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频谱感知技术可以优化频谱资源的利用、提高通信质量、实现智能无线网络，能有效缓解移动通信和物联网对高速、高质量无线连接的需求与有限频谱资源间的矛盾。鉴于此，对传统的频谱感知技术进行了综述；归纳了基于深度学习的频谱感知检测方法，对这些方法的优势和不足进行了深入分析；梳理了智能反射面(Intelligent Reflecting Surface, IRS)与频谱感知相结合的技术；探讨了频谱感知检测技术现阶段面临的问题和未来发展趋势。
Abstract：Spectrum sensing technology can optimize the use of spectrum resources, improve communication quality and realize intelligent wireless networks, and can effectively alleviate the contradiction between the demand for high-speed, high-quality wireless connections in mobile communications and the Internet of Things and limited spectrum resources. In view of this, the traditional spectrum sensing techniques are reviewed; spectrum sensing detection methods based on deep learning are summarized, and the advantages and disadvantages of these methods are analyzed in depth; the technologies that combine Intelligent Reflecting Surface(IRS) with spectrum sensing are sorted out; the current problems and future development trends of spectrum sensing detection technology are discussed.
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基本信息:
中图分类号:TN925
引用信息:
[1]张航领,周顺勇,胡琴,等.认知无线电频谱感知技术研究综述[J].无线电工程,2024,54(11):2527-2536.
基金信息:
国家自然科学基金(61801319); 四川省科技厅省院省校重点项目(2020YFSY0027); 四川轻化工大学研究生创新基金(Y2023310)~~
2024-03-19
2024-03-19
2024-03-19