Method and apparatus in node used for wireless communication

Abstract

The present application discloses a method and apparatus in a node used for wireless communication. A first node receives a target CSI reporting configuration. The target CSI reporting configuration is used for configuring reporting of target CSI on a target cell, and the generation mode of the target CSI is AI-based. A first information block is received, the first information block indicating a target identifier. The target CSI is sent. The generation mode of the target CSI is associated with a first-type identifier. Whether the first-type identifier associated with the generation mode of the target CSI is updated to the target identifier depends on whether the target cell belongs to a first cell set, and only when the target cell belongs to the first cell set is the first-type identifier associated with the generation mode of the target CSI updated to the target identifier. A first cell is a serving cell in the first cell set, and the first cell depends on the first information block. The target cell is different from the first cell.

Description

A method and apparatus in a node used for wireless communication

[0001] This application claims priority to the Chinese patent application No. 202410735087.0, filed on June 6, 2024, with the State Intellectual Property Office, and entitled "A method and apparatus in a node used for wireless communication", the whole content of which is incorporated herein by reference. TECHNICAL FIELD

[0002] The present application relates to a transmission method and apparatus in a wireless communication system, and in particular to a scheme and apparatus for reporting channel information in a wireless communication system. BACKGROUND

[0003] In a conventional wireless communication, a UE (User Equipment) obtains channel information by measuring a downlink reference signal. The channel information includes, but is not limited to, one or more of CRI (CSI-RS Resource Indicator), RI (Rank Indicator), PMI (Precoding Matrix Indicator), or CQI (Channel quality indicator).

[0004] With the adoption of new technologies, the increase in the number of antennas, the diversification of application scenarios, and the improvement of system performance requirements, the traditional measurement and reporting method will bring a large amount of redundant overhead. Therefore, in NR R(release)18, the research on AI(Artificial Intelligence) / ML(Machine Learning) technology is launched to explore its impact on system performance and system design. Compared with the traditional processing method, AI / ML has the characteristics of being based on training and needing to be deployed. SUMMARY

[0005] Applicant found through research that when AI / ML function is introduced, the existing measurement mechanism, reporting mechanism and related configuration signaling may not be able to adapt to the needs of AI / ML. In view of the above problems, a solution is disclosed. It should be noted that although a large number of embodiments of the present application are developed for AI / ML, the present application is also applicable to other schemes, such as traditional CSI reporting schemes. In addition, the use of a unified solution in different scenarios (including but not limited to AI / ML-based schemes and traditional CSI reporting schemes) helps to reduce hardware complexity and cost. In the case of no conflict, the embodiments in the first node and the features in the embodiments of the present application can be applied to the second node, and vice versa. In the case of no conflict, the embodiments of the present application and the features in the embodiments can be arbitrarily combined with each other.

[0006] As an embodiment, the explanation of the terms in the present application is based on the definition of the specification agreement TS38 series of 3GPP.

[0007] As an embodiment, the explanation of the terms in the present application is based on the definition of the specification agreement TS28 series of 3GPP.

[0008] The present application discloses a method in a first node used for wireless communication, characterized in that it comprises:

[0009] Receiving a target CSI reporting configuration; the target CSI reporting configuration is used to configure the reporting of target CSI on a target cell, and the generation mode of the target CSI is AI-based; receiving a first information block, the first information block indicating a target identifier;

[0010] Sending a target CSI;

[0011] Wherein, the generation mode of the target CSI is associated with a first type of identifier; whether the first type of identifier associated with the generation mode of the target CSI is updated to the target identifier depends on whether the target cell belongs to a first cell set; only when the target cell belongs to the first cell set, the first type of identifier associated with the generation mode of the target CSI is updated to the target identifier; the first cell set includes a plurality of serving cells, and a first cell is a serving cell in the first cell set, the first cell depends on the first information block; the target cell and the first cell are different.

[0012] As an embodiment, the problem to be solved by the present application includes: when multiple cells use AI-based CSI generation mode, how to unify the understanding of different AI entities or functions, and perform channel information reporting.

[0013] As an embodiment, in the method, the target identifier indicated by the first information block determines a generation manner of CSI in the plurality of cells.

[0014] As an embodiment, the method has the feature that the understanding of different AI entities or functions is unified among the plurality of nodes.

[0015] As an embodiment, the method has the benefit that channel information of a plurality of time units is obtained based on measurement of a resource set.

[0016] As an embodiment, the method has the benefit that the accuracy and real-time performance of reporting channel information are improved, and the reporting overhead is reduced.

[0017] As an embodiment, the AI (Artificial Intelligence) includes ML (Machine Learning).

[0018] As an embodiment, the method has the benefit that various application scenarios and terminals are better adapted to, and the flexibility and adaptability are improved.

[0019] As an embodiment, the method has the benefit that signaling overhead is saved.

[0020] As an embodiment, the method has the benefit that the accuracy and real-time performance of reporting channel information are improved.

[0021] According to an aspect of the present application, the first node is a user equipment.

[0022] According to an aspect of the present application, the first node is a relay node.

[0023] According to an aspect of the present application, the first information block is applied to each serving cell in the first set of cells.

[0024] As an embodiment, the method has the benefit that signaling overhead is saved.

[0025] According to an aspect of the present application, the first information block indicates the first cell.

[0026] As an embodiment, the method has the benefit that good flexibility is achieved.

[0027] According to an aspect of the present application, the first cell is a serving cell in which a physical channel carrying the first information block is located.

[0028] As an embodiment, benefits of the above method include: simplifying design.

[0029] According to an aspect of the present application, the target CSI reporting configuration indicates a first resource set, the first resource set is used for at least one of channel measurement or interference measurement of the target CSI, and the first resource set includes one or more RS resources; the target CSI indicates at least one resource in a second resource set, and the second resource set includes resources not belonging to the first resource set.

[0030] As an embodiment, benefits of the above method include: reducing the overhead required to obtain channel information.

[0031] As an embodiment, benefits of the above method include: reducing the measurement resources required to obtain channel information.

[0032] According to an aspect of the present application, the target CSI reporting configuration indicates a first resource set, the first resource set is used for at least one of channel measurement or interference measurement of the target CSI, and the first resource set includes one or more RS resources; the target CSI is generated in a manner including the first node or a receiver of the target CSI reporting configuration performing a first operation, an input of the first operation depends on measurement based on the first resource set, and the target CSI depends on an output of the first operation.

[0033] As an embodiment, benefits of the above method include: better adaptation to various application scenarios or terminals, improving flexibility and adaptability.

[0034] As an embodiment, benefits of the above method include: improving the accuracy of channel information reporting.

[0035] According to an aspect of the present application, the target CSI generation manner being associated to the first type of identifier includes: the first operation being associated to the first type of identifier.

[0036] As an embodiment, benefits of the above method include: identifying an AI entity or function through the first type of identifier, simplifying design and unifying understanding of different AI entities or functions among multiple nodes.

[0037] According to an aspect of the present application, the target CSI generation manner being associated to the first type of identifier includes: the target CSI reporting configuration indicating a first type of identifier, and the first type of identifier indicated by the target CSI reporting configuration being the first type of identifier to which the target CSI generation manner is associated.

[0038] As an embodiment, the benefits of the above method include: the first type of identifier is indicated by the target CSI reporting configuration, which simplifies the design and is easy to implement.

[0039] According to an aspect of the present application, the generation mode of the target CSI associated with the first type of identifier includes: the generation mode of the target CSI uses an AI model identified by the first type of identifier, or the target CSI is generated by an AI entity identified by the first type of identifier, or the target CSI is used for an AI function identified by the first type of identifier.

[0040] As an embodiment, the AI (Artificial Intelligence) includes ML (Machine Learning).

[0041] As an embodiment, the benefits of the above method include: better adaptation to various application scenarios and terminals, improving flexibility and adaptability.

[0042] As an embodiment, the benefits of the above method include: improving the accuracy and real-time performance of channel information reporting.

[0043] According to an aspect of the present application, it comprises:

[0044] Receiving a first higher layer parameter;

[0045] The first higher layer parameter indicates the first set of cells.

[0046] As an embodiment, the benefits of the above method include: multiple cells are indicated by the first higher layer parameter, which simplifies the design and unifies the understanding of different AI entities or functions among multiple nodes.

[0047] According to an aspect of the present application, it comprises:

[0048] Sending a second information block;

[0049] The second information block indicates that the generation mode of the CSI on multiple serving cells is associated with the same first type of identifier.

[0050] As an embodiment, the benefits of the above method include: the first node reports terminal capabilities to help the base station select a more suitable channel information measurement and reporting scheme, improving transmission performance.

[0051] The present application discloses a method used in a second node for wireless communication, characterized by comprising:

[0052] transmit a target CSI reporting configuration; the target CSI reporting configuration is used for configuring reporting of a target CSI on a target cell, a generation manner of the target CSI is AI-based; transmit a first information block, the first information block indicates a target identity;

[0053] receive the target CSI;

[0054] wherein the generation manner of the target CSI is associated to a first type of identity; whether the first type of identity associated to the generation manner of the target CSI is updated to the target identity depends on whether the target cell belongs to a first cell set; only when the target cell belongs to the first cell set, the first type of identity associated to the generation manner of the target CSI is updated to the target identity; the first cell set comprises a plurality of serving cells, a first cell is one serving cell in the first cell set, the first cell depends on the first information block; the target cell is different from the first cell.

[0055] According to an aspect of the present application, the second node is a base station.

[0056] According to an aspect of the present application, the second node is a user equipment.

[0057] According to an aspect of the present application, the second node is a relay node.

[0058] According to an aspect of the present application, the first information block is applied to each serving cell in the first cell set.

[0059] According to an aspect of the present application, the first information block indicates the first cell.

[0060] According to an aspect of the present application, the first cell is a serving cell on which a physical channel carrying the first information block is located.

[0061] According to an aspect of the present application, the target CSI reporting configuration indicates a first resource set, the first resource set is used for at least one of channel measurement or interference measurement of the target CSI, the first resource set comprises one or more RS resources on the target cell; the target CSI indicates at least one resource in a second resource set, the second resource set comprises resources not belonging to the first resource set.

[0062] According to an aspect of the present application, the target CSI reporting configuration indicates a first resource set, the first resource set is used for at least one of channel measurement or interference measurement of the target CSI, the first resource set includes one or more RS resources; the generation manner of the target CSI includes that a receiver of the target CSI reporting configuration performs a first operation, an input of the first operation depends on measurement based on the first resource set, and the target CSI depends on an output of the first operation.

[0063] According to an aspect of the present application, the first operation is associated to the first type identifier.

[0064] According to an aspect of the present application, the first operation is associated to the first type identifier.

[0065] According to an aspect of the present application, the first operation is associated to the first type identifier.

[0066] According to an aspect of the present application, the first operation is associated to the first type identifier.

[0067] The first higher layer parameter is transmitted.

[0068] The first higher layer parameter indicates the first cell set.

[0069] The first operation is associated to the first type identifier.

[0070] The second information block is received.

[0071] The second information block indicates that the generation manners of the CSIs on the plurality of serving cells are associated to the same first type identifier.

[0072] The present application discloses a terminal, characterized in that the terminal comprises one or more processors and a memory.

[0073] The memory is coupled with the one or more processors and stores computer program code, the computer program code comprising computer instructions that, when invoked by the one or more processors, cause the terminal to perform the method in the first node.

[0074] The application discloses a base station, characterized in that the base station comprises one or more processors and a memory.

[0075] The memory is coupled with the one or more processors and stores computer program code, the computer program code comprising computer instructions that, when invoked by the one or more processors, cause the base station to perform the method in the second node.

[0076] The application discloses a first node used for wireless communication, characterized in that comprising:

[0077] The first receiver receives a target CSI reporting configuration, the target CSI reporting configuration being used for configuring reporting of a target CSI on a target cell, and the target CSI being generated in an AI-based manner; and the first receiver receives a first information block, the first information block indicating a target identity.

[0078] The first processor sends a target CSI.

[0079] The target CSI is generated in a manner associated with a first type of identity; whether the first type of identity associated with the generation manner of the target CSI is updated to the target identity depends on whether the target cell belongs to a first cell set; only when the target cell belongs to the first cell set, the first type of identity associated with the generation manner of the target CSI is updated to the target identity; the first cell set comprises a plurality of serving cells, a first cell is one serving cell in the first cell set, and the first cell depends on the first information block; and the target cell is different from the first cell.

[0080] The application discloses a second node used for wireless communication, characterized in that comprising:

[0081] The second processor sends a target CSI reporting configuration, the target CSI reporting configuration being used for configuring reporting of a target CSI on a target cell, and the target CSI being generated in an AI-based manner; the second processor sends a first information block, the first information block indicating a target identity; and the second processor receives a target CSI.

[0082] The generation mode of the target CSI is associated with a first type identifier; whether the first type identifier associated with the generation mode of the target CSI is updated as the target identifier depends on whether the target cell belongs to a first cell set; only when the target cell belongs to the first cell set, the first type identifier associated with the generation mode of the target CSI is updated as the target identifier; the first cell set includes a plurality of serving cells, a first cell is one serving cell in the first cell set, and the first cell depends on the first information block; and the target cell is different from the first cell.

[0083] As an embodiment, compared with the conventional scheme, the present application has the following advantages:

[0084] Higher channel information accuracy and real-time performance, enhanced overall system performance;

[0085] Signaling overhead is saved;

[0086] Lower air interface overhead;

[0087] More flexible and diverse input information;

[0088] Better flexibility and adaptability;

[0089] Enhanced reliability and robustness. BRIEF DESCRIPTION OF DRAWINGS

[0090] Other features, objects and advantages of the present application will become more apparent from the following detailed description of non-limiting embodiments with reference to the attached drawings:

[0091] Fig. 1 shows a flowchart of target CSI reporting configuration, a first information block and target CSI according to an embodiment of the present application;

[0092] Fig. 2 shows a schematic diagram of a network architecture according to an embodiment of the present application;

[0093] Fig. 3 shows a schematic diagram of an embodiment of a wireless protocol architecture of a user plane and a control plane according to an embodiment of the present application;

[0094] Fig. 4 shows a schematic diagram of a first communication device and a second communication device according to an embodiment of the present application;

[0095] Fig. 5 shows a flowchart of transmission between a first node and a second node according to an embodiment of the present application;

[0096] Fig. 6 shows a schematic diagram of a first information block according to an embodiment of the present application;

[0097] Figure 7 shows a schematic diagram of a first cell depending on a first information block according to one embodiment of the application;

[0098] Figure 8 shows a schematic diagram of a first cell depending on a first information block according to another embodiment of the application;

[0099] Figure 9 shows a schematic diagram of a first resource set and a second resource set according to one embodiment of the application;

[0100] Figure 10 shows a schematic diagram of a relationship of a first operation and a target CSI according to one embodiment of the application;

[0101] Figure 11 shows a schematic diagram of a generation manner of a target CSI being associated to a first type of identification according to one embodiment of the application;

[0102] Figure 12 shows a schematic diagram of a first operation according to one embodiment of the application;

[0103] Figure 13 shows a schematic diagram of a generation manner of a target CSI being associated to a first type of identification according to another embodiment of the application;

[0104] Figure 14 shows a schematic diagram of a generation manner of a target CSI being associated to a first type of identification according to yet another embodiment of the application;

[0105] Figure 15 shows a schematic diagram of a first higher layer parameter according to one embodiment of the application;

[0106] Figure 16 shows a schematic diagram of a second information block according to one embodiment of the application;

[0107] Figure 17 shows a schematic diagram of a first operation according to another embodiment of the application.

[0108] Figure 18 shows a schematic diagram of a first node deploying a first operation according to one embodiment of the application.

[0109] Figure 19 shows a schematic diagram of an artificial intelligence or machine learning based processing system according to one embodiment of the application;

[0110] Figure 20 shows a schematic diagram of an artificial intelligence or machine learning according to one embodiment of the application;

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

[0112] Figure 22 shows a structural block diagram of a processing apparatus for use in a second node according to one embodiment of the application. DETAILED DESCRIPTION

[0113] The technical solutions of the present application will be further described in detail below with reference to the drawings. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other arbitrarily without conflict. Based on performance, flexibility, complexity, overhead and compatibility, etc., the person skilled in the art has the motivation to combine the embodiments in different drawings flexibly without conflict, for example, but not limited to, the embodiments in FIG. 1 and the embodiments in FIG. 5-FIG. 22, the embodiments in FIG. 5 and the embodiments in FIG. 6-FIG. 22, etc.

[0114] Embodiment 1

[0115] Embodiment 1 illustrates a flowchart of target CSI reporting configuration, first information block and target CSI according to an embodiment of the present application, as shown in FIG. 1. In 100 shown in FIG. 1, each block represents a step. In particular, the order of the steps in the blocks does not represent a specific time sequence between the steps.

[0116] In embodiment 1, the first node receives a target CSI reporting configuration in step 101; receives a first information block in step 102; and sends a target CSI in step 103; wherein the target CSI reporting configuration is used to configure the reporting of the target CSI on a target cell, the generation mode of the target CSI is based on AI; the first information block indicates a target identity; the generation mode of the target CSI is associated with a first type of identity; whether the first type of identity associated with the generation mode of the target CSI is updated to the target identity depends on whether the target cell belongs to a first cell set; only when the target cell belongs to the first cell set, the first type of identity associated with the generation mode of the target CSI is updated to the target identity; the first cell set includes a plurality of serving cells, a first cell is one serving cell in the first cell set, the first cell depends on the first information block; and the target cell is different from the first cell.

[0117] As an embodiment, the target CSI reporting configuration is carried by higher layer signaling.

[0118] As an embodiment, the target CSI reporting configuration is carried by RRC (Radio Resource Control) signaling.

[0119] As an embodiment, the target CSI reporting configuration is carried by one RRC IE (Information Element).

[0120] As one embodiment, the target CSI reporting configuration is carried by at least one RRC IE.

[0121] As one embodiment, the target CSI reporting configuration includes information in one or more fields in at least one RRC IE.

