Data collection methods, terminal devices and network devices

Abstract

The present application relates to data collection methods, terminal devices, network devices, a chip, a computer-readable storage medium, a computer program product, a computer program and a communication system. A method comprises: a terminal device sends first reporting information to a network device, wherein the first reporting information comprises data set information; the data set information comprises N groups of labels, each of the N groups of labels comprising first channel information of K time slots; the first channel information comprises feature information that is obtained on the basis of a first codebook and that corresponds to second channel information, the first codebook being related to time domain features of the second channel information; and N is an integer greater than or equal to 1, and K is an integer greater than or equal to 1. The embodiments of the present application can reduce the overhead caused by data collection and improve the accuracy of collected data.

Description

Data collection methods, terminal devices, and network devices Technical Field

[0001] This application relates to the field of communications, and more specifically, to a data collection method, terminal equipment, network equipment, chip, computer-readable storage medium, computer program product, computer program, and communication system. Background Technology

[0002] In recent years, Artificial Intelligence (AI) technology, relying on the development of different types of neural networks and deep learning algorithms, has been widely applied in various fields such as image, speech, and video processing. Drawing on the rapid development of AI technology, the combination of AI and wireless communication technology has also attracted widespread interest from academia and industry. Currently, extensive research, evaluation, and standardization work has been carried out on AI-based Channel State Information (CSI) feedback technology. AI technology can extract features from channel matrix data and reconstruct the compressed channel matrix information fed back from the terminal as accurately as possible on the network device side, providing the possibility of reducing CSI feedback overhead while ensuring the restoration of channel information.

[0003] AI-based CSI feedback requires deploying models on both the network and user sides. For network-side model training or performance monitoring, data collection becomes essential. Therefore, it's necessary to consider how to reduce the overhead of data collection and improve the accuracy of the collected data. Summary of the Invention

[0004] This application provides a data collection method, terminal device, network device, chip, computer-readable storage medium, computer program product, computer program, and communication system, which can improve the accuracy of collected data and reduce the overhead of data collection.

[0005] This application provides a data collection method, including:

[0006] The terminal device sends its first reporting information to the network device;

[0007] The first reported information includes dataset information, which includes N sets of labels. Each set of labels in the N sets includes first channel information for K time slots. The first channel information includes feature information corresponding to the second channel information obtained based on the first codebook. The time-domain features of the first codebook and the second channel information are related. N is an integer greater than or equal to 1, and K is an integer greater than or equal to 1.

[0008] This application provides a data collection method, including:

[0009] The network device receives the first reported information from the terminal device;

[0010] The first reported information includes dataset information, which includes N sets of labels. Each set of labels in the N sets includes first channel information for K time slots. The first channel information includes feature information corresponding to the second channel information obtained based on the first codebook. The time-domain features of the first codebook and the second channel information are related. N is an integer greater than or equal to 1, and K is an integer greater than or equal to 1.

[0011] This application provides a terminal device, including:

[0012] The first communication module is used to send the first reporting information to the network device;

[0013] The first reported information includes dataset information, which includes N sets of labels. Each set of labels in the N sets includes first channel information for K time slots. The first channel information includes feature information corresponding to the second channel information obtained based on the first codebook. The time-domain features of the first codebook and the second channel information are related. N is an integer greater than or equal to 1, and K is an integer greater than or equal to 1.

[0014] This application provides a network device, including:

[0015] The second communication module is used to receive the first reported information from the terminal device;

[0016] The first reported information includes dataset information, which includes N sets of labels. Each set of labels in the N sets includes first channel information for K time slots. The first channel information includes feature information corresponding to the second channel information obtained based on the first codebook. The time-domain features of the first codebook and the second channel information are related. N is an integer greater than or equal to 1, and K is an integer greater than or equal to 1.

[0017] This application provides a terminal device, including a transceiver, a processor, and a memory. The memory stores a computer program, the transceiver communicates with other devices, and the processor calls and runs the computer program stored in the memory to enable the terminal device to perform the data collection method described above.

[0018] This application provides a network device, including a transceiver, a processor, and a memory. The memory stores a computer program, the transceiver communicates with other devices, and the processor invokes and runs the computer program stored in the memory to enable the network device to perform the data collection method described above.

[0019] This application provides a chip for implementing the above-described data collection method.

[0020] Specifically, the chip includes a processor for retrieving and running a computer program from memory, causing a device equipped with the chip to perform the aforementioned data collection method.

[0021] This application provides a computer-readable storage medium for storing a computer program that, when run by a device, causes the device to perform the data collection method described above.

[0022] This application provides a computer program product, including computer program instructions that cause a computer to execute the data collection method described above.

[0023] This application provides a computer program that, when run on a computer, causes the computer to perform the data collection method described above.

[0024] This application provides a communication system, including a terminal device and a network device for performing the data collection method described above.

[0025] In this embodiment, the terminal device processes the second channel information using a first codebook related to time-domain features to obtain first channel information. Based on the first channel information across multiple time slots, a set of tags is obtained. The terminal device then transmits a dataset containing one or more sets of tags to the network device via first reporting information. This codebook-based feedback method reduces the overhead of data collection and improves tag reporting accuracy by utilizing the time-domain features of the channel information, thus enhancing the accuracy of the collected data. Attached Figure Description

[0026] Figure 1 is a schematic diagram of a communication system according to an embodiment of this application.

[0027] Figure 2A is a schematic diagram of the periodic CSI reporting method.

[0028] Figure 2B is a schematic diagram of semi-persistent CSI transmission on PUCCH.

[0029] Figure 2C is a schematic diagram of semi-persistent CSI transmission on the PUSCH.

[0030] Figure 2D is a schematic diagram of the non-periodic CSI reporting method.

[0031] Figure 3 is a schematic diagram of the AI-based CSI autoencoder framework.

[0032] Figure 4 is a schematic flowchart of a data collection method according to an embodiment of this application.

[0033] Figure 5 is a schematic flowchart of a data collection method according to another embodiment of this application.

[0034] Figure 6 is a schematic diagram of an AI-based spatial-frequency-time joint CSI compressed feedback model.

[0035] Figure 7 is a schematic diagram of the AI-based joint CSI prediction and compression model.

[0036] Figure 8 is a schematic diagram of the application flow of the data collection method according to an embodiment of this application.

[0037] Figure 9 is a schematic flowchart of a data collection method according to another embodiment of this application.

[0038] Figure 10 is a schematic block diagram of a terminal device according to an embodiment of this application.

[0039] Figure 11 is a schematic block diagram of a terminal device according to another embodiment of this application.

[0040] Figure 12 is a schematic block diagram of a terminal device according to another embodiment of this application.

[0041] Figure 13 is a schematic block diagram of a terminal device according to another embodiment of this application.

[0042] Figure 14 is a schematic block diagram of a network device according to an embodiment of this application.

[0043] Figure 15 is a schematic block diagram of a communication device according to an embodiment of this application.

[0044] Figure 16 is a schematic block diagram of a chip according to an embodiment of this application.

[0045] Figure 17 is a schematic block diagram of a communication system according to an embodiment of this application. Detailed Implementation

[0046] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0047] The technical solutions of this application embodiment can be applied to various communication systems, such as: Long Term Evolution (LTE) systems, Advanced Long Term Evolution (LTE-A) systems, New Radio (NR) systems, evolution systems of NR systems, LTE-based access to unlicensed spectrum (LTE-U) systems, NR-based access to unlicensed spectrum (NR-U) systems, Non-Terrestrial Networks (NTN) systems, Universal Mobile Telecommunication System (UMTS), Wireless Local Area Networks (WLAN), Wireless Fidelity (WiFi), 5th Generation (5G) systems, 6th Generation (6G) systems, or other communication systems.

[0048] Traditional communication systems typically support a limited number of connections and are easy to implement. However, with the development of communication technology, mobile communication systems will not only support traditional communication but also, for example, device-to-device (D2D) communication, machine-to-machine (M2M) communication, machine-type communication (MTC), vehicle-to-vehicle (V2V) communication, or vehicle-to-everything (V2X) communication. The embodiments of this application can also be applied to these communication systems.

[0049] In one implementation, the communication system in this application embodiment can be applied to a carrier aggregation (CA) scenario, a dual connectivity (DC) scenario, or a standalone (SA) network deployment scenario.

[0050] In one embodiment, the communication system in this application can be applied to unlicensed spectrum, wherein the unlicensed spectrum can also be considered as shared spectrum; or, the communication system in this application can also be applied to licensed spectrum, wherein the licensed spectrum can also be considered as non-shared spectrum.

[0051] This application describes various embodiments in conjunction with network devices and terminal devices. The terminal device may also be referred to as user equipment (UE), access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent, or user device, etc.

[0052] Terminal devices can be stations (STAs) in WLANs, cellular phones, cordless phones, Session Initiation Protocol (SIP) phones, Wireless Local Loop (WLL) stations, Personal Digital Assistant (PDA) devices, handheld devices with wireless communication capabilities, computing devices or other processing devices connected to a wireless modem, in-vehicle devices, wearable devices, terminal devices in next-generation communication systems such as NR networks, or terminal devices in future evolved Public Land Mobile Network (PLMN) networks, etc.

[0053] In the embodiments of this application, the terminal device can be deployed on land, including indoor or outdoor, handheld, wearable or vehicle-mounted; it can also be deployed on water (such as ships); and it can also be deployed in the air (such as airplanes, balloons and satellites).

[0054] In the embodiments of this application, the terminal device may be a mobile phone, a tablet computer, a computer with wireless transceiver capabilities, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical care, a wireless terminal device in a smart grid, a wireless terminal device in transportation safety, a wireless terminal device in a smart city, or a wireless terminal device in a smart home, etc.

[0055] By way of example and not limitation, in this embodiment, the terminal device can also be a wearable device. Wearable devices, also known as wearable smart devices, are a general term for devices that utilize wearable technology to intelligently design and develop everyday wearables, such as glasses, gloves, watches, clothing, and shoes. Wearable devices are portable devices that are worn directly on the body or integrated into the user's clothing or accessories. Wearable devices are not merely hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include those that are feature-rich, large in size, and can achieve complete or partial functions without relying on a smartphone, such as smartwatches or smart glasses, as well as those that focus on a specific type of application function and require the use of other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0056] In the embodiments of this application, the network device can be a device for communicating with mobile devices, such as an access point (AP) in a WLAN, an evolved Node B (eNB or eNodeB) in LTE, a relay station or access point, or a vehicle-mounted device, a wearable device, a network device (gNB) in an NR network, or a network device in a future evolved PLMN network or an NTN network, etc.

[0057] By way of example and not limitation, in this embodiment, the network device may have mobility characteristics; for example, the network device may be a mobile device. Optionally, the network device may be a satellite or a balloon station. For example, the satellite may be a low Earth orbit (LEO) satellite, a medium Earth orbit (MEO) satellite, a geostationary earth orbit (GEO) satellite, a high elliptical orbit (HEO) satellite, etc. Optionally, the network device may also be a base station located on land, water, or other similar locations.

[0058] In this embodiment, the network device can provide services to a cell. The terminal device communicates with the network device through the transmission resources (e.g., frequency domain resources, or spectrum resources) used by the cell. The cell can be the cell corresponding to the network device (e.g., a base station). The cell can belong to a macro base station or to a base station corresponding to a small cell. The small cell can include: metro cell, micro cell, pico cell, femto cell, etc. These small cells have the characteristics of small coverage area and low transmission power, and are suitable for providing high-speed data transmission services.

[0059] Figure 1 illustrates an exemplary communication system 100. The communication system includes a network device 110 and two terminal devices 120. In one embodiment, the communication system 100 may include multiple network devices 110, and the coverage area of ​​each network device 110 may include other numbers of terminal devices 120; this embodiment does not limit the scope of the present application.

[0060] In one embodiment, the communication system 100 may also include other network entities such as a Mobility Management Entity (MME) and an Access and Mobility Management Function (AMF), which are not limited in this application.

[0061] Network equipment can be further divided into access network equipment and core network equipment. That is, the wireless communication system also includes multiple core networks used to communicate with the access network equipment. Access network equipment can be evolved Node Bs (eNBs or e-NodeBs) in Long-Term Evolution (LTE), Next-Generation Radio (NR) (mobile communication system), or Authorized Auxiliary Access Long-Term Evolution (LAA-LTE) systems, such as macro base stations, micro base stations (also called "small base stations"), pico base stations, access points (APs), transmission points (TPs), or new generation Node Bs (gNodeBs).

[0062] It should be understood that devices with communication functions in the network / system of this application embodiment can be referred to as communication devices. Taking the communication system shown in Figure 1 as an example, the communication device may include network devices and terminal devices with communication functions. The network devices and terminal devices can be specific devices in this application embodiment, which will not be described in detail here. The communication device may also include other devices in the communication system, such as network controllers, mobility management entities, and other network entities. This application embodiment does not limit this.

[0063] It should be understood that the terms "system" and "network" are often used interchangeably in this document. The term "and / or" in this document merely describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Furthermore, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0064] It should be understood that the term "instruction" mentioned in the embodiments of this application can be a direct instruction, an indirect instruction, or an indication of a relationship. For example, A instructing B can mean that A directly instructs B, such as B being able to obtain information through A; it can also mean that A indirectly instructs B, such as A instructing C, so B can obtain information through C; or it can mean that there is a relationship between A and B.

[0065] In the description of the embodiments of this application, the term "correspondence" may indicate that there is a direct or indirect correspondence between two things, or that there is an association between two things, or that there is a relationship of instruction and being instructed, configuration and being configured, etc.

[0066] To facilitate understanding of the technical solutions of the embodiments of this application, the relevant technologies of the embodiments of this application are described below. The following relevant technologies are optional solutions and can be combined with the technical solutions of the embodiments of this application in any way, and they all fall within the protection scope of the embodiments of this application.

[0067] (I) CSI Feedback in NR

[0068] In current NR systems, CSI feedback schemes typically employ codebook-based eigenvector feedback to enable network devices to acquire downlink CSI. Specifically, the network device sends a downlink Channel State Information Reference Signal (CSI-RS) to the user. The user uses the CSI-RS to estimate the downlink channel's CSI and performs eigenvalue decomposition on the estimated downlink channel to obtain its corresponding eigenvector. NR provides two codebook design schemes: Type I and Type II. Type I codebooks are used for CSI feedback with standard accuracy, primarily for Single-user Multiple-Input Multiple-Output (SU-MIMO) scenarios. Type II codebooks are mainly used to improve the transmission performance of Multi-User Multiple-Input Multiple-Output (MU-MIMO) scenarios. For both Type I and Type II codebooks, a two-stage codebook feedback system W = W1W2 is used. W1 describes the channel's bandwidth and long-term characteristics, defining a set of Discrete Fourier Transform (DFT) beams (containing L DFT beams). W2 describes the channel's sub-band and short-term characteristics. Specifically, for the Type I codebook, W2 selects one beam from the L DFT beams; for the Type II codebook, W2 linearly combines the L DFT beams from W1, providing feedback in amplitude and phase terms. Generally, the Type II codebook utilizes a higher number of feedback bits to achieve higher precision CSI feedback performance.

[0069] Terminals can report CSI in three ways: periodic CSI, semi-persistent CSI, and aperiodic CSI.

[0070] Figure 2A is a schematic diagram of the periodic CSI reporting method. The periodic CSI is transmitted on the Physical Uplink Control Channel (PUCCH). Its CSI reporting configuration is configured by Radio Resource Control (RRC) signaling. After receiving the corresponding RRC configuration, the terminal periodically reports the CSI.

