Method and apparatus used in node for wireless communication and artificial intelligence

Abstract

The present application discloses a method and apparatus used in a node for wireless communication and artificial intelligence (AI). The method comprises: a node receives a first reporting configuration; and determines whether to generate and send a first measurement result. The generation of the first measurement result occupies at least one processing resource, and the at least one processing resource occupied by the generation of the first measurement result belongs to one of a first resource group or a second resource group. The first resource group is used for the generation of a measurement result for a first type of measurement, and the second resource group is used for the generation of a measurement result for a second type of measurement. When one of the first resource group and the second resource group is fully occupied and the other is not fully occupied, whether the first measurement result is generated and sent depends on at least the former of the following two: which resource group among the first resource group and the second resource group is the resource group that is not fully occupied; and whether the measurement corresponding to the first measurement result is the first type of measurement or the second type of measurement. The present application enhances an AI-based CPU occupancy mechanism.

Description

A method and apparatus for use in nodes for wireless communication and artificial intelligence

[0001] This application claims priority to Chinese Patent Application No. 202411614821.4, filed on November 12, 2024, entitled "A method and apparatus for use in a node for wireless communication and artificial intelligence", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to signal transmission methods and apparatus in wireless communication systems, and more particularly to methods and apparatus for CSI (Channel State Information). Background Technology

[0003] In traditional wireless communication, the UE (User Equipment) reports various auxiliary information obtained through measurements of downlink signals and / or channels, such as channel information, beam management-related auxiliary information, and positioning-related auxiliary information. Channel information includes, but is not limited to, one or more of CRI (Channel State Information Reference Signal Resource Indicator), RI (Rank Indicator), PMI (Precoding Matrix Indicator), or CQI (Channel Quality Indicator). The UE can use this information to select appropriate transmission parameters or report this information. The network equipment selects appropriate transmission parameters for the UE based on the reported information, such as the cell to be used, MCS (Modulation and Coding Scheme), TPMI (Transmitted Precoding Matrix Indicator), and TCI (Transmission Configuration Indication). Furthermore, UE reporting can be used to optimize network parameters, such as improving cell coverage and switching base stations on / off based on the UE's location.

[0004] In traditional cellular communication, the antenna port is used to describe reference signal resources; unlike the physical antenna, the antenna port can be considered a virtualization / overlay operation of the physical antenna.

[0005] With the adoption of new technologies, the increase in the number of antennas, the diversification of application scenarios, and the increasing demands on system performance, traditional measurement and reporting methods incur significant redundancy overhead. Therefore, in NR (New Radio) Rel-18 (Release-18), research on AI (Artificial Intelligence) / ML (Machine Learning) technologies was initiated to explore their impact on system performance and design. Compared to traditional processing methods, AI / ML offers advantages such as training-based and deployment-required features. According to the 3GPP (3rd Generation Partnership Project) standard TS 38.300, AI / ML models and algorithms extend beyond the scope of 3GPP. Summary of the Invention

[0006] In the current standard, the concept of CPU (CSI Processing Unit) is introduced to represent the terminal's ability to process CSI, and the number of CPUs occupied by each CSI report and the time occupied by the CPU are specified. After the introduction of AI / ML model, when the UE supports channel information generated based on AI / ML model for different measurement purposes, the CPU occupancy mechanism is an urgent problem to be solved.

[0007] To address the aforementioned issues, this application discloses a solution. It should be noted that while this application is initially intended for AI / ML scenarios, it can also be applied to other non-AI / ML scenarios. Furthermore, adopting a unified design scheme for different scenarios (such as other non-AI / ML scenarios, including but not limited to Vehicle to Everything (V2X), capacity enhancement systems, short-range communication systems, NTN (Non-Terrestrial Network), IoT (Internet of Things), and URLLC (Ultra-Reliable Low-Latency Communication) networks) helps reduce hardware complexity and cost. Where there is no conflict, embodiments and features in any node of this application can be applied to any other node. Where there is no conflict, embodiments and features in any embodiment of this application can be arbitrarily combined with each other.

[0008] In particular, the interpretation of terms, nouns, functions, and variables in this application (unless otherwise specified) can be found in the definitions of the TS38 and TS37 series of 3GPP (3rd Generation Partnership Project) Technical Specifications (TS). Where necessary, reference can be made to TS38.211, TS38.212, TS38.213, TS38.214, TS38.215, TS38.300, TS38.304, TS38.305, TS38.321, TS38.331, TS37.355, and TS38.423 in the 3GPP technical specifications to aid in understanding this application.

[0009] As an example, the interpretation of terms in this application is based on the definitions in the 3GPP specification protocol TS38 series.

[0010] As an example, the interpretation of the terms in this application is based on the definitions in the 3GPP specification protocol TS37 series.

[0011] As an example, the interpretation of the terms used in this application is based on the definitions in 3GPP specification protocol Rel-17.

[0012] As an example, the interpretation of the terms used in this application is based on the definitions in 3GPP specification protocol Rel-18.

[0013] This application discloses a method for a first node in wireless communication and artificial intelligence, comprising:

[0014] Receive the first reported configuration;

[0015] Determine whether to generate and send the first measurement result;

[0016] Wherein, the first reporting configuration is used to configure the reporting of the first measurement result; the generation of the first measurement result occupies at least one processing resource; the at least one processing resource occupied by the generation of the first measurement result belongs to one of a first resource group or a second resource group; the first resource group includes one or more processing resources in the first node; the second resource group includes one or more processing resources in the first node; the first resource group is used for the generation of measurement results for a first type of measurement; the second resource group is used for the generation of measurement results for a second type of measurement; both the measurement results for the first type of measurement and the measurement results for the second type of measurement are generated based on inference; the first type of measurement and the second type of measurement are different; when one of the first resource group and the second resource group is fully occupied and the other is not fully occupied, whether the first measurement result is generated and sent depends on at least the former of the following two:

[0017] -Which of the first and second resource groups is the resource group that is not fully occupied?

[0018] -Is the measurement corresponding to the first measurement result the first type of measurement or the second type of measurement?

[0019] As an example, the features of the above method include: the first node is a terminal.

[0020] As an example, the problem this application aims to solve includes: when a terminal simultaneously supports multiple different types of inference-based channel information generation processes, which part of the processing resources the terminal uses to generate channel information.

[0021] As an example, the problem this application aims to solve includes: when a new measurement process is still generated and sent when two different processing resource groups are occupied for different types of measurement processes based on inference, and the processing resources included in one of the two different processing resource groups are occupied.

[0022] As an example, the features of the above method include: In this application, the first type of measurement and the second type of measurement of the first node occupy two different processing resource groups respectively. When the processing resources included in one of the two different processing resource groups are occupied, whether the first node still starts a new measurement process depends on whether the new measurement process can occupy the unoccupied processing resources, thereby solving the above problem.

[0023] As an example, the features of the above method include: in this application, whether the generation of the first measurement result can occupy unoccupied processing resources depends on the type of measurement served by the unoccupied processing resources, thereby solving the above problem.

[0024] As an example, the features of the above method include: the processing resources include a CSI processing unit, which includes a CSI processing unit that generates CSI based on AI and a CSI processing unit that generates CSI in Release-18 and earlier versions.

[0025] As an example, the features of the above method include: the processing resources include a CSI processing unit, and the CSI processing unit includes only a CSI processing unit that generates CSI based on AI.

[0026] As an example, the features of the above method include: the processing resource is a minimum processing unit required to generate channel information, and the minimum processing unit is atomic.

[0027] As an example, the features of the above method include: the meaning that one of the first resource group and the second resource group is fully occupied and the other is not fully occupied means that, in a given symbol, all processing resources included in one of the first resource group and the second resource group are occupied and the other processing resource group includes unoccupied processing resources.

[0028] As an example, the features of the above method include: the first reporting configuration indicates the type of measurement to which the first measurement result is applied.

[0029] As an example, the advantages of the above method include: this application supports the deep integration of AI and communication, improves the adaptability and intelligence level of the communication system, and thus enhances the performance, efficiency and user experience of the communication system.

[0030] As an example, the advantages of the above method include: this application supports split CPU usage, reduces interference caused by high-load operation, and thus enhances the robustness of the system.

[0031] As an example, the benefits of the above method include: improving system energy efficiency and optimizing power consumption management.

[0032] As an example, the advantages of the above method include: avoiding the complexity of task scheduling and reducing scheduling overhead.

[0033] As an example, the benefits of the above method include: enhancing the robustness of the system and reducing performance fluctuations.

[0034] As an example, the advantages of the above method include: the first type of measurement can occupy the processing resources in the second resource group, while the second type of measurement cannot occupy the processing resources in the first resource group, thereby ensuring that more processing resources are available to serve the first type of measurement and guaranteeing the performance of the first type of measurement.

[0035] According to one aspect of this application, the above method is characterized in that when the first resource group is fully occupied and the second resource group is not fully occupied, and the amount of processing resources occupied by the generation of the first measurement result is not greater than the amount of unoccupied processing resources in the second resource group, the first measurement result is generated and sent regardless of whether the measurement corresponding to the first measurement result is the first type of measurement or the second type of measurement.

[0036] As an example, the advantages of the above method include: the processing resources in the second resource group can be shared by the first type of measurement and the second type of measurement, thereby ensuring the utilization rate of the processing resources.

[0037] According to one aspect of this application, the above method is characterized in that, when the second resource group in the first resource group and the second resource group are fully occupied and the first resource group is not fully occupied, and the number of processing resources occupied by the generation of the first measurement result is not greater than the number of unoccupied processing resources in the first resource group; when the measurement corresponding to the first measurement result is the first type of measurement, the first measurement result is generated and sent; when the measurement corresponding to the first measurement result is the second type of measurement, the first measurement result is not generated and is not sent.

[0038] As an example, the advantages of the above method include: the processing resources in the first resource group can only be occupied by the first type of measurement, ensuring that there are enough processing resources for the first type of measurement, thereby ensuring the performance of the first type of measurement.

[0039] According to one aspect of this application, the above method is characterized in that the first type of measurement includes measurements for layer 1, and the second type of measurement includes measurements for layer 3.

[0040] As an example, the advantages of the above method include: ensuring the reservation of processing resources for Layer 1 measurements, thereby ensuring the performance of Layer 1 measurements.

[0041] As an example, the advantages of the above method include: Layer 1 measurement requires higher real-time performance than Layer 3 measurement, so the first resource group reserved for Layer 1 measurement will not be occupied by Layer 3 measurement, thus ensuring the real-time performance of Layer 1 measurement.

[0042] According to one aspect of this application, the above method is characterized in that the first type of measurement includes measurements for CSI, and the second type of measurement includes measurements for positioning.

[0043] As an example, the advantages of the above method include: ensuring the reservation of processing resources for CSI measurements, thereby ensuring the performance of CSI measurements.

[0044] As an example, the advantages of the above method include: since CSI measurements require higher real-time performance than positioning measurements, the first resource group reserved for CSI measurements will not be occupied by positioning measurements, thus ensuring the real-time performance of CSI measurements.

[0045] According to one aspect of this application, the above method is characterized in that the processing resources include at least the former of storage resources or computing resources.

[0046] As an example, the advantages of the above method include: traditional CPU resources only consider computing resources, while AI / ML-based processing also has huge storage requirements, so the processing resources of this application also take storage resources into account.

[0047] According to one aspect of this application, the above method is characterized by comprising:

[0048] Receive the first information block;

[0049] Wherein, the maximum computing power that the first node can support is equal to a first integer; the first information block indicates a first ratio value, and the product of the first integer and the first ratio value, after being rounded down, is equal to a second integer; the number of processing resources included in the second resource group is equal to the second integer, and the number of processing resources included in the first resource group is equal to the difference between the first integer and the second integer; or, the number of processing resources included in the first resource group is equal to the second integer, and the number of processing resources included in the second resource group is equal to the difference between the first integer and the second integer.

[0050] As an example, the features of the above method include: the first integer is the sum of the processing resources included in the first resource group and the processing resources included in the second resource group.

[0051] As an example, the features of the above method include: the first integer is the total amount of processing resources included in the first node for generating channel information.

[0052] As an example, the features of the above method include: in this application, the ratio of processing resources of the first node used for the first type of measurement to processing resources used for the second type of measurement is indicated by the base station.

[0053] As an example, the advantages of the above method include: good compatibility.

[0054] As an example, the advantages of the above method include: the base station indicates that the first ratio value can be balanced in different scenarios to reduce the frequent feedback caused by measurement while meeting real-time requirements, thereby achieving a better balance between latency and accuracy.

[0055] As an example, the advantages of the above method include: the first ratio value is configurable, which improves the flexibility of the system.

[0056] According to one aspect of this application, the above method is characterized by comprising:

[0057] Send the second information block;

[0058] The second information block is used to trigger the reconfiguration of the first ratio value.

[0059] As an example, the features of the above method include: the second information block is event-triggered.

[0060] As an example, the features of the above method include: the second information block instructing the resource utilization of the first node.

[0061] As an example, the features of the above method include: the second information block indicates the performance of the deployed model of the first node.

[0062] As an example, the advantages of the above method include: flexible adaptation to different channel dynamics, facilitating the selection of appropriate ratio values ​​based on channel characteristics, and improving network adaptability.

[0063] As an example, the advantages of the above method include: maintaining stable transmission and adapting to changes in user needs and network conditions.

[0064] As an example, the benefits of the above method include: improved service quality and user experience.

[0065] As an example, the advantages of the above method include: by monitoring and providing feedback on different types of AI / ML through the terminal, the base station can determine the effectiveness of different types of AI / ML measurements in a specific environment and adjust resource allocation accordingly to ensure the efficiency and accuracy of AI / ML in critical business scenarios and improve user experience.

[0066] According to one aspect of this application, the above method is characterized by comprising:

[0067] Receive M configuration messages, each of which indicates one or more RS resource groups. Each of the M RS resource groups includes one or more RS resources, and M is a positive integer greater than 1.

[0068] For each of the M configuration messages, calculate the performance parameters;

[0069] The calculation of the performance parameters depends on the measurement of the RS resource group indicated by the corresponding configuration message; the second information block depends on the performance parameters.

[0070] As an example, the characteristics of the above method include: the performance parameters are used to measure the performance of the inference model for the first type of measurement and / or the second type of measurement.

[0071] As an example, the features of the above method include: the second information block is event-triggered, the event including the performance of the model for generating channel information by the first node being better than a given threshold.

[0072] As an example, the features of the above method include: the first node performs model monitoring and indicates model performance changes to the base station according to the base station configuration.

[0073] As an example, the benefits of the above method include: enhancing the adaptability and robustness of the model.

[0074] As an example, the benefits of the above method include: timely adjustment of model parameters or switching to different algorithm configurations to ensure that the model continues to run in the best state.

[0075] According to one aspect of this application, the above method is characterized in that the first node is a user equipment.

[0076] According to one aspect of this application, the above method is characterized in that the first node is a terminal.

[0077] This application discloses a method for a second node in wireless communication and artificial intelligence, comprising:

[0078] Send the first reporting configuration;

[0079] Wherein, the receiver of the first reporting configuration includes a first node; the first reporting configuration is used to configure the reporting of a first measurement result, the generation of the first measurement result occupies at least one processing resource, the at least one processing resource occupied by the generation of the first measurement result belongs to one of a first resource group or a second resource group, the first resource group includes one or more processing resources in the first node, the second resource group includes one or more processing resources in the first node; the first resource group is used for the generation of measurement results for a first type of measurement, the second resource group is used for the generation of measurement results for a second type of measurement; the measurement results of the first type of measurement and the measurement results of the second type of measurement are both generated based on inference; the first type of measurement and the second type of measurement are different; when one of the first resource group and the second resource group is fully occupied and the other is not fully occupied, whether the first measurement result is generated and sent depends on at least the former of the following two:

[0080] -Which of the first and second resource groups is the resource group that is not fully occupied?

[0081] -Is the measurement corresponding to the first measurement result the first type of measurement or the second type of measurement?

[0082] As one embodiment, the above method is characterized by the following feature: the second node is a base station.

[0083] As an example, the above method is characterized by the following feature: the second node is an eNB.

[0084] As an example, the above method is characterized by the following feature: the second node is a gNB.

[0085] As an example, the above method is characterized by the following: the second node is a network device, which includes at least one of a core network device and an access network device.

[0086] As an example, the above method is characterized by the following: the second node is a device that provides wireless communication function services, can communicate with terminal devices, and is usually located on the network side.

[0087] As one embodiment, the above method is characterized by the following: the second node includes a base station.

[0088] As an example, the above method is characterized by the following: the second node includes a core network.

[0089] As an example, the above method is characterized by the following: the second node includes a base station and a core network.

[0090] As an example, the above method is characterized by the following: the second node includes an entity for deploying AI / ML models.

[0091] As an example, the above method is characterized by the following: the second node includes a node for deploying AI / ML models.

[0092] As an example, the above method is characterized by the following: the base station in this application includes a core network.

[0093] As an example, the above method is characterized by the following: the base station in this application includes core network equipment.

[0094] As an example, the above method is characterized by the following: the base station in this application includes an entity for deploying AI / ML models.

[0095] As an example, the above method is characterized by the following: the base station in this application includes nodes for deploying AI / ML models.

[0096] According to one aspect of this application, the above method is characterized by comprising:

[0097] Receive the first measurement result.

[0098] According to one aspect of this application, the above method is characterized by comprising:

[0099] Discontinue receiving the first measurement result.

[0100] According to one aspect of this application, the above method is characterized in that when the first resource group is fully occupied and the second resource group is not fully occupied, and the amount of processing resources occupied by the generation of the first measurement result is not greater than the amount of unoccupied processing resources in the second resource group, the first measurement result is generated and sent by the first node regardless of whether the measurement corresponding to the first measurement result is the first type of measurement or the second type of measurement.

