Method and apparatus for channel information generation in node for wireless communication

Abstract

The invention discloses a method and an apparatus for channel information generation in a node for wireless communication. The first node receives the first report configuration; sending the first channel information block; the first reporting configuration is used for configuring the reporting of the first channel information block, and 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; 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 reasoning; the at least one processing resource occupied by the generation of the first channel information block only belongs to the second resource group only when the first channel information block is not generated based on reasoning. The method and the device are suitable for more scenes and terminals, and the channel information accuracy is improved.

Description

[0001] Technical Field This application relates to a transmission method and apparatus in a wireless communication system, and particularly to a scheme and apparatus for generating channel information in a wireless communication system. Background Art

[0002] In traditional wireless communication, a UE (User Equipment) calculates CSI (channel state information) by measuring downlink reference signals, where the CSI includes one or more of, but is not limited to, CRI (Channel state information-reference signal Resource Indicator), RI (Rank Indicator), PMI (Precoding Matrix Indicator), or CQI (Channel quality indicator).

[0003] With the adoption of new technologies, the increase in the number of antennas, the diversification of application scenarios, and the improvement of system performance requirements, etc., the traditional measurement and reporting methods will bring a large amount of redundant overhead. Therefore, in NR R (release) 18, the research on AI (Artificial Intelligence) / ML (Machine Learning) technology was initiated to explore its impact on system performance and system design. Compared with the traditional processing methods, AI / ML has characteristics such as being based on training and requiring deployment. In addition, AI / ML is also a key candidate technology for future 6G communication. When the AI / ML function is introduced, the existing measurement mechanisms, generation and / or reporting mechanisms related to channel information, and related configuration signaling may not be able to meet the requirements of AI / ML. Summary of the Invention

[0004] The applicant has found through research that the generation of a channel information requires the occupation of certain processing resources. Generally, the transceiver needs to have a consistent understanding of the occupation of processing resources. Therefore, how to determine the occupation of processing resources is the key problem to be solved. In view of the above problems, the present application discloses a solution. It should be noted that although a large number of embodiments of the present application are directed to AI / ML, the present application is also applicable to other solutions, such as traditional channel information reporting solutions. In addition, adopting a unified solution in different scenarios (including but not limited to AI / ML-based solutions and traditional information reporting solutions) helps to reduce hardware complexity and cost. Without conflict, the embodiments and features in the first node of the present application can be applied to the second node, and vice versa. Without conflict, the embodiments and features in the embodiments of the present application can be combined with each other arbitrarily.

[0005] As an embodiment, the interpretation of the terms in the present application refers to the definitions in the 3GPP specification protocol TS38 series.

[0006] As an embodiment, the interpretation of the terms in the present application refers to the definitions in the 3GPP specification protocol TS28 series.

[0007] The present application discloses a method in a first node for use in wireless communication, characterized by comprising:

[0008] Receiving a first reporting configuration; sending a first channel information block;

[0009] 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 only belongs to the second resource group.

[0010] As an embodiment, the advantages of the above method include: ensuring that the transceiver has a consistent understanding of the occupation of processing resources.

[0011] As an embodiment, the advantages of the above method include: better adapting to various different application scenarios or terminals.

[0012] As an embodiment, the advantages of the above method include: high flexibility and strong adaptability.

[0013] As an embodiment, the advantages of the above method include: better adaptation to various different processing capabilities.

[0014] As an embodiment, the advantages of the above method include: better adaptation to various different terminal capabilities.

[0015] As an embodiment, the advantages of the above method include: better adaptation to various different channel information reports, high flexibility and strong adaptability.

[0016] As an embodiment, the advantages of the above method include: better adaptation to various different processing capabilities, better adaptation to various different application scenarios or terminals, high flexibility and strong adaptability.

[0017] As an embodiment, the first node is a terminal.

[0018] As an embodiment, the first node is a user equipment.

[0019] As an embodiment, the user equipment is a terminal.

[0020] As an embodiment, the first node is a relay node.

[0021] According to one aspect of the present 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.

[0022] As an embodiment, the advantages of the above method include: strong adaptability and easy to implement.

[0023] According to one aspect of the present 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.

[0024] As an embodiment, 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, high flexibility and strong adaptability.

[0025] According to one aspect of the present application, the first channel information block is generated based on inference; only when the reporting amount included in the first channel information block belongs to the first reporting amount set, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group; the first reporting amount set includes one or more reporting amounts.

[0026] As an embodiment, the feature of the above method is that: according to whether the first channel information block belongs to the first reporting amount set, the processing resources occupied by the generation of the first channel information block are determined.

[0027] As an embodiment, the advantages of the above method include: small changes to the existing standard and good backward compatibility.

[0028] According to one aspect of the present application, it is characterized in that the first channel information block is generated based on inference;

[0029] The first channel information block being generated based on inference includes that the generation of the first channel information block corresponds to a first identifier;

[0030] 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.

[0031] As an embodiment, the advantages of the above method include: whether the processing resources occupied by the channel information generated based on inference are in the first resource group or the second resource group is determined per identifier; applicable to different scenarios with high flexibility.

[0032] According to one aspect of the present application, it is characterized in that 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.

[0033] As an embodiment, the advantages of the above method include: the base station can flexibly control / adjust the occupation of processing resources, and also ensures consistent understanding between the transceiver ends.

[0034] According to one aspect of the present application, it is characterized in that the generation of the first channel information block corresponds to a first identifier; a higher layer parameter indicates whether the generation of the channel information corresponding to the first identifier occupies the processing resources in the first resource group or the processing resources in the second resource group.

[0035] As an embodiment, the advantages of the above method include: indicating the occupation of processing resources through the higher layer parameter, which ensures consistent understanding between the transceiver ends.

[0036] According to one aspect of the present application, it is characterized in that it includes:

[0037] Transmit a first information block;

[0038] Among them, 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.

[0039] As an embodiment, the advantages of the above method include: the UE controls / adjusts the occupation of processing resources, better adapts to various different processing capabilities, has high flexibility and strong adaptability, and also ensures consistent understanding between the transceiver ends.

[0040] According to one aspect of the present application, it is characterized in that the generation of the first channel information block corresponds to a first identifier; the first information block indicates whether the generation of the channel information corresponding to the first identifier occupies the processing resources in the first resource group or the processing resources in the second resource group.

[0041] As an embodiment, the advantages of the above method include: better adapting to various different application scenarios or terminals.

[0042] According to one aspect of the present application, it is characterized in that only the first resource group in the first resource group and the second resource group includes one or more storage resources in the first node.

[0043] As an embodiment, the advantages of the above method include: having good backward compatibility.

[0044] According to one aspect of the present application, it is characterized in that it includes:

[0045] Receiving RS in a first resource set;

[0046] Among them, 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.

[0047] As an embodiment, the advantages of the above method include: having good backward compatibility.

[0048] According to one aspect of the present application, a terminal is characterized in that the terminal includes:

[0049] One or more processors and a memory;

[0050] The memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the terminal to execute the method in the first node.

[0051] The present application discloses a method in a second node for wireless communication, which is characterized by including:

[0052] Sending a first reporting configuration; receiving a first channel information block;

[0053] 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, and 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 sender of the first channel information block, and the second resource group includes one or more processing resources in the sender 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 reasoning; only when the first channel information block is not generated based on reasoning, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0054] According to one aspect of the present application, when the first channel information block is generated based on reasoning, the at least one processing resource occupied by the generation of the first channel information block belongs only to the first resource group.

[0055] According to one aspect of the present application, when the first channel information block is generated based on reasoning, 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.

[0056] According to one aspect of the present application, the first channel information block is generated based on reasoning; only when the reporting amount included in the first channel information block belongs to a first reporting amount set, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group; the first reporting amount set includes one or more reporting amounts.

[0057] According to one aspect of the present application, the first channel information block is generated based on reasoning;

[0058] The first channel information block being generated based on reasoning includes that the generation of the first channel information block corresponds to a first identifier;

[0059] 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.

[0060] According to one aspect of the present application, it is characterized in that 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.

[0061] According to one aspect of the present application, it is characterized in that the generation of the first channel information block corresponds to a first identifier; a higher layer parameter indicates whether the generation of the channel information corresponding to the first identifier occupies the processing resources in the first resource group or the processing resources in the second resource group.

[0062] According to one aspect of the present application, it includes:

[0063] Receive a first information block;

[0064] 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.

[0065] According to one aspect of the present application, it is characterized in that the generation of the first channel information block corresponds to a first identifier; the first information block indicates whether the generation of the channel information corresponding to the first identifier occupies the processing resources in the first resource group or the processing resources in the second resource group.

[0066] According to one aspect of the present application, it is characterized in that only the first resource group among the first resource group and the second resource group includes one or more storage resources of the sender of the first channel information block.

[0067] According to one aspect of the present application, it includes:

[0068] Transmit RS in a first resource set;

[0069] 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.

[0070] According to one aspect of the present application, a base station is characterized in that the base station includes:

[0071] One or more processors and a memory;

[0072] The memory is coupled to the one or more processors, and the memory 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.

[0073] This application discloses a first node for use in wireless communication, which is characterized by including:

[0074] A first processor, receiving a first reporting configuration; sending a first channel information block;

[0075] 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, and 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.

[0076] This application discloses a second node for use in wireless communication, which is characterized by including:

[0077] A second processor, sending a first reporting configuration; receiving a first channel information block;

[0078] 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, and 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 sender of the first channel information block, and the second resource group includes one or more processing resources in the sender 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.

[0079] As an embodiment, compared with the traditional solution, this application has the following advantages:

[0080] Better adapt to various different application scenarios;

[0081] Better adapt to various different processing capabilities;

[0082] Better adapt to various different terminals;

[0083] Better adapt to various different channel information reports;

[0084] High flexibility;

[0085] Strong adaptability;

[0086] Higher channel information accuracy and real-time performance;

[0087] Enhanced reliability and robustness;

[0088] Enhanced overall system performance. Description of the Drawings

[0089] By reading the following detailed description of the non-limiting embodiments with reference to the accompanying drawings, other features, objects, and advantages of the present application will become more apparent:

[0090] Figure 1 Shows a flowchart of a first reporting configuration and a first channel information block according to an embodiment of the present application;

[0091] Figure 2 Shows a schematic diagram of a network architecture according to an embodiment of the present application;

[0092] Figure 3 Shows a schematic diagram of an embodiment of a radio protocol architecture of a user plane and a control plane according to an embodiment of the present application;

[0093] Figure 4 Shows a schematic diagram of a first communication device and a second communication device according to an embodiment of the present application;

[0094] Figure 5 Shows a flowchart of a transmission according to an embodiment of the present application;

[0095] Figure 6 Shows a schematic diagram of the relationship between a first channel information block generated based on reasoning and a first resource group or a second resource group according to an embodiment of the present application;

[0096] Figure 7 Shows a schematic diagram of the relationship between a first channel information block generated based on reasoning and a first resource group or a second resource group according to another embodiment of the present application;

[0097] Figure 8A schematic diagram showing 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 the present application;

[0098] Figure 9 A schematic diagram showing that a first channel information block is generated based on inference according to an embodiment of the present application;

[0099] Figure 10 A schematic diagram showing the processing resources occupied by the generation of a first channel information block according to an embodiment of the present application;

[0100] Figures 11A - 11C Schematic diagrams respectively showing that the generation of a first channel information block corresponds to a first identifier according to an embodiment of the present application;

[0101] Figure 12 A schematic diagram showing that higher layer parameters indicate the generation of channel information corresponding to a first identifier according to an embodiment of the present application;

[0102] Figure 13 A schematic diagram showing a first information block according to an embodiment of the present application;

[0103] Figure 14 A schematic diagram showing that a first information block indicates the generation of channel information corresponding to a first identifier according to an embodiment of the present application;

[0104] Figures 15A - 15C Schematic diagrams respectively showing a first resource group and a second resource group according to an embodiment of the present application;

[0105] Figure 16 A schematic diagram showing a first resource set according to an embodiment of the present application;

[0106] Figures 17A - 17B Schematic diagrams respectively showing a first node deploying a first operation according to an embodiment of the present application;

[0107] Figure 18 A schematic diagram showing the deployment of AI / ML functions in the RAN (Radio Access Network) domain according to an embodiment of the present application;

[0108] Figure 19 A schematic diagram showing the deployment of AI / ML functions of a UE according to an embodiment of the present application;

[0109] Figure 20 A schematic diagram showing a processing system based on artificial intelligence or machine learning according to an embodiment of the present application;

[0110] Figure 21 A structural block diagram of a processing device in a first node according to an embodiment of the present application is shown;

[0111] Figure 22 A structural block diagram of a processing device in a second node according to an embodiment of the present application is shown. Detailed implementation manners

[0112] The technical solutions of the present application will be further described in detail below with reference to the accompanying drawings. It should be noted that, without conflict, the embodiments and features in the embodiments of the present application can be combined arbitrarily. Considering aspects such as performance, flexibility, complexity, overhead, and compatibility, those skilled in the art have the motivation to flexibly combine the embodiments in different drawings on the premise of non-conflict, for example, but not limited to the embodiments in Figure 1 and the embodiments in Figure 5 - Figure 22 and the embodiments in Figure 5 and the embodiments in Figure 6 - Figure 22 and the embodiments in, etc.