[0071] Semi-persistent CSI can be transmitted on the PUCCH or the Physical Uplink Shared Channel (PUSCH). Figure 2B is a schematic diagram of semi-persistent CSI transmission on the PUCCH. The CSI reporting configuration corresponding to the CSI transmitted on the PUCCH is pre-configured by RRC signaling and activated or deactivated by Media Access Control (MAC) layer signaling, such as the MAC Control Element (MAC CE). Figure 2C is a schematic diagram of semi-persistent CSI transmission on the PUSCH. The CSI reporting configuration corresponding to the CSI transmitted on the PUSCH is dynamically indicated (activated or deactivated) by Downlink Control Information (DCI). After receiving the activation or indication signaling from the network configuration, the terminal periodically transmits CSI on the PUCCH or PUSCH until it receives the deactivation signaling and stops reporting.

[0072] Figure 2D is a schematic diagram of the non-periodic CSI reporting method. The CSI reporting configuration for non-periodic CSI reporting is pre-configured via RRC signaling. Part of this configuration can be activated via MAC layer signaling, and then the CSI trigger signaling in the DCI indicates the CSI reporting configuration used for CSI reporting. After receiving the CSI trigger signaling, the terminal reports the corresponding CSI on the scheduled PUSCH in one go according to the indicated CSI reporting configuration.

[0073] (ii) AI-based CSI feedback

[0074] In recent years, AI and ML technologies, relying on the development of different types of neural networks and machine learning algorithms, have been widely applied in various fields such as image, speech, and video processing. Typical neural network architectures include fully connected networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and Transformer structures with self-attention mechanisms, which can accomplish different task objectives.

[0075] Drawing on the rapid development of AI / ML technologies, the integration of artificial intelligence with wireless communication technologies has attracted widespread interest from both academia and industry. Extensive research, evaluation, and standardization efforts have been undertaken for AI / ML-based CSI feedback and prediction, beam management, and positioning technologies.

[0076] Given the tremendous success of deep learning in computer vision and natural language processing, the communications field has begun to explore its application to solve technical challenges that traditional communication methods struggle with. The neural network architectures commonly used in deep learning are non-linear and data-driven, enabling feature extraction from actual channel matrix data and, on the network device side, reconstructing the compressed channel matrix information from the UE (User Equipment) feedback as accurately as possible. This not only ensures accurate channel information reconstruction but also reduces CSI (Content Support Interface) feedback overhead on the UE side. Deep learning-based CSI feedback treats channel information as an image to be compressed, using a deep learning autoencoder to compress the input channel information and then reconstructing the compressed channel image at the transmitting end, thus preserving channel information to a greater extent.

[0077] Figure 3 is a schematic diagram of the AI-based CSI feedback framework. As shown in Figure 3, the main implementation framework of AI-based CSI feedback is as follows:

[0078] An AI-based CSI autoencoder method is adopted. The entire feedback system is divided into encoder and decoder parts, deployed on the user equipment and network equipment respectively. After obtaining channel information through channel estimation, the user equipment uses the channel information as input to the encoder. The encoder's neural network compresses and encodes the channel information, and the compressed feedback bitstream is fed back to the network equipment through the air interface feedback link. The network equipment uses the decoder to recover the channel information based on the feedback bitstream and outputs the complete feedback channel information. The neural networks of the encoder and decoder can adopt DNN composed of multiple fully connected layers, CNN composed of multiple convolutional layers, or RNN with structures such as Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). Various neural network architectures such as residual and self-attention mechanisms can also be used to improve the performance of the encoder and decoder.

[0079] The input of the encoder and the output of the decoder described above can both be full-channel information or feature vector information obtained based on full-channel information. Although full-channel information feedback can achieve compression and feedback of full-channel information, the feedback bitstream overhead is high. The feature vector-based feedback method is the feedback architecture currently supported by NR systems. It can achieve higher CSI feedback accuracy with the same feedback bit overhead, or significantly reduce feedback overhead while achieving the same CSI feedback accuracy.

[0080] The CSI input and output mentioned above can both be full-channel information or feature vector information obtained based on full-channel information. Therefore, current deep learning-based channel information feedback methods are mainly divided into full-channel information feedback and feature vector feedback. While the former can achieve compression and feedback of full-channel information, it has high feedback bitstream overhead and is not supported in existing NR systems. Feature vector-based feedback methods are the feedback architecture currently supported by NR systems. AI-based feature vector feedback methods can achieve higher CSI feedback accuracy with the same feedback bit overhead, or significantly reduce feedback overhead while achieving the same CSI feedback accuracy.

[0081] AI-based CSI feedback requires deploying models on both the network and user sides. For network-side model training or performance monitoring, data collection becomes essential. Therefore, it's necessary to consider how to improve the accuracy of the collected data and reduce the signaling overhead associated with data collection.

[0082] The technical solutions of the embodiments of this application can solve at least one of the above problems.

[0083] Figure 4 is a schematic flowchart of a data collection method according to an embodiment of this application. This method can optionally be applied to the system shown in Figure 1, but is not limited thereto. The method includes:

[0084] S410, The terminal device sends the first reporting information to the network device.

[0085] The first reported information includes dataset information, which includes N sets of labels. Each set of labels in the N sets includes first channel information for K time slots. The first channel information includes feature information corresponding to the second channel information obtained based on the first codebook. The time-domain features of the first codebook and the second channel information are related. N is an integer greater than or equal to 1, and K is an integer greater than or equal to 1.

[0086] To facilitate understanding of the implementation and technical effects of the above methods, some exemplary application scenarios are introduced below. It should be understood that the application scenarios described below are exemplary and not limiting. In actual applications, the technical solutions of the embodiments of this application can also be applied to other scenarios, and are not limited thereto.

[0087] In some application scenarios, the aforementioned dataset information can be used to train models. For example, before using a model to perform related tasks, network devices need to train the model using the dataset information, that is, to train a model that meets the usage requirements. Optionally, the network device can determine the loss calculated by the model based on the labels in the dataset information and the model's output information, and use this loss to optimize the model's parameters. Through multiple iterations of optimization, the training of the model is completed.

[0088] In some application scenarios, the aforementioned dataset information can be used to monitor models. For example, when using a model to perform related tasks, network devices can periodically collect dataset information or trigger the collection of dataset information based on specific events, using the dataset information to evaluate / monitor the model's performance. Optionally, network devices can determine the model's performance metrics based on the similarity, difference, or distance between the labels in the dataset information and the model's output results.

[0089] Alternatively, the above model can be an AI model.

[0090] Optionally, the model can be a model for processing channel information. Optionally, the model is a model in which the input information and / or output information includes channel information, such as a model for channel information feedback, a model for channel information prediction, or a model for joint channel information prediction and compressed feedback.

[0091] For example, the model can be a model for channel information feedback. For instance, the model includes an autoencoder-based CSI feedback model, which achieves compressed feedback of CSI by encoding the channel information, transmitting it through the channel, and then decoding it. Another example is a CSI feedback model based on Joint Source-channel Coding (JSCC).

[0092] For example, the model can be a model for channel information prediction, such as a model for predicting channel information at future times based on channel information at historical times and / or the current time.

[0093] For example, the model can be a model for joint channel information prediction and compressed feedback. For instance, the model can feed back channel information for future times to the network device based on channel information at historical and / or current times.

[0094] In this embodiment, the terminal device reports dataset information by sending first reporting information to the network device. Optionally, the first reporting information can be carried by physical layer signaling, such as uplink control information (UCI), transmitted via PUCCH or PUSCH. Reporting via physical layer signaling can reduce signaling latency. For example, when model training or model monitoring is required, the first reporting information can be carried by physical layer signaling.

[0095] Optionally, the first reported information can be carried by higher-level signaling, such as MDT, which can improve the carrying capacity. For example, when model training is required, higher-level signaling can be used to carry the first reported information.

[0096] In this embodiment, the dataset information includes N sets of labels, where N is an integer greater than or equal to 1, meaning the dataset information can include one or more sets of labels. Each set of labels includes first channel information for K time slots, where K is an integer greater than or equal to 1, meaning each set of labels includes first channel information for one or more time slots. For example, each set of labels can include multiple sets of first channel information, each set corresponding to one time slot. Here, a time slot can also be understood as a time unit (or time unit) or moment, meaning each set of labels includes first channel information at different times. Optionally, the terminal device transmits the dataset information to the network device. Each set of labels in the dataset information is a sample containing first channel information for multiple time slots, which can be used to train or monitor a model related to the channel information of multiple time slots. For example, the model can be an autoencoder for encoding and decoding the channel information of multiple time slots, or a model for predicting the channel information of multiple time slots.

[0097] Optionally, the aforementioned K time slots can be K consecutive time slots.

[0098] Furthermore, in the first channel information of the K time slots, each piece of first channel information includes feature information corresponding to the second channel information obtained based on the first codebook. The first codebook is related to the time-domain features of the second channel information. The second channel information can be understood as either the original channel information or the channel information to be transmitted. For example, the second channel information could be the CSI obtained by the terminal device based on measurements. The first channel information can be understood as the transmission form of the second channel information; that is, the terminal device reports the second channel information by transmitting the first channel information, and the network device can recover the second channel information based on the received first channel information.

[0099] The channel information in this embodiment, including first channel information and second channel information, can all be used to characterize the channel state, and therefore can also be called CSI. Since the first channel information is feature information obtained based on the first codebook, the number of bits in the feedback bitstream corresponding to the first channel information is relatively smaller than the number of bits in the feedback bitstream corresponding to the second channel information, which can reduce tag reporting overhead. Furthermore, by processing the second channel information based on the first codebook related to time-domain features, the resulting first channel information can reflect the time-domain features of the second channel information. Therefore, at the receiving side, for the first channel information of multiple time slots in a group of tags, the time-domain features can be fully utilized to improve recovery accuracy. For example, these time-domain features can reflect the time-domain correlation between the second channel information of multiple time slots, thereby utilizing the time-domain correlation between channel information at different times to improve tag recovery accuracy.

[0100] For example, the terminal device can select the feature information (which can be understood as codewords in the codebook) that best matches the second channel information from the first codebook as the first channel information; wherein, the feature information in the first codebook can be obtained based on the combination of multiple vectors, wherein a vector for representing the time domain features can be set, so that the first channel information can reflect the time domain features in the second channel information.

[0101] In summary, in the data collection method of this application embodiment, the terminal device processes the second channel information using a first codebook related to time-domain features to obtain the first channel information, obtains a set of tags based on the first channel information of multiple time slots, and transmits the dataset information containing one or more sets of tags to the network device through the first reporting information. The overhead caused by data collection is reduced by the codebook-based feedback method, and the accuracy of tag reporting is improved by utilizing the time-domain features of the channel information, that is, the accuracy of the collected data is improved.

[0102] Figure 5 is a schematic flowchart of a data collection method according to another embodiment of this application. This method can optionally be applied to the system shown in Figure 1, but is not limited thereto. The method includes:

[0103] S510, The network device receives the first reported information from the terminal device;

[0104] The first reported information includes dataset information, which includes N sets of labels. Each set of labels in the N sets includes first channel information for K time slots. The first channel information includes feature information corresponding to the second channel information obtained based on the first codebook. The time-domain features of the first codebook and the second channel information are related. N is an integer greater than or equal to 1, and K is an integer greater than or equal to 1.

[0105] For specific examples and technical effects of the method executed by the network device in this application embodiment, please refer to the relevant description of the network device in the above method. For the sake of brevity, it will not be repeated here.

[0106] In one application example, the data collection method described above is used to train or monitor an AI-based spatial-frequency-time joint CSI compressed feedback model.

[0107] Figure 6 is a schematic diagram of an AI-based joint spatial-frequency-time CSI compression feedback model. This model includes an encoder deployed on the user side (terminal device) and a decoder deployed on the network side (network device). The encoder input on the user side includes not only the CSI measurement information at the current time (e.g., time t), but also the CSI (historical CSI) at past times (e.g., time t-1). This historical CSI is characterized by the feature output of the latent vector space from the encoder at past times and does not have explicit physical meaning. Similarly, the decoder input on the network side includes not only the feedback information at the current time, but also the CSI (historical CSI) at past times. This historical CSI is characterized by the feature output of the latent space from the decoder at past times and also does not have explicit physical meaning. For the feedback information at time t on the air interface, it not only implicitly represents the features of the current time's CSI, but also includes information features from historical CSI that help in recovering the current time's CSI, which can be used by the network side to better recover the current time's CSI.

[0108] Based on the data collection method provided in this application, each set of labels in the dataset information may include first channel information of multiple time slots (including at least one first channel information corresponding to a historical time and a first channel information corresponding to the current time). The network device determines second channel information of multiple time slots based on the first channel information of multiple time slots (including at least one second channel information corresponding to a historical time and a second channel information corresponding to the current time). The second channel information of multiple time slots is used as the actual label for training or monitoring the model. For example, the second channel information of multiple time slots is input into the encoder, and the feedback information output by the encoder is then processed by the decoder to obtain third channel information. Based on the third channel information and the second channel information corresponding to the current time, the loss calculated by the model or the performance index of the model is determined.

[0109] In one application example, the data collection method described above is used to train or monitor an AI-based joint CSI prediction and compression model. Figure 7 is a schematic diagram of the AI-based joint CSI prediction and compression model. This model includes a CSI prediction module and an encoder deployed on the user side, and a decoder deployed on the network side. The user-side CSI prediction module takes the CSI measurement information within the measurement window (the measured CSI) as input and outputs the predicted CSI at at least one time step. The predicted CSI at at least one time step is preprocessed (e.g., the predicted CSI information is full-channel information, and SVD decomposition can be used to extract feature vectors from different layers for the CSI compression process) and then used as input to the encoder. When the encoder input is CSI information from multiple time steps, the encoder output is joint feedback information, and the decoder can simultaneously recover CSI information from multiple prediction time steps. By extracting the correlation information of CSI from multiple time steps, the performance of CSI feedback can be further enhanced with preferential air interface feedback overhead. Meanwhile, the CSI prediction and CSI encoding compression process on the user side can be either a separate processing process as shown in Figure 7 or a coupled processing process. That is, the part shown in the dashed box in Figure 7 can be completed by an AI model (e.g., an encoder).

[0110] Based on the data collection method provided in this application, each set of labels in the dataset information may include first channel information of multiple time slots (corresponding to the measured second channel information). The network device determines second channel information of multiple time slots based on the first channel information of multiple time slots, and uses the second channel information of multiple time slots as the actual labels to train or monitor the model. For example, the second channel information of multiple time slots is input into the CSI prediction module, and then processed by the encoder and decoder to obtain third channel information of multiple time slots. Based on the third channel information of multiple time slots and the second channel information of multiple time slots, the loss calculated by the model or the performance index of the model is determined.

[0111] In the above application examples, a set of tags contains samples from multiple consecutive time periods. According to the method of this application embodiment, during the data collection process, the temporal domain features of each channel information in the tag are extracted based on the first codebook, which can improve the tag accuracy.

[0112] Figure 8 illustrates the application flow of the data collection method according to an embodiment of this application. For various CSI feedback methods, on the one hand, training is required to obtain a high-performance model (including an encoder deployed on the terminal device and a decoder deployed on the network device); on the other hand, performance monitoring of the model is needed during inference. Therefore, to enable these two functions on the network side, the user, i.e., the terminal device, needs to report the measured channel information as a tag to the network side. As shown in Figure 8, the steps include:

[0113] Step 1: The terminal device reports tags to the network device; the reported tags are used for model training.

[0114] Step 2: Network devices perform network-side model training.

[0115] Step 3: The network device sends the dataset or model to the terminal device.

[0116] Step 4: The terminal device performs user-side model training.

[0117] Step 5: The terminal device reports CSI based on the model obtained from training.

[0118] Step 6: The terminal device reports tags to the network device; the reported tags are used for model monitoring.

[0119] In step 1, tag reporting is used by the network device to complete data collection and subsequent model training. In step 6, tag reporting is used by the network device to monitor model performance during inference. In related technologies, tag reporting generally uses unquantized float32 or high-precision codebooks for channel information to ensure the accuracy of tag reporting. This embodiment can use a first codebook related to time-domain features for tag reporting. It should be noted that tag reporting is different from CSI reporting in step 5. CSI reporting in step 5 exists in the model inference process, referring to the terminal device reporting the result output by the user-side model (encoder). The information reported in step 5 is used by the network device to recover the measured CSI using the network-side model (decoder).

[0120] In some embodiments, the first codebook is used to obtain feature information based on the temporal correlation of second channel information across multiple time slots. For example, the first codebook may include a vector characterizing the temporal correlation of channel information across multiple consecutive time slots, such that the feature information determined based on the first codebook may contain temporal correlation information.

[0121] Optionally, the first codebook can be used to jointly feed back second channel information from multiple time slots. For example, the terminal device can, based on the first codebook, jointly determine multiple first channel information matching the multiple second channel information.

[0122] According to the above embodiments, the first channel information in the dataset is not only related to the time domain features, but also to the time domain correlation between the second channel information in multiple time slots. Based on this, by transmitting the first channel information of multiple time slots to report the second channel information of multiple time slots, the reporting accuracy can be further improved.

[0123] In some embodiments, K is related to a fourth parameter of the first codebook; the fourth parameter is the number of time slots corresponding to the channel information processed based on the first codebook. In other words, assuming the fourth parameter is X, and the first codebook is used to process the second channel information based on X time slots to obtain the first channel information in X time slots, then K is related to X, where X is an integer greater than or equal to 1.

[0124] In some embodiments, K is a positive integer multiple of the fourth parameter X, or K is equal to the fourth parameter X. That is, K = mX, where m is a positive integer. For example, based on the first codebook, a set of second channel information can be processed at once. A set of second channel information includes second channel information in X time slots. By processing one or more sets of second channel information, first channel information in K time slots can be obtained, that is, a set of tags can be obtained.

[0125] Optionally, the values ​​of K and / or X can be determined based on configuration information issued by the network device, or they can be default values. For example, the configuration information issued by the network device can indicate the value of X, and K defaults to X.

[0126] In some embodiments, the first codebook includes a Doppler-eTypeII codebook. The Doppler-eTypeII codebook can be used to jointly feed back channel information (CSI) at multiple time points in the spatial, frequency, and time domains. Specifically, the Doppler-eTypeII codebook selects L DFT beams of length N1N2 on N1N2 ports. i As basis vectors in the spatial domain, M DFT vectors f of length N3 are selected from the N3 subbands. j As basis vectors in the frequency domain, Q = 2 DFT vectors d of length N4 are selected in the time domain, which are N4 = {1, 2, 4, 8} time units. k As basis vectors in the time domain, the Doppler-eTypeII codebook is composed of basis vectors from three orthogonal domains, with corresponding combination coefficients c chosen in the two polarization directions. i,j,k and c i+L,j,k The result can be expressed using the following formula:

[0127] Since the Doppler-eTypeII codebook can extract the temporal correlation between channel information of multiple time slots, it can effectively improve the accuracy of the tags transmitted in the embodiments of this application.

[0128] In some embodiments, the aforementioned feature information includes a feature vector, i.e., the first channel information is a feature vector.

[0129] In some embodiments, the data collection method may further include: a network device sending a first reference signal to a terminal device; wherein the first reference signal is used by the terminal device to obtain second channel information.

[0130] Accordingly, in some embodiments, the data collection method may further include: a terminal device receiving a first reference signal from a network device; wherein the first reference signal is used by the terminal device to obtain second channel information.

[0131] For example, the first reference signal may include CSI-RS. The network device first sends CSI-RS to the terminal device. Based on CSI-RS, the terminal device determines the second channel information, and then determines the first channel information based on the second channel information. After forming a dataset information containing N sets of tags, the terminal device reports the dataset information through the first reporting information. Optionally, the first reference signal may also include other reference signals. For example, a downlink reference signal dedicated to data collection.

[0132] Optionally, the first reference signal can be a periodic, aperiodic, or semi-continuous reference signal.

[0133] In some embodiments, the second channel information is obtained by the terminal device based on the measurement of the first reference signal, or by the terminal device based on the measurement of the first reference signal and prediction processing.

[0134] For example, the terminal device performs channel estimation based on the measurement of the first reference signal to obtain the second channel information.

[0135] For example, the terminal device performs channel estimation based on the measurement of the first reference signal to obtain fourth channel information, and then predicts second channel information based on the fourth channel information. The time corresponding to the fourth channel information is prior to the time corresponding to the second channel information; for example, the second channel information at a future time is predicted based on the currently measured fourth channel information. Optionally, the prediction can be based on an AI model or an ML model, or it can be based on a non-AI / ML algorithm, such as an autoregressive algorithm or a Kalman filter algorithm.

[0136] In some embodiments, the first reported information further includes one or more of the following information A to D:

[0137] A. First indication information; wherein, the first indication information is used to indicate that the dataset information is obtained based on measurement or prediction.

[0138] The first indication information can be referred to as tag type indication information. Optionally, the first indication information is specifically used to indicate that the second channel information corresponding to the tag (i.e., the first channel information) in the dataset information is obtained based on measurement or prediction. For example, if the first indication information indicates that the dataset information is obtained based on measurement, then the second channel information is obtained by the terminal device based on the measurement of the first reference signal; if the first indication information indicates that the dataset information is obtained based on prediction, then the second channel information is obtained by the terminal device based on the measurement of the first reference signal and then prediction based on a model or algorithm.

[0139] Optionally, the network device can configure the terminal device to report tags by issuing first configuration information, wherein the first configuration information can indicate that the tags required by the network device are based on measurement or prediction. If the first configuration information does not indicate that the tags are based on measurement or prediction, the first indication information can be carried in the first reporting information.

[0140] B. Quality information of the dataset.

[0141] In some embodiments, the quality information includes one or more of the following: Channel Quality Indicator (CQI), Signal to Noise Ratio (SNR), Signal to Interference plus Noise Ratio (SINR), Reference Signal Receiving Power (RSRP), and Received Signal Strength Indicator (RSSI).

[0142] By describing the quality of the dataset information in the first reported information, network devices can select higher-quality samples for model training based on the quality information of different datasets when there are enough samples.

[0143] C. First auxiliary information; wherein, the first auxiliary information is used to indicate information related to the collection process of the dataset information.

[0144] Optionally, the first auxiliary information is used to indicate the characteristics of the data set information collection process, so that the network device can classify the data set information and train a model suitable for different conditions or configurations.

[0145] In some embodiments, the first auxiliary information includes one or more of the following: area information, location information, and status information of the terminal device during the data collection process.

[0146] For example, the first auxiliary information package contains area information or location information, which is used to describe the area and location where the terminal device obtains data, such as different cells (area information includes cell ID, or PCI identifier, etc.), different sectors within the cell, or different scenarios (outdoor or indoor) within the cell.

[0147] For example, the first auxiliary information includes the status information of the terminal device, which describes the state of the terminal device. For example, the status information includes movement speed, geographical location information, posture information, etc.

[0148] D. Identification information of dataset information; where the identification information is used to distinguish dataset information collected under different user configurations.

[0149] Optionally, the identification information in the dataset may include a set of identification information related to UE-side additional condition information. UE-side additional condition information may include, for example, the user's antenna spacing, antenna arrangement, beam direction, or the prediction algorithm used (e.g., non-AI / ML algorithm or AI / ML algorithm). The terminal device associates the UE-side additional condition information by reporting a set of identification information.

[0150] Optionally, the correspondence between the aforementioned identification information and user configuration is not reported to the network device. That is, the terminal device can determine the correspondence between the identification information and user configuration, as well as the correspondence between the identification information and dataset information. The network device can determine the correspondence between the identification information and dataset information. Therefore, it can classify datasets from different users based on this identification information to train models corresponding to different identification information. The terminal device can obtain and use the model corresponding to its own configuration based on the correspondence between the identification information and user configuration. In this way, a more suitable model can be trained and used without exposing user privacy.

[0151] It should be noted that the first reported information may include one or more of the information A through D above. That is, the first reported information may include information A, information B, information C, or information D, or it may include information A and B, or information A and C, or information A and D, etc. In practical applications, the content of the information carried in the first reported information can be determined according to system conventions, protocol conventions, or scenario requirements. For the sake of brevity, all possible situations will not be listed here.

[0152] In some embodiments, the data collection method may further include: the network device sending first configuration information to the terminal device.

[0153] Accordingly, in some embodiments, the data collection method may further include: the terminal device receiving first configuration information from the network device.

[0154] Optionally, the first configuration information is RRC configuration information.

[0155] Optionally, the first configuration information can be used to configure relevant information of the first reference signal or the first reported information.

[0156] Optionally, the first configuration information may include one or more of the following information E to H:

[0157] E. Configuration information of the resources for the first reported information.

[0158] Optionally, the network device can configure one or more reporting resources on downlink component carriers (CC) or bandwidth parts (BWP) for the terminal device using the first configuration information.

[0159] For example, the reporting resources may include time-domain resources and / or frequency-domain resources for transmitting the first reporting information.

[0160] F. Configuration information of measurement resources for the first reference signal.

[0161] Optionally, the network device can configure one or more measurement resources on a CC or BWP for the terminal device using the first configuration information.

[0162] For example, measurement resources may include time-domain resources and / or frequency-domain resources for transmitting a first reference signal.

[0163] G. Configuration information for the first codebook.

[0164] For example, the configuration information of the first codebook includes one or more of the following:

[0165] Second instruction information; wherein, the second instruction information is used by the terminal device to determine that the first codebook is used;

[0166] Configuration information for the parameters of the first codebook.

[0167] For example, the configuration information of the first codebook includes second instruction information, which is used to configure the codebook used by the reporting tag to be the first codebook, such as the Doppler-eTypeII codebook.

[0168] For example, the configuration information of the first codebook includes configuration information of the parameters of the first codebook. For instance, the use of the first codebook during data collection is pre-agreed upon, such as by protocol agreement or pre-configuration, and the network device needs to configure the parameters of the first codebook when issuing the first configuration information.

[0169] For example, the configuration information of the first codebook includes the second indication information and the configuration information of the parameters of the first codebook. For instance, the network device configures the codebook used for reporting tags to be the Doppler-eTypeII codebook in the configuration information of the first codebook, and also configures the parameters of the Doppler-eTypeII codebook.

[0170] Optionally, the configuration information of the parameters of the first codebook can be an identifier or index corresponding to the parameters of the first codebook, with different identifiers or indices corresponding to different parameter combinations. For example, identifier 10 corresponds to parameter combination L = 8. For example, identifier 11 corresponds to parameter combination L = 10. Where L is the number of orthogonal DFT basis vectors in the spatial domain, p v β is a high-level configuration parameter used to determine the number of frequency domain orthogonal DFT basis vectors, and β is a high-level configuration parameter used to determine the maximum number of non-zero coefficients reported in the set of all linear combination coefficients.

[0171] Taking the Doppler-eTypeII codebook as an example, the configuration information of the first codebook can include the parameter `codebookType`, indicating that the codebook used is Doppler-eTypeII. The configuration information of the first codebook can also include the parameter configuration `paramCombination-Doppler`, which can refer to existing protocols and take values ​​from 1 to 9. To obtain higher-precision labels for data collection, higher configurations can be selected, for example, corresponding to L,p values ​​different from 1 to 9. ν ,β combination.

[0172] H. Configuration information for the parameters of the dataset.

[0173] Optionally, the parameters of the dataset information include one or more of the following:

[0174] (1) First parameter; where the first parameter is the number of labels N in the dataset information.

[0175] The first parameter N configured in the first configuration information can be understood as the number of tags that the terminal device should report. Optionally, there can be multiple ways to configure the first parameter, and the configuration information of the first parameter included in the first configuration information can also take different forms.

[0176] For example, the configuration information of the first parameter is used to indicate the value of the first parameter. That is, the specific value of the first parameter is directly configured by the first configuration information, such as N=20 or N=50, etc.

[0177] For example, the configuration information of the first parameter is used to indicate the value range of the first parameter; wherein, the value range of the first parameter is used by the terminal device to determine the first parameter based on the MAC CE and / or DCI within the value range. For example, the configuration information of the first parameter is used to configure the value range of N to N≥50, and then the MAC CE and / or DCI indicate / activate a first parameter within the value range.

[0178] For example, the configuration information of the first parameter is used to indicate the first parameter set; wherein, the first parameter set is used by the terminal device to determine the first parameter based on the MAC CE and / or DCI in the first parameter set. For example, the configuration information of the first parameter is used to configure the first parameter set N∈{20,50,100}, and then the MAC CE and / or DCI indicates / activates a first parameter in {20,50,100}.

[0179] Optionally, the method by which the MAC CE and / or DCI determine the first parameter within the value range or the first parameter set can be either that the first parameter is dynamically activated by the MAC CE or DCI, or that the MAC CE configures a smaller value range or parameter set, and then the DCI dynamically activates it. For example, the first configuration information may configure N≥50, then the MAC CE configures the first parameter set N∈{50,100}, and then the DCI dynamically activates it.

[0180] Optionally, the first parameter may not be explicitly configured in the first configuration information. In this case, the first parameter may be determined based on downlink activation signaling and / or deactivation signaling sent by the network device, or based on uplink request signaling sent by the terminal device.

[0181] (2) Second parameter; where the second parameter is the number of time slots K corresponding to each group of tags, that is, the number of channel information included in each group of tags.

[0182] Optionally, there can be multiple ways to configure the second parameter, and the configuration information of the second parameter included in the first configuration information can also take different forms.

[0183] For example, the configuration information of the second parameter is used to indicate the value of the second parameter. For example, K=8, or K=16.

[0184] For example, the configuration information of the second parameter is used to indicate the value range of the second parameter; wherein, the value range of the second parameter is used by the terminal device to determine the second parameter within the value range based on MAC CE and / or DCI. For example, the configuration information of the second parameter is used to configure the value range of K to K≥16, and then MAC CE and / or DCI indicate / activate a second parameter within this value range.

[0185] For example, the configuration information of the second parameter is used to indicate the second parameter set; wherein, the second parameter set is used by the terminal device to determine the second parameter in the second parameter set based on the MAC CE and / or DCI. For example, the configuration information of the second parameter is used to configure the second parameter set K∈{4,8,16}, and then the MAC CE and / or DCI indicates / activates a second parameter in {4,8,16}.

[0186] Optionally, the method by which the MAC CE and / or DCI determine the second parameter within the value range or the second parameter set can be either that the second parameter is dynamically activated by the MAC CE or DCI, or that the MAC CE configures a smaller value range or parameter set, and then the DCI dynamically activates it. For example, if the first configuration information configures K≥16, then the MAC CE indicates a second parameter set, such as K∈{16,32}, and then the DCI dynamically activates it.