[0122] As one embodiment, the target CSI reporting configuration includes information in one or more fields in each of a plurality of RRC IEs.

[0123] As one embodiment, the target CSI reporting configuration is one RRC IE.

[0124] As one embodiment, the target CSI reporting configuration belongs to a CSI-ReportConfig IE.

[0125] As one embodiment, the target CSI reporting configuration belongs to a ServingCellConfig IE.

[0126] As one embodiment, the target CSI reporting configuration belongs to a CSI-MeasConfig IE.

[0127] As one embodiment, the target CSI reporting configuration belongs to a ServingCellConfigCommon IE.

[0128] As one embodiment, the target CSI reporting configuration belongs to a ServingCellConfigCommonSIB IE.

[0129] As one embodiment, the target CSI reporting configuration includes some or all fields in a CSI-ReportConfig IE.

[0130] As one embodiment, the target CSI reporting configuration includes some or all fields in a ServingCellConfig IE.

[0131] As one embodiment, the target CSI reporting configuration includes some or all fields in a CSI-MeasConfig IE.

[0132] As one embodiment, the target CSI reporting configuration includes some or all fields in a ServingCellConfigCommon IE.

[0133] As one embodiment, the target CSI reporting configuration includes some or all fields in a ServingCellConfigCommonSIB IE.

[0134] As one embodiment, the target CSI reporting configuration includes one CSI resource configuration, the one CSI resource configuration is used to indicate a first resource set, the first resource set is used for at least one of channel measurement or interference measurement of the target CSI.

[0135] As one sub-embodiment of the above embodiment, the one CSI resource configuration is an IE CSI-ResourceConfig.

[0136] As one sub-embodiment of the above embodiment, the target CSI reporting configuration includes a resourcesForChannelMeasurement field, the resourcesForChannelMeasurement field included in the target CSI reporting configuration indicates the one CSI resource configuration.

[0137] As one embodiment, the target CSI reporting configuration includes multiple CSI resource configurations, one CSI resource configuration in the multiple CSI resource configurations is used to configure the first RS resource set.

[0138] As one embodiment, the target CSI reporting configuration includes a reportConfigType field; the reportConfigType field in the target CSI reporting configuration indicates which one of periodic, semi Persistent On PUSCH, semi Persistent On PUCCH, or aperiodic the target CSI is.

[0139] As one embodiment, the target CSI is periodic, semi-persistent, or aperiodic.

[0140] As one embodiment, the target CSI reporting configuration further indicates a reporting quantity included in the target CSI.

[0141] As one embodiment, the target CSI reporting configuration includes a reportQuantity field, the reportQuantity field in the target CSI reporting configuration indicates a reporting quantity included in the target CSI.

[0142] As an embodiment, the reporting quantity comprised in the target CSI comprises at least one of a CQI (Channel Quality Indicator), a PMI (Precoding Matrix Indicator), a CRI (CSI-RS Resource Indicator), an SS / PBCH Block Resource indicator (SSBRI), a Layer Indicator (LI), an RI (Rank Indicator), an L1-RSRP (Layer 1 reference signal received power), or an L1-SINR (Layer 1 signal-to-noise and interference ratio).

[0143] As an embodiment, the target CSI reporting configuration is used for configuring reporting of the target CSI on a target cell comprises that the RS resource used for the reporting of the target CSI is transmitted on the target cell.

[0144] As an embodiment, the target CSI reporting configuration is used for configuring reporting of the target CSI on a target cell comprises that the time-frequency domain resource occupied by the RS resource used for the reporting of the target CSI belongs to the target cell.

[0145] As an embodiment, the target CSI reporting configuration is used for configuring reporting of the target CSI on a target cell comprises that the target CSI reporting configuration indicates at least one resource set, the at least one resource set indicated by the target CSI reporting configuration is used for reporting of the target CSI, and the at least one resource set used for reporting of the target CSI belongs to the target cell.

[0146] As an embodiment, the target CSI reporting configuration is used for configuring reporting of the target CSI on a target cell comprises that the reporting of the target CSI is transmitted on the target cell.

[0147] As an embodiment, the target CSI reporting configuration is used for configuring reporting of the target CSI on a target cell comprises that the time-frequency domain resource carrying the reporting of the target CSI belongs to the target cell.

[0148] As an embodiment, the first information block is carried by physical layer signaling.

[0149] As one embodiment, the first information block comprises DCI.

[0150] As one embodiment, the first information block comprises part or all fields in DCI.

[0151] As one embodiment, the first information block comprises a MAC CE.

[0152] As one embodiment, the first information block is cell common.

[0153] As one embodiment, the first information block is cell specific.

[0154] As one embodiment, the first information block is UE group common.

[0155] As one embodiment, the first information block is UE group specific.

[0156] As one embodiment, the first information block is UE specific.

[0157] As one embodiment, the first information block explicitly indicates the target identity.

[0158] As one embodiment, the first information block implicitly indicates the target identity.

[0159] As one embodiment, the first information block comprises a field, and the first information block comprises the field to indicate the target identity.

[0160] Typically, the target cell is a serving cell of the first node, and all serving cells of the first node comprise the first cell set and at least one serving cell outside the first cell set.

[0161] Typically, the target cell is a serving cell of the first node, and the target cell is a serving cell in the first cell set or a serving cell outside the first cell set.

[0162] Typically, the first type identity associated with the generation manner of the target CSI is updated to the target identity only when the target cell belongs to the first cell set, and the first type identity associated with the generation manner of the target CSI is not updated to the target identity when the target cell does not belong to the first cell set.

[0163] As one embodiment, the first-type identity being updated to the target identity comprises: the first-type identity being equal to the target identity.

[0164] As one embodiment, the first-type identity being updated to the target identity comprises: the first-type identity being set to the target identity.

[0165] As one embodiment, the first-type identity being updated to the target identity comprises: the first node assuming that the first-type identity is the target identity.

[0166] As one embodiment, the first cell set is a cell set to which the first cell belongs.

[0167] As one embodiment, the first cell set is one cell set including the first cell in a plurality of cell sets of the first node; any cell set in the plurality of cell sets includes one or more serving cells.

[0168] As one embodiment, the plurality of serving cells included in the first cell set belong to a same cell group, and the first cell belongs to the one cell group.

[0169] As one embodiment, the plurality of serving cells included in the first cell set belong to a same cell group, and the first cell is a SpCell (Special Cell) or a SCell (Secondary Cell) in the one cell group.

[0170] As one embodiment, the plurality of serving cells included in the first cell set belong to a same cell group, and the one cell group is a PCG (Primary Cell Group), and the first cell is a PCell (Primary Cell) in the one cell group.

[0171] As one embodiment, the plurality of serving cells included in the first cell set belong to a same cell group, and the one cell group is a PCG (Primary Cell Group), and the first cell is a SCell (Secondary Cell) in the one cell group.

[0172] As one embodiment, the plurality of serving cells included in the first cell set belong to a same cell group, and the one cell group is a SCG (Secondary Cell Group), and the first cell is a PSCell (Primary Secondry Cell) in the one cell group.

[0173] As an embodiment, the first set of cells comprises a plurality of serving cells belonging to one cell group, the one cell group being a SCG (Secondary Cell Group), and the first cell being an SCell (Secondary Cell) in the one cell group.

[0174] As an embodiment, the target identity is a first type of identity.

[0175] As an embodiment, the target identity is a non-negative integer.

[0176] As an embodiment, the target identity is a string.

[0177] As an embodiment, the target identity is used to identify an AI model.

[0178] As an embodiment, the target identity is used to identify an AI entity.

[0179] As an embodiment, the target identity is used to identify an AI function.

[0180] As an embodiment, the benefit of the above method includes that identifying an AI entity or function by the target identity simplifies the design and unifies the understanding of different AI entities or functions among multiple nodes.

[0181] As an embodiment, the target identity is a model identity.

[0182] As an embodiment, the target identity is used to identify an AI model.

[0183] As an embodiment, the target identity is used by the first node to determine an AI model.

[0184] As an embodiment, the target identity is used by the first node to determine an AI model used by the first operation.

[0185] As an embodiment, the benefit of the above method includes that identifying an AI model / entity / function by the target identity simplifies the design and unifies the understanding of different AI entities / functions among multiple nodes.

[0186] As an embodiment, the benefit of the above method includes that all serving cells in the first set of cells can use the same AI model.

[0187] As an embodiment, the benefit of the above method includes that CSI on all serving cells in the first set of cells can be generated by the same AI entity.

[0188] As an embodiment, the target identity is used to identify or indicate a resource set.

[0189] As an embodiment, the target identity is used to identify or indicate a resource set, the resource set identified or indicated by the target identity includes resources on each serving cell in the first cell set, the resources include at least one of time-frequency resources or RS resources.

[0190] As an embodiment, the target identity is used to identify or indicate a resource set, the measurement of the resource set identified or indicated by the target identity is used to obtain a training data set.

[0191] As an embodiment, the target identity is used to identify or indicate a resource set, the resource set identified or indicated by the target identity includes resources on each serving cell in the first cell set, the resources include at least one of time-frequency resources or RS resources; the measurement of the resource set identified or indicated by the target identity is used to obtain a training data set.

[0192] As an embodiment, the target identity is used to identify or indicate a resource set.

[0193] As an embodiment, the target identity is used to identify or indicate a training data set.

[0194] As an embodiment, the target identity is used to identify or indicate a training data set, the training data set identified or indicated by the target identity includes training data on each serving cell in the first cell set.

[0195] As an embodiment, the benefits of the above method include that by identifying an AI training or AI training data set, the inference generated by this AI training or AI training data set is identified, consensus is established between different AI functions, and design is further simplified.

[0196] As an embodiment, the benefits of the above method include that all serving cells in the first cell set can use the same AI model, the training data for training the same AI model comes from all serving cells in the first cell set, more accurate training data can be obtained, and the reliability and accuracy of the AI model are improved.

[0197] As an embodiment, the generation of the target CSI is based on AI.

[0198] As an embodiment, the generation manner of the target CSI is AI-based includes that the generation manner of the target CSI is based on training.

[0199] As an embodiment, the generation manner of the target CSI is AI-based includes that the generation of the target CSI uses an AI model.

[0200] As an embodiment, the generation manner of the target CSI is AI-based includes that the target CSI includes information based on artificial intelligence or machine learning.

[0201] As an embodiment, the generation manner of the target CSI is AI-based includes that the target CSI includes information generated based on a neural network.

[0202] As an embodiment, the generation manner of the target CSI is AI-based includes that the target CSI includes information generated based on a CNN (Conventional Neural Networks).

[0203] As an embodiment, the generation manner of the target CSI is AI-based includes that the target CSI reporting configuration indicates a first type of identifier.

[0204] As an embodiment, the generation manner of the target CSI is AI-based includes that the target CSI reporting configuration indicates a first type of identifier, and the first operation is associated with the first type of identifier indicated by the target CSI reporting configuration.

[0205] As an embodiment, the generation manner of the target CSI is AI-based includes that the generation manner of the target CSI is associated with a first type of identifier.

[0206] As an embodiment, the generation manner of the target CSI is associated with a first type of identifier includes that the generation manner of the target CSI belongs to an AI function, and the first type of identifier is used to identify the AI function.

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

[0208] As an embodiment, the first type of identifier is a string.

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

[0210] As an embodiment, the first type of identifier is used to identify an AI entity.

[0211] As one embodiment, the first type of identifier is used to identify an AI function.

[0212] As one embodiment, the benefit of the above method includes that the design is simplified and the understanding of different AI entities or functions is unified among multiple nodes by identifying an AI entity or function through the first type of identifier.

[0213] As one embodiment, the first type of identifier is a model identifier.

[0214] As one embodiment, the first type of identifier is used to identify an AI model.

[0215] As one embodiment, the first type of identifier is used by the first node to determine an AI model.

[0216] As one embodiment, the first type of identifier is used by the first node to determine an AI model used by the first operation.

[0217] As one embodiment, the benefit of the above method includes that the design is simplified and the understanding of different AI entities or functions is unified among multiple nodes by identifying an AI model / entity / function through the first type of identifier.

[0218] As one embodiment, the first type of identifier is used to identify or indicate a resource set.

[0219] As one embodiment, the first type of identifier is used to identify or indicate a resource set, and the measurement of the resource set is used to obtain a training data set.

[0220] As one embodiment, the first type of identifier is used to identify or indicate a resource set.

[0221] As one embodiment, the first type of identifier is used to identify or indicate a training data set.

[0222] As one embodiment, the benefit of the above method includes that the design is further simplified by identifying an AI training or an AI training data set and establishing a consensus among different AI functions to identify the inference generated by this AI training or AI training data set.

[0223] As one embodiment, the target CSI is sent later than the first time.

[0224] As one embodiment, only when the target cell belongs to the first cell set, the first type of identifier associated with the generation mode of the target CSI is updated to the target identifier from the first time, which is later than the reception of the first information block.

[0225] As one embodiment, the first time instant is a time instant at which the first information block starts to take effect.

[0226] As one embodiment, a HARQ-ACK (Hybrid Automatic Repeat request-Acknowledgement) corresponding to the first information block is transmitted in the first physical channel.

[0227] As one embodiment, the first physical channel comprises a PUSCH (Physical uplink shared channel) transmission.

[0228] As one embodiment, the first physical channel comprises a PUCCH (Physical uplink control channel) transmission.

[0229] Typically, the HARQ-ACK corresponding to the first information block is a positive HARQ-ACK corresponding to the first information block.

[0230] As one embodiment, the HARQ-ACK corresponding to the first information block indicates that the first information block is correctly received.

[0231] As one embodiment, the HARQ-ACK corresponding to the first information block indicates that a PDSCH scheduled by the first information block is correctly received.

[0232] As one embodiment, the HARQ-ACK corresponding to the first information block indicates that an activation command carried by the first information block is correctly received.

[0233] As one embodiment, the positive HARQ-ACK corresponding to the first information block indicates that the first information block is correctly received.

[0234] As one embodiment, the positive HARQ-ACK corresponding to the first information block indicates that a PDSCH scheduled by the first information block is correctly received.

[0235] As one embodiment, the positive HARQ-ACK corresponding to the first information block indicates that an activation command carried by the first information block is correctly received.

[0236] As one embodiment, the first time instant is later than the first physical channel in time domain.

[0237] As one embodiment, the first time instance is the first time slot later than the first reference time interval after the last symbol occupied by the first physical channel.

[0238] As one embodiment, the first time instance is the first time slot later than the first reference time interval after the last symbol occupied by the first physical channel.

[0239] As one embodiment, the first time instance is the first time slot later than the first reference time interval after the last symbol occupied by the first physical channel.

[0240] As one embodiment, the first time instance is the first time slot later than the first reference time interval after the last symbol occupied by the first physical channel.

[0241] As one embodiment, the first time instance is the first time slot later than the first reference time interval after the last symbol occupied by the first physical channel.

[0242] As one embodiment, the first physical channel is transmitted on time slot n, the first time instance is the first time slot after time slot m, and m equals n + the first reference time interval.

[0243] As one embodiment, the first reference time interval is a positive real number.

[0244] As one embodiment, the first reference time interval is a time length of a positive integer number of symbols.

[0245] As one embodiment, the unit of the first reference time interval is symbol.

[0246] As one embodiment, the unit of the first reference time interval is millisecond.

[0247] As one embodiment, the unit of the first reference time interval is time slot.

[0248] As one embodiment, the first reference time interval is a time length of a positive integer number of time slots.

[0249] As one embodiment, the first reference time interval is beamAppTime.

[0250] As one embodiment, the first reference time interval is

[0251] As one sub-embodiment of the above embodiment, the μ is a subcarrier spacing configuration of the first physical channel.

[0252] As one sub-embodiment of the above embodiment, the is a number of slots included in a subframe.

[0253] As a sub-embodiment of the above-mentioned embodiment, the k mac is equal to 0, or the k mac is equal to a value of a parameter K-Mac.

[0254] As an embodiment, the first reference time interval is reported by the first node.

[0255] As an embodiment, the first reference time interval is indicated by a capability report of the first node.

[0256] As an embodiment, the symbol is a single carrier symbol.

[0257] As an embodiment, the symbol is a multi-carrier symbol.

[0258] As an embodiment, the symbol is an OFDM (Orthogonal Frequency Division Multiplexing) symbol.

[0259] As an embodiment, the symbol is obtained after OFDM symbol generation from an output of a transform precoding.

[0260] As an embodiment, the symbol is a DFT-S-OFDM (Discrete Fourier Transform Spread OFDM) symbol.

[0261] As an embodiment, the multi-carrier symbol is an OFDM (Orthogonal Frequency Division Multiplexing) symbol.

[0262] As an embodiment, the symbol is obtained after OFDM symbol generation from an output of a transform precoding.

[0263] As an embodiment, the symbol is an SC-FDMA (Single Carrier-Frequency Division Multiple Access) symbol.

[0264] As one embodiment, the symbol is a DFT-S-OFDM (Discrete Fourier Transform Spread OFDM) symbol.

[0265] As one embodiment, the multi-carrier symbol is a FBMC (Filter Bank Multi Carrier) symbol.

[0266] As one embodiment, the multi-carrier symbol comprises a CP (Cyclic Prefix).

[0267] Embodiment 2

[0268] Embodiment 2 illustrates a schematic diagram of a network architecture according to one embodiment of the present application, as shown in FIG. 2.

[0269] FIG. 2 illustrates a network architecture 200. The network architecture 200 is a 5G NR (New Radio) / LTE (Long-Term Evolution) / LTE-A (Long-Term Evolution Advanced) system, or the network architecture 200 is a 5G+ network architecture, or the network architecture 200 is a 6G network architecture, or the network architecture 200 is a network architecture adopted in 3GPP future continued evolution; the network architecture 200 can be referred to as 5GS (5G System) / EPS (Evolved Packet System), or the network architecture 200 can be referred to as 6GS (6G System); the network architecture 200 includes at least one of a UE (User Equipment) 201, a RAN (Radio Access Network) 202, a core network 210, a HSS (Home Subscriber Server) / UDM (Unified Data Management) 220, and an Internet service 230. The network architecture 200 can be interconnected with other access networks, but these entities / interfaces are not shown for simplicity. As illustrated, the network architecture 200 provides packet-switched services, however, those skilled in the art will readily appreciate that the various concepts presented throughout this application are amenable to use with networked or other wireless communication systems, providing circuit-switched service. The RAN includes a node 203. The RAN can also include other nodes 204. The node 203 provides user and control plane protocol terminations toward the UE 201. The node 203 can be connected to the other nodes 204 via an Xn interface (e.g., backhaul) / X2 interface. The node 203 can also be referred to as a base station, a base transceiver station, a radio base station, a radio transceiver, a transceiver function, a basic service set (BSS), an extended service set (ESS), a TRP (Transmission Reception Point), or some other suitable terminology. The core network 210 is a 5GC (5G Core Network) / EPC (Evolved Packet Core), or the core network 210 is a 6GC; the node 203 provides access to the core network 210 for the UE 201.Examples of UE 201 include cellular phones, smart phones, Session Initiation Protocol (SIP) phones, laptop computers, Personal Digital Assistants (PDAs), satellite radios, non-terrestrial base station communications, satellite mobile communications, global positioning systems, multimedia devices, video devices, digital audio players (e.g., MP3 players), cameras, game consoles, drones, aerial vehicles, narrowband internet of things devices, machine type communication devices, land vehicles, automobiles, wearable devices, or any other similar functional device. Those skilled in the art will also recognize that a UE 201 can be referred to as a mobile station, a subscriber station, a mobile unit, a subscriber unit, a wireless unit, a remote unit, a mobile device, a wireless device, a wireless communication device, a remote device, a mobile subscriber station, an access terminal, a mobile terminal, a wireless terminal, a remote terminal, a handset, a user agent, a mobile client, a client, or some other suitable terminology. Node 203 is connected to the core network 210 through an S1 / NG interface. The core network 210 includes a MME (Mobility Management Entity) / AMF (Authentication Management Field) / SMF (Session Management Function) 211, other MME / AMF / SMF 214, a 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 a 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 Protocal) packets are transferred through the S-GW / UPF 212, which itself is connected to the P-GW / UPF 213. The P-GW provides UE IP address allocation as well as other functions. The P-GW / UPF 213 is connected to the Internet services 230. The Internet services 230 include operator corresponding Internet protocol services, which can specifically include the Internet, an intranet, an IMS (IP Multimedia Subsystem), and a packet switching service.

[0270] As one embodiment, the first node comprises the UE 201.

[0271] As one embodiment, the second node comprises the node 203.

[0272] As one embodiment, the wireless link between the UE 201 and the node 203 comprises a cellular network link.

[0273] As one embodiment, the sender of the target CSI reporting configuration comprises the node 203.

[0274] As one embodiment, the receiver of the target CSI reporting configuration comprises the UE 201.

[0275] As one embodiment, the sender of the first information block comprises the node 203.

[0276] As one embodiment, the receiver of the first information block comprises the UE 201.

[0277] As one embodiment, the sender of the target CSI comprises the UE 201.

[0278] As one embodiment, the receiver of the target CSI comprises the node 203.

[0279] As one embodiment, the sender of the first higher layer parameter comprises the node 203.

[0280] As one embodiment, the receiver of the first higher layer parameter comprises the UE 201.

[0281] As one embodiment, the sender of the second information block comprises the UE 201.

[0282] As one embodiment, the receiver of the second information block comprises the node 203.

[0283] Embodiment 3

[0284] Embodiment 3 illustrates a schematic diagram of an embodiment of a radio protocol architecture for the user plane and control plane according to one embodiment of the application, as shown in Figure 3.

[0285] 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 showing three layers of the radio protocol architecture for the control plane 300 between a first communication node device (UE, gNB or RSU in V2X (Vehicular to X)) and a second communication node device (gNB, UE or RSU in V2X) or between two UEs: Layer 1, Layer 2, and Layer 3. Layer 1 (LI layer) is the lowest layer and implements various PHY (Physical layer) signal processing functions. The LI layer will be referred to as the PHY 301 herein. Layer 2 (L2 layer) 305 is above the PHY 301 and is responsible for the link between the first communication node device and the second communication node device or between two UEs. The L2 layer 305 includes a MAC (Medium Access Control) sublayer 302, a RLC (Radio Link Control) sublayer 303, and a PDCP (Packet Data Convergence Protocol) sublayer 304, which terminate the functions of the second communication node device. The PDCP sublayer 304 provides multiplexing between different radio bearers and logical channels. The PDCP sublayer 304 also provides security functions, such as ciphering of the data packets, and header compression. The RLC sublayer 303 provides segmentation and reassembly of upper layer data packets, retransmission of lost data packets, and reordering of data packets to compensate for out-of-order reception due to HARQ. The MAC sublayer 302 provides multiplexing between logical and transport channels. The MAC sublayer 302 is also responsible for allocating the various radio resources (e.g., resource blocks) in one cell among the UEs. The MAC sublayer 302 is also responsible for HARQ operations. The RRC (Radio Resource Control) sublayer 306 in Layer 3 (L3 layer) in the control plane 300 is responsible for obtaining radio resources (i.e., radio bearers) and configuring the lower layers using RRC signaling between the second communication node device and the first communication node device. The radio protocol architecture for the user plane 350 includes Layer 1 (LI layer) and Layer 2 (L2 layer), which are substantially the same as the corresponding layers and sublayers in the control plane 300 for the physical layer 351, the PDCP sublayer 354 in the L2 layer 355, the RLC sublayer 353 in the L2 layer 355, and the MAC sublayer 352 in the L2 layer 355 for the first communication node device and the second communication node device, but the PDCP sublayer 354 also provides header compression for upper layer data packets to reduce radio transmission overhead.The L2 layer 355 in the user plane 350 also includes a SDAP (Service Data Adaptation Protocol) sublayer 356, which is responsible for mapping between QoS (Quality of Service) flows and data radio bearers (DRBs) to support the diversity of services. Although not illustrated, the first communication node device can have several upper layers above the L2 layer 355, including a network layer (e.g., IP layer) that terminates at a P-GW on the network side and an application layer that terminates at the other end of the connection (e.g., a remote UE, a server, etc.).

[0286] As one embodiment, the wireless protocol architecture in FIG. 3 is applicable to the first node.

[0287] As one embodiment, the wireless protocol architecture in FIG. 3 is applicable to the second node.

[0288] As one embodiment, the higher layer in this application refers to a layer above the physical layer.

[0289] As one embodiment, the target CSI reporting configuration is generated at the RRC sublayer 306.

[0290] As one embodiment, the first information block is generated at the PHY 301 or the PHY 351.

[0291] As one embodiment, the first information block is generated at the MAC sublayer 302 or the MAC sublayer 352.

[0292] As one embodiment, the target CSI is generated at the PHY 301 or the PHY 351.

[0293] As one embodiment, the target CSI is generated at the MAC sublayer 302 or the MAC sublayer 352.

[0294] As one embodiment, the first higher layer parameter is generated at the RRC sublayer 306.

[0295] As one embodiment, the first higher layer parameter is generated at the MAC sublayer 302 or the MAC sublayer 352.

[0296] As one embodiment, the second information block is generated at the RRC sublayer 306.

[0297] As one embodiment, the second information block is generated at the MAC sublayer 302 or the MAC sublayer 352.

[0298] As an embodiment, the second information block is generated at the PHY 301 or the PHY 351.

[0299] Embodiment 4

[0300] Embodiment 4 illustrates a schematic diagram of a first communication device and a second communication device according to an embodiment of the present 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.

[0301] The first communication device 410 comprises a controller / processor 475, a memory 476, a receive processor 470, a transmit processor 416, a multi-antenna receive processor 472, a multi-antenna transmit processor 471, a transmitter / receiver 418 and an antenna 420.

[0302] The second communication device 450 comprises a controller / processor 459, a memory 460, a data source 467, a transmit processor 468, a receive processor 456, a multi-antenna transmit processor 457, a multi-antenna receive processor 458, a transmitter / receiver 454 and an antenna 452.

[0303] In the transmission from the first communication device 410 to the second communication device 450, at the first communication device 410, upper layer packets from the core network are provided to the controller / processor 475. The controller / processor 475 implements functionality of the L2 layer. In the DL (DownLink), the controller / processor 475 provides header compression, ciphering, packet segmentation and reordering, multiplexing between logical and transport channels, and radio resource allocations for the second communication device 450 based on various priority metrics. The controller / processor 475 is also responsible for HARQ operations, retransmission of lost packets, and signaling to the second communication device 450. The transmit processor 416 and the multi-antenna transmit processor 471 implement various signal processing functions for the LI layer (i.e., physical layer). The transmit processor 416 implements coding and interleaving to facilitate forward error correction (FEC) at the second communication device 450 and constellation mapping based on various modulation schemes (e.g., binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), M-phase shift keying (M-PSK), M-quadrature amplitude modulation (M-QAM)). The multi-antenna transmit processor 471 performs digital spatial pre-coding of the coded and modulated symbols, including codebook-based and non-codebook-based pre-coding, and beamforming processing, generating one or more parallel streams. The transmit processor 416 then maps to each parallel stream to subcarriers, multiplexes the modulated symbols with reference signals (e.g., pilot) in time domain and / or frequency domain, and then performs an inverse fast Fourier transform (IFFT) to generate time domain multi-carrier symbol streams. The multi-antenna transmit processor 471 then performs transmit analog pre-coding / beamforming operations on the time domain multi-carrier symbol streams. Each transmitter 418 converts the baseband multi-carrier symbol streams provided by the multi-antenna transmit processor 471 into radio frequency signals, and then provides the radio frequency signals to the different antennas 420.

[0304] In 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 respective antenna 452. Each receiver 454 recovers information modulated onto an RF carrier and converts the RF stream into a baseband, multicarrier symbol stream to receive processor 456. The receive processor 456 and the multi-antenna receive processor 458 implement various signal processing functions of the Ll layer. The multi-antenna receive processor 458 performs receive analog precoding / beamforming operation on the baseband, multicarrier symbol stream from the receivers 454. The receive processor 456 converts the baseband, multicarrier symbol stream from the receive analog precoding / beamforming operation from the time domain to the frequency domain using a Fast Fourier Transform (FFT). In the frequency domain, the physical layer data signals and the reference signals are demultiplexed by the receive processor 456, where the reference signals will be used for channel estimation, and the data signals are recovered after multi-antenna detection in the multi-antenna receive processor 458 for any parallel streams destined to the second communication device 450. The symbols on each parallel stream are demodulated and recovered in the receive processor 456 and generate soft decisions. The receive processor 456 then decodes and de-interleaves the soft decisions to recover the upper layer data and control signals transmitted by the first communication device 410 on the physical channels. The upper layer data and control signals are then provided to the controller / processor 459. The controller / processor 459 implements the functions of the L2 layer. The controller / processor 459 can be associated with a memory 460 that stores program codes and data. The memory 460 can be referred to as a computer-readable medium. In the DL, the controller / processor 459 provides demultiplexing between transport and logical channels, packet reassembly, deciphering, header decompression, control signal processing to recover upper layer data packets from the core network. The upper layer data packets are then provided to all protocol layers above the L2 layer. Various control signals can also be provided to the L3 for L3 processing. The controller / processor 459 is also responsible for error detection using an acknowledgement (ACK) and / or negative acknowledgement (NACK) protocol to support HARQ operations.

[0305] 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 packets to a controller / processor 459. The data source 467 represents all protocol layers above the L2 layer. Similar to the transmit function described at the first communication device 410 in the DL, the controller / processor 459 implements header compression, ciphering, packet segmentation and reordering, and multiplexing between logical and transport channels based on radio resource allocations for the first communication device 410, implements L2 layer functionality 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. A transmit processor 468, under direction of a controller / processor 459, performs modulation mapping, channel coding processing, and a multi-antenna transmit processor 457 performs digital multi-antenna spatial processing, including codebook-based and non-codebook-based precoding, and beamforming processing, and then the transmit processor 468 modulates the generated parallel streams into multiplexed / singular carrier symbol streams, which are then provided to different antennas 452 via transmitters 454 after analog precoding / beamforming operations in the multi-antenna transmit processor 457. Each transmitter 454 first converts the baseband symbol stream provided by the multi-antenna transmit processor 457 into a RF signal and then provides the RF signal to the antenna 452.

[0306] In the transmission from the second communication device 450 to the first communication device 410, the functionality at the first communication device 410 is similar to the functionality described in connection with the reception at the second communication device 450 in the transmission from the first communication device 410 to the second communication device 450. Each receiver 418 receives a signal through its respective antenna 420, converts the received signal into a baseband signal, and provides the baseband signal to a multi-antenna receive processor 472 and a receive processor 470. The receive processor 470 and the multi-antenna receive processor 472, in conjunction with the controller / processor 475, implement the L1 layer functions. The controller / processor 475 implements L2 layer functions. The controller / processor 475 can be associated with a memory 476 that stores program codes and data. The memory 476 can be referred to as a computer-readable medium. The controller / processor 475 provides demultiplexing between transport and logical channels, packet reassembly, deciphering, header decompression, control signal processing to recover upper layer packets from the second communication device 450. Upper layer packets from the controller / processor 475 can be provided to a core network. The controller / processor 475 is also responsible for error detection using an ACK and / or NACK (negative acknowledgement) protocol to support HARQ operations.

[0307] As one embodiment, the second communication device 450 comprises: at least one processor and at least one memory including computer program code; the at least one memory and the computer program code configured to, with the at least one processor, cause the performance of the following: receiving a target CSI reporting configuration; the target CSI reporting configuration being used for configuring reporting of a target CSI on a target cell, a generation manner of the target CSI being AI-based; receiving a first information block, the first information block indicating a target identity; transmitting the target CSI; wherein the generation manner of the target CSI is associated to a first type of identity; whether the first type of identity associated to the generation manner of the target CSI is updated to the target identity depends on whether the target cell belongs to a first cell set; only when the target cell belongs to the first cell set, the first type of identity associated to the generation manner of the target CSI is updated to the target identity; the first cell set comprises a plurality of serving cells, a first cell being one serving cell in the first cell set, the first cell depending on the first information block; the target cell and the first cell are different.

[0308] As one embodiment, the second communication device 450 comprises: a memory storing a computer readable program of instructions which, when executed by at least one processor, causes the performance of the following: receiving a target CSI reporting configuration; the target CSI reporting configuration being used for configuring reporting of a target CSI on a target cell, a generation manner of the target CSI being AI-based; receiving a first information block, the first information block indicating a target identity; transmitting the target CSI; wherein the generation manner of the target CSI is associated to a first type of identity; whether the first type of identity associated to the generation manner of the target CSI is updated to the target identity depends on whether the target cell belongs to a first cell set; only when the target cell belongs to the first cell set, the first type of identity associated to the generation manner of the target CSI is updated to the target identity; the first cell set comprises a plurality of serving cells, a first cell being one serving cell in the first cell set, the first cell depending on the first information block; the target cell and the first cell are different.

[0309] As one embodiment, the first communication device 410 comprises: at least one processor and at least one memory including a computer program code; the at least one memory and the computer program code are configured to, with the at least one processor, cause the first communication device 410 to perform the following actions: transmitting a target CSI reporting configuration; the target CSI reporting configuration is used to configure reporting of a target CSI on a target cell, a generation manner of the target CSI is AI-based; transmitting a first information block, the first information block indicates a target identity; receiving a target CSI; wherein the generation manner of the target CSI is associated to a first type of identity; whether the first type of identity associated to the generation manner of the target CSI is updated to the target identity depends on whether the target cell belongs to a first cell set; only when the target cell belongs to the first cell set, the first type of identity associated to the generation manner of the target CSI is updated to the target identity; the first cell set comprises a plurality of serving cells, a first cell is one serving cell in the first cell set, the first cell depends on the first information block; the target cell is different from the first cell.

[0310] As one embodiment, the first communication device 410 comprises: a memory storing a computer readable program of instructions which, when executed by at least one processor, causes actions comprising: transmitting a target CSI reporting configuration; the target CSI reporting configuration is used to configure reporting of a target CSI on a target cell, a generation manner of the target CSI is AI-based; transmitting a first information block, the first information block indicates a target identity; receiving a target CSI; wherein the generation manner of the target CSI is associated to a first type of identity; whether the first type of identity associated to the generation manner of the target CSI is updated to the target identity depends on whether the target cell belongs to a first cell set; only when the target cell belongs to the first cell set, the first type of identity associated to the generation manner of the target CSI is updated to the target identity; the first cell set comprises a plurality of serving cells, a first cell is one serving cell in the first cell set, the first cell depends on the first information block; the target cell is different from the first cell.

[0311] As one embodiment, the first node in the present application comprises the second communication device 450.

[0312] As one embodiment, the second node in the present application comprises the first communication device 410.

[0313] As one embodiment, at least one of {the antenna 452, the receiver 454, the receive processor 456, the multi-antenna receive processor 458, the controller / processor 459, the memory 460, the data source 467} is configured to receive the target CSI reporting configuration; at least one of {the antenna 420, the transmitter 418, the transmit processor 416, the multi-antenna transmit processor 471, the controller / processor 475, the memory 476} is configured to transmit the target CSI reporting configuration.

[0314] As one embodiment, at least one of {the antenna 452, the receiver 454, the receive processor 456, the multi-antenna receive processor 458, the controller / processor 459, the memory 460, the data source 467} is configured to receive the first information block; at least one of {the antenna 420, the transmitter 418, the transmit processor 416, the multi-antenna transmit processor 471, the controller / processor 475, the memory 476} is configured to transmit the first information block.

[0315] As one embodiment, at least one of {the antenna 420, the receiver 418, the receive processor 470, the multi-antenna receive processor 472, the controller / processor 475, the memory 476} is configured to receive the target CSI; at least one of {the antenna 452, the transmitter 454, the transmit processor 468, the multi-antenna transmit processor 457, the controller / processor 459, the memory 460, the data source 467} is configured to transmit the target CSI.

