Method and apparatus used in node of wireless communication reference signal

Abstract

The invention discloses a method and an apparatus in a node used for wireless communication reference signals. The first node receives a first signaling, and the first signaling triggers a BWP change; determining whether first information is reported in a first resource set, wherein the first information comprises first CSI; the first node does not receive at least one CSI-related opportunity after the BWP change and before a first reference moment, the CSI-related opportunity being used for channel measurement or interference measurement; whether the first CSI is reported depends on a generation mode of the first CSI; when the first CSI is generated based on AI, the first information is reported; when the first CSI is not generated based on AI, the first information is abandoned. The application supports fusion of AI and communication, ensures the continuity of channel state reporting, and further improves the efficiency and reliability of a communication system.

Description

Technical Field

[0001] The present application relates to a signal transmission method and device in a wireless communication system, and in particular to a reference signal-related method and device in a wireless communication system. Background Art

[0002] In traditional wireless communication, UE (User Equipment) reports various auxiliary information obtained by measuring downlink signals and / or channels, such as channel information, auxiliary information related to beam management, auxiliary information related to positioning, etc. The channel information includes but is not limited to one or more of CRI (CSI-RS Resource Indicator, channel state information reference signal resource indication), RI (Rank Indicator, rank indication), PMI (Precoding Matrix Indicator, precoding indication) or CQI (Channel quality indicator). The UE can use this information to select appropriate transmission parameters or report this information. The network device selects appropriate transmission parameters for the UE according to the UE's report, such as the resident cell, MCS (Modulation and Coding Scheme, modulation and coding scheme), TPMI (Transmitted Precoding Matrix Indicator, transmission precoding matrix indication), TCI (Transmission Configuration Indication) and other parameters. In addition, UE reporting can be used to optimize network parameters, such as better cell coverage, switching base stations according to UE location, etc.

[0003] In traditional cellular communications, antenna ports are used to describe reference signal resources; different from physical antennas, antenna ports can be considered as virtualization / superposition operations of physical antennas.

[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, traditional measurement and reporting methods will bring a lot of redundant overhead. Therefore, in NR (New Radio) Rel-18 (Release-18), the research on AI (Artificial Intelligence) / ML (Machine Learning) technology was established to explore its impact on system performance and system design. Compared with traditional processing methods, AI / ML has the characteristics of being based on training and requiring deployment. According to the 3GPP (3rd Generation Partnership Project) standard TS 38.300, AI / ML models and algorithms are beyond the scope of 3GPP. Summary of the invention

[0005] Through research, the applicant found that when AI / ML functions are introduced, the existing measurement mechanism, reporting mechanism and related configuration signaling may not be able to adapt to the needs of AI / ML.

[0006] In response to the above problems, the present application discloses a solution. It should be noted that, in the description of the above problems, the NR system is used as an example, and the present application is also applicable to scenarios such as the future 6G system, achieving technical effects similar to the NR system; further, although the original intention of the present application is for AI / ML scenarios, the present application can also be applied to other non-AI / ML scenarios; further, the use of a unified design scheme for different scenarios (such as other non-AI / ML scenarios, including but not limited to vehicle networking (Vehicle to Everything, V2X), capacity enhancement systems, short-range communication systems, NTN (Non Terrestrial Network, non-terrestrial network), IoT (Internet of Things, Internet of Things), URLLC (Ultra Reliable Low Latency Communication, ultra-robust low-latency communication) networks, etc.) can also help reduce hardware complexity and cost. In the absence of conflict, the embodiments and features in any node of the present application can be applied to any other node. In the absence of conflict, the embodiments and features in the embodiments of the present application can be arbitrarily combined with each other.

[0007] In particular, the interpretation of the terms, nouns, functions, and variables in this application (if not otherwise specified) may refer to the definitions in the TS38 series and TS37 series in the technical specifications (TS) of 3GPP (the 3rd Generation Partnership Project). If necessary, reference may be made to TS38.211, TS38.212, TS38.213, TS38.214, TS38.215, TS38.300, TS38.304, TS38.305, TS38.321, TS38.331, TS37.355, and TS38.423 in the 3GPP technical standards to assist in the understanding of this application.

[0008] As an example, the interpretation of the terms in the present application refers to the definitions of the TS38 series of specification protocols of 3GPP.

[0009] As an example, the interpretation of the terms in the present application refers to the definitions of the TS37 series of specification protocols of 3GPP.

[0010] As an example, the interpretation of the terms in the present application refers to the definition of the TS40 series of specification protocols of 3GPP.

[0011] As an example, the interpretation of the terms in the present application refers to the definitions of the TS39 series of specification protocols of 3GPP.

[0012] As an example, the interpretation of the terms in the present application refers to the definitions in the Rel-17 version of the specification protocol of 3GPP.

[0013] As an example, the interpretation of the terms in the present application refers to the definitions in the Rel-18 version of the specification protocol of 3GPP.

[0014] As an example, the interpretation of the terms in the present application refers to the definitions in the Rel-19 version of the specification protocol of 3GPP.

[0015] As an example, the interpretation of the terms in the present application refers to the definitions in the Rel-20 version of the specification protocol of 3GPP.

[0016] The present application discloses a method in a first node used for wireless communication reference signal, which includes:

[0017] receiving a first signaling, wherein the first signaling triggers a BWP change;

[0018] Determine whether to report first information in a first resource set, where the first information includes first CSI;

[0019] Among them, the first node does not receive at least one CSI-related opportunity after the BWP changes and before the first reference time, and the CSI-related opportunity is for channel measurement or interference measurement; whether the first CSI is reported depends on the generation method of the first CSI; when the first CSI is generated based on AI, the first information is reported; when the first CSI is not generated based on AI, the first information is abandoned.

[0020] As an embodiment, the problem to be solved by the present application includes: whether the first node reports the first information in the first resource set.

[0021] As an embodiment, the problem to be solved by the present application includes: whether the first node reports the first information in the first resource set after the BWP changes.

[0022] As an embodiment, the problems to be solved by the present application include: in the present application, when the first node reports the first information, it depends on the generation method of the first CSI included in the first information, thereby solving the above problem.

[0023] As an embodiment, the characteristics of the above method include: the first resource set is no later than the first reference time.

[0024] As an embodiment, the characteristics of the above method include: AI can understand the characteristics of the channel by learning a large amount of data and can adapt to different environments and scenarios. Therefore, the CSI generated based on AI has higher adaptability and generalization ability and can adapt to the requirements of different BWPs.

[0025] As an embodiment, the characteristics of the above method include: when the first CSI is generated based on AI, the first CSI can be applicable to at least two BWPs at the same time.

[0026] As an embodiment, the benefits of the above method include: the application supports the integration of AI and communication, improves the adaptability and intelligence level of the communication system, and thereby improves the performance, efficiency and user experience of the communication system.

[0027] As an embodiment, the benefits of the above method include: reducing the overhead of channel estimation.

[0028] As an embodiment, the benefits of the above method include: reducing transmission delay, improving the real-time performance of channel estimation, and enhancing the flexibility and response speed of the system.

[0029] As an embodiment, the benefits of the above method include: the CSI generated by AI can provide channel estimation across BWP, thereby helping the system to optimize resource allocation and scheduling strategies.

[0030] According to one aspect of the present application, the method is characterized in that the first CSI is generated based on AI, which means that it includes at least one of the following:

[0032] - the first CSI is generated by prediction;

[0033] - the first CSI is generated by inference;

[0034] -The first CSI is generated by a model, and the model is at least one of AI or ML.

[0035] As an embodiment, the characteristics of the above method include: the first CSI is the output of the AI ​​model.

[0036] As an embodiment, the characteristics of the above method include: the first CSI is a prediction of channel characteristics.

[0037] As an embodiment, the benefits of the above method include: it is conducive to promoting the deep integration of 5G and AI.

[0038] As an embodiment, the benefits of the above method include: improving system performance, and increasing the efficiency and reliability of the communication system.

[0039] As an embodiment, the benefits of the above method include: making the generated CSI more adaptable and generalizable.

[0040] According to one aspect of the present application, the above method is characterized in that the CSI-related opportunities include at least the first two of CSI-RS transmission opportunities for channel measurement, CSI-RS, and CSI-IM opportunities for interference measurement.

[0041] As an embodiment, the characteristics of the above method include: the first CSI is generated based on AI, and the model for generating the first CSI can generate the first CSI without receiving the CSI-RS on the newly activated BWP.

[0042] As an embodiment, the characteristics of the above method include: the first CSI is a prediction of channel characteristics.

[0043] As an embodiment, the characteristics of the above method include: even if the CSI-related opportunity is not received on the new BWP, CSI can be generated based on historical data through the AI ​​model.

[0044] As an embodiment, the benefits of the above method include: ensuring the continuity of channel status reporting, so that the communication system can continue to provide services even when the reference signal is unavailable at a specific moment.

[0045] As an embodiment, the benefits of the above method include: good backward compatibility.

[0046] According to one aspect of the present application, the above method is characterized in that the first reference moment depends on the time domain resources occupied by the CSI reference resources of the first CSI, or the first reference moment depends on the time domain resources occupied by the first resource set.

[0047] As an embodiment, the characteristics of the above method include: the first reference time is the time domain resource occupied by the CSI reference resource of the first CSI.

[0048] As an embodiment, the characteristics of the above method include: the first reference time is not later than the time domain resources occupied by the first resource set.

[0049] As an embodiment, the benefits of the above method include: enhancing system robustness.

[0050] As an embodiment, the benefits of the above method include: good backward compatibility.

[0051] According to one aspect of the present application, the above method is characterized in that it includes:

[0052] receiving a first configuration information block;

[0053] Reporting the first information in the first resource set;

[0054] The first information includes a first identifier, or the first configuration information block indicates a first identifier; the first identifier indicates that the first CSI is generated based on AI.

[0055] As an embodiment, the problem to be solved by the present application includes: how a receiver of the first information determines the generation method of the first CSI.

[0056] As an embodiment, the characteristics of the above method include: a first identifier is introduced in the present application, the first identifier indexes different AI / ML models, and the first information carries the first identifier, thereby solving the above problem.

[0057] As an embodiment, the characteristics of the above method include: the first configuration information block carries multiple identifiers, the multiple identifiers include the first identifier, and the multiple identifiers indicate multiple AI / ML models.

[0058] As an embodiment, the benefits of the above method include: facilitating the base station to identify and manage different models, and track and monitor different models.

[0059] As an embodiment, the benefits of the above method include: the base station can evaluate the accuracy, stability and adaptability of different models by comparing the CSI generated by different AI / ML models, thereby helping to improve and optimize the design and performance of the AI ​​model.

[0060] According to one aspect of the present application, the above method is characterized in that it includes:

[0061] Performing channel measurement in a first time window;

[0062] Among them, the first CSI is generated based on AI; the end time of the first time window is the first reference time; the first node receives at least one CSI-related opportunity in the first time window; the duration of the first time window depends on the model for generating the first CSI, or the duration of the first time window depends on the first identifier and the model for generating the first CSI is associated with the first identifier.

[0063] As an embodiment, the characteristics of the above method include: the input data of the AI / ML model for generating the first CSI includes a reference signal received at least in the first time window.

[0064] As an embodiment, the characteristics of the above method include: the first time window includes multiple CSI-related opportunities.

[0065] As an embodiment, the characteristics of the above method include: compared with traditional generation methods, AI-based CSI generation can use a long time window for training and reasoning.

[0066] As an embodiment, the benefits of the above method include: increasing the amount of model data, thereby improving the reliability of the model.

[0067] As an embodiment, the benefits of the above method include: helping AI / ML models to better understand the characteristics and changing trends of channels, thereby improving the accuracy of channel estimation and channel prediction.

[0068] As an embodiment, the benefits of the above method include: reducing the impact of extreme values ​​or outliers of channel measurement on channel estimation, and ensuring the stability and reliability of the system.

[0069] According to one aspect of the present application, the above method is characterized in that the BWP change triggered by the first signaling includes switching from a first BWP to a second BWP, and at least one downlink signal in the first BWP is quasi-co-located with a downlink signal in the second BWP.