[0187] Optionally, the second parameter may not be included in the first configuration information, and the second parameter can take a default value. For example, the default K is equal to the fourth parameter, which is the number of time slots corresponding to the channel information processed based on the first codebook. The fourth parameter can be configured in the configuration information of the first codebook.

[0188] As explained above, the second parameter K is related to the fourth parameter of the first codebook. For example, K = mX, where X is the fourth parameter. In this way, the terminal device can obtain a set of tags based on the processing results of m first codebooks.

[0189] (3) The third parameter; where the third parameter is used to indicate that the dataset information is based on measurement or prediction.

[0190] Specifically, the third parameter indicates whether the tags to be reported by the terminal device are based on measured channel information or predicted channel information. For example, when the third parameter is configured to 0, N groups of tags report channel information measured in each of K consecutive time slots; when the third parameter is configured to 1, N groups of tags report channel information predicted after measurement in each of K consecutive time slots.

[0191] Optionally, the first configuration information may not include the third parameter, which is indicated by the terminal device through the first reporting information. For example, the third parameter may indicate the same information as the first indication information in the first reporting information. When the first configuration information includes configuration information with a third parameter, the first reporting information does not need to include the third parameter; when the first configuration information does not include configuration information with a third parameter, the first reporting information may include the first indication information.

[0192] It should be noted that the first configuration information may include one or more of the information E to H mentioned above. That is, the first configuration information may include information E, F, G, or H, or it may include information E and F, or information E, F, and G, or information E, F, G, and H, etc. In practical applications, the content of the information carried in the first configuration information can be determined according to system conventions, protocol conventions, or scenario requirements. For the sake of brevity, all possible situations will not be listed here.

[0193] In some embodiments, the data collection method may further include: the terminal device sending first capability information to the network device.

[0194] Accordingly, in some embodiments, the data collection method may further include: the network device receiving first capability information from the terminal device.

[0195] Optionally, the first capability information can be used to indicate capabilities related to measurement or information reporting (data collection).

[0196] Optionally, the first capability information is used to indicate one or more of the following:

[0197] Capability parameters related to channel measurements;

[0198] Capability parameters related to channel information reporting;

[0199] Does the terminal device support reporting the first channel information based on the first codebook?

[0200] The terminal device supports reporting the maximum time range corresponding to the first channel information simultaneously.

[0201] For example, the first capability information is used to indicate capability parameters related to channel measurements.

[0202] For example, the first capability information indicates how many ports of channel measurement a terminal device can support at most on a downlink CC / BWP. Specifically, if the terminal device reports this capability parameter as 32, it means that the UE can support a maximum of 32 ports of channel measurement on a downlink CC / BWP.

[0203] For example, the first capability information indicates the maximum duration of channel measurement that a terminal device can support on a downlink CC / BWP. This duration can be the number of time slots for channel measurement and reporting. Specifically, if the terminal device reports this capability parameter as 10, it means that the terminal device can support a maximum of 10 time slots for channel measurement on a downlink CC / BWP.

[0204] For example, the first capability information indicates how many downlink CC / BWP channel measurements the terminal device supports simultaneously. Specifically, if the terminal device reports this capability parameter as 16, it means that the terminal device supports 16 downlink CC / BWP channel measurements simultaneously.

[0205] For example, the first capability information is used to indicate capability parameters related to channel information reporting.

[0206] For example, the first capability information indicates how many ports of channel information reporting a terminal device can support at most on a downlink CC / BWP. Specifically, if the terminal device reports this capability parameter as 32, it means that the UE can support a maximum of 32 ports of channel information reporting on a downlink CC / BWP.

[0207] For example, the first capability information indicates the maximum duration for which a terminal device can report channel information on a downlink CC / BWP. This duration can be the number of time slots for channel measurement and reporting. Specifically, if the terminal device reports this capability parameter as 10, it means that the terminal device can support a maximum of 10 time slots for channel information reporting on a downlink CC / BWP.

[0208] For example, the first capability information indicates how many downlink CC / BWP channel information reports the terminal device can simultaneously support. Specifically, if the terminal device reports this capability parameter as 16, it means that the terminal device can simultaneously support 16 downlink CC / BWP channel information reports.

[0209] For example, the first capability information is used to indicate whether the terminal device supports reporting first channel information based on the first codebook. For instance, if the first codebook is a Doppler-eTypeII codebook, the terminal device can report channel information that supports reporting based on the Doppler-eTypeII codebook.

[0210] For example, the first capability information is used to indicate the maximum time range corresponding to the simultaneous reporting of the first channel information by the terminal device. For example, the first capability information is used to indicate the maximum number of time slots of channel information that the terminal device can simultaneously report. For instance, if the terminal device reports this capability parameter as 4, it means that the terminal device supports reporting channel information from a maximum of 4 time slots using the first codebook.

[0211] For example, the first capability information can also be used to indicate two or more capabilities; for instance, the first capability information can be used to indicate all of the above four capabilities. In practical applications, the content indicated in the first capability information can be determined according to system conventions, protocol conventions, or scenario requirements. For the sake of brevity, all possible situations will not be listed here.

[0212] To facilitate understanding of the above technical solutions, an example of a data collection method is provided below, using the first codebook including the Doppler-eTypeII codebook as an example. Figure 9 is a schematic flowchart of this example. As shown in Figure 9, the data collection method includes the following four steps:

[0213] Step 1: User (terminal device) reports terminal capabilities. Different users have different data collection capabilities, therefore users need to report their ability to collect data for the network. This capability includes, but is not limited to:

[0214] ● The maximum number of ports that can be supported for channel measurement and reporting on a single downlink CC / BWP. For example, if the UE reports this capability parameter as 32, it means that the UE can support a maximum of 32 ports for channel measurement and reporting on a single downlink CC / BWP.

[0215] ● The maximum duration of channel measurement and reporting capability supported on a downlink CC / BWP. For example, the duration can be the number of time slots for channel measurement and reporting. If the UE reports this capability parameter as 10, it means that the UE can support a maximum of 10 time slots for channel measurement and reporting on a downlink CC / BWP.

[0216] ● The ability to simultaneously support channel measurement and reporting on a number of downlink CC / BWPs. For example, if the UE reports this capability parameter as 16, it means that the UE simultaneously supports channel measurement and reporting on 16 downlink CC / BWPs.

[0217] ●Whether it supports CSI feedback based on the Doppler-eTypeII codebook, and the maximum number of times CSI can be reported simultaneously. For example, if the UE reports support for Doppler-eTypeII CSI feedback, and the maximum reporting capability value is 4, it means that the UE supports reporting CSI using the Doppler-eTypeII codebook at a maximum of 4 times.

[0218] Step 2: The network device sends RRC configuration information.

[0219] Specifically, based on the capabilities reported by the UE, the network configures one or more measurement and reporting resources on the downlink CC / BWP for the UE. The number of configured measurement and reporting resources does not exceed the capability parameters reported by the UE. The RRC also includes the following configuration information:

[0220] ● Configure the codebook type (codebookType) as Doppler-eTypeII, and configure the parameters of Doppler-eTypeII.

[0221] The parameter configuration can be used to configure existing parameter combinations of the current protocol, or, to obtain more accurate tags for data collection, a higher configuration can be selected, corresponding to different L,p values. ν Combinations of β. For example, one possible configuration parameter combination is L=8. Another possible configuration parameter combination is L=10, Etc. This is merely an example; the higher-precision Doppler-eTypeII codebook and the corresponding parameter configuration combinations are all included in the RRC configuration information and are within the scope of the embodiments of this application.

[0222] ● Configure data collection parameters, including at least:

[0223] 1) The first parameter N is the number of tags that the user should report. The configuration method for the first parameter N is, for example, that it can be directly configured by RRC, such as N=20 or N=50;

[0224] A first parameter set can be configured by RRC, for example, N∈{20,50,100}, and then dynamically activated by MAC CE or DCI; or a first parameter range or set can be configured by RRC, for example, N≥50, and then a first parameter set can be configured by MAC CE, for example, N∈{50,100}, and then dynamically activated by DCI.

[0225] It can be configured without explicit configuration. In this case, the number of tags reported by the user is determined by the downlink activation signaling and / or deactivation signaling of the base station, or by the user's uplink request signaling.

[0226] 2) The second parameter K is the number of consecutive time slots included in each group of tags. The configuration of the second parameter K is, for example:

[0227] It can be configured without explicit configuration. In this case, K is equal to the value of N4 by default. N4∈{1,2,4,8} is a parameter of the Doppler-eTypeII codebook configured by RRC, which is used to determine the number of consecutive time slots included in a single CSI report.

[0228] Specific values ​​can be configured directly by RRC, for example, K=8 or K=16;

[0229] A second set of parameters can be configured by RRC, for example, K∈{4,8,16}, and dynamically activated by MAC CE or DCI;

[0230] A second parameter range or set can be configured by RRC, for example, K≥16, and a second parameter set can be indicated by MAC CE, for example, K∈{16,32}, and then dynamically activated by DCI.

[0231] Generally, the second parameter K = mN4, where m is a positive integer. This configuration method is for users to combine m Doppler-eTypeII codebook reports into a set of labeled samples.

[0232] 3) A third parameter, which indicates whether the user-reported tags are based on measured CSI or predicted CSI. For example, when the third parameter is configured to 0, the N tags contain CSI reports for each group of K consecutive measurement time slots; when the third parameter is configured to 1, the N tags contain CSI reports for each group of K consecutive predicted time slots. Optionally, the third parameter can be omitted in the RRC and indicated by the user through the first reporting information.

[0233] Step 3: The network device sends the first reference signal.

[0234] Optionally, the first reference signal is transmitted on the RRC configuration resources in step 2, that is, on the configured downlink CC / BWP and on the configured port. The first reference signal generally refers to the downlink CSI-RS. In this case, step 3 can reuse existing CSI-RS configuration and transmission methods and does not need to be specifically designed for this application embodiment; or, the first reference signal is a downlink reference signal specifically used for downlink channel measurement and data collection in this application embodiment. The first reference signal can be periodic, aperiodic, or semi-persistent.

[0235] Different first reference signal transmission modes will have different signaling indications.

[0236] Step 4: The user sends the first reporting information to the base station. The first reporting information includes at least:

[0237] The dataset information includes N groups of labels, each group containing channel information for K consecutive time slots. This channel information, according to the third parameter in the RRC, can be channel information measured based on a first reference signal, or channel information measured and predicted based on the first reference signal. The quantization method for each group of labels is as follows: using the Doppler-eTypeII codebook, and selecting the corresponding parameter configuration combination for quantization according to the RRC configuration information. Based on the second parameter K configured in the RRC and the N4 parameter configuration of the Doppler-eTypeII codebook, the K consecutive time slot channel information for each group of labels is arranged in time sequence, including m groups of Doppler-eTypeII reports, where K = mN4.

[0238] The label type indication information indicates whether the label reported by the user is based on measured CSI or predicted CSI. If the user receives an indication of a third parameter in the RRC, they do not need to report this label type indication information; if the RRC does not indicate a third parameter, they must report this label type indication information. The prediction method can be non-AI / ML, such as autoregressive algorithms or Kalman filtering algorithms; it can also be a prediction algorithm based on an AI / ML model, depending on the user's implementation.

[0239] Dataset quality information, including downlink channel quality measurements such as CQI, SNR, SINR, RSRP, and RSSI, is used to describe the dataset quality. The network can select high-quality samples from the datasets uploaded by different users for model training when there are enough samples available.

[0240] Additional auxiliary information: Relevant information and characteristics used to describe and indicate the dataset and the dataset acquisition process, which may include, but are not limited to, the following:

[0241] • Data acquisition area and location information: This describes the area and location where the UE acquires data, such as different cells (identified by cell ID or PCI, etc.), different sectors within a cell, or different scenarios within a cell (outdoor, indoor, etc.).

[0242] • User-related information: Auxiliary information used to describe the state of the UE, such as user movement speed, user geographical location information, user posture information, etc.;

[0243] Dataset identification information: A set of identification information related to user-side additional condition information (e.g., the user's antenna spacing, antenna arrangement, beam direction, or the CSI prediction algorithm used is based on non-AI / ML or AI / ML, etc.). The user reports a set of identification information (e.g., associated ID) to associate with the user-side additional condition information.

[0244] The first type of information to be reported can be physical layer signaling, such as UCI, via PUCCH or PUSCH. The advantage of physical layer signaling is that the signaling latency is low, which can be used for model performance monitoring. Alternatively, it can be reported via higher layer signaling, such as MDT. The advantage of higher layer signaling is that the reporting capacity is large, which can be used for model training.

[0245] The above example introduces the Doppler-eTypeII codebook containing temporal correlation as a quantization method for reporting high-precision label information. This allows the reported label information to utilize temporal correlation information, further improving the label reporting accuracy, reducing label reporting overhead, and making it better suited for network-side training or performance monitoring of models containing temporal correlation information.

[0246] In practical applications, data collection can be periodic, semi-continuous, or aperiodic. Below are some examples of periodic data collection methods.

[0247] In some embodiments, the first configuration information is used to configure periodic measurement resources; the first configuration information includes configuration information of a first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter.

[0248] For example, the network device configures periodic measurement resources via RRC signaling (first configuration information) and sends a first reference signal on those measurement resources. In this case, the RRC signaling needs to explicitly configure the value of the first parameter N. Optionally, the second parameter K does not need to be configured; the network device can combine tags according to the tag order reported by the terminal device. Optionally, the RRC signaling can also indicate a third parameter.

[0249] In some embodiments, the terminal device sends first reporting information to the network device, including: the terminal device periodically acquires tags and reports the tags through higher-layer signaling based on periodic measurement resources, until the number of tags reaches N groups.

[0250] Accordingly, in some embodiments, the network device receives first reported information from the terminal device, including: the network device receiving tags reported by the terminal device through higher-layer signaling until the number of tags reaches N groups; wherein the tags are acquired by the terminal device based on periodic measurement resources.

[0251] For example, if higher-layer signaling is used to report dataset information (e.g., MDT reporting), the terminal device can periodically receive a first reference signal and begin measurement and tag determination from the moment the first first reference signal is received. This tag, indicated by third information in the RRC signaling or according to user implementation, can correspond to a measured CSI or a predicted CSI. After determining the tag, the terminal device can store it and transmit it on the PUSCH via higher-layer signaling. The process stops when the number of reported tags reaches the first parameter N.

[0252] In some embodiments, the periodic measurement resources include measurement resources based on a first period. The terminal device sends first reporting information to the network device, including: the terminal device acquiring a tag based on the measurement resources based on the first period; and the terminal device reporting the tag via physical layer signaling based on a second period.

[0253] Accordingly, the network device receives first reported information from the terminal device, including: the network device receives a tag reported by the terminal device through physical layer signaling based on the second cycle; wherein the tag is obtained by the terminal device based on the measurement resources of the first cycle.

[0254] For example, if physical layer signaling (e.g., UCI) is used to report data collection information, the transmission period of the first reference signal configured by the network device is a first period T1, and the period for reporting data collection information by physical layer signaling can be a second period T2, which can be different from T1.

[0255] In some embodiments, the first configuration information may further include configuration information for a first period and / or configuration information for a second period.

[0256] For example, the first configuration information includes measurement resources based on the first period, that is, it includes configuration information of the first period; the first configuration information may also include configuration information of the second period, which may include specific values ​​of the second period, or parameters related to the second period.

