基于CvM算法的Nakagami衰落信道统计特性检验

Nakagami信道通过不同的衰落因子m可以仿真不同的信道衰落环境，仿真数据与实际测量值吻合度较高，在信道仿真领域得到广泛应用。然而，目前针对Nakagami信道模型的可信性研究较少，缺少科学的比对验证方法。根据典型Nakagami信道的一阶包络序列服从Nakagami分布这一信道统计特性，提出一种基于Cramer-von Mises （CvM）算法的拟合优度检验方法。使用“高斯+瑞利+直流”组合法建立Nakagami衰落信道模型，得到信道输出序列并从中提取包络序列。在此基础上，利用双样本CvM检验算法对包络序列的理论分布和实际分布进行拟合优度检验，实现对Nakagami信道模型的可信性评估。半实物仿真结果表明，与K-S检验、卡方检验和Z检验+卡方检验融合检验算法相比，CvM针对不同m下的Nakagami衰落信道均具有较好的识别性能，同时在可靠性和复杂度方面也具有优势，其对虚警概率为0.01以下的Nakagami衰落信道识别准确率达到92.6%，对样本长度为300 000以上的Nakagami衰落信道平均识别准确率达到96.4%，而当待检验信道为其他信道时，不存在误识别的情况。

Statistical Characteristics Test of Nakagami Fading Channel Based on CvM Algorithm

The Nakagami fading channel model can simulate different channel fading environments using different values of fading factor m, and the simulation data are in good agreement with the actual measured values, which are widely used in the field of channel simulation.However, at present, there are few studies on the credibility of the Nakagami fading channel model, and there is a lack of scientific comparison and verification methods.According to the channel statistical characteristic that the first-order envelope sequence of a typical Nakagami channel obeys the Nakagami distribution, a goodness-of-fit test method based on the Cramer-von Mises (CvM) algorithm is proposed.The ‘Gaussian+Rayleigh+ DC’ combination method is used to develop the Nakagami fading channel model, which obtains the channel output sequence, and extracts the envelope sequence.On this basis, the two-sample CvM test algorithm is used to test the goodness-of-fit between the theoretical distribution and the actual distribution of the envelope sequence, to evaluate the credibility of the Nakagami fading channel model.The results of the hardware-in-the-loop simulation show that, compared with the K-S test, chi-square test, and Z+chi-square fusion test algorithms, the CvM algorithm has better recognition performance for Nakagami fading channels under different m values and has advantages in reliability and complexity.Its recognition accuracies for Nakagami fading channels with a false alarm probability of less than 0.01 and a sample length of more than 300 000 reach 92.6% and 96.4%, whereas for the other channels tested, there is no false recognition.