[0070] As an embodiment, the characteristics of the above method include: the CSI generated based on AI can perform channel estimation on two BWPs based on quasi-co-located reference signals.

[0071] As an embodiment, the benefits of the above method include: simplifying system design and management, and improving system consistency and reliability.

[0072] As an embodiment, the benefits of the above method include: improving the accuracy of CSI generated based on AI and improving the accuracy of channel estimation.

[0073] As an embodiment, the benefits of the above method include: reducing the overhead of channel estimation.

[0074] According to one aspect of the present application, the above method is characterized in that the first node is a user equipment.

[0075] According to one aspect of the present application, the above method is characterized in that the first node is a relay node.

[0076] According to one aspect of the present application, the above method is characterized in that the first node has AI / ML capabilities.

[0077] According to one aspect of the present application, the above method is characterized in that the first node supports CSI calculation based on AI / ML.

[0078] According to one aspect of the present application, the above method is characterized in that the first node supports AI / ML-based CSI reporting.

[0079] The present application discloses a method in a second node used for wireless communication reference signal, which includes:

[0080] Sending a first signaling, wherein the first signaling triggers a BWP change;

[0081] Among them, the sender of the first information is the first node, the first node determines whether to report the first information in the first resource set, and the first information includes the first CSI; the first node does not receive at least one CSI-related opportunity after the BWP changes and before the first reference time, and the CSI-related opportunity is for channel measurement or interference measurement; whether the first CSI is reported depends on the generation method of the first CSI; when the first CSI is generated based on AI, the first information is reported; when the first CSI is not generated based on AI, the first information is abandoned.

[0082] According to one aspect of the present application, the method is characterized in that the first CSI is generated based on AI, which means that it includes at least one of the following:

[0084] - the first CSI is generated by prediction;

[0085] - the first CSI is generated by inference;

[0086] -The first CSI is generated by a model, and the model is at least one of AI or ML.

[0087] According to one aspect of the present application, the above method is characterized in that the CSI-related opportunities include at least the first two of CSI-RS transmission opportunities for channel measurement, CSI-RS, and CSI-IM opportunities for interference measurement.

[0088] According to one aspect of the present application, the above method is characterized in that the first reference moment depends on the time domain resources occupied by the CSI reference resources of the first CSI, or the first reference moment depends on the time domain resources occupied by the first resource set.

[0089] According to one aspect of the present application, the above method is characterized in that it includes:

[0090] Sending a first configuration information block;

[0091] Receiving the first information in the first resource set;

[0092] The first information includes a first identifier, or the first configuration information block indicates a first identifier; the first identifier indicates that the first CSI is generated based on AI.

[0093] According to one aspect of the present application, the above method is characterized in that the first node performs channel measurement in a first time window; the first CSI is generated based on AI; the end time of the first time window is the first reference time; the first node receives at least one CSI-related opportunity in the first time window; the duration of the first time window depends on a model for generating the first CSI, or the duration of the first time window depends on a first identifier and the model for generating the first CSI is associated with the first identifier.

[0094] According to one aspect of the present application, the above method is characterized in that the BWP change triggered by the first signaling includes switching from a first BWP to a second BWP, and at least one downlink signal in the first BWP is quasi-co-located with a downlink signal in the second BWP.

[0095] According to one aspect of the present application, the above method is characterized in that the second node is a base station.

[0096] According to one aspect of the present application, the above method is characterized in that the second node is a user equipment.

[0097] According to one aspect of the present application, the above method is characterized in that the second node is a TRP.

[0098] The present application discloses a device for a first node used for wireless communication reference signal, including:

[0099] A first receiver receives a first signaling, wherein the first signaling triggers a BWP change;

[0100] A first transmitter determines whether to report first information in a first resource set, where the first information includes a first CSI;

[0101] Among them, the first node does not receive at least one CSI-related opportunity after the BWP changes and before the first reference time, and the CSI-related opportunity is for channel measurement or interference measurement; whether the first CSI is reported depends on the generation method of the first CSI; when the first CSI is generated based on AI, the first information is reported; when the first CSI is not generated based on AI, the first information is abandoned.

[0102] The present application discloses a device for a second node used for wireless communication reference signal, including:

[0103] A second transmitter sends a first signaling, wherein the first signaling triggers a BWP change;

[0104] Among them, the sender of the first information is the first node, the first node determines whether to report the first information in the first resource set, and the first information includes the first CSI; the first node does not receive at least one CSI-related opportunity after the BWP changes and before the first reference time, and the CSI-related opportunity is for channel measurement or interference measurement; whether the first CSI is reported by the first node depends on the generation method of the first CSI; when the first CSI is generated based on AI, the first information is reported; when the first CSI is not generated based on AI, the first information is abandoned.

[0105] As an embodiment, compared with the traditional solution, the present application has the following advantages but not limited to:

[0106] This application supports the integration of AI and communications, improves the adaptability and intelligence level of communication systems, and thus improves the performance, efficiency and user experience of communication systems;

[0107] Reduce transmission delay, improve the real-time performance of channel estimation, and enhance system flexibility and response speed;

[0108] Improve the accuracy of AI-generated CSI and improve the accuracy of channel estimation. BRIEF DESCRIPTION OF THE DRAWINGS

[0109] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments with reference to the following drawings:

[0110] Figure 1 A flowchart showing first node transmission according to an embodiment of the present application is shown;

[0111] Figure 2 A schematic diagram of a network architecture according to an embodiment of the present application is shown;

[0112] Figure 3 A schematic diagram showing an embodiment of a wireless protocol architecture of a user plane and a control plane according to an embodiment of the present application;

[0113] Figure 4 A schematic diagram showing a first communication device and a second communication device according to an embodiment of the present application is shown;

[0114] Figure 5 A flow chart showing transmission between a first node and a second node according to an embodiment of the present application is shown;

[0115] Figure 6 A schematic diagram of a first time window according to an embodiment of the present application is shown;

[0116] Figure 7 A schematic diagram showing a BWP change according to an embodiment of the present application;

[0117] Figure 8 A schematic diagram of RAN domain AI / ML function deployment according to an embodiment of the present application is shown;

[0118] Fig. 9 A schematic diagram showing the deployment of AI / ML functions of a UE according to an embodiment of the present application is shown;

[0119] Fig.10 A schematic diagram of a processing system based on artificial intelligence or machine learning according to an embodiment of the present application is shown;

[0120] Fig.11 A schematic diagram based on artificial intelligence or machine learning according to an embodiment of the present application is shown;

[0121] Fig.12 A structural block diagram of a processing device used in a first node according to an embodiment of the present application is shown;

[0122] Fig.13 A structural block diagram of a processing device used in a second node according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0123] The technical solution of the present application will be further described in detail below in conjunction with the accompanying drawings. It should be noted that the embodiments and features in the embodiments of the present application can be arbitrarily combined with each other without conflict. Based on considerations such as performance, flexibility, complexity, overhead, and compatibility, those skilled in the art are motivated to flexibly combine the embodiments in different drawings without conflict, including but not limited to the attached drawings. Figure 1 The embodiments and appendix Figure 5 -Attached Fig.13 The embodiments in Figure 5 The embodiments and appendix Figure 6 -Attached Fig.13 The embodiments in , etc.

[0124] Example 1

[0125] Embodiment 1 illustrates a flowchart of the first node transmission according to an embodiment of the present application, as shown in the attached Figure 1 As shown in the attached Figure 1 In the example, each box represents a step. In particular, the order of the steps in the box does not represent a specific time sequence between the steps.

[0126] In step 101, the first node receives first signaling, which triggers a BWP change; in step 102, it is determined whether to report first information in a first resource set, where the first information includes a first CSI.

[0127] In embodiment 1, the first node does not receive at least one CSI-related opportunity after the BWP changes and before the first reference time, and the CSI-related opportunity is for channel measurement or interference measurement; whether the first CSI is reported depends on the generation method of the first CSI; when the first CSI is generated based on AI, the first information is reported; when the first CSI is not generated based on AI, the first information is abandoned.

[0128] As an embodiment, the first node is the first node in the present application.

[0129] As an embodiment, the BWP refers to: BandWidth Part, partial bandwidth.

[0130] As an embodiment, the CSI refers to: Channel State Information, channel state information.

[0131] As an embodiment, the AI ​​refers to: Artificial Intelligence.

[0132] As an embodiment, the AI ​​includes: Machine Learning.

[0133] As an embodiment, the AI ​​includes: Deep Learning.

[0134] As an embodiment, the first node receives the first signaling.

[0135] As an embodiment, the first signaling is dynamic signaling.

[0136] As an embodiment, the first signaling is physical layer signaling.

[0137] As an embodiment, the first signaling is layer 1 (Layer 1, L1) signaling.

[0138] As an embodiment, the first signaling includes DCI (Downlink Control Information).

[0139] As an embodiment, the first signaling includes information in one or more fields in a DCI.

[0140] As an embodiment, the CRC (Cyclic redundancy check) of the first signaling is scrambled by C (Cell)-RNTI (Radio Network Temporary Identifier).

[0141] As an embodiment, the CRC of the first signaling is scrambled by CS (Configured Scheduled)-RNTI.

[0142] As an embodiment, the CRC of the first signaling is scrambled by SP (Semi-Persistent)-CSI-RNTI.

[0143] As an embodiment, the CRC of the first signaling is scrambled by MCS (Modulation and coding scheme)-C-RNTI.

[0144] As an embodiment, the first signaling is a DCI.

[0145] As an embodiment, the first signaling is a downlink (DownLink, DL) DCI.

[0146] As an embodiment, the first signaling is an uplink (UpLink, UL) DCI.

[0147] As an embodiment, the format of the first signaling is one of format 0_1, format 0_2, format 0_3, format 1_1, format 1_2 or format 1_3.

[0148] As an embodiment, the first signaling includes at least one DCI field, and one DCI field in the at least one DCI field triggers a BWP change.

[0149] As an embodiment, the first signaling includes a bandwidth part indicator field.

[0150] As an embodiment, the first signaling is MAC (Medium Access Control) layer signaling.

[0151] As an embodiment, the first signaling includes MAC CE (Control Element, information unit).

[0152] As an embodiment, the first signaling triggers the BWP change.

[0153] As an embodiment, the first node supports DCI-based BWP switching.

[0154] As an embodiment, the first node is configured with at least one BWP.

[0155] As an embodiment, the BWP change includes BWP switching.

[0156] As an embodiment, the BWP change includes a BWP exchange.

[0157] As an embodiment, the BWP change refers to a change in an active BWP.

[0158] As an embodiment, the BWP change includes: switching from a current BWP to a BWP indicated by the first signaling.

[0159] As an embodiment, the first signaling indicates the second BWP in this application.

[0160] As an embodiment, the first signaling indicates the bwp-Id of the second BWP in this application.

[0161] As an embodiment, the first signaling carries the bwp-Id of the second BWP in this application.

[0162] As an embodiment, in response to receiving the first signaling, the active BWP of the first node is switched from the first BWP in the present application to the second BWP in the present application.

[0163] As an embodiment, after the first node receives the first signaling, the active BWP of the first node switches from the first BWP in the present application to the second BWP in the present application.

[0164] As an embodiment, after the first node successfully decodes the first signaling, the active BWP of the first node switches from the first BWP in the present application to the second BWP in the present application.

[0165] As an embodiment, the first node determines whether to report the first information in the first resource set.

[0166] As an embodiment, the first resource set includes a positive integer number of REs (Resource Elements) greater than 1.

[0167] As an embodiment, the first resource set occupies frequency domain resources corresponding to a positive integer number of RBs (Resource Blocks) in the frequency domain, and occupies a positive integer number of multi-carrier symbols in the time domain.

[0168] Typically, one RE described in the present application occupies one symbol in the time domain and one subcarrier in the frequency domain.

[0169] Typically, one RB described in the present application occupies 12 consecutive subcarriers in the frequency domain.

[0170] As an embodiment, the multi-carrier symbol described in the present application includes an OFDM (Orthogonal Frequency Division Multiplexing) symbol.

[0171] As an embodiment, the multi-carrier symbol described in the present application is an OFDM symbol.

[0172] As an embodiment, the multi-carrier symbol described in the present application is an OFDM symbol including a CP (Cyclic Prefix).

[0173] As an embodiment, the multi-carrier symbol described in the present application includes a FBMC (Filter Bank Multi Carrier) symbol.

[0174] As an embodiment, the multi-carrier symbol described in the present application includes a UFMC (Universal Filtered MultiCarrier) symbol.

[0175] As an embodiment, the multi-carrier symbols described in the present application include F-OFDM (Filtered-OFDM, filtered-orthogonal frequency division multiplexing) symbols.

[0176] As an embodiment, the first resource set corresponds to a PUSCH (Physical Uplink Shared CHannel, physical uplink shared channel) resource.

[0177] As an embodiment, the first resource set corresponds to a time-frequency resource occupied by a PUSCH.

[0178] As an embodiment, the first resource set is a PUSCH opportunity.

[0179] As an embodiment, the first resource set corresponds to a PUCCH (Physical Uplink ControlCHannel, physical uplink control channel) resource.

[0180] As an embodiment, the first resource set corresponds to the time-frequency resources occupied by a PUCCH.

[0181] As an embodiment, the first resource set is a PUCCH opportunity.

[0182] As an embodiment, the frequency domain resources occupied by the first resource set belong to the second BWP in this application.

[0183] As an embodiment, the first resource set is configured to the second BWP in this application.

[0184] As an embodiment, the first information includes the first CSI.

[0185] As an embodiment, the first information is carried by a baseband signal.

[0186] As an embodiment, the first information is carried by a radio frequency signal.

[0187] As an embodiment, the first information is carried by a wireless signal.

[0188] As an embodiment, the first information includes the first CSI.

[0189] As an embodiment, the first information includes a channel quality report.

[0190] As an embodiment, the first information includes a measurement report.

[0191] As an embodiment, the first information includes a report on mobility management.

[0192] As an embodiment, the first information includes a result of BFR (Beam Failure Recovery).

[0193] As an embodiment, the first information includes a result of cell selection.

[0194] As an embodiment, the first information includes a beam quality report.

[0195] As an embodiment, the first information includes beam management reporting.

[0196] As an embodiment, the first information includes a channel impulse response.

[0197] As an embodiment, the first information includes a channel matrix.

[0198] As an embodiment, the first information includes received signal quality.

[0199] As an embodiment, the first CSI is periodic CSI.

[0200] As an embodiment, the first CSI is a semi-persistent (SP) CSI.

[0201] As an embodiment, the first CSI is aperiodic (AP) CSI.

[0202] As an embodiment, the first CSI includes LI (layer indicator).

[0203] As an embodiment, the first CSI includes RI (rank indicator).

[0204] As an embodiment, the first CSI includes CQI (Channel Quality Indicator).

[0205] As an embodiment, the first CSI includes PMI (Precoding Matrix Indicator).

[0206] As an embodiment, the first CSI includes CRI (CSI-RS resource indicator, channel state information reference signal resource indicator).

[0207] As an embodiment, the first CSI includes SSBRI (SS / PBCH Block Resource indicator, synchronization / physical broadcast channel block resource indication).

[0208] As an embodiment, the first CSI includes L1-RSRP (Layer 1 Reference Signal Received Power, layer 1 reference signal received power).

[0209] As an embodiment, the first node does not receive at least one of the CSI-related opportunities after the BWP changes and before the first reference time.

[0210] As an embodiment, the first node does not receive any of the CSI-related opportunities after the BWP changes and before the first reference time.

[0211] As an embodiment, the BWP changes include: after the first node receives the first signaling.

[0212] As an embodiment, the BWP changes include: the first node correctly demodulates the first signaling.

[0213] As an embodiment, the BWP change includes: the active BWP of the first node is switched to the BWP indicated by the first signaling.

[0214] As an embodiment, the first reference time depends on the time domain resources occupied by the CSI reference resources of the first CSI, or the first reference time depends on the time domain resources occupied by the first resource set.

[0215] As an embodiment, the first reference time depends on the time domain resources occupied by the CSI reference resources of the first CSI.

[0216] As an embodiment, the first reference time is the time domain position where the CSI reference resource corresponding to the first CSI is located.

[0217] As a sub-embodiment of this embodiment, the first reference time is a time domain resource occupied by a CSI reference resource of the first CSI.

[0218] As a sub-embodiment of this embodiment, the first reference time is a time when the time domain resources occupied by the CSI reference resource of the first CSI are advanced by a first time interval, and the first time interval is fixed, or the first time interval is configurable.

[0219] As a sub-embodiment of this embodiment, the first reference moment is a moment when the time domain resources occupied by the CSI reference resource of the first CSI are delayed by a first time interval, and the first time interval is fixed, or the first time interval is configurable.

[0220] As an embodiment, the first reference time is the time when the time slot occupied by the CSI reference resource of the first CSI ends.

[0221] As an embodiment, the first reference time is the time when the time slot occupied by the CSI reference resource of the first CSI ends after the time slot is advanced by a first time interval, and the first time interval is fixed, or the first time interval is configurable.

[0222] As an embodiment, the first reference time is the time when the time slot occupied by the CSI reference resource of the first CSI ends after being delayed by a first time interval, and the first time interval is fixed, or the first time interval is configurable.

[0223] As an embodiment, the first reference time is not earlier than the time when the time slot occupied by the CSI reference resource of the first CSI ends.

[0224] As an embodiment, the first reference time is no earlier than the time when the time slot occupied by the CSI reference resource of the first CSI ends after the first time interval, and the first time interval is fixed, or the first time interval is configurable.

[0225] As an embodiment, the first reference time is no earlier than the time when the time slot occupied by the CSI reference resource of the first CSI ends after the first time interval is delayed, and the first time interval is fixed, or the first time interval is configurable.

[0226] As an embodiment, the unit of the first time interval in the present application is a time slot.

[0227] As an embodiment, the unit of the first time interval in the present application is millisecond (ms).

[0228] As an embodiment, the CSI reference resource of the first CSI occupies one time slot in the time domain.

[0229] As an embodiment, the CSI reference resource of the first CSI occupies a valid downlink time slot in the time domain.

[0230] As an embodiment, a valid downlink timeslot described in the present application includes at least one downlink symbol or flexible symbol configured by a higher layer.

[0231] As an embodiment, the valid downlink time slot described in the present application does not belong to the measurement gap configured by the first node.

[0232] As an embodiment, the CSI reference resource of the first CSI depends on the measurement subband of the first CSI in the frequency domain.

[0233] As an embodiment, the CSI reference resource of the first CSI occupies multiple PRBs (Physical Resource Blocks) in the frequency domain.

[0234] As an embodiment, the first reference time depends on the time domain resources occupied by the first resource set.

[0235] As an embodiment, the first reference time depends on the time domain resources occupied by the first resource set.

[0236] As a sub-embodiment of this embodiment, the first reference time is a time when the time domain resources occupied by the first resource set are advanced by a second time interval, and the second time interval is fixed, or the second time interval is configurable.

[0237] As an embodiment, the first reference time is no later than the time when the time domain resources occupied by the first resource set start.

[0238] As an embodiment, the first reference time is the time when the time domain resources occupied by the first resource set end in advance of the time slot in which the second time interval is located, and the second time interval is fixed, or the second time interval is configurable.

[0239] As an embodiment, the first reference time is no earlier than the time when the time domain resources occupied by the first resource set end in the time slot where the second time interval is located, and the second time interval is fixed, or the second time interval is configurable.

[0240] As an embodiment, the unit of the second time interval in the present application is a time slot.

[0241] As an embodiment, the unit of the second time interval in the present application is milliseconds.

[0242] As an embodiment, the CSI reference resource of the first CSI is located in the time slot The first resource set is located in time slot n′, where n CSI_ref , K offset , 2 μDL , The definition of n refers to Section 5.2.2.5 of TS 38.214.

[0243] As an embodiment, the time interval between the CSI reference resource of the first CSI and the first resource set depends on the K configured by the high layer. offset , the K offset Refer to Section 5.2.2.5 of TS 38.214 for the definition.

[0244] As an embodiment, the time interval between the CSI reference resource of the first CSI and the first resource set depends on the current downlink SCS (SubCarrier Spacing) of the first node.

[0245] As an embodiment, the time interval between the CSI reference resource of the first CSI and the first resource set depends on the current uplink SCS of the first node.

[0246] As an embodiment, the CSI-related opportunity is for channel measurement (channel measurement) or interference measurement (Interference Measurement, IM).

[0247] As an embodiment, the CSI-related opportunity is for channel measurement.

[0248] As an embodiment, the CSI-related opportunity is for interference measurement.

[0249] As an embodiment, the CSI related opportunity is for channel prediction.

[0250] As an embodiment, the CSI related timing is for interference prediction.

[0251] As an embodiment, the CSI-related opportunities include at least the first two of the CSI-RS (Channel State Information-Reference Signal) transmission opportunities for channel measurement of the first CSI, CSI-RS, and CSI-IM (Channel State Information-InterferenceMeasurement) opportunities for interference measurement.

[0252] As an embodiment, the CSI-related opportunity includes a CSI-RS transmission opportunity for channel measurement and a CSI-RS.

[0253] As an embodiment, the CSI-related opportunities include CSI-RS transmission opportunities, CSI-RS, and CSI-IM opportunities for interference measurement.

[0254] As an embodiment, the CSI-related opportunity includes at least one transmitted CSI-RS.

[0255] As an embodiment, the CSI-related opportunity includes at least one reference signal for channel measurement.

[0256] As an embodiment, the CSI-related opportunity includes at least one reference signal for interference measurement.

[0257] As an embodiment, the first node receives a CSI-RS in the CSI-related opportunity, and the CSI-RS is used for channel measurement or interference measurement.

[0258] As an embodiment, the CSI related timing is for CSI that is not generated based on AI.

[0259] As an embodiment, whether the first CSI is reported depends on the generation method of the first CSI.

[0260] As an embodiment, the first CSI is generated based on AI, and the first information is reported.

[0261] As an embodiment, the meaning of AI-based generation in the present application includes: ML-based generation.

[0262] As an embodiment, the meaning that the first CSI is generated based on AI includes: the first CSI is generated by prediction.

[0263] As an embodiment, the meaning that the first CSI is generated based on AI includes: the first CSI is generated by inferring.

[0264] As an embodiment, the meaning that the first CSI is generated based on AI includes: the first CSI is generated by a model, and the model is (for) AI.

[0265] As an embodiment, the first CSI is generated based on AI, which means that the first CSI is generated by a model, and the model is ML.

[0266] As an embodiment, the meaning that the first CSI is generated based on AI includes: the first CSI is generated based on AI based on measurement.

[0267] As an embodiment, the first CSI is generated based on AI, which means that the channel information recovered by the receiver based on the received first CSI is unknown to the first node.

[0268] As an embodiment, the first CSI is generated based on AI, which means that: a generator for generating the first CSI is obtained based on training.

[0269] As an embodiment, the first CSI being generated based on AI means that the first CSI does not belong to the CSI defined in 3GPP Rel-18 or a version earlier than 3GPP Rel-18.

[0270] As an embodiment, the first CSI is not generated based on AI, and the first information is discarded.

[0271] As an embodiment, the meaning that the first CSI is not generated based on AI includes: the first CSI is not generated by reasoning or prediction.

[0272] As an embodiment, the first CSI is not generated based on AI, which means that the channel information recovered by the receiver based on the received first CSI is known to the first node.

[0273] As an embodiment, the meaning that the first CSI is not generated based on AI includes: the first CSI is obtained through measurement.

[0274] As an embodiment, the meaning that the first CSI is not generated based on AI includes: the first CSI is obtained by measuring a downlink reference signal.

[0275] As an embodiment, the meaning that the first CSI is not generated based on AI includes: the first CSI belongs to the CSI defined in 3GPP Rel-18 or a version earlier than 3GPP Rel-18.

