【摘要】 多维主用户信号检测是认知无线电系统中需要解决的主要问题之一.传统的主用户检测方法主要集中在频域检测,检测结果仅给出主用户对某频段的占用状态.针对频率-时间域的主用户检测技术,提出了利用AR谱估计方法估计接收信号的距离-多普勒谱图,以谱图的峰值大小作为检测统计量来判断是否有主用户信号,推导出检测概率和虚警概率表达式.利用MATLAB软件进行仿真,得到了ROC曲线,并与常用的能量法进行对比.仿真结果证实了低信噪比条件下AR模型比能量法有更好的检测性能.同时对AR模型的最佳阶数选择进行了初步探讨.更多还原

【Abstract】 The multi-dimensional detection of primary user is one of the essential problems in cognitive radio.The conventional detection shows only the spectral occupancy.Here we propose a method based on auto-regressive(AR)spectral estimation to go around the frequency-time detection for primary users in low singal-tonoise ratio(SNR).The proposed method uses AR spectral estimation to estimate the Range-Doppler spectrum of received signal,and then considers the peak of Range-Doppler spectrum as the test statistic.The expressions of the detection probability and false probability are deduced respectively.The simulation by MATLAB shows the spectral occupancy in the frequency-time dimension,receiver operating characteristic(ROC)curve.It confirms the AR model spectrum sensing has better performance than the energy detection in cognitive radio.Meanwhile,we also research the optimal order of AR model.更多还原