[0101] According to one aspect of this application, the above method is characterized in that, when the second resource group in the first resource group and the second resource group are fully occupied and the first resource group is not fully occupied, and the number of processing resources occupied by the generation of the first measurement result is not greater than the number of unoccupied processing resources in the first resource group; when the measurement corresponding to the first measurement result is the first type of measurement, the first measurement result is generated and sent by the first node; when the measurement corresponding to the first measurement result is the second type of measurement, the first measurement result is not generated by the first node and is not sent.

[0102] According to one aspect of this application, the above method is characterized in that the first type of measurement includes measurements for layer 1, and the second type of measurement includes measurements for layer 3.

[0103] According to one aspect of this application, the above method is characterized in that the first type of measurement includes measurements for CSI, and the second type of measurement includes measurements for positioning.

[0104] According to one aspect of this application, the above method is characterized in that the processing resources include at least the former of storage resources or computing resources.

[0105] According to one aspect of this application, the above method is characterized by comprising:

[0106] Send the first information block;

[0107] Wherein, the maximum computing power that the first node can support is equal to a first integer; the first information block indicates a first ratio value, and the product of the first integer and the first ratio value, after being rounded down, is equal to a second integer; the number of processing resources included in the second resource group is equal to the second integer, and the number of processing resources included in the first resource group is equal to the difference between the first integer and the second integer; or, the number of processing resources included in the first resource group is equal to the second integer, and the number of processing resources included in the second resource group is equal to the difference between the first integer and the second integer.

[0108] According to one aspect of this application, the above method is characterized by comprising:

[0109] Receive the second information block;

[0110] The second information block is used to trigger the reconfiguration of the first ratio value.

[0111] As an example, the features of the above method include: the second node receiving the second information block decides to reconfigure the first ratio value.

[0112] As an example, the features of the above method include: the second node receiving the second information block multiple times and deciding to reconfigure the first ratio value.

[0113] As an example, the features of the above method include: the second information block is used by the second node to determine whether to reconfigure the first ratio value for the first node.

[0114] As an example, the advantages of the above method include: increasing the amount of base station information, which is conducive to the rational allocation of processing resources and improving the terminal processing capability.

[0115] As an example, the advantages of the above method include: rationally allocating processing resources based on terminal feedback helps the base station obtain more channel information.

[0116] As an example, the advantages of the above method include: combining real-time feedback from the UE with resource adjustments by the base station to achieve intelligent network management and improve the reliability of AI algorithms.

[0117] According to one aspect of this application, the above method is characterized by comprising:

[0118] Send M configuration messages, each of which indicates one or more RS resource groups. Each of the M RS resource groups includes one or more RS resources, and M is a positive integer greater than 1.

[0119] Specifically, the first node calculates performance parameters for each of the M configuration messages; the calculation of the performance parameters depends on the measurement of the RS resource group indicated by the corresponding configuration message; the second information block depends on the performance parameters.

[0120] According to one aspect of this application, the method described above is characterized in that the second node is a base station.

[0121] This application discloses a device for a first node in wireless communication and artificial intelligence, comprising:

[0122] The first receiver receives the first reported configuration;

[0123] The first processor determines whether to generate and send the first measurement result;

[0124] Wherein, the first reporting configuration is used to configure the reporting of the first measurement result; the generation of the first measurement result occupies at least one processing resource; the at least one processing resource occupied by the generation of the first measurement result belongs to one of a first resource group or a second resource group; the first resource group includes one or more processing resources in the first node; the second resource group includes one or more processing resources in the first node; the first resource group is used for the generation of measurement results for a first type of measurement; the second resource group is used for the generation of measurement results for a second type of measurement; both the measurement results for the first type of measurement and the measurement results for the second type of measurement are generated based on inference; the first type of measurement and the second type of measurement are different; when one of the first resource group and the second resource group is fully occupied and the other is not fully occupied, whether the first measurement result is generated and sent depends on at least the former of the following two:

[0125] -Which of the first and second resource groups is the resource group that is not fully occupied?

[0126] -Is the measurement corresponding to the first measurement result the first type of measurement or the second type of measurement?

[0127] This application discloses a device for a second node in wireless communication and artificial intelligence, comprising:

[0128] The first transmitter sends the first reported configuration;

[0129] Wherein, the receiver of the first reporting configuration includes a first node; the first reporting configuration is used to configure the reporting of a first measurement result, the generation of the first measurement result occupies at least one processing resource, the at least one processing resource occupied by the generation of the first measurement result belongs to one of a first resource group or a second resource group, the first resource group includes one or more processing resources in the first node, the second resource group includes one or more processing resources in the first node; the first resource group is used for the generation of measurement results for a first type of measurement, the second resource group is used for the generation of measurement results for a second type of measurement; the measurement results of the first type of measurement and the measurement results of the second type of measurement are both generated based on inference; the first type of measurement and the second type of measurement are different; when one of the first resource group and the second resource group is fully occupied and the other is not fully occupied, whether the first measurement result is generated and sent depends on at least the former of the following two:

[0130] -Which of the first and second resource groups is the resource group that is not fully occupied?

[0131] -Is the measurement corresponding to the first measurement result the first type of measurement or the second type of measurement?

[0132] As an example, compared with conventional solutions, this application has the following advantages, but is not limited to:

[0133] This application supports the deep integration of AI and communication to improve the adaptability and intelligence of communication systems, thereby enhancing the performance, efficiency, and user experience of communication systems.

[0134] The second resource group reserved for the second type of measurement can be occupied by the process of the second type of measurement, while the first resource group reserved for the first type of measurement cannot be occupied by the process of the second type of measurement. The above method ensures the processing resources required for the first type of measurement, thereby ensuring system performance.

[0135] It reduces the requirements for the terminal and has good compatibility.

[0136] It can flexibly adapt to different channel dynamics, making it easy to select and configure appropriate ratio values ​​according to channel characteristics, thereby improving the network's adaptability. Attached Figure Description

[0137] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0138] Figure 1 illustrates a flowchart of the first node transmission according to an embodiment of this application;

[0139] Figure 2 shows a schematic diagram of a network architecture according to an embodiment of this application;

[0140] Figure 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for the user plane and control plane according to an embodiment of this application;

[0141] Figure 4 shows a schematic diagram of a first communication device and a second communication device according to an embodiment of this application;

[0142] Figure 5 shows a first flowchart of the transmission between a first node and a second node according to an embodiment of this application;

[0143] Figure 6 illustrates a second flowchart of the transmission between a first node and a second node according to an embodiment of this application;

[0144] Figure 7 illustrates a third flowchart of the transmission between a first node and a second node according to an embodiment of this application;

[0145] Figure 8 shows a fourth schematic diagram of transmission between a first node and a second node according to an embodiment of this application;

[0146] Figure 9 shows a first schematic diagram of the occupancy of a first resource group and a second resource group according to an embodiment of this application;

[0147] Figure 10 shows a second schematic diagram of the occupancy of the first and second resource groups according to an embodiment of this application;

[0148] Figure 11 shows a schematic diagram of RAN domain AI / ML function deployment according to an embodiment of this application;

[0149] Figure 12 shows a schematic diagram of the deployment of AI / ML functions of a UE according to an embodiment of this application;

[0150] Figure 13 shows a schematic diagram of a processing system based on artificial intelligence or machine learning according to an embodiment of this application;

[0151] Figure 14 illustrates a schematic diagram of artificial intelligence or machine learning according to an embodiment of this application;

[0152] Figure 15 shows a structural block diagram of a processing apparatus for a first node according to an embodiment of this application;

[0153] Figure 16 shows a structural block diagram of a processing apparatus for a second node according to an embodiment of the present application. Detailed Implementation

[0154] The technical solutions of this application will be further described in detail below with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other. Considering performance, flexibility, complexity, overhead, and compatibility, those skilled in the art are motivated to flexibly combine the embodiments in different drawings without conflict, including but not limited to the embodiments in Figure 1 and the embodiments in Figures 5-16, the embodiments in Figure 5 and the embodiments in Figures 6-16, etc.

[0155] Example 1

[0156] Example 1 illustrates a flowchart of the first node transmission according to an embodiment of this application, as shown in Figure 1. In Figure 1, each block represents a step. In particular, the order of the steps in the blocks does not represent a specific temporal relationship between the steps.

[0157] In step 101, the first node receives the first reporting configuration; in step 102, it determines whether to generate and send the first measurement result.

[0158] In Example 1, the first reporting configuration is used to configure the reporting of the first measurement result. The generation of the first measurement result occupies at least one processing resource. The at least one processing resource occupied by the generation of the first measurement result belongs to one of a first resource group or a second resource group. The first resource group includes one or more processing resources in the first node, and the second resource group includes one or more processing resources in the first node. The first resource group is used for the generation of measurement results for a first type of measurement, and the second resource group is used for the generation of measurement results for a second type of measurement. Both the measurement results for the first type of measurement and the measurement results for the second type of measurement are generated based on inference. The first type of measurement and the second type of measurement are different. When one of the first resource group and the second resource group is fully occupied and the other is not fully occupied, whether the first measurement result is generated and sent depends on at least the former of the following two:

[0159] -Which of the first and second resource groups is the resource group that is not fully occupied?

[0160] -Is the measurement corresponding to the first measurement result the first type of measurement or the second type of measurement?

[0161] As one example, the first node is a user equipment (UE).

[0162] As one example, the first node is a terminal.

[0163] As an example, the first node is the first node in this application.

[0164] As an example, the first node receives the first reported configuration.

[0165] As an example, the first reported configuration is carried by higher layer signaling.

[0166] As an example, the first reported configuration is carried by RRC (Radio Resource Control) signaling.

[0167] As an example, the first reporting configuration includes some or all of the fields in one or more RRC IEs (Information Elements).

[0168] As one embodiment, the first reporting configuration includes some or all of the domains of each of the multiple RRC IEs.

[0169] As one example, the first reported configuration includes some or all of the domains in the ServingCellConfigCommon IE.

[0170] As one example, the first reported configuration includes some or all of the domains in the ServingCellConfig IE.

[0171] As one example, the first reporting configuration includes some or all of the domains in the CSI-MeasConfig IE.

[0172] As one example, the first reporting configuration includes some or all of the domains in a CSI-ReportConfig IE.

[0173] As one example, the first reporting configuration includes some or all of the domains in a LocationInfo IE.

[0174] As an example, the first reporting configuration includes some or all of the fields in a LocationMeasurementInfo IE.

[0175] As one example, the first reporting configuration includes some or all of the domains in a MeasConfig IE.

[0176] As one example, the first reporting configuration includes some or all of the domains in a MeasConfig IE.

[0177] As an example, the first reporting configuration includes some or all of the domains in a MeasObjectCLI IE.

[0178] As an example, the first reporting configuration includes some or all of the domains in a MeasObjectEUTRA IE.

[0179] As one example, the first reporting configuration includes some or all of the domains in a MeasObjectNR IE.

[0180] As one example, the first reporting configuration includes some or all of the fields in a MeasObjectToAddModList IE.

[0181] As an example, the first reporting configuration includes some or all of the fields in a MobilityStateParameters IE.

[0182] As one example, the first reporting configuration includes some or all of the domains in a MeasConfig IE.

[0183] As an example, the first reporting configuration includes some or all of the fields in a SelectedPSCellForCHO-WithSCG IE.

[0184] As one example, the first reporting configuration includes some or all of the domains in an LTM-Candidate IE.

[0185] As one example, the first reporting configuration includes some or all of the domains in an LTM-Config IE.

[0186] As one example, the first reporting configuration includes some or all of the domains in an LTM-CSI-ReportConfig IE.

[0187] As one example, the first reporting configuration includes some or all of the domains in an LTM-CSI-ResourceConfig IE.

[0188] As one example, the first reported configuration includes some or all of the domains in a CondReconfigToAddModList IE.

[0189] As one example, the first reported configuration includes some or all of the domains in a ConditionalReconfiguration IE.

[0190] As an example, the name of the RRC signaling carrying the first reporting configuration includes: CSI.

[0191] As an example, the name of the RRC signaling carrying the first reporting configuration includes: Report.

[0192] As an example, the name of the RRC signaling carrying the first reported configuration includes: Config.

[0193] As an example, the name of the RRC signaling carrying the first reporting configuration includes: Meas.

[0194] As an example, the name of the RRC signaling carrying the first reporting configuration includes: CSI-Report.

[0195] As an example, the name of the RRC signaling carrying the first reporting configuration includes: Location.

[0196] As an example, the name of the RRC signaling carrying the first reporting configuration includes: Mobility.

[0197] As an example, the name of the RRC signaling carrying the first reporting configuration includes: CHO.

[0198] As an example, the name of the RRC signaling carrying the first reporting configuration includes: LTM.

[0199] As an example, the name of the RRC signaling carrying the first reporting configuration includes: Cond.

[0200] As an example, the name of the RRC signaling carrying the first reporting configuration includes: Conditional.

[0201] As an example, the first reporting configuration depends on whether the measurement corresponding to the first measurement result is the first type of measurement or the second type of measurement.

[0202] As one embodiment, the first reporting configuration indicates at least one of a first resource set, a reporting type, or a reporting quantity; the first resource set includes one or more RS (Reference Signal) resources, and the first resource set is used for at least one of channel measurement or interference measurement of the first measurement result.

[0203] As a sub-example of this embodiment, the first node performs at least one of channel measurement or interference measurement on the one or more RS resources included in the first resource set.

[0204] As one embodiment, generating and sending the first measurement result includes: receiving an RS used to generate the first measurement result.

[0205] As one embodiment, generating and sending the first measurement result includes: receiving the RS used to generate the first measurement result in the corresponding RS resource.

[0206] As one embodiment, the first reporting configuration indicates at least one of a first resource set, a second resource set, a reporting type, or a reporting quantity; the first resource set includes one or more RS resources, and the first resource set is used for at least one of channel measurement or interference measurement of the first measurement result; the second resource set includes one or more resources.

[0207] As a sub-implementation of this embodiment, the second resource set includes one or more RS resources.

[0208] As a sub-implementation of this embodiment, the resources in the second resource set include at least one of antenna port(s), TCI (Transmission Configuration Indicator) state, QCL (Quasi Co-Located) information, time-frequency resources, time-frequency code resources, beams, RS resources, vectors, or matrices.

[0209] As a sub-implementation of this embodiment, the first resource set is used to infer and generate the first measurement result.

[0210] As a sub-example of this embodiment, the first node measures one or more RS resources included in the first resource set.

[0211] As a sub-example of this embodiment, the first node does not measure the one or more RS resources included in the second resource set.

[0212] As a sub-implementation of this embodiment, the first measurement result is associated with the second resource set.

[0213] As a sub-implementation of this embodiment, the first measurement result indicates a beam index belonging to the second resource set; the beam index is one of CRI and SSBRI.

[0214] As a sub-implementation of this embodiment, the first resource set corresponds to a CSI-ResourceConfigId.

[0215] As a sub-implementation of this embodiment, the first reporting configuration indicates at least the former of the first resource set and the second resource set by instructing CSI-ResourceConfigId.

[0216] As a sub-implementation of this embodiment, the first resource set and the second resource set correspond to the same CSI-ResourceConfigId.

[0217] As a sub-implementation of this embodiment, the first resource set and the second resource set correspond to different CSI-ResourceConfigIds.

[0218] As an example, the reporting type described in this application indicates at least one of periodic reporting, semi-persistent (SP) reporting, aperiodic (AP) reporting, or event-triggered reporting.

[0219] As an example, the reporting type in this application indicates at least one of periodic reporting, semi-persistent reporting, or non-periodic reporting.

[0220] As an example, the first measurement result is based on a non-codebook.

[0221] As an example, the first measurement result includes the channel matrix.

[0222] As an example, the first measurement result includes at least one of the channel's feature values ​​or feature vectors.

[0223] As one embodiment, the first measurement result includes a resource indication, which is used to indicate beam or RS resources.

[0224] As an example, the first measurement result includes at least one of a resource indication or RSRP (Reference Signal Received Power), the resource indication being used to indicate a beam or RS resource.

[0225] As an example, the first measurement result includes at least one of resource indication, RSRP, PMI, CQI, SINR, channel matrix, eigenvalue of the channel, or eigenvector of the channel; the resource indication is used to indicate beam or RS resources.

[0226] As an example, the first measurement result includes one of beam information, predicted CSI (Channel State Information), or compressed CSI.

[0227] As an example, the beam information in this application includes a resource indicator, which is used to indicate a beam or RS resource.

[0228] As an example, the beam information in this application includes at least one of a resource indicator or an RSRP, wherein the resource indicator is used to indicate a beam or RS resource.

[0229] As an example, the first measurement result includes at least one of CQI (Channel Quality Indicator), PMI (Precoding Matrix Indicator), CRI (CSI-RS Resource Indicator), SSBRI (SS / PBCH Block Resource Indicator), LI (Layer Indicator), RI (Rank Indicator), L1-RSRP (Layer 1-Reference Signal Received Power), L1-SINR (Layer 1-Signal-to-Interference-plus-Noise Ratio), Capability Index, TDCP (Time Domain Channel Properties), and Confidence Information (CI).

[0230] As an example, the first measurement result includes CSI.

[0231] As a sub-example of this embodiment, the CSI includes beam information.

[0232] As a sub-example of this embodiment, the CSI includes predicted CSI.

[0233] As a sub-example of this embodiment, the CSI includes compressed CSI.

[0234] As a supplementary embodiment of this sub-example, the compressed CSI is based on non-codebook channel information.