[0276] Those skilled in the art know that the first CSI represents the parameters of the wireless channel between the base station and the first node. The specific form depends on different receiver algorithms and can be determined by the supplier of the first node; it can also be clearly defined by the standard. The following takes CQI as an example to provide some non-limiting implementation methods:

[0277] The first node first performs channel measurement on a CSI-RS resource to obtain a channel parameter matrix H r×t , where r and t are the number of receiving antennas and the number of antenna ports used for transmission respectively; when using the precoding matrix W t×l Under the condition of , the channel parameter matrix after precoding is H r×t ·W t×l , where l is the rank or number of layers; the first node calculates H based on a specific algorithm r×t ·W t×l The equivalent channel capacity is then used to determine the CQI by looking up the equivalent channel capacity. Generally speaking, the calculation of the equivalent channel capacity requires the first node to estimate noise and interference. Generally speaking, the mapping between the equivalent channel capacity and the CQI value depends on the receiver performance or hardware-related factors such as the modulation method. The precoding matrix W t×l Usually, the first node feeds back the information through RI or PMI.

[0278] Compared with CQI, L1-SINR does not carry the information of the receiver, so the calculation of the equivalent channel capacity is omitted.

[0279] As an embodiment, the first CSI is generated based on AI, and the first node obtains the channel parameter matrix H based on AI / ML reasoning r×t .

[0280] As an embodiment, the first CSI is generated based on AI, and the input of the first node based on AI / ML reasoning includes a channel parameter matrix H obtained by channel measurement r×t and the precoding matrix W t×l , the output of the AI / ML reasoning includes equivalent channel capacity.

[0281] As an embodiment, the first CSI is not generated based on AI, and the first node performs channel measurement on a CSI-RS resource to obtain a channel parameter matrix H r×t .

[0282] As a sub-embodiment of this embodiment, the CSI-RS transmitted in the one CSI-RS resource occupies a CSI-related opportunity described in this application.

[0283] As an embodiment, the first CSI is not generated based on AI, and the first node uses SINR, EESM (Exponential Effective SINR Mapping), or RBIR (Received Blockmean mutual Information Ratio) criteria to calculate the equivalent channel capacity.

[0284] Example 2

[0285] Embodiment 2 illustrates a schematic diagram of a network architecture according to an embodiment of the present application, as shown in the attached Figure 2 shown.

[0286] Attached Figure 2 A network architecture 200 is illustrated. The network architecture 200 is a network architecture for LTE (Long-Term Evolution), LTE-A (Long-Term Evolution Advanced), 5G system, 5G-Advanced and future 6G system. The network architecture for LTE, LTE-A, 5G system, 5G-Advanced and future 6G system is referred to as EPS (Evolved Packet System). The 5GNR or LTE network architecture may be referred to as 5GS (5G System) / EPS or some other suitable term; the 6G network architecture may be referred to as 6GS (6G System) / EPS or some other suitable term. The network architecture 200 may include one or more UEs 201, RAN (Next Generation Radio Access Network) 202, a core network 210, an HSS (Home Subscriber Server) / UDM (Unified Data Management) 220 and an Internet service 230. . The network architecture 200 can be interconnected with other access networks, but for simplicity these entities / interfaces are not shown. Figure 2As shown, the network architecture 200 provides packet switching services, however, those skilled in the art will readily appreciate that the various concepts presented throughout this application can be extended to networks that provide circuit switching services. RAN 202 includes Node B 203 and other nodes 204. Node 203 provides user and control plane protocol terminations toward UE 201. Node 203 can be connected to other nodes 204 via an Xn interface (e.g., backhaul). Node 203 may also be referred to as a base station, a base transceiver station, a wireless base station, a wireless transceiver, a transceiver function, a Basic Service Set (BSS), an Extended Service Set (ESS), a TRP (Transmitter Receiver Point), or some other suitable terminology. Node 203 provides an access point to a core network 210 for UE 201; the core network 210 is a 5GC (5G Core Network, 5G Core Network) / EPC (Evolved Packet Core), or the core network 210 is a 6GC. Examples of UE 201 include cellular phones, smart phones, Session Initiation Protocol (SIP) phones, laptop computers, Personal Digital Assistants (PDAs), satellite radios, global positioning systems, multimedia devices, video devices, digital audio players (e.g., MP3 players), cameras, game consoles, drones, aircraft, narrowband physical network devices, machine type communication devices, land vehicles, cars, wearable devices, or any other similar functional devices. Those skilled in the art may also refer to UE 201 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 term. Node 203 is connected to core network 210 via an S1 / NG interface.The core network 210 includes MME (Mobility Management Entity) / AMF (Authentication Management Field) / SMF (Session Management Function) 211, other MME / AMF / SMF 214, S-GW (Service Gateway) / UPF (User Plane Function) 212, and P-GW (Packet Data Network Gateway) / UPF 213. MME / AMF / SMF 211 is a control node that handles signaling between UE 201 and 5G-CN / EPC 210. In general, MME / AMF / SMF 211 provides bearer and connection management. All user IP (Internet Protocol) packets are transmitted through S-GW / UPF 212, which itself is connected to P-GW / UPF 213. P-GW provides UE IP address allocation and other functions. P-GW / UPF 213 is connected to Internet service 230. Internet service 230 includes operator-specific Internet protocol services, which may specifically include Internet, Intranet, IMS (IP Multimedia Subsystem) and packet switching services.

[0287] As an embodiment, the first node in the present application includes the UE 201.

[0288] As an embodiment, the second node in the present application includes the node 203.

[0289] As an embodiment, the node 203 is a macro cell base station.

[0290] As an embodiment, the node 203 is a micro cell base station.

[0291] As an embodiment, the node 203 is a pico cell base station.

[0292] As an embodiment, the node 203 is a home base station (Femtocell).

[0293] As an embodiment, the node 203 is a base station device that supports a large delay difference.

[0294] As an embodiment, the node 203 is a flying platform device.

[0295] As an embodiment, the node 203 is a satellite device.

[0296] As an embodiment, the node 203 is a test device (eg, a transceiver device simulating some functions of a base station, a signaling tester).

[0297] As an embodiment, the UE 201 includes a mobile phone.

[0298] As an embodiment, the UE 201 is a vehicle including a car.

[0299] As an embodiment, the wireless link from the UE 201 to the node 203 is an uplink, and the uplink is used to perform uplink transmission.

[0300] As an embodiment, the wireless link from the node 203 to the UE 201 is a downlink, and the downlink is used to perform downlink transmission.

[0301] As an embodiment, the wireless link between the node 203 and the UE 201 includes a cellular network link.

[0302] As an embodiment, the node 203 and the UE 201 are connected via a Uu air interface.

[0303] As an embodiment, the sender of the first signaling includes the node 203.

[0304] As an embodiment, the recipient of the first signaling includes the UE 201.

[0305] As an embodiment, the sender of the first information includes the UE 201.

[0306] As an embodiment, the receiver of the first information includes the node 203.

[0307] As an embodiment, the sender of the first configuration information block includes the node 203.

[0308] As an embodiment, the recipient of the first configuration information block includes the UE 201.

[0309] As an embodiment, the UE 201 supports generating reports using AI / ML.

[0310] As an embodiment, the UE 201 supports generating a trained model or partial parameters in the model using training data.

[0311] As an embodiment, the UE 201 supports determining at least part of the parameters for CSI reporting enhancement through training.

[0312] As an embodiment, the UE 201 supports AI / ML-based CSI reporting.

[0313] As an embodiment, the UE 201 supports CSI reporting based on neural networks.

[0314] As an embodiment, the UE 201 supports CSI reporting based on CNN (Convolutional Neural Networks).

[0315] As an embodiment, the UE 201 supports Transformer-based CSI reporting.

[0316] As an embodiment, the UE 201 supports CSI reporting based on ResNet (Residual Network).

[0317] As an embodiment, the UE 201 supports a 5G system.

[0318] As an embodiment, the node 203 supports a 5G system.

[0319] As an embodiment, the UE 201 at least supports the 6G system.

[0320] As an embodiment, the node 203 at least supports the 6G system.

[0321] Example 3

[0322] Embodiment 3 illustrates 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, as shown in the attached figure. Figure 3 shown.

[0323] Figure 3 is a schematic diagram illustrating an embodiment of a radio protocol architecture for a user plane 350 and a control plane 300, Figure 3The wireless protocol architecture of the control plane 300 for a first communication node device (RSU (Road Side Unit) in UE or V2X (Vehicle to Everything), vehicle-mounted device or vehicle-mounted communication module) and a second node device (gNB, RSU in UE or V2X, vehicle-mounted device or vehicle-mounted communication module), or between two UEs is presented in three layers: Layer 1 (Layer 1, L1), Layer 2 (Layer 2, L2) and Layer 3 (Layer 3, L3). L1 is the lowest layer and implements various PHY (PHYsical layer) signal processing functions. L1 will be referred to as PHY 301 in this article. L2 305 is above PHY 301 and is responsible for the link between the first node device and the second node device, or between two UEs through PHY 301. L2305 includes a MAC (Medium Access Control) sublayer 302, an RLC (Radio Link Control) sublayer 303, and a PDCP (Packet Data Convergence Protocol) sublayer 304, which terminate at the second node device. The PDCP sublayer 304 provides multiplexing between different radio bearers and logical channels. The PDCP sublayer 304 also provides security by encrypting data packets, and provides inter-zone mobility support for the first communication node device between the second communication node device. 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 caused by HARQ (Hybrid Automatic Repeat reQuest). The MAC sublayer 302 provides multiplexing between logical and transport channels. The MAC sublayer 302 is also responsible for allocating various radio resources (e.g., resource blocks) in a cell between the first communication node devices. The MAC sublayer 302 is also responsible for HARQ operations. The RRC (Radio Resource Control) sublayer 306 in L3 in the control plane 300 is responsible for obtaining radio resources (ie, radio bearers) and configuring lower layers using RRC signaling between the second communication node device and the first communication node device.The wireless protocol architecture of the user plane 350 includes layer 1 (L1) and layer 2 (L2). The wireless protocol architecture for the first communication node device and the second communication node device in the user plane 350 is substantially the same as the corresponding layers and sublayers in the control plane 300 for the physical layer 351, the PDCP sublayer 354 in L2355, the RLC sublayer 353 in L2355, and the MAC sublayer 352 in L2355, but the PDCP sublayer 354 also provides header compression for upper layer data packets to reduce wireless transmission overhead. L2355 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 business diversity. Although not shown in the figure, the first communication node device may have several upper layers above L2355, including a network layer (e.g., IP (Internet Protocol) layer) terminating at the P-GW on the network side and an application layer terminating at the other end of the connection (e.g., a remote UE, a server, etc.).

[0324] As an example, Figure 3 The wireless protocol architecture in is applicable to the first node in this application.

[0325] As an example, Figure 3 The wireless protocol architecture in is applicable to the second node in this application.

[0326] As an embodiment, the first signaling is generated by the PHY 301 or PHY 351.

[0327] As an embodiment, the first signaling is generated in the MAC sublayer 302 or the MAC sublayer 352.

[0328] As an embodiment, the first configuration information block is generated in the RRC 306.

[0329] As an embodiment, the higher layer mentioned in this application refers to a layer above the physical layer.

[0330] As an embodiment, the higher layer described in the present application includes a MAC layer.

[0331] As an embodiment, the higher layer described in the present application includes an RRC layer.

[0332] Example 4

[0333] 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 the attached figure. Figure 4 Attached 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.

[0334] The first communication device 410 includes 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 .

[0335] The second communication device 450 includes 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.