[0316] As one embodiment, at least one of {the antenna 452, the receiver 454, the receive processor 456, the multi-antenna receive processor 458, the controller / processor 459, the memory 460, the data source 467} is configured to receive the first higher layer parameter; at least one of {the antenna 420, the transmitter 418, the transmit processor 416, the multi-antenna transmit processor 471, the controller / processor 475, the memory 476} is configured to transmit the first higher layer parameter.

[0317] As an embodiment, at least one of {the antenna 420, the receiver 418, the receive processor 470, the multi-antenna receive processor 472, the controller / processor 475, the memory 476} is configured to receive the second information block; at least one of {the antenna 452, the transmitter 454, the transmit processor 468, the multi-antenna transmit processor 457, the controller / processor 459, the memory 460, the data source 467} is configured to transmit the second information block.

[0318] Embodiment 5

[0319] Embodiment 5 illustrates a flowchart of a transmission between a first node and a second node according to an embodiment of the present application; as shown in FIG. 5. In FIG. 5, the second node U1 and the first node U2 are communication nodes for a transmission over an air interface. In FIG. 5, the steps in the block F51 to the block F53 are optional respectively.

[0320] For the second node U1, the second information block is received in the step S511; the first higher layer parameter is transmitted in the step S512; the target CSI reporting configuration is transmitted in the step S5101; the first information block is transmitted in the step S5102; and the target CSI is received in the step S5103.

[0321] For the first node U2, the second information block is transmitted in the step S521; the first higher layer parameter is received in the step S522; the target CSI reporting configuration is received in the step S5201; the first information block is received in the step S5202; the first operation is performed in the step S523; and the target CSI is transmitted in the step S5203.

[0322] In Embodiment 5, the target CSI reporting configuration is configured to configure a reporting of a target CSI on a target cell, a generation manner of the target CSI is based on an AI; the first information block indicates a target identity; the generation manner of the target CSI is associated to a first type identity; whether the first type identity associated to the generation manner of the target CSI is updated to the target identity depends on whether the target cell belongs to a first cell set; only when the target cell belongs to the first cell set, the first type identity associated to the generation manner of the target CSI is updated to the target identity; the first cell set includes a plurality of serving cells, a first cell is one serving cell in the first cell set, the first cell depends on the first information block; and the target cell is different from the first cell.

[0323] As an embodiment, the first node U2 is the first node in the present application.

[0324] As one embodiment, the second node U1 is the second node in the present application.

[0325] As one embodiment, the air interface between the second node U1 and the first node U2 comprises a wireless interface between a base station device and a user equipment.

[0326] As one embodiment, the air interface between the second node U1 and the first node U2 comprises a wireless interface between a relay node device and a user equipment.

[0327] As one embodiment, the air interface between the second node U1 and the first node U2 comprises a wireless interface between a user equipment and a user equipment.

[0328] As one embodiment, the second node U1 is a serving cell maintaining base station of the first node U2.

[0329] As one embodiment, the step in block F51 in figure 5 is present; the method in the first node used for wireless communication comprises: transmitting a second information block.

[0330] As one embodiment, the step in block F51 in figure 5 is present; the method in the second node used for wireless communication comprises: receiving a second information block.

[0331] As one embodiment, the step in block F52 in figure 5 is present; the method in the first node used for wireless communication comprises: receiving a first higher layer parameter.

[0332] As one embodiment, the step in block F52 in figure 5 is present; the method in the second node used for wireless communication comprises: transmitting a first higher layer parameter.

[0333] As one embodiment, the step in block F53 in figure 5 is present; the method in the first node used for wireless communication comprises: performing a first operation.

[0334] As one embodiment, the target CSI reporting configuration is transmitted on a PDSCH (Physical Downlink Shared Channel).

[0335] As one embodiment, the first information block is transmitted on a PDSCH (Physical Downlink Shared Channel).

[0336] As one embodiment, the first information block is transmitted on a PDCCH (Physical Downlink Control Channel).

[0337] As one embodiment, the target CSI is transmitted on a PUCCH (Physical Uplink Control Channel).

[0338] As one embodiment, the target CSI is transmitted on a PUSCH (Physical Uplink Shared Channel).

[0339] As one embodiment, the first higher layer parameter is transmitted on a PDSCH (Physical Downlink Shared Channel).

[0340] As one embodiment, the second information block is transmitted on a PUCCH (Physical Uplink Control Channel).

[0341] As one embodiment, the second information block is transmitted on a PUSCH (Physical Uplink Shared Channel).

[0342] As one embodiment, the reception of the second information block is earlier than the transmission of the first information block.

[0343] As one embodiment, the reception of the second information block is earlier than the transmission of the first higher layer parameter.

[0344] As one embodiment, the reception of the second information block is earlier than the transmission of the target CSI reporting configuration.

[0345] As one embodiment, the reception of the second information block is not earlier than the transmission of the target CSI reporting configuration.

[0346] As one embodiment, the first higher layer parameter is earlier than the target CSI reporting configuration.

[0347] As one embodiment, the first higher layer parameter is not earlier than the target CSI reporting configuration.

[0348] As one embodiment, the reception of the first information block is earlier than the first node performing the first operation.

[0349] Embodiment 6

[0350] Embodiment 6 illustrates a diagram of a first information block according to an embodiment of the present application; as shown in Figure 6. In Embodiment 6, the first information block is applied to each serving cell in the first set of cells.

[0351] As one embodiment, the first information block is used to update the first type identity in each serving cell in the first set of cells.

[0352] As one embodiment, the first information block is applied to each serving cell in the first set of cells starting from a first time instant; the first time instant is later than a time instant of receiving the first information block.

[0353] As one embodiment, the first information block indicates a target identity, the target identity indicated by the first information block is used to update the first type identity in each serving cell in the first set of cells.

[0354] As one embodiment, the first type identity in each serving cell in the first set of cells is updated to the target identity starting from a first time instant.

[0355] Embodiment 7

[0356] Embodiment 7 illustrates a diagram of a first cell dependent first information block according to an embodiment of the present application; as shown in Figure 7. In Embodiment 7, the first information block indicates the first cell.

[0357] As one embodiment, the first information block explicitly indicates the first cell.

[0358] As one embodiment, the first information block implicitly indicates the first cell.

[0359] As one embodiment, the first cell indicated by the first information block comprises only the first cell.

[0360] As one embodiment, the first information block comprises a first field, the first field comprises at least one bit, the first field in the first information block indicates the first cell.

[0361] As one embodiment, the first information block comprises a first field, the first field in the first information block indicates a cell index, the first cell is identified by the cell index.

[0362] As one embodiment, the first information block comprises a first field, the first field in the first information block comprises a cell index, the first cell is identified by the cell index.

[0363] As one embodiment, the cell index comprises at least one of ServCellIndex or SCellIndex.

[0364] As one embodiment, the first information block comprises a first field, the first field in the first information block is used to indicate the first cell from a plurality of cell candidates.

[0365] As one embodiment, the first information block indicates the first cell comprises: the first information block indicates whether the first cell is activated.

[0366] As one embodiment, the first information block comprises a first field, the first field comprises at least one bit, each bit in the first field in the first information block respectively corresponds to one cell, each bit in the first field in the first information block indicates whether the corresponding cell is activated.

[0367] As one sub-embodiment of the above embodiment, when one bit in the first field in the first information block corresponding to the first cell is set to 1, the first cell is activated.

[0368] As one sub-embodiment of the above embodiment, when one bit in the first field in the first information block corresponding to the first cell is set to 0, the first cell is deactivated.

[0369] As one embodiment, the first information block indicates the first cell comprises: the first information block indicates whether the first cell is activated, the first cell is one serving cell in a first cell set; when the first cell is activated, the first type identifier associated with the generation mode of CSI on each cell in the first cell set is updated to the target identifier; when the first cell is deactivated, the first type identifier associated with the generation mode of CSI on each cell in the first cell set is not updated to the target identifier.

[0370] As one embodiment, the first information block indicates the first cell, the first cell is one serving cell in the first cell set; the first type identifier associated with the generation mode of CSI on each cell in the first cell set is updated to the target identifier.

[0371] As one embodiment, the first information block indicates the first cell, the first cell is one serving cell in the first cell set; whether the first type identifier associated with the generation mode of the target CSI is updated to the target identifier depends on whether the target cell belongs to the first cell set.

[0372] Embodiment 8

[0373] Embodiment 8 illustrates a diagram of a first cell depending on a first information block according to another embodiment of the present application; as shown in FIG. 8. In embodiment 8, the first cell is a serving cell where a physical channel carrying the first information block is located.

[0374] As an embodiment, the first cell being a serving cell where a physical channel carrying the first information block is located includes that the first information block is transmitted on the first cell.

[0375] As an embodiment, the first cell being a serving cell where a physical channel carrying the first information block is located includes that the physical channel carrying the first information block belongs to the first cell.

[0376] As an embodiment, the first cell being a serving cell where a physical channel carrying the first information block is located includes that a RB (Resource Block) occupied by the physical channel carrying the first information block belongs to the first cell.

[0377] As an embodiment, the first cell being a serving cell where a physical channel carrying the first information block is located includes that a BWP (Bandwidth Part) occupied by the physical channel carrying the first information block belongs to the first cell.

[0378] As an embodiment, the physical channel carrying the first information block is a PDCCH.

[0379] As an embodiment, the physical channel carrying the first information block is a PDSCH.

[0380] Embodiment 9

[0381] Embodiment 9 illustrates a diagram of a first resource set and a second resource set according to an embodiment of the present application; as shown in FIG. 9. In embodiment 9, the target CSI reporting configuration indicates a first resource set, the first resource set is used for at least one of channel measurement or interference measurement of the target CSI, the first resource set includes one or more RS resources on the target cell; the target CSI indicates at least one resource in a second resource set, the second resource set includes resources not belonging to the first resource set.

[0382] As an embodiment, the target CSI reporting configuration includes one CSI resource configuration, the one CSI resource configuration is used to indicate the first resource set.

[0383] As a sub-example of the above embodiment, the one CSI resource configuration is one IE CSI-ResourceConfig.

[0384] As a sub-example of the above embodiment, the target CSI reporting configuration includes a resourcesForChannelMeasurement field, and the resourcesForChannelMeasurement field included in the target CSI reporting configuration indicates the one CSI resource configuration.

[0385] As an example, the target CSI reporting configuration includes a plurality of CSI resource configurations, and one CSI resource configuration of the plurality of CSI resource configurations is used to indicate the first resource set.

[0386] As an example, one CSI resource configuration used to configure the first resource set includes an identification or an index of each RS resource in the first resource set.

[0387] As an example, one CSI resource configuration used to configure the first resource set includes an identification of each RS resource in the first resource set.

[0388] As an example, one CSI resource configuration used to configure the first resource set is used to configure each RS resource in the first resource set.

[0389] As an example, one CSI resource configuration used to configure the first resource set includes configuration information of each RS resource in the first resource set.

[0390] As an example, the target CSI reporting configuration includes a resourcesForChannelMeasurement field, and the resourcesForChannelMeasurement field included in the target CSI reporting configuration is used to indicate the first resource set.

[0391] As an example, a resource in the first resource set includes at least one of an antenna port, a TCI (Transmission Configuration Indication) state, QCL (Quasi Co-Location) information, a time-frequency resource, a time-frequency code resource, a beam, an RS resource, a vector, or a matrix.

[0392] As one embodiment, the first resource set comprises one or more RS (Reference Signal) resource sets, one RS resource set comprises one or more RS resources.

[0393] As one embodiment, the first resource set comprises at least one of at least one CSI-RS resource set, at least one CSI-SSB (Channel State Information-Synchronization Signal Block) resource set, or at least one CSI-IM (Channel State Information-Interference Measurement) resource set.

[0394] As one embodiment, the first resource set comprises at least one RS resource set for channel measurement, one RS resource set for channel measurement comprises one or more RS resources.

[0395] As one embodiment, the first resource set comprises at least one RS resource set for channel measurement and at least one RS resource set for interference measurement; one RS resource set for channel measurement comprises one or more RS resources, one RS resource set for interference measurement comprises one or more RS resources.

[0396] As one embodiment, the first resource set comprises at least one RS resource set for interference measurement; one RS resource set for interference measurement comprises one or more RS resources.

[0397] As one embodiment, one RS resource set for channel measurement comprises one or more RS resources, any RS resource in the one RS resource set for channel measurement is a CSI-RS resource or a synchronization signal resource.

[0398] As one embodiment, one RS resource set for interference measurement comprises one or more RS resources.

[0399] As one embodiment, one RS resource set for interference measurement comprises one or more RS resources, any RS resource in the one RS resource set for interference measurement is a CSI-IM resource or a NZP (non-zero power) CSI-RS resource for interference measurement.

[0400] As one embodiment, the first resource set comprises one or more RS resources.

[0401] As one embodiment, the first resource set comprises one or more downlink RS resources.

[0402] As an embodiment, the first set of resources comprises one or more RS resources, any RS resource in the first set of resources is a CSI-RS (Channel State Information Reference Signal) resource or a synchronization signal resource.

[0403] As an embodiment, the synchronization signal resource comprises at least a resource occupied by a synchronization signal.

[0404] As an embodiment, the synchronization signal resource is a SSB (Synchronization Signal Block).

[0405] As an embodiment, the synchronization signal resource is a SS / PBCH (synchronization signal / physical broadcast channel) block resource.

[0406] As an embodiment, the target CSI reporting configuration indicates at least one resource configuration, the at least one resource configuration indicates the first set of resources.

[0407] As an embodiment, the target CSI reporting configuration comprises at least one resource configuration, the at least one resource configuration indicates the first set of resources.

[0408] As an embodiment, one resource configuration is used to configure a CSI resource.

[0409] As an embodiment, one resource configuration is an IE CSI-ResourceConfig.

[0410] As an embodiment, one resource configuration is carried by an RRC IE.

[0411] As an embodiment, one resource configuration is carried by a CSI-ResourceConfig IE.

[0412] As an embodiment, the target CSI reporting configuration indicates configuration information of the first set of resources.

[0413] As an embodiment, the target CSI reporting configuration indicates an identity of the first set of resources.

[0414] As an embodiment, the first resource set is used for channel measurement of the target CSI, any RS resource in the first resource set used for the channel measurement of the target CSI is a CSI-RS resource or a synchronization signal resource.

[0415] As an embodiment, the first resource set is used for interference measurement of the target CSI, any RS resource in the first resource set used for the interference measurement of the target CSI is a CSI-IM resource or a NZP (non-zero power) CSI-RS resource for interference measurement.

[0416] As an embodiment, the first resource set includes resources belonging to the target cell.

[0417] As an embodiment, the RS resources included in the first resource set are transmitted on the target cell.

[0418] As an embodiment, the first resource set only includes one or more RS resources on the target cell.

[0419] As an embodiment, the first resource set includes at least one RS resource not belonging to the target cell.

[0420] As an embodiment, the target CSI reporting configuration indicates a first resource set, the first resource set is used for channel measurement of the target CSI, and the target CSI includes at least RSRP.

[0421] As an embodiment, the target CSI reporting configuration includes a resourcesForChannelMeasurement field, the resourcesForChannelMeasurement field included in the target CSI reporting configuration is used to indicate the first resource set, the first resource set is used for channel measurement of the target CSI, and the target CSI includes at least RSRP.

[0422] As an embodiment, the target CSI includes at least one CSI report.

[0423] As an embodiment, the target CSI includes predicted channel information.

[0424] As an embodiment, the target CSI includes predicted beam information.

[0425] As one embodiment, the target CSI comprises at least one of CQI (Channel Quality Indicator), PMI (Precoding Matrix Indicator), CRI (CSI-RS Resource Indicator), SS / PBCH Block Resource indicator (SSBRI), Layer Indicator (LI), RI (Rank Indicator), L1-RSRP (Layer 1 reference signal received power), or L1-SINR (Layer 1 signal-to-noise and interference ratio)

[0426] As one embodiment, the target CSI comprises one or more of PMI, CRI, CQI, RI, LI, SSBRI, RSRP, SINR, capability index, and TDCP.

[0427] As one embodiment, the target CSI comprises a channel matrix.

[0428] As one embodiment, the target CSI comprises an eigenvector.

[0429] As one embodiment, the target CSI comprises an eigenvector and an eigenvalue.

[0430] As one embodiment, the target CSI comprises precoding information.

[0431] As one embodiment, the target CSI comprises non-codebook-based precoding information.

[0432] As one embodiment, the target CSI is used to determine at least one precoding matrix.

[0433] As one embodiment, the target CSI indicates at least one precoding matrix.

[0434] As one embodiment, the precoding matrix is spatial-frequency domain.

[0435] As one embodiment, the precoding matrix is angular-delay domain projection.

[0436] As one embodiment, the target CSI comprises information of relative phase, amplitude and / or coefficients between multiple antenna ports.

[0437] As one embodiment, the target CSI comprises compressed CSI.

[0438] As one embodiment, the target CSI comprises predicted / estimated CSI.

[0439] As one embodiment, the first node is not required to measure the second set of resources.

[0440] As one embodiment, the first set of resources is used for measurement and the second set of resources is used for prediction.

[0441] As one embodiment, only the first set of resources among the first set of resources and the second set of resources is used for measurement.

[0442] As one embodiment, only the first set of resources among the first set of resources and the second set of resources is used for measurement comprises that only the first set of resources among the first set of resources and the second set of resources is used for measurement by the first node.

[0443] As one embodiment, only the first set of resources among the first set of resources and the second set of resources is used for measurement comprises that the first set of resources is used for measurement by the first node and the first node is not required to measure the second set of resources.

[0444] As one embodiment, the target CSI is generated in an AI-based manner and the first node is not required to measure the second set of resources.

[0445] As one embodiment, the target CSI is generated in an AI-based manner, the first set of resources is used for measurement and the second set of resources is used for prediction.

