Information reporting method and apparatus in node used for wireless communication

Abstract

The present application discloses an information reporting method and apparatus in a node used for wireless communication. The method comprises: a first node receiving a first information set, the first information set indicating M configurations, and M being a positive integer greater than 1; executing a first reference operation; and sending a first information report, or abandoning the sending of the first information report. A first configuration among the M configurations is used for configuring the first information report. The first configuration comprises a first-type indicator, and the first-type indicator in the first configuration is used for indicating a configuration other than the first configuration among the M configurations. The first information report depends on an output of the first reference operation. The first reference operation depends on a second configuration, and the second configuration is the configuration indicated by the first-type indicator in the first configuration.

Description

A method and apparatus for information reporting in nodes used in wireless communication Technical Field

[0001] This application relates to transmission methods and apparatus in wireless communication systems, and more particularly to schemes and apparatus for information reporting in wireless communication systems. Background Technology

[0002] In traditional wireless communication, the UE (User Equipment) obtains channel information by measuring downlink reference signals. This channel information includes, but is not limited to, one or more of the following: CRI (CSI-RS 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 increasing demands on system performance, traditional measurement and reporting methods incur significant redundancy overhead. Therefore, in NR R (release) 18, research on AI (Artificial Intelligence) / ML (Machine Learning) technologies was initiated to explore their impact on system performance and design. Compared to traditional processing methods, AI / ML offers advantages such as training-based and deployment-required features. Furthermore, AI / ML is also a key candidate technology for future 6G communications. Summary of the Invention

[0004] The applicant discovered through research that when AI / ML functionality is introduced, existing information reporting measurement mechanisms, reporting mechanisms, and related configuration signaling may not be able to adapt to the needs of AI / ML. To address these issues, this application discloses a solution. It should be noted that while many embodiments of this application are specifically for AI / ML, this application is also applicable to other solutions, such as traditional channel information reporting schemes. Furthermore, adopting a unified solution for different scenarios (including but not limited to AI / ML-based schemes and traditional information reporting schemes) helps reduce hardware complexity and cost. Where there is no conflict, the embodiments and features in the embodiments of the first node of this application can be applied to the second node, and vice versa. Where there is no conflict, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other.

[0005] As an example, the interpretation of terms in this application is based on the definitions in the 3GPP specification protocol TS38 series.

[0006] As an example, the interpretation of the terms in this application is based on the definitions in the 3GPP specification protocol TS28 series.

[0007] This application discloses a method used in a first node of wireless communication, characterized by comprising:

[0008] Receive a first information set; the first information set indicates M configurations, where M is a positive integer greater than 1;

[0009] Perform the first reference operation; send the first information report, or abandon sending the first information report; the first configuration among the M configurations is used to configure the first information report;

[0010] Wherein, the first configuration includes a first type of indication, which is used to indicate a configuration other than the first configuration among the M configurations; the first information reporting depends on the output of the first reference operation, which depends on a second configuration, which is the configuration indicated by the first type of indication in the first configuration.

[0011] According to one aspect of this application, the first node is a user equipment.

[0012] According to one aspect of this application, the first node is a relay node.

[0013] As an example, the problem this application aims to solve includes: how to process information reporting based on multiple configurations.

[0014] As an example, the advantages of the above method include ensuring that the sending and receiving ends have a consistent understanding of the configuration and processing of information reporting.

[0015] As an example, the advantages of the above method include: supporting the association of one information report and multiple configurations through the first type of indication, simplifying the design and providing high flexibility.

[0016] As an example, the advantages of the above method include: multiple configurations for obtaining a single information report improve accuracy, reduce latency, lower reporting overhead, and improve overall system performance.

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

[0018] According to one aspect of this application, it is characterized by comprising:

[0019] Perform the first operation;

[0020] The first information reporting depends on the output of the first operation, and the input of the first operation depends on the output of the first reference operation.

[0021] As an example, the advantages of the above method include: multiple operations are used to obtain information reports, which improves accuracy, reduces latency, reduces reporting overhead, and improves the overall system performance.

[0022] According to one aspect of this application, the output of the first reference operation is used to generate the first information report.

[0023] As one embodiment, the first configuration indicates a first type of resource set, the first type of resource set including at least one RS resource for the measurement used for the first information reporting; the first information reporting indicates at least one resource in a second type of resource set.

[0024] As an example, the output of the first operation includes a first CSI, the first information report carries the first CSI, and the first CSI is used as input to the second operation by the target recipient of the first information report to generate a second CSI.

[0025] According to one aspect of this application, the second configuration indicates the first reference operation.

[0026] According to one aspect of this application, the second configuration includes a first type identifier, which is different from a first type indication, and the first reference operation is associated with the first type identifier in the second configuration.

[0027] According to one aspect of this application, the first configuration indicates the first operation, and the second configuration indicates the first reference operation.

[0028] According to one aspect of this application, the first configuration includes a first type identifier, the second configuration includes a first type identifier, the first type identifier being different from the first type indication; the first operation is associated with the first type identifier in the first configuration, and the first reference operation is associated with the first type identifier in the second configuration.

[0029] According to one aspect of this application, the second configuration includes a first type identifier, which is different from a first type indication; the target identifier is a first type identifier; when the first type identifier in the second configuration is the same as the target identifier, the first information reporting is abandoned.

[0030] According to one aspect of this application, the first information report is abandoned if a first condition is met; the first condition includes that the first class identifier and the target identifier in the second configuration are the same; when the first class identifier and the target identifier in the second configuration are the same, the first information report is abandoned.

[0031] According to one aspect of this application, the second configuration includes a first type identifier, which is different from a first type indication; the target identifier is a first type identifier; when the first type identifier in the second configuration is the same as the target identifier, the first information reporting is not updated.

[0032] According to one aspect of this application, the first information report is not updated if a first condition is met; the first condition includes that the first class identifier and the target identifier in the second configuration are the same; when the first class identifier and the target identifier in the second configuration are the same, the first information report is not updated.

[0033] According to one aspect of this application, the target operation is associated with the target identifier, and the target operation is invalidated.

[0034] According to one aspect of this application, the first node determines the target identifier itself; or, the first node determines that the target operation has failed, and the target operation is associated with the target identifier.

[0035] As an example, the advantages of the above method include high flexibility and adaptability to different terminals.

[0036] As an example, the advantages of the above method include reduced signaling overhead.

[0037] As an example, the advantages of the above method include timely detection of failed operations, thus improving performance.

[0038] According to one aspect of this application, it is characterized by comprising:

[0039] Receive the first signaling; among which,

[0040] The first signaling indicates the target identifier;

[0041] or,

[0042] The first signaling indicates that the target operation has failed, and the target operation is associated with the target identifier.

[0043] As an example, the advantages of the above method include reducing the complexity of the first node and reducing energy consumption.

[0044] According to one aspect of this application, it is characterized by comprising:

[0045] Deploy the first reference operation.

[0046] As an example, the advantages of the above method include that it provides sufficient freedom for the first node, adapting to various different scenarios and terminals, and has adaptability and flexibility.

[0047] As an example, the advantages of the above method include: training for the first operation can be performed outside the first node, reducing the processing power requirements and power consumption of the first node.

[0048] As an example, the first reference operation is based on training or AI.

[0049] As an example, the AI ​​(Artificial Intelligence) includes ML (Machine Learning).

[0050] As one example, the AI ​​includes AI / ML.

[0051] As an example, the first reference operation is obtained by loading.

[0052] According to one aspect of this application, it is characterized by comprising:

[0053] Deploy the first operation.

[0054] As an example, the advantages of the above method include that it provides sufficient freedom for the first node, adapting to various different scenarios and terminals, and has adaptability and flexibility.

[0055] As an example, the advantages of the above method include: training for the first operation can be performed outside the first node, reducing the processing power requirements and power consumption of the first node.

[0056] As an example, the first operation is based on training or AI.

[0057] As an example, the first operation is obtained by loading.

[0058] This application discloses a method used in a second node for wireless communication, characterized by comprising:

[0059] Send a first set of information; the first set of information indicates M configurations;

[0060] Wherein, the target receiver of the first information set performs a first reference operation; the target receiver of the first information set sends a first information report or abandons sending the first information report; a first configuration among the M configurations is used to configure the first information report; the first configuration includes a first type of indication, the first type of indication in the first configuration is used to indicate a configuration other than the first configuration among the M configurations; the first information report depends on the output of the first reference operation, the first reference operation depends on a second configuration, the second configuration is the configuration indicated by the first type of indication in the first configuration.

[0061] As one embodiment, the second node monitors whether the first information report is sent by the target recipient of the first information set.

[0062] As one embodiment, the second node determines on its own whether to give up receiving the first information report.

[0063] According to one aspect of this application, it is characterized by comprising:

[0064] Receive the first information report, or choose not to receive the first information report.

[0065] According to one aspect of this application, the target recipient of the first information set performs a first operation; the first information reporting depends on the output of the first operation, and the input of the first operation depends on the output of the first reference operation.

[0066] According to one aspect of this application, the output of the first reference operation is used to generate the first information report.

[0067] As one embodiment, the first configuration indicates a first type of resource set, the first type of resource set including at least one RS resource for the measurement used for the first information reporting; the first information reporting indicates at least one resource in a second type of resource set.

[0068] As one embodiment, it includes:

[0069] Perform a second operation; wherein the output of the first operation includes a first CSI, the first information report carries the first CSI, and the first CSI is used as input to the second operation to generate a second CSI.

[0070] According to one aspect of this application, the second configuration indicates the first reference operation.

[0071] According to one aspect of this application, the second configuration includes a first type identifier, which is different from a first type indication, and the first reference operation is associated with the first type identifier in the second configuration.

[0072] According to one aspect of this application, the first configuration indicates the first operation, and the second configuration indicates the first reference operation.

[0073] According to one aspect of this application, the first configuration includes a first type identifier, the second configuration includes a first type identifier, the first type identifier being different from the first type indication; the first operation is associated with the first type identifier in the first configuration, and the first reference operation is associated with the first type identifier in the second configuration.

[0074] According to one aspect of this application, the second configuration includes a first type identifier, which is different from a first type indication; the target identifier is a first type identifier; when the first type identifier in the second configuration is the same as the target identifier, the first information report is abandoned by the target receiver of the first information set.

[0075] According to one aspect of this application, when the first type identifier and the target identifier in the second configuration are the same, the first information report is abandoned by the second node.

[0076] According to one aspect of this application, the first information report is abandoned if a first condition is met; the first condition includes that the first class identifier and the target identifier in the second configuration are the same; when the first class identifier and the target identifier in the second configuration are the same, the first information report is abandoned.

[0077] According to one aspect of this application, the second configuration includes a first type identifier, which is different from a first type indication; the target identifier is a first type identifier; when the first type identifier in the second configuration is the same as the target identifier, the first information reporting is not updated.

[0078] According to one aspect of this application, the first information report is not updated depending on whether a first condition is met; the first condition includes that the first class identifier in the second configuration is the same as the target identifier; when the first class identifier in the second configuration is the same as the target identifier, the first information report is not updated by the target receiver of the first information set.

[0079] According to one aspect of this application, the target operation is associated with the target identifier, and the target operation is invalidated.

[0080] According to one aspect of this application, the target recipient of the first information set determines the target identifier itself; or, the target recipient of the first information set determines that the target operation has failed, and the target operation is associated with the target identifier.

[0081] According to one aspect of this application, it is characterized by comprising:

[0082] Send the first signaling; among which,

[0083] The first signaling indicates the target identifier;

[0084] or,

[0085] The first signaling indicates that the target operation has failed, and the target operation is associated with the target identifier.

[0086] As an example, the target recipient of the first information set deploys the first reference operation.

[0087] As an example, the first reference operation is based on training or AI.

[0088] As an example, the first reference operation is obtained by loading.

[0089] As an example, the first operation is based on training or AI.

[0090] As an example, the target recipient of the first information set deploys the first operation.

[0091] As an example, the first operation is obtained by loading.

[0092] According to one aspect of this application, it is characterized by comprising:

[0093] Deploy the second operation.

[0094] As an example, the advantages of the above method include that it provides sufficient freedom for the second node, adapting to various different scenarios and terminals, and possessing adaptability and flexibility.

[0095] As an example, the advantages of the above method include: training for the second operation can be performed outside the second node, reducing the processing power requirements and power consumption of the second node.

[0096] As one example, the second operation is based on training or AI.

[0097] As an example, the second operation is obtained by loading.

[0098] This application discloses a first node used for wireless communication, characterized in that it comprises:

[0099] A first processor receives a first information set; the first information set indicates M configurations, where M is a positive integer greater than 1.

[0100] The first processor performs a first reference operation; it sends a first information report or abandons sending the first information report; the first configuration among the M configurations is used to configure the first information report.

[0101] Wherein, the first configuration includes a first type of indication, which is used to indicate a configuration other than the first configuration among the M configurations; the first information reporting depends on the output of the first reference operation, which depends on a second configuration, which is the configuration indicated by the first type of indication in the first configuration.

[0102] This application discloses a second node used for wireless communication, characterized in that it comprises:

[0103] The second processor sends a first information set; the first information set indicates M configurations;

[0104] Wherein, the target receiver of the first information set performs a first reference operation; the target receiver of the first information set sends a first information report or abandons sending the first information report; a first configuration among the M configurations is used to configure the first information report; the first configuration includes a first type of indication, the first type of indication in the first configuration is used to indicate a configuration other than the first configuration among the M configurations; the first information report depends on the output of the first reference operation, the first reference operation depends on a second configuration, the second configuration is the configuration indicated by the first type of indication in the first configuration.

[0105] As an example, compared with conventional solutions, this application has the following advantages:

[0106] It supports the association of one information report with multiple configurations, simplifying the design and providing high flexibility;

[0107] It supports multiple configurations for obtaining a single information report;

[0108] It is better adapted to various application scenarios or terminals, and is highly flexible;

[0109] It improved accuracy, reduced latency, lowered reporting overhead, and improved overall system performance;

[0110] Enhanced reliability and robustness. Attached Figure Description

[0111] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0112] Figure 1 illustrates a flowchart of a first information set and a first information reporting according to an embodiment of this application;

[0113] Figure 2 shows a schematic diagram of a network architecture according to an embodiment of this application;

[0114] Figure 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for the user plane and control plane according to an embodiment of this application;

[0115] Figure 4 shows a schematic diagram of a first communication device and a second communication device according to an embodiment of this application;

[0116] Figure 5 illustrates the transmission between a first node and a second node according to an embodiment of this application;

[0117] Figures 6A-6B respectively illustrate schematic diagrams of the output of a first information reporting dependent on a first reference operation according to an embodiment of this application;

[0118] Figures 7A-7B respectively illustrate schematic diagrams of the first information reporting according to an embodiment of this application;

[0119] Figures 8A-8B respectively illustrate schematic diagrams of the deployment of a first given operation by the first node according to an embodiment of this application;

[0120] Figures 9A-9B respectively illustrate schematic diagrams showing the relationship between a first configuration and a first operation, and the relationship between a second configuration and a first reference operation according to an embodiment of this application;

[0121] Figures 10A-10B respectively illustrate schematic diagrams of a first information report being abandoned according to an embodiment of this application;

[0122] Figures 11A-11B respectively illustrate schematic diagrams of a first information report not being updated according to an embodiment of this application;

[0123] Figure 12 illustrates a schematic diagram of a target identifier and a target operation according to an embodiment of this application;

[0124] Figures 13A-13B respectively show schematic diagrams of a target identifier according to an embodiment of this application;

[0125] Figure 14 illustrates a schematic diagram of the deployment of AI / ML functions in a RAN (Radio Access Network) domain according to an embodiment of this application;

[0126] Figure 15 shows a schematic diagram of the AI / ML function deployment of a UE according to an embodiment of this application;

[0127] Figure 16 shows a schematic diagram of a processing system based on artificial intelligence or machine learning according to an embodiment of this application;

[0128] Figure 17 illustrates a schematic diagram based on artificial intelligence or machine learning according to an embodiment of this application;

[0129] Figure 18 shows a structural block diagram of a processing apparatus for a first node according to an embodiment of the present application;

[0130] Figure 19 shows a structural block diagram of a processing apparatus for a second node according to an embodiment of the present application. Detailed Implementation

[0131] The technical solutions of this application will be further described in detail below with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other. Considering performance, flexibility, complexity, overhead, and compatibility, those skilled in the art are motivated to flexibly combine the embodiments in different drawings without conflict, such as, but not limited to, the embodiments in Figure 1 and the embodiments in Figures 5-19, the embodiments in Figure 5 and the embodiments in Figures 6A-19, etc.

[0132] Example 1

[0133] Example 1 illustrates a flowchart of a first information set and a first information reporting according to an embodiment of this application, as shown in Figure 1. In Figure 1, each block represents a step. In particular, the order of the steps in the blocks does not represent a specific temporal relationship between the steps.

[0134] In Embodiment 1, the first node receives a first information set in step 101; performs a first reference operation in step 102; and sends a first information report or abandons sending the first information report in step 103. The first configuration includes a first type of indication, which is used to indicate a configuration other than the first configuration among the M configurations. The first information report depends on the output of the first reference operation, which depends on a second configuration, which is the configuration indicated by the first type of indication in the first configuration.

[0135] As one embodiment, the first information set is carried by higher layer signaling.

[0136] As an example, the first information set is carried by RRC (Radio Resource Control) signaling.

[0137] As an example, the first information set is carried by RRC signaling and MAC CE signaling.

[0138] As an example, the first information set includes an RRC IE (Information Element).

[0139] As one embodiment, the first information set includes multiple RRC IEs.

[0140] As one embodiment, the first information set includes some or all of the fields in one or more RRC IEs.

[0141] As one embodiment, the first information set includes one or more IE CSI-ReportConfigs.

[0142] As one embodiment, the first information set includes some or all of the domains in one or more IE CSI-ReportConfig.

[0143] As one embodiment, the first information set includes N IE CSI-ReportConfigs, and the N IE CSI-ReportConfigs are respectively used to configure N first information reports.

[0144] As one embodiment, the first information set includes some or all of the domains in IE ServingCellConfig.

[0145] As one embodiment, the first information set includes some or all of the domains in IE CSI-MeasConfig IE.

[0146] As one embodiment, the first information set includes some or all of the domains in IE ServingCellConfigCommon IE.

[0147] As one embodiment, the first information set includes some or all of the domains in IE ServingCellConfig.

[0148] As one embodiment, the first information set indicating M configurations includes: the first information set indicating the identifier of each of the M configurations.

[0149] As one embodiment, the first information set indicates that the M configurations include: the first information set includes M configurations.

[0150] As one embodiment, the first information set indicates M configurations including: the first information set includes at least one RRC IE, and the M configurations are carried by the at least one RRC IE.

[0151] As one embodiment, the first information set indicates that the M configurations include: the first information set includes M RRC IEs, and the M configurations are carried by the M RRC IEs respectively, or the M configurations each include the M RRC IEs.

[0152] As an example, the M configurations each include M RRC IEs.

[0153] As an example, the M configurations are each carried by M RRC IEs.

[0154] As an example, the M configurations are carried by at least one RRC IE.

[0155] As one embodiment, the M configurations include some or all of the domains in at least one RRC IE.

[0156] As an example, at least one of the M configurations is used for configuration information reporting, and the first configuration is used to configure the first information reporting, wherein the first configuration is one of the M configurations.

[0157] As an example, the M configurations are used to configure M information reports respectively, and the first configuration is used to configure the first information report. The first configuration is one of the M configurations, and the first information report is one of the M information reports.

[0158] As an example, the first configuration indicates at least one of a first type of resource set, the reporting type of the first information report, or the reporting amount of the first information report; the first type of resource set includes at least one RS resource for the measurement of the first information report.

[0159] As an example, the first configuration indicates at least one of a first type of resource set, a second type of resource set, the reporting type of the first information report, or the reporting amount of the first information report; the first type of resource set includes at least one RS resource for the measurement of the first information report.

[0160] As an example, the measurement used for the first information reporting refers to at least one of channel measurement or interference measurement used for the first information reporting.

[0161] As an example, the measurement used for the first information reporting refers to: channel measurement used for the first information reporting.

[0162] As an example, the measurement used for the first information reporting refers to channel measurement and interference measurement used for the first information reporting.

[0163] As a sub-implementation of the above embodiments, the reporting type indicates at least periodic reporting, semi-persistent reporting, non-periodic reporting, or event-triggered reporting.

[0164] As a sub-example of the above embodiments, the reporting type indicates at least periodic reporting, semi-persistent reporting, or non-periodic reporting.

[0165] As an example, the first information report includes UCI (Uplink Control Information).

[0166] As an example, the first information is reported and transmitted on PUSCH (Physical Uplink Shared Channel).

[0167] As an example, the first information is reported and transmitted on the PUCCH (Physical Uplink Control Channel).

[0168] As an example, the first information report includes at least one of the following: predicted beam information, predicted CSI, estimated CSI, compressed CSI, confidence information, or performance monitoring results.

[0169] As an example, the first information report is used for at least one of performance monitoring, positioning, beam management, CSI prediction, CSI estimation, CSI compression, RLF (radio link failure) prediction, cell handover prediction, or serving cell prediction.

[0170] As an example, the first information report includes at least one of performance monitoring results, location information, RLF prediction, beam failure prediction, cell handover prediction, beam handover prediction, or serving cell prediction.

[0171] As one embodiment, the beam management includes at least one of beam prediction, beam switching, beam failure prediction, or beam failure recovery.

[0172] As an example, the first information reporting includes reporting volumes that do not belong to 3GPP Rel-18 and earlier versions.

[0173] As one example, the first information reporting includes reporting quantities that are not defined in the 5G standard.

[0174] As an example, the first information reporting includes the reporting volume defined in the 6G standard.

[0175] As one example, the first information report includes information generated based on artificial intelligence or machine learning.

[0176] As one example, the first information report includes information generated based on a neural network.

[0177] As an example, the first information report includes information generated based on CNN (Conventional Neural Networks).

[0178] As one example, the first information report includes channel information.

[0179] As one embodiment, the first information report includes information other than channel information.

[0180] As one example, the information other than the channel information includes performance monitoring results.

[0181] As an example, the performance monitoring includes performance monitoring for the AI ​​model.

[0182] As an example, the performance monitoring includes performance monitoring for AI functions.

[0183] As an example, the performance monitoring includes performance monitoring of the first reference operation, and the performance monitoring result includes whether the first reference operation has failed.

[0184] As an example, the performance monitoring includes performance monitoring of the first operation in this application, and the performance monitoring result includes whether the first operation has failed.

[0185] As an example, the performance monitoring includes performance monitoring for at least one of the first reference operation or the first operation, and the performance monitoring result includes whether the first reference operation or at least one of the first operations has failed.

[0186] As an example, the performance monitoring results include whether the first reference operation failed.

[0187] As an example, the performance monitoring results include whether the first operation failed.

[0188] As an example, the performance monitoring results include whether the first reference operation or at least one of the first operations failed.

[0189] As one example, the information other than the channel information includes RLF prediction.

[0190] As one example, the information other than the channel information includes cell handover prediction.

[0191] As one example, the information other than the channel information includes serving cell prediction.

[0192] As one example, the information other than the channel information includes positioning based on artificial intelligence or machine learning.

[0193] As one example, the information other than the channel information includes artificial intelligence or machine learning-assisted positioning.

[0194] As one example, the channel information includes beam failure prediction.

[0195] As one example, the channel information includes beam switching prediction.

[0196] As one embodiment, the channel information includes at least one of predicted beam information, switched beam information, predicted CSI, estimated CSI, or compressed CSI.

[0197] As one example, the beam information includes the beam.

[0198] As an example, the beam information includes at least one of resource indication or RSRP (reference signal received power).

[0199] As one example, the beam information includes RSRP.

[0200] As an example, the resource indication in this application is used to indicate beam or RS resources.

[0201] As an example, the resource indication in this application is used to indicate at least one of beam, CSI-RS resource, or SS / PBCH block resource.

[0202] As an example, the resource indication in this application includes at least one of beam indication, CRI (CSI-RS Resource Indicator, Channel State Information Reference Signal Resource Indicator), or SS / PBCH Block Resource Indicator (SSBRI).

[0203] As one example, the channel information includes CSI (channel state information).

[0204] As one example, the channel information includes CSI or beam information.

[0205] As one example, the channel information includes the channel impulse response.

[0206] As one example, the channel information includes small-scale characteristics.

[0207] As one embodiment, the channel information includes one or more of delay spread, Doppler spread, Doppler shift, average delay, or average gain.

[0208] As one example, the channel information includes a channel matrix.

[0209] As an example, the channel matrix is ​​in the spatial-frequency domain.

[0210] As an example, the channel matrix is ​​in the angular-delay domain projection.

[0211] As one embodiment, the channel information includes at least one of the channel's feature values ​​or feature vectors.

[0212] As an example, the channel information includes one or more of the following: beam information, PMI (Precoding Matrix Indicator), CRI (CSI-RS Resource Indicator), CQI (Channel Quality Indicator), RI (Rank Indicator), LI (layer indicator), SSBRI (SS / PBCH Block Resource Indicator), RSRP (Reference Signal Received Power), SINR (Signal-to-Interference-plus-Noise Ratio), Capability Index, and TDCP (Time Domain Channel Properties).

[0213] As an example, the compressed CSI is based on a non-codebook.

[0214] As an example, the compressed CSI is not a reporting quantity defined by 3GPP Rel-18, nor is it a reporting quantity defined by versions prior to 3GPP Rel-18.

[0215] As an example, the compressed CSI is not a reporting quantity defined by 3GPP Rel-19, nor is it a reporting quantity defined by versions prior to 3GPP Rel-19.

[0216] As an example, the compressed CSI is not part of the reporting volume defined by the 5G standard.

[0217] As an example, the channel parameters recovered by the target receiver of the compressed CSI based on the compressed CSI are unknown to the sender of the compressed CSI.

[0218] As an example, the compressed CSI is based on artificial intelligence or machine learning.

[0219] As an example, the compressed CSI is based on a neural network.

[0220] As an example, the compressed CSI is based on CNN (Conventional Neural Networks).

[0221] As an example, the first class indicator in the first configuration is different from the identifier in the first configuration.

[0222] As an example, the first type indication in the first configuration is not an identifier of the first configuration.

[0223] As an example, the first type of indication in the first configuration being used to indicate a configuration other than the first configuration among the M configurations means that: the first type of indication in the first configuration is used to identify a configuration other than the first configuration among the M configurations.

[0224] As an example, the first type of indication in the first configuration being used to indicate a configuration other than the first configuration among the M configurations means that: the first type of indication in the first configuration is an identifier of a configuration other than the first configuration among the M configurations.

[0225] As an example, the first type of indication in the first configuration being used to indicate a configuration other than the first configuration among the M configurations means: the first type of indication in the first configuration being used to indicate the identifier of a configuration other than the first configuration among the M configurations.

[0226] As an example, the first type of indication in the first configuration being used to indicate a configuration other than the first configuration among the M configurations means that the first type of indication in the first configuration is used to indicate a configuration other than the first configuration among the M configurations from multiple configurations.

[0227] As an example, the first type of indication is an identifier.

[0228] As an example, the first type of indication is an index.

[0229] As an example, the first type of indication is a non-negative integer.

[0230] As an example, the first type of indication includes one or more characters.

[0231] As an example, at least one of the M configurations includes a first type of indication, and the given configuration is any of the M configurations that includes the first type of indication, wherein the first type of indication in the given configuration is used to indicate a configuration other than the given configuration among the M configurations.

[0232] As an example, at least one of the M configurations includes a first type of indication, wherein the first configuration is any one of the M configurations that includes the first type of indication.

[0233] As an example, at least one of the M configurations includes a first type of indication, wherein the first configuration is one of the M configurations that includes the first type of indication.

[0234] As an example, the first reference operation is based on training or AI.

[0235] As an example, the first reference operation includes inference.

[0236] As one example, the first reference operation includes an AI entity.

[0237] As an example, the first reference operation includes an AI entity for inference.

[0238] As an example, the first reference operation includes a portion of an AI entity.

[0239] As an example, the first reference operation includes a portion of an AI entity used for inference.

[0240] As one embodiment, the first reference operation includes reasoning for obtaining the first information report.

[0241] As an example, the reasoning includes AI (Artificial Intelligence) inference.

[0242] As an example, the first reference operation includes AI inference for obtaining CSI.

[0243] As one example, the first reference operation includes AI inference for obtaining channel information.

[0244] As one example, the first reference operation includes AI inference for obtaining information other than channel information.

[0245] As an example, the first reference operation includes AI inference for at least one of beam management, positioning or assisted positioning, CSI prediction, CSI estimation, or CSI compression.

[0246] As an example, the first reference operation includes AI inference for at least one of performance monitoring, positioning, beam management, CSI prediction, CSI estimation, CSI compression, RLF (radio link failure) prediction, cell handover prediction, or serving cell prediction.

[0247] As an example, the first reference operation is used for an AI function.

[0248] As one example, the AI ​​function includes AI inference functionality.

[0249] As one example, the AI ​​functionality includes AI training functionality.

[0250] As one example, the AI ​​functionality includes AI management functionality.

[0251] As one example, the AI ​​function includes AI performance monitoring.

[0252] As one example, the AI ​​includes ML (Machine Learning).

[0253] As one example, the AI ​​includes AI and ML.

[0254] As one example, the AI ​​includes AI or ML.

[0255] As an example, the first reference operation is performed by the physical layer of the first node.

[0256] As an example, the first reference operation is performed at a higher level than the first node.

[0257] As an example, the model of the first reference operation is obtained through training.

[0258] As an example, the training of the first reference operation is performed by the first node.

[0259] As an example, the training of the first reference operation is performed by the sender of the first information set.

[0260] As an example, the training of the first reference operation is performed by the core network.

[0261] As an example, the training of the first reference operation is performed by an AI training producer.

[0262] As an example, the training of the first reference operation is performed by the MDA (Management Data Analytics Function).

[0263] As an example, the training of the first reference operation is performed by the MDA function located at the first node.

[0264] As an example, the training of the first reference operation is performed by the MDA function of the sender located in the first information set.

[0265] As an example, the training of the first reference operation is performed by NWDAF (Network Data Analytics Function).

[0266] As an example, the training of the first reference operation is performed by the MDAS (Management Data Analytics Service) producer.

[0267] As an example, the training of the first reference operation is performed by the MnS (Management Service) producer.

[0268] As an example, the first reference operation requires deployment.

[0269] As an example, the first reference operation is obtained by loading.

[0270] As an example, the first reference operation is obtained from the serving cell of the first node.

[0271] As an example, the first reference operation is obtained from the sustaining base station of the serving cell of the first node.

[0272] As an example, the first node deploys the first reference operation.

[0273] As an example, the first reference operation does not require deployment.

[0274] As an example, the first reference operation is obtained from the core network.

[0275] As an example, the first reference operation is based on artificial intelligence or machine learning.

[0276] As an example, the first reference operation is based on a neural network.

[0277] As an example, the first reference operation is based on CNN (Conventional Neural Networks).

[0278] As one embodiment, the first reference operation includes preprocessing.

[0279] As an example, the preprocessing includes one or more of the following: quantization, DFT (Discrete Fourier Transform), matrix decomposition, matrix transformation or projection, spatial-to-angular-domain transformation, angular-to-spatial-domain transformation, frequency-to-time-domain transformation, time-to-frequency-domain transformation, truncation, padding, mapping, or labeling.

[0280] As an example, the preprocessing includes DFT (Discrete Fourier Transform).

[0281] As one example, the preprocessing includes one or more of matrix decomposition, matrix transformation, or projection.

[0282] As an example, the preprocessing includes one or more of the following: quantization, spatial-to-angular-domain transformation, angular-to-spatial-domain transformation, frequency-to-time-domain transformation, or time-to-frequency-domain transformation.

[0283] As one example, the preprocessing includes truncation and / or padding.

[0284] As one example, the preprocessing includes mapping.

[0285] As one example, the preprocessing includes mapping to vectors.

[0286] As one example, the preprocessing includes labeling.

[0287] As an example, the label refers to a mark made with a label.

[0288] As one embodiment, the first reference operation includes post-processing.

[0289] As one example, the post-processing includes DFT.

[0290] As one example, the post-processing includes quantization.

[0291] As an example, the post-processing includes one or more of the following: angular domain to spatial domain transformation, spatial domain to angular domain transformation, time domain to frequency domain transformation, and frequency domain to time domain transformation.

[0292] As one example, the post-processing includes truncation and / or padding.

[0293] As an example, the first reference operation includes one or more of convolution, pooling, cascading, and activation.

[0294] As one embodiment, the first reference operation includes a fully connected layer.

[0295] As an example, the first reference operation includes a pooling layer.

[0296] As an example, the first reference operation includes at least one convolutional layer.

[0297] As an example, the first reference operation includes at least one coding layer.

[0298] As an example, an encoding layer includes at least one convolutional layer and one pooling layer.

[0299] As an example, in a convolutional layer, at least one convolutional kernel is used to convolve the input to generate a corresponding feature map, and at least one feature map output by the convolutional layer is reshaped into a vector and input to a fully connected layer; the fully connected layer transforms the vector into an output.

[0300] As an example, some or all of the kernel size, number of convolutional layers, stride, kernel size, stride, pooling function, activation function, and number of feature maps in the first reference operation are obtained through training.

[0301] As an example, some or all of the convolution kernel, pooling kernel, pooling function, activation function, parameters of the pooling function, and parameters of the activation function in the first reference operation are obtained through training.

[0302] As an example, the output of the first reference operation includes channel information.

[0303] As an example, the output of the first reference operation includes information other than channel information.

[0304] As an example, the output of the first reference operation includes a channel matrix.

[0305] As an example, the output of the first reference operation includes CSI.

[0306] As an example, the output of the first reference operation includes compressed CSI.

[0307] As an example, the output of the first reference operation includes CSI.

[0308] As an example, the output of the first reference operation includes a non-codebook-based CSI.

[0309] As an example, the output of the first reference operation includes a channel impulse response.

[0310] As an example, the output of the first reference operation includes small-scale characteristics.

[0311] As an example, the output of the first reference operation is used to determine one or more precoding matrices.

[0312] In one embodiment, the output of the first reference operation includes the predicted CSI.

[0313] In one embodiment, the output of the first reference operation includes predicted beam information.

[0314] In one embodiment, the output of the first reference operation includes positioning information.

[0315] As an example, the first reference operation includes CSI compression based on artificial intelligence or machine learning.

[0316] As an example, the first reference operation includes an encoder for CSI compression based on artificial intelligence or machine learning.

[0317] As an example, the first reference operation includes CSI prediction or CSI estimation based on artificial intelligence or machine learning.

[0318] As an example, the first reference operation includes beam management based on artificial intelligence or machine learning.

[0319] As one embodiment, the beam management includes at least one of beam prediction, beam switching, beam failure prediction, or beam failure recovery.

[0320] As one example, the first reference operation includes localization based on artificial intelligence or machine learning.

[0321] As one example, the first reference operation includes artificial intelligence or machine learning-assisted positioning.

[0322] As an example, the input to the first reference operation includes measurements obtained based on at least one RS resource.

[0323] As an example, the input to the first reference operation includes channel measurements obtained based on CSI-RS resources or SS / PBCH block resources.

[0324] As an example, the input to the first reference operation includes interference measurements obtained based on CSI-RS resources or CSI-IM resources.

[0325] As an example, the inputs to the first reference operation include the reception quality of at least one physical channel or physical signal.

[0326] As one embodiment, the first reference operation depends on a second configuration including: the second configuration instructing the first reference operation.

[0327] As one embodiment, the first reference operation depends on a second configuration including: the second configuration includes a first type identifier, which is different from a first type indication, and the first reference operation is associated with the first type identifier in the second configuration.

[0328] As an example, the first type of identifier is a non-negative integer.

[0329] As an example, the first type of identifier is a string.

[0330] As an example, the first type of identifier is used to identify AI models.

[0331] As an example, the first type of identifier is used to identify AI entities.

[0332] As an example, the first type of identifier is used to identify AI functions.

[0333] As an example, the advantages of the above method include that identifying an AI entity or function through the first type of identifier simplifies the design and unifies the understanding of different AI entities or functions across multiple nodes.

[0334] As an example, the first type of identifier is a model identifier.

[0335] As an example, the first type of identifier is used to identify an AI model.

[0336] As an example, the first type of identifier is used by the first node to identify an AI model.

[0337] As an example, the first type of identifier is used by the first node to determine the AI ​​model adopted by the first reference operation.

[0338] As an example, the advantages of the above method include that identifying an AI model / entity / function through the first type of identifier simplifies the design and unifies the understanding of different AI entities / functions across multiple nodes.

[0339] As an example, the first type of identifier is used to identify or indicate a set of resources.

[0340] As one embodiment, the first type of identifier is used to identify or indicate a set of resources, the measurement of which is used to obtain a training dataset.

[0341] As an example, the first type of identifier is used to identify or indicate a set of resources.

[0342] As an example, the first type of identifier is used to identify or indicate the training dataset.

[0343] As an example, the benefits of the above method include establishing consensus among different AI functions by identifying an AI training or AI training dataset to recognize the inferences generated by that AI training or AI training dataset, further simplifying the design.

[0344] Example 2

[0345] Example 2 illustrates a schematic diagram of a network architecture according to an embodiment of this application, as shown in Figure 2.

[0346] Figure 2 illustrates network architecture 200. Network architecture 200 is a 5G NR (New Radio) / LTE (Long-Term Evolution) / LTE-A (Long-Term Evolution Advanced) system, or a 5G+ network architecture, or a 6G network architecture, or a network architecture adopted in future evolutions by 3GPP; network architecture 200 may be referred to as 5GS (5G System) / EPS (Evolved Packet System), or 6GS (6G System); network architecture 200 includes at least one of UE (User Equipment) 201, RAN (Radio Access Network) 202, core network 210, HSS (Home Subscriber Server) / UDM (Unified Data Management) 220, and Internet service 230. The network architecture 200 can interconnect with other access networks, but these entities / interfaces are not shown for simplicity. As shown, the network architecture 200 provides packet-switched services; however, those skilled in the art will readily understand that the various concepts presented throughout this application can be extended to networks providing circuit-switched services or other cellular networks. The RAN includes node 203. The RAN may also include other nodes 204. Node 203 provides user and control plane protocol termination toward UE 201. Node 203 may be connected to other nodes 204 via an Xn interface (e.g., backhaul) / X2 interface. Node 203 may also be referred to as a base station, base transceiver station, radio base station, radio transceiver, transceiver function, basic service set (BSS), extended service set (ESS), TRP (transmitter-receiver node), or some other suitable term. The core network 210 is a 5GC (5G Core Network) / EPC (Evolved Packet Core), or the core network 210 is a 6GC; node 203 provides UE 201 with an access point to the core network 210.Examples of UE201 include cellular phones, smartphones, Session Initiation Protocol (SIP) phones, laptops, personal digital assistants (PDAs), satellite radios, non-terrestrial base station communications, satellite mobile communications, global positioning systems, multimedia devices, video devices, digital audio players (e.g., MP3 players), cameras, game consoles, drones, aircraft, narrowband IoT devices, machine-type communication devices, land vehicles, automobiles, wearable devices, or any other similar functional devices. Those skilled in the art may also refer to UE201 as a mobile station, subscriber station, mobile unit, subscriber unit, radio unit, remote unit, mobile device, radio device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handheld device, user agent, mobile client, client, or any other suitable term. Node 203 is connected to the core network 210 via an S1 / NG interface. The core network 210 includes an MME (Mobility Management Entity) / AMF (Authentication Management Field) / SMF (Session Management Function) 211, other MMEs / AMFs / SMFs 214, an S-GW (Service Gateway) / UPF (User Plane Function) 212, and a P-GW (Packet Data Network Gateway) / UPF 213. The MME / AMF / SMF 211 is the control node that handles signaling between the UE 201 and the core network 210. Generally, the MME / AMF / SMF 211 provides bearer and connection management. All user IP (Internet Protocol) packets are transmitted through the S-GW / UPF 212, which is itself connected to the P-GW / UPF 213. The P-GW provides UE IP address allocation and other functions. The P-GW / UPF 213 is connected to the Internet service 230. Internet services 230 include operator-compliant Internet protocol services, which may specifically include Internet, intranet, IMS (IP Multimedia Subsystem), and packet switching services.

[0347] As an example, the first node includes the UE201.

[0348] As one embodiment, the second node includes the node 203.

[0349] As an example, the wireless link between the UE201 and the node203 includes a cellular link.

[0350] As an example, the sender of the first information set includes the node 203.

[0351] As an example, the recipient of the first information set includes the UE201.

[0352] As an example, the sender of the first information report includes the UE201.

[0353] As an example, the recipient of the first information report includes the node 203.

[0354] As an example, the executor of the first reference operation includes the UE201.

[0355] As an example, the executor of the first operation includes the UE201.

[0356] As an example, the executor of the second reference operation includes the node 203.

[0357] As an example, the executor of the second operation includes the node 203.

[0358] Example 3

[0359] Example 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for the user plane and control plane according to an embodiment of this application, as shown in Figure 3.

[0360] Example 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for a user plane and control plane according to this application, as shown in Figure 3. Figure 3 is a schematic diagram illustrating an embodiment of a radio protocol architecture for a user plane 350 and a control plane 300. Figure 3 shows the radio protocol architecture for the control plane 300 between a first communication node device (UE, gNB, or RSU in V2X) and a second communication node device (gNB, UE, or RSU in V2X), or between two UEs, using three layers: Layer 1, Layer 2, and Layer 3. Layer 1 (L1 layer) is the lowest layer and implements various PHY (physical layer) signal processing functions. Layer 1 will be referred to herein as PHY 301. Layer 2 (L2 layer) 305 is above PHY 301 and is responsible for the link between the first communication node device and the second communication node device, or between two UEs. Layer L2 305 includes a MAC (Medium Access Control) sublayer 302, an RLC (Radio Link Control) sublayer 303, and a PDCP (Packet Data Convergence Protocol) sublayer 304, which terminate at the second communication node device. The PDCP sublayer 304 provides multiplexing between different radio bearers and logical channels. It also provides security through encrypted data packets and supports cross-cell mobility between the second communication node devices and the first communication node device. The RLC sublayer 303 provides upper-layer packet segmentation and reassembly, retransmission of lost packets, and packet reordering to compensate for out-of-order reception due to HARQ. The MAC sublayer 302 provides multiplexing between logical and transport channels. It is also responsible for allocating various radio resources (e.g., resource blocks) within a cell among the first communication node devices. Furthermore, the MAC sublayer 302 handles HARQ operations. In the control plane 300, the Radio Resource Control (RRC) sublayer 306 of Layer 3 (L3) is responsible for acquiring radio resources (i.e., radio bearers) and configuring the lower layers using RRC signaling between the second and first communication node devices. The user plane 350's radio protocol architecture includes Layer 1 (L1) and Layer 2 (L2). The radio protocol architecture for the first and second communication node devices in the user plane 350 is largely the same as the corresponding layers and sublayers in the control plane 300 for Physical Layer 351, PDCP sublayer 354 in L2 Layer 355, RLC sublayer 353 in L2 Layer 355, and MAC sublayer 352 in L2 Layer 355. However, PDCP sublayer 354 also provides header compression for upper layer data packets to reduce radio transmission overhead.The L2 layer 355 in the user plane 350 also includes an SDAP (Service Data Adaptation Protocol) sublayer 356, which is responsible for mapping between QoS streams and data radio bearers (DRBs) to support service diversity. Although not illustrated, the first communication node device may have several upper layers above the L2 layer 355, including a network layer (e.g., IP layer) terminating at the P-GW on the network side and an application layer terminating at the other end of the connection (e.g., a remote UE, server, etc.).

[0361] As an example, the wireless protocol architecture in Figure 3 is applicable to the first node.

[0362] As an example, the wireless protocol architecture in Figure 3 is applicable to the second node.

[0363] As an example, the higher layer mentioned in this application refers to the layer above the physical layer.

[0364] As an example, the first information set is generated in the RRC sublayer 306.

[0365] As an example, the first information set is generated in the MAC sublayer 302 or the MAC sublayer 352.

[0366] As an example, the first information report is generated in the MAC sublayer 302 or the MAC sublayer 352.

[0367] As an example, the first information report is generated in the PHY301 or the PHY351.

[0368] Example 4

[0369] Example 4 illustrates a schematic diagram of a first communication device and a second communication device according to an embodiment of this application, as shown in Figure 4. Figure 4 is a block diagram of a first communication device 410 and a second communication device 450 communicating with each other in an access network.

[0370] The first communication device 410 includes a controller / processor 475, a memory 476, a receiver processor 470, a transmitter processor 416, a multi-antenna receiver processor 472, a multi-antenna transmitter processor 471, a transmitter / receiver 418, and an antenna 420.

[0371] 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.

[0372] In the transmission from the first communication device 410 to the second communication device 450, at the first communication device 410, upper-layer data packets from the core network are provided to the controller / processor 475. The controller / processor 475 implements L2 layer functionality. In DL (Downlink), the controller / processor 475 provides header compression, encryption, packet segmentation and reordering, multiplexing between logical and transport channels, and radio resource allocation to the second communication device 450 based on various priority metrics. The controller / processor 475 is also responsible for HARQ operation, retransmission of lost packets, and signaling to the second communication device 450. The transmit processor 416 and the multi-antenna transmit processor 471 implement various signal processing functions for L1 layer (i.e., physical layer). Transmit processor 416 performs encoding and interleaving to facilitate forward error correction (FEC) at the second communication device 450, and constellation mapping based on various modulation schemes (e.g., binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), M-phase shift keying (M-PSK), and M-quadrature amplitude modulation (M-QAM). Multi-antenna transmit processor 471 performs digital spatial precoding on the encoded and modulated symbols, including codebook-based precoding and non-codebook-based precoding, and beamforming processing, generating one or more parallel... The transmit processor 416 then maps each parallel stream to a subcarrier, multiplexes the modulated symbols with a reference signal (e.g., a pilot) in the time and / or frequency domains, and then uses an inverse fast Fourier transform (IFFT) to generate a physical channel carrying the time-domain multicarrier symbol stream. The multi-antenna transmit processor 471 then performs transmit analog precoding / beamforming operations on the time-domain multicarrier symbol stream. Each transmitter 418 converts the baseband multicarrier symbol stream provided by the multi-antenna transmit processor 471 into an RF stream, which is then provided to a different antenna 420.

[0373] In the transmission from the first communication device 410 to the second communication device 450, at the second communication device 450, each receiver 454 receives a signal through its corresponding antenna 452. Each receiver 454 recovers the information modulated onto the radio frequency carrier and converts the radio frequency stream into a baseband multicarrier symbol stream, which is then provided to the receiver processor 456. The receiver processor 456 and the multi-antenna receiver processor 458 implement various signal processing functions of the L1 layer. The multi-antenna receiver processor 458 performs receive analog precoding / beamforming operations on the baseband multicarrier symbol stream from the receiver 454. The receiver processor 456 uses a Fast Fourier Transform (FFT) to convert the baseband multicarrier symbol stream after the receive analog precoding / beamforming operations from the time domain to the frequency domain. In the frequency domain, the physical layer data signal and the reference signal are demultiplexed by the receiver processor 456, where the reference signal is used for channel estimation, and the data signal is recovered in the multi-antenna receiver processor 458 after multi-antenna detection to recover any parallel stream destined for the second communication device 450. Symbols on each parallel stream are demodulated and recovered in the receive processor 456, generating soft decisions. The receive processor 456 then decodes and deinterleaves the soft decisions to recover the upper-layer data and control signals transmitted over the physical channel by the first communication device 410. The upper-layer data and control signals are then provided to the controller / processor 459. The controller / processor 459 implements the functions of Layer 2 (L2). The controller / processor 459 may be associated with a memory 460 storing program code and data. The memory 460 may be referred to as computer-readable media. In the DL (Layered Logic), the controller / processor 459 provides multiplexing, packet reassembly, decryption, header decompression, and control signal processing between the transmission and logical channels to recover upper-layer packets from the core network. The upper-layer packets are then provided to all protocol layers above Layer 2. Various control signals may also be provided to Layer 3 (L3) for L3 processing. The controller / processor 459 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operation.

[0374] In the transmission from the second communication device 450 to the first communication device 410, at the second communication device 450, a data source 467 is used to provide upper-layer data packets to the controller / processor 459. The data source 467 represents all protocol layers above the L2 layer. Similar to the transmission functions at the first communication device 410 described in the DL, the controller / processor 459 implements header compression, encryption, packet segmentation and reordering, and multiplexing between logical and transport channels based on the radio resource allocation of the first communication device 410, implementing L2 layer functions for the user plane and control plane. The controller / processor 459 is also responsible for HARQ operations, retransmission of lost packets, and signaling to the first communication device 410. Transmit processor 468 performs modulation mapping and channel coding processing, while multi-antenna transmit processor 457 performs digital multi-antenna spatial precoding, including codebook-based and non-codebook-based precoding, and beamforming processing. Subsequently, transmit processor 468 modulates the generated parallel stream into a multi-carrier / single-carrier symbol stream. After analog precoding / beamforming operations in multi-antenna transmit processor 457, the stream is provided to different antennas 452 via transmitter 454. Each transmitter 454 first converts the baseband symbol stream provided by multi-antenna transmit processor 457 into a radio frequency symbol stream before providing it to antenna 452.

[0375] In the transmission from the second communication device 450 to the first communication device 410, the function at the first communication device 410 is similar to the receiving function at the second communication device 450 described in the transmission from the first communication device 410 to the second communication device 450. Each receiver 418 receives radio frequency signals through its corresponding antenna 420, converts the received radio frequency signals into baseband signals, and provides the baseband signals to the multi-antenna receiving processor 472 and the receiving processor 470. The receiving processor 470 and the multi-antenna receiving processor 472 jointly implement the L1 layer functions. The controller / processor 475 implements the L2 layer functions. The controller / processor 475 may be associated with a memory 476 that stores program code and data. The memory 476 may be referred to as computer-readable media. The controller / processor 475 provides multiplexing, packet reassembly, decryption, header decompression, and control signal processing between the transmission and logical channels to recover upper-layer data packets from the second communication device 450. The upper-layer data packets from the controller / processor 475 may be provided to the core network. The controller / processor 475 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operation.

[0376] As one embodiment, the second communication device 450 includes: at least one processor and at least one memory, the at least one memory including computer program code; the at least one memory and the computer program code are configured to be used with the at least one processor. The second communication device 450 means at least: receiving a first information set; the first information set indicating M configurations, M being a positive integer greater than 1; performing a first reference operation; sending a first information report, or abandoning the sending of the first information report; a first configuration among the M configurations being used to configure the first information report; wherein the first configuration includes a first type of indication, the first type of indication in the first configuration being used to indicate a configuration other than the first configuration among the M configurations; the first information report depends on the output of the first reference operation, the first reference operation depending on a second configuration, the second configuration being the configuration indicated by the first type of indication in the first configuration.

[0377] As one embodiment, the second communication device 450 includes: a memory storing a computer-readable instruction program that, when executed by at least one processor, produces actions including: receiving a first information set; the first information set indicating M configurations, where M is a positive integer greater than 1; performing a first reference operation; sending a first information report, or abandoning the sending of the first information report; a first configuration among the M configurations being used to configure the first information report; wherein the first configuration includes a first type of indication, the first type of indication in the first configuration being used to indicate a configuration other than the first configuration among the M configurations; the first information report depending on the output of the first reference operation, the first reference operation depending on a second configuration, the second configuration being the configuration indicated by the first type of indication in the first configuration.

[0378] As one embodiment, the first communication device 410 includes: at least one processor and at least one memory, the at least one memory including computer program code; the at least one memory and the computer program code are configured to be used with the at least one processor. The first communication device 410 means at least: transmitting a first information set; the first information set indicating M configurations; wherein a target recipient of the first information set performs a first reference operation; the target recipient of the first information set transmits a first information report, or abandons transmitting the first information report; a first configuration among the M configurations is used to configure the first information report; the first configuration includes a first type of indication, the first type of indication in the first configuration being used to indicate a configuration other than the first configuration among the M configurations; the first information report depends on the output of the first reference operation, the first reference operation depending on a second configuration, the second configuration being the configuration indicated by the first type of indication in the first configuration.

[0379] As one embodiment, the first communication device 410 includes: a memory storing a computer-readable instruction program that, when executed by at least one processor, produces actions including: sending a first information set; the first information set indicating M configurations; wherein a target recipient of the first information set performs a first reference operation; the target recipient of the first information set sends a first information report or abandons sending the first information report; a first configuration among the M configurations is used to configure the first information report; the first configuration includes a first type of indication, the first type of indication in the first configuration being used to indicate a configuration other than the first configuration among the M configurations; the first information report depends on the output of the first reference operation, the first reference operation depending on a second configuration, the second configuration being the configuration indicated by the first type of indication in the first configuration.

[0380] As an example, the first node in this application includes the second communication device 450.

[0381] As an example, the second node in this application includes the first communication device 410.

[0382] As an example, at least one of {the antenna 452, the receiver 454, the receiving processor 456, the multi-antenna receiving processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to receive the first information 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, and the memory 476} is used to transmit the first information set in this application.

[0383] As an example, at least one of the following is used to send the first information report in this application, or to abandon sending the first information report: {the antenna 452, the transmitter / receiver 454, the transmission processor 468, the multi-antenna transmission processor 457, the receiving processor 456, the multi-antenna receiving processor 458, the controller / processor 459, the memory 460, and the data source 467}.

[0384] As an example, at least one of the following is used to receive the first information report in this application, or to waive the right to receive the first information report: {the antenna 420, the transmitter / receiver 418, the receiving processor 470, the multi-antenna receiving processor 472, the transmitting processor 416, the multi-antenna transmitting processor 471, the controller / processor 475, and the memory 476}.

[0385] As an example, at least one of the following is used to perform the first reference operation in this application: {the antenna 452, the receiver / transmitter 454, the receiving processor 456, the transmitting processor 468, the multi-antenna receiving processor 458, the multi-antenna transmitting processor 457, the controller / processor 459, the memory 460, and the data source 467}.

[0386] As an example, at least one of the following is used to perform the first operation in this application: {the antenna 452, the receiver / transmitter 454, the receiving processor 456, the transmitting processor 468, the multi-antenna receiving processor 458, the multi-antenna transmitting processor 457, the controller / processor 459, the memory 460, and the data source 467}.

[0387] As an example, at least one of the following is used to perform the second reference operation in this application: {the antenna 420, the transmitter / receiver 418, the receiver processor 470, the transmitter processor 416, the multi-antenna receiver processor 472, the multi-antenna transmitter processor 471, the controller / processor 475, and the memory 476}.

[0388] As an example, at least one of the following is used to perform the second operation in this application: {the antenna 420, the transmitter / receiver 418, the receiving processor 470, the transmitting processor 416, the multi-antenna receiving processor 472, the multi-antenna transmitting processor 471, the controller / processor 475, and the memory 476}.

[0389] Example 5

[0390] Example 5 illustrates a transmission flowchart according to an embodiment of this application; as shown in Figure 5. In Figure 5, the second node U1 and the first node U2 are communication nodes transmitting via an air interface. In Figure 5, the steps in blocks F50 to F54 are optional, while the steps in blocks F55 and F56 are alternatives.

[0391] For the second node U1, a second reference operation is deployed in step S5100; a second operation is deployed in step S5101; and a first information set is sent in step S511.

[0392] For the first node U2, in step S5200, a first reference operation is deployed; in step S5201, a first operation is deployed; in step S521, a first information set is received; in step S522, the first reference operation is executed; in step S5202, the first operation is executed; in step S523, a first information report is sent; and in step S524, the sending of the first information report is abandoned.

[0393] In embodiment 5, the first information set indicates M configurations, where M is a positive integer greater than 1; a first configuration among the M configurations is used to configure the first information reporting; the first configuration includes a first type of indication, which is used to indicate a configuration other than the first configuration among the M configurations; the first information reporting depends on the output of the first reference operation, which depends on a second configuration, which is the configuration indicated by the first type of indication in the first configuration.

[0394] As an example, the first node U2 is the first node in this application.

[0395] As an example, the second node U1 is the second node in this application.

[0396] As one embodiment, the air interface between the second node U1 and the first node U2 includes a wireless interface between the base station equipment and the user equipment.

[0397] As one embodiment, the air interface between the second node U1 and the first node U2 includes a wireless interface between the relay node device and the user equipment.

[0398] As one embodiment, the air interface between the second node U1 and the first node U2 includes a wireless interface between user equipment and user equipment.

[0399] In one embodiment, the second node U1 is the serving cell sustaining base station of the first node U2.

[0400] As an example, the AI ​​training function in the RAN (Radio Access Network) domain is located in the RAN domain-specific management function, while the AI ​​inference function is located in the UE.

[0401] As an example, RAN domain-specific management functions provide AI training function management capabilities and AI inference function management capabilities.

[0402] As an example, the AI ​​training function is located in the RAN domain-specific management function, while the AI ​​inference function is located locally in the gNB.

[0403] As an example, the management capability of AI training is provided by RAN domain-specific management functions, while the management capability of AI inference is provided locally by the gNB.

[0404] As an example, MnF refers to Management Function.

[0405] As an example, both the AI ​​training function and the AI ​​inference function are located in the UE, wherein the UE provides the ability to train and infer.

[0406] As an example, RAN domain-specific management functions provide management capabilities for AI training and AI inference functions.

[0407] As an example, both the AI ​​training function and the AI ​​inference function are located in the gNB.

[0408] As an example, the management capabilities for both AI training and AI inference are provided locally by gNB.

[0409] As one embodiment, the deployment of the first operation includes: obtaining the first operation.

[0410] As an example, the deployment first operation includes: loading the first operation.

[0411] As one embodiment, the deployment of the first operation includes: submitting a request to load the first operation.

[0412] As one embodiment, the deployment of the second operation includes: obtaining the second operation.

[0413] As an example, the deployment of the second operation includes: loading the second operation.

[0414] As one embodiment, the deployment of the second operation includes: submitting a request to load the second operation.

[0415] As one embodiment, the deployment of the first reference operation includes: obtaining the first reference operation.

[0416] As an example, the deployment of the first reference operation includes: loading the first reference operation.

[0417] As one embodiment, the deployment of the first reference operation includes: submitting a request to load the first reference operation.

[0418] As one embodiment, the deployment of the second reference operation includes: obtaining the second reference operation.

[0419] As one embodiment, the deployment of the second reference operation includes: loading the second reference operation.

[0420] As one embodiment, the deployment of the second reference operation includes: submitting a request to load the second reference operation.

[0421] As an example, the deployment of the first reference operation precedes the reception of the first information set.

[0422] As an example, the deployment of the first reference operation is later than the reception of the first information set.

[0423] As an example, the deployment of the second reference operation precedes the transmission of the first information set.

[0424] As an example, the deployment of the second reference operation is later than the transmission of the first information set.

[0425] As one embodiment, the first reference operation is used for information compression, and the second reference operation is used for information recovery.

[0426] As one embodiment, the first reference operation is used for CSI compression, and the second reference operation is used for CSI recovery.

[0427] As an example, when a two-sided AI model is adopted, the first node performs a first reference operation and the second node performs a second reference operation.

[0428] As an example, when a single-side AI model is used, the step in box F51 is not present.

[0429] As an example, when a single-side AI model is adopted, the step in block F51 is not present, and the first reference operation is used for at least one of beam management, CSI prediction, CSI estimation, RLF (radio link failure) prediction, cell handover prediction, or serving cell prediction.

[0430] As an example, when a single-side AI model is adopted, the step in block F51 is not present, and the first reference operation is used for at least one of performance monitoring, positioning, beam management, CSI prediction, CSI estimation, RLF (radio link failure) prediction, cell handover prediction, or serving cell prediction.

[0431] As an example, the deployment of the first operation precedes the reception of the first information set.

[0432] As an example, the deployment of the first operation is later than the reception of the first information set.

[0433] As one example, the deployment of the second operation precedes the transmission of the first information set.

[0434] As an example, the deployment of the second operation is later than the transmission of the first information set.

[0435] As an example, step S5202 exists, where the first information reporting depends on the output of the first operation, and the input of the first operation depends on the output of the first reference operation.

[0436] As an example, steps S5201 and S5202 are not present.

[0437] As an example, the first operation is used for CSI compression, and the second operation is used for CSI recovery.

[0438] As an example, when a two-sided AI model is adopted, the first node performs a first operation and the second node performs a second operation.

[0439] As an example, when a single-side AI model is used, the step in box F53 is not present.

[0440] As an example, when a single-side AI model is adopted, the step in block F53 is not present, and the first operation is used for at least one of beam management, CSI prediction, CSI estimation, RLF (radio link failure) prediction, cell handover prediction, or serving cell prediction.

[0441] As an example, when a single-side AI model is adopted, the step in block F53 is not present, and the first operation is used for at least one of performance monitoring, positioning, beam management, CSI prediction, CSI estimation, RLF (radio link failure) prediction, cell handover prediction, or serving cell prediction.

[0442] Examples 6A-6B

[0443] Examples 6A-6B illustrate schematic diagrams of the first information reporting depending on the output of a first reference operation according to an embodiment of this application, as shown in Figures 6A-6B respectively.

[0444] In embodiment 6A, the first information reporting depends on the output of the first operation, and the input of the first operation depends on the output of the first reference operation.

[0445] As an example, the first operation is based on training or AI.

[0446] As an example, the first operation includes inference.

[0447] As one example, the first operation includes an AI entity.

[0448] As an example, the first operation includes an AI entity for inference.

[0449] As an example, the first operation includes a portion of an AI entity.

[0450] As an example, the first operation includes a portion of an AI entity used for inference.

[0451] As one embodiment, the first operation includes reasoning for obtaining the first information report.

[0452] As an example, the reasoning includes AI (Artificial Intelligence) inference.

[0453] As an example, the first operation includes AI inference for obtaining CSI.

[0454] As one example, the first operation includes AI inference for obtaining channel information.

[0455] As one example, the first operation includes AI inference for obtaining information other than channel information.

[0456] As an example, the first operation includes AI inference for at least one of beam management, positioning or assisted positioning, CSI prediction, CSI estimation, or CSI compression.

[0457] As an example, the first operation includes AI inference for at least one of performance monitoring, positioning, beam management, CSI prediction, CSI estimation, CSI compression, RLF (radio link failure) prediction, cell handover prediction, or serving cell prediction.

[0458] As an example, the first operation is used for an AI function.

[0459] As an example, the first operation is performed by the physical layer of the first node.

[0460] As an example, the first operation is performed at a higher level than the first node.

[0461] As an example, the model for the first operation is obtained through training.

[0462] As an example, the training for the first operation is performed by the first node.

[0463] As an example, the training of the first operation is performed by the sender of the first information set.

[0464] As an example, the training for the first operation is performed by the core network.

[0465] As an example, the training of the first operation is performed by an AI training producer.

[0466] As an example, the training of the first operation is performed by the MDA (Management Data Analytics Function).

[0467] As an example, the training of the first operation is performed by the MDA function located at the first node.

[0468] As an example, the training of the first operation is performed by the MDA function of the sender located in the first information set.

[0469] As an example, the training of the first operation is performed by NWDAF (Network Data Analytics Function).

[0470] As an example, the training of the first operation is performed by the MDAS (Management Data Analytics Service) producer.

[0471] As an example, the training of the first operation is performed by the MnS (Management Service) producer.

[0472] As an example, the first operation requires deployment.

[0473] As an example, the first operation is obtained by loading.

[0474] As an example, the first operation is obtained from the serving cell of the first node.

[0475] As an example, the first operation is obtained from the sustaining base station of the serving cell of the first node.

[0476] As an example, the first node deploys the first operation.

[0477] As an example, the first operation does not require deployment.

[0478] As an example, the first operation is obtained from the core network.

[0479] As an example, the first operation is based on artificial intelligence or machine learning.

[0480] As an example, the first operation is based on a neural network.

[0481] As an example, the first operation is based on CNN (Conventional Neural Networks).

[0482] As one example, the first operation includes preprocessing.

[0483] As one example, the first operation includes post-processing.

[0484] As one example, the post-processing includes DFT.

[0485] As one example, the post-processing includes quantization.

[0486] As an example, the post-processing includes one or more of the following: angular domain to spatial domain transformation, spatial domain to angular domain transformation, time domain to frequency domain transformation, and frequency domain to time domain transformation.

[0487] As one example, the post-processing includes truncation and / or padding.

[0488] As an example, the first operation includes one or more of convolution, pooling, cascading, and activation.

[0489] As one embodiment, the first operation includes a fully connected layer.

[0490] As an example, the first operation includes a pooling layer.

[0491] As one embodiment, the first operation includes at least one convolutional layer.

[0492] As an example, the first operation includes at least one encoding layer.

[0493] As an example, an encoding layer includes at least one convolutional layer and one pooling layer.

[0494] As an example, in a convolutional layer, at least one convolutional kernel is used to convolve the input to generate a corresponding feature map, and at least one feature map output by the convolutional layer is reshaped into a vector and input to a fully connected layer; the fully connected layer transforms the vector into an output.

[0495] As an example, some or all of the following parameters in the first operation—convolution kernel size, number of convolutional layers, convolution stride, pooling kernel size, pooling kernel stride, pooling function, activation function, and number of feature maps—are obtained through training.

[0496] As an example, some or all of the convolution kernel, pooling kernel, pooling function, activation function, parameters of the pooling function, and parameters of the activation function in the first operation are obtained through training.

[0497] As an example, the output of the first operation includes channel information.

[0498] As an example, the output of the first operation includes information other than channel information.

[0499] As an example, the output of the first operation includes a channel matrix.

[0500] As an example, the output of the first operation includes CSI.

[0501] As an example, the output of the first operation includes compressed CSI.

[0502] As an example, the output of the first operation includes CSI.

[0503] As an example, the output of the first operation includes non-codebook-based CSI.

[0504] As an example, the output of the first operation includes a channel impulse response.

[0505] As an example, the output of the first operation includes small-scale characteristics.

[0506] As an example, the output of the first operation is used to determine one or more precoding matrices.

[0507] As an example, the first operation includes CSI compression based on artificial intelligence or machine learning.

[0508] As an example, the first operation includes an encoder for CSI compression based on artificial intelligence or machine learning.

[0509] As an example, the first operation includes CSI prediction or CSI estimation based on artificial intelligence or machine learning.

[0510] As one example, the first operation includes beam management based on artificial intelligence or machine learning.

[0511] As one embodiment, the beam management includes at least one of beam prediction, beam switching, beam failure prediction, or beam failure recovery.

[0512] As an example, the first operation includes localization based on artificial intelligence or machine learning.

[0513] As one example, the first operation includes artificial intelligence or machine learning-assisted positioning.

[0514] As an example, the input to the first operation includes measurements obtained based on at least one RS resource.

[0515] As an example, the input to the first operation includes channel measurements obtained based on CSI-RS resources or SS / PBCHblock resources.

[0516] As an example, the input to the first operation includes interference measurements obtained based on CSI-RS resources or CSI-IM resources.

[0517] As an example, the input to the first operation includes the reception quality of at least one physical channel or physical signal.

[0518] As an example, the input to the first operation includes a matrix or vector obtained by preprocessing the channel matrix obtained from measurements based on at least one RS resource.

[0519] As an example, the output of the first operation is used to generate the first information report.

[0520] As an example, the first information reporting includes the output of the first operation.

[0521] As an example, the first information report includes the post-processed output of the first operation.

[0522] As an example, the first information report includes the truncated and / or quantized output of the first operation.

[0523] As an example, the output of the first operation, after post-processing, is used to generate the first information report.

[0524] As an example, the output of the first operation, after being truncated and / or quantized, is used to generate the first information report.

[0525] As an example, some or all of the output of the first operation is post-processed and used to generate the first information report.

[0526] As an example, some or all of the output of the first operation is truncated and / or quantized and then used to generate the first information report.

[0527] As an example, the input to the first operation includes the output of the first reference operation.

[0528] As an example, the input to the first operation includes some or all of the output of the first reference operation.

[0529] As an example, the output of the first reference operation is used to obtain some or all of the input of the first operation.

[0530] As one embodiment, some or all of the output of the first reference operation is used as the input of the first operation.

[0531] As an example, the input to the first operation includes the post-processed output of the first reference operation.

[0532] As an example, the input to the first operation includes at least a portion of the post-processed output of the first reference operation.

[0533] As an example, at least a portion of the output of the first reference operation is post-processed and used as the input of the first operation.

[0534] As an example, the post-processing includes one or more of the following: quantization, truncation, DFT (Discrete Fourier Transform), angular domain to spatial domain transformation, spatial domain to angular domain transformation, time domain to frequency domain transformation, and frequency domain to time domain transformation.

[0535] As an example, the output of the first reference operation and the output of the first operation are different types of information.

[0536] As an example, the output of the first reference operation and the output of the first operation are two of the following: performance monitoring, positioning, beam management, CSI prediction, CSI estimation, CSI compression, RLF (radio link failure) prediction, cell handover prediction, and serving cell prediction.

[0537] As an example, the output of the first reference operation includes channel information, and the output of the first operation includes information other than channel information.

[0538] As an example, the output of the first reference operation includes channel information, and the output of the first operation includes at least one of performance monitoring results, RLF prediction, cell handover prediction, serving cell prediction, or location.

[0539] As an example, the output of the first reference operation includes beam information, and the output of the first operation includes at least one of predicted CSI, estimated CSI, or compressed CSI.

[0540] As an example, the output of the first reference operation includes predicted beam information or switched beam information, and the output of the first operation includes at least one of predicted CSI, estimated CSI, or compressed CSI.

[0541] As an example, the output of the first reference operation includes the predicted CSI, and the output of the first operation includes the compressed CSI obtained by compressing the predicted CSI.

[0542] As an example, the output of the first reference operation includes positioning information, and the output of the first operation includes channel information.

[0543] As an example, the output of the first reference operation includes positioning information, and the output of the first operation includes beam information.

[0544] As an example, the output of the first reference operation includes location information, and the output of the first operation includes at least one of predicted CSI, estimated CSI, or compressed CSI.

[0545] As an example, the output of the first reference operation includes location information, and the output of the first operation includes at least one of performance monitoring results, RLF prediction, cell handover prediction, or serving cell prediction.

[0546] As an example, the first operation and the first reference operation are jointly trained.

[0547] As an example, the advantages of the above method include that it optimizes the first operation and the first reference operation.

[0548] As an example, the first operation and the first reference operation are trained separately.

[0549] As an example, the advantages of the above method include increased flexibility.

[0550] As one embodiment, the training of the first operation depends on the training result of the first reference operation, or the training of the first reference operation depends on the training result of the first operation.

[0551] As an example, the advantages of the above method include achieving a better balance between performance and flexibility.

[0552] As an example, the training of the first operation and the training of the first reference operation are independent.

[0553] As an example, the advantages of the above method include increased flexibility.

[0554] In Example 6B, the output of the first reference operation is used to generate the first information report.

[0555] As an example, the output of the first reference operation is used to generate the first information report.

[0556] As one embodiment, the first information reporting includes the output of the first reference operation.

[0557] As one embodiment, the first information reporting includes the post-processed output of the first reference operation.

[0558] As one embodiment, the first information report includes the truncated and / or quantized output of the first reference operation.

[0559] As an example, the output of the first reference operation, after post-processing, is used to generate the first information report.

[0560] As an example, the output of the first reference operation, after being truncated and / or quantized, is used to generate the first information report.

[0561] As an example, some or all of the output of the first reference operation is post-processed and used to generate the first information report.

[0562] As an example, some or all of the output of the first reference operation, after being truncated and / or quantized, is used to generate the first information report.

[0563] As an example, measurements obtained based on at least one RS resource and the output of the first reference operation are used to generate the first information report.

[0564] As an example, the reception quality of at least one physical channel or physical signal and the output of the first reference operation are used to generate the first information report.

[0565] As one embodiment, the first configuration indicates a first type of resource set, the first type of resource set including at least one RS resource for the measurement used for the first information report; the measurement for the first type of resource set and the output of the first reference operation are used to generate the first information report.

[0566] As one embodiment, generating the first information report includes: calculating the first information report.

[0567] As one example, how the output of the first reference operation is used to generate the first information report is determined by the manufacturer of the first node, or is implementation-dependent. Some typical but non-limiting implementations are described below:

[0568] As an example, the output of the first reference operation includes predicted channel information, and a comparison between the channel information obtained from measurements based on at least one RS resource and the predicted channel information is used to generate the first information report.

[0569] As an example, the output of the first reference operation includes predicted beam information, and a comparison between the beam information obtained from measurements based on at least one RS resource and the predicted beam information is used to generate the first information report.

[0570] As an example, the output of the first reference operation includes predicted beam information, and whether the beam information obtained from the measurement of at least one RS resource is the same as the predicted beam information is used to generate the first information report.

[0571] As an example, the output of the first reference operation includes predicted beam information, and the first information report includes CSI.

[0572] As an example, the output of the first reference operation includes predicted beam information; when the comparison result between the beam information obtained from measurements based on at least one RS resource and the predicted beam information is greater than a certain threshold, the first information report indicates that the first reference operation has failed.

[0573] As an example, the output of the first reference operation includes predicted beam information; when the predicted beam information is worse than a certain threshold, the first information report indicates that the first reference operation has failed.

[0574] As an example, the output of the first reference operation includes predicted beam information; when the predicted beam information is worse than a certain threshold, the first information report indicates beam failure.

[0575] As an example, the output of the first reference operation includes the predicted RSRP; when the difference between the RSRP measured based on at least one RS resource and the predicted RSRP is greater than a certain threshold, the first information report indicates that the first reference operation has failed.

[0576] As an example, the output of the first reference operation includes the predicted link quality; when the difference between the link quality measured based on at least one RS resource and the predicted link quality is greater than a certain threshold, the first information report indicates that the first reference operation has failed.

[0577] As an example, the output of the first reference operation includes the predicted link quality; when the predicted link quality is worse than a certain threshold, the first information report indicates RLF or beam failure.

[0578] As an example, the output of the first reference operation includes predicted beam information, and the first information report includes one of performance monitoring results, RLF prediction, cell handover prediction, or serving cell prediction.

[0579] As an example, the output of the first reference operation includes predicted channel information, and the first information report includes one of performance monitoring results, RLF prediction, cell handover prediction, or serving cell prediction.

[0580] As one embodiment, the output of the first reference operation includes positioning information, and the first information report includes channel information.

[0581] As an example, the method for generating the first information report based on the output of the first reference operation is not based on artificial intelligence or machine learning.

[0582] Examples 7A-7B

[0583] Examples 7A-7B illustrate schematic diagrams of first information reporting according to an embodiment of this application, as shown in Figures 7A-7B respectively.

[0584] In embodiment 7A, the first configuration indicates a first type of resource set, which includes at least one RS resource for the measurement used in the first information reporting; the first information reporting indicates at least one resource in a second type of resource set. In Figure 7A, the first type of resource set includes resources #1, ..., resource #J1; the second type of resource set includes resources #1, ..., resource #J2.

[0585] As an example, the first information report includes a resource indication, which is used to indicate at least one resource in the second type of resource set.

[0586] As an example, the first information report includes at least one of resource indication or RSRP (reference signal received power); the resource indication is used to indicate at least one resource in the second type of resource set.

[0587] As one example, how the first information report is generated is determined by the manufacturer of the first node, or is implementation-related. A typical but non-limiting implementation is described below:

[0588] The first node first measures the RS resources in the first type of resource set to obtain the channel parameter matrix H. r×t Where r and t are the number of receiving antennas and the number of antenna ports, respectively; at least the channel parameter matrix H r×t Alternatively, its feature vector is input to the first operation, and the output of the first operation is used to obtain the first information report.

[0589] Without loss of generality, the parameters or AI model used in the first operation are determined by the manufacturer of the first node.

[0590] As an example, the first type of resource set includes one or more RS (Reference Signal) resource sets, and an RS resource set includes one or more RS resources.

[0591] As an example, the first type of resource set includes at least one of at least a CSI-RS resource set, at least one CSI-SSB (Channel State Information-Synchronization Signal Block) resource set, or at least one CSI-IM (Channel State Information-Interference Measurement) resource set.

[0592] As an example, the first type of resource set includes at least one RS resource set for channel measurement, and an RS resource set for channel measurement includes one or more RS resources.

[0593] As one embodiment, the first type of resource set includes at least one RS resource set for channel measurement and at least one RS resource set for interference measurement; an RS resource set for channel measurement includes one or more RS resources, and an RS resource set for interference measurement includes one or more RS resources.

[0594] As one embodiment, the first type of resource set includes at least one RS resource set for interference measurement; an RS resource set for interference measurement includes one or more RS resources.

[0595] As an example, a set of RS resources for channel measurement includes one or more RS resources, wherein any RS resource in the set of RS resources for channel measurement is a CSI-RS resource or a synchronization signal resource.

[0596] As an example, a set of RS resources for interference measurement includes one or more RS resources.

[0597] As an example, an RS resource set for interference measurement includes one or more RS resources, wherein any RS resource in the RS resource set for interference measurement is a CSI-IM resource or an NZP (non-zero power) CSI-RS resource for interference measurement.

[0598] As an example, the first type of resource set includes at least one of CSI-RS (Channel State Information Reference Signal) resources or synchronization signal resources.

[0599] As one embodiment, the synchronization signal resources include at least the resources occupied by the synchronization signal.

[0600] As an example, the synchronization signal resource is an SSB (Synchronization Signal Block).

[0601] As an example, the synchronization signal resource is an SS / PBCH (synchronization signal / physical broadcast channel) block resource.

[0602] As an example, the first configuration indicates at least one resource configuration, and the at least one resource configuration indicates a first type of resource set.

[0603] As an example, a resource configuration is used to configure CSI resources.

[0604] As an example, a resource configuration is an IE CSI-ResourceConfig.

[0605] As an example, a resource configuration includes an RRC IE.

[0606] As an example, a resource configuration includes IE CSI-ResourceConfig.

[0607] As one embodiment, the first configuration includes an identifier for the first type of resource set.

[0608] As an example, the second type of resource set is the first type of resource set.

[0609] As one embodiment, the second type of resource set includes resources that do not belong to the first type of resource set.

[0610] As one embodiment, the first configuration indicates a first type of resource set, the first type of resource set including at least one RS resource for the measurement used for the first information reporting; the first information reporting indicates at least one resource and RSRP in a second type of resource set, the second type of resource set including resources that do not belong to the first type of resource set.

[0611] As an example, the first node is not required to measure some or all of the resources in the second type of resource set.

[0612] As an example, the first type of resource set is used for measurement, and the second type of resource set is used for prediction.

[0613] As an example, the first type of resource set is used for measurement, and the second type of resource set is used for prediction.

[0614] As an example, only the first type of resource set and the second type of resource set are used for measurement.

[0615] As one embodiment, using only the first type of resource set in the first type of resource set and the second type of resource set for measurement includes: using only the first type of resource set in the first type of resource set and the second type of resource set for measurement by the first node.

[0616] As one embodiment, the use of only the first type of resource set for measurement in the first type of resource set and the second type of resource set includes: the first type of resource set being used for measurement by the first node, and the first node not being required to measure some or all of the resources in the second type of resource set.

[0617] As one embodiment, the first node not being required to measure the second type of resource set includes: the first node not measuring some or all of the resources in the second type of resource set.

[0618] As one embodiment, the first node not being required to measure the second type of resource set includes: whether the first node measures some or all of the resources in the second type of resource set is implementation-related or determined by the first node itself.

[0619] As one embodiment, the second type of resource set includes the first type of resource set and resources other than the first type of resource set.

[0620] As one embodiment, the first type of resource set includes one or more RS resources, the second type of resource set includes one or more RS resources, and the second type of resource set includes the first type of resource set and RS resources other than the first type of resource set.

[0621] As an example, the number of resources included in the first type of resource set is less than the number of resources included in the second type of resource set.

[0622] As an example, the number of RS resources included in the first type of resource set is less than the number of RS resources included in the second type of resource set.

[0623] As one embodiment, the second type of resource set includes resources that do not belong to the first type of resource set.

[0624] As one embodiment, the second type of resource set includes antenna ports that do not belong to the first type of resource set.

[0625] As an example, the second type of resource set includes resources that do not belong to the first type of resource set. The resources in the second type of resource set include at least one of antenna ports, TCI status, QCL information, time and frequency resources, time and frequency code resources, beams, RS resources, vectors, or matrices.

[0626] As an example, the second type of resource set includes at least one training dataset.

[0627] As an example, the second type of resource set is used to train an AI model.

[0628] As an example, the second type of resource set is used to train the first operation in this application.

[0629] As an example, the second type of resource set includes one or more RS (Reference Signal) resource sets, and an RS resource set includes one or more RS resources.

[0630] As one embodiment, the first configuration includes a first type identifier, and the second type of resource set depends on the first type identifier in the first configuration.

[0631] As one embodiment, the second type of resource set depends on the first type of identifier, which is used to identify the second type of resource set.

[0632] As one embodiment, the second type of resource set depends on the first type of identifier, which includes: the first type of identifier is used to identify a reference resource set, the reference resource set including the second type of resource set.

[0633] As one embodiment, the second type of resource set depends on the first type of identifier, which includes: the first type of identifier being used to identify a reference resource set, the reference resource set including the second type of resource set, and the first configuration being used to indicate the second type of resource set from the reference resource set.

[0634] As an example, information other than the first configuration indicates the second type of resource set.

[0635] As one embodiment, information outside the first information set indicates the second type of resource set.

[0636] As one example, the information indicating the second type of resource set in addition to the first configuration includes higher-level parameters.

[0637] As one example, the information indicating the second type of resource set in addition to the first configuration includes RRC parameters.

[0638] As one embodiment, the information indicating the second type of resource set in addition to the first configuration includes part or all of an RRC IE domain.

[0639] As an example, the information indicating the second type of resource set in addition to the first configuration includes MAC CE.

[0640] As an example, the information indicating the second type of resource set in addition to the first configuration includes DCI (downlink control information).

[0641] In embodiment 7B, the output of the first operation includes a first CSI, the first information report carries the first CSI, and the first CSI is used as input to the second operation by the target recipient of the first information report to generate a second CSI.

[0642] As an example, the advantages of the above method include improved CSI reporting performance by leveraging the advantages of the first operation, including more accurate reporting and / or lower overhead.

[0643] As an example, the first CSI is used to generate the first information report.

[0644] As one embodiment, the first information report includes the first CSI.

[0645] As an example, the first CSI includes a compressed CSI.

[0646] As one example, the first CSI includes compressed predicted channel information.

[0647] As an example, the first CSI is post-processed and used to generate the first information report.

[0648] As one embodiment, the first information report includes the first CSI after post-processing.

[0649] As an example, the first information report carries the first CSI after post-processing.

[0650] As an example, the first CSI is truncated and / or quantized and used to generate the first information report.

[0651] As one embodiment, the first information report includes the first CSI after truncation and / or quantization.

[0652] As an example, the first information report carries the first CSI after truncation and / or quantization.

[0653] As one embodiment, the first CSI includes a channel matrix.

[0654] As one example, the first CSI includes a feature vector.

[0655] As an example, the first CSI includes a feature vector and feature values.

[0656] As an example, the first CSI includes precoded information.

[0657] As one embodiment, the first CSI includes pre-encoded information based on a non-codebook.

[0658] As an example, the first CSI is used to determine at least one precoding matrix.

[0659] As an example, the first CSI indicates at least one precoding matrix.

[0660] As an example, the precoding matrix is ​​in the spatial-frequency domain.

[0661] As an example, the precoding matrix is ​​an angular-delay domain projection.

[0662] As one embodiment, the first CSI includes information on the relative phase, amplitude, and / or coefficients between multiple antenna ports.

[0663] As an example, the first CSI includes a compressed CSI.

[0664] As an example, the first CSI includes predicted / estimated CSI.

[0665] As an example, the first operation is used for CSI compression, and the second operation is used for CSI recovery.

[0666] As one embodiment, the second CSI includes the recovery of at least a portion of the input of the first operation.

[0667] As one embodiment, the second CSI includes a channel matrix.

[0668] As one embodiment, the second CSI includes a feature vector and / or feature values.

[0669] As one embodiment, the second CSI includes a precoding matrix.

[0670] As one embodiment, the second CSI includes one or more of the following: channel matrix, eigenvector, eigenvalue, or precoding matrix.

[0671] As one embodiment, the target recipient of the first information report is the sender configured in the first configuration.

[0672] As an example, the second operation is the inverse operation of the first operation.

[0673] As an example, the second operation is based on training.

[0674] As one example, the training for obtaining the second operation is performed by the target receiver of the first information report.

[0675] As one example, the training for obtaining the second operation is performed by the MDA function.

[0676] As an example, the training for obtaining the second operation is performed by the MDAS producer.

[0677] As an example, the training for obtaining the second operation is performed by NWDAF.

[0678] As an example, the training for obtaining the second operation is performed by the core network.

[0679] As an example, the training for obtaining the second operation is performed by an AI (Artificial Intelligence) training producer.

[0680] As an example, the first operation and the second operation are obtained through different training.

[0681] As an example, the first operation and the second operation are obtained through independent training.

[0682] As an example, the advantages of the above method include: saving air interface overhead, having better flexibility, being adaptable to different terminals, and having better forward compatibility.

[0683] As an example, the first operation and the second operation are obtained through joint training.

[0684] As an example, the advantages of the above method include: optimized performance.

[0685] As an example, the training of the second operation depends on the first operation.

[0686] As an example, the producer of the second operation trains the second operation based on the output of the first operation.

[0687] As one example, the second operation includes inference.

[0688] As one example, the second operation includes AI inference.

[0689] As one example, the second operation includes AI inference for CSI.

[0690] As an example, the second operation is AI inference for CSI recovery.

[0691] As an example, the second operation is AI inference for CSI decompression.

[0692] As an example, the second operation is performed by the AI ​​entity deployed on the second node in this application.

[0693] As an example, the second operation is used for the AI ​​function of the second node in this application.

[0694] As an example, the second operation requires deployment.

[0695] As an example, the second operation is obtained by loading.

[0696] As an example, the second operation is obtained from the core network.

[0697] As an example, the second operation is obtained from the producer.

[0698] As an example, the second operation is obtained from the producer of the second operation.

[0699] As an example, the second operation is obtained from loading from the AL entity producer.

[0700] As an example, the second operation is obtained from the AL function producer.

[0701] As an example, the second operation is obtained from loading from the MnS producer.

[0702] As an example, the second operation is based on artificial intelligence or machine learning.

[0703] As an example, the second operation is based on a neural network.

[0704] As one example, the second operation includes a decoder for CSI compression based on a neural network.

[0705] As one example, the second operation includes a CNN-based CSI compression encoder.

[0706] As an example, the second operation is performed by the physical layer of the second node.

[0707] As one example, the second operation is performed at a higher level of the second node.

[0708] Examples 8A-8B

[0709] Examples 8A-8B respectively illustrate schematic diagrams of the deployment of a first given operation by the first node according to an embodiment of this application; as shown in Figures 8A-8B respectively.

[0710] In embodiment 8A, the first node requests the first producer to load a first given operation and obtains the first given operation from the first producer. The first given operation is the first operation in this application, or the first given operation is the first reference operation in this application.

[0711] As one example, the deployment includes obtaining the first given operation.

[0712] As one example, the deployment includes obtaining an AI entity.

[0713] As one example, the deployment includes obtaining an AI entity that performs the first given operation.

[0714] As one example, the deployment includes obtaining an AI entity that includes AI functionality to perform the first given operation.

[0715] As one example, the deployment includes loading the first given operation.

[0716] As one example, the deployment includes submitting a request to load the first given operation.

[0717] As an example, the first given operation is obtained from the serving cell of the first node.

[0718] As an example, the first given operation is loaded from the sustaining base station of the serving cell of the first node.

[0719] As an example, the first given operation is obtained from the core network.

[0720] As an example, the first given operation is obtained from loading from the first producer.

[0721] As an example, the deployment is accomplished by an AI function.

[0722] As an example, the deployment is accomplished by AI functionality deployed on the first node.

[0723] As an example, the deployment is accomplished by an AI deployment function.

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

[0725] As an example, the deployment is accomplished using AI inference functionality.

[0726] As an example, the deployment is accomplished by an AI inference function deployed on the first node.

[0727] As an example, the deployment is performed by an AI entity.

[0728] As an example, the deployment is performed by an AI entity deployed on the first node.

[0729] As an example, the deployment is performed by an AI entity with a deployment function.

[0730] As an example, the deployment is performed by an AI entity with deployment capabilities deployed on the first node.

[0731] As an example, the deployment is accomplished by an AI entity with an inference function.

[0732] As an example, the deployment is performed by an AI entity with inference capabilities deployed on the first node.

[0733] As one embodiment, the deployment includes obtaining the first given operation from a first producer.

[0734] As one embodiment, the deployment includes making a request to the first producer to load the first given operation.

[0735] As one embodiment, the deployment includes loading the first given operation from the first producer.

[0736] As an example, the first producer generates and provides the AL entity.

[0737] As an example, the first producer generates and provides AL functionality.

[0738] As an example, the first producer is the producer of the first given operation.

[0739] As an example, the first producer includes an AL entity producer.

[0740] As one example, the first producer includes an AL function producer.

[0741] As one example, the first producer includes an AL deployment producer.

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

[0743] As one example, the first producer includes an AL-trained producer.

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

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

[0746] As one example, the first producer includes the producer that loads the AL entity.

[0747] As an example, the first producer includes an MnS (Management Service) producer.

[0748] As an example, the sender of the first configuration is the first producer.

[0749] As an example, the sender in the first configuration is different from the first producer.

[0750] As an example, the training for obtaining the first given operation is performed by the first producer.

[0751] As an example, the executor used to obtain the training for the first given operation is different from the first producer.

[0752] As one example, the AI ​​includes ML (Machine Learning).

[0753] In embodiment 8B, the first node requests the second producer to load the first given operation and obtains the first given operation from the first producer. The first given operation is the first operation in this application, or the first given operation is the first reference operation in this application.

[0754] As one example, the deployment includes obtaining the first given operation.

[0755] As one example, the deployment includes obtaining an AI entity or AI function that performs the first given operation.

[0756] As one example, the deployment includes loading the first given operation.

[0757] As one example, the deployment includes submitting a request to load the first given operation.

[0758] As an example, the deployment is accomplished by AI functionality deployed on the first node.

[0759] As an example, the deployment is accomplished by the AI ​​deployment function deployed on the first node.

[0760] As an example, the deployment is performed by an AI entity with a deployment function.

[0761] As one example, the second producer generates and provides AI entities or AI functions.

[0762] As one example, the second producer includes an MnS (Management Service) producer.

[0763] As an example, the second producer includes the producer of the AI ​​model training.

[0764] As one example, the second producer is the sender of the first information set.

[0765] As one example, the second producer is different from the sender of the first information set.

[0766] As one example, the second producer is the serving cell of the first node.

[0767] As one example, the second producer is the maintenance base station of the serving cell of the first node.

[0768] As one example, the second producer is the core network.

[0769] As an example, the first given operation is obtained from the serving cell of the first node.

[0770] As an example, the first given operation is loaded from the sustaining base station of the serving cell of the first node.

[0771] As an example, the first given operation is obtained from the core network.

[0772] As an example, the training for obtaining the first given operation is performed by the second producer.

[0773] As an example, the second producer is different from the first producer.

[0774] As an example, the first producer generates and provides the AL entity.

[0775] As an example, the first producer generates and provides AL functionality.

[0776] As an example, the first producer is the producer of the first given operation.

[0777] As an example, the first producer includes an AL entity producer.

[0778] As one example, the first producer includes an AL function producer.

[0779] As one example, the first producer includes an AL deployment producer.

[0780] As one example, the first producer includes an AL loading producer.

[0781] As one example, the first producer includes an AL-trained producer.

[0782] As an example, the first producer includes an AL inference producer.

[0783] As an example, the first producer includes the producer of the AL entity deployment.

[0784] As one example, the first producer includes the producer that loads the AL entity.

[0785] As an example, the first producer includes an MnS (Management Service) producer.

[0786] Examples 9A-9B

[0787] Examples 9A-9B illustrate schematic diagrams illustrating the relationship between a first configuration and a first operation, and the relationship between a second configuration and a first reference operation, according to an embodiment of this application, respectively, as shown in Figures 9A-9B.

[0788] In embodiment 9A, the first configuration indicates the first operation, and the second configuration indicates the first reference operation.

[0789] As an example, the first configuration explicitly indicates the first operation, and the second configuration explicitly indicates the first reference operation.

[0790] As an example, the first configuration implicitly indicates the first operation, and the second configuration implicitly indicates the first reference operation.

[0791] As an example, the first configuration directly indicates the first operation, and the second configuration directly indicates the first reference operation.

[0792] As an example, the first configuration indirectly indicates the first operation, and the second configuration indirectly indicates the first reference operation.

