利用功率谱最大最小平均比的频谱感知算法

Spectrum Sensing Algorithm Using the Ratio of Average Value of Maximum and Minimum Power Spectral

由于载波频偏未知和噪声不确定性影响,信号功率谱的最大值和最小值不能根据单个频点来准确估计。该文提出利用功率谱最大最小平均比的频谱感知算法。利用基频附近一段功率谱的平均值作为功率谱最大值估计,利用功率谱中点频率附近一段的平均值作为功率谱最小值估计,将此二者之比作为检测统计量。推导了算法的虚警概率,得到了判决门限。加性高斯白噪声信道和瑞利衰落信道下的仿真结果表明:该算法性能优于基于功率谱分段对消频谱感知算法(PSC)和基于功率谱的平均比值算法(PSRA),降低了载波频偏未知和噪声不确定性对频谱感知算法性能的影响。

Owing to the influence of unknown carrier offset and noise uncertainty,the maximum value and the minimum value of signal＇s power spectral were unable to be evaluated by frequency single point. The spectrum sensing algorithm using the ratio of average value of maximum and minimum power spectral was proposed. This algorithm was specifically designed as follows. Firstly,the maximum value was estimated by the power spectral average of neighboring points to the base frequency,and the minimum value was estimated by the power spectral average of neighboring points to the midpoint frequency. Secondly,the ratio of the maximum and the minimum value was used as the detection statistics. Finally,the algorithm＇s false alarm probability and a detection threshold were deducted. The simulation results in Additive White Gaussian Noise channel and Rayleigh fading channel show that the proposed algorithm is better than the PSC、PSRA algorithm,and the influence of the unknown carrier offset and noise uncertainty on the algorithm is reduced.