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

By configuring processing resources in the terminal device, the resource requirements of traditional CSI generation are ensured, the CPU usage conflict caused by the introduction of AI/ML models is resolved, the system's adaptability and intelligence level are improved, and the performance and resource utilization efficiency of CSI generation are guaranteed.

WO2026091744A1PCT designated stage Publication Date: 2026-05-07HONOR DEVICE CO LTD
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Patent Information

Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
HONOR DEVICE CO LTD
Filing Date
2025-08-06
Publication Date
2026-05-07

AI Technical Summary

Technical Problem

After introducing AI/ML models, conflicts arise in the CPU usage mechanism of terminal devices when generating CSI, leading to resource constraints and affecting the performance and system compatibility of traditional CSI generation.

Method used

By configuring processing resources, the resource requirements of traditional CSI generation are ensured, avoiding the complete consumption of all resources by inference-based CSI. A parameter reservation mechanism is adopted to guarantee the priority of traditional CSI generation, and information blocks are flexibly configured to adapt to different scenarios. AI/ML model performance is monitored to adjust resource usage.

Benefits of technology

It achieves deep integration of AI and communication, improves system adaptability and intelligence, ensures the performance of traditional CSI generation, reduces resource waste, and improves CPU utilization efficiency and system compatibility.

✦ Generated by Eureka AI based on patent content.

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Abstract

Disclosed in the present application are a method and apparatus used in a node for wireless communication and artificial intelligence. The method comprises: a node receiving a first report configuration, and only when a first value is not greater than the number of remaining processing resources of a first node, generating a first channel information block and sending same, wherein the first report configuration is used for configuring the report of the first channel information block, and the number of processing resources occupied for generating the first channel information block is equal to the first value; the number of remaining processing resources of the first node is equal to the result of subtracting a second value from the total number of processing resources comprised in the first node, and the second value depends on the number of processing resources of the first node that have been occupied; and whether the second value is equal to the number of processing resources of the first node that have been occupied depends on whether the first channel information block is generated on the basis of inference. The present application optimizes the usage criteria for processing resources of a node, so as to improve the overall performance.
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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. 202411569821.7, filed on November 4, 2024, entitled "A Method and Apparatus Used 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] Leveraging AI / ML (Artificial Intelligence / Machine Learning) technologies to enhance 5G network performance is a crucial component of achieving deep integration of 5G and AI / ML and building intelligent dimensions for 5G-Advanced (5.5G) networks. The 3GPP (3rd Generation Partnership Project) standards organization initiated research on standards for RAN (Radio Access Networks) intelligence starting with Rel-16 (Release-16), primarily focusing on intelligent use cases, enhanced data collection, and the potential impact on RAN nodes and interfaces. Rel-18 formally established a project for AI / ML-based 5G air interface enhancement, initiating international standardization work on the integration of 5G air interface and AI / ML, mainly focusing on research into use cases, lifecycle management (LCM), simulation verification, and data collection.

[0004] Currently, the development of AI / ML has entered the stage of large-scale models. Large-scale communication models can realize autonomous networks and intelligent services, support network operation optimization, and improve network efficiency. The deep integration of communication and AI is an important direction for the future evolution of communication. AI will empower the development and upgrading of 5G, 5.5G to 6G, bringing new management models such as automated management of frequency bands and traffic, real-time analysis of user data and network load, and prediction of network status. Summary of the Invention

[0005] In the current standard, the concept of CPU 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 two CSI generation methods at the same time, namely CSI generation based on traditional measurement and CSI generation based on UE-side AI / ML model, the CPU occupancy mechanism is an urgent problem to be solved.

[0006] 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.

[0007] 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.

[0008] As an example, the interpretation of terms in this application is based on the definitions in the 3GPP specification protocol TS38 series.

[0009] As an example, the interpretation of terms in this application is based on the definitions in the 3GPP specification protocol TS37 series.

[0010] As an example, the interpretation of the terms used in this application is based on the definitions in 3GPP specification protocol Rel-17.

[0011] As an example, the interpretation of the terms used in this application is based on the definitions in 3GPP specification protocol Rel-18.

[0012] This application discloses a method for a first node in wireless communication and artificial intelligence, comprising:

[0013] Receive the first reported configuration;

[0014] The first channel information block is generated and sent only when the first value is not greater than the amount of remaining processing resources of the first node;

[0015] Wherein, the first reporting configuration is used to configure the reporting of the first channel information block, the amount of processing resources occupied by the generation of the first channel information block is equal to the first value; the amount of the remaining processing resources of the first node is equal to the total amount of processing resources included in the first node minus a second value, the second value depends on the amount of processing resources already occupied by the first node; whether the second value is equal to the amount of processing resources already occupied by the first node depends on whether the first channel information block is generated based on inference.

[0016] As an example, the problem this application aims to solve includes: how to configure processing resources when the processing resources of the first node are directly shared between traditional CSI generation and inference-based CSI generation.

[0017] As an example, the features of the above method include: when processing resources are shared, by configuring the second value, a portion of the resources are reserved for traditional CSI generation, so as to ensure that the processing resources are not completely occupied by prediction-based CSI generation.

[0018] As an example, the features of the above method include: ensuring the processing resources required for traditional CSI generation, thereby ensuring backward compatibility of the first node.

[0019] As an example, the characteristics of the above method include: making the most of existing CPU processing methods to simplify the design of the terminal.

[0020] 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.

[0021] According to one aspect of this application, the above method is characterized in that, when the first channel information is generated based on inference, the second value is equal to the number of processing resources already occupied by the first node plus the first parameter; when the first channel information is not generated based on inference, the second value is equal to the number of processing resources already occupied by the first node.

[0022] As an example, the features of the above method include: the first parameter is used to configure the processing resources reserved for traditional CSI generation, thereby ensuring the basic performance of traditional CSI generation.

[0023] As an example, the characteristics of the above method include: traditional CSI generation can completely occupy all processing resources, while inference-based CSI generation cannot completely occupy all processing resources. That is, when processing resources are relatively scarce, the priority of traditional CSI generation is increased to ensure performance.

[0024] According to one aspect of this application, the above method is characterized in that the first parameter is the amount of reserved processing resources, which are used for the generation of channel information not based on inference.

[0025] According to one aspect of this application, the above method is characterized by comprising:

[0026] Send the first information block;

[0027] The first information block is used to indicate the first parameter.

[0028] As an example, the features of the above method include: flexibly configuring the first parameter through the first information block to adapt to different scenarios and improve the applicability of the solution in this application.

[0029] According to one aspect of this application, the above method is characterized by comprising:

[0030] Send the second information block;

[0031] The second information block is used to trigger the reconfiguration of the first parameter.

[0032] As an example, the features of the above method include: the second information block is a report from the first node on the performance monitoring of the AI / ML model, thereby enabling flexible adjustment of the first parameter to fully utilize the processing resources of the first node while ensuring performance.

[0033] According to one aspect of this application, the above method is characterized by comprising:

[0034] Receive M configuration messages, each of which indicates one or more RS (Reference Signal) resource groups. Each of the M RS resource groups includes one or more RS resources, and M is a positive integer greater than 1.

[0035] For each of the M configuration messages, calculate the performance parameters;

[0036] 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.

[0037] As an example, the features of the above method include: the first node monitors the performance of the AI / ML model through the M configuration messages and the corresponding M RS resource groups, and then reports the second information block.

[0038] According to one aspect of this application, the above method is characterized in that the first value depends on whether the first channel information block is generated based on inference, and the priority associated with the first channel information block does not depend on whether the first channel information block is generated based on inference.

[0039] As an example, the features of the above method include: when the generation method of the first channel information block adopts inference, it should occupy more processing resources, and thus allocate more processing resources.

[0040] As an example, the features of the above method include: the generation method of the first channel information block should not affect the priority. Thus, after ensuring the processing resources reserved for traditional CSI generation, the priority of the CSI process generated based on inference and the priority of the traditional CSI process are only distinguished in a way similar to the existing process type, and are not affected by the generation method.

[0041] According to one aspect of this application, the above method is characterized in that the first node is a user equipment.

[0042] According to one aspect of this application, the above method is characterized in that the first node is a terminal.

[0043] This application discloses a method for a second node in wireless communication and artificial intelligence, comprising:

[0044] Send the first reporting configuration;

[0045] Receive the first channel information block;

[0046] Wherein, the sender of the first reporting configuration includes a first node, which generates and sends the first channel information block only when the first value is not greater than the number of remaining processing resources of the first node; the first reporting configuration is used to configure the reporting of the first channel information block, and the number of processing resources occupied by the generation of the first channel information block is equal to the first value; the number of remaining processing resources of the first node is equal to the total number of processing resources included in the first node minus a second value, the second value depending on the number of processing resources already occupied by the first node; whether the second value is equal to the number of processing resources already occupied by the first node depends on whether the first channel information block is generated based on inference.

[0047] As one embodiment, receiving the first channel information block includes: detecting the first channel information block.

[0048] As one embodiment, receiving the first channel information block includes: monitoring the first channel information block.

[0049] As one embodiment, receiving the first channel information block includes: blind decoding the first channel information block.

[0050] As one embodiment, the second node knows whether the first channel information block has been sent before receiving the first channel information block.

[0051] As an example, the second node does not know whether the first channel information block has been sent before receiving the first channel information block.

[0052] As an example, the second node knows the time-frequency resources occupied by the first channel information block before receiving the first channel information block.

[0053] As an example, the features of the above method include: the second node is a network device, which includes at least one of a core network device and an access network device.

[0054] As an example, the features of the above method include: 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.

[0055] As an example, the features of the above method include: the second node is a base station.

[0056] As an example, the features of the above method include: the second node is an eNB.

[0057] As an example, the features of the above method include: the second node is a gNB.

[0058] As an example, the features of the above method include: the second node includes a base station.

[0059] As an example, the features of the above method include: the second node includes a core network.

[0060] As an example, the features of the above method include: the second node includes a base station and a core network.

[0061] As an example, the features of the above method include: the second node includes an entity for deploying AI / ML models.

[0062] As an example, the features of the above method include: the second node includes a node for deploying AI / ML models.

[0063] As an example, the features of the above method include: the base station in this application includes a core network.

