Communication method and apparatus

Abstract

The present application relates to the technical field of communications. Provided is a communication method. In the method, a first communication device receives first indication information, second indication information and third indication information from a second communication device, wherein the first indication information indicates that the first communication device receives information of a nominal reference signal resource set from the second communication device; the second indication information indicates that the first communication device receives information of a first reference signal resource set from the second communication device; and the third indication information indicates a first relationship. The nominal reference signal resource set is used for representing a reference signal resource set corresponding to an output result of a first model of the first communication device; the first reference signal resource set is used by the first communication device to perform an AI operation on the first model, and the AI operation here comprises performing training and / or inference and / or monitoring; and the first relationship indicates the relationship between the nominal reference signal resource set and the first reference signal resource set. By means of the method, the efficiency of beam management is improved.

Description

A communication method and apparatus

[0001] This application claims priority from the Chinese Patent Application No. 202410458068.8 filed on April 16, 2024, and entitled "A communication method and apparatus", the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0002] The present application relates to the field of communication technology, and in particular to a communication method and apparatus. BACKGROUND

[0003] A model (such as an artificial intelligence (AI) or machine learning (ML) model) can be applied to improve communication. For example, a terminal device can use a model to select a suitable beam to improve the communication quality between the terminal device and a network device. The network device can configure a model for the terminal device, i.e., the model is deployed in the terminal device. The terminal device can improve the communication quality with the network device based on the model. However, how to monitor the performance of the model is currently not provided with a corresponding solution. SUMMARY

[0004] Embodiments of the present application provide a communication method, in particular to provide a beam management mechanism.

[0005] In a first aspect, embodiments of the present application provide a beam management method. The method is applied to a first communication device, a chip system or other functional modules in the first communication device. The other functional modules may, for example, be a software module (such as a program), a hardware module, or a hardware module running a program, etc., which are not specifically limited. For ease of description, the following will mainly be described by taking application to the first communication device as an example. The method comprises: receiving, by the first communication device, first indication information, second indication information and third indication information from a second communication device; the first indication information indicates that the first communication device receives nominal reference signal resource set information from the second communication device; the second indication information indicates that the first communication device receives first reference signal resource set information from the second communication device; and the third indication information indicates a first relationship. The nominal reference signal resource set is used to represent a reference signal resource set corresponding to an output result of a first model of the first communication device; and the first reference signal resource set is used for the first communication device to perform AI operation on the first model, where the AI operation includes training and / or inference and / or monitoring.

[0006] The first relationship indicates a relationship between the nominal reference signal resource set and the first reference signal resource set.

[0007] The nominal reference resource indicated by the first indication information can be a set of beams to be scanned, or a reference signal such as a CSI-RS signal, an SSB signal, or the like.

[0008] The first relationship includes an association relationship and / or a mapping relationship. The association relationship refers to the association relationship between the two resource sets. For example, in the configuration information corresponding to the first resource set, an additional field is introduced to indicate the configuration of the nominal reference resource, such as CSI-reportConfig ID, resourceSet ID, resourceConfig ID, or the like. The mapping relationship refers to a subset relationship between a resource set (small set) and another resource set (large set), and each resource in the small set corresponds to a one-to-one mapping of the resource in the large set. For example, the first reference signal resource set is a subset of the nominal reference signal resource set, and each signal resource in the first reference signal resource set corresponds to the position of the signal resource in the nominal reference signal resource set.

[0009] In the embodiments of the present application, the nominal reference signal resource set is used to represent the reference signal resource set corresponding to the output result of the first model of the first communication device, so that the input information is wider during AI model training and / or inference and / or monitoring, which is beneficial to the comparison of measurement results and further improves the efficiency of beam management.

[0010] The first model herein can be an AI model, which is a function model that maps a certain dimension of input to a certain dimension of output, and the model parameters are obtained through machine learning training. The type of AI model can be a neural network, a linear regression model, a decision tree model, a support vector machine (SVM), a Bayesian network, a Q learning model, or other machine learning models; or it can be a first function, and the first function can be a set of AI configurations, such as reference signal configurations and / or CSI report configurations corresponding to model input / output.