[0113] Example 1

[0114] Embodiment 1 exemplifies a flowchart of a first reporting configuration and a first channel information block according to an embodiment of the present application, as shown in Figure 1 . In 100 shown in Figure 1 , each block represents a step. In particular, the order of the steps in the block does not represent a specific temporal sequence between the steps.

[0115] In Embodiment 1, the first node receives a first reporting configuration in step 101; and sends a first channel information block in step 102; 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 reasoning; only when the first channel information block is not generated based on reasoning, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0116] Typically, the generation of the first channel information block occupies M processing resources, where M is a positive integer; among them,

[0117] the number of unoccupied processing resources in the first resource group shall be not 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 be not less than M, and the generation of the first channel information block occupies M processing resources in the second resource group.

[0118] As an embodiment, a processing resource being unoccupied includes: a processing resource is not being used for at least one of processing, computing, or reasoning.

[0119] As an embodiment, a processing resource being occupied includes: a processing resource has been used for at least one of processing, computing, or reasoning.

[0120] As an embodiment, a processing resource being occupied includes: a processing resource is not idle.

[0121] As an embodiment, a processing resource being unoccupied includes: a processing resource is idle.

[0122] As an embodiment, a processing resource being occupied includes: a processing resource has been used for at least one of computing or reasoning.

[0123] As an embodiment, a processing resource being unoccupied includes: a processing resource is not being used for at least one of computing or reasoning.

[0124] In the above method, the unoccupied processing resources are unoccupied when determining the processing resources occupied by the generation of the first channel information block. The resource group occupied by the generation of the first channel information block shall satisfy: the number of unoccupied processing resources included shall be not less than the number of processing resources required for the generation of the first channel information block.

[0125] As an embodiment, the first reporting configuration is carried by higher layer signaling.

[0126] As an embodiment, the first reporting configuration is carried by RRC (Radio Resource Control) signaling.

[0127] As an embodiment, the first reporting configuration includes some or all fields in one or more RRC IEs (Information Elements).

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

[0129] As an example, the first reporting configuration includes some or all fields in an IE ServingCellConfig.

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

[0131] As an example, the first reporting configuration includes some or all fields in an IE ServingCellConfigCommon.

[0132] As an example, the first reporting configuration includes some or all fields in an IE ServingCellConfig.

[0133] As an example, the first reporting configuration at least 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.

[0134] As an example, the first reporting configuration at least 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.

[0135] As a sub-example of the above example, the second resource set includes one or more RS resources.

[0136] As a sub-example of the above example, the resources in the second resource set include at least one of an antenna port, a TCI state, QCL information, a time-frequency resource, a time-frequency code resource, a beam, an RS resource, a vector, or a matrix.

[0137] As an example, the reporting type indicates at least one of periodic reporting, semi-persistent reporting, aperiodic reporting, or event-triggered reporting.

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

[0139] As an example, the first channel information block includes CSI (channel state information).

[0140] As an example, the CSI includes beam information.

[0141] As an example, the CSI includes compressed CSI.

[0142] As an example, the compressed CSI is non-codebook-based channel information.

[0143] As an example, the target receiver of the compressed CSI does not know the channel parameters recovered based on the compressed CSI for the sender of the compressed CSI.

[0144] As an example, the compressed CSI is artificial-intelligence- or machine-learning-based channel information.

[0145] As an example, the compressed CSI is NeuralNetwork-based channel information.

[0146] As an example, the compressed CSI is ConventionalNeuralNetworks (CNN)-based channel information.

[0147] As an example, the first channel information block includes a channel matrix.

[0148] As an example, the first channel information block includes at least one of the eigenvalues or eigenvectors of the channel.

[0149] As an example, the first channel information block includes one of beam information, predicted CSI, or compressed CSI.

[0150] As an example, the first channel information block includes at least one of PMI (Precoding Matrix Indicator), CRI (CSI-RS Resource Indicator), CQI (Channel quality indicator), RI (Rank Indicator), layer indicator (Layer Indicator, LI), SS / PBCH block resource indicator (SS / PBCH Block Resource indicator, SSBRI), RSRP, SINR (signal-to-noise and interference ratio), capability index, TDCP (Time domain channel properties), or confidence information.

[0151] As an example, the first channel information block includes at least one of a resource indicator, RSRP (reference signal received power), PMI, CQI, SINR, channel matrix, eigenvalue of the channel, or eigenvector of the channel; the resource indicator is used to indicate a beam or RS resource.

[0152] As an example, the first channel information block is non-codebook based.

[0153] As an example, the first channel information block includes a resource indicator, and the resource indicator is used to indicate a beam or RS (reference signal) resource.

[0154] As an example, the first channel information block includes at least one of a resource indicator or RSRP (reference signal received power), and the resource indicator is used to indicate a beam or RS resource.

[0155] As an example, the beam information includes a resource indicator, and the resource indicator is used to indicate a beam or RS resource.

[0156] As an example, the beam information includes at least one of a resource indicator or RSRP (reference signal received power), and the resource indicator is used to indicate a beam or RS resource.

[0157] As an example, the resource indication is used to indicate one of a beam, a CSI-RS (Channel State Information Reference Signal) resource, or a synchronization signal resource.

[0158] As an example, the resource indication is a CRI (CSI-RS Resource Indicator) or an SS / PBCH block resource indicator (SSBRI).

[0159] As an example, the synchronization signal resource includes at least the resources occupied by the synchronization signal.

[0160] As an example, the synchronization signal resource is an SSB (Synchronization Signal Block).

[0161] As an example, the synchronization signal resource is an SS / PBCH (Synchronization Signal / Physical Broadcast CHannel) block resource.

[0162] 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 a PMI, a CQI, and an RI.

[0163] As an example, the first channel information block is generated based on inference, and the first channel information block includes at least one of a resource indication, an RSRP, a channel matrix, an eigenvalue of a channel, or an eigenvector of a channel; the resource indication is used to indicate a beam or an RS resource.

[0164] 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 a PMI, a CQI, an RI, a CRI, an SSBRI, an RSRP, and a SINR.

[0165] As an example, the first channel information block is generated based on inference, and the first channel information block includes at least one of a resource indication, an RSRP, a channel matrix, an eigenvalue of a channel, an eigenvector of a channel, or compressed CSI; the resource indication is used to indicate a beam or an RS resource.

[0166] As an example, the generation of the first channel information block includes: the calculation or inference of the first channel information block.

[0167] As an embodiment, the first channel information block is generated based on inference; the generation of the first channel information block includes: the inference of the first channel information block.

[0168] As an embodiment, the first channel information block is generated based on inference; the generation of the first channel information block includes: in order to obtain the inference of the first channel information block.

[0169] As an 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 performs a first operation, the first channel information block depends on the output of the first operation, and the first operation includes inference.

[0170] As an embodiment, the first channel information block is generated based on inference, and the first channel information block is calculated or generated by artificial intelligence or machine learning.

[0171] As an embodiment, the generation of the first channel information block occupies M processing resources, where M is a positive integer.

[0172] As an embodiment, 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 the capability information of the first node.

[0173] As an embodiment, the processing resources are used for at least one of processing, computing, or inference.

[0174] As an embodiment, the processing resources are used for at least addition and multiplication operations.

[0175] As an embodiment, the processing resources are used for at least convolution operations.

[0176] As an embodiment, a processing resource is a processing unit.

[0177] As an embodiment, a processing resource belongs to a processing unit.

[0178] As an embodiment, the processing resources include computing power resources.

[0179] As an embodiment, the inference includes AI inference.

[0180] As an embodiment, that the first channel information block is generated based on inference includes: the generation of the first channel information block is based on training.

[0181] As an example, the first channel information block is generated based on inference, including that the generation of the first channel information block uses an AI model.

[0182] As an example, the first channel information block is generated based on inference, including that information generated based on artificial intelligence or machine learning is used in the generation of the first channel information block.

[0183] As an example, the first channel information block is generated based on inference, including that information generated based on a Neural Network is used in the generation of the first channel information block.

[0184] As an example, the first channel information block is generated based on inference, including that information generated based on a CNN (Conventional Neural Networks, convolutional neural network) is used in the generation of the first channel information block.

[0185] As an example, the first channel information block is generated based on inference, including that the first channel information block includes information generated based on artificial intelligence or machine learning.

[0186] As an example, the first channel information block is generated based on inference, including that the first channel information block includes information generated based on a Neural Network.

[0187] As an example, the first channel information block is generated based on inference, including that the first channel information block includes information generated based on a CNN (Conventional Neural Networks).

[0188] As an example, the first channel information block is generated based on inference, including that the generation of the first channel information block corresponds to a first identifier.

[0189] As an example, for the case where the first channel information block is generated based on inference, how to generate the first channel information block is determined by the manufacturer of the first node itself or is implementation-related. The following describes a typical but non-limiting implementation manner:

[0190] The first node measures RS resources for channel measurement to obtain a 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 or its eigenvector is input into an AI model, and the output of the AI model is used to obtain the first channel information block.

[0191] If the first channel information block requires the first node to estimate interference (including noise), the first node may measure the RS resources for interference measurement to obtain the measured interference.

[0192] In one implementation, the measured interference is also input into the AI model.

[0193] In another implementation, the measured interference is not input into the AI model, and the output of the AI model and the measured interference are jointly used to generate the first channel information block.

[0194] 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 itself.

[0195] As an example, 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.

[0196] 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 the AI model.

[0197] As an example, the first channel information block not being generated based on inference includes: the information generated based on artificial intelligence or machine learning is not used in the generation of the first channel information block.

[0198] As an example, the first channel information block not being generated based on inference includes: the information generated based on the Neural Network is not used in the generation of the first channel information block.

[0199] As an example, the first channel information block not being generated based on inference includes: the information generated based on CNN (Conventional Neural Networks) is not used in the generation of the first channel information block.

[0200] As an example, the first channel information block not being generated based on inference includes: the first channel information block does not include the information generated based on artificial intelligence or machine learning.

[0201] As an example, the first channel information block not being generated based on inference includes: the first channel information block does not include the information generated based on the Neural Network.

[0202] As an example, that the first channel information block is not generated based on inference includes: the first channel information block does not include information generated based on a CNN (Convolutional Neural Networks).

[0203] As an example, that the first channel information block is not generated based on inference includes: the generation of the first channel information block does not correspond to a first type of identifier.

[0204] As an example, for the case where 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 itself, or is implementation-related. The following describes a typical but non-limiting implementation manner:

[0205] The first node measures the RS 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; the channel parameter matrix H r×t is power-adjusted, and the adjusted channel parameter matrix is where P is the assumed ratio of PDSCH EPRE to CSI-RS EPRE; under the condition of using the precoding matrix W t×l , the precoded channel parameter matrix is where l is the rank or the number of layers. In one case, l is a positive integer not greater than t, and in another case, the precoding matrix is the identity matrix, and at this time 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), and the first configuration information block also indicates the RS resources for interference measurement. The first node can measure one or more transmission opportunities of the RS resources for interference measurement to obtain accurate measured interference. Generally, the calculation of the target information depends on receiver performance or hardware-related factors such as the modulation method.

[0206] As an example, the first identifier is a non-negative integer.

[0207] As an example, the first identifier is a string.

[0208] As an example, the first identifier is different from the reporting configuration identifier of the first channel information block.

[0209] As an example, the first identifier is used to identify an AI model.

[0210] As an example, the first identifier is used to identify an AI model, and the first channel information block is generated based on the inference using the AI model identified by the first identifier.

[0211] As an example, the first identifier is used by the first node to determine an AI model.

[0212] As an example, the first identifier is used by the first node to determine the AI model used for the first operation in this application.

