Contribuciones
[ AI/Cuestión: Q20/13 ] |
|
Número
|
Título
|
Origen
|
AI/Cuestión
|
Fecha
|
|
[ 649 ]
|
Proposed modifications to TD-WP1-0306- Unified architecture for ML in 5G and future networks
|
Ministry of Communications (India)
|
Q20/13
|
2019-02-19 |
|
[ 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
|
China Mobile Communications Corporation
|
Q20/13
|
2019-02-15 |
|
[ 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
|
China Mobile Communications Corporation
|
Q20/13
|
2019-02-15 |
|
[ 584 ]
(Rev.1) |
Draft Recommendation ITU-T Y.IMT2020-CEF: Capability exposure procedure in IMT-2020 networks slice
|
China Mobile Communications Corporation
|
Q20/13
|
2019-02-15 |
|
[ 583 ]
(Rev.1) |
Draft Recommendation ITU-T Y.IMT2020-CEF: Capability exposure procedure in IMT-2020 networks - QoS
|
China Mobile Communications Corporation
|
Q20/13
|
2019-02-15 |
|
[ 580 ]
(Rev.1) |
Draft Recommendation ITU-T Y.IMT2020-CEF, "Capability exposure procedure in IMT-2020 networks"-general aspect
|
China Mobile Communications Corporation
|
Q20/13
|
2019-02-15 |
|
[ 565 ]
|
Machine learning in 5G and future networks: use cases and basic requirements
|
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
|
Q20/13
|
2019-02-14 |
Resultados :7 documentos
|
Telecarga de múltiples documentos: Formatos e idiomas que hay que tener en cuenta (si están disponibles):