Method and device for node used for wireless communication

Abstract

The present application discloses a method and device for a node used for wireless communication. A first node performs measurement on a first RS resource, and sends a first information block. The first information block comprises first channel information; the first channel information depends on the measurement on the first RS resource. The first channel information is for a layer l, a first parameter set is used for generating the first channel information, and the first parameter set depends on the layer l. The method reduces reporting overhead while improving reporting performance, thereby improving system performance.

Description

A method and apparatus for use in a node for wireless communication

[0001] This application claims priority to Chinese Patent Application No. 202411513867.7, filed on October 28, 2024, entitled "A Method and Apparatus for Use in a Node for Wireless Communication", the entire contents of which are incorporated herein by reference. Technical Field

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

[0003] In traditional wireless communication, the UE (User Equipment) reports various auxiliary information obtained through measurements of downlink signals and / or channels. This information includes channel information, beam management-related auxiliary information, positioning-related auxiliary information, HARQ-ACK (Hybrid Automatic Repeat reQuest Acknowledgement) information, beam / radio link failure auxiliary information, and so on. The UE reports this information to the network equipment, which then selects appropriate transmission parameters for the UE based on this information. These parameters include the cell to be used, MCS (Modulation and Coding Scheme), TPMI (Transmitted Precoding Matrix Indicator), and TCI (Transmission Configuration Indication). Furthermore, UE reporting can be used to optimize network parameters, such as improving cell coverage and switching base stations on / off based on the UE's location.

[0004] In NRR (release) 18, research on AI (Artificial Intelligence) / ML (Machine Learning) technologies was initiated to explore their impact on system performance and design. AI / ML aims to significantly improve the performance of wireless communications by leveraging advanced artificial intelligence and machine learning techniques. Using AI / ML, systems can not only intelligently provide high-quality services based on perception and learning of the surrounding environment, such as scheduling, data reception, signal processing, encoding / decoding, measurement, and reporting, but also intelligently achieve network self-optimization and self-maintenance. Compared to traditional processing methods, AI / ML has some unique characteristics, such as model dependence, training-based nature, deployment requirements, and different demands on computing / processing and storage capabilities compared to traditional technologies. According to 3GPP (3rd Generation Partner Project) standard TS (Technical Specification) 38.300, AI / ML models and algorithms extend beyond the scope of 3GPP. Summary of the Invention

[0005] The applicant's research revealed that existing measurement, computation, and reporting mechanisms may be inadequate to meet the demands of AI / ML when AI / ML functionality is introduced. For example, AI / ML models are training-based, and training relies on large amounts of training data. The impact of measuring and transmitting large amounts of training data on communication systems is a concern. To address these issues, this application discloses a solution. It should be noted that while this application is motivated by AI / ML applications and many embodiments are specifically designed for AI / ML, it is also applicable to other solutions, such as traditional measurement, computation, and reporting schemes. Although the specification of this application includes descriptions of some AI / ML models and algorithms, those skilled in the art will understand that these descriptions are not essential or irreplaceable for solutions related to wireless cellular communication. Furthermore, adopting a unified solution for different scenarios (including but not limited to AI / ML-based solutions and traditional measurement, computation, and reporting schemes) helps reduce signaling overhead / complexity, hardware complexity, and cost. Where there is no conflict, the embodiments and features in the embodiments of the first node of this application can be applied to the second node, and vice versa. Where there is no conflict, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other.

[0006] When necessary, the interpretation of terms used in this application shall be based on the definitions in the 3GPP specification protocol TS38 series, or the definitions in the 3GPP specification protocol TS28 series.

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

[0008] Measured on the first RS resource;

[0009] Send a first information block, the first information block including first channel information;

[0010] Wherein, the first channel information depends on the measurement on the first RS resource; the first channel information is for layer l, and a first parameter set is used to generate the first channel information, the first parameter set depending on l.

[0011] As an example, the problem this application aims to solve includes how to optimize the reporting of channel information.

[0012] As an example, in the above method, the first set of parameters used to generate the first channel information depends on the layer to which the first channel information is targeted, thereby solving this problem.

[0013] As an example, the above method allows the first node to use different parameters for different layers to generate channel information, which better optimizes the relationship between the reliability and overhead of channel information reporting, and reduces overhead while improving reporting reliability.

[0014] As an example, the advantages of the above method include optimizing the overall system performance.

[0015] As an example, the advantages of the above method include flexible design and adaptability to different terminals.

[0016] As an example, the advantages of the above method include good forward compatibility.

[0017] According to one aspect of this application, it is characterized by comprising:

[0018] Send the second information block;

[0019] The second information block indicates the first parameter set.

[0020] As an example, the advantages of the above method include greater flexibility and adaptability to different terminals and application scenarios.

[0021] According to one aspect of this application, the first information block includes K channel information, where K is a positive integer greater than 1, the first channel information is one of the K channel information, and the K channel information are respectively for K layers; K parameter sets are respectively used to generate the K channel information, and at least two parameter sets in the K parameter sets are different.

[0022] As an example, the advantages of the above method include using different parameters for different layers to generate channel information, thus optimizing the relationship between the reliability and overhead of channel information reporting.

[0023] According to one aspect of this application, the first information block includes a first channel quality, the calculation of which is based on the K channel information.

[0024] As an example, the advantages of the above method include good backward compatibility.

[0025] According to one aspect of this application, it is characterized by comprising:

[0026] Send the second information block;

[0027] The second information block indicates all or part of the parameter sets in the K parameter sets.

[0028] As an example, the advantages of the above method include greater flexibility and adaptability to different terminals and application scenarios.

[0029] According to one aspect of this application, the first channel information is directed to a first time-frequency resource, and the first information block indicates the first time-frequency resource.

[0030] As an example, the advantages of the above method include improving the accuracy and efficiency of reporting by selecting the time-frequency resources targeted by the first channel information according to the actual channel environment.

[0031] According to one aspect of this application, it is characterized by comprising:

[0032] Receive the first configuration information block;

[0033] The first configuration information block indicates at least one of the configuration information of the first RS resource and the first information block.

[0034] As an example, the advantages of the above method include flexible signaling design.

[0035] As an example, the advantages of the above method include good backward compatibility.

[0036] According to one aspect of this application, the first information block belongs to a first dataset.

[0037] As an example, the advantages of the above method include better meeting the specific needs of AI or ML solutions and optimizing the performance improvements brought by AI or ML solutions.

[0038] As an example, the benefits of the above method include optimizing data reporting for AI / ML training.

[0039] According to one aspect of this application, the first information block is transmitted on a first radio bearer, which is a new radio bearer other than the radio bearers supported by 3GPP R19.

[0040] As an example, the advantages of the above method include good forward compatibility.

[0041] According to one aspect of this application, the first channel information is associated with a first identifier, and the first model is associated with the first identifier.

[0042] As an example, the advantages of the above method include optimizing data reporting for AI / ML model training, reducing reporting overhead while ensuring reporting accuracy, thereby optimizing the performance of AI / ML solutions.

[0043] As an example, the benefits of the above method include making AI / ML model training and inference more well-matched, further improving the performance of AI / ML solutions.

[0044] As an example, the advantages of the above method include making the AI / ML model more specialized, reducing the number of parameters required by the model, reducing complexity, and improving performance.

[0045] This application discloses a method used in a second node for wireless communication, characterized by comprising:

[0046] Receive a first information block, the first information block including first channel information;

[0047] Wherein, the first channel information depends on measurements on the first RS resource; the first channel information is for layer l, and a first parameter set is used to generate the first channel information, the first parameter set depending on l.

[0048] According to one aspect of this application, it is characterized by comprising:

[0049] Receive the second information block;

[0050] The second information block indicates the first parameter set.

[0051] According to one aspect of this application, the first information block includes K channel information, where K is a positive integer greater than 1, the first channel information is one of the K channel information, and the K channel information are respectively for K layers; K parameter sets are respectively used to generate the K channel information, and at least two parameter sets in the K parameter sets are different.

[0052] According to one aspect of this application, the first information block includes a first channel quality, the calculation of which is based on the K channel information.

[0053] According to one aspect of this application, it is characterized by comprising:

[0054] Receive the second information block;

[0055] The second information block indicates all or part of the parameter sets in the K parameter sets.

[0056] According to one aspect of this application, the first channel information is directed to a first time-frequency resource, and the first information block indicates the first time-frequency resource.

[0057] According to one aspect of this application, it is characterized by comprising:

[0058] Send the first configuration information block;

[0059] The first configuration information block indicates at least one of the configuration information of the first RS resource and the first information block.

[0060] According to one aspect of this application, the first information block belongs to a first dataset.

[0061] According to one aspect of this application, the first information block is transmitted on a first radio bearer, which is a new radio bearer other than the radio bearers supported by 3GPP R19.

[0062] According to one aspect of this application, the first channel information is associated with a first identifier, and the first model is associated with the first identifier.

[0063] This application discloses a first node used for wireless communication, characterized in that it includes:

[0064] The first receiver measures on the first RS resource;

[0065] A first transmitter transmits a first information block, the first information block including first channel information;

[0066] Wherein, the first channel information depends on the measurement on the first RS resource; the first channel information is for layer l, and a first parameter set is used to generate the first channel information, the first parameter set depending on l.

[0067] This application discloses a second node used for wireless communication, characterized by comprising:

[0068] A first processor receives a first information block, the first information block including first channel information;

[0069] Wherein, the first channel information depends on measurements on the first RS resource; the first channel information is for layer l, and a first parameter set is used to generate the first channel information, the first parameter set depending on l.

[0070] As an example, compared with conventional solutions, this application has the following advantages:

[0071] More accurate channel information reporting improves system performance;

[0072] It improves reporting performance while saving reporting overhead;

[0073] Flexible design, excellent forward compatibility;

[0074] It fully optimizes the performance improvements brought by AI or ML technologies. Attached Figure Description

[0075] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0076] Figure 1 illustrates a flowchart of a first RS resource and a first information block according to an embodiment of this application;

[0077] Figure 2 shows a schematic diagram of a network architecture according to an embodiment of this application;

[0078] Figure 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for the user plane and control plane according to an embodiment of this application;

[0079] Figure 4 shows a schematic diagram of a first communication device and a second communication device according to an embodiment of this application;

[0080] Figure 5 illustrates the transmission between a first node and a second node according to an embodiment of this application;

[0081] Figure 6 shows a schematic diagram of first channel information according to an embodiment of this application;

[0082] Figure 7 shows a schematic diagram of first channel information according to an embodiment of this application;

[0083] Figure 8 shows a schematic diagram of first channel information according to an embodiment of this application;

[0084] Figure 9 shows a schematic diagram of a second information block according to an embodiment of this application;

[0085] Figure 10 shows a schematic diagram of a set of K parameters and K channel information according to an embodiment of this application;

[0086] Figure 11 shows a schematic diagram of K channel information being used to generate K sets of precoding matrices according to an embodiment of this application;

[0087] Figure 12 illustrates a schematic diagram of how K channel information, according to an embodiment of this application, is used to generate K sets of precoding matrices;

[0088] Figure 13 shows a schematic diagram of a first information block including a first channel quality according to an embodiment of this application;

[0089] Figure 14 shows a schematic diagram of a second information block according to an embodiment of this application;

[0090] Figure 15 shows a schematic diagram of a first time-frequency resource according to an embodiment of this application;

[0091] Figure 16 shows a schematic diagram of a first configuration information block according to an embodiment of this application;

[0092] Figure 17 illustrates a schematic diagram of a first information block belonging to a first dataset according to an embodiment of this application;

[0093] Figure 18 shows a schematic diagram of a first information block being transmitted on a first radio bearer according to an embodiment of this application;

[0094] Figure 19 shows a schematic diagram in which first channel information and a first model are both associated with a first identifier according to an embodiment of this application;

[0095] Figure 20 shows a schematic diagram of the deployment of a first model according to an embodiment of this application;

[0096] Figure 21 shows a schematic diagram of a processing system based on artificial intelligence or machine learning according to an embodiment of this application;

[0097] Figure 22 illustrates a schematic diagram based on artificial intelligence or machine learning according to an embodiment of this application;

[0098] Figure 23 shows a schematic diagram of AI function deployment according to an embodiment of this application;

[0099] Figure 24 shows a schematic diagram of AI function deployment according to an embodiment of this application;

[0100] Figure 25 shows a structural block diagram of a processing apparatus for a first node according to an embodiment of the present application;

[0101] Figure 26 shows a structural block diagram of a processing apparatus for a second node according to an embodiment of this application. Detailed Implementation

[0102] The technical solutions of this application will be further described in detail below with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other. Considering performance, flexibility, complexity, overhead, and compatibility, those skilled in the art are motivated to flexibly combine the embodiments in different drawings without conflict, such as, but not limited to, the embodiments in Figure 1 and the embodiments in Figures 5-26, the embodiments in Figure 5 and the embodiments in Figures 6-26, etc.

[0103] Example 1

[0104] Example 1 illustrates a flowchart of a first RS resource and a first information block according to an embodiment of this application, as shown in Figure 1. In Figure 1, each block represents a step. In particular, the order of the steps in the blocks does not represent a specific temporal sequence between the steps.

[0105] In Example 1, the first node measures on the first RS resource in step 101; and sends a first information block in step 102. The first information block includes first channel information; the first channel information depends on the measurement on the first RS resource; the first channel information is for layer 1, and a first parameter set is used to generate the first channel information, the first parameter set depending on layer 1.

[0106] As an example, the first RS resource includes a CSI-RS (Channel State Information Reference Signal) resource.

[0107] As an example, the first RS resource includes SS / PBCH (Synchronisation Signal / Physical Broadcast Channel) block resources.

[0108] As an example, the first RS resource includes DMRS (Demodulation Reference Signal).

[0109] As an example, the first RS resource includes a PRS (Positioning Reference Signal) resource.

[0110] As an example, the first RS resource includes PTRS (Phase-Tracking Reference Signal).

[0111] As an example, the first RS resource is a CSI-RS resource.

[0112] As an example, the first RS resource is an SS / PBCH block resource.

[0113] As an example, the first RS resource is a DMRS.

[0114] As an example, the first RS resource is a PRS resource.

[0115] As an example, the first RS resource is PTRS.

[0116] As one example, the first RS resource includes multiple ports.

[0117] As one example, the port includes an antenna port.

[0118] As one example, the port includes an RS port.

[0119] As one example, the port includes a CSI-RS port.

[0120] As an example, measuring on the first RS resource means measuring the RS transmitted on the first RS resource.

[0121] As an example, measuring on the first RS resource means measuring the RS transmitted on the first RS resource.

[0122] As one example, the measurement includes channel measurement.

[0123] As one example, the measurement includes the measurement of received power.

[0124] As an example, the measurement includes the measurement of the channel matrix.

[0125] As one example, the measurement includes interference measurement.

[0126] As one example, the first information block includes CSI (Channel State Information).

[0127] As one example, the first information block includes UCI (Uplink Control Information).

[0128] As an example, the first information block includes a MAC CE (Medium Access Control layer Control Element).

[0129] As an example, the first information block includes RRC (Radio Resource Control) IE (Information Element).

[0130] As one embodiment, the first information block includes UE capability IE.

[0131] As an example, the first information block includes one or more of the following: CQI (Channel Quality Indicator), PMI (Precoding Matrix Indicator), CRI (CSI-RS Resource Indicator), LI (Layer Indicator), RI (Rank Indicator), SSBRI (SS / PBCH Block Resource Indicator), RSRP (Reference Signal Received Power), SINR (Signal-to-Interference and Noise Ratio), RSRQ (Reference Signal Received Quality), RSSI (Received Signal Strength Indicator), Capability Index, and TDCP (Time Domain Channel Properties).

[0132] In a preferred embodiment, the first channel information is PMI.

[0133] In a preferred embodiment, the first channel information includes some or all of the information in the PMI.

[0134] As one embodiment, the first channel information includes some or all of the information in the codebook-based PMI.

[0135] As an example, the first channel information is a codebook-based PMI.

[0136] As an example, the codebook refers to a codebook supported by 3GPP R18 or earlier versions.

[0137] As an example, the codebook is a Type II codebook.

[0138] In a preferred embodiment, the first channel information is a PMI based on the Type II codebook.

[0139] In a preferred embodiment, the first channel information includes some or all of the information in the PMI based on the Type II codebook.

[0140] As one example, the Type II codebook includes an enhanced Type II codebook and a further enhanced Type II codebook.

[0141] As an example, the Type II codebook includes the codebooks in sections 5.2.2.2.3 to 5.2.2.2.11 of 3GPP TS38.214.

[0142] As an example, the definition of the Type II codebook can be found in sections 5.2.2.2.3 to 5.2.2.2.11 of 3GPP TS38.214.

[0143] As one embodiment, the first channel information includes a portion of the PMI based on the Type II codebook for layer 1.

[0144] As one embodiment, the first channel information includes a portion of the PMI based on the Type II codebook used to generate the precoding matrix of layer 1.

[0145] As one embodiment, the first channel information includes a precoding matrix.

[0146] As one embodiment, the first channel information includes precoding information.

[0147] As an example, the first channel information is used to determine at least one precoding matrix.

[0148] As one example, the first channel information includes small-scale characteristics.

[0149] As one embodiment, the first channel information includes channel parameters.

[0150] As one embodiment, the first channel information includes a channel matrix.

[0151] As an example, the channel matrix is ​​in the spatial-frequency domain.

[0152] As an example, the channel matrix is ​​in the angular-delay domain projection.

[0153] As one embodiment, the first channel information includes an eigenvector.

[0154] As one embodiment, the first channel information includes a feature vector and an eigenvalue.

[0155] As an example, the first channel information depends on channel measurements on the first RS resource.

[0156] As an example, the calculation of the first channel information depends on channel measurements on the first RS resource.

[0157] As an example, the first node calculates the first RS resource based on the measurement on the first channel information.

[0158] As an example, the first node calculates the first RS resource based on channel measurements on the first channel information.

[0159] As an example, the first node obtains channel measurements for calculating the first channel information based on the first RS resource.

[0160] As an example, the first node obtains channel measurements for calculating the first channel information based solely on the first RS resource.

[0161] In a preferred embodiment, the layer refers to a MIMO (Multiple Input Multiple Output) layer.

[0162] In a preferred embodiment, the layer refers to the transmission layer.

[0163] As an example, the first channel information is used to generate the precoding matrix of layer l.

[0164] As an example, the first channel information for layer l means that the first channel information is used to generate the precoding matrix of layer l.

[0165] As an example, the first channel information for layer 1 means that the first channel information includes the portion of PMI used to generate the precoding matrix of layer 1.

[0166] In a preferred embodiment, l is a positive integer.

[0167] As an example, l is a positive integer not greater than 4.

[0168] As an example, l is a positive integer not greater than 8.

[0169] As an example, l is a positive integer not greater than 16.

[0170] As an example, layer l is the l-th layer.

[0171] As one example, the first parameter set includes one or more parameters.

[0172] In a preferred embodiment, the first channel information includes some or all of the information in the codebook-based PMI, and the first parameter set includes the parameters of the codebook.

[0173] In a preferred embodiment, the first channel information includes some or all of the information in the PMI based on the Type II codebook, and the first parameter set includes the parameters of the Type II codebook.

[0174] In a preferred embodiment, the number of bits included in the first channel information depends on the first parameter set.

[0175] In a preferred embodiment, the payload size of the first channel information depends on the first set of parameters.

[0176] As an example, the accuracy of the first channel information depends on the first set of parameters.

[0177] As an example, the payload size of the first channel information generated based on the first parameter set increases as l decreases.

[0178] The advantages of the above method include using higher load sizes for layers with higher importance to improve their reporting accuracy, thereby improving system performance while reducing reporting overhead.

[0179] As an example, the accuracy of the first channel information generated based on the first parameter set increases as l decreases.

[0180] The advantages of the above method include higher reporting accuracy for layers with higher importance, improving system performance while reducing reporting overhead.

[0181] As an example, the smaller the value of l, the more important the layer l is among all layers.

[0182] As an example, the smaller l is, the larger the eigenvalue of the feature vector corresponding to layer l is.

[0183] As one example, the first set of parameters includes frequency domain configuration parameters.

[0184] As an example, the frequency domain configuration parameters include higher-level parameters whose names include reportFreqConfiguration.

[0185] As an example, the frequency domain configuration parameters in the first parameter set indicate the frequency domain resources to which the first channel information is targeted.

[0186] As an example, the first parameter set includes parameters related to the number of vectors and coefficients.

[0187] As an example, the parameters related to the number of vectors and coefficients include at least one of the following: a higher-level parameter whose name includes numberOfBeams, a higher-level parameter whose name includes paramCombination, a higher-level parameter whose name includes numberOfPMI-SubbandsPerCQI-Subband, and a higher-level parameter whose name includes subbandAmplitude.

[0188] As one embodiment, the first channel information indicates multiple vectors and multiple coefficients, wherein the number of vectors and the number of coefficients with non-fixed values ​​depend on parameters related to the number of vectors and coefficients in the first parameter set.

[0189] As an example, the first parameter set includes quantization-related parameters.

[0190] As an example, the quantization-related parameters include higher-level parameters whose names include phaseAlphabetSize.