[0213] As an example, the first identifier is used to identify an AI entity.

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

[0215] As an example, the advantages of the above method include that by using the first identifier to identify an AI model / entity / function, the design is simplified and the understanding of different AI entities or functions is unified among multiple nodes.

[0216] As an example, the first identifier is used to identify or indicate a resource set.

[0217] As an example, the first identifier is used to identify or indicate a resource set, and the measurement of a resource set is used to obtain a training data set.

[0218] As an example, the first identifier is used to identify or indicate a resource set, and the resource set identified or indicated by the first identifier includes one or more RS resources.

[0219] As an example, the first identifier is used to identify or indicate a training data set.

[0220] As an example, the advantages of the above method include that by identifying an AI training or an AI training data set to recognize the inference generated by this AI training or AI training data set, a consensus is established among different AI functions, further simplifying the design.

[0221] As an example, the first type of identifier is a non - negative integer.

[0222] As an example, the first type of identifier is a string.

[0223] As an example, the first type of identifier is different from the reporting configuration identifier of the first channel information block.

[0224] As an example, the first type of identifier is used to identify an AI model.

[0225] As an example, the first type of identifier is used to identify an AI model, and the channel information generated based on inference is generated based on the inference using the AI model identified by the first type of identifier.

[0226] As an example, the first type of identifier is used by the first node to determine an AI model.

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

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

[0229] As an example, the advantages of the above method include that by using the first type of identifier to identify an AI model / entity / function, the design is simplified and the understanding of different AI entities or functions is unified among multiple nodes.

[0230] As an example, the first type of identifier is used to identify or indicate a resource set.

[0231] As an example, the first type of identifier is used to identify or indicate a resource set, and the measurement of the resource set is used to obtain a training data set.

[0232] As an example, the first type of identifier is used to identify or indicate a resource set, and the resource set identified or indicated by the first type of identifier includes one or more RS resources.

[0233] As an example, the first type of identifier is used to identify or indicate a training data set.

[0234] As an example, the advantages of the above method include that by identifying an AI training or an AI training data set to recognize the inference generated by this AI training or AI training data set, a consensus is established among different AI functions, further simplifying the design.

[0235] Example 2

[0236] Example 2 illustrates a schematic diagram of a network architecture according to an embodiment of the present application, as shown in the appendix Figure 2 as shown.

[0237] Appendix Figure 2Describes the network architecture 200. The network architecture 200 is a 5G NR (New Radio) / LTE (Long-Term Evolution) / LTE-A (Long-Term Evolution Advanced) system, or the network architecture 200 is a 5G+ network architecture, or the network architecture 200 is a 6G network architecture, or the network architecture 200 is a network architecture adopted in the future continuous evolution of 3GPP; the network architecture 200 can be referred to as 5GS (5G System) / EPS (Evolved Packet System), or the network architecture 200 can be referred to as 6GS (6G System); the 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 be interconnected with other access networks, but these entities / interfaces are not shown for simplicity. As shown, the network architecture 200 provides packet switching services. However, those skilled in the art will easily understand that the various concepts presented throughout this application can be extended to networks providing circuit switching 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 towards UE 201. Node 203 can be connected to other nodes 204 via the Xn interface (e.g., backhaul) / X2 interface. Node 203 can 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 (Transmit Receive Point), or some other appropriate term. The core network 210 is 5GC (5G Core Network) / EPC (Evolved Packet Core), or the core network 210 is 6GC; node 203 provides an access point for UE 201 to the core network 210.Examples of the UE 201 include cellular phones, smart phones, Session Initiation Protocol (SIP) phones, laptop computers, 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 Internet of Things devices, machine type communication devices, land vehicles, automobiles, wearable devices, or any other similar functional devices. Those skilled in the art may also refer to the UE 201 as a mobile station, subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, or some other suitable term. The node 203 is connected to the core network 210 through the 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 Date Network Gateway) / UPF 213. The MME / AMF / SMF 211 is a control node that processes the 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 Protocal) packets are transmitted through the S-GW / UPF 212, and the S-GW / UPF 212 itself is connected to the P-GW / UPF 213. The P-GW provides UE IP address allocation and other functions. The P-GW / UPF 213 is connected to the Internet service 230. The Internet service 230 includes carrier-corresponding Internet protocol services, specifically including the Internet, intranet, IMS (IP Multimedia Subsystem), and packet switching services.

[0238] As an embodiment, the first node includes the UE 201.

[0239] As an embodiment, the second node includes the node 203.

[0240] As an embodiment, the second node includes the core network 210.

[0241] As an embodiment, the second node includes the node 203 and the core network 210.

[0242] As an embodiment, the radio link between the UE 201 and the node 203 includes a cellular network link.

[0243] As an embodiment, the processing resources in this application are in the UE 201.

[0244] As an embodiment, the storage resources in this application are in the UE 201.

[0245] As an embodiment, the first resource group in this application is in the UE 201.

[0246] As an embodiment, the second resource group in this application is in the UE 201.

[0247] As an embodiment, the first information block is generated in the UE 201.

[0248] As an embodiment, the sender of the first information block includes the UE 201.

[0249] As an embodiment, the target receiver of the first information block includes the node 203.

[0250] As an embodiment, the first channel information block is generated in the UE 201.

[0251] As an embodiment, the sender of the first channel information block includes the UE 201.

[0252] As an embodiment, the target receiver of the first channel information block includes the node 203.

[0253] As an embodiment, the first reporting configuration is generated in the node 203.

[0254] As an embodiment, the sender of the first reporting configuration includes the node 203.

[0255] As an embodiment, the target receiver of the first reporting configuration includes the UE 201.

[0256] Example 3

[0257] Embodiment 3 exemplifies a schematic diagram of an embodiment of the radio protocol architecture of the user plane and the control plane according to an embodiment of this application, as shown in the appendix Figure 3 as follows.

[0258] Example 3 shows a schematic diagram of an embodiment of a radio protocol architecture for a user plane and a control plane according to the present application, as shown in the appendix Figure 3 as shown 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 3The radio protocol architecture of the control plane 300 for the first communication node device (UE, gNB or RSU in V2X) and the second communication node device (gNB, UE or RSU in V2X), or between two UEs, is shown with 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 as PHY 301 in this document. 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 2 305 includes a MAC (Medium Access Control) sublayer 302, an RLC (Radio Link Control) sublayer 303, and a PDCP (Packet Data Convergence Protocol) sublayer 304, and these sublayers terminate at the second communication node device. The PDCP sublayer 304 provides multiplexing between different radio bearers and logical channels. The PDCP sublayer 304 also provides security by encrypting data packets and provides handover support for the first communication node device between the second communication node devices. The RLC sublayer 303 provides segmentation and reassembly of upper layer data packets, retransmission of lost data packets, and reordering of data packets to compensate for disordered reception due to HARQ. The MAC sublayer 302 provides multiplexing between logical and transport channels. The MAC sublayer 302 is also responsible for allocating various radio resources (e.g., resource blocks) in a cell between the first communication node devices. The MAC sublayer 302 is also responsible for HARQ operations. The RRC (Radio Resource Control) sublayer 306 in Layer 3 (L3 layer) of the control plane 300 is responsible for obtaining radio resources (i.e., radio bearers) and configuring the lower layers using RRC signaling between the second communication node device and the first communication node device. The radio protocol architecture of the user plane 350 includes Layer 1 (L1 layer) and Layer 2 (L2 layer). The radio protocol architecture for the first communication node device and the second communication node device in the user plane 350 is generally the same as the corresponding layers and sublayers in the control plane 300 for the physical layer 351, the PDCP sublayer 354 in the L2 layer 355, the RLC sublayer 353 in the L2 layer 355, and the MAC sublayer 352 in the L2 layer 355, but the 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 further includes an SDAP (Service Data Adaptation Protocol) sub-layer 356. The SDAP sub-layer 356 is responsible for the mapping between QoS flows and data radio bearers (DRBs) to support the diversity of services. Although not shown, the first communication node device may have several upper layers above the L2 layer 355, including a network layer (e.g., IP layer) terminated at the P-GW on the network side and an application layer terminated at the other end of the connection (e.g., a remote UE, a server, etc.).

[0259] As an example, the Figure 3 radio protocol architecture in is applicable to the first node.

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

[0261] As an example, the higher layer in this application refers to the layer above the physical layer.

[0262] As an example, the first information block is generated in the RRC sub-layer 306.

[0263] As an example, the first information block is generated in the PHY301 or the PHY351.

[0264] As an example, the first information block is generated in the MAC sub-layer 302 or the MAC sub-layer 352.

[0265] As an example, the first reporting configuration is generated in the RRC sub-layer 306.

[0266] As an example, the reference signal in the first resource set is generated in the PHY301 or the PHY351.

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

[0268] As an example, the first channel information block is generated in the PHY301 or the PHY351.

[0269] Example 4

[0270] 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 the attached Figure 4 shown. The attached Figure 4It is a block diagram of a first communication device 410 and a second communication device 450 that communicate with each other in an access network.

[0271] The first communication device 410 includes a controller / processor 475, a memory 476, a receiving processor 470, a transmitting processor 416, a multi-antenna receiving processor 472, a multi-antenna transmitting processor 471, a transmitter / receiver 418, and an antenna 420.

[0272] 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.

[0273] 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 the functions of the L2 layer. In the 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 operations, retransmission of lost packets, and signaling to the second communication device 450. The transmitting processor 416 and the multi-antenna transmitting processor 471 implement various signal processing functions for the L1 layer (i.e., the physical layer). The transmitting processor 416 implements coding 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), M-quadrature amplitude modulation (M-QAM)). The multi-antenna transmitting processor 471 performs digital space precoding on the coded and modulated symbols, including codebook-based precoding and non-codebook-based precoding, and beamforming processing, to generate one or more parallel streams. The transmitting processor 416 then maps each parallel stream to subcarriers, multiplexes the modulated symbols with reference signals (e.g., pilots) in the time domain and / or frequency domain, and then uses the inverse fast Fourier transform (IFFT) to generate a physical channel carrying a time-domain multi-carrier symbol stream. Subsequently, the multi-antenna transmitting processor 471 performs transmission analog precoding / beamforming operations on the time-domain multi-carrier symbol stream. Each transmitter 418 converts the baseband multi-carrier symbol stream provided by the multi-antenna transmitting processor 471 into a radio frequency stream, and then provides it to different antennas 420.

[0274] 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 signals through its respective antenna 452. Each receiver 454 recovers the information modulated onto the radio frequency carrier, and converts the radio frequency stream into a baseband multi-carrier symbol stream and provides it to the receive processor 456. The receive processor 456 and the multi-antenna receive processor 458 perform various signal processing functions of the L1 layer. The multi-antenna receive processor 458 performs receive analog precoding / beamforming operations on the baseband multi-carrier symbol stream from the receivers 454. The receive processor 456 uses the Fast Fourier Transform (FFT) to convert the baseband multi-carrier 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 receive processor 456, where the reference signal will be used for channel estimation, and the data signal recovers any parallel streams destined for the second communication device 450 after multi-antenna detection in the multi-antenna receive processor 458. The symbols on each parallel stream are demodulated and recovered in the receive processor 456, and soft decisions are generated. Subsequently, the receive processor 456 decodes and de-interleaves the soft decisions to recover the upper layer data and control signals transmitted by the first communication device 410 on the physical channel. Subsequently, the upper layer data and control signals are provided to the controller / processor 459. The controller / processor 459 performs the functions of the L2 layer. The controller / processor 459 may be associated with a memory 460 that stores program code and data. The memory 460 may be referred to as a computer-readable medium. In the DL, the controller / processor 459 provides demultiplexing between the transmission and the logical channels, packet reassembly, decryption, header decompression, control signal processing to recover the upper layer data packets from the core network. Subsequently, the upper layer data packets are provided to all protocol layers above the L2 layer. Various control signals may also be provided to the L3 for L3 processing. The controller / processor 459 is also responsible for error detection using the acknowledgment (ACK) and / or negative acknowledgment (NACK) protocols to support HARQ operations.

[0275] 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 an upper layer data packet to a controller / processor 459. The data source 467 represents all protocol layers above the L2 layer. Similar to the transmit function 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, and implements L2 layer functions for the user plane and the control plane. The controller / processor 459 is also responsible for HARQ operations, retransmission of lost packets, and signaling to the first communication device 410. A transmit processor 468 performs modulation mapping and channel coding processing. A multi-antenna transmit processor 457 performs digital multi-antenna spatial precoding, including codebook-based precoding and non-codebook-based precoding, and beamforming processing. Subsequently, the transmit processor 468 modulates the generated parallel streams into multi-carrier / single-carrier symbol streams, and after passing through analog precoding / beamforming operations in the multi-antenna transmit processor 457, provides them to different antennas 452 via a transmitter 454. Each transmitter 454 first converts the baseband symbol stream provided by the multi-antenna transmit processor 457 into a radio frequency symbol stream and then provides it to the antenna 452.

[0276] In the transmission from the second communication device 450 to the first communication device 410, the functions at the first communication device 410 are similar to the receive functions 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 a radio frequency signal through its corresponding antenna 420, converts the received radio frequency signal into a baseband signal, and provides the baseband signal to a multi-antenna receive processor 472 and a receive processor 470. The receive processor 470 and the multi-antenna receive processor 472 jointly implement the functions of the L1 layer. A controller / processor 475 implements 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 a computer-readable medium. The controller / processor 475 provides demultiplexing between transport and logical channels, packet reassembly, decryption, header decompression, and control signal processing to recover the upper layer data packet from the second communication device 450. The upper layer data packet from the controller / processor 475 may be provided to the core network. The controller / processor 475 is also responsible for error detection using the ACK and / or NACK protocols to support HARQ operations.

[0277] As an 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 together with the at least one processor. The second communication device 450 is at least configured to: receive a first reporting configuration; send 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, and 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 reasoning; only when the first channel information block is not generated based on reasoning, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0278] As an embodiment, the second communication device 450 includes: a memory storing a computer-readable instruction program, the computer-readable instruction program generating actions when executed by at least one processor, the actions including: receiving a first reporting configuration; 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, and 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 reasoning; only when the first channel information block is not generated based on reasoning, 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 an example, the first communication device 410 includes: at least one processor and at least one memory, where the at least one memory includes computer program code; the at least one memory and the computer program code are configured to be used together with the at least one processor. The first communication device 410 is at least configured to: send a first reporting configuration; receive a first channel information block; where 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, and 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 reasoning; only when the first channel information block is not generated based on reasoning, 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 an example, the first communication device 410 includes: a memory storing a computer-readable instruction program, and the computer-readable instruction program generates actions when executed by at least one processor. The actions include: sending a first reporting configuration; receiving a first channel information block; where 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, and 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 reasoning; only when the first channel information block is not generated based on reasoning, 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 an example, the first node in the present application includes the second communication device 450.

[0282] As an example, the second node in the present application includes the first communication device 410.

[0283] 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, 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, the memory 476} is used to send the first reporting configuration in this application.

[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, the data source 467} is used to receive the reference signal in the first resource set 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, the memory 476} is used to send the reference signal in the first resource set 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, the data source 467} is used to receive the reference signal in the second resource set 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, the memory 476} is used to send the reference signal in the second resource set in this application.

[0286] As an example, at least one of {the antenna 452, the transmitter 454, the transmitting processor 468, the multi-antenna transmitting processor 457, the controller / processor 459, the memory 460, the data source 467} is used to send the first information block in this application; at least one of {the antenna 420, receiver 418, the receiving processor 470, the multi-antenna receiving processor 472, the controller / processor 475, the memory 476} is used to receive the first information block in this application.

[0287] As an example, at least one of {the antenna 452, the transmitter / receiver 454, the transmit processor 468, the multi-antenna transmit processor 457, the receive processor 456, the multi-antenna receive processor 458, the controller / processor 459, the memory 460, the data source 467} is used for the generation of the first channel information block in this application.

[0288] As an example, at least one of {the antenna 452, the transmitter / receiver 454, the transmit processor 468, the multi-antenna transmit processor 457, the receive processor 456, the multi-antenna receive processor 458, the controller / processor 459, the memory 460, the data source 467} is used for the first operation in this application.

[0289] As an example, at least one of {the antenna 452, the transmitter 454, the transmit processor 468, the multi-antenna transmit processor 457, the receive processor 456, the multi-antenna receive processor 458, the controller / processor 459, the memory 460, the data source 467} is used for the first operation in this application; at least one of {the antenna 420, the receiver 418, the receive processor 470, the multi-antenna receive processor 472, the transmit processor 416, the multi-antenna transmit processor 471, the controller / processor 475, the memory 476} is used for the second operation in this application.

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

[0291] Example 5

[0292] Embodiment 5 exemplifies a flowchart of a transmission according to an embodiment of this application; as shown in the appendix Figure 5 shown. In the appendix Figure 5 In it, the second node N1 and the first node U1 are communication nodes for air interface transmission. In the appendixFigure 5 Among them, the steps in boxes F51 to F56 are optional respectively.

[0293] For the second node N1, deploy a second operation in step S5101; receive a first information block in step S5102; send a first reporting configuration in step S511; send an RS in a first resource set in step S5103; execute the second operation in step S5104; receive a first channel information block in step S512.

[0294] For the first node U1, deploy a first operation in step S5201; send a first information block in step S5202; receive a first reporting configuration in step S521; receive an RS in a first resource set in step S5203; execute the first operation in step S5204; send a first channel information block in step S522.

[0295] 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, and 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 reasoning; only when the first channel information block is not generated based on reasoning, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0296] As an embodiment, the first node U1 is the first node in this application.

[0297] As an embodiment, the second node N1 is the second node in this application.

[0298] As an embodiment, the air interface between the second node N1 and the first node U1 includes a wireless interface between a base station device and a user equipment.

[0299] As an embodiment, the air interface between the second node N1 and the first node U1 includes a wireless interface between a relay node device and a user equipment.

[0300] As an embodiment, the air interface between the second node N1 and the first node U1 includes a wireless interface between user equipments.

[0301] As an example, the second node N1 is the serving cell maintenance base station of the first node U1.

[0302] As an example, the transmission of the first reporting configuration is later than the transmission of the first information block.

[0303] As an example, when the steps in the dashed box F53 exist, the method in the first node for wireless communication includes: sending 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.

[0304] As an example, when the steps in the dashed box F53 exist, the method in the second node for 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.

[0305] As an example, when the steps in the dashed box F54 exist, the method 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.

[0306] As an example, when the steps in the dashed box F54 exist, the method in the second node for wireless communication includes: sending 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, when the steps in the dashed box F52 exist, the method in the first node for wireless communication includes: deploying a first operation.

[0308] As an example, when the steps in the dashed box F56 exist, the method in the first node for wireless communication includes: performing a first operation.

[0309] 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.

[0310] As an example, the first node deploys a first operation.

[0311] As an example, the deploying of the first operation includes: obtaining the first operation.

[0312] As an example, the deploying of the first operation includes: loading the first operation.

[0313] As an example, the deploying of the first operation includes: sending a request to load the first operation.

[0314] As an example, the first operation is for CSI prediction, beam prediction, or CSI compression.

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

[0316] As an example, the first node executes the first operation, and the second node executes the second operation; wherein, the first channel information block is generated based on inference.

[0317] As an example, when the steps in the dashed box F51 exist, the method in the second node for wireless communication includes: deploying the second operation.

[0318] As an example, when the steps in the dashed box F55 exist, the method in the second node for wireless communication includes: executing the second operation.

[0319] As an example, the second node executes the second operation; wherein, the first channel information block is generated based on inference, the first node executes the 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 an input of the second operation to generate a second CSI.

[0320] As an example, the second node deploys the second operation.

[0321] As an example, the deploying of the second operation includes: obtaining the second operation.

[0322] As an example, the deploying of the second operation includes: loading the second operation.

[0323] As an example, the deploying of the second operation includes: sending a request to load the second operation.

[0324] As an example, the first operation is for CSI compression, and the second operation is for CSI recovery.

[0325] As an example, the first channel information block is generated based on inference. The output of the first operation includes first CSI. The first channel information block carries the first CSI, and the first CSI is used by the second node as an input to a second operation to generate second CSI.

[0326] As an example, the execution of the second operation is later than the execution of the first operation.

[0327] As an example, the first reporting configuration is transmitted on a PDSCH (Physical Downlink Shared Channel).

[0328] As an example, the first channel information block is transmitted on a PUCCH (Physical Uplink Control Channel).

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

[0330] As an example, the first information block is transmitted on a PUCCH (Physical Uplink Control Channel).

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

[0332] Example 6

[0333] Embodiment 6 exemplifies 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 the present application; as shown in the appendix Figure 6 shown; processing resources #1,..., processing resources #n,... represent the processing resources in the first resource group.

[0334] 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.

[0335] 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.

[0336] In the above method, the channel information generated based on inference occupies only the processing resources in the first resource group, and the 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, with high flexibility and strong adaptability.

[0337] Example 7

[0338] Embodiment 7 exemplifies a schematic diagram of the relationship between the first channel information block generated based on inference according to another embodiment of the present application, and the first resource group or the second resource group; as shown in the appendix Figure 7 shown; processing resources #1,..., processing resources #n,... represent the processing resources in the first resource group, or, processing resources #1,..., processing resources #n,... represent the processing resources in the second resource group.

[0339] 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.

[0340] 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.

[0341] In the above method, the processing resources occupied by the channel information generated based on inference can be in the first resource group or in the second resource group, while the reporting of the channel information not generated based on inference only occupies the processing resources in the second resource group.

[0342] As an embodiment, the first channel information block is generated based on inference; the generation of the first channel information block preferentially occupies the processing resources in the first resource group.

[0343] 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.

[0344] 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.

[0345] 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.

[0346] In the above method, the generation of less channel information occupies the processing resources in the second resource group, and the generation of more channel information occupies the processing resources in the first resource group; the advantages include: accelerating the generation of channel information, improving the channel estimation accuracy, and reducing the reporting delay.

[0347] Example 8

[0348] Example 8 exemplifies a schematic diagram of the relationship between the first channel information block generated based on inference according to another example of the present application and the first resource group or the second resource group; as shown in the appendix Figure 8 shown; Processing resources #1,..., processing resources #n,... represent the processing resources in the second resource group.

[0349] In Example 8, the first channel information block is generated based on inference; only when the reported amount included in the first channel information block belongs to the first reported amount set, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group; the first reported amount set includes one or more reported amounts.

[0350] 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 reported amount included in the first channel information block.

[0351] As an example, the first reported amount set includes at least one of a resource indicator or an RSRP.

[0352] As an embodiment, the first reporting quantity set includes reporting quantities for beam prediction.

[0353] As an embodiment, the first reporting quantity set includes beam information.

[0354] As an embodiment, the first channel information block includes a resource indication, and the resource indication is used to indicate a beam or an RS (reference signal) resource.

[0355] As an embodiment, the first channel information block includes at least one of a resource indication or an RSRP (reference signal received power), and the resource indication is used to indicate a beam or an RS resource.

[0356] As an embodiment, the beam information includes a resource indication, and the resource indication is used to indicate a beam or an RS resource.

[0357] As an embodiment, the beam information includes at least one of a resource indication or an RSRP (reference signal received power), and the resource indication is used to indicate a beam or an RS resource.

[0358] As an embodiment, the resource indication is used to indicate one of a beam, a CSI-RS (Channel State Information Reference Signal) resource, or a synchronization signal resource.

[0359] As an embodiment, the resource indication is a CRI (CSI-RS Resource Indicator) or an SS / PBCH block resource indicator (SS / PBCH Block Resource indicator, SSBRI).

[0360] As an embodiment, the synchronization signal resource includes at least the resources occupied by the synchronization signal.

[0361] As an embodiment, the synchronization signal resource is an SSB (Synchronization Signal Block).

[0362] As an example, the synchronization signal resource is an SS / PBCH (Synchronization Signal / Physical Broadcast CHannel) block resource.

[0363] As an example, the reporting amount for CSI compression does not belong to the first reporting amount set.

[0364] As an example, the reporting amount for CSI prediction does not belong to the first reporting amount set.

[0365] As an example, the channel matrix does not belong to the first reporting amount set.

[0366] As an example, PMI or CQI does not belong to the first reporting amount set.

[0367] Example 9

[0368] Embodiment 9 exemplifies a schematic diagram in which a first channel information block according to an embodiment of the present application is generated based on inference; as shown in the appendix Figure 9 as follows.

[0369] In Embodiment 9, the first channel information block is generated based on inference;

[0370] The generation of the first channel information block based on inference includes a first identifier corresponding to the generation of the first channel information block;

[0371] 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.

[0372] 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; 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.

[0373] As a sub - embodiment of the above - mentioned embodiment, only when the size of the parameters in the AI model identified by the first identifier is less than a second threshold, the at least one processing resource occupied by the generation of the first channel information block belongs to the second resource group.

