Recent Advances on Sub-Nyquist Sampling-Based Wideband Spectrum Sensing

Jun Fang, Bin Wang, Hongbin Li, Ying Chang Liang

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

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.

Original languageEnglish
Article number9448009
Pages (from-to)115-121
Number of pages7
JournalIEEE Wireless Communications
Volume28
Issue number3
DOIs
StatePublished - Jun 2021

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