[0257] For example, the first configuration information includes configuration information for a first cycle; the second cycle may be the default.

[0258] In some embodiments, the second period is related to the first period, and the second period is related to the fourth parameter X of the first codebook.

[0259] For example, the second period is related to the product of the first period and the fourth parameter of the first codebook. For example, the second period is a positive integer multiple of this product. For example, T2 = XT1.

[0260] For example, the second period T2 can be indicated in the following ways:

[0261] (1) Without additional instructions, the second period T2 = XT1 is assumed to be in this case. That is, after the user measures X first reference signals, the tag is reported based on the configuration of the first codebook. The reported tag can be the measurement CSI of X consecutive first reference signals, or the predicted CSI of X consecutive future times based on multiple past times.

[0262] (2) Configure the second period T2 = nXT1, where n is an integer greater than 1. In this case, the first configuration information can directly configure the second period T2, or configure the coefficient n. After the terminal device measures nX first reference signals, it reports them in n groups according to time sequence. The reported tags can be the measured CSI of nX consecutive first reference signals, or the predicted CSI of nX consecutive first reference signals predicted based on multiple past time points.

[0263] The aforementioned periodic data collection methods can support reporting via PUCCH or PUSCH to increase reporting capacity.

[0264] The following provides some examples of semi-persistent data collection methods.

[0265] In some embodiments, the first configuration information is used to configure semi-continuous measurement resources; the first configuration information includes configuration information of a first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter, or the value range of the first parameter, or the set of the first parameter.

[0266] For example, the network device configures a semi-persistent measurement resource via RRC signaling (first configuration information) and sends a first reference signal on that measurement resource. In this case, the RRC signaling needs to configure the value of the first parameter N, or the RRC signaling configures the value range or set of the first parameter N, with the specific first parameter activated by the MAC CE or DCI. Optionally, the second parameter K does not need to be configured; the network device can combine tags according to the tag order reported by the terminal device. Optionally, the RRC signaling can also indicate a third parameter.

[0267] In some embodiments, the data collection method may further include: a network device sending an activation indication to a terminal device; wherein the activation indication is used to trigger the terminal device to periodically acquire tags and report the tags via higher-layer signaling based on semi-persistent measurement resources until the number of tags reaches N sets.

[0268] Accordingly, in some embodiments, the terminal device sends first reporting information to the network device, including: after receiving the activation indication of the semi-persistent measurement resources, the terminal device periodically acquires tags and reports the tags through higher-layer signaling based on the semi-persistent measurement resources until the number of tags reaches N groups.

[0269] Alternatively, the activation instruction can be issued via MAC CE or DCI.

[0270] For example, if higher-layer signaling is used to report dataset information (e.g., MDT reporting), the terminal device can periodically receive a first reference signal and report it after receiving a MAC CE activation or DCI signaling dynamic indication. When the number of reported tags reaches the first parameter N, or when a MAC CE or DCI deactivation indication is received, the terminal device stops reporting tags.

[0271] In some embodiments, the data collection method may further include: a network device sending an activation indication to a terminal device; wherein the activation indication is used to trigger the terminal device to periodically acquire tags based on a first period and semi-persistent measurement resources, and to report the tags via physical layer signaling based on a second period.

[0272] Accordingly, in some embodiments, the terminal device sends first reporting information to the network device, including: after receiving an activation indication of semi-persistent measurement resources, the terminal device acquires a tag based on a first period and the semi-persistent measurement resources; the terminal device reports the tag through physical layer signaling based on a second period.

[0273] For example, if physical layer signaling (e.g., UCI) is used to report data collection information, the transmission period of the first reference signal configured by the network device is a first period T1, and the period for reporting data collection information by physical layer signaling can be a second period T2, which can be different from T1.

[0274] In some embodiments, the first configuration information may further include configuration information for a first period and / or configuration information for a second period.

[0275] In some embodiments, the second period is related to the first period and is related to the fourth parameter of the first codebook.

[0276] In some embodiments, the second period is related to the product of the first period and a fourth parameter of the first codebook. For example, the second period is a positive integer multiple of the product.

[0277] Optionally, if tags are transmitted on the PUCCH, the first period T1 of the first reference signal and the second period T2 of tag reporting are pre-configured by the first configuration information and activated and deactivated by the MAC CE. If tags are transmitted on the PUSCH, the configuration of the first period T1 of the first reference signal and the second period T2 of tag reporting is dynamically indicated for activation or deactivation via DCI signaling. The configuration and indication of T1 and T2 are the same as in the aforementioned periodic data collection method embodiments, and can be specifically set with reference to the aforementioned embodiments. When the number of reported tags reaches the first parameter N, or when a deactivation indication is received from the MAC CE or DCI, the terminal device stops reporting tags.

[0278] The following provides an example of a non-periodic data collection method.

[0279] In some embodiments, the first configuration information is used to configure aperiodic measurement resources; wherein, the aperiodic measurement resources include N sets of measurement resources; each of the N sets of measurement resources includes K time slots; the K time slots are used by the terminal device to acquire a set of tags.

[0280] For example, for non-periodic data collection, the network device configures the measurement resources and reporting configuration of the first reference signal via RRC signaling (first configuration information), and transmits the first reference signal on the measurement resources. The RRC signaling can pre-configure the value of the first parameter N and the value of the second parameter K, or it can configure the value range / set of the first parameter N and the value range / set of the second parameter K, activate some of the configurations via MAC layer signaling, and then dynamically trigger them via DCI. Optionally, the RRC signaling can also indicate a third parameter.

[0281] For aperiodic first reference signal measurements, network devices will aperiodically schedule N sets of measurement resources for the first reference signals. Each set of measurement resources for the first reference signal includes K consecutive first reference signal measurement time slots. The terminal device obtains and reports K measurement CSIs based on the first reference signals in the measurement resource set, or predicts and reports K CSIs based on the K measurements. The first reported information can be reported via higher layers (e.g., MDT signaling) or UCI through PUSCH.

[0282] In summary, the data collection method proposed in this application introduces a first codebook related to time-domain features as a quantification method for reporting high-precision label information. This allows the reported label information to utilize time-domain features, improving the accuracy of label reporting, reducing label reporting overhead, and enabling better use by the network side for training or performance monitoring of models containing time-domain information.

[0283] Figure 10 is a schematic block diagram of a terminal device 1000 according to an embodiment of the present application. The terminal device 1000 may include:

[0284] The first communication module 1010 is used to send the first reporting information to the network device;

[0285] The first reported information includes dataset information, which includes N sets of labels. Each set of labels in the N sets includes first channel information for K time slots. The first channel information includes feature information corresponding to the second channel information obtained based on the first codebook. The time-domain features of the first codebook and the second channel information are related. N is an integer greater than or equal to 1, and K is an integer greater than or equal to 1.

[0286] In some embodiments, the first codebook is used to obtain feature information based on the temporal correlation of second channel information across multiple time slots.

[0287] In some embodiments, the first codebook includes the Doppler-eTypeII codebook.

[0288] In some embodiments, the feature information includes feature vectors.

[0289] In some embodiments, the first communication module 1010 is further configured to:

[0290] Receive a first reference signal from a network device; wherein the first reference signal is used by the terminal device to obtain second channel information.

[0291] In some embodiments, the second channel information is obtained by the terminal device based on the measurement of the first reference signal, or by the terminal device based on the measurement of the first reference signal and prediction processing.

[0292] In some embodiments, the first reported information also includes one or more of the following:

[0293] First indication information; wherein, the first indication information is used to indicate that the dataset information is obtained based on measurement or prediction;

[0294] Quality information of the dataset;

[0295] First auxiliary information; wherein, the first auxiliary information is used to indicate information related to the data set information collection process;

[0296] Identification information for dataset information; where the identification information is used to distinguish dataset information collected under different user configurations.

[0297] In some embodiments, the quality information includes one or more of CQI, SNR, SINR, RSRP, and RSSI.

[0298] In some embodiments, the first auxiliary information includes one or more of the following: area information, location information, and status information of the terminal device during the data collection process.

[0299] In some embodiments, the first communication module 1010 is further configured to:

[0300] Receive first configuration information from the network device; wherein the first configuration information includes one or more of the following:

[0301] The first reported information includes the configuration information of the resources being reported;

[0302] Configuration information of measurement resources for the first reference signal;

[0303] Configuration information for the first codebook;

[0304] Configuration information for the parameters of the dataset.

[0305] In some embodiments, the configuration information of the first codebook includes one or more of the following:

[0306] Second instruction information; wherein, the second instruction information is used by the terminal device to determine that the first codebook is used;

[0307] Configuration information for the parameters of the first codebook.

[0308] In some embodiments, the parameters of the dataset information include one or more of the following:

[0309] The first parameter; where the first parameter is the number of labels N in the dataset information;

[0310] The second parameter; where the second parameter is the number of time slots K corresponding to each group of tags;

[0311] The third parameter indicates whether the dataset information is based on measurement or prediction.

[0312] In some embodiments, the configuration information of the first parameter is used to indicate the value of the first parameter, the range of values ​​of the first parameter, or the set of first parameters;

[0313] The range of values ​​for the first parameter is used by the terminal device to determine the first parameter within the range based on MAC CE and / or DCI.

[0314] The first parameter set is used by the terminal device to determine the first parameter based on the MAC CE and / or DCI in the first parameter set.

[0315] In some embodiments, the configuration information of the second parameter is used to indicate the value of the second parameter, the range of values ​​of the second parameter, or the set of second parameters;

[0316] The range of values ​​for the second parameter is used by the terminal device to determine the second parameter within the range based on MAC CE and / or DCI.

[0317] The second parameter set is used by the terminal device to determine the second parameter based on the MAC CE and / or DCI.

[0318] In some embodiments, K is related to a fourth parameter of the first codebook; the fourth parameter is the number of time slots corresponding to the channel information processed based on the first codebook.

[0319] In some embodiments, K is a positive integer multiple of the fourth parameter or K is equal to the fourth parameter.

[0320] In some embodiments, the first configuration information is used to configure periodic measurement resources; the first configuration information includes configuration information of a first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter.

[0321] In some embodiments, as shown in FIG11, the terminal device 1000 includes a first processing module 1110.

[0322] In one implementation, the first processing module 1110 is used to periodically acquire tags based on periodic measurement resources. Correspondingly, the first communication module 1010 is used to report the tags via higher-layer signaling until the number of tags reaches N groups.

[0323] In some embodiments, the periodic measurement resources include measurement resources based on a first period. The first processing module 1110 is configured to acquire tags based on the measurement resources based on the first period. The first communication module 1010 is configured to report tags via physical layer signaling based on a second period.

[0324] In some embodiments, the first configuration information is used to configure semi-continuous measurement resources; the first configuration information includes configuration information of a first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter, or the value range of the first parameter, or the set of the first parameter.

[0325] In some embodiments, as shown in FIG12, the terminal device 1000 includes a second processing module 1210, which is used to periodically acquire tags based on the semi-persistent measurement resources after receiving an activation indication of the semi-persistent measurement resources. A first communication module 1010 is used to report tags via higher-layer signaling until the number of tags reaches N groups.

[0326] In some embodiments, as shown in FIG13, the terminal device 1000 includes a third processing module 1310, which is used to acquire a tag based on a first period and the semi-persistent measurement resource after receiving an activation indication of the semi-persistent measurement resource. A first communication module 1010 is used to report the tag via physical layer signaling based on a second period.

[0327] In some embodiments, the first configuration information may further include configuration information for a first period and / or configuration information for a second period.

[0328] In some embodiments, the second period is related to the first period and is related to the fourth parameter of the first codebook.

[0329] In some embodiments, the second period is related to the product of the first period and a fourth parameter of the first codebook.

[0330] In some embodiments, the first configuration information is used to configure aperiodic measurement resources; wherein, the aperiodic measurement resources include N sets of measurement resources; each of the N sets of measurement resources includes K time slots; the K time slots are used by the terminal device to acquire a set of tags.

[0331] In some embodiments, the first communication module 1010 is further configured to:

[0332] Send first capability information to the network device; wherein the first capability information is used to indicate one or more of the following:

[0333] Capability parameters related to channel measurements;

[0334] Capability parameters related to channel information reporting;

[0335] Does the terminal device support reporting first channel information based on the first codebook?

[0336] The terminal device supports reporting the maximum time range corresponding to the first channel information simultaneously.

[0337] The terminal device 1000 of this application embodiment can implement the corresponding functions of the terminal device in the foregoing method embodiments. The processes, functions, implementation methods, and beneficial effects of each module (sub-module, unit, or component, etc.) in the terminal device 1000 can be found in the corresponding descriptions in the above method embodiments, and will not be repeated here. It should be noted that the functions described for each module (sub-module, unit, or component, etc.) in the terminal device 1000 of the application embodiment can be implemented by different modules (sub-modules, units, or components, etc.) or by the same module (sub-module, unit, or component, etc.).

[0338] Figure 14 is a schematic block diagram of a network device 1400 according to an embodiment of the present application. The network device 1400 may include:

[0339] The second communication module 1410 is used to receive first reported information from the terminal device;

[0340] The first reported information includes dataset information, which includes N sets of labels. Each set of labels in the N sets includes first channel information for K time slots. The first channel information includes feature information corresponding to the second channel information obtained based on the first codebook. The time-domain features of the first codebook and the second channel information are related. N is an integer greater than or equal to 1, and K is an integer greater than or equal to 1.

[0341] In one implementation, the first codebook is used to obtain feature information based on the temporal correlation of second channel information across multiple time slots.

[0342] In one implementation, the first codebook includes the Doppler-eTypeII codebook.

[0343] In one implementation, the feature information includes a feature vector.

[0344] In one embodiment, the second communication module 1410 is further configured to:

[0345] A first reference signal is sent to the terminal device; wherein the first reference signal is used by the terminal device to obtain the second channel information.

[0346] In one implementation, the first reported information further includes one or more of the following:

[0347] First indication information; wherein, the first indication information is used to indicate that the dataset information is obtained based on measurement or prediction;

[0348] Quality information of the dataset;

[0349] First auxiliary information; wherein, the first auxiliary information is used to indicate information related to the data set information collection process;

[0350] Identification information for dataset information; where the identification information is used to distinguish dataset information collected under different user configurations.

[0351] In one implementation, the quality information includes one or more of CQI, SNR, SINR, reference signal received power RSRP, and RSSI.

[0352] In one implementation, the first auxiliary information includes one or more of the following: area information, location information, and status information of the terminal device during the data collection process.

[0353] In one embodiment, the second communication module 1410 is further configured to:

[0354] Send first configuration information to the terminal device; wherein the first configuration information includes one or more of the following:

[0355] The first reported information includes the configuration information of the resources being reported;

[0356] Configuration information of measurement resources for the first reference signal;

[0357] Configuration information for the first codebook;

[0358] Configuration information for the parameters of the dataset.

[0359] In one implementation, the configuration information of the first codebook includes one or more of the following:

[0360] Second instruction information; wherein, the second instruction information is used by the terminal device to determine that the first codebook is used;

[0361] Configuration information for the parameters of the first codebook.

[0362] In one implementation, the parameters of the dataset information include one or more of the following:

[0363] The first parameter; where the first parameter is the number of labels N in the dataset information;

[0364] The second parameter; where the second parameter is the number of time slots K corresponding to each group of tags;

[0365] The third parameter indicates whether the dataset information is based on measurement or prediction.