[0374] As an example, the first identifier is used to identify the 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.

[0375] As an example, the first identifier is used to identify the 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.

[0376] As an example, the first identifier is used to identify the 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.

[0377] In the above method, whether the processing resources occupied by the channel information generated based on inference belong to the processing resources in the first resource group or the second resource group is determined for each identifier; the advantages include: being applicable to different AI models / entities / functions, with high flexibility.

[0378] Example 10

[0379] Embodiment 10 exemplifies a schematic diagram of the processing resources occupied by the generation of the first channel information block according to an embodiment of the present application; as shown in the appendix Figure 10 as follows.

[0380] 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.

[0381] 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.

[0382] As an example, RRC parameters different from the first reporting configuration indicate 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] In the above method, the base station indicates whether the processing resources occupied by a channel information generated based on inference belong to the processing resources in the first resource group or the second resource group. The advantages include: the base station can flexibly control / adjust the occupation of processing resources, and it also ensures consistent understanding between the transceiver ends.

[0384] Examples 11A - 11C

[0385] Embodiments 11A - 11C respectively illustrate schematic diagrams of generating a first channel information block corresponding to a first identifier according to an embodiment of the present application; as shown in the appendix. Figures 11A - 11C As shown.

[0386] 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.

[0387] In the above method, the generation of the first channel information block corresponds to the first identifier indicated by the first reporting configuration.

[0388] As an embodiment, the advantages of the above method include: simplifying the design and flexibly configuring the corresponding first identifier for the first channel information block.

[0389] 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.

[0390] As an 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 performs a first operation, the first operation includes inference, the first channel information block depends on the output of the first operation, and the first operation corresponds to the first identifier.

[0391] As an embodiment, the first operation is training - based or AI - based.

[0392] As an embodiment, the first operation includes inference.

[0393] As an embodiment, the first operation includes an AI entity.

[0394] As an embodiment, the first operation includes an AI entity for inference.

[0395] As an embodiment, the first operation includes a part of an AI entity.

[0396] As an embodiment, the first operation includes the part of an AI entity for inference.

[0397] As an embodiment, the first operation includes inference for obtaining the first channel information block.

[0398] As an example, the inference includes: AI (Artificial Intelligence) inference.

[0399] As an example, the first operation includes AI inference for obtaining CSI.

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

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

[0402] As an example, the first operation is used for the AI function.

[0403] As an example, the first operation is performed by the physical layer of the first node.

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

[0405] As an example, the model of the first operation is obtained through training.

[0406] As an example, the training of the first operation is performed by the first node.

[0407] As an example, the training of the first operation is performed by the target receiver of the first channel information block.

[0408] As an example, the training of the first operation is performed by the core network.

[0409] As an example, the training of the first operation is performed by an AI training producer.

[0410] As an example, the training of the first operation is performed by the MDA function (Management Data Analytics Function).

[0411] As an example, the training of the first operation is performed by the MDA function located at the first node.

[0412] As an example, the training of the first operation is performed by the MDA function located at the target receiver of the first channel information block.

[0413] As an example, the training of the first operation is performed by the NWDAF (Network Data Analytics Function).

[0414] As an example, the training of the first operation is performed by a producer of MDAS (Management Data Analytics Service).

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

[0416] As an example, the first operation needs to be deployed.

[0417] As an example, the first operation is obtained by loading.

[0418] As an example, the first operation is obtained by loading from the serving cell of the first node.

[0419] As an example, the first operation is obtained by loading from the maintenance base station of the serving cell of the first node.

[0420] As an example, the first node deploys the first operation.

[0421] As an example, the first operation does not need to be deployed.

[0422] As an example, the first operation is obtained by loading from the core network.

[0423] As an example, the first operation is based on artificial intelligence or machine learning.

[0424] As an example, the first operation is based on a Neural Network.

[0425] As an example, the first operation is based on CNN (Conventional Neural Networks).

[0426] As an example, the first operation includes preprocessing.

[0427] As an example, the first operation includes postprocessing.

[0428] As an example, the postprocessing includes DFT.

[0429] As an example, the postprocessing includes quantization.

[0430] As an example, the post-processing includes one or more of a transformation from the angular domain to the spatial domain, a transformation from the spatial domain to the angular domain, a transformation from the time domain to the frequency domain, and a transformation from the frequency domain to the time domain.

[0431] As an example, the post-processing includes truncation and / or padding.

[0432] As an example, the first operation includes one or more of convolution, pooling, concatenation, and activation.

[0433] As an example, the first operation includes a fully-connected layer.

[0434] As an example, the first operation includes a pooling layer.

[0435] As an example, the first operation includes at least one convolutional layer.

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

[0437] As an example, an encoding layer includes at least one convolutional layer and one pooling layer.

[0438] As an example, in the 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 the fully-connected layer; the fully-connected layer converts the vector into an output.

[0439] As an example, some or all of the convolutional kernel size, number of convolutional layers, convolutional stride, pooling kernel size, pooling kernel stride, pooling function, activation function, and number of feature maps of the first operation are obtained through training.

[0440] As an example, some or all of the convolutional kernel, pooling kernel, pooling function, activation function, parameters of the pooling function, and parameters of the activation function of the first operation are obtained through training.

[0441] As an example, the output of the first operation includes channel information.

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

[0443] As an example, the output of the first operation includes a channel matrix.

[0444] As an example, the output of the first operation includes CSI.

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

[0446] As an example, the output of the first operation includes non-codebook-based CSI.

[0447] As an example, the output of the first operation includes channel impulse response.

[0448] As an example, the output of the first operation includes small-scale characteristics.

[0449] As an example, the output of the first operation is used to determine one or more precoding matrices.

[0450] As an example, the first operation includes AI or machine learning-based CSI compression.

[0451] As an example, the first operation includes an encoder for AI or machine learning-based CSI compression.

[0452] As an example, the first operation includes AI or machine learning-based CSI prediction or CSI estimation.

[0453] As an example, the first operation includes AI or machine learning-based beam management.

[0454] As an example, the beam management includes at least one of beam prediction, beam switching, beam failure prediction, or beam failure recovery.

[0455] As an example, the input of the first operation includes measurements obtained based on at least one RS resource.

[0456] As an example, the input of the first operation includes channel measurements obtained based on CSI-RS resources or SS / PBCH block resources.

[0457] As an example, the input of the first operation includes interference measurements obtained based on CSI-RS resources or CSI-IM resources.

[0458] As an example, the input of the first operation includes the reception quality of at least one physical channel or physical signal.

[0459] As an example, the input of the first operation includes a matrix or vector obtained after preprocessing a channel matrix obtained from measurements based on at least one RS resource.

[0460] As an example, the AI function includes an AI inference function.

[0461] As an example, the AI function includes an AI training function.

[0462] As an example, the AI function includes an AI management function.

[0463] As an example, the AI function includes AI performance monitoring.

[0464] As an example, the AI includes ML (Machine Learning).

[0465] As an example, the AI includes AI and ML.

[0466] As an example, the AI includes AI or ML.

[0467] As an example, the preprocessing includes one or more of quantization, DFT (Discrete Fourier Transform), matrix decomposition, matrix transformation or projection, transformation from spatial domain to angular domain, transformation from angular domain to spatial domain, transformation from frequency domain to time domain, transformation from time domain to frequency domain, truncation, padding, mapping, or labeling.

[0468] As an example, the preprocessing includes DFT (Discrete Fourier Transform).

[0469] As an example, the preprocessing includes one or more of matrix decomposition, matrix transformation or projection.

[0470] As an example, the preprocessing includes one or more of quantization, transformation from spatial domain to angular domain, transformation from angular domain to spatial domain, transformation from frequency domain to time domain, or transformation from time domain to frequency domain.

[0471] As an example, the preprocessing includes truncation and / or padding.

[0472] As an example, the preprocessing includes mapping.

[0473] As an example, the preprocessing includes mapping to a vector.

[0474] As an example, the preprocessing includes a label.

[0475] As an example, the label refers to labeling with a label.

[0476] As an example, the postprocessing includes DFT.

[0477] As an example, the post - processing includes quantization.

[0478] As an example, the post - processing includes one or more of a transformation from the angular domain to the spatial domain, a transformation from the spatial domain to the angular domain, a transformation from the time domain to the frequency domain, and a transformation from the frequency domain to the time domain.

[0479] As an example, the post - processing includes truncation and / or padding.

[0480] As an example, an encoding layer includes at least one convolutional layer and one pooling layer.

[0481] As an example, in the 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 converts the said one vector into an output.

[0482] As an example, that the first operation corresponds to the first identifier includes: the first operation is identified by the first identifier.

[0483] As an example, that the first operation corresponds to the first identifier includes: the AI model adopted by the first operation is identified by the first identifier.

[0484] As an example, that the first operation corresponds to the first identifier includes: the AI entity included in the first operation is identified by the first identifier.

[0485] As an example, that the first operation corresponds to the first identifier includes: the AI function to which the first operation is applied is identified by the first identifier.

[0486] As an example, the advantages of the above - mentioned method include that by using the first identifier to identify an AI entity or function, the design is simplified and the understanding of different AI entities or functions is unified among multiple nodes.

[0487] As an example, that the first operation corresponds to the first identifier includes: the AI entity that executes the first operation is identified by the first identifier.

[0488] As an example, that the first operation corresponds to the first identifier includes: the first identifier is used by the first node to determine the AI model adopted by the first operation.

[0489] As an example, the advantages of the above - mentioned method include that by using the first identifier to identify an AI model / entity / function, the design is simplified and the understanding of different AI entities / functions is unified among multiple nodes.

[0490] As an example, 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 for the set of RS resources is used to obtain the training data set for the first operation.

[0491] As an example, the first operation corresponding to the first identifier includes: the training for obtaining the first operation is identified by the first identifier.

[0492] As an example, the first operation corresponding to the first identifier includes: the data set for the training of the first operation is identified by the first identifier.

[0493] As an example, the benefits of the above method include that by identifying an AI training or an AI training data set to recognize the inference generated by this AI training or AI training data set, a consensus is established among different AI functions, further simplifying the design.

[0494] As an example, the first operation corresponding to the first identifier includes: the first operation performs spatial domain beam prediction for a second resource set based on the measurement of a first resource set, and the second resource set depends on the first identifier.

[0495] As an example, the benefits of the above method include reducing the RS overhead and reducing the feedback delay.

[0496] As an example, 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, and the second resource set depends on the first identifier.

[0497] As an example, the first operation corresponding to the first identifier includes: the first operation performs temporal beam prediction for a second resource set based on the historic measurement of a first resource set, and the second resource set depends on the first identifier.

[0498] As an example, the benefits of the above method include reducing the beam feedback delay and improving the real-time performance of beam acquisition.

[0499] As an example, the first operation corresponding to the first identifier includes: the first operation performs temporal channel information prediction for a second resource set based on the historic measurement of a first resource set, and the second resource set depends on the first identifier.

[0500] As an example, the benefits of the above method include reducing the channel information feedback delay and improving the real-time performance of channel information acquisition.

[0501] As an example, the output of the first operation is used to generate the first channel information block.

[0502] As an example, the first channel information block includes the output of the first operation.

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

[0504] As an example, the first channel information block includes the truncated and / or quantized output of the first operation.

[0505] As an example, after the output of the first operation is post-processed, it is used to generate the first channel information block.

[0506] As an example, after the output of the first operation is truncated and / or quantized, it is used to generate the first channel information block.

[0507] As an example, part or all of the output of the first operation, after being post-processed, is used to generate the first channel information block.

[0508] As an example, part or all of the output of the first operation, after being truncated and / or quantized, is used to generate the first channel information block.

[0509] As an example, the output of the first operation includes a first CSI, and the first CSI is used to generate the first channel information block.

[0510] As an example, the benefits of the above method include improving the CSI reporting performance by leveraging the advantages of the first operation, including more accurate reporting and / or lower overhead.

[0511] As an example, the first channel information block includes the first CSI.

[0512] As an example, after the first CSI is post-processed, it is used to generate the first channel information block.

[0513] As an example, the first channel information block includes the post-processed first CSI.

[0514] As an example, the first channel information block carries the post-processed first CSI.

[0515] As an example, the first CSI is used to generate the first channel information block after being truncated and / or quantized.

[0516] As an example, the first channel information block includes the first CSI after being truncated and / or quantized.

