Method and apparatus for ai model definition and ai model transfer

Patent metadata

Field	Value
Publication number	US-2026040096-A1
Application number	US-202318997013-A
Country	US
Kind code	A1
Filing date	Jul 28, 2023
Priority date	Aug 1, 2022
Publication date	Feb 5, 2026
Grant date	—

Abstract

An apparatus of a user equipment (UE), the apparatus comprising a processor, and a memory storing instructions that, when executed by the processor, configure the apparatus to receive, from a base station of an operator network, Protocol Data Units (PDUs) carrying Artificial Intelligence (AI) model data in either a control plane or a user plane, and decapsulate the PDUs to obtain and store the AI model data, wherein the AI model data is indicative of an AI model configured for inference in Access Network (AN) protocol layers at the UE.

First claim

1 . An apparatus of a user equipment (UE), the apparatus comprising:
a processor; and a memory storing instructions that, when executed by the processor, cause the UE to:
receive from a base station of an operator network, Protocol Data Units (PDUs) carrying Artificial Intelligence (AI) model data; and
decapsulate the PDUs to obtain and store the AI model data, wherein the AI model data is indicative of an AI model configured for inference in Access Network (AN) protocol layers at the UE,
wherein a unique AI model ID is assigned to the AI model globally across the operator network and other operator networks.

2 . The apparatus of claim 1 , wherein the AI model data originates from a server outside of the operator network, and is transferred to the base station via a core network of the operator network in either a control plane or a user plane.

3 . The apparatus of claim 1 , wherein the AI model data originates from a core network of the operator network, and is transferred to the UE via a user plane.

4 . The apparatus of claim 1 , wherein the AI model data originates from a Radio Access Network (RAN) cloud of the operator network, and is transferred to the UE in a user plane.

5 . The apparatus of claim 1 , wherein the PDUs are Radio Resource Control (RRC) PDUs in a control plane, or Service Data Adaptation Protocol (SDAP) PDUs.

6 . The apparatus of claim 1 , wherein the AI model data is transferred in response to a request from the UE or a request from the base station.

7 . The apparatus of claim 1 , wherein the AI model is a one-sided model or a part of a two-sided model which performs inference at the UE.

8 . The apparatus of claim 1 , wherein the unique AI model ID is provided by a specification.

9 . The apparatus of claim 8 , wherein the AI model ID includes one or more of UE vendor identification, network device vendor identification, PLMN ID of the operator network, Use case ID, and model number for a use case.

10 . An apparatus in a base station of an operator network, the apparatus comprising:
a processor; and a memory storing instructions that, when executed by the processor, cause the base station to:
receive Protocol Data Units (PDUs) carrying Artificial Intelligence (AI) model data in either a control plane or a user plane,
wherein the AI model data is indicative of an AI model configured for inference in Access Network (AN) protocol layers at the base station or at a UE.

11 . The apparatus of claim 10 , wherein the AI model data originates from a core network of the operator network, and is transferred to the based station in the control plane.

12 . The apparatus of claim 10 , wherein the AI model data originates from a Radio Access Network (RAN) cloud of the operator network, and is accessed by the base station in the control plane.

13 . The apparatus of claim 10 , wherein the instructions that, when executed by the processor, further configure the apparatus to:
decapsulate the PDUs to obtain and store the AI model data, wherein the AI model is configured for inference at the base station.

14 . The apparatus of claim 10 , wherein the instructions that, when executed by the processor, further configure the apparatus to:
transfer, to a UE, the AI model data in either a control plane or a user plane, wherein the AI model is configured for inference at the UE.

15 . The apparatus of claim 14 , wherein the AI model data is transferred to the UE in Radio Resource Control (RRC) PDUs or in Service Data Adaptation Protocol (SDAP) PDUs.

16 . The apparatus of claim 10 , wherein the AI model data includes AI model ID indicative of the AI model, metadata describing the AI model, and a model file storing the AI model.

17 . The apparatus of claim 16 , wherein the model file is reformatted to be applicable to the UE by one of a server outside the operator network, a core network in the operator network, or the base station.

18 . The apparatus of claim 16 , wherein the metadata describes one or more of the following:
training status of the AI model; functionality/object, input/output of the AI model; latency benchmarks, memory requirements, accuracy of the AI model; compression status of the AI model; inferencing/operating condition of the AI model; and pre-processing and post-processing of measurement for input/output of the AI model.

19 - 23 . (canceled)

24 . An apparatus, the apparatus comprising:
a processor; and a memory storing instructions that, when executed by the processor, cause the apparatus to:
assign a unique model ID to an Artificial Intelligence (AI) model;
generate metadata for describing the AI model; and
store the AI model in association with the model ID and the metadata.

25 . The apparatus of claim 24 ,
wherein the AI model ID includes one or more of UE vendor identification, network device vendor identification, PLMN ID of an operator network, Use case ID, and model number for a use case, and wherein the metadata describes one or more of the following:
training status of the AI model;
functionality/object, input/output of the AI model;
latency benchmarks, memory requirements, accuracy of the AI model;
compression status of the AI model;
inferencing/operating condition of the AI model; and
pre-processing and post-processing of measurement for input/output of the AI model.

Assignees

• Apple Inc

Inventors

• Niu Huaning
• Hu Haijing
• Zhang Dawei
• Gupta Vivek G
• Zeng Wei
• Oteri Oghenekome
• Yang Weidong
• Cheng Peng

Classifications

• G06N3/0455

  Auto-encoder networks; Encoder-decoder networks · CPC title

• H04W24/02 Primary

  Arrangements for optimising operational condition · CPC title

• G06N3/0495

  Quantised networks; Sparse networks; Compressed networks · CPC title

• H04L41/16

  using machine learning or artificial intelligence · CPC title

• H04L41/0833

  for reduction of network energy consumption · CPC title