Project description
Harnessing machine learning will seamlessly optimise 5G-network management
Machine learning is a subset of AI in which algorithms and statistical models are used to analyse and draw inferences from patterns in data, enabling a system to learn, adapt and ‘make decisions’ without explicit instructions. As wireless communication networks become increasingly complex and must manage exponentially increasing amounts of data, network management and optimisation tools based on machine learning have the potential to significantly enhance efficiency and reliability. With the support of the Marie Skłodowska-Curie Actions programme, the WINDMILL project is establishing a training network to integrate wireless communications and machine learning for 5G networks and beyond.
Fields of science
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationstelecommunications networksmobile network5G
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsradio technology
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Programme(s)
Coordinator
9220 Aalborg
Denmark
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Participants (9)
06410 Biot
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08860 Castelldefels Barcelona
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02150 Espoo
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35122 Padova
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164 80 Stockholm
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91300 Massy
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08014 Barcelona
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
8092 Zuerich
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70839 Gerlingen-schillerhoehe
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Partners (11)
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
19801 Wilmington
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
14850 Ithaca Ny
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
85579 Neubiberg
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
78701 2982 Austin
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
08034 Barcelona
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
70174 Stuttgart
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
91192 Gif Sur Yvette
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
22203 Arlington
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
22201 Arlington Va
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
69621 Villeurbanne Cedex
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
1331 Fornebu
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