[0336] In transmission from the first communication device 410 to the second communication device 450, at the first communication device 410, upper layer data packets from the core network are provided to the controller / processor 475. The controller / processor 475 implements the functionality of L2. In DL, the controller / processor 475 provides header compression, encryption, packet segmentation and reordering, multiplexing between logical and transport channels, and radio resource allocation to the second communication device 450 based on various priority metrics. The controller / processor 475 is also responsible for HARQ 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 L1 (i.e., physical layer). The transmit processor 416 implements coding and interleaving to facilitate forward error correction (FEC) at the second communication device 450, as well as mapping of signal constellations based on various modulation schemes (e.g., binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), M-PSK, M-quadrature amplitude modulation (M-QAM)). The multi-antenna transmit processor 471 performs digital spatial precoding on the coded and modulated symbols, including codebook-based precoding and non-codebook-based precoding and beamforming processing, to generate one or more parallel streams. The transmit processor 416 then maps each parallel stream to a subcarrier, multiplexes the modulated symbols with a reference signal (e.g., pilot) in the time domain and / or frequency domain, and then uses an Inverse Fast Fourier Transform (IFFT) to generate a physical channel carrying a time domain multi-carrier symbol stream. The multi-antenna transmit processor 471 then performs a transmit analog precoding / beamforming operation on the time domain multi-carrier symbol stream. Each transmitter 418 converts the baseband multi-carrier symbol stream provided by the multi-antenna transmit processor 471 into a radio frequency stream, and then provides it to different antennas 420.

[0337] In the transmission from the first communication device 410 to the second communication device 450, at the second communication device 450, each receiver 454 receives a signal through its corresponding antenna 452. Each receiver 454 recovers the information modulated onto the RF carrier and converts the RF stream into a baseband multi-carrier symbol stream and provides it to the receiving processor 456. The receiving processor 456 and the multi-antenna receiving processor 458 implement various signal processing functions of L1. The multi-antenna receiving processor 458 performs a receiving analog precoding / beamforming operation on the baseband multi-carrier symbol stream from the receiver 454. The receiving processor 456 uses a fast Fourier transform (FFT) to convert the baseband multi-carrier symbol stream after the receiving analog precoding / beamforming operation from the time domain to the frequency domain. In the frequency domain, the physical layer data signal and the reference signal are demultiplexed by the receiving processor 456, where the reference signal will be used for channel estimation, and the data signal is recovered after multi-antenna detection in the multi-antenna receiving processor 458 to any parallel stream with the second communication device 450 as the destination. The symbols on each parallel stream are demodulated and recovered in the receiving processor 456, and soft decisions are generated. The receiving processor 456 then decodes and deinterleaves the soft decisions to recover the upper layer data and control signals transmitted by the first communication device 410 on the physical channel. The upper layer data and control signals are then provided to the controller / processor 459. The controller / processor 459 implements the functions of L2. The controller / processor 459 may be associated with a memory 460 storing program codes and data. The memory 460 may be referred to as a computer-readable medium. In DL, the controller / processor 459 provides multiplexing, packet reassembly, decryption, header decompression, and control signal processing between the transmission and logical channels to recover the upper layer data packets from the core network. The upper layer data packets are then provided to all protocol layers above L2. Various control signals may also be provided to L3 for L3 processing. The controller / processor 459 is also responsible for error detection using ACKnowledgement (ACK) and / or negative ACKnowledgement (Negative ACKnowledgement, NACK) protocols to support HARQ operations.

[0338] In the transmission from the second communication device 450 to the first communication device 410, at the second communication device 450, a data source 467 is used to provide upper layer data packets to the controller / processor 459. The data source 467 represents all protocol layers above L2. Similar to the transmission function at the first communication device 410 described in DL, the controller / processor 459 implements header compression, encryption, packet segmentation and reordering, and multiplexing between logical and transport channels based on the radio resource allocation of the first communication device 410, and implements L2 functions for the user plane and the control plane. The controller / processor 459 is also responsible for HARQ operations, retransmission of lost packets, and signaling to the first communication device 410. The transmit processor 468 performs modulation mapping and channel coding processing, and the multi-antenna transmit processor 457 performs digital multi-antenna spatial precoding, including codebook-based precoding and non-codebook-based precoding, and beamforming processing. Then, the transmit processor 468 modulates the generated parallel stream into a multi-carrier / single-carrier symbol stream, which is then provided to different antennas 452 via the transmitter 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 radio frequency symbol stream, and then provides it to the antenna 452.

[0339] In the transmission from the second communication device 450 to the first communication device 410, the function at the first communication device 410 is similar to the reception function at the second communication device 450 described in the transmission from the first communication device 410 to the second communication device 450. Each receiver 418 receives a radio frequency signal through its corresponding antenna 420, converts the received radio frequency signal into a baseband signal, and provides the baseband signal to the multi-antenna reception processor 472 and the reception processor 470. The reception processor 470 and the multi-antenna reception processor 472 jointly implement the functions of L1. The controller / processor 475 implements the L2 functions. The controller / processor 475 can be associated with a memory 476 storing program codes and data. The memory 476 can be referred to as a computer-readable medium. The controller / processor 475 provides demultiplexing between transmission and logical channels, packet reassembly, decryption, header decompression, control signal processing to recover the upper layer data packets from the second communication device 450. The upper layer data packets from the controller / processor 475 can be provided to the core network. The controller / processor 475 is also responsible for error detection using an ACK and / or NACK protocol to support HARQ operations.

[0340] As an embodiment, the second communication device 450 includes: at least one processor and at least one memory, the at least one memory including computer program code; the at least one memory and the computer program code are configured to be used together with the at least one processor. The second communication device 450 device at least receives a first signaling, the first signaling triggers a BWP change; determines whether to report a first information in a first resource set, the first information including a first CSI; the first node does not receive at least one CSI-related opportunity after the BWP change and before the first reference time, the CSI-related opportunity is for channel measurement or interference measurement; whether the first CSI is reported depends on the generation method of the first CSI; when the first CSI is generated based on AI, the first information is reported; when the first CSI is not generated based on AI, the first information is abandoned.

[0341] As an embodiment, the second communication device 450 includes: a memory storing a computer-readable instruction program, wherein the computer-readable instruction program generates an action when executed by at least one processor, and the action includes: receiving a first signaling; determining whether to report first information in a first resource set.

[0342] As an embodiment, the first communication device 410 includes: at least one processor and at least one memory, the at least one memory including computer program code; the at least one memory and the computer program code are configured to be used together with the at least one processor. The first communication device 410 device at least sends a first signaling, the first signaling triggers a BWP change; the sender of the first information is the second communication device 450, the second communication device 450 determines whether to report the first information in the first resource set, the first information includes the first CSI; the first node does not receive at least one CSI-related opportunity after the BWP change and before the first reference time, the CSI-related opportunity is for channel measurement or interference measurement; whether the first CSI is reported by the first node depends on the generation method of the first CSI; when the first CSI is generated based on AI, the first information is reported; when the first CSI is not generated based on AI, the first information is abandoned.

[0343] As an embodiment, the first communication device 410 includes: a memory storing a computer-readable instruction program, wherein the computer-readable instruction program generates an action when executed by at least one processor, and the action includes: sending a first signaling.

[0344] As an embodiment, the first node in the present application includes the second communication device 450.

[0345] As an embodiment, the second node in the present application includes the first communication device 410.

[0346] As an embodiment, at least one of {the antenna 420, the transmitter 418, the transmit processor 416, the multi-antenna transmit processor 471, the controller / processor 475, and the memory 476} is used to send a first signaling; and 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, and the data source 467} is used to receive a first signaling.

[0347] As an embodiment, 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, and the data source 467} is used to determine whether to report the first information in the first resource set.

[0348] As an embodiment, at least one of {the antenna 420, the transmitter 418, the transmit processor 416, the multi-antenna transmit processor 471, the controller / processor 475, and the memory 476} is used to send a first configuration information block; and 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, and the data source 467} is used to receive a first configuration information block.

[0349] As an embodiment, at least one of {the antenna 452, the receiver 454, the receiving processor 456, the multi-antenna receiving processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to perform channel measurement in the first time window.

[0350] As an embodiment, 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, and the data source 467} is used to report first information in a first resource set; at least one of {the antenna 420, the receiver 418, the receive processor 470, the multi-antenna receive processor 472, the controller / processor 475, and the memory 476} is used to receive first information in a first resource set.

[0351] Example 5

[0352] Embodiment 5 illustrates a flow chart of transmission between a first node and a second node according to an embodiment of the present application, as shown in the attached figure. Figure 5 As shown in the attached Figure 5 In the embodiment, the first node U1 communicates with the second node N2 via a wireless link; Figure 5 The steps in block F51 and block F52 are optional. It should be noted that the sequence in this embodiment does not limit the signal transmission sequence and implementation sequence in this application.

[0353] For the first node U1, a first configuration information block is received in step S5110; a first signaling is received in step S510; a determination is made in step S511 whether to report first information in a first resource set; and first information is reported in a first resource set in step S5120.

[0354] For the second node N2, a first configuration information block is sent in step S5210; a first signaling is sent in step S520; and first information is received in a first resource set in step S5220.

[0355] In Example 5, the first signaling triggers a BWP change; the first information includes a first CSI; the first node does not receive at least one CSI-related opportunity after the BWP change and before the first reference time, and the CSI-related opportunity is for channel measurement or interference measurement; whether the first CSI is reported depends on the generation method of the first CSI; when the first CSI is generated based on AI, the first information is reported; when the first CSI is not generated based on AI, the first information is abandoned.

[0356] As an embodiment, the first node U1 is the first node in this application.

[0357] As an embodiment, the second node N2 is the second node in this application.

[0358] As an embodiment, the air interface between the second node N2 and the first node U1 includes a wireless interface between a base station device and a user equipment.

[0359] As an embodiment, the air interface between the second node N2 and the first node U1 includes a wireless interface between a relay node device and a user equipment.

[0360] As an embodiment, the air interface between the second node N2 and the first node U1 includes a wireless interface between user equipments.

[0361] As an embodiment, the second node N2 and the first node U1 communicate with each other via a Uu interface.

[0362] As an embodiment, the second node N2 is a base station maintaining a service cell of the first node U1.

[0363] As an embodiment, the physical layer channel occupied by the first signaling includes PDCCH (Physical Downlink Control CHannel, physical downlink control channel).

[0364] As an embodiment, the physical layer channel occupied by the first signaling includes PDSCH (Physical Downlink Shared CHannel, physical downlink shared channel).

[0365] As an embodiment, step S511 is performed after step S510.

[0366] As an example, Figure 5 The steps in box F51 exist; the method applied to the first node N1 in the present application includes: receiving a first configuration information block.

[0367] As an embodiment, the first configuration information block is carried by higher layer signaling.

[0368] As an embodiment, the first configuration information block is transmitted via RRC (Radio Resource Control) signaling.

[0369] As an embodiment, the first configuration information block is carried by RRC layer signaling.

[0370] As an embodiment, the first configuration information block includes one or more RRC IE (Information Element, information unit).

[0371] As an embodiment, the first configuration information block includes one or more fields in an RRC IE.

[0372] As an embodiment, the first configuration information block includes one or more fields of each RRC IE in multiple RRC IEs.

[0373] As an embodiment, the first configuration information block includes ServingCellConfig IE.

[0374] As an embodiment, the first configuration information block includes one or more fields in the ServingCellConfig IE.

[0375] As an embodiment, the first configuration information block includes CSI-MeasConfig IE.

[0376] As an embodiment, the first configuration information block includes one or more fields in the CSI-MeasConfig IE.

[0377] As an embodiment, the first configuration information block includes CSI-AperiodicTriggerStateListIE.

[0378] As an embodiment, the first configuration information block includes one or more fields in the CSI-AperiodicTriggerStateList IE.

[0379] As an embodiment, the first configuration information block includes CSI-AperiodicTriggerState IE.

[0380] As an embodiment, the first configuration information block includes one or more fields in the CSI-AperiodicTriggerState IE.

[0381] As an embodiment, the first configuration information block includes CSI-AssociatedReportConfigInfoIE.

[0382] As an embodiment, the first configuration information block includes one or more fields in CSI-AssociatedReportConfigInfoIE.

[0383] As an embodiment, the first configuration information block includes CSI-SemiPersistentOnPUSCH-TriggerStateList IE.

[0384] As an embodiment, the first configuration information block includes one or more fields in the CSI-SemiPersistentOnPUSCH-TriggerStateList IE.