[0793] As one embodiment, the first configuration indicates the first operation by indicating a first higher-level parameter, and the second configuration indicates the first reference operation by indicating a second higher-level parameter.

[0794] In embodiment 9B, the first configuration includes a first type identifier, the second configuration includes a first type identifier, the first type identifier is different from the first type indication; the first operation is associated with the first type identifier in the first configuration, and the first reference operation is associated with the first type identifier in the second configuration.

[0795] As an example, the first configuration indicates the use of the AI ​​model by indicating a first-class identifier.

[0796] As an example, the first configuration indicates at least one of the AI ​​model, AI entity, AI function, or AI inference associated with the first type of identifier by indicating a first type of identifier.

[0797] As an example, the first configuration indicates the first operation by indicating a first type of identifier.

[0798] As an example, the first configuration obtains input for AI entities / functions / inferences associated with the first type of identifier by instructing a first type of identifier.

[0799] As an example, the second configuration indicates the use of the AI ​​model by indicating a first-class identifier.

[0800] As an example, the second configuration indicates at least one of the AI ​​models, AI entities, AI functions, or AI inferences associated with the first type of identifier by indicating a first type of identifier.

[0801] As an example, the second configuration indicates the first reference operation by indicating a first type of identifier.

[0802] As one example, the second configuration obtains input for AI entities / functions / inferences associated with the first type of identifier by instructing a first type of identifier.

[0803] As one embodiment, associating a given operation with a given identifier includes: the given operation being identified by the given identifier; wherein the given operation is the first operation and the given identifier is the first type of identifier in the first configuration; or, the given operation is the first reference operation and the given identifier is the first type of identifier in the second configuration; or, the given operation is the target operation in this application and the given identifier is the target identifier.

[0804] As one embodiment, associating a given operation with a given identifier includes: the AI ​​model used by the given operation being identified by the given identifier; wherein, the given operation is the first operation, and the given identifier is the first type of identifier in the first configuration; or, the given operation is the first reference operation, and the given identifier is the first type of identifier in the second configuration; or, the given operation is the target operation in this application, and the given identifier is the target identifier.

[0805] As one embodiment, associating a given operation with a given identifier includes: the AI ​​entity included in the given operation being identified by the given identifier; wherein, the given operation is the first operation, and the given identifier is the first type of identifier in the first configuration; or, the given operation is the first reference operation, and the given identifier is the first type of identifier in the second configuration; or, the given operation is the target operation in this application, and the given identifier is the target identifier.

[0806] As one embodiment, associating a given operation with a given identifier includes: the AI ​​function to which the given operation is used is identified by the given identifier; wherein, the given operation is the first operation and the given identifier is the first type of identifier in the first configuration; or, the given operation is the first reference operation and the given identifier is the first type of identifier in the second configuration; or, the given operation is the target operation in this application and the given identifier is the target identifier.

[0807] As an example, the advantages of the above method include that identifying an AI entity or function through the first type of identifier simplifies the design and unifies the understanding of different AI entities or functions across multiple nodes.

[0808] As one embodiment, associating a given operation with a given identifier includes: the AI ​​entity performing the given operation being identified by the given identifier; wherein, the given operation is the first operation, and the given identifier is the first type of identifier in the first configuration; or, the given operation is the first reference operation, and the given identifier is the first type of identifier in the second configuration; or, the given operation is the target operation in this application, and the given identifier is the target identifier.

[0809] As one embodiment, associating a given operation with a given identifier includes: the given identifier being used by the first node to determine the AI ​​model adopted by the given operation; wherein, the given operation is the first operation, and the given identifier is the first type of identifier in the first configuration; or, the given operation is the first reference operation, and the given identifier is the first type of identifier in the second configuration; or, the given operation is the target operation in this application, and the given identifier is the target identifier.

[0810] As an example, the advantages of the above method include that identifying an AI model / entity / function through the first type of identifier simplifies the design and unifies the understanding of different AI entities / functions across multiple nodes.

[0811] As one embodiment, associating a given operation with a given identifier includes: the given identifier being used to identify or indicate a set of RS resources, and a measurement of the set of RS resources being used to obtain a training dataset for the given operation; wherein the given operation is the first operation, and the given identifier is the first type identifier in the first configuration; or, the given operation is the first reference operation, and the given identifier is the first type identifier in the second configuration; or, the given operation is the target operation in this application, and the given identifier is the target identifier.

[0812] As one embodiment, associating a given operation with a given identifier includes: obtaining training for the given operation that is identified by the given identifier; wherein the given operation is the first operation and the given identifier is the first type of identifier in the first configuration; or, the given operation is the first reference operation and the given identifier is the first type of identifier in the second configuration; or, the given operation is the target operation in this application and the given identifier is the target identifier.

[0813] As one embodiment, associating a given operation with a given identifier includes: the dataset used for training the given operation is identified by the given identifier; wherein the given operation is the first operation and the given identifier is the first type identifier in the first configuration; or, the given operation is the first reference operation and the given identifier is the first type identifier in the second configuration; or, the given operation is the target operation in this application and the given identifier is the target identifier.

[0814] As an example, the benefits of the above method include establishing consensus among different AI functions by identifying an AI training or AI training dataset to recognize the inferences generated by that AI training or AI training dataset, further simplifying the design.

[0815] As one embodiment, the given operation associated with a given identifier includes: the given operation performing spatial beam prediction for a second type of resource set based on measurements of a first type of resource set, the second type of resource set depending on the given identifier; wherein, the given operation is the first operation, and the given identifier is the first type identifier in the first configuration; or, the given operation is the first reference operation, and the given identifier is the first type identifier in the second configuration; or, the given operation is the target operation in this application, and the given identifier is the target identifier.

[0816] As an example, the advantages of the above method include reduced RS overhead and reduced feedback latency.

[0817] As one embodiment, associating a given operation with a given identifier includes: the given operation performing channel information prediction for a second type of resource set based on measurements of the first type of resource set, the second type of resource set depending on the given identifier; wherein, the given operation is the first operation, and the given identifier is the first type of identifier in the first configuration; or, the given operation is the first reference operation, and the given identifier is the first type of identifier in the second configuration; or, the given operation is the target operation in this application, and the given identifier is the target identifier.

[0818] As an example, the channel information in this application includes beam information.

[0819] As one embodiment, associating a given operation with a given identifier includes: the given operation performing temporal beam prediction for a second type of resource set based on historical measurements of a first type of resource set, the second type of resource set depending on the given identifier; wherein, the given operation is the first operation, and the given identifier is the first type identifier in the first configuration; or, the given operation is the first reference operation, and the given identifier is the first type identifier in the second configuration; or, the given operation is the target operation in this application, and the given identifier is the target identifier.

[0820] As an example, the advantages of the above method include reducing beam feedback delay and improving the real-time performance of beam acquisition.

[0821] As one embodiment, associating a given operation with a given identifier includes: the given operation performing temporal channel information prediction for a second type of resource set based on historical measurements of a first type of resource set, the second type of resource set depending on the given identifier; wherein, the given operation is the first operation, and the given identifier is the first type identifier in the first configuration; or, the given operation is the first reference operation, and the given identifier is the first type identifier in the second configuration; or, the given operation is the target operation in this application, and the given identifier is the target identifier.

[0822] As an example, the advantages of the above method include reducing channel information feedback delay and improving the real-time performance of channel information acquisition.

[0823] Examples 10A-10B

[0824] Examples 10A-10B illustrate schematic diagrams of a first information report being abandoned according to an embodiment of this application, as shown in Figures 10A-10B respectively.

[0825] In embodiment 10A, the second configuration includes a first type identifier, which is different from the first type indication; the target identifier is a first type identifier; when the first type identifier in the second configuration is the same as the target identifier, the first information reporting is abandoned.

[0826] In embodiment 10B, whether the first information report is abandoned depends on whether a first condition is met; the first condition includes that the first class identifier in the second configuration and the target identifier are the same; when the first class identifier in the second configuration and the target identifier are the same, the first information report is abandoned.

[0827] As an example, when the first type identifier and the target identifier in the second configuration are different, the first information report is sent.

[0828] As an example, when the first type identifier in the second configuration is different from the target identifier, and the second configuration does not include the first type indication, the first information report is sent.

[0829] As an example, when the first type identifier in the second configuration is different from the target identifier, and the second configuration includes a first type indication, the first type indication in the second configuration is used to indicate a third configuration, the third configuration is a configuration other than the second configuration among the M configurations, the third configuration includes a first type identifier, and the first type identifier in the third configuration is the same as the target identifier, the first information reporting is abandoned.

[0830] As an example, whether the first information report is abandoned depends on whether the first condition is met, meaning that when the first condition is met, the first information report is abandoned; when the first condition is not met, the first information report is sent.

[0831] As an example, the first condition includes multiple sub-conditions. The first sub-condition includes the first class identifier and the target identifier being the same in the second configuration. The first sub-condition is one of the sub-conditions of the first condition. When one of the multiple sub-conditions is satisfied, the first condition is satisfied. When none of the multiple sub-conditions are satisfied, the first condition is not satisfied.

[0832] As an example, the first condition includes multiple sub-conditions, and the first sub-condition and the second sub-condition are two sub-conditions of the first condition; the first sub-condition includes that the first type identifier in the second configuration is the same as the target identifier; the second sub-condition includes that the first type identifier in the second configuration is different from the target identifier, and the second configuration includes a first type indication, the first type indication in the second configuration is used to indicate a third configuration, the third configuration is a configuration other than the second configuration among the M configurations, the third configuration includes a first type identifier, and the first type identifier in the third configuration is the same as the target identifier.

[0833] As an example, the advantages of the above method include: if the target identifier indicates that the first reference operation has failed, then the first information report that depends on the output of the first reference operation is abandoned, saving energy and reducing resource consumption.

[0834] Examples 11A-11B

[0835] Examples 11A-11B illustrate schematic diagrams of a first information report not being updated according to an embodiment of this application, as shown in Figures 11A-11B respectively.

[0836] In embodiment 11A, the second configuration includes a first type identifier, which is different from the first type indication; the target identifier is a first type identifier; when the first type identifier in the second configuration is the same as the target identifier, the first information reporting is not updated.

[0837] As an example, the first node sends a first information report; the second configuration includes a first type identifier, which is different from the first type indication; the target identifier is a first type identifier; when the first type identifier in the second configuration is the same as the target identifier, the first information report is not updated.

[0838] In Example 11B, whether the first information report is not updated depends on whether a first condition is met; the first condition includes that the first class identifier in the second configuration and the target identifier are the same; when the first class identifier in the second configuration and the target identifier are the same, the first information report is not updated.

[0839] As an example, the first node sends a first information report; whether the first information report is not updated depends on whether a first condition is met; the first condition includes that the first class identifier in the second configuration and the target identifier are the same; when the first class identifier in the second configuration and the target identifier are the same, the first information report is not updated.

[0840] As an example, when the first type identifier and the target identifier in the second configuration are different, the first information report is updated.

[0841] As an example, when the first type identifier in the second configuration is different from the target identifier, and the second configuration does not include the first type indication, the first information report is updated.

[0842] As an example, when the first type identifier in the second configuration is different from the target identifier, and the second configuration includes a first type indication, the first type indication in the second configuration is used to indicate a third configuration, the third configuration is a configuration other than the second configuration among the M configurations, the third configuration includes a first type identifier, and the first type identifier in the third configuration is the same as the target identifier, the first information report is not updated.

[0843] As an example, whether the first information report is not updated depends on whether the first condition is met, meaning that: when the first condition is met, the first information report is not updated; when the first condition is not met, the first information report is updated.

[0844] As an example, the first condition includes multiple sub-conditions. The first sub-condition includes the first class identifier and the target identifier being the same in the second configuration. The first sub-condition is one of the sub-conditions of the first condition. When one of the multiple sub-conditions is satisfied, the first condition is satisfied. When none of the multiple sub-conditions are satisfied, the first condition is not satisfied.

[0845] As an example, the first condition includes multiple sub-conditions, and the first sub-condition and the second sub-condition are two sub-conditions of the first condition; the first sub-condition includes that the first type identifier in the second configuration is the same as the target identifier; the second sub-condition includes that the first type identifier in the second configuration is different from the target identifier, and the second configuration includes a first type indication, the first type indication in the second configuration is used to indicate a third configuration, the third configuration is a configuration other than the second configuration among the M configurations, the third configuration includes a first type identifier, and the first type identifier in the third configuration is the same as the target identifier.

[0846] As an example, the advantages of the above method include: if the first reference operation fails, the first information report that depends on the output of the first reference operation will not be updated, thus saving computational overhead and energy consumption.

[0847] As one embodiment, the first information report being updated includes: the first information report being valid.

[0848] As one embodiment, the first information report being updated includes: the first information report being different from the most recent report configured by the first configuration.

[0849] As one embodiment, the first information report being updated includes: the first information report may be different from the most recent report configured by the first configuration.

[0850] As one embodiment, the first information report being updated includes: the first information report is not necessarily the same as the most recent report configured by the first configuration.

[0851] As one embodiment, the first information report being updated includes: the first information report being obtained based on measurements of at least one RS resource.

[0852] As one embodiment, the first information report being updated includes: the first information report being generated based on a measurement of at least the most recent RS timing of at least one RS resource no later than the CSI reference resource of the first information report.

[0853] As one embodiment, updating the first information report includes: the first information report being updated based on a measurement of at least the most recent RS timing of at least one RS resource no later than the CSI reference resource of the first information report.

[0854] As one embodiment, the first information report not being updated includes: the first node is not expected to update the first information report.

[0855] As one embodiment, the first node is not expected to update the first information report, including: whether the first information report is actually updated is determined by the first node itself or is implementation-related.

[0856] As one embodiment, the first information report not being updated includes: the first information report being invalid.

[0857] As an example, the first information report not being updated includes: the first information report is not updated based on the most recent report configured in the first configuration.

[0858] As one embodiment, the first information report not being updated includes: the first information report being the same as the most recent report configured by the first configuration.

[0859] As an example, the first information report not being updated includes: the first information report must be the same as the most recent report configured by the first configuration.

[0860] As one embodiment, the first information report not being updated includes: the first information report being unrelated to the measurement of the RS resource used for the measurement of the first information report at a time no later than the most recent RS timing of the CSI reference resource of the first information report.

[0861] As one embodiment, the first information report not being updated includes: the first information report includes a default value.

[0862] As one embodiment, the first information report not being updated includes: the first information report being unrelated to the measurement of RS resources.

[0863] As one embodiment, the first information report not being updated includes: the first information report is not generated based on measurements of RS resources.

[0864] Example 12

[0865] Example 12 illustrates a schematic diagram of a target identifier and target operation according to an embodiment of this application; as shown in Figure 12.

[0866] In Example 12, the target operation is associated with the target identifier, and the target operation is invalidated.

[0867] As an example, the failure of the target operation includes: the target operation needs to be retrained.

[0868] As an example, the failure of the target operation includes: the target operation needs to be redeployed or reloaded.

[0869] As an example, when the first class identifier and the target identifier in the second configuration are the same, the first reference operation fails.

[0870] As an example, the first operation fails when the first reference operation fails.

[0871] As an example, whether the first operation fails depends on whether the first reference operation fails; when the first reference operation fails, the first operation fails.

[0872] As an example, the first operation fails when the first type identifier and the target identifier in the second configuration are the same.

[0873] Examples 13A-13B

[0874] Examples 13A-13B illustrate schematic diagrams of target identifiers according to an embodiment of this application, as shown in Figures 13A-13B respectively.

[0875] In Example 13A, the first node determines the target identifier itself; or, the first node determines that the target operation has failed, and the target operation is associated with the target identifier.

[0876] As an example, the first node determines the target identifier itself in the first processor.

[0877] As an example, the first node determines that the target operation failure occurs in the first processor.

[0878] As an example, the first node determines for itself whether an operation has failed.

[0879] Generally, how the first node determines whether an operation has failed is determined by the hardware manufacturer. Below are some non-limiting implementation methods:

[0880] As an example, the first node determines whether an operation has failed by monitoring whether an operation has achieved a given performance target.

[0881] As an example, the first node determines whether the operation has achieved the given performance target by monitoring the reception quality of the signal or channel generated based on the output of an operation.

[0882] As a sub-example of the above embodiments, the output of an operation includes one or more precoding matrices, and the signal or channel generated based on the output of this operation refers to a signal or channel precoded by the one or more precoding matrices.

[0883] As a sub-example of the above embodiments, the output of an operation includes one or more beams, and the signal or channel generated based on the output of this operation refers to a signal or channel employing the one or more beams.

[0884] As a sub-example of the above embodiments, the output of an operation includes one or more CQIs, which are used to determine one or more MCS (Modulation and Coding Schemes). The signal or channel generated based on the output of this operation refers to the signal or channel using the one or more MCSs.

[0885] As an example, the output of an operation includes reliability, and the first node determines whether the operation has achieved the given performance target by the relationship between the reliability and a certain threshold.

[0886] As an example, the output of an operation includes confidence information, and the first node determines whether the operation has achieved the given performance target by the relationship between the confidence information and a certain threshold.

[0887] As an example, the first node determines whether an operation meets the given performance target by performing ML testing or ML simulation on a model of an operation.

[0888] As an example, the first node recovers the input of an operation based on the output of the operation, and then determines whether the operation has achieved the given performance target by comparing the recovered input with the actual input.

[0889] As an example, one operation corresponds to one timer, and the first node determines whether the operation has failed based on whether the timer has expired.

[0890] As an example, an operation failure includes: an operation needs to be retrained.

[0891] As an example, an operation failure includes: an operation requiring redeployment or reloading.

[0892] As an example, if the first node is retrained for an operation, that operation becomes invalid.

[0893] As an example, the first node determines for itself whether an operation needs to be retrained.

[0894] As an example, the first node determines for itself whether an operation needs to be redeployed or reloaded.

[0895] As an example, if an operation fails to achieve the expected performance or performance target, the operation is considered to have failed.

[0896] As an example, the first node determines that an operation has failed based on the fact that an operation cannot achieve the expected performance or performance target.

[0897] As an example, if an operation requires retraining, the operation is invalidated.

[0898] As an example, if an operation needs to be redeployed or reloaded, the operation fails.

[0899] As an example, a producer of an operation indicates whether the operation can achieve the expected performance or performance target.

[0900] As an example, if the timer corresponding to an operation expires, the operation becomes invalid.

[0901] As an example, a timer is started or restarted after the training of the corresponding operation is completed.

[0902] As an example, a timer is started or restarted after the deployment of the corresponding operation is completed.

[0903] As an example, a timer is started or restarted after the most recent training of the corresponding operation is completed.

[0904] As an example, a timer is started or restarted after the most recent deployment of the corresponding operation has been completed.

[0905] As an example, a timer is started or restarted after the corresponding operation is performed.

[0906] As an example, a timer is started or restarted after each output of the corresponding operation.

