基于模糊推理的CRN协作频谱感知方案

摘要

为提高认知无线电网络(CRN)中协作频谱感知的性能,提出一种基于自适应参数调整模糊推理系统的协作频谱感知方案.每个二级用户(SU)测量其在感兴趣频带上接收信号的能量,将其观测数据传输到融合中心(FC);FC使用在线学习方法,根据接收到的数据自适应调整Takagi-Sugeno模糊系统参数;利用自适应模糊系统估计信号的均值和方差,推理主要用户(PU)信号的当前状态,以此做出最终协作感知决策.实验结果表明,该方案具有较高的检测率和较低的虚警率.%To improve the performance of collaborative spectrum sensing in cognitive radio networks (CRN), a cooperative spectrum sensing scheme based on a fuzzy inference system with adaptive parameter adjustment was proposed.Each of the second users (SU) measured the received signal energy in the interest frequency band, and the observation data was transmitted to the fusion center (FC).The FC used the online learning method to adaptively adjust Takagi-Sugeno fuzzy system parameters according to the received data.The adaptive fuzzy system was used to estimate the mean and variance of primary user (PU) signal, which was used to infer the PU's current state, and then the final decision of cooperative sensing was made.Experimental results show that this scheme has higher detection rate and lower false alarm rate.