Abstract
Spectrum sensing is used to perceive the spectral environment over a wide frequency band. The multiple measurement vector (MMV) model can be applied to the spectrum sensing scenario since it enables jointly sparse signal recovery. In this paper, a novel spectrum sensing algorithm, referred to as multiple subspace matching pursuit (MSMP), is proposed to reduce the miss detection and false alarm events in the spectrum sensing. Numerical simulations demonstrate that the proposed algorithm shows the outstanding recovery performance with the reduction of the incorrect spectrum decisions.
Original language | English |
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Title of host publication | 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 3594-3598 |
Number of pages | 5 |
ISBN (Electronic) | 9781509041176 |
DOIs | |
Publication status | Published - 2017 Jun 16 |
Externally published | Yes |
Event | 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - New Orleans, United States Duration: 2017 Mar 5 → 2017 Mar 9 |
Other
Other | 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 |
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Country | United States |
City | New Orleans |
Period | 17/3/5 → 17/3/9 |
Keywords
- false alarm
- miss detection
- multiple measurement vector (MMV)
- Spectrum sensing
- spectrum utilization
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering