Information transmission method, apparatus, and storage medium

Abstract

Provided are an information transmission method, an apparatus, and a storage medium. The method comprises: acquiring classification parameters, and classifying N pieces of information into M information groups on the basis of the classification parameters; and transmitting L information groups among the M information groups, wherein N, M, and L are all positive integers, L is less than or equal to M, and M is less than or equal to N.

Description

Information transmission methods, devices and storage media

[0001] This disclosure claims priority to Chinese patent application No. 202510028091.8, filed on January 6, 2025, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This disclosure relates to the field of wireless communication technology, and in particular to an information transmission method, apparatus and storage medium. Background Technology

[0003] In today's increasingly complex wireless communication systems, with ever-growing demands for high performance, employing cutting-edge information processing technologies has become crucial for optimizing system performance. These technologies include various nonlinear processing methods, such as those based on artificial intelligence (AI). By utilizing AI technologies, such as beam management, channel state information compression and prediction, and channel estimation, advanced information processing techniques can significantly improve the efficiency and reliability of communication systems.

[0004] To maximize the advantages of these advanced technologies, it is essential to prioritize the training, fine-tuning, and performance monitoring of AI models. This relies on building high-quality datasets, as data quality directly impacts model performance and generalization ability. A high-quality dataset should contain rich and accurate information elements to ensure the effectiveness and robustness of the AI ​​algorithm. Summary of the Invention

[0005] On the one hand, an information transmission method is provided, the method comprising:

[0006] Obtain the classification parameters, and divide the N pieces of information into M information groups based on the classification parameters;

[0007] Transmit L information groups out of M information groups; here, N, M, and L are all positive integers, L is less than or equal to M, and M is less than or equal to N.

[0008] On the other hand, an information transmission method is provided, the method comprising:

[0009] Receive L information groups from M information groups, where M information groups are obtained by dividing N information groups based on classification parameters;

[0010] Here, N, M, and L are all positive integers, L is less than or equal to M, and M is less than or equal to N.

[0011] In another aspect, an information transmission device is provided, the device comprising:

[0012] The communication module is used to obtain classification parameters;

[0013] The processing module is used to divide N pieces of information into M information groups based on classification parameters;

[0014] The communication module is used to transmit L information groups out of M information groups; here, N, M, and L are all positive integers, L is less than or equal to M, and M is less than or equal to N.

[0015] In another aspect, an information transmission device is provided, the device comprising:

[0016] The communication module is used to receive L information groups out of M information groups. The M information groups are obtained by dividing N information groups based on classification parameters. Here, N, M, and L are all positive integers, L is less than or equal to M, and M is less than or equal to N.

[0017] In another aspect, a communication device is provided, comprising: a memory and a processor; the memory and the processor are coupled; the memory is used to store computer program instructions executable by the processor; and the processor implements the information transmission method of any of the above embodiments when executing the computer program instructions.

[0018] In another aspect, a computer-readable storage medium is provided, on which computer program instructions are stored, which, when executed on a computer (e.g., a communication device or an information transmission device), implement the information transmission method of any of the above embodiments.

[0019] In another aspect, a computer program product is provided, which includes computer program instructions that, when executed, implement the information transmission method of any of the above embodiments. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in this disclosure, the accompanying drawings used in some embodiments of this disclosure will be briefly described below. Obviously, the drawings described below are merely drawings of some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings.

[0021] Figure 1 is a schematic diagram of a wireless communication system according to some embodiments.

[0022] Figure 2 is a flowchart of an information transmission method according to some embodiments.

[0023] Figure 3 is a flowchart of another information transmission method provided according to some embodiments.

[0024] Figure 4 is a block diagram of an information transmission device according to some embodiments.

[0025] Figure 5 is a block diagram of another information transmission device provided according to some embodiments.

[0026] Figure 6 is a block diagram of a communication device according to some embodiments. Detailed Implementation

[0027] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this disclosure.

[0028] It should be understood that the specific implementations described herein are for interpreting this disclosure only and are not intended to limit this disclosure.

[0029] In the following description, the use of suffixes such as “module,” “part,” or “unit” to denote elements is solely for the purpose of illustrative purposes and has no particular meaning in itself. Therefore, “module,” “part,” or “unit” may be used interchangeably.

[0030] In this disclosure, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. "And / or" in this document is merely a description of 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, and B alone. Furthermore, "at least one" means one or more, and "multiple" means two or more. The terms "first," "second," etc., do not limit the quantity or order of execution, and "first," "second," etc., do not necessarily imply differences.

[0031] Unless the context otherwise requires, throughout the specification and claims, the term "comprise" and its other forms, such as the third-person singular "comprises" and the present participle "comprising," are interpreted as open-ended and encompassing, meaning "including, but not limited to." In the description of the specification, terms such as "one embodiment," "some embodiments," "exemplary embodiments," "example," "specific example," or "some examples," etc., are intended to indicate that a particular feature, structure, material, or characteristic associated with that embodiment or example is included in at least one embodiment or example of this disclosure. The illustrative representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics mentioned may be included in any suitable manner in any one or more embodiments or examples.

[0032] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this disclosure, unless otherwise stated, "a plurality of" means two or more.

[0033] In this disclosure, the terms "exemplarily" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplarily" or "for example" in this disclosure should not be construed as being more preferred or advantageous than other embodiments or designs. Rather, the use of the terms "exemplarily" or "for example" is intended to present the relevant concepts in a specific manner.

[0034] In addition, the use of “based on” implies openness and inclusivity, because processes, steps, calculations or other actions “based on” one or more of the stated conditions or values ​​may in practice be based on additional conditions or values ​​beyond those stated.

[0035] Multi-antenna technology, as a key means to improve the spectrum efficiency of wireless communication, is widely used in various wireless communication systems. Multi-antenna technology includes, but is not limited to, multiple-input multiple-output (MIMO), joint transmission (JT), and high-frequency beamforming. Its performance optimization is inseparable from accurate channel state information (CSI).

[0036] In today's increasingly complex wireless communication systems, with ever-growing demands for high performance, employing cutting-edge information processing technologies has become crucial for optimizing system performance. These technologies include various nonlinear processing methods, such as those based on artificial intelligence (AI). By utilizing AI technologies, such as beam management, channel state information compression and prediction, and channel estimation, advanced information processing techniques can significantly improve the efficiency and / or reliability of communication systems.

[0037] To maximize the advantages of these advanced technologies, it is crucial to prioritize the training, fine-tuning, and performance monitoring of AI models. This relies on constructing high-quality datasets, as data quality directly impacts model performance and generalization ability. A high-quality dataset should contain rich and accurate information elements to ensure the effectiveness and robustness of AI algorithms. Therefore, in the field of wireless communication, how to collect and construct high-quality datasets that meet these requirements has become a critical issue that urgently needs to be addressed.

[0038] In view of this, this disclosure provides an information transmission method, which includes: dividing N pieces of information into M information groups based on classification parameters; and transmitting L information groups from the M information groups. Since the information in the transmitted L information groups is of higher quality than that in the M information groups, collecting such information can improve the quality of the acquired dataset. Using high-quality information to train, fine-tune, or monitor the performance of the model corresponding to the information processing method is beneficial to improving the performance of the information processing method.

[0039] In this disclosure, higher-layer signaling includes, but is not limited to, radio resource control (RRC), media access control control element (MAC CE), and other higher-layer signaling other than physical layer signaling. Physical layer signaling includes, but is not limited to: downlink physical layer signaling transmitted on the physical downlink control channel (PDCCH), uplink physical layer signaling transmitted on the physical uplink control channel (PUCCH), and physical layer signaling transmitted on the physical uplink shared channel (PUSCH).

[0040] In this disclosure, the various parameter indicators can also be called indexes or identifiers (IDs). Indicators, identifiers, and indexes are equivalent concepts, and in some embodiments they can be used interchangeably.

[0041] In some embodiments, the resource identifier of the wireless system includes, but is not limited to, one of the following: reference signal resources, reference signal resource groups, reference signal resource configurations, CSI reports, CSI report sets, terminals, base stations, panels, neural network models, sub-neural network models, neural network layers, precoding matrices, beams, transmission methods, transmission methods, reception methods, modules, models, functional modules, functions, and corresponding indexes. The base station can send the identifier of one or a group of resources to the terminal via various higher-layer signaling and / or physical layer signaling. The terminal can send the identifier of one or a group of resources to the base station via various higher-layer signaling and / or physical layer signaling.

[0042] In some embodiments, the resource index i can range from 1 to a maximum value D. However, in other embodiments, the resource index i can range from 0 to a maximum value D-1. D is the maximum number of resources. Resources can be one or a group of the aforementioned wireless resources.

[0043] In some embodiments, transmission includes sending or receiving. For example, sending data or signals, or receiving data or signals.

[0044] In some embodiments, communication nodes need to transmit reference signals (RS) to obtain channel state information or perform channel estimation, mobility management, positioning, etc. Here, reference signals include, but are not limited to, channel-state information reference signals (CSI-RS), channel-state information interference measurement (CSI-IM), sounding reference signals (SRS), synchronization signals blocks (SSBs), physical broadcast channels (PBCHs), and synchronization signal block / physical broadcast channel (SSB / PBCH). In some embodiments, the SSB includes synchronization signals blocks and / or physical broadcast channels. Furthermore, the time-frequency resources used to transmit reference signals are called reference signal resources. Reference signal resources include a set of one or more resource elements (REs), such as CSI-RS resources, SRS resources, CSI-IM resources, SSB resources, etc. Reference signals are transmitted on reference signal resources.

[0045] In some embodiments, to save signaling overhead, multiple reference signal resources may be divided into multiple reference signal resource sets. A reference signal resource set (resource set) can also be called a reference signal resource group, such as a CSI-RS resource set, CSI-IM resource set, SRS resource set, SSB resource set, etc. A reference signal resource set includes at least one reference signal resource, and multiple reference signal resource sets may originate from the same reference signal resource setting. The reference signal resource setting can be used to configure parameter information, such as configuring the reference signal resource set. In some embodiments, the reference signal resource setting includes, but is not limited to, a CSI-RS resource setting, a CSI-IM resource setting, an SRS resource setting, and an SSB resource setting. Here, the CSI-RS resource setting may be merged with the CSI-IM resource setting and both are referred to as a CSI-RS resource setting. A reference signal resource setting may include at least one reference signal resource set. Additionally, a reference signal resource setting can also be called a reference signal configuration (RS config), such as a CSI-RS resource config, a CSI-IM resource config, an SRS resource config, and an SSB resource config.

[0046] In some embodiments, a time instance represents a time period, such as a slot, mini-slot, or symbol group. A slot or mini-slot may include at least one symbol. In one embodiment, a symbol refers to a time unit within a subframe, frame, or slot, and the unit may be milliseconds, microseconds, nanoseconds, seconds, etc. In one embodiment, a symbol may be an orthogonal frequency division multiplexing (OFDM) symbol, a single-carrier frequency division multiple access (SC-FDMA) symbol, an orthogonal frequency division multiple access (OFDMA) symbol, or symbols corresponding to various waveforms in future communication systems. In some embodiments, a slot may be replaced by a time instance, mini-slot, etc.

[0047] In some embodiments, the transmission unit carrying a modulation symbol is a resource element (RE), where RE is the minimum hourly frequency resource used to transmit a modulation symbol, including a subcarrier and radio resources on the symbol. The hourly frequency resources consisting of one or more subcarriers on one or more symbols constitute a physical resource block (PRB). In one embodiment, S1 consecutive symbols and C1 consecutive subcarriers correspond to the hourly frequency resources, which constitute a physical resource block, where S1 and C1 are positive integers.

[0048] In some embodiments, when classifying information based on classification parameters, threshold values, or preset threshold values, related to these classification parameters are required. These threshold values ​​can be at least one of the following: real numbers, positive integers, integers, Boolean values, characters, or strings. The threshold values ​​can be agreed upon by the base station and the terminal, or be default values, or empirical values ​​obtained through simulation or practice, or values ​​indicated to each other by communication nodes through higher-layer and / or physical-layer signaling. For ease of differentiation, a first threshold, a second threshold, etc., can be included; these are only used to distinguish different threshold values, not for sorting. In other embodiments, thresholds can be replaced by threshold groups, each threshold group including one or more thresholds.

[0049] In some embodiments, the communication node selects an information processing method to process the received information, thereby obtaining an information processing result. In some embodiments, the information processing result is also a type of information. In some embodiments, the processing result includes one or more channel state information, or one or more beam parameter information. In one embodiment, the information can be obtained based on the received reference signal, including but not limited to at least one of the following: channel information, angle information, position information, channel state information, and beam parameter information.

[0050] In some embodiments, channel information is information obtained from a reference signal (such as CSI-RS) to describe the channel environment between communication nodes. In one embodiment, channel information is a complex matrix, which may be called a channel matrix. The size of the channel matrix is ​​related to the number of transmit antennas Nt, the number of receive antennas Nr, and the number of resource elements. For example, there is at least one Nr*Nt channel matrix on a physical resource block (PRB).

[0051] In some embodiments, the channel information may include at least one of the following: time-domain channel information, frequency-domain channel information, one or more eigenvectors of the correlation matrix corresponding to the time-domain channel information, one or more singular vectors of the correlation matrix corresponding to the time-domain channel information, one or more eigenvectors of the correlation matrix corresponding to the frequency-domain channel information, one or more singular vectors of the correlation matrix corresponding to the frequency-domain channel information, a precoding matrix corresponding to the frequency-domain channel, a precoding matrix corresponding to the time-domain channel, one or more codewords corresponding to the frequency-domain channel, and one or more codewords corresponding to the time-domain channel. Here, both the time-domain channel information and the frequency-domain channel information can represent information describing channel characteristics between at least one transmit antenna and at least one receive antenna, and can be a matrix or a multi-dimensional array or matrix.

[0052] In some embodiments, a vector can also be referred to as a matrix. A matrix can also be replaced by concepts such as tensors and arrays.

[0053] In some embodiments, a beam includes a transmit beam, a receive beam, a receive beam, and a transmit beam pair, and a transmit beam and a receive beam pair. In some embodiments, a beam is a resource, such as a reference signal resource, a transmit spatial filter, a receive spatial filter, a spatial filter, spatial reception parameters, transmit precoding, receive precoding, an antenna port, an antenna weight vector, an antenna weight matrix, etc. A beam index can be replaced with a resource index, such as the reference signal resource index corresponding to the beam, because a beam can be bound to resources in at least one of the time domain, frequency domain, and code domain. A beam can also be a transmission mode; transmission modes can include spatial division multiplexing, frequency diversity, time diversity, beamforming, etc. In some embodiments, a beam pair includes a combination of a transmit beam and a receive beam.

[0054] In some embodiments, the information processing methods include at least linear and nonlinear information processing methods. Here, nonlinear information processing methods include, but are not limited to, various advanced information processing technologies, such as AI. In some embodiments, for ease of description, nonlinear information processing methods are also referred to as first-type information processing methods, and linear information processing methods are also referred to as second-type information processing methods.

[0055] In some embodiments, AI includes self-learning devices, components, software, modules, models, functional modules, and functional functions such as machine learning (ML), deep learning, reinforcement learning, transfer learning, deep reinforcement learning, and meta-learning. In some embodiments, artificial intelligence is implemented through artificial intelligence networks (or neural networks). In some embodiments, artificial intelligence can also be implemented using various large models. In some embodiments, artificial intelligence can also be referred to as intelligent technology.

[0056] In some embodiments, a model refers to the data flow from input to output of a sample through multiple linear or nonlinear components. The model includes neural network models, non-AI modules for processing information, and functional components or functions that map input information to output information; this mapping includes linear and nonlinear mappings. In some embodiments, each model corresponds to a model identity (Model ID). In some embodiments, the model identity may also have other equivalent names or concepts such as: model index, first identifier, function indicator (ID), model indicator, etc.

[0057] In some embodiments, a communication node sends a functionality or function index to another communication node, informing the other node that the functionality can be used to process information. Here, a functionality can also be referred to as a functional module, functional function, functional mapping, etc., to describe the characteristics or type of information processing method. Function types include various types, such as those for positioning, beam management, CSI prediction, beam prediction, channel estimation, etc. The characteristics of a function include, but are not limited to, descriptions of the scenarios to which the function is adapted, descriptions of input parameters, and descriptions of output parameters. Here, one function corresponds to one or more information processing methods, and each information processing method can be implemented using one or more models. Alternatively, one function can be implemented using one or more models.

[0058] In some embodiments, a dataset is required for training, fine-tuning, and performance monitoring of the model. A dataset includes one or more pieces of information. In some embodiments, information can be interchanged with one of the following concepts: sample, measurement result, measurement parameter, data.

[0059] In some embodiments, model parameters are obtained through online or offline training. For example, the model parameters are trained by inputting at least one piece of information. Here, an piece of information (also referred to in some contexts as a sample, measurement result, measurement parameter, data, etc.) includes at least one feature and at least one label. The feature is used as the input to the model, while the sample is the ideal value corresponding to the model's output, used for performance monitoring or calculating the loss function, etc.

[0060] In some embodiments, a piece of information includes P features and Q labels. Here, P is a positive integer, and Q is an integer greater than or equal to 0. Multiple samples constitute a dataset.

[0061] In some embodiments, a feature can be an array; in some embodiments, a label is also an array. Here, the array can be a vector, a matrix, or a tensor larger than two dimensions. The dimension of the array corresponding to the sample is also called the dimension of the sample array. Each element in the array can be a discrete value, a real value, a real value between 0 and 1, or a real value between -0.5 and 0.5, etc. It should be noted that in some embodiments, the elements in the array corresponding to the information need to be quantized. Different numbers of quantization bits will yield information with different quantization precisions, called the quantization precision of the information.

[0062] In some embodiments, CSI includes downlink channel state information and uplink channel state information, which are referred to as downlink channel state information and uplink channel state information, respectively.

[0063] In some embodiments, downlink channel state information includes, but is not limited to, at least one of the following: channel state information - reference signal resource indicator (CSI-RS resource indicator, CRI), synchronization signals block resource indicator (SSBRI), L1 reference signal received power (L1-RSRP), differential RSRP (differential L1-RSRP), L1 signal-to-interference noise ratio (L1-SINR), differential L1-SINR (differential L1-SINR), reference signal received quality (RSRQ), differential RSRQ, channel quality indicator (CQI), wideband CQI, subband CQI, precoding matrix indicator (PMI), layer indicator (LI), rank indicator (RI), precoding information, channel information, capability index, and time-domain channel properties (TDCP).

[0064] In some embodiments, L1-RSRP or differential RSRP is collectively referred to as L1-RSRP, or simply RSRP. In some embodiments, L1-SINR or differential SINR is collectively referred to as L1-SINR, or simply SINR.

[0065] In some embodiments, the uplink channel state information includes, but is not limited to, at least one of the following: uplink sounding signal resource indicator (SRS resource Indicator, SRI), uplink sounding signal resource set indicator (SRSI), transmitted precoding matrix indicator (TPMI), transmitted rank indicator (TRI), modulation and coding scheme (MCS), L1-RSRP, L1-SINR, and L1-RSRQ. Additionally, TPMI and TRI may be jointly coded, using precoding information and the number of layers (PINL) field from the DCI.

[0066] In some embodiments, the precoding information includes a first type of precoding information and a second type of precoding information. The precoding information may include the precoding itself or the quantization value corresponding to the precoding, precoding matrix indicators (PMIs) for various subbands or widebands, etc.

[0067] In some embodiments, the first type of precoding information is precoding information implemented in a nonlinear manner, such as precoding information obtained based on AI and other technologies, including CSI generated by compression based on at least one dimension of space-time-frequency, such as channel state information generated by joint space-frequency compression and channel state information generated by joint space-time-frequency compression.

[0068] In some embodiments, the second type of precoding information is traditional precoding information generated using linear techniques, such as codebook-based precoding information, or various DFT vector-based codebook acquisition techniques. The precoding matrix indicator PMI in this disclosure is one type of codebook-based precoding information.

[0069] In some embodiments, the correlation parameters include, but are not limited to, one of the following: correlation, cosine similarity (CS), mean squared error (MSE), squared generalized cosine similarity (SGCS), normalized mean squared error (NMSE), channel coherence time, and time-difference carrier-phase (TDCP). The definitions of the correlation parameters will not be elaborated further below.

[0070] In some embodiments, the channel rank can also be replaced by one of the following concepts: layer, codeword, transport layer, rank, row / column, number of receive antennas, number of transmit antennas, number of reference signal ports, number of transmit ports, number of receive ports, etc. Further details will not be provided in other embodiments.

[0071] In some embodiments, the statistical value of a set of numbers refers to calculating one of the following from the set of numbers: weighted average, geometric mean, harmonic mean, arithmetic mean, maximum value, minimum value, and variance. In other embodiments, the set of numbers is replaced by a set of parameters, or one or more parameter values. Further details will not be provided below.

[0072] In some embodiments, data transmission involves carrying data on uplink transmission resources. In one embodiment, transmitting a CSI report means transmitting the content indicated in the CSI report, such as CSI data, etc., where transmission includes sending or receiving.

[0073] In some embodiments, to transmit measurement results, such as channel state information, at the physical layer, the communication node needs to configure a report (e.g., a CSI report or CSI report configuration). This report defines at least one of the following parameters: time-frequency resources used to transmit the measurement results, report quantity, report time-domain type (reportConfigType), channel measurement resources, interference measurement resources, and measurement bandwidth. The report can be transmitted on uplink resources, including PUSCH and PUCCH, and the report time-domain type includes periodic reports (e.g., periodic CSI report, P-CSI), aperiodic reports (e.g., aperiodic CSI report, AP-CSI), and semi-persistent reports (e.g., semi-persistent CSI report, SP-CSI).

[0074] In some embodiments, the antenna is a physical antenna. In some embodiments, the antenna is a logical antenna. In some embodiments, the port and antenna, antenna port, reference signal port, and pilot port are interchangeable. In some embodiments, the antenna is a transmitting antenna. In some embodiments, the antenna is a receiving antenna. In some embodiments, the antenna includes an antenna pair consisting of a transmitting antenna and a receiving antenna.

[0075] The technical solutions provided in this disclosure can be applied to various wireless communication systems, such as third-generation (3G), fourth-generation (4G) mobile communication technologies and new radio (NR) wireless communication systems using fifth-generation (5G) technologies, future wireless communication systems, such as sixth-generation mobile communication systems, or multiple communication convergence systems, etc. This disclosure does not limit these applications.

[0076] The wireless communication system in this disclosure may include network-side devices (e.g., including but not limited to base stations) and receiving-side devices (e.g., including but not limited to terminals). The first communication node and the second communication node may each be a base station or a terminal. The first communication node and the second communication node may be simply referred to as the first node and the second node, respectively. In one embodiment, the first communication node is a base station and the second communication node is a terminal. In another embodiment, the first communication node is a base station and the second communication node is a base station. In yet another embodiment, the first communication node is a terminal and the second communication node is a terminal. In yet another embodiment, the first communication node is a terminal and the second communication node is a base station. In some embodiments, the communication node may be a first node and / or a second node; in some embodiments, the communication node may also be simply referred to as a node, and a node may be either a first node or a second node.

[0077] Figure 1 is a schematic diagram of a wireless communication system according to some embodiments. As shown in Figure 1, the wireless communication system includes, but is not limited to, a first node 110 and a second node 120. Here, the first node 110 and the second node 120 can transmit and receive wireless signals and perform related interactions.

[0078] In a wireless communication scenario, the first node 110 and the second node 120 communicate via a wireless channel. For example, the first node 110 may be a base station, and the second node 120 a terminal; the base station and the terminal communicate via a wireless channel. Alternatively, the first node 110 may be a wireless router, and the second node 120 a terminal; the wireless router and the terminal communicate via a wireless channel. Another example is that the first node 110 may be a first base station, and the second node 120 a second base station; the first base station and the second base station communicate via a wireless channel. Yet another example is that the first node 110 may be a first terminal, and the second node 120 a second terminal; the first terminal and the second terminal communicate via a wireless channel. Finally, the first node 110 may be a base station, and the second node 120 a repeater; the base station and the repeater communicate via a wireless channel. Finally, the first node 110 may be a repeater, and the second node 120 a terminal; the repeater and the terminal communicate via a wireless channel. For example, node 110 is a first repeater, and node 120 is a second repeater; the first repeater and the second repeater communicate via a wireless channel. Alternatively, node 110 can be a base station, and node 120 a satellite; the satellite and the base station communicate via a wireless channel. Another example: node 110 can be a satellite, and node 120 a base station; the base station and the satellite communicate via a wireless channel. Yet another example: node 110 can be a terminal, and node 120 a satellite; the satellite and the terminal communicate via a wireless channel. Again, node 110 can be a satellite, and node 120 a terminal; the terminal and the satellite communicate via a wireless channel. Finally, node 110 can be ground equipment, and node 120 can be an aircraft; the aircraft and the ground equipment communicate via a wireless channel. Finally, node 110 can be a first aircraft, and node 120 a second aircraft; the first aircraft and the second aircraft communicate via a wireless channel.

[0079] In this disclosure, the base station can be a base station in Long Term Evolution (LTE), Long Term Evolution Advanced (LTEA), or an evolved Node B (eNB or eNodeB), a base station device in a fifth-generation wireless communication system, or a base station in a future wireless communication system (such as 6G). The base station can include various macro base stations, micro base stations, home base stations (Femtocell or Home eNodeB), wireless remote extensions, reconfigurable intelligent surfaces (RISS), routers, wireless fidelity (WIFI) devices, and other network-side devices.

[0080] In this disclosure, the terminal is a device with wireless transceiver capabilities, which can be deployed on land, including indoors or outdoors, or inside a vehicle; it can also be deployed on water (such as on ships); and it can also be deployed in the air (e.g., on airplanes, balloons, satellites, drones, various aircraft, etc.). The terminal can be a mobile phone, tablet computer, computer with wireless transceiver capabilities, virtual reality (VR) terminal, augmented reality (AR) terminal, wireless terminal in industrial control, wireless terminal in self-driving, wireless terminal in remote medical care, wireless terminal in smart grid, wireless terminal in transportation safety, wireless terminal in smart city, wireless terminal in smart home, wireless terminal on drones and other aircraft, etc. The embodiments of this disclosure do not limit the application scenarios. A terminal may also be referred to as a user, user equipment (UE), access terminal, UE unit, UE station, mobile station, mobile station, remote station, remote terminal, mobile device, UE terminal, wireless communication equipment, UE agent, or UE device, etc. The embodiments disclosed herein are not limited to these terms.

[0081] The application scenarios of the embodiments disclosed herein are not limited. The system architecture and business scenarios described in the embodiments of this disclosure are for the purpose of more clearly illustrating the technical solutions of the embodiments of this disclosure, and do not constitute a limitation on the technical solutions provided by the embodiments of this disclosure. As those skilled in the art will know, with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of this disclosure are also applicable to similar technical problems.

[0082] In some embodiments, a wireless communication system includes one or more base stations and one or more terminals. Each base station includes multiple antennas, and each terminal may include one or more antennas. The base station transmits a reference signal on at least one reference signal resource, and the terminal receives the reference signal on at least one reference signal resource and measures the reference signal to obtain one or more pieces of information. This information is then transmitted to the base station. The base station collects information from different terminals or information from the same terminal at different times to form a dataset. The terminal itself may also locally store a subset of the dataset consisting of one or more pieces of information. The base station and the terminal may also transmit the obtained dataset to a third-party server for storage, or receive datasets stored from a third-party server.

[0083] In some embodiments, the features and / or labels of the information include one or more types of channel state information. In one embodiment, both the features and / or labels of the information are channel matrices.

[0084] In some embodiments, the information is characterized by channel information corresponding to one or more base stations, and the information is labeled with at least one of the following: the coordinates of the terminal, the absolute coordinates of the terminal, the polar coordinates of the terminal, line-of-sight parameters, angle-related information, and transmission time-related information. In one embodiment, the line-of-sight parameters include, but are not limited to, line-of-sight (LOS) / non-line-of-sight (NLOS) indicators, LOS probability, NLOS probability, and soft information about LOS or NLOS.

[0085] In some embodiments, the information is characterized by a set of received reference signal quality-related information, and the information is labeled with at least one of the following: the coordinates of the terminal, the absolute coordinates of the terminal, the polar coordinates of the terminal, the line-of-sight parameter, the angle-related information, and the transmission time-related information.

[0086] In some embodiments, the information is characterized by a first set of received reference signal quality related information, and the information is labeled by a second set of received reference signal quality related information. Here, the number L1 contained in the first set of received reference signal quality related information and the number L2 contained in the second set of received reference signal quality related information are different. For example, in one embodiment, the characteristic is a first set of RSRPs, and the label is a second set of RSRPs. Here, the beam corresponding to the first set of RSRPs is a subset of the beam corresponding to the second set of RSRPs, or the beam corresponding to the first set of RSRPs is a wide beam, and the beam corresponding to the second set of RSRPs is a narrow beam.

[0087] In some embodiments, the information is characterized by N1 sets of received reference signal quality-related information, and the information is labeled by another M1 sets of received reference signal quality-related information. Here, the i-th set of received reference signal quality-related information corresponds to the received reference signal quality-related information at the i-th time, where the i-th time can correspond to the i-th time slot, or the time slot corresponding to the i-th period of the reference signal, i = 1, ..., N1+M1. In one embodiment, the N1 sets of received reference signal quality-related information are received reference signal quality-related information obtained by the measurement window, and the other M1 sets of received reference signal quality-related information are received reference signal quality-related information obtained by the prediction window.

[0088] In some embodiments, transmission time-related information includes at least one of the following: time of arrival (TOA), reference signal time difference (RSTD), relative time of arrival (RTOA), transmit-receive time difference (Rx-Tx time difference), transmit-receive time difference (Tx-Rx time difference), etc.

[0089] In some embodiments, angle-related information includes at least one of the following: angle of arrival (AoA), angle of departure (AOD), zenith angle of arrival (ZOA), and azimuth angle of departure (AOD), wherein the angle of departure includes the zenith angle of departure (ZOD) and the azimuth angle of departure (AOA).

[0090] In some embodiments, the information related to the quality of the received reference signal includes at least one of the following: reference signal received power (RSRP or L1-RSRP), signal to interference plus noise ratio (SINR) (or L1-SINR), CQI, signal-to-noise ratio (SNR), and RSRQ.

[0091] In some embodiments, the information label may include location coordinates or other location parameter information, such as at least one of TOA, RSTD, line-of-sight parameters, or angle information. In some embodiments, the information label may also include beam metric parameters in beam management, such as at least one of L1-SINR, L1-RSRP, CRI, SSBRI, etc. In some embodiments, the information label may also be channel state information, such as channel information or feature vectors. In some embodiments, the information label may also be the channel matrix in channel estimation.

[0092] In some embodiments, the base station transmits a reference signal to the terminal; the terminal obtains channel information over N1 time slots by measuring the reference signal, using this information as a feature, and obtains channel information over M1 time slots, using this information as a tag. Here, N1 and M1 are positive integers, the N1 time slots are within a measurement window, and the M1 time slots are within a prediction window. In one embodiment, the N1 time slots and the M1 time slots are non-contiguous time slots, and can be multiple time slots that are equally spaced or unequally spaced.

[0093] In some embodiments, the base station sends a reference signal to the terminal; the terminal obtains the channel information in the time slot by measuring the reference signal, and uses a portion of the channel information as a feature as a tag for the information.

[0094] In another embodiment, the terminal sends an uplink reference signal, such as an SRS. The base station obtains channel information by receiving the SRS and, based on the channel information, obtains the channel matrix or one or more feature vectors of the channel matrix, or their quantized values, for each subband. These are then used as one or more pieces of information.

[0095] The dataset in this disclosure is also referred to as a data set, dataset, or collection of information, and is a collection of one or more pieces of information. In some embodiments, the base station receives one or more first datasets (including N pieces of information) and forms them into a large dataset, which is then stored locally or transmitted to a third-party dataset storage server. When the base station and / or the terminal needs to train a model, R pieces of information are extracted from the large dataset. To distinguish it from the first dataset, the dataset containing R pieces of information is referred to as the second dataset, where R is a positive integer. In some embodiments, during a model training or model testing process, all or part of the information in one or more second datasets may be used, and this is not limited.

[0096] This disclosure provides an information transmission method that can be applied to a first node. As shown in Figure 2, the method includes the following steps:

[0097] S101. Obtain classification parameters and divide N pieces of information into M information groups based on the classification parameters.

[0098] Here, N and M are both positive integers, and M is less than or equal to N.

[0099] In some embodiments, the classification parameters include quality parameters and / or correlation parameters.

[0100] In some embodiments, the quality parameters include at least one of the following: wideband signal-to-interference-plus-noise ratio, subband signal-to-interference-plus-noise ratio, reference signal received power, reference signal received quality, channel quality indication, modulation and coding scheme, interference intensity, line-of-sight parameter, quantization accuracy, quantization step size, and tag level.

[0101] In some embodiments, the correlation parameter includes at least one of the following: time-domain correlation parameter, spatial-domain correlation parameter, and frequency-domain correlation parameter.

[0102] In some embodiments, the time-domain correlation parameter is related to at least one of the following: the moving speed of the first node, the carrier spacing, the time interval between information segments, and the period of the reference signal. It can be replaced by at least one of the following: the moving speed, the carrier spacing, the time interval between information segments, and the period of the reference signal.

[0103] In some embodiments, the spatial correlation parameter is related to at least one of the following: the geographic location region of the first node, the distance between the first and second nodes, LOS and NLOS, the transmitting antenna topology, the receiving antenna topology, and the transmitting and / or receiving beams used. This can be replaced by at least one of the following: geographic location region, the distance between the first and second nodes, LOS and NLOS, the transmitting antenna topology, and the receiving antenna topology.

[0104] In some embodiments, frequency domain correlation parameters include, but are not limited to, one of the following: bandwidth size, number of subbands, number of physical resource blocks, and bandwidth part (BWP).

[0105] In some embodiments, the first node acquiring classification parameters includes: the first node acquiring first signaling, the first signaling indicating the classification parameters. In some embodiments, the first node receives first signaling sent by a second node. In some embodiments, the first node sends first request information to the second node; correspondingly, the second node receives the first request information sent by the first node, the first request information requesting the second node to send one or more classification parameters; then the second node sends first signaling to the first node; correspondingly, the first node receives the first signaling sent by the second node.

[0106] For example, the terminal receives a first signaling, which indicates that the classification parameter is at least one of the following: wideband signal-to-interference-plus-noise ratio, subband signal-to-interference-plus-noise ratio, reference signal received power, reference signal received quality, channel quality indication, modulation and coding scheme, interference intensity, line-of-sight parameter, quantization accuracy, quantization step size, tag level, time domain correlation parameter, spatial domain correlation parameter, and frequency domain correlation parameter.

[0107] In some embodiments, the classification parameters can also be determined by the negotiation method between the first node and the second node or by a pre-configuration method.

[0108] For example, taking the first node as the terminal and the second node as the base station, the base station sends classification parameters to the terminal via first signaling, and the terminal obtains the classification parameters by receiving the first signaling. Alternatively, the terminal obtains the classification parameters through a pre-configured method (the default method), such as the terminal determining the classification parameters of the information based on the channel scenario, the characteristics of the information, or the available classification parameters. For example, if the terminal can obtain the quality parameters of the information, it uses the quality parameters to classify the information; if the terminal cannot obtain the quality parameters, it can use the correlation of the information to classify it. Alternatively, the terminal and the base station obtain the classification parameters through negotiation.

[0109] In some embodiments, in order to classify information, in addition to obtaining classification parameters, it is also necessary to obtain one or more threshold values ​​(e.g., the first preset threshold and the second preset threshold below) related to the classification parameters. In some embodiments, threshold values ​​can be replaced by threshold intervals.

[0110] In some embodiments, the first node acquires second signaling, which indicates a threshold value or threshold range for classification parameters. In some embodiments, the first node receives second signaling sent by the second node. In some embodiments, the first node sends second request information to the second node; correspondingly, the second node receives the second request information sent by the first node, which requests the second node to send one or more threshold values ​​or threshold ranges for classification parameters; then the second node sends second signaling to the first node; correspondingly, the first node receives the second signaling sent by the second node.

[0111] In some embodiments, the threshold value or threshold range of the classification parameter can also be determined by the following methods: negotiation between the first node and the second node or by pre-configuration.

[0112] For example, taking the first node as the terminal and the second node as the base station, the base station sends at least one threshold value related to the classification parameters to the terminal via a second signaling. The terminal obtains the at least one threshold value related to the classification parameters by receiving the second signaling. In some embodiments, the terminal obtains the at least one threshold value related to the classification parameters through a pre-configured method (the default method). In some embodiments, the terminal and the base station obtain the at least one threshold value related to the classification parameters through negotiation. In other embodiments, the thresholds mentioned herein can be replaced by threshold groups or threshold intervals.

[0113] For example, taking the first node as the terminal, the terminal can acquire N pieces of information at different times and / or different locations. These N pieces of information are then classified using classification parameters to obtain M information groups.

[0114] In some embodiments, different information groups among the M information groups may include different numbers of information. There may be information groups among the M information groups that contain only 0 pieces of information. In some embodiments, information groups containing only 0 pieces of information will be deleted, and each of the M information groups will contain at least one piece of information.

[0115] In some embodiments, the classification parameters include quality parameters, and N pieces of information are divided into M information groups based on the classification parameters, including one of the following implementation methods:

[0116] a) Divide the N pieces of information into M information groups based on M preset quality intervals. For each piece of information, determine the quality parameter of the information. If the quality parameter of the information belongs to the i-th preset quality interval, determine that the information belongs to the i-th information group, where i is less than or equal to M.

[0117] (b) Obtain the quality parameter for each of the N pieces of information. Sort the N pieces of information according to the quality parameter ranking. Based on the ranking, divide the N pieces of information into M equal groups. Here, the number of pieces of information in the last group may be less than the number of pieces of information in the first group.

[0118] c) Divide the N pieces of information into two information groups based on a threshold value (first preset threshold) related to a quality parameter. For example, obtain the quality parameter of each of the N pieces of information. If the quality parameter of each piece of information is greater than or equal to the first preset threshold, the information belongs to the first information group; or, if the quality parameter of each piece of information is less than the first preset threshold, the information belongs to the second information group. For example, if the quality parameter of the j-th piece of information is greater than the first preset threshold, then the j-th piece of information is assigned to the first information group; otherwise, it is assigned to the second information group, where j is a positive integer less than or equal to N.

[0119] In some embodiments, when the classification parameters include quality parameters, the quality parameter of any information in at least one information group is greater than a third preset threshold T, where T is a positive real number.

[0120] In some embodiments, the classification parameters include relevance parameters, and the classification parameters are used to divide N pieces of information into M information groups, including one of the following implementation methods:

[0121] a) For each piece of information among N pieces of information, determine the correlation parameters a1, a2, ..., aM between the information and M reference information. If the correlation parameter aj between the information and the j-th reference information among the M reference information is the smallest (i.e., aj is the smallest among a1, a2, ..., aM), determine that the information belongs to the j-th information group, where j is less than or equal to M. In one embodiment, a1, a2, ..., aM are real numbers from 0 to 1.

[0122] (b) Obtain the relevance parameter for each of the N pieces of information. Sort the N pieces of information according to the magnitude of their qualitative relevance parameters. Based on this sorting, divide the N pieces of information into M equal groups. Here, the last group may contain fewer pieces of information than the first group.

[0123] c) Divide the N pieces of information into two information groups based on a threshold value related to a relevance parameter (e.g., a second preset threshold). Obtain the relevance parameter of each of the N pieces of information. If the relevance parameter of each piece of information is less than or equal to the second preset threshold, the information belongs to the first information group; or, if the relevance parameter of each piece of information is greater than the second preset threshold, the information belongs to the second information group. For example, if the relevance parameter of the j-th piece of information is less than or equal to the second preset threshold, then this information is assigned to the first information group; otherwise, it is assigned to the second information group, where j is a positive integer less than or equal to N.

[0124] d) Divide the N pieces of information into M information groups based on M preset relevance intervals. For each piece of information, determine the relevance parameter of the information. If the relevance parameter of the information belongs to the i-th preset relevance interval, determine that the information belongs to the i-th information group, where i is less than or equal to M.

[0125] Here, the relevance parameter of an information can be its relevance to reference information. Reference information can be a piece of information within an information group, such as the first piece of information. In some embodiments, reference information can be the first M pieces of information (i.e., the M pieces of information with the smallest information index), the last M pieces of information, or the M pieces of information with the best quality. Of course, other methods can also be used to determine reference information, and there are no restrictions here. For example, M reference information can be obtained by taking one piece of information every C pieces of information based on its index or corresponding acquisition time. Alternatively, it can be obtained by dividing the information into multiple regions based on geographical coordinates, with one reference piece of information for each region. Here, M is a positive integer.

[0126] In other embodiments, the information in the above-mentioned information group is highly correlated, that is, it is quite similar. Sometimes when training a model, the model trained with similar information does not perform well. Therefore, it is necessary to minimize the correlation between the information in the same group that needs to be fed back.

[0127] In some embodiments, where the classification parameters include a correlation parameter, the correlation parameter of any information in at least one information group is less than a fourth preset threshold.

[0128] In some embodiments, when the classification parameters include a correlation parameter, the correlation parameter between any two pieces of information in the same information group is less than a fifth preset threshold S, where S is a positive real number.

[0129] In some embodiments, the classification parameters further include at least one of the following: associated ID, reference signal resource indication, reference signal resource set indication, and cell indication.

[0130] In some embodiments, taking the first node as the terminal and the second node as the base station as an example, the base station implicitly instructs the terminal to provide an auxiliary identifier. After obtaining the auxiliary identifier, the terminal groups information with the same auxiliary identifier into a single information group. Different auxiliary identifiers correspond to different information groups. Here, the implicit method includes binding the auxiliary identifier to a resource. The auxiliary identifier includes, but is not limited to, one of the following: a reference signal resource indicator, a reference signal resource set indicator, a CSI report indicator, a cell ID, a sector ID, a port group ID, etc. In other embodiments, the indicator can be replaced with an identifier or an index.

[0131] In some embodiments, taking the first node as the terminal and the second node as the base station as an example, the base station instructs the terminal to provide an auxiliary identifier through higher-layer and / or physical-layer signaling. After obtaining the auxiliary identifier, the terminal groups information with the same auxiliary identifier into one information group. Different auxiliary identifiers correspond to different information groups.

[0132] In some embodiments, taking the first node as the terminal and the second node as the base station as an example, the base station instructs the terminal to provide a reference signal resource indication through higher-layer and / or physical-layer signaling. After obtaining the reference signal resource indication, the terminal groups information with the same reference signal resource indication into one information group. Different reference signal resource indications correspond to different information groups.

[0133] In some embodiments, taking the first node as the terminal and the second node as the base station as an example, the base station instructs the terminal to provide a reference signal resource set indication via higher-layer and / or physical-layer signaling. After obtaining the reference signal resource set indication, the terminal groups information with the same reference signal resource set indication into one information group. Different reference signal resource set indications correspond to different information groups. In other embodiments, the reference signal resource set here can be replaced by cell ID, CSI report ID, or transmission configuration indicator (TCI). The reference signal resource set indication may include, but is not limited to, one of the following: Channel State Information Reference Signal Resource Set Identifier (CSI-RS resource set ID), Synchronization Signal Block Resource Set Identifier (SSB resource set ID), or Probe Reference Signal Resource Set Identifier (SRS resource set ID).

[0134] In one embodiment, taking the first node as the terminal and the second node as the base station as an example, the area served by the base station is divided into M equal areas. If the physical location of the terminal is in the i-th area, then the information it obtains belongs to the i-th information group, i = 1, ..., M.

[0135] In one embodiment, the transmitting and / or receiving beams used by the communication node (first node) are divided into M different beam groups. If the communication node uses the i-th beam group to obtain information, then the information it obtains belongs to the i-th information group, i = 1, ..., M.

[0136] In one embodiment, the different moving speeds of the communication node (first node) are divided into M different speed intervals. If the moving speed of the communication node (first node) is in the i-th moving interval, then the information it obtains belongs to the i-th information group, i = 1, ..., M.

[0137] In one embodiment, the quantization precision of different codewords by the communication node (first node) is divided into M different quantization precision intervals. If the information obtained by the communication node (first node) is quantized using the i-th quantization precision, then the information it obtains belongs to the i-th information group, i = 1, ..., M.

[0138] In one embodiment, the communication node (first node) divides the interference into M different interference intervals according to the different levels of interference it receives. If the communication node (first node) measures the interference it receives while measuring the information, and the interference it receives belongs to the i-th interference interval, then the information it obtains belongs to the i-th information group, i = 1, ..., M.

[0139] S102, Transmit L information groups out of M information groups.

[0140] Here, L is a positive integer, and L is less than or equal to M.

[0141] In some embodiments, the first node sends L of the M information groups to the second node.

[0142] In some embodiments, the first node determines the transmission priority of each of the M information groups. The first node determines the L information groups with the highest transmission priority among the M information groups based on the transmission priority of each of the M information groups. The first node transmits the L information groups with the highest transmission priority among the M information groups. Correspondingly, the second node receives the L information groups with the highest transmission priority among the M information groups.

[0143] In some embodiments, the first node transmits L of the M information groups, including: determining the transmission priority of each of the M information groups; based on the transmission priority of each of the M information groups, transmitting the L information groups among the M information groups whose transmission priority is greater than a preset threshold; correspondingly, the second node receives the L information groups among the M information groups whose transmission priority is greater than the preset threshold.

[0144] In some embodiments, the first node determines the transmission priority of each of the M information groups according to the index of each of the M information groups.

[0145] In one embodiment, the transmission priority of an information group with a larger information group index is less than the transmission priority of an information group with a smaller information index.

[0146] For example, when the information groups are classified according to the quality parameter of the information, and the information quality of the i-th information group is greater than the information quality of the j-th information group, where 1 <= i < j <= M. For example, the M information groups are sorted in descending order of information quality. For each channel group among the M information groups, the sorting sequence number of the channel group is used as the index of the channel group. That is, there is a negative correlation between the index of the channel group and the quality of the channel group. That is, the smaller the information group index, the greater the information quality in the information group, and the higher the transmission priority of the information group.

[0147] In one embodiment, the transmission priority of an information group with a larger information group index is greater than the transmission priority of an information group with a smaller information group index.

[0148] For example, when information groups are classified according to the quality parameters of information, and the information quality of the i-th information group is lower than that of the j-th information group, where 1 <= i < j <= M. For example, the M information groups are sorted in ascending order of information quality. For each channel group among the M information groups, the sorting sequence number of the channel group is used as the index of the channel group. That is, there is a negative correlation between the index of the channel group and the quality of the channel group. That is, the larger the information group index, the higher the information quality in the information group, and the higher the transmission priority of the information group.

[0149] In other embodiments or examples, the information quality can also be replaced with other indicators of information groups, that is, the information groups are sorted according to the indicators of the information groups from large to small or from small to large.

[0150] Therefore, the index of the information group reflects the information quality in the information group to a certain extent. Therefore, the transmission priority of each information group among the M information groups can be determined according to the index size of each information group among the M information groups.

[0151] In some embodiments, the first node determines the transmission priority of each information group among the M information groups according to the indicators of each information group among the M information groups.

[0152] In some embodiments, the indicators of the information group include at least one of the following: signal-to-interference-plus-noise ratio of the broadband, signal-to-interference-plus-noise ratio of the sub-band, reference signal received power, reference signal received quality, channel quality indicator, modulation and coding strategy, interference intensity, quantization accuracy, quantization step size, level of the label, time domain correlation (temporal correlation), spatial domain correlation (spatial correlation).

[0153] In one embodiment, the larger the indicator of the information group, the higher the transmission priority of the information group. That is, if the indicator of the i-th information group is greater than the indicator of the j-th information group, the transmission priority of the i-th information group is higher than that of the j-th information group. Here, i and j are positive integers less than or equal to M.

[0154] In another embodiment, the smaller the indicator of the information group, the higher the transmission priority of the information group. This is related to the specific indicators of the information group. That is, if the indicator of the i-th information group is less than the information indicator of the j-th information group, the transmission priority of the i-th information group is higher than that of the j-th information group. Here, i and j are positive integers less than or equal to M.

[0155] In one embodiment, the indicator of the information group is the statistical value SINR0 of the broadband SINR corresponding to all or part of the information in an information group. The larger SINR0 is, the higher the transmission priority of this information group. The SINR here can include the absolute value or the difference value. In other embodiments, the SINR can also be replaced with SNR, etc.

[0156] In one embodiment, the index of an information group is the statistical value L1-SINR0 of all or part of the information in the information group. The larger the L1-SINR0, the higher the transmission priority of the information group. Here, L1-SINR can include absolute value or differential value.

[0157] In one embodiment, the index of an information group is the statistical value L1-RSRP0 of all or part of the information in the information group. The larger the L1-RSRP0, the higher the transmission priority of this information group. Here, L1-RSRP can include absolute values ​​or differential values. In other embodiments, RSRP can also be replaced by RSRQ, etc.

[0158] In one embodiment, the index of an information group is the statistical value CQI0 of the CQI corresponding to all or part of the information in the information group. The larger the CQI0, the higher the transmission priority of the information group. Here, CQI0 can include absolute value or differential value.

[0159] In one embodiment, the index of an information group is the statistical value MCS0 of the MCS corresponding to all or part of the information in the information group. The larger the MCS0, the higher the transmission priority of the information group.

[0160] In one embodiment, the metric for an information group is a statistical value P0 representing the quantization precision of all or part of the information in the group. A larger P0 indicates a higher transmission priority for the information group. In other embodiments, information precision can be replaced by other concepts, such as the number of bits in the information quantization or the quality of the tag.

[0161] In one embodiment, the index of an information group is the statistical value IM0 of the interference intensity corresponding to all or part of the information in the information group. The smaller the IM0, the higher the transmission priority of the information group.

[0162] In one embodiment, the index of an information group is the statistical value S0 of the quantization step size corresponding to all or part of the information in the information group. The smaller S0 is, the higher the transmission priority of the information group.

[0163] In one embodiment, the index of an information group is the statistical value T0 of the temporal correlation of all or part of the information in the information group. The smaller T0 is, the higher the transmission priority of the information group. In some scenarios, the larger T0 is, the higher the transmission priority of the information group.

[0164] In one embodiment, the index of an information group is the statistical value SP0 of the spatial relevance of all or part of the information in the information group. The smaller the SP0, the higher the transmission priority of the information group. In some scenarios, the larger the SP0, the higher the transmission priority of the information group.

[0165] It is understandable that a single metric may not be sufficient to completely determine the transmission priority of each of the M information groups. For example, if two information groups in the M information groups have the same metric, the transmission priority of these two information groups cannot be determined. Based on this, the present disclosure provides the following method.

[0166] In some embodiments, the indicators of each information group include C indicators, where C is a positive integer. Determining the transmission priority of each of the M information groups based on the indicators of each of the M information groups includes: determining the transmission priority of each of the M information groups based on the first i indicators out of the C indicators. For at least two information groups in the M information groups that have the same first i indicators, determining the transmission priority of each of the at least two information groups based on the (i+1)th indicator of each of the at least two information groups, where i is a positive integer less than C-1 or C.

[0167] For example, the priorities of M information groups are determined based on C indicators. Then, based on the sorting of the C information group indicators, the transmission priority of the M information groups is first determined by the i-th sorting indicator. For information groups with the same i-th sorting indicator, the transmission priority is sorted by the (i+1)-th sorting indicator, and so on, until the transmission priorities of all M information groups are determined. Here, i = 1, ..., C.

[0168] For example, suppose there are 5 information groups (information group 1, information group 2, information group 3, information group 4, and information group 5). Each information group has 5 indicators, arranged in the following order: indicator A, indicator B, indicator C, indicator D, and indicator E. First, based on indicator A, the transmission priorities of the 5 information groups are determined from high to low as information group 3, information group 2, information group 1, information group 4, and information group 5. Here, information group 2, information group 1, and information group 4 have the same value for indicator A, so the transmission priorities of these three information groups cannot be determined separately based on indicator A (or the determined transmission priorities of these three information groups are the same). Then, it is determined that the corresponding indicator B values ​​of these three information groups are also the same, so the transmission priorities of these three information groups are determined based on indicator C, with the transmission priorities from high to low as information group 2, information group 4, and information group 1. Here, information group 4 and information group 1 have the same value for index C. Therefore, the transmission priority of these two information groups cannot be determined separately based on index C (or the determined transmission priorities of these two information groups are the same). According to the index arrangement order, information group 4 and information group 1 have the same value for index D, but the corresponding index E values ​​are also the same. Therefore, the transmission priority of these two information groups is determined based on index E, with the transmission priorities from high to low being information group 4 and information group 1. Finally, the final transmission priorities of these 5 information groups, from high to low, are information group 3, information group 2, information group 4, information group 1, and information group 5.

[0169] In some embodiments, the order of the C indicators is determined based on the third signaling received by the first node or a pre-configured method.

[0170] In other embodiments, the metric (or the metric of the information group) may also be referred to as a performance metric, performance parameter, metric, performance metric, etc.

[0171] In some embodiments, the first node transmits L information groups out of M information groups, including: determining at least one coded block based on at least one piece of information in the L information groups, and transmitting the at least one coded block. For example, at least one piece of information in the L information groups is encoded to obtain at least one coded block, and the at least one coded block is transmitted.

[0172] In some embodiments, the first node transmits at least one coded block, including one of the following: transmitting at least one coded block in at least one channel state information report; or transmitting at least one coded block in higher-layer signaling. Correspondingly, the second node receives at least one coded block, including one of the following: receiving at least one coded block in at least one channel state information report; or receiving at least one coded block in higher-layer signaling.

[0173] In some embodiments, the first node transmitting L information groups out of M information groups means transmitting at least one piece of information from the L information groups in at least one channel state information report. In some embodiments, the first node transmitting L information groups out of M information groups means transmitting at least one piece of information from the L information groups in higher-layer signaling.

[0174] For example, taking the first node as the terminal and the second node as the base station, the terminal can acquire N pieces of information at different times and / or different locations. The N pieces of information are then classified using classification parameters to obtain M information groups. The transmission priority of the M information groups is determined. The L information groups with the highest priority are sent. The base station receives the L information groups with the highest priority. In one embodiment, the terminal sorts all the information in the L information groups with the highest priority according to a preset rule to obtain K pieces of information. The K pieces of information are then quantized and encoded to obtain at least one encoded block. The at least one encoded block is transmitted in at least one CSI report. In one embodiment, at least one CSI report corresponds to a report instance on a different time slot of the same periodic report or semi-persistent report. In some embodiments, the base station receives at least one CSI report on the uplink transmission resources indicated by at least one CSI report, obtains at least one encoded block through the at least one CSI report, and obtains K pieces of information, which belong to the L information groups, through a series of processes.

[0175] For example, taking the first node as the terminal and the second node as the base station, the terminal sorts all the information in the L highest priority information groups according to a preset rule to obtain K pieces of information. The terminal can transmit the K pieces of information in higher-layer signaling. In some embodiments, uplink transmission resources are allocated (or scheduled) to the communication node through higher-layer signaling and / or physical layer signaling. The uplink transmission resources are used to transmit uplink data (such as channel state information or datasets). Allocating (or scheduling) uplink transmission resources to the communication node through higher-layer signaling and / or physical layer signaling includes two methods: dynamic grant (DG) and configured grant (CG). Here, configuration grant includes two types: configuration grant type 1 (or first type configuration grant) indicated by higher-layer signaling and configuration grant type 2 (or second type configuration grant) indicated by both higher-layer and physical layer signaling. The dynamic grant method is indicated by physical layer signaling. In one embodiment, the base station receives K pieces of information in higher-layer signaling, and the K pieces of information belong to L information groups.

[0176] For example, taking the first node as the terminal and the second node as the base station, the terminal independently encodes the information in each of the L highest priority information groups to obtain L coded blocks. These L coded blocks are then transmitted in the L CSI reports. In one embodiment, the L CSI reports correspond to report instances on different time slots of the same periodic report or semi-persistent report. In another embodiment, the terminal can also concatenate the L codes into a single coded block and transmit it in a single CSI report. In one embodiment, the L codes can be transmitted at higher layers, and the terminal can transmit K pieces of information in higher-layer signaling. In some embodiments, the base station receives the L reports on the uplink transmission resources indicated by the L reports, obtains the L coded blocks from the L reports, and obtains K pieces of information through a series of processes. These K pieces of information belong to the L information groups. In one embodiment, the base station receives these K pieces of information in higher-layer signaling, and these K pieces of information belong to the L information groups.

[0177] In one embodiment, the M information groups include at least a first information group and a second information group, and the first information group and the second information group satisfy at least one of the following:

[0178] a) The quantization precision of the information in the first information group is higher than that of the information in the second information group. Or, the number of quantized bits in the first information group is greater than the number of quantized bits in the second information group. For example, if the SINR corresponding to the information in the first information group is higher, a higher quantization precision can be used.

[0179] b) The quantization step size (number of quantized bits) in the first information group is greater than the quantization step size (number of quantized bits) in the second information group. Or, the quantization step size in the first information group is longer than the quantization step size in the second information group. For example, the quantization step size used for the information in the first information group is a1, and the quantization step size used for the information in the second information group is a2. Here, a1 and a2 are positive real numbers, and a1 > a2.

[0180] c) The tag quality of the first information group is higher than that of the tag quality of the second information group. In some embodiments, higher tag quality may correspond to higher quantization accuracy, shorter quantization step size, or less interference.

[0181] Here, high-precision or high-quality tags require a larger number of quantized bits, necessitating greater feedback overhead. As an example, tag quality is affected by the location of the first node within the cell. For instance, if the first node is in the cell center, the channel quality is better, resulting in better tag quality; conversely, if the first node is at the cell edge, the channel quality is poor, and due to interference with channel information acquisition, the tag quality is also worse.

[0182] In some embodiments, the first node also needs to send group index information of L information groups; correspondingly, the second node receives group index information of L information groups. Here, the group index information is a non-negative integer less than M or an M-bit bitmap.

[0183] In one embodiment, group index information for L information groups is sent in the first part of the CSI report (CSI part I). For example, there is a field in the first part of the CSI report that indicates the group index information for the L information groups. In one embodiment, the group index information for each information group is an integer from 0 to M-1, indicated by log2(M) bits. In another embodiment, the group index information for the L information groups is M bits, where the i-th bit is used to indicate whether the i-th information group has been sent. For example, if the i-th bit has a first value, it means that the i-th information group has been sent; otherwise, the i-th information group has not been sent. The first value and the second value are one of the following: two different integers, two different boolean values, two different strings, two different characters, etc.

