Contributions
[ AI/Question: Q20/13 ]  |
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Numéro
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Titre
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Source
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AI/Question
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Date
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[ 649 ]
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Proposed modifications to TD-WP1-0306- Unified architecture for ML in 5G and future networks
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Ministry of Communications (India)
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Q20/13
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2019-02-19 |
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[ 587 ]
(Rev.1) |
Proposal for adding detailed description for network function apply to the IMT-2020 network concerning the exposure of the network slice management capability in Y.IMT2020-CE-Req
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China Mobile Communications Corporation
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Q20/13
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2019-02-15 |
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[ 585 ]
(Rev.1) |
Proposal for adding detailed description for network function apply to the IMT-2020 network concerning the exposure of the network data analytics exposure capability in Y.IMT2020-CE-Req
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China Mobile Communications Corporation
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Q20/13
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2019-02-15 |
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[ 584 ]
(Rev.1) |
Draft Recommendation ITU-T Y.IMT2020-CEF: Capability exposure procedure in IMT-2020 networks slice
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China Mobile Communications Corporation
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Q20/13
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2019-02-15 |
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[ 583 ]
(Rev.1) |
Draft Recommendation ITU-T Y.IMT2020-CEF: Capability exposure procedure in IMT-2020 networks - QoS
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China Mobile Communications Corporation
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Q20/13
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2019-02-15 |
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[ 580 ]
(Rev.1) |
Draft Recommendation ITU-T Y.IMT2020-CEF, "Capability exposure procedure in IMT-2020 networks"-general aspect
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China Mobile Communications Corporation
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Q20/13
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2019-02-15 |
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[ 565 ]
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Machine learning in 5G and future networks: use cases and basic requirements
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KT, Intel, Vodafone, ETRI, Chinese Academy of Sciences, China Mobile, Tsinghua University, China Unicom, KDDI Corporation, Hitachi Ltd, NEC Corporation, NICT, The University of Tokyo, Turkcell
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Q20/13
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2019-02-14 |
Resultats:7 documents
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