[0366] In one implementation, the configuration information of the first parameter is used to indicate the value of the first parameter, or the range of values ​​of the first parameter, or the set of the first parameters;

[0367] The range of values ​​for the first parameter is used by the terminal device to determine the first parameter within the range based on MAC CE and / or DCI.

[0368] The first parameter set is used by the terminal device to determine the first parameter based on the MAC CE and / or DCI in the first parameter set.

[0369] In one implementation, the configuration information of the second parameter is used to indicate the value of the second parameter, or the range of values ​​of the second parameter, or the set of the second parameters;

[0370] The range of values ​​for the second parameter is used by the terminal device to determine the second parameter within the range based on MAC CE and / or DCI.

[0371] The second parameter set is used by the terminal device to determine the second parameter based on the MAC CE and / or DCI.

[0372] In one implementation, K is related to a fourth parameter of the first codebook; the fourth parameter is the number of time slots corresponding to the channel information processed based on the first codebook.

[0373] In one implementation, K is a positive integer multiple of the fourth parameter or K is equal to the fourth parameter.

[0374] In one implementation, the first configuration information is used to configure periodic measurement resources; the first configuration information includes configuration information of a first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter.

[0375] In one embodiment, the second communication module 1410 is further configured to:

[0376] The receiving terminal device reports tags via higher-layer signaling until the number of tags reaches N sets; the tags are acquired by the terminal device based on periodic measurement resources.

[0377] In one implementation, the periodic measurement resources include measurement resources based on a first period;

[0378] The second communication module 1410 is also used for:

[0379] Based on the second cycle, the receiving terminal device reports tags via physical layer signaling; wherein, the tags are acquired by the terminal device based on the measurement resources of the first cycle.

[0380] In one implementation, the first configuration information is used to configure semi-continuous measurement resources; the first configuration information includes configuration information of a first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter, or the value range of the first parameter, or the set of the first parameter.

[0381] In one embodiment, the second communication module 1410 is further configured to:

[0382] Send an activation instruction to the terminal device; wherein the activation instruction is used to trigger the terminal device to periodically acquire tags and report the tags through higher-layer signaling based on semi-persistent measurement resources until the number of tags reaches N groups.

[0383] In one embodiment, the second communication module 1410 is further configured to:

[0384] Send an activation instruction to the terminal device; wherein the activation instruction is used to trigger the terminal device to periodically acquire tags based on the first period and semi-continuous measurement resources, and to report the tags through physical layer signaling based on the second period.

[0385] In one implementation, the first configuration information further includes configuration information for a first period and / or configuration information for a second period.

[0386] In one implementation, the second period is related to the first period, and the second period is related to the fourth parameter of the first codebook.

[0387] In one implementation, the second period is related to the product of the first period and the fourth parameter of the first codebook.

[0388] In one implementation, the first configuration information is used to configure aperiodic measurement resources; wherein, the aperiodic measurement resources include N sets of measurement resources; each of the N sets of measurement resources includes K time slots; the K time slots are used by the terminal device to acquire a set of tags.

[0389] In one embodiment, the second communication module 1410 is further configured to:

[0390] Receive first capability information from the terminal device; wherein the first capability information is used to indicate one or more of the following:

[0391] Capability parameters related to channel measurements;

[0392] Capability parameters related to channel information reporting;

[0393] Does the terminal device support reporting first channel information based on the first codebook?

[0394] The terminal device supports reporting the maximum time range corresponding to the first channel information simultaneously.

[0395] The network device 1400 of this application embodiment can realize the corresponding functions of the network device in the foregoing method embodiments. The processes, functions, implementation methods, and beneficial effects of each module (submodule, unit, or component, etc.) in the network device 1400 can be found in the corresponding descriptions in the above method embodiments, and will not be repeated here. It should be noted that the functions described for each module (submodule, unit, or component, etc.) in the network device 1400 of the application embodiment can be implemented by different modules (submodules, units, or components, etc.) or by the same module (submodule, unit, or component, etc.).

[0396] Figure 15 is a schematic structural diagram of a communication device 1500 according to an embodiment of this application. The communication device 1500 includes a processor 1510, which can call and run computer programs from memory to enable the communication device 1500 to implement the methods in the embodiments of this application.

[0397] In one embodiment, the communication device 1500 may further include a memory 1520. The processor 1510 can retrieve and run computer programs from the memory 1520 to enable the communication device 1500 to implement the methods described in the embodiments of this application.

[0398] The memory 1520 can be a separate device independent of the processor 1510, or it can be integrated into the processor 1510.

[0399] In one embodiment, the communication device 1500 may further include a transceiver 1530, and the processor 1510 may control the transceiver 1530 to communicate with other devices. Specifically, it may send information or data to other devices or receive information or data sent by other devices.

[0400] The transceiver 1530 may include a transmitter and a receiver. The transceiver 1530 may further include an antenna, and the number of antennas may be one or more.

[0401] In one embodiment, the communication device 1500 may be a network device in the embodiments of this application, and the communication device 1500 may implement the corresponding processes implemented by the network device in the various methods of the embodiments of this application. For the sake of brevity, it will not be described in detail here.

[0402] In one embodiment, the communication device 1500 may be a terminal device in the embodiments of this application, and the communication device 1500 may implement the corresponding processes implemented by the terminal device in the various methods of the embodiments of this application. For the sake of brevity, it will not be described in detail here.

[0403] Figure 16 is a schematic structural diagram of a chip 1600 according to an embodiment of this application. The chip 1600 includes a processor 1610, which can call and run computer programs from memory to implement the methods in the embodiments of this application.

[0404] In one embodiment, chip 1600 may further include memory 1620. Processor 1610 can retrieve and run computer programs from memory 1620 to implement the methods executed by a terminal device or network device in this embodiment.

[0405] The memory 1620 can be a separate device independent of the processor 1610, or it can be integrated into the processor 1610.

[0406] In one embodiment, the chip 1600 may further include an input interface 1630. The processor 1610 can control the input interface 1630 to communicate with other devices or chips; specifically, it can acquire information or data sent by other devices or chips.

[0407] In one embodiment, the chip 1600 may further include an output interface 1640. The processor 1610 can control the output interface 1640 to communicate with other devices or chips; specifically, it can output information or data to other devices or chips.

[0408] In one implementation, the chip can be applied to the network device in the embodiments of this application, and the chip can implement the corresponding processes implemented by the network device in the various methods of the embodiments of this application. For the sake of brevity, it will not be described in detail here.

[0409] In one embodiment, the chip can be applied to the terminal device in the embodiments of this application, and the chip can implement the corresponding processes implemented by the terminal device in the various methods of the embodiments of this application. For the sake of brevity, it will not be described in detail here.

[0410] The chips used in network equipment and terminal equipment can be the same chip or different chips.

[0411] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0412] The processors mentioned above can be general-purpose processors, digital signal processors (DSPs), field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), or other programmable logic devices, transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processors mentioned above can be microprocessors or any conventional processor.

[0413] The aforementioned memory can be volatile memory or non-volatile memory, or a combination of both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM).

[0414] It should be understood that the above-described memory is exemplary and not a limiting description. For example, the memory in the embodiments of this application may also be static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DR RAM), etc. That is to say, the memory in the embodiments of this application is intended to include, but is not limited to, these and any other suitable types of memory.

[0415] Figure 17 is a schematic block diagram of a communication system 1700 according to an embodiment of this application. The communication system 1700 includes a terminal device 1710 and a network device 1720.

[0416] Terminal device 1710 sends first reporting information to network device 1720; wherein, the first reporting information includes dataset information, the dataset information includes N sets of tags, each set of tags in the N sets of tags includes first channel information of K time slots; the first channel information includes feature information corresponding to the second channel information obtained based on the first codebook; the first codebook is related to the time domain features of the second channel information; wherein, N is an integer greater than or equal to 1, and K is an integer greater than or equal to 1.

[0417] Network device 1720 receives the first reported information from terminal device 1710.

[0418] Specifically, the terminal device 1710 can be used to implement the corresponding functions implemented by the terminal device in the above method, and the network device 1720 can be used to implement the corresponding functions implemented by the network device in the above method. For the sake of brevity, further details are omitted here.

[0419] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. This computer program product includes one or more computer instructions. When these computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

[0420] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0421] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0422] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A data collection method, comprising: The terminal device sends its first reporting information to the network device; Wherein, the first reported information includes dataset information, the dataset information includes N sets of tags, each set of tags in the N sets of tags includes first channel information of K time slots; the first channel information includes feature information corresponding to the second channel information obtained based on the first codebook; the first codebook is related to the time domain features of the second channel information; wherein, N is an integer greater than or equal to 1, and K is an integer greater than or equal to 1.

2. The method according to claim 1, wherein, The first codebook is used to obtain the feature information based on the temporal correlation of the second channel information in multiple time slots.

3. The method according to claim 1 or 2, wherein, The first codebook includes the Doppler-eTypeII codebook.

4. The method according to any one of claims 1-3, wherein, The feature information includes feature vectors.

5. The method according to any one of claims 1-4, wherein, The method further includes: The terminal device receives a first reference signal from the network device; wherein the first reference signal is used by the terminal device to obtain the second channel information.

6. The method according to claim 5, wherein, The second channel information is obtained by the terminal device based on the measurement of the first reference signal, or by the terminal device based on the measurement and prediction processing of the first reference signal.

7. The method according to any one of claims 1-6, wherein, The first reported information also includes one or more of the following: First indication information; wherein, the first indication information is used to indicate that the dataset information is obtained based on measurement or prediction; The quality information of the dataset; First auxiliary information; wherein, the first auxiliary information is used to indicate information related to the collection process of the dataset information; The identification information of the dataset information; wherein, the identification information is used to distinguish the dataset information collected under different user configurations.

8. The method according to claim 7, wherein, The quality information includes one or more of the following: Channel Quality Indicator (CQI), Signal-to-Noise Ratio (SNR), Signal-to-Interference Plus-Noise Ratio (SINR), Reference Signal Received Power (RSRP), and Received Signal Strength Indicator (RSSI).

9. The method according to claim 7 or 8, wherein, The first auxiliary information includes one or more of the area information, location information, and status information of the terminal device during the data collection process.

10. The method according to any one of claims 1-9, wherein, The method further includes: The terminal device receives first configuration information from the network device; wherein the first configuration information includes one or more of the following: The configuration information of the reporting resources for the first reported information; Configuration information of measurement resources for the first reference signal; Configuration information of the first codebook; The configuration information of the parameters of the dataset information.

11. The method according to claim 10, wherein, The configuration information of the first codebook includes one or more of the following: Second indication information; wherein, the second indication information is used by the terminal device to determine that the first codebook is used; The configuration information of the parameters of the first codebook.

12. The method according to claim 10 or 11, wherein, The parameters of the dataset information include one or more of the following: The first parameter; wherein, the first parameter is the number of labels N in the dataset information; The second parameter; wherein, the second parameter is the number K of time slots corresponding to each group of tags; The third parameter indicates that the dataset information is based on measurement or prediction.

13. The method according to claim 12, wherein, The configuration information of the first parameter is used to indicate the value of the first parameter, or the range of values ​​of the first parameter, or the set of first parameters; The range of values ​​for the first parameter is used by the terminal device to determine the first parameter based on the Media Access Control (MAC) CE and / or Downlink Control Information (DCI) within the range of values. The first parameter set is used by the terminal device to determine the first parameter based on MAC CE and / or DCI.

14. The method according to claim 12 or 13, wherein, The configuration information of the second parameter is used to indicate the value of the second parameter, or the range of values ​​of the second parameter, or the set of the second parameter; The range of values ​​for the second parameter is used by the terminal device to determine the second parameter based on MAC CE and / or DCI within the range of values. The second parameter set is used by the terminal device to determine the second parameter based on MAC CE and / or DCI.

15. The method according to any one of claims 1-14, wherein, K is related to the fourth parameter of the first codebook; the fourth parameter is the number of time slots corresponding to the channel information processed based on the first codebook.

16. The method according to claim 15, wherein, K is a positive integer multiple of the fourth parameter or K is equal to the fourth parameter.

17. The method according to any one of claims 9-14, wherein, The first configuration information is used to configure periodic measurement resources; the first configuration information includes the configuration information of the first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter.

18. The method according to claim 17, wherein, The terminal device sends first reporting information to the network device, including: The terminal device periodically acquires tags based on the periodic measurement resources and reports the tags via higher-layer signaling until the number of tags reaches N sets.

19. The method of claim 17, wherein, The periodic measurement resources include measurement resources based on a first period; The terminal device sends first reporting information to the network device, including: The terminal device acquires tags based on the measurement resources based on the first period; The terminal device reports the tag via physical layer signaling based on the second cycle.

20. The method according to any one of claims 9-14, wherein, The first configuration information is used to configure semi-continuous measurement resources; the first configuration information includes the configuration information of the first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter, or the value range of the first parameter, or the first parameter set.

21. The method according to claim 20, wherein, The terminal device sends a first reporting message to the network device, including: After receiving the activation instruction of the semi-persistent measurement resource, the terminal device periodically acquires tags and reports the tags through higher-layer signaling based on the semi-persistent measurement resource until the number of tags reaches N groups.

22. The method according to claim 20, wherein, The terminal device sends a first reporting message to the network device, including: After receiving the activation instruction of the semi-persistent measurement resource, the terminal device acquires a tag based on the first period and the semi-persistent measurement resource; The terminal device reports the tag via physical layer signaling based on the second cycle.

23. The method according to claim 19 or 22, wherein, The first configuration information also includes the configuration information for the first period and / or the configuration information for the second period.

24. The method according to claim 19, 22 or 23, wherein, The second period is related to the first period, and the second period is related to the fourth parameter of the first codebook.

25. The method according to claim 24, wherein, The second period is related to the product of the first period and the fourth parameter of the first codebook.

26. The method according to any one of claims 9-14, wherein, The first configuration information is used to configure non-periodic measurement resources; wherein, the non-periodic measurement resources include N sets of measurement resources; each of the N sets of measurement resources includes K time slots; the K time slots are used by the terminal device to acquire a set of tags.

27. The method according to any one of claims 1-26, wherein, The method further includes: The terminal device sends first capability information to the network device; wherein the first capability information is used to indicate one or more of the following: Capability parameters related to channel measurements; Capability parameters related to channel information reporting; Whether the terminal device supports reporting the first channel information based on the first codebook; The terminal device supports the maximum time range corresponding to simultaneously reporting the first channel information.

28. A data collection method, comprising: The network device receives the first reported information from the terminal device; Wherein, the first reported information includes dataset information, the dataset information includes N sets of tags, each set of tags in the N sets of tags includes first channel information of K time slots; the first channel information includes feature information corresponding to the second channel information obtained based on the first codebook; the first codebook is related to the time domain features of the second channel information; wherein, N is an integer greater than or equal to 1, and K is an integer greater than or equal to 1.

29. The method according to claim 28, wherein, The first codebook is used to obtain the feature information based on the temporal correlation of the second channel information in multiple time slots.

30. The method according to claim 28 or 29, wherein, The first codebook includes the Doppler-eTypeII codebook.

31. The method according to any one of claims 28-30, wherein, The feature information includes feature vectors.

32. The method according to any one of claims 28-31, wherein, The method further includes: The network device sends a first reference signal to the terminal device; wherein the first reference signal is used by the terminal device to obtain the second channel information.