[0517] As an example, the first channel information block carries the first CSI after being truncated and / or quantized.

[0518] As an example, the first CSI includes one or more of PMI, CRI, CQI, RI, LI, SSBRI, RSRP, SINR, capability index, and TDCP.

[0519] 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.

[0520] As an example, the first CSI includes a channel matrix.

[0521] As an example, the first CSI includes an eigenvector.

[0522] As an example, the first CSI includes an eigenvector and an eigenvalue.

[0523] As an example, the first CSI includes precoding information.

[0524] As an example, the first CSI includes non-codebook-based precoding information.

[0525] As an example, the first CSI is used to determine at least one precoding matrix.

[0526] As an example, the first CSI indicates at least one precoding matrix.

[0527] As an example, the precoding matrix is in the spatial-frequency domain.

[0528] As an example, the precoding matrix is an angular-delay domain projection.

[0529] As an example, the first CSI includes information on the relative phases, amplitudes, and / or coefficients between multiple antenna ports.

[0530] As an example, the first CSI includes compressed CSI.

[0531] As an example, the first CSI includes predicted / estimated CSI.

[0532] As an example, how to generate the first channel information block based on the first operation is determined by the manufacturer of the first node itself or is implementation-related. A typical but non-limiting implementation is described below:

[0533] The first node first measures the RS resources 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 or its eigenvector is input into the AI model, and the output of the AI model is used to obtain the first channel information block.

[0534] If the first channel information block requires the first node to estimate interference (including noise), the first node may measure the RS resources for interference measurement to obtain the measured interference.

[0535] In one implementation, the measured interference is also input into the AI model.

[0536] In another implementation, the measured interference is not input into the AI model, and the output of the AI model and the measured interference are jointly used to generate the first channel information block.

[0537] 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 itself.

[0538] 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 the AI model identified by the first identifier, or the first channel information block is generated in the AI entity identified by the first identifier, or the first channel information block is used for the AI function identified by the first identifier.

[0539] As an example, 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 the inference using the AI model identified by the first identifier.

[0540] As an example, the generation of the first channel information block uses the AI model identified by the first identifier.

[0541] As an example, the first channel information block is generated in the AI entity identified by the first identifier.

[0542] As an example, the first channel information block is used for the AI function identified by the first identifier.

[0543] As an example, the advantages of the above method include: better adaptation to various different application scenarios or terminals, high flexibility, and strong adaptability.

[0544] Example 12

[0545] Embodiment 12 exemplifies a schematic diagram of the generation of channel information corresponding to the first identifier by a higher layer parameter according to an embodiment of the present application; as shown in the appendix Figure 12 as shown.

[0546] In Embodiment 12, the generation of the first channel information block corresponds to the first identifier; the higher layer parameter indicates whether the generation of the channel information corresponding to the first identifier occupies the processing resources in the first resource group or the processing resources in the second resource group.

[0547] As an example, the higher layer parameter in the first reporting configuration indicates whether the generation of the channel information corresponding to the first identifier occupies the processing resources in the first resource group or the processing resources in the second resource group.

[0548] As an example, the higher layer parameter different from the first reporting configuration indicates whether the generation of the channel information corresponding to the first identifier occupies the processing resources in the first resource group or the processing resources in the second resource group.

[0549] In the above method, whether the processing resources occupied by the channel information generated based on reasoning are in the first resource group or the second resource group is indicated per identifier; the advantages include: applicable to different AI models / entities / functions, with high flexibility.

[0550] Example 13

[0551] Embodiment 13 exemplifies a schematic diagram of the first information block according to an embodiment of the present application; as shown in the appendix Figure 13 as shown.

[0552] In Embodiment 13, the first node sends the first information block;

[0553] wherein, the first channel information block is generated based on reasoning; 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.

[0554] In the above method, the first node reports whether the processing resources occupied by the channel information generated based on inference are the processing resources in the first resource group or the processing resources in the second resource group. The advantages include that the UE can control / adjust the occupation of processing resources, better adapt to various different processing capabilities, has high flexibility and strong adaptability, and also ensures consistent understanding between the transceiver ends.

[0555] As an embodiment, the first information block is carried by higher layer signaling.

[0556] As an embodiment, the first information block includes one or more fields in one or more IEs (information elements).

[0557] As an embodiment, the first information block includes a MAC CE.

[0558] As an embodiment, the first information block includes control information.

[0559] As an embodiment, the first information block includes UCI (uplink control information).

[0560] As an embodiment, the first information block is carried by physical layer signaling.

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

[0562] As an embodiment, the first information block is transmitted on a physical layer channel.

[0563] As an embodiment, the first information block is transmitted on a physical layer uplink channel.

[0564] As an embodiment, the first information block is transmitted on a PUCCH (Physical Uplink Control Channel).

[0565] As an embodiment, the first information block is transmitted on a PUSCH (Physical Uplink Shared Channel).

[0566] As an embodiment, the first information block belongs to the capability information of the first node.

[0567] As an embodiment, the first information block includes the capability information of the first node.

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

[0569] As an example, the first information block includes one or more fields in a UE (user equipment) capability IE (information element).

[0570] As an example, the first information block includes one or more fields in one or more UE (user equipment) capability IEs (information elements).

[0571] As an example, the first information block includes one or more parameters in one or more UE (user equipment) capabilities IE.

[0572] As an example, after receiving a UE capability enquiry from the network, the first node transmits the capability information of the first node, and the first information block belongs to the capability information of the first node.

[0573] As an example, the capability information of the first node includes UECapabilityInformation.

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

[0575] Example 14

[0576] Example 14 illustrates a schematic diagram of the generation of channel information corresponding to a first identifier indicated by a first information block according to an embodiment of the present application; as shown in the appendix Figure 14 as follows.

[0577] In Example 14, the generation of the first channel information block corresponds to a first identifier; whether the first information block indicates that the generation of channel information corresponding to the first identifier occupies the processing resources in the first resource group or the processing resources in the second resource group.

[0578] In the above method, whether the processing resources occupied by the channel information generated based on reasoning are in the first resource group or the second resource group is reported per identifier; the advantages include: being applicable to different AI models / entities / functions, with high flexibility.

[0579] Examples 15A - 15C

[0580] Embodiments 15A - 15C respectively illustrate schematic diagrams of a first resource group and a second resource group according to an embodiment of the present application; as shown in the appendix Figures 15A - 15C as follows.

[0581] In Embodiment 15A, only the first resource group among the first resource group and the second resource group includes one or more storage resources in the first node.

[0582] As an 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.

[0583] As an embodiment, 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.

[0584] As an embodiment, 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.

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

[0586] As an embodiment, 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.

[0587] As an embodiment, the storage resource is used for storage.

[0588] As an embodiment, the storage resource includes a storage unit or a storage space.

[0589] As an embodiment, the storage resource includes memory.

[0590] As an embodiment, the storage resource is used to store some or all of the parameters required for inference.

[0591] As an embodiment, the storage resource is used to store at least one of some or all of the inference intermediate results or some or all of the inference outputs.

[0592] As an embodiment, the storage resource is used to store some or all of the parameters of the AI model.

[0593] As an embodiment, the storage resource is used to store at least one of part or all of the parameters of the AI model, part or all of the inference intermediate results, or part or all of the inference outputs.

[0594] As an embodiment, the storage resource is used to store one or more of the convolution kernel size, the number of convolution layers, the convolution stride, the pooling kernel size, the pooling kernel stride, the pooling function, the activation function, or the number of feature maps.

[0595] As an embodiment, the storage resource is used to store one or more of the convolution kernel, the pooling kernel, the pooling function, the activation function, the parameters of the pooling function, or the parameters of the activation function.

[0596] As an embodiment, the storage resource is used to store part or all of the parameters in the target first type of parameter group in Embodiment 20 of the present application.

[0597] As an embodiment, the processing resource is used for at least one of processing, computing, or inference, and the storage resource is used for storage.

[0598] As an embodiment, the processing resource is a processing unit, and the storage resource is used for storage.

[0599] As an embodiment, 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 the capability information of the first node.

[0600] In Embodiment 15B, the names of the processing resources in the first resource group and the processing resources in the second resource group are the same.

[0601] As an embodiment, 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 a processing unit (PU).

[0602] As an embodiment, the processing resources in the first resource group and the processing resources in the second resource group are both CSI processing units (CPUs).

[0603] As an embodiment, the first resource group and the second resource group are respectively in different types of hardware resources of the first node.

[0604] As an example, the processing resources in the first resource group are in an AI processing unit (APU), and the processing resources in the second resource group are in a Central Processing Unit.

[0605] As an example, the processing resources in the first resource group are in a GPU (graphics processing unit), and the processing resources in the second resource group are in a Central Processing Unit.

[0606] As an example, the processing resources in the first resource group are in a general-purpose processing unit, and the processing resources in the second resource group are in a Central Processing Unit.

[0607] As an example, the processing resources in the first resource group are in a general-purpose graphics processing unit (GPGPU), and the processing resources in the second resource group are in a Central Processing Unit.

[0608] In Embodiment 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.

[0609] As an example, the processing resources in the first resource group are an AI processing unit (APU), and the processing resources in the second resource group are a CSI processing unit.

[0610] As an example, 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, and the names of the processing resources in both the first resource group and the second resource group include "processing unit" (PU).

[0611] As an example, the processing resources in the first resource group are an AI processing unit (APU), and the processing resources in the second resource group are a Central Processing Unit or a CSI processing unit.

[0612] 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 processing units.

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

[0614] 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.

[0615] As an example, the first resource group and the second resource group are respectively in different types of hardware resources of the first node.

[0616] As an example, the processing resources in the first resource group are in an AI processing unit (APU), and the processing resources in the second resource group are in a central processing unit (CPU).

[0617] As an example, the processing resources in the first resource group are in a GPU (graphics processing unit), and the processing resources in the second resource group are in a central processing unit (CPU).

[0618] As an example, 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 (CPU).

[0619] As an example, the processing resources in the first resource group are in general-purpose computing on graphics processing units (GPGPUs), and the processing resources in the second resource group are in a central processing unit (CPU).

[0620] As an example, the processing resources in the first resource group are in an AI processing unit (APU), and the processing resources in the second resource group are CSI processing units.

[0621] As an example, the processing resources in the first resource group are in a GPU (graphics processing unit), 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 a general processing unit, and the processing resources in the second resource group are CSI processing units.

[0623] 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.

[0624] Example 16

[0625] Embodiment 16 exemplifies a schematic diagram of a first resource set according to an embodiment of the present application; as shown in the appendix Figure 16 as shown.

[0626] In Embodiment 16, the first processor receives an RS in the first resource set;

[0627] 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.

[0628] As an example, a first reporting configuration is used to configure the first channel information block, and the first reporting configuration indicates the first resource set.

[0629] As an example, the first channel information block indicates at least one RS resource in the first resource set.

[0630] As an example, the first channel information block indicates at least one resource in a second resource set, and the second resource set includes resources that do not belong to the first resource set.

[0631] As an example, the resources in the first resource set include at least one of antenna ports, TCI (Transmission Configuration Indication) states, QCL (Quasi Co-Location) information, time-frequency resources, time-frequency code resources, beams, RS resources, vectors, or matrices.

[0632] As an example, the first resource set includes one or more RS (Reference Signal) resource sets, and one RS resource set includes one or more RS resources.

[0633] As an example, the first resource set includes at least one of at least one 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.

[0634] As an example, the first resource set includes at least one RS resource set for channel measurement, and one RS resource set for channel measurement includes one or more RS resources.

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

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

[0637] As an example, one RS resource set for channel measurement includes one or more RS resources, and any RS resource in the one RS resource set for channel measurement is a CSI-RS resource or a synchronization signal resource.

[0638] As an example, one RS resource set for interference measurement includes one or more RS resources.

[0639] As an example, a set of RS resources for interference measurement includes one or more RS resources, and any RS resource in the set of RS resources for interference measurement is a CSI-IM resource or a NZP (non-zero power) CSI-RS resource for interference measurement.

[0640] As an example, the first set of resources includes one or more RS resources.

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

[0642] As an example, the first set of resources includes one or more RS resources, and any RS resource in the first set of resources is a CSI-RS (Channel State Information Reference Signal) resource or a synchronization signal resource.

[0643] As an example, the synchronization signal resource includes at least the resources occupied by the synchronization signal.

[0644] As an example, the synchronization signal resource is an SSB (Synchronization Signal Block).

[0645] As an example, the synchronization signal resource is an SS / PBCH (synchronization signal / physical broadcast channel) block resource.

