基于快速变极化的认知无线电频谱感知算法

Rapid Polarization Adaptation Based Spectrum Sensing Algorithm for Cognitive Radios

为充分利用授权信号的极化状态矢量信息进行频谱感知,该文提出一种基于K臂赌博机的快速变极化算法,通过将双自由度搜索问题转化为K个1维问题,能够实现满足实时频谱感知要求的授权信号极化状态识别。给出了算法收敛时预期收益的上下确界。最后分析了基于该算法进行极化匹配接收的频谱感知性能。仿真结果表明,算法能够快速收敛,并高精度识别授权信号极化状态,对频谱感知性能提升显著。

To utilize the polarization state of primary signal which is the crucial vector characteristic for spectrum sensing,a rapid polarization adaptation algorithm is proposed based on the K-armed bandit.The proposed algorithm can reduce the complexity and converge rapidly by transferring the two-degree-of-freedom search issue to K single-dimensional issues,and identify the polarization state of primary signal to realize real-time spectrum sensing for Cognitive Radios（CR）.Further,the theoretical boundary of the proposed algorithm is derived.The spectrum sensing performance on the basis of the polarization state identification is discussed by receiver operation characteristic curve finally.The simulation results show that the proposed algorithm converges fast,and obtains a high accuracy on polarization state identification for primary signal.The detection performance is more effective with the rapid polarization adaptation.