Cognitive radio (CR) is a promising technology enabling efficient utilization of the spectrum resource for future wireless systems. As future CR networks are envisioned to operate over a wide frequency range, advanced wideband spectrum sensing (WBSS) capable of quickly and reliably detecting idle spectrum bands across a wide frequency span is essential. In this article, we provide an overview of recent advances on sub-Nyquist sampling-based WBSS techniques, including compressed sensing-based methods and compressive covariance sensing-based methods. An elaborate discussion of the pros and cons of each approach is presented, along with some challenging issues for future research. A comparative study suggests that the compressive covariance sensing-based approach offers a more competitive solution for reliable real-time WBSS.

中文翻译：

---

基于亚奈奎斯特采样的宽带频谱传感的最新进展

认知无线电 (CR) 是一项有前途的技术，可以为未来的无线系统有效利用频谱资源。由于设想未来的 CR 网络在很宽的频率范围内运行，因此能够快速可靠地检测宽频率跨度上的空闲频谱带的先进宽带频谱感知 (WBSS) 至关重要。在本文中，我们概述了基于亚奈奎斯特采样的 WBSS 技术的最新进展，包括基于压缩感知的方法和基于压缩协方差感知的方法。详细讨论了每种方法的优缺点，以及未来研究的一些具有挑战性的问题。一项比较研究表明，基于压缩协方差传感的方法为可靠的实时 WBSS 提供了更具竞争力的解决方案。