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计算机系统应用英文版:2022,31(2):260-266
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基于无线环境图信息辅助的多循环频率协作频谱感知方法
(西安理工大学 自动化与信息工程学院, 西安 710048)
Multi-cycle-frequency Cooperative Spectrum Sensing Method Based on Radio Environment Map Information
(Faculty of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710048, China)
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Received:April 27, 2021    Revised:May 28, 2021
中文摘要: 针对频谱感知中单循环频率检测不能充分利用信号循环谱信息的缺点, 本文提出一种基于无线环境图(radio environment map, REM)信息辅助的多循环频率协作频谱感知方法. 本文方法第1步在多个认知用户处分别选取多个相同的循环频率进行循环平稳检测, 选取谱相关函数幅度作为检测统计量, 根据推导的判决门限公式设定恒虚警概率时的门限值, 经判决融合得出单个认知用户处的检测结果; 第2步根据REM提供的授权用户与认知用户之间的距离信息计算各认知节点处的权值系数, 并通过与对应节点处的检测结果加权融合来提高检测结果的可信度. 仿真结果表明, 改进方法能有效检测到授权用户, 在低信噪比条件下有更好的检测性能且具有更强的实用性.
Abstract:Given that single-cycle frequency detection cannot make full use of the cyclic spectrum information in spectrum sensing, this study proposes a multi-cycle frequency cooperative spectrum sensing method based on radio environment map (REM) information. The first step of this method is to select multiple same cyclic frequencies at multiple cognitive users for cyclostationary detection. The spectral correlation function amplitude is adopted as the detection statistic. The threshold value at a constant false-alarm rate (CFAR) is set according to the derived decision threshold formula, and the detection result at a single cognitive user is obtained through decision fusion. In the second step, the weight coefficient at each cognitive node is calculated according to the distance between the authorized user and the cognitive user provided by the REM. Weighted fusion of the weight coefficients and the detection results of the corresponding nodes are conducted to improve the reliability of the detection results. Simulation results show that the improved method can effectively detect authorized users and has better detection performance and stronger practicability under a low signal-to-noise ratio (SNR).
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基金项目:国家自然科学基金(61671375)
引用文本:
刘高辉,马李庆.基于无线环境图信息辅助的多循环频率协作频谱感知方法.计算机系统应用,2022,31(2):260-266
LIU Gao-Hui,MA Li-Qing.Multi-cycle-frequency Cooperative Spectrum Sensing Method Based on Radio Environment Map Information.COMPUTER SYSTEMS APPLICATIONS,2022,31(2):260-266