[0235] As a supplementary embodiment of this sub-example, the channel parameters recovered by the target receiver of the compressed CSI based on the compressed CSI are unknown to the sender of the compressed CSI.

[0236] As a supplementary embodiment of this sub-example, the compressed CSI is based on AI / ML (Artificial Intelligence / Machine Learning) channel information.

[0237] As a supplementary embodiment of this sub-example, the compressed CSI is based on channel information from a neural network.

[0238] As a supplementary embodiment of this sub-example, the compressed CSI is based on channel information from CNN (Conventional Neural Networks).

[0239] As an example, the first measurement result was used to trigger CHO.

[0240] As an example, the first measurement result is used to trigger LTM.

[0241] As an example, the first measurement result was used for random access.

[0242] As an example, the first measurement result is used to carry an L1 measurement report.

[0243] As an example, the first measurement result was used for positioning.

[0244] As one example, the first measurement result includes measurement reporting.

[0245] As an example, the first measurement result includes reporting.

[0246] As an example, the first reporting configuration is used to configure the reporting of the first measurement result.

[0247] As an example, the meaning of the first reporting configuration being used to configure the reporting of the first measurement result includes: the first reporting configuration being used to indicate the reporting period of the first measurement result.

[0248] As an example, the meaning of the first reporting configuration being used to configure the reporting of the first measurement result includes: the first reporting configuration being used to indicate the time domain resources occupied by the first measurement result.

[0249] As an example, the meaning of the first reporting configuration being used to configure the reporting of the first measurement result includes: the first reporting configuration being used to indicate the frequency domain resources occupied by the first measurement result.

[0250] As an example, the meaning of the first reporting configuration being used to configure the reporting of the first measurement result includes: the first reporting configuration being used to indicate the physical layer channel occupied by the first measurement result.

[0251] As an example, the meaning of the first reporting configuration being used to configure the reporting of the first measurement result includes: the first reporting configuration being used to trigger the reporting of the first measurement result.

[0252] As an example, the meaning of the first reporting configuration being used to configure the reporting of the first measurement result includes: the first reporting configuration being used to indicate the reporting conditions of the first measurement result.

[0253] As an example, the meaning of the first reporting configuration being used to configure the reporting of the first measurement result includes: the first reporting configuration being used to indicate the CSI type of the first measurement result.

[0254] As a sub-example of this embodiment, the candidates for the CSI type include one or more of CQI, PMI, CRI, SSBRI, LI, RI, L1-RSRP, L1-SINR, Capability Index, TDCP, SINR (Signal to Noise and Interference Ratio), SSB-Index, Capability Set Index, and confidence information.

[0255] As an example, the generation of the first measurement result consumes at least one processing resource.

[0256] As an example, the generation of the first measurement result occupies K processing resources, where K is a positive integer.

[0257] As one embodiment, the generation of the first measurement result includes: calculation or inference of the first measurement result.

[0258] As one embodiment, the generation of the first measurement result includes: inference to generate the first measurement result.

[0259] As one embodiment, the generation of the first measurement result includes: calculating and generating the first measurement result.

[0260] As one embodiment, the generation of the first measurement result includes: measuring and generating the first measurement result.

[0261] As an example, the inference described in this application includes AI / ML inference.

[0262] As one embodiment, the generation of the first measurement result includes: calculation or inference of the first measurement result.

[0263] As an example, the generation of the first measurement result includes: reasoning about the first measurement result.

[0264] As an example, the generation of the first measurement result includes: reasoning to obtain the first measurement result.

[0265] As one embodiment, the generation of the first measurement result includes: the sender of the first measurement result performing a first operation, the first measurement result depending on the output of the first operation, the first operation including inference.

[0266] As an example, the first measurement result is calculated or generated through artificial intelligence or machine learning.

[0267] As an example, the generation of the first measurement result is based on training.

[0268] As an example, the generation of the first measurement result uses an AI model.

[0269] As an example, the generation of the first measurement result uses information generated based on artificial intelligence or machine learning.

[0270] As an example, the generation of the first measurement result uses information generated based on a neural network.

[0271] As an example, the generation of the first measurement result uses information generated based on CNN (Conventional Neural Networks).

[0272] As an example, the first measurement result includes information generated based on artificial intelligence or machine learning.

[0273] As an example, the first measurement result includes information generated based on a neural network.

[0274] As an example, the first measurement result includes information generated based on CNN (Conventional Neural Networks).

[0275] As an example, the first measurement result is generated based on an AI / ML model.

[0276] As an example, the generation of the first measurement result corresponds to a first identifier.

[0277] As an example, how the first measurement result is generated is determined by the manufacturer of the first node, or is implementation-dependent. A typical, but non-limiting, implementation is described below:

[0278] The first node measures the RS resources used for channel measurement to obtain the channel parameter matrix H. r×t Where r and t are the number of receiving antennas and the number of antenna ports, respectively; at least the channel parameter matrix H r×t Alternatively, its feature vector is input into an AI model, and the output of the AI ​​model is used to obtain the first measurement result.

[0279] If the first measurement result requires the first node to estimate interference (including noise), the first node can measure the RS resources used for interference measurement to obtain the measurement interference.

[0280] In one implementation, measurement interference is also input into the AI ​​model.

[0281] In another implementation, the measurement interference is not input into the AI ​​model; the output of the AI ​​model and the measurement interference are used together to generate the first measurement result.

[0282] Without loss of generality, the AI ​​model or the parameters of the AI ​​model used to generate the first measurement result are determined by the manufacturer of the first node.

[0283] Typically, the amount of processing resources required to generate the first measurement result is equal to the first value.

[0284] As an example, the first value is a positive integer.

[0285] As an example, the first value is a positive integer greater than 1.

[0286] As an example, the first value is a positive real number.

[0287] As an example, the first value depends on the first reporting configuration.

[0288] As an example, the first value depends on the higher-level parameters corresponding to the first reporting configuration.

[0289] As an example, the first value depends on the first measurement result.

[0290] As an example, the first value depends on the contents included in the first measurement result.

[0291] As one embodiment, the remaining processing resources of the first node include: unused processing resources among the processing resources included in the first node.

[0292] As a sub-example of this embodiment, "not occupied" includes not being occupied by CSI calculation.

[0293] As a sub-example of this embodiment, the term "unoccupied" includes "not occupied by channel measurement".

[0294] As a sub-example of this embodiment, "unoccupied" includes "not occupied by channel calculation".

[0295] As a sub-example of this embodiment, "not occupied" includes not being occupied by CSI-reported calculations.

[0296] As an example, the total processing resources included in the first node include: all processing resources included in the first node for CSI calculation.

[0297] As one embodiment, the total processing resources included in the first node include: all processing resources included in the first node for channel measurement.

[0298] As one embodiment, the total processing resources included in the first node include: all processing resources included in the first node for channel calculation.

[0299] As one embodiment, the total processing resources included in the first node include: all processing resources included in the first node for CSI reporting calculation.

[0300] As an example, the statement that the measurements in this application are based on inference to generate corresponding measurement results means that the generation of the measurement results is based on training.

[0301] As an example, the statement that the measurements in this application are based on inference to generate corresponding measurement results means that the generation of the measurement results uses an AI model.

[0302] As an example, the statement that the measurements in this application are based on reasoning to generate corresponding measurement results means that the generation of the measurement results uses information generated based on artificial intelligence or machine learning.

[0303] As an example, the statement that the measurements in this application are based on inference to generate corresponding measurement results means that the generation of the measurement results uses information generated based on a neural network.

[0304] As an example, the meaning of "the measurements in this application are all based on inference to generate corresponding measurement results" includes: the generation of the measurement results uses information generated based on CNN (Conventional Neural Networks).

[0305] As an example, the meaning of "measurement results generated based on reasoning" in this application includes: the measurement results include information generated based on artificial intelligence or machine learning.

[0306] As an example, the statement that the measurements in this application are based on inference to generate corresponding measurement results means that the measurement results include information generated based on a neural network.

[0307] As an example, the meaning of "the measurements in this application are all based on inference to generate corresponding measurement results" includes: the measurement results include information generated based on CNN (Conventional Neural Networks).

[0308] As an example, the statement that the measurements in this application are based on inference to generate corresponding measurement results means that the measurement results are generated based on AI / ML models.

[0309] As an example, the first type of measurement is for measurement of layer 1, and the second type of measurement is for measurement outside of layer 1.

[0310] As an example, the first type of measurement is for CSI of Layer 1, and the second type of measurement is for CSI outside of CSI of Layer 1.

[0311] As an example, the second type of measurement is for positioning, while the first type of measurement is for measurements other than those for positioning.

[0312] As an example, the second type of measurement is for mobility management, while the first type of measurement is for measurements other than those for mobility management.

[0313] As an example, the second type of measurement is for cell handover, while the first type of measurement is for measurements other than those for cell handover.

[0314] As an example, the results of the first type of measurement and the results of the second type of measurement correspond to the measurement results of different layers.

[0315] As an example, the first type of measurement and the second type of measurement are associated with different associated IDs.

[0316] As an example, the first type of measurement and the second type of measurement are associated with different sets of associated IDs.

[0317] As an example, the first type of measurement and the second type of measurement are associated with different Model IDs.

[0318] As an example, the first type of measurement and the second type of measurement are associated with different sets of Model IDs.

[0319] As an example, the first type of measurement and the second type of measurement are associated with different functionalities.

[0320] As an example, the first type of measurement and the second type of measurement are associated with different functionalities.

[0321] As an example, the first type of measurement and the second type of measurement are associated with different functionality groups.

[0322] As one embodiment, the meaning of the first resource group being used for generating measurement results for a first type of measurement includes: the processing resources included in the first resource group are configured for generating measurement results for the first type of measurement.

[0323] As an example, the meaning of the first resource group being used for generating measurement results for a first type of measurement includes: the generation of measurement results for a first type of measurement preferentially occupies the processing resources included in the first resource group.

[0324] As an example, the meaning of the first resource group being used for generating measurement results for a first type of measurement includes: when there are idle processing resources in the first resource group, the generation of measurement results for a second type of measurement cannot occupy the processing resources included in the first resource group.

[0325] As an example, the meaning of the first resource group being used for generating measurement results for a first type of measurement includes: the generation of measurement results for a first type of measurement can occupy the processing resources included in the first resource group and the processing resources included in the second resource group.

[0326] As one embodiment, the meaning of the second resource group being used for generating measurement results for the second type of measurement includes: the processing resources included in the second resource group are configured for generating measurement results for the second type of measurement.

[0327] As one embodiment, the meaning of the second resource group being used for generating measurement results for the second type of measurement includes: the generation of measurement results for the second type of measurement preferentially occupies the processing resources included in the second resource group.

[0328] As an example, the second resource group being used for generating measurement results for a second type of measurement means that when there are idle processing resources in the second resource group, the generation of measurement results for a second type of measurement can only occupy the processing resources included in the second resource group.

[0329] Example 2

[0330] Example 2 illustrates a schematic diagram of a network architecture according to an embodiment of this application, as shown in Figure 2.

[0331] Figure 2 illustrates network architecture 200. Network architecture 200 is the network architecture for LTE (Long-Term Evolution), LTE-A (Long-Term Evolution Advanced), 5G systems, 5G-Advanced, and future 6G systems. The network architectures for LTE, LTE-A, 5G systems, 5G-Advanced, and future 6G systems are referred to as EPS (Evolved Packet System). The 5G NR or LTE network architecture may be referred to as 5GS (5G System) / EPS or some other suitable terminology; the 6G network architecture may be referred to as 6GS (6G System) / EPS or some other suitable terminology.

[0332] The network architecture 200 may include one or more UEs 201, a RAN (Radio Access Network) 202, a core network 210, an HSS (Home Subscriber Server) / UDM (Unified Data Management) 220, and an Internet service 230. The network architecture 200 may interconnect with other access networks, but these entities / interfaces are not shown for simplicity.

[0333] As shown in Figure 2, the network architecture 200 provides packet switching services; however, those skilled in the art will readily understand that the various concepts presented throughout this application can be extended to networks providing circuit-switched services or other cellular networks. The RAN 202 includes Node B 203 and other nodes 204. Node B 203 provides user and control plane protocol termination toward the UE 201. Node B 203 may be connected to other nodes 204 via an Xn interface (e.g., backhaul). Node B 203 may also be referred to as eNB (evolved Node B), gNB, base station, base transceiver station, radio base station, radio transceiver, transceiver function, Basic Service Set (BSS), Extended Service Set (ESS), TRP (Transmitter Receiver Point), or some other suitable term. Node B 203 provides UE 201 with an access point to the core network 210; the core network 210 is a 5GC (5G Core network) / EPC (Evolved Packet Core), or the core network 210 is a 6GC (6G Core network). Examples of the UE 201 include cellular phones, smartphones, Session Initiation Protocol (SIP) phones, laptops, personal digital assistants (PDAs), satellite radios, GPS devices, multimedia devices, video devices, digital audio players (e.g., MP3 players), cameras, game consoles, drones, aircraft, narrowband physical network devices, machine-type communication devices, land vehicles, automobiles, wearable devices, or any other similar functional devices. Those skilled in the art may also refer to the UE 201 as a mobile station, subscriber station, mobile unit, subscriber unit, radio unit, remote unit, mobile device, radio device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, radio terminal, remote terminal, handheld device, user agent, mobile client, client, or any other suitable term. The Node B 203 is connected to the core network 210 via an S1 / NG interface.The core network 210 includes an MME (Mobility Management Entity) / AMF (Authentication Management Field) / SMF (Session Management Function) 211, other MMEs / AMFs / SMFs 214, an S-GW (Service Gateway) / UPF (User Plane Function) 212, and a P-GW (Packet Data Network Gateway) / UPF 213. The MME / AMF / SMF 211 is the control node that handles signaling between the UE 201 and the core network 210. Generally, the MME / AMF / SMF 211 provides bearer and connection management. All user IP (Internet Protocol) packets are transmitted through the S-GW / UPF 212, which is itself connected to the P-GW / UPF 213. The P-GW provides UE IP address allocation and other functions. The P-GW / UPF 213 is connected to the Internet service 230. The Internet service 230 includes carrier-compliant Internet protocol services, specifically including the Internet, intranet, IMS (IP Multimedia Subsystem), and packet-switched streaming services.

[0334] As an example, the first node in this application includes the UE 201.

[0335] As an example, the second node in this application includes node B 203.

[0336] As an example, node B 203 is a macrocell base station.

[0337] As an example, node B 203 is a microcell base station.

[0338] As an example, node B 203 is a pico cell base station.

[0339] As an example, node B 203 is a femtocell.

[0340] As an example, node B 203 is a base station device that supports large latency differences.

[0341] As an example, node B 203 is a flight platform device.

[0342] As an example, node B 203 is a satellite device.

[0343] As one embodiment, the node B 203 is a test device (e.g., a transceiver device simulating part of the base station's functions, a signaling tester).

[0344] As an example, the UE 201 includes a mobile phone.

[0345] As an example, the UE 201 is a vehicle including a car.

[0346] As an example, the wireless link from the UE 201 to the node B 203 is an uplink, which is used to perform uplink transmissions.

[0347] As an example, the radio link from the node B 203 to the UE 201 is a downlink, which is used to perform downlink transmissions.

[0348] As an example, the wireless link between the node B 203 and the UE 201 includes a cellular link.

[0349] As an example, the node B 203 and the UE 201 are connected via the Uu air interface.

[0350] As an example, the sender of the first reporting configuration in this application includes the node B 203.

[0351] As an example, the recipient of the first reported configuration in this application includes the UE 201.

[0352] As an example, in this application, the first measurement result is generated and sent, and the sender of the first measurement result includes the UE 201.

[0353] As an example, in this application, the first measurement result is generated and sent, and the recipient of the first measurement result includes the node B 203.

[0354] As an example, the sender of the second information block in this application includes the UE 201.

[0355] As an example, the recipient of the second information block in this application includes the node B 203.

[0356] As an example, the sender of the first information block in this application includes the node B 203.

[0357] As an example, the recipient of the first information block in this application includes the UE 201.

[0358] As an example, the sender of the M configuration messages in this application includes the node B 203.

[0359] As an example, the recipient of the M configuration messages in this application includes the UE 201.

[0360] As an example, the node B 203 supports the deployment of network-side (NW-side) AI / ML models.

[0361] As an example, the UE 201 supports the deployment of UE-side AI / ML models.

[0362] As an example, the node B 203 supports AI / ML-based beam management (BM).

[0363] As an example, the UE 201 supports AI / ML-based beam management (BM).

[0364] As an example, node B 203 supports CSI generation based on AI / ML.

[0365] As an example, the UE 201 supports CSI generation based on AI / ML.

[0366] As an example, the UE 201 supports a 5G system.

[0367] As an example, the node B 203 supports a 5G system.

[0368] As an example, the UE 201 supports at least a 6G system.

[0369] As an example, the node B 203 supports at least a 6G system.

[0370] Example 3

[0371] Example 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for the user plane and control plane according to an embodiment of this application, as shown in Figure 3.

