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A deep learning approach for LoS/NLoS identification via PRACH in UAV-assisted public safety networks

author
statement of authorship
Davide Scazzoli, Maurizio Magarini, Luca Reggiani, Yannick Le Moullec, Muhammad Mahtab Alam
source
2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications, August 31 - September 3, 2020 in London, United Kingdom : proceedings
location of publication
Danvers
publisher
year of publication
pages
6 p
conference name, date
IEEE 31st International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), August 31 - September 3, 2020
conference location
London, United Kingdom
url
ISSN
1558-2612
ISBN
978-1-7281-4490-0
notes
Bibliogr.: 21 ref
TTÜ department
language
inglise
Reserch Group
Cognitronic lab-on-a-chip research group
Research laboratory for cognitronics
Communication systems research group
Scazzoli, D., Magarini, M., Reggiani, L., Le Moullec, Y., Mahtab Alam, M. A deep learning approach for LoS/NLoS identification via PRACH in UAV-assisted public safety networks // 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications, August 31 - September 3, 2020 in London, United Kingdom : proceedings. Danvers : IEEE, 2020. 6 p. https://doi.org/10.1109/PIMRC48278.2020.9217127