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频谱感知是认知无线电的关键技术之一。随着无线宽带技术的快速发展,宽带频谱感知在频谱信息的采集、存储和处理方面遇到了空前的挑战。如何在缓解这些压力的同时又能够有效获取频谱空洞成为亟需解决的问题。近年来出现压缩感知(CS)理论能够以欠奈奎斯特(Nyquist)采样速率感知信号,为解决上述问题提供了新的思路。文章首先简要阐述了压缩感知理论框架;然后着重介绍了几种基于压缩感知理论框架的宽带频谱感知新技术,并就这些方法进行了分析和评论;最后探讨了相关技术的未来发展方向。
Spectrum sensing is one of the key technologies of cognitive radio. With the rapid development of wireless broadband technology, broadband spectrum sensing has encountered unprecedented challenges in the collection, storage and processing of spectrum information. How to relieve these pressures and at the same time effectively obtain the spectrum hole has become an urgent problem to be solved. In recent years, the emergence of compressed sensing (CS) theory can sense the signal with Nyquist sampling rate, which provides a new idea for solving the above problems. Firstly, the paper briefly introduces the theoretical framework of compressed sensing. Then, it introduces several new broadband spectrum sensing technologies based on the compressed sensing theory framework, and analyzes and comments on these methods. Finally, the future development of related technologies is discussed.