[0372] Figure 3 is a schematic diagram illustrating an embodiment of the wireless protocol architecture for the user plane 350 and the control plane 300. Figure 3 shows the wireless protocol architecture for the control plane 300 between a first communication node device (UE or RSU in V2X, onboard equipment or onboard communication module) and a second node device (gNB, RSU in UE or V2X, onboard equipment or onboard communication module), or between two UEs, using three layers: Layer 1 (L1), Layer 2 (L2), and Layer 3 (L3). L1 is the lowest layer and implements various PHY (Physical layer) signal processing functions. L1 will be referred to herein as PHY 301. L2 305 is above PHY 301 and is responsible for the link between the first node device and the second node device, or between two UEs, through PHY 301. L2 305 includes a MAC (Medium Access Control) sublayer 302, an RLC (Radio Link Control) sublayer 303, and a PDCP (Packet Data Convergence Protocol) sublayer 304, which terminate at the second node device. The PDCP sublayer 304 provides multiplexing between different radio bearers and logical channels. It also provides security through encrypted data packets and supports cross-cell mobility between the second communication node devices and the first communication node device. The RLC sublayer 303 provides upper-layer packet segmentation and reassembly, retransmission of lost packets, and packet reordering to compensate for out-of-order reception due to HARQ (Hybrid Automatic Repeat reQuest). The MAC sublayer 302 provides multiplexing between logical and transport channels. It is also responsible for allocating various radio resources (e.g., resource blocks) within a cell between the first communication node devices. The MAC sublayer 302 is also responsible for HARQ operations. The RRC (Radio Resource Control) sublayer 306 in L3 of the control plane 300 is responsible for obtaining radio resources (i.e., radio bearers) and using RRC signaling between the second communication node device and the first communication node device to configure the lower layer.The wireless protocol architecture of user plane 350 includes Layer 1 (L1) and Layer 2 (L2). The wireless protocol architecture for the first and second communication node devices in user plane 350 is largely the same as the corresponding layers and sublayers in control plane 300 for Physical Layer 351, PDCP sublayer 354 in L2 355, RLC sublayer 353 in L2 355, and MAC sublayer 352 in L2 355. However, PDCP sublayer 354 also provides header compression for upper-layer packets to reduce wireless transmission overhead. L2 355 in user plane 350 also includes SDAP (Service Data Adaptation Protocol) sublayer 356. SDAP sublayer 356 is responsible for mapping between QoS (Quality of Service) streams and Data Radio Bearers (DRBs) to support service diversity. Although not illustrated, the first communication node device may have several upper layers above L2 355, including a network layer (e.g., IP (Internet Protocol) layer) terminating at the P-GW on the network side and an application layer terminating at the other end of the connection (e.g., remote UE, server, etc.).

[0373] As an example, the wireless protocol architecture in Figure 3 is applicable to the first node in this application.

[0374] As an example, the wireless protocol architecture in Figure 3 is applicable to the second node in this application.

[0375] As an example, the first reporting configuration in this application is generated in the RRC 306.

[0376] As an example, the first measurement result in this application is generated in the RRC 306.

[0377] As an example, the first measurement result in this application is generated by the MAC 302 or the MAC 352.

[0378] As an example, the first measurement result in this application is generated in the PHY 301 or the PHY 351.

[0379] As an example, in this application, the first information block is generated in the RRC 306.

[0380] As an example, the second information block in this application is generated in the RRC 306.

[0381] As an example, the second information block in this application is generated in MAC 302 or MAC 352.

[0382] As an example, the second information block in this application is generated in the PHY 301 or the PHY 351.

[0383] As an example, the M configuration messages described in this application are generated in the RRC 306.

[0384] As an example, the higher layer mentioned in this application refers to the layer above the physical layer.

[0385] As an example, the higher layer described in this application includes the RRC layer.

[0386] As an example, the higher-layer signaling described in this application includes RRC IE.

[0387] As an example, the higher-level signaling described in this application includes RRC messages.

[0388] As an example, the higher layer described in this application includes the MAC layer.

[0389] As an example, the higher-layer signaling described in this application includes MAC CE.

[0390] Example 4

[0391] Example 4 illustrates a schematic diagram of a first communication device and a second communication device according to an embodiment of this application, as shown in Figure 4. Figure 4 is a block diagram of a first communication device 410 and a second communication device 450 communicating with each other in an access network.

[0392] The first communication device 410 includes a controller / processor 475, a memory 476, a receiver processor 470, a transmitter processor 416, a multi-antenna receiver processor 472, a multi-antenna transmitter processor 471, a transmitter / receiver 418, and an antenna 420.

[0393] The second communication device 450 includes a controller / processor 459, a memory 460, a data source 467, a transmitting processor 468, a receiving processor 456, a multi-antenna transmitting processor 457, a multi-antenna receiving processor 458, a transmitter / receiver 454, and an antenna 452.

[0394] In the transmission from the first communication device 410 to the second communication device 450, at the first communication device 410, upper-layer data packets from the core network are provided to the controller / processor 475. The controller / processor 475 implements L2 functionality. In the DL, the controller / processor 475 provides header compression, encryption, packet segmentation and reordering, multiplexing between logical and transport channels, and radio resource allocation to the second communication device 450 based on various priority metrics. The controller / processor 475 is also responsible for HARQ operation, retransmission of lost packets, and signaling to the second communication device 450. The transmit processor 416 and the multi-antenna transmit processor 471 implement various signal processing functions for L1 (i.e., the physical layer). Transmit processor 416 performs encoding and interleaving to facilitate forward error correction (FEC) at the second communication device 450, and mapping of signal clusters based on various modulation schemes (e.g., Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying (QPSK), M-PSK, and M-Quadrature Amplitude Modulation (M-QAM)). Multi-antenna transmit processor 471 performs digital spatial precoding on the encoded and modulated symbols, including codebook-based precoding and non-codebook-based precoding, and beamforming processing, generating one or more parallel streams. The transmit processor 416 then maps each parallel stream to a subcarrier, multiplexes the modulated symbols with a reference signal (e.g., a pilot) in the time and / or frequency domains, and then uses an inverse fast fourier transform (IFFT) to generate a physical channel carrying the time-domain multicarrier symbol stream. The multi-antenna transmit processor 471 then performs transmit analog precoding / beamforming operations on the time-domain multicarrier symbol stream. Each transmitter 418 converts the baseband multicarrier symbol stream provided by the multi-antenna transmit processor 471 into an RF stream, which is then provided to a different antenna 420.

[0395] In the transmission from the first communication device 410 to the second communication device 450, at the second communication device 450, each receiver 454 receives a signal through its corresponding antenna 452. Each receiver 454 recovers the information modulated onto the radio frequency carrier and converts the radio frequency stream into a baseband multicarrier symbol stream, which is then provided to the receiver processor 456. The receiver processor 456 and the multi-antenna receiver processor 458 implement various L1 signal processing functions. The multi-antenna receiver processor 458 performs receive analog precoding / beamforming operations on the baseband multicarrier symbol stream from the receiver 454. The receiver processor 456 uses a Fast Fourier Transform (FFT) to convert the baseband multicarrier symbol stream after the receive analog precoding / beamforming operations from the time domain to the frequency domain. In the frequency domain, the physical layer data signal and the reference signal are demultiplexed by the receiver processor 456, where the reference signal is used for channel estimation, and the data signal is recovered in the multi-antenna receiver processor 458 after multi-antenna detection to recover any parallel stream destined for the second communication device 450. Symbols on each parallel stream are demodulated and recovered in the receive processor 456, generating soft decisions. The receive processor 456 then decodes and deinterleaves the soft decisions to recover the upper-layer data and control signals transmitted by the first communication device 410 over the physical channel. The upper-layer data and control signals are then provided to the controller / processor 459. The controller / processor 459 implements L2 functionality. The controller / processor 459 may be associated with a memory 460 storing program code and data. The memory 460 may be referred to as computer-readable media. In the DL, the controller / processor 459 provides multiplexing, packet reassembly, decryption, header decompression, and control signal processing between the transmission and logical channels to recover upper-layer packets from the core network. The upper-layer packets are then provided to all protocol layers above L2. Various control signals may also be provided to L3 for L3 processing. The controller / processor 459 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operation.

[0396] In the transmission from the second communication device 450 to the first communication device 410, at the second communication device 450, a data source 467 is used to provide upper-layer data packets to the controller / processor 459. The data source 467 represents all protocol layers above L2. Similar to the transmission functions at the first communication device 410 described in the DL, the controller / processor 459 implements header compression, encryption, packet segmentation and reordering, and multiplexing between logical and transport channels based on the radio resource allocation of the first communication device 410, implementing L2 functions for the user plane and control plane. The controller / processor 459 is also responsible for HARQ operations, retransmission of lost packets, and signaling to the first communication device 410. Transmit processor 468 performs modulation mapping and channel coding processing, while multi-antenna transmit processor 457 performs digital multi-antenna spatial precoding, including codebook-based and non-codebook-based precoding, and beamforming processing. Subsequently, transmit processor 468 modulates the generated parallel stream into a multi-carrier / single-carrier symbol stream. After analog precoding / beamforming operations in multi-antenna transmit processor 457, the stream is provided to different antennas 452 via transmitter 454. Each transmitter 454 first converts the baseband symbol stream provided by multi-antenna transmit processor 457 into a radio frequency symbol stream before providing it to antenna 452.

[0397] In the transmission from the second communication device 450 to the first communication device 410, the function at the first communication device 410 is similar to the receiving function at the second communication device 450 described in the transmission from the first communication device 410 to the second communication device 450. Each receiver 418 receives radio frequency signals through its corresponding antenna 420, converts the received radio frequency signals into baseband signals, and provides the baseband signals to the multi-antenna receiving processor 472 and the receiving processor 470. The receiving processor 470 and the multi-antenna receiving processor 472 jointly implement the L1 function. The controller / processor 475 implements the L2 function. The controller / processor 475 may be associated with a memory 476 storing program code and data. The memory 476 may be referred to as computer-readable media. The controller / processor 475 provides multiplexing, packet reassembly, decryption, header decompression, and control signal processing between the transmission and logical channels to recover upper-layer data packets from the second communication device 450. The upper-layer data packets from the controller / processor 475 may be provided to the core network. The controller / processor 475 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operation.

[0398] As one embodiment, the second communication device 450 includes: at least one processor and at least one memory, the at least one memory including computer program code; the at least one memory and the computer program code are configured to be used with the at least one processor. The second communication device 450 receives at least a first reporting configuration; and determines whether to generate and send a first measurement result; the first reporting configuration is used to configure the reporting of the first measurement result, the generation of the first measurement result occupies at least one processing resource, the at least one processing resource occupied by the generation of the first measurement result belongs to one of a first resource group or a second resource group, the first resource group including one or more processing resources in the second communication device 450, the second resource group including one or more processing resources in the second communication device 450; the first resource group is used for the generation of measurement results for a first type of measurement, the second resource group is used for the generation of measurement results for a second type of measurement; both the measurement results for the first type of measurement and the measurement results for the second type of measurement are generated based on inference; the first type of measurement and the second type of measurement are different; when one of the first resource group and the second resource group is fully occupied and the other is not fully occupied, whether the first measurement result is generated and sent depends on at least the former of the following two:

[0399] -Which of the first and second resource groups is the resource group that is not fully occupied?

[0400] -Is the measurement corresponding to the first measurement result the first type of measurement or the second type of measurement?

[0401] As one embodiment, the second communication device 450 includes: a memory storing a computer-readable instruction program that, when executed by at least one processor, produces actions including: receiving a first reporting configuration; and determining whether to generate and send a first measurement result.

[0402] As one embodiment, the first communication device 410 includes: at least one processor and at least one memory, the at least one memory including computer program code; the at least one memory and the computer program code are configured to be used with the at least one processor. The first communication device 410 transmits at least a first reporting configuration; the recipient of the first reporting configuration includes a second communication device 450; the first reporting configuration is used to configure the reporting of a first measurement result, the generation of the first measurement result occupies at least one processing resource, the at least one processing resource occupied by the generation of the first measurement result belongs to one of a first resource group or a second resource group, the first resource group including one or more processing resources in the second communication device 450, the second resource group including one or more processing resources in the second communication device 450; the first resource group is used for the generation of measurement results for a first type of measurement, the second resource group is used for the generation of measurement results for a second type of measurement; the measurement results of the first type of measurement and the measurement results of the second type of measurement are both generated based on inference; the first type of measurement and the second type of measurement are different; when one of the first resource group and the second resource group is fully occupied and the other is not fully occupied, whether the first measurement result is generated and transmitted depends on at least the former of the following two:

[0403] -Which of the first and second resource groups is the resource group that is not fully occupied?

[0404] -Is the measurement corresponding to the first measurement result the first type of measurement or the second type of measurement?

[0405] As one embodiment, the first communication device 410 includes: a memory storing a computer-readable instruction program that produces an action when executed by at least one processor, the action including: sending a first reporting configuration.

[0406] As one embodiment, the first communication device 410 includes: a memory storing a computer-readable instruction program that produces an action when executed by at least one processor, the action including: receiving the first measurement result.

[0407] As an example, the first node in this application includes the second communication device 450.

[0408] As an example, the second node in this application includes the first communication device 410.

[0409] As an example, at least one of {the antenna 420, the transmitter 418, the transmitter processor 416, the multi-antenna transmitter processor 471, the controller / processor 475, and the memory 476} is used to transmit the first reporting configuration in this application; at least one of {the antenna 452, the receiver 454, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to receive the first reporting configuration in this application.

[0410] As an example, at least one of the following is used to determine whether to generate and transmit the first measurement result in this application: {antenna 452, transmitter / receiver 454, transmitter processor 468, receiver processor 456, multi-antenna transmitter processor 457, multi-antenna receiver processor 458, controller / processor 459, memory 460, data source 467}.

[0411] As a sub-implementation of this embodiment, at least one of the following is used to determine the first measurement result in the non-cost application: {antenna 452, transmitter / receiver 454, transmitter processor 468, receiver processor 456, multi-antenna transmitter processor 457, multi-antenna receiver processor 458, controller / processor 459, memory 460, data source 467}.

[0412] As a sub-implementation of this embodiment, at least one of the following is used to determine the generation and transmission of the first measurement result in this application: {antenna 452, transmitter / receiver 454, transmitter processor 468, receiver processor 456, multi-antenna transmitter processor 457, multi-antenna receiver processor 458, controller / processor 459, memory 460, data source 467}.

[0413] As an example, at least one of {the antenna 420, the transmitter 418, the transmitter processor 416, the multi-antenna transmitter processor 471, the controller / processor 475, and the memory 476} is used to transmit the first information block in this application; at least one of {the antenna 452, the receiver 454, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to receive the first information block in this application.

[0414] As an example, at least one of the following is used to transmit the second information block in this application: {the antenna 452, the transmitter / receiver 454, the transmitting processor 468, the receiving processor 456, the multi-antenna transmitting processor 457, the multi-antenna receiving processor 458, the controller / processor 459, the memory 460, and the data source 467}. At least one of the following is used to receive the second information block in this application: {the antenna 420, the receiver 418, the receiving processor 470, the multi-antenna receiving processor 472, the controller / processor 475, and the memory 476}.

[0415] As an example, at least one of {the antenna 420, the transmitter 418, the transmitter processor 416, the multi-antenna transmitter processor 471, the controller / processor 475, and the memory 476} is used to transmit the M configuration messages described in this application; at least one of {the antenna 452, the receiver 454, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to receive the M configuration messages described in this application.

[0416] As an example, at least one of the following is used to calculate the performance parameters described in this application for each of the M configuration messages described in this application: {antenna 452, transmitter / receiver 454, transmitter processor 468, receiver processor 456, multi-antenna transmitter processor 457, multi-antenna receiver processor 458, controller / processor 459, memory 460, data source 467}.

[0417] Example 5

[0418] Example 5 illustrates a first flowchart of transmission between a first node and a second node according to an embodiment of this application, as shown in Figure 5. In Figure 5, the first node U1 and the second node N2 communicate via a wireless link; the steps in block F51 are optional. It should be noted that the order in this embodiment does not limit the signal transmission order or the order of implementation in this application.

[0419] For the first node U1, in step S510, the first reporting configuration is received; in step S511, it is determined whether to generate and send the first measurement result; in step S512, it is determined whether to generate and send the first measurement result.

[0420] For the second node N2, the first reporting configuration is sent in step S520; the first measurement result is received in step S521.

[0421] In Example 5, the first reporting configuration is used to configure the reporting of the first measurement result. The generation of the first measurement result occupies at least one processing resource. The at least one processing resource occupied by the generation of the first measurement result belongs to one of a first resource group or a second resource group. The first resource group includes one or more processing resources in the first node, and the second resource group includes one or more processing resources in the first node. The first resource group is used for the generation of measurement results for a first type of measurement, and the second resource group is used for the generation of measurement results for a second type of measurement. Both the measurement results for the first type of measurement and the measurement results for the second type of measurement are generated based on inference. The first type of measurement and the second type of measurement are different. When one of the first resource group and the second resource group is fully occupied and the other is not fully occupied, whether the first measurement result is generated and sent depends on at least the former of the following two:

[0422] -Which of the first and second resource groups is the resource group that is not fully occupied?

[0423] -Is the measurement corresponding to the first measurement result the first type of measurement or the second type of measurement?

[0424] As an example, the first node U1 is the first node in this application.

[0425] As an example, the second node N2 is the second node in this application.

[0426] As one embodiment, the air interface between the second node N2 and the first node U1 includes a wireless interface between the base station equipment and the user equipment.

[0427] As one embodiment, the air interface between the second node N2 and the first node U1 includes a wireless interface between the relay node device and the user equipment.

[0428] As one embodiment, the air interface between the second node N2 and the first node U1 includes a wireless interface between user equipment and user equipment.

[0429] As one example, the second node N2 and the first node U1 communicate via the Uu interface.

[0430] As one example, the second node N2 is the maintenance base station of the serving cell of the first node U1.

[0431] As an example, the transmission channel occupied by the first reporting configuration includes DL-SCH (DownLink-Shared Channel).

[0432] As an example, the physical layer channel occupied by the first reporting configuration includes PDSCH.

[0433] As an example, step S520 includes: sending an RS in a first RS resource or a first RS resource set, the RS being used to generate the first measurement result.

[0434] As a sub-implementation of this embodiment, the first reporting configuration is used to configure the first RS resource.

