Method and device applied to node of wireless communication and artificial intelligence

By configuring multiple resource sets based on feature combinations for the terminals in the wireless communication system, the problem of how to indicate more information to the base station as early as possible during the random access process is solved, the deep fusion of AI/ML and communication is achieved, and the success rate and network performance of the random access are improved.

CN120224425APending Publication Date: 2025-06-27HONOR DEVICE CO LTD
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Patent Information

Application Number
CN202411237705.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-09-04
Publication Date
2025-06-27

AI Technical Summary

Technical Problem

In the wireless communication system after the introduction of AI/ML technology, how to instruct more information to the base station as soon as possible during the random access process to promote the deep integration of AI/ML and communication.

Method used

By configuring a multiple resource set based on feature combinations for the terminal in the wireless communication system, the base station can determine whether the AI/ML characteristics are supported or whether the executed random access process is triggered based on the AI/ML characteristics through the random access preamble during the random access process.

Benefits of technology

It increases the probability of success in random access, allows base stations to obtain terminal information earlier, thereby applying AI/ML models earlier, and optimizing network resource utilization and user experience.

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Abstract

The invention discloses a method and a device in a node used for wireless communication and artificial intelligence. A first node receives a first information block, the first information block indicating a plurality of resource sets; transmitting a first signal in a first resource block, the first resource block belonging to one of the plurality of resource sets; the first signal carries a random access preamble, and the first signal is sent based on competition; the plurality of resource sets respectively aim at a plurality of characteristic combinations, and any characteristic combination in the plurality of characteristic combinations comprises at least one characteristic aiming at AI / ML (Artificial Intelligence / Markup Language); the first resource block comprises at least one of a time domain resource, a frequency domain resource or a sequence resource. According to the invention, the resource occupation of the signal in the random access process indicates the characteristic combination supported by the terminal or triggers the characteristic combination of the random access of the terminal, so that the base station can obtain the terminal information earlier.
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Claims

1. A method in a terminal for wireless communication and artificial intelligence, characterized in that: include: receiving a first information block, the first information block indicating a plurality of resource sets; Sending a first signal in a first resource block, wherein the first resource block belongs to one of the multiple resource sets; The first signal carries a random access preamble, and the sending of the first signal is contention-based; the multiple resource sets are respectively for multiple feature combinations, and at least one feature combination of the multiple feature combinations includes at least one feature for AI / ML; the first resource block includes at least one of time domain resources, frequency domain resources or sequence resources.

2. The method according to claim 1, characterized in that include: sending a second signal; The second signal is for random access; one of the characteristics for AI / ML included in the plurality of characteristic combinations is to determine that the terminal supports AI / ML capability; the second signal indicates AI / ML information of the terminal, and the AI / ML information of the terminal includes at least one of the following: -The ID of the AI / ML model supported by the terminal; - Functionality corresponding to the AI / ML model supported by the terminal; - a training data set supported by the terminal; - Associated IDs supported by the terminal; -Category for AI / ML corresponding to the terminal.

3. The method according to any one of claims 1 or 2, characterized in that: The time domain resources occupied by the first resource block belong to a first time domain resource set, and the terminal supports AI / ML capabilities; the time domain resources occupied by the first resource block do not belong to the first time domain resource set, and the terminal does not support AI / ML capabilities.

4. The method according to any one of claims 1 or 2, characterized in that: The frequency domain resources occupied by the first resource block belong to a first frequency domain resource set, and the terminal supports AI / ML capabilities; the frequency domain resources occupied by the first resource block do not belong to the first frequency domain resource set, and the terminal does not support AI / ML capabilities.

5. The method according to any one of claims 1 or 2, characterized in that: The sequence resources occupied by the first resource block belong to a first sequence resource set, and the terminal supports AI / ML capabilities; the sequence resources occupied by the first resource block do not belong to the first sequence resource set, and the terminal does not support AI / ML capabilities.

6. The method according to any one of claims 2 to 5, characterized in that: The second signal includes a first field, and the first field included in the second signal indicates the AI / ML information of the terminal; when the terminal does not support AI / ML capabilities, the value of the first field included in the second signal is fixed or predefined.

7. The method according to any one of claims 2 to 6, characterized in that: The first signal is Msg1 and the second signal is Msg3; or the first signal is PRACH in MsgA and the second signal is PUSCH in MsgA.

8. A terminal, characterized in that: The terminal includes: one or more processors and a memory; The memory is coupled to the one or more processors, and the memory is used to store computer program codes, where the computer program codes include computer instructions. The one or more processors call the computer instructions to enable the terminal to execute the method according to any one of claims 1 to 7.

9. A method for a base station for wireless communication and artificial intelligence, characterized in that: include: Sending a first information block, wherein the first information block indicates a plurality of resource sets; receiving a first signal in a first resource block, the first resource block belonging to one of the plurality of resource sets; Among them, the first signal carries a random access preamble, and the sending of the first signal is based on contention; the multiple resource sets are respectively for multiple feature combinations, and any feature combination of the multiple feature combinations includes at least one feature for AI / ML; the first resource block includes at least one of time domain resources, frequency domain resources or sequence resources.

10. The method according to claim 9, characterized in that include: receiving a second signal; The second signal is for random access; the sender of the second signal is a terminal, and one of the characteristics for AI / ML included in the plurality of characteristic combinations is to determine that the terminal supports AI / ML capability; the second signal indicates AI / ML information of the terminal, and the AI / ML information of the terminal includes at least one of the following: -The ID of the AI / ML model supported by the terminal; - Functionality corresponding to the AI / ML model supported by the terminal; - a training data set supported by the terminal; - Associated IDs supported by the terminal; -Category for AI / ML corresponding to the terminal.

11. The method according to any one of claims 9 or 10, characterized in that: The time domain resources occupied by the first resource block belong to a first time domain resource set, and the terminal supports AI / ML capabilities; the time domain resources occupied by the first resource block do not belong to the first time domain resource set, and the terminal does not support AI / ML capabilities.

12. The method according to any one of claims 9 or 10, characterized in that: The frequency domain resources occupied by the first resource block belong to a first frequency domain resource set, and the terminal supports AI / ML capabilities; the frequency domain resources occupied by the first resource block do not belong to the first frequency domain resource set, and the terminal does not support AI / ML capabilities.

13. The method according to any one of claims 9 or 10, characterized in that: The sequence resources occupied by the first resource block belong to a first sequence resource set, and the terminal supports AI / ML capabilities; the sequence resources occupied by the first resource block do not belong to the first sequence resource set, and the terminal does not support AI / ML capabilities.

14. The method according to any one of claims 10 to 13, characterized in that The second signal includes a first field, and the first field included in the second signal indicates the AI / ML information of the terminal; when the terminal does not support AI / ML capabilities, the value of the first field included in the second signal is fixed or predefined.

15. The method according to any one of claims 10 to 14, characterized in that The first signal is Msg1 and the second signal is Msg3; or the first signal is PRACH in MsgA and the second signal is PUSCH in MsgA.

16. A base station, characterized in that: The base station includes: one or more processors and a memory; The memory is coupled to the one or more processors, and the memory is used to store computer program codes, where the computer program codes include computer instructions, and the one or more processors call the computer instructions to enable the base station to perform the method according to any one of claims 9 to 15.

Citation Information

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