[0446] As one embodiment, the target CSI is generated in an AI-based manner, the first set of resources is used for measurement and the second set of resources is used for prediction.

[0447] As one embodiment, the target CSI is generated in an AI-based manner, only the first set of resources among the first set of resources and the second set of resources is used for measurement.

[0448] As one embodiment, only the first set of resources among the first set of resources and the second set of resources is used for measurement comprises that only the first set of resources among the first set of resources and the second set of resources is used for measurement by the first node.

[0449] As one embodiment, the first resource set and only the first resource set of the second resource set are used for measurement includes that the first resource set is used for measurement by the first node, the first node is not required to measure part or all of the resources in the second resource set.

[0450] As one embodiment, the first node is not required to measure the second resource set includes that the first node does not measure part or all of the resources in the second resource set.

[0451] As one embodiment, the first node is not required to measure the second resource set includes that whether the first node measures part or all of the resources in the second resource set is implementation dependent or self-determined by the first node.

[0452] As one embodiment, the second resource set includes the first resource set and resources outside the first resource set.

[0453] As one embodiment, the first resource set includes one or more RS resources, the second resource set includes one or more RS resources, and the second resource set includes RS resources outside the first resource set.

[0454] As one embodiment, the first resource set includes less resources than the second resource set.

[0455] As one embodiment, the first resource set includes less RS resources than the second resource set.

[0456] As one embodiment, the second resource set includes resources that are not in the first resource set.

[0457] As one embodiment, the second resource set includes antenna ports that are not in the first resource set.

[0458] As one embodiment, the second resource set includes resources that are not in the first resource set, and the resources in the second resource set include at least one of antenna ports, TCI states, QCL information, frequency resources, time-frequency code resources, beams, RS resources, vectors, or matrices.

[0459] As one embodiment, the second resource set includes at least one RS resource.

[0460] As one embodiment, the second resource set includes at least one beam.

[0461] As an embodiment, the second resource set comprises one or more beams.

[0462] As an embodiment, the second resource set comprises one or more vectors.

[0463] As an embodiment, the second resource set comprises one or more matrices.

[0464] As an embodiment, the second resource set comprises one or more codebooks.

[0465] As an embodiment, the second resource set comprises one or more DFT vectors.

[0466] As an embodiment, the second resource set comprises one or more DFT codebooks.

[0467] As an embodiment, the second resource set comprises one or more antenna ports.

[0468] As an embodiment, the second resource set comprises at least one training dataset.

[0469] As an embodiment, the second resource set is used for training an AI model.

[0470] As an embodiment, the second resource set comprises one or more RS (Reference Signal) resource sets, one RS resource set comprising one or more RS resources.

[0471] As an embodiment, the second resource set comprises at least one of at least one CSI-RS (Channel State Information-Reference Signal) 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.

[0472] As an embodiment, the second resource set comprises at least one RS resource set for channel measurement, one RS resource set for channel measurement comprising one or more RS resources.

[0473] As an embodiment, the second resource set comprises at least one RS resource set for channel measurement and at least one RS resource set for interference measurement; one RS resource set for channel measurement comprising one or more RS resources, and one RS resource set for interference measurement comprising one or more RS resources.

[0474] As an embodiment, the second resource set comprises at least one RS resource set for interference measurement; one RS resource set for interference measurement comprises one or more RS resources.

[0475] As an embodiment, the second resource set comprises one or more RS resources.

[0476] As an embodiment, the second resource set comprises one or more downlink RS resources.

[0477] As an embodiment, the second resource set comprises one or more RS resources, any RS resource in the second resource set is a Channel State Information Reference Signal (CSI-RS) resource or a synchronization signal resource.

[0478] As an embodiment, the target CSI reporting configuration indicates at least one resource configuration, the at least one resource configuration indicates the second resource set.

[0479] As an embodiment, the target CSI reporting configuration comprises at least one resource configuration, the at least one resource configuration indicates the second resource set.

[0480] As an embodiment, the target CSI reporting configuration indicates at least one resource configuration, the at least one resource configuration indicates the first resource set and the second resource set.

[0481] As an embodiment, the target CSI reporting configuration comprises at least one resource configuration, the at least one resource configuration indicates the first resource set and the second resource set.

[0482] As an embodiment, the target CSI reporting configuration indicates one resource configuration, the one resource configuration indicates the first resource set and the second resource set.

[0483] As an embodiment, the target CSI reporting configuration indicates two resource configurations, the two resource configurations respectively indicate the first resource set and the second resource set.

[0484] As an embodiment, the target CSI reporting configuration indicates configuration information of the second resource set.

[0485] As an embodiment, the target CSI reporting configuration indicates an identity of the second resource set.

[0486] As an embodiment, the target CSI reporting configuration is used to indicate the second resource set from a reference resource set.

[0487] As an embodiment, the target CSI reporting configuration indicates a first type of identity, and the second resource set depends on the first type of identity.

[0488] As an embodiment, the second resource set depending on the first type of identity includes that the first type of identity is used to identify the second resource set.

[0489] As an embodiment, the second resource set depending on the first type of identity includes that the first type of identity is used to identify a reference resource set, and the reference resource set includes the second resource set.

[0490] As an embodiment, the second resource set depending on the first type of identity includes that the first type of identity is used to identify a reference resource set, and the reference resource set includes the second resource set, and the target CSI reporting configuration is used to indicate the second resource set from the reference resource set.

[0491] As an embodiment, the information other than the target CSI reporting configuration indicating the second resource set includes a higher layer parameter.

[0492] As an embodiment, the information other than the target CSI reporting configuration indicating the second resource set includes an RRC parameter.

[0493] As an embodiment, the information other than the target CSI reporting configuration indicating the second resource set includes part or all fields of an RRC IE.

[0494] As an embodiment, the information other than the target CSI reporting configuration indicating the second resource set includes a MAC CE.

[0495] As an embodiment, the information other than the target CSI reporting configuration indicating the second resource set includes DCI (downlink control information).

[0496] As an embodiment, the target CSI indicates at least one resource in a second resource set, and the second resource set includes resources not belonging to the first resource set.

[0497] As an embodiment, the target CSI is generated in an AI-based manner, and the target CSI indicates at least one resource in a second resource set, and the second resource set includes resources not belonging to the first resource set.

[0498] As an embodiment, whether the resource indicated by the target CSI belongs to the first resource set depends on whether the generation manner of the target CSI is AI-based; when the generation manner of the target CSI is AI-based, the resource indicated by the target CSI belongs to a second resource set, the second resource set including resources not belonging to the first resource set; when the generation manner of the target CSI is not AI-based, the resource indicated by the target CSI belongs to the first resource set.

[0499] As an embodiment, whether the RS resource indicated by the target CSI belongs to the first resource set depends on whether the generation manner of the target CSI is AI-based; when the generation manner of the target CSI is AI-based, the RS resource indicated by the target CSI belongs to a second resource set, the second resource set including RS resources not belonging to the first resource set; only when the generation manner of the target CSI is not AI-based, the RS resource indicated by the target CSI belongs to the first resource set.

[0500] As an embodiment, the target CSI indicates at least one resource in the second resource set.

[0501] As an embodiment, the second resource set includes at least one RS resource; the target CSI indicating at least one resource in the second resource set includes the target CSI indicating at least one RS resource in the second resource set.

[0502] As an embodiment, the second resource set includes at least one beam; the target CSI indicating at least one resource in the second resource set includes the target CSI indicating at least one beam in the second resource set.

[0503] As an embodiment, the second resource set includes one or more beams; the target CSI indicating at least one resource in the second resource set includes the target CSI indicating at least one beam in the second resource set.

[0504] As an embodiment, the second resource set includes one or more vectors; the target CSI indicating at least one resource in the second resource set includes the target CSI indicating at least one vector in the second resource set.

[0505] As an embodiment, the second resource set includes one or more matrices; the target CSI indicating at least one resource in the second resource set includes the target CSI indicating at least one matrix in the second resource set.

[0506] As an embodiment, the second resource set comprises one or more DFT vectors; the target CSI indicating at least one resource in the second resource set comprises: the target CSI indicating at least one DFT vector in the second resource set.

[0507] As an embodiment, the second resource set comprises one or more codebooks; the target CSI indicating at least one resource in the second resource set comprises: the target CSI indicating at least one codebook in the second resource set.

[0508] As an embodiment, the second resource set comprises one or more antenna ports; the target CSI indicating at least one resource in the second resource set comprises: the target CSI indicating at least one antenna port in the second resource set.

[0509] Embodiment 10

[0510] Embodiment 10 illustrates a schematic diagram of the relationship between the first operation and the target CSI according to an embodiment of the present application; as shown in FIG. 10. In embodiment 10, the target CSI reporting configuration indicates a first resource set, the first resource set is used for at least one of channel measurement or interference measurement of the target CSI, the first resource set comprises one or more RS resources; the generation manner of the target CSI comprises that the first node or the receiver of the target CSI reporting configuration performs a first operation, the input of the first operation depends on the measurement based on the first resource set, and the target CSI depends on the output of the first operation.

[0511] Typically, the first processor performs the first operation.

[0512] As an embodiment, the first operation is used for beam prediction, and the first node adopts a single side AI model.

[0513] As an embodiment, the first resource set comprises at least one RS resource set for channel measurement, and one RS resource set for channel measurement comprises one or more RS resources; the input of the first operation depending on the measurement based on the first resource set comprises: the input of the first operation depending on the channel measurement obtained based on the first resource set.

[0514] As an embodiment, the first resource set comprises at least one RS resource set for interference measurement, and one RS resource set for interference measurement comprises one or more RS resources; the input of the first operation depending on the measurement based on the first resource set comprises: the input of the first operation depending on the interference measurement obtained based on the first resource set.

[0515] As one embodiment, the first resource set comprises at least one RS resource set for channel measurement and at least one RS resource set for interference measurement; one RS resource set for channel measurement comprises one or more RS resources, and one RS resource set for interference measurement comprises one or more RS resources; the input of the first operation depending on the measurement based on the first resource set comprises: the channel measurement and the interference measurement obtained based on the first resource set are used to generate the input of the first operation.

[0516] As one embodiment, the input of the first operation depending on the measurement based on the first resource set comprises: the measurement based on the first resource set is used to generate the input of the first operation.

[0517] As one embodiment, the first resource set comprises at least one RS resource set for channel measurement; the input of the first operation depending on the measurement based on the first resource set comprises: the channel measurement obtained based on the first resource set is used to generate the input of the first operation.

[0518] As one embodiment, the first resource set comprises at least one RS resource set for interference measurement; the input of the first operation depending on the measurement based on the first resource set comprises: the interference measurement obtained based on the first resource set is used to generate the input of the first operation.

[0519] As one embodiment, the first resource set comprises at least one RS resource set for channel measurement and at least one RS resource set for interference measurement; one RS resource set for channel measurement comprises one or more RS resources, and one RS resource set for interference measurement comprises one or more RS resources; the input of the first operation depending on the measurement based on the first resource set comprises: the channel measurement and the interference measurement obtained based on the first resource set are used to generate the input of the first operation.

[0520] As one embodiment, the channel measurement obtained based on the first resource set means: the channel measurement obtained based on at least one reference signal transmitted in the first resource set.

[0521] As one embodiment, the channel measurement obtained based on the first resource set means: the channel measurement obtained in the first resource set.

[0522] As one embodiment, the interference measurement obtained based on the first set of resources refers to an interference measurement obtained based on at least one reference signal transmitted in the first set of resources.

[0523] As one embodiment, the interference measurement obtained based on the first set of resources refers to an interference measurement obtained in the first set of resources.

[0524] As one embodiment, the channel measurement obtained based on the first set of resources comprises a channel matrix.

[0525] As one embodiment, the channel measurement obtained based on the first set of resources comprises a raw channel matrix.

[0526] As one embodiment, the channel measurement obtained based on the first set of resources comprises an eigenvector.

[0527] As one embodiment, the channel measurement obtained based on the first set of resources comprises an eigenvector and an eigenvalue.

[0528] As one embodiment, the channel measurement obtained based on the first set of resources comprises one or more of a BLER, a delay spread, a Doppler spread, a Doppler shift, a mean delay, a mean gain, a path loss, and a RSRP.

[0529] As one embodiment, the interference measurement obtained based on the first set of resources comprises at least one of an interference power, an interference variance, or an interference power spectral density.

[0530] As one embodiment, the interference measurement obtained based on the first set of resources comprises an interference channel matrix.

[0531] As one embodiment, the interference measurement obtained based on the first set of resources comprises an interference covariance matrix.

[0532] As one embodiment, the interference measurement obtained based on the first set of resources comprises an interference eigenvector.

[0533] As one embodiment, the interference measurement obtained based on the first set of resources comprises an interference eigenvector and an interference eigenvalue.

[0534] As one embodiment, the interference measurement obtained based on the first set of resources comprises an interference beam.

[0535] Generally, how the first node determines the input of the first operation based on the measurements of the first set of resources is up to the device vendor, and some non-limiting embodiments are described as follows:

[0536] As one embodiment, the input of the first operation includes channel measurements obtained based on the first set of resources.

[0537] As one embodiment, the input of the first operation includes channel measurements and interference measurements obtained based on the first set of resources.

[0538] As one embodiment, the input of the first operation includes interference measurements obtained based on the first set of resources.

[0539] As one embodiment, the interference measurements include one or more of interference power, interference variance, or interference power spectral density.

[0540] As one embodiment, the input of the first operation includes channel impulse responses obtained based on the measurements for the first set of resources.

[0541] As one embodiment, the input of the first operation includes a channel matrix obtained based on the measurements for the first set of resources.

[0542] As one embodiment, the input of the first operation includes eigenvectors and eigenvalues of a channel matrix obtained based on the measurements for the first set of resources.

[0543] As one embodiment, the input of the first operation includes a matrix or vector obtained by pre-processing a channel matrix obtained based on the measurements for the first set of resources.

[0544] As one embodiment, the channel matrix is in spatial-frequency domain.

[0545] As one embodiment, the channel matrix is in angular-delay domain projection.

[0546] As one embodiment, the pre-processing includes one or more of 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 and time-to-frequency domain transformation, truncation, padding, mapping, labeling.

[0547] As one embodiment, the pre-processing includes one or more of matrix decomposition, matrix transformation or projection.

[0548] As one embodiment, the pre-processing comprises quantization.

[0549] As one embodiment, the pre-processing comprises DFT.

[0550] As one embodiment, the pre-processing comprises one or more of quantization, spatial-to-angle domain transformation, angle domain-to-spatial domain transformation, frequency domain-to-time domain transformation, and time domain-to-frequency domain transformation.

[0551] As one embodiment, the pre-processing comprises truncation and / or padding.

[0552] As one embodiment, the pre-processing comprises mapping.

[0553] As one embodiment, the pre-processing comprises mapping to a vector.

[0554] As one embodiment, the pre-processing comprises labeling.

[0555] As one embodiment, the labeling refers to labeling with a label.

[0556] As one embodiment, the target CSI comprises an output of the first operation.

[0557] As one embodiment, the target CSI comprises a post-processed output of the first operation.

[0558] As one embodiment, the target CSI comprises a truncated and / or quantized output of the first operation.

[0559] As one embodiment, the output of the first operation is used to generate the target CSI.

[0560] As one embodiment, the output of the first operation, after post-processing, is used to generate the target CSI.

[0561] As one embodiment, the output of the first operation, after truncation and / or quantization, is used to generate the target CSI.

[0562] As one embodiment, part or all of the output of the first operation, after post-processing, is used to generate the target CSI.

[0563] As one embodiment, part or all of the output of the first operation, after truncation and / or quantization, is used to generate the target CSI.

[0564] As one embodiment, the target CSI indicates at least one resource in the first set of resources.

[0565] As one embodiment, the first resource set comprises at least one RS resource; the target CSI indicating at least one resource in the first resource set comprises: the target CSI indicating at least one RS resource in the first resource set.

[0566] As one embodiment, the first resource set comprises at least one beam; the target CSI indicating at least one resource in the first resource set comprises: the target CSI indicating at least one beam in the first resource set.

[0567] As one embodiment, the first resource set comprises one or more beams; the target CSI indicating at least one resource in the first resource set comprises: the target CSI indicating at least one beam in the first resource set.

[0568] As one embodiment, the first resource set comprises one or more vectors; the target CSI indicating at least one resource in the first resource set comprises: the target CSI indicating at least one vector in the first resource set.

[0569] As one embodiment, the first resource set comprises one or more matrices; the target CSI indicating at least one resource in the first resource set comprises: the target CSI indicating at least one matrix in the first resource set.

[0570] As one embodiment, the first resource set comprises one or more DFT vectors; the target CSI indicating at least one resource in the first resource set comprises: the target CSI indicating at least one DFT vector in the first resource set.

[0571] As one embodiment, the first resource set comprises one or more codebooks; the target CSI indicating at least one resource in the first resource set comprises: the target CSI indicating at least one codebook in the first resource set.

[0572] As one embodiment, the first resource set comprises one or more antenna ports; the target CSI indicating at least one resource in the first resource set comprises: the target CSI indicating at least one antenna port in the first resource set.

[0573] As one embodiment, the first operation is based on measurement of the first resource set for spatial beam prediction for the second resource set.

[0574] As one embodiment, the above method has the benefits of reducing RS overhead and reducing feedback delay.

[0575] As one embodiment, the first operation is based on measurements of the first set of resources for channel information prediction for the second set of resources.

[0576] As one embodiment, the channel information in this disclosure includes beam information.

[0577] As one embodiment, the first operation is based on historic measurements of the first set of resources for temporal beam prediction for the second set of resources.

[0578] As one embodiment, the benefits of the above method include reduced beam feedback delay, improved real-time beam acquisition.

[0579] As one embodiment, the first operation is based on historic measurements of the first set of resources for temporal channel information prediction for the second set of resources.

[0580] As one embodiment, the benefits of the above method include reduced channel information feedback delay, improved real-time channel information acquisition.

[0581] As one embodiment, the input of the first operation further includes the second set of resources.