[0435] As a sub-implementation of this embodiment, the first reporting configuration is used to configure the first RS resource set.

[0436] As a sub-example of this embodiment, the first RS resource is associated with the first measurement result.

[0437] As a sub-implementation of this embodiment, the first RS resource set is associated with the first measurement result.

[0438] As an example, step S510 includes: receiving an RS in a first RS resource or a first RS resource set, the RS being used to generate the first measurement result.

[0439] As a sub-implementation of this embodiment, the first reporting configuration is used to configure the first RS resource.

[0440] As a sub-implementation of this embodiment, the first reporting configuration is used to configure the first RS resource set.

[0441] As a sub-example of this embodiment, the first RS resource is associated with the first measurement result.

[0442] As a sub-implementation of this embodiment, the first RS resource set is associated with the first measurement result.

[0443] As a sub-example of this embodiment, the RS is associated with an inference RS, which is used to generate the first measurement result.

[0444] As a sub-example of this embodiment, the first node U1 measures the RS to generate the first measurement result.

[0445] As a sub-example of this embodiment, the first node U1 measures the RS and generates a time-domain inference result of the RS, and the time-domain inference result is used to generate the first measurement result.

[0446] As a sub-example of this embodiment, the first node U1 measures the RS and generates a spatial domain inference result of the RS, and the spatial domain inference result is used to generate the first measurement result.

[0447] As an example, the steps in box F51 of FIG5 exist, and the method used for the first node in this application includes: determining to generate and send the first measurement result.

[0448] As a sub-implementation of this embodiment, the physical layer channel occupied by the first measurement result includes PUSCH (Physical Uplink Shared Channel).

[0449] As a sub-example of this embodiment, the physical layer channel occupied by the first measurement result includes PUCCH (Physical Uplink Control Channel).

[0450] As a sub-implementation of this embodiment, the first reporting configuration indicates the physical layer channel occupied by the first measurement result.

[0451] As an example, the steps in box F51 of FIG5 exist, and the method used for the second node in this application includes: receiving the first measurement result.

[0452] As a sub-implementation of this embodiment, receiving the first measurement result includes: detecting the first measurement result.

[0453] As a sub-example of this embodiment, receiving the first measurement result includes: monitoring the first measurement result.

[0454] As a sub-implementation of this embodiment, receiving the first measurement result includes: blind decoding the first measurement result.

[0455] As a sub-implementation of this embodiment, the second node knows whether the first measurement result has been sent before receiving the first measurement result.

[0456] As a sub-implementation of this embodiment, the second node does not know whether the first measurement result has been sent before receiving the first measurement result.

[0457] As a sub-implementation of this embodiment, the second node knows the time-frequency resources occupied by the first measurement result before receiving the first measurement result.

[0458] Typically, the first type of measurement includes measurements for layer 1, and the second type of measurement includes measurements for layer 3.

[0459] As one embodiment, the measurement corresponding to the first measurement result is the first type of measurement, and the first reporting configuration is configured as a layer 1 measurement; the measurement corresponding to the first measurement result is the second type of measurement, and the first reporting configuration is configured as a layer 3 measurement.

[0460] Typically, the first type of measurement includes measurements for CSI, and the second type of measurement includes measurements for positioning.

[0461] As one embodiment, the measurement corresponding to the first measurement result is the first type of measurement, and the first reporting configuration is configured for CSI measurement; the measurement corresponding to the first measurement result is the second type of measurement, and the first reporting configuration is configured for positioning measurement.

[0462] Typically, the processing resources include at least the former of storage resources or computing resources.

[0463] As one embodiment, the processing resources include the storage resources.

[0464] As one embodiment, the processing resources include the computing resources.

[0465] As one embodiment, the processing resources include both the storage resources and the computing resources.

[0466] As one example, the processing resources include the resources required for computation.

[0467] As one example, the processing resources include the resources required for storage.

[0468] As one example, the processing resources include the resources required for reading and writing.

[0469] As one example, the processing resources include the resources required for process control.

[0470] As one example, the processing resources include memory bandwidth.

[0471] As one example, the processing resources include cache resources.

[0472] As one example, the processing resources include bandwidth resources.

[0473] As one example, the processing resources include read and write resources.

[0474] As one example, the processing resources include cache resources.

[0475] As one example, the processing resources include register resources.

[0476] As one example, the processing resources include data interaction resources.

[0477] As one example, the processing resources include computing resources.

[0478] As one embodiment, the processing resources are used for at least one of processing, computation, or inference.

[0479] As one example, the processing resources are used for storage.

[0480] As one example, the processing resources are used for reading and writing.

[0481] As one example, the processing resources are used for data interaction.

[0482] As one example, the processing resources are used for at least addition and multiplication operations.

[0483] As one example, the processing resources are used for at least convolution operations.

[0484] As an example, one of the processing resources belongs to one processing unit.

[0485] As an example, one of the processing resources is a processing unit.

[0486] As an example, one of the processing resources is a process.

[0487] As an example, one of the processing resources is a storage unit.

[0488] As an example, one of the processing resources is a computing unit.

[0489] As an example, one of the processing resources is an Arithmetic and Logic Unit (ALU).

[0490] As an example, one of the processing resources is a Special Function Unit (SFU).

[0491] As an example, one of the processing resources corresponds to one NPU (Neural network Processing Unit).

[0492] As an example, one processing resource corresponds to one IPU (Inference Processing Unit).

[0493] As an example, one processing resource corresponds to one CPU.

[0494] As an example, one processing resource corresponds to one APU.

[0495] As an example, the CPU mentioned in this application refers to: Central Processing Unit.

[0496] As an example, the CPU mentioned in this application refers to: CSI Processing Unit, CSI processor.

[0497] As an example, the APU mentioned in this application refers to: Accelerated Processing Unit.

[0498] As an example, the APU mentioned in this application refers to: AI / ML Processing Unit, AI / ML processor.

[0499] As an example, the unit of the processing resources is GHz.

[0500] As an example, the unit of the processing resources is frequency.

[0501] As an example, the unit of the processed resources is bytes.

[0502] As an example, the unit of the processing resources is MB.

[0503] As an example, the unit of the processed resources is GB.

[0504] As an example, step S510 occurs before step S511.

[0505] As an example, step S5110 is after step S511; step S5210 is after step S520.

[0506] Example 6

[0507] Example 6 illustrates a second flowchart of transmission between a first node and a second node according to an embodiment of this application, as shown in Figure 6. In Figure 6, the first node U3 and the second node N4 communicate via a wireless link. It should be noted that the order in this embodiment does not limit the signal transmission order or the order of implementation in this application.

[0508] For the first node U3, the first information block is received in step S630.

[0509] For the second node N4, the first information block is sent in step S640.

[0510] In embodiment 6, the maximum computing power that the first node U3 can support is equal to a first integer; the first information block indicates a first ratio value, and the product of the first integer and the first ratio value, when rounded down, equals a second integer; the number of processing resources included in the second resource group is equal to the second integer, and the number of processing resources included in the first resource group is equal to the difference between the first integer and the second integer; or, the number of processing resources included in the first resource group is equal to the second integer, and the number of processing resources included in the second resource group is equal to the difference between the first integer and the second integer.

[0511] As an example, the first node U3 is the first node in this application.

[0512] As an example, the second node N4 is the second node in this application.

[0513] As one embodiment, the air interface between the second node N4 and the first node U3 includes a wireless interface between the base station equipment and the user equipment.

[0514] As one embodiment, the air interface between the second node N4 and the first node U3 includes a wireless interface between the relay node device and the user equipment.

[0515] As one embodiment, the air interface between the second node N4 and the first node U3 includes a wireless interface between user equipment and user equipment.

[0516] As one example, the second node N4 and the first node U3 communicate via the Uu interface.

[0517] As one example, the second node N4 is the sustaining base station for the serving cell of the first node U3.

[0518] As one embodiment, the first information block is carried by higher layer signaling.

[0519] As an example, the first information block is carried by RRC (Radio Resource Control) signaling.

[0520] As one embodiment, the first information block includes some or all of the fields in one or more RRC IEs (Information Elements).

[0521] As an example, the first information block explicitly indicates the first ratio value.

[0522] As an example, the first information block implicitly indicates the first ratio value.

[0523] As an example, the first information block directly indicates the first ratio value.

[0524] As an example, the first information block indirectly indicates the first ratio value.

[0525] As an example, the first integer corresponds to the total number of CPUs in the first node.

[0526] As an example, the first integer corresponds to the number of CSI calculations that the first node supports simultaneously in a CC (Component Carrier).

[0527] As an example, the first integer corresponds to the number of times the first node supports simultaneous CSI calculations across all CCs.

[0528] As an example, the first integer corresponds to simultaneousCSI-ReportsPerCC.

[0529] As an example, the first integer corresponds to simultaneousCSI-ReportsAllCC.

[0530] As an example, the first integer corresponds to simultaneousCSI-ReportsPerCC-r19.

[0531] As an example, the first integer corresponds to simultaneousCSI-ReportsAllCC-r19.

[0532] As an example, the first integer corresponds to simultaneousCSI-ReportsPerCC-AI.

[0533] As an example, the first integer corresponds to simultaneousCSI-ReportsAllCC-AI.

[0534] As an example, the first node reports the first integer via UAI.

[0535] As an example, the first node reports the first integer through OtherConfig.

[0536] As an example, the first node reports the first integer via mimo-ParametersPerBand.

[0537] As an example, the first node reports the first integer via RF-Parameters IE.

[0538] As an example, the first ratio value is a number between 0 and 1.

[0539] As an example, the product of the first integer and the first ratio value, when rounded down, equals the second integer.

[0540] As an example, the product of the first integer and the first ratio value, rounded up, equals the second integer.

[0541] As an example, the name of the RRC signaling carrying the first information block includes: CSI.

[0542] As an example, the name of the RRC signaling carrying the first information block includes: Report.

[0543] As an example, the name of the RRC signaling carrying the first information block includes: Inference.

[0544] As an example, the name of the RRC signaling carrying the first information block includes: Config.

[0545] As an example, the name of the RRC signaling carrying the first information block includes: AI.

[0546] As an example, the name of the RRC signaling carrying the first information block includes: ML.

[0547] As an example, the name of the RRC signaling carrying the first information block includes: Layer.

[0548] As an example, the first integer is a positive integer.

[0549] As an example, the first integer is a positive integer greater than 1.

[0550] As an example, the first integer is equal to (K1+K2) as described in this application.

[0551] As an example, the candidates for the first ratio value include 0.

[0552] As an example, the candidates for the first ratio value include 1.

[0553] As an example, the default value of the first ratio is 0.5.

[0554] As one embodiment, the first information block indicates the first ratio value.

[0555] As one embodiment, the first information block is configured with the first ratio value.

[0556] As an example, the first information block is reconfigured with the first ratio value.

[0557] As an example, the first information block indicates a change in the first ratio value.

[0558] As an example, the product of the first integer and the first ratio value, when rounded down, equals the second integer.

[0559] As an example, the product of the first integer and the first ratio value, when rounded down, equals the second integer.

[0560] As an example, the product of the first integer and the first ratio value, rounded up, equals the second integer.

[0561] As one embodiment, the number of processing resources included in the second resource group is equal to the second integer.

[0562] As an example, the number of processing resources included in the first resource group is equal to the difference between the first integer and the second integer.

[0563] As an example, the number of processing resources included in the first resource group is equal to the second integer.

[0564] As an example, the number of processing resources included in the second resource group is equal to the difference between the first integer and the second integer.

[0565] As an example, the second integer is a positive integer.

[0566] As an example, the second integer is a positive integer greater than 1.

[0567] As an example, the second integer is equal to K1 as described in this application.

[0568] As an example, the second integer is equal to K2 as described in this application.

[0569] As an example, the number of processing resources included in the first resource group is equal to K1 as described in this application.

[0570] As an example, the number of processing resources included in the second resource group is equal to K2 as described in this application.

[0571] As an example, the transmission channel occupied by the first information block includes DL-SCH.

[0572] As an example, the physical layer channel occupied by the first information block includes PDSCH.

[0573] As an example, step S630 precedes step S511 in Figure 5.

[0574] As an example, step S630 precedes step S510 in Figure 5; step S640 precedes step S520 in Figure 5.

[0575] As an example, step S630 follows step S510 in Figure 5; step S640 follows step S520 in Figure 5.

[0576] As an example, the first information block and the first reporting configuration belong to different domains of the same RRC IE, or the first information block and the first reporting configuration are carried by the same RRC information; steps S630 and S510 occur simultaneously, and steps S640 and S520 occur simultaneously.

[0577] Example 7

[0578] Example 7 illustrates a third flowchart of transmission between a first node and a second node according to an embodiment of this application, as shown in Figure 7. In Figure 7, the first node U5 and the second node N6 communicate via a wireless link. It should be noted that the order in this embodiment does not limit the signal transmission order or the order of implementation in this application.

[0579] For the first node U5, the second information block is sent in step S750.

[0580] For the second node N6, the second information block is received in step S760.

[0581] In Example 7, the second information block is used to trigger the reconfiguration of the first ratio value.

[0582] As an example, the first node U5 is the first node in this application.

[0583] As an example, the second node N6 is the second node in this application.

[0584] As one embodiment, the air interface between the second node N6 and the first node U5 includes a wireless interface between the base station equipment and the user equipment.

[0585] As one embodiment, the air interface between the second node N6 and the first node U5 includes a wireless interface between the relay node device and the user equipment.

[0586] As one embodiment, the air interface between the second node N6 and the first node U5 includes a wireless interface between user equipment and user equipment.

[0587] As one example, the second node N6 and the first node U5 communicate via the Uu interface.

[0588] As one example, the second node N6 is the sustaining base station for the serving cell of the first node U5.

[0589] As one embodiment, the second information block is used to trigger the second node N6 to increase or decrease the first ratio value.

[0590] As an example, the second information block relies on the results of performance monitoring of the AI / ML model.

[0591] As a sub-example of this embodiment, the results of the performance monitoring are for different types of AI / ML models.

[0592] As an example, the second information block relies on the performance evaluation results of the AI / ML model.

[0593] As a sub-example of this embodiment, the results of the performance evaluation are for different types of AI / ML models.

[0594] As one embodiment, the second information block is event-triggered, the event including the requirement that the performance of the AI / ML model for the first type of measurement is better than a given threshold.

[0595] As one embodiment, the second information block is event-triggered, the event including the performance of the AI / ML model for a second type of measurement being better than a given threshold.

[0596] As an example, the second information block is event-triggered, the event including that the number of unoccupied processing resources in the first resource group of the first node U5 is not less than a given threshold.

[0597] As an example, the second information block is event-triggered, the event including that the number of unoccupied processing resources in the second resource group of the first node U5 is not less than a given threshold.

[0598] As an example, the second information block is event-triggered, the event including that the number of unoccupied processing resources in the first resource group of the first node U5 is not less than a given threshold, and that the number of occupied processing resources in the second resource group is not greater than a given threshold.

[0599] As an example, the second information block is event-triggered, the event including that the number of unoccupied processing resources in the second resource group of the first node U5 is not less than a given threshold, and that the number of occupied processing resources in the first resource group is not greater than the given threshold.

[0600] As one embodiment, the transmission channel occupied by the second information block includes UL-SCH (UpLink-Shared Channel).

[0601] As an example, the physical layer channel occupied by the second information block includes PUCCH.

[0602] As an example, the physical layer channel occupied by the second information block includes PUSCH.

[0603] As an example, step S750 precedes step S511 as shown in Figure 5.

[0604] As an example, step S750 follows step S511 as shown in Figure 5.

[0605] As an example, step S750 precedes step S510 in Figure 5; step S760 precedes step S520 in Figure 5.

[0606] As an example, step S750 follows step S510 in Figure 5; step S760 follows step S520 in Figure 5.

[0607] As an example, step S750 follows step S630 in Figure 6; step S760 follows step S640 in Figure 6.

[0608] As an example, step S750 precedes step S630 in Figure 6; step S760 precedes step S640 in Figure 6.

[0609] Example 8

[0610] Example 8 illustrates a fourth flowchart of transmission between a first node and a second node according to an embodiment of this application, as shown in Figure 8. In Figure 8, the first node U7 and the second node N8 communicate via a wireless link. It should be noted that the order in this embodiment does not limit the signal transmission order or the order of implementation in this application.

[0611] For the first node U7, M configuration messages are received in step S870; and performance parameters are calculated for each of the M configuration messages in step S871.

[0612] For the second node N8, M configuration messages are sent in step S880.

[0613] In Example 8, the M configuration messages respectively indicate M RS resource groups, each of the M RS resource groups includes one or more RS resources, and M is a positive integer greater than 1; the calculation of the performance parameter depends on the measurement for the RS resource group indicated by the corresponding configuration message; the second information block depends on the performance parameter.

[0614] As an example, the first node U7 is the first node in this application.

[0615] As an example, the second node N8 is the second node in this application.

[0616] As one embodiment, the air interface between the second node N8 and the first node U7 includes a wireless interface between the base station equipment and the user equipment.

[0617] As one embodiment, the air interface between the second node N8 and the first node U7 includes a wireless interface between the relay node device and the user equipment.

[0618] As one embodiment, the air interface between the second node N8 and the first node U7 includes a wireless interface between user equipment and user equipment.

[0619] As one example, the second node N8 and the first node U7 communicate via the Uu interface.

[0620] As one example, the second node N8 is the sustaining base station for the serving cell of the first node U7.

[0621] As an example, RS stands for Reference Signal.

[0622] As an example, step S871 includes receiving RSs from the M RS resource groups.

[0623] As an example, step S880 includes sending the RSs in the M RS resource groups.