[0191] As an example, the first channel information indicates a plurality of coefficients, the rounding range of at least some of which depends on the quantization-related parameters in the first parameter set.

[0192] As one example, the first set of parameters includes time slot interval configuration parameters.

[0193] As an example, the time slot interval configuration parameters include higher-level parameters whose names include td-dd-config.

[0194] As an example, the first parameter set includes some or all of the following: frequency domain configuration parameters, parameters related to the number of vectors and coefficients, quantization-related parameters, and time slot interval configuration parameters.

[0195] As an example, the first parameter set includes frequency domain configuration parameters as well as parameters related to the number of vectors and coefficients.

[0196] As an example, the first parameter set includes frequency domain configuration parameters, parameters related to the number of vectors and coefficients, and quantization-related parameters.

[0197] As an example, the first parameter set includes frequency domain configuration parameters, parameters related to the number of vectors and coefficients, quantization-related parameters, and time slot interval configuration parameters.

[0198] As an example, the first parameter set includes higher-level parameters whose names include reportFreqConfiguration.

[0199] As an example, the first parameter set includes higher-level parameters whose names include numberOfBeams.

[0200] As an example, the first parameter set includes higher-level parameters whose names include "paramCombination".

[0201] As an example, the first parameter set includes higher-level parameters whose names include numberOfPMI-SubbandsPerCQI-Subband.

[0202] As an example, the first parameter set includes higher-level parameters whose names include td-dd-config.

[0203] As one embodiment, the first channel information indicates multiple vectors and multiple coefficients.

[0204] As a sub-implementation of the above embodiments, the generation of the plurality of vectors and the plurality of coefficients depends on the first parameter set.

[0205] As a sub-implementation of the above embodiments, the plurality of vectors and the plurality of coefficients are used to generate at least one precoding matrix.

[0206] As a reference embodiment of the above sub-example, any one of the at least one precoding matrix depends on the sum of the plurality of vectors after being weighted by weighted coefficients, wherein the weighted coefficients depend on the plurality of coefficients.

[0207] As a sub-implementation of the above embodiments, the number of vectors indicated by the first channel information depends on the first parameter set.

[0208] As a sub-implementation of the above embodiments, the number of vectors indicated by the first channel information depends on at least one of the parameters related to the number of vectors and coefficients in the first parameter set and the frequency domain configuration parameters.

[0209] As a sub-implementation of the above embodiments, the number of coefficients indicated by the first channel information depends on the first parameter set.

[0210] As a sub-implementation of the above embodiments, the number of coefficients of the non-fixed values ​​indicated by the first channel information depends on the first parameter set.

[0211] As a sub-implementation of the above embodiments, the number of coefficients of the non-fixed value indicated by the first channel information depends on the parameters related to the number of vectors and coefficients in the first parameter set.

[0212] As a sub-implementation of the above embodiment, the plurality of coefficients includes amplitude coefficients, and the number of non-zero amplitude coefficients among the plurality of coefficients depends on the parameters related to the number of vectors and coefficients in the first parameter set.

[0213] As a sub-implementation of the above embodiments, the value range of at least some of the plurality of coefficients depends on the first parameter set.

[0214] As a sub-implementation of the above embodiments, the value range of at least some of the plurality of coefficients depends on at least one of the vector and coefficient quantity related parameters and the quantization related parameters in the first parameter set.

[0215] As a sub-implementation of the above embodiment, the plurality of coefficients includes a plurality of amplitude coefficients, and the number of non-zero amplitude coefficients indicated by the first channel information increases as l decreases.

[0216] As a sub-implementation of the above embodiment, the plurality of coefficients includes a plurality of phase coefficients, and the number of phase coefficients with non-fixed values ​​indicated by the first channel information increases as l decreases.

[0217] As a sub-implementation of the above embodiment, the plurality of coefficients includes a plurality of subband amplitude coefficients, and the number of non-fixed subband amplitude coefficients indicated by the first channel information increases as l decreases.

[0218] As a sub-implementation of the above embodiment, the plurality of coefficients includes a plurality of amplitude coefficients, and the quantization precision of at least some of the non-zero amplitude coefficients indicated by the first channel information increases as l decreases.

[0219] As a sub-implementation of the above embodiment, the plurality of coefficients includes a plurality of phase coefficients, and the quantization accuracy of the phase coefficients, which are at least partially non-fixed values ​​indicated by the first channel information, increases as l decreases.

[0220] As a sub-implementation of the above embodiment, the plurality of coefficients includes a plurality of sub-band amplitude coefficients, and the quantization accuracy of at least some of the non-fixed values ​​of the sub-band amplitude coefficients indicated by the first channel information increases as l decreases.

[0221] The above method provides different reporting accuracies for channel information of layers of different importance, thereby improving system performance while reducing overhead.

[0222] As an example, the first channel information is used to determine a plurality of precoding matrices, each of which is for a plurality of time-frequency resources.

[0223] As a sub-implementation of the above embodiments, the first channel information indicates multiple vectors and multiple coefficients, which are used to generate the multiple precoding matrices.

[0224] As a sub-implementation of the above embodiments, the number of the plurality of precoding matrices depends on the first parameter set.

[0225] As a sub-implementation of the above embodiments, the number of the plurality of precoding matrices depends on at least one of the frequency domain configuration parameters and the time slot interval configuration parameters in the first parameter set.

[0226] As a sub-implementation of the above embodiments, the plurality of time-frequency resources depend on the first parameter set.

[0227] As a sub-implementation of the above embodiments, at least one of the time-domain length and frequency-domain length of any of the plurality of time-frequency resources depends on the first parameter set.

[0228] As a sub-implementation of the above embodiments, the time domain length of any one of the plurality of time-frequency resources depends on the time slot interval configuration parameter in the first parameter set.

[0229] As a sub-implementation of the above embodiments, the frequency domain length of any one of the plurality of time-frequency resources depends on the frequency domain configuration parameters in the first parameter set.

[0230] As an example, the time domain length of a time-frequency resource is expressed as s (seconds), ms (milliseconds), or μs (microseconds).

[0231] As an example, the time-domain length of a time-frequency resource is represented as the number of symbols, the number of time slots, the number of frames, or the number of subframes.

[0232] As an example, the frequency domain length of a time-frequency resource is expressed in Hz, kHz, or MHz.

[0233] As an example, the frequency domain length of a time-frequency resource is expressed as the number of subcarriers, the number of RBs (Resource Blocks), or the number of sub-bands.

[0234] As an example, the first channel information is used to determine W precoding matrices, each of which is for one of the W PMI subbands, where W is a positive integer.

[0235] As an example, W depends on the frequency domain configuration parameters included in the first parameter set.

[0236] As an example, W equals 1.

[0237] As an example, W is greater than 1.

[0238] As an example, the length of each PMI subband in the W PMI subbands depends on the first set of parameters.

[0239] As an example, the length of each PMI subband in the W PMI subbands depends on the frequency domain configuration parameters in the first parameter set.

[0240] As an example, a PMI subband includes a positive integer number of consecutive RBs.

[0241] As an example, the length of a PMI subband refers to the number of RBs included in the PMI subband.

[0242] As an example, a PMI subband is a subband or a part of a subband.

[0243] As an example, one of the subbands includes a plurality of consecutive RBs.

[0244] As one embodiment, the subband includes a CQI subband.

[0245] As an example, the sub-band refers to the CQI sub-band.

[0246] As an example, the number of RBs included in other subbands, except for those located at the edge of the BWP (Bandwidth part), increases with the increase of the BWP bandwidth.

[0247] As an example, apart from the sub-bands located at the edge of the BWP, the number of RBs included in any sub-band is P0, where P0 is a positive integer greater than 1.

[0248] As an example, the P0 is indicated by higher-level signaling.

[0249] As a sub-example of the above embodiment, P0 is indicated by a higher-level parameter whose name includes subbandSize.

[0250] As a sub-example of the above embodiment, P0 is indicated by the higher-level parameter subbandSize.

[0251] As an example, P0 relates to the number of RBs included in the BWP.

[0252] As an example, the number of RBs included in the starting subband of a BWP is P0 – (Ns mod P0); the number of RBs included in the last subband of a BWP is (Ns + Nw) mod P0 or P0, where Ns is the index of the starting RB in the BWP and Nw is the number of RBs included in the BWP.

[0253] As an example, the subcarrier spacing corresponding to one RB or one subband is fixed.

[0254] As an example, the subcarrier spacing corresponding to an RB or a subband varies with the frequency range to which it belongs.

[0255] As an example, the RB includes a PRB (Physical resource block).

[0256] As an example, W depends on a first coefficient, which is a positive integer.

[0257] As an example, the length of each PMI subband in the W PMI subbands depends on a first coefficient, which is a positive integer.

[0258] As an example, the first parameter set indicates the first coefficient.

[0259] In a preferred embodiment, the first parameter set includes the first coefficient.

[0260] As an example, the parameters related to the number of vectors and coefficients in the first parameter set include the first coefficients.

[0261] As an example, the name in the first parameter set includes a higher-level parameter, numberOfPMI-SubbandsPerCQI-Subband, indicating the first coefficient.

[0262] As an example, the first coefficient is a positive integer.

[0263] As an example, the first coefficient indicates the number of PMI subbands included in a subband.

[0264] As an example, the first coefficient depends on l.

[0265] As an example, the first coefficient does not depend on l.

[0266] As an example, any one of the W PMI subbands consists of part or all of the RBs in one of the W1 subbands, where W1 is a positive integer and W depends on W1 and a first coefficient.

[0267] As a sub-example of the above embodiment, W1 is equal to 1.

[0268] As a sub-example of the above embodiment, W1 is greater than 1.

[0269] As a sub-implementation of the above embodiment, when the first coefficient is equal to 1, W is equal to W1, and the W PMI subbands are the W1 subbands.

[0270] As a sub-example of the above embodiment, when the first coefficient is greater than 1, W is not greater than the product of W1 and the first coefficient.

[0271] As a sub-implementation of the above embodiment, when the first coefficient is greater than 1, W is equal to the product of W1 and the first coefficient, the product of W1 and the first coefficient minus 1, or the product of W1 and the first coefficient minus 2.

[0272] As a sub-example of the above embodiment, when the first coefficient is greater than 1, each of the W PMI subbands, except for the first PMI subband and the last PMI subband, is composed of a portion of the RB of one of the W1 subbands.

[0273] As a reference embodiment of the above sub-example, when the first sub-band among the W1 sub-bands is the first sub-band of BWP, the first PMI sub-band is the first sub-band or is composed of a portion of the RBs in the first sub-band.

[0274] As a reference embodiment of the above sub-example, when the last sub-band among the W1 sub-bands is the last sub-band of BWP, the last PMI sub-band is the last sub-band or is composed of a portion of the RBs in the last sub-band.

[0275] As a sub-implementation of the above embodiments, the frequency domain configuration parameters included in the first parameter set indicate the W1 sub-bands.

[0276] As a sub-implementation of the above embodiments, the frequency domain resources targeted by the first channel information are the W1 sub-bands.

[0277] As a sub-implementation of the above embodiments, the time-frequency resources targeted by the first channel information include the W1 sub-bands.

[0278] As an example, the per-port per-PRB frequency density of the first RS resource in the W1 subbands is not less than the density configured for the first RS resource.

[0279] As an example, the first node does not expect the per-port per-PRB frequency density of the first RS resource in the W1 subbands to be less than the density of the first RS resource configured.

[0280] As an example, the density configured for the first RS resource refers to the number of REs (Resource Elements) per port per PRB.

[0281] As an example, the density configured for the first RS resource is configured by a higher-level parameter, density.

[0282] As an example, the first channel information is used to determine N precoding matrix groups, each of which is for N slot intervals, where N is a positive integer.

[0283] As one embodiment, the first channel information indicates multiple vectors and multiple coefficients, which are used to generate the N precoding matrix groups.

[0284] As an example, N equals 1.

[0285] As an example, N is greater than 1.

[0286] As an example, the length of N and each of the N time slot intervals depends on the first set of parameters.

[0287] As an example, the length of N and each of the N time slot intervals depends on the time slot interval configuration parameters in the first parameter set.

[0288] As a sub-example of the above embodiment, the time slot interval configuration parameter in the first parameter set indicates the N.

[0289] As a sub-implementation of the above embodiment, the time slot interval configuration parameter in the first parameter set indicates the length of the first time slot interval, and the length of each of the N time slot intervals is equal to the length of the first time slot interval.

[0290] As an example, the N time slot intervals are continuous in the time domain.

[0291] As an example, the N time slot intervals are of equal length.

[0292] As an example, a time slot interval comprises a positive integer number of consecutive time slots.

[0293] As an example, the length of a time slot interval refers to the number of time slots included in the time slot interval.

[0294] As an example, each of the N precoding matrix groups includes W precoding matrices.

[0295] As a sub-implementation of the above embodiment, W depends on at least one of the parameters related to the number of vectors and coefficients in the first parameter set and the frequency domain configuration parameters.

[0296] As a sub-implementation of the above embodiment, the W precoding matrices are respectively for W PMI subbands, and the length of W and each PMI subband in the W PMI subbands depends on a first coefficient, and the first parameter set includes the first coefficient.

[0297] As one example, the first channel information indicates L vectors.

[0298] As a sub-implementation of the above embodiment, the L vectors are used to compute the W precoding matrices.

[0299] As a sub-implementation of the above embodiment, the W precoding matrices depend on the sum of the L vectors after being weighted by weighted coefficients.

[0300] As one embodiment, the first channel information indicates L vectors and M vectors.

[0301] As a sub-implementation of the above embodiment, the L vectors and the M vectors are used together to calculate the W precoding matrices.

[0302] As a sub-implementation of the above embodiment, the W precoding matrices depend on the sum of the L vectors after being weighted by weighted coefficients, and the weighted coefficients depend on the M vectors.

[0303] As one embodiment, the first channel information indicates L vectors and L2 coefficient groups, where L2 is equal to L multiplied by 2.

[0304] As a sub-implementation of the above embodiment, the L vectors and the L2 coefficient groups are used together to calculate the W precoding matrices.

[0305] As a sub-implementation of the above embodiment, the W precoding matrices depend on the sum of the L vectors after being weighted by weighted coefficients, and the weighted coefficients depend on the L2 coefficient groups.

[0306] As one embodiment, the first channel information indicates L vectors, M vectors and L2 coefficient groups, where L2 is equal to L multiplied by 2.

[0307] As a sub-implementation of the above embodiment, the L vectors, the M vectors, and the L2 coefficient groups are used together to calculate the W precoding matrices.

[0308] As a sub-implementation of the above embodiment, the W precoding matrices depend on the sum of the L vectors after being weighted by weighted coefficients, and the weighted coefficients depend on the M vectors and the L2 coefficient groups.

[0309] As one embodiment, the first channel information indicates L vectors, M vectors, Q vectors and L2 coefficient groups, where L2 is equal to L multiplied by 2.

[0310] As a sub-implementation of the above embodiment, the L vectors, the M vectors, the Q vectors, and the L2 coefficient groups are used together to calculate the N precoding matrix groups.

[0311] As a sub-implementation of the above embodiment, the N precoding matrix groups depend on the sum of the L vectors after being weighted by weighted coefficients, and the weighted coefficients depend on the M vectors, the Q vectors and the L2 coefficient groups.

[0312] As an example, L is a positive integer greater than 1.

[0313] As an example, L is the number of beams.

[0314] As one example, L depends on the number of beams.

[0315] As an example, L increases with the number of beams.

[0316] As an example, the L vectors are mutually orthogonal.

[0317] As an example, the L vectors each represent a L beam.

[0318] As an example, the length of any one of the L vectors depends on the number of ports.

[0319] As an example, the length of any one of the L vectors is equal to the number of ports of the first RS resource.

[0320] As an example, any one of the L vectors can be represented as in Where q1 and q2 are non-negative integers, any two different vectors among the L vectors have different values ​​of q1, or different values ​​of q2, or different values ​​of q1 and q2; N1, N2, O1 and O2 are positive integers, N1 and N2 are the number of ports, and O1 and O2 depend on N1 and N2.

[0321] As a sub-implementation of the above embodiments, O1 and O2 depend on the first parameter set.

[0322] As a sub-implementation of the above embodiments, the first parameter set indicates O1 and O2.

[0323] As a sub-example of the above embodiment, the number of ports of the first RS resource is equal to the product of N1 and N2.

[0324] As an example, the L vectors are related to the spatial or angular characteristics of the channel.

[0325] In a preferred embodiment, the first channel information indicates the L vectors by indicating q1 and q2.

[0326] As an example, the first channel information indicates q and q2 corresponding to each of the L vectors.

[0327] As an example, L depends on the first set of parameters.

[0328] As an example, the parameters related to the number of vectors and coefficients in the first parameter set indicate the L.

[0329] As an example, L is independent of l.

[0330] As an example, the first parameter set indicates the L, and the L indicated by the first parameter set is independent of the l.

[0331] As an example, M is a positive integer greater than 1.

[0332] As an example, the M vectors are mutually orthogonal pairwise.

[0333] As an example, the length of any one of the M vectors is equal to the length of W.

[0334] As an example, any one of the M vectors can be represented as Wherein, q3 is a non-negative integer, and the value of q3 is different for any two different vectors among the M vectors.

[0335] As an example, the M vectors are related to frequency domain characteristics or time delay domain characteristics.

[0336] In a preferred embodiment, the first channel information indicates the M vectors by indicating q3.

[0337] As an example, the first channel information indicates that each of the M vectors indicates the corresponding q3.

[0338] As one example, M depends on the first set of parameters.

[0339] As an example, M depends on at least one of the parameters related to the number of vectors and coefficients included in the first parameter set and the frequency domain configuration parameters.

[0340] As one embodiment, the first channel information is for W1 sub-bands, and M depends on W1.

[0341] As an example, M increases as W1 increases.

[0342] As an example, the first channel information is used to determine W precoding matrices, each of which is for one of the W PMI subbands, and M depends on W.

[0343] As an example, M increases as W increases.

[0344] As an example, M depends on the product of W and a second coefficient, where the second coefficient is a positive real number less than 1.

[0345] As an example, M depends on W, the first coefficient and the second coefficient, wherein the second coefficient is a positive real number less than 1.

[0346] As a sub-example of the above embodiment, M is equal to W divided by the first coefficient, multiplied by the second coefficient, and then rounded down.

[0347] In a preferred embodiment, the second coefficient depends on the first set of parameters.

[0348] As an example, the first set of parameters indicates the second coefficient.

[0349] As an example, the parameters related to the number of vectors and coefficients in the first parameter set indicate the second coefficients.

[0350] In a preferred embodiment, the first parameter set includes the first coefficient, and the parameters related to the number of vectors and coefficients in the first parameter set indicate the second coefficient.

[0351] As an example, M depends on l.

[0352] As an example, M does not depend on l.

[0353] As an example, the second coefficient depends on l.

[0354] As an example, the second coefficient does not depend on l.

[0355] As an example, Q is a positive integer greater than 1.

[0356] As an example, the Q vectors are pairwise orthogonal.

[0357] As an example, the length of any one of the Q vectors is equal to the length of N.

[0358] As an example, any one of the Q vectors can be represented as Wherein, q4 is a non-negative integer, and the value of q4 is different for any two different vectors among the Q vectors.

[0359] As an example, the Q vectors are related to Doppler domain characteristics or time domain characteristics.

[0360] In a preferred embodiment, the first channel information indicates the Q vectors by indicating q4.

[0361] As an example, the first channel information indicates that each of the Q vectors indicates the corresponding q4.

[0362] As one example, Q depends on the first set of parameters.

[0363] As an example, the time slot interval configuration parameter in the first parameter set indicates the Q.

[0364] As an example, Q does not depend on l.

[0365] As an example, the length of any of the N time slot intervals depends on the first set of parameters.

[0366] As an example, the time slot interval configuration parameter in the first parameter set indicates the length of any one of the N time slot intervals.

[0367] As an example, the length of any one of the N time slot intervals does not depend on l.

[0368] As an example, the number of coefficients in the L2 coefficient groups depends on the first parameter set.

[0369] As an example, the number of non-fixed coefficients in the L2 coefficient groups depends on the first parameter set.

[0370] As an example, the number of non-fixed coefficients in the L2 coefficient groups depends on the parameters related to the number of vectors and coefficients in the first parameter set.

[0371] As an example, any one of the L2 coefficient groups includes at least one amplitude coefficient.

[0372] As an example, any one of the L2 coefficient groups includes at least one phase coefficient.

[0373] As an example, any one of the L2 coefficient groups includes at least one sub-band amplitude coefficient.

[0374] As an example, any one of the L2 coefficient groups includes at least one amplitude coefficient and at least one phase coefficient.

[0375] As an example, any one of the L2 coefficient groups includes at least one amplitude coefficient, at least one phase coefficient, and at least one sub-band amplitude coefficient.

[0376] As an example, the weighting coefficient of any of the L vectors depends on the product of the amplitude coefficient and the phase coefficient.

[0377] As an example, the weighting coefficient of any of the L vectors is equal to the product of an amplitude coefficient, a phase coefficient, and a sub-band amplitude coefficient.

[0378] As an example, the first channel information explicitly indicates the L2 coefficient groups.

[0379] As an example, the first channel information implicitly indicates the L2 coefficient groups.