[0582] As one embodiment, the first operation is associated to a first type of identity.

[0583] As one embodiment, the first operation is associated to a first type of identity, and the target identity is a first type of identity.

[0584] As one embodiment, the target CSI reporting configuration indicates a first type of identity, and the first operation is associated to the first type of identity indicated by the target CSI reporting configuration.

[0585] Embodiment 11

[0586] Embodiment 11 illustrates a schematic diagram of a manner of generating a target CSI according to an embodiment of the present application being associated to a first type of identification; as shown in FIG. 11. In Embodiment 11, the target CSI reporting configuration indicates a first resource set, the first resource set being used for at least one of channel measurement or interference measurement of the target CSI, the first resource set comprising one or more RS resources; the manner of generating the target CSI comprises a first operation performed by the first node or a receiver of the target CSI reporting configuration, an input of the first operation being dependent on measurement based on the first resource set, the target CSI being dependent on an output of the first operation; the manner of generating the target CSI being associated to the first type of identification comprises: the first operation being associated to the first type of identification.

[0587] As an embodiment, the first type of identification is a non-negative integer.

[0588] As an embodiment, the first type of identification is a string.

[0589] As an embodiment, the first operation is identified by the first type of identification.

[0590] As an embodiment, an AI model used by the first operation is identified by the first type of identification.

[0591] As an embodiment, an AI entity to which the first operation belongs is identified by the first type of identification.

[0592] As an embodiment, an AI function to which the first operation belongs is identified by the first type of identification.

[0593] As an embodiment, an AI entity or an AI function to which the first operation belongs is identified by the first type of identification.

[0594] As an embodiment, a benefit of the above method comprises: identifying an AI entity or a function by the first type of identification, simplifying design and unifying understanding of different AI entities or functions among multiple nodes.

[0595] As an embodiment, an AI function performing the first operation is identified by the first type of identification.

[0596] As an embodiment, an AI entity performing the first operation is identified by the first type of identification.

[0597] As an embodiment, an AI entity or an AI function performing the first operation is identified by the first type of identification.

[0598] As an embodiment, the first type of identification is a model identification.

[0599] As an embodiment, the first type of identification is used to identify an AI model.

[0600] As an embodiment, the first type of identification is used by the first node to determine an AI model.

[0601] As an embodiment, the first type of identification is used by the first node to determine an AI model employed by the first operation.

[0602] As an embodiment, the benefit of the above method includes that the identification of an AI model / entity / function through the first type of identification simplifies the design and unifies the understanding of different AI entities / functions among multiple nodes.

[0603] As an embodiment, the first type of identification is used to identify or indicate a first set of resources, measurements on the first set of resources are used to obtain a training dataset for the first operation.

[0604] As an embodiment, the first type of identification is used to identify configuration information of a first set of resources, measurements on the first set of resources are used to obtain a training dataset for the first operation.

[0605] As an embodiment, the training for the first operation is identified by the first type of identification.

[0606] As an embodiment, the dataset for the training of the first operation is identified by the first type of identification.

[0607] As an embodiment, the benefit of the above method includes that the identification of an AI training or AI training dataset identifies the inference generated by this AI training or AI training dataset, consensus is established among different AI functions, and the design is further simplified.

[0608] As an embodiment, the target CSI reporting configuration indicates the first operation by indicating the first type of identification.

[0609] As an embodiment, the target CSI reporting configuration indicates the use of an AI model by indicating the first type of identification.

[0610] As an embodiment, the target CSI reporting configuration obtains the input of an AI entity / function / inference associated with the first type of identification by indicating the first type of identification.

[0611] As an embodiment, the first operation is spatial beam prediction for a second set of resources based on measurements on the first set of resources, the second set of resources depends on the first type of identification.

[0612] As an embodiment, benefits of the above method include: reduced RS overhead, reduced feedback latency.

[0613] As an embodiment, the first operation is based on a measurement of the first set of resources for a channel information prediction for a second set of resources, the second set of resources relying on the first type of indication.

[0614] As an embodiment, the channel information in this application includes beam information.

[0615] As an embodiment, the first operation is based on a historic measurement of the first set of resources for a temporal beam prediction for a second set of resources, the second set of resources relying on the first type of indication.

[0616] As an embodiment, benefits of the above method include: reduced beam feedback latency, improved real-time beam acquisition.

[0617] As an embodiment, the first operation is based on a historic measurement of the first set of resources for a temporal channel information prediction for a second set of resources, the second set of resources relying on the first type of indication.

[0618] As an embodiment, benefits of the above method include: reduced channel information feedback latency, improved real-time channel information acquisition.

[0619] As an embodiment, the first type of indication is used to indicate the second set of resources.

[0620] Embodiment 12

[0621] Embodiment 12 illustrates a schematic diagram of the first operation according to another embodiment of this application; as shown in FIG. 12. In embodiment 12, the first operation is based on training or based on AI.

[0622] As an embodiment, the first operation is based on training.

[0623] As an embodiment, the first operation is based on AI.

[0624] As an embodiment, the measurement based on the first set of resources includes pre-compression channel information, and the output of the first operation includes post-compression channel information.

[0625] As an embodiment, benefits of the above method include: applicable to channel compression, reduced feedback overhead.

[0626] As one embodiment, the measurement based on the first set of resources comprises measurement obtained channel information, and the output of the first operation comprises predicted channel information.

[0627] As one embodiment, the measurement based on the first set of resources comprises measurement obtained channel information, and the output of the first operation comprises spatial beam prediction.

[0628] As one embodiment, the measurement based on the first set of resources comprises measurement obtained channel information, and the output of the first operation comprises spatial beam prediction for a second set of resources.

[0629] As one embodiment, the resources in the second set of resources comprise at least one of antenna ports, time-frequency resources, time-frequency code resources, beams, RS resources, vectors, or matrices.

[0630] As one embodiment, the benefits of the above method comprise reduced RS overhead and reduced feedback delay.

[0631] As one embodiment, the channel information in the present application comprises beam information.

[0632] As one embodiment, the measurement based on the first set of resources comprises current channel information, and the output of the first operation comprises predicted channel information.

[0633] As one embodiment, the measurement based on the first set of resources comprises historic channel information, and the output of the first operation comprises predicted channel information.

[0634] As one embodiment, the measurement based on the first set of resources comprises historic channel information, and the output of the first operation comprises Temporal beam prediction.

[0635] As one embodiment, the measurement based on the first set of resources comprises historic channel information, and the output of the first operation comprises Temporal beam prediction for the second set of resources.

[0636] As one embodiment, the benefits of the above method comprise reduced channel information feedback delay and improved real-time channel information acquisition.

[0637] As one embodiment, the measurement based on the first set of resources comprises current channel information, and the output of the first operation comprises channel information after a period of time.

[0638] As one embodiment, the measurement based on the first set of resources comprises current channel information, and the output of the first operation comprises future channel information.

[0639] As one embodiment, the measurement based on the first set of resources comprises historical channel information, and the output of the first operation comprises future channel information.

[0640] As one embodiment, the benefits of the above method comprise: improved CSI accuracy and timeliness, and reduced RS overhead.

[0641] As one embodiment, the measurement based on the first set of resources comprises incomplete channel information, and the output of the first operation comprises complete channel information.

[0642] As one embodiment, the benefits of the above method comprise: reduced RS overhead, and improved CSI accuracy and completeness.

[0643] As one embodiment, the measurement based on the first set of resources comprises channel information of P1 antenna ports, and the output of the first operation comprises channel information of P2 antenna ports, the P1 and the P2 are positive integers greater than 1 respectively, and the P1 is less than the P2.

[0644] As one sub-embodiment of the above embodiment, the P1 antenna ports are a proper subset of the P2 antenna ports.

[0645] As one sub-embodiment of the above embodiment, the P2 antenna ports belong to the second set of resources.

[0646] As one embodiment, the measurement based on the first set of resources comprises channel information of first frequency domain resources, and the output of the first operation comprises channel information of second frequency domain resources, the second frequency domain resources comprising frequency domain resources not belonging to the first frequency domain resources.

[0647] As one sub-embodiment of the above embodiment, the first frequency domain resources are a proper subset of the second frequency domain resources.

[0648] As one embodiment, the first operation is based on training.

[0649] As one embodiment, the first operation is obtained through training.

[0650] As one embodiment, the training for obtaining the first operation is performed by the first node.

[0651] As one embodiment, the training for obtaining the first operation is performed by a sender of the target CSI reporting configuration.

[0652] As one embodiment, the training for obtaining the first operation is performed by a sender of the first set of resources.

[0653] As one embodiment, the training for obtaining the first operation is performed by an MDA function (Management Data Analytics Function).

[0654] As one embodiment, the training for obtaining the first operation is performed by an MDAS (Management Data Analytics Service) producer.

[0655] As one embodiment, the training for obtaining the first operation is performed by a NWDAF (Network Data Analytics Function).

[0656] As one embodiment, the training for obtaining the first operation is performed by a core network.

[0657] As one embodiment, the training for obtaining the first operation is performed by an AI training producer.

[0658] As one embodiment, a performer of the training for obtaining the first operation is different from a sender of the target CSI reporting configuration.

[0659] As one embodiment, a performer of the training for obtaining the first operation is different from a sender of the first set of resources.

[0660] As one embodiment, the first operation includes inference.

[0661] As one embodiment, the first operation includes AI (Artificial Intelligence).

[0662] As one embodiment, the first operation is inference.

[0663] As one embodiment, the first operation is AI inference.

[0664] As one embodiment, the first operation includes AI inference for CSI.

[0665] As one embodiment, the first operation includes AI inference for beam prediction.

[0666] As one embodiment, benefits of the above method include improved performance of measurement and reporting of CSI (including beams), including more accurate CSI, lower reference signal overhead and reporting overhead, thereby improving overall system performance.

[0667] As one embodiment, the first operation is AI inference for CSI.

[0668] As one embodiment, the first operation includes AI inference for at least one of beam prediction, CSI prediction, CSI estimation, or CSI compression.

[0669] As one embodiment, the CSI prediction includes beam prediction.

[0670] As one embodiment, benefits of the above method include more accurate and complete CSI, lower reference signal overhead, improved real-time performance of CSI.

[0671] As one embodiment, the first operation is based on an AI model.

[0672] As one embodiment, the first operation includes an AI entity.

[0673] As one embodiment, the first operation includes an AI inference entity.

[0674] As one embodiment, the first operation includes an AI entity for inference.

[0675] As one embodiment, the first operation includes a portion of an AI entity.

[0676] As one embodiment, the first operation includes a portion of an AI entity for inference.

[0677] As one embodiment, the first operation includes an AI entity for CSI.

[0678] As one embodiment, the first operation includes an AI entity for beam prediction.

[0679] As one embodiment, the first operation includes an AI entity for CSI prediction, estimation, or compression.

[0680] As one embodiment, the first operation includes inference of an AI entity for CSI.

[0681] As one embodiment, the first operation includes inference of an AI entity for CSI prediction, estimation, or compression.

[0682] As one embodiment, the first operation is performed by an AI entity.

[0683] As one embodiment, the first operation is performed by an AI entity deployed at the first node.

[0684] As one embodiment, the first operation is performed by an AI function.

[0685] As one embodiment, the first operation is performed by an AI function deployed at the first node.

[0686] As one embodiment, the AI function comprises an AI inference function.

[0687] As one embodiment, the AI function comprises an AI training function.

[0688] As one embodiment, the AI function comprises an AI management function.

[0689] As one embodiment, the first operation is performed by a physical layer of the first node.

[0690] As one embodiment, the first operation is performed by a higher layer of the first node.

[0691] As one embodiment, the first operation is a deployment.

[0692] As one embodiment, the first operation is obtained by a load.

[0693] As one embodiment, the first operation is obtained by a load from a serving cell of the first node.

[0694] As one embodiment, the first operation is obtained by a load from a maintaining base station of a serving cell of the first node.

[0695] As one embodiment, the first operation is obtained by a load from a core network.

[0696] As one embodiment, the first operation is based on artificial intelligence or machine learning.

[0697] As one embodiment, the first operation is based on a neural network.

[0698] As one embodiment, the first operation comprises neural network based CSI compression.

[0699] As one embodiment, the first operation comprises an encoder for neural network based CSI compression.

[0700] As one embodiment, the first operation comprises CNN based CSI compression.

[0701] As one embodiment, the first operation comprises an encoder for CNN based CSI compression.

[0702] As one embodiment, the output of the first operation is non-codebook based.

[0703] As one embodiment, the output of the first operation is neither CSI defined in 3GPP Rel-18 nor CSI defined in a version before 3GPP Rel-18.

[0704] As one embodiment, the output of the first operation is based on artificial intelligence or machine learning.

[0705] As one embodiment, the output of the first operation is based on neural network.

[0706] As one embodiment, the output of the first operation is based on CNN.

[0707] As one embodiment, the output of the first operation comprises CSI.

[0708] As one embodiment, the output of the first operation comprises predicted beam information.

[0709] As one embodiment, the output of the first operation comprises beam indication and RSRP.

[0710] As one embodiment, the output of the first operation comprises RS resource indication and RSRP.

[0711] As one embodiment, the output of the first operation comprises resource indication and RSRP.

[0712] As one embodiment, the output of the first operation comprises one or more of beam indication, CRI (CSI-RS Resource Indicator), SS / PBCH Block Resource indicator (SSBRI), or RSRP (reference signal received power).

[0713] As one embodiment, the output of the first operation includes one or more of PMI, CRI, CQI, RI, LI, SSBRI, RSRP, SINR, capability index, and TDCP.

[0714] As one embodiment, the output of the first operation includes channel impulse response.

[0715] As one embodiment, the output of the first operation includes small scale properties.

[0716] As one embodiment, the output of the first operation includes one or more of delay spread, Doppler spread, Doppler shift, average delay, and average gain.

[0717] As one embodiment, the output of the first operation includes channel matrix.

[0718] As one embodiment, the output of the first operation includes target CSI.

[0719] As one embodiment, the target CSI includes predicted or estimated CSI.

[0720] As one embodiment, the target CSI includes predicted beam information.

[0721] As one embodiment, in the above method, the first operation is used for beam prediction, CSI prediction or estimation to reduce RS overhead and / or improve CSI accuracy / integrity.

[0722] As one embodiment, the first node is a consumer.

[0723] As one embodiment, the first node is a consumer of AI function.

[0724] As one embodiment, the first node is a consumer of AI inference.

[0725] As one embodiment, the first node is a consumer of AI training.

[0726] As one embodiment, the first node is a MnS (Management Service) consumer.

[0727] As one embodiment, the first node is a producer of AI inference.

[0728] As one embodiment, the first node is a producer of AI training.

[0729] As one embodiment, the first operation comprises pre-processing.

[0730] As one embodiment, the pre-processing comprises a DFT (Discrete Fourier Transform).

[0731] As one embodiment, the pre-processing comprises one or more of matrix decomposition, matrix transformation, and projection.

[0732] As one embodiment, the pre-processing comprises one or more of quantization, spatial-to-angle domain transformation, angle-to-spatial domain transformation, frequency-to-time domain transformation, and time-to-frequency domain transformation.

[0733] As one embodiment, the pre-processing comprises truncation and / or padding.

[0734] As one embodiment, the pre-processing comprises mapping.

[0735] As one embodiment, the pre-processing comprises mapping to a vector.

[0736] As one embodiment, the pre-processing comprises a label.

[0737] As one embodiment, the label refers to labeling with a label.

[0738] As one embodiment, the first operation comprises post-processing.

[0739] As one embodiment, the post-processing comprises a DFT.

[0740] As one embodiment, the post-processing comprises quantization.

[0741] As one embodiment, the post-processing comprises one or more of angle-to-spatial domain transformation, spatial-to-angle domain transformation, time-to-frequency domain transformation, and frequency-to-time domain transformation.

[0742] As one embodiment, the post-processing comprises truncation and / or padding.

[0743] As one embodiment, the first operation comprises one or more of convolution, pooling, concatenation, and activation.

[0744] As one embodiment, the first operation comprises a fully connected layer.

[0745] As one embodiment, the first operation comprises a pooling layer.

[0746] As one embodiment, the first operation comprises at least one convolution layer.

[0747] As an embodiment, the first operation comprises at least one encoding layer.

[0748] As an embodiment, an encoding layer comprises at least one convolution layer and one pooling layer.

[0749] As an embodiment, in a convolution layer, at least one convolution kernel is used to convolve an input to generate a corresponding feature map, at least one feature map output by the convolution layer is reshaped into a vector input to a fully connected layer; the fully connected layer converts the one vector into an output.

[0750] As an embodiment, part or all of the convolution kernel size, the number of convolution layers, the convolution step, the pooling kernel size, the pooling kernel step, the pooling function, the activation function, and the number of feature maps of the first operation are obtained through training.

[0751] As an embodiment, part or all of the convolution kernel, the pooling kernel, the pooling function, the activation function, the parameters of the pooling function, and the parameters of the activation function of the first operation are obtained through training.

[0752] Embodiment 13

[0753] Embodiment 13 illustrates a schematic diagram of the association between the generation mode of the target CSI and the first type of identification according to another embodiment of the present application; as shown in FIG. 13. In embodiment 13, the association between the generation mode of the target CSI and the first type of identification comprises: the target CSI reporting configuration indicates the first type of identification, and the first type of identification indicated by the target CSI reporting configuration is the first type of identification associated with the generation mode of the target CSI.

[0754] As an embodiment, the target CSI reporting configuration explicitly indicates the first type of identification.

[0755] As an embodiment, the target CSI reporting configuration implicitly indicates the first type of identification.

[0756] As an embodiment, the target CSI reporting configuration comprises a reference domain, and the reference domain included in the target CSI reporting configuration indicates the first type of identification.

[0757] As an embodiment, the target CSI reporting configuration indicates the first operation by indicating the first type of identification.

[0758] As an embodiment, the target CSI reporting configuration indicates the use of the AI model adopted by the first operation by indicating the first type of identification.