[0624] As an example, any one of the M configuration messages is transmitted via higher-layer signaling.

[0625] As an example, any one of the M configuration messages is carried by RRC layer signaling.

[0626] As an example, any one of the M configuration messages is transmitted via RRC signaling.

[0627] As an example, any one of the M configuration messages is transmitted via an RRC message.

[0628] As an example, any one of the M configuration messages includes RRC signaling.

[0629] As an example, any one of the M configuration messages includes one or more RRC IEs.

[0630] As an example, any one of the M configuration messages includes one or more fields in an RRC IE.

[0631] As an example, any one of the M configuration messages includes one or more fields in each of the multiple RRC IEs.

[0632] As an example, the M configuration messages are carried by the same RRC signaling.

[0633] As an example, the M configuration messages belong to a list included in an RRC IE.

[0634] As a sub-implementation of this embodiment, the M configuration messages correspond to the same domain of the RRC IE.

[0635] As a sub-implementation of this embodiment, the M configuration messages correspond to the M elements of the list.

[0636] As a sub-implementation of this embodiment, the name of the list carrying the M configuration messages includes: Add.

[0637] As a sub-implementation of this embodiment, the name of the list carrying the M configuration messages includes: Mod.

[0638] As a sub-implementation of this embodiment, the name of the list carrying the M configuration messages includes: ToAddModList.

[0639] As an example, any one of the M configuration messages includes ServingCellConfig IE.

[0640] As an example, any one of the M configuration messages includes one or more domains in the ServingCellConfig IE.

[0641] As an example, any one of the M configuration messages includes CSI-MeasConfig IE.

[0642] As an example, any one of the M configuration messages includes one or more domains in the CSI-MeasConfig IE.

[0643] As an example, any one of the M configuration messages includes NZP-CSI-RS-Resource IE.

[0644] As an example, any one of the M configuration messages includes one or more domains in the NZP-CSI-RS-Resource IE.

[0645] As an example, any one of the M configuration messages includes the CSI-RS-ResourceMapping IE.

[0646] As an example, any one of the M configuration messages includes one or more domains in the CSI-RS-ResourceMapping IE.

[0647] As an example, any one of the M configuration messages includes CSI-FrequencyOccupation IE.

[0648] As an example, any one of the M configuration messages includes one or more domains in the CSI-FrequencyOccupation IE.

[0649] As an example, any one of the M configuration messages includes CSI-ResourcePeriodicityAndOffset IE.

[0650] As an example, any one of the M configuration messages includes one or more domains in CSI-ResourcePeriodicityAndOffset IE.

[0651] As an example, any one of the M configuration messages includes NZP-CSI-RS-ResourceSet IE.

[0652] As an example, any one of the M configuration messages includes one or more domains in the NZP-CSI-RS-ResourceSet IE.

[0653] As an example, any one of the M configuration messages includes CSI-IM-Resource IE.

[0654] As an example, any one of the M configuration messages includes one or more domains in the CSI-IM-Resource IE.

[0655] As an example, any one of the M configuration messages includes CSI-IM-ResourceSet IE.

[0656] As an example, any one of the M configuration messages includes one or more domains in the CSI-IM-ResourceSet IE.

[0657] As an example, any one of the M configuration messages includes CSI-SSB-ResourceSet IE.

[0658] As an example, any one of the M configuration messages includes one or more domains in the CSI-SSB-ResourceSet IE.

[0659] As an example, any one of the M configuration messages includes CSI-ResourceConfig IE.

[0660] As an example, any one of the M configuration messages includes one or more domains in the CSI-ResourceConfig IE.

[0661] As an example, any one of the M configuration messages includes CSI-RS-ResourceConfigMobility IE.

[0662] As an example, any one of the M configuration messages includes one or more domains in the CSI-RS-ResourceConfigMobility IE.

[0663] As an example, any one of the M configuration messages includes CSI-ReportConfig IE.

[0664] As an example, any one of the M configuration messages includes one or more fields in the CSI-ReportConfig IE.

[0665] As an example, any one of the M configuration messages includes a CSI-AperiodicTriggerStateList IE.

[0666] As an example, any one of the M configuration messages includes one or more domains in the CSI-AperiodicTriggerStateList IE.

[0667] As an example, any one of the M configuration messages includes a CSI-AperiodicTriggerState IE.

[0668] As an example, any one of the M configuration messages includes one or more domains in the CSI-AperiodicTriggerState IE.

[0669] As an example, any one of the M configuration messages includes a CSI-AssociatedReportConfigInfo IE.

[0670] As an example, any one of the M configuration messages includes one or more domains in the CSI-AssociatedReportConfigInfo IE.

[0671] As an example, any one of the M configuration messages includes CSI-SemiPersistentOnPUSCH-TriggerStateList IE.

[0672] As an example, any one of the M configuration messages includes one or more domains in the CSI-SemiPersistentOnPUSCH-TriggerStateList IE.

[0673] As an example, any one of the M configuration messages includes CSI-SemiPersistentOnPUSCH-TriggerState IE.

[0674] As an example, any one of the M configuration messages includes one or more domains in the CSI-SemiPersistentOnPUSCH-TriggerState IE.

[0675] As an example, any one of the M configuration messages includes a CSI-ReportSubConfigTriggerList IE.

[0676] As an example, any one of the M configuration messages includes one or more domains in the CSI-ReportSubConfigTriggerList IE.

[0677] As an example, any one of the M configuration messages includes CSI-ReportSubConfig IE.

[0678] As an example, any one of the M configuration messages includes one or more domains in the CSI-ReportSubConfig IE.

[0679] As an example, any one of the M configuration messages includes LTM-CSI-ReportConfig IE.

[0680] As an example, any one of the M configuration messages includes one or more domains in the LTM-CSI-ReportConfig IE.

[0681] As an example, the name of the RRC signaling used to transmit any one of the M configuration messages includes CSI.

[0682] As an example, the name of the RRC signaling used to transmit any one of the M configuration messages includes CSI-RS.

[0683] As an example, the name of the RRC signaling used to transmit any one of the M configuration messages includes Report.

[0684] As an example, the name of the RRC signaling used to transmit any one of the M configuration messages includes Config.

[0685] As an example, the M configuration messages are all used for prediction.

[0686] As an example, the M configuration messages are all used for AI / ML inference.

[0687] As an example, the M configuration messages are M prediction configuration messages.

[0688] As an example, the M configuration messages are M parameter sets.

[0689] As an example, the M configuration messages are M beam configuration messages.

[0690] As an example, the M configuration messages include the first reported configuration.

[0691] As an example, the first reported configuration is associated with at least one of the M configuration messages.

[0692] As an example, the M configuration messages do not include the first reported configuration.

[0693] As an example, the first reported configuration is not associated with any of the M configuration messages.

[0694] As an example, the M configuration messages respectively indicate the M RS resource groups.

[0695] As an example, the M configuration messages configure the M RS resource groups respectively.

[0696] As an example, the M configuration messages correspond one-to-one with the M RS resource groups.

[0697] As an example, any one of the M configuration messages indicates an RS resource group.

[0698] As an example, any one of the M configuration messages configures an RS resource group.

[0699] As an example, any one of the M configuration messages indicates one of the M RS resource groups.

[0700] As an example, any one of the M configuration messages configures one of the M RS resource groups.

[0701] As an example, the M RS resource groups each correspond to M beams.

[0702] As an example, the M RS resource groups correspond to M RS resource sets.

[0703] As an example, each of the M configuration messages indicates the measurement period for the corresponding RS resource group.

[0704] As an example, each of the M configuration messages indicates the measurement period for each RS resource in the corresponding RS resource group.

[0705] As an example, each of the M configuration messages indicates the RS resources included in the corresponding RS resource group.

[0706] As an example, each of the M configuration messages indicates the configuration information of the RS resources included in the corresponding RS resource group.

[0707] As an example, the configuration information of RS resources described in this application includes time-domain resources, frequency-domain resources, density, CDM (Code Division Multiplexing), transmit power, scrambling ID, and QCL.

[0708] As an example, the configuration information of RS resources described in this application includes some or all of the following: time domain resources, frequency domain resources, CDM type, CDM group, RS sequence, scrambling code, period, time slot offset, QCL relationship, TCI status, density, or number of CSI-RS ports.

[0709] As an example, each of the M configuration messages includes a reported configuration.

[0710] As an example, the M configuration messages respectively indicate M reported configurations.

[0711] As an example, each of the M configuration messages indicates the reporting configuration for the RS resources included in the corresponding RS resource group.

[0712] As an example, two of the M configuration messages include the first reported configuration.

[0713] As an example, the RS resource reporting configuration described in this application includes one or more of the following: time domain resources, frequency domain resources, codebook, occupied channels, and CSI types.

[0714] As a sub-example of this embodiment, the candidates for the CSI type include one or more of L1-RSRP, CRI, RI, PMI, CQI, LI, SSB-Index, SSBRI, SINR, L1-SINR, Capability Index, and Capability Set Index.

[0715] As an example, any one of the M RS resource groups includes one or more RS resources.

[0716] As an example, at least one RS resource group among the M RS resource groups includes only one RS resource, and at least one RS resource group among the M RS resource groups includes multiple RS resources.

[0717] As an example, the RS resource group includes only one RS resource.

[0718] As an example, the RS resource group includes multiple RS resources.

[0719] As an example, at least one of the M RS resource groups contains only one RS resource.

[0720] As an example, at least one of the M RS resource groups includes multiple RS resources.

[0721] As a sub-example of this embodiment, the plurality of RS resources included in the RS resource group belong to different RS resource sets.

[0722] As a sub-example of this embodiment, at least two of the plurality of RS resources included in the RS resource group correspond to different NZP-CSI-RS-ResourceSetId.

[0723] As a sub-example of this embodiment, the plurality of RS resources included in the RS resource group belong to the same RS resource set.

[0724] As a sub-example of this embodiment, the plurality of RS resources included in the RS resource group correspond to the same NZP-CSI-RS-ResourceSetId.

[0725] As an example, the RS resources included in any of the M RS resource groups belong to an RS resource set.

[0726] As an example, the RS resources described in this application are periodic.

[0727] As an example, the RS resources described in this application are semi-persistent.

[0728] As an example, the RS resources described in this application include antenna ports.

[0729] As an example, the RS resource described in this application includes a reference signal port.

[0730] As an example, the RS resources described in this application include CSI-RS ports.

[0731] As an example, the RS resource described in this application is one of CSI-RS resources or SSB.

[0732] As an example, the RS resources described in this application include CSI-RS resources.

[0733] As an example, the RS resource described in this application is a CSI-RS resource.

[0734] As an example, the RS resources described in this application include NZP (Non-Zero Power) CSI-RS resources.

[0735] As an example, the RS resource described in this application is an NZP CSI-RS resource.

[0736] As an example, one RS resource described in this application corresponds to one CSI-RS resource ID.

[0737] As an example, one RS resource described in this application corresponds to one NZP-CSI-RS-ResourceId.

[0738] As an example, the RS resources described in this application include SSBs.

[0739] As an example, the RS resource described in this application is an SSB.

[0740] As an example, one RS resource described in this application corresponds to one SSB-Index.

[0741] As an example, one RS resource described in this application corresponds to one ssb-Index.

[0742] As an example, SSB in this application refers to Synchronization Signal Block.

[0743] As an example, the SSB mentioned in this application refers to: SS (Synchronization Signal) / PBCH (Physical Broadcast Channel) block.

[0744] Typically, the PBCH, PSS (Primary Synchronization Signal), and SSS (Secondary Synchronization Signal) are received in consecutive symbols and form an SS / PBCH block.

[0745] As an example, when the RS resources included in the RS resource group are CSI-RS resources or SSBs, the above method has good forward compatibility; however, in order to adapt to the performance requirements of future wireless networks such as 6G, the signals included in the RS resource group may also be other types of RS to better meet the performance requirements of measurement reporting.

[0746] As an example, each of the M RS resource groups includes RS resources that are either CSI-RS resources or SSBs.

[0747] As an example, any one of the M RS resource groups is a CSI-RS resource group or an SSB group.

[0748] As an example, any one of the M RS resource groups is a CSI-RS resource group.

[0749] As an example, any one of the M RS resource groups is an SSB group.

[0750] As an example, for each of the M configuration messages, the first node U7 calculates the performance parameters.

[0751] As an example, the first node U7 calculates M performance parameters, each of which relates to one of the M configuration messages.

[0752] As a sub-example of this embodiment, the M performance parameters are respectively used for performance monitoring of the M predictions corresponding to the M configuration messages.

[0753] As a supplementary embodiment of this sub-example, the M predictions correspond to M prediction sub-models respectively.

[0754] As a supplementary embodiment of this sub-example, the M predictions each correspond to the M prediction functions of a model.

[0755] As a supplementary embodiment of this sub-example, the M predictions each correspond to the M prediction targets of a model.

[0756] As a supplementary embodiment of this sub-example, the M predictions each correspond to one of the M prediction tasks of a model.

[0757] As an example, the performance parameter corresponds to a performance metric.

[0758] As an example, the performance parameter corresponds to a KPI (Key Performance Indicator).

[0759] As an example, the performance parameter is the intermediate KPI.

[0760] As an example, the performance parameter is the final KPI (eventual KPI).

[0761] As an example, the performance parameter is used for performance monitoring of one of the M configuration messages.

[0762] As an example, the performance parameter is used for performance monitoring of the measurement indicated by one of the M configuration messages.

[0763] As an example, the signaling carrying the M configuration messages indicates the performance parameters.

[0764] As an example, each of the M configuration messages indicates the performance parameter.

[0765] As an example, the candidates for the performance parameters include one or more of GCS (Generalized Cosine Similarity), SGSC (Squared Generalized Cosine Similarity), NMSE (Normalized Mean Squared Error), truth ground CSI, equivalent MSE (equivalent Mean Squared Error), and numerical spectral efficiency gap.

[0766] As an example, the candidates for the performance parameter include one or more of throughput, BLER (Block Error Rate), and hypothetical BLER.

[0767] As an example, the performance parameter is NMSE.

[0768] As an example, the performance parameter is SGCS.

[0769] As an example, the performance parameter is truth ground CSI.

[0770] As an example, the calculation of the performance parameters depends on the measurement of the RS resource group indicated by the corresponding configuration message.

[0771] As an example, any one of the M configuration messages indicates a measurement for the corresponding RS resource group.

[0772] As an example, the measurement includes measurements of at least one of RSRP (Reference Signal Received Power), RSRQ (Reference Signal Received Quality), RSSI (Received Signal Strength Indicator), and SNR (Signal To Noise Ratio).

[0773] As an example, the measurement includes measurements for RSRP.

[0774] As an example, the measurement includes a measurement for RSRQ.

[0775] As an example, the measurement includes a measurement of RSSI.

[0776] As an example, the measurement includes a measurement of SNR.

[0777] As an example, the first node U7 performs the calculation of the performance parameters accordingly.

[0778] As an example, the first node U7 obtains the performance parameters by comparing the measurement results of the RS resource group indicated by the corresponding configuration message with the prediction results obtained from the corresponding configuration message.

[0779] As an example, the first node U7 obtains the performance parameter by calculating the difference between the measurement result of the RS resource group indicated by the corresponding configuration message and the prediction result obtained from the corresponding configuration message.

[0780] As an example, the first node U7 obtains the performance parameter by calculating the Euclidean metric between the measurement results of the RS resource group indicated by the corresponding configuration message and the prediction results obtained from the corresponding configuration message.

[0781] As an example, the second information block depends on the performance parameters.

[0782] As one example, whether the second information block is sent depends on the performance parameters.

[0783] As an example, the generation of the second information block depends on the performance parameters.

[0784] As an example, whether the second information block is sent depends on the M performance parameters.

[0785] As an example, the generation of the second information block depends on the M performance parameters.

[0786] As one embodiment, the second information block includes the performance parameters.

[0787] As an example, the second information block includes at least one of the M performance parameters.

[0788] As an example, the M performance parameters are ordered from smallest to largest, and the second information block includes the first N parameters among the M performance parameters, where N is a positive integer and is predefined or configurable.

[0789] As an example, the M performance parameters are ordered from largest to smallest, and the second information block includes the first N parameters among the M performance parameters, where N is a positive integer and is predefined or configurable.

[0790] As one example, the performance parameters are used to trigger the transmission of the second information block.

[0791] As an example, if the performance parameter is higher than the first threshold, the second information block is triggered.

[0792] As an example, if at least one of the M performance parameters is higher than the first threshold, the second information block is triggered.

[0793] As an example, if one of the M performance parameters is higher than the first threshold, the second information block is triggered.

[0794] As an example, if at least N of the M performance parameters are higher than the first threshold, the second information block is triggered, where N is a positive integer.

[0795] As a sub-implementation of this embodiment, N is either predefined or configured by the second node N8.

[0796] As a sub-implementation of this embodiment, the meaning of "not less than N of the M performance parameters being higher than the first threshold" includes: the first node maintains a first counter, the first configuration message is any one of the M configuration messages, the first node calculates the performance parameter corresponding to the first configuration message, and when the performance parameter corresponding to the first configuration message is higher than the first threshold, or when the number of times or the duration of the performance parameter corresponding to the first configuration message being higher than the first threshold is not higher than a second threshold, the value of the first counter is incremented by 1; the second threshold is predefined or configurable.

[0797] As a sub-implementation of this embodiment, the meaning that not less than N of the M performance parameters are higher than the first threshold includes: the first node maintains a first counter, the first configuration message is any one of the M configuration messages, the first node periodically calculates the performance parameter corresponding to the first configuration message, and when the performance parameter corresponding to the first configuration message is higher than the first threshold in one period, the value of the first counter is incremented by 1; and when the performance parameter corresponding to the first configuration message is higher than the first threshold in another period, the value of the first counter continues to be incremented by 1.