[0385] As an embodiment, the first configuration information block includes CSI-SemiPersistentOnPUSCH-TriggerState IE.

[0386] As an embodiment, the first configuration information block includes one or more fields in the CSI-SemiPersistentOnPUSCH-TriggerState IE.

[0387] As an embodiment, the first configuration information block includes CSI-ReportSubConfigTriggerListIE.

[0388] As an embodiment, the first configuration information block includes one or more fields in CSI-ReportSubConfigTriggerListIE.

[0389] As an embodiment, the first configuration information block includes CSI-ReportConfig IE.

[0390] As an embodiment, the first configuration information block includes one or more fields in the CSI-ReportConfig IE.

[0391] As an embodiment, the first configuration information block includes CSI-ReportSubConfig IE.

[0392] As an embodiment, the first configuration information block includes one or more fields in the CSI-ReportSubConfig IE.

[0393] As an embodiment, the first configuration information block includes NZP-CSI-RS-Resource IE.

[0394] As an embodiment, the first configuration information block includes one or more fields in the NZP-CSI-RS-Resource IE.

[0395] As an embodiment, the first configuration information block includes NZP-CSI-RS-ResourceSet IE.

[0396] As an embodiment, the first configuration information block includes one or more fields in the NZP-CSI-RS-ResourceSet IE.

[0397] As an embodiment, the first configuration information block includes CSI-IM-Resource IE.

[0398] As an embodiment, the first configuration information block includes one or more fields in the CSI-IM-Resource IE.

[0399] As an embodiment, the first configuration information block includes CSI-IM-ResourceSet IE.

[0400] As an embodiment, the first configuration information block includes one or more fields in the CSI-IM-ResourceSet IE.

[0401] As an embodiment, the first configuration information block includes CSI-SSB-ResourceSet IE.

[0402] As an embodiment, the first configuration information block includes one or more fields in the CSI-SSB-ResourceSet IE.

[0403] As an embodiment, the first configuration information block includes CSI-ResourceConfig IE.

[0404] As an embodiment, the first configuration information block includes one or more fields in the CSI-ResourceConfig IE.

[0405] As an embodiment, the name of the RRC signaling used to transmit the first configuration information block includes CSI.

[0406] As an embodiment, the name of the RRC signaling used to transmit the first configuration information block includes Report.

[0407] As an embodiment, the name of the RRC signaling used to transmit the first configuration information block includes Resource.

[0408] As an embodiment, the name of the RRC signaling used to transmit the first configuration information block includes Config.

[0409] As an embodiment, the first configuration information block indicates a first identifier.

[0410] As an embodiment, the first identifier is an AI model ID (identifier).

[0411] As an embodiment, the first identifier is AI-model-Id.

[0412] As an embodiment, the first identifier is model-Id.

[0413] As an embodiment, the first identifier is a non-zero integer.

[0414] As an embodiment, the first identifier indicates an AI model ID (identifier).

[0415] As an embodiment, the first identifier indexes the ML model (also called AI model) used for the ML reasoning.

[0416] As an embodiment, the first identification indication is used to generate the first CSI data set.

[0417] As an embodiment, the first configuration information block includes a bit indicating the first identifier.

[0418] As an embodiment, the first configuration information block includes a field indicating the first identifier.

[0419] As an embodiment, the first configuration information block does not indicate the first identifier.

[0420] As an embodiment, the first configuration information block indicates that the domain of the first identifier is a default.

[0421] As an embodiment, the first configuration information block configures configuration information of AI-based CSI.

[0422] As an embodiment, the transmission channel occupied by the first configuration information block includes DL-SCH (DownLink-Shared CHannel, downlink shared channel).

[0423] As an embodiment, the physical layer channel occupied by the first configuration information block includes PDSCH (Physical Downlink Shared CHannel, physical downlink shared channel).

[0424] As an embodiment, the steps in box F51 exist, and step S5110 is before step S510; step S5210 is before step S520.

[0425] As an example, Figure 5 The steps in box F52 exist; the method applied to the first node N1 in the present application includes: reporting first information in a first resource set; the first information includes the first identifier; the first identifier indicates that the first CSI is generated based on AI.

[0426] As an embodiment, the first information includes UCI (Uplink Control Information, uplink control information).

[0427] As an embodiment, the first information includes a first identifier.

[0428] As an embodiment, the first information includes a bit indicating the first identifier.

[0429] As an embodiment, the first information includes a field indicating the first identifier.

[0430] As an embodiment, the time domain resources occupied by the first information indicate the first identifier.

[0431] As an embodiment, the frequency domain resources occupied by the first information indicate the first identifier.

[0432] As an embodiment, the time-frequency resources occupied by the first information indicate the first identifier.

[0433] As an embodiment, the first identifier indicates that the first CSI is generated based on AI, which means that the first identifier indicates the ID of the model that generates the first CSI.

[0434] As an embodiment, the meaning that the first identifier indicates that the first CSI is generated based on AI includes: the first identifier indicates that the first CSI is generated based on prediction.

[0435] As an embodiment, the meaning that the first identifier indicates that the first CSI is generated based on AI includes: the first identifier indicates that the first CSI is generated based on reasoning.

[0436] As an embodiment, the first identifier indicates that the first CSI is generated based on AI, which means that the first identifier indicates the ID of the data used to generate the first CSI.

[0437] As an embodiment, the first identifier indicates that the first CSI is generated based on AI, which means that the first identifier indicates the ID of the data set used to generate the first CSI.

[0438] As an embodiment, the transmission channel occupied by the first information includes UL-SCH (Up Link-Shared CHannel, uplink shared channel).

[0439] As an embodiment, the physical layer channel occupied by the first information includes PUSCH.

[0440] As an embodiment, the physical layer channel occupied by the first information includes PUCCH.

[0441] As an embodiment, the steps in box F52 exist, and step S5120 is after step S511; step S5220 is after step S520.

[0442] As an embodiment, the steps in box F51 exist and the steps in box F52 exist.

[0443] As an embodiment, the steps in block F51 exist and the steps in block F52 do not exist.

[0444] As an embodiment, the step in block F51 does not exist, and the step in block F52 does not exist.

[0445] Example 6

[0446] Example 6 illustrates a schematic diagram of a first time window according to an embodiment of the present application, as shown in the attached figure. Figure 6 As shown in the attached Figure 6 In the embodiment, the end time of the first time window is a first reference time; the first node receives at least one CSI-related opportunity in the first time window.

[0447] In Example 6, the first node performs channel measurement in the first time window; the first CSI is generated based on AI; the duration of the first time window depends on the model for generating the first CSI, or the duration of the first time window depends on the first identifier in the present application and the model for generating the first CSI is associated with the first identifier in the present application.

[0448] As an embodiment, the first node performs channel measurement in the first time window.

[0449] As an embodiment, the duration of the first time window in the time domain is multiple time slots.

[0450] Typically, one time slot in the present application includes 14 consecutive multi-carrier symbols in the time domain.

[0451] As an embodiment, the duration of the first time window in the time domain is multiple milliseconds.

[0452] As an embodiment, the first time window includes the moment when the BWP changes as described in this application.

[0453] As an embodiment, the starting time of the first time window is before the BWP is changed in the present application.

[0454] As an embodiment, the BWP change does not stop the first time window.

[0455] As an embodiment, the duration of the first time window depends on a model for generating the first CSI.

[0456] As an embodiment, the model for generating the first CSI is one of K1 candidate models, the K1 candidate models correspond to K1 time windows respectively, and the model for generating the first CSI is used to determine the first time window from the K1 time windows, and K1 is a positive integer greater than 1.

[0457] As a sub-embodiment of this embodiment, the K1 time windows correspond to K1 durations respectively.

[0458] As an embodiment, the duration of the first time window depends on the first identifier in the present application and the model for generating the first CSI is associated with the first identifier in the present application.

[0459] As an embodiment, the model for generating the first CSI is one of K1 candidate models, the K1 candidate models correspond to K1 identifiers respectively, the model for generating the first CSI is used to determine the first identifier from the K1 identifiers, and K1 is a positive integer greater than 1.

[0460] As a sub-embodiment of this embodiment, the K1 identifiers correspond to K1 durations respectively.

[0461] As a sub-embodiment of this embodiment, the K1 identifiers are respectively configured with K1 durations.

[0462] Example 7

[0463] Example 7 illustrates a schematic diagram of BWP changes according to an embodiment of the present application, as shown in the attached Figure 7 As shown in the attached Figure 7 In the embodiment, the BWP change triggered by the first signaling includes switching from the first BWP to the second BWP.

[0464] In Embodiment 7, at least one downlink signal in the first BWP is quasi-co-located with a downlink signal in the second BWP.

[0465] As an embodiment, the first BWP and the second BWP have different bwp-Ids.

[0466] As an embodiment, the first signaling is used to determine the bwp-Id of the second BWP.

[0467] As an embodiment, the first signaling indicates the bwp-Id of the second BWP.

[0468] As an embodiment, the first BWP includes at least one RB.

[0469] As an embodiment, the second BWP includes at least one RB.

[0470] As an embodiment, the first BWP and the second BWP occupy overlapping frequency domain resources.

[0471] As an embodiment, the frequency domain resources occupied by the first BWP include the frequency domain resources occupied by the second BWP.

[0472] As an embodiment, the first BWP and the second BWP occupy orthogonal frequency domain resources.

[0473] As an embodiment, the first signaling includes a DCI, and a Bandwidthpart indicator in a DCI field in the first signaling is used to determine the second BWP.

[0474] As an embodiment, the first signaling includes a DCI, and a Bandwidthpart indicator in a DCI field in the first signaling is used to indicate the second BWP.

[0475] As an embodiment, the first signaling includes a DCI, and the DCI field Bandwidthpart indicator in the first signaling includes a bit, and the one bit indicates the bwp-Id of the second BWP.

[0476] As an embodiment, the first signaling includes a DCI, and the DCI field Bandwidthpart indicator in the first signaling includes two bits, and the two bits indicate the bwp-Id of the second BWP.

[0477] As an embodiment, the bwp-Id of the second BWP is equal to the value of the Bandwidthpart indicator in the DCI domain in the first signaling plus 1.

[0478] As an embodiment, the bwp-Id of the second BWP is equal to the value of the DCI domain Bandwidthpart indicator in the first signaling.

[0479] As an embodiment, the first BWP and the second BWP are quasi co-located (Quasi Co-Located, QCLed).

[0480] As an embodiment, any one downlink signal in the first BWP and one downlink signal in the second BWP are quasi-co-located.

[0481] As an embodiment, a downlink signal in the first BWP and a downlink signal in the second BWP are quasi-co-located.

[0482] As an embodiment, any one downlink signal in the second BWP and one downlink signal in the first BWP are quasi-co-located.

[0483] As an embodiment, a downlink signal in the second BWP and a downlink signal in the first BWP are quasi-co-located.

[0484] As an embodiment, the first configuration information block in the present application indicates a first reference signal resource, and there is a reference signal resource in the first BWP that is quasi-co-located with the first reference signal resource.

[0485] As an embodiment, the types of QCL described in this application include typeA, typeB, typeC and typeD.

[0486] As an embodiment, the specific definitions of typeA, typeB, typeC and typeD described in this application refer to Section 5.1.5 of 3GPP TS 38.214.

[0487] As an embodiment, the downlink signal includes CSI-RS.

[0488] As an embodiment, the downlink signal includes SSB.

[0489] As an embodiment, the SSB described in this application refers to: Synchronization Signal Block.

[0490] As an embodiment, the SSB described in this application refers to: SS (Synchronization Signal) / PBCH (Physical Broadcast Channel) block, synchronization signal / physical broadcast channel block.

[0491] Typically, the reception timings of the PBCH, PSS (Primary Synchronization Signal) and SSS (Secondary Synchronization Signal) are in consecutive symbols and form an SS / PBCH block.

