Characterization of Received Signal Strength Perturbations using Allan Variance
- Submitting institution
-
University of Ulster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 76473555
- Type
- D - Journal article
- DOI
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10.1109/TAES.2017.2768278
- Title of journal
- IEEE Transactions on Aerospace and Electronic Systems
- Article number
- -
- First page
- 873
- Volume
- 54
- Issue
- 2
- ISSN
- 0018-9251
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
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C - Pervasive Computing Research Centre
- Citation count
- 7
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- <06> This paper challenges the classic assumptions that the received signal strength measurements contain only white noise, and has led to a change of research direction in the field (see DOIs: 10.1109/TAES.2019.2929998; 10.1109/JIOT.2020.3019199; 10.1109/TVT.2019.2943517). This research has also led to interdisciplinary innovation e.g., as adopted by Casaseca-De-La-Higuera’s SmartCough project funded by the Digital Health and Care Institute (https://www.dhi-scotland.com/projects/smartcough/, 2015-2016). It has also underpinned a follow-up industry grant sponsored by a leading Telecom company- Huawei, (H02016050002CG), and contributed to the NERC project (NE/V003402/1, 2020-2022) which will build an IoT testbed to detect sensor movement.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -