Channel information generation method and apparatus used in node for wireless communication

Abstract

Disclosed in the present application are a channel information generation method and apparatus used in a node for wireless communication. The method comprises: a first node receiving a first report configuration; and sending a first channel information block, wherein the first report configuration is used for configuring the report of the first channel information block, and at least one processing resource occupied by the generation of the first channel information block belongs to one of a first resource group or a second resource group; whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on whether the first channel information block is generated on the basis of inference; and it is only when the first channel information block is not generated on the basis of inference that the at least one processing resource occupied by the generation of the first channel information block belongs solely to the second resource group. The present application is applicable to more scenarios and terminals, and improves the accuracy of channel information.

Description

A method and apparatus for generating channel information in a node for wireless communication.

[0001] This application claims priority to Chinese Patent Application No. 202411436710.9, filed on October 14, 2024, entitled "A Method and Apparatus for Generating Channel Information in a Node for Wireless Communication", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to transmission methods and apparatus in wireless communication systems, and more particularly to schemes and apparatus for generating channel information in wireless communication systems. Background Technology

[0003] In traditional wireless communication, the UE (User Equipment) calculates CSI (channel state information) by measuring downlink reference signals. The CSI includes, but is not limited to, one or more of CRI (Channel state information-reference signal resource indicator), RI (Rank indicator), PMI (Precoding Matrix indicator), or CQI (Channel quality indicator).

[0004] With the adoption of new technologies, the increase in the number of antennas, the diversification of application scenarios, and the increasing demands on system performance, traditional measurement and reporting methods incur significant redundancy overhead. Therefore, in NR R (release) 18, research on AI (Artificial Intelligence) / ML (Machine Learning) technologies was initiated to explore their impact on system performance and design. Compared to traditional processing methods, AI / ML offers advantages such as training-based and deployment-required features. Furthermore, AI / ML is a key candidate technology for future 6G communications. Once AI / ML functionality is introduced, existing channel information-related measurement mechanisms, generation and / or reporting mechanisms, and related configuration signaling may become inadequate to meet the demands of AI / ML. Summary of the Invention

[0005] The applicant discovered through research that generating channel information requires certain processing resources. Typically, the transmitting and receiving ends need a consistent understanding of these resource usages. Therefore, determining the required processing resources is a key issue that needs to be addressed. To address this issue, this application discloses a solution. It should be noted that while many embodiments of this application are geared towards AI / ML, this application is also applicable to other solutions, such as traditional channel information reporting schemes. Furthermore, adopting a unified solution across different scenarios (including but not limited to AI / ML-based schemes and traditional information reporting schemes) helps reduce hardware complexity and cost. Where there is no conflict, the embodiments and features in the embodiments of the first node of this application can be applied to the second node, and vice versa. Where there is no conflict, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other.

[0006] As an example, the interpretation of terms in this application is based on the definitions in the 3GPP specification protocol TS38 series.

[0007] As an example, the interpretation of the terms in this application is based on the definitions in the 3GPP specification protocol TS28 series.

[0008] This application discloses a method used in a first node of wireless communication, comprising:

[0009] Receive the first reported configuration; send the first channel information block;

[0010] Wherein, the first reporting configuration is used to configure the reporting of the first channel information block. The generation of the first channel information block occupies at least one processing resource. The at least one processing resource occupied by the generation of the first channel information block belongs to one of a first resource group or a second resource group. The first resource group includes one or more processing resources in the first node, and the second resource group includes one or more processing resources in the first node. Whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on whether the first channel information block is generated based on inference. Only when the first channel information block is not generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0011] As an example, the advantages of the above method include ensuring that the sending and receiving ends have a consistent understanding of the processing resource usage.

[0012] As an example, the advantages of the above method include: better adaptability to various application scenarios or terminals.

[0013] As an example, the advantages of the above method include: high flexibility and strong adaptability.

[0014] As an example, the advantages of the above method include: better adaptability to various processing capabilities.

[0015] As an example, the advantages of the above method include: better adaptability to various different terminal capabilities.

[0016] As an example, the advantages of the above method include: better adaptability to various types of channel information reporting, high flexibility, and strong adaptability.

[0017] As an example, the advantages of the above method include: better adaptability to various processing capabilities, better adaptability to various application scenarios or terminals, high flexibility, and strong adaptability.

[0018] As one example, the first node is a terminal.

[0019] As one example, the first node is a user equipment.

[0020] As one example, the user equipment is a terminal.

[0021] As an example, the first node is a relay node.

[0022] According to one aspect of this application, when the first channel information block is generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the first resource group.

[0023] As an example, the advantages of the above method include: high adaptability and ease of implementation.

[0024] According to one aspect of this application, when the first channel information block is generated based on inference, the candidate range of the resource group to which the at least one processing resource occupied by the generation of the first channel information block belongs includes the first resource group and the second resource group.

[0025] As an example, the advantages of the above method include: the generation of the first channel information block can occupy the first resource group or the second resource group, which is highly flexible and adaptable.

[0026] According to one aspect of this application, the first channel information block is generated based on inference; the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group only when the reported quantity included in the first channel information block belongs to a first reported quantity set; the first reported quantity set includes one or more reported quantities.

[0027] As an example, the feature of the above method is that the processing resources occupied by the generation of the first channel information block are determined based on whether the first channel information block belongs to the first reporting set.

[0028] As an example, the advantages of the above method include: minimal changes to existing standards and good backward compatibility.

[0029] According to one aspect of this application, the first channel information block is generated based on inference;

[0030] The first channel information block is generated based on inference and includes the first identifier corresponding to the generation of the first channel information block;

[0031] Whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on the first identifier.

[0032] As an example, the advantages of the above method include: whether the channel information generated based on inference occupies the processing resources in the first resource group or the second resource group is determined per (per) identifier; it is applicable to different scenarios and has high flexibility.

[0033] According to one aspect of this application, the first channel information block is generated based on inference; whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group is configurable.

[0034] As an example, the advantages of the above method include: the base station can flexibly control / adjust the usage of processing resources, and it also ensures consistency of understanding between the transmitting and receiving ends.

[0035] According to one aspect of this application, the generation of the first channel information block corresponds to a first identifier; higher-level parameters indicate whether the generation of channel information corresponding to the first identifier occupies processing resources in the first resource group or occupies processing resources in the second resource group.

[0036] As an example, the advantages of the above method include: by indicating the resource occupancy status through the higher-level parameters, consistent understanding between the sending and receiving ends is ensured.

[0037] According to one aspect of this application, it includes:

[0038] Send the first information block;

[0039] The first channel information block is generated based on inference; the first information block indicates whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group.

[0040] As an example, the advantages of the above method include: the UE can control / adjust the usage of processing resources, better adapt to various processing capabilities, have high flexibility and adaptability, and also ensure consistent understanding between the transmitting and receiving ends.

[0041] According to one aspect of this application, the generation of the first channel information block corresponds to a first identifier; the first information block indicates whether the generation of channel information corresponding to the first identifier occupies processing resources in the first resource group or occupies processing resources in the second resource group.

[0042] As an example, the advantages of the above method include: better adaptability to various application scenarios or terminals.

[0043] According to one aspect of this application, only the first resource group and the second resource group include one or more storage resources in the first node.

[0044] As an example, the advantages of the above method include good backward compatibility.

[0045] According to one aspect of this application, it includes:

[0046] Receive RS in the first resource set;

[0047] The first resource set includes one or more RS resources, and the first resource set is used for at least one of the channel measurement or interference measurement of the first channel information block.

[0048] As an example, the advantages of the above method include good backward compatibility.

[0049] According to one aspect of this application, a terminal includes:

[0050] One or more processors and memory;

[0051] The memory is coupled to the one or more processors and is used to store computer program code, which includes computer instructions. The one or more processors invoke the computer instructions to cause the terminal to execute the method in the first node.

[0052] This application discloses a method used in a second node for wireless communication, comprising:

[0053] Send the first reporting configuration; receive the first channel information block;

[0054] Wherein, the first reporting configuration is used to configure the reporting of the first channel information block. The generation of the first channel information block occupies at least one processing resource. The at least one processing resource occupied by the generation of the first channel information block belongs to one of a first resource group or a second resource group. The first resource group includes one or more processing resources of the senders of the first channel information block, and the second resource group includes one or more processing resources of the senders of the first channel information block. Whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on whether the first channel information block is generated based on inference. Only when the first channel information block is not generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0055] According to one aspect of this application, when the first channel information block is generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the first resource group.

[0056] According to one aspect of this application, when the first channel information block is generated based on inference, the candidate range of the resource group to which the at least one processing resource occupied by the generation of the first channel information block belongs includes the first resource group and the second resource group.

[0057] According to one aspect of this application, the first channel information block is generated based on inference; the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group only when the reported quantity included in the first channel information block belongs to a first reported quantity set; the first reported quantity set includes one or more reported quantities.

[0058] According to one aspect of this application, the first channel information block is generated based on inference;

[0059] The first channel information block is generated based on inference and includes the first identifier corresponding to the generation of the first channel information block;

[0060] Whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on the first identifier.

[0061] According to one aspect of this application, the first channel information block is generated based on inference; whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group is configurable.

[0062] According to one aspect of this application, the generation of the first channel information block corresponds to a first identifier; higher-level parameters indicate whether the generation of channel information corresponding to the first identifier occupies processing resources in the first resource group or occupies processing resources in the second resource group.

[0063] According to one aspect of this application, it includes:

[0064] Receive the first information block;

[0065] The first channel information block is generated based on inference; the first information block indicates whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group.

[0066] According to one aspect of this application, the generation of the first channel information block corresponds to a first identifier; the first information block indicates whether the generation of channel information corresponding to the first identifier occupies processing resources in the first resource group or occupies processing resources in the second resource group.

[0067] According to one aspect of this application, only the first resource group and the second resource group include one or more storage resources of the sender of the first channel information block.

[0068] According to one aspect of this application, it includes:

[0069] Send RS in the first resource set;

[0070] The first resource set includes one or more RS resources, and the first resource set is used for at least one of the channel measurement or interference measurement of the first channel information block.

[0071] According to one aspect of this application, a base station includes:

[0072] One or more processors and memory;

[0073] The memory is coupled to the one or more processors and is used to store computer program code, which includes computer instructions. The one or more processors invoke the computer instructions to cause the base station to execute the method in the second node.

[0074] This application discloses a first node used for wireless communication, comprising:

[0075] The first processor receives the first reported configuration and sends the first channel information block.

[0076] Wherein, the first reporting configuration is used to configure the reporting of the first channel information block. The generation of the first channel information block occupies at least one processing resource. The at least one processing resource occupied by the generation of the first channel information block belongs to one of a first resource group or a second resource group. The first resource group includes one or more processing resources in the first node, and the second resource group includes one or more processing resources in the first node. Whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on whether the first channel information block is generated based on inference. Only when the first channel information block is not generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0077] This application discloses a second node used for wireless communication, comprising:

[0078] The second processor sends the first reporting configuration and receives the first channel information block.

[0079] Wherein, the first reporting configuration is used to configure the reporting of the first channel information block. The generation of the first channel information block occupies at least one processing resource. The at least one processing resource occupied by the generation of the first channel information block belongs to one of a first resource group or a second resource group. The first resource group includes one or more processing resources of the senders of the first channel information block, and the second resource group includes one or more processing resources of the senders of the first channel information block. Whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on whether the first channel information block is generated based on inference. Only when the first channel information block is not generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0080] As an example, compared with conventional solutions, this application has the following advantages:

[0081] Better adaptable to various application scenarios;

[0082] Better adaptable to various processing capabilities;

[0083] Better adaptable to various different terminals;

[0084] Better adaptable to reporting various types of channel information;

[0085] High flexibility;

[0086] Highly adaptable;

[0087] Higher accuracy and real-time performance of channel information;

[0088] Enhanced reliability and robustness;

[0089] Enhanced overall system performance. Attached Figure Description

[0090] 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:

[0091] Figure 1 shows a flowchart of a first reporting configuration and a first channel information block according to an embodiment of this application;

[0092] Figure 2 shows a schematic diagram of a network architecture according to an embodiment of this application;

[0093] 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;

[0094] Figure 4 shows a schematic diagram of a first communication device and a second communication device according to an embodiment of this application;

[0095] Figure 5 illustrates a flowchart of a transmission process according to an embodiment of this application;

[0096] Figure 6 illustrates a schematic diagram of the relationship between a first channel information block generated based on inference and a first resource group or a second resource group according to an embodiment of this application;

[0097] Figure 7 illustrates a schematic diagram of the relationship between a first channel information block generated based on inference and a first resource group or a second resource group according to another embodiment of this application;

[0098] Figure 8 shows a schematic diagram of the relationship between a first channel information block generated based on inference and a first resource group or a second resource group according to yet another embodiment of this application;

[0099] Figure 9 illustrates a schematic diagram of a first channel information block generated based on inference according to an embodiment of this application;

[0100] Figure 10 shows a schematic diagram of the processing resources occupied by the generation of a first channel information block according to an embodiment of this application;

[0101] Figures 11A-11C respectively show schematic diagrams of the generation of a first channel information block corresponding to a first identifier according to an embodiment of this application;

[0102] Figure 12 illustrates a schematic diagram of the generation of channel information corresponding to a first identifier by higher-level parameter indication according to an embodiment of this application;

[0103] Figure 13 shows a schematic diagram of a first information block according to an embodiment of this application;

[0104] Figure 14 shows a schematic diagram of the generation of channel information corresponding to a first identifier in a first information block according to an embodiment of the present application;

[0105] Figures 15A-15C respectively show schematic diagrams of a first resource group and a second resource group according to an embodiment of this application;

[0106] Figure 16 shows a schematic diagram of a first resource set according to an embodiment of this application;

[0107] Figures 17A and 17B respectively illustrate schematic diagrams of the deployment of the first node in a first operation according to an embodiment of this application;

[0108] Figure 18 illustrates a schematic diagram of the deployment of AI / ML functions in a RAN (Radio Access Network) domain according to an embodiment of this application;

[0109] Figure 19 shows a schematic diagram of the AI / ML function deployment of a UE according to an embodiment of this application;

[0110] Figure 20 shows a schematic diagram of a processing system based on artificial intelligence or machine learning according to an embodiment of this application;

[0111] Figure 21 shows a structural block diagram of a processing apparatus for a first node according to an embodiment of the present application;

[0112] Figure 22 shows a structural block diagram of a processing apparatus for a second node according to an embodiment of the present application. Detailed Implementation

[0113] 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, such as, but not limited to, the embodiments in Figure 1 and the embodiments in Figures 5-22, the embodiments in Figure 5 and the embodiments in Figures 6-22, etc.

[0114] Example 1

[0115] Example 1 illustrates a flowchart of a first reporting configuration and a first channel information block 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.

[0116] In Embodiment 1, the first node receives a first reporting configuration in step 101 and sends a first channel information block in step 102. The first reporting configuration is used to configure the reporting of the first channel information block. The generation of the first channel information block occupies at least one processing resource. The at least one processing resource occupied by the generation of the first channel information block belongs to either a first resource group or a second resource group. The first resource group includes one or more processing resources in the first node, and the second resource group includes one or more processing resources in the first node. Whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on whether the first channel information block is generated based on inference. Only when the first channel information block is not generated based on inference does the at least one processing resource occupied by the generation of the first channel information block belong only to the second resource group.

[0117] Typically, the generation of the first channel information block occupies M processing resources, where M is a positive integer; where,

[0118] The number of unoccupied processing resources in the first resource group shall not be less than M, and the generation of the first channel information block occupies M processing resources in the first resource group; or, the number of unoccupied processing resources in the second resource group shall not be less than M, and the generation of the first channel information block occupies M processing resources in the second resource group.

[0119] As one embodiment, an unoccupied processing resource includes: a processing resource not being used for at least one of processing, computation, or inference.

[0120] As an example, a processing resource being occupied includes: a processing resource being used for at least one of processing, computation, or inference.

[0121] As one example, a processing resource being occupied includes: a processing resource not being idle.

[0122] As one example, an unoccupied processing resource includes: a processing resource being idle.

[0123] As an example, a processing resource being occupied includes: a processing resource being used for at least one of computation or inference.

[0124] As an example, an unoccupied processing resource includes: a processing resource not being used for at least one of computation or inference.

[0125] In the above method, the unoccupied processing resources are those that are not occupied when it is determined that the generation of the first channel information block occupies the processing resources. The resource group occupied by the generation of the first channel information block must satisfy the following condition: the number of unoccupied processing resources included must not be less than the number of processing resources required for the generation of the first channel information block.

[0126] As an example, the first reported configuration is carried by higher layer signaling.

[0127] As an example, the first reported configuration is carried by RRC (Radio Resource Control) signaling.

[0128] As an example, the first reporting configuration includes some or all of the fields in one or more RRC IEs (Information Elements).

[0129] As one example, the first reporting configuration includes some or all of the domains in an IE CSI-ReportConfig.

[0130] As one example, the first reported configuration includes some or all of the domains in IE ServingCellConfig.

[0131] As one example, the first reporting configuration includes some or all of the domains in IE CSI-MeasConfig.

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

[0133] As one example, the first reported configuration includes some or all of the domains in IE ServingCellConfig.

[0134] 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.

[0135] 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.

[0136] As a sub-implementation of the above embodiments, the second resource set includes one or more RS resources.

[0137] As a sub-implementation of the above embodiments, the resources in the second resource set include at least one of antenna port, TCI status, QCL information, time-frequency resources, time-frequency code resources, beam, RS resources, vector, or matrix.

[0138] As an example, the reporting type indicates at least one of periodic reporting, semi-persistent reporting, non-periodic reporting, or event-triggered reporting.

[0139] As an example, the reporting type indicates at least one of periodic reporting, semi-persistent reporting, or non-periodic reporting.

[0140] As an example, the first channel information block includes CSI (channel state information).

[0141] As an example, the CSI includes beam information.

[0142] As an example, the CSI includes compressed CSI.

[0143] As an example, the compressed CSI is based on non-codebook channel information.

[0144] As an 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.

[0145] As an example, the compressed CSI is channel information based on artificial intelligence or machine learning.

[0146] As an example, the compressed CSI is based on channel information from a neural network.

[0147] As an example, the compressed CSI is based on channel information from CNN (Conventional Neural Networks).

[0148] As one embodiment, the first channel information block includes a channel matrix.

[0149] As one embodiment, the first channel information block includes at least one of the channel's feature values ​​or feature vectors.

[0150] As one embodiment, the first channel information block includes one of beam information, predicted CSI, or compressed CSI.

[0151] 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.

[0152] 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.

[0153] As an example, the first channel information block is based on a non-codebook.

[0154] As one embodiment, the first channel information block includes a resource indication, which is used to indicate beam or RS (reference signal) resources.

[0155] 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.

[0156] As one embodiment, the beam information includes a resource indicator, which is used to indicate a beam or RS resource.

[0157] As an example, the beam information includes at least one of a resource indicator or RSRP (reference signal received power), wherein the resource indicator is used to indicate the beam or RS resource.

[0158] As an example, the resource indication is used to indicate one of beam, CSI-RS (Channel State Information Reference Signal) resources, or synchronization signal resources.

[0159] As an example, the resource indicator is a CRI (CSI-RS Resource Indicator) or an SS / PBCH Block Resource indicator (SSBRI).

[0160] As one embodiment, the synchronization signal resources include at least the resources occupied by the synchronization signal.

[0161] As an example, the synchronization signal resource is an SSB (Synchronization Signal Block).

[0162] As an example, the synchronization signal resource is an SS / PBCH (Synchronization Signal / Physical Broadcast Channel) block resource.

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] As one embodiment, the generation of the first channel information block includes: calculation or inference of the first channel information block.

[0168] 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.

[0169] 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.

[0170] 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.

[0171] 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.

[0172] As an example, the generation of the first channel information block occupies M processing resources, where M is a positive integer.

[0173] As an example, the first node reports the total number of processing resources in the first resource group and the total number of processing resources in the second resource group in its capability information.

[0174] As one embodiment, the processing resources are used for at least one of processing, computation, or inference.

[0175] As an example, the processing resources are used for at least addition and multiplication operations.

[0176] As one example, the processing resources are used for at least convolution operations.

[0177] As an example, a processing resource is a processing unit.

[0178] As an example, a processing resource belongs to a processing unit.

[0179] As one example, the processing resources include computing resources.

[0180] As an example, the reasoning includes AI reasoning.

[0181] 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.

[0182] 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 model.

[0183] 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.

[0184] 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.

[0185] 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).

[0186] 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.

[0187] 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.

[0188] 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).

[0189] 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.

[0190] As an example, in 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:

[0191] 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.

[0192] 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.

[0193] In one implementation, measurement interference is also input into the AI ​​model.

[0194] 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.

[0195] 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.

[0196] 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.

[0197] 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.

[0198] As an 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.

[0199] 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.

[0200] 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).

[0201] 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.

[0202] 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.

[0203] 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).

[0204] 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.

[0205] 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:

[0206] 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×l Under 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.

[0207] As an example, the first identifier is a non-negative integer.

[0208] As an example, the first identifier is a string.

[0209] As an example, the first identifier is different from the reporting configuration identifier of the first channel information block.

[0210] As an example, the first identifier is used to identify the AI ​​model.

[0211] As an example, the first identifier is used to identify an AI model, and the first channel information block is generated based on inference using the AI ​​model identified by the first identifier.

[0212] As an example, the first identifier is used by the first node to identify an AI model.

[0213] As an example, the first identifier is used by the first node to determine the AI ​​model used in the first operation of this application.

[0214] As an example, the first identifier is used to identify the AI ​​entity.

[0215] As an example, the first identifier is used to identify AI functionality.

[0216] As an example, the advantages of the above method include that identifying an AI model / entity / function through the first identifier simplifies the design and unifies the understanding of different AI entities or functions across multiple nodes.

[0217] As one embodiment, the first identifier is used to identify or indicate a set of resources.

[0218] As one embodiment, the first identifier is used to identify or indicate a set of resources, the measurement of which is used to obtain a training dataset.

[0219] As one embodiment, the first identifier is used to identify or indicate a resource set, the resource set identified or indicated by the first identifier including one or more RS resources.

[0220] As an example, the first identifier is used to identify or indicate the training dataset.

[0221] As an example, the benefits of the above method include identifying the inference generated by an AI training or AI training dataset by identifying the AI ​​training or AI training dataset, establishing consensus among different AI functions, and further simplifying the design.

[0222] As an example, the first type of identifier is a non-negative integer.

[0223] As an example, the first type of identifier is a string.

[0224] As an example, the first type of identifier is different from the reporting configuration identifier of the first channel information block.

[0225] As an example, the first type of identifier is used to identify AI models.

[0226] As an example, the first type of identifier is used to identify the AI ​​model, and the channel information generated based on inference is generated based on inference using the AI ​​model identified by the first type of identifier.

[0227] As an example, the first type of identifier is used by the first node to identify an AI model.

[0228] As an example, the first type of identifier is used to identify AI entities.

[0229] As an example, the first type of identifier is used to identify AI functions.

[0230] As an example, the advantages of the above method include that identifying an AI model / entity / function through the first type of identifier simplifies the design and unifies the understanding of different AI entities or functions across multiple nodes.

[0231] As an example, the first type of identifier is used to identify or indicate a set of resources.

[0232] As one embodiment, the first type of identifier is used to identify or indicate a set of resources, the measurement of which is used to obtain a training dataset.

[0233] As one embodiment, the first type of identifier is used to identify or indicate a resource set, the resource set identified or indicated by the first type of identifier including one or more RS resources.

[0234] As an example, the first type of identifier is used to identify or indicate the training dataset.

[0235] As an example, the benefits of the above method include identifying the inference generated by an AI training or AI training dataset by identifying the AI ​​training or AI training dataset, establishing consensus among different AI functions, and further simplifying the design.

[0236] Example 2

[0237] Example 2 illustrates a schematic diagram of a network architecture according to an embodiment of this application, as shown in Figure 2.

[0238] Figure 2 illustrates network architecture 200. Network architecture 200 is a 5G NR (New Radio) / LTE (Long-Term Evolution) / LTE-A (Long-Term Evolution Advanced) system, or a 5G+ network architecture, or a 6G network architecture, or a network architecture adopted in future evolutions by 3GPP; network architecture 200 may be referred to as 5GS (5G System) / EPS (Evolved Packet System), or 6GS (6G System); network architecture 200 includes at least one of UE (User Equipment) 201, RAN (Radio Access Network) 202, core network 210, HSS (Home Subscriber Server) / UDM (Unified Data Management) 220, and Internet service 230. The network architecture 200 can interconnect with other access networks, but these entities / interfaces are not shown for simplicity. As shown, the network architecture 200 provides packet-switched 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 includes node 203. The RAN may also include other nodes 204. Node 203 provides user and control plane protocol termination toward UE 201. Node 203 may be connected to other nodes 204 via an Xn interface (e.g., backhaul) / X2 interface. Node 203 may also be referred to as a base station, base transceiver station, radio base station, radio transceiver, transceiver function, basic service set (BSS), extended service set (ESS), TRP (transmitter-receiver node), or some other suitable term. The core network 210 is a 5GC (5G Core Network) / EPC (Evolved Packet Core), or the core network 210 is a 6GC; node 203 provides UE 201 with an access point to the core network 210.Examples of UE201 include cellular phones, smartphones, Session Initiation Protocol (SIP) phones, laptops, personal digital assistants (PDAs), satellite radios, non-terrestrial base station communications, satellite mobile communications, global positioning systems, multimedia devices, video devices, digital audio players (e.g., MP3 players), cameras, game consoles, drones, aircraft, narrowband IoT 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 UE201 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, wireless terminal, remote terminal, handheld device, user agent, mobile client, client, or any other suitable term. Node 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. Internet services 230 include operator-compliant Internet protocol services, which may specifically include Internet, intranet, IMS (IP Multimedia Subsystem), and packet switching services.

[0239] As an example, the first node includes the UE201.

[0240] As one embodiment, the second node includes the node 203.

[0241] As one embodiment, the second node includes the core network 210.

[0242] As one embodiment, the second node includes the node 203 and the core network 210.

[0243] As an example, the wireless link between the UE201 and the node203 includes a cellular link.

[0244] As an example, the processing resources described in this application are in the UE201.

[0245] As an example, the storage resources described in this application are in the UE201.

[0246] As an example, the first resource group in this application is in the UE201.

[0247] As an example, the second resource group in this application is in the UE201.

[0248] As an example, the first information block is generated in the UE201.

[0249] As an example, the sender of the first information block includes the UE201.

[0250] As an example, the target recipient of the first information block includes the node 203.

[0251] As an example, the first channel information block is generated in the UE201.

[0252] As an example, the sender of the first channel information block includes the UE201.

[0253] As an example, the target receiver of the first channel information block includes the node 203.

[0254] As an example, the first reporting configuration is generated in node 203.

[0255] As an example, the sender of the first reporting configuration includes the node 203.

[0256] As an example, the target recipient of the first reporting configuration includes the UE201.

[0257] Example 3

[0258] 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.

[0259] Example 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for a user plane and control plane according to this application, as shown in Figure 3. Figure 3 is a schematic diagram illustrating an embodiment of a radio protocol architecture for a user plane 350 and a control plane 300. Figure 3 shows the radio protocol architecture for the control plane 300 between a first communication node device (UE, gNB, or RSU in V2X) and a second communication node device (gNB, UE, or RSU in V2X), or between two UEs, using three layers: Layer 1, Layer 2, and Layer 3. Layer 1 (L1 layer) is the lowest layer and implements various PHY (physical layer) signal processing functions. Layer 1 will be referred to herein as PHY 301. Layer 2 (L2 layer) 305 is above PHY 301 and is responsible for the link between the first communication node device and the second communication node device, or between two UEs. Layer 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 communication 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. 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 among the first communication node devices. Furthermore, the MAC sublayer 302 handles HARQ operations. In the control plane 300, the Radio Resource Control (RRC) sublayer 306 of Layer 3 (L3) is responsible for acquiring radio resources (i.e., radio bearers) and configuring the lower layers using RRC signaling between the second and first communication node devices. The user plane 350's radio protocol architecture includes Layer 1 (L1) and Layer 2 (L2). The radio protocol architecture for the first and second communication node devices in the user plane 350 is largely the same as the corresponding layers and sublayers in the control plane 300 for Physical Layer 351, PDCP sublayer 354 in L2 Layer 355, RLC sublayer 353 in L2 Layer 355, and MAC sublayer 352 in L2 Layer 355. However, PDCP sublayer 354 also provides header compression for upper layer data packets to reduce radio transmission overhead.The L2 layer 355 in the user plane 350 also includes an SDAP (Service Data Adaptation Protocol) sublayer 356, which is responsible for mapping between QoS streams and data radio bearers (DRBs) to support service diversity. Although not illustrated, the first communication node device may have several upper layers above the L2 layer 355, including a network layer (e.g., IP layer) terminating at the P-GW on the network side and an application layer terminating at the other end of the connection (e.g., a remote UE, server, etc.).

[0260] As an example, the wireless protocol architecture in Figure 3 is applicable to the first node.

[0261] As an example, the wireless protocol architecture in Figure 3 is applicable to the second node.

[0262] As an example, the higher layer mentioned in this application refers to the layer above the physical layer.

[0263] As an example, the first information block is generated in the RRC sublayer 306.

[0264] As an example, the first information block is generated in the PHY301 or the PHY351.

[0265] As an example, the first information block is generated in the MAC sublayer 302 or the MAC sublayer 352.

[0266] As an example, the first reporting configuration is generated in the RRC sublayer 306.

[0267] As an example, the reference signal in the first resource set is generated in the PHY301 or the PHY351.

[0268] As an example, the reference signal in the second resource set is generated in the PHY301 or the PHY351.

[0269] As an example, the first channel information block is generated in the PHY301 or the PHY351.

[0270] Example 4

[0271] 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.

[0272] 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.

[0273] 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.

[0274] 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 layer functionality. In DL (Downlink), 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 layer (i.e., physical layer). Transmit processor 416 performs encoding and interleaving to facilitate forward error correction (FEC) at the second communication device 450, and constellation mapping based on various modulation schemes (e.g., binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), M-phase shift keying (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... 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.

[0275] 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 signal processing functions of the L1 layer. 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 over the physical channel by the first communication device 410. The upper-layer data and control signals are then provided to the controller / processor 459. The controller / processor 459 implements the functions of Layer 2 (L2). 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 (Layered Logic), 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 Layer 2. Various control signals may also be provided to Layer 3 (L3) for L3 processing. The controller / processor 459 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operation.

[0276] 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 the L2 layer. 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 layer 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.

[0277] 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 layer functions. The controller / processor 475 implements the L2 layer functions. The controller / processor 475 may be associated with a memory 476 that stores 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.

[0278] 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 means at least: receiving a first reporting configuration; transmitting a first channel information block; wherein the first reporting configuration is used to configure the reporting of the first channel information block, the generation of the first channel information block occupies at least one processing resource, the at least one processing resource occupied by the generation of the first channel information block belongs to one of a first resource group or a second resource group, the first resource group including one or more processing resources in the first node, and the second resource group including one or more processing resources in the first node; whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on whether the first channel information block is generated based on inference; only when the first channel information block is not generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0279] As one embodiment, the second communication device 450 includes: a memory storing a computer-readable instruction program, which, when executed by at least one processor, produces actions including: receiving a first reporting configuration; and sending a first channel information block; wherein the first reporting configuration is used to configure the reporting of the first channel information block, the generation of the first channel information block occupies at least one processing resource, the at least one processing resource occupied by the generation of the first channel information block belongs to one of a first resource group or a second resource group, the first resource group including one or more processing resources in the first node, and the second resource group including one or more processing resources in the first node; whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on whether the first channel information block is generated based on inference; only when the first channel information block is not generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0280] 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 means at least: transmitting a first reporting configuration; receiving a first channel information block; wherein the first reporting configuration is used to configure the reporting of the first channel information block, the generation of the first channel information block occupies at least one processing resource, the at least one processing resource occupied by the generation of the first channel information block belongs to one of a first resource group or a second resource group, the first resource group including one or more processing resources in the first node, and the second resource group including one or more processing resources in the first node; whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on whether the first channel information block is generated based on inference; only when the first channel information block is not generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0281] As one embodiment, the first communication device 410 includes: a memory storing a computer-readable instruction program, which, when executed by at least one processor, generates actions including: sending a first reporting configuration; and receiving a first channel information block; wherein the first reporting configuration is used to configure the reporting of the first channel information block, the generation of the first channel information block occupies at least one processing resource, the at least one processing resource occupied by the generation of the first channel information block belongs to one of a first resource group or a second resource group, the first resource group including one or more processing resources in the first node, and the second resource group including one or more processing resources in the first node; whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on whether the first channel information block is generated based on inference; only when the first channel information block is not generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0282] As an example, the first node in this application includes the second communication device 450.

[0283] As an example, the second node in this application includes the first communication device 410.

[0284] As an example, at least one of {the antenna 452, the receiver 454, the receiving processor 456, the multi-antenna receiving 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; at least one of {the antenna 420, the transmitter 418, the transmitting processor 416, the multi-antenna transmitting processor 471, the controller / processor 475, and the memory 476} is used to transmit the first reporting configuration in this application.

[0285] As an example, at least one of {the antenna 452, the receiver 454, the receiving processor 456, the multi-antenna receiving processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to receive the reference signal in the first resource set of this application; at least one of {the antenna 420, the transmitter 418, the transmitting processor 416, the multi-antenna transmitting processor 471, the controller / processor 475, and the memory 476} is used to transmit the reference signal in the first resource set of this application.

[0286] As one embodiment, at least one of {the antenna 452, the receiver 454, the receiving processor 456, the multi-antenna receiving processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to receive the reference signal in the second resource set of this application; at least one of {the antenna 420, the transmitter 418, the transmitting processor 416, the multi-antenna transmitting processor 471, the controller / processor 475, and the memory 476} is used to transmit the reference signal in the second resource set of this application.

[0287] As an example, at least one of {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} is used to transmit the first information block in this application; 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 information block in this application.

[0288] As an example, at least one of the following is used in the generation of the first channel information block in this application: {the antenna 452, the transmitter / receiver 454, the transmitter processor 468, the multi-antenna transmitter processor 457, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467}.

[0289] As an example, at least one of the following is used in the first operation of this application: {the antenna 452, the transmitter / receiver 454, the transmitter processor 468, the multi-antenna transmitter processor 457, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467}.

[0290] As an example, at least one of {the antenna 452, the transmitter 454, the transmitter processor 468, the multi-antenna transmitter processor 457, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467} is used in the first operation of this application; at least one of {the antenna 420, the receiver 418, the receiver processor 470, the multi-antenna receiver processor 472, the transmitter processor 416, the multi-antenna transmitter processor 471, the controller / processor 475, and the memory 476} is used in the second operation of this application.

[0291] As an example, at least one of {the antenna 452, the transmitter 454, the transmitter processor 468, the multi-antenna transmitter processor 457, 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 transmit the first channel information block in this application; at least one of {the antenna 420, the receiver 418, the receiver processor 470, the multi-antenna receiver processor 472, the transmitter processor 416, the multi-antenna transmitter processor 471, the controller / processor 475, and the memory 476} is used to receive the first channel information block in this application.

[0292] Example 5

[0293] Example 5 illustrates a transmission flowchart according to an embodiment of this application; as shown in Figure 5. In Figure 5, the second node N1 and the first node U1 are communication nodes transmitting via an air interface. In Figure 5, the steps in blocks F51 to F56 are optional.

[0294] For the second node N1, the second operation is deployed in step S5101; the first information block is received in step S5102; the first reporting configuration is sent in step S511; RS is sent in the first resource set in step S5103; the second operation is executed in step S5104; and the first channel information block is received in step S512.

[0295] For the first node U1, the first operation is deployed in step S5201; the first information block is sent in step S5202; the first reported configuration is received in step S521; RS is received in the first resource set in step S5203; the first operation is executed in step S5204; and the first channel information block is sent in step S522.

[0296] In Embodiment 5, the first reporting configuration is used to configure the reporting of the first channel information block. The generation of the first channel information block occupies at least one processing resource. The at least one processing resource occupied by the generation of the first channel information block belongs to one of a first resource group or a second resource group. The first resource group includes one or more processing resources in the first node, and the second resource group includes one or more processing resources in the first node. Whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on whether the first channel information block is generated based on inference. Only when the first channel information block is not generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0297] As an example, the first node U1 is the first node in this application.

[0298] As an example, the second node N1 is the second node in this application.

[0299] As one embodiment, the air interface between the second node N1 and the first node U1 includes a wireless interface between the base station equipment and the user equipment.

[0300] As one embodiment, the air interface between the second node N1 and the first node U1 includes a wireless interface between the relay node device and the user equipment.

[0301] As one embodiment, the air interface between the second node N1 and the first node U1 includes a wireless interface between user equipment and user equipment.

[0302] As one example, the second node N1 is the serving cell sustaining base station of the first node U1.

[0303] As an example, the transmission of the first reported configuration is later than the transmission of the first information block.

[0304] As an example, the steps in dashed box F53 are present, and the method described above for use in the first node of wireless communication includes: transmitting a first information block; wherein the first channel information block is generated based on inference; the first information block indicates whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group.

[0305] As an example, the steps in dashed box F53 are present, and the method described above for use in the second node of wireless communication includes: receiving a first information block; wherein the first channel information block is generated based on inference; the first information block indicates whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group.

[0306] As an example, the steps in dashed box F54 are present, and the method used in the first node for wireless communication includes: receiving RS in a first resource set; wherein 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.

[0307] As an example, the steps in dashed box F54 are present, and the method described above for use in the second node of wireless communication includes: transmitting RS in a first resource set; wherein 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.

[0308] As an example, the steps in the dashed box F52 are present, and the method described above for the first node used in wireless communication includes: deploying a first operation.

[0309] As an example, the steps in dashed box F56 are present, and the method described above for use in the first node of wireless communication includes: performing a first operation.

[0310] As an example, the first channel information block is generated based on inference, the first node performs a first operation, and the first channel information block depends on the output of the first operation.

[0311] As an example, the first node deploys the first operation.

[0312] As one embodiment, the deployment of the first operation includes: obtaining the first operation.

[0313] As an example, the deployment first operation includes: loading the first operation.

[0314] As one embodiment, the deployment of the first operation includes: submitting a request to load the first operation.

[0315] As an example, the first operation is used for CSI prediction, beam prediction, or CSI compression.

[0316] As an example, the first operation is used for beam prediction or CSI prediction.

[0317] As one embodiment, the first node performs a first operation, and the second node performs a second operation; wherein the first channel information block is generated based on inference.

[0318] As an example, the steps in dashed box F51 are present, and the method described above for the second node used in wireless communication includes: deploying a second operation.

[0319] As an example, the steps in the dashed box F55 are present, and the method described above for the second node used in wireless communication includes: performing a second operation.

[0320] As one embodiment, the second node performs a second operation; wherein the first channel information block is generated based on inference, the first node performs a first operation, the output of the first operation includes a first CSI, the first channel information block carries the first CSI, and the first CSI is used as input to the second operation to generate a second CSI.

[0321] As an example, the second node deploys the second operation.

[0322] As one embodiment, the deployment of the second operation includes: obtaining the second operation.

[0323] As an example, the deployment of the second operation includes: loading the second operation.

[0324] As one embodiment, the deployment of the second operation includes: submitting a request to load the second operation.

[0325] As an example, the first operation is used for CSI compression, and the second operation is used for CSI recovery.

[0326] As an example, the first channel information block is generated based on inference, the output of the first operation includes a first CSI, the first channel information block carries the first CSI, and the first CSI is used by the second node as input to the second operation to generate a second CSI.

[0327] As an example, the execution of the second operation is later than the execution of the first operation.

[0328] As an example, the first reported configuration is transmitted on PDSCH (Physical Downlink Shared Channel).

[0329] As an example, the first channel information block is transmitted on the PUCCH (Physical Uplink Control Channel).

[0330] As an example, the first channel information block is transmitted on PUSCH (Physical Uplink Shared Channel).

[0331] As an example, the first information block is transmitted on PUCCH (Physical Uplink Control Channel).

[0332] As an example, the first information block is transmitted on PUSCH (Physical Uplink Shared Channel).

[0333] Example 6

[0334] Example 6 illustrates a schematic diagram of the relationship between a first channel information block generated based on inference and a first resource group or a second resource group according to an embodiment of this application; as shown in Figure 6; processing resources #1, ..., processing resources #n, ... represent processing resources in the first resource group.

[0335] In Embodiment 6, when the first channel information block is generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the first resource group.

[0336] When the first channel information block is not generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group; when the first channel information block is generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the first resource group.

[0337] In the above method, channel information generated based on inference occupies only the processing resources in the first resource group, while channel information not generated based on inference occupies only the processing resources in the second resource group. The advantages include: the processing resources required for channel information generated in different ways can be different, which has high flexibility and strong adaptability.

[0338] Example 7

[0339] Example 7 illustrates a schematic diagram of the relationship between a first channel information block generated based on inference and a first resource group or a second resource group according to another embodiment of this application; as shown in Figure 7; processing resources #1, ..., processing resources #n, ... represent processing resources in the first resource group, or processing resources #1, ..., processing resources #n, ... represent processing resources in the second resource group.

[0340] In Embodiment 7, when the first channel information block is generated based on inference, the candidate range of the resource group to which the at least one processing resource occupied by the generation of the first channel information block belongs includes the first resource group and the second resource group.

[0341] When the first channel information block is not generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group; when the first channel information block is generated based on inference, the candidate range of the resource group to which the at least one processing resource occupied by the generation of the first channel information block belongs includes the first resource group and the second resource group.

[0342] In the above method, the processing resources occupied by the channel information generated based on inference can be either those in the first resource group or those in the second resource group, rather than the channel information reported based on inference only occupying the processing resources in the second resource group.

[0343] As an example, the first channel information block is generated based on inference; the generation of the first channel information block preferentially occupies processing resources in the first resource group.

[0344] As an example, the first channel information block is generated based on inference, and the generation of the first channel information block occupies M processing resources, where M is a positive integer; when the unoccupied processing resources in the first resource group are not less than M, the generation of the first channel information block occupies M processing resources in the first resource group; when the unoccupied processing resources in the first resource group are less than M, the generation of the first channel information block occupies M processing resources in the second resource group.

[0345] As an example, the first channel information block is generated based on inference; whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on the number of bits included in the first channel information block.

[0346] As an example, the first channel information block is generated based on inference; only when the number of bits included in the first channel information block is less than a first threshold, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0347] In the above method, the generation of less channel information occupies the processing resources in the second resource group, while the generation of more channel information occupies the processing resources in the first resource group. The advantages include: speeding up the generation of channel information, improving the accuracy of channel estimation, and reducing the reporting delay.

[0348] Example 8

[0349] Example 8 illustrates a schematic diagram of the relationship between a first channel information block generated based on inference and a first resource group or a second resource group according to yet another embodiment of this application; as shown in Figure 8; processing resources #1, ..., processing resources #n, ... represent processing resources in the second resource group.

[0350] In embodiment 8, the first channel information block is generated based on inference; the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group only when the reported quantity included in the first channel information block belongs to the first reported quantity set; the first reported quantity set includes one or more reported quantities.

[0351] As an example, whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on the reporting volume included in the first channel information block.

[0352] As an example, the first set of reported quantities includes at least one of resource indications or RSRPs.

[0353] As one embodiment, the first set of reported quantities includes reported quantities used for beam prediction.

[0354] As one embodiment, the first set of reported quantities includes beam information.

[0355] As one embodiment, the first channel information block includes a resource indication, which is used to indicate beam or RS (reference signal) resources.

[0356] 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.

[0357] As one embodiment, the beam information includes a resource indicator, which is used to indicate a beam or RS resource.

[0358] As an example, the beam information includes at least one of a resource indicator or RSRP (reference signal received power), wherein the resource indicator is used to indicate the beam or RS resource.

[0359] As an example, the resource indication is used to indicate one of beam, CSI-RS (Channel State Information Reference Signal) resources, or synchronization signal resources.

[0360] As an example, the resource indicator is a CRI (CSI-RS Resource Indicator) or an SS / PBCH Block Resource indicator (SSBRI).

[0361] As one embodiment, the synchronization signal resources include at least the resources occupied by the synchronization signal.

[0362] As an example, the synchronization signal resource is an SSB (Synchronization Signal Block).

[0363] As an example, the synchronization signal resource is an SS / PBCH (Synchronization Signal / Physical Broadcast Channel) block resource.

[0364] As an example, the reported amount used for CSI compression does not belong to the first reported amount set.

[0365] As an example, the reported volume used for CSI prediction does not belong to the first reported volume set.

[0366] As an example, the channel matrix is ​​not part of the first set of reported quantities.

[0367] As an example, PMI or CQI does not belong to the first set of reported quantities.

[0368] Example 9

[0369] Example 9 illustrates a schematic diagram of a first channel information block generated based on inference according to an embodiment of the present application; as shown in Figure 9.

[0370] In embodiment 9, the first channel information block is generated based on inference;

[0371] The first channel information block is generated based on inference and includes the first identifier corresponding to the generation of the first channel information block;

[0372] Whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on the first identifier.

[0373] As one embodiment, the first identifier is used to identify an AI model, and the first channel information block is generated based on inference using the AI ​​model identified by the first identifier; whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on the size of the parameters in the AI ​​model identified by the first identifier.

[0374] As a sub-implementation of the above embodiment, the at least one processing resource occupied by the generation of the first channel information block belongs to the second resource group only when the size of the parameter in the AI ​​model identified by the first identifier is less than the second threshold.

[0375] As an example, the first identifier is used to identify an AI function; when the AI ​​function identified by the first identifier is beam prediction, the at least one processing resource occupied by the generation of the first channel information block belongs to the second resource group.

[0376] As an example, the first identifier is used to identify an AI function; when the AI ​​function identified by the first identifier is CSI compression, the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group.

[0377] As an example, the first identifier is used to identify an AI function; when the AI ​​function identified by the first identifier is CSI compression, the generation of the first channel information block preferentially occupies the processing resources in the first resource group.

[0378] In the above method, whether the channel information generated based on inference occupies the processing resources in the first resource group or the second resource group is determined per (per) identifier; the advantages include: it is applicable to different AI models / entities / functions and has high flexibility.

[0379] Example 10

[0380] Example 10 illustrates a schematic diagram of the processing resources occupied by the generation of a first channel information block according to an embodiment of this application; as shown in Figure 10.

[0381] In embodiment 10, the first channel information block is generated based on inference; whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group is configurable.

[0382] As an example, the first reporting configuration indicates whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group.

[0383] As an example, unlike the first reporting configuration RRC parameter which indicates whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group.

[0384] In the above method, the base station indicates whether a channel information generated based on inference occupies the processing resources in the first resource group or the second resource group. The advantages include: the base station can flexibly control / adjust the occupancy of processing resources, and also ensures consistency of understanding between the transmitting and receiving ends.

[0385] Examples 11A-11C

[0386] Examples 11A-11C illustrate schematic diagrams of the generation of a first channel information block corresponding to a first identifier according to an embodiment of this application, as shown in Figures 11A-11C.

[0387] In embodiment 11A, the generation of the first channel information block corresponding to the first identifier includes: a first reporting configuration is used to configure the reporting of the first channel information block, and the first reporting configuration indicates the first identifier.

[0388] In the above method, the generation of the first channel information block corresponds to the first identifier of the first reporting configuration indication.

[0389] As an example, the advantages of the above method include: simplified design, and the ability to flexibly configure the corresponding first identifier for the first channel information block.

[0390] In embodiment 11B, the generation of the first channel information block corresponding to the first identifier includes: the first node or the generator of the first channel information block performs a first operation, the first channel information block depends on the output of the first operation, and the first operation corresponds to the first identifier.

[0391] As one embodiment, the generation of the first channel information block corresponding to the first identifier includes: the first node or the generator of the first channel information block performing a first operation, the first operation including reasoning, the first channel information block depending on the output of the first operation, and the first operation corresponding to the first identifier.

[0392] As an example, the first operation is based on training or AI.

[0393] As an example, the first operation includes inference.

[0394] As one example, the first operation includes an AI entity.

[0395] As an example, the first operation includes an AI entity for inference.

[0396] As an example, the first operation includes a portion of an AI entity.

[0397] As an example, the first operation includes a portion of an AI entity used for inference.

[0398] As one embodiment, the first operation includes inference for obtaining the first channel information block.

[0399] As an example, the reasoning includes AI (Artificial Intelligence) inference.

[0400] As an example, the first operation includes AI inference for obtaining CSI.

[0401] As one example, the first operation includes AI inference for obtaining channel information.

[0402] As one example, the first operation includes AI inference for obtaining information other than channel information.

[0403] As an example, the first operation is used for an AI function.

[0404] As an example, the first operation is performed by the physical layer of the first node.

[0405] As an example, the first operation is performed at a higher level than the first node.

[0406] As an example, the model for the first operation is obtained through training.

[0407] As an example, the training for the first operation is performed by the first node.

[0408] As an example, the training of the first operation is performed by the target receiver of the first channel information block.

[0409] As an example, the training for the first operation is performed by the core network.

[0410] As an example, the training of the first operation is performed by an AI training producer.

[0411] As an example, the training of the first operation is performed by the MDA (Management Data Analytics Function).

[0412] As an example, the training of the first operation is performed by the MDA function located at the first node.

[0413] As an example, the training of the first operation is performed by the MDA function of the target receiver located in the first channel information block.

[0414] As an example, the training of the first operation is performed by NWDAF (Network Data Analytics Function).

[0415] As an example, the training of the first operation is performed by the MDAS (Management Data Analytics Service) producer.

[0416] As an example, the training of the first operation is performed by the MnS (Management Service) producer.

[0417] As an example, the first operation requires deployment.

[0418] As an example, the first operation is obtained by loading.

[0419] As an example, the first operation is obtained from the serving cell of the first node.

[0420] As an example, the first operation is obtained from the sustaining base station of the serving cell of the first node.

[0421] As an example, the first node deploys the first operation.

[0422] As an example, the first operation does not require deployment.

[0423] As an example, the first operation is obtained from the core network.

[0424] As an example, the first operation is based on artificial intelligence or machine learning.

[0425] As an example, the first operation is based on a neural network.

[0426] As an example, the first operation is based on CNN (Conventional Neural Networks).

[0427] As one example, the first operation includes preprocessing.

[0428] As one example, the first operation includes post-processing.

[0429] As one example, the post-processing includes DFT.

[0430] As one example, the post-processing includes quantization.

[0431] As an example, the post-processing includes one or more of the following: angular domain to spatial domain transformation, spatial domain to angular domain transformation, time domain to frequency domain transformation, and frequency domain to time domain transformation.

[0432] As one example, the post-processing includes truncation and / or padding.

[0433] As an example, the first operation includes one or more of convolution, pooling, cascading, and activation.

[0434] As one embodiment, the first operation includes a fully connected layer.

[0435] As an example, the first operation includes a pooling layer.

[0436] As an example, the first operation includes at least one convolutional layer.

[0437] As an example, the first operation includes at least one encoding layer.

[0438] As an example, an encoding layer includes at least one convolutional layer and one pooling layer.

[0439] As an example, in a convolutional layer, at least one convolutional kernel is used to convolve the input to generate a corresponding feature map, and at least one feature map output by the convolutional layer is reshaped into a vector and input to a fully connected layer; the fully connected layer transforms the vector into an output.

[0440] As an example, some or all of the following parameters in the first operation—convolution kernel size, number of convolutional layers, convolution stride, pooling kernel size, pooling kernel stride, pooling function, activation function, and number of feature maps—are obtained through training.

[0441] As an example, some or all of the convolution kernel, pooling kernel, pooling function, activation function, parameters of the pooling function, and parameters of the activation function in the first operation are obtained through training.

[0442] As an example, the output of the first operation includes channel information.

[0443] As an example, the output of the first operation includes information other than channel information.

[0444] As an example, the output of the first operation includes a channel matrix.

[0445] As an example, the output of the first operation includes CSI.

[0446] As an example, the output of the first operation includes compressed CSI.

[0447] As an example, the output of the first operation includes non-codebook-based CSI.

[0448] As an example, the output of the first operation includes a channel impulse response.

[0449] As an example, the output of the first operation includes small-scale characteristics.

[0450] As an example, the output of the first operation is used to determine one or more precoding matrices.

[0451] As an example, the first operation includes CSI compression based on artificial intelligence or machine learning.

[0452] As an example, the first operation includes an encoder for CSI compression based on artificial intelligence or machine learning.

[0453] As an example, the first operation includes CSI prediction or CSI estimation based on artificial intelligence or machine learning.

[0454] As one example, the first operation includes beam management based on artificial intelligence or machine learning.

[0455] As one embodiment, the beam management includes at least one of beam prediction, beam switching, beam failure prediction, or beam failure recovery.

[0456] As an example, the input to the first operation includes measurements obtained based on at least one RS resource.

[0457] As an example, the input to the first operation includes channel measurements obtained based on CSI-RS resources or SS / PBCH block resources.

[0458] As an example, the input to the first operation includes interference measurements obtained based on CSI-RS resources or CSI-IM resources.

[0459] As an example, the input to the first operation includes the reception quality of at least one physical channel or physical signal.

[0460] As an example, the input to the first operation includes a matrix or vector obtained by preprocessing the channel matrix obtained from measurements based on at least one RS resource.

[0461] As one example, the AI ​​function includes AI inference functionality.

[0462] As one example, the AI ​​functionality includes AI training functionality.

[0463] As one example, the AI ​​functionality includes AI management functionality.

[0464] As one example, the AI ​​function includes AI performance monitoring.

[0465] As one example, the AI ​​includes ML (Machine Learning).

[0466] As one example, the AI ​​includes AI and ML.

[0467] As one example, the AI ​​includes AI or ML.

[0468] As an example, the preprocessing includes one or more of the following: quantization, DFT (Discrete Fourier Transform), matrix decomposition, matrix transformation or projection, spatial-to-angular-domain transformation, angular-to-spatial-domain transformation, frequency-to-time-domain transformation, time-to-frequency-domain transformation, truncation, padding, mapping, or labeling.

[0469] As an example, the preprocessing includes DFT (Discrete Fourier Transform).

[0470] As one example, the preprocessing includes one or more of matrix decomposition, matrix transformation, or projection.

[0471] As an example, the preprocessing includes one or more of the following: quantization, spatial-to-angular-domain transformation, angular-to-spatial-domain transformation, frequency-to-time-domain transformation, or time-to-frequency-domain transformation.

[0472] As one example, the preprocessing includes truncation and / or padding.

[0473] As one example, the preprocessing includes mapping.

[0474] As one example, the preprocessing includes mapping to vectors.

[0475] As one example, the preprocessing includes labeling.

[0476] As an example, the label refers to a mark made with a label.

[0477] As one example, the post-processing includes DFT.

[0478] As one example, the post-processing includes quantization.

[0479] As an example, the post-processing includes one or more of the following: angular domain to spatial domain transformation, spatial domain to angular domain transformation, time domain to frequency domain transformation, and frequency domain to time domain transformation.

[0480] As one example, the post-processing includes truncation and / or padding.

[0481] As an example, an encoding layer includes at least one convolutional layer and one pooling layer.

[0482] As an example, in a convolutional layer, at least one convolutional kernel is used to convolve the input to generate a corresponding feature map, and at least one feature map output by the convolutional layer is reshaped into a vector and input to a fully connected layer; the fully connected layer transforms the vector into an output.

[0483] As one embodiment, the first operation corresponding to the first identifier includes: the first operation being identified by the first identifier.

[0484] As an example, the first operation corresponding to the first identifier includes: the AI ​​model used in the first operation is identified by the first identifier.

[0485] As one embodiment, the first operation corresponding to the first identifier includes: the AI ​​entity included in the first operation is identified by the first identifier.

[0486] As one embodiment, the first operation corresponding to the first identifier includes: the AI ​​function to which the first operation is used is identified by the first identifier.

[0487] As an example, the advantages of the above method include that identifying an AI entity or function through the first identifier simplifies the design and unifies the understanding of different AI entities or functions across multiple nodes.

[0488] As one embodiment, the first operation corresponding to the first identifier includes: the AI ​​entity performing the first operation is identified by the first identifier.

[0489] As one embodiment, the first operation corresponding to the first identifier includes: the first identifier is used by the first node to determine the AI ​​model adopted by the first operation.

[0490] As an example, the advantages of the above method include that identifying an AI model / entity / function through the first identifier simplifies the design and unifies the understanding of different AI entities / functions across multiple nodes.

[0491] As one embodiment, the first operation corresponding to the first identifier includes: the first identifier is used to identify or indicate a set of RS resources, and the measurement of the set of RS resources is used to obtain a training dataset for the first operation.

[0492] As one embodiment, the first operation corresponding to the first identifier includes: obtaining the training for the first operation identified by the first identifier.

[0493] As one embodiment, the first operation corresponding to the first identifier includes: the dataset used for training the first operation is identified by the first identifier.

[0494] As an example, the benefits of the above method include identifying the inference generated by an AI training or AI training dataset by identifying the AI ​​training or AI training dataset, establishing consensus among different AI functions, and further simplifying the design.

[0495] As one embodiment, the first operation corresponding to the first identifier includes: the first operation performs spatial beam prediction for a second resource set based on measurements of a first resource set, the second resource set depending on the first identifier.

[0496] As an example, the advantages of the above method include reduced RS overhead and reduced feedback latency.

[0497] As one embodiment, the first operation corresponding to the first identifier includes: the first operation performs channel information prediction for a second resource set based on the measurement of a first resource set, the second resource set depending on the first identifier.

[0498] As one embodiment, the first operation corresponding to the first identifier includes: the first operation performs temporal beam prediction for a second resource set based on historical measurements of a first resource set, the second resource set depending on the first identifier.

[0499] As an example, the advantages of the above method include reducing beam feedback delay and improving the real-time performance of beam acquisition.

[0500] As one embodiment, the first operation corresponding to the first identifier includes: the first operation predicts temporal channel information for a second resource set based on historical measurements of a first resource set, the second resource set depending on the first identifier.

[0501] As an example, the advantages of the above method include reducing channel information feedback delay and improving the real-time performance of channel information acquisition.

[0502] As an example, the output of the first operation is used to generate the first channel information block.

[0503] As an example, the first channel information block includes the output of the first operation.

[0504] As one embodiment, the first channel information block includes the post-processed output of the first operation.

[0505] As one embodiment, the first channel information block includes the truncated and / or quantized output of the first operation.

[0506] As an example, the output of the first operation, after post-processing, is used to generate the first channel information block.

[0507] As an example, the output of the first operation, after being truncated and / or quantized, is used to generate the first channel information block.

[0508] As an example, some or all of the output of the first operation is post-processed and used to generate the first channel information block.

[0509] As an example, some or all of the output of the first operation, after being truncated and / or quantized, is used to generate the first channel information block.

[0510] As an example, the output of the first operation includes a first CSI, which is used to generate the first channel information block.

[0511] As an example, the advantages of the above method include improved CSI reporting performance by leveraging the advantages of the first operation, including more accurate reporting and / or lower overhead.

[0512] As one embodiment, the first channel information block includes the first CSI.

[0513] As an example, the first CSI is post-processed and used to generate the first channel information block.

[0514] As one embodiment, the first channel information block includes the first CSI after post-processing.

[0515] As an example, the first channel information block carries the first CSI after post-processing.

[0516] As an example, the first CSI is truncated and / or quantized and used to generate the first channel information block.

[0517] As one embodiment, the first channel information block includes the first CSI after truncation and / or quantization.

[0518] As one embodiment, the first channel information block carries the first CSI after truncation and / or quantization.

[0519] As an example, the first CSI includes one or more of PMI, CRI, CQI, RI, LI, SSBRI, RSRP, SINR, Capability Index, and TDCP.

[0520] As an example, the first CSI includes one or more of PMI, CRI, CQI, RI, LI, SSBRI, RSRP, SINR, capability index, TDCP, predicted channel information, predicted beam information, or confidence information.

[0521] As one embodiment, the first CSI includes a channel matrix.

[0522] As one example, the first CSI includes a feature vector.

[0523] As an example, the first CSI includes a feature vector and feature values.

[0524] As an example, the first CSI includes precoded information.

[0525] As one embodiment, the first CSI includes pre-encoded information based on a non-codebook.

[0526] As an example, the first CSI is used to determine at least one precoding matrix.

[0527] As an example, the first CSI indicates at least one precoding matrix.

[0528] As an example, the precoding matrix is ​​in the spatial-frequency domain.

[0529] As an example, the precoding matrix is ​​an angular-delay domain projection.

[0530] As one embodiment, the first CSI includes information on the relative phase, amplitude, and / or coefficients between multiple antenna ports.

[0531] As an example, the first CSI includes a compressed CSI.

[0532] As an example, the first CSI includes predicted / estimated CSI.

[0533] As one example, how the first channel information block is generated based on the first operation is determined by the manufacturer of the first node, or is implementation-related. A typical but non-limiting implementation is described below:

[0534] The first node first 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.

[0535] 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.

[0536] In one implementation, measurement interference is also input into the AI ​​model.

[0537] 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.

[0538] 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.

[0539] In embodiment 11C, the generation of the first channel information block corresponding to the first identifier includes: the generation of the first channel information block uses an AI model identified by the first identifier, or the first channel information block is generated in an AI entity identified by the first identifier, or the first channel information block is used for an AI function identified by the first identifier.

[0540] As one embodiment, the generation of the first channel information block corresponding to the first identifier includes: the first identifier is used to identify an AI model, and the first channel information block is generated based on inference using the AI ​​model identified by the first identifier.

[0541] As an example, the generation of the first channel information block uses an AI model identified by the first identifier.

[0542] As an example, the first channel information block is generated in the AI ​​entity identified by the first identifier.

[0543] As an example, the first channel information block is used for the AI ​​function identified by the first identifier.

[0544] As an example, the advantages of the above method include: better adaptability to various application scenarios or terminals, high flexibility, and strong adaptability.

[0545] Example 12

[0546] Example 12 illustrates a schematic diagram of the generation of channel information corresponding to a first identifier by a higher-level parameter indication according to an embodiment of this application; as shown in Figure 12.

[0547] In embodiment 12, the generation of the first channel information block corresponds to a first identifier; higher-level parameters indicate whether the generation of channel information corresponding to the first identifier occupies processing resources in the first resource group or occupies processing resources in the second resource group.

[0548] As an example, the higher-level parameters in the first reporting configuration indicate whether the generation of channel information corresponding to the first identifier occupies processing resources in the first resource group or processing resources in the second resource group.

[0549] As an example, unlike the first reporting configuration, the higher-level parameters indicate whether the generation of channel information corresponding to the first identifier occupies processing resources in the first resource group or in the second resource group.

[0550] In the above method, whether the channel information generated based on inference occupies the processing resources in the first resource group or the second resource group is indicated by the per (per) identifier; the advantages include: it is applicable to different AI models / entities / functions and has high flexibility.

[0551] Example 13

[0552] Example 13 illustrates a schematic diagram of a first information block according to an embodiment of this application; as shown in Figure 13.

[0553] In embodiment 13, the first node sends a first information block;

[0554] The first channel information block is generated based on inference; the first information block indicates whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group.

[0555] In the above method, the first node reports whether the channel information generated based on inference occupies the processing resources in the first resource group or the processing resources in the second resource group. The advantages include: the UE can control / adjust the occupancy of processing resources, better adapt to various processing capabilities, have high flexibility and strong adaptability, and also ensure consistent understanding between the transmitting and receiving ends.

[0556] As one embodiment, the first information block is carried by higher-layer signaling.

[0557] As one example, the first information block includes one or more fields in one or more IEs (information elements).

[0558] As an example, the first information block includes a MAC CE.

[0559] As one embodiment, the first information block includes control information.

[0560] As one embodiment, the first information block includes UCI (uplink control information).

[0561] As one embodiment, the first information block is carried by physical layer signaling.

[0562] As one embodiment, the first information block is carried by physical layer uplink signaling.

[0563] As one example, the first information block is transmitted over a physical layer channel.

[0564] As one embodiment, the first information block is transmitted on the physical layer uplink channel.

[0565] As an example, the first information block is transmitted on PUCCH (Physical Uplink Control Channel).

[0566] As an example, the first information block is transmitted on PUSCH (Physical Uplink Shared Channel).

[0567] As an example, the first information block belongs to the capability information of the first node.

[0568] As one embodiment, the first information block includes the capability information of the first node.

[0569] As one embodiment, the first information block includes one or more capability parameters of the first node.

[0570] As one embodiment, the first information block includes one or more fields in a UE (user equipment) capability IE (information element).

[0571] As one embodiment, the first information block includes one or more fields in one or more UE (user equipment) capability IE (information element).

[0572] As one embodiment, the first information block includes one or more parameters in one or more UE (user equipment) capability IEs.

[0573] As an example, after receiving a UE Capability Enquiry from the network, the first node transmits the first node's capability information, and the first information block belongs to the first node's capability information.

[0574] As an example, the capability information of the first node includes UECapabilityInformation.

[0575] As an example, the capability information of the first node includes the radio access capability of the first node.

[0576] Example 14

[0577] Example 14 illustrates a schematic diagram of the generation of channel information corresponding to a first identifier in a first information block indication according to an embodiment of this application; as shown in Figure 14.

[0578] In Embodiment 14, the generation of the first channel information block corresponds to a first identifier; the first information block indicates whether the generation of channel information corresponding to the first identifier occupies processing resources in the first resource group or occupies processing resources in the second resource group.

[0579] In the above method, whether the channel information generated based on inference occupies the processing resources in the first resource group or the second resource group is reported per identifier; the advantages include: it is applicable to different AI models / entities / functions and has high flexibility.

[0580] Examples 15A-15C

[0581] Examples 15A-15C illustrate schematic diagrams of a first resource group and a second resource group according to an embodiment of this application, as shown in Figures 15A-15C.

[0582] In Example 15A, only the first resource group and the second resource group include one or more storage resources in the first node.

[0583] As one embodiment, the first resource group includes one or more processing resources and one or more storage resources; the second resource group includes one or more processing resources.

[0584] As an example, the first channel information block is generated based on inference; some or all of the parameters used in the generation of the first channel information block are stored in at least one storage resource.

[0585] As an example, the first channel information block is generated based on inference; some or all of the parameters of the AI ​​model used in the generation of the first channel information block are stored in at least one storage resource.

[0586] As an example, the first channel information block is generated based on inference; at least one of the parameters of some or all of the AI ​​model used in the generation of the first channel information block, some or all of the intermediate inference results, or some or all of the inference outputs is stored in at least one storage resource.

[0587] As an example, the first channel information block is generated based on inference; at least one of some or all of the inference intermediate results or some or all of the inference outputs in the generation of the first channel information block is stored in at least one storage resource.

[0588] As one example, the storage resources are used for storage.

[0589] As one embodiment, the storage resource includes storage units or storage space.

[0590] As one example, the storage resource includes memory.

[0591] As one example, the storage resources are used to store some or all of the parameters required for inference.

[0592] As one embodiment, the storage resources are used to store at least one of some or all of the inference intermediate results, or some or all of the inference outputs.

[0593] As one example, the storage resources are used to store some or all of the parameters of the AI ​​model.

[0594] As an example, the storage resources are used to store at least one of some or all of the parameters of the AI ​​model, some or all of the intermediate inference results, or some or all of the inference outputs.

[0595] As one embodiment, the storage resources are used to store one or more of the following: convolution kernel size, number of convolutional layers, convolution stride, pooling kernel size, pooling kernel stride, pooling function, activation function, or number of feature maps.

[0596] As an example, the storage resources are used to store 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.

[0597] As an example, the storage resources are used to store some or all of the parameters in the target first type of parameter group in Embodiment 20 of this application.

[0598] As one embodiment, the processing resources are used for at least one of processing, computing, or reasoning, and the storage resources are used for storage.

[0599] As one embodiment, the processing resource is a processing unit, and the storage resource is used for storage.

[0600] As an example, the first node reports the total number of processing resources in the first resource group, the total number of storage resources in the first resource group, and the total number of processing resources in the second resource group in its capability information.

[0601] In Example 15B, the processing resources in the first resource group and the processing resources in the second resource group have the same name.

[0602] As an example, the names of the processing resources in the first resource group and the processing resources in the second resource group are the same, and the names of the processing resources in the first resource group and the second resource group include processing units (PU).

[0603] As an example, the processing resources in the first resource group and the processing resources in the second resource group are both CSI processing units (CPUs).

[0604] As one example, the first resource group and the second resource group are respectively located in different types of hardware resources of the first node.

[0605] As one embodiment, the processing resources in the first resource group are in the AI ​​processing unit (APU), and the processing resources in the second resource group are in the central processing unit (C Processing Unit).

[0606] As one embodiment, the processing resources in the first resource group are in the GPU (graphics processing unit), and the processing resources in the second resource group are in the central processing unit (Central Processing Unit).

[0607] As one embodiment, the processing resources in the first resource group are in a general processing unit, and the processing resources in the second resource group are in a central processing unit.

[0608] As one embodiment, the processing resources in the first resource group are in a general-purpose computing on graphics processing unit (GPGPU), and the processing resources in the second resource group are in a central processing unit (C Processing Unit).

[0609] In Example 15C, the names of the processing resources in the first resource group are different from the names of the processing resources in the second resource group.

[0610] As an example, the processing resources in the first resource group are AI processing units (APUs), and the processing resources in the second resource group are CSI processing units.

[0611] As an example, the names of the processing resources in the first resource group and the processing resources in the second resource group are different, and the names of the processing resources in both the first resource group and the second resource group include processing unit (PU).

[0612] As an example, the processing resources in the first resource group are AI processing units (APUs), and the processing resources in the second resource group are central processing units (C Processing Units) or CSI processing units.

[0613] As an example, the processing resources in the first resource group are GPUs (graphics processing units), and the processing resources in the second resource group are central processing units (CPUs) or CSI units.

[0614] As an example, the processing resources in the first resource group are general-purpose processing units, and the processing resources in the second resource group are central processing units (CPUs) or CSI processing units.

[0615] As an example, the processing resources in the first resource group are general-purpose computing on graphics processing units (GPGPUs), and the processing resources in the second resource group are central processing units (CPUs) or CSI processing units.

[0616] As one example, the first resource group and the second resource group are respectively located in different types of hardware resources of the first node.

[0617] As one embodiment, the processing resources in the first resource group are in the AI ​​processing unit (APU), and the processing resources in the second resource group are in the central processing unit (C Processing Unit).

[0618] As one embodiment, the processing resources in the first resource group are in the GPU (graphics processing unit), and the processing resources in the second resource group are in the Central Processing Unit.

[0619] As one embodiment, the processing resources in the first resource group are in a general processing unit, and the processing resources in the second resource group are in a central processing unit.

[0620] As one embodiment, the processing resources in the first resource group are in a general-purpose computing on graphics processing unit (GPGPU), and the processing resources in the second resource group are in a central processing unit (C Processing Unit).

[0621] As an example, the processing resources in the first resource group are in the AI ​​processing unit (APU), and the processing resources in the second resource group are CSI processing units.

[0622] As an example, the processing resources in the first resource group are in the GPU (graphics processing unit), and the processing resources in the second resource group are CSI processing units.

[0623] As one embodiment, the processing resources in the first resource group are in a general processing unit, and the processing resources in the second resource group are CSI processing units.

[0624] As an example, the processing resources in the first resource group are in a general-purpose computing on graphics processing unit (GPGPU), and the processing resources in the second resource group are CSI processing units.

[0625] Example 16

[0626] Example 16 illustrates a schematic diagram of a first resource set according to an embodiment of this application; as shown in Figure 16.

[0627] In embodiment 16, the first processor receives RS in the first resource set;

[0628] The first resource set includes one or more RS resources, and the first resource set is used for at least one of the channel measurement or interference measurement of the first channel information block.

[0629] As one embodiment, the first reporting configuration is used to configure the first channel information block, and the first reporting configuration indicates the first resource set.

[0630] As an example, the first channel information block indicates at least one RS resource in the first resource set.

[0631] As one embodiment, the first channel information block indicates at least one resource in a second resource set, the second resource set including resources that do not belong to the first resource set.

[0632] As an example, the resources in the first resource set include at least one of antenna port, TCI (Transmission Configuration Indication) status, QCL (Quasi Co-Location) information, time-frequency resources, time-frequency code resources, beam, RS resources, vector, or matrix.

[0633] As one embodiment, the first resource set includes one or more RS (Reference Signal) resource sets, and an RS resource set includes one or more RS resources.

[0634] As one embodiment, the first resource set includes at least one of at least a CSI-RS resource set, at least one CSI-SSB (Channel State Information-Synchronization Signal Block) resource set, or at least one CSI-IM (Channel State Information-Interference Measurement) resource set.

[0635] As one embodiment, the first resource set includes at least one RS resource set for channel measurement, and an RS resource set for channel measurement includes one or more RS resources.

[0636] As one embodiment, the first resource set includes at least one RS resource set for channel measurement and at least one RS resource set for interference measurement; an RS resource set for channel measurement includes one or more RS resources, and an RS resource set for interference measurement includes one or more RS resources.

[0637] As one embodiment, the first resource set includes at least one RS resource set for interference measurement; an RS resource set for interference measurement includes one or more RS resources.

[0638] As an example, a set of RS resources for channel measurement includes one or more RS resources, wherein any RS resource in the set of RS resources for channel measurement is a CSI-RS resource or a synchronization signal resource.

[0639] As an example, a set of RS resources for interference measurement includes one or more RS resources.

[0640] As an example, an RS resource set for interference measurement includes one or more RS resources, wherein any RS resource in the RS resource set for interference measurement is a CSI-IM resource or an NZP (non-zero power) CSI-RS resource for interference measurement.

[0641] As one example, the first resource set includes one or more RS resources.

[0642] As one embodiment, the first resource set includes one or more downlink RS resources.

[0643] As one embodiment, the first resource set includes one or more RS resources, and any RS resource in the first resource set is a CSI-RS (Channel State Information Reference Signal) resource or a synchronization signal resource.

[0644] As one embodiment, the synchronization signal resources include at least the resources occupied by the synchronization signal.

[0645] As an example, the synchronization signal resource is an SSB (Synchronization Signal Block).

[0646] As an example, the synchronization signal resource is an SS / PBCH (synchronization signal / physical broadcast channel) block resource.

[0647] As one embodiment, the first reported configuration indicates at least one resource configuration, and the at least one resource configuration indicates the first resource set.

[0648] As an example, the first reporting configuration includes at least one resource configuration, the at least one resource configuration indicating the first resource set.

[0649] As an example, a resource configuration is used to configure CSI resources.

[0650] As an example, a resource configuration is an IE CSI-ResourceConfig.

[0651] As an example, a resource configuration is carried by an RRC IE.

[0652] As an example, a resource configuration is carried by the CSI-ResourceConfig IE.

[0653] As an example, the first reported configuration indicates the configuration information of the first resource set.

[0654] As one embodiment, the first reporting configuration indicates the identifier of the first resource set.

[0655] As an example, the first resource set consists of one or more periodic or semi-persistent RS resources.

[0656] As an example, the first resource set consists of one or more aperiodic RS resources.

[0657] As an example, the RS resource is a CSI-RS resource.

[0658] As an example, the RS resource is a CSI-RS resource or an SS / PBCH block resource.

[0659] As one embodiment, the use of the first resource set for channel measurement or interference measurement of the first channel information block includes: obtaining channel measurement of the first channel information block based on at least one reference signal transmitted in the first resource set.

[0660] As one embodiment, the use of the first resource set for channel measurement or interference measurement of the first channel information block includes: obtaining channel measurement of the first channel information block in the first resource set.

[0661] As one embodiment, the use of the first resource set for channel measurement or interference measurement of the first channel information block includes: obtaining interference measurement of the first channel information block based on at least one reference signal transmitted in the first resource set.

[0662] As one embodiment, the use of the first resource set for channel measurement or interference measurement of the first channel information block includes: obtaining interference measurement of the first channel information block in the first resource set.

[0663] As one example, the channel measurement obtained based on the first resource set includes a channel matrix.

[0664] As an example, the channel measurements obtained based on the first resource set include the raw channel matrix.

[0665] As an example, the channel measurement obtained based on the first resource set includes an eigenvector.

[0666] As an example, the channel measurements obtained based on the first resource set include feature vectors and eigenvalues.

[0667] As an example, the channel measurements obtained based on the first resource set include one or more of BLER, delay spread, Doppler spread, Doppler shift, average delay, average gain, path loss, and RSRP.

[0668] As an example, the interference measurement obtained based on the first resource set includes at least one of interference power, interference variance, or interference power spectral density.

[0669] As an example, the interference measurement obtained based on the first resource set includes an interference channel matrix.

[0670] As an example, the interference measurement obtained based on the first resource set includes the interference covariance matrix.

[0671] As an example, the interference measurement obtained based on the first resource set includes an interference feature vector.

[0672] As an example, the interference measurement obtained based on the first resource set includes interference feature vectors and interference feature values.

[0673] As one example, the interference measurement obtained based on the first resource set includes interference beams.

[0674] Examples 17A-17B

[0675] Examples 17A-17B illustrate schematic diagrams of the deployment of the first operation of the first node according to an embodiment of this application, as shown in Figures 17A-17B respectively.

[0676] In Example 17A, the first node requests the first producer to load the first operation and obtains the first operation from the first producer.

[0677] As one embodiment, the deployment includes obtaining the first operation.

[0678] As one example, the deployment includes obtaining an AI entity.

[0679] As one example, the deployment includes obtaining an AI entity that performs the first operation.

[0680] As one example, the deployment includes obtaining an AI entity that includes AI functions to perform the first operation.

[0681] As one example, the deployment includes loading the first operation.

[0682] As one example, the deployment includes submitting a request to load the first operation.

[0683] As an example, the first operation is obtained from the serving cell of the first node.

[0684] As an example, the first operation is obtained from the sustaining base station of the serving cell of the first node.

[0685] As an example, the first operation is obtained from the core network.

[0686] As an example, the first operation is obtained from loading from the first producer.

[0687] As an example, the deployment is accomplished by an AI function.

[0688] As an example, the deployment is accomplished by AI functionality deployed on the first node.

[0689] As an example, the deployment is accomplished by an AI deployment function.

[0690] As an example, the deployment is accomplished by the AI ​​deployment function deployed on the first node.

[0691] As an example, the deployment is accomplished by AI inference functionality.

[0692] As an example, the deployment is accomplished by an AI inference function deployed on the first node.

[0693] As an example, the deployment is performed by an AI entity.

[0694] As an example, the deployment is performed by an AI entity deployed on the first node.

[0695] As an example, the deployment is performed by an AI entity with a deployment function.

[0696] As an example, the deployment is performed by an AI entity with deployment capabilities deployed on the first node.

[0697] As an example, the deployment is performed by an AI entity with an inference function.

[0698] As an example, the deployment is performed by an AI entity with reasoning capabilities deployed on the first node.

[0699] As one embodiment, the deployment includes obtaining the first operation from a first producer.

[0700] As one embodiment, the deployment includes requesting a first producer to load the first operation.

[0701] As one embodiment, the deployment includes loading the first operation from the first producer.

[0702] As an example, the first producer generates and provides the AL entity.

[0703] As an example, the first producer generates and provides AL functionality.

[0704] As an example, the first producer is the producer of the first operation.

[0705] As an example, the first producer includes an AL entity producer.

[0706] As one example, the first producer includes an AL function producer.

[0707] As one example, the first producer includes an AL deployment producer.

[0708] As one example, the first producer includes an AL loading producer.

[0709] As one example, the first producer includes an AL-trained producer.

[0710] As an example, the first producer includes an AL inference producer.

[0711] As an example, the first producer includes the producer of the AL entity deployment.

[0712] As one example, the first producer includes the producer that loads the AL entity.

[0713] As an example, the first producer includes an MnS (Management Service) producer.

[0714] As an example, the sender of the first reporting configuration is the first producer.

[0715] As an example, the sender of the first reporting configuration is different from the first producer.

[0716] As an example, the training for obtaining the first operation is performed by the first producer.

[0717] As an example, the executor used to obtain the training for the first operation is different from the first producer.

[0718] As one example, the AI ​​includes ML (Machine Learning).

[0719] In Example 17B, the first node requests the second producer to load the first operation and obtains the first operation from the first producer.

[0720] As one embodiment, the deployment includes obtaining the first operation.

[0721] As one example, the deployment includes obtaining an AI entity or AI function to perform the first operation.

[0722] As one example, the deployment includes loading the first operation.

[0723] As one example, the deployment includes submitting a request to load the first operation.

[0724] As an example, the deployment is accomplished by AI functionality deployed on the first node.

[0725] As an example, the deployment is accomplished by the AI ​​deployment function deployed on the first node.

[0726] As an example, the deployment is performed by an AI entity with a deployment function.

[0727] As one example, the second producer generates and provides AI entities or AI functions.

[0728] As one example, the second producer includes an MnS (Management Service) producer.

[0729] As an example, the second producer includes the producer of the AI ​​model training.

[0730] As one example, the second producer is the target receiver of the first channel information block.

[0731] As one example, the second producer is different from the target receiver of the first channel information block.

[0732] As one example, the second producer is the serving cell of the first node.

[0733] As one example, the second producer is the maintenance base station of the serving cell of the first node.

[0734] As one example, the second producer is the core network.

[0735] As an example, the first operation is obtained from the serving cell of the first node.

[0736] As an example, the first operation is obtained from the sustaining base station of the serving cell of the first node.

[0737] As an example, the first operation is obtained from the core network.

[0738] As an example, the training for obtaining the first operation is performed by the second producer.

[0739] As an example, the second producer is different from the first producer.

[0740] As an example, the first producer generates and provides the AL entity.

[0741] As an example, the first producer generates and provides AL functionality.

[0742] As an example, the first producer is the producer of the first operation.

[0743] As an example, the first producer includes an AL entity producer.

[0744] As one example, the first producer includes an AL function producer.

[0745] As one example, the first producer includes an AL deployment producer.

[0746] As one example, the first producer includes an AL loading producer.

[0747] As one example, the first producer includes an AL-trained producer.

[0748] As an example, the first producer includes an AL inference producer.

[0749] As an example, the first producer includes the producer of the AL entity deployment.

[0750] As one example, the first producer includes the producer that loads the AL entity.

[0751] As an example, the first producer includes an MnS (Management Service) producer.

[0752] Example 18

[0753] Example 18 illustrates a schematic diagram of RAN (Radio Access Network) domain AI / ML function deployment according to one embodiment of this application; as shown in Figure 18. The gNB in ​​Example 18 can be replaced with, for example, an eNB, or a network device such as a 6G base station.

[0754] 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.

[0755] ML training functionality 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 functionality for MDA (Management Data Analytics) can be deployed on MDAF (MDA Function); ML training for network data analytics can be deployed on NWDAF (Network Data Analytics Function), meaning the ML training functionality is an MTLF (Model Training Logical Function).

[0756] 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.

[0757] Similarly, ML testing capabilities can also be deployed in cross-domain management systems or domain-specific management systems.

[0758] In Example 18, the RAN domain ML training function 1402 is located in the RAN domain management function 1403; while the ML inference function is located in the base station, that is, the AI / ML inference function 1404 is located in gNB 1405, the AI / ML inference function 1406 is located in gNB 1407, and so on.

[0759] In Figure 18, the management of ML inference functions of multiple base stations is completed by RAN domain management function 1403, that is, data interaction with RAN domain MnS (Management Service) consumer / cross-domain management 1401 (as shown by the dashed arrow in Figure 18).

[0760] 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 1401.

[0761] It should be noted that Example 18 is merely a non-limiting implementation; optionally, the ML training function of the RAN domain may also be deployed in 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.

[0762] As an example, one of the gNBs (or base stations) in Example 18 is the second node of this application.

[0763] As an example, the second processor in this application includes an AL / ML inference function, namely 1404 or 1406, as shown in Figure 18.

[0764] Example 19

[0765] Example 19 illustrates a schematic diagram of the deployment of AI / ML functionality in a UE according to one embodiment of this application; as shown in Figure 19. The RAN domain ML training function 1505 in Figure 19 is optional.

[0766] UE function 1504 is deployed in the first node of this application, and the UE function 1504 includes AI / ML inference function 1506; the AI / ML inference function 1506 uses an ML model (also called an AI model) for inference; an ML model is typically trained before being used for AI / ML inference.

[0767] As an example, the first channel information block in this application is obtained through inference by the AI / ML inference function 1506.

[0768] As an example, the first processor in this application includes an AL / ML inference function 1506 in Figure 19.

[0769] As an example, the UE function 1504 includes a RAN domain ML training function 1505, 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.

[0770] 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.

[0771] Optionally, the UE function 1504 also includes a CN domain ML training function (not shown in Figure 19).

[0772] Optionally, the UE function 1504 also includes an AI / ML deployment function (not shown in Figure 19) for loading ML models and data.

[0773] 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.

[0774] As an example, the ML model and the associated metadata are loaded by the first node from a network device or a remote server.

[0775] Optionally, the UE function 1504 is an MnS (Management Service) producer that provides data to the CN domain MnF (Management Function) 1501, and / or the RAN domain MnF 1502, and / or the cross-domain management system 1503 for management or analysis (as shown by double arrow 1507).

[0776] Optionally, the UE function 1504 is an MnS consumer that loads data from the CN domain MnF (Management Function) 1501, and / or the RAN domain MnF 1502, and / or the cross-domain management system 1503 for AI / ML-related management, such as managing data requests, ML model activation, and / or ML training (as shown by double arrow 1507).

[0777] As an example, the ML model is based on a neural network.

[0778] As an example, the ML model is based on CNN (Conventional Neural Networks).

[0779] As an example, the ML model is based on the Transformer architecture.

[0780] Example 20

[0781] Example 20 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 20. Figure 20(a) includes a third processor, a fourth processor, and a fifth processor, and Figure 20(b) includes a third processor, a fourth processor, a fifth processor, and a sixth processor.

[0782] In Example 20(a), the third processor sends a first dataset to the fourth processor and a second dataset to the fifth processor; the fourth processor generates a target first-type parameter set based on the first dataset, and sends the generated target first-type parameter set to the fifth processor; the fifth processor processes the second dataset using the target first-type parameter set to obtain a first-type output. In Figure 20(a), the first-type feedback is optional.

[0783] In Example 20(b), the third processor sends a first dataset to the fourth processor and a second dataset to the fifth processor; the fourth processor generates a target first-type parameter set based on the first dataset, and sends the generated target first-type parameter set to the fifth processor; the fifth processor processes the second dataset using the target first-type parameter set to obtain a first-type output, and sends the first-type output to the sixth processor. In Figure 20(b), the first-type feedback and the second-type feedback are optional.

[0784] As an example, in Figure 20(a), the fifth processor sends the first type of output to the second node in this application.

[0785] As an example, Figure 20(a) employs a single-side AI model, in which the fifth processor performs the first operation of this application.

[0786] As an example, Figure 20(b) employs a two-sided AI model, wherein the fifth processor performs the first operation of this application, and the sixth processor includes the second operation of this application.

[0787] As an example, the AI ​​includes ML (Machine Learning) inference.

[0788] As an example, the fifth processor performs the first operation in this application.

[0789] As one embodiment, the sixth processor includes the second operation described in this application.

[0790] As an example, the fifth processor sends a first type of feedback to the fourth processor, and the first type of feedback is used to trigger a recalculation or update of the target first type of parameter group.

[0791] As one embodiment, the sixth processor sends a second type of feedback to the third processor, the second type of feedback being used to generate the first dataset or the second dataset, or the second type of feedback being used to trigger the sending of the first dataset or the second dataset.

[0792] As one embodiment, the third processor generates the first dataset and the second dataset based on measurements of a first type of wireless signal, the first type of wireless signal including downlink RS.

[0793] As one embodiment, the fifth processor belongs to the first node, and the sixth processor belongs to the second node.

[0794] As an example, the first channel information block belongs to the first type of output.

[0795] As an example, the second dataset includes the input of the first operation.

[0796] As an example, for the first operation in this application, the second dataset includes information obtained based on the first reporting configuration.

[0797] As an example, the first dataset includes training data.

[0798] As an example, the fourth processor belongs to the producer of the first operation.

[0799] As one embodiment, the fourth processor includes an AI training producer.

[0800] As one embodiment, the fourth processor includes an AI training function.

[0801] As an example, the fourth processor is used for model training, and the trained model is described by the target first class of parameter sets.

[0802] As an example, the fourth processor belongs to the first node.

[0803] The above embodiments avoid passing the first dataset to the second node.

[0804] As one example, the fourth processor belongs to the second node.

[0805] The above embodiments support joint training and optimize system performance.

[0806] As an example, the fourth processor belongs to the core network.

[0807] The above embodiments support network-wide joint training, further optimizing system performance.

[0808] As an example, the second dataset includes inference data.

[0809] As one embodiment, the fifth processor includes an AI inference producer.

[0810] As one embodiment, the fifth processor includes an AI inference function.

[0811] As an example, the fifth processor belongs to the first node.

[0812] As an example, the fifth 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.

[0813] As an example, the first operation is described by the target first type of parameter group.

[0814] As an example, the target first type of parameter group is used to construct the first operation.

[0815] As one embodiment, the fifth processor includes the second operation.

[0816] As an example, the fifth 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.

[0817] As a sub-example of the above embodiment, the generation of the recovery dataset adopts a similar operation to the second one.

[0818] 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 fourth processing opportunity recalculates the target first type of parameter set.

[0819] 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.

[0820] 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.

[0821] 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 pooling function, or parameters of activation function.

[0822] Example 21

[0823] Example 21 illustrates a structural block diagram of a processing apparatus for a first node according to an embodiment of this application; as shown in Figure 21. In Figure 21, the processing apparatus 2100 in the first node includes a first processor 2101.

[0824] As one example, the first node is a user equipment.

[0825] As one example, the user equipment is a terminal.

[0826] As an example, the first node is a relay node device.

[0827] As an example, the first processor 2101 includes at least one of the following in embodiment 4: {antenna 452, receiver / transmitter 454, receiver processor 456, transmitter processor 468, multi-antenna receiver processor 458, multi-antenna transmitter processor 457, controller / processor 459, memory 460, data source 467}.

[0828] The first processor 2101 receives the first reported configuration and sends the first channel information block.

[0829] In embodiment 21, the first reporting configuration is used to configure the reporting of the first channel information block. The generation of the first channel information block occupies at least one processing resource. The at least one processing resource occupied by the generation of the first channel information block belongs to one of a first resource group or a second resource group. The first resource group includes one or more processing resources in the first node, and the second resource group includes one or more processing resources in the first node. Whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on whether the first channel information block is generated based on inference. Only when the first channel information block is not generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0830] As an example, when the first channel information block is generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the first resource group.

[0831] As an example, when the first channel information block is generated based on inference, the candidate range of the resource group to which the at least one processing resource occupied by the generation of the first channel information block belongs includes the first resource group and the second resource group.

[0832] As an example, the first channel information block is generated based on inference; the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group only when the reported quantity included in the first channel information block belongs to the first reported quantity set; the first reported quantity set includes one or more reported quantities.

[0833] As one example, the first channel information block is generated based on inference;

[0834] The first channel information block is generated based on inference and includes the first identifier corresponding to the generation of the first channel information block;

[0835] Whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on the first identifier.

[0836] As an example, the first channel information block is generated based on inference; whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group is configurable.

[0837] As one embodiment, the generation of the first channel information block corresponds to a first identifier; higher-level parameters indicate whether the generation of channel information corresponding to the first identifier occupies processing resources in the first resource group or in the second resource group.

[0838] As one embodiment, it includes:

[0839] The first processor 2101 sends the first information block;

[0840] The first channel information block is generated based on inference; the first information block indicates whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group.

[0841] As one embodiment, the generation of the first channel information block corresponds to a first identifier; the first information block indicates whether the generation of channel information corresponding to the first identifier occupies processing resources in the first resource group or occupies processing resources in the second resource group.

[0842] As one embodiment, only the first resource group and the second resource group include one or more storage resources in the first node.

[0843] As one embodiment, it includes:

[0844] The first processor 2101 receives RS from the first resource set;

[0845] The first resource set includes one or more RS resources, and the first resource set is used for at least one of the channel measurement or interference measurement of the first channel information block.

[0846] Example 22

[0847] Example 22 illustrates a structural block diagram of a processing apparatus for a second node according to an embodiment of this application; as shown in Figure 22. In Figure 22, the processing apparatus 2200 in the second node includes a second processor 2201.

[0848] In one embodiment, the second node is a base station device.

[0849] In one embodiment, the second node is a user equipment.

[0850] As one embodiment, the second node is a relay node device.

[0851] As one embodiment, the second processor 2201 includes at least one of the following in embodiment 4: {antenna 420, receiver / transmitter 418, receiver processor 470, transmitter processor 416, multi-antenna receiver processor 472, multi-antenna transmitter processor 471, controller / processor 475, memory 476}.

[0852] The second processor 2201 sends the first reporting configuration and receives the first channel information block.

[0853] In embodiment 22, the first reporting configuration is used to configure the reporting of the first channel information block. The generation of the first channel information block occupies at least one processing resource. The at least one processing resource occupied by the generation of the first channel information block belongs to one of a first resource group or a second resource group. The first resource group includes one or more processing resources of the senders of the first channel information block, and the second resource group includes one or more processing resources of the senders of the first channel information block. Whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on whether the first channel information block is generated based on inference. Only when the first channel information block is not generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0854] As an example, when the first channel information block is generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the first resource group.

[0855] As an example, when the first channel information block is generated based on inference, the candidate range of the resource group to which the at least one processing resource occupied by the generation of the first channel information block belongs includes the first resource group and the second resource group.

[0856] As an example, the first channel information block is generated based on inference; the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group only when the reported quantity included in the first channel information block belongs to the first reported quantity set; the first reported quantity set includes one or more reported quantities.

[0857] As one example, the first channel information block is generated based on inference;

[0858] The first channel information block is generated based on inference and includes the first identifier corresponding to the generation of the first channel information block;

[0859] Whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on the first identifier.

[0860] As an example, the first channel information block is generated based on inference; whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group is configurable.

[0861] As one embodiment, the generation of the first channel information block corresponds to a first identifier; higher-level parameters indicate whether the generation of channel information corresponding to the first identifier occupies processing resources in the first resource group or in the second resource group.

[0862] As one embodiment, it includes:

[0863] The second processor 2201 receives the first information block;

[0864] The first channel information block is generated based on inference; the first information block indicates whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group.

[0865] As one embodiment, the generation of the first channel information block corresponds to a first identifier; the first information block indicates whether the generation of channel information corresponding to the first identifier occupies processing resources in the first resource group or occupies processing resources in the second resource group.

[0866] As one embodiment, only the first resource group and the second resource group include one or more storage resources of the sender of the first channel information block.

[0867] As one embodiment, it includes:

[0868] The second processor 2201 sends RS in the first resource set;

[0869] The first resource set includes one or more RS resources, and the first resource set is used for at least one of the channel measurement or interference measurement of the first channel information block.

[0870] 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. Accordingly, 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 access cards, IoT terminals, RFID terminals, NB-IoT terminals, MTC (Machine Type Communication) terminals, eMTC (enhanced MTC) terminals, data cards, internet access cards, vehicle-mounted communication equipment, low-cost mobile phones, low-cost tablets, and other wireless communication devices. The base stations or system equipment in this application include, but are not limited to, macrocell base stations, microcell base stations, small cell base stations, home base stations, relay base stations, eNBs, gNBs, TRPs (Transmitter Receiver Points), GNSS, relay satellites, satellite base stations, airborne base stations, RSUs (Road Side Units), drones, and testing equipment, such as transceivers or signaling testers that simulate some functions of a base station, and other wireless communication equipment.

[0871] 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 be considered descriptive rather than restrictive in any way. The scope of the invention is defined by the appended claims rather than the foregoing description, and all modifications within their equivalent meaning and scope are considered to be included therein.

Claims

1. A method in a first node used for wireless communication, characterized by, include: Receive the first reported configuration; Send the first channel information block; Wherein, the first reporting configuration is used to configure the reporting of the first channel information block, the generation of the first channel information block occupies at least one processing resource, the at least one processing resource occupied by the generation of the first channel information block belongs to one of a first resource group or a second resource group, the first resource group includes one or more processing resources in the first node, and the second resource group includes one or more processing resources in the first node; whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on whether the first channel information block is generated based on inference. The at least one processing resource used for the generation of the first channel information block belongs only to the second resource group, provided that the first channel information block is not generated based on inference.

2. The method in the first node according to claim 1, characterized by, When the first channel information block is generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the first resource group.

3. The method in the first node according to claim 1, characterized by, When the first channel information block is generated based on inference, the candidate range of the resource group to which the at least one processing resource occupied by the generation of the first channel information block belongs includes the first resource group and the second resource group.

4. A method in a first node according to claim 1 or 3, characterized by, The first channel information block is generated based on inference; the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group only when the reported quantity included in the first channel information block belongs to the first reported quantity set; the first reported quantity set includes one or more reported quantities.

5. The method in the first node according to any of claims 1, 3, 4, characterized by, The first channel information block is generated based on inference; The first channel information block is generated based on inference and includes the first identifier corresponding to the generation of the first channel information block; Whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on the first identifier.

6. A method in a first node according to any of claims 1, 3, 4, 5, characterized by, The first channel information block is generated based on inference; whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group is configurable.

7. A method in a first node according to claim 6, characterized by, The generation of the first channel information block corresponds to a first identifier; higher-level parameters indicate whether the generation of channel information corresponding to the first identifier occupies processing resources in the first resource group or in the second resource group.

8. The method in a first node according to any of claims 1, 3, 4, 5, characterized by, include: Send the first information block; The first channel information block is generated based on inference; The first information block indicates whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group.

9. A method in a first node according to claim 8, characterised by, The generation of the first channel information block corresponds to a first identifier; the first information block indicates whether the generation of channel information corresponding to the first identifier occupies processing resources in the first resource group or processing resources in the second resource group.

10. A terminal, characterized by comprising: 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 to 9.

11. A method in a second node used for wireless communication, characterized by, include: Send the first reporting configuration; Receive the first channel information block; Wherein, the first reporting configuration is used to configure the reporting of the first channel information block. The generation of the first channel information block occupies at least one processing resource. The at least one processing resource occupied by the generation of the first channel information block belongs to one of a first resource group or a second resource group. The first resource group includes one or more processing resources of the senders of the first channel information block, and the second resource group includes one or more processing resources of the senders of the first channel information block. Whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on whether the first channel information block is generated based on inference. Only when the first channel information block is not generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

12. A method in a second node according to claim 11, characterised by, When the first channel information block is generated based on inference, the at least one processing resource occupied by the generation of the first channel information block belongs only to the first resource group.

13. A method in a second node according to claim 11, characterised by, When the first channel information block is generated based on inference, the candidate range of the resource group to which the at least one processing resource occupied by the generation of the first channel information block belongs includes the first resource group and the second resource group.

14. A method in a second node according to claim 11 or 13, characterized by, The first channel information block is generated based on inference; the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group only when the reported quantity included in the first channel information block belongs to the first reported quantity set; the first reported quantity set includes one or more reported quantities.

15. A method in a second node according to any of the claims 11, 13, 14, characterized by, The first channel information block is generated based on inference; The first channel information block is generated based on inference and includes the first identifier corresponding to the generation of the first channel information block; Whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group depends on the first identifier.

16. A method in a second node according to any of the claims 11, 13, 14, 15, characterized by, The first channel information block is generated based on inference; whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group is configurable.

17. A method in a second node according to claim 16, characterised by, The generation of the first channel information block corresponds to a first identifier; higher-level parameters indicate whether the generation of channel information corresponding to the first identifier occupies processing resources in the first resource group or in the second resource group.

18. A method in a second node according to any of the claims 11, 13, 14, 15, characterized by, include: Receive the first information block; The first channel information block is generated based on inference; The first information block indicates whether the at least one processing resource occupied by the generation of the first channel information block belongs to the first resource group or the second resource group.

19. A method in a second node according to claim 18, characterised by, The generation of the first channel information block corresponds to a first identifier; the first information block indicates whether the generation of channel information corresponding to the first identifier occupies processing resources in the first resource group or processing resources in the second resource group.

20. A base station, comprising: The base station includes: one or more processors and a memory; The memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the base station to perform the method as described in any one of claims 11 to 19.

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