[0380] As an example, the first channel information explicitly indicates a portion of the coefficients in the L2 coefficient groups and implicitly indicates another portion of the coefficients in the L2 coefficient groups.

[0381] As an example, the first channel information indicates the coefficient group containing the strongest coefficient among the L2 coefficient groups, wherein the amplitude coefficient, phase coefficient, and sub-band amplitude coefficient of the coefficient group containing the strongest coefficient are all 1.

[0382] As an example, the first channel information indicates the coefficients of non-fixed values ​​in the L2 coefficient groups and indicates the position of the coefficients of non-fixed values.

[0383] As a sub-implementation of the above embodiments, the non-fixed value means that the amplitude coefficient is non-fixed to 0, the phase coefficient is non-fixed to 1, and the sub-band amplitude coefficient is non-fixed to 1.

[0384] As an example, the upper limit of the total number of non-zero coefficients included in the L2 coefficient groups depends on a third coefficient, which is a positive real number less than 1. The parameters related to the number of vectors and coefficients in the first parameter set indicate the third coefficient.

[0385] As an example, the non-zero coefficient refers to a non-zero amplitude coefficient.

[0386] As an example, the value range of at least some of the coefficients in the L2 coefficient groups depends on the first parameter set.

[0387] As an example, the value range of at least some coefficients in the L2 coefficient groups depends on the quantization-related parameters in the first parameter set.

[0388] As an example, the number of non-zero amplitude coefficients in the L2 coefficient groups depends on the first parameter set.

[0389] As an example, the number of non-zero amplitude coefficients in the L2 coefficient groups depends on the parameters related to the number of vectors and coefficients in the first parameter set.

[0390] As an example, the range of values ​​for at least some of the amplitude coefficients in the L2 coefficient groups depends on the quantization-related parameters in the first parameter set.

[0391] As an example, the range of values ​​for any non-zero amplitude coefficient in the L2 coefficient groups depends on the quantization-related parameters in the first parameter set.

[0392] As an example, the first parameter set indicates at least one of the upper limit of the number of non-zero amplitude coefficients included in one of the L2 coefficient groups and the upper limit of the total number of non-zero amplitude coefficients included in the L2 coefficient groups.

[0393] As an example, the first channel information indicates the non-zero amplitude coefficients in the L2 coefficient groups and indicates the position of the non-zero amplitude coefficients.

[0394] As an example, the number of phase coefficients included in the L2 coefficient groups depends on the first parameter set.

[0395] As an example, the number of non-fixed phase coefficients in the L2 coefficient groups depends on the first parameter set.

[0396] As an example, the number of non-fixed phase coefficients in the L2 coefficient groups depends on the parameters related to the number of vectors and coefficients in the first parameter set.

[0397] As an example, the first parameter set indicates the upper limit of the number of non-fixed phase coefficients in the L2 coefficient groups.

[0398] As an example, the first channel information indicates the phase coefficients of non-fixed values ​​in the L2 coefficient groups and indicates the position of the phase coefficients of non-fixed values.

[0399] As an example, the range of values ​​for at least some of the phase coefficients in the L2 coefficient groups depends on the first parameter set.

[0400] As an example, the range of values ​​for at least some of the phase coefficients in the L2 coefficient groups depends on the quantization-related parameters in the first parameter set.

[0401] As an example, the range of values ​​for any non-fixed phase coefficient in the L2 coefficient groups depends on the quantization-related parameters in the first parameter set.

[0402] As an example, the phase coefficient of any non-fixed value in the L2 coefficient groups is represented as e. j2πc / N3 Where c is a non-negative integer, N3 is a positive integer greater than 1, N3 is configurable, and c needs to be indicated for any non-fixed value of the phase coefficient in the L2 coefficient groups.

[0403] As an example, the non-fixed phase coefficient refers to a phase coefficient that is not fixed at 1, and the c corresponding to any phase coefficient that is fixed at 1 is fixed at 0.

[0404] As an example, the first channel information indicates the corresponding c for each non-fixed value phase coefficient in the L2 coefficient groups.

[0405] As an example, the first channel information indicates the phase coefficients of the non-fixed values ​​in the L2 coefficient groups by indicating the corresponding c for each non-fixed value phase coefficient in the L2 coefficient groups.

[0406] In a preferred embodiment, N3 depends on the first set of parameters.

[0407] As an example, N3 depends on the quantization-related parameters in the first parameter set.

[0408] As an example, for a portion of the phase coefficients with non-fixed values ​​in the L2 coefficient groups, N3 is equal to a first integer; for another portion of the phase coefficients with non-fixed values ​​in the L2 coefficient groups, N3 is equal to a second integer; the first integer is not equal to the second integer.

[0409] As an example, at least one of the first integer and the second integer depends on the first set of parameters.

[0410] As an example, the quantization-related parameters in the first parameter set indicate at least one of the first integer and the second integer.

[0411] As an example, the quantization-related parameters in the first parameter set include the first integer and the second integer.

[0412] As an example, at least one of the first integer and the second integer depends on l.

[0413] As an example, at least one of the first integer and the second integer increases as l decreases.

[0414] As an example, the number of non-fixed subband amplitude coefficients in the L2 coefficient groups depends on the first parameter set.

[0415] As an example, the number of non-fixed-value subband amplitude coefficients in the L2 coefficient groups depends on the parameters related to the number of vectors and coefficients in the first parameter set.

[0416] As an example, the first parameter set indicates the upper limit of the number of non-fixed value subband amplitude coefficients in the L2 coefficient groups.

[0417] As an example, the first channel information indicates the non-fixed value subband amplitude coefficients in the L2 coefficient groups and indicates the position of the non-fixed value subband amplitude coefficients.

[0418] As an example, the non-fixed value sub-band amplitude coefficient refers to a sub-band amplitude coefficient that is not fixed at 1.

[0419] As an example, the range of values ​​for at least some of the sub-band amplitude coefficients in the L2 coefficient groups depends on the first parameter set.

[0420] As an example, the range of values ​​for at least some of the subband amplitude coefficients in the L2 coefficient groups depends on the quantization-related parameters in the first parameter set.

[0421] As an example, the number of sub-band amplitude coefficients that are fixed at 1 in the L2 coefficient groups depends on the parameters related to the number of vectors and coefficients in the first parameter set.

[0422] As an example, the amplitude coefficient is a non-negative real number not greater than 1.

[0423] As an example, the amplitude coefficient is a positive real number not greater than 1.

[0424] As an example, the phase coefficient is a complex number with a modulus of 1.

[0425] As an example, the sub-band amplitude coefficient is a positive real number not greater than 1.

[0426] As an example, the range of values ​​for a coefficient indicates the quantization precision of that coefficient.

[0427] As an example, the range of values ​​for a coefficient is related to the quantization precision of that coefficient.

[0428] As an example, the range of values ​​for a coefficient is related to the number of bits required to represent that coefficient.

[0429] As an example, the first node determines the first parameter set based on l.

[0430] As an example, the target recipient of the first information block determines the first parameter set based on the l.

[0431] As an example, all parameters in the first parameter set depend on l.

[0432] In a preferred embodiment, only some parameters in the first parameter set depend on l.

[0433] The advantages of the above approach include more flexible design and a better balance between performance and overhead.

[0434] As an example, some parameters in the first parameter set depend on l, while other parameters do not depend on l.

[0435] As an example, the parameters related to the number of vectors and coefficients in the first parameter set depend on l.

[0436] As an example, the parameters related to the number of vectors and coefficients in the first parameter set indicate multiple parameters, some of which depend on l, and others of which do not depend on l.

[0437] As a sub-implementation of the above embodiments, the plurality of parameters includes the number of beams, which is independent of l.

[0438] As a sub-implementation of the above embodiments, the plurality of parameters includes the first coefficient, which depends on l.

[0439] As a sub-implementation of the above embodiments, the plurality of parameters includes the first coefficient, which is independent of l.

[0440] As a sub-implementation of the above embodiment, the plurality of parameters includes the second coefficient, which is independent of l.

[0441] As a sub-implementation of the above embodiments, the plurality of parameters includes the second coefficient, which depends on l.

[0442] As a sub-implementation of the above embodiments, the plurality of parameters includes the third coefficient, which depends on l.

[0443] As an example, the quantization-related parameters in the first parameter set depend on l.

[0444] As an example, the quantization-related parameters in the first parameter set indicate N3, which depends on l.

[0445] As an example, the quantization-related parameters in the first parameter set indicate at least one of the first integer and the second integer, and at least one of the first integer and the second integer depends on l.

[0446] As an example, the frequency domain configuration parameters included in the first parameter set do not depend on l.

[0447] As an example, the time slot interval configuration parameters included in the first parameter set do not depend on l.

[0448] As an example, the first node generates the first channel information based on the first parameter set.

[0449] Generally, how the first node generates the first channel information based on the first parameter set is determined by the hardware equipment vendor. Below are some non-limiting implementation methods:

[0450] As an example, the first node obtains the original channel matrix based on the measurement results on the first RS resource; the first node projects the original channel matrix onto the basis matrix to obtain the weights on each basis vector; the first node determines the multiple basis vectors with the highest importance and their coefficients based on the first parameter set, and represents the multiple basis vectors with the highest importance and their coefficients in the form of a Type II codebook based on the first parameter set.

[0451] As an example, one of the basis matrices is a full-rank matrix.

[0452] As an example, the product of a basis matrix and its conjugate transpose is an identity matrix.

[0453] As an example, the basis matrix includes at least one of the following: spatial or angular domain basis matrix, frequency or delay domain time domain basis matrix, and time domain or Doppler domain basis matrix.

[0454] Example 2

[0455] Example 2 illustrates a schematic diagram of a network architecture according to an embodiment of this application, as shown in Figure 2.

[0456] Figure 2 illustrates network architecture 200. Network architecture 200 is a 5G NR (New Radio) / LTE (Long-Term Evolution) / LTE-A (Long-Term Evolution Advanced) system, or a 5G+ network architecture, or a 6G network architecture, or a network architecture adopted in future evolutions by 3GPP; network architecture 200 may be referred to as 5GS (5G System) / EPS (Evolved Packet System), or 6GS (6G System); network architecture 200 includes at least one of UE (User Equipment) 201, RAN (Radio Access Network) 202, core network 210, HSS (Home Subscriber Server) / UDM (Unified Data Management) 220, and Internet service 230. The network architecture 200 can interconnect with other access networks, but these entities / interfaces are not shown for simplicity. As shown, the network architecture 200 provides packet-switched services; however, those skilled in the art will readily understand that the various concepts presented throughout this application can be extended to networks providing circuit-switched services or other cellular networks. The RAN includes node 203. The RAN may also include other nodes 204. Node 203 provides user and control plane protocol termination toward UE 201. Node 203 may be connected to other nodes 204 via an Xn interface (e.g., backhaul) / X2 interface. Node 203 may also be referred to as a base station, base transceiver station, radio base station, radio transceiver, transceiver function, basic service set (BSS), extended service set (ESS), TRP (transmitter-receiver node), or some other suitable term. The core network 210 is a 5GC (5G Core Network) / EPC (Evolved Packet Core), or the core network 210 is a 6GC; node 203 provides UE 201 with an access point to the core network 210.Examples of UE201 include cellular phones, smartphones, Session Initiation Protocol (SIP) phones, laptops, personal digital assistants (PDAs), satellite radios, non-terrestrial base station communications, satellite mobile communications, global positioning systems, multimedia devices, video devices, digital audio players (e.g., MP3 players), cameras, game consoles, drones, aircraft, narrowband IoT devices, machine-type communication devices, land vehicles, automobiles, wearable devices, or any other similar functional devices. Those skilled in the art may also refer to UE201 as a mobile station, subscriber station, mobile unit, subscriber unit, radio unit, remote unit, mobile device, radio device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handheld device, user agent, mobile client, client, or any other suitable term. Node 203 is connected to the core network 210 via an S1 / NG interface. The core network 210 includes an MME (Mobility Management Entity) / AMF (Authentication Management Field) / SMF (Session Management Function) 211, other MMEs / AMFs / SMFs 214, an S-GW (Service Gateway) / UPF (User Plane Function) 212, and a P-GW (Packet Data Network Gateway) / UPF 213. The MME / AMF / SMF 211 is the control node that handles signaling between the UE 201 and the core network 210. Generally, the MME / AMF / SMF 211 provides bearer and connection management. All user IP (Internet Protocol) packets are transmitted through the S-GW / UPF 212, which is itself connected to the P-GW / UPF 213. The P-GW provides UE IP address allocation and other functions. The P-GW / UPF 213 is connected to the Internet service 230. Internet services 230 include operator-compliant Internet protocol services, which may specifically include Internet, intranet, IMS (IP Multimedia Subsystem), and packet switching services.

[0457] As an example, the first node includes the UE201.

[0458] As one embodiment, the second node includes the node 203.

[0459] As an example, the wireless link between the UE201 and the node203 includes a cellular link.

[0460] As an example, the sender of the RS in the first RS resource includes the node 203.

[0461] As an example, the recipient of the RS in the first RS resource includes the UE201.

[0462] As an example, the sender of the first information block includes the UE201.

[0463] As an example, the recipient of the first information block includes the node 203.

[0464] As one embodiment, the sender of the second information block includes the UE201.

[0465] As one embodiment, the recipient of the second information block includes the node 203.

[0466] As an example, the sender of the first configuration information block includes the node 203.

[0467] As an example, the recipient of the first configuration information block includes the UE201.

[0468] As an example, the UE201 supports AI- or ML-based operations.

[0469] As an example, node 203 supports AI- or ML-based operations.

[0470] Example 3

[0471] Example 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for the user plane and control plane according to an embodiment of this application, as shown in Figure 3.

[0472] Example 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for a user plane and control plane according to this application, as shown in Figure 3. Figure 3 is a schematic diagram illustrating an embodiment of a radio protocol architecture for a user plane 350 and a control plane 300. Figure 3 shows the radio protocol architecture for the control plane 300 between a first communication node device (UE, gNB, or RSU in V2X) and a second communication node device (gNB, UE, or RSU in V2X), or between two UEs, using three layers: Layer 1, Layer 2, and Layer 3. Layer 1 (L1 layer) is the lowest layer and implements various PHY (physical layer) signal processing functions. Layer 1 will be referred to herein as PHY 301. Layer 2 (L2 layer) 305 is above PHY 301 and is responsible for the link between the first communication node device and the second communication node device, or between two UEs. Layer L2 305 includes a MAC (Medium Access Control) sublayer 302, an RLC (Radio Link Control) sublayer 303, and a PDCP (Packet Data Convergence Protocol) sublayer 304, which terminate at the second communication node device. The PDCP sublayer 304 provides multiplexing between different radio bearers and logical channels. It also provides security through encrypted data packets and supports cross-cell mobility between the second communication node devices and the first communication node device. The RLC sublayer 303 provides upper-layer packet segmentation and reassembly, retransmission of lost packets, and packet reordering to compensate for out-of-order reception due to HARQ. The MAC sublayer 302 provides multiplexing between logical and transport channels. It is also responsible for allocating various radio resources (e.g., resource blocks) within a cell among the first communication node devices. Furthermore, the MAC sublayer 302 handles HARQ operations. In the control plane 300, the Radio Resource Control (RRC) sublayer 306 of Layer 3 (L3) is responsible for acquiring radio resources (i.e., radio bearers) and configuring the lower layers using RRC signaling between the second and first communication node devices. The user plane 350's radio protocol architecture includes Layer 1 (L1) and Layer 2 (L2). The radio protocol architecture for the first and second communication node devices in the user plane 350 is largely the same as the corresponding layers and sublayers in the control plane 300 for Physical Layer 351, PDCP sublayer 354 in L2 Layer 355, RLC sublayer 353 in L2 Layer 355, and MAC sublayer 352 in L2 Layer 355. However, PDCP sublayer 354 also provides header compression for upper layer data packets to reduce radio transmission overhead.The L2 layer 355 in the user plane 350 also includes an SDAP (Service Data Adaptation Protocol) sublayer 356, which is responsible for mapping between QoS streams and data radio bearers (DRBs) to support service diversity. Although not illustrated, the first communication node device may have several upper layers above the L2 layer 355, including a network layer (e.g., IP layer) terminating at the P-GW on the network side and an application layer terminating at the other end of the connection (e.g., a remote UE, server, etc.).

[0473] As an example, the wireless protocol architecture in Figure 3 is applicable to the first node.

[0474] As an example, the wireless protocol architecture in Figure 3 is applicable to the second node.

[0475] As an example, the higher layer mentioned in this application refers to the layer above the physical layer.

[0476] As an example, the first information block is generated in the PHY301 or the PHY351.

[0477] As an example, the first information block is generated in the MAC sublayer 302 or the MAC sublayer 352.

[0478] As an example, the second information block is generated in the MAC sublayer 302 or the MAC sublayer 352.

[0479] As an example, the second information block is generated in the RRC sublayer 306.

[0480] As an example, the first configuration information block is generated in the RRC sublayer 306.

[0481] Example 4

[0482] Example 4 illustrates a schematic diagram of a first communication device and a second communication device according to an embodiment of this application, as shown in Figure 4. Figure 4 is a block diagram of a first communication device 410 and a second communication device 450 communicating with each other in an access network.

[0483] The first communication device 410 includes a controller / processor 475, a memory 476, a receiver processor 470, a transmitter processor 416, a multi-antenna receiver processor 472, a multi-antenna transmitter processor 471, a transmitter / receiver 418, and an antenna 420.

[0484] The second communication device 450 includes a controller / processor 459, a memory 460, a data source 467, a transmitting processor 468, a receiving processor 456, a multi-antenna transmitting processor 457, a multi-antenna receiving processor 458, a transmitter / receiver 454, and an antenna 452.

[0485] In the transmission from the first communication device 410 to the second communication device 450, at the first communication device 410, upper-layer data packets from the core network are provided to the controller / processor 475. The controller / processor 475 implements L2 layer functionality. In DL (Downlink), the controller / processor 475 provides header compression, encryption, packet segmentation and reordering, multiplexing between logical and transport channels, and radio resource allocation to the second communication device 450 based on various priority metrics. The controller / processor 475 is also responsible for HARQ operation, retransmission of lost packets, and signaling to the second communication device 450. The transmit processor 416 and the multi-antenna transmit processor 471 implement various signal processing functions for L1 layer (i.e., physical layer). Transmit processor 416 performs encoding and interleaving to facilitate forward error correction (FEC) at the second communication device 450, and constellation mapping based on various modulation schemes (e.g., binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), M-phase shift keying (M-PSK), and M-quadrature amplitude modulation (M-QAM). Multi-antenna transmit processor 471 performs digital spatial precoding on the encoded and modulated symbols, including codebook-based precoding and non-codebook-based precoding, and beamforming processing, generating one or more parallel... The transmit processor 416 then maps each parallel stream to a subcarrier, multiplexes the modulated symbols with a reference signal (e.g., a pilot) in the time and / or frequency domains, and then uses an inverse fast Fourier transform (IFFT) to generate a physical channel carrying the time-domain multicarrier symbol stream. The multi-antenna transmit processor 471 then performs transmit analog precoding / beamforming operations on the time-domain multicarrier symbol stream. Each transmitter 418 converts the baseband multicarrier symbol stream provided by the multi-antenna transmit processor 471 into an RF stream, which is then provided to a different antenna 420.

[0486] In the transmission from the first communication device 410 to the second communication device 450, at the second communication device 450, each receiver 454 receives a signal through its corresponding antenna 452. Each receiver 454 recovers the information modulated onto the radio frequency carrier and converts the radio frequency stream into a baseband multicarrier symbol stream, which is then provided to the receiver processor 456. The receiver processor 456 and the multi-antenna receiver processor 458 implement various signal processing functions of the L1 layer. The multi-antenna receiver processor 458 performs receive analog precoding / beamforming operations on the baseband multicarrier symbol stream from the receiver 454. The receiver processor 456 uses a Fast Fourier Transform (FFT) to convert the baseband multicarrier symbol stream after the receive analog precoding / beamforming operations from the time domain to the frequency domain. In the frequency domain, the physical layer data signal and the reference signal are demultiplexed by the receiver processor 456, where the reference signal is used for channel estimation, and the data signal is recovered in the multi-antenna receiver processor 458 after multi-antenna detection to recover any parallel stream destined for the second communication device 450. Symbols on each parallel stream are demodulated and recovered in the receive processor 456, generating soft decisions. The receive processor 456 then decodes and deinterleaves the soft decisions to recover the upper-layer data and control signals transmitted over the physical channel by the first communication device 410. The upper-layer data and control signals are then provided to the controller / processor 459. The controller / processor 459 implements the functions of Layer 2 (L2). The controller / processor 459 may be associated with a memory 460 storing program code and data. The memory 460 may be referred to as computer-readable media. In the DL (Layered Logic), the controller / processor 459 provides multiplexing, packet reassembly, decryption, header decompression, and control signal processing between the transmission and logical channels to recover upper-layer packets from the core network. The upper-layer packets are then provided to all protocol layers above Layer 2. Various control signals may also be provided to Layer 3 (L3) for L3 processing. The controller / processor 459 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operation.