[0184] In some embodiments, the information group may also have other concepts, that is, it can be replaced with other concepts, such as including but not limited to one of the following: information set, data group, data collection. In some embodiments, information may also have other concepts, including but not limited to: data point, instance, observation point, input vector, labeled data, unlabeled data, etc.

[0185] In some embodiments, information includes a feature and a label, such as information in supervised learning. In one embodiment, a first channel matrix is ​​used as the feature, and a second channel matrix is ​​used as the label. Here, the number of antennas corresponding to the first channel matrix is ​​less than the number of antennas used by the second channel matrix.

[0186] In some embodiments, a piece of information has only one feature and no label, such as information from unsupervised learning. In one embodiment, some information is unlabeled. For example, suppose dataset D contains *a* labeled pieces of information and *ma* unlabeled pieces of information. For instance, dataset D can be represented as D = {(x1, y1), ..., (x...} a ,y a ),x a+1 ,…,x m}, here, x i For labeled information, and x i The label is y iLet i be a positive integer less than or equal to a, a be a positive integer less than m, and m be a positive integer. At this point, the terminal needs to send one or more tag enable indications, and the base station needs to receive the tag enable indications. Here, the tag enable indication is used to indicate whether a piece of information or a set of information has a tag.

[0187] In some embodiments, a piece of information has multiple features and a label, such as in a supervised learning network model with multiple inputs and a single output. In one embodiment, the channel matrix at one or more time steps is used as the feature, while the label is the channel matrix at one or more future time steps.

[0188] In some embodiments, a piece of information includes a feature and multiple labels, such as in a supervised learning network model with single input multiple output.

[0189] In some embodiments, a single piece of information may include multiple features and multiple labels, such as in a supervised learning network model with multiple inputs and multiple outputs. For example, in temporal beam prediction, the features are groups of RSRPs for multiple historical time slots, and the labels are groups of RSRPs for multiple time slots to be predicted. Some labels may also include the CRIs for multiple time slots.

[0190] In some embodiments, such as CSI prediction, CSI compression, or beamforming, the tag reliability differs under different SINRs. In this case, the terminal may need to provide the tag's reliability level. For example, for each message or group of messages, the terminal might send the tag level or reliability level of that message.

[0191] Based on this, N pieces of information are divided into M information groups according to classification parameters; L of the M information groups are then transmitted. Since the information in the transmitted L information groups is of higher quality than that in the M information groups, collecting such information can improve the quality of the acquired dataset. Using this high-quality information to train, fine-tune, or monitor the performance of the model corresponding to the information processing method is beneficial to improving the performance of the information processing method.

[0192] This disclosure provides an information transmission method that can be applied to a second node. As shown in Figure 3, the method includes the following steps:

[0193] S201. Receive L information groups from M information groups, where the M information groups are obtained by dividing N information groups based on classification parameters.

[0194] Here, N, M, and L are all positive integers, L is less than or equal to M, and M is less than or equal to N.

[0195] In some embodiments, the second node receives L information groups, including receiving at least one coded block, wherein the at least one coded block is determined based on at least one piece of information from the L information groups.

[0196] In some embodiments, the second node receives at least one encoded block, including one of the following:

[0197] Receive at least one coded block in at least one channel state information report;

[0198] Receive at least one coded block in higher-level signaling.

[0199] In some embodiments, the second node sends a first signaling message, which is used to indicate classification parameters.

[0200] In some embodiments, the second node sends a second signaling message, which is used to indicate the threshold value or threshold range of the classification parameters.

[0201] In some embodiments, the second node receives group index information for L information groups; here, the group index information is a non-negative integer less than M or a bitmap of M bits.

[0202] In some embodiments, the second node determines which of the M information groups the first node is sending based on the group index information of the L information groups.

[0203] In some embodiments, the second node may need to send the collected dataset to the terminal to train the model. When sending the dataset, the second node simultaneously instructs the terminal to send a dataset indicator. In some embodiments, if the first node is to train a generalized model, the second node may need to instruct the terminal to send one or more dataset indicators. These dataset indicators can be implicit, such as being bound to a reference signal resource or a set of reference signal resources. They can also be explicit, such as directly instructing multiple dataset indicators via higher-level and / or physical layer signaling; the dataset indicator can also be an associated ID.

[0204] For a more detailed description of S201, as well as a more detailed description of the various technical features and the beneficial effects, please refer to the descriptions in the above embodiments or examples, which will not be repeated here.

[0205] The foregoing primarily describes the solutions of the embodiments of this disclosure from a methodological perspective. The following also illustrates an information transmission apparatus for executing the information transmission methods in any of the above embodiments and their possible implementations. It is understood that, in order to implement the information transmission method, the information transmission apparatus includes hardware structures and / or software modules corresponding to the execution of various functions; those skilled in the art should readily recognize that, in conjunction with the algorithm steps of the examples described in the embodiments of this disclosure, this disclosure can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0206] This disclosure embodiment can divide the information transmission device into functional modules according to the above method embodiment. For example, each function can be divided into a separate functional module, or two or more functions can be integrated into one functional module. The integrated module can be implemented in hardware or software. It should be noted that the module division in this disclosure embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods. The following description uses the example of dividing each functional module according to each function.

[0207] Figure 4 is a block diagram of an information transmission device according to some embodiments. The information transmission device 300 includes an acquisition module 301, a processing module 302, and a communication module 303.

[0208] Here, module 301 is used to obtain classification parameters;

[0209] Processing module 302 is used to divide N pieces of information into M information groups based on classification parameters;

[0210] The communication module 303 is used to transmit L information groups out of M information groups; here, N, M, and L are all positive integers, L is less than or equal to M, and M is less than or equal to N.

[0211] In some embodiments, the classification parameters include quality parameters and / or correlation parameters.

[0212] In some embodiments, the classification parameters include quality parameters. The processing module 302 is used to determine that the information belongs to the first information group if the quality parameter of the information is greater than or equal to a first preset threshold for each of the N pieces of information; or, to determine that the information belongs to the second information group if the quality parameter of the information is less than the first preset threshold for each of the N pieces of information.

[0213] In some embodiments, the classification parameters include quality parameters. The processing module 302 is used to determine, for each piece of information among N pieces of information, that the information belongs to the i-th information group if the quality parameter of the information belongs to the i-th preset quality range, where i is less than or equal to M.

[0214] In some embodiments, the classification parameters include a correlation parameter. The processing module 302 is used to determine that the information belongs to the first information group if the correlation parameter of the information is less than or equal to a second preset threshold for each of the N pieces of information; or, to determine that the information belongs to the second information group if the correlation parameter of the information is greater than the second preset threshold for each of the N pieces of information.

[0215] In some embodiments, the classification parameters include correlation parameters. The processing module 302 is used to determine, for each piece of information among N pieces of information, that the information belongs to the i-th information group if the correlation parameter of the information belongs to the i-th preset correlation interval, where i is less than or equal to M.

[0216] In some embodiments, the classification parameters include correlation parameters. The processing module 302 is used to determine the correlation parameters between the information and M reference information for each of the N information pieces. If the correlation parameter between the information and the j-th reference information is the smallest, it is determined that the information belongs to the j-th information group, where j is less than or equal to M.

[0217] In some embodiments, the acquisition module 301 is further configured to acquire a first signaling, the first signaling being used to indicate classification parameters.

[0218] In some embodiments, the acquisition module 301 is further configured to acquire a second signaling, the second signaling being used to indicate a threshold value or threshold range of the classification parameter.

[0219] In some embodiments, the processing module 302 is used to determine the transmission priority of each information group in the M information groups; the processing module 302 is also used to determine the L information groups with the highest transmission priority in the M information groups based on the transmission priority of each information group in the M information groups; the communication module 303 is used to transmit the L information groups with the highest transmission priority in the M information groups.

[0220] In some embodiments, the processing module 302 is configured to determine the transmission priority of each of the M information groups based on the indicators of each of the M information groups.

[0221] In some embodiments, the processing module 302 is configured to determine the transmission priority of each information group in the M information groups based on the first i-th indicator among the C indicators; for at least two information groups in the M information groups where the first i indicators among the C indicators are the same, the transmission priority of each information group in the at least two information groups is determined based on the (i+1)-th indicator among the C indicators of each information group in the at least two information groups, where i is a positive integer less than C.

[0222] In some embodiments, the processing module 302 is configured to determine the transmission priority of each of the M information groups based on the index of each information group in the M information groups.

[0223] In some embodiments, the processing module 302 is used to determine at least one coded block based on at least one piece of information in L information groups; the communication module 303 is used to transmit at least one coded block.

[0224] In some embodiments, the communication module 303 is used to: transmit L information groups in at least one channel state information report; or transmit L information groups in higher-layer signaling.

[0225] In some embodiments, the communication module 303 is further configured to send group index information of L information groups; here, the group index information is a non-negative integer less than M or a bitmap of M bits.

[0226] For a more detailed description of the acquisition module 301, processing module 302, and communication module 303, as well as a more detailed description of the various technical features and the beneficial effects, please refer to the corresponding method embodiment sections above, which will not be repeated here.

[0227] Figure 5 is a block diagram of another information transmission device according to some embodiments. The information transmission device 400 includes: a first communication module 401 and a second communication module 402.

[0228] Here, the first communication module 401 is used to receive L information groups out of M information groups. The M information groups are obtained by dividing N information groups based on classification parameters. Here, N, M, and L are all positive integers, L is less than or equal to M, and M is less than or equal to N.

[0229] In some embodiments, the first communication module 401 is configured to receive at least one encoded block, wherein the at least one encoded block is determined based on at least one piece of information from L information groups.

[0230] In some embodiments, the first communication module 401 is configured to: receive at least one coded block in at least one channel state information report; or receive at least one coded block in higher-layer signaling.

[0231] In some embodiments, the second communication module 402 is used to send a first signaling, which is used to indicate classification parameters.

[0232] In some embodiments, the second communication module 402 is further configured to send a second signaling, the second signaling being used to indicate a threshold value or threshold range for the classification parameters.