[0492] Example 8

[0493] Embodiment 8 illustrates a schematic diagram of RAN domain AI / ML function deployment according to an embodiment of the present application, as shown in the attached figure. Figure 8 As shown in the attached Figure 8 In this case, gNB can be replaced by network equipment such as eNB or 6G base station.

[0494] In Embodiment 8, the management of the ML reasoning functions of multiple base stations is completed by the RAN domain management function 802, that is, data interaction with the RAN domain MnS (Management Service) consumer / cross-domain management 801 (see attached Figure 8 ). The RAN domain ML training function 803 is located in the RAN domain management function 802; and the ML reasoning function is located in the base station, that is, the AI / ML reasoning function 804 is located in the gNB 805, the AI / ML reasoning function 806 is located in the gNB 807, and so on.

[0495] AI / ML related functions include ML training function (also called AI training, or AI / ML training), ML testing function, ML inference function (also called AI inference, or AI / ML inference), etc. ML training function, ML testing function, and ML inference function can be deployed independently or co-located. The deployment of AI / ML related functions can be achieved through software, such as downloading and / or running executable files; it can also be achieved through a combination of software and hardware, such as accelerating specific computing units through hardware to increase computing speed or save power consumption.

[0496] For ML training functions, they can be deployed in a cross-domain management system or a domain-specific management system; the domain-specific management system is used to manage the RAN domain or the CN (Core Network) domain. For example, the ML training function for MDA (Management Data Analytics) can be deployed in MDAF (Management Data Analytic Function); ML training for network data analysis can be deployed in NWDAF (Network Data Analytics Function), that is, the ML training function is MTLF (Model Training Logical Function).

[0497] The ML reasoning function can also be deployed in a cross-domain management system or a domain-specific management system; for example, the ML reasoning function is MDAF, or the ML reasoning function is AnLF (Analytics Logical Function) located in NWDAF.

[0498] Similarly, ML testing capabilities can also be deployed in cross-domain management systems, or domain-specific management systems.

[0499] Optionally, the management of the ML reasoning function may also be performed by the base station itself, that is, each base station may independently interact with the RAN domain MnS consumer / cross-domain management 801 for data.

[0500] It should be noted that Example 8 is merely a non-restrictive implementation method; optionally, the ML training function of the RAN domain may also be deployed in the base station; or optionally, some base stations deploy the ML reasoning function and the ML training function of the RAN domain, while some base stations only deploy the ML reasoning function.

[0501] As an embodiment, a gNB (or base station) in Embodiment 8 is the second node of the present application.

[0502] Example 9

[0503] Embodiment 9 illustrates a schematic diagram of the AI / ML function deployment of a UE according to an embodiment of the present application, as shown in the attached Fig. 9 As shown in the attached Fig. 9 In the example, the RAN domain ML training function 904 is optional.

[0504] The UE function 903 is deployed in the first node of the present application, and the UE function 903 includes an AI / ML reasoning function 905; the AI / ML reasoning function 905 uses an ML model (also called an AI model) for reasoning; an ML model is usually trained before being used for AI / ML reasoning.

[0505] As an embodiment, the UE function 903 includes a RAN domain ML training function 904, and the RAN domain ML training function 904 runs the training data through the ML model to derive relevant losses, and adjusts the parameters of the ML model based on the calculated losses; the ML training includes at least one of ML initial training, ML re-training, and reinforcement learning; the above scheme reduces the complexity of the base station, or saves air interface resources caused by reporting training data; however, it places higher requirements on the processing capabilities on the UE side.

[0506] Optionally, the UE function 903 also includes a CN domain ML training function ( Fig. 9 not included).

[0507] Optionally, the UE function 903 further includes an AI / ML deployment function: Fig. 9 Not included, used to load ML models and data.

[0508] As an embodiment, the first node indicates whether the ML training function is supported (RAN domain or CN domain) through capability reporting, and the capability reporting is RRC signaling, or NAS (Non-Access Stratum) signaling.

[0509] As an embodiment, the ML model and related metadata are loaded by the first node from a network device or a remote server.

[0510] Optionally, the UE function 903 is an MnS producer, providing data to the CN domain MnF (Management Function) and / or the RAN domain MnF and / or the cross-domain management system 901 for management or analysis (as shown by the double arrow 902).

[0511] Optionally, the UE function 903 is an MnS consumer, loading data from the CN domain MnF and / or the RAN domain MnF and / or the cross-domain management system 901 for AI / ML related management, such as management data requests, ML model activation, and / or ML training, etc. (as shown by the double arrow 902).

[0512] As an embodiment, the first CSI in the present application is obtained through reasoning of the AI / ML reasoning function 905.

[0513] As an embodiment, the ML model is based on a neural network.

[0514] As an embodiment, the ML model is based on CNN (Conventional Neural Networks).

[0515] As an embodiment, the ML model is based on the Transformer architecture.

[0516] As an embodiment, the ML model is based on ResNet (Residual Network) CSI reporting.

[0517] Example 10

[0518] Embodiment 10 illustrates a schematic diagram of a processing system based on artificial intelligence or machine learning according to an embodiment of the present application, as shown in the attached Fig.10 As shown in the attached Fig.10 In the invention, the processing system based on artificial intelligence or machine learning includes a first processor, a second processor, a third processor and a fourth processor.

[0519] In Embodiment 10, the first processor sends a first data set to the second processor, and sends a second data set to the third processor; the second processor generates a target first-category parameter group based on the first data set, and the second processor sends the generated target first-category parameter group to the third processor; the third processor processes the second data set using the target first-category parameter group to obtain a first-category output, and optionally, the third processor sends the first-category output to the fourth processor. Fig.10 In the embodiment, the first type of feedback and the second type of feedback are optional; the second processor includes ML training function; and the third processor includes ML reasoning function.

[0520] As an embodiment, the fourth processor includes ML testing functionality.

[0521] As an embodiment, the fourth processor includes performance monitoring / evaluation of the ML model.

[0522] As an embodiment, the third processor sends the first type of feedback to the second processor; the first type of feedback is used to trigger recalculation or updating of the target first type parameter group, that is, triggering ML initial training or ML retraining.

[0523] As an embodiment, the fourth processor sends a second type of feedback to the first processor; the second type of feedback is used to generate the first data set or the second data set, or the second type of feedback is used to trigger the sending of the first data set or the sending of the second data set.

[0524] As an embodiment, the first processor generates the first data set and the second data set based on measurement of a reference signal.

[0525] As an embodiment, the third processor belongs to the first node, and the fourth processor belongs to the second node.

[0526] As an embodiment, the first type of output includes the first information.

[0527] As an embodiment, the first data set includes training data.

[0528] As an embodiment, the second processor is used to train an ML model, and the trained model is described by the target first-category parameter group.

[0529] As an embodiment, the second processor belongs to the first node; the above method avoids transferring the first data set to the second node.

[0530] As an embodiment, the second processor belongs to the second node; the above method supports joint training and optimizes system performance.

[0531] As an embodiment, the second processor belongs to the core network; the above method supports joint training of the entire network, further optimizing system performance.

[0532] As an embodiment, the second data set includes inference data.

[0533] As an embodiment, the third processor belongs to the first node.

[0534] As an embodiment, the third processing machine constructs a model according to the target first-category parameter group, and then inputs the second data set into the constructed model to obtain the first-category output.

[0535] As an embodiment, the second data set includes a channel matrix measured by the first node in the first time window.

[0536] As an embodiment, the first type of output includes the first CSI.

[0537] As an embodiment, the second data set includes a received reference signal.

[0538] As an embodiment, the first type of output includes a channel matrix.

[0539] As an embodiment, the third processing machine generates a restored data set according to the first type of output, and an error between the restored data set and the second data set is used to generate the first type of feedback.

[0540] As an embodiment, the first type of feedback is used to reflect the performance of the trained model; when the performance of the trained model cannot meet the requirements, the second processor will recalculate the target first type parameter group.

[0541] As an embodiment, when the error is too large or has not been updated for too long, the performance of the trained model is considered to be unable to meet the requirements.

[0542] As an embodiment, the target first-category parameter group includes: one or more of a convolution kernel, a pooling kernel, a pooling function, an activation function, parameters of a pooling function, or parameters of an activation function.

[0543] As an embodiment, the target first category parameter group includes: convolution kernel size, number of convolution layers, convolution step, pooling kernel size, pooling kernel step, pooling function, activation function, or one or more of the number of feature maps.

[0544] Embodiment 11

[0545] Embodiment 11 illustrates a schematic diagram based on artificial intelligence or machine learning according to an embodiment of the present application, as shown in the attached Fig.11 As shown in the attached Fig.11 In the embodiment, the first operation and the second operation belong to the first stage, the third operation belongs to the second stage, the fourth operation belongs to the third stage, and the fifth operation belongs to the fourth stage; the lines with arrows indicate the order of the process.

[0546] As an embodiment, the first operation includes AI / ML training, the second operation includes AI / ML testing, the third operation includes AI / ML simulation, the fourth operation includes AI / ML entity loading, and the fifth operation includes AI / ML inference.

[0547] As an embodiment, 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.

[0548] As an embodiment, the first stage includes AI / ML model training.

[0549] As an embodiment, the first stage includes AI / ML model training and AI / ML testing.

[0550] As an embodiment, the AI / ML model training includes initial training and re-training of one or a group of AI / ML entities.

[0551] As an embodiment, the AI / ML model training relies on training data.

[0552] As an embodiment, the AI / ML model training includes AI / ML entity validation.

[0553] As an embodiment, the AI / ML entity verification is used to evaluate the performance of the AI / ML entity.

[0554] As an embodiment, the AI / ML entity verification relies on verification data.

[0555] As an example, if the result of AI / ML entity verification does not meet expectations, the AI / ML model will be retrained.

[0556] As an embodiment, the AI / ML testing includes testing the verified AI / ML entity to estimate the performance of the trained AI / ML model.

[0557] As an example, if the result of the AI / ML test meets expectations, the AI / ML entity proceeds to the next stage; otherwise the AI / ML model will be retrained.

[0558] As an embodiment, the AI / ML testing relies on test data.

[0559] As an embodiment, the second stage includes AI / ML simulation, which performs reasoning of AI / ML entities in a simulation environment.

[0560] As an embodiment, the AI / ML simulation estimates the performance of AI / ML entity reasoning in a simulation environment before using the AI / ML entity.

[0561] As an embodiment, the second stage is optional.

[0562] As an embodiment, the third stage includes AI / ML entity loading, and the AI / ML entity loading is to obtain the trained AI / ML entity to obtain the desired AI / ML reasoning function.

[0563] As an embodiment, the third stage is optional.

[0564] As an example, when the training function and the inference function are co-located, the third stage is no longer required.

[0565] As an embodiment, the fourth stage includes AI / ML reasoning.

[0566] As an embodiment, the first CSI is generated based on AI, and the first CSI is output by the fourth stage.

[0567] Example 12

[0568] Embodiment 12 illustrates a structural block diagram of a processing device used in a first node according to an embodiment of the present application, as shown in the attached figure. Fig.12 As shown in the attached Fig.12 In the embodiment, the processing device 1200 in the first node includes a first receiver 1201 and a first transmitter 1202.

[0569] In Embodiment 12, the first receiver 1201 receives first signaling, and the first signaling triggers a BWP change; the first transmitter 1202 determines whether to report first information in a first resource set, and the first information includes a first CSI.

[0570] In embodiment 12, the first node does not receive at least one CSI-related opportunity after the BWP changes and before the first reference time, and the CSI-related opportunity is for channel measurement or interference measurement; whether the first CSI is reported depends on the generation method of the first CSI; when the first CSI is generated based on AI, the first information is reported; when the first CSI is not generated based on AI, the first information is abandoned.

[0571] As an embodiment, the first CSI being generated based on AI means at least one of the following:

[0572] - the first CSI is generated by prediction;

[0573] - the first CSI is generated by inference;

[0574] -The first CSI is generated by a model, and the model is at least one of AI or ML.

[0575] As an embodiment, the CSI-related opportunities include at least the first two of a CSI-RS transmission opportunity for channel measurement, a CSI-RS, and a CSI-IM opportunity for interference measurement.