[0011] In a second aspect, the embodiments of the present application provide a beam management method. The method is applied to a second communication device, a chip system or other functional modules in the second communication device. The other functional modules may, for example, be a software module (such as a program), a hardware module, or a hardware module running a program, and the like, without specific limitation. For ease of description, the following mainly takes the application to the second communication device as an example for introduction. The method comprises: a first communication device receiving first indication information, second indication information, third indication information, fourth indication information, and fifth indication information from a second communication device; the first indication information indicating that the first communication device receives nominal reference signal resource set information from the second communication device; the second indication information indicating that the first communication device receives first reference signal resource set information from the second communication device; the third indication information indicating a first relationship; the fourth indication information indicating that the first communication device receives second reference signal resource set information from the second communication device; and the fifth indication information indicating a second relationship.

[0012] The nominal reference signal resource set is used to represent a reference signal resource set corresponding to an output result of a first model of the first communication device; the first reference signal resource set is used for the first communication device to perform AI operation on the first model, where the AI operation includes training and / or inference and / or monitoring. The second reference signal resource set is used for the first communication device to perform AI operation on the first model, where the AI operation includes training and / or inference and / or monitoring. The nominal reference signal resource set can be a full set of beams to be scanned, or a reference signal such as a CSI-RS signal, an SSB signal, and the like.

[0013] The first relationship indicates a relationship between the nominal reference signal resource set and the first reference signal resource set.

[0014] The first relationship includes an association relationship and / or a mapping relationship. The association relationship refers to the relevant association relationship between two resource sets. For example, in the configuration information corresponding to the first resource set, an additional field is introduced to indicate the configuration of the nominal reference resource, such as CSI-reportConfig ID, resourceSet ID, resourceConfig ID, and the like. The mapping relationship refers to a subset relationship between a resource set (small set) and another resource set (large set), where each resource in the small set corresponds to a one-to-one mapping of the resource in the large set, such as: the first reference signal resource set is a subset of the nominal reference signal resource set, and each signal resource in the first reference signal resource set corresponds to the position of the signal resource in the nominal reference signal resource set.

[0015] The second relationship includes an association relationship between the first reference signal resource set and the second reference signal resource set and / or a mapping relationship between the first reference signal resource set and the second reference signal resource set. The association relationship includes a second field in configuration information of the second reference signal resource set, and the second field is used for first reference signal resource set configuration information. The configuration information of the first reference signal resource set includes a configuration identifier ID of the first reference signal resource set. The mapping relationship indicates that the second reference signal resource set is a subset of the first reference signal resource set, and includes a position of each signal resource in the second reference signal resource set corresponding to a signal resource in the first reference signal resource set.

[0016] In the embodiments of the present application, the first communication device obtains a first measurement result for the first reference signal resource set; the first communication device obtains a second measurement result for the second reference signal resource set; the first measurement result contains a label determined by the first communication device through first model training or monitoring; and the second measurement result contains an input used by the first communication device for first model inference.

[0017] In a possible embodiment, the first communication device obtains a third measurement result for the first reference signal resource set, and the third measurement result contains an input used by the first communication device for first model inference.

[0018] The first model herein can be an AI model, which is a function model that maps a certain dimension of input to a certain dimension of output, and the model parameters of the AI model are obtained through machine learning training. The type of the AI model can be a neural network, a linear regression model, a decision tree model, a support vector machine (SVM), a Bayesian network, a Q learning model, or other machine learning models; or it can be a first function, and the first function can be a set of AI configurations, such as reference signal configurations and / or CSI report configurations corresponding to model input / output.

[0019] In a third aspect, the embodiments of the present application provide a communication apparatus. The communication apparatus can be the first communication device in the first aspect, or a module (for example, a chip system) configured in the first communication device, or an apparatus having the function of the first communication device. The communication apparatus includes means or modules for performing the corresponding steps of the first aspect or any possible implementation. For example, the communication apparatus includes a transceiver module (also known as a transceiver unit). Optionally, the communication apparatus further includes a processing module (also known as a processing unit).