[0064] As an example, the features of the above method include: the base station in this application includes core network equipment.

[0065] As an example, the features of the above method include: the base station in this application includes an entity for deploying AI / ML models.

[0066] As an example, the features of the above method include: the base station in this application includes nodes for deploying AI / ML models.

[0067] According to one aspect of this application, the above method is characterized in that, when the first channel information is generated based on inference, the second value is equal to the number of processing resources already occupied by the first node plus the first parameter; when the first channel information is not generated based on inference, the second value is equal to the number of processing resources already occupied by the first node.

[0068] According to one aspect of this application, the above method is characterized in that the first parameter is the amount of reserved processing resources, which are used for the generation of channel information not based on inference.

[0069] According to one aspect of this application, the above method is characterized by comprising:

[0070] Send the first information block;

[0071] The first information block is used to indicate the first parameter.

[0072] According to one aspect of this application, the above method is characterized by comprising:

[0073] Receive the second information block;

[0074] The second information block is used to trigger the reconfiguration of the first parameter.

[0075] According to one aspect of this application, the above method is characterized by comprising:

[0076] 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.

[0077] The first node calculates a performance parameter for each of the M configuration messages; the calculation of the performance parameter depends on the measurement of the RS resource group indicated by the corresponding configuration message; the second information block depends on the performance parameter.

[0078] According to one aspect of this application, the above method is characterized in that the first value depends on whether the first channel information block is generated based on inference, and the priority associated with the first channel information block does not depend on whether the first channel information block is generated based on inference.

[0079] According to one aspect of this application, the above method is characterized in that the second node is a base station.

[0080] This application discloses a device for a first node in wireless communication and artificial intelligence, comprising:

[0081] The first receiver receives the first reported configuration;

[0082] The first processor generates and sends the first channel information block only when the first value is not greater than the amount of remaining processing resources of the first node;

[0083] Wherein, the first reporting configuration is used to configure the reporting of the first channel information block, the amount of processing resources occupied by the generation of the first channel information block is equal to the first value; the amount of the remaining processing resources of the first node is equal to the total amount of processing resources included in the first node minus a second value, the second value depends on the amount of processing resources already occupied by the first node; whether the second value is equal to the amount of processing resources already occupied by the first node depends on whether the first channel information block is generated based on inference.

[0084] This application discloses a device for a second node in wireless communication and artificial intelligence, comprising:

[0085] The first transmitter sends the first reported configuration;

[0086] The second receiver receives the first channel information block;

[0087] Wherein, the sender of the first reporting configuration includes a first node, which generates and sends the first channel information block only when the first value is not greater than the number of remaining processing resources of the first node; the first reporting configuration is used to configure the reporting of the first channel information block, and the number of processing resources occupied by the generation of the first channel information block is equal to the first value; the number of remaining processing resources of the first node is equal to the total number of processing resources included in the first node minus a second value, the second value depending on the number of processing resources already occupied by the first node; whether the second value is equal to the number of processing resources already occupied by the first node depends on whether the first channel information block is generated based on inference.

[0088] As an example, compared with conventional solutions, this application has the following advantages, but is not limited to:

[0089] 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.

[0090] Ensure the processing resources required for traditional CSI generation, and avoid exhausting the processing resources required for traditional CSI generation by introducing AI / ML algorithms;

[0091] To avoid wasting resources and improve the utilization efficiency of CSI processing units, thereby reducing the overall CPU load;

[0092] It reduces the requirements for the terminal and has good compatibility.

[0093] 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

[0094] 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:

[0095] Figure 1 illustrates a flowchart of the first node transmission according to an embodiment of this application;

[0096] Figure 2 shows a schematic diagram of a network architecture according to an embodiment of this application;

[0097] 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;

[0098] Figure 4 shows a schematic diagram of a first communication device and a second communication device according to an embodiment of this application;

[0099] Figure 5 shows a first flowchart of the transmission between a first node and a second node according to an embodiment of this application;

[0100] Figure 6 illustrates a second flowchart of the transmission between a first node and a second node according to an embodiment of this application;

[0101] Figure 7 illustrates a third flowchart of the transmission between a first node and a second node according to an embodiment of this application;

[0102] Figure 8 shows a fourth schematic diagram of transmission between a first node and a second node according to an embodiment of this application;

[0103] Figure 9 shows a schematic diagram of the already occupied processing resources of the first node according to an embodiment of this application;

[0104] Figure 10 shows a schematic diagram of the first parameter according to an embodiment of this application;

[0105] Figure 11 shows a schematic diagram of RAN domain AI / ML function deployment according to an embodiment of this application;

[0106] Figure 12 shows a schematic diagram of the deployment of AI / ML functions of a UE according to an embodiment of this application;

[0107] Figure 13 shows a schematic diagram of a processing system based on artificial intelligence or machine learning according to an embodiment of this application;

[0108] Figure 14 illustrates a schematic diagram of artificial intelligence or machine learning according to an embodiment of this application;

[0109] Figure 15 shows a structural block diagram of a processing apparatus for a first node according to an embodiment of this application;

[0110] 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

[0111] 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.

[0112] Example 1

[0113] 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.

[0114] In step 101, the first node receives the first reported configuration; in step 102, it determines that the first channel information block is generated and sent only if the first value is not greater than the amount of the remaining processing resources of the first node.

[0115] In Embodiment 1, the first reporting configuration is used to configure the reporting of the first channel information block, and the amount of processing resources occupied by the generation of the first channel information block is equal to the first value; the amount of the remaining processing resources of the first node is equal to the total amount of processing resources included in the first node minus a second value, the second value depending on the amount of processing resources already occupied by the first node; whether the second value is equal to the amount of processing resources already occupied by the first node depends on whether the first channel information block is generated based on inference.

[0116] As one example, the first node is a user equipment (UE).

[0117] As one example, the first node is a terminal.

[0118] As an example, the first node is the first node in this application.

[0119] As one embodiment, generating and transmitting the first channel information block includes: receiving an RS used to generate the first channel information block.

[0120] As one embodiment, generating and sending the first channel information block includes: receiving an RS used to generate the first channel information block in the corresponding RS resource.

[0121] As one example, the first node is a user equipment (UE).

[0122] As one example, the first node is a terminal.

[0123] As an example, the first node is the first node in this application.

[0124] As an example, the first reported configuration is carried by higher layer signaling.

[0125] As an example, the first reported configuration is carried by RRC (Radio Resource Control) signaling.

[0126] As an example, the first reporting configuration includes some or all of the fields in one or more RRC IEs (Information Elements).

[0127] As one embodiment, the first reporting configuration includes some or all of the domains of each of the multiple RRC IEs.

[0128] As one example, the first reporting configuration includes some or all of the domains in an IE CSI-ReportConfig.

[0129] As one example, the first reported configuration includes some or all of the domains in IE ServingCellConfig.

[0130] As one example, the first reporting configuration includes some or all of the domains in IE CSI-MeasConfig.

[0131] As one example, the first reported configuration includes some or all of the domains in IE ServingCellConfigCommon.

[0132] As one example, the first reported configuration includes some or all of the domains in IE ServingCellConfig.

[0133] As an example, the name of the RRC signaling carrying the first reporting configuration includes: CSI.

[0134] As an example, the name of the RRC signaling carrying the first reporting configuration includes: Report.

[0135] As an example, the name of the RRC signaling carrying the first reported configuration includes: Config.

[0136] As an example, the name of the RRC signaling carrying the first reporting configuration includes: Meas.

[0137] As an example, the name of the RRC signaling carrying the first reporting configuration includes: CSI-Report.

[0138] 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 resources, and the first resource set is used for at least one of channel measurement or interference measurement of the first channel information block.

[0139] 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.

[0140] 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 channel information block; the second resource set includes one or more resources.

[0141] As a sub-implementation of the above embodiments, the second resource set includes one or more RS resources.

[0142] As a sub-implementation of the above embodiments, the resources in the second resource set include at least one of antenna port, TCI (Transmission Configuration Indication) status, QCL (Quasi Co-Located) information, time-frequency resources, time-frequency code resources, beam, RS resources, vector, or matrix.

[0143] As a sub-implementation of this embodiment, the first resource set is used to infer and generate the first channel information block.

[0144] As a sub-example of this embodiment, the first node measures one or more RS resources included in the first resource set.

[0145] 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.

[0146] As a sub-implementation of this embodiment, the first channel information block is associated with the second resource set.

[0147] As a sub-implementation of this embodiment, the first channel information block indicates a beam index, which belongs to the second resource set; the beam index is one of CRI and SSBRI.

[0148] As a sub-implementation of this embodiment, the first resource set corresponds to a CSI-ResourceConfigId.

[0149] 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.

[0150] As a sub-implementation of this embodiment, the first resource set and the second resource set correspond to the same CSI-ResourceConfigId.

[0151] As a sub-implementation of this embodiment, the first resource set and the second resource set correspond to different CSI-ResourceConfigIds.

[0152] As an example, the reporting type in this application indicates at least one of periodic reporting, semi-persistent reporting, non-periodic reporting, or event-triggered reporting.

[0153] As an example, the reporting type in this application indicates at least one of periodic reporting, semi-persistent reporting, or non-periodic reporting.

[0154] As an example, the first channel information block includes CSI (channel state information).

[0155] As a sub-example of this embodiment, the CSI includes beam information.

[0156] As a sub-example of this embodiment, the CSI includes compressed CSI.

[0157] As a supplementary embodiment of this sub-example, the compressed CSI is based on non-codebook channel information.

[0158] 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.

[0159] As a supplementary embodiment of this sub-example, the compressed CSI is channel information based on artificial intelligence or machine learning.

[0160] As a supplementary embodiment of this sub-example, the compressed CSI is based on channel information from a neural network.

[0161] As a supplementary embodiment of this sub-example, the compressed CSI is based on channel information from CNN (Conventional Neural Networks).

[0162] As an example, the beam information in this application includes a resource indicator, which is used to indicate a beam or RS resource.

[0163] 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.

[0164] As one embodiment, the first channel information block includes a channel matrix.

[0165] As one embodiment, the first channel information block includes at least one of the channel's feature values ​​or feature vectors.

[0166] As one embodiment, the first channel information block includes one of beam information, predicted CSI, or compressed CSI.

[0167] As an example, the first channel information block includes at least one of the following: PMI (Precoding Matrix Indicator), CRI (CSI-RS Resource Indicator), CQI (Channel Quality Indicator), RI (Rank Indicator), Layer Indicator (LI), SS / PBCH Block Resource Indicator (SSBRI), RSRP, SINR (signal-to-noise and interference ratio), capability index, TDCP (Time domain channel properties), or confidence information.

[0168] As an example, the first channel information block includes at least one of resource indication, RSRP (reference signal received power), 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.

[0169] As one example, the first channel information block is based on a non-codebook.

[0170] As one embodiment, the first channel information block includes a resource indication, which is used to indicate beam or RS (reference signal) resources.

[0171] As an example, the first channel information block includes at least one of a resource indication or an RSRP (reference signal received power), wherein the resource indication is used to indicate a beam or RS resource.

[0172] As a sub-example of this embodiment, the beam information includes a resource indication, which is used to indicate a beam or RS resource.

[0173] As a sub-implementation of this embodiment, the beam information includes at least one of resource indication or RSRP (reference signal received power), wherein the resource indication is used to indicate the beam or RS resource.

[0174] As a sub-implementation of this embodiment, the resource indicator is a CRI (CSI-RS Resource Indicator, Channel State Information Reference Signal Resource Indicator) or an SS / PBCH Block Resource Indicator (SSBRI).

[0175] As a sub-example of this embodiment, the resource indication is used to indicate one of beam, CSI-RS (Channel State Information Reference Signal) resources, or synchronization signal resources.

[0176] As a supplementary embodiment of this sub-example, the synchronization signal resources include at least the resources occupied by the synchronization signal.

[0177] As an additional embodiment of this sub-example, the synchronization signal resource is an SSB (Synchronization Signal Block).

[0178] As an additional embodiment of this sub-example, the synchronization signal resource is an SS / PBCH (Synchronization Signal / Physical Broadcast Channel) block resource.

[0179] As an example, the first channel information block is not generated based on inference, and the first channel information block includes at least one of PMI, CQI, and RI.

[0180] As an example, the first channel information block is generated based on inference, and the first channel information block includes at least one of resource indication, RSRP, channel matrix, channel eigenvalue, or channel eigenvector; the resource indication is used to indicate beam or RS resources.

[0181] As an example, the first channel information block is not generated based on inference, and the first channel information block includes at least one of PMI, CQI, RI, CRI, SSBRI, RSRP, and SINR.

[0182] As an example, the first channel information block is generated based on inference, and the first channel information block includes at least one of resource indication, RSRP, channel matrix, channel eigenvalue, channel eigenvector, or compressed CSI; the resource indication is used to indicate beam or RS resources.

[0183] As one embodiment, the generation of the first channel information block includes: calculation or inference of the first channel information block.

[0184] As an example, the first channel information block is generated based on inference; the generation of the first channel information block includes: inference of the first channel information block.

[0185] As one embodiment, the first channel information block is generated based on inference; the generation of the first channel information block includes: inference to obtain the first channel information block.

[0186] As one embodiment, the first channel information block is generated based on inference; the generation of the first channel information block includes: the sender of the first channel information block performing a first operation, the first channel information block depending on the output of the first operation, the first operation including inference.

[0187] As an example, the first channel information block is generated based on inference, and the first channel information block is calculated or generated through artificial intelligence or machine learning.

[0188] As one embodiment, the first channel information block is generated based on inference, including the generation of the first channel information block being based on training.

[0189] As one embodiment, the first channel information block is generated based on inference, including the generation of the first channel information block using an AI / ML model.

[0190] As one embodiment, the first channel information block is generated based on inference, including: the generation of the first channel information block uses information generated based on artificial intelligence or machine learning.

[0191] As one embodiment, the first channel information block is generated based on inference, including: the generation of the first channel information block uses information generated based on a neural network.

[0192] As one embodiment, the first channel information block is generated based on inference and includes: the generation of the first channel information block uses information generated based on CNN (Conventional Neural Networks).

[0193] As one embodiment, the first channel information block is generated based on inference and includes: the first channel information block includes information generated based on artificial intelligence or machine learning.

[0194] As one embodiment, the first channel information block is generated based on inference and includes: the first channel information block includes information generated based on a neural network.

[0195] As one embodiment, the first channel information block is generated based on inference and includes: the first channel information block includes information generated based on CNN (Conventional Neural Networks).

[0196] As one embodiment, the first channel information block is generated based on inference and includes: the generation of the first channel information block corresponds to a first identifier.

[0197] As one embodiment, for the case where the first channel information block is generated based on inference, how the first channel information block is generated is determined by the manufacturer of the first node, or is implementation-related. A typical but non-limiting implementation is described below:

[0198] 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 channel information block.

[0199] If the first channel information block requires the first node to estimate interference (including noise), the first node can measure the RS resources used for interference measurement to obtain the measured interference.

[0200] In one implementation, measurement interference is also input into the AI ​​model.

[0201] 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 channel information block.

[0202] Without loss of generality, the AI ​​model or the parameters of the AI ​​model used to generate the first channel information block are determined by the manufacturer of the first node.

[0203] As an example, the first channel information block is not generated based on inference; the generation of the first channel information block includes: the first channel information block is generated in a non-AI manner.

[0204] As an example, the first channel information block is not generated based on inference; the generation of the first channel information block includes: the first channel information block is generated by a linear method.

[0205] As an example, the first channel information block is not generated based on inference; the generation of the first channel information block includes: the first channel information block is generated using the Rel-18 and earlier Release methods.

[0206] As one embodiment, the first channel information block not being generated based on inference includes: the generation of the first channel information block is not based on training.

[0207] As one embodiment, the first channel information block not being generated based on inference includes: the generation of the first channel information block does not use an AI model.

[0208] As one example, the first channel information block not being generated based on reasoning includes: the generation of the first channel information block does not use information generated based on artificial intelligence or machine learning.

[0209] As one embodiment, the first channel information block not being generated based on inference includes: the generation of the first channel information block does not use information generated based on a neural network.

[0210] As an example, the first channel information block not being generated based on inference includes: the generation of the first channel information block does not use information generated based on CNN (Conventional Neural Networks).

[0211] As an example, the first channel information block not being generated based on inference includes: the first channel information block does not include information generated based on artificial intelligence or machine learning.

[0212] As an example, the first channel information block is not generated based on inference, including: the first channel information block does not include information generated based on a neural network.

[0213] As an example, the first channel information block is not generated based on inference, including: the first channel information block does not include information generated based on CNN (Conventional Neural Networks).

[0214] As one embodiment, the first channel information block not being generated based on inference includes: the generation of the first channel information block does not correspond to the first type of identifier, and the first type of identifier is used for AI.

[0215] As an example, if the first channel information block is not generated based on inference, how to generate the first channel information block is determined by the manufacturer of the first node, or is implementation-related. A typical but non-limiting implementation is described below:

[0216] The first node performs measurements on the RS 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; for the channel parameter matrix H r×t Power adjustment is performed, and the adjusted channel parameter matrix is ​​as follows: Where P is the assumed ratio of PDSCH EPRE to CSI-RS EPRE; when using the precoding matrix W t×lUnder these conditions, the precoded channel parameter matrix is: Where l is the rank or the number of layers, in one case l is a positive integer no greater than t, in another case the precoding matrix is ​​an identity matrix, in which case t = l; the target information is generated using criteria such as maximum SINR (Signal Interference Noise Ratio), EESM (Exponential Effective SINR Mapping), or maximum channel capacity. Generally, the calculation of the first channel information block requires the first node to estimate interference (including noise). The first configuration information block also indicates RS resources used for interference measurement. The first node can measure one or more transmission times of the RS resources for interference measurement to obtain accurate interference measurement. Generally, the calculation of the target information depends on receiver performance or hardware-related factors such as modulation scheme.

[0217] As one embodiment, the first channel information block includes CSI.

[0218] As a sub-example of this embodiment, the CSI includes beam information.

[0219] As a sub-example of this embodiment, the CSI includes predicted CSI.

[0220] As a sub-example of this embodiment, the CSI includes compressed CSI.

[0221] As a supplementary embodiment of this sub-example, the compressed CSI is based on non-codebook channel information.

[0222] 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.

[0223] As a supplementary embodiment of this sub-example, the compressed CSI is based on AI / ML (Artificial Intelligence / Machine Learning) channel information.

[0224] As a supplementary embodiment of this sub-example, the compressed CSI is based on channel information from a neural network.

[0225] As a supplementary embodiment of this sub-example, the compressed CSI is based on channel information from CNN (Conventional Neural Networks).

[0226] As one embodiment, the processing resources are used for at least one of processing, computation, or inference.

[0227] As one example, the processing resources are used for at least addition and multiplication operations.

[0228] As one example, the processing resources are used for at least convolution operations.

[0229] As one example, the processing resources include the resources required for computation.

[0230] As one example, the processing resources include the resources required for storage.

[0231] As one example, the processing resources include the resources required for reading and writing.

[0232] As one example, the processing resources include the resources required for process control.

[0233] As one example, the processing resources include memory bandwidth.

[0234] As one example, the processing resources include cache resources.

[0235] As one example, the processing resources include bandwidth resources.

[0236] As one example, the processing resources include read and write resources.

[0237] As one example, the processing resources include cache resources.

[0238] As one example, the processing resources include register resources.

[0239] As one example, the processing resources include data interaction resources.

[0240] As an example, a processing resource is a processing unit.

[0241] As an example, a processing resource belongs to a processing unit.

[0242] As one example, the processing resources include computing resources.

[0243] As an example, the inference includes AI / ML inference.

[0244] As one example, the processing resources are used for storage.

[0245] As one example, the processing resources are used for reading and writing.

[0246] As one example, the processing resources are used for data interaction.

[0247] As an example, one of the processing resources is a process.

[0248] As an example, one of the processing resources is a storage unit.

[0249] As an example, one of the processing resources is a computing unit.

[0250] As an example, one of the processing resources is an Arithmetic and Logic Unit (ALU).

[0251] As an example, one of the processing resources is a Special Function Unit (SFU).

[0252] As an example, one of the processing resources corresponds to one NPU (Neural network Processing Unit).

[0253] As an example, one processing resource corresponds to one IPU (Inference Processing Unit).

[0254] As an example, one processing resource corresponds to one CPU.

[0255] As an example, one processing resource corresponds to one APU.

[0256] As an example, the CPU mentioned in this application refers to: Central Processing Unit.

[0257] As an example, the CPU mentioned in this application refers to: CSI Processing Unit, CSI processor.

[0258] As an example, the APU mentioned in this application refers to: Accelerated Processing Unit.

[0259] As an example, the APU mentioned in this application refers to: AI / ML Processing Unit, AI / ML processor.

[0260] As an example, the generation of the first channel information block occupies at least one processing resource.

[0261] As an example, the generation of the first channel information block occupies K processing resources, where K is a positive integer.

[0262] As one embodiment, the generation of the first channel information block includes: calculation or inference of the first channel information block.

[0263] As one embodiment, the generation of the first channel information block includes: inference to generate the first channel information block.

[0264] As one embodiment, the generation of the first channel information block includes: calculating and generating the first channel information block.

[0265] As one embodiment, the generation of the first channel information block includes: measuring and generating the first channel information block.

[0266] As an example, the meaning of the first reporting configuration being used to configure the reporting of the first channel information block includes: the first reporting configuration being used to indicate the reporting period of the first channel information block.

[0267] As an example, the meaning of the first reporting configuration being used to configure the reporting of the first channel information block includes: the first reporting configuration being used to indicate the time domain resources occupied by the first channel information block.

[0268] As an example, the meaning of the first reporting configuration being used to configure the reporting of the first channel information block includes: the first reporting configuration being used to indicate the frequency domain resources occupied by the first channel information block.

[0269] As an example, the meaning of "the first reporting configuration is used to configure the reporting of the first channel information block" includes: the first reporting configuration is used to trigger the reporting of the first channel information block.

[0270] As an example, the meaning of the first reporting configuration being used to configure the reporting of the first channel information block includes: the first reporting configuration being used to indicate the reporting conditions of the first channel information block.

[0271] As an example, the meaning of the first reporting configuration being used to configure the reporting of the first channel information block includes: the first reporting configuration being used to indicate the physical layer channel occupied by the first channel information block.

[0272] As an example, the first value is a positive integer.

[0273] As an example, the first value is a positive integer greater than 1.

[0274] As an example, the first value is a positive real number.

[0275] As an example, the first value depends on the first reporting configuration.

[0276] As an example, the first value depends on the higher-level parameters corresponding to the first reporting configuration.

[0277] As an example, the first value depends on the first channel information block.

[0278] As an example, the first value depends on the content included in the first channel information block.

[0279] As one embodiment, the remaining processing resources of the first node include: unused processing resources among the processing resources included in the first node.

[0280] As a sub-example of this embodiment, "not occupied" includes not being occupied by CSI calculation.

[0281] As a sub-example of this embodiment, the term "unoccupied" includes "not occupied by channel measurement".

[0282] As a sub-example of this embodiment, "unoccupied" includes "not occupied by channel calculation".

[0283] As a sub-example of this embodiment, "not occupied" includes not being occupied by CSI-reported calculations.

[0284] As an example, the total processing resources included in the first node include: all processing resources included in the first node for CSI calculation.

[0285] As one embodiment, the total processing resources included in the first node include: all processing resources included in the first node for channel measurement.

[0286] As one embodiment, the total processing resources included in the first node include: all processing resources included in the first node for channel calculation.

[0287] 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.

[0288] As an example, the second value is a positive integer.

[0289] As an example, the second value is a positive integer greater than 1.

[0290] As an example, the second value is a positive real number.

[0291] As an example, the second value is linearly related to the amount of processing resources that have been occupied by the first node.

[0292] As an example, the second value is equal to the sum of the number of processing resources already occupied by the first node and a value configured by a higher-level parameter.

[0293] As an example, the second value is equal to the product of the number of processing resources already occupied by the first node and a value configured in a higher-level parameter.

[0294] Example 2

[0295] Example 2 illustrates a schematic diagram of a network architecture according to an embodiment of this application, as shown in Figure 2.

[0296] 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.

[0297] 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.

[0298] 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.

[0299] As an example, the first node in this application includes the UE 201.

[0300] As an example, the second node in this application includes node B 203.

[0301] As an example, node B 203 is a macrocell base station.

[0302] As an example, node B 203 is a microcell base station.

[0303] As an example, node B 203 is a pico cell base station.

[0304] As an example, node B 203 is a femtocell.

[0305] As an example, node B 203 is a base station device that supports large latency differences.

[0306] As an example, node B 203 is a flight platform device.

[0307] As an example, node B 203 is a satellite device.

[0308] 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).

[0309] As an example, the UE 201 includes a mobile phone.

[0310] As an example, the UE 201 is a vehicle including a car.

[0311] 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.

[0312] 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.

[0313] As an example, the wireless link between the node B 203 and the UE 201 includes a cellular link.

[0314] As an example, the node B 203 and the UE 201 are connected via the Uu air interface.

[0315] As an example, the sender of the first reporting configuration in this application includes the node B 203.

[0316] As an example, the recipient of the first reported configuration in this application includes the UE 201.

[0317] As an example, in this application, the first channel information block is generated and sent, and the sender of the first channel information block includes the UE 201.

[0318] As an example, in this application, the first channel information block is generated and sent, and the receiver of the first channel information block includes the node B 203.

[0319] As an example, the sender of the second information block in this application includes the UE 201.

[0320] As an example, the recipient of the second information block in this application includes the node B 203.

[0321] As an example, the sender of the first information block in this application includes the node B 203.

[0322] As an example, the recipient of the first information block in this application includes the UE 201.

[0323] As an example, the sender of the M configuration messages in this application includes the node B 203.

[0324] As an example, the recipient of the M configuration messages in this application includes the UE 201.

[0325] As an example, the node B 203 supports the deployment of network-side (NW-side) AI / ML models.

[0326] As an example, the UE 201 supports the deployment of UE-side AI / ML models.

[0327] As an example, the UE 201 supports a 5G system.

[0328] As an example, the node B 203 supports a 5G system.

[0329] As an example, the UE 201 supports at least a 6G system.

[0330] As an example, the node B 203 supports at least a 6G system.

[0331] Example 3

[0332] 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.

[0333] 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.).

[0334] As an example, the wireless protocol architecture in Figure 3 is applicable to the first node in this application.

[0335] As an example, the wireless protocol architecture in Figure 3 is applicable to the second node in this application.

[0336] As an example, the first reporting configuration in this application is generated in the RRC 306.

[0337] As an example, in this application, the first channel information block is generated in the RRC 306.

[0338] As an example, in this application, the first channel information block is generated in MAC 302 or MAC 352.

[0339] As an example, in this application, the first channel information block is generated in the PHY 301 or the PHY 351.

[0340] As an example, in this application, the first information block is generated in the RRC 306.

[0341] As an example, the second information block in this application is generated in the RRC 306.

[0342] As an example, the second information block in this application is generated in MAC 302 or MAC 352.

[0343] As an example, the second information block in this application is generated in the PHY 301 or the PHY 351.

[0344] As an example, the M configuration messages described in this application are generated in the RRC 306.

[0345] As an example, the higher layer mentioned in this application refers to the layer above the physical layer.

[0346] As an example, the higher layer described in this application includes the RRC layer.

[0347] As an example, the higher-layer signaling described in this application includes RRC IE.

[0348] As an example, the higher-level signaling described in this application includes RRC messages.

[0349] As an example, the higher layer described in this application includes the MAC layer.

[0350] As an example, the higher-layer signaling described in this application includes MAC CE.

[0351] Example 4

[0352] 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.

[0353] 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.

[0354] 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.

[0355] 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.

[0356] 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.

[0357] 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.

[0358] 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.

[0359] 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; generates and transmits a first channel information block only if the first value is not greater than the amount of remaining processing resources of the second communication device 450; the first reporting configuration is used to configure the reporting of the first channel information block, the amount of processing resources occupied by the generation of the first channel information block being equal to the first value; the amount of remaining processing resources of the second communication device 450 is equal to the total amount of processing resources included in the second communication device 450 minus a second value, the second value depending on the amount of processing resources already occupied by the second communication device 450; whether the second value is equal to the amount of processing resources already occupied by the second communication device 450 depends on whether the first channel information block is generated based on inference.

[0360] 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 reported configuration; and generating and transmitting a first channel information block only if the first value is not greater than the amount of remaining processing resources of the second communication device 450.

[0361] 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 at least sends a first reporting configuration; receives a first channel information block; the sender of the first reporting configuration includes the second communication device 450, the second communication device 450 generating and sending the first channel information block only when a first value is not greater than the amount of remaining processing resources of the second communication device 450; the first reporting configuration is used to configure the reporting of the first channel information block, the amount of processing resources occupied by the generation of the first channel information block is equal to the first value; the amount of remaining processing resources of the second communication device 450 is equal to the total amount of processing resources included in the second communication device 450 minus a second value, the second value depending on the amount of processing resources already occupied by the second communication device 450; whether the second value is equal to the amount of processing resources already occupied by the second communication device 450 depends on whether the first channel information block is generated based on inference.

[0362] As one embodiment, the first communication device 410 includes: a memory storing a computer-readable instruction program that produces actions when executed by at least one processor, the actions including: sending a first reporting configuration and receiving a first channel information block.

[0363] As an example, the first node in this application includes the second communication device 450.

[0364] As an example, the second node in this application includes the first communication device 410.

[0365] 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.

[0366] As an example, at least one of the following is used to determine whether to generate and transmit the first channel information block in this application: the antenna 452, the transmitter / receiver 454, the transmitter processor 468, the receiver processor 456, the multi-antenna transmitter processor 457, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467.

[0367] As a sub-implementation of this embodiment, at least one of the following is used to determine the first channel information block in the non-cost application: the antenna 452, the transmitter / receiver 454, the transmitter processor 468, the receiver processor 456, the multi-antenna transmitter processor 457, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467.

[0368] As a sub-implementation of this embodiment, at least one of {the antenna 452, the transmitter / receiver 454, the transmitter processor 468, the receiver processor 456, the multi-antenna transmitter processor 457, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to generate and transmit the first channel information block only when the first value is not greater than the amount of remaining processing resources of the first node; at least one of {the antenna 420, the receiver 418, the receiver processor 470, the multi-antenna receiver processor 472, the controller / processor 475, and the memory 476} is used to receive the first channel information block in this application.

[0369] 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.

[0370] 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}.

[0371] 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.

[0372] As an example, at least one of the following is used to calculate the first parameter in this application for each of the M configuration messages in this application: the antenna 452, the transmitter / receiver 454, the transmitter processor 468, the receiver processor 456, the multi-antenna transmitter processor 457, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467.

[0373] Example 5

[0374] 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. 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.

[0375] For the first node U1, the first reported configuration is received in step S510; in step S511, the first channel information block is generated and sent only when the first value is not greater than the number of remaining processing resources of the first node.

[0376] For the second node N2, the first reporting configuration is sent in step S520; and the first channel information block is received in step S521.

[0377] In Embodiment 5, the first reporting configuration is used to configure the reporting of the first channel information block, and the amount of processing resources occupied by the generation of the first channel information block is equal to the first value; the amount of the remaining processing resources of the first node is equal to the total amount of processing resources included in the first node minus a second value, the second value depending on the amount of processing resources already occupied by the first node; whether the second value is equal to the amount of processing resources already occupied by the first node depends on whether the first channel information block is generated based on inference.

[0378] As an example, the first node U1 is the first node in this application.

[0379] As an example, the second node N2 is the second node in this application.

[0380] 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.

[0381] 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.

[0382] 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.

[0383] As one example, the second node N2 and the first node U1 communicate via the Uu interface.

[0384] As one example, the second node N2 is the maintenance base station of the serving cell of the first node U1.

[0385] As an example, the transmission channel occupied by the first reporting configuration includes DL-SCH (DownLink-Shared Channel).

[0386] As an example, the physical layer channel occupied by the first reporting configuration includes PDSCH (Physical DownLink Shared Channel).

[0387] As an example, the first node U1 generates and sends the first channel information block.

[0388] As a sub-example of this embodiment, the receiver of the first channel information block is the second node N2.

[0389] As a sub-implementation of this embodiment, the physical layer channels occupied by the first channel information block include PUSCH (Physical Uplink Shared Channel).

[0390] As a sub-example of this embodiment, the physical layer channel occupied by the first channel information block includes PUCCH (Physical Uplink Control Channel).

[0391] As a sub-implementation of this embodiment, the first reporting configuration indicates the physical layer channel occupied by the first channel information block.

[0392] As an example, step S510 is performed before step S511.

[0393] As an example, step S520 includes: transmitting an RS in a first RS resource or a first RS resource set, wherein the RS is used to generate the first channel information block.

[0394] As a sub-implementation of this embodiment, the first reporting configuration is used to configure the first RS resource.

[0395] As a sub-implementation of this embodiment, the first reporting configuration is used to configure the first RS resource set.

[0396] As a sub-implementation of this embodiment, the first RS resource is associated with the first channel information block.

[0397] As a sub-implementation of this embodiment, the first RS resource set is associated with the first channel information block.

[0398] Typically, the first value depends on whether the first channel information block is generated based on inference, and the priority associated with the first channel information block does not depend on whether the first channel information block is generated based on inference.

[0399] As an example, the meaning of "the first value depends on whether the first channel information block is generated based on inference" includes: when the content included in the first information block does not change; when the first channel information block is not generated based on inference, the first value is equal to the first candidate value; when the first channel information block is generated based on inference, the first value is equal to the second candidate value; and when the first candidate value and the second candidate value are different.

[0400] As an example, the meaning of "the first value depends on whether the first channel information block is generated based on inference" includes: when the content included in the first information block does not change; when the first channel information block is not generated based on inference, the first value is equal to the first candidate value; when the first channel information block is generated based on inference, the first value is equal to the first candidate value multiplied by a given coefficient; the given coefficient is predefined, or the given coefficient is configured through higher-level parameters.

[0401] As a sub-example of this embodiment, the given coefficient is greater than 1.

[0402] As an example, the meaning of "the first value depends on whether the first channel information block is generated based on inference" includes: when the content included in the first information block does not change; when the first channel information block is not generated based on inference, the first value is equal to the first candidate value; when the first channel information block is generated based on inference, the first value is equal to the first candidate value plus a given offset value; the given offset value is predefined, or the given offset value is configured through higher-level parameters.

[0403] As a sub-example of this embodiment, the given offset value is greater than 1.

[0404] As an example, the fact that the priority associated with the first channel information block does not depend on whether the first channel information block is generated based on inference means that: regardless of whether the first channel information is generated based on inference, the priority associated with the first channel information block remains unchanged when the configuration parameters for the first channel information block included in the first reporting configuration remain unchanged.

[0405] As a sub-example of this embodiment, the configuration parameters for the first channel information block included in the first reporting configuration include the configuration of the reporting period.

[0406] As a sub-example of this embodiment, the configuration parameters for the first channel information block included in the first reporting configuration include the configuration of the bearer channel.

[0407] As a sub-implementation of this embodiment, the configuration parameters for the first channel information block included in the first reporting configuration include the configuration of the reporting content.

[0408] As a sub-example of this embodiment, the configuration parameters for the first channel information block included in the first reporting configuration include the configuration of the serving cell index.

[0409] As a sub-example of this embodiment, the configuration parameters for the first channel information block included in the first reporting configuration include the configuration of ReportConfigID(Index).

[0410] As a sub-example of this embodiment, the configuration parameters for the first channel information block included in the first reporting configuration do not include AI-related configurations.

[0411] As a sub-example of this embodiment, the configuration parameters for the first channel information block included in the first reporting configuration do not include inference-related configurations.

[0412] As a sub-example of this embodiment, the configuration parameters for the first channel information block included in the first reporting configuration do not include the configuration related to associated ID.

[0413] As a sub-example of this embodiment, the configuration parameters for the first channel information block included in the first reporting configuration do not include the configuration related to Model ID.

[0414] Example 6

[0415] 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.

[0416] For the first node U3, the first information block is received in step S630.

[0417] For the second node N4, the first information block is sent in step S640.

[0418] In embodiment 6, the first information block is used to indicate the first parameter.

[0419] As an example, the first node U3 is the first node in this application.

[0420] As an example, the second node N4 is the second node in this application.

[0421] 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.

[0422] 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.

[0423] 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.

[0424] As one example, the second node N4 and the first node U3 communicate via the Uu interface.

[0425] As one example, the second node N4 is the sustaining base station for the serving cell of the first node U3.

[0426] As one embodiment, the first information block is carried by higher layer signaling.

[0427] As an example, the first information block is carried by RRC (Radio Resource Control) signaling.

[0428] As one embodiment, the first information block includes some or all of the fields in one or more RRC IEs (Information Elements).

[0429] As an example, the first information block explicitly indicates the first parameter.

[0430] As an example, the first information block implicitly indicates the first parameter.

[0431] As an example, the first information block directly indicates the first parameter.

[0432] As an example, the first information block indirectly indicates the first parameter.

[0433] Typically, the total number of processing resources included in the first node is equal to a first integer.

[0434] As an example, the first information block indicates a first coefficient, and the product of the first integer and the first coefficient is the first parameter.

[0435] As an example, the first integer corresponds to the total number of CPUs in the first node.

[0436] As an example, the first integer corresponds to the number of CSI calculations that the first node supports performing simultaneously in a CC.

[0437] As an example, the first integer corresponds to the number of times the first node supports simultaneous CSI calculations across all CCs.

[0438] As an example, the first integer is a positive integer.

[0439] As an example, the first integer is a positive integer greater than 1.

[0440] As an example, the first integer corresponds to simultaneousCSI-ReportsPerCC.

[0441] As an example, the first integer corresponds to simultaneousCSI-ReportsAllCC.

[0442] As an example, the first integer corresponds to simultaneousCSI-ReportsPerCC-r19.

[0443] As an example, the first integer corresponds to simultaneousCSI-ReportsAllCC-r19.

[0444] As an example, the first integer corresponds to simultaneousCSI-ReportsPerCC-AI.

[0445] As an example, the first integer corresponds to simultaneousCSI-ReportsAllCC-AI.

[0446] As an example, the first node reports the first integer via UAI.

[0447] As an example, the first node reports the first integer through OtherConfig.

[0448] As an example, the first node reports the first integer via mimo-ParametersPerBand.

[0449] As an example, the first node reports the first integer via RF-Parameters IE.

[0450] As an example, the first coefficient is a number between 0 and 1.

[0451] As an example, the product of the first integer and the first coefficient, when rounded down, equals the first parameter.

[0452] As an example, the product of the first integer and the first coefficient, rounded up, equals the first parameter.

[0453] As one embodiment, the first information block includes some or all of an RRC IE field.

[0454] As one embodiment, the first information block includes part or all of the fields of each of the plurality of RRC IEs.

[0455] As an example, the name of the RRC signaling carrying the first information block includes: CSI.

[0456] As an example, the name of the RRC signaling carrying the first information block includes: Report.

[0457] As an example, the name of the RRC signaling carrying the first information block includes: Inference.

[0458] As an example, the name of the RRC signaling carrying the first information block includes: Config.

[0459] As an example, the transmission channel occupied by the first information block includes DL-SCH.

[0460] As an example, the physical layer channel occupied by the first information block includes PDSCH.

[0461] As an example, step S630 precedes step S511 in Figure 5.

[0462] As an example, step S630 precedes step S510 in Figure 5; step S640 precedes step S520 in Figure 5.

[0463] As an example, step S630 follows step S510 in Figure 5; step S640 follows step S520 in Figure 5.

[0464] 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.

[0465] Example 7

[0466] 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.

[0467] For the first node U5, the second information block is sent in step S750.

[0468] For the second node N6, the second information block is received in step S760.

[0469] In Example 7, the second information block is used to trigger the reconfiguration of the first parameter.

[0470] As an example, the first node U5 is the first node in this application.

[0471] As an example, the second node N6 is the second node in this application.

[0472] 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.

[0473] 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.

[0474] 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.

[0475] As one example, the second node N6 and the first node U5 communicate via the Uu interface.

[0476] As one example, the second node N6 is the sustaining base station for the serving cell of the first node U5.

[0477] As an example, the physical layer channel occupied by the second information block includes PUCCH (Physical Uplink Control Channel).

[0478] As an example, the physical layer channel occupied by the second information block includes PUSCH (Physical Uplink Shared Channel).

[0479] As one embodiment, the second information block is used to trigger the receiver of the second information block to increase or decrease the first parameter.

[0480] As an example, the second information block relies on the results of performance monitoring of the AI ​​model.

[0481] As an example, the second information block relies on the results of the performance evaluation of the AI ​​model.

[0482] As an example, step S750 precedes step S511 as shown in Figure 5.

[0483] As an example, step S750 follows step S511 as shown in Figure 5.

[0484] As an example, step S750 precedes step S510 in Figure 5; step S760 precedes step S520 in Figure 5.

[0485] As an example, step S750 follows step S510 in Figure 5; step S760 follows step S520 in Figure 5.

[0486] As an example, step S750 follows step S630 in Figure 6; step S760 follows step S640 in Figure 6.

[0487] As an example, step S750 precedes step S630 in Figure 6; step S760 precedes step S640 in Figure 6.

[0488] As one embodiment, the second information block is used to trigger the second node N6 to increase or decrease the first ratio value.

[0489] Example 8

[0490] 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.

[0491] 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.

[0492] For the second node N8, M configuration messages are sent in step S880.

[0493] 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.

[0494] As an example, step S870 includes receiving RSs from the M RS resource groups.

[0495] As an example, step S880 includes sending the RSs in the M RS resource groups.

[0496] As an example, the first node U7 is the first node in this application.

[0497] As an example, the second node N8 is the second node in this application.

[0498] 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.

[0499] 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.

[0500] 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.

[0501] As one example, the second node N8 and the first node U7 communicate via the Uu interface.

[0502] As one example, the second node N8 is the sustaining base station for the serving cell of the first node U7.

[0503] As an example, RS stands for Reference Signal.

[0504] As an example, any one of the M configuration messages is transmitted via higher-layer signaling.

[0505] As an example, any one of the M configuration messages is carried by RRC layer signaling.

[0506] As an example, any one of the M configuration messages is transmitted via RRC signaling.

[0507] As an example, any one of the M configuration messages is transmitted via an RRC message.

[0508] As an example, any one of the M configuration messages includes RRC signaling.

[0509] As an example, any one of the M configuration messages includes one or more RRC IEs.

[0510] As an example, any one of the M configuration messages includes one or more fields in an RRC IE.

[0511] As an example, any one of the M configuration messages includes one or more fields in each of the multiple RRC IEs.

[0512] As an example, the M configuration messages are carried by the same RRC signaling.

[0513] As an example, the M configuration messages belong to a list included in an RRC IE.

[0514] As a sub-implementation of this embodiment, the M configuration messages correspond to the same domain of the RRC IE.

[0515] As a sub-implementation of this embodiment, the M configuration messages correspond to the M elements of the list.

[0516] As a sub-implementation of this embodiment, the name of the list carrying the M configuration messages includes: Add.

[0517] As a sub-implementation of this embodiment, the name of the list carrying the M configuration messages includes: Mod.

[0518] As a sub-implementation of this embodiment, the name of the list carrying the M configuration messages includes: ToAddModLi st.

[0519] As an example, any one of the M configuration messages includes ServingCellConfig IE.

[0520] As an example, any one of the M configuration messages includes one or more domains in the ServingCellConfig IE.

[0521] As an example, any one of the M configuration messages includes CSI-MeasConfig IE.

[0522] As an example, any one of the M configuration messages includes one or more domains in the CSI-MeasConfig IE.

[0523] As an example, any one of the M configuration messages includes NZP-CSI-RS-Resource IE.

[0524] As an example, any one of the M configuration messages includes one or more domains in the NZP-CSI-RS-Resource IE.

[0525] As an example, any one of the M configuration messages includes the CSI-RS-ResourceMapping IE.

[0526] As an example, any one of the M configuration messages includes one or more domains in the CSI-RS-ResourceMapping IE.

[0527] As an example, any one of the M configuration messages includes CSI-FrequencyOccupation IE.

[0528] As an example, any one of the M configuration messages includes one or more domains in the CSI-FrequencyOccupation IE.

[0529] As an example, any one of the M configuration messages includes CSI-ResourcePeriodicityAndOffset IE.

[0530] As an example, any one of the M configuration messages includes one or more domains in CSI-ResourcePeriodicityAndOffset IE.

[0531] As an example, any one of the M configuration messages includes NZP-CSI-RS-ResourceSet IE.

[0532] As an example, any one of the M configuration messages includes one or more domains in the NZP-CSI-RS-ResourceSet IE.

[0533] As an example, any one of the M configuration messages includes CSI-IM-Resource IE.

[0534] As an example, any one of the M configuration messages includes one or more domains in the CSI-IM-Resource IE.

[0535] As an example, any one of the M configuration messages includes CSI-IM-ResourceSet IE.

[0536] As an example, any one of the M configuration messages includes one or more domains in the CSI-IM-ResourceSet IE.

[0537] As an example, any one of the M configuration messages includes CSI-SSB-ResourceSet IE.

[0538] As an example, any one of the M configuration messages includes one or more domains in the CSI-SSB-ResourceSet IE.

[0539] As an example, any one of the M configuration messages includes CSI-ResourceConfig IE.

[0540] As an example, any one of the M configuration messages includes one or more domains in the CSI-ResourceConfig IE.

[0541] As an example, any one of the M configuration messages includes CSI-RS-ResourceConfigMobility IE.

[0542] As an example, any one of the M configuration messages includes one or more domains in the CSI-RS-ResourceConfigMobility IE.

[0543] As an example, any one of the M configuration messages includes CSI-ReportConfig IE.

[0544] As an example, any one of the M configuration messages includes one or more fields in the CSI-ReportConfig IE.

[0545] As an example, any one of the M configuration messages includes a CSI-AperiodicTriggerStateList IE.

[0546] As an example, any one of the M configuration messages includes one or more domains in the CSI-AperiodicTriggerStateList IE.

[0547] As an example, any one of the M configuration messages includes a CSI-AperiodicTriggerState IE.

[0548] As an example, any one of the M configuration messages includes one or more domains in the CSI-AperiodicTriggerState IE.

[0549] As an example, any one of the M configuration messages includes a CSI-AssociatedReportConfigInfo IE.

[0550] As an example, any one of the M configuration messages includes one or more domains in the CSI-AssociatedReportConfigInfo IE.

[0551] As an example, any one of the M configuration messages includes CSI-SemiPersistentOnPUSCH-TriggerStateList IE.

[0552] As an example, any one of the M configuration messages includes one or more domains in the CSI-SemiPersistentOnPUSCH-TriggerStateList IE.

[0553] As an example, any one of the M configuration messages includes CSI-SemiPersistentOnPUSCH-TriggerState IE.

[0554] As an example, any one of the M configuration messages includes one or more domains in the CSI-SemiPersistentOnPUSCH-TriggerState IE.

[0555] As an example, any one of the M configuration messages includes a CSI-ReportSubConfigTriggerList IE.

[0556] As an example, any one of the M configuration messages includes one or more domains in the CSI-ReportSubConfigTriggerList IE.

[0557] As an example, any one of the M configuration messages includes CSI-ReportSubConfig IE.

[0558] As an example, any one of the M configuration messages includes one or more domains in the CSI-ReportSubConfig IE.

[0559] As an example, any one of the M configuration messages includes LTM-CSI-ReportConfig IE.

[0560] As an example, any one of the M configuration messages includes one or more domains in the LTM-CSI-ReportConfig IE.

[0561] As an example, the name of the RRC signaling used to transmit any one of the M configuration messages includes CSI.

[0562] As an example, the name of the RRC signaling used to transmit any one of the M configuration messages includes CSI-RS.

[0563] As an example, the name of the RRC signaling used to transmit any one of the M configuration messages includes Report.

[0564] As an example, the name of the RRC signaling used to transmit any one of the M configuration messages includes Config.

[0565] As an example, the M configuration messages are all used for prediction.

[0566] As an example, the M configuration messages are all used for AI / ML inference.

[0567] As an example, the M configuration messages are M prediction configuration messages.

[0568] As an example, the M configuration messages are M parameter sets.

[0569] As an example, the M configuration messages are M beam configuration messages.

[0570] As an example, the M configuration messages respectively indicate the M RS resource groups.

[0571] As an example, the M configuration messages configure the M RS resource groups respectively.

[0572] As an example, the M configuration messages correspond one-to-one with the M RS resource groups.

[0573] As an example, any one of the M configuration messages indicates an RS resource group.

[0574] As an example, any one of the M configuration messages configures an RS resource group.

[0575] As an example, any one of the M configuration messages indicates one of the M RS resource groups.

[0576] As an example, any one of the M configuration messages configures one of the M RS resource groups.

[0577] As an example, the M RS resource groups each correspond to M beams.

[0578] As an example, the M RS resource groups correspond to M RS resource sets.

[0579] As an example, each of the M configuration messages indicates the measurement period for the corresponding RS resource group.

[0580] As an example, each of the M configuration messages indicates the measurement period for each RS resource in the corresponding RS resource group.

[0581] As an example, each of the M configuration messages indicates the RS resources included in the corresponding RS resource group.

[0582] As an example, each of the M configuration messages indicates the configuration information of the RS resources included in the corresponding RS resource group.

[0583] 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.

[0584] 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.

[0585] As an example, each of the M configuration messages includes a reported configuration.

[0586] As an example, the M configuration messages respectively indicate M reported configurations.

[0587] As an example, each of the M configuration messages indicates the reporting configuration for the RS resources included in the corresponding RS resource group.

[0588] 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.

[0589] 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.

[0590] As an example, any one of the M RS resource groups includes one or more RS resources.

[0591] 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.

[0592] As an example, the RS resource group includes only one RS resource.

[0593] As an example, the RS resource group includes multiple RS resources.

[0594] As an example, at least one of the M RS resource groups contains only one RS resource.

[0595] As an example, at least one of the M RS resource groups includes multiple RS resources.

[0596] As a sub-example of this embodiment, the plurality of RS resources included in the RS resource group belong to different RS resource sets.

[0597] 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.

[0598] 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.

[0599] 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.

[0600] As an example, the RS resources included in any of the M RS resource groups belong to an RS resource set.

[0601] As an example, the RS resources described in this application are periodic.

[0602] As an example, the RS resources described in this application are semi-persistent.

[0603] As an example, the RS resources described in this application include antenna ports.

[0604] As an example, the RS resource described in this application includes a reference signal port.

[0605] As an example, the RS resources described in this application include CSI-RS ports.

[0606] As an example, the RS resource described in this application is one of CSI-RS resources or SSB.

[0607] As an example, the RS resources described in this application include CSI-RS resources.

[0608] As an example, the RS resource described in this application is a CSI-RS resource.

[0609] As an example, the RS resources described in this application include NZP (Non-Zero Power) CSI-RS resources.

[0610] As an example, the RS resource described in this application is an NZP CSI-RS resource.

[0611] As an example, one RS resource described in this application corresponds to one CSI-RS resource ID.

[0612] As an example, one RS resource described in this application corresponds to one NZP-CSI-RS-ResourceId.

[0613] As an example, the RS resources described in this application include SSBs.

[0614] As an example, the RS resource described in this application is an SSB.

[0615] As an example, one RS resource described in this application corresponds to one SSB-Index.

[0616] As an example, one RS resource described in this application corresponds to one ssb-Index.

[0617] As an example, SSB in this application refers to Synchronization Signal Block.

[0618] As an example, the SSB mentioned in this application refers to: SS (Synchronization Signal) / PBCH (Physical Broadcast Channel) block.

[0619] Typically, the PBCH, PSS (Primary Synchronization Signal), and SSS (Secondary Synchronization Signal) are received in consecutive symbols and form an SS / PBCH block.

[0620] 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.

[0621] As an example, each of the M RS resource groups includes RS resources that are either CSI-RS resources or SSBs.

[0622] As an example, any one of the M RS resource groups is a CSI-RS resource group or an SSB group.

[0623] As an example, any one of the M RS resource groups is a CSI-RS resource group.

[0624] As an example, any one of the M RS resource groups is an SSB group.

[0625] As an example, for each of the M configuration messages, the first node U7 calculates the performance parameters.

[0626] As an example, the first node U7 calculates M performance parameters, each of which relates to one of the M configuration messages.

[0627] 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.

[0628] As a supplementary embodiment of this sub-example, the M predictions correspond to M prediction sub-models respectively.

[0629] As a supplementary embodiment of this sub-example, the M predictions each correspond to the M prediction functions of a model.

[0630] As a supplementary embodiment of this sub-example, the M predictions each correspond to the M prediction targets of a model.

[0631] As a supplementary embodiment of this sub-example, the M predictions each correspond to one of the M prediction tasks of a model.

[0632] As an example, the performance parameter corresponds to a performance metric.

[0633] As an example, the performance parameter corresponds to a KPI (Key Performance Indicator).

[0634] As an example, the performance parameter is the intermediate KPI.

[0635] As an example, the performance parameter is the final KPI (eventual KPI).

[0636] As an example, the performance parameter is used for performance monitoring of one of the M configuration messages.

[0637] As an example, the performance parameter is used for performance monitoring of the measurement indicated by one of the M configuration messages.

[0638] As an example, the signaling carrying the M configuration messages indicates the performance parameters.

[0639] As an example, each of the M configuration messages indicates the performance parameter.

[0640] 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.

[0641] As an example, the candidates for the performance parameter include one or more of throughput, BLER (Block Error Rate), and hypothetical BLER.

[0642] As an example, the performance parameter is NMSE.

[0643] As an example, the performance parameter is SGCS.

[0644] As an example, the performance parameter is truth ground CSI.

[0645] As an example, the calculation of the performance parameters depends on the measurement of the RS resource group indicated by the corresponding configuration message.

[0646] As an example, any one of the M configuration messages indicates a measurement for the corresponding RS resource group.

[0647] 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).

[0648] As an example, the measurement includes measurements for RSRP.

[0649] As an example, the measurement includes a measurement for RSRQ.

[0650] As an example, the measurement includes a measurement of RSSI.

[0651] As an example, the measurement includes a measurement of SNR.

[0652] As an example, the first node U7 performs the calculation of the performance parameters accordingly.

[0653] 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.

[0654] 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.

[0655] 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.

[0656] As an example, the second information block depends on the performance parameters.

[0657] As one example, whether the second information block is sent depends on the performance parameters.

[0658] As an example, the generation of the second information block depends on the performance parameters.

[0659] As an example, whether the second information block is sent depends on the M performance parameters.

[0660] As an example, the generation of the second information block depends on the M performance parameters.

[0661] As one example, the performance parameters are used to trigger the transmission of the second information block.

[0662] As an example, if the performance parameter is higher than the first threshold, the second information block is triggered.

[0663] As an example, if at least one of the M performance parameters is higher than the first threshold, the second information block is triggered.

[0664] As an example, if one of the M performance parameters is higher than the first threshold, the second information block is triggered.

[0665] 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.

[0666] As a sub-implementation of this embodiment, N is either predefined or configured by the second node N8.

[0667] 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.

[0668] 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.

[0669] As an example, the M configuration messages occupy at least one PDSCH.

[0670] As an example, the M configuration messages occupy one PDSCH.

[0671] As an example, the M configuration messages are transmitted on a PDSCH, and step S870 includes receiving the PDSCH.

[0672] As an example, the M configuration messages are transmitted on multiple PDSCHs, and step S870 includes receiving the multiple PDSCHs.

[0673] As an example, the performance parameter corresponds to a performance metric.

[0674] As an example, the first node performs the settlement of the relevant performance parameters.

[0675] As an example, the first node 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.

[0676] As an example, the first node 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.

[0677] As an example, the computation time includes CPU usage time.

[0678] As one example, the computation time includes the time during which computing power is used.

[0679] As one example, the computation time includes the APU's downtime.

[0680] As an example, the calculation time includes the measurement period of the RS resource group indicated by the corresponding configuration message.

[0681] As an example, the calculation time includes the period of measurement calculation results of the RS resource group as indicated by the corresponding configuration message.

[0682] As an example, if the performance parameter is lower than a first threshold, the second information block is triggered.

[0683] As one example, the performance parameters are used to trigger the transmission of the second information block.

[0684] As an example, step S870 precedes step S511 as shown in Figure 5.

[0685] As an example, step S870 precedes step S510 in Figure 5; step S880 precedes step S520 in Figure 5.

[0686] As an example, step S870 follows step S510 in Figure 5; step S880 follows step S520 in Figure 5.

[0687] 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.

[0688] As an example, step S871 precedes step S750 in Figure 7.

[0689] Example 9

[0690] Example 9 illustrates a schematic diagram of the occupied processing resources of the first node according to an embodiment of this application, as shown in Figure 9. In Figure 9, a solid-lined rectangle represents a processing resource, gray-filled rectangles represent occupied processing resources, diamond-shaped filled rectangles represent processing resources corresponding to the first parameter, and unfilled rectangles represent occupied processing resources and processing resources other than those corresponding to the first parameter; the total number of processing resources included in the first node is equal to K1, where K1 is a positive integer greater than 1.

[0691] In Example 9, when the first channel information is generated based on inference, the second value is equal to the number of processing resources already occupied by the first node plus the first parameter; when the first channel information is not generated based on inference, the second value is equal to the number of processing resources already occupied by the first node.

[0692] As an example, the first parameter is a positive integer.

[0693] As an example, the first parameter is a positive integer greater than 1.

[0694] As an example, the first parameter is a positive real number.

[0695] As an example, the first channel information is generated based on inference, and the second value is equal to the amount of processing resources already occupied by the first node plus the first parameter.

[0696] As an example, the first channel information is not generated based on inference, and the second value is equal to the amount of processing resources that the first node has already occupied.

[0697] As an example, the first parameter is predefined.

[0698] As an example, the first parameter is configured through higher-level parameters.

[0699] As an example, the first parameter is configured via higher-layer signaling.

[0700] As an example, the first parameter is indicated via RRC signaling.

[0701] As an example, the first parameter is determined by RRC signaling.

[0702] Example 10

[0703] Example 10 illustrates a first parameter diagram according to an embodiment of this application, as shown in Figure 10. In Figure 10, a solid-lined rectangle represents a processing resource, and gray-filled rectangles represent the number of reserved processing resources.

[0704] In Example 10, the first parameter is the number of reserved processing resources, which are used for the generation of channel information not generated based on inference; the first parameter is equal to K2, where K2 is a positive integer greater than 1.

[0705] As one example, the reserved processing resources are used to generate channel information generated via legacy methods.

[0706] As an example, the reserved processing resources are used to generate channel information generated in the manner of Release 18 and earlier.

[0707] As one example, the reserved processing resources are used to generate channel information in a linear manner.

[0708] Example 11

[0709] 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.

[0710] 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.

[0711] 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.

[0712] 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).

[0713] 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.

[0714] Similarly, ML testing functionality can also be deployed in cross-domain management systems or domain-specific management systems.

[0715] 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.

[0716] 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.

[0717] As an example, one of the gNBs (or base stations) in Example 11 is the second node of this application.

[0718] Example 12

[0719] 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.

[0720] 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.

[0721] 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.

[0722] 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.

[0723] Optionally, the UE function 1203 also includes a CN domain ML training function (not shown in Figure 12).

[0724] Optionally, the UE function 1203 also includes an AI / ML deployment function—not shown in Figure 12—for loading ML models and data.

[0725] 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.

[0726] As an example, the ML model and the associated metadata are loaded by the first node from a network device or a remote server.

[0727] 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).

[0728] 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).

[0729] As an example, the first channel information block in this application is generated based on inference, and the first channel information block is obtained through inference by the AI / ML inference function 1205.

[0730] As an example, the ML model is based on NN (Neural Networks).

[0731] As an example, the ML model is based on ANN (Artificial Neural Networks).

[0732] As an example, the ML model is based on CNN (Convolutional Neural Networks).

[0733] As an example, the ML model is based on the LLM (Large Language Model) architecture.

[0734] As an example, the ML model is based on the Transformer architecture.

[0735] As an example, the ML model is based on the GPT (Generative Pre-Trained) architecture.

[0736] As an example, the ML model is based on LSTM (Long Short-Term Memory network).

[0737] As an example, the ML model is based on MLP (MultiLayer Perceptron).

[0738] As an example, the ML model is based on GAN (Generative Adversarial Nets).

[0739] As an example, the ML model is based on a lightweight neural network.

[0740] As a sub-example of this embodiment, the lightweight neural network includes one or more of MobileNet, ShuffleNet, and SqueezeNet.

[0741] Example 13

[0742] 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.

[0743] 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.

[0744] As one embodiment, the fourth processor includes ML testing functionality.

[0745] As one embodiment, the fourth processor includes performance monitoring / evaluation of the ML model.

[0746] 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.

[0747] 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.

[0748] As one embodiment, the third processor belongs to the first node, and the fourth processor belongs to the second node.

[0749] As an example, the third processor belongs to the first node.

[0750] As an example, the first dataset includes training data.

[0751] 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.

[0752] As an example, the second processor belongs to the first node; the above method avoids passing the first dataset to the second node.

[0753] As an example, the second processor belongs to the second node in this application; the above method supports joint training and optimizes system performance.

[0754] As an example, the second processor belongs to the core network; the above method supports network-wide joint training, further optimizing system performance.

[0755] As an example, the second dataset includes inference data.

[0756] 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.

[0757] As one embodiment, the output of the third processor includes the first channel information block.

[0758] As one embodiment, the output of the third processor includes the performance parameters described in this application.

[0759] 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.

[0760] 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.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] Example 14

[0765] 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.

[0766] 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.

[0767] 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.

[0768] As an example, the first stage includes AI / ML model training.

[0769] As an example, the first stage includes AI / ML model training and AI / ML testing.

[0770] As an example, the AI / ML model training includes initial training and re-training of one or a group of AI / ML entities.

[0771] As an example, the training of the AI / ML model depends on training data.

[0772] As an example, the AI / ML model training includes AI / ML entity validation.

[0773] As an example, the AI / ML entity verification is used to evaluate the performance of the AI / ML entity.

[0774] As an example, the AI / ML entity verification relies on verification data.

[0775] As an example, if the AI / ML entity verification results do not meet expectations, the AI / ML model will be retrained.

[0776] As an example, the AI / ML testing includes testing the validated AI / ML entities to estimate the performance of the trained AI / ML model.

[0777] 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.

[0778] As an example, the AI / ML test relies on test data.

[0779] As one embodiment, the second stage includes AI / ML simulation, which performs AI / ML entity reasoning in a simulation environment.

[0780] As an example, the AI / ML simulation estimates the performance of AI / ML entity reasoning in a simulation environment before using AI / ML entities.

[0781] As one embodiment, the second stage is optional.

[0782] 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.

[0783] As an example, the third stage is optional.

[0784] As an example, the third stage is no longer needed when the training and inference functions are co-located.

[0785] As an example, the fourth stage includes AI / ML inference.

[0786] As an example, the first channel information block is generated based on the fourth stage.

[0787] Example 15

[0788] 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 transmitter 1502.

[0789] In embodiment 15, the first receiver 1501 receives the first reporting configuration; the first processor 1502 generates and sends the first channel information block only when the first value is not greater than the number of remaining processing resources of the first node.

[0790] In Example 15, the first reporting configuration is used to configure the reporting of the first channel information block, and the amount of processing resources occupied by the generation of the first channel information block is equal to the first value; the amount of the remaining processing resources of the first node is equal to the total amount of processing resources included in the first node minus a second value, the second value depending on the amount of processing resources already occupied by the first node; whether the second value is equal to the amount of processing resources already occupied by the first node depends on whether the first channel information block is generated based on inference.

[0791] As an example, when the first channel information is generated based on inference, the second value is equal to the number of processing resources already occupied by the first node plus the first parameter; when the first channel information is not generated based on inference, the second value is equal to the number of processing resources already occupied by the first node.

[0792] As an example, the first parameter is the amount of reserved processing resources, which are used for generating channel information that is not generated based on inference.

[0793] As an example, the first receiver 1501 receives a first information block; the first information block is used to indicate the first parameter.

[0794] As an example, the first processor 1502 sends a second information block; the second information block is used to trigger the reconfiguration of the first parameter.

[0795] 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.

[0796] As an example, the first value depends on whether the first channel information block is generated based on inference, and the priority associated with the first channel information block does not depend on whether the first channel information block is generated based on inference.

[0797] As one embodiment, the first processor 1502 receives RS used to generate the first channel information block.

[0798] As an example, the first processor 1502 receives the RSs in the M RS resource groups indicated by the M configuration messages respectively.

[0799] As an example, the first node 1500 is a user equipment.

[0800] As an example, the first node 1500 is a terminal.

[0801] As an example, the first node 1500 is a relay node device.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] Example 16

[0806] 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.

[0807] In embodiment 16, the first transmitter 1601 sends a first reporting configuration; the second receiver 1602 receives a first channel information block.

[0808] In Example 16, the sender of the first reporting configuration includes a first node. The first node generates and sends the first channel information block only when the first value is not greater than the amount of the remaining processing resources of the first node. The first reporting configuration is used to configure the reporting of the first channel information block. The amount of processing resources occupied by the generation of the first channel information block is equal to the first value. The amount of the remaining processing resources of the first node is equal to the total amount of processing resources included in the first node minus a second value. The second value depends on the amount of processing resources already occupied by the first node. Whether the second value is equal to the amount of processing resources already occupied by the first node depends on whether the first channel information block is generated based on inference.

[0809] As an example, when the first channel information is generated based on inference, the second value is equal to the number of processing resources already occupied by the first node plus the first parameter; when the first channel information is not generated based on inference, the second value is equal to the number of processing resources already occupied by the first node.

[0810] As an example, the first parameter is the amount of reserved processing resources, which are used for generating channel information that is not generated based on inference.

[0811] As an example, the first transmitter 1601 transmits a first information block; the first information block is used to indicate the first parameter.

[0812] As an example, the first transmitter 1601 transmits RS used to generate the first channel information block.

[0813] 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 parameter.

[0814] 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.

[0815] As an example, the first transmitter 1601 transmits RS in the M RS resource groups indicated by the M configuration messages respectively.

[0816] As an example, the first value depends on whether the first channel information block is generated based on inference, and the priority associated with the first channel information block does not depend on whether the first channel information block is generated based on inference.

[0817] As one example, the second node 1600 is a base station device.

[0818] As one example, the second node 1600 is a user equipment.

[0819] As an example, the second node 1600 is a TRP.

[0820] 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.

[0821] 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.

[0822] 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.

[0823] 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

A method for use in terminals for wireless communication and artificial intelligence, characterized in that, include: Receive the first reported configuration; The first channel information block is generated and sent only when the first value is not greater than the amount of remaining processing resources of the terminal; Wherein, the first reporting configuration is used to configure the reporting of the first channel information block, and the amount of processing resources occupied by the generation of the first channel information block is equal to the first value; the amount of the remaining processing resources of the terminal is equal to the total amount of processing resources included in the terminal minus a second value, the second value depending on the amount of processing resources already occupied by the terminal; whether the second value is equal to the amount of processing resources already occupied by the terminal depends on whether the first channel information block is generated based on inference. The method in the terminal according to claim 1, characterized in that, When the first channel information is generated based on inference, the second value is equal to the number of processing resources already occupied by the terminal plus the first parameter; when the first channel information is not generated based on inference, the second value is equal to the number of processing resources already occupied by the terminal. The method in the terminal according to claim 2, characterized in that, The first parameter is the amount of reserved processing resources, which are used for the generation of channel information that is not generated based on inference. The method in the terminal according to claim 2 or 3 is characterized in that, include: Receive the first information block; The first information block is used to indicate the first parameter. The method in the terminal according to claim 4, characterized in that, include: Send the second information block; The second information block is used to trigger the reconfiguration of the first parameter. The method in the terminal according to claim 5, characterized in that, 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. The method in the terminal according to any one of claims 1 to 6 is characterized in that, The first value depends on whether the first channel information block is generated based on inference, and the priority associated with the first channel information block does not depend on whether the first channel information block is generated based on inference. 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 1-7. A method for use in base stations for wireless communication and artificial intelligence, characterized in that, include: Send the first reporting configuration; Receive the first channel information block; Wherein, the sender of the first reporting configuration includes a terminal, which generates and sends the first channel information block only when the first value is not greater than the number of remaining processing resources of the terminal; the first reporting configuration is used to configure the reporting of the first channel information block, and the number of processing resources occupied by the generation of the first channel information block is equal to the first value; the number of remaining processing resources of the terminal is equal to the total number of processing resources included in the terminal minus a second value, the second value depending on the number of processing resources already occupied by the terminal; whether the second value is equal to the number of processing resources already occupied by the terminal depends on whether the first channel information block is generated based on inference. The method in the base station according to claim 9, characterized in that, When the first channel information is generated based on inference, the second value is equal to the number of processing resources already occupied by the terminal plus the first parameter; when the first channel information is not generated based on inference, the second value is equal to the number of processing resources already occupied by the terminal. The method in the base station according to claim 10, characterized in that, The first parameter is the amount of reserved processing resources, which are used for the generation of channel information that is not generated based on inference. The method in the base station according to claim 10 or 11 is characterized in that, include: Send the first information block; The first information block is used to indicate the first parameter. The method in the base station according to claim 12, characterized in that, include: Receive the second information block; The second information block is used to trigger the reconfiguration of the first parameter. The method in the base station according to claim 13 is characterized in that, 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. The terminal calculates a performance parameter for each of the M configuration messages; the calculation of the performance parameter depends on the measurement of the RS resource group indicated by the corresponding configuration message; the second information block depends on the performance parameter. The method in the base station according to any one of claims 9 to 14 is characterized in that, The first value depends on whether the first channel information block is generated based on inference, and the priority associated with the first channel information block does not depend on whether the first channel information block is generated based on inference. 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 9-15.

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