基于Stackelberg博弈的多任务协作频谱感知算法

随着移动设备的增多,认知无线电技术诞生,而频谱感知是认知无线电技术中的重要一环。本文将群智感知和频谱感知结合,提出了一种基于Stackelberg博弈的多任务协作频谱感知算法。该算法将融合中心(平台)与次用户分别建模为Stackelberg博弈领导者和从属者。在领导者博弈中,平台给次用户发布最优的报酬值以获得最佳的效用;在从属者博弈中,本文着重考虑了剩余能量对次用户的影响,次用户在平台给的报酬下改变感知时间以获得最优的效用。仿真结果表明,该算法可以提高融合中心对频谱的检测概率。 

A multi-task cooperative spectrum sensing algorithm based on Stackelberg game

With the increase of mobile devices, cognitive radio(CR) has emerged as an innovative technology. Spectrum sensing is an important part of CR technology which can detect whether the primary user is present or not. A multi task cooperative spectrum sensing algorithm based on Stackelberg game is proposed in this paper, which applies crowd sensing and game theory to study spectrum sensing. In the Stackelberg game, the fusion center (platform) is modeled as the leader, while secondary users are modeled as the follower. In the leader game, the platform publishes the optimal reward value to the secondary users to get the optimal utility. In the follower game, we focus on the influence of residual energy on the secondary users. In this stage, the secondary users under the same task constantly adjust their participation time under the reward of the platform to achieve equilibrium. Eventually, the secondary users can obtain their own optimal utility. The simulation results show that the algorithm can improve the detection probability of the fusion center.