[0020] For example, the transceiver module is configured to receive the first indication information, the second indication information, and the third indication information.

[0021] In an alternative implementation, the communication apparatus is further configured to implement any possible implementation of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a communication apparatus. The communication apparatus can be the second communication device in the second aspect, or a module (for example, a chip system) configured in the second communication device, or an apparatus having the function of the second communication device. The second communication apparatus comprises means or modules for performing the corresponding steps of the second aspect or any possible implementation. For example, the communication apparatus comprises a transceiver module (sometimes referred to as a transceiver unit). Optionally, the communication apparatus further comprises a processing module (sometimes referred to as a processing unit).

[0023] For example, the transceiver module is configured to transmit the first indication information, the second indication information, the third indication information, the fourth indication information, and the fifth indication information.

[0024] In an alternative implementation, the communication apparatus is further configured to implement any possible implementation of the second aspect.

[0025] In a fifth aspect, an embodiment of the present application provides a communication apparatus. The communication apparatus comprises a processor and an interface circuit. The interface circuit is configured to receive a signal from another communication apparatus outside the communication apparatus and transmit the signal to the processor, or transmit a signal from the processor to another communication apparatus outside the communication apparatus. The processor is configured to implement any method in the first aspect and any possible implementation, or the second aspect and any possible implementation, by means of a logic circuit or executing code instructions.

[0026] In the implementation process, the communication apparatus can be a chip, and the processor can be a transistor, a gate circuit, a flip-flop, and various logic circuits, etc. The specific implementation of the processor is not limited in the embodiments of the present application.

[0027] In an implementation, the communication apparatus can be a wireless communication device, i.e., a computer device supporting wireless communication function. Specifically, the wireless communication device can be a terminal device such as a smart phone, or a network device such as a wireless access network device (e.g., a base station).

[0028] In yet another implementation, the communication apparatus can be part of a device in a wireless communication device, such as an integrated circuit product, e.g., a system on chip (SoC) or a communication chip. The system on chip can also be referred to as an SoC chip. The communication chip can include a baseband processing chip and a radio frequency processing chip. The baseband processing chip can also be referred to as a modem or a baseband chip. The radio frequency processing chip can also be referred to as a radio frequency transceiver or a radio frequency chip. In physical implementation, part or all of the chips in the communication chip can be integrated inside the SoC chip. For example, the baseband processing chip is integrated in the SoC chip, and the radio frequency processing chip is not integrated with the SoC chip. The interface circuit can be a radio frequency processing chip in the wireless communication device, and the processor can be a baseband processing chip in the wireless communication device. The interface circuit can be an input / output interface, an interface circuit, an output circuit, an input circuit, a pin or related circuitry on the chip or chip system. The processor can also be embodied as a processing circuit or a logic circuit.

[0029] In yet another implementation, the communication apparatus can be a chip system, which can be composed of a chip or can include a chip and other discrete devices. The chip system can include, for example, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on chip (SoC), a CPU, a network processor (NP), a DSP, a micro controller unit (MCU), a programmable logic device (PLD), or other integrated chip.

[0030] In a sixth aspect, an embodiment of the present application provides a communication apparatus. The communication apparatus includes a processor. When the communication apparatus is running, the processor performs the method in any possible implementation of the first aspect and any possible implementation of the second aspect. Optionally, the communication apparatus further includes a memory storing one or more computer programs, and the processor can execute the one or more computer programs to implement the method in any possible implementation of the first aspect and any possible implementation of the second aspect.

[0031] Optionally, the communication apparatus further includes other components, e.g., an antenna, an input / output module, an interface (e.g., a communication interface), etc. These components can be hardware, software, or a combination of hardware and software.

[0032] In a seventh aspect, an embodiment of the present application provides a communication system. The communication system includes a first communication device and a second communication device. The first communication device is used to implement the functions of the method described in the first aspect and any possible implementation manner, and the second communication device is used to implement the functions of the method described in the second aspect and any possible implementation manner. Furthermore, the first communication device is, for example, the communication device described in the third aspect or any possible implementation manner, and the second communication device is, for example, the communication device described in the fourth aspect or any possible implementation manner.

[0033] In an eighth aspect, an embodiment of the present application provides a chip system. The chip system includes a processor. Optionally, the chip system may further include an interface (such as a communication interface). The processor may be used to implement the method described in the first aspect and any possible implementation manner or the second aspect and any possible implementation manner. Optionally, the chip system also includes a memory. The memory is used to store computer programs (also referred to as codes, or instructions). The processor is used to call and run the computer program from the memory so that the device equipped with the chip system executes the method described in the first aspect and any possible implementation manner or the second aspect and any possible implementation manner. The implementation method of the chip system can refer to the content of the chip system involved in the foregoing text and will not be listed here.

[0034] In a ninth aspect, embodiments of the present application provide a computer-readable storage medium for storing a computer program or instruction that, when executed, implements the method described in the first aspect and any possible implementation manner or the second aspect and any possible implementation manner.

[0035] In a tenth aspect, embodiments of the present application provide a computer program product that, when executed on a computer, implements any of the methods described in the first aspect and any possible implementation manner or the second aspect and any possible implementation manner.

[0036] In one possible implementation, the computer program product includes a computer program, which, when executed on a computer, enables the computer to execute any method described in the first aspect and any possible implementation or the second aspect and any possible implementation.

[0037] In another possible implementation, the computer program product includes instructions, and when the instructions are executed on a computer, the computer executes any method described in the first aspect and any possible implementation or the second aspect and any possible implementation.

[0038] Regarding the beneficial effects of any technical solution in the above-mentioned second to tenth aspects, reference can be made to the beneficial effects discussion of the corresponding technical solution in the first aspect, and the repeated parts will not be listed here. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] FIGs. 1-4 are schematic diagrams of architectures of communication systems to which embodiments of the present application are applicable;

[0040] FIG. 5 is a schematic flow chart of a communication method 500 according to an embodiment of the present application;

[0041] FIG. 6 is a schematic flow chart of a communication method 600 according to another embodiment of the present application;

[0042] FIG. 7 is a schematic flow chart of a communication method 700 according to another embodiment of the present application;

[0043] FIGs. 8-10 are schematic diagrams of structures of communication apparatuses according to embodiments of the present application. DETAILED DESCRIPTION

[0044] In order to make the objects, technical solutions and advantages of embodiments of the present application clearer, the following will further describe the embodiments of the present application with reference to the accompanying drawings.

[0045] The following explains some terms related to the embodiments of the present application, so as to facilitate understanding by those skilled in the art.

[0046] 1. Artificial intelligence (AI)

[0047] Artificial intelligence is to make machines have human intelligence, and to apply software and hardware of computers to simulate some intelligent behaviors of humans, including machine learning and many other methods.

[0048] 2. Machine learning (ML)

[0049] Machine learning is to make machines have human intelligence, and to apply software and hardware of computers to simulate some intelligent behaviors of humans, including machine learning and many other methods. Machine learning can be divided into supervised learning, unsupervised learning and reinforcement learning.

[0050] Supervised learning is to learn the mapping relationship from samples to labels according to samples and labels, and to express the learned mapping relationship by a model. The process of training the model can be regarded as the process of learning such mapping relationship. For example, in signal detection, a signal containing noise can be regarded as a sample, and the real constellation point corresponding to the signal can be regarded as a label, and machine learning expects to learn the mapping relationship between the sample and the label through training, that is, to make the model learn to detect the signal. In the process of training the model, the error between the predicted value of the model and the label is used to optimize the parameters of the model. After training the model, the model can be used to predict the label of each new sample. The mapping relationship learned by supervised learning includes linear mapping and nonlinear mapping. According to the type of label, the learned task can be divided into classification task and regression task.

[0051] Unsupervised learning is to find or learn the internal pattern of samples by algorithm according to sample values. In unsupervised learning, a class of algorithms uses the sample itself as a supervision signal, that is, the model learns the mapping relationship from sample to sample, so this learning can be called self-supervised learning. In the process of training the model, the error between the prediction value of the calculation model and the sample is used to optimize the model parameters. Self-supervised learning can be used for signal compression and decompression recovery applications. Models suitable for self-supervised learning include autoencoders and generative adversarial networks.

[0052] Reinforcement learning is different from supervised learning, which is a class of algorithms that learn strategies to solve problems by interacting with the environment. Unlike supervised learning and unsupervised learning, reinforcement learning problems do not have explicit "correct" labels. The algorithm needs to interact with the environment to obtain the reward signal of the environmental feedback, and then adjust the decision action to obtain a larger reward signal value. For example, in downlink power control, the reinforcement learning model adjusts the downlink transmission power of each user according to the system total throughput rate feedback by the wireless network, and then expects to obtain a higher system throughput rate. The goal of reinforcement learning is also to learn the mapping relationship between the state of the environment and the optimal decision action. However, because the "correct" label cannot be obtained in advance, the error between the action and the "correct" label cannot be used to optimize the network. Reinforcement learning training is achieved through iterative interaction with the environment.

[0053] 3、Model

[0054] Model is a form of implementation of machine learning, or the purpose of machine learning is to obtain a model that can implement corresponding functions. The model is a specific implementation of one or more functions, representing the mapping relationship between the input and output of the model. The model can include one or more parameters. A substructure (or, sub-module) of the model can include one or more parameters. For example, f(x) = ax 2 +b can be regarded as a model, a and b correspond to the parameters of the model, and the parameters of the model can be obtained by learning and training. The process of training the model can be regarded as the process of optimizing the parameters of the model. The process of using the model to implement the corresponding function can be regarded as the inference process of the model. The output of the model in the inference process of the model can be referred to as the inference result.

[0055] In the field of ML and AI, a model can be understood as an algorithm or system that can make predictions or perform tasks after being trained and learned from input data. A model includes, for example, an ML model, an AI model, an algorithm, a feature, or a function, etc. An AI model can be at least one of a linear regression model, a logistic regression model, a decision tree model, a support vector machine (SVM), a neural network model, a clustering model, a Bayesian network, a Q-learning model, a generative adversarial network, or other machine learning models, without limitation. A neural network model is a mathematical model that simulates the behavior characteristics of animal neural networks for distributed parallel information processing. The neural network model can be, for example, one or more of a feed forward neural network (FNN), a convolutional neural network (CNN), and a recurrent neural network (RNN), without limitation.

[0056] A neural network is a typical model. A neural network, for example, a deep neural network (DNN), is a specific implementation form of machine learning. According to the universal approximation theorem, a neural network can theoretically approximate any continuous function, thereby enabling the neural network to learn any mapping.

[0057] Taking the model of a neural network as an example, a model can include at least one layer, and a “layer” can include a “network layer”. Each “network layer” can include at least one node, which can also be referred to as a “neuron”. Please refer to FIG. 1 for a schematic diagram of a structure of a model. Taking the model shown in FIG. 1 as an example, there are an input layer, a hidden layer, and an output layer. The circles in FIG. 1 represent neurons, and the connections between the circles between network layers represent connections. Optionally, the model can also include a loss layer, which corresponds to, for example, a cross entropy loss function. Any layer involved herein can be regarded as a network layer. For example, there can be at least one parameter between a network layer and a network layer, such as a weight or an operator, for example, a convolution operator, a full connection operator, etc.

[0058] The neurons of a certain network layer are connected to the neurons of an adjacent network layer through weights, and one connection can be regarded as an operation. Taking the connection between the input layer and the hidden layer shown in FIG. 1 as an example, the parameters of the model between the input layer and the hidden layer are that each neuron of the input layer is connected to each neuron of the hidden layer.

