论文部分内容阅读
在认知无线电网络中,主用户状态改变和低信噪比都会造成频谱检测的性能下降.本文提出了一种新的加权(weight-p)能量检测算法,用于抵抗主用户状态改变和低信噪比对认知用户检测性能的影响.为减少实现复杂性和节约需要的功耗,我们将weight-p能量检测器的最优权值建模成一个最小采样时间(MST)的优化问题,找出了最优权值和次优权值.仿真表明,在主用户状态改变和低信噪比的场景下,本文提出的weight-p能量检测算法可以提高认知用户的检测性能和降低虚警概率,并且在获得相同检测性能的前提下可以压缩检测时间.
In the cognitive radio network, the change of the primary user state and the low signal-to-noise ratio all lead to the performance degradation of the spectrum detection.In this paper, a new weight-p energy detection algorithm is proposed to resist the change of the primary user’s state and low Effect of Signal-to-Noise Ratio on Cognitive User Detection Performance In order to reduce the power required to achieve complexity and save power, we model the optimal weight of the weight-p energy detector as an optimization problem with a minimum sampling time (MST) , And finds the optimal weights and sub-optimal weights.The simulation shows that the weight-p energy detection algorithm proposed in this paper can improve the detection performance and reduce the cognitive users under the condition of changing the state of the primary user and the low signal-to-noise ratio False alarm probability, and can achieve the same detection performance under the premise of compressing the detection time.