EP-4740579-A1 - SLICE RESOURCE OPTIMIZATION METHOD FOR WIRELESS COMMUNICATION, APPARATUS, AND COMPUTER-READABLE STORAGE MEDIUM

Abstract

A wireless communication method includes obtaining input information, including at least one of: slice measurement result information, one or more first pieces of information, one or more second pieces of information, or inference feedback information and using the input information to perform at least one of model training of a slice radio resource management model or generating an inference output with the slice radio resource management model.

Inventors

• LI, DAPENG
• GAO, YIN
• ZHANG, Man
• LIU, ZHUANG
• Liu, Yansheng
• CHEN, JIAJUN

Assignees

• ZTE Corporation

Dates

Publication Date

20260513

Application Date

20230714

Claims (18)

1. A wireless communication method, comprising: obtaining input information, comprising at least one of: slice measurement result information, comprising at least one of: UE location information; UE measurement information; or UE capability information; one or more first pieces of information, comprising at least one of: first current or predicted slice available capacity information; first current or predicted shared network slice information; first current or predicted prioritized network slice information; first current or predicted dedicated network slices information; first multi-carrier resource sharing configuration information; first slice radio resource management (RRM) policy or restriction information; resource deployment information; slice-based cell reselection information; slice service level agreements information; PDU session quality of service (QoS) information; information of attribute of the used slice resource; predicted service traffic information; dual connectivity configuration information; validate time information; or confidence information; one or more second pieces of information, comprising at least one of: second current or predicted slice available capacity information; second current or predicted shared network slice information; second current or predicted prioritized network slice information; second current or predicted dedicated network slices information; second multi-carrier resource sharing configuration information; or second slice radio resource management (RRM) policy or restriction information; or inference feedback information; and using the input information to perform at least one of model training of a slice radio resource management model or generating an inference output with the slice radio resource management model.
2. The method of claim 1, wherein the inference output comprises at least one of: random access network (RAN) slice allocation strategy output information; cell handover or reselection strategy output information; predicted shared network slice output information; predicted prioritized network slice output information; predicted dedicated network slice output information; predicted remapping policy output information; predicted service traffic output information; or validate time output information.
3. The method of claim 1, wherein the inference feedback information comprises at least one of: shared resource usage feedback information; prioritized resource usage feedback information; dedicated resource usage feedback information; service interruption feedback information; validate time feedback information; service interruption times; system performance feedback information; or QoS measurements feedback information.
4. The method of claim 1, wherein using the input information to perform at least one of model training or generating the inference output comprises performing the model training and generating of the inference output by a first network node, the method further comprising: receiving the slice measurement result information of user equipment (UE) ; sending the inference output to a second network node; and receiving the inference feedback information form the second network node.
5. The method of claim 4, further comprising: sending, by the first network node to the second network node, a first request for the one or more second pieces of information for the training; and sending, by the first network node to the second network node, a second request for the one or more second pieces of information for generating the inference output.
6. The method of claims 4 or 5, wherein the first network node is a first base station and the second network node is a second base station.
7. The method of claims 4 or 5, wherein the first network node is a base station centralized unit and the second network node is a base station distributed unit.
8. The method of claim 1, wherein using the input information to perform at least one of model training or generating the inference output comprises performing the model training by a third network node.
9. The method of claim 8, further comprising sending, according to a result of the training by the third network node, a model deployment or update information to a first network node to prepare the slice radio resource management model, which the first network node uses to generate the inference output.
10. The method of claim 8, wherein the third network node comprises an OAM (Operations, Administration, and Maintenance) unit of a core network.
11. The method of claim 1, wherein using the input information to perform at least one of model training or generating the inference output comprises generating the inference output by a first network node based on the slice radio resource management model trained by a third network node.
12. The method of claim 11, further comprising: sending, by the first network node to the second network node, a first request for the one or more first pieces of information for generating the inference output; and sending, by the first network node to the second network node, the inference output.
13. The method of claim 1, wherein using the input information to perform at least one of model training or generating the inference output comprises performing the model training by a first network node, the method further comprising: sending, by a first network node to a second network node according to a result of the training by the first network node, a model deployment or update information to prepare the slice radio resource management model, which the second network node uses to generate the inference output.
14. The method of claim 1, wherein using the input information to perform at least one of model training of a slice radio resource management model or generating the inference output comprises generating the inference output by a second network node based on the slice radio resource management model trained by a first network node.
15. The method of claim 14, further comprising: sending, by the second network node to the first network node, a first request for the one or more first pieces of information for generating the inference output; and sending, by the second network node to the first network node, the inference output.
16. The method of claim 14 or 15, wherein the first network node is a base station centralized unit and the second network node is a base station distributed unit.
17. A wireless communication apparatus, comprising one or more memory units storing one or more programs and one or more processors electrically coupled to the one or more memory units and configured to execute the one or more programs to perform any one of the methods or their combinations of claims 1 to 16.
18. A non-transitory computer-readable storage medium, storing one or more programs, the one or more programs being configured to, when executed by at least one processor, cause to perform any one of the methods or their combinations of claims 1 to 16.

Description

SLICE RESOURCE OPTIMIZATION METHOD FOR WIRELESS COMMUNICATION, APPARATUS, AND COMPUTER-READABLE STORAGE MEDIUM TECHNICAL FIELD This disclosure is generally related to wireless communication, and more particularly to optimization of RAN slice resource. BACKGROUND Wireless communication technologies are pivotal components of the increasingly interconnecting global communication networks. Wireless communications rely on accurately allocated time and frequency resources for transmitting and receiving wireless signals. Random Access Network (RAN) resource slicing includes partitioning the RAN resources into multiple slices or segments for different applications and services. For example, a slice can be assigned with a specific set of resources for specific services or users it serves. Distribution and optimization of the assignment of the RAN slice resource is an issue for efficient use of the communication resources of a communication system. SUMMARY This summary is a brief description of certain aspects of this disclosure. It is not intended to limit the scope of this disclosure. According to some embodiments of this disclosure, a wireless communication method is disclosed. The method includes obtaining input information and using the input information to perform at least one of model training of a slice radio resource management model or generating an inference output with the slice radio resource management model. The input information includes at least one of: slice measurement result information, one or more first pieces of information, one or more second pieces of information, or inference feedback information. The slice measurement result information includes at least one of: UE location information; UE measurement information; or UE capability information. The one or more first pieces of information includes first current or predicted slice available capacity information; first current or predicted shared network slice information; first current or predicted prioritized network slice information; first current or predicted dedicated network slices information; first  multi-carrier resource sharing configuration information; first slice radio resource management (RRM) policy or restriction information; resource deployment information; slice-based cell reselection information; slice service level agreements information; PDU session quality of service (QoS) information; information of attribute of the used slice resource; predicted service traffic information; dual connectivity configuration information; validate time information; or confidence information. The one or more second pieces of information includes at least one of: second current or predicted slice available capacity information; second current or predicted shared network slice information; second current or predicted prioritized network slice information; second current or predicted dedicated network slices information; second multi-carrier resource sharing configuration information; or second slice radio resource management (RRM) policy or restriction information. Still another embodiment of this disclosure provides a wireless communication apparatus, including one or more memory units storing one or more programs and one or more processors electrically coupled to the one or more memory units and configured to execute the one or more programs to perform any method or step or their combinations in this disclosure. Still another embodiment of this disclosure provides non-transitory computer-readable storage medium, storing one or more programs, the one or more programs being configured to, when performed by at least one processor, cause to perform any method or step or their combinations in this disclosure. According to some embodiments of this disclosure, one or more wireless communication methods are further disclosed; the methods include combinations of certain methods, aspects, elements, and steps (either in a generic view or specific view) disclosed in the various embodiments or examples of this disclosure. The above and other aspects and their implementations are described in greater detail in the drawings, the descriptions, and the claims. BRIEF DESCRIPTION OF THE DRAWINGS Various exemplary embodiments of the present disclosure are described in detail below with reference to the following drawings. The drawings are provided for purposes of illustration only and merely depict exemplary embodiments of the present disclosure to  facilitate the understanding of the present disclosure. Therefore, the drawings should not be considered as limiting of the breadth, scope, or applicability of the present disclosure. It should be noted that for clarity and ease of illustration these drawings are not necessarily drawn to scale. Figs. 1A and 1B shows handover of UE from a source RAN node to a target RAN node. Fig. 2 illustrates a functional framework of RAN intelligent slice resource management system. Fig. 3 shows a flow chart of w