33. The method according to any one of claims 28-32, wherein, The first reported information also includes one or more of the following: First indication information; wherein, the first indication information is used to indicate that the dataset information is obtained based on measurement or prediction; The quality information of the dataset; First auxiliary information; wherein, the first auxiliary information is used to indicate information related to the collection process of the dataset information; The identification information of the dataset information; wherein, the identification information is used to distinguish the dataset information collected under different user configurations.

34. The method according to claim 33, wherein, The quality information includes one or more of the following: Channel Quality Indicator (CQI), Signal-to-Noise Ratio (SNR), Signal-to-Interference Plus-Noise Ratio (SINR), Reference Signal Received Power (RSRP), and Received Signal Strength Indicator (RSSI).

35. The method according to claim 33 or 34, wherein, The first auxiliary information includes one or more of the area information, location information, and status information of the terminal device during the data collection process.

36. The method according to any one of claims 28-35, wherein, The method further includes: The network device sends first configuration information to the terminal device; wherein the first configuration information includes one or more of the following: The configuration information of the reporting resources for the first reported information; Configuration information of measurement resources for the first reference signal; Configuration information of the first codebook; The configuration information of the parameters of the dataset information.

37. The method of claim 36, wherein, The configuration information of the first codebook includes one or more of the following: Second indication information; wherein, the second indication information is used by the terminal device to determine that the first codebook is used; The configuration information of the parameters of the first codebook.

38. The method according to claim 36 or 37, wherein, The parameters of the dataset information include one or more of the following: The first parameter; wherein, the first parameter is the number of labels N in the dataset information; The second parameter; wherein, the second parameter is the number K of time slots corresponding to each group of tags; The third parameter indicates that the dataset information is based on measurement or prediction.

39. The method according to claim 38, wherein, The configuration information of the first parameter is used to indicate the value of the first parameter, or the range of values ​​of the first parameter, or the set of first parameters; The range of values ​​for the first parameter is used by the terminal device to determine the first parameter based on the Media Access Control (MAC) CE and / or Downlink Control Information (DCI) within the range of values. The first parameter set is used by the terminal device to determine the first parameter based on MAC CE and / or DCI.

40. The method according to claim 38 or 39, wherein, The configuration information of the second parameter is used to indicate the value of the second parameter, or the range of values ​​of the second parameter, or the set of the second parameter; The range of values ​​for the second parameter is used by the terminal device to determine the second parameter based on MAC CE and / or DCI within the range of values. The second parameter set is used by the terminal device to determine the second parameter based on MAC CE and / or DCI.

41. The method according to any one of claims 28-40, wherein, K is related to the fourth parameter of the first codebook; the fourth parameter is the number of time slots corresponding to the channel information processed based on the first codebook.

42. The method according to claim 41, wherein, K is a positive integer multiple of the fourth parameter or K is equal to the fourth parameter.

43. The method according to any one of claims 36-40, wherein, The first configuration information is used to configure periodic measurement resources; the first configuration information includes the configuration information of the first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter.

44. The method according to claim 43, wherein, The network device receives first reported information from the terminal device, including: The network device receives tags reported by the terminal device via higher-layer signaling until the number of tags reaches N sets; wherein the tags are acquired by the terminal device based on the periodic measurement resources.

45. The method according to claim 43, wherein, The periodic measurement resources include measurement resources based on a first period; The network device receives first reported information from the terminal device, including: The network device receives tags reported by the terminal device via physical layer signaling based on a second cycle; wherein the tags are acquired by the terminal device based on measurement resources in the first cycle.

46. ​​The method according to any one of claims 36-40, wherein, The first configuration information is used to configure semi-continuous measurement resources; the first configuration information includes the configuration information of the first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter, or the value range of the first parameter, or the first parameter set.

47. The method according to claim 46, wherein, The method further includes: The network device sends an activation instruction to the terminal device; wherein the activation instruction is used to trigger the terminal device to periodically acquire tags and report the tags through higher-layer signaling based on the semi-persistent measurement resources until the number of tags reaches N sets.

48. The method according to claim 46, wherein, The method further includes: The network device sends an activation instruction to the terminal device; wherein the activation instruction is used to trigger the terminal device to periodically acquire tags based on a first period and the semi-persistent measurement resources, and to report the tags via physical layer signaling based on a second period.

49. The method of claim 45 or 48, wherein, The first configuration information also includes the configuration information for the first period and / or the configuration information for the second period.

50. The method of claim 45, 48, or 49, wherein, The second period is related to the first period, and the second period is related to the fourth parameter of the first codebook.

51. The method of claim 50, wherein, The second period is related to the product of the first period and the fourth parameter of the first codebook.

52. The method of any one of claims 36-40, wherein, The first configuration information is used to configure non-periodic measurement resources; wherein, the non-periodic measurement resources include N sets of measurement resources; each of the N sets of measurement resources includes K time slots; the K time slots are used by the terminal device to acquire a set of tags.

53. The method of any one of claims 28-52, wherein, The method further includes: The network device receives first capability information from the terminal device; wherein the first capability information is used to indicate one or more of the following: Capability parameters related to channel measurements; Capability parameters related to channel information reporting; Whether the terminal device supports reporting the first channel information based on the first codebook; The terminal device supports the maximum time range corresponding to simultaneously reporting the first channel information.

54. A terminal device, comprising: The first communication module is used to send the first reporting information to the network device; Wherein, the first reported information includes dataset information, the dataset information includes N sets of tags, each set of tags in the N sets of tags includes first channel information of K time slots; the first channel information includes feature information corresponding to the second channel information obtained based on the first codebook; the first codebook is related to the time domain features of the second channel information; wherein, N is an integer greater than or equal to 1, and K is an integer greater than or equal to 1.

55. The terminal device of claim 54, wherein, The first codebook is used to obtain the feature information based on the temporal correlation of the second channel information in multiple time slots.

56. The terminal device of claim 54 or 55, wherein, The first codebook includes the Doppler-eTypeII codebook.

57. The terminal device of any one of claims 54-56, wherein, The feature information includes feature vectors.

58. The terminal device of any one of claims 54-57, wherein, The first communication module is further configured to: The terminal device receives a first reference signal from the network device; wherein the first reference signal is used by the terminal device to obtain the second channel information.

59. The terminal device of claim 58, wherein, The second channel information is obtained by the terminal device based on the measurement of the first reference signal, or by the terminal device based on the measurement and prediction processing of the first reference signal.

60. The terminal device of any one of claims 54-59, wherein, The first reported information also includes one or more of the following: First indication information; wherein, the first indication information is used to indicate that the dataset information is obtained based on measurement or prediction; The quality information of the dataset; First auxiliary information; wherein, the first auxiliary information is used to indicate information related to the collection process of the dataset information; The identification information of the dataset information; wherein, the identification information is used to distinguish the dataset information collected under different user configurations.

61. The terminal device of claim 60, wherein, The quality information includes one or more of CQI, SNR, SINR, RSRP, and RSSI.

62. The terminal device of claim 60 or 61, wherein, The first auxiliary information includes one or more of the area information, location information, and status information of the terminal device during the data collection process.

63. The terminal device of any one of claims 54-62, wherein, The first communication module is further configured to: Receive first configuration information from the network device; wherein the first configuration information includes one or more of the following: The configuration information of the reporting resources for the first reported information; Configuration information of measurement resources for the first reference signal; Configuration information of the first codebook; The configuration information of the parameters of the dataset information.

64. The terminal device of claim 63, wherein, The configuration information of the first codebook includes one or more of the following: Second indication information; wherein, the second indication information is used by the terminal device to determine that the first codebook is used; The configuration information of the parameters of the first codebook.

65. The terminal device of claim 63 or 64, wherein, The parameters of the dataset information include one or more of the following: The first parameter; wherein, the first parameter is the number of labels N in the dataset information; The second parameter; wherein, the second parameter is the number K of time slots corresponding to each group of tags; The third parameter indicates that the dataset information is based on measurement or prediction.

66. The terminal device of claim 65, wherein, The configuration information of the first parameter is used to indicate the value of the first parameter, or the range of values ​​of the first parameter, or the set of first parameters; The value range of the first parameter is used by the terminal device to determine the first parameter based on MAC CE and / or DCI within the value range; The first parameter set is used by the terminal device to determine the first parameter based on MAC CE and / or DCI.

67. The terminal device of claim 65 or 66, wherein, The configuration information of the second parameter is used to indicate the value of the second parameter, or the range of values ​​of the second parameter, or the set of the second parameter; The range of values ​​for the second parameter is used by the terminal device to determine the second parameter based on MAC CE and / or DCI within the range of values. The second parameter set is used by the terminal device to determine the second parameter based on MAC CE and / or DCI.

68. The terminal device of any one of claims 54-67, wherein, K is related to the fourth parameter of the first codebook; the fourth parameter is the number of time slots corresponding to the channel information processed based on the first codebook.

69. The terminal device of claim 68, wherein, K is a positive integer multiple of the fourth parameter or K is equal to the fourth parameter.

70. The terminal device of any one of claims 62-67, wherein, The first configuration information is used to configure periodic measurement resources; the first configuration information includes the configuration information of the first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter.

71. The terminal device of claim 70, wherein, The terminal device includes a first processing module, which is used to: periodically acquire tags based on the periodic measurement resources; The first communication module is used to report the tags via higher-layer signaling until the number of tags reaches N groups.

72. The terminal device of claim 70, wherein, The periodic measurement resources include measurement resources based on a first period; the terminal device includes a first processing module, which is used to: acquire tags based on the measurement resources based on the first period; The first communication module is used to report the tag via physical layer signaling based on the second cycle.

73. The terminal device of any one of claims 62-67, wherein, The first configuration information is used to configure semi-continuous measurement resources; the first configuration information includes the configuration information of the first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter, or the value range of the first parameter, or the first parameter set.

74. The terminal device of claim 73, wherein, The terminal device includes a second processing module, which is configured to: periodically acquire tags based on the semi-persistent measurement resources after receiving an activation indication of the semi-persistent measurement resources; The first communication module is used to report the tags via higher-layer signaling until the number of tags reaches N groups.

75. The terminal device of claim 73, wherein, The terminal device includes a third processing module, which is used to: after receiving the activation indication of the semi-persistent measurement resource, acquire a tag based on the first period and the semi-persistent measurement resource; The first communication module is used to report the tag via physical layer signaling based on the second cycle.

76. The terminal device according to claim 72 or 75, wherein, The first configuration information also includes the configuration information for the first period and / or the configuration information for the second period.

77. The terminal device of claim 72, 75 or 76, wherein, The second period is related to the first period, and the second period is related to the fourth parameter of the first codebook.

78. The terminal device of claim 77, wherein, The second period is related to the product of the first period and the fourth parameter of the first codebook.

79. The terminal device of any one of claims 62-67, wherein, The first configuration information is used to configure non-periodic measurement resources; wherein, the non-periodic measurement resources include N sets of measurement resources; each of the N sets of measurement resources includes K time slots; the K time slots are used by the terminal device to acquire a set of tags.

80. The terminal device of any one of claims 54-79, wherein, The first communication module is further configured to: Send first capability information to the network device; wherein the first capability information is used to indicate one or more of the following: Capability parameters related to channel measurements; Capability parameters related to channel information reporting; Whether the terminal device supports reporting the first channel information based on the first codebook; The terminal device supports the maximum time range corresponding to simultaneously reporting the first channel information.

81. A network device, comprising: The second communication module is used to receive the first reported information from the terminal device; Wherein, the first reported information includes dataset information, the dataset information includes N sets of tags, each set of tags in the N sets of tags includes first channel information of K time slots; the first channel information includes feature information corresponding to the second channel information obtained based on the first codebook; the first codebook is related to the time domain features of the second channel information; wherein, N is an integer greater than or equal to 1, and K is an integer greater than or equal to 1.

82. The network device of claim 81, wherein, The first codebook is used to obtain the feature information based on the temporal correlation of the second channel information in multiple time slots.

83. The network device of claim 81 or 82, wherein, The first codebook includes the Doppler-eTypeII codebook.

84. The network device of any of claims 81-83, wherein, The feature information includes feature vectors.

85. The network device of any of claims 81-84, wherein, The second communication module is also used for: A first reference signal is sent to the terminal device; wherein the first reference signal is used by the terminal device to obtain the second channel information.

86. The network device of any of claims 81-85, wherein, The first reported information also includes one or more of the following: First indication information; wherein, the first indication information is used to indicate that the dataset information is obtained based on measurement or prediction; The quality information of the dataset; First auxiliary information; wherein, the first auxiliary information is used to indicate information related to the collection process of the dataset information; The identification information of the dataset information; wherein, the identification information is used to distinguish the dataset information collected under different user configurations.

87. The network device of claim 86, wherein, The quality information includes one or more of CQI, SNR, SINR, reference signal received power RSRP, and RSSI.

88. The network device of claim 86 or 87, wherein, The first auxiliary information includes one or more of the area information, location information, and status information of the terminal device during the data collection process.

89. The network device of any of claims 81-88, wherein, The second communication module is also used for: Send first configuration information to the terminal device; wherein the first configuration information includes one or more of the following: The configuration information of the reporting resources for the first reported information; Configuration information of measurement resources for the first reference signal; Configuration information of the first codebook; The configuration information of the parameters of the dataset information.

90. The network device of claim 89, wherein, The configuration information of the first codebook includes one or more of the following: Second indication information; wherein, the second indication information is used by the terminal device to determine that the first codebook is used; The configuration information of the parameters of the first codebook.

91. The network device of claim 89 or 90, wherein, The parameters of the dataset information include one or more of the following: The first parameter; wherein, the first parameter is the number of labels N in the dataset information; The second parameter; wherein, the second parameter is the number K of time slots corresponding to each group of tags; The third parameter indicates that the dataset information is based on measurement or prediction.

92. The network device of claim 91, wherein, The configuration information of the first parameter is used to indicate the value of the first parameter, or the range of values ​​of the first parameter, or the set of first parameters; The value range of the first parameter is used by the terminal device to determine the first parameter based on MAC CE and / or DCI within the value range; The first parameter set is used by the terminal device to determine the first parameter based on MAC CE and / or DCI.

93. The network device of claim 91 or 92, wherein, The configuration information of the second parameter is used to indicate the value of the second parameter, or the range of values ​​of the second parameter, or the set of the second parameter; The range of values ​​for the second parameter is used by the terminal device to determine the second parameter based on MAC CE and / or DCI within the range of values. The second parameter set is used by the terminal device to determine the second parameter based on MAC CE and / or DCI.

94. The network device of any of claims 81-93, wherein, K is related to the fourth parameter of the first codebook; the fourth parameter is the number of time slots corresponding to the channel information processed based on the first codebook.

95. The network device of claim 94, wherein, K is a positive integer multiple of the fourth parameter or K is equal to the fourth parameter.

96. The network device of any of claims 89-93, wherein, The first configuration information is used to configure periodic measurement resources; the first configuration information includes the configuration information of the first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter.

97. The network device of claim 96, wherein, The second communication module is also used for: The terminal device receives tags reported by the terminal device via higher-layer signaling until the number of tags reaches N sets; wherein the tags are acquired by the terminal device based on the periodic measurement resources.

98. The network device of claim 96, wherein, The periodic measurement resources include measurement resources based on a first period; The second communication module is also used for: Based on the second cycle, the terminal device receives tags reported by the terminal device through physical layer signaling; wherein the tags are acquired by the terminal device based on the measurement resources of the first cycle.