[0759] As an embodiment, the target CSI reporting configuration is obtained by indicating the first type of identity, and an input of an AI entity / function / inference associated with the first type of identity is obtained by the first type of identity.

[0760] Embodiment 14

[0761] Embodiment 14 illustrates a schematic diagram of a target CSI generation manner associated with a first type of identity according to yet another embodiment of the present application; as shown in FIG. 14. In embodiment 14, the target CSI generation manner associated with the first type of identity comprises: the target CSI generation manner uses an AI model identified by the first type of identity, or the target CSI is generated by an AI entity identified by the first type of identity, or the target CSI is used for an AI function identified by the first type of identity.

[0762] As an embodiment, the target CSI generation manner uses an AI model identified by the first type of identity.

[0763] As an embodiment, the target CSI is generated by an AI entity identified by the first type of identity.

[0764] As an embodiment, an AI model used by the first operation is identified by the first type of identity, and the target CSI depends on an output of the first operation.

[0765] As an embodiment, an AI entity or an AI function to which the first operation belongs is identified by the first type of identity, and the target CSI depends on an output of the first operation.

[0766] As an embodiment, an AI entity or an AI function performing the first operation is identified by the first type of identity, and the target CSI depends on an output of the first operation.

[0767] As an embodiment, the target CSI is used for an AI function identified by the first type of identity.

[0768] As an embodiment, the target CSI is used to obtain a training data set of an AI function identified by the first type of identity.

[0769] Embodiment 15

[0770] Embodiment 15 illustrates a schematic diagram of a first higher layer parameter according to an embodiment of the present application; as shown in FIG. 15. In embodiment 15, the first receiver receives a first higher layer parameter; wherein the first higher layer parameter indicates the first set of cells.

[0771] As an embodiment, the first higher layer parameter is carried by a higher layer signaling.

[0772] As an embodiment, the first higher layer parameter is carried by a Radio Resource Control (RRC) signaling.

[0773] As an embodiment, the first higher layer parameter is carried by one RRC Information Element (IE).

[0774] As an embodiment, the first higher layer parameter is carried by at least one RRC IE.

[0775] As an embodiment, the first higher layer parameter comprises information in one or more fields in at least one RRC IE.

[0776] As an embodiment, the first higher layer parameter comprises information in one or more fields in each of a plurality of RRC IEs.

[0777] As an embodiment, the first higher layer parameter is one RRC IE.

[0778] As an embodiment, the first higher layer parameter comprises a MAC CE.

[0779] As an embodiment, the first higher layer parameter comprises sCellToAddModList or sCellToAddModListSCG.

[0780] As an embodiment, the first higher layer parameter comprises a name including: Cell.

[0781] As an embodiment, the first higher layer parameter comprises a name including: List.

[0782] As an embodiment, the first higher layer parameter comprises a name including: CellToAddModList.

[0783] As an embodiment, the first higher layer parameter comprises a name including: Set of CellsToAddModList.

[0784] As an embodiment, the first higher layer parameter indicates an index of each cell in the first set of cells.

[0785] As one embodiment, the first higher layer parameter indicates an index of each cell in the first set of cells, the index indicated by the first higher layer parameter is SCellIndex or ServCellIndex.

[0786] As one embodiment, the first higher layer parameter indicates a plurality of sets of cells, the first set of cells is one set of cells among the plurality of sets of cells indicated by the first higher layer parameter, any set of cells among the plurality of sets of cells includes at least one serving cell.

[0787] As one embodiment, each cell in the first set of cells is one serving cell of the first node.

[0788] As one embodiment, the first node has performed secondary serving cell addition for each cell in the first set of cells.

[0789] As one embodiment, the first node's latest received sCellToAddModList or sCellToAddModListSCG includes each cell in the first set of cells.

[0790] As one embodiment, for each cell in the first set of cells, the first node is assigned SCellIndex or ServCellIndex for this cell.

[0791] As one embodiment, an RRC connection has been established between the first node and each cell in the first set of cells.

[0792] As one embodiment, the first node's C-RNTI is assigned by one cell in the first set of cells.

[0793] As one embodiment, the first node's C-RNTI is assigned by one cell not belonging to the first set of cells.

[0794] As one embodiment, the first set of cells includes the first node's SpCell (Special Cell).

[0795] As one embodiment, the first set of cells includes the first node's SCell (Secondary Cell).

[0796] As one embodiment, any cell in the first set of cells is the first node's SpCell or SCell.

[0797] As one embodiment, the definition of serving cell refers to 3GPP TS 38.331.

[0798] As one embodiment, the first set of cells belong to the same cell group.

[0799] As one embodiment, the first set of cells all belong to MCG (Master Cell Group) or all belong to SCG (Secondary Cell Group).

[0800] As one embodiment, the first set of cells belong to the same PUCCH (Physical Uplink Control Channel) group.

[0801] As one embodiment, a PUCCH group includes a set of cells whose PUCCH signaling is associated with the PUCCH of a SpCell (Special Cell) or a PUCCH SCell (Secondary Cell); a PUCCH SCell is an SCell configured with PUCCH.

[0802] As one embodiment, a PUCCH group includes a set of cells whose PUCCH signaling is associated with the PUCCH of the same cell.

[0803] As one embodiment, the cells in the first set of cells have the same numerology.

[0804] As one embodiment, the cells in the first set of cells have the same subcarrier spacing configuration.

[0805] Embodiment 16

[0806] Embodiment 16 illustrates a schematic diagram of a second information block according to one embodiment of the present application; as shown in FIG. 16. In embodiment 16, the first processor transmits a second information block; wherein the second information block indicates that the generation mode of CSI on multiple serving cells is associated to the same first type identifier.

[0807] As one embodiment, the second information block is carried by RRC (Radio Resource Control) signaling.

[0808] As one embodiment, the second information block is carried by an RRC IE (Information Element).

[0809] As one embodiment, the second information block is carried by at least one RRC IE.

[0810] As one embodiment, the second information block comprises information in one or more fields in at least one RRC IE.

[0811] As one embodiment, the second information block comprises information in one or more fields in each of a plurality of RRC IEs.

[0812] As one embodiment, the second information block is one RRC IE.

[0813] As one embodiment, the second information block comprises IE UECapabilityInformation.

[0814] As one embodiment, the second information block is IE UECapabilityInformation.

[0815] As one embodiment, the second information block comprises information in one or more fields in IE UECapabilityInformation.

[0816] As one embodiment, the second information block is carried by physical layer signaling.

[0817] As one embodiment, the second information block comprises one MAC CE.

[0818] As one embodiment, the second information block indicates that the manner of CSI generation on the first set of cells is associated to the same first type identifier.

[0819] As one embodiment, the second information block indicates that the manner of CSI generation on the set of cells where the first cell is located is associated to the same first type identifier.

[0820] As one embodiment, the second information block indicating that the manner of CSI generation on a plurality of serving cells is associated to the same first type identifier comprises: the second information block indicating that the manner of respective at least one CSI on a plurality of serving cells is associated to the same first type identifier.

[0821] As one embodiment, the second information block indicating that the manner of CSI generation on a plurality of serving cells is associated to the same first type identifier comprises: the second information block indicating that the sender of the target CSI reporting configuration can configure the manner of CSI generation on a plurality of serving cells to be associated to the same first type identifier.

[0822] As one embodiment, the second information block belongs to capability reporting of the first node.

[0823] Embodiment 17

[0824] Embodiment 17 illustrates a schematic diagram of a first operation according to another embodiment of the application; as shown in FIG. 17. In embodiment 17, the first operation comprises K1 sub-operations, where K1 is a positive integer not greater than 1. In FIG. 17, the K1 sub-operations are denoted as sub-operation #0, …, sub-operation #(K1-1), respectively.

[0825] As an embodiment, each of the K1 sub-operations is based on training.

[0826] As an embodiment, at least one of the K1 sub-operations is based on training.

[0827] As an embodiment, each of the K1 sub-operations based on training is based on training performed by a same performer.

[0828] As an embodiment, two of the K1 sub-operations are based on training performed by different performers.

[0829] As an embodiment, at least one of the K1 sub-operations is deployment- requiring.

[0830] As an embodiment, at least one of the K1 sub-operations is loading- requiring.

[0831] As an embodiment, all of the K1 sub-operations that are loading-requiring are loaded from a same producer.

[0832] As an embodiment, two of the K1 sub-operations that are loading-requiring are loaded from different producers.

[0833] As an embodiment, at least one of the K1 sub-operations is not based on training.

[0834] As an embodiment, at least one of the K1 sub-operations is based on a codebook for precoding defined by a 3GPP R18 or a version before 3GPP R18.

[0835] As an embodiment, one or more of the K1 sub-operations is based on AI.

[0836] As an embodiment, one or more of the K1 sub-operations comprises inference.

[0837] As one embodiment, one or more of the K1 sub-operations includes AI inference.

[0838] As one embodiment, one or more of the K1 sub-operations includes AI inference for CSI.

[0839] As one embodiment, the AI includes ML.

[0840] As one embodiment, one or more of the K1 sub-operations includes pre-processing.

[0841] As one embodiment, one or more of the K1 sub-operations includes post-processing.

[0842] As one embodiment, two of the K1 sub-operations are in series, such as all sub-operations in (a) of FIG. 17, sub-operation #2 to sub-operation #(K1-1) in (b) of FIG. 17, and sub-operation #0 to sub-operation #(K1-4) in (c) of FIG. 17.

[0843] As one embodiment, two sub-operations being in series means that the output of one of the two sub-operations is used as the input of the other of the two sub-operations.

[0844] As one embodiment, two of the K1 sub-operations are in parallel, such as sub-operation #0 and sub-operation #1 in (b) of FIG. 17, sub-operation #(K1-3) and sub-operation #(K1-2) in (c) of FIG. 17.

[0845] As one embodiment, two sub-operations being in parallel means that the outputs of the two sub-operations are collectively used as the input of another sub-operation.

[0846] As one embodiment, the K1 sub-operations include one or more of convolution, pooling, concatenation, or activation.

[0847] As one embodiment, one of the K1 sub-operations includes a fully connected layer.

[0848] As one embodiment, one of the K1 sub-operations includes a pooling layer.

[0849] As one embodiment, one of the K1 sub-operations includes at least one convolution layer.

[0850] As an example, one of the K1 sub-operations includes at least one encoding layer.

[0851] As an example, two of the K1 sub-operations respectively include a fully connected layer and at least one encoding layer.

[0852] As an example, one encoding layer includes at least one convolutional layer and one pooling layer.

[0853] Embodiment 18

[0854] Embodiment 18 illustrates a schematic diagram of a first node deploying a first operation according to an embodiment of the present application; as shown in FIG. 18. In embodiment 18, the first processor deploys the first operation.

[0855] As an example, the deployment of the first operation is earlier than the reception of the target CSI reporting configuration.

[0856] As an example, the deployment of the first operation is later than the reception of the target CSI reporting configuration.

[0857] As an example, the deployment includes obtaining the first operation.

[0858] As an example, the deployment includes obtaining an AI entity.

[0859] As an example, the deployment includes obtaining an AI entity that executes the first operation.

[0860] As an example, the deployment includes obtaining an AI entity that includes an AI function that executes the first operation.

[0861] As an example, the deployment includes loading the first operation.

[0862] As an example, the deployment includes making a request to load the first operation.

[0863] As an example, the request in FIG. 18 is a request made by the first node to load the first operation.

[0864] As an example, the response in FIG. 18 is a response to the request made by the first node to load the first operation.

[0865] As an example, the first node obtains the first operation through the response in FIG. 18.

[0866] As an example, the first operation is obtained from loading at a serving cell of the first node.

[0867] As one embodiment, the first operation is obtained from a serving cell of the first node.

[0868] As one embodiment, the first operation is obtained from a core network.

[0869] As one embodiment, the first operation is obtained from a first producer.

[0870] As one embodiment, the first producer provides the first operation to the first node by the response in FIG. 18.

[0871] As one embodiment, the deployment is done by an AI function.

[0872] As one embodiment, the deployment is done by an AI function deployed at the first node.

[0873] As one embodiment, the deployment is done by an AI deployment function.

[0874] As one embodiment, the deployment is done by an AI deployment function deployed at the first node.

[0875] As one embodiment, the deployment is done by an AI inference function.

[0876] As one embodiment, the deployment is done by an AI inference function deployed at the first node.

[0877] As one embodiment, the deployment is done by an AI entity.

[0878] As one embodiment, the deployment is done by an AI entity deployed at the first node.

[0879] As one embodiment, the deployment is done by an AI entity with a deployment function.

[0880] As one embodiment, the deployment is done by an AI entity with a deployment function deployed at the first node.

[0881] As one embodiment, the deployment is done by an AI entity with an inference function.

[0882] As one embodiment, the deploying is done by an AI entity with inference functionality deployed at the first node.

[0883] As one embodiment, the deploying includes obtaining the first operation from a first producer.

[0884] As one embodiment, the deploying includes making a request to a first producer to load the first operation.

[0885] As one embodiment, the deploying includes loading the first operation from a first producer.

[0886] As one embodiment, the first producer generates and provides an AI entity.

[0887] As one embodiment, the first producer generates and provides an AI functionality.

[0888] As one embodiment, the first producer is a producer of the first operation.

[0889] As one embodiment, the first producer includes an AI entity producer.

[0890] As one embodiment, the first producer includes an AI functionality producer.

[0891] As one embodiment, the first producer includes an AI deployment producer.

[0892] As one embodiment, the first producer includes an AI load producer.

[0893] As one embodiment, the first producer includes an AI training producer.

[0894] As one embodiment, the first producer includes an AI inference producer.

[0895] As one embodiment, the first producer includes a producer of deployment of an AI entity.

[0896] As one embodiment, the first producer includes a producer of loading of an AI entity.

[0897] As one embodiment, the first producer includes a MnS (Management Service) producer.

[0898] As one embodiment, the sender of the target CSI reporting configuration is the first producer.

[0899] As one embodiment, the sender of the target CSI reporting configuration is different from the first producer.

[0900] As one embodiment, the training for obtaining the first operation is performed by the first producer.

[0901] As one embodiment, the performer of the training for obtaining the first operation is different from the first producer.

[0902] As one embodiment, the AI includes ML (Machine Learning).

[0903] Embodiment 19

[0904] Embodiment 19 illustrates a schematic diagram of an artificial intelligence or machine learning based processing system according to one embodiment of the present application; as shown in FIG. 19. In (a) of FIG. 19, it includes a third processor, a fourth processor and a fifth processor. In (b) of FIG. 19, it includes a third processor, a fourth processor, a fifth processor and a sixth processor.

[0905] In embodiment 19(a), the third processor sends a first data set to the fourth processor, and sends a second data set to the fifth processor; the fourth processor generates a target first type parameter set according to the first data set, and sends the generated target first type parameter set to the fifth processor; the fifth processor processes the second data set using the target first type parameter set to obtain a first type output. In (a) of FIG. 19, the first type feedback is optional.

[0906] In embodiment 19(b), the third processor sends a first data set to the fourth processor, and sends a second data set to the fifth processor; the fourth processor generates a target first type parameter set according to the first data set, and sends the generated target first type parameter set to the fifth processor; the fifth processor processes the second data set using the target first type parameter set to obtain a first type output, and sends the first type output to the sixth processor. In (b) of FIG. 19, the first type feedback and the second type feedback are optional.

[0907] As one embodiment, in (a) of FIG. 19, the fifth processor sends the first type output to the second node in the present application.

[0908] As one embodiment, in (a) of FIG. 19, a single side AI model is used for beam prediction or channel information prediction, and the fifth processor performs the first operation for beam prediction or channel information prediction.

[0909] As one embodiment, the AI comprises ML (Machine Learning) inference.

[0910] As one embodiment, the fifth processor performs the first operation.

[0911] As one embodiment, the fifth processor sends first type feedback to the fourth processor, the first type feedback is used to trigger re-computation or update of the target first type parameter group.

[0912] As one embodiment, the sixth processor sends second type feedback to the third processor, the second type feedback is used to generate the first data set or the second data set, or the second type feedback is used to trigger sending of the first data set or sending of the second data set.

[0913] As one embodiment, the third processor generates the first data set and the second data set according to measurement of first type wireless signals, the first type wireless signals comprise downlink RS.

[0914] As one embodiment, the fifth processor belongs to the first node, and the sixth processor belongs to the second node.

[0915] As one embodiment, the target CSI belongs to the first type output.

[0916] As one embodiment, the second data set comprises the input of the first operation.

[0917] As one embodiment, the second data set comprises information obtained based on the first configuration and the M1 configurations.

[0918] As one embodiment, the first data set comprises Training Data.

[0919] As one embodiment, the fourth processor belongs to a producer of the first operation.

[0920] As one embodiment, the fourth processor comprises an AI training producer.

[0921] As one embodiment, the fourth processor comprises an AI training function.

[0922] As one embodiment, the fourth processor is used for Model Training, and a trained model is described by the target first type parameter group.

[0923] As an embodiment, the fourth processor belongs to the first node.

[0924] The above embodiment avoids passing the first data set to the second node.

[0925] As an embodiment, the fourth processor belongs to the second node.

[0926] The above embodiment supports joint training, optimizing system performance.

[0927] As an embodiment, the fourth processor belongs to the core network.

[0928] The above embodiment supports network-wide joint training, further optimizing system performance.

[0929] As an embodiment, the second data set includes inference data.

[0930] As an embodiment, the fifth processor includes an AI inference producer.

[0931] As an embodiment, the fifth processor includes an AI inference function.

[0932] As an embodiment, the fifth processor belongs to the first node.

[0933] As an embodiment, the fifth processor constructs a model according to the target first-type parameter set, and then inputs the second data set into the constructed model to obtain the first-type output.

[0934] As an embodiment, the first operation is described by the target first-type parameter set.

[0935] As an embodiment, the target first-type parameter set is used to construct the first operation.

[0936] As an embodiment, the fifth processor generates a recovery data set according to the first-type output, and the error of the recovery data set and the second data set is used to generate the first-type feedback.