[0907] As an example, when a start instruction for a timer is received, the first node starts or restarts the timer.

[0908] As an example, if an operation is not updated within a time window, the operation fails.

[0909] As an example, updating an operation includes updating the input of the operation.

[0910] As an example, updating an operation includes updating the output of the operation.

[0911] As an example, different operations correspond to their respective time windows.

[0912] As an example, different operations correspond to the same time window.

[0913] As an example, the time windows corresponding to different operations are configured separately.

[0914] As an example, the failure of the target operation includes: the target operation needs to be retrained.

[0915] As an example, the failure of the target operation includes: the target operation needs to be redeployed or reloaded.

[0916] Generally, how the first node determines the failure of the target operation is determined by the hardware equipment manufacturer. Below are some non-limiting implementation methods:

[0917] As an example, the first node determines that the target operation has failed by monitoring that the target operation has not achieved a given performance target.

[0918] As an example, the first node determines that the target operation has not achieved the given performance target by monitoring the reception quality of the signal or channel generated based on the output of the target operation.

[0919] As a sub-example of the above embodiments, the output of the target operation includes one or more precoding matrices, and the signal or channel generated based on the output of the target operation refers to a signal or channel precoded by the one or more precoding matrices.

[0920] As a sub-example of the above embodiments, the output of the target operation includes one or more beams, and the signal or channel generated based on the output of the target operation refers to a signal or channel using the one or more beams.

[0921] As a sub-example of the above embodiment, the output of the target operation includes one or more CQIs, which are used to determine one or more MCS (Modulation and Coding Schemes). The signal or channel generated based on the output of the target operation refers to the signal or channel using the one or more MCSs.

[0922] As a sub-example of the above embodiment, the output of the target operation includes reliability, and the first node determines that the target operation has not achieved the given performance target by the reliability being lower than a certain threshold.

[0923] As a sub-example of the above embodiment, the output of the target operation includes confidence information, and the first node determines that the target operation has not achieved the given performance target by the confidence information being lower than a certain threshold.

[0924] As an example, the output of the target operation includes reliability, and the first node determines that the target operation has failed if the reliability is lower than a certain threshold.

[0925] As an example, the output of the target operation includes confidence information, and the first node determines that the target operation has failed when the confidence information is lower than a certain threshold.

[0926] As an example, the first node determines that the target operation has not achieved the given performance target by performing ML testing or ML simulation on the model of the target operation.

[0927] As an example, the first node recovers the input of the target operation based on the output of the target operation, and then determines that the target operation has not achieved the given performance target by comparing the recovered input of the target operation with the actual input of the target operation.

[0928] As an example, the target operation corresponds to a timer, and the first node determines that the target operation has failed based on the expiration of the timer.

[0929] As an example, the first node retrains the target operation, and the target operation becomes invalid.

[0930] As an example, the first node determines on its own that the target operation needs to be retrained.

[0931] As an example, the first node determines on its own whether the target operation needs to be redeployed or reloaded.

[0932] As an example, if the target operation fails to achieve the expected performance or performance target, the target operation fails.

[0933] As an example, the first node determines that the target operation has failed based on the fact that the target operation cannot achieve the expected performance or performance target.

[0934] In embodiment 13B, the first node receives a first signaling; wherein the first signaling indicates the target identifier; or, the first signaling indicates that the target operation has failed, and the target operation is associated with the target identifier.

[0935] As one embodiment, the first signaling includes higher layer signaling.

[0936] As an example, the first signaling includes RRC (Radio Resource Control) signaling.

[0937] As an example, the first signaling includes MAC CE signaling.

[0938] As one example, the first signaling includes DCI.

[0939] As one example, the first signaling includes RRC signaling and MAC CE.

[0940] As one embodiment, the first signaling includes higher-layer signaling and DCI.

[0941] As an example, the first signaling is RRC signaling.

[0942] As an example, the first signaling is MAC CE signaling.

[0943] As an example, the first signaling is DCI.

[0944] Generally, how the sender of the first signaling determines that the target operation has failed is determined by the hardware equipment manufacturer. Below are some non-limiting implementation methods:

[0945] As an example, the sender of the first signaling generates and sends a signal based on the output of the target operation that is fed back, and determines that the target operation has failed based on the signal reception quality fed back by the receiver of this signal.

[0946] As an example, the sender of the first signaling receives the input and output of the target operation as feedback. The sender of the first signaling recovers the input based on the output. If the comparison result between the recovered input and the feedback input is greater than a certain threshold, the sender determines that the target operation has failed.

[0947] As an example, the executor of the target operation recovers the input of the target operation based on the output of the target operation, and feeds back the comparison result between the recovered input and the actual input to the sender of the first signaling. The sender of the first signaling determines that the target operation has failed based on the feedback comparison result being greater than a certain threshold.

[0948] As an example, the sender of the first signaling determines that the target operation has failed based on the expiration of a timer.

[0949] As an example, the sender of the first signaling determines that the target operation has failed by performing ML testing or ML evaluation on the model of the target operation.

[0950] As an example, the sender of the first signaling determines that the target operation has failed based on the instructions of the core network.

[0951] As an example, if the sender of the first signaling indicates that the target operation needs to be retrained, the target operation becomes invalid.

[0952] As an example, if the sender of the first signaling indicates that the target operation needs to be redeployed or reloaded, the target operation fails.

[0953] As an example, the first signaling indicates a failed operation.

[0954] As an example, the first signaling indicates whether an operation has failed.

[0955] As an example, the first node relies on the first signaling to determine whether an operation has failed.

[0956] As an example, the first signaling explicitly indicates a failed operation and implicitly indicates a successful operation.

[0957] As an example, the first signaling explicitly indicates an operation that has not failed, and implicitly indicates an operation that has failed.

[0958] As an example, the first signaling indicates which operations have not failed by indicating which operations have failed.

[0959] As an example, an operation that was not indicated as invalid by the first signaling was not invalid.

[0960] As an example, the first signaling indicates an operation that has not failed.

[0961] As one embodiment, the first signaling indicates which operations have failed by indicating which operations have not failed.

[0962] As an example, an operation that was not indicated as not invalid by the first signaling failed.

[0963] Generally, how the sender of the first signaling determines whether an operation has failed is determined by the hardware equipment manufacturer. Below are some non-limiting implementation methods:

[0964] As an example, the sender of the first signaling generates and sends a signal based on the output of an operation being fed back, and determines whether the operation has failed based on the signal reception quality fed back by the receiver of the signal.

[0965] As an example, the sender of the first signaling receives the input and output of a feedback operation, the sender of the first signaling recovers the input based on the output, and compares the recovered input with the feedback input to determine whether the operation has failed.

[0966] As an example, an operator recovers the input of an operation based on the output of the operation, and feeds back the comparison result between the recovered input and the actual input to the sender of the first signaling. The sender of the first signaling determines whether the operation has failed based on the feedback comparison result.

[0967] As an example, the sender of the first signaling determines whether an operation has failed based on whether a timer has expired.

[0968] As an example, the sender of the first signaling determines whether an operation has failed by performing ML testing or ML evaluation on a model of the operation.

[0969] As an example, the sender of the first signaling determines an operation failure based on the instructions of the core network.

[0970] As an example, if the sender of the first signaling indicates that an operation needs to be retrained, the operation fails.

[0971] As an example, if the sender of the first signaling indicates that an operation needs to be redeployed or reloaded, the operation fails.

[0972] Example 14

[0973] Example 14 illustrates a schematic diagram of RAN (Radio Access Network) domain AI / ML function deployment according to one embodiment of this application; as shown in Figure 14. The gNB in ​​Example 14 can be replaced with, for example, an eNB, or a network device such as a 6G base station.

[0974] AI / ML related functions include ML training (also known as AI training, or AI / ML training), ML testing, and ML inference (also known as AI inference, or AI / ML inference), etc. ML training, ML testing, and ML inference functions can be deployed independently or co-located. Deployment of AI / ML related functions can be implemented through software, such as downloading and / or running executable files; or it can be implemented through a combination of software and hardware, such as accelerating specific computing units through hardware to improve computing speed or save power.

[0975] ML training functionality can be deployed in a cross-domain management system or a domain-specific management system; the domain-specific management system is used to manage the RAN domain or the CN (Core Network) domain. For example, ML training functionality for MDA (Management Data Analytics) can be deployed on MDAF (MDA Function); ML training for network data analytics can be deployed on NWDAF (Network Data Analytics Function), meaning the ML training functionality is an MTLF (Model Training Logical Function).

[0976] The ML inference function can also be deployed in a cross-domain management system or a domain-specific management system; for example, the ML inference function is MDAF, or the ML inference function is AnLF (Analytics logical function) located in NWDAF.

[0977] Similarly, ML testing capabilities can also be deployed in cross-domain management systems or domain-specific management systems.

[0978] In Example 14, the RAN domain ML training function 1402 is located in the RAN domain management function 1403; while the ML inference function is located in the base station, that is, the AI / ML inference function 1404 is located in gNB 1405, the AI / ML inference function 1406 is located in gNB 1407, and so on.

[0979] In Figure 14, the management of ML inference functions of multiple base stations is completed by RAN domain management function 1403, that is, data interaction with RAN domain MnS (Management Service) consumer / cross-domain management 1401 (as shown by the dashed arrow in Figure 14).

[0980] Optionally, the management of ML inference function can also be completed by the base station itself, that is, each base station can independently interact with the RAN domain MnS consumer / cross-domain management 1401.

[0981] It should be noted that Example 14 is merely a non-limiting implementation; optionally, the ML training function of the RAN domain may also be deployed at the base station; or optionally, some base stations may deploy both the ML inference function and the ML training function of the RAN domain, while some base stations may only deploy the ML inference function.

[0982] As an example, one of the gNBs (or base stations) in Example 14 is the second node of this application.

[0983] As an example, the second processor in this application includes an AL / ML inference function, namely 1404 or 1406, as shown in Figure 14.

[0984] Example 15

[0985] Example 15 illustrates a schematic diagram of the deployment of AI / ML functionality in a UE according to one embodiment of this application; as shown in Figure 15. The RAN domain ML training function 1505 in Figure 15 is optional.

[0986] UE function 1504 is deployed in the first node of this application, and the UE function 1504 includes AI / ML inference function 1506; the AI / ML inference function 1506 uses an ML model (also called an AI model) for inference; an ML model is typically trained before being used for AI / ML inference.

[0987] As an example, the first information report in this application is obtained through inference by the AI / ML inference function 1506.

[0988] As an example, the first processor in this application includes an AL / ML inference function 1506 in Figure 15.

[0989] As an example, the UE function 1504 includes a RAN domain ML training function 1505, which runs training data through an ML model to obtain a relevant loss and adjusts the parameters of the ML model based on the calculated loss; the ML training includes at least one of ML initial training, ML re-training, and reinforcement learning.

[0990] The above embodiments can reduce the complexity of the base station, or save air interface resources caused by reporting training data; however, the above embodiments place high demands on the processing capabilities of the UE side.

[0991] Optionally, the UE function 1504 also includes a CN domain ML training function (not shown in Figure 15).

[0992] Optionally, the UE function 1504 also includes an AI / ML deployment function—not shown in Figure 15—for loading ML models and data.

[0993] As an example, the first node indicates whether it supports ML training function (RAN domain or CN domain) through capability reporting. The capability reporting is RRC signaling or NAS (Non-Access Stratum) signaling.

[0994] As an example, the ML model and the associated metadata are loaded by the first node from a network device or a remote server.

[0995] Optionally, the UE function 1504 is an MnS (Management Service) producer that provides data to the CN domain MnF (Management Function) 1501, and / or the RAN domain MnF 1502, and / or the cross-domain management system 1503 for management or analysis (as shown by double arrow 1507).

[0996] Optionally, the UE function 1504 is an MnS consumer that loads data from the CN domain MnF (Management Function) 1501, and / or the RAN domain MnF 1502, and / or the cross-domain management system 1503 for AI / ML-related management, such as managing data requests, ML model activation, and / or ML training (as shown by double arrow 1507).

[0997] As an example, the ML model is based on a neural network.

[0998] As an example, the ML model is based on CNN (Conventional Neural Networks).

[0999] As an example, the ML model is based on the Transformer architecture.

[1000] Example 16

[1001] Example 16 illustrates a schematic diagram of a processing system based on artificial intelligence or machine learning according to an embodiment of this application; as shown in Figure 16. Figure 16(a) includes a third processor, a fourth processor, and a fifth processor, and Figure 16(b) includes a third processor, a fourth processor, a fifth processor, and a sixth processor.

[1002] In Example 16(a), the third processor sends a first dataset to the fourth processor and a second dataset to the fifth processor; the fourth processor generates a target first-type parameter set based on the first dataset, and sends the generated target first-type parameter set to the fifth processor; the fifth processor processes the second dataset using the target first-type parameter set to obtain a first-type output. In Figure 16(a), the first-type feedback is optional.

[1003] In Example 16(b), the third processor sends a first dataset to the fourth processor and a second dataset to the fifth processor; the fourth processor generates a target first-type parameter set based on the first dataset, and sends the generated target first-type parameter set to the fifth processor; the fifth processor processes the second dataset using the target first-type parameter set to obtain a first-type output, and sends the first-type output to the sixth processor. In Figure 16(b), the first-type feedback and the second-type feedback are optional.

[1004] As an example, in Figure 16(a), the fifth processor sends the first type of output to the second node in this application.

[1005] As an example, Figure 16(a) employs a single-side AI model, in which the fifth processor performs the first reference operation of this application.

[1006] As an example, Figure 16(b) employs a two-sided AI model, wherein the fifth processor executes the first reference operation of this application, and the sixth processor includes the second reference operation of this application.

[1007] As an example, Figure 16(a) employs a single-side AI model, in which the fifth processor performs the first operation of this application.

[1008] As an example, Figure 16(b) employs a two-sided AI model, in which the fifth processor performs the first operation of this application, and the sixth processor performs the second operation of this application.

[1009] As an example, the AI ​​includes machine learning (ML) inference.

[1010] As an example, the fifth processor performs the first reference operation in this application.

[1011] As one embodiment, the sixth processor includes the second reference operation described in this application.

[1012] As an example, the fifth processor performs the first operation in this application.

[1013] As one embodiment, the sixth processor includes the second operation described in this application.

[1014] As an example, the fifth processor sends a first type of feedback to the fourth processor, and the first type of feedback is used to trigger a recalculation or update of the target first type of parameter group.

[1015] As one embodiment, the sixth processor sends a second type of feedback to the third processor, the second type of feedback being used to generate the first dataset or the second dataset, or the second type of feedback being used to trigger the sending of the first dataset or the second dataset.

[1016] As one embodiment, the third processor generates the first dataset and the second dataset based on measurements of a first type of wireless signal, the first type of wireless signal including downlink RS.

[1017] As one embodiment, the fifth processor belongs to the first node, and the sixth processor belongs to the second node.

[1018] As an example, the first information report belongs to the first type of output.

[1019] As an example, the second dataset includes the input of the first operation.

[1020] As an example, the second dataset includes the input of the first reference operation.

[1021] As an example, for the first operation in this application, the second dataset includes information obtained based on the first configuration and information obtained based on the output of the first reference operation.

[1022] As an example, for the first operation in this application, the second dataset includes information obtained based on the first configuration.

[1023] As an example, for the first reference operation in this application, the second dataset includes information obtained based on the second configuration.

[1024] As an example, the first dataset includes training data.

[1025] As an example, the fourth processor belongs to the producer of the first operation.

[1026] As one embodiment, the fourth processor belongs to the producer of the first reference operation.

[1027] As one embodiment, the fourth processor includes an AI training producer.

[1028] As one embodiment, the fourth processor includes an AI training function.

[1029] As an example, the fourth processor is used for model training, and the trained model is described by the target first class of parameter sets.

[1030] As an example, the fourth processor belongs to the first node.

[1031] The above embodiments avoid passing the first dataset to the second node.

[1032] As one example, the fourth processor belongs to the second node.

[1033] The above embodiments support joint training and optimize system performance.

[1034] As an example, the fourth processor belongs to the core network.

[1035] The above embodiments support network-wide joint training, further optimizing system performance.

[1036] As an example, the second dataset includes inference data.

[1037] As one embodiment, the fifth processor includes an AI inference producer.

[1038] As one embodiment, the fifth processor includes an AI inference function.

[1039] As an example, the fifth processor belongs to the first node.

[1040] As an example, the fifth processor constructs a model based on the target first type of parameter group, and then inputs the second dataset into the constructed model to obtain the first type of output.

[1041] As an example, the first reference operation is described by the target first type of parameter group.

[1042] As an example, the first operation is described by the target first type of parameter group.

[1043] As an example, the target first type of parameter group is used to construct the first operation.

[1044] As an example, the target first type of parameter group is used to construct the first reference operation.

[1045] As one embodiment, the fifth processor includes the second reference operation.

[1046] As one embodiment, the fifth processor includes the second operation.

[1047] As an example, the fifth processor generates a recovery dataset based on the first type of output, and the error between the recovery dataset and the second dataset is used to generate the first type of feedback.

[1048] As a sub-example of the above embodiments, the generation of the recovery dataset adopts a similar approach to the second reference operation.

[1049] As a sub-example of the above embodiment, the generation of the recovery dataset adopts a similar operation to the second one.

[1050] As an example, the first type of feedback is used to reflect the performance of the trained model; when the performance of the trained model fails to meet the requirements, the fourth processing opportunity recalculates the target first type of parameter set.

[1051] As an example, when the error is too large or the update has not been performed for too long, the performance of the trained model is considered to be unsatisfactory.

[1052] As an example, the target first type of parameter group includes one or more of the following: convolution kernel size, number of convolution layers, convolution stride, pooling kernel size, pooling kernel stride, pooling function, activation function, or number of feature maps.

[1053] As an example, the target first type of parameter group includes one or more of the following: convolution kernel, pooling kernel, pooling function, activation function, parameters of pooling function, or parameters of activation function.

[1054] Example 17

[1055] Example 17 illustrates a schematic diagram based on artificial intelligence or machine learning according to an embodiment of this application; as shown in Figure 17. Figure 17 includes a third operation, a fourth operation, a fifth operation, a sixth operation, and a seventh operation. In Example 17, the third and fourth operations belong to a first stage, the fifth operation belongs to a second stage, the sixth operation belongs to a third stage, and the seventh operation belongs to a fourth stage. In Figure 17, the lines with arrows indicate the sequence of processes.

[1056] As an example, the third operation includes AI training, the fourth operation includes AI testing, the fifth operation includes AI emulation, the sixth operation includes AI entity loading, and the seventh operation includes AI inference.

[1057] As an example, the first stage includes a training phase, the second stage includes an emulation phase, the third stage includes a deployment phase, and the fourth stage includes an emulation phase.