[0646] As an example, the first reporting configuration indicates at least one resource configuration, and the at least one resource configuration indicates the first set of resources.

[0647] As an example, the first reporting configuration includes at least one resource configuration, and the at least one resource configuration indicates the first set of resources.

[0648] As an example, a resource configuration is used to configure CSI resources.

[0649] As an example, a resource configuration is an IE CSI-ResourceConfig.

[0650] As an example, a resource configuration is carried by an RRC IE.

[0651] As an example, a resource configuration is carried by a CSI-ResourceConfig IE.

[0652] As an embodiment, the first reporting configuration indicates configuration information of the first resource set.

[0653] As an embodiment, the first reporting configuration indicates an identifier of the first resource set.

[0654] As an embodiment, the first resource set consists of one or more periodic or semi-persistent RS resources.

[0655] As an embodiment, the first resource set consists of one or more aperiodic RS resources.

[0656] As an embodiment, the RS resource is a CSI-RS resource.

[0657] As an embodiment, the RS resource is a CSI-RS resource or an SS / PBCH block resource.

[0658] As an embodiment, the first resource set being used 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.

[0659] As an embodiment, the first resource set being used 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.

[0660] As an embodiment, the first resource set being used 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.

[0661] As an embodiment, the first resource set being used 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.

[0662] As an embodiment, the channel measurement obtained based on the first resource set includes a channel matrix.

[0663] As an embodiment, the channel measurement obtained based on the first resource set includes a raw channel matrix.

[0664] As an embodiment, the channel measurement obtained based on the first resource set includes an eigenvector.

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

[0666] As an example, the channel measurement obtained based on the first resource set includes one or more of BLER, delay spread, Doppler spread, Doppler shift, average delay, average gain, path loss, and RSRP.

[0667] 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.

[0668] As an example, the interference measurement obtained based on the first resource set includes an interference channel matrix.

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

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

[0671] As an example, the interference measurement obtained based on the first resource set includes an interference eigenvector and an interference eigenvalue.

[0672] As an example, the interference measurement obtained based on the first resource set includes an interference beam.

[0673] Examples 17A - 17B

[0674] Embodiments 17A - 17B respectively illustrate schematic diagrams of the first node deploying the first operation according to an embodiment of the present application; as shown in the appendix respectively. Figures 17A - 17B Shown as follows.

[0675] In Embodiment 17A, the first node sends a request to load the first operation to the first producer and obtains the first operation from the first producer.

[0676] As an example, the deployment includes obtaining the first operation.

[0677] As an example, the deployment includes obtaining an AI entity.

[0678] As an example, the deployment includes obtaining an AI entity that executes the first operation.

[0679] As an example, the deployment includes obtaining an AI entity that includes an AI function for executing the first operation.

[0680] As an example, the deployment includes loading the first operation.

[0681] As an example, the deployment includes sending a request to load the first operation.

[0682] As an example, the first operation is obtained by loading from the serving cell of the first node.

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

[0684] As an example, the first operation is obtained by loading from the core network.

[0685] As an example, the first operation is obtained by loading from a first producer.

[0686] As an example, the deployment is completed by an AI function.

[0687] As an example, the deployment is completed by an AI function deployed on the first node.

[0688] As an example, the deployment is completed by an AI deployment function.

[0689] As an example, the deployment is completed by an AI deployment function deployed on the first node.

[0690] As an example, the deployment is completed by an AI inference function.

[0691] As an example, the deployment is completed by an AI inference function deployed on the first node.

[0692] As an example, the deployment is completed by an AI entity.

[0693] As an example, the deployment is completed by an AI entity deployed on the first node.

[0694] As an example, the deployment is completed by an AI entity with a deployment function.

[0695] As an example, the deployment is completed by an AI entity with a deployment function deployed on the first node.

[0696] As an example, the deployment is completed by an AI entity with an inference function.

[0697] As an example, the deployment is completed by an AI entity with an inference function deployed on the first node.

[0698] As an example, the deployment includes obtaining the first operation from a first producer.

[0699] As an example, the deployment includes sending a request to the first producer to load the first operation.

[0700] As an example, the deployment includes loading the first operation from the first producer.

[0701] As an example, the first producer generates and provides an AL entity.

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

[0703] As an example, the first producer is the producer of the first operation.

[0704] As an example, the first producer includes an AL entity producer.

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

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

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

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

[0709] As an example, the first producer includes an AL inference producer.

[0710] As an example, the first producer includes a producer of the deployment of an AL entity.

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

[0712] As an example, the first producer includes a MnS (Management Service) producer.

[0713] As an example, the sender of the first reporting configuration is the first producer.

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

[0715] As an example, the training for obtaining the first operation is performed by the first producer.

[0716] As an example, the executor of the training for obtaining the first operation is different from the first producer.

[0717] As an example, the AI includes ML (Machine Learning).

[0718] In Embodiment 17B, the first node requests the second producer to load the first operation and obtains the first operation from the first producer.

[0719] As an example, the deployment includes obtaining the first operation.

[0720] As an example, the deployment includes obtaining an AI entity or AI function for executing the first operation.

[0721] As an example, the deployment includes loading the first operation.

[0722] As an example, the deployment includes requesting to load the first operation.

[0723] As an example, the deployment is completed by an AI function deployed on the first node.

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

[0725] As an example, the deployment is completed by an AI entity having a deployment function.

[0726] As an example, the second producer generates and provides an AI entity or AI function.

[0727] As an example, the second producer includes an MnS (Management Service) producer.

[0728] As an example, the second producer includes a producer for the training of an AI model.

[0729] As an example, the second producer is the target receiver of the first channel information block.

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

[0731] As an example, the second producer is the serving cell of the first node.

[0732] As an example, the second producer is the maintenance base station of the serving cell of the first node.

[0733] As an example, the second producer is the core network.

[0734] As an example, the first operation is obtained by loading from the serving cell of the first node.

[0735] As an example, the first operation is obtained by loading from the maintenance base station of the serving cell of the first node.

[0736] As an example, the first operation is obtained by loading from the core network.

[0737] As an example, the training for obtaining the first operation is performed by the second producer.

[0738] As an example, the second producer is different from the first producer.

[0739] As an example, the first producer generates and provides an AL entity.

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

[0741] As an example, the first producer is the producer of the first operation.

[0742] As an example, the first producer includes an AL entity producer.

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

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

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

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

[0747] As an example, the first producer includes an AL inference producer.

[0748] As an example, the first producer includes a deployed producer of the AL entity.

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

[0750] As an example, the first producer includes a MnS (Management Service) producer.

[0751] Example 18

[0752] Example 18 illustrates a schematic diagram of the deployment of RAN (Radio Access Network) domain AI / ML functions according to an embodiment of the present application; as shown in the appendix Figure 18 shown. The gNB in Example 18 can be replaced with network devices such as an eNB, or a 6G base station, etc.

[0753] AI / ML-related functions include ML training functions (also known as AI training, or AI / ML training), ML testing functions, ML inference (also known as AI inference, or AI / ML inference) functions, etc. The ML training function, ML testing function, and ML inference function can be deployed independently or co-located. The deployment of AI / ML-related functions can be achieved through software, such as the download and / or running of executable files; it can also be achieved through a combination of software and hardware, such as accelerating specific computing units through hardware to improve the operation speed or save power consumption.

[0754] For the ML training function, it 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, the ML training function for MDA (Management Data Analytics) can be deployed in the MDAF (MDA function); the ML training for network data analysis can be deployed in the NWDAF (Network Data Analytics Function), that is, the ML training function is the MTLF (Model Training logical function).

[0755] For the ML inference function, it can also be deployed in a cross-domain management system or a domain-specific management system; for example, the ML inference function is the MDAF, or the ML inference function is the AnLF (Analytics logical function) in the NWDAF.

[0756] Similarly, the ML testing function can also be deployed in a cross-domain management system or a domain-specific management system.

[0757] In Embodiment 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 the gNB 1405, the AI / ML inference function 1406 is located in the gNB 1407,....

[0758] Appendix Figure 18 In, the management of the ML inference functions of multiple base stations is completed by the RAN domain management function 1403, that is, data interaction is performed with the RAN domain MnS (Management Service) consumer / cross-domain management 1401 (as shown by the dotted arrow in Appendix Figure 18 .

[0759] Optionally, the management of the ML inference function can also be completed by the base station itself, that is, each base station can independently perform data interaction with the RAN domain MnS consumer / cross-domain management 1401.

[0760] It should be noted that Embodiment 18 is merely a non-limiting implementation; optionally, the RAN domain ML training function may also be deployed in the base station; or optionally, some base stations deploy the ML inference function and the RAN domain ML training function, while some base stations only deploy the ML inference function.

[0761] As an embodiment, one gNB (or base station) in Embodiment 18 is the second node described in this application.

[0762] As an embodiment, the second processor in this application includes an AL / ML inference function in Appendix Figure 18 , that is, 1404 or 1406.

[0763] Example 19

[0764] Embodiment 19 illustrates a schematic diagram of the deployment of the AI / ML functions of the UE according to an embodiment of this application; as shown in Appendix Figure 19 . The RAN domain ML training function 1505 in Appendix Figure 19 is optional.

[0765] The UE function 1504 is deployed in the first node of this application. The UE function 1504 includes an AI / ML inference function 1506; the AI / ML inference function 1506 uses an ML model (also known as an AI model) for inference; an ML model usually needs to be trained before being used for AI / ML inference.

[0766] As an embodiment, the first channel information block in this application is obtained through the inference of the AI / ML inference function 1506.

[0767] As an embodiment, the first processor in this application includes Figure 19 an AL / ML inference function 1506 therein.

[0768] As an embodiment, the UE function 1504 includes a RAN domain ML training function 1505. The RAN domain ML training function 1505 runs training data through an ML model, obtains relevant losses, and adjusts the parameters of the ML model based on the calculated losses; the ML training includes at least one of ML initial training, ML re-training, and reinforcement learning.

[0769] The above embodiments can reduce the complexity of the base station, or save the radio interface resources caused by reporting training data; however, the above embodiments place relatively high requirements on the processing capabilities of the UE side.

[0770] Optionally, the UE function 1504 further includes a CN domain ML training function ( Figure 19 not included therein).

[0771] Optionally, the UE function 1504 further includes an AI / ML deployment function - Figure 19 not included therein, for loading the ML model and data.

[0772] As an embodiment, the first node indicates whether it supports the ML training function (RAN domain or CN domain) through capability reporting. The capability reporting is RRC signaling or NAS (Non-Access Stratum) signaling.

[0773] As an embodiment, the ML model and related metadata are loaded by the first node from a network device or a remote server.

[0774] Optionally, the UE function 1504 is an MnS (Management Service) Producer that provides data for management or analysis to the CN domain MnF (Management Function) 1501, and / or the RAN domain MnF 1502, and / or the cross-domain management system 1503 (as shown by the double arrow 1507).

[0775] 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 management data requests, ML model activation, and / or ML training, etc. (as shown by the double arrow 1507).

[0776] As an example, the ML model is based on a Neural Network.

[0777] As an example, the ML model is based on a CNN (Conventional Neural Networks, Convolutional Neural Network).

[0778] As an example, the ML model is based on a Transformer architecture.

[0779] Example 20

[0780] Embodiment 20 illustrates a schematic diagram of an artificial intelligence or machine learning-based processing system according to an embodiment of the present application; as shown in the attached Figure 20 figure. The attached Figure 20 (a) includes a third processor, a fourth processor, and a fifth processor, as shown in the attached Figure 20 (b) includes a third processor, a fourth processor, a fifth processor, and a sixth processor.

[0781] In Embodiment 20(a), the third processor sends a first data set to the fourth processor and a second data set to the fifth processor; the fourth processor generates a target first type of parameter group based on the first data set, and the fourth processor sends the generated target first type of parameter group to the fifth processor; the fifth processor processes the second data set using the target first type of parameter group to obtain a first type of output. In the attached Figure 20 (a), the first type of feedback is optional.

[0782] In Embodiment 20(b), the third processor sends a first data set to the fourth processor and a second data set to the fifth processor; the fourth processor generates a target first type of parameter set according to the first data set, and the fourth processor sends the generated target first type of parameter set to the fifth processor; the fifth processor processes the second data set by using the target first type of parameter set to obtain a first type of output, and the fifth processor sends the first type of output to the sixth processor. In the appendix Figure 20 (b), the first type of feedback and the second type of feedback are optional.