[0576] As an embodiment, the first reference time depends on the time domain resources occupied by the CSI reference resources of the first CSI, or the first reference time depends on the time domain resources occupied by the first resource set.

[0577] As an embodiment, the first receiver 1201 receives a first configuration information block; the first transmitter 1202 reports the first information in the first resource set; the first information includes a first identifier, or the first configuration information block indicates a first identifier; the first identifier indicates that the first CSI is generated based on AI.

[0578] As an embodiment, the first receiver 1201 performs channel measurement in a first time window; the first CSI is generated based on AI; the end time of the first time window is the first reference time; the first node receives at least one CSI-related opportunity in the first time window; the duration of the first time window depends on a model for generating the first CSI, or the duration of the first time window depends on a first identifier and the model for generating the first CSI is associated with the first identifier.

[0579] As an embodiment, the BWP change triggered by the first signaling includes switching from a first BWP to a second BWP, and at least one downlink signal in the first BWP is quasi-co-located with a downlink signal in the second BWP.

[0580] As an embodiment, the first CSI is generated based on AI, which means that the channel information recovered by the receiver based on the received first CSI is unknown to the first node.

[0581] As an embodiment, the first CSI is generated based on AI, which means that: a generator for generating the first CSI is obtained based on training.

[0582] As an embodiment, the first CSI being generated based on AI means that the first CSI does not belong to the CSI defined in 3GPP Rel-18 or a version earlier than 3GPP Rel-18.

[0583] As an embodiment, the first signaling carries the bwp-Id of the second BWP in this application.

[0584] As an embodiment, in response to receiving the first signaling, the active BWP of the first node is switched from the first BWP in the present application to the second BWP in the present application.

[0585] As an embodiment, the first configuration information block in the present application indicates a first reference signal resource, and there is a reference signal resource in the first BWP that is quasi-co-located with the first reference signal resource.

[0586] As an embodiment, the first time window includes the moment when the BWP changes as described in this application.

[0587] As an embodiment, the starting time of the first time window is before the BWP is changed in the present application.

[0588] As an embodiment, the first node is user equipment.

[0589] As an embodiment, the first node is a relay node device.

[0590] As an embodiment, the first receiver 1201 includes at least one of {the antenna 452, the receiver 454, the receiving processor 456, the multi-antenna receiving processor 458, the controller / processor 459, the memory 460, and the data source 467} in Example 4.

[0591] As an embodiment, the first transmitter 1202 includes 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, and the data source 467} in Embodiment 4.

[0592] Example 13

[0593] Embodiment 13 illustrates a structural block diagram of a processing device used in a second node according to an embodiment of the present application, as shown in the attached figure. Fig.13 As shown in the attached Fig.13 In the embodiment, the processing device 1300 in the second node includes a second transmitter 1301 and a second receiver 1302, wherein the second receiver 1302 is optional.

[0594] In Embodiment 13, the second transmitter 1301 sends a first signaling, and the first signaling triggers a BWP change.

[0595] In embodiment 13, the sender of the first information is a first node, and the first node determines whether to report the first information in a first resource set, and the first information includes a first CSI; the first node does not receive at least one CSI-related opportunity after the BWP changes and before the first reference time, and the CSI-related opportunity is for channel measurement or interference measurement; whether the first CSI is reported by the first node depends on the generation method of the first CSI; when the first CSI is generated based on AI, the first information is reported; when the first CSI is not generated based on AI, the first information is abandoned.

[0596] As an embodiment, the first CSI being generated based on AI means at least one of the following:

[0597] - the first CSI is generated by prediction;

[0598] - the first CSI is generated by inference;

[0599] -The first CSI is generated by a model, and the model is at least one of AI or ML.

[0600] As an embodiment, the CSI-related opportunities include at least the first two of a CSI-RS transmission opportunity for channel measurement, a CSI-RS, and a CSI-IM opportunity for interference measurement.

[0601] As an embodiment, the first reference time depends on the time domain resources occupied by the CSI reference resources of the first CSI, or the first reference time depends on the time domain resources occupied by the first resource set.

[0602] As an embodiment, the second transmitter 1301 sends a first configuration information block; the second receiver 1302 receives the first information in the first resource set; the first information includes a first identifier, or the first configuration information block indicates a first identifier; the first identifier indicates that the first CSI is generated based on AI.

[0603] As an embodiment, the first node performs channel measurement in a first time window; the first CSI is generated based on AI; the end time of the first time window is the first reference time; the first node receives at least one CSI-related opportunity in the first time window; the duration of the first time window depends on a model for generating the first CSI, or the duration of the first time window depends on a first identifier and the model for generating the first CSI is associated with the first identifier.

[0604] As an embodiment, the BWP change triggered by the first signaling includes switching from a first BWP to a second BWP, and at least one downlink signal in the first BWP is quasi-co-located with a downlink signal in the second BWP.

[0605] As an embodiment, the first CSI is generated based on AI, which means that the channel information recovered by the second node based on the received first CSI is unknown to the sender.

[0606] As an embodiment, the first CSI is generated based on AI, which means that: a generator for generating the first CSI is obtained based on training.

[0607] As an embodiment, the first CSI being generated based on AI means that the first CSI does not belong to the CSI defined in 3GPP Rel-18 or a version earlier than 3GPP Rel-18.

[0608] As an embodiment, the first signaling carries the bwp-Id of the second BWP in this application.

[0609] As an embodiment, in response to receiving the first signaling, the active BWP of the first node is switched from the first BWP in the present application to the second BWP in the present application.

[0610] As an embodiment, the first configuration information block in the present application indicates a first reference signal resource, and there is a reference signal resource in the first BWP that is quasi-co-located with the first reference signal resource.

[0611] As an embodiment, the first time window includes the moment when the BWP changes as described in this application.

[0612] As an embodiment, the starting time of the first time window is before the BWP is changed in the present application.

[0613] As an embodiment, the second node is a base station device.

[0614] As an embodiment, the second node is user equipment.

[0615] As an embodiment, the second node is a TRP.

[0616] As an embodiment, the second transmitter 1301 includes at least one of {the antenna 420, the transmitter 418, the transmit processor 416, the multi-antenna transmit processor 471, the controller / processor 475, and the memory 476} in Embodiment 4.

[0617] As an embodiment, the second receiver 1302 includes at least one of {the antenna 420, the receiver 418, the receiving processor 470, the multi-antenna receiving processor 472, the controller / processor 475, and the memory 476} in Embodiment 4.

[0618] A person of ordinary skill in the art can understand that all or part of the steps in the above method can be completed by instructing the relevant hardware through a program, and the program can be stored in a computer-readable storage medium, such as a read-only memory, a hard disk or an optical disk. Optionally, all or part of the steps in the above embodiment can also be implemented using one or more integrated circuits. Accordingly, each module unit in the above embodiment 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 software and hardware combination. The user equipment, terminal and UE in the present application include but are not limited to drones, communication modules on drones, remote-controlled aircraft, aircraft, small aircraft, mobile phones, tablet computers, notebooks, vehicle-mounted communication equipment, transportation tools, vehicles, RSUs, wireless sensors, Internet cards, Internet of Things terminals, RFID (Radio Frequency Identification, Radio Frequency Identification Technology) terminals, NB-IoT (Narrow Band Internet of Things, Narrow Band Internet of Things) terminals, MTC (Machine Type Communication, Machine Type Communication) terminals, eMTC (enhanced MTC, enhanced MTC) terminals, data cards, Internet cards, vehicle-mounted communication equipment, low-cost mobile phones, low-cost tablet computers and other wireless communication devices. The base stations or system equipment in this application include but are not limited to macrocell base stations, microcell base stations, small cell base stations, home base stations, relay base stations, eNB (evolved Node B), gNB, TRP, GNSS (Global Navigation Satellite System), relay satellites, satellite base stations, aerial base stations, RSU, drones, test equipment, such as transceivers that simulate some functions of base stations or signaling testers and other wireless communication equipment.

[0619] It should be understood by those skilled in the art that the present invention may be implemented in other specified forms without departing from its core or essential features. Therefore, the embodiments disclosed herein should be considered illustrative rather than restrictive in any way. The scope of the invention is determined by the appended claims rather than the preceding description, and all modifications within their equivalent meanings and regions are considered to be included therein.

Claims

1. A first node used in a wireless communication reference signal, characterized in that: include: A first receiver receives a first signaling, wherein the first signaling triggers a BWP change; A first transmitter determines whether to report first information in a first resource set, where the first information includes a first CSI; Among them, the first node does not receive at least one CSI-related opportunity after the BWP changes and before the first reference time, and the CSI-related opportunity is for channel measurement or interference measurement; whether the first CSI is reported depends on the generation method of the first CSI; when the first CSI is generated based on AI, the first information is reported; when the first CSI is not generated based on AI, the first information is abandoned.

2. The first node according to claim 1, characterized in that: The first CSI is generated based on AI, which means that it includes at least one of the following: - the first CSI is generated by prediction; - the first CSI is generated by inference; -The first CSI is generated by a model, and the model is at least one of AI or ML.

3. The first node according to claim 1 or 2, characterized in that: The CSI-related opportunities include at least the first two of a CSI-RS transmission opportunity for channel measurement, a CSI-RS, and a CSI-IM opportunity for interference measurement.

4. The first node according to any one of claims 1 to 3, characterized in that: The first reference time depends on the time domain resources occupied by the CSI reference resources of the first CSI, or the first reference time depends on the time domain resources occupied by the first resource set.

5. The first node according to any one of claims 1 to 4, characterized in that: include: The first receiver receives a first configuration information block; The first transmitter reports the first information in the first resource set; The first information includes a first identifier, or the first configuration information block indicates a first identifier; the first identifier indicates that the first CSI is generated based on AI.

6. The first node according to any one of claims 1 to 5, characterized in that: include: The first receiver performs channel measurement in a first time window; Among them, the first CSI is generated based on AI; the end time of the first time window is the first reference time; the first node receives at least one CSI-related opportunity in the first time window; the duration of the first time window depends on the model for generating the first CSI, or the duration of the first time window depends on the first identifier and the model for generating the first CSI is associated with the first identifier.

7. The first node according to any one of claims 1 to 6, characterized in that: The BWP change triggered by the first signaling includes switching from a first BWP to a second BWP, and at least one downlink signal in the first BWP is quasi-co-located with a downlink signal in the second BWP.

8. A second node used in a wireless communication reference signal, characterized in that: include: A second transmitter sends a first signaling, wherein the first signaling triggers a BWP change; Among them, the sender of the first information is the first node, the first node determines whether to report the first information in the first resource set, and the first information includes the first CSI; the first node does not receive at least one CSI-related opportunity after the BWP changes and before the first reference time, and the CSI-related opportunity is for channel measurement or interference measurement; whether the first CSI is reported by the first node depends on the generation method of the first CSI; when the first CSI is generated based on AI, the first information is reported; when the first CSI is not generated based on AI, the first information is abandoned.

9. A method for a first node in a wireless communication reference signal, characterized in that: include: receiving a first signaling, wherein the first signaling triggers a BWP change; Determine whether to report first information in a first resource set, where the first information includes first CSI; Among them, the first node does not receive at least one CSI-related opportunity after the BWP changes and before the first reference time, and the CSI-related opportunity is for channel measurement or interference measurement; whether the first CSI is reported depends on the generation method of the first CSI; when the first CSI is generated based on AI, the first information is reported; when the first CSI is not generated based on AI, the first information is abandoned.

10. A method for a second node in a wireless communication reference signal, characterized in that: include: Sending a first signaling, wherein the first signaling triggers a BWP change; Among them, the sender of the first information is the first node, the first node determines whether to report the first information in the first resource set, and the first information includes the first CSI; the first node does not receive at least one CSI-related opportunity after the BWP changes and before the first reference time, and the CSI-related opportunity is for channel measurement or interference measurement; whether the first CSI is reported depends on the generation method of the first CSI; when the first CSI is generated based on AI, the first information is reported; when the first CSI is not generated based on AI, the first information is abandoned.

Images