5G新型多载波信号识别算法研究  

Research on 5G New Multi-carrier Signal Recognition Algorithm

作　　者：韩磊 胡国兵 杨莉 赵嫔姣 Han Lei;Hu Guobing;Yang Li;Zhao Pinjiao(School of Electronics and Optical Engineering,School of Microelectronics,Nanjing University of Posts and Telecommunications,Nanjing 210023,China;School of Electronic Information Engineering,Jinling Institute of Technology,Nanjing 211169,China)

机构地区：[1]南京邮电大学电子与光学工程学院、微电子学院,南京210023 [2]金陵科技学院电子信息工程学院,南京211169

出　　处：《信息化研究》2020年第6期8-16,共9页INFORMATIZATION RESEARCH

基　　金：江苏省高等学校自然科学研究重大项目(No:20KJA510008);江苏省基础研究计划(自然科学基金)(No:BK20161104);金陵科技学院高层次人才引进项目(No:jit-b-201630)。

摘　　要：文章提出了一种基于极值分布理论及小波变换特征分析的5G新型多载波信号识别算法,可对OFDM、FOFDM、FBMC及UFMC等4种常用多载波信号进行有效识别。首先,通过极值分布拟合检验实现对OFDM类信号与非OFDM类信号的类间识别,而后利用Haar小波变换提取多载波信号频谱的小波变换模值特征以实现类内识别。仿真结果表明,在信噪比5 dB时,算法的平均识别正确率可以达到85%以上。This paper proposes a new 5 G multi-carrier signal identification algorithm based on extreme value theory and wavelet transform feature analysis, which can identify four common multi-carrier signals such as OFDM, FOFDM, FBMC and UFMC. Firstly, the extreme value theory distribution fitting test is used to realize the inter-class identification of the OFDM signal and the other two signals, and then the Haar wavelet transform is used to extract the wavelet transform modulus characteristics of the multi-carrier signal spectrum to perform the intra-class identification. The simulation results show that when the signal-to-noise ratio is 5 dB, the average recognition accuracy of the proposed algorithm is up to 85 percent.

关 键 词：多载波信号识别 极值分布 小波变换 5G 

分 类 号：TN929.5[电子电信—通信与信息系统]