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.
@article{arxiv.2105.03029,
title = {Recent Advances on Sub-Nyquist Sampling-Based Wideband Spectrum Sensing},
author = {Jun Fang and Bin Wang and Hongbin Li and Ying-Chang Liang},
journal= {arXiv preprint arXiv:2105.03029},
year = {2021}
}
Comments
This paper has been accepted by IEEE Wireless Communications Magazine for future publication