[0487] In the transmission from the second communication device 450 to the first communication device 410, at the second communication device 450, a data source 467 is used to provide upper-layer data packets to the controller / processor 459. The data source 467 represents all protocol layers above the L2 layer. Similar to the transmission functions at the first communication device 410 described in the DL, the controller / processor 459 implements header compression, encryption, packet segmentation and reordering, and multiplexing between logical and transport channels based on the radio resource allocation of the first communication device 410, implementing L2 layer functions for the user plane and control plane. The controller / processor 459 is also responsible for HARQ operations, retransmission of lost packets, and signaling to the first communication device 410. Transmit processor 468 performs modulation mapping and channel coding processing, while multi-antenna transmit processor 457 performs digital multi-antenna spatial precoding, including codebook-based and non-codebook-based precoding, and beamforming processing. Subsequently, transmit processor 468 modulates the generated parallel stream into a multi-carrier / single-carrier symbol stream. After analog precoding / beamforming operations in multi-antenna transmit processor 457, the stream is provided to different antennas 452 via transmitter 454. Each transmitter 454 first converts the baseband symbol stream provided by multi-antenna transmit processor 457 into a radio frequency symbol stream before providing it to antenna 452.

[0488] In the transmission from the second communication device 450 to the first communication device 410, the function at the first communication device 410 is similar to the receiving function at the second communication device 450 described in the transmission from the first communication device 410 to the second communication device 450. Each receiver 418 receives radio frequency signals through its corresponding antenna 420, converts the received radio frequency signals into baseband signals, and provides the baseband signals to the multi-antenna receiving processor 472 and the receiving processor 470. The receiving processor 470 and the multi-antenna receiving processor 472 jointly implement the L1 layer functions. The controller / processor 475 implements the L2 layer functions. The controller / processor 475 may be associated with a memory 476 that stores program code and data. The memory 476 may be referred to as computer-readable media. The controller / processor 475 provides multiplexing, packet reassembly, decryption, header decompression, and control signal processing between the transmission and logical channels to recover upper-layer data packets from the second communication device 450. The upper-layer data packets from the controller / processor 475 may be provided to the core network. The controller / processor 475 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operation.

[0489] As one embodiment, the second communication device 450 includes: at least one processor and at least one memory, the at least one memory including computer program code; the at least one memory and the computer program code are configured to be used with the at least one processor. The second communication device 450 means at least: measuring on the first RS resource; and transmitting the first information block. The first information block includes first channel information; the first channel information depends on the measurement on the first RS resource; the first channel information is for layer l, and a first set of parameters is used to generate the first channel information, the first set of parameters depending on layer l.

[0490] As one embodiment, the second communication device 450 includes: a memory storing a computer-readable instruction program that, when executed by at least one processor, produces actions including: measuring on the first RS resource; and transmitting the first information block.

[0491] As one embodiment, the first communication device 410 includes: at least one processor and at least one memory, the at least one memory including computer program code; the at least one memory and the computer program code are configured to be used with the at least one processor. The first communication device 410 means at least: receiving the first information block. The first information block includes first channel information; the first channel information depends on measurements on a first RS resource; the first channel information is for layer l, and a first set of parameters is used to generate the first channel information, the first set of parameters depending on layer l.

[0492] As one embodiment, the first communication device 410 includes: a memory storing a computer-readable instruction program that produces an action when executed by at least one processor, the action including: receiving the first information block.

[0493] As an example, the first node in this application includes the second communication device 450.

[0494] As an example, the second node in this application includes the first communication device 410.

[0495] As an example, at least one of {the antenna 452, the receiver 454, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to measure on the first RS resource; at least one of {the antenna 420, the transmitter 418, the transmitter processor 416, the multi-antenna transmitter processor 471, the controller / processor 475, and the memory 476} is used to transmit on the first RS resource.

[0496] As an example, 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} is used to receive the first information block; at least one of {the antenna 452, the transmitter 454, the transmitting processor 468, the multi-antenna transmitting processor 457, the controller / processor 459, the memory 460, and the data source 467} is used to transmit the first information block.

[0497] As an example, 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} is used to receive the second information block; at least one of {the antenna 452, the transmitter 454, the transmitting processor 468, the multi-antenna transmitting processor 457, the controller / processor 459, the memory 460, and the data source 467} is used to transmit the second information block.

[0498] As an example, at least one of {the antenna 452, the receiver 454, the receiving processor 456, the multi-antenna receiving processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to receive the first configuration information block; at least one of {the antenna 420, the transmitter 418, the transmitting processor 416, the multi-antenna transmitting processor 471, the controller / processor 475, and the memory 476} is used to transmit the first configuration information block.

[0499] Example 5

[0500] Example 5 illustrates a transmission flowchart according to an embodiment of this application; as shown in Figure 5. In Figure 5, the second node U1 and the first node U2 are communication nodes transmitting via an air interface. In Figure 5, the steps in blocks F51 to F56 are optional.

[0501] For the second node U1, the first configuration information block is sent in step S5101; it is sent on the first RS resource in step S5102; the second information block is received in step S5103; and the first information block is received in step S511.

[0502] For the first node U2, in step S5201, a first configuration information block is received; in step S521, a measurement is performed on the first RS resource; in step S5202, a second information block is sent; in step S522, a first information block is sent; in step S5203, a first model is deployed; and in step S5204, inference of the first model is performed.

[0503] In embodiment 5, the first information block includes first channel information; the first channel information depends on measurements on the first RS resource; the first channel information is for layer l, and a first parameter set is used to generate the first channel information, the first parameter set depending on l.

[0504] As an example, the first node U2 is the first node in this application.

[0505] As an example, the second node U1 is the second node in this application.

[0506] As one embodiment, the air interface between the second node U1 and the first node U2 includes a wireless interface between the base station equipment and the user equipment.

[0507] As one embodiment, the air interface between the second node U1 and the first node U2 includes a wireless interface between the relay node device and the user equipment.

[0508] As one embodiment, the air interface between the second node U1 and the first node U2 includes the interface between the core network equipment and the user equipment.

[0509] As one embodiment, the air interface between the second node U1 and the first node U2 includes the interface between the OTT server (Over-The-Top server) and the user equipment.

[0510] As one embodiment, the air interface between the second node U1 and the first node U2 includes the interface between the NAS (Network Access Server) device and the user equipment.

[0511] As one embodiment, the air interface between the second node U1 and the first node U2 includes a wireless interface between user equipment and user equipment.

[0512] As one embodiment, the second node U1 includes the serving cell sustaining base station of the first node U2.

[0513] As one embodiment, the second node U1 includes an OTT server (Over-The-Top server).

[0514] As an example, the second node U1 includes OAM (Operation Administration and Maintenance).

[0515] As one embodiment, the second node U1 includes a NAS device.

[0516] As one embodiment, the second node U1 includes core network equipment.

[0517] As an example, the first information block is transmitted on PUSCH (Physical Uplink Shared Channel).

[0518] As an example, the first information block is transmitted on PUCCH (Physical Uplink Control Channel).

[0519] As an example, the step in block F53 of Figure 5 exists, and the method described above for the second node used in wireless communication includes: transmitting on the first RS resource.

[0520] As an example, sending on the first RS resource means sending RS on the first RS resource.

[0521] As an example, the step in block F53 of Figure 5 is absent, and the sender of the first RS resource is different from the second node U1.

[0522] In one embodiment, the second node U1 is a core network device, and the sender of the first RS resource is the serving cell of the first node.

[0523] As an example, the sender of the first RS resource refers to the sender of the RS in the first RS resource.

[0524] As an example, the step in block F54 of Figure 5 exists, and the second information block indicates the first parameter set.

[0525] As an example, the second information block is transmitted on the PUSCH.

[0526] As one embodiment, the first information block includes the second information block.

[0527] As one embodiment, the second information block and the first information block are transmitted on different PUSCHes.

[0528] As one embodiment, the second information block is transmitted on the PUSCH, and the first information block is transmitted on the PUCCH.

[0529] As one embodiment, the transmission of the second information block is earlier than the transmission of the first information block.

[0530] As one embodiment, the transmission of the second information block is later than the transmission of the first information block.

[0531] As an example, the first information block includes K channel information, where K is a positive integer greater than 1, the first channel information is one of the K channel information, and the K channel information are respectively for K layers; K parameter sets are respectively used to generate the K channel information, and at least two parameter sets in the K parameter sets are different.

[0532] As an example, the first information block includes a first channel quality, which is calculated based on the K channel information.

[0533] As an example, the step in block F54 of Figure 5 exists, whereby the second information block indicates all or part of the parameter sets in the K parameter sets.

[0534] As one embodiment, the first channel information is for a first time-frequency resource, and the first information block indicates the first time-frequency resource.

[0535] As an example, the step in block F52 of Figure 5 includes the first configuration information block indicating at least one of the configuration information of the first RS resource and the first information block.

[0536] As an example, the step in block F51 of Figure 5 includes the first configuration information block indicating at least one of the configuration information of the first RS resource and the first information block.

[0537] As an example, the first configuration information block is transmitted on the PDSCH.

[0538] As an example, both steps in blocks F51 and F52 of Figure 5 are present, and the sender of the first configuration information block is the second node U1.

[0539] As an example, the step in block F51 of Figure 5 is absent, the step in F52 is present, and the sender of the first configuration information block is different from the second node U1.

[0540] As an example, the first information block belongs to the first dataset.

[0541] As one embodiment, the first information block is transmitted on a first radio bearer, which is a new radio bearer other than the radio bearers supported by 3GPP R19.

[0542] As one embodiment, the first channel information is associated with a first identifier, and the first model is associated with the first identifier.

[0543] As an example, the steps in block F55 of Figure 5 are present, and the method described above for use in the first node of wireless communication includes:

[0544] Deploy the first model.

[0545] As an example, the deployment of the first model precedes the transmission of the first information block.

[0546] As an example, the deployment of the first model is later than the sending of the first information block.

[0547] As an example, the step in block F56 of Figure 5 exists, and the method described above for the first node used in wireless communication includes: performing inference of the first model.

[0548] Example 6

[0549] Example 6 illustrates a schematic diagram of first channel information according to an embodiment of this application; as shown in Figure 6. In Example 6, the first channel information indicates L vectors and L2 coefficient groups, where L2 is equal to L multiplied by 2; the L vectors and the L2 coefficient groups are used to determine a first precoding matrix; the first precoding matrix is ​​equal to a concatenation of a first submatrix and a second submatrix, the first submatrix being equal to the sum of the L vectors weighted by L first weighting coefficients, and the second submatrix being equal to the sum of the L vectors weighted by L second weighting coefficients, the L first weighting coefficients depending on the first L coefficient groups in the L2 coefficient groups, and the L second weighting coefficients depending on the last L coefficient groups in the L2 coefficient groups; any coefficient group in the L2 coefficient groups includes at least one of an amplitude coefficient, a phase coefficient, and a subband amplitude coefficient.

[0550] In Figure 6, the L vectors are represented as vector #i (i = 0 to L-1); the first L coefficient groups of the L2 coefficient groups are represented as coefficient group #i (i = 0 to L-1), and the last L coefficient groups of the L2 coefficient groups are represented as coefficient group #(L+i) (i = 0 to L-1); the L first weighted coefficients and the L second weighted coefficients are represented as first weighted coefficient #i (i = 0 to L-1) and second weighted coefficient #i (i = 0 to L-1), respectively; the amplitude coefficient, phase coefficient, and sub-band amplitude coefficient included in coefficient group #i (i = 0 to L-1) are represented as first amplitude coefficient #i, first phase coefficient #i, and first sub-band amplitude coefficient #i, respectively; the amplitude coefficient, phase coefficient, and sub-band amplitude coefficient included in coefficient group #(L+i) (i = 0 to L-1) are represented as second amplitude coefficient #i, second phase coefficient #i, and second sub-band amplitude coefficient #i, respectively.

[0551] As an example, any one of the L2 coefficient groups includes at least two of the following: an amplitude coefficient, a phase coefficient, and a sub-band amplitude coefficient.

[0552] As an example, any one of the L2 coefficient groups includes an amplitude coefficient, a phase coefficient, and a sub-band amplitude coefficient.

[0553] As an example, the first channel information indicates the coefficient group in which the strongest coefficient is located among the L2 coefficient groups, and the coefficient group in which the strongest coefficient is located includes an amplitude coefficient, a phase coefficient, and a sub-band amplitude coefficient that are all equal to 1.

[0554] As an example, the L first weighting coefficients correspond one-to-one with the first L coefficient groups, and the first weighting coefficient #i (i = 0, ..., L-1) corresponds to the coefficient group #i; the coefficient group #i includes a non-zero amplitude coefficient and a phase coefficient, and the first weighting coefficient #i is equal to the product of the non-zero amplitude coefficient and the phase coefficient; or the coefficient group #i includes a non-zero amplitude coefficient, a phase coefficient and a sub-band amplitude coefficient, and the first weighting coefficient #i is equal to the product of the non-zero amplitude coefficient, the phase coefficient and the sub-band amplitude coefficient; or the coefficient group #i includes a zero amplitude coefficient and the first weighting coefficient #i is equal to 0.

[0555] As one embodiment, the L second weighting coefficients correspond one-to-one with the following L coefficient groups. The second weighting coefficient #i (i = 0, ..., L-1) corresponds to the coefficient group #(L+i). The coefficient group #(L+i) includes a non-zero amplitude coefficient and a phase coefficient, and the second weighting coefficient #i is equal to the product of the non-zero amplitude coefficient and the phase coefficient; or the coefficient group #(L+i) includes a non-zero amplitude coefficient, a phase coefficient, and a sub-band amplitude coefficient, and the second weighting coefficient #i is equal to the product of the non-zero amplitude coefficient, the phase coefficient, and the sub-band amplitude coefficient; or the coefficient group #(L+i) includes a zero amplitude coefficient, and the second weighting coefficient #i is equal to 0.

[0556] As an example, any one of the L2 coefficient groups includes an amplitude coefficient, a phase coefficient, and a sub-band amplitude coefficient; the L first weighted coefficients correspond one-to-one with the first L coefficient groups, and any one of the L first weighted coefficients is equal to the product of the amplitude coefficient, phase coefficient, and sub-band amplitude coefficient of the corresponding coefficient group; the L second weighted coefficients correspond one-to-one with the last L coefficient groups, and any one of the L second weighted coefficients is equal to the product of the amplitude coefficient, phase coefficient, and sub-band amplitude coefficient of the corresponding coefficient group.

[0557] As an example, the first set of parameters indicates the L.

[0558] As an example, the number of non-zero amplitude coefficients in the L2 coefficient groups depends on the parameters related to the number of vectors and coefficients in the first parameter set.

[0559] As a sub-example of the above embodiment, the number of non-zero amplitude coefficients in the L2 coefficient groups depends on l.

[0560] As an example, the parameters related to the number of vectors and coefficients in the first parameter set indicate the upper limit of the number of non-zero amplitude coefficients in the L2 coefficient groups.

[0561] As a sub-implementation of the above embodiment, the upper limit of the number of non-zero amplitude coefficients in the L2 coefficient groups depends on l.

[0562] As an example, the number of sub-band amplitude coefficients included in the L2 coefficient groups depends on the parameters related to the number of vectors and coefficients in the first parameter set.

[0563] As an example, the number of non-fixed-value sub-band amplitude coefficients included in the L2 coefficient groups depends on the parameters related to the number of vectors and coefficients in the first parameter set.

[0564] As a sub-example of the above embodiment, the number of non-fixed value sub-band amplitude coefficients in the L2 coefficient groups depends on l.

[0565] As an example, the parameters related to the number of vectors and coefficients in the first parameter set indicate the upper limit of the number of non-fixed-value subband amplitude coefficients included in the L2 coefficient groups.

[0566] As an example, the upper limit of the number of non-fixed-value sub-band amplitude coefficients included in the L2 coefficient groups depends on l.

[0567] As an example, the quantization-related parameters in the first parameter set indicate the value range of at least some amplitude coefficients of the L2 coefficient groups.

[0568] As an example, the range of values ​​for at least some of the amplitude coefficients in the L2 coefficient groups depends on l.

[0569] As an example, the first amplitude coefficient of the L2 coefficient groups is taken from the first amplitude group, which includes multiple amplitudes.

[0570] As a sub-implementation of the above embodiment, the first amplitude coefficient is any amplitude coefficient in the L2 coefficient groups.

[0571] As a sub-implementation of the above embodiment, the first amplitude coefficient is any non-zero amplitude coefficient in the L2 coefficient groups.

[0572] As a sub-implementation of the above embodiments, the quantization-related parameters in the first parameter set indicate the first amplitude group.

[0573] As a sub-implementation of the above embodiments, the first amplitude group depends on the l.

[0574] As a sub-implementation of the above embodiment, when l is less than a first threshold, the first amplitude group is a first candidate amplitude group; when l is not less than the first threshold, the first amplitude group is a second candidate amplitude group; the first candidate amplitude group and the second candidate amplitude group each include a maximum amplitude equal to 1, a minimum amplitude, and one or more other amplitudes between the maximum amplitude and the minimum amplitude; the number of amplitudes in the first candidate amplitude group is greater than the number of amplitudes in the second candidate amplitude group.

[0575] As a reference embodiment of the above sub-example, the minimum amplitude is equal to 0.

[0576] As a reference embodiment of the above sub-example, the minimum amplitude is a positive real number less than 1.

[0577] As a reference embodiment of the above sub-example, the minimum amplitude in the first candidate amplitude group and the second candidate amplitude group is equal.

[0578] As a reference embodiment of the above sub-example, the minimum amplitude in the first candidate amplitude group is smaller than the minimum amplitude in the second candidate amplitude group.

[0579] As a sub-implementation of the above embodiment, the first amplitude group remains unchanged regardless of the value of l.

[0580] As an example, the quantization-related parameters in the first parameter set indicate the value range of at least some phase coefficients of the L2 coefficient groups.

[0581] As an example, the range of values ​​for at least some of the phase coefficients in the L2 coefficient groups depends on l.

[0582] As an example, the first phase coefficient is a non-fixed value phase coefficient among the L2 coefficient groups, and the first phase coefficient is e. j2πc1 / N3 Where N3 is a positive integer greater than 1, and c1 takes values ​​from 0, 1, ..., N3-1; the first channel information indicates c1.

[0583] As a sub-implementation of the above embodiment, the first phase coefficient is any non-fixed value of the phase coefficient in the L2 coefficient groups.

[0584] As a sub-implementation of the above embodiment, the first channel information indicates the first phase coefficient by indicating c1.

[0585] As a sub-example of the above embodiment, the quantization-related parameters in the first parameter set indicate N3.

[0586] As a sub-implementation of the above embodiments, N3 depends on l.

[0587] As a reference embodiment of the above sub-example, the value of N3 is greater when l is less than the first threshold than the value of N3 when l is not less than the first threshold.

[0588] As a sub-implementation of the above embodiment, when the amplitude coefficient corresponding to the first phase coefficient is one of the largest P1 amplitude coefficients among all amplitude coefficients in the L2 coefficient groups, N3 is equal to a first integer; when the amplitude coefficient corresponding to the first phase coefficient is not one of the largest P1 amplitude coefficients, N3 is equal to a second integer; the first integer is greater than the second integer.

[0589] As a reference embodiment of the above sub-example, the first parameter set indicates P1.

[0590] As a reference embodiment of the above sub-example, the parameters related to the number of vectors and coefficients in the first parameter set indicate P1.

[0591] As a reference embodiment of the above sub-example, P1 depends on l.

[0592] As a reference embodiment of the above sub-example, the value of P1 is greater when l is less than the first threshold than the value of P1 when l is not less than the first threshold.

[0593] As a reference embodiment of the above sub-example, the quantization-related parameters in the first parameter set indicate at least one of the first integer and the second integer.

[0594] As a reference embodiment of the above sub-example, at least one of the first integer and the second integer depends on l.

[0595] As an example, the quantization-related parameters in the first parameter set indicate the value range of at least some sub-band amplitude coefficients of the L2 coefficient groups.

[0596] As an example, the range of values ​​for at least some of the sub-band amplitude coefficients in the L2 coefficient groups depends on l.

[0597] As an example, the first sub-band amplitude coefficient is a non-fixed value of one of the L2 coefficient groups of the first sub-band amplitude coefficient, the first sub-band amplitude coefficient being taken from the first sub-band amplitude group, the first sub-band amplitude group including multiple sub-band amplitudes.

[0598] As a sub-implementation of the above embodiment, the first sub-band amplitude coefficient is any non-fixed value of the sub-band amplitude coefficient in the L2 coefficient groups.

[0599] As a sub-implementation of the above embodiments, the quantization-related parameters in the first parameter set indicate the first sub-band amplitude group.

[0600] As a sub-implementation of the above embodiment, the first sub-band amplitude group depends on l.

[0601] As a sub-implementation of the above embodiment, when l is less than a first threshold, the first sub-band amplitude group is a first candidate sub-band amplitude group; when l is not less than the first threshold, the first sub-band amplitude group is a second candidate sub-band amplitude group; the first candidate sub-band amplitude group and the second candidate sub-band amplitude group each include a maximum sub-band amplitude equal to 1, a minimum sub-band amplitude less than 1 and greater than 0, and one or more other sub-band amplitudes between the maximum sub-band amplitude and the minimum sub-band amplitude; the number of sub-band amplitudes in the first candidate sub-band amplitude group is greater than the number of sub-band amplitudes in the second candidate sub-band amplitude group.

[0602] As an example, the parameters related to the number of vectors and coefficients in the first parameter set indicate the L.

[0603] As an example, L is independent of l.

[0604] Example 7

[0605] Example 7 illustrates a schematic diagram of first channel information according to an embodiment of this application; as shown in Figure 7. In Example 7, the first channel information indicates L vectors, M vectors, and L2 coefficient groups, where L2 is equal to L multiplied by 2; the L vectors, M vectors, and L2 coefficient groups are used to determine W precoding matrices, where the length of any of the M vectors is equal to W; in Figure 7, the W precoding matrices are represented as precoding matrices #t (t = 0, ..., W-1); precoding matrices #t (t = 0, ..., W-1) are equal to a concatenation of a first submatrix #t and a second submatrix #t, where the first submatrix is ​​equal to The sum of the L vectors after being weighted by L first weighting coefficients, and the second submatrix is ​​equal to the sum of the L vectors after being weighted by L second weighting coefficients. The L first weighting coefficients depend on the first L coefficient groups in the L2 coefficient groups and the M vectors, and the L second weighting coefficients depend on the last L coefficient groups in the L2 coefficient groups and the M vectors. Any coefficient group in the L2 coefficient groups includes M coefficient subgroups, and any coefficient subgroup in any coefficient group in the L2 coefficient groups includes an amplitude coefficient and a phase coefficient.

[0606] In Figure 7, the L vectors are represented as vectors #i (i = 0 to L-1); the first L coefficient groups of the L2 coefficient groups are represented as coefficient group #i (i = 0 to L-1), and the last L coefficient groups of the L2 coefficient groups are represented as coefficient group #(L+i) (i = 0 to L-1); the L first weighted coefficients and the L second weighted coefficients are represented as first weighted coefficient #i (i = 0 to L-1) and second weighted coefficient #i (i = 0 to L-1), respectively; the M coefficient subgroups in coefficient group #i (i = 0 to L-1) are represented as coefficient subgroup #(i,0), ..., coefficient subgroup #(i,M-1); coefficient subgroup #(i,f) (i = 0 to L-1) The amplitude coefficients and phase coefficients included in the coefficient group #(L+i)(i=0~L-1) are represented as the first amplitude coefficient #(i,f) and the first phase coefficient #(i,f), respectively; the M coefficient subgroups in the coefficient group #(L+i)(i=0~L-1) are represented as coefficient subgroup #(L+i,0), ..., coefficient subgroup #(L+i,M-1), respectively; the amplitude coefficients and phase coefficients included in the coefficient subgroup #(L+i,f)(i=0~L-1,f=0,…,M-1) are represented as the second amplitude coefficient #(i,f) and the second phase coefficient #(i,f), respectively; the elements in the M vectors are represented as the element #(t,f)(t=0,…,W-1,f=0,…,M-1).

[0607] In Example 7, elements #(0,f), ..., element #(W-1,f) form one of the M vectors, f = 0, ..., M-1.

[0608] As an example, the L first weighting coefficients correspond one-to-one with the first L coefficient groups, and the first weighting coefficient #i (i = 0, ..., L-1) corresponds to the coefficient group #i; the first weighting coefficient #i is equal to the sum of the first values ​​#0, ..., the first values ​​#(M-1) multiplied by the third amplitude coefficient, where the first value #f (f = 0, ..., M-1) is equal to the product of the first amplitude coefficient #(i,f) and the first phase coefficient #(i,f) multiplied by the element #(t,f).

[0609] As an example, the L second weighting coefficients correspond one-to-one with the following L coefficient groups, and the second weighting coefficient #i (i = 0, ..., L-1) corresponds to the coefficient group #(L+i); the second weighting coefficient #i is equal to the sum of the second values ​​#0, ..., the second values ​​#(M-1) multiplied by the fourth amplitude coefficient, where the second value #f (f = 0, ..., M-1) is equal to the product of the second amplitude coefficient #(i,f) and the second phase coefficient #(i,f) multiplied by the element #(t,f).

[0610] As an example, the first channel information indicates the third amplitude coefficient and the fourth amplitude coefficient.

[0611] As an example, the third amplitude coefficient and the fourth amplitude coefficient are both positive real numbers not greater than 1.

[0612] As an example, the first channel information indicates the coefficient subgroup containing the strongest coefficient among the L2 coefficient groups, wherein the amplitude coefficient and phase coefficient of the coefficient subgroup containing the strongest coefficient are both equal to 1.

[0613] As an example, the first channel information indicates that the L2 coefficient groups include coefficient subgroups with non-zero coefficients.

[0614] As an example, the amplitude coefficients in the L2 coefficient groups, except for the coefficient subgroups that include non-zero coefficients, are all defaulted to 0.

[0615] As an example, the coefficients in the coefficient subgroups with non-zero coefficients in the L2 coefficient groups need to be reported.

[0616] As an example, the first channel information indicates which coefficients in the L2 coefficient groups need to be reported.

[0617] As an example, the coefficients in the L2 coefficient groups other than those containing non-zero coefficients do not need to be reported.

[0618] As an example, the non-zero coefficient refers to a non-zero amplitude coefficient.

[0619] As an example, the first parameter set indicates the upper limit of the total number of non-zero coefficients included in the L2 coefficient groups.

[0620] As an example, the parameters related to the number of vectors and coefficients in the first parameter set indicate the upper limit of the total number of non-zero coefficients included in the L2 coefficient groups.

[0621] As an example, the upper limit of the total number of non-zero coefficients included in the L2 coefficient groups depends on l.

[0622] As an example, when l is less than the first threshold, the upper limit of the total number of non-zero coefficients included in the L2 coefficient groups is greater than the upper limit of the total number of non-zero coefficients included in the L2 coefficient groups when l is not less than the first threshold.

[0623] As an example, the upper limit of the total number of non-zero coefficients included in the L2 coefficient groups depends on the product of the total number of coefficients in the L2 coefficient groups and the third coefficient, wherein the vector and coefficient number-related parameters in the first parameter set indicate the third coefficient, which is a positive real number less than 1.

[0624] As a sub-implementation of the above embodiments, the third coefficient depends on l.

[0625] As a sub-example of the above embodiment, the third coefficient increases as l decreases.

[0626] As an example, the quantization-related parameters in the first parameter set indicate the value range of at least some amplitude coefficients of the L2 coefficient groups, and the value range of the at least some amplitude coefficients depends on l.

[0627] As an example, the quantization-related parameters in the first parameter set indicate the value range of at least some phase coefficients of the L2 coefficient groups, and the value range of the at least some phase coefficients depends on l.

[0628] As an example, the first set of parameters indicates the M.

[0629] As an example, M depends on the frequency domain configuration parameters and the parameters related to the number of vectors and coefficients in the first parameter set.

[0630] As an example, M depends on l.

[0631] As an example, when l is less than a first threshold, the value of M is not equal to the value of M when l is not less than the first threshold.

[0632] As an example, the W precoding matrices are respectively for W PMI subbands, where W is a positive integer, and M depends on W, a first coefficient, and a second coefficient.

[0633] As a sub-example of the above embodiment, M is equal to W divided by the first coefficient, multiplied by the second coefficient, and then rounded down.

[0634] As one embodiment, the first parameter set includes the first coefficient, and the parameters related to the number of vectors and coefficients in the first parameter set indicate the second coefficient.

[0635] As an example, the first coefficient depends on l.

[0636] As an example, when l is less than a first threshold, the first coefficient is equal to 2; when l is not less than the first threshold, the first coefficient is equal to 1.

[0637] As an example, the second coefficient depends on l.

[0638] As an example, when l is less than the first threshold, the value of the second coefficient is greater than the value of the second coefficient when l is not less than the first threshold.

[0639] As an example, both the first coefficient and the second coefficient depend on l.

[0640] As an example, the first coefficient does not depend on l, while the second coefficient depends on l.

[0641] As an example, any PMI subband among the W PMI subbands belongs to one of the W1 subbands, where W1 is a positive integer, and W depends on W1 and a first coefficient.

[0642] As an example, when the first coefficient is equal to 1, W is equal to W1, and the W PMI subbands are the W1 subbands; when the first coefficient is greater than 1, W is greater than W1 but not greater than the product of the first coefficient and W1.

[0643] As an example, the frequency domain configuration parameters in the first parameter set indicate the W1 sub-bands.

[0644] As an example, W1 does not depend on l.

[0645] Example 8

[0646] Example 8 illustrates a schematic diagram of first channel information according to an embodiment of this application; as shown in Figure 8. In Example 8, the first channel information indicates L vectors, M vectors, Q vectors, and L2 coefficient groups, where L2 is equal to L multiplied by 2; the L vectors, M vectors, Q vectors, and L2 coefficient groups are used to determine N precoding matrix groups, each of the N precoding matrix groups targeting N time slot intervals; each of the N precoding matrix groups includes W precoding matrices; the length of any one of the M vectors is equal to W; the length of any one of the Q vectors is equal to N. In Figure 8, the precoding matrix in the N precoding matrix groups is represented as precoding matrix #(ι,t) (ι=0,…,N-1,t=0,…,W-1); the precoding matrix #(ι,t) (ι=0,…,N-1,t=0,…,W-1) is equal to the concatenation of the first submatrix and the second submatrix. The first submatrix is ​​equal to the sum of the L vectors after being weighted by L first weighting coefficients, and the second submatrix is ​​equal to the sum of the L vectors after being weighted by L second weighting coefficients. The L first weighting coefficients depend on the first L coefficient groups, the M vectors and the Q vectors in the L2 coefficient groups. The L second weighting coefficients depend on the last L coefficient groups, the M vectors and the Q vectors in the L2 coefficient groups. Any coefficient group in the L2 coefficient groups includes M coefficient subgroups, and any coefficient subgroup in any coefficient group in the L2 coefficient groups includes Q amplitude coefficients and Q phase coefficients.

[0647] In Figure 8, the L vectors are represented as vectors #i (i = 0 to L-1); the first L coefficient groups of the L2 coefficient groups are represented as coefficient group #i (i = 0 to L-1), and the last L coefficient groups of the L2 coefficient groups are represented as coefficient group #(L+i) (i = 0 to L-1); the L first weighted coefficients and the L second weighted coefficients are represented as first weighted coefficient #i and second weighted coefficient #i (i = 0 to L-1); the M coefficient subgroups in coefficient group #i (i = 0 to L-1) are represented as coefficient subgroup #(i,0), ..., coefficient subgroup #(i,M-1); the Q amplitude coefficients / Q phase coefficients included in coefficient subgroup #(i,f) (i = 0 to L-1, f = 0, ..., M-1) are represented as first amplitude coefficient #(i,f,0) / first phase coefficient #(i,f,0), ..., first amplitude coefficient #(i,f,Q-1) / First phase coefficient#(i,f,Q-1); The M coefficient subgroups in the coefficient group #(L+i) (i=0~L-1) are respectively represented as coefficient subgroups #(L+i,0), ..., coefficient subgroup #(L+i,M-1); The Q amplitude coefficients / Q phase coefficients included in the coefficient subgroup #(L+i,f) (i=0~L-1,f=0,…,M-1) are respectively represented as second amplitude coefficients#. (i,f,0) / second phase coefficient #(i,f,0), ..., second amplitude coefficient #(i,f,Q-1) / second phase coefficient #(i,f,Q-1); the elements in the M vectors are represented as the first element #(t,f)(t=0,…,W-1,f=0,…,M-1), and the elements in the Q vectors are represented as the second element #(ι,τ)(ι=0,…,N-1,τ=0,…,Q-1).

[0648] In Example 8, the first element #(0,f),..., first element #(W-1,f) forms one of the M vectors, where f = 0,...,M-1; the second element #(0,τ),..., second element #(N-1,τ) forms one of the Q vectors, where τ = 0,...,Q-1.

[0649] As an example, the L first weighting coefficients correspond one-to-one with the first L coefficient groups, and the first weighting coefficient #i (i = 0, ..., L-1) corresponds to the coefficient group #i; the first weighting coefficient #i is equal to the sum of the first values ​​#0, ..., the first values ​​#(M-1) multiplied by the third amplitude coefficient, where the first value #f (f = 0, ..., M-1) is equal to the product of the sum of the third values ​​#0, ..., the third values ​​#(Q-1) and the first element #(t,f), and the third value #τ (τ = 0, ..., Q-1) is equal to the product of the first amplitude coefficient #(i,f,τ) and the first phase coefficient #(i,f,τ) multiplied by the second element #(ι,τ).

[0650] As an example, the L second weighting coefficients correspond one-to-one with the following L coefficient groups, and the second weighting coefficient #i (i = 0, ..., L-1) corresponds to the coefficient group #(L+i); the second weighting coefficient #i is equal to the sum of the second values ​​#0, ..., the second values ​​#(M-1) multiplied by the fourth amplitude coefficient, where the second value #f (f = 0, ..., M-1) is equal to the product of the sum of the fourth values ​​#0, ..., the fourth values ​​#(Q-1) and the first element #(t,f), and the fourth value #τ (τ = 0, ..., Q-1) is equal to the product of the second amplitude coefficient #(i,f,τ) and the second phase coefficient #(i,f,τ) multiplied by the second element #(ι,τ).

[0651] As an example, the first channel information indicates the third amplitude coefficient and the fourth amplitude coefficient.

[0652] As an example, the third amplitude coefficient and the fourth amplitude coefficient are both positive real numbers not greater than 1.

[0653] As one example, Q depends on the first set of parameters.

[0654] As an example, the time slot interval configuration parameter in the first parameter set indicates the Q.

[0655] As an example, Q does not depend on l.

[0656] As one example, the N time slot intervals depend on the first set of parameters.

[0657] As one example, N depends on the first set of parameters.

[0658] As an example, the time slot interval configuration parameter in the first parameter set indicates the N.

[0659] As an example, any two time slots among the N time slot intervals have the same length.

[0660] As an example, the length of any one of the N time slot intervals depends on the first set of parameters.

[0661] As an example, the time slot interval configuration parameter in the first parameter set indicates a first length, and the length of any time slot interval among the N time slot intervals is equal to the first length.

[0662] As an example, N does not depend on l.

[0663] As an example, the length of any one of the N time slot intervals does not depend on l.

[0664] As an example, the first channel information indicates the coefficient subgroup to which the strongest coefficient in the L2 coefficient groups belongs and the position of the strongest coefficient in the coefficient subgroup to which it belongs, wherein the amplitude coefficient and phase coefficient at the position in the coefficient subgroup to which the strongest coefficient belongs are both equal to 1.

[0665] As an example, the first channel information indicates the coefficient subgroups including non-zero coefficients in the L2 coefficient groups and the position of the non-zero coefficients in their respective coefficient subgroups.

[0666] As an example, the first channel information indicates which coefficient subgroups among the L2 coefficient groups include non-zero coefficients, and the positions of the non-zero coefficients within these coefficient subgroups.

[0667] As an example, the amplitude coefficients in all coefficient subgroups of the L2 coefficient groups except for those containing non-zero coefficients are all 0.

[0668] As an example, in the L2 coefficient groups, the amplitude coefficients at positions other than the non-zero coefficients in the coefficient subgroups are all 0.

[0669] As an example, the coefficients in the L2 coefficient groups, except for those in the positions of non-zero coefficients in the coefficient subgroups that include non-zero coefficients, do not need to be fed back.

[0670] As an example, the coefficients at the positions of the non-zero coefficients in only the coefficient subgroups of the L2 coefficient groups need to be fed back.

[0671] As an example, the first channel information indicates which coefficients in the L2 coefficient groups need to be fed back.

[0672] As an example, the non-zero coefficient refers to a non-zero amplitude coefficient.

[0673] As an example, the position refers to the nth amplitude coefficient or the nth phase coefficient among the Q amplitude coefficients or Q phase coefficients included in a coefficient subgroup.

[0674] As an example, the parameters related to the number of vectors and coefficients in the first parameter set indicate an upper limit on the total number of non-zero coefficients included in the L2 coefficient groups, the upper limit depending on l.

[0675] As an example, the quantization-related parameters in the first parameter set indicate the value range of at least some amplitude coefficients of the L2 coefficient groups, and the value range of the at least some amplitude coefficients depends on l.

[0676] As an example, the quantization-related parameters in the first parameter set indicate the value range of at least some phase coefficients of the L2 coefficient groups, and the value range of the at least some phase coefficients depends on l.

[0677] Example 9

[0678] Example 9 illustrates a schematic diagram of a second information block according to an embodiment of this application; as shown in Figure 9. In Example 9, the second information block indicates the first parameter set.

[0679] As an example, the second information block explicitly indicates the first set of parameters.

[0680] As one embodiment, the second information block indicates each parameter in the first parameter set.

[0681] As one embodiment, the second information block indicates the first parameter set from a plurality of candidate parameter sets.

[0682] As an example, some parameters in the first parameter set are the same as some parameters in a reference parameter set, while other parameters in the first parameter set are different from other parameters in the reference parameter set. The second information block only indicates the other part of the parameters in the first parameter set.

[0683] As a sub-implementation of the above embodiments, the reference parameter set is configured by a higher-layer signaling.

[0684] As a sub-implementation of the above embodiments, the reference parameter set is configured for the first node.

[0685] As a sub-implementation of the above embodiments, the reference parameter set is reported by the first node.

[0686] As an example, some parameters in the first parameter set depend on l, while other parameters in the first parameter set do not depend on l, and the second information block only indicates the portion of parameters in the first parameter set.

[0687] As a sub-implementation of the above embodiments, another part of the parameters in the first parameter set are configured by higher-layer signaling.

[0688] As a sub-implementation of the above embodiment, another part of the parameters in the first parameter set is configured for the first node.

[0689] As a sub-implementation of the above embodiment, the other part of the parameters in the first parameter set are reported by the first node.

[0690] As one example, the second information block implicitly indicates the first parameter set.

[0691] As one embodiment, the second information block indicates the first parameter set by indicating other information.

[0692] As an example, only a portion of the parameters in the first parameter set depend on l, and the second information block indicates the portion of parameters in the first parameter set by indicating other information.

[0693] As an example, the other information includes, but is not limited to, one or more of the following: channel environment type, mobile speed, subcarrier spacing, carrier frequency, delay spread, Doppler spread, Doppler shift, average delay, and spatial reception parameters.

[0694] As an example, the first node determines the first parameter set.

[0695] As an example, the first node determines the first parameter set on its own.

[0696] The advantages of the above method include giving the first node sufficient degrees of freedom to select the first parameter set according to the actual channel conditions, thereby optimizing the reporting.

[0697] Generally, how the first node determines the first parameter set is determined by the hardware device manufacturer. Below are some non-limiting implementation methods:

[0698] As an example, the first node determines the first parameter set based on l.

[0699] As an example, the first node determines the first parameter set from the plurality of candidate parameter sets such that the smaller the l is, the larger the payload size of the first channel information generated based on the first parameter set.

[0700] As an example, the first node determines the first parameter set from the plurality of candidate parameter sets such that the smaller the value of l, the higher the accuracy of the first channel information generated based on the first parameter set.

[0701] As an example, the first parameter belongs to the parameters related to the number of vectors and coefficients in the first parameter set, and the first node determines the first parameter from M1 candidate parameters, where M1 is a positive integer greater than 1.

[0702] As an example, the first node determines the first parameter from the M1 candidate parameters based on at least one of the following:

[0703] The smaller l is, the greater the number of non-zero amplitude coefficients or non-zero coefficients indicated by the first channel information generated based on the first parameter;

[0704] The smaller l is, the greater the number of non-fixed value phase coefficients indicated by the first channel information generated based on the first parameter;

[0705] The smaller l is, the greater the number of non-fixed value subband amplitude coefficients indicated by the first channel information generated based on the first parameter;

[0706] The smaller l is, the larger the value of M is.

[0707] As an example, the second parameter is a quantization-related parameter in the first parameter set, and the first node determines the second parameter from M2 candidate parameters, where M2 is a positive integer greater than 1.

[0708] As an example, the first node determines the second parameter from the M2 candidate parameters based on at least one of the following:

[0709] The smaller l is, the higher the quantization accuracy of the amplitude coefficient indicated by the first channel information generated based on the second parameter;

[0710] The smaller l is, the higher the quantization accuracy of the phase coefficient indicated by the first channel information generated based on the second parameter;

[0711] The smaller l is, the higher the quantization accuracy of the subband amplitude coefficient indicated by the first channel information generated based on the second parameter;

[0712] As an example, the quantization precision of a coefficient is related to the number of bits required to represent that coefficient.

[0713] As an example, the quantization precision of a coefficient increases with the increase in the number of bits required to represent the coefficient.

[0714] As an example, the first node determines the first set of parameters based on the measurements taken on the first RS resource.

[0715] As an example, the first node determines the first set of parameters based on the channel characteristics obtained from the measurements on the first RS resource.

[0716] As an example, the channel characteristics include one or more of delay spread, Doppler spread, Doppler shift, average delay, or spatial reception parameters.

[0717] As one example, the channel characteristics include the rate of change of the channel in the time domain and frequency domain.

[0718] As one example, the channel characteristics include the number of spatial reflection paths of the channel.

[0719] As one example, the channel characteristics include the number of multipath paths.

[0720] As one example, the channel characteristics include the number of multipaths that contribute more than a threshold.

[0721] As an example, the channel characteristics include one or more of the following: channel impulse response, small-scale characteristics, channel matrix, and the number of eigenvalues ​​of the channel matrix that are greater than a threshold.

[0722] As an example, the faster the channel changes in the frequency domain, the larger the first node selects the first set of parameters such that W is larger.

[0723] As an example, the faster the channel changes in the frequency domain, the more the first node selects the first parameter set such that each of the W PMI subbands includes a smaller number of RBs.

[0724] As an example, the faster the channel changes in the time domain, the smaller the N becomes when the first node selects the first set of parameters.

[0725] As an example, the faster the channel changes in the time domain, the more the first node selects the first set of parameters such that the length of each of the N time slot intervals is smaller.

[0726] As an example, the greater the number of spatial reflection paths of the channel, the larger the L is when the first node selects the first set of parameters.

[0727] As one example, the first node randomly selects the first parameter set from a plurality of candidate parameter sets.

[0728] As an example, the first node sequentially selects multiple candidate parameter sets as the first parameter set.

[0729] As an example, the first node takes the result of the measurement on the first RS resource as an input to an inference, the output of which includes the first set of parameters.

[0730] As an example, the first node determines all parameters in the first parameter set on its own.

[0731] As an example, the first node determines some parameters in the first parameter set on its own, and uses parameters from a reference parameter set as another part of the parameters in the first parameter set.

[0732] As an example, only a portion of the parameters in the first parameter set depend on l, and the first node determines the portion of parameters in the first parameter set on its own.

[0733] As a sub-implementation of the above embodiments, another part of the parameters in the first parameter set is configured to the first node.

[0734] As a sub-implementation of the above embodiments, another part of the parameters in the first parameter set are configured by higher-level parameters.

[0735] As a sub-implementation of the above embodiments, another part of the parameters in the first parameter set comes from a reference parameter set.

[0736] As an example, the first channel information is used to determine at least one precoding matrix for layer l, and the first node determines the first set of parameters such that the difference between the at least one precoding matrix and at least one optimal precoding matrix for layer l is less than a threshold.

[0737] As a sub-implementation of the above embodiment, the threshold depends on l.

[0738] As a sub-example of the above embodiment, the threshold increases as l increases.

[0739] Example 10

[0740] Example 10 illustrates a schematic diagram of K parameter sets and K channel information according to an embodiment of this application; as shown in Figure 10. In Example 10, the K channel information refers to K layers respectively. In Figure 10, the K parameter sets are represented as parameter set #0, ..., parameter set #(K-1); the K channel information is represented as channel information #0, ..., channel information #(K-1); and the K layers are represented as layer 1, ..., layer K.

[0741] As an example, K is a positive integer no greater than 4.

[0742] As an example, K is a positive integer not greater than 8.

[0743] As an example, K is a positive integer no greater than 16.

[0744] As an example, the first channel information is any one of the K channel information.

[0745] As one example, the K layers are K MIMO layers.

[0746] As one example, the K layers are K transport layers.

[0747] As an example, K is the number of layers.

[0748] As an example, the number of layers refers to the number of MIMO layers.

[0749] As an example, the number of layers refers to the number of transmission layers.

[0750] As an example, the number of layers refers to the transmission rank.

[0751] As an example, the K layers are layer 1, layer 2, ..., layer K.

[0752] As an example, l is not greater than K.

[0753] As an example, l is any positive integer not greater than K.

[0754] In a preferred embodiment, the first information block indicates the K.

[0755] As an example, the K channel information is PMI.

[0756] As an example, the K channel information is a codebook-based PMI.

[0757] In a preferred embodiment, the K channel information is a PMI based on the Type II codebook.

[0758] As an example, the K channel information are PMIs for the K layers respectively.

[0759] As an example, the K channel information each includes portions of the PMI based on the Type II codebook for the K layers.

[0760] As an example, the K channel information each includes a portion of the PMI based on the Type II codebook used to generate the precoding matrix of the K layers.

[0761] As an example, any one of the K channel information includes a portion of the PMI based on the Type II codebook used only to generate the precoding matrix of the layer to which this channel information is targeted, and one of the K channel information also includes a portion of the PMI based on the Type II codebook used to generate the precoding matrix of each of the K layers.

[0762] As an example, the second channel information in the K channel information refers to layer v in the K layers. For any layer v1 in the K layers other than layer v, the channel information corresponding to layer v1 in the K channel information and the second channel information are used together to generate the precoding matrix of layer v1. For layer v, only the second channel information in the K channel information is used to generate the precoding matrix of layer v.

[0763] As a sub-example of the above embodiment, v is equal to 1.

[0764] As a sub-example of the above embodiment, v is equal to l.

[0765] As an example, the K channel information are used to determine K sets of precoding matrices, which are precoding matrices for the K layers respectively.

[0766] In a preferred embodiment, the K channel information refers to the same group of subbands.

[0767] As an example, the CSI reporting frequency bands of the K channel information are the same group of sub-bands.

[0768] As an example, the same group of subbands refers to the W1 subbands.

[0769] As an example, the sub-band is described in Example 1.

[0770] As an example, the K channel information targets the same CSI reporting frequency band.

[0771] In a preferred embodiment, the K channel information refers to the same CSI reference resource.

[0772] As an example, the K channel information targets the same time-frequency resource.

[0773] In a preferred embodiment, any one of the K channel information depends on the measurement on the first RS resource.

[0774] As an example, the first node obtains channel measurements for calculating any one of the K channel information based on the first RS resource.

[0775] As an example, the first parameter set is the set of parameters used to generate the first channel information from the K parameter sets.

[0776] As an example, two channel information generated based on any two different parameter sets from the K parameter sets have different load sizes.

[0777] As an example, any two different parameter sets in the K parameter sets include parameters related to different vectors and coefficient counts or parameters related to different quantization.

[0778] As an example, the number of non-zero amplitude coefficients indicated by two channel information generated based on any two different parameter sets from the K parameter sets are different.

[0779] As an example, the number of phase coefficients of non-fixed values ​​indicated by two channel information generated based on any two different parameter sets from the K parameter sets are different.

[0780] As an example, the number of non-fixed values ​​of the subband amplitude coefficients indicated by the two channel information generated based on any two different parameter sets from the K parameter sets are different.

[0781] As an example, the quantization precision of at least one of the amplitude coefficients or phase coefficients indicated by two channel information generated based on any two different parameter sets from the K parameter sets is different.

[0782] As an example, any two different parameter sets in the K parameter sets include some parameters that are the same.

[0783] As an example, at least two of the K parameter sets are different and include partially identical parameters.

[0784] As an example, any two parameter sets among the K parameter sets are different.

[0785] As an example, there are two identical parameter sets among the K parameter sets.

[0786] As an example, each of the K parameter sets depends on which layer it corresponds to.

[0787] As an example, the smaller the value of l, the more important the layer l is among the K layers.

[0788] Example 11

[0789] Example 11 illustrates a schematic diagram of K channel information being used to generate K sets of precoding matrices according to an embodiment of this application, as shown in Figure 11. In Example 11, the K sets of precoding matrices are used to generate W concatenated precoding matrices, each of which targets W PMI subbands. Any one of the W concatenated precoding matrices is formed by concatenating one precoding matrix from each of the K sets of precoding matrices. In Figure 11, the K channel information is represented as channel information #0, ..., channel information #(K-1); the K sets of precoding matrices are represented as precoding matrix group #0, ..., precoding matrix group #(K-1); and the W PMI subbands are represented as PMI subband #0, ..., PMI subband #(W-1).

[0790] In Figure 11(a), the W concatenated precoding matrices are respectively represented as concatenated precoding matrix #0, ..., concatenated precoding matrix #(W-1); the number of precoding matrices included in any one of the K groups of precoding matrices is equal to the number of precoding matrices, and the W precoding matrices included in any one of the K groups of precoding matrices are respectively for the W PMI subbands. The W precoding matrices included in the precoding matrix group #p (p = 0 to K-1) are respectively represented as precoding matrix #(p,0), ..., precoding matrix #(p,W-1); any one of the W concatenated precoding matrices is formed by concatenating the precoding matrices for the same PMI subband in each of the K groups of precoding matrices.

[0791] In Figure 11(b), any PMI subband among the W PMI subbands is composed of all or part of the RBs in one of the W1 subbands. The number of precoding matrices included in each of the K1 precoding matrices in the K groups of precoding matrices is equal to the number of W1 precoding matrices. The number of precoding matrices included in each of the K2 precoding matrices in the K groups of precoding matrices is equal to the number of W precoding matrices. The W1 precoding matrices included in any of the K1 precoding matrices are respectively for the W1 subbands. The W precoding matrices included in any of the K2 precoding matrices are respectively for the W PMI subbands.

[0792] In Figure 11(b), the W1 subbands are respectively represented as subband #0, ..., subband #(W1-1); any precoding matrix group #p1 (0≤p1≤K-1) in the K1 precoding matrix group includes W1 precoding matrices respectively represented as precoding matrix #(p1,0), ..., precoding matrix #(p1,W1-1); any precoding matrix group #p2 (0≤p2≤K-1) in the K2 precoding matrix group includes W precoding matrices respectively represented as precoding matrix #(p2,0), ..., precoding matrix #(p2,W-1).

[0793] In Figure 11(b), the concatenated precoding matrix #t (t = 0 to W-1) is any one of the W concatenated precoding matrices, the concatenated precoding matrix #t is for the PMI subband #t, the subband #j includes the PMI subband #t; the concatenated precoding matrix #t includes the precoding matrix for the subband #j in each of the K1 groups of precoding matrices, and includes the precoding matrix for the PMI subband #t in each of the K2 groups of precoding matrices.

[0794] In Figure 11(b), precoding matrix group #0 is a group of precoding matrices in the K2 group of precoding matrices, and precoding matrix group #(K-1) is a group of precoding matrices in the K1 group of precoding matrices.

[0795] Example 12

[0796] Example 12 illustrates a schematic diagram of K channel information being used to generate K sets of precoding matrices according to an embodiment of this application, as shown in Figure 12. In Example 12, any one of the K sets of precoding matrices includes N precoding matrix subgroups, each of which is for N time slot intervals; each of the precoding matrix subgroups includes W precoding matrices for W PMI subbands; the K sets of precoding matrices are used to generate N sets of concatenated precoding matrices, each of which is for the N time slot intervals; any one of the N sets of concatenated precoding matrices includes W concatenated precoding matrices for W PMI subbands; the W concatenated precoding matrices in any one of the N sets of concatenated precoding matrices are formed by concatenating the precoding matrices for the same PMI subband from the precoding matrix subgroups corresponding to the same time slot interval in each of the K sets of precoding matrices.

[0797] In Figure 12, the K channel information are represented as channel information #0, ..., channel information #(K-1); the K precoding matrices are represented as precoding matrix group #0, ..., precoding matrix group #(K-1); the W PMI subbands are represented as PMI subband #0, ..., PMI subband #(W-1); the N precoding matrix subgroups included in precoding matrix group #p (p = 0 to K-1) are represented as precoding matrix subgroup #(p,0), ..., precoding matrix subgroup #(p,N-1); precoding... The code matrix subgroup #(p,ι) (p=0~K-1,ι=0~N-1) includes W precoding matrices, which are represented as precoding matrix #(p,ι,0)… and precoding matrix #(p,ι,W-1); N concatenated precoding matrices are represented as concatenated precoding matrix group #0,… and concatenated precoding matrix group #(N-1); the concatenated precoding matrix group #ι (ι=0~N-1) includes W concatenated precoding matrices, which are represented as concatenated precoding matrix #(ι,0)… and concatenated precoding matrix #(ι,W-1).

[0798] Example 13

[0799] Example 13 illustrates a schematic diagram of a first information block including a first channel quality according to an embodiment of this application; as shown in Figure 13. In Example 13, the calculation of the first channel quality is based on the K channel information.

[0800] In a preferred embodiment, the first channel quality includes CQI.

[0801] As one example, the first channel quality includes RSRP.

[0802] As one example, the first channel quality includes SINR.

[0803] As one example, the first channel quality includes RSRQ.

[0804] As an example, the first channel quality is CQI.

[0805] As an example, the first channel quality is RSRP.

[0806] As an example, the first channel quality is SINR.

[0807] As an example, the first channel quality is RSRQ.

[0808] In a preferred embodiment, the quality of the first channel depends on the measurement on the first RS resource.

[0809] As an example, the first node obtains channel measurements for calculating the first channel quality based on the first RS resource.

[0810] As an example, K is the number of layers, and the calculation of the first channel quality is based on the K channel information and K.

[0811] As an example, the K channel information are used to determine K sets of precoding matrices, the K sets of precoding matrices are used to generate at least one concatenated precoding matrix, and the calculation of the first channel quality is conditional on the at least one concatenated precoding matrix.

[0812] As an example, K is the number of layers, the K channel information is used to determine K sets of precoding matrices, the K sets of precoding matrices are used to generate at least one concatenated precoding matrix, and the calculation of the first channel quality is based on K and the at least one concatenated precoding matrix.

[0813] As an example, the first channel quality is the highest CQI index that satisfies the following condition:

[0814] Using a modulation scheme corresponding to a CQI index, a combination of target code rate and transport block size, and occupying a PDSCH transport block of CSI reference resources, it can be received with a transport block error probability not exceeding the second threshold.

[0815] As a sub-example of the above embodiment, the second threshold is equal to 0.1.

[0816] As a sub-example of the above embodiment, the second threshold is equal to 0.00001.

[0817] As a sub-implementation of the above embodiments, the CSI reference resource is the CSI reference resource of the first channel quality.

[0818] As a sub-implementation of the above embodiments, the CSI reference resource is the CSI reference resource of the first channel information.

[0819] As a sub-implementation of the above embodiment, the CSI reference resource is the CSI reference resource of the K channel information.

[0820] As a sub-example of the above embodiment, the number of layers of the PDSCH signal carrying the PDSCH transport block is equal to K.

[0821] As a sub-example of the above embodiment, the K channel information are used to determine K sets of precoding matrices, and the PDSCH signal carrying the PDSCH transport block adopts the K sets of precoding matrices.

[0822] As a reference embodiment of the above sub-example, the K layers carrying the PDSCH signal of the PDSCH transport block respectively adopt the K groups of precoding matrices.

[0823] As a sub-implementation of the above embodiment, the K channel information are respectively used to determine K sets of precoding matrices, the K precoding matrices are used to generate at least one concatenated precoding matrix, and the PDSCH signal carrying the PDSCH transport block adopts the K precoding matrices.

[0824] As an example, the definition of the CSI reference resource is based on 3GPP TS38.214.

[0825] Example 14

[0826] Example 14 illustrates a schematic diagram of a second information block according to an embodiment of this application; as shown in Figure 14. In Figure 14(a), the second information block indicates the K parameter sets; in Figure 14(b), the second information block indicates a portion of the parameter sets among the K parameter sets.

[0827] As an example, the second information block indicates each of the K parameter sets.

[0828] As an example, the second information block indicates each of the K parameter sets.

[0829] As an example, the second information block does not repeatedly indicate the same set of parameters among the K parameter sets.

[0830] As an example, the second information block explicitly indicates each of the K parameter sets.

[0831] As an example, the second information block explicitly indicates each parameter in each of the K parameter sets.

[0832] As an example, the second information block indicates the K parameter sets respectively.

[0833] As one embodiment, the second information block indicates the K parameter sets respectively from multiple candidate parameter sets.

[0834] As an example, the second information block indicates only the portion of each of the K parameter sets that differs from a reference parameter set.

[0835] As a sub-implementation of the above embodiments, the reference parameter set is configured by a higher-layer signaling.

[0836] As a sub-implementation of the above embodiments, the reference parameter set is configured for the first node.

[0837] As a sub-implementation of the above embodiments, the reference parameter set is reported by the first node.

[0838] As an example, the second information block implicitly indicates the set of K parameters.

[0839] As an example, the second information block indicates the K parameter sets by indicating other information.

[0840] As an example, the other information includes, but is not limited to, one or more of the following: channel environment type, mobile speed, subcarrier spacing, carrier frequency, delay spread, Doppler spread, Doppler shift, average delay, and spatial reception parameters.

[0841] As an example, the second information block indicates all parameters in one of the K parameter sets, and indicates the parts in the other parameter sets that are different from the one parameter set.

[0842] As an example, the second information block indicates only a portion of the parameter sets from the K parameter sets.

[0843] As a sub-example of the above embodiment, another part of the parameter set in the K parameter sets is configured to the first node.

[0844] As a sub-example of the above embodiment, another part of the parameter set in the K parameter sets is configured to the first node by higher-level parameters.

[0845] As a sub-implementation of the above embodiment, the second information block indicates each parameter set in the partial parameter set.

[0846] As a sub-implementation of the above embodiment, the second information block indicates each parameter set in the partial parameter set from multiple candidate parameter sets.

[0847] As a sub-implementation of the above embodiments, the second information block only indicates the portion of each parameter set in the partial parameter set that is different from a reference parameter set.

[0848] As an example, the first node determines the set of K parameters.

[0849] As an example, the first node determines the set of K parameters on its own.

[0850] As an example, the first node determines a portion of the parameter set from the K parameter sets on its own, and the first node is instructed to another portion of the parameter set from the K parameter sets.

[0851] As a sub-implementation of the above embodiment, the second information block only indicates a portion of the parameter set.

[0852] As an example, the way the first node determines any one of the K parameter sets is similar to the way the first node determines the first parameter set.

[0853] Example 15

[0854] Example 15 illustrates a schematic diagram of a first time-frequency resource according to an embodiment of this application; as shown in Figure 15. In Example 15, the first channel information pertains to the first time-frequency resource, and the first information block indicates the first time-frequency resource.

[0855] As an example, the K channel information are all related to the first time-frequency resource.

[0856] As one embodiment, a channel information for a time-frequency resource includes: the channel information relates to the time-frequency resource.

[0857] As an example, a channel information for a time-frequency resource includes: the channel information is reported for the time-frequency resource.

[0858] As an example, a channel information includes a time-frequency resource, and the channel information is valid within the time-frequency resource.

[0859] As one embodiment, a channel information for a time-frequency resource includes: channel measurements used to calculate the channel information are obtained from an RS located within the time-frequency resource.

[0860] As an example, a channel information for a time-frequency resource includes: the CSI reference resource of the channel information is the time-frequency resource.

[0861] As an example, the definition of the CSI reference resource is based on 3GPP TS38.214.

[0862] As an example, a channel information for a time-frequency resource includes: the channel information reflects the channel state within the time-frequency resource.

[0863] As an example, the first time-frequency resource includes a continuous time period in the time domain.

[0864] As an example, the first time-frequency resource includes a continuous time period in the time domain, represented as s, ms, or μs.

[0865] As an example, the first time-frequency resource includes a positive integer number of symbols in the time domain.

[0866] As an example, the symbol is an OFDM (Orthogonal Frequency Division Multiplexing) symbol.

[0867] As an example, the symbols are obtained by passing the output of the transform precoding through OFDM symbol generation.

[0868] As an example, the symbol includes a prefix.

[0869] As an example, the first time-frequency resource includes a positive integer number of time slots in the time domain.

[0870] As one embodiment, the first time-frequency resource includes a positive integer number of frames or sub-frames in the time domain.

[0871] As an example, the first time-frequency resource includes a continuous frequency domain resource in the frequency domain.

[0872] As an example, the first time-frequency resource includes a discontinuous frequency domain resource in the frequency domain.

[0873] As one embodiment, the first time-frequency resource includes frequency domain resources represented as Hz, kHz, or MHz in the frequency domain.

[0874] As one embodiment, the first time-frequency resource includes a positive integer number of subcarriers in the frequency domain.

[0875] As an example, the first time-frequency resource includes a positive integer number of RBs (Resource Blocks) in the frequency domain.

[0876] As one embodiment, the first time-frequency resource includes a positive integer number of sub-bands in the frequency domain.

[0877] As an example, the first time-frequency resource includes the W1 sub-bands in the frequency domain.

[0878] As an example, the first time-frequency resource includes the W PMI subbands in the frequency domain.

[0879] As an example, the first time-frequency resource includes the N time slot intervals in the time domain.

[0880] As an example, the per-port per-PRB frequency density of the first RS resource within the frequency domain of the first time-frequency resource is not less than the density configured for the first RS resource.

[0881] As an example, the first node does not expect the per-port per-PRB frequency density of the first RS resource within the frequency domain of the first time-frequency resource to be less than the density configured for the first RS resource.

[0882] As an example, the first node obtains channel measurements for calculating the first channel information based solely on the transmission occasion of the first RS resource in the time domain, which is no later than that of the first time-frequency resource.

[0883] As an example, the K channel information are all related to the first time-frequency resource.

[0884] As an example, the first information block explicitly indicates the first time-frequency resource.

[0885] As an example, the first information block indicates the start time of the first time-frequency resource.

[0886] As an example, the first information block indicates the time domain length of the first time-frequency resource.

[0887] As an example, the first information block indicates the lowest frequency point of the first time-frequency resource.