[0798] As an example, the M configuration messages occupy at least one PDSCH.

[0799] As an example, the M configuration messages occupy one PDSCH.

[0800] As an example, at least one of the M configuration messages is for the first type of measurement.

[0801] As a sub-implementation of this embodiment, "for the first type of measurement" means: for the performance evaluation of the AI / ML model for the first type of measurement.

[0802] As a sub-example of this embodiment, "for the first type of measurement" means: for the performance monitoring of the AI / ML model for the first type of measurement.

[0803] As an example, at least one of the M configuration messages is for the second type of measurement.

[0804] As a sub-example of this embodiment, "for the second type of measurement" means: for the performance evaluation of the AI / ML model for the second type of measurement.

[0805] As a sub-example of this embodiment, the meaning of "for the second type of measurement" includes: performance monitoring of AI / ML models for the second type of measurement.

[0806] As an example, the M configuration messages are transmitted on a PDSCH, and step S870 includes receiving the PDSCH.

[0807] As an example, the M configuration messages are transmitted on multiple PDSCHs, and step S870 includes receiving the multiple PDSCHs.

[0808] As an example, step S870 precedes step S511 as shown in Figure 5.

[0809] As an example, step S870 precedes step S510 in Figure 5; step S880 precedes step S520 in Figure 5.

[0810] As an example, step S870 follows step S510 in Figure 5; step S880 follows step S520 in Figure 5.

[0811] As an example, the M configuration messages and the first reported configuration belong to different domains of the same RRC IE, or the M configuration messages and the first reported configuration are carried by the same RRC information, or the M configuration messages include the first reported configuration; steps S870 and S510 occur simultaneously, and steps S880 and S520 occur simultaneously.

[0812] As an example, step S871 precedes step S750 in Figure 7.

[0813] Example 9

[0814] Example 9 illustrates a first schematic diagram of the occupancy of a first resource group and a second resource group according to an embodiment of this application, as shown in Figure 9. In Figure 9, a solid-lined rectangle represents a processing resource, where an unfilled rectangle represents an unoccupied processing resource, a gray-filled rectangle represents an occupied processing resource, and a diamond-shaped filled rectangle represents the processing resources occupied for generating a first measurement result; the first resource group includes K1 processing resources, and the second resource group includes K2 processing resources, where K1 and K2 are positive integers; the second resource group is not fully occupied and the first resource group is fully occupied, and the number of processing resources occupied for generating the first measurement result is not greater than the number of unoccupied processing resources in the second resource group; regardless of whether the measurement corresponding to the first measurement result is a first type of measurement or a second type of measurement, the first measurement result is generated and sent.

[0815] In Example 9, the number of unoccupied processing resources in the first resource group is not less than the number of processing resources required for the first measurement result.

[0816] As an example, whether the first measurement result is generated and sent depends solely on which of the first and second resource groups the resource group that is not fully occupied is.

[0817] As an example, when the first resource group is not fully occupied and the second resource group is fully occupied, whether the first measurement result is generated and sent does not depend on whether the first measurement result is generated based on inference.

[0818] As an example, when the first resource group is not fully occupied and the second resource group is fully occupied, whether the first measurement result is generated and sent depends on the number of unoccupied processing resources in the first resource group.

[0819] As an example, when the first resource group is not fully occupied and the second resource group is fully occupied, whether the first measurement result is generated and sent depends on whether the number of unoccupied processing resources in the first resource group is less than the number of processing resources required for the first measurement result.

[0820] As a sub-implementation of this embodiment, when the number of unoccupied processing resources in the first resource group is less than the number of processing resources required for the first measurement result, the first measurement result is not generated.

[0821] As a sub-implementation of this embodiment, when the number of unoccupied processing resources in the first resource group is less than the number of processing resources required for the first measurement result, the first measurement result is not updated.

[0822] As a sub-implementation of this embodiment, when the number of unoccupied processing resources in the first resource group is less than the number of processing resources required for the first measurement result, the first node is not required to update the first measurement result.

[0823] As a sub-implementation of this embodiment, the first measurement result is generated and sent when the number of unoccupied processing resources in the first resource group is not less than the number of processing resources required for the first measurement result.

[0824] As an example, the meaning of "the first resource group is not fully occupied" includes: the number of unoccupied processing resources in the first resource group is not less than the number of processing resources required by the first measurement result.

[0825] As an example, the conditions for generating and sending the first measurement result include: the first resource group is not fully occupied, and the amount of remaining processing resources in the first resource group is not less than the amount of processing resources required by the first measurement result.

[0826] As an example, whether the first measurement result is generated and sent depends on which of the first and second resource groups the unoccupied resource group is, and whether the amount of processing resources occupied by the generation of the first measurement result is not greater than the amount of unoccupied processing resources in the second resource group.

[0827] As an example, the meaning of "the second resource group is not fully occupied" includes: at least one processing resource in the second resource group is not occupied.

[0828] As an example, the fact that the first resource group is fully occupied means that there is no unoccupied processing resource in the first resource group.

[0829] As an example, if the amount of processing resources required to generate the first measurement result is greater than the amount of unused processing resources in the second resource group, the first measurement result will not be generated or sent.

[0830] Example 10

[0831] Example 10 illustrates a second schematic diagram of the occupancy of a first resource group and a second resource group according to an embodiment of this application, as shown in Figure 10. In Figure 10, a rectangle with a solid line frame represents a processing resource, wherein an unfilled rectangle represents an unoccupied processing resource, a gray-filled rectangle represents an occupied processing resource, and a rectangle filled with diamond crosses represents the processing resources occupied for generating a first measurement result; the first resource group includes K1 processing resources, and the second resource group includes K2 processing resources, where K1 and K2 are positive integers; the second resource group is fully occupied and the first resource group is not fully occupied; the number of processing resources occupied for generating the first measurement result is not greater than the number of unoccupied processing resources in the first resource group; when the measurement corresponding to the first measurement result is a first type of measurement, the first measurement result is generated and sent.

[0832] In Example 10, when the measurement corresponding to the first measurement result is the second type of measurement, the first measurement result is not generated and is not sent.

[0833] As one embodiment, whether the first measurement result is generated and sent depends on which of the first and second resource groups the unoccupied resource group is, whether the measurement corresponding to the first measurement result is the first type of measurement or the second type of measurement, and whether the amount of processing resources occupied by the generation of the first measurement result is not greater than the amount of unoccupied processing resources in the first resource group.

[0834] As an example, if the amount of processing resources required to generate the first measurement result is greater than the amount of unused processing resources in the first resource group, the first measurement result will not be generated or sent.

[0835] Example 11

[0836] Example 11 illustrates a schematic diagram of RAN domain AI / ML function deployment according to one embodiment of this application, as shown in Figure 11. In Figure 11, the gNB can be replaced with, for example, an eNB, or a network device such as a 6G base station.

[0837] In Example 11, the management of ML inference functions of multiple base stations is completed by the RAN domain management function 1102, that is, data interaction with the RAN domain MnS (Management Service) consumer / cross-domain management 1101 (as shown by the dashed arrow in Figure 11). The RAN domain ML training function 1103 is located in the RAN domain management function 1102; while the ML inference function is located in the base station, that is, the AI / ML inference function 1104 is located in gNB 1105, the AI / ML inference function 1106 is located in gNB 1107, and so on.

[0838] AI / ML related functions include ML training (also known as AI training or AI / ML training), ML testing, and ML inference (also known as AI inference or AI / ML inference), etc. ML training, ML testing, and ML inference functions can be deployed independently or co-located. Deployment of AI / ML related functions can be implemented through software, such as downloading and / or running executable files; or it can be implemented through a combination of software and hardware, such as accelerating specific computing units through hardware to improve computing speed or save power.

[0839] ML training functions can be deployed in a cross-domain management system or a domain-specific management system; the domain-specific management system is used to manage the RAN domain or the CN (Core Network) domain. For example, ML training functions for MDA (Management Data Analytics) can be deployed in MDAF (Management Data Analytic Function); ML training for network data analytics can be deployed in NWDAF (Network Data Analytics Function), meaning the ML training function is an MTLF (Model Training Logical Function).

[0840] The ML inference function can also be deployed in a cross-domain management system or a domain-specific management system; for example, the ML inference function is MDAF, or the ML inference function is AnLF (Analytics Logical Function) located in NWDAF.

[0841] Similarly, ML testing capabilities can also be deployed in cross-domain management systems or domain-specific management systems.

[0842] Optionally, the management of ML inference function can also be completed by the base station itself, that is, each base station can independently interact with the RAN domain MnS consumer / cross-domain management 1101.

[0843] It should be noted that Example 11 is merely a non-limiting implementation; optionally, the ML training function of the RAN domain may also be deployed at the base station; or optionally, some base stations may deploy both the ML inference function and the ML training function of the RAN domain, while some base stations may only deploy the ML inference function.

[0844] As an example, one of the gNBs (or base stations) in Example 11 is the second node of this application.

[0845] Example 12

[0846] Example 12 illustrates a schematic diagram of the deployment of AI / ML functions in a UE according to one embodiment of this application, as shown in Figure 12. In Figure 12, the RAN domain ML training function 1204 is optional.

[0847] UE function 1203 is deployed in the first node of this application, and the UE function 1203 includes AI / ML inference function 1205; the AI / ML inference function 1205 uses an ML model (also called an AI model) for inference; an ML model is typically trained before being used for AI / ML inference.

[0848] As an example, the UE function 1203 includes a RAN domain ML training function 1204, which runs training data through an ML model to obtain a relevant loss and adjusts the parameters of the ML model based on the calculated loss; the ML training includes at least one of ML initial training, ML re-training, and reinforcement learning.

[0849] The above embodiments can reduce the complexity of the base station, or save air interface resources caused by reporting training data; however, the above embodiments place high demands on the processing capabilities of the UE side.

[0850] Optionally, the UE function 1203 also includes a CN domain ML training function (not shown in Figure 12).

[0851] Optionally, the UE function 1203 also includes an AI / ML deployment function—not shown in Figure 12—for loading ML models and data.

[0852] As an example, the first node indicates whether it supports ML training function (RAN domain or CN domain) through capability reporting. The capability reporting is RRC signaling or NAS (Non-Access Stratum) signaling.

[0853] As an example, the ML model and the associated metadata are loaded by the first node from a network device or a remote server.

[0854] Optionally, the UE function 1203 is an MnS producer that provides data to the CN domain MnF (Management Function) and / or the RAN domain MnF and / or the cross-domain management system 1201 for management or analysis (as shown by the double arrow 1202).

[0855] Optionally, the UE function 1203 is an MnS consumer that loads data from the CN domain MnF and / or RAN domain MnF and / or cross-domain management system 1201 for AI / ML-related management, such as managing data requests, ML model activation, and / or ML training (as shown by double arrow 1202).

[0856] As an example, the first measurement result in this application is generated based on inference, and the first measurement result is obtained through inference by the AI / ML inference function 1205.

[0857] As an example, the first measurement result in this application is not generated based on inference, and the first measurement result has not been inferred by the AI / ML inference function 1205.

[0858] As an example, the ML model is based on NN (Neural Networks).

[0859] As an example, the ML model is based on ANN (Artificial Neural Networks).

[0860] As an example, the ML model is based on CNN (Convolutional Neural Networks).

[0861] As an example, the ML model is based on the LLM (Large Language Model) architecture.

[0862] As an example, the ML model is based on the Transformer architecture.

[0863] As an example, the ML model is based on the GPT (Generative Pre-Trained) architecture.

[0864] As an example, the ML model is based on LSTM (Long Short-Term Memory network).

[0865] As an example, the ML model is based on MLP (MultiLayer Perceptron).

[0866] As an example, the ML model is based on GAN (Generative Adversarial Nets).

[0867] As an example, the ML model is based on a lightweight neural network.

[0868] As a sub-example of this embodiment, the lightweight neural network includes one or more of MobileNet, ShuffleNet, and SqueezeNet.

[0869] Example 13

[0870] Example 13 illustrates a schematic diagram of a processing system based on artificial intelligence or machine learning according to an embodiment of this application, as shown in Figure 13. In Figure 13, the processing system based on artificial intelligence or machine learning includes a first processor, a second processor, a third processor, and a fourth processor.

[0871] In Example 13, the first processor sends a first dataset to the second processor and a second dataset to the third processor; the second processor generates a target first-class parameter set based on the first dataset, and sends the generated target first-class parameter set to the third processor; the third processor processes the second dataset using the target first-class parameter set to obtain a first-class output, optionally sending the first-class output to the fourth processor. In Figure 13, the first-class feedback and the second-class feedback are optional; the second processor includes ML training functionality; the third processor includes ML inference functionality.

[0872] As one embodiment, the fourth processor includes ML testing functionality.

[0873] As one embodiment, the fourth processor includes performance monitoring / evaluation of the ML model.

[0874] As an example, the third processor sends a first type of feedback to the second processor; the first type of feedback is used to trigger the recalculation or update of the target first type of parameter set, that is, to trigger ML initial training or ML retraining.

[0875] As one embodiment, the fourth processor sends a second type of feedback to the first processor; the second type of feedback is used to generate the first dataset or the second dataset, or the second type of feedback is used to trigger the sending of the first dataset or the sending of the second dataset.

[0876] As one embodiment, the third processor belongs to the first node, and the fourth processor belongs to the second node.

[0877] As an example, the third processor belongs to the first node.

[0878] As an example, the first dataset includes training data.

[0879] As one embodiment, the second processor is used to train an ML model, and the trained model is described by the target first class of parameter sets.

[0880] As an example, the second processor belongs to the first node; the above method avoids passing the first dataset to the second node.

[0881] As an example, the second processor belongs to the second node in this application; the above method supports joint training and optimizes system performance.

[0882] As an example, the second processor belongs to the core network; the above method supports network-wide joint training, further optimizing system performance.

[0883] As an example, the second dataset includes inference data.

[0884] As an example, the third processor constructs a model based on the target first type of parameter group, and then inputs the second dataset into the constructed model to obtain the first type of output.

[0885] As one embodiment, the output of the third processor includes the first measurement result.

[0886] As one embodiment, the output of the third processor includes the performance parameters described in this application.

[0887] As an example, the third processor generates a recovery dataset based on the first type of output, and the error between the recovery dataset and the second dataset is used to generate the first type of feedback.

[0888] As an example, the first type of feedback is used to reflect the performance of the trained model; when the performance of the trained model fails to meet the requirements, the second processing opportunity will recalculate the target first type of parameter set.

[0889] As an example, when the error is too large or the update has not been performed for too long, the performance of the trained model is considered to be unsatisfactory.

[0890] As an example, the target first type of parameter group includes one or more of the following: convolution kernel, pooling kernel, pooling function, activation function, parameters of the pooling function, or parameters of the activation function.

[0891] As an example, the target first type of parameter group includes one or more of the following: convolution kernel size, number of convolution layers, convolution stride, pooling kernel size, pooling kernel stride, pooling function, activation function, or number of feature maps.

[0892] Example 14

[0893] Example 14 illustrates a schematic diagram based on artificial intelligence or machine learning according to an embodiment of this application, as shown in Figure 14. In Figure 14, the first and second operations belong to a first stage, the third operation belongs to a second stage, the fourth operation belongs to a third stage, and the fifth operation belongs to a fourth stage; the arrowed lines indicate the sequence of processes.

[0894] As an example, the first operation includes AI / ML training, the second operation includes AI / ML testing, the third operation includes AI / ML emulation, the fourth operation includes AI / ML entity loading, and the fifth operation includes AI / ML inference.

[0895] As an example, the first stage includes a training phase, the second stage includes an emulation phase, the third stage includes a deployment phase, and the fourth stage includes an inference phase.

[0896] As an example, the first stage includes AI / ML model training.

[0897] As an example, the first stage includes AI / ML model training and AI / ML testing.

[0898] As an example, the AI / ML model training includes initial training and re-training of one or a group of AI / ML entities.

[0899] As an example, the training of the AI / ML model depends on training data.

[0900] As an example, the AI / ML model training includes AI / ML entity validation.

[0901] As an example, the AI / ML entity verification is used to evaluate the performance of the AI / ML entity.

[0902] As an example, the AI / ML entity verification relies on verification data.

[0903] As an example, if the AI / ML entity verification results do not meet expectations, the AI / ML model will be retrained.

[0904] As an example, the AI / ML testing includes testing the validated AI / ML entities to estimate the performance of the trained AI / ML model.

[0905] As an example, if the AI / ML test results meet expectations, the AI / ML entity proceeds to the next stage; otherwise, the AI / ML model will be retrained.

[0906] As an example, the AI / ML test relies on test data.

[0907] As one embodiment, the second stage includes AI / ML simulation, which performs AI / ML entity reasoning in a simulation environment.

[0908] As an example, the AI / ML simulation estimates the performance of AI / ML entity reasoning in a simulation environment before using AI / ML entities.

[0909] As one embodiment, the second stage is optional.

[0910] As an example, the third stage includes AI / ML entity loading, which is to obtain trained AI / ML entities to obtain the desired AI / ML inference function.

[0911] As an example, the third stage is optional.

[0912] As an example, the third stage is no longer needed when the training and inference functions are co-located.

[0913] As an example, the fourth stage includes AI / ML inference.

[0914] As an example, the first measurement result is generated based on the fourth stage.

[0915] Example 15

[0916] Example 15 illustrates a structural block diagram of a processing apparatus for a first node according to an embodiment of the present application, as shown in Figure 15. In Figure 15, the processing apparatus 1500 in the first node includes a first receiver 1501 and a first processor 1502.

