WO2024028702 - GENERATING A MEASUREMENT REPORT USING ONE OF MULTIPLE AVAILABLE ARTIFICIAL INTELLIGENCE MODELS
National phase entry is expected:
Publication Number
WO/2024/028702
Publication Date
08.02.2024
International Application No.
PCT/IB2023/057590
International Filing Date
26.07.2023
Title **
[English]
GENERATING A MEASUREMENT REPORT USING ONE OF MULTIPLE AVAILABLE ARTIFICIAL INTELLIGENCE MODELS
[French]
GÉNÉRATION D'UN RAPPORT DE MESURE À L'AIDE D'UN MODÈLE PARMI DE MULTIPLES MODÈLES D'INTELLIGENCE ARTIFICIELLE DISPONIBLES
Applicants **
LENOVO (SINGAPORE) PTE. LTD.
Inventors
HINDY, Ahmed
POURAHMADI, Vahid
KOTHAPALLI, Venkata Srinivas
NANGIA, Vijay
BAGHERI, Hossein
Priority Data
63/394,814
03.08.2022
US
63/394,822
03.08.2022
US
63/394,857
03.08.2022
US
Application details
| Total Number of Claims/PCT | * |
| Number of Independent Claims | * |
| Number of Priorities | * |
| Number of Multi-Dependent Claims | * |
| Number of Drawings | * |
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| Number of Pages with Drawings | * |
| Pages of Specification | * |
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| Number of Office Actions | * |
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International Searching Authority |
EPO
* |
| Recordal of a Change of the Applicant's Name/Address |
Change of Applicant's Name and Address
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| Type of Assignment |
The Standard Agent's Assignment
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| Applicant's Legal Status |
Legal Entity
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| * | |
| * | |
| * | |
| * | |
| * | |
| Entry into National Phase under |
Chapter I
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| Patent Delivery |
Send the Letters Patent by Courier
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| Translation |
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Quotation for National Phase entry
| Country | Stages | Total | |
|---|---|---|---|
| China | Filing, Examination, Granting | 2880 | |
| EPO | Filing, Examination, Granting | 13029 | |
| Japan | Filing, Examination, Granting | 2338 | |
| South Korea | Filing, Examination, Granting | 2384 | |
| USA | Filing, Examination, Granting | 9990 |
Total:
30,621
The term for entry into the National Phase has expired. This quotation is for informational purposes only
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Abstract[English]
Various aspects of the present disclosure relate to a user equipment (UE) configured with multiple artificial intelligence (AI) models each of which has been configured (e.g., trained) based on training data sets corresponding to one or more of different conditions, such as location of the UE, orientation of the UE, whether the UE is indoors or outdoors, whether the UE is line-of- sight or non-line-of-sight with a base station, and so forth. A network entity (e.g., a gNB) configures the UE with a set of reference signals for measurement of at least one quantity. The UE generates the measurement report based at least in part on the set of reference signals and one of the multiple AI models, and transmits the measurement report to the network entity (e.g., gNB).[French]
Divers aspects de la présente divulgation concernent un équipement utilisateur (UE) configuré avec de multiples modèles d'intelligence artificielle (IA) dont chacun a été configuré (par exemple, entraîné) sur la base d'ensembles de données d'entraînement correspondant à une ou à plusieurs conditions différentes, telles que l'emplacement de l'UE, l'orientation de l'UE, le fait que l'UE est à l'intérieur ou à l'extérieur, le fait que l'UE est dans la ligne de visée ou hors de la ligne de visée d'une une station de base, etc. Une entité de réseau (par exemple, un gNB) configure l'UE avec un ensemble de signaux de référence pour la mesure d'au moins une quantité. L'UE génère le rapport de mesure sur la base, au moins en partie, de l'ensemble de signaux de référence et de l'un des multiples modèles d'IA, et transmet le rapport de mesure à l'entité de réseau (par exemple, le gNB).