[0937] As an embodiment, the first-type feedback is used to reflect the performance of the trained model; when the performance of the trained model cannot meet the requirements, the fourth processor can recalculate the target first-type parameter set.

[0938] As an embodiment, when the error is too large or the time of updating is too long, the performance of the trained model is considered to be unable to meet the requirements.

[0939] As an example, the target first-type parameter group includes one or more of a convolution kernel size, a convolution layer number, a convolution stride, a pooling kernel size, a pooling kernel stride, a pooling function, an activation function, or a feature map number.

[0940] As an example, the target first-type parameter group includes one or more of a convolution kernel, a pooling kernel, a pooling function, an activation function, a parameter of the pooling function, or a parameter of the activation function.

[0941] Embodiment 20

[0942] Embodiment 20 illustrates a schematic diagram based on artificial intelligence or machine learning according to an embodiment of the present application; as shown in FIG. 20. FIG. 20 includes a third operation, a fourth operation, a fifth operation, a sixth operation, and a seventh operation. In Embodiment 20, the third operation and the fourth operation belong to a first phase, the fifth operation belongs to a second phase, the sixth operation belongs to a third phase, and the seventh operation belongs to a fourth phase. In FIG. 20, the line with an arrow indicates the order of the flow.

[0943] 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.

[0944] As an example, the first phase includes a training phase, the second phase includes an emulation phase, the third phase includes a deployment phase, and the fourth phase includes an inference phase.

[0945] As an example, the first phase includes AI model training.

[0946] As an example, the first phase includes AI model training and AI testing.

[0947] As an example, the AI includes ML (Machine Learning) inference.

[0948] As an example, the AI model training includes initial training and re-training of one or a group of AI entities.

[0949] As one embodiment, the AI model training relies on training data.

[0950] As one embodiment, the AI model training includes AI entity validation.

[0951] As one embodiment, the AI entity validation is used to evaluate the performance of the AI entity.

[0952] As one embodiment, the AI entity validation relies on validation data.

[0953] As one embodiment, if the result of AI entity validation does not meet the expectation, the AI model will be retrained.

[0954] As one embodiment, the AI testing includes testing the validated AI entity to evaluate the performance of the trained AI model.

[0955] As one embodiment, if the result of AI testing meets the expectation, the AI entity proceeds to the next stage; otherwise, the AI model will be retrained.

[0956] As one embodiment, the AI testing relies on testing data.

[0957] As one embodiment, the second stage includes AI simulation, which is the inference of the AI entity in a simulation environment.

[0958] As one embodiment, the AI simulation is to evaluate the performance of the inference of the AI entity in a simulation environment before using the AI entity.

[0959] As one embodiment, the second stage is optional.

[0960] As one embodiment, the third stage includes AI entity loading, which is to obtain the trained AI entity to obtain the desired AI inference function.

[0961] As one embodiment, the third stage is optional.

[0962] As one embodiment, the third stage is no longer needed when the training function and the inference function are co-located.

[0963] As one embodiment, the fourth stage includes AI inference.

[0964] As one embodiment, the seventh operation includes the first operation.

[0965] Embodiment 21

[0966] Embodiment 21 illustrates a structural block diagram of a processing apparatus in a first node according to an embodiment of the present application; as shown in Figure 21. In Figure 21, the processing apparatus 2100 in the first node comprises a first receiver 2101 and a first processor 2102.

[0967] As one embodiment, the first node is a user equipment.

[0968] As one embodiment, the first node is a relay node device.

[0969] As one embodiment, the first receiver 2101 comprises at least one of {antenna 452, receiver 454, receive processor 456, multi-antenna receive processor 458, controller / processor 459, memory 460, data source 467} in Embodiment 4.

[0970] As one embodiment, the first processor 2102 comprises at least one of {antenna 452, receiver / transmitter 454, receive processor 456, transmit processor 468, multi-antenna receive processor 458, multi-antenna transmit processor 457, controller / processor 459, memory 460, data source 467} in Embodiment 4.

[0971] The first receiver 2101 receives a target CSI reporting configuration; the target CSI reporting configuration is used for configuring reporting of a target CSI on a target cell, and a generation manner of the target CSI is AI-based; receives a first information block, the first information block indicating a target identity.

[0972] The first processor 2102 transmits a target CSI.

[0973] In Embodiment 21, a generation manner of the target CSI is associated to a first type of identity; whether the first type of identity associated to the generation manner of the target CSI is updated to the target identity depends on whether the target cell belongs to a first cell set; only when the target cell belongs to the first cell set, the first type of identity associated to the generation manner of the target CSI is updated to the target identity; the first cell set comprises a plurality of serving cells, a first cell is one serving cell in the first cell set, and the first cell depends on the first information block; and the target cell is different from the first cell.

[0974] As one embodiment, the first information block is applied to each serving cell in the first cell set.

[0975] As one embodiment, the first information block indicates the first cell.

[0976] As an embodiment, the first cell is a serving cell where a physical channel carrying the first information block is located.

[0977] As an embodiment, the target CSI reporting configuration indicates a first resource set, the first resource set is used for at least one of channel measurement or interference measurement of the target CSI, the first resource set includes one or more RS resources on the target cell; the target CSI indicates at least one resource in a second resource set, the second resource set includes resources not belonging to the first resource set.

[0978] As an embodiment, the target CSI reporting configuration indicates a first resource set, the first resource set is used for at least one of channel measurement or interference measurement of the target CSI, the first resource set includes one or more RS resources; the generation manner of the target CSI includes that a first node or a receiver of the target CSI reporting configuration performs a first operation, an input of the first operation depends on measurement based on the first resource set, and the target CSI depends on an output of the first operation.

[0979] As an embodiment, the generation manner of the target CSI being associated to a first type identifier includes that the first operation is associated to the first type identifier.

[0980] As an embodiment, the generation manner of the target CSI being associated to a first type identifier includes that the target CSI reporting configuration indicates a first type identifier, and the first type identifier indicated by the target CSI reporting configuration is the first type identifier to which the generation manner of the target CSI is associated.

[0981] As an embodiment, the generation manner of the target CSI being associated to a first type identifier includes that the generation manner of the target CSI uses an AI model identified by the first type identifier, or the target CSI is generated by an AI entity identified by the first type identifier, or the target CSI is used for an AI function identified by the first type identifier.

[0982] As an embodiment, comprising:

[0983] The first receiver 2101 receives a first higher layer parameter;

[0984] The first higher layer parameter indicates the first cell set.

[0985] As an embodiment, comprising:

[0986] The first processor 2102 sends a second information block;

[0987] wherein the second information block indicates that the generation manners of the CSI on the plurality of serving cells are associated to the same first type identifier.

[0988] As an example, the first receiver 2101 receives a signal in the first set of resources.

[0989] As an example, the first receiver 2101 receives a reference signal in the first set of resources, the first set of resources comprising one or more RS resources.

[0990] As an example, the first operation is training-based or AI-based.

[0991] As an example, the first operation is deployment-needed.

[0992] As an example, the first operation is obtained by load.

[0993] Embodiment 22

[0994] Embodiment 22 illustrates a structural block diagram of a processing apparatus in a second node according to an embodiment of the present application; as shown in FIG. 22. In FIG. 22, the processing apparatus 2200 in the second node comprises a second processor 2201.

[0995] As an example, the second node is a base station device.

[0996] As an example, the second node is a user equipment.

[0997] As an example, the second node is a relay node device.

[0998] As an example, the second processor 2201 comprises at least one of {antenna 420, receiver / transmitter 418, reception processor 470, transmission processor 416, multi-antenna reception processor 472, multi-antenna transmission processor 471, controller / processor 475, memory 476} in Embodiment 4.

[0999] The second processor 2201 transmits a target CSI reporting configuration; the target CSI reporting configuration is used for configuring reporting of a target CSI on a target cell, a generation manner of the target CSI being AI-based; transmits a first information block, the first information block indicating a target identifier; receives the target CSI.

[1000] In Embodiment 22, the generation manner of the target CSI is associated to a first type of identity; whether the first type of identity associated to the generation manner of the target CSI is updated to the target identity depends on whether the target cell belongs to a first cell set; the first type of identity associated to the generation manner of the target CSI is updated to the target identity only when the target cell belongs to the first cell set; the first cell set includes a plurality of serving cells, a first cell is one serving cell in the first cell set, the first cell depends on the first information block; and the target cell is different from the first cell.

[1001] As one embodiment, the first information block is applied to each serving cell in the first cell set.

[1002] As one embodiment, the first information block indicates the first cell.

[1003] As one embodiment, the first cell is a serving cell on which a physical channel carrying the first information block is located.

[1004] As one embodiment, the target CSI reporting configuration indicates a first resource set, the first resource set is used for at least one of channel measurement or interference measurement of the target CSI, the first resource set includes one or more RS resources on the target cell; and the target CSI indicates at least one resource in a second resource set, the second resource set includes resources not belonging to the first resource set.

[1005] As one embodiment, the target CSI reporting configuration indicates a first resource set, the first resource set is used for at least one of channel measurement or interference measurement of the target CSI, the first resource set includes one or more RS resources; and the generation manner of the target CSI includes that a first operation of a receiver of the target CSI reporting configuration performs a first operation, an input of the first operation depends on measurement based on the first resource set, and the target CSI depends on an output of the first operation.

[1006] As one embodiment, the generation manner of the target CSI being associated to a first type of identity includes that the first operation is associated to the first type of identity.

[1007] As one embodiment, the generation manner of the target CSI being associated to a first type of identity includes that the target CSI reporting configuration indicates a first type of identity, and the first type of identity indicated by the target CSI reporting configuration is the first type of identity associated to the generation manner of the target CSI.

[1008] As an embodiment, the generation mode of the target CSI is associated to the first type identifier includes that: the generation mode of the target CSI uses an AI model identified by the first type identifier, or the target CSI is generated by an AI entity identified by the first type identifier, or the target CSI is used for an AI function identified by the first type identifier.

[1009] As an embodiment, the method comprises:

[1010] The second processor 2201 sends a first higher layer parameter.

[1011] The first higher layer parameter indicates the first set of cells.

[1012] As an embodiment, the method comprises:

[1013] The second processor 2201 receives a second information block.

[1014] The second information block indicates that the generation mode of the CSI on multiple serving cells is associated to the same first type identifier.

[1015] As an embodiment, the second processor 2201 sends a reference signal in the first set of resources.

[1016] As an embodiment, the first operation is based on training or based on AI.

[1017] As an embodiment, the first operation is deployment required.

[1018] As an embodiment, the first operation is obtained by loading.

[1019] Those skilled in the art can understand that all or part of the steps in the foregoing method can be instructed by programs to related hardware, and the programs can be stored in a computer readable storage medium, such as a read-only memory, a hard disk, an optical disk or the like. Alternatively, all or part of the steps of the foregoing embodiments can also be implemented using one or more integrated circuits. Correspondingly, each module unit in the foregoing embodiments can be implemented in the form of hardware or in the form of a software function module, and the present application is not limited to any specific form of combination of software and hardware. The user equipment, terminal and UE in the present application include but are not limited to unmanned aerial vehicles, communication modules on unmanned aerial vehicles, remote control aircraft, aircraft, small aircraft, mobile phones, tablet computers, notebooks, vehicle-mounted communication devices, vehicles, vehicles, RSUs, wireless sensors, network cards, Internet of Things terminals, RFID (Radio Frequency Identification) terminals, NB-IOT (Narrow Band Internet of Things) terminals, MTC (Machine Type Communication) terminals, eMTC (enhanced MTC) terminals, data cards, network cards, vehicle-mounted communication devices, low-cost mobile phones, low-cost tablet computers and other wireless communication devices. The base station or system device in the present application includes but is not limited to macro cellular base stations, micro cellular base stations, small cellular base stations, home base stations, relay base stations, eNBs, gNBs, TRPs (Transmitter Receiver Points), GNSS (Global Navigation Satellite System), relay satellites, satellite base stations, air base stations, RSUs (Road Side Units), unmanned aerial vehicles, test equipment such as wireless communication devices that simulate part of the functions of base stations or signaling testers, and the like.

[1020] Those skilled in the art will understand that the present application can be implemented by other specified forms without departing from the core or essential characteristics thereof. Therefore, the presently disclosed embodiments should in no way be considered as descriptive rather than limiting. The scope of the present application is determined by the appended claims rather than the foregoing description, and all modifications within the equivalent meaning and range of the claims are considered to be included therein.

Claims

1. A method in a first node used for wireless communication, characterized by, Comprising: receiving a target CSI reporting configuration; the target CSI reporting configuration is used for configuring reporting of a target CSI on a target cell, a generation manner of the target CSI is AI-based; receiving a first information block, the first information block indicates a target identity; sending a target CSI; wherein the generation manner of the target CSI is associated to a first type of identity; whether the first type of identity associated to the generation manner of the target CSI is updated to the target identity depends on whether the target cell belongs to a first cell set; only when the target cell belongs to the first cell set, the first type of identity associated to the generation manner of the target CSI is updated to the target identity; the first cell set comprises a plurality of serving cells, a first cell is one serving cell in the first cell set, the first cell depends on the first information block; the target cell and the first cell are different.

2. The method in the first node according to claim 1, characterized by, The first information block is applied to each serving cell in the first cell set.

3. A method in a first node according to claim 1 or 2, characterized by, The first information block indicates the first cell.

4. The method in a first node according to claim 1 or 2, characterized by, The first cell is a serving cell on which a physical channel carrying the first information block is located.

5. A method in a first node according to any of claims 1 to 4, characterized by, The target CSI reporting configuration indicates a first resource set, the first resource set is used for at least one of channel measurement or interference measurement of the target CSI, the first resource set comprises one or more RS resources on the target cell; the target CSI indicates at least one resource in a second resource set, the second resource set comprises resources not belonging to the first resource set.

6. A method in a first node according to any of claims 1 to 5, characterized by, The target CSI reporting configuration indicates a first resource set, the first resource set is used for at least one of channel measurement or interference measurement of the target CSI, the first resource set comprises one or more RS resources; the generation manner of the target CSI comprises that a first node or a receiver of the target CSI reporting configuration performs a first operation, an input of the first operation depends on measurement based on the first resource set, the target CSI depends on an output of the first operation.

7. A method in a first node according to claim 6, characterized by, The generation manner of the target CSI being associated to a first type of identity comprises that the first operation is associated to the first type of identity.

8. A method in a first node according to any of claims 1 to 7, characterized by, The generation manner of the target CSI being associated to a first type of identity comprises that the target CSI reporting configuration indicates a first type of identity, the first type of identity indicated by the target CSI reporting configuration is the first type of identity associated to the generation manner of the target CSI.

9. A method in a first node according to any of claims 1 to 8, characterized by, The generation manner of the target CSI being associated to a first type of identity comprises that the generation manner of the target CSI uses an AI model identified by the first type of identity, or the target CSI is generated by an AI entity identified by the first type of identity, or the target CSI is used for an AI function identified by the first type of identity.

10. A terminal, characterized by comprising: The terminal comprises one or more processors and a memory; The memory is coupled with the one or more processors, and is configured to store computer program codes, the computer program codes comprising computer instructions, which are invoked by the one or more processors to cause the terminal to perform the method according to any one of claims 1 to 9.

11. A method in a second node used for wireless communication, characterized by, Comprise: sending a target CSI reporting configuration; the target CSI reporting configuration is used for configuring reporting of a target CSI on a target cell, a generation manner of the target CSI is AI-based; sending a first information block, the first information block indicating a target identity; receiving a target CSI; wherein the generation manner of the target CSI is associated to a first type of identity; whether the first type of identity associated to the generation manner of the target CSI is updated to the target identity depends on whether the target cell belongs to a first cell set; only when the target cell belongs to the first cell set, the first type of identity associated to the generation manner of the target CSI is updated to the target identity; the first cell set comprises a plurality of serving cells, a first cell is one serving cell in the first cell set, the first cell depends on the first information block; the target cell and the first cell are different.

12. A method in a second node according to claim 11, characterised by, The first information block is applied to each serving cell in the first cell set.

13. A method in a second node according to claim 11 or 12, characterized by, The first information block indicates the first cell.

14. A method in a second node according to claim 11 or 12, characterized by, The first cell is a serving cell where a physical channel carrying the first information block is located.

15. A method in a second node according to any of claims 11-14, characterized by, The target CSI reporting configuration indicates a first resource set, the first resource set is used for at least one of channel measurement or interference measurement of the target CSI, the first resource set comprises one or more RS resources on the target cell; the target CSI indicates at least one resource in a second resource set, the second resource set comprises resources not belonging to the first resource set.

16. A method in a second node according to any of claims 11-15, characterized by, The target CSI reporting configuration indicates a first resource set, the first resource set is used for at least one of channel measurement or interference measurement of the target CSI, the first resource set comprises one or more RS resources; the generation manner of the target CSI comprises a first operation performed by a receiver of the target CSI reporting configuration, an input of the first operation depends on measurement based on the first resource set, the target CSI depends on an output of the first operation.

17. A method in a second node according to claim 16, characterised by, The generation manner of the target CSI being associated to a first type of identity comprises: the first operation being associated to the first type of identity.

18. A method in a second node according to any of claims 11-17, characterized by, The generation manner of the target CSI being associated to a first type of identity comprises: the target CSI reporting configuration indicating a first type of identity, the first type of identity indicated by the target CSI reporting configuration being the first type of identity associated to the generation manner of the target CSI.

19. A method in a second node according to any of claims 11-18, characterized by, The generation mode of the target CSI is associated with the first type of identifier, including that the generation mode of the target CSI uses an AI model identified by the first type of identifier, or the target CSI is generated by an AI entity identified by the first type of identifier, or the target CSI is used for an AI function identified by the first type of identifier.

20. A base station, comprising: The base station comprises one or more processors and a memory; The memory is coupled to the one or more processors, and the memory is configured to store computer program codes, the computer program codes comprising computer instructions, and the one or more processors are configured to invoke the computer instructions to cause the base station to perform the method according to any one of claims 11 to 19.

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