Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Claudia Parera"'
Publikováno v:
WONS
The use of artificial intelligence is foreseen to be pervasive in future mobile radio networks, enabling dynamic and proactive radio resource provisioning and allocation as well as end-to-end optimization of the network architecture. Current approach
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c4d1e11734640d403bbfafe07af920b1
http://hdl.handle.net/11311/1185330
http://hdl.handle.net/11311/1185330
Autor:
Dan Wellington, Matteo Cesana, Ilaria Malanchini, Alessandro Redondi, Claudia Parera, Qi Liao
Publikováno v:
PIMRC
Accurate and efficient resource utilization predictions are of vital importance for the future generation of mobile wireless networks. By anticipating network resource demand, the operator can perform proactive resource allocation and predictive netw
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::543d6461aeadf054706104867276f4b4
http://hdl.handle.net/11311/1153630
http://hdl.handle.net/11311/1153630
Autor:
Qi Liao, Claudia Parera, Ilaria Malanchini, Cristian Tatino, Alessandro Redondi, Matteo Cesana
Machine learning will play a major role in handling the complexity of future mobile wireless networks by improving network management and orchestration capabilities. Due to the large number of parameters that can be monitored and configured in the ne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1411c07d0c394adc0aae26698b22cb8
http://hdl.handle.net/11311/1129446
http://hdl.handle.net/11311/1129446
Autor:
Stefano Tubaro, Daniele Moro, Alessandro Lieto, Francesco Devoti, Vincenzo Lipari, Paolo Bestagini, Claudia Parera
Publikováno v:
ICASSP
Automatic speech generation algorithms, enhanced by deep learning techniques, enable an increasingly seamless and immediate machine-to-human interaction. As a result, the latest generation of phone-calling bots sounds more convincingly human than pre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ea3c1f9e50cc7fde9632e7496f8345f0
https://doi.org/10.1109/icassp.2019.8682743
https://doi.org/10.1109/icassp.2019.8682743
Publikováno v:
2019 IEEE International Symposium on Measurements & Networking (M&N)
M&N
M&N
The ability to predict the quality of a wireless channel is essential for enabling anticipatory networking tasks. Traditional channel quality prediction problems encompass predicting future conditions based on past measurements of the same channel. I
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d3ea5220f749b2e4bf676495fdfe834
http://hdl.handle.net/11311/1100770
http://hdl.handle.net/11311/1100770
Publikováno v:
2018 IEEE Wireless Communications and Networking Conference (WCNC)
WCNC
WCNC
Fifth generation wireless networks (5G) will face key challenges caused by diverse patterns of traffic demands and massive deployment of heterogeneous access points. In order to handle this complexity, machine learning techniques are expected to play
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62dd89a1e92490ff9ddd2d7490510a23