[1058] As an example, the first stage includes AI model training.

[1059] As an example, the first stage includes AI model training and AI testing.

[1060] As an example, the AI ​​includes machine learning (ML) inference.

[1061] As an example, the AI ​​model training includes initial training and re-training of one or a group of AI entities.

[1062] As an example, the training of the AI ​​model depends on training data.

[1063] As an example, the AI ​​model training includes AI entity validation.

[1064] As an example, the AI ​​entity verification is used to evaluate the performance of the AI ​​entity.

[1065] As an example, the AI ​​entity verification relies on verification data.

[1066] As an example, if the AI ​​entity verification results do not meet expectations, the AI ​​model will be retrained.

[1067] As an example, the AI ​​testing includes testing the validated AI entity to estimate the performance of the trained AI model.

[1068] As an example, if the AI ​​test results meet expectations, the AI ​​entity proceeds to the next stage; otherwise, the AI ​​model will be retrained.

[1069] As an example, the AI ​​test relies on test data.

[1070] As an example, the second stage includes AI simulation, which performs inference of AI entities in a simulation environment.

[1071] As an example, the AI ​​simulation estimates the performance of AI entity inference in a simulation environment before using the AI ​​entity.

[1072] As one embodiment, the second stage is optional.

[1073] As an example, the third stage includes AI entity loading, which is to obtain trained AI entities to obtain the desired AI inference capabilities.

[1074] As an example, the third stage is optional.

[1075] As an example, the third stage is no longer needed when the training and inference functions are co-located.

[1076] As an example, the fourth stage includes AI inference.

[1077] As an example, the seventh operation includes the first reference operation.

[1078] As an example, the seventh operation includes the first operation.

[1079] As one embodiment, the seventh operation includes the second reference operation.

[1080] As an example, the seventh operation includes the second operation.

[1081] Example 18

[1082] Example 18 illustrates a structural block diagram of a processing apparatus for a first node according to an embodiment of the present application; as shown in Figure 18. In Figure 18, the processing apparatus 1800 in the first node includes a first processor 1801.

[1083] As one example, the first node is a user equipment.

[1084] As an example, the first node is a relay node device.

[1085] As an example, the first processor 1801 includes at least one of the following in embodiment 4: {antenna 452, receiver / transmitter 454, receiving processor 456, transmitting processor 468, multi-antenna receiving processor 458, multi-antenna transmitting processor 457, controller / processor 459, memory 460, data source 467}.

[1086] The first processor 1801 receives a first information set; the first information set indicates M configurations, where M is a positive integer greater than 1;

[1087] The first processor 1801 performs a first reference operation; sends a first information report, or abandons sending the first information report; the first configuration among the M configurations is used to configure the first information report;

[1088] In embodiment 18, the first configuration includes a first type of indication, which is used to indicate a configuration other than the first configuration among the M configurations; the first information reporting depends on the output of the first reference operation, which depends on a second configuration, which is the configuration indicated by the first type of indication in the first configuration.

[1089] As one embodiment, it includes:

[1090] The first processor 1801 executes the first operation;

[1091] The first information reporting depends on the output of the first operation, and the input of the first operation depends on the output of the first reference operation.

[1092] As an example, the output of the first reference operation is used to generate the first information report.

[1093] As one embodiment, the first configuration indicates a first type of resource set, the first type of resource set including at least one RS resource for the measurement used for the first information reporting; the first information reporting indicates at least one resource in a second type of resource set.

[1094] As an example, the output of the first operation includes a first CSI, the first information report carries the first CSI, and the first CSI is used as input to the second operation by the target recipient of the first information report to generate a second CSI.

[1095] As one embodiment, the second configuration instructs the first reference operation.

[1096] As one embodiment, the second configuration includes a first type identifier, which is different from a first type indication, and the first reference operation is associated with the first type identifier in the second configuration.

[1097] As one embodiment, the first configuration indicates the first operation, and the second configuration indicates the first reference operation.

[1098] As one embodiment, the first configuration includes a first type identifier, the second configuration includes a first type identifier, the first type identifier is different from the first type indication; the first operation is associated with the first type identifier in the first configuration, and the first reference operation is associated with the first type identifier in the second configuration.

[1099] As one embodiment, the second configuration includes a first type identifier, which is different from the first type indication; the target identifier is a first type identifier; when the first type identifier in the second configuration is the same as the target identifier, the first information reporting is abandoned.

[1100] As an example, whether the first information report is abandoned depends on whether a first condition is met; the first condition includes that the first class identifier in the second configuration and the target identifier are the same; when the first class identifier in the second configuration and the target identifier are the same, the first information report is abandoned.

[1101] As one embodiment, the second configuration includes a first type identifier, which is different from the first type indication; the target identifier is a first type identifier; when the first type identifier in the second configuration is the same as the target identifier, the first information reporting is not updated.

[1102] As an example, whether the first information report is not updated depends on whether a first condition is met; the first condition includes that the first class identifier and the target identifier in the second configuration are the same; when the first class identifier and the target identifier in the second configuration are the same, the first information report is not updated.

[1103] As an example, the target operation is associated with the target identifier, and the target operation is invalidated.

[1104] As one embodiment, the first node determines the target identifier on its own; or, the first node determines that the target operation has failed, and the target operation is associated with the target identifier.

[1105] As one embodiment, it includes:

[1106] The first processor 1801 receives the first signaling; wherein,

[1107] The first signaling indicates the target identifier;

[1108] or,

[1109] The first signaling indicates that the target operation has failed, and the target operation is associated with the target identifier.

[1110] As an example, the first reference operation is based on training or AI.

[1111] As an example, the first reference operation requires deployment.

[1112] As an example, the first reference operation is obtained by loading.

[1113] As an example, the first processor 1801 deploys the first reference operation.

[1114] As an example, the first operation is based on training or AI.

[1115] As an example, the first operation requires deployment.

[1116] As an example, the first operation is obtained by loading.

[1117] As an example, the first processor 1801 deploys the first operation.

[1118] Example 19

[1119] Example 19 illustrates a structural block diagram of a processing apparatus for a second node according to an embodiment of the present application; as shown in Figure 19. In Figure 19, the processing apparatus 1900 in the second node includes a second processor 1901.

[1120] In one embodiment, the second node is a base station device.

[1121] In one embodiment, the second node is a user equipment.

[1122] As one embodiment, the second node is a relay node device.

[1123] As an example, the second processor 1901 includes at least one of the following in embodiment 4: {antenna 420, receiver / transmitter 418, receiving processor 470, transmitting processor 416, multi-antenna receiving processor 472, multi-antenna transmitting processor 471, controller / processor 475, memory 476}.

[1124] The second processor 1901 sends a first information set; the first information set indicates M configurations.

[1125] Wherein, the target receiver of the first information set performs a first reference operation; the target receiver of the first information set sends a first information report or abandons sending the first information report; a first configuration among the M configurations is used to configure the first information report; the first configuration includes a first type of indication, the first type of indication in the first configuration is used to indicate a configuration other than the first configuration among the M configurations; the first information report depends on the output of the first reference operation, the first reference operation depends on a second configuration, the second configuration is the configuration indicated by the first type of indication in the first configuration.

[1126] As one embodiment, the second node monitors whether the first information report is sent by the target recipient of the first information set.

[1127] As one embodiment, the second node determines on its own whether to give up receiving the first information report.

[1128] As one embodiment, the second processor 1901 may receive the first information report or choose not to receive the first information report.

[1129] As one embodiment, the target receiver of the first information set performs a first operation; the first information reporting depends on the output of the first operation, and the input of the first operation depends on the output of the first reference operation.

[1130] As an example, the output of the first reference operation is used to generate the first information report.

[1131] As one embodiment, the first configuration indicates a first type of resource set, the first type of resource set including at least one RS resource for the measurement used for the first information reporting; the first information reporting indicates at least one resource in a second type of resource set.

[1132] As one embodiment, the second processor 1901 performs a second operation; wherein the output of the first operation includes a first CSI, the first information report carries the first CSI, and the first CSI is used as input to the second operation to generate a second CSI.

[1133] As one embodiment, the second configuration instructs the first reference operation.

[1134] As one embodiment, the second configuration includes a first type identifier, which is different from a first type indication, and the first reference operation is associated with the first type identifier in the second configuration.

[1135] As one embodiment, the first configuration indicates the first operation, and the second configuration indicates the first reference operation.

[1136] As one embodiment, the first configuration includes a first type identifier, the second configuration includes a first type identifier, the first type identifier is different from the first type indication; the first operation is associated with the first type identifier in the first configuration, and the first reference operation is associated with the first type identifier in the second configuration.

[1137] As one embodiment, the second configuration includes a first type identifier, which is different from the first type indication; the target identifier is a first type identifier; when the first type identifier in the second configuration is the same as the target identifier, the first information report is abandoned by the target receiver of the first information set.

[1138] As an example, when the first type identifier and the target identifier in the second configuration are the same, the first information report is abandoned by the second node.

[1139] As an example, whether the first information report is abandoned depends on whether a first condition is met; the first condition includes that the first class identifier in the second configuration and the target identifier are the same; when the first class identifier in the second configuration and the target identifier are the same, the first information report is abandoned.

[1140] As one embodiment, the second configuration includes a first type identifier, which is different from the first type indication; the target identifier is a first type identifier; when the first type identifier in the second configuration is the same as the target identifier, the first information reporting is not updated.

[1141] As an example, whether the first information report is not updated depends on whether a first condition is met; the first condition includes that the first class identifier in the second configuration is the same as the target identifier; when the first class identifier in the second configuration is the same as the target identifier, the first information report is not updated by the target receiver of the first information set.

[1142] As an example, the target operation is associated with the target identifier, and the target operation is invalidated.

[1143] As one embodiment, the target recipient of the first information set determines the target identifier itself; or, the target recipient of the first information set determines that the target operation has failed, and the target operation is associated with the target identifier.

[1144] As one embodiment, the second processor 1901 sends a first signaling; wherein,

[1145] The first signaling indicates the target identifier;

[1146] or,

[1147] The first signaling indicates that the target operation has failed, and the target operation is associated with the target identifier.

[1148] As an example, the first reference operation is based on training or AI.

[1149] As an example, the first reference operation requires deployment.

[1150] As an example, the first reference operation is obtained by loading.

[1151] As an example, the first operation is based on training or AI.

[1152] As an example, the first operation requires deployment.

[1153] As an example, the first operation is obtained by loading.

[1154] As an example, the second processor 1901 deploys the second operation.

[1155] As one example, the second operation is based on training or AI.

[1156] As an example, the second operation is obtained by loading.

[1157] Those skilled in the art will understand that all or part of the steps in the above methods can be implemented by a program instructing related hardware, and the program can be stored in a computer-readable storage medium, such as a read-only memory, hard disk, or optical disk. Optionally, all or part of the steps in the above embodiments can also be implemented using one or more integrated circuits. Accordingly, each module unit in the above embodiments can be implemented in hardware or in the form of software functional modules. This application is not limited to any specific combination of software and hardware. The user equipment, terminal, and UE in this application include, but are not limited to, drones, communication modules on drones, remote-controlled aircraft, aircraft, small aircraft, mobile phones, tablets, laptops, vehicle-mounted communication equipment, vehicles, RSUs, wireless sensors, internet access cards, IoT terminals, RFID terminals, NB-IoT terminals, MTC (Machine Type Communication) terminals, eMTC (enhanced MTC) terminals, data cards, internet access cards, vehicle-mounted communication equipment, low-cost mobile phones, low-cost tablets, and other wireless communication devices. The base stations or system equipment in this application include, but are not limited to, macrocell base stations, microcell base stations, small cell base stations, home base stations, relay base stations, eNBs, gNBs, TRPs (Transmitter Receiver Points), GNSS, relay satellites, satellite base stations, airborne base stations, RSUs (Road Side Units), drones, and testing equipment, such as transceivers or signaling testers that simulate some functions of a base station, and other wireless communication equipment.

[1158] Those skilled in the art will understand that the present invention can be practiced in other specified forms without departing from its core or essential characteristics. Therefore, the embodiments disclosed herein should in any way be considered descriptive rather than restrictive. The scope of the invention is defined by the appended claims rather than the foregoing description, and all modifications within their equivalent meaning and scope are considered to be included therein.

Claims

1. A first node used for wireless communication, characterized in that, include: The first processor receives the first set of information; The first information set indicates M configurations, where M is a positive integer greater than 1; The first processor executes the first reference operation; Send the first information report, or abandon sending the first information report; the first configuration among the M configurations is used to configure the first information report; Wherein, the first configuration includes a first type of indication, which is used to indicate a configuration other than the first configuration among the M configurations; the first information reporting depends on the output of the first reference operation, which depends on a second configuration, which is the configuration indicated by the first type of indication in the first configuration.

2. The first node according to claim 1, characterized in that, include: The first processor executes the first operation; The first information reporting depends on the output of the first operation, and the input of the first operation depends on the output of the first reference operation.

3. The first node according to claim 1 or 2, characterized in that, The second configuration includes a first type identifier, which is different from the first type indication; The target identifier is a first-class identifier; when the first-class identifier in the second configuration is the same as the target identifier, the first information report is abandoned.

4. The first node according to claim 1 or 2, characterized in that, The second configuration includes a first type identifier, which is different from the first type indication; The target identifier is a first-class identifier; when the first-class identifier in the second configuration is the same as the target identifier, the first information report is not updated.

5. The first node according to claim 4, characterized in that, The target operation is associated with the target identifier, and the target operation is invalidated.

6. The first node according to claim 4 or 5, characterized in that, The first node determines the target identifier itself; or, the first node determines that the target operation has failed, and the target operation is associated with the target identifier.

7. The first node according to claim 4 or 5, characterized in that, include: The first processor receives the first signaling; wherein, The first signaling indicates the target identifier; or, The first signaling indicates that the target operation has failed, and the target operation is associated with the target identifier.

8. A second node used for wireless communication, characterized in that, include: The second processor sends the first set of information. The first information set indicates M configurations; In this context, the target recipient of the first information set performs a first reference operation; The target receiver of the first information set sends a first information report or abandons sending the first information report; a first configuration among the M configurations is used to configure the first information report; the first configuration includes a first type of indication, which is used to indicate a configuration other than the first configuration among the M configurations; the first information report depends on the output of the first reference operation, which depends on a second configuration, which is the configuration indicated by the first type of indication in the first configuration.

9. The second node according to claim 8, characterized in that, The target receiver of the first information set performs a first operation; the first information reporting depends on the output of the first operation, and the input of the first operation depends on the output of the first reference operation.

10. The second node according to claim 8 or 9, characterized in that, The second configuration includes a first type identifier, which is different from the first type indication; The target identifier is a first-class identifier; when the first-class identifier in the second configuration is the same as the target identifier, the first information report is abandoned by the target receiver of the first information set.

11. The second node according to claim 8 or 9, characterized in that, The second configuration includes a first-class identifier, which is different from the first-class indication; the target identifier is a first-class identifier; when the first-class identifier in the second configuration is the same as the target identifier, the first information report is not updated.

12. The second node according to claim 11, characterized in that, The target operation is associated with the target identifier, and the target operation is invalidated.

13. The second node according to claim 11 or 12, characterized in that, The target recipient of the first information set determines the target identifier itself; or, the target recipient of the first information set determines that the target operation has failed, and the target operation is associated with the target identifier.

14. The second node according to claim 11 or 12, characterized in that, include: The second processor sends the first signaling; wherein, The first signaling indicates the target identifier; or, The first signaling indicates that the target operation has failed, and the target operation is associated with the target identifier.

15. A method used in a first node of wireless communication, characterized in that, include: Receive the first set of information; The first information set indicates M configurations, where M is a positive integer greater than 1; Perform the first reference operation; Send the first information report, or abandon sending the first information report; the first configuration among the M configurations is used to configure the first information report; Wherein, the first configuration includes a first type of indication, which is used to indicate a configuration other than the first configuration among the M configurations; the first information reporting depends on the output of the first reference operation, which depends on a second configuration, which is the configuration indicated by the first type of indication in the first configuration.

16. The method according to claim 15, characterized in that, include: The first processor executes the first operation; The first information reporting depends on the output of the first operation, and the input of the first operation depends on the output of the first reference operation.

17. The method according to claim 15 or 16, characterized in that, The second configuration includes a first-class identifier, which is different from the first-class indication; the target identifier is a first-class identifier; when the first-class identifier in the second configuration is the same as the target identifier, the first information reporting is abandoned.

18. The method according to claim 15 or 16, characterized in that, The second configuration includes a first-class identifier, which is different from the first-class indication; the target identifier is a first-class identifier; when the first-class identifier in the second configuration is the same as the target identifier, the first information report is not updated.

19. The method according to claim 18, characterized in that, The target operation is associated with the target identifier, and the target operation is invalidated.

20. The method according to claim 18 or 19, characterized in that, The first node determines the target identifier itself; or, the first node determines that the target operation has failed, and the target operation is associated with the target identifier.

21. The method according to claim 18 or 19, characterized in that, include: Receive the first signaling; among which, The first signaling indicates the target identifier; or, The first signaling indicates that the target operation has failed, and the target operation is associated with the target identifier.

22. A method used in a second node of wireless communication, characterized in that, include: Send the first set of information; The first information set indicates M configurations; In this context, the target recipient of the first information set performs a first reference operation; The target receiver of the first information set sends a first information report or abandons sending the first information report; a first configuration among the M configurations is used to configure the first information report; the first configuration includes a first type of indication, which is used to indicate a configuration other than the first configuration among the M configurations; the first information report depends on the output of the first reference operation, which depends on a second configuration, which is the configuration indicated by the first type of indication in the first configuration.

23. The method according to claim 22, characterized in that, The target receiver of the first information set performs a first operation; the first information reporting depends on the output of the first operation, and the input of the first operation depends on the output of the first reference operation.

24. The method according to claim 22 or 23, characterized in that, The second configuration includes a first-class identifier, which is different from the first-class indication; the target identifier is a first-class identifier; when the first-class identifier in the second configuration is the same as the target identifier, the first information report is abandoned by the target receiver of the first information set.

25. The method according to claim 22 or 23, characterized in that, The second configuration includes a first-class identifier, which is different from the first-class indication; the target identifier is a first-class identifier; when the first-class identifier in the second configuration is the same as the target identifier, the first information report is not updated.

26. The method according to claim 25, characterized in that, The target operation is associated with the target identifier, and the target operation is invalidated.

27. The method according to claim 25 or 26, characterized in that, The target recipient of the first information set determines the target identifier itself; or, the target recipient of the first information set determines that the target operation has failed, and the target operation is associated with the target identifier.

28. The method according to claim 25 or 26, characterized in that, include: Send the first signaling; among which, The first signaling indicates the target identifier; or, The first signaling indicates that the target operation has failed, and the target operation is associated with the target identifier.

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