99. The network device of any of claims 89-93, wherein, The first configuration information is used to configure semi-continuous measurement resources; the first configuration information includes the configuration information of the first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter, or the value range of the first parameter, or the first parameter set.

100. The network device of claim 99, wherein, The second communication module is also used for: An activation instruction is sent to the terminal device; wherein the activation instruction is used to trigger the terminal device to periodically acquire tags and report the tags through higher-layer signaling based on the semi-persistent measurement resources until the number of tags reaches N groups.

101. The network device of claim 99, wherein, The second communication module is also used for: An activation instruction is sent to the terminal device; wherein the activation instruction is used to trigger the terminal device to periodically acquire tags based on a first period and the semi-persistent measurement resources, and to report the tags via physical layer signaling based on a second period.

102. The network device of claim 98 or 101, wherein, The first configuration information also includes the configuration information for the first period and / or the configuration information for the second period.

103. The network device of claim 98, 101, or 102, wherein, The second period is related to the first period, and the second period is related to the fourth parameter of the first codebook.

104. The network device of claim 103, wherein, The second period is related to the product of the first period and the fourth parameter of the first codebook.

105. The network device of any of claims 89-93, wherein, The first configuration information is used to configure non-periodic measurement resources; wherein, the non-periodic measurement resources include N sets of measurement resources; each of the N sets of measurement resources includes K time slots; the K time slots are used by the terminal device to acquire a set of tags.

106. The network device of any of claims 81-105, wherein, The second communication module is also used for: Receive first capability information from the terminal device; wherein the first capability information is used to indicate one or more of the following: Capability parameters related to channel measurements; Capability parameters related to channel information reporting; Whether the terminal device supports reporting the first channel information based on the first codebook; The terminal device supports the maximum time range corresponding to simultaneously reporting the first channel information.

107. A terminal device comprising: The transceiver, processor, and memory, wherein the memory stores computer programs, the transceiver communicates with other devices, and the processor invokes and runs the computer programs stored in the memory to cause the terminal device to perform the following: Send the first reporting information to the network device; Wherein, the first reported information includes dataset information, the dataset information includes N sets of tags, each set of tags in the N sets of tags includes first channel information of K time slots; the first channel information includes feature information corresponding to the second channel information obtained based on the first codebook; the first codebook is related to the time domain features of the second channel information; wherein, N is an integer greater than or equal to 1, and K is an integer greater than or equal to 1.

108. The terminal device of claim 107, wherein, The first codebook is used to obtain the feature information based on the temporal correlation of the second channel information in multiple time slots.

109. The terminal device of claim 107 or 108, wherein, The first codebook includes the Doppler-eTypeII codebook.

110. The terminal device of any one of claims 107-109, wherein, The feature information includes feature vectors.

111. The terminal device of any one of claims 107-110, wherein, The processor is also configured to enable the terminal device to perform: The terminal device receives a first reference signal from the network device; wherein the first reference signal is used by the terminal device to obtain the second channel information.

112. The terminal device of claim 111, wherein, The second channel information is obtained by the terminal device based on the measurement of the first reference signal, or by the terminal device based on the measurement and prediction processing of the first reference signal.

113. The terminal device of any one of claims 107-112, wherein, The first reported information also includes one or more of the following: First indication information; wherein, the first indication information is used to indicate that the dataset information is obtained based on measurement or prediction; The quality information of the dataset; First auxiliary information; wherein, the first auxiliary information is used to indicate information related to the collection process of the dataset information; The identification information of the dataset information; wherein, the identification information is used to distinguish the dataset information collected under different user configurations.

114. The terminal device of claim 113, wherein, The quality information includes one or more of CQI, SNR, SINR, RSRP, and RSSI.

115. The terminal device of claim 113 or 114, wherein, The first auxiliary information includes one or more of the area information, location information, and status information of the terminal device during the data collection process.

116. The terminal device of any of claims 107-115, wherein, The processor is also configured to enable the terminal device to perform: Receive first configuration information from the network device; wherein the first configuration information includes one or more of the following: The configuration information of the reporting resources for the first reported information; Configuration information of measurement resources for the first reference signal; Configuration information of the first codebook; The configuration information of the parameters of the dataset information.

117. The terminal device of claim 116, wherein, The configuration information of the first codebook includes one or more of the following: Second indication information; wherein, the second indication information is used by the terminal device to determine that the first codebook is used; The configuration information of the parameters of the first codebook.

118. The terminal device of claim 116 or 117, wherein, The parameters of the dataset information include one or more of the following: The first parameter; wherein, the first parameter is the number of labels N in the dataset information; The second parameter; wherein, the second parameter is the number K of time slots corresponding to each group of tags; The third parameter indicates that the dataset information is based on measurement or prediction.

119. The terminal device of claim 118, wherein, The configuration information of the first parameter is used to indicate the value of the first parameter, or the range of values ​​of the first parameter, or the set of first parameters; The value range of the first parameter is used by the terminal device to determine the first parameter based on MAC CE and / or DCI within the value range; The first parameter set is used by the terminal device to determine the first parameter based on MAC CE and / or DCI.

120. The terminal device of claim 118 or 119, wherein, The configuration information of the second parameter is used to indicate the value of the second parameter, or the range of values ​​of the second parameter, or the set of the second parameter; The range of values ​​for the second parameter is used by the terminal device to determine the second parameter based on MAC CE and / or DCI within the range of values. The second parameter set is used by the terminal device to determine the second parameter based on MAC CE and / or DCI.

121. The terminal device of any of claims 107-120, wherein, K is related to the fourth parameter of the first codebook; the fourth parameter is the number of time slots corresponding to the channel information processed based on the first codebook.

122. The terminal device of claim 121, wherein, K is a positive integer multiple of the fourth parameter or K is equal to the fourth parameter.

123. The terminal device of any one of claims 115-120, wherein, The first configuration information is used to configure periodic measurement resources; the first configuration information includes the configuration information of the first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter.

124. The terminal device of claim 123, wherein, The processor is also configured to enable the terminal device to perform: Based on the periodic measurement resources, tags are periodically acquired and reported via higher-layer signaling until the number of tags reaches N sets.

125. The terminal device according to claim 123, wherein, The periodic measurement resources include measurement resources based on a first period; The processor is also configured to enable the terminal device to perform: Based on the measurement resources based on the first period, obtain the tags; Based on the second cycle, the tag is reported via physical layer signaling.

126. The terminal device according to any one of claims 115-120, wherein, The first configuration information is used to configure semi-continuous measurement resources; the first configuration information includes the configuration information of the first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter, or the value range of the first parameter, or the first parameter set.

127. The terminal device according to claim 126, wherein, The processor is also configured to enable the terminal device to perform: Upon receiving the activation instruction of the semi-persistent measurement resource, the system periodically acquires tags based on the semi-persistent measurement resource and reports the tags via higher-layer signaling until the number of tags reaches N groups.

128. The terminal device according to claim 126, wherein, The processor is also configured to enable the terminal device to perform: Upon receiving the activation indication of the semi-persistent measurement resource, a tag is acquired based on the first period and the semi-persistent measurement resource; Based on the second cycle, the tag is reported via physical layer signaling.

129. The terminal device according to claim 125 or 128, wherein, The first configuration information also includes the configuration information for the first period and / or the configuration information for the second period.

130. The terminal device according to claim 125, 128 or 129, wherein, The second period is related to the first period, and the second period is related to the fourth parameter of the first codebook.

131. The terminal device according to claim 130, wherein, The second period is related to the product of the first period and the fourth parameter of the first codebook.

132. The terminal device according to any one of claims 115-120, wherein, The first configuration information is used to configure non-periodic measurement resources; wherein, the non-periodic measurement resources include N sets of measurement resources; each of the N sets of measurement resources includes K time slots; the K time slots are used by the terminal device to acquire a set of tags.

133. The terminal device according to any one of claims 107-132, wherein, The processor is also configured to enable the terminal device to perform: Send first capability information to the network device; wherein the first capability information is used to indicate one or more of the following: Capability parameters related to channel measurements; Capability parameters related to channel information reporting; Whether the terminal device supports reporting the first channel information based on the first codebook; The terminal device supports the maximum time range corresponding to simultaneously reporting the first channel information.

134. A network device, comprising: The network device includes a transceiver, a processor, and a memory. The memory stores computer programs. The transceiver communicates with other devices. The processor invokes and runs the computer programs stored in the memory to cause the network device to perform the following: Receive the first reported information from the terminal device; Wherein, the first reported information includes dataset information, the dataset information includes N sets of tags, each set of tags in the N sets of tags includes first channel information of K time slots; the first channel information includes feature information corresponding to the second channel information obtained based on the first codebook; the first codebook is related to the time domain features of the second channel information; wherein, N is an integer greater than or equal to 1, and K is an integer greater than or equal to 1.

135. The network device according to claim 134, wherein, The first codebook is used to obtain the feature information based on the temporal correlation of the second channel information in multiple time slots.

136. The network device according to claim 134 or 135, wherein, The first codebook includes the Doppler-eTypeII codebook.

137. The network device according to any one of claims 134-136, wherein, The feature information includes feature vectors.

138. The network device according to any one of claims 134-137, wherein, The processor is also configured to enable the network device to perform: A first reference signal is sent to the terminal device; wherein the first reference signal is used by the terminal device to obtain the second channel information.

139. The network device according to any one of claims 134-138, wherein, The first reported information also includes one or more of the following: First indication information; wherein, the first indication information is used to indicate that the dataset information is obtained based on measurement or prediction; The quality information of the dataset; First auxiliary information; wherein, the first auxiliary information is used to indicate information related to the collection process of the dataset information; The identification information of the dataset information; wherein, the identification information is used to distinguish the dataset information collected under different user configurations.

140. The network device of claim 139, wherein, The quality information includes one or more of CQI, SNR, SINR, RSRP, and RSSI.

141. The network device according to claim 139 or 140, wherein, The first auxiliary information includes one or more of the area information, location information, and status information of the terminal device during the data collection process.

142. The network device according to any one of claims 134-141, wherein, The processor is also configured to enable the network device to perform: Send first configuration information to the terminal device; wherein the first configuration information includes one or more of the following: The configuration information of the reporting resources for the first reported information; Configuration information of measurement resources for the first reference signal; Configuration information of the first codebook; The configuration information of the parameters of the dataset information.

143. The network device according to claim 142, wherein, The configuration information of the first codebook includes one or more of the following: Second indication information; wherein, the second indication information is used by the terminal device to determine that the first codebook is used; The configuration information of the parameters of the first codebook.

144. The network device according to claim 142 or 143, wherein, The parameters of the dataset information include one or more of the following: The first parameter; wherein, the first parameter is the number of labels N in the dataset information; The second parameter; wherein, the second parameter is the number K of time slots corresponding to each group of tags; The third parameter indicates that the dataset information is based on measurement or prediction.

145. The network device according to claim 144, wherein, The configuration information of the first parameter is used to indicate the value of the first parameter, or the range of values ​​of the first parameter, or the set of first parameters; The value range of the first parameter is used by the terminal device to determine the first parameter based on MAC CE and / or DCI within the value range; The first parameter set is used by the terminal device to determine the first parameter based on MAC CE and / or DCI.

146. The network device according to claim 144 or 145, wherein, The configuration information of the second parameter is used to indicate the value of the second parameter, or the range of values ​​of the second parameter, or the set of the second parameter; The range of values ​​for the second parameter is used by the terminal device to determine the second parameter based on MAC CE and / or DCI within the range of values. The second parameter set is used by the terminal device to determine the second parameter based on MAC CE and / or DCI.

147. The network device according to any one of claims 134-146, wherein, K is related to the fourth parameter of the first codebook; the fourth parameter is the number of time slots corresponding to the channel information processed based on the first codebook.

148. The network device according to claim 147, wherein, K is a positive integer multiple of the fourth parameter or K is equal to the fourth parameter.

149. The network device according to any one of claims 142-146, wherein, The first configuration information is used to configure periodic measurement resources; the first configuration information includes the configuration information of the first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter.

150. The network device of claim 149, wherein, The processor is also configured to enable the network device to perform: The terminal device receives tags reported by the terminal device via higher-layer signaling until the number of tags reaches N sets; wherein the tags are acquired by the terminal device based on the periodic measurement resources.

151. The network device of claim 149, wherein, The periodic measurement resources include measurement resources based on a first period; The processor is also configured to enable the network device to perform: Based on the second cycle, the terminal device receives tags reported by the terminal device through physical layer signaling; wherein the tags are acquired by the terminal device based on the measurement resources of the first cycle.

152. The network device of any of claims 142-151, wherein, The first configuration information is used to configure semi-continuous measurement resources; the first configuration information includes the configuration information of the first parameter, and the configuration information of the first parameter is used to indicate the value of the first parameter, or the value range of the first parameter, or the first parameter set.

153. The network device according to claim 152, wherein, The processor is also configured to enable the network device to perform: An activation instruction is sent to the terminal device; wherein the activation instruction is used to trigger the terminal device to periodically acquire tags and report the tags through higher-layer signaling based on the semi-persistent measurement resources until the number of tags reaches N groups.

154. The network device of claim 152, wherein, The processor is also configured to enable the network device to perform: An activation instruction is sent to the terminal device; wherein the activation instruction is used to trigger the terminal device to periodically acquire tags based on a first period and the semi-persistent measurement resources, and to report the tags via physical layer signaling based on a second period.

155. The network device of claim 151 or 154, wherein, The first configuration information also includes the configuration information for the first period and / or the configuration information for the second period.

156. The network device of claim 151, 154, or 155, wherein, The second period is related to the first period, and the second period is related to the fourth parameter of the first codebook.

157. The network device of claim 156, wherein, The second period is related to the product of the first period and the fourth parameter of the first codebook.

158. The network device of any of claims 142-146, wherein, The first configuration information is used to configure non-periodic measurement resources; wherein, the non-periodic measurement resources include N sets of measurement resources; each of the N sets of measurement resources includes K time slots; the K time slots are used by the terminal device to acquire a set of tags.

159. The network device of any of claims 134-158, wherein, The processor is also configured to enable the network device to perform: Receive first capability information from the terminal device; wherein the first capability information is used to indicate one or more of the following: Capability parameters related to channel measurements; Capability parameters related to channel information reporting; Whether the terminal device supports reporting the first channel information based on the first codebook; The terminal device supports the maximum time range corresponding to simultaneously reporting the first channel information.

160. A chip comprising: A processor for retrieving and running a computer program from memory, causing a device on which the chip is mounted to perform the method as described in any one of claims 1 to 27.

161. A chip comprising: A processor for retrieving and running a computer program from memory, causing a device on which the chip is mounted to perform the method as described in any one of claims 28 to 53.

162. A computer-readable storage medium for storing a computer program that, when run by a device, causes the device to perform the method as claimed in any one of claims 1 to 27.

163. A computer-readable storage medium for storing a computer program that, when run by a device, causes the device to perform the method as claimed in any one of claims 28 to 53.

164. A computer program product comprising computer program instructions that cause a computer to perform the method as claimed in any one of claims 1 to 27.

165. A computer program product comprising computer program instructions that cause a computer to perform the method as described in any one of claims 28 to 53.

166. A computer program that causes a computer to perform the method as claimed in any one of claims 1 to 27.

167. A computer program that causes a computer to perform the method as claimed in any one of claims 28 to 53.

168. A communication system, comprising: A terminal device for performing the method as described in any one of claims 1 to 27; A network device for performing the method as described in any one of claims 28 to 53.

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