[0888] As an example, the first information block indicates the frequency domain length of the first time-frequency resource.

[0889] As an example, the first information block implicitly indicates the first time-frequency resource.

[0890] As an example, the first node determines the first time-frequency resource on its own.

[0891] The advantages of the above method include giving the first node sufficient degrees of freedom to determine the time-frequency resources targeted by the first channel information based on the actual channel conditions, thereby optimizing the reporting.

[0892] Generally, how the first node determines the first time-frequency resource is determined by the hardware equipment manufacturer. Below are some non-limiting implementation methods:

[0893] As an example, the first node determines the time domain length of the first time-frequency resource itself.

[0894] As an example, the first node determines the frequency domain length of the first time-frequency resource itself.

[0895] As an example, the first node determines the first time-frequency resource based on the measurement of RS.

[0896] As an example, the first node determines the first time-frequency resource based on instructions from the network side and measurements of the RS.

[0897] As an example, the first node determines the first time-frequency resource by determining the rate of change of the channel in the time domain or frequency domain.

[0898] As an example, the first node selects the first time-frequency resource such that the channel variation within the first time-frequency resource is less than a threshold.

[0899] As an example, the first node inputs the RS measurement result into an inference, and the output of the inference indicates the first time-frequency resource.

[0900] As an example, the first node determines the first time-frequency resource based on its movement speed.

[0901] As an example, the first node determines the first time-frequency resource based on the received beam update or TCI update rate.

[0902] As an example, the first node randomly divides a time-frequency range to obtain multiple time-frequency resources, and the first time-frequency resource is one of the multiple time-frequency resources.

[0903] Example 16

[0904] Example 16 illustrates a schematic diagram of a first configuration information block according to an embodiment of this application; as shown in Figure 16.

[0905] As one embodiment, the first configuration information block is carried by higher-level signaling.

[0906] As an example, the first configuration information block is carried by RRC signaling.

[0907] As an example, the first configuration information block is carried by one or more RRC IE (Information Element).

[0908] As one embodiment, the first configuration information block includes some or all of the information in one or more RRC IEs.

[0909] As one embodiment, the first configuration information block includes some or all of the information in the CSI-ReportConfig IE.

[0910] As one embodiment, the first configuration information block includes some or all of the information in the CSI-MeasConfig IE.

[0911] As one embodiment, the first configuration information block includes some or all of the information in the ServingCellConfig IE.

[0912] As one example, the first configuration information block includes some or all of the information in CellGroupConfig IE.

[0913] As one embodiment, the first configuration information block includes some or all of the information in the CSI-ResourceConfig IE.

[0914] As one embodiment, the first configuration information block includes some or all of the information in the CSI-SSB-ResourceSet IE.

[0915] As one embodiment, the first configuration information block includes some or all of the information in the NZP-CSI-RS-ResourceSet IE.

[0916] As an example, the first configuration information block is transmitted on the PDSCH.

[0917] As an example, the first configuration information block indicates the first RS resource.

[0918] As an example, the first configuration information block indicates that the first RS resource is used for channel measurement.

[0919] As an example, the first configuration information block indicates the identifier in the first RS resource.

[0920] As a sub-implementation of the above embodiments, the identifier in the first RS resource is NZP-CSI-RS-ResourceId or SSB-Index.

[0921] As an example, the first RS resource belongs to an RS resource set, and the first configuration information block indicates the RS resource set.

[0922] As a sub-implementation of the above embodiments, the first configuration information block indicates the first RS resource by indicating the RS resource set.

[0923] As a sub-implementation of the above embodiments, the RS resource set is a CSI-RS resource set or a CSI-SSB (Synchronization Signal Block) resource set.

[0924] As an example, the first configuration information block indicates the configuration information of the first information block.

[0925] As an example, the configuration information of the first information block includes the reporting quantity.

[0926] As an example, the reported quantity is cri-RI-PMI-CQI or cri-RI-LI-PMI-CQI.

[0927] As one embodiment, the configuration information of the first information block includes the physical layer channel carrying the first information block.

[0928] As a sub-implementation of the above embodiments, the physical layer channel carrying the first information block is PUSCH or PUCCH.

[0929] As an example, the configuration information of the first information block includes time-domain behavior, which includes periodic, semi-persistent, and aperiodic behavior.

[0930] As an example, the configuration information of the first information block includes at least one of period and time slot offset.

[0931] As one embodiment, the configuration information of the first information block includes frequency domain resources.

[0932] As an example, the first configuration information block indicates the configuration information of the first RS resource and the first information block.

[0933] As an example, the first configuration information block indicates the first parameter set.

[0934] The advantages of the above methods include facilitating unified optimization on the network side and improving system performance.

[0935] As an example, the first configuration information block indicates that the first parameter set is used to generate channel information for layer l.

[0936] As an example, the first configuration information block indicates at least some of the parameters in the first parameter set.

[0937] As an example, the first configuration information block indicates only a portion of the parameters in the first parameter set.

[0938] Example 17

[0939] Example 17 illustrates a schematic diagram of a first information block belonging to a first dataset according to an embodiment of this application; as shown in Figure 17.

[0940] As an example, the first dataset is used for training or retraining.

[0941] In a preferred embodiment, the first dataset is used for training or retraining a model.

[0942] As an example, the first dataset includes a training dataset.

[0943] As an example, the first dataset belongs to a training dataset.

[0944] As an example, the first dataset is a training dataset.

[0945] As an example, the training dataset for the first model includes the first dataset.

[0946] As an example, the first dataset was used for performance monitoring.

[0947] As an example, the first dataset was used for performance monitoring of a model.

[0948] As an example, the performance testing dataset for the first model includes the first dataset.

[0949] As an example, the first dataset was used for inference.

[0950] As an example, the first dataset was used for inference of a model.

[0951] As an example, the first dataset includes an inference dataset.

[0952] As an example, the first dataset belongs to an inference dataset.

[0953] As an example, the first dataset is an inference dataset.

[0954] As an example, the model is an AI model or an ML model.

[0955] As an example, the dataset to which the first information block belongs is configured by a higher-level signaling layer.

[0956] As an example, the dataset to which the first information block belongs is configured by RRC signaling.

[0957] As an example, the dataset to which the first information block belongs is indicated to the first node by the serving cell of the first node.

[0958] As an example, the dataset to which the first information block belongs is indicated to the first node by the core network device.

[0959] As an example, the dataset to which the first information block belongs is indicated to the first node by the OTT server.

[0960] As an example, the dataset to which the first information block belongs is indicated to the first node by OAM.

[0961] As an example, the dataset to which the first information block belongs is indicated to the first node by the NAS device.

[0962] As an example, the dataset to which the first information block belongs is reported by the first node.

[0963] As an example, the first information block indicates that the dataset to which it belongs is the first dataset.

[0964] As an example, the first configuration information block indicates that the dataset to which the first information block belongs is the first dataset.

[0965] In a preferred embodiment, the first dataset is associated with the first identifier.

[0966] As one embodiment, the first information block indicates a first identifier, and the first dataset is associated with the first identifier.

[0967] As an example, the first configuration information block indicates a first identifier, and the first dataset is associated with the first identifier.

[0968] As one embodiment, associating the first dataset with the first identifier includes the first dataset being identified by the first identifier.

[0969] As one embodiment, the association of the first dataset with the first identifier includes that the first dataset is a training dataset of a model, and the model is identified by the first identifier.

[0970] As one embodiment, the association of the first dataset with the first identifier includes that the first dataset is a training dataset of a model, and the training or retraining of the model is identified by the first identifier.

[0971] As an example, the association of the first dataset with the first identifier includes that the first dataset is a training dataset of a model, and the inference of the model is identified by the first identifier.

[0972] As an example, the association of the first dataset with the first identifier includes that the first dataset is a training dataset of a model, and the AI ​​function or AI entity that performs the training or retraining of the model is identified by the first identifier.

[0973] As an example, the association of the first dataset with the first identifier includes that the first dataset is a training dataset of a model, and the AI ​​entity or AI function that performs inference of the model is identified by the first identifier.

[0974] As an example, the association of the first dataset with the first identifier includes that the first dataset is a training dataset of a model, and the function implemented by the model is identified by the first identifier.

[0975] As one embodiment, the association of the first dataset with the first identifier includes the first dataset being a training dataset of a model, wherein the inference output of the model indicates one or more RS resources associated with the first identifier.

[0976] As an example, the association of the first dataset with the first identifier includes that the first dataset is an inference dataset or performance monitoring dataset of a model, wherein the model is identified by the first identifier.

[0977] As an example, the association of the first dataset with the first identifier includes that the first dataset is an inference dataset or a performance monitoring dataset of a model, wherein the inference or performance monitoring of the model is identified by the first identifier.

[0978] As an example, the association of the first dataset with the first identifier includes that the first dataset is an inference dataset or performance monitoring dataset of a model, and the AI ​​function or AI entity that performs the inference or performance monitoring of the model is identified by the first identifier.

[0979] As an example, the association of the first dataset with the first identifier includes that the first dataset is an inference dataset or performance monitoring dataset of a model, and the function implemented by the model is identified by the first identifier.

[0980] As one embodiment, the association of the first dataset with the first identifier includes the first dataset being an inference dataset or performance monitoring dataset of a model, wherein the output of the inference of the model indicates that it is associated with one or more RS resources of the first identifier.

[0981] Example 18

[0982] Example 18 illustrates a schematic diagram of a first information block transmitted on a first radio bearer according to an embodiment of this application; as shown in Figure 18.

[0983] As one example, the first wireless bearer is dedicated to AI or ML.

[0984] As an example, the first wireless bearer is dedicated to an AI model or an ML model.

[0985] As an example, the first radio bearer is an SRB (Signalling Radio Bearer) that is not supported by 3GPP R19 or earlier versions, such as SRB6 or SRB7.

[0986] As an example, the first radio bearer is a type of radio bearer used for transmitting unicast data, other than DRB (Data Radio Bearer) and SRB.

[0987] As a sub-implementation of the above embodiments, the name of the first wireless bearer includes RB, and the name of the first wireless bearer includes I, AI, ML, or LLM.

[0988] As one embodiment, the first radio bearer includes a higher-level entity that is above the PDCP (Packet Data Convergence Protocol) and belongs to the Radio Access Network RAN ​​(i.e., not to the core network).

[0989] As a sub-implementation of the above embodiments, the first radio bearer includes the higher-layer entity, the PDCP entity, and the RLC (Radio Link Control) entity.

[0990] Example 19

[0991] Example 19 illustrates a schematic diagram of a first channel information and a first model associated with a first identifier according to an embodiment of this application; as shown in Figure 19.

[0992] As an example, each of the K channel information is associated with the first identifier.

[0993] As one example, the first channel quality is associated with the first identifier.

[0994] As an example, the first information block is associated with the first identifier.

[0995] As an example, the first dataset is associated with the first identifier.

[0996] As an example, the first RS resource is associated with the first identifier.

[0997] As one embodiment, the first information block indicates the first identifier.

[0998] As one embodiment, the first configuration information block indicates the first identifier.

[0999] As an example, the first identifier is a non-negative integer.

[1000] As an example, the first identifier is a string.

[1001] As an example, the first identifier indicates an association between two or more RS resources.

[1002] As a sub-implementation of the above embodiments, the association includes having the same or similar characteristics.

[1003] As a sub-implementation of the above embodiments, the association includes quasi-co-located.

[1004] As a sub-implementation of the above embodiments, the association includes quasi-co-addressing and the corresponding quasi-co-addressing type includes TypeD.

[1005] As a sub-example of the above embodiments, the association includes training datasets used to generate the same model.

[1006] As a sub-example of the above embodiments, the association includes inference datasets used to generate the same model.

[1007] As a sub-example of the above embodiments, the association includes training datasets or inference datasets used to generate the same model.

[1008] As an example, the features include one or more of delay spread, Doppler spread, Doppler shift, average delay, or spatial reception parameters.

[1009] As an example, the first identifier indicates the association between a dataset and a model.

[1010] As a sub-example of the above embodiments, the association includes that the dataset belongs to the training dataset of the model.

[1011] As a sub-example of the above embodiments, the association includes that the dataset belongs to the inference dataset of the model.

[1012] As an example, the first identifier indicates the association between an RS resource or a collection of RS resources and a model.

[1013] As a sub-example of the above embodiments, the association includes the use of the RS resource or RS resource set to generate the training dataset of the model.

[1014] As a sub-example of the above embodiments, the association includes the use of the RS resource or RS resource set to generate the inference dataset of the model.

[1015] As a sub-example of the above embodiments, the association includes the output of the inference of the model indicating one or more RS resources in the RS resource or RS resource set.

[1016] As one embodiment, associating a channel information with a first identifier includes associating the dataset to which the channel information belongs with the first identifier.

[1017] As one embodiment, a channel information associated with a first identifier includes the channel information being used for training or retraining a model, the model being associated with the first identifier.

[1018] As one embodiment, a channel information associated with a first identifier includes the channel information being used for inference of a model, the model being associated with the first identifier.

[1019] As an example, a model associated with the first identifier includes the model being identified by the first identifier.

[1020] As an example, a model associated with the first identifier includes the inference of the model being identified by the first identifier.

[1021] As an example, a model associated with the first identifier includes an AI function or AI entity that performs training of the model being identified by the first identifier.

[1022] As an example, a model associated with the first identifier includes an AI function or AI entity that performs inference for the model being identified by the first identifier.

[1023] As an example, a model associated with the first identifier includes the training of the model being identified by the first identifier.

[1024] As an example, associating a model with the first identifier includes having the training dataset of the model identified by the first identifier.

[1025] As an example, a model being associated with the first identifier includes the inference dataset or performance monitoring dataset of the model being identified by the first identifier.

[1026] As an example, a model associated with the first identifier includes the functionality implemented by the model being identified by the first identifier.

[1027] As an example, a model associated with the first identifier includes the output of the inference of the model indicating one or more RS resources associated with the first identifier.

[1028] As an example, the model refers to an AI model or an ML model.

[1029] As one embodiment, a channel information associated with a first identifier includes channel measurements used to generate the channel information being obtained based on one or more RS resources associated with the first identifier.

[1030] As one embodiment, an RS resource associated with the first identifier includes an RS resource configured with the first identifier.

[1031] As one embodiment, associating an RS resource with the first identifier includes the configuration IE of the RS resource indicating the first identifier.

[1032] As an example, the configuration IE for an RS resource is one of NZP-CSI-RS-Resource IE, CSI-ResourceConfig IE, NZP-CSI-RS-ResourceSet IE, or CSI-SSB-ResourceSet IE.

[1033] As an example, an RS resource associated with the first identifier includes the fact that the RS resource and another RS ​​resource associated with the first identifier are quasi-co-located.

[1034] As an example, an RS resource associated with the first identifier includes an RS resource and another RS ​​resource associated with the first identifier having the same or similar characteristics.

[1035] As an example, an RS resource associated with the first identifier includes the fact that the RS resource and another RS ​​resource associated with the first identifier are used to generate the training dataset for the same model.

[1036] As an example, an RS resource associated with the first identifier includes the fact that the RS resource and another RS ​​resource associated with the first identifier are used to generate the same model's inference dataset.

[1037] As an example, an RS resource associated with the first identifier includes the RS resource being used to generate a training dataset for a model, and another RS ​​resource associated with the first identifier being used to generate an inference dataset for the model.

[1038] As one embodiment, an RS resource associated with the first identifier includes the RS resource set to which the RS resource belongs being associated with the first identifier.

[1039] As an example, an RS resource is a CSI-RS resource and the RS resource set to which the RS resource belongs is a CSI-RS resource set, or an RS resource is an SSB / PBCH block resource and the RS resource set to which the RS resource belongs is a CSI-SSB resource set.

[1040] As one embodiment, an RS resource set associated with the first identifier includes an RS resource set configured with the first identifier.

[1041] As one embodiment, an RS resource set associated with the first identifier includes a configuration IE of the RS resource set indicating the first identifier.

[1042] As an example, the configuration IE for an RS resource set is one of NZP-CSI-RS-ResourceSet IE, CSI-ResourceConfig IE, or CSI-SSB-ResourceSet IE.

[1043] As an example, an RS resource set associated with the first identifier includes any RS resource in the RS resource set and any RS resource in another RS ​​resource set associated with the first identifier being quasi-co-located.

[1044] As an example, an RS resource set associated with the first identifier includes any RS resource in the RS resource set having the same or similar characteristics as any RS resource in another RS ​​resource set associated with the first identifier.

[1045] As one example, an RS resource set associated with the first identifier includes the fact that the RS resource set and another RS ​​resource set associated with the first identifier are used to generate the training dataset for the same model.

[1046] As an example, an RS resource set associated with the first identifier includes the fact that the RS resource set and another RS ​​resource set associated with the first identifier are used to generate an inference dataset for the same model.

[1047] As one embodiment, an RS resource set associated with the first identifier includes the RS resource set being used to generate a training dataset for a model, and another RS ​​resource set associated with the first identifier being used to generate an inference dataset for the model.

[1048] As an example, an RS resource set associated with the first identifier includes an RS resource set used to generate a training dataset or inference dataset for a model, wherein the inference output of the model indicates one or more RS resources in another RS ​​resource set associated with the first identifier.

[1049] In a preferred embodiment, the first model is an AI model or an ML model.

[1050] As one example, the AI ​​includes ML (Machine Learning).

[1051] As an example, the AI ​​includes AI and ML.

[1052] As one example, the AI ​​includes AI or ML.

[1053] In a preferred embodiment, the first model is obtained through training.

[1054] As an example, the training of the first model is performed by the serving cell of the first node.

[1055] As an example, the training of the first model is performed by the core network.

[1056] As an example, the training of the first model is performed by the MDA (Management Data Analytics Function).

[1057] As an example, the training of the first model is performed by NWDAF (Network Data Analytics Function).

[1058] As an example, the training of the first model is performed by the MDAS (Management Data Analytics Service) producer.

[1059] As an example, the training of the first model is performed by the MnS (Management Service) producer.

[1060] As an example, the training of the first model is performed by an AI entity or an AI training function.

[1061] As an example, the inference of the first model is performed by an AI entity or an AI inference function.

[1062] As an example, the first model is based on artificial intelligence or machine learning.

[1063] As an example, the first model is based on a neural network.

[1064] As an example, the first model was used to generate CSI (Channel State Information).

[1065] As an example, the first model is used for beam management or beam prediction.

[1066] As an example, the first model was used for CSI compression.

[1067] As an example, the first model was used for localization.

[1068] As an example, the output of the first model includes CSI or compressed CSI.

[1069] As an example, the output of the first model includes predicted beam information.

[1070] As an example, the beam information includes at least one of CRI, SSBRI, and RSRP.

[1071] As an example, the first model requires deployment.

[1072] As an example, the first model is obtained by loading.

[1073] As an example, the first dataset was used to train the first model.

[1074] As an example, the training dataset for the first model includes the first dataset.

[1075] As an example, the first dataset was used for performance monitoring of the first model.

[1076] As an example, the first dataset was used for inference of the first model.

[1077] As an example, the first model is identified by the first identifier.

[1078] As an example, the reasoning of the first model is identified by the first identifier.

[1079] As an example, the AI ​​function or AI entity that performs the training of the first model is identified by the first identifier.

[1080] As an example, the AI ​​function or AI entity that performs the reasoning of the first model is identified by the first identifier.

[1081] As an example, the training of the first model is identified by the first identifier.

[1082] As an example, the training dataset of the first model is identified by the first identifier.

[1083] As an example, the inference dataset of the first model is identified by the first identifier.

[1084] As an example, the performance monitoring dataset of the first model is identified by the first identifier.

[1085] As an example, the output of the first model indicates that it is associated with one or more RS resources of the first identifier.

[1086] As an example, both the first channel information and the first model are associated with the first identifier, which indicates that the first channel information belongs to the training dataset of the first model.

[1087] As an example, both the first channel information and the first model are associated with the first identifier, which indicates that the first channel information belongs to the inference dataset or performance monitoring dataset of the first model.

[1088] As an example, both the first channel information and the first model are associated with the first identifier, which indicates that the RS resources used to obtain channel measurements for calculating the first channel information are used to generate the training dataset or inference dataset of the first model.

[1089] Example 20

[1090] Example 20 illustrates a schematic diagram of deploying a first model according to an embodiment of this application, as shown in Figure 20; in Example 20, the first node requests to load the first model from the first producer and obtains the first model from the first producer.

[1091] As an example, the first model needs to be deployed.

[1092] As an example, the deployment includes obtaining the first model.

[1093] As one example, the deployment includes obtaining an AI entity.

[1094] As one example, the deployment includes obtaining an AI entity that performs inference for the first model.

[1095] As one example, the deployment includes acquiring an AI function.

[1096] As one example, the deployment includes acquiring AI capabilities to perform inference for the first model.

[1097] As one example, the deployment includes loading the first model.

[1098] As one example, the deployment includes making a request to load the first model.

[1099] As an example, the request in Figure 20 is a request made by the first node to load the first model.

[1100] As an example, the response in Figure 20 is a response to the request made by the first node to load the first model.

[1101] As an example, the first node obtains the first model through the response shown in Figure 20.

[1102] As an example, the first producer provides the first model to the first node via the response shown in Figure 20.

