认知无人机网络中基于SPRT的协同频谱传感及其性能要求

IF 0.6 4区数学 Q4 STATISTICS & PROBABILITY

Sequential Analysis-Design Methods and Applications Pub Date : 2022-01-02 DOI:10.1080/07474946.2022.2043048

Jun Wu, Pei Li, Jia Zhang, Zehao Chen, J. Bao

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引用次数: 1

摘要

摘要针对无人机通信系统的频谱稀缺性，使用协同频谱感知（CSS）来识别认知无人机网络（CUAVN）的可用频谱。由于飞行无人机的位置灵活，本文首先设计了一种帧内协作方式来取代传统的帧间协作来实现CSS。考虑到CUAVN中的某些性能要求，我们深入分析了基于序列概率比测试（SPRT）的CSS的性能指标之间的关系，并通过忽略超边界和随机游走来近似实际检测性能和停止时间。最后，数值结果证实了我们理论分析的有效性和正确性，比较结果表明了我们的建议的优越性。

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SPRT-based cooperative spectrum sensing with performance requirements in cognitive unmanned aerial vehicle networks (CUAVNs)

Abstract In view of the spectrum scarcity of unmanned aerial vehicles’ (UAVs) communication systems, cooperative spectrum sensing (CSS) is used to identify the available spectrum for cognitive UAV networks (CUAVNs). Due to the flexible locations of flying UAVs, we first design an intraframe cooperation way to replace the traditional interframe cooperation to achieve CSS in this article. Considering certain performance requirements in CUAVNs, we perform an in-depth analysis of the relationship among performance indices of sequential probability ratio test (SPRT)-based CSS and approximate the actual detection performance and the stopping time by ignoring the excess over the boundaries and the random walk. Finally, numerical results corroborate the effectiveness and correctness of our theoretical analysis, and comparison results represent the superiority of our proposal.

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来源期刊

Sequential Analysis-Design Methods and Applications STATISTICS & PROBABILITY-

CiteScore

1.40

自引率

12.50%

发文量

期刊介绍： The purpose of Sequential Analysis is to contribute to theoretical and applied aspects of sequential methodologies in all areas of statistical science. Published papers highlight the development of new and important sequential approaches. Interdisciplinary articles that emphasize the methodology of practical value to applied researchers and statistical consultants are highly encouraged. Papers that cover contemporary areas of applications including animal abundance, bioequivalence, communication science, computer simulations, data mining, directional data, disease mapping, environmental sampling, genome, imaging, microarrays, networking, parallel processing, pest management, sonar detection, spatial statistics, tracking, and engineering are deemed especially important. Of particular value are expository review articles that critically synthesize broad-based statistical issues. Papers on case-studies are also considered. All papers are refereed.