[0917] In embodiment 15, the first receiver 1501 receives the first reporting configuration, and the first processor 1502 determines whether to generate and send the first measurement result.

[0918] In Example 15, the first reporting configuration is used to configure the reporting of the first measurement result. The generation of the first measurement result occupies at least one processing resource. The at least one processing resource occupied by the generation of the first measurement result belongs to one of a first resource group or a second resource group. The first resource group includes one or more processing resources in the first node, and the second resource group includes one or more processing resources in the first node. The first resource group is used for the generation of measurement results for a first type of measurement, and the second resource group is used for the generation of measurement results for a second type of measurement. Both the measurement results for the first type of measurement and the measurement results for the second type of measurement are generated based on inference. The first type of measurement and the second type of measurement are different. When one of the first resource group and the second resource group is fully occupied and the other is not fully occupied, whether the first measurement result is generated and sent depends on at least the former of the following two:

[0919] -Which of the first and second resource groups is the resource group that is not fully occupied?

[0920] -Is the measurement corresponding to the first measurement result the first type of measurement or the second type of measurement?

[0921] As an example, when the first resource group is fully occupied and the second resource group is not fully occupied, and the amount of processing resources occupied by the generation of the first measurement result is not greater than the amount of unoccupied processing resources in the second resource group, the first measurement result is generated and sent regardless of whether the measurement corresponding to the first measurement result is the first type of measurement or the second type of measurement.

[0922] As an example, when the second resource group in the first resource group and the second resource group are fully occupied and the first resource group is not fully occupied, and the amount of processing resources occupied by the generation of the first measurement result is not greater than the amount of unoccupied processing resources in the first resource group; when the measurement corresponding to the first measurement result is the first type of measurement, the first measurement result is generated and sent; when the measurement corresponding to the first measurement result is the second type of measurement, the first measurement result is not generated and is not sent.

[0923] As one embodiment, the first type of measurement includes measurements for layer 1, and the second type of measurement includes measurements for layer 3.

[0924] As one embodiment, the first type of measurement includes measurements for CSI, and the second type of measurement includes measurements for positioning.

[0925] As one embodiment, the processing resources include at least the former of storage resources or computing resources.

[0926] As one embodiment, the first receiver 1501 receives a first information block; the maximum computing power that the first node can support is equal to a first integer; the first information block indicates a first ratio value, and the product of the first integer and the first ratio value, when rounded down, equals a second integer; the number of processing resources included in the second resource group is equal to the second integer, and the number of processing resources included in the first resource group is equal to the difference between the first integer and the second integer; or, the number of processing resources included in the first resource group is equal to the second integer, and the number of processing resources included in the second resource group is equal to the difference between the first integer and the second integer.

[0927] As one embodiment, the first processor 1502 sends a second information block; the second information block is used to trigger the reconfiguration of the first ratio value.

[0928] As an example, the first receiver 1501 receives M configuration messages, each of which indicates M RS resource groups, and any one of the M RS resource groups includes one or more RS resources, where M is a positive integer greater than 1; the first processor 1502 calculates performance parameters for each of the M configuration messages; the calculation of the performance parameters depends on the measurement of the RS resource group indicated by the corresponding configuration message; the second information block depends on the performance parameters.

[0929] As a sub-example of this embodiment, the first processor 1502 receives RSs from the M RS resource groups.

[0930] As an example, the first processor 1502 receives RS for generating the first measurement result.

[0931] As an example, the first processor 1502 measures the RS that generates the first measurement result.

[0932] As an example, the first processor 1502 determines to generate and send the first measurement result.

[0933] As an example, the first processor 1502 sends the first measurement result.

[0934] As an example, the first processor 1502 receives and measures the RS resources in the RS resource set indicated by the first reporting configuration, and infers and generates and sends the first measurement result based on the measurement result.

[0935] As an example, the first processor 1502 generates and sends the first measurement result.

[0936] As an example, the first processor 1502 does not update the first measurement result.

[0937] As an example, the first node 1500 is a user equipment.

[0938] As an example, the first node 1500 is a terminal.

[0939] As an example, the first node 1500 is a relay node device.

[0940] As an example, the first receiver 1501 includes at least one of the following in embodiment 4: the antenna 452, the receiver 454, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467.

[0941] As an example, the first processor 1502 includes at least one of the following in embodiment 4: the antenna 452, the receiver 454, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467.

[0942] As an example, the first processor 1502 includes at least one of the following in embodiment 4: the antenna 452, the transmitter 454, the transmitter processor 468, the multi-antenna transmitter processor 457, the controller / processor 459, the memory 460, and the data source 467.

[0943] Example 16

[0944] Example 16 illustrates a structural block diagram of a processing apparatus for a second node according to an embodiment of this application, as shown in Figure 16. In Figure 16, the processing apparatus 1600 in the second node includes a first transmitter 1601 and a second receiver 1602, wherein the second receiver 1602 is optional.

[0945] In embodiment 16, the first transmitter 1601 sends a first reporting configuration.

[0946] In Example 16, the receiver of the first reporting configuration includes a first node; the first reporting configuration is used to configure the reporting of a first measurement result, the generation of the first measurement result occupies at least one processing resource, the at least one processing resource occupied by the generation of the first measurement result belongs to one of a first resource group or a second resource group, the first resource group includes one or more processing resources in the first node, the second resource group includes one or more processing resources in the first node; the first resource group is used for the generation of measurement results for a first type of measurement, the second resource group is used for the generation of measurement results for a second type of measurement; the measurement results of the first type of measurement and the measurement results of the second type of measurement are both generated based on inference; the first type of measurement and the second type of measurement are different; when one of the first resource group and the second resource group is fully occupied and the other is not fully occupied, whether the first measurement result is generated and sent depends on at least the former of the following two:

[0947] -Which of the first and second resource groups is the resource group that is not fully occupied?

[0948] -Is the measurement corresponding to the first measurement result the first type of measurement or the second type of measurement?

[0949] As an example, the second receiver 1602 receives the first measurement result.

[0950] As an example, when the first resource group is fully occupied and the second resource group is not fully occupied, and the amount of processing resources occupied by the generation of the first measurement result is not greater than the amount of unoccupied processing resources in the second resource group, the first measurement result is generated and sent regardless of whether the measurement corresponding to the first measurement result is the first type of measurement or the second type of measurement.

[0951] As an example, when the second resource group in the first resource group and the second resource group are fully occupied and the first resource group is not fully occupied, and the amount of processing resources occupied by the generation of the first measurement result is not greater than the amount of unoccupied processing resources in the first resource group; when the measurement corresponding to the first measurement result is the first type of measurement, the first measurement result is generated and sent; when the measurement corresponding to the first measurement result is the second type of measurement, the first measurement result is not generated and is not sent.

[0952] As one embodiment, the first type of measurement includes measurements for layer 1, and the second type of measurement includes measurements for layer 3.

[0953] As one embodiment, the first type of measurement includes measurements for CSI, and the second type of measurement includes measurements for positioning.

[0954] As one embodiment, the processing resources include at least the former of storage resources or computing resources.

[0955] As one embodiment, the first transmitter 1601 transmits a first information block; the maximum computing power that the first node can support is equal to a first integer; the first information block indicates a first ratio value, and the product of the first integer and the first ratio value, when rounded down, equals a second integer; the number of processing resources included in the second resource group is equal to the second integer, and the number of processing resources included in the first resource group is equal to the difference between the first integer and the second integer; or, the number of processing resources included in the first resource group is equal to the second integer, and the number of processing resources included in the second resource group is equal to the difference between the first integer and the second integer.

[0956] As one embodiment, the second receiver 1602 receives a second information block; the second information block is used to trigger the reconfiguration of the first ratio value.

[0957] As an example, the first transmitter 1601 sends M configuration messages, each of which indicates M RS resource groups. Each of the M RS resource groups includes one or more RS resources, and M is a positive integer greater than 1. The first node calculates performance parameters for each of the M configuration messages. The calculation of the performance parameters depends on the measurement of the RS resource group indicated by the corresponding configuration message. The second information block depends on the performance parameters.

[0958] As an example, the first transmitter 1601 sends the RS resource or RS resource set associated with the first reporting configuration.

[0959] As an example, the first transmitter 1601 transmits the M RS resource groups indicated by the M configuration messages.

[0960] As one embodiment, the first reporting configuration indicates a first resource set and a second resource set, and the first transmitter 1601 transmits the first resource set.

[0961] As one embodiment, the first reporting configuration indicates a first resource set, and the first transmitter 1601 transmits the first resource set.

[0962] As one example, the second node 1600 is a base station device.

[0963] As one example, the second node 1600 is a user equipment.

[0964] As an example, the second node 1600 is a TRP.

[0965] As an example, the first transmitter 1601 includes at least one of the following in embodiment 4: the antenna 420, the transmitter 418, the transmission processor 416, the multi-antenna transmission processor 471, the controller / processor 475, and the memory 476.

[0966] As one embodiment, the second receiver 1602 includes at least one of the following in embodiment 4: the antenna 420, the receiver 418, the receiver processor 470, the multi-antenna receiver processor 472, the controller / processor 475, and the memory 476.

[0967] Those skilled in the art will understand that all or part of the steps in the above methods can be implemented by a program instructing related hardware, and the program can be stored in a computer-readable storage medium, such as a read-only memory, hard disk, or optical disk. Optionally, all or part of the steps in the above embodiments can also be implemented using one or more integrated circuits. Correspondingly, each module unit in the above embodiments can be implemented in hardware or in the form of software functional modules. This application is not limited to any specific combination of software and hardware. The user equipment, terminal, and UE in this application include, but are not limited to, drones, communication modules on drones, remote-controlled aircraft, aircraft, small aircraft, mobile phones, tablets, laptops, vehicle-mounted communication equipment, vehicles, RSUs, wireless sensors, internet cards, IoT terminals, RFID (Radio Frequency Identification) terminals, NB-IoT (Narrow Band Internet of Things) terminals, MTC (Machine Type Communication) terminals, eMTC (enhanced MTC) terminals, data cards, internet cards, vehicle-mounted communication equipment, low-cost mobile phones, low-cost tablets, and other wireless communication devices. The base station or system equipment in this application includes, but is not limited to, macrocell base stations, microcell base stations, small cell base stations, home base stations, relay base stations, eNB (evolved Node B), gNB, TRP, GNSS (Global Navigation Satellite System), relay satellites, satellite base stations, airborne base stations, RSUs, unmanned aerial vehicles, and test equipment, such as transceivers or signaling testers that simulate some functions of a base station, and other wireless communication equipment.

[0968] Those skilled in the art will understand that the present invention can be practiced in other specified forms without departing from its core or essential characteristics. Therefore, the embodiments disclosed herein should in any way be considered descriptive rather than restrictive. The scope of the invention is defined by the appended claims rather than the foregoing description, and all modifications within their equivalent meaning and scope are considered to be included therein.

Claims

1. A method in a terminal for wireless communication with artificial intelligence, characterized by, include: Receive the first reported configuration; Determine whether to generate and send the first measurement result; Wherein, the first reporting configuration is used to configure the reporting of the first measurement result; the generation of the first measurement result occupies at least one processing resource; the at least one processing resource occupied by the generation of the first measurement result belongs to one of a first resource group or a second resource group; the first resource group includes one or more processing resources in the terminal; the second resource group includes one or more processing resources in the terminal; the first resource group is used for the generation of measurement results for a first type of measurement; the second resource group is used for the generation of measurement results for a second type of measurement; both the measurement results for the first type of measurement and the measurement results for the second type of measurement are generated based on inference; the first type of measurement and the second type of measurement are different; when one of the first resource group and the second resource group is fully occupied and the other is not fully occupied, whether the first measurement result is generated and sent depends on at least the former of the following two: -Which of the first and second resource groups is the resource group that is not fully occupied? -Is the measurement corresponding to the first measurement result the first type of measurement or the second type of measurement? 2. A method in a terminal according to claim 1, characterized by, When the first resource group is fully occupied and the second resource group is not fully occupied, and the amount of processing resources occupied by the generation of the first measurement result is not greater than the amount of unoccupied processing resources in the second resource group, the first measurement result is generated and sent regardless of whether the measurement corresponding to the first measurement result is the first type of measurement or the second type of measurement.

3. The method in a terminal according to claim 1, characterized by, When the second resource group in the first resource group and the second resource group are fully occupied and the first resource group is not fully occupied, and the amount of processing resources occupied by the generation of the first measurement result is not greater than the amount of unoccupied processing resources in the first resource group; when the measurement corresponding to the first measurement result is the first type of measurement, the first measurement result is generated and sent; when the measurement corresponding to the first measurement result is the second type of measurement, the first measurement result is not generated and is not sent.

4. A method in a terminal according to any of claims 1 to 3, characterized by, The first type of measurement includes measurements for layer 1, and the second type of measurement includes measurements for layer 3.

5. A method in a terminal according to any of claims 1 to 3, characterized by, The first type of measurement includes measurements for CSI, and the second type of measurement includes measurements for positioning.

6. A method in a terminal according to any of claims 1 to 5, characterized by, The processing resources include at least the former of storage resources or computing resources.

7. A method in a terminal according to any of claims 1 to 6, characterized by, include: Receive the first information block; Wherein, the maximum computing power that the terminal can support is equal to the first integer; The first information block indicates a first ratio value, and the product of the first integer and the first ratio value, when rounded down, equals a second integer; the number of processing resources included in the second resource group is equal to the second integer, and the number of processing resources included in the first resource group is equal to the difference between the first integer and the second integer; or, the number of processing resources included in the first resource group is equal to the second integer, and the number of processing resources included in the second resource group is equal to the difference between the first integer and the second integer.

8. A method in a terminal according to claim 7, characterized by, include: Send the second information block; The second information block is used to trigger the reconfiguration of the first ratio value.

9. A method in a terminal according to claim 8, characterized by, include: Receive M configuration messages, each of which indicates one or more RS resource groups. Each of the M RS resource groups includes one or more RS resources, and M is a positive integer greater than 1. For each of the M configuration messages, calculate the performance parameters; The calculation of the performance parameters depends on the measurement of the RS resource group indicated by the corresponding configuration message; the second information block depends on the performance parameters.

10. A terminal, characterized in that, The terminal includes: one or more processors and memory; The memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the terminal to perform the method as described in any one of claims 1-9.

11. A method in a base station for wireless communication with artificial intelligence, characterized by, include: Send the first reporting configuration; Wherein, the recipient of the first reporting configuration includes a terminal; the first reporting configuration is used to configure the reporting of a first measurement result, the generation of the first measurement result occupies at least one processing resource, the at least one processing resource occupied by the generation of the first measurement result belongs to one of a first resource group or a second resource group, the first resource group includes one or more processing resources in the terminal, the second resource group includes one or more processing resources in the terminal; the first resource group is used for the generation of measurement results for a first type of measurement, the second resource group is used for the generation of measurement results for a second type of measurement; the measurement results of the first type of measurement and the measurement results of the second type of measurement are both generated based on inference; the first type of measurement and the second type of measurement are different; when one of the first resource group and the second resource group is fully occupied and the other is not fully occupied, whether the first measurement result is generated and sent depends on at least the former of the following two: -Which of the first and second resource groups is the resource group that is not fully occupied? -Is the measurement corresponding to the first measurement result the first type of measurement or the second type of measurement? 12. A method in a base station according to claim 11, characterized by When the first resource group is fully occupied and the second resource group is not fully occupied, and the amount of processing resources occupied by the generation of the first measurement result is not greater than the amount of unoccupied processing resources in the second resource group, the first measurement result is generated and sent by the terminal regardless of whether the measurement corresponding to the first measurement result is the first type of measurement or the second type of measurement.

13. A method in a base station according to claim 11, characterized by When the second resource group in the first resource group and the second resource group are fully occupied and the first resource group is not fully occupied, and the amount of processing resources occupied by the generation of the first measurement result is not greater than the amount of unoccupied processing resources in the first resource group; when the measurement corresponding to the first measurement result is the first type of measurement, the first measurement result is generated and sent by the terminal; when the measurement corresponding to the first measurement result is the second type of measurement, the first measurement result is not generated and not sent by the terminal.

14. A method in a base station according to any of claims 11 to 13, characterized by The first type of measurement includes measurements for layer 1, and the second type of measurement includes measurements for layer 3.

15. A method in a base station according to any of claims 11 to 13, characterized by, The first type of measurement includes measurements for CSI, and the second type of measurement includes measurements for positioning.

16. A method in a base station according to any of claims 11 to 15, characterized by The processing resources include at least the former of storage resources or computing resources.

17. A method in a base station according to any of claims 11 to 16, characterized by include: Send the first information block; Wherein, the maximum computing power that the terminal can support is equal to the first integer; The first information block indicates a first ratio value, and the product of the first integer and the first ratio value, when rounded down, equals a second integer; the number of processing resources included in the second resource group is equal to the second integer, and the number of processing resources included in the first resource group is equal to the difference between the first integer and the second integer; or, the number of processing resources included in the first resource group is equal to the second integer, and the number of processing resources included in the second resource group is equal to the difference between the first integer and the second integer.

18. A method in a base station according to claim 17, characterized by include: Receive the second information block; The second information block is used to trigger the reconfiguration of the first ratio value.

19. A method in a base station according to claim 18, characterized by include: Send M configuration messages, each of which indicates one or more RS resource groups. Each of the M RS resource groups includes one or more RS resources, and M is a positive integer greater than 1. Specifically, the terminal calculates performance parameters for each of the M configuration messages; the calculation of the performance parameters depends on the measurement of the RS resource group indicated by the corresponding configuration message; the second information block depends on the performance parameters.

20. 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, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the base station to perform the method as described in any one of claims 11-19.

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