[1103] As an example, the deployment is accomplished by an AI function.

[1104] As an example, the deployment is accomplished by AI functionality deployed on the first node.

[1105] As an example, the deployment is accomplished by an AI deployment function.

[1106] As an example, the deployment is accomplished by the AI ​​deployment function deployed on the first node.

[1107] As an example, the deployment is accomplished by AI inference functionality.

[1108] As an example, the deployment is accomplished by an AI inference function deployed on the first node.

[1109] As an example, the deployment is performed by an AI entity.

[1110] As an example, the deployment is performed by an AI entity deployed on the first node.

[1111] As an example, the deployment is performed by an AI entity with a deployment function.

[1112] As an example, the deployment is performed by an AI entity with deployment capabilities deployed on the first node.

[1113] As an example, the deployment is performed by an AI entity with an inference function.

[1114] As an example, the first producer generates and provides an AI model.

[1115] As an example, the first producer generates and provides AI entities.

[1116] As an example, the first producer generates and provides AI functionality.

[1117] As an example, the first producer is the producer of the first model.

[1118] As an example, the first producer is the producer that trains the first model.

[1119] As one example, the first producer includes an AI entity producer.

[1120] As one example, the first producer includes an AI function producer.

[1121] As one example, the first producer includes an AI deployment producer.

[1122] As one example, the first producer includes an AI training producer.

[1123] As one example, the first producer includes an AI inference producer.

[1124] As an example, the first producer includes the producer of the AI ​​model training.

[1125] As one example, the first producer includes an MnS (Management Service) producer.

[1126] As an example, the first producer is the serving cell of the first node.

[1127] As an example, the first producer is the maintenance base station of the serving cell of the first node.

[1128] As an example, the first producer is a core network device.

[1129] As an example, the first producer is a NAS device.

[1130] As an example, the first producer is an OTT server.

[1131] As an example, the training of the first model is performed by the first producer.

[1132] Example 21

[1133] Example 21 illustrates a schematic diagram of an artificial intelligence or machine learning-based processing system according to an embodiment of this application, as shown in Figure 21. In Example 21, the second processor sends a second dataset to the third processor and a third dataset to the fourth processor; the third processor generates a target first-class parameter set based on the second dataset, and sends the generated target first-class parameter set to the fourth processor; the fourth processor processes the third dataset using the target first-class parameter set to obtain a first-class output, and sends the first-class output to the fifth processor. In Figure 21, the first-class feedback and the second-class feedback are optional; the third processor includes ML training functionality; the fourth processor includes ML inference functionality.

[1134] As one embodiment, the fifth processor includes ML testing functionality.

[1135] As one embodiment, the fifth processor includes performance monitoring / evaluation of the ML model.

[1136] As one embodiment, the fifth processor includes the inverse operation of the fourth processor.

[1137] As an example, the fourth processor sends a first type of feedback to the third processor. The first type of feedback is used to trigger the recalculation or update of the target first type of parameter set, that is, to trigger ML initial training or ML retraining.

[1138] As one embodiment, the fifth processor sends a second type of feedback to the second processor, the second type of feedback being used to generate the second dataset or the third dataset, or the second type of feedback being used to trigger the sending of the second dataset or the third dataset.

[1139] As one embodiment, the second processor generates the second dataset and the third dataset based on the measurement of the reference signal.

[1140] As one embodiment, the fourth processor is located at the first node.

[1141] As one embodiment, the fifth processor is located at the first node or the second node.

[1142] As an example, the fourth processor performs the inference of the first model.

[1143] As an example, the fifth processor performs the inverse operation of the reasoning of the first model.

[1144] As an example, the third dataset includes measurements for RS.

[1145] As an example, the third dataset includes the reception of PDSCH.

[1146] As an example, the second dataset includes training data.

[1147] As an example, the second dataset includes the first dataset.

[1148] As an example, the third processor is used to train an ML model, and the trained model is described by the target first class of parameter sets.

[1149] As one embodiment, the third processor is located at the second node.

[1150] The above embodiments support joint training and optimize system performance.

[1151] As one embodiment, the third processor is located in the core network.

[1152] The above embodiments support network-wide joint training, further optimizing system performance.

[1153] As an example, the third dataset includes inference data.

[1154] As an example, the fourth processor constructs a model based on the target first type of parameter group, and then inputs the third dataset into the constructed model to obtain the first type of output.

[1155] As an example, the fourth processor compares the real data with the first type of output, and the resulting error is used to generate the first type of feedback.

[1156] As an example, the fourth processor generates the first type of feedback through performance monitoring.

[1157] As an example, the first type of feedback is used to reflect the performance of the trained model; when the performance of the trained model fails to meet the requirements, the third processing opportunity recalculates the target first type of parameter set.

[1158] As an example, the fifth processor compares the real data with the first type of output, and the resulting error is used to generate the second type of feedback.

[1159] As an example, the fifth processor generates the second type of feedback through performance monitoring.

[1160] As an example, the second type of feedback is used to reflect the performance of the trained model; when the performance of the trained model fails to meet the requirements, the second processor sends the second dataset to trigger or assist the third processor in recalculating the target first type of parameter set.

[1161] As an example, when the error is too large or the update has not been performed for too long, the performance of the trained model is considered to be unsatisfactory.

[1162] As an example, the target first type of parameter group includes one or more of the following: convolution kernel size, number of convolution layers, convolution stride, pooling kernel size, pooling kernel stride, pooling function, activation function, or number of feature maps.

[1163] As an example, the target first type of parameter group includes one or more of the following: convolution kernel, pooling kernel, pooling function, activation function, parameters of pooling function, or parameters of activation function.

[1164] As one example, the ML includes AI.

[1165] As an example, the ML includes ML and AI.

[1166] Example 22

[1167] Example 22 illustrates a schematic diagram based on artificial intelligence or machine learning according to an embodiment of this application; as shown in Figure 22. Figure 22 includes a first operation, a second operation, a third operation, a fourth operation, and a fifth operation. In Example 22, the first and second operations belong to a first stage, the third operation belongs to a second stage, the fourth operation belongs to a third stage, and the fifth operation belongs to a fourth stage. In Figure 22, the lines with arrows indicate the sequence of processes.

[1168] As an example, the first operation includes ML training, the second operation includes ML testing, the third operation includes ML emulation, the fourth operation includes ML entity loading, and the fifth operation includes AI inference.

[1169] As one embodiment, the first stage includes a training phase, the second stage includes an emulation phase, the third stage includes a deployment phase, and the fourth stage includes an emulation phase.

[1170] As an example, the first stage includes ML model training.

[1171] As an example, the first stage includes ML model training and ML testing.

[1172] As an example, the ML model training includes initial training and re-training of one or a group of ML models.

[1173] As an example, the training of the ML model depends on training data.

[1174] As an example, the ML model training includes ML entity validation.

[1175] As an example, the ML entity verification is used to evaluate the performance of the ML entity.

[1176] As an example, the ML entity verification depends on verification data.

[1177] As an example, if the results of ML entity verification do not meet expectations, the ML model will be retrained.

[1178] As an example, the ML testing includes testing the validated ML entities to estimate the performance of the trained ML model.

[1179] As an example, if the ML test results meet expectations, the ML entity proceeds to the next stage; otherwise, the ML model will be retrained.

[1180] As an example, the ML test relies on test data.

[1181] As one embodiment, the second stage includes ML simulation, which performs inference of ML entities in a simulation environment.

[1182] As an example, the ML simulation estimates the performance of ML entity reasoning in a simulation environment before using ML entities.

[1183] As one embodiment, the second stage is optional.

[1184] As an example, the third stage includes ML entity loading, which is to obtain trained ML entities to obtain the desired AI inference capabilities.

[1185] As an example, the third stage is optional.

[1186] As an example, the third stage is no longer needed when the training and inference functions are co-located.

[1187] As an example, the fourth stage includes AI inference.

[1188] As one example, the ML includes AI.

[1189] As one example, the AI ​​includes ML.

[1190] Example 23

[1191] Example 23 illustrates a schematic diagram of AI function deployment according to one embodiment of this application; as shown in Figure 23.

[1192] In Example 23, the AI ​​training function of the RAN (Radio Access Network) domain is located in the 3GPP RAN domain-specific management function, while the AI ​​inference function is located in the UE.

[1193] In Example 23, RAN domain-specific management functions provide AI training function management capabilities and AI inference function management capabilities.

[1194] Example 24

[1195] Example 24 illustrates a schematic diagram of AI function deployment according to one embodiment of this application; as shown in Figure 24.

[1196] In Example 24, the AI ​​training function is a RAN domain-specific management function, while the AI ​​inference function is located locally on the UE.

[1197] In Example 24, the management capability of the AI ​​training function is provided by the RAN domain-specific management function, while the management capability of the AI ​​inference function is provided locally by the UE.

[1198] In Figure 24, MnF refers to Management Function.

[1199] Example 25

[1200] Example 25 illustrates a structural block diagram of a processing apparatus for a first node according to an embodiment of this application; as shown in Figure 25. In Figure 25, the processing apparatus 2500 in the first node includes a receiver 2501 and a first transmitter 2502.

[1201] In embodiment 25, the first receiver 2501 measures on the first RS resource, and the first transmitter 2502 transmits the first information block.

[1202] In embodiment 25, the first information block includes first channel information; the first channel information depends on measurements on the first RS resource; the first channel information is for layer l, and a first parameter set is used to generate the first channel information, the first parameter set depending on l.

[1203] As one embodiment, the first channel information includes some or all of the information in the codebook-based PMI, and the first parameter set includes the parameters of the codebook.

[1204] As one example, the number of bits included in the first channel information depends on the first parameter set.

[1205] As an example, the layer refers to the MIMO layer.

[1206] As an example, the layer refers to the transmission layer.

[1207] As one embodiment, the first transmitter 2502 transmits a second information block; wherein the second information block indicates the first parameter set.

[1208] As an example, the first information block includes K channel information, where K is a positive integer greater than 1, the first channel information is one of the K channel information, and the K channel information are respectively for K layers; K parameter sets are respectively used to generate the K channel information, and at least two parameter sets in the K parameter sets are different.

[1209] As a sub-implementation of the embodiment, the first information block indicates the K.

[1210] As a sub-implementation of the embodiment, any one of the K channel information depends on the measurement on the first RS resource.

[1211] As an example, the first information block includes a first channel quality, which is calculated based on the K channel information.

[1212] As a sub-implementation of the embodiment, the first channel quality is CQI.

[1213] As one embodiment, the first transmitter 2502 transmits a second information block; wherein the second information block indicates all or part of the parameter sets in the K parameter sets.

[1214] As one embodiment, the first channel information is for a first time-frequency resource, and the first information block indicates the first time-frequency resource.

[1215] As one embodiment, the first receiver 2501 receives a first configuration information block; wherein the first configuration information block indicates at least one of the configuration information of the first RS resource and the first information block.

[1216] As an example, the first information block belongs to the first dataset.

[1217] As a sub-implementation of the embodiment, the first dataset is used for training or retraining an AI model or ML model.

[1218] As one embodiment, the first information block is transmitted on a first radio bearer, which is a new radio bearer other than the radio bearers supported by 3GPP R19.

[1219] As one embodiment, the first channel information is associated with a first identifier, and the first model is associated with the first identifier.

[1220] As a sub-implementation of the embodiment, the first model is an AI model or an ML model.

[1221] As a sub-implementation of the embodiment, the first model is obtained through training.

[1222] As an example, at least one of the first receiver 2501 and the first transmitter 2502 deploys the first model.

[1223] As an example, at least one of the first receiver 2501 and the first transmitter 2502 performs the inference of the first model.

[1224] As one embodiment, the first node includes a terminal.

[1225] As one embodiment, the terminal includes the first node.

[1226] As one embodiment, the first node includes a user equipment.

[1227] As one embodiment, the first node includes a relay node device.

[1228] As an example, the first receiver 2501 includes at least one of the following in embodiment 4: {antenna 452, receiver 454, receiver processor 456, multi-antenna receiver processor 458, controller / processor 459, memory 460, data source 467}.

[1229] As one embodiment, the first transmitter 2502 includes at least one of the following in embodiment 4: {antenna 452, transmitter 454, transmission processor 468, multi-antenna transmission processor 457, controller / processor 459, memory 460, data source 467}.

[1230] Example 26

[1231] Example 26 illustrates a structural block diagram of a processing apparatus for a second node according to an embodiment of the present application; as shown in Figure 26. In Figure 26, the processing apparatus 2600 in the second node includes a first processor 2601.

[1232] In embodiment 26, the first processor 2601 receives the first information block.

[1233] In embodiment 26, the first information block includes first channel information; the first channel information depends on measurements on a first RS resource; the first channel information is for layer l, and a first parameter set is used to generate the first channel information, the first parameter set depending on l.

[1234] As one embodiment, the first channel information includes some or all of the information in the codebook-based PMI, and the first parameter set includes the parameters of the codebook.

[1235] As one example, the number of bits included in the first channel information depends on the first parameter set.

[1236] As an example, the layer refers to the MIMO layer.

[1237] As an example, the layer refers to the transmission layer.

[1238] As one embodiment, the first processor 2601 receives a second information block; wherein the second information block indicates the first parameter set.

[1239] As an example, the first information block includes K channel information, where K is a positive integer greater than 1, the first channel information is one of the K channel information, and the K channel information are respectively for K layers; K parameter sets are respectively used to generate the K channel information, and at least two parameter sets in the K parameter sets are different.

[1240] As a sub-implementation of the embodiment, the first information block indicates the K.

[1241] As a sub-implementation of the embodiment, any one of the K channel information depends on the measurement on the first RS resource.

[1242] As an example, the first information block includes a first channel quality, which is calculated based on the K channel information.

[1243] As a sub-implementation of the embodiment, the first channel quality is CQI.

[1244] As one embodiment, the first processor 2601 receives a second information block; wherein the second information block indicates all or part of the parameter sets in the K parameter sets.

[1245] As one embodiment, the first channel information is for a first time-frequency resource, and the first information block indicates the first time-frequency resource.

[1246] As one embodiment, the first processor 2601 sends a first configuration information block; wherein the first configuration information block indicates at least one of the configuration information of the first RS resource and the first information block.

[1247] As an example, the first information block belongs to the first dataset.

[1248] As a sub-implementation of the embodiment, the first dataset is used for training or retraining an AI model or ML model.

[1249] As one embodiment, the first information block is transmitted on a first radio bearer, which is a new radio bearer other than the radio bearers supported by 3GPP R19.

[1250] As one embodiment, the first channel information is associated with a first identifier, and the first model is associated with the first identifier.

[1251] As a sub-implementation of the embodiment, the first model is an AI model or an ML model.

[1252] As a sub-implementation of the embodiment, the first model is obtained through training.

[1253] As one embodiment, the second node includes a base station.

[1254] As one embodiment, the base station includes the second node.

[1255] As one embodiment, the second node includes a base station device.

[1256] As one embodiment, the second node includes a relay node device.

[1257] As one embodiment, the second node includes the sustaining base station of the serving cell of the first node.

[1258] As one embodiment, the second node includes an OTT (Over-The-Top) server.

[1259] As an example, the second node provides OAM (Operation Administration and Maintenance).

[1260] As one embodiment, the second node includes a NAS (Network Access Server).

[1261] As one embodiment, the second node includes a NAS device.

[1262] As one example, the second node provides network access services.

[1263] As one embodiment, the second node includes core network equipment.

[1264] As one embodiment, the second node includes base station equipment and core network equipment.

[1265] As one embodiment, the second node includes a base station device and a NAS device.

[1266] As one embodiment, the second node includes an MDA function producer.

[1267] As one embodiment, the second node includes an NWDAF producer.

[1268] As one example, the second node includes an MDAS producer.

[1269] As one embodiment, the second node includes an MnS producer.

[1270] As an example, the first processor 2601 includes at least one of the following in embodiment 4: {antenna 420, receiver / transmitter 418, receiving processor 470, transmitting processor 416, multi-antenna receiving processor 472, multi-antenna transmitting processor 471, controller / processor 475, memory 476}.

[1271] Those skilled in the art will understand that all or part of the steps in the above methods can be implemented by a program instructing related hardware, and the program can be stored in a computer-readable storage medium, such as a read-only memory, hard disk, or optical disk. Optionally, all or part of the steps in the above embodiments can also be implemented using one or more integrated circuits. Accordingly, each module unit in the above embodiments can be implemented in hardware or in the form of software functional modules. This application is not limited to any specific combination of software and hardware. The user equipment, terminal, and UE in this application include, but are not limited to, drones, communication modules on drones, remote-controlled aircraft, aircraft, small aircraft, mobile phones, tablets, laptops, vehicle-mounted communication equipment, vehicles, RSUs, wireless sensors, internet access cards, IoT terminals, RFID terminals, NB-IoT terminals, MTC (Machine Type Communication) terminals, eMTC (enhanced MTC) terminals, data cards, internet access cards, vehicle-mounted communication equipment, low-cost mobile phones, low-cost tablets, and other wireless communication devices. The base stations or system equipment in this application include, but are not limited to, macrocell base stations, microcell base stations, small cell base stations, home base stations, relay base stations, eNBs, gNBs, TRPs (Transmitter Receiver Points), GNSS, relay satellites, satellite base stations, airborne base stations, RSUs (Road Side Units), drones, and testing equipment, such as transceivers or signaling testers that simulate some functions of a base station, and other wireless communication equipment.

[1272] Those skilled in the art will understand that the present invention can be practiced in other specified forms without departing from its core or essential characteristics. Therefore, the embodiments disclosed herein should in any way be considered descriptive rather than restrictive. The scope of the invention is defined by the appended claims rather than the foregoing description, and all modifications within their equivalent meaning and scope are considered to be included therein.

Claims

1. A method used in a terminal for wireless communication, characterized in that, include: Measured on the first RS resource; Send a first information block, the first information block including first channel information; Wherein, the first channel information depends on the measurement on the first RS resource; the first channel information is for layer l, and a first parameter set is used to generate the first channel information, the first parameter set depending on l.

2. The method according to claim 1, characterized in that, include: Send the second information block; The second information block indicates the first parameter set.

3. The method according to claim 1 or 2, characterized in that, The first information block includes K channel information, where K is a positive integer greater than 1. The first channel information is one of the K channel information. The K channel information are respectively for K layers. K parameter sets are used to generate the K channel information. At least two parameter sets in the K parameter sets are different.

4. The method according to claim 3, characterized in that, The first information block includes a first channel quality, which is calculated based on the K channel information.

5. The method according to claim 3 or 4, characterized in that, include: Send the second information block; The second information block indicates all or part of the parameter sets in the K parameter sets.

6. The method according to any one of claims 1 to 5, characterized in that, The first channel information is for the first time-frequency resource, and the first information block indicates the first time-frequency resource.

7. The method according to any one of claims 1 to 6, characterized in that, include: Receive the first configuration information block; The first configuration information block indicates at least one of the configuration information of the first RS resource and the first information block.

8. The method according to any one of claims 1 to 7, characterized in that, The first information block belongs to the first dataset.

9. The method according to any one of claims 1 to 8, characterized in that, The first information block is transmitted on a first radio bearer, which is a new radio bearer other than the radio bearers supported by 3GPP R19.

10. The method according to any one of claims 1 to 9, characterized in that, The first channel information is associated with the first identifier, and the first model is associated with the first identifier.

11. A terminal, characterized in that, The terminal includes: one or more processors and memory; The memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the terminal to perform the method as described in any one of claims 1-10.

12. A method used in a base station for wireless communication, characterized in that, include: Receive a first information block, the first information block including first channel information; Wherein, the first channel information depends on measurements on the first RS resource; the first channel information is for layer l, and a first parameter set is used to generate the first channel information, the first parameter set depending on l.

13. The method according to claim 12, characterized in that, include: Receive the second information block; The second information block indicates the first parameter set.

14. The method according to claim 12 or 13, characterized in that, The first information block includes K channel information, where K is a positive integer greater than 1. The first channel information is one of the K channel information. The K channel information are respectively for K layers. K parameter sets are used to generate the K channel information. At least two parameter sets in the K parameter sets are different.

15. The method according to claim 14, characterized in that, The first information block includes a first channel quality, which is calculated based on the K channel information.

16. The method according to claim 14 or 15, characterized in that, include: Receive the second information block; The second information block indicates all or part of the parameter sets in the K parameter sets.

17. The method according to any one of claims 12 to 16, characterized in that, The first channel information is for the first time-frequency resource, and the first information block indicates the first time-frequency resource.

18. The method according to any one of claims 12 to 17, characterized in that, include: Send the first configuration information block; The first configuration information block indicates at least one of the configuration information of the first RS resource and the first information block.

19. The method according to any one of claims 12 to 18, characterized in that, The first information block belongs to the first dataset.

20. The method according to any one of claims 12 to 19, characterized in that, The first information block is transmitted on a first radio bearer, which is a new radio bearer other than the radio bearers supported by 3GPP R19.

21. The method according to any one of claims 12 to 20, characterized in that, The first channel information is associated with the first identifier, and the first model is associated with the first identifier.

22. A base station, characterized in that, The base station includes: one or more processors and a memory; The memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the base station to perform the method as described in any one of claims 12-21.

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