,为达到资源效用最大化所需要的最优的感知用户数目.仿真结果表明通过最优感知用户数目的选择,认知网络的效用高于其他算法,并和穷举算法的效用接近,但是计算复杂度大为降低,从而降低融合中心的计算能耗,有助于绿色节能认知网络的实现.

A low complexity optimal number of secondary user selection algorithm through maximizing resource utility

Spectrum sensing is a key technology in Cognitive Radio (CR) and cooperative spectrum sensing is derived due to the effects of channel fading. We focus on the optimal number of secondary users in cooperative spectrum sensing to maximize the utility in CR networks. By considering both the detection error probability and the resource used by the secondary users in cooperation, we derive the analytical suboptimal number of secondary users in a special CR network where all the Sus have the same SNR. The simulation results show that the utility of suboptimal scheme is greater than that of other schemes and nearly the same as that of the optimal scheme with exhaust search. The energy cost of the fusion center is reduced and it is conducive to the realigation of the green energy-saving cognitive communication network.