[0783] As an embodiment, in the appendix Figure 20 (a), the fifth processor sends the first type of output to the second node in the present application.

[0784] As an embodiment, in the appendix Figure 20 (a), a single side AI model is adopted, and the fifth processor executes the first operation in the present application.

[0785] As an embodiment, in the appendix Figure 20 (b), a two-sided AI model is adopted, the fifth processor executes the first operation in the present application, and the sixth processor includes the second operation in the present application.

[0786] As an embodiment, the AI includes ML (Machine Learning) inference.

[0787] As an embodiment, the fifth processor executes the first operation in the present application.

[0788] As an embodiment, the sixth processor includes the second operation in the present application.

[0789] As an embodiment, the fifth processor sends a first type of feedback to the fourth processor, and the first type of feedback is used to trigger recalculation or update of the target first type of parameter set.

[0790] As an embodiment, the sixth processor sends a second type of feedback to the third processor, and the second type of feedback is used to generate the first data set or the second data set, or the second type of feedback is used to trigger the sending of the first data set or the sending of the second data set.

[0791] As an embodiment, the third processor generates the first data set and the second data set according to the measurement of a first type of wireless signal, and the first type of wireless signal includes downlink RS.

[0792] As an embodiment, the fifth processor belongs to the first node, and the sixth processor belongs to the second node.

[0793] As an embodiment, the first channel information block belongs to the first type of output.

[0794] As an embodiment, the second data set includes the input of the first operation.

[0795] As an embodiment, for the first operation in this application, the second data set includes information obtained based on the first reporting configuration.

[0796] As an embodiment, the first data set includes Training Data.

[0797] As an embodiment, the fourth processor belongs to the producer of the first operation.

[0798] As an embodiment, the fourth processor includes an AI training producer.

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

[0800] As an embodiment, the fourth processor is used for Model Training, and the trained model is described by the target first type of parameter group.

[0801] As an embodiment, the fourth processor belongs to the first node.

[0802] The above embodiment avoids transmitting the first data set to the second node.

[0803] As an embodiment, the fourth processor belongs to the second node.

[0804] The above embodiment supports joint training and optimizes the system performance.

[0805] As an embodiment, the fourth processor belongs to the core network.

[0806] The above embodiment supports full-network joint training and further optimizes the system performance.

[0807] As an embodiment, the second data set includes Inference Data.

[0808] As an embodiment, the fifth processor includes an AI inference producer.

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

[0810] As an embodiment, the fifth processor belongs to the first node.

[0811] As an embodiment, the fifth processor constructs a model according to the target first type of parameter group, and then inputs the second data set into the constructed model to obtain the first type of output.

[0812] As an embodiment, the first operation is described by the target first type of parameter group.

[0813] As an embodiment, the target first type of parameter group is used to construct the first operation.

[0814] As an embodiment, the fifth processor includes the second operation.

[0815] As an embodiment, the fifth processor generates a recovery data set according to the first type of output, and the error between the recovery data set and the second data set is used to generate the first type of feedback.

[0816] As a sub - embodiment of the above - mentioned embodiment, the generation of the recovery data set adopts a method similar to the second operation.

[0817] As an embodiment, the first type of feedback is used to reflect the performance of the trained model; when the performance of the trained model does not meet the requirements, the fourth processor recalculates the target first type of parameter group.

[0818] As an embodiment, when the error is too large or there is no update for too long, the performance of the trained model is considered not to meet the requirements.

[0819] As an embodiment, the target first type of parameter group includes one or more of: convolution kernel size, number of convolution layers, convolution stride, pooling kernel size, pooling kernel stride, pooling function, activation function, or number of feature maps.

[0820] As an embodiment, the target first type of parameter group includes one or more of: convolution kernel, pooling kernel, pooling function, activation function, parameters of the pooling function, or parameters of the activation function.

[0821] Example 21

[0822] Embodiment 21 illustrates a structural block diagram of a processing device in a first node according to an embodiment of the present application; as shown in the appendix Figure 21 shown. In the appendix Figure 21Among them, the processing device 2100 in the first node includes a first processor 2101.

[0823] As an embodiment, the first node is a user equipment.

[0824] As an embodiment, the user equipment is a terminal.

[0825] As an embodiment, the first node is a relay node device.

[0826] As an embodiment, the first processor 2101 includes at least one of {antenna 452, receiver / transmitter 454, receive processor 456, transmit processor 468, multi-antenna receive processor 458, multi-antenna transmit processor 457, controller / processor 459, memory 460, data source 467} in Embodiment 4.

[0827] The first processor 2101 receives a first reporting configuration and sends a first channel information block.

[0828] 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.

[0829] As an embodiment, 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.

[0830] As an embodiment, 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.

[0831] As an example, the first channel information block is generated based on inference; only when the reporting amount included in the first channel information block belongs to a first reporting amount set, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group; the first reporting amount set includes one or more reporting amounts.

[0832] As an example, the first channel information block is generated based on inference;

[0833] The first channel information block being generated based on inference includes that the generation of the first channel information block corresponds to a first identifier;

[0834] 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.

[0835] 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.

[0836] As an example, the generation of the first channel information block corresponds to a first identifier; a higher layer parameter indicates whether the generation of the channel information corresponding to the first identifier occupies the processing resources in the first resource group or the processing resources in the second resource group.

[0837] As an example, it includes:

[0838] The first processor 2101 sends a first information block;

[0839] 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.

[0840] As an example, the generation of the first channel information block corresponds to a first identifier; the first information block indicates whether the generation of the channel information corresponding to the first identifier occupies the processing resources in the first resource group or the processing resources in the second resource group.

[0841] As an example, only the first resource group among the first resource group and the second resource group includes one or more storage resources in the first node.

[0842] As an example, it includes:

[0843] The first processor 2101 receives RS in a first resource set;

[0844] Among them, 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.

[0845] Example 22

[0846] Embodiment 22 exemplifies a structural block diagram of a processing device in a second node according to an embodiment of the present application; as shown in the appendix Figure 22 shown. In the appendix Figure 22 In it, the processing device 2200 in the second node includes a second processor 2201.

[0847] As an embodiment, the second node is a base station device.

[0848] As an embodiment, the second node is a user equipment.

[0849] As an embodiment, the second node is a relay node device.

[0850] As an embodiment, the second processor 2201 includes at least one of {antenna 420, receiver / transmitter 418, receive processor 470, transmit processor 416, multi-antenna receive processor 472, multi-antenna transmit processor 471, controller / processor 475, memory 476} in Embodiment 4.

[0851] The second processor 2201 sends a first reporting configuration and receives a first channel information block.

[0852] 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 in the sender of the first channel information block, and the second resource group includes one or more processing resources in the sender 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 reasoning. Only when the first channel information block is not generated based on reasoning, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group.

[0853] As an embodiment, 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.

[0854] As an embodiment, 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.

[0855] As an embodiment, the first channel information block is generated based on inference; only when the reporting amount included in the first channel information block belongs to the first reporting amount set, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group; the first reporting amount set includes one or more reporting amounts.

[0856] As an embodiment, the first channel information block is generated based on inference;

[0857] The first channel information block being generated based on inference includes that the generation of the first channel information block corresponds to a first identifier;

[0858] 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.

[0859] As an embodiment, 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.

[0860] As an embodiment, the generation of the first channel information block corresponds to a first identifier; a higher layer parameter indicates whether the generation of the channel information corresponding to the first identifier occupies the processing resources in the first resource group or the processing resources in the second resource group.

[0861] As an embodiment, it includes:

[0862] The second processor 2201 receives a first information block;

[0863] 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.

[0864] As an embodiment, the generation of the first channel information block corresponds to a first identifier; the first information block indicates whether the generation of the channel information corresponding to the first identifier occupies the processing resources in the first resource group or the processing resources in the second resource group.

[0865] As an embodiment, only the first resource group among the first resource group and the second resource group includes one or more storage resources of the sender of the first channel information block.

[0866] As an embodiment, it includes:

[0867] The second processor 2201 sends RS in a first resource set;

[0868] 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.

[0869] Those of ordinary skill in the art can understand that all or part of the steps in the above method can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium, such as a read-only memory, a hard disk, or an optical disc, etc. Optionally, all or part of the steps in the above embodiments can also be implemented using one or more integrated circuits. Correspondingly, each module unit in the above embodiments can be implemented in a hardware form or in the form of a software function module. This application is not limited to any specific form of the combination of software and hardware. The user equipment, terminal, and UE in this application include, but are not limited to, unmanned aerial vehicles, communication modules on unmanned aerial vehicles, remote control airplanes, aircraft, small airplanes, mobile phones, tablet computers, laptops, vehicle-mounted communication devices, transportation means, vehicles, RSU, wireless sensors, network cards, Internet of Things terminals, RFID terminals, NB-IOT terminals, MTC (Machine Type Communication) terminals, eMTC (enhanced MTC) terminals, data cards, network cards, vehicle-mounted communication devices, low-cost mobile phones, low-cost tablet computers and other wireless communication devices. The base station or system equipment in this application includes, but is not limited to, macrocell base stations, microcell base stations, small cell base stations, home base stations, relay base stations, eNB, gNB, TRP (Transmitter Receiver Point), GNSS, relay satellites, satellite base stations, aerial base stations, RSU (Road Side Unit), unmanned aerial vehicles, test equipment, such as transceiver devices or signaling testers that simulate some functions of base stations, and other wireless communication devices.

[0870] Those skilled in the art should understand that the present invention can be implemented in other specific forms without departing from its core or essential features. Therefore, the presently disclosed embodiments should be considered descriptive rather than restrictive in any case. The scope of the invention is determined by the appended claims rather than the preceding description, and all modifications within the equivalent meaning and scope thereof are considered to be included therein.

Claims

1. A method in a first node for wireless communication, characterized in that: include: Receiving a first reporting configuration; sending a first channel information block; 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 occupied by the generation of the first channel information block belongs only to the second resource group only when the first channel information block is not generated based on inference.

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

5. The method in the first node according to any one of claims 1, 3 and 4, characterized in that: The first channel information block is generated based on inference; The first channel information block is generated based on inference and includes a 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. The method in the first node according to any one of claims 1, 3, 4, and 5, characterized in that: The first channel information block is generated based on inference; and 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. The method in the first node according to claim 6, characterized in that: The generation of the first channel information block corresponds to a first identifier; a higher-layer parameter indicates whether the generation of the channel information corresponding to the first identifier occupies processing resources in the first resource group or occupies processing resources in the second resource group.

8. The method in the first node according to any one of claims 1, 3, 4, and 5, characterized in that: include: Sending 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.

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

10. A terminal, characterized in that: The terminal includes: one or more processors and a memory; The memory is coupled to the one or more processors, and the memory is used to store computer program codes, where the computer program codes include computer instructions. The one or more processors call the computer instructions to enable the terminal to execute the method according to any one of claims 1 to 9.

11. A method in a second node for wireless communication, characterized in that: include: Sending the first reporting configuration; receiving a first channel information block; Among them, 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 the first resource group or the second resource group, the first resource group includes one or more processing resources in the sender of the first channel information block, and the second resource group includes one or more processing resources in the sender 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. The method in the second node according to claim 11, characterized in that: 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. The method in the second node according to claim 11, characterized in that: When the first channel information block is generated based on inference, a candidate range of a 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. The method in the second node according to claim 11 or 13, characterized in that: The first channel information block is generated based on inference; only when the reporting quantity included in the first channel information block belongs to the first reporting quantity set, the at least one processing resource occupied by the generation of the first channel information block belongs only to the second resource group; the first reporting quantity set includes one or more reporting quantities.

15. The method in the second node according to any one of claims 11, 13 and 14, characterized in that: The first channel information block is generated based on inference; The first channel information block is generated based on inference and includes a 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. The method in the second node according to any one of claims 11, 13, 14 and 15, characterized in that: The first channel information block is generated based on inference; and 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. The method in the second node according to claim 16, characterized in that: The generation of the first channel information block corresponds to a first identifier; a higher-layer parameter indicates whether the generation of the channel information corresponding to the first identifier occupies processing resources in the first resource group or occupies processing resources in the second resource group.

18. The method in the second node according to any one of claims 11, 13, 14 and 15, characterized in that: include: 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.

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

20. A base station, characterized in that: The base station includes: one or more processors and a memory; The memory is coupled to the one or more processors, and the memory is used to store computer program codes, where the computer program codes include computer instructions, and the one or more processors call the computer instructions to enable the base station to perform the method according to any one of claims 11 to 19.

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