Data-Assisted Low Complexity Compressive Spectrum Sensing on Real-Time Signals under Sub-Nyquist Rate
- Submitting institution
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Queen Mary University of London
- Unit of assessment
- 12 - Engineering
- Output identifier
- 693
- Type
- D - Journal article
- DOI
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10.1109/TWC.2015.2485992
- Title of journal
- IEEE Transactions on Wireless Communications
- Article number
- -
- First page
- 1174
- Volume
- 15
- Issue
- 2
- ISSN
- 1558-2248
- Open access status
- Out of scope for open access requirements
- Month of publication
- September
- Year of publication
- 2015
- URL
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- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
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- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Determines free spectrum in the TV white-space (TVWS) band using a compressive sensing via low cost analog-to-digital converters and has been verified using the over-the-air TVWS signals. Work kick-started by Gao’s EPSRC First Grant (EP/L024241/1, 2014) and IEEE Distinguished Lecturership to Gao https://vtsociety.org/member-resources/distinguished-lecturers/ . Work contributed to Gao being one of 5 international researchers awarded the 2016 €0.5 million EU Horizon Prize on Collaborative Spectrum Sharing (https://ec.europa.eu/research/horizonprize/index.cfm?prize=spectrum-sharing) and his award of EPSRC 5-yr Fellowship “GBSense” (EP/R00711X/1, 2018). Paper was Web of Science highly cited paper and 11th most frequently downloaded paper Feb. 2016.
- Author contribution statement
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- Non-English
- No
- English abstract
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