主用户状态改变和低信噪比环境下的weight-p能量检测算法

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.

A new weight--p energy detector for primary user status changes and low SNR environments

Spectrum-sensing performance is significantly degraded as the primary user＇s status changes with randomly arriving or leaving signals in a low Signal-to-Noise （SNR） environment in cognitive radio networks. This paper presents a new weight -p Energy Detector （ED） to improve the detection performance in these situations. To reduce the implementation complexities and save energy consumption, the optimum weight operation of weight - p ED is modeled as a Minimum Sampling Time （MST） optimization problem, and the optimum and sub-optimal weights are obtained through our analyses. Numerical simulation results show that the proposed weight - p ED offers better detection performance with a reduced probability of false alarms, and compresses sensing time compared with conventional ED for the same detection performance.