[0233] In some embodiments, the first communication module 401 is used to receive group index information of L information groups; here, the group index information is a non-negative integer less than M or a bitmap of M bits.

[0234] For a more detailed description of the first communication module 401 and the second communication module 402, as well as a more detailed description of the various technical features and the beneficial effects, please refer to the corresponding method embodiment section above, which will not be repeated here.

[0235] It should be noted that the modules in Figure 4 and / or Figure 5 can also be referred to as units; for example, a communication module can be referred to as a communication unit. Furthermore, in the embodiments shown in Figure 4 and / or Figure 5, the names of the modules may not be those shown in the figures; for example, a communication module can also be referred to as a transmitting module or a receiving module.

[0236] If the units or modules in Figures 4 and / or 5 are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this disclosure, in essence, or the parts that contribute to some technologies, or all or part of the technical solutions, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this disclosure. Storage media for storing computer software products include: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0237] In the case of implementing the functions of the integrated modules described above in hardware, this disclosure also provides a possible structure for a communication device used to execute the information transmission method provided in this disclosure. As shown in FIG6, the communication device 500 includes: a communication interface 503, a processor 502, and a bus 504. In some embodiments, the communication device may further include a memory 501.

[0238] Processor 502 may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with embodiments of this disclosure. Processor 502 may be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with embodiments of this disclosure. Processor 502 may also be a combination that implements computational functions, such as a combination of one or more microprocessors, a digital signal processor (DSP), and a microprocessor, etc.

[0239] Communication interface 503 is used to connect to other devices via a communication network. This communication network can be Ethernet, wireless access network, wireless local area network (WLAN), etc.

[0240] The memory 501 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), disk storage medium or other magnetic storage device, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto.

[0241] In some embodiments, the memory 501 may exist independently of the processor 502. The memory 501 may be connected to the processor 502 via a bus 504 and is used to store instructions or program code. When the processor 502 calls and executes the instructions or program code stored in the memory 501, it can implement the information transmission method provided in the embodiments of this disclosure.

[0242] In other embodiments, memory 501 may also be integrated with processor 502.

[0243] Bus 504 can be an extended industry standard architecture (EISA) bus, etc. Bus 504 can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in Figure 6, but this does not mean that there is only one bus or one type of bus.

[0244] Some embodiments of this disclosure provide a computer-readable storage medium (e.g., a non-transitory computer-readable storage medium) storing computer program instructions that, when executed on a computer, cause the computer to perform the information transmission method as described in any of the above embodiments.

[0245] In one exemplary embodiment, the computer may be the aforementioned information transmission device, and this disclosure does not limit the specific form of the computer.

[0246] In some embodiments, the computer-readable storage media described above may include, but are not limited to: magnetic storage devices (e.g., hard disks, floppy disks, or magnetic tapes), optical disks (e.g., compact disks (CDs), digital versatile disks (DVDs), etc.), smart cards, and flash memory devices (e.g., erasable programmable read-only memory (EPROMs), cards, sticks, or key drives, etc.). The various computer-readable storage media described in this disclosure may represent one or more devices for storing information and / or other machine-readable storage media. The term "machine-readable storage media" may include, but is not limited to, wireless channels and various other media capable of storing, containing, and / or carrying instructions and / or data.

[0247] This disclosure provides a computer program product containing instructions that, when run on a computer, cause the computer to perform the information transmission method described in any of the above embodiments.

[0248] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any changes or substitutions within the technical scope disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

A method of information transmission, wherein The method includes: Obtain classification parameters, and divide N pieces of information into M information groups based on the classification parameters; Transmit L information groups out of the M information groups; wherein N, M, and L are all positive integers, L is less than or equal to M, and M is less than or equal to N. The method of claim 1, wherein, The classification parameters include quality parameters and / or correlation parameters. The method of claim 2, wherein, The quality parameters include at least one of the following: broadband signal-to-interference-plus-noise ratio, subband signal-to-interference-plus-noise ratio, reference signal received power, reference signal received quality, channel quality indication, modulation and coding scheme, interference intensity, line-of-sight parameter, quantization accuracy, quantization step size, and tag level. The method of claim 2, wherein, The correlation parameters include at least one of the following: time-domain correlation parameters, spatial-domain correlation parameters, and frequency-domain correlation parameters. The method of claim 2, wherein, The classification parameters also include at least one of the following: auxiliary identifier, reference signal resource indicator, reference signal resource set indicator, and cell indicator. The method of claim 2, wherein, The classification parameters include the quality parameters, and the step of dividing the N pieces of information into M information groups based on the classification parameters includes: For each of the N pieces of information, if the quality parameter of the information is greater than or equal to a first preset threshold, then the information is determined to belong to the first information group; or... For each of the N pieces of information, if the quality parameter of the information is less than a first preset threshold, the information is determined to belong to the second information group. The method of claim 2, wherein, The classification parameters include the quality parameters, and the step of dividing the N pieces of information into M information groups based on the classification parameters includes: For each of the N pieces of information, if the quality parameter of the information belongs to the i-th preset quality range, the information is determined to belong to the i-th information group, where i is less than or equal to M. The method of claim 2, wherein, The classification parameters include the correlation parameters, and the step of dividing the N pieces of information into M information groups based on the classification parameters includes: For each of the N pieces of information, if the relevance parameter of the information is less than or equal to a second preset threshold, then the information is determined to belong to the first information group; or... For each of the N pieces of information, if the correlation parameter of the information is greater than a second preset threshold, the information is determined to belong to the second information group. The method of claim 2, wherein, The classification parameters include the correlation parameters, and the step of dividing the N pieces of information into M information groups based on the classification parameters includes: For each of the N pieces of information, if the relevance parameter of the information belongs to the i-th preset relevance interval, the information is determined to belong to the i-th information group, where i is less than or equal to M. The method of claim 2, wherein, The classification parameters include the correlation parameters, and the step of dividing the N pieces of information into M information groups based on the classification parameters includes: For each of the N pieces of information, determine the correlation parameter between the information and M reference information. If the correlation parameter between the information and the j-th reference information is the smallest, determine that the information belongs to the j-th information group, where j is less than or equal to M. The method of claim 1, wherein, The acquisition of classification parameters includes: Obtain a first signaling message, which is used to indicate the classification parameters. The method of claim 2, wherein, The method further includes: Obtain a second signaling signal, which is used to indicate the threshold value or threshold range of the classification parameter. The method of claim 1, wherein, The transmission of L information groups out of the M information groups includes: Determine the transmission priority of each of the M information groups; Based on the transmission priority of each of the M information groups, determine the L information groups with the highest transmission priority among the M information groups; Transmit the L information groups. The method of claim 13, wherein, Determining the transmission priority of each of the M information groups includes: The transmission priority of each of the M information groups is determined based on the indicators of each information group. The method of claim 14, wherein, The metrics of the information group include at least one of the following: Broadband signal-to-interference-plus-noise ratio, subband signal-to-interference-plus-noise ratio, reference signal received power, reference signal received quality, channel quality indication, modulation and coding strategy, interference intensity, quantization accuracy, quantization step size, tag level, time domain correlation, and spatial domain correlation. The method of claim 14, wherein, Each of the information groups includes C indicators, where C is a positive integer; determining the transmission priority of each of the M information groups based on the indicators of each information group includes: Based on the first i indicators among the C indicators, determine the transmission priority of each information group in the M information groups; For at least two information groups in the M information groups where the first i indicators are the same, the transmission priority of each information group is determined based on the (i+1)th indicator of each information group in the at least two information groups, where i is a positive integer less than C. The method of claim 13, wherein, Determining the transmission priority of each of the M information groups includes: The transmission priority of each of the M information groups is determined based on the index of each information group. The method of claim 1, wherein, The transmission of L information groups out of the M information groups includes: At least one coded block is determined based on at least one piece of information from the L information groups, and the at least one coded block is transmitted. The method of claim 18, wherein, The transmission of the at least one encoded block includes one of the following: The at least one coded block is transmitted in at least one channel state information report; The at least one coded block is transmitted in higher-level signaling. The method of claim 1, wherein, The M information groups include at least a first information group and a second information group, wherein the first information group and the second information group satisfy at least one of the following: The quantization precision of the information in the first information group is higher than that of the information in the second information group; The information quantization step size in the first information group is larger than the information quantization step size in the second information group; The quality of the tags in the first information group is higher than that of the tags in the second information group. The method of claim 1, wherein, The method further includes: Send the group index information of the L information groups; wherein the group index information is a non-negative integer less than M or a bitmap of M bits. The method of claim 21, wherein, The method further includes a field in the first part of the CSI report that indicates the group index information of the L information groups. A method of information transmission, wherein The method includes: Receive L information groups from M information groups, wherein the M information groups are obtained by dividing N information based on classification parameters, where N, M, and L are all positive integers, L is less than or equal to M, and M is less than or equal to N. The method of claim 23, wherein, The receiving of L information groups includes: Receive at least one encoded block, wherein the at least one encoded block is determined based on at least one piece of information from the L information groups. The method of claim 23, wherein, Receiving the at least one coded block includes one of the following: The at least one coded block is received in at least one channel state information report; Receive the at least one coded block in higher-level signaling. The method of claim 23, wherein, The method further includes: Send a first signaling message, which is used to indicate the classification parameters. The method of claim 23, wherein, The method further includes: Send a second signaling message, which is used to indicate the threshold value or threshold range of the classification parameter. The method of claim 23, wherein, The method further includes: Receive group index information of the L information groups; wherein the group index information is a non-negative integer less than M or a bitmap of M bits. A communication device, wherein include: Memory and processor; Memory and processor are coupled; The memory is used to store instructions that can be executed by the processor; When the processor executes the instructions, it performs the method as described in any one of claims 1-28. A computer-readable storage medium, wherein, The computer-readable storage medium stores computer instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1-28. A computer program product, wherein, The computer program product includes computing technology program instructions that, when executed by a processor, implement the method as described in any one of claims 1-28.

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