引用本文:刘宝,邓军,王伟峰,等.基于多模型假设检验的认知无线电频谱感知方法[J].控制与决策,2020,35(8):1909-1915
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基于多模型假设检验的认知无线电频谱感知方法
刘宝1, 邓军2, 王伟峰2, 王静婷3, 黄梦涛1
(1. 西安科技大学电气与控制工程学院,西安710054;2. 西安科技大学安全科学与工程学院,西安710054;3. 西安翻译学院工程技术学院,西安710105)
摘要:
提出一种基于序贯概率似然比多模型假设检验的认知无线电协作频谱感知方法,用于检测可能含有不同结构和参数不确定性的未知信号.传统的认知无线电协作频谱感知方法(如基于序贯概率似然比的单模型假设检验、M元假设检验等),仅限于处理已知信号分布,不考虑信号分布的不确定性,可能会造成检测误判.所提出方法不仅可以处理认知无线电信号分布模型的不确定性问题,而且可以得到满足错误概率约束的有效检测.对频谱感知的一个典型场景进行仿真实验,结果表明所提出基于序贯概率似然比多模型假设检验方法相对于传统方法的检测有效性.
关键词:  认知无线电  频谱感知  多模型假设检验  序贯概率似然比检验
DOI:10.13195/j.kzyjc.2018.1669
分类号:TN98
基金项目:国家自然科学基金项目(61703329);陕西省教育厅科研计划项目(17JK0504,18JK1005);陕西省自然科学基础研究计划项目(2018JQ5197);中国博士后科学基金项目(2018M633538);西安科技大学科研培育基金项目(201738);西安科技大学博士学位获得者科研启动基金项目(2016QDJ039,2016QDJ033).
Cognitive radio spectrum sensing approach based on multiple-model hypothesis testing
LIU Bao1,DENG Jun2,WANG Wei-feng2,WANG Jing-ting3,HUANG Meng-tao1
(1. College of Electrical and Control Engineering,Xián University of Science and Technology,Xián 710054,China;2. School of Safety Science and Engineering,Xián University of Science and Technology,Xián 710054,China;3. Department of Engineering and Technology,Xián Fanyi University,Xián 710105,China)
Abstract:
This paper presents a multiple-model hypothesis testing approach based on sequential probability ratio test for cognitive radio spectrum sensing to detect unknown signal that may have multiple possible distributions with different structural or parametric uncertainties. The traditional cognitive radio spectrum sensing scheme (e.g., single model hypothesis testing based on sequential probability ratio test and M-ary hypothesis testing) may be not correct, because it only handles the totally known signal distribution case without considering the uncertainties of signals. The proposed multiple-model hypothesis testing scheme not only copes with the uncertainties of signals, but also has a setting that can provide efficient detection results. Performance of the proposed scheme is evaluated for spectrum sensing in an illustrative scenario. Simulation results demonstrate its detection efficiency compared with the traditional schemes.
Key words:  cognitive radio  spectrum sensing  multiple-model hypothesis testing  sequential probability ratio test

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