EP4214912A1 - Services non en temps réel pour ia/ml - Google Patents
Services non en temps réel pour ia/mlInfo
- Publication number
- EP4214912A1 EP4214912A1 EP21870184.5A EP21870184A EP4214912A1 EP 4214912 A1 EP4214912 A1 EP 4214912A1 EP 21870184 A EP21870184 A EP 21870184A EP 4214912 A1 EP4214912 A1 EP 4214912A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- model
- training
- rapp
- ric
- indication
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000010801 machine learning Methods 0.000 claims abstract description 265
- 238000013473 artificial intelligence Methods 0.000 claims abstract description 181
- 238000012549 training Methods 0.000 claims abstract description 165
- 238000000034 method Methods 0.000 claims abstract description 80
- 238000012544 monitoring process Methods 0.000 claims abstract description 64
- 230000008569 process Effects 0.000 claims abstract description 20
- 238000012545 processing Methods 0.000 claims abstract description 18
- 230000006870 function Effects 0.000 claims description 39
- 230000004044 response Effects 0.000 claims description 18
- 238000005070 sampling Methods 0.000 claims description 14
- 238000011156 evaluation Methods 0.000 claims description 7
- 238000012360 testing method Methods 0.000 claims description 7
- 238000010200 validation analysis Methods 0.000 claims description 7
- 238000001914 filtration Methods 0.000 claims description 3
- 230000003993 interaction Effects 0.000 claims 1
- 238000007726 management method Methods 0.000 description 31
- 239000000243 solution Substances 0.000 description 11
- 238000012217 deletion Methods 0.000 description 7
- 230000037430 deletion Effects 0.000 description 7
- 238000001228 spectrum Methods 0.000 description 7
- 230000002787 reinforcement Effects 0.000 description 6
- 239000013256 coordination polymer Substances 0.000 description 4
- 238000005259 measurement Methods 0.000 description 4
- 230000009471 action Effects 0.000 description 3
- 230000008901 benefit Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000002372 labelling Methods 0.000 description 3
- 230000007246 mechanism Effects 0.000 description 3
- 238000005457 optimization Methods 0.000 description 3
- 238000007781 pre-processing Methods 0.000 description 3
- 238000013480 data collection Methods 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 230000002085 persistent effect Effects 0.000 description 2
- 239000000725 suspension Substances 0.000 description 2
- 102100022734 Acyl carrier protein, mitochondrial Human genes 0.000 description 1
- 101000678845 Homo sapiens Acyl carrier protein, mitochondrial Proteins 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000002347 injection Methods 0.000 description 1
- 239000007924 injection Substances 0.000 description 1
- 238000003064 k means clustering Methods 0.000 description 1
- 238000012417 linear regression Methods 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 230000007257 malfunction Effects 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000035515 penetration Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 229920006395 saturated elastomer Polymers 0.000 description 1
- 238000013341 scale-up Methods 0.000 description 1
- 238000013179 statistical model Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 239000013598 vector Substances 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/06—Testing, supervising or monitoring using simulated traffic
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W88/00—Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices
- H04W88/12—Access point controller devices
Abstract
L'invention concerne un appareil pour des services de contrôleur d'intelligence de réseau d'accès radio (RIC) non en temps réel pour l'intelligence artificielle (IA)/l'apprentissage machine (ML) dans un réseau d'accès radio ouvert (O-RAN), l'appareil comprenant de la circuiterie de traitement configurée pour recevoir, d'une application de RIC non-RT (rApp), une demande de service d'entraînement d'intelligence artificielle (IA)/d'apprentissage machine (ML), la demande de service d'entraînement d'IA/ML comprenant une indication d'une structure de modèle d'IA/ML, des préférences d'entraînement, et une description de données d'entraînement, et configurée pour envoyer une identification de processus d'entraînement (ID) à la rAPP, l'ID de processus d'entraînement identifiant la demande de service d'entraînement d'IA/ML. De plus, la circuiterie de traitement est configurée pour réaliser une surveillance de modèle d'IA/ML, une gestion de modèle d'IA/ML et un référentiel de modèles d'IA/ML. La rAPP est configurée pour utiliser les services fournis par le RIC non-RT.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US202063079248P | 2020-09-16 | 2020-09-16 | |
| PCT/US2021/050577 WO2022060923A1 (fr) | 2020-09-16 | 2021-09-16 | Services non en temps réel pour ia/ml |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| EP4214912A1 true EP4214912A1 (fr) | 2023-07-26 |
Family
ID=80777584
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP21870184.5A Pending EP4214912A1 (fr) | 2020-09-16 | 2021-09-16 | Services non en temps réel pour ia/ml |
Country Status (2)
| Country | Link |
|---|---|
| EP (1) | EP4214912A1 (fr) |
| WO (1) | WO2022060923A1 (fr) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11528636B2 (en) * | 2020-02-04 | 2022-12-13 | Parallel Wireless, Inc. | OpenRAN networking infrastructure |
| WO2023204211A1 (fr) * | 2022-04-19 | 2023-10-26 | 京セラ株式会社 | Dispositif de communication et procédé de communication |
| WO2023227349A1 (fr) * | 2022-05-25 | 2023-11-30 | Telefonaktiebolaget Lm Ericsson (Publ) | Gestion de données destinées à être utilisées dans l'apprentissage d'un modèle |
| WO2023240590A1 (fr) * | 2022-06-17 | 2023-12-21 | Nokia Shanghai Bell Co., Ltd. | Procédé, appareil et programme d'ordinateur |
| EP4319083A1 (fr) * | 2022-08-05 | 2024-02-07 | Nokia Solutions and Networks Oy | Mise à jour de capacité ml |
| WO2024072441A1 (fr) * | 2022-09-27 | 2024-04-04 | Rakuten Mobile, Inc. | Système et procédé d'optimisation de reconfiguration de canal radiofréquence dans un réseau de télécommunications |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11620571B2 (en) * | 2017-05-05 | 2023-04-04 | Servicenow, Inc. | Machine learning with distributed training |
| US11323884B2 (en) * | 2017-06-27 | 2022-05-03 | Allot Ltd. | System, device, and method of detecting, mitigating and isolating a signaling storm |
| EP3686805A1 (fr) * | 2019-01-28 | 2020-07-29 | Koninklijke Philips N.V. | Association d'un descripteur de population à l'aide d'un modèle formé |
-
2021
- 2021-09-16 WO PCT/US2021/050577 patent/WO2022060923A1/fr unknown
- 2021-09-16 EP EP21870184.5A patent/EP4214912A1/fr active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| WO2022060923A1 (fr) | 2022-03-24 |
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Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: THE INTERNATIONAL PUBLICATION HAS BEEN MADE |
|
| PUAI | Public reference made under article 153(3) epc to a published international application that has entered the european phase |
Free format text: ORIGINAL CODE: 0009012 |
|
| STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: REQUEST FOR EXAMINATION WAS MADE |
|
| 17P | Request for examination filed |
Effective date: 20221223 |
|
| AK | Designated contracting states |
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| DAV | Request for validation of the european patent (deleted) | ||
| DAX | Request for extension of the european patent (deleted) |