基于隐马尔可夫模型和状态持久性的动态频谱检测  

Dynamic Spectrum Detection Based on HMM and State Persistence

作　　者：郭德超 张豪[2] GUO Dechao;ZHANG Hao(School of Public Health and Management,Guangzhou University of Chinese Medicine,Guangzhou 510006,China;Guangzhou Center for Disease Control and Prevention,Guangzhou 510440,China)

机构地区：[1]广州中医药大学公共卫生与管理学院,广州510006 [2]广州市疾病预防控制中心,广州510440

出　　处：《计算机测量与控制》2022年第12期91-97,共7页Computer Measurement &Control

基　　金：国家自然科学基金委员会面上项目(81973979);广东省中医药健康服务与产业发展中心(2020YJZX016)。

摘　　要：针对复杂无线通信环境中的动态频谱接入进行了研究,提出了一种基于隐马尔可夫模型和状态持久性的动态频谱检测方案;具体来说,提出的方案在能量窗口检测的基础上,首先将每个主用户随时间变化的信号能量表示为一个随机过程,然后利用隐马尔可夫模型和状态持久性的概念设计出了两种检测器来检测这些主用户和二级用户之间的差异,并尝试根据它们的统计特征来区分信号,从而提高可用空白频谱的检测精度和它们的动态频谱接入能力;仿真实验结果表明,提出的方案不仅可区分复杂无线通信环境中的传输源,而且还可提高动态频谱检测的性能。Dynamic spectrum access problem in complex wireless communication environment is studied in this paper,and a dynamic spectrum detection scheme based on hidden Markov model(HMM)and state persistence is proposed.Specifically,on the basis of the energy window detection,firstly,the proposed scheme represents that the signal energy of each primary user changing with time is represented as a random process,secondly,two detectors are designed to detect the differences between the primary and secondary users by using the HMM and concept of state persistence,and try to distinguish the signal according to their statistical characteristics,so as to improve the detection accuracy of available white spectrum and access ability of the dynamic spectrum.The simulation results show that the proposed scheme can not only distinguish the transmission source in the complex wireless communication environment,but also improve the performance of the dynamic spectrum detection.

关 键 词：无线通信环境 频谱利用 能量窗口检测 隐马尔可夫模型 状态持久性 检测精度 

分 类 号：TN925[电子电信—通信与信息系统]