[0059] The neuron is exemplified below in connection with a schematic diagram of a neuron shown in FIG. 2. As shown in FIG. 2, the neuron performs a weighted sum operation on its inputs, and the weighted sum result is passed through a non-linear function to produce an output. Suppose the inputs to the neuron are x = [x0,..., x n ], the weights corresponding to the inputs are d = [d0,..., d n ], and the bias of the weighted sum is b, then the output of the neuron is

[0060] In a possible implementation, the model is used to predict CSI, i.e., the inference result of the model is a CSI prediction result. In this case, the input of the model is, for example, a reference signal, and specifically, for example, a CSI-RS, etc. Alternatively, the model is used to predict a beam, i.e., the inference result of the model is a beam prediction result. In this case, the input of the model is, for example, a measurement result of a reference signal.

[0061] 4. Beam (beam)

[0062] A beam can be understood as a spatial filter or spatial parameters. A beam used for transmitting a signal can be referred to as a transmit beam, a transmission beam (Tx beam), a spatial domain transmit filter, or spatial transmit parameters (spatial Tx parameters). A transmit beam can also refer to the distribution of signal strength in different directions in space after a signal is transmitted by an antenna. In this sense, a transmit beam can also be a spatial transmission angle (such as Azimuth (also referred to as horizontal angle), Zenith (also referred to as elevation angle)) or a spatial transmission angle range (such as azimuth center angle and offset, azimuth uncertainty, azimuth protection range, zenith center angle and offset, zenith uncertainty, zenith protection range), etc. Correspondingly, a beam used for receiving a signal can be referred to as a reception beam (Rx beam), a spatial domain receive filter, or spatial receive parameters (spatial Rx parameters). A reception beam can also refer to the distribution of signal strength in different directions in space after a wireless signal is received by an antenna. In this sense, a reception beam can also be a spatial reception angle (such as Azimuth, Zenith) or a spatial reception angle range (such as azimuth center angle and offset, azimuth uncertainty, azimuth protection range, zenith center angle and offset, zenith uncertainty, zenith protection range), etc.

[0063] A beam can be divided into a wide beam and a narrow beam. A wide beam refers to a beam with a relatively large radiation range of a transmitting or receiving antenna when transmitting or receiving a signal. A wide beam is usually used in application scenarios that require broadcasting signals to a larger area or a wider coverage range. It can provide a wider coverage area, but the signal strength is relatively weak. A narrow beam refers to a beam with a relatively small radiation range of a transmitting or receiving antenna. A narrow beam is usually used in application scenarios that require focusing signals to a specific target or area. It can provide higher signal strength and higher directivity, but the coverage range is relatively small.

[0064] 5、Reference signal (RS)

[0065] The reference signal can also be referred to as a pilot signal or a pilot. It is a known signal, for example, a known signal provided by a sending end to a receiving end for channel estimation, channel sounding, data demodulation, etc. The reference signal is, for example, a synchronization signal block (SSB) and a channel state information-reference signal (CSI-RS). The SSB is a cell broadcast signal, which includes a primary synchronization signal (PSS), a secondary synchronization signal (SSS), a physical broadcast channel (PBCH), and a demodulation reference signal (DMRS). There are various reference signals, and with the continuous evolution of standards, the names of the above-mentioned reference signals may change, and more reference signals may appear. No specific limitation is made.

[0066] The CSI includes at least one of rank indication (RI) information, channel quality indicator (CQI) information, precoding matrix indicator (PMI), or layer 1 reference signal receiver power (L1-RSRP).

[0067] The reference signal includes a periodic reference signal, a semi-periodic reference signal, or a non-periodic reference signal. Alternatively, it can be described that the device (such as a terminal device) reports a measurement result of the reference signal, which includes a periodic reporting of the measurement result, a semi-periodic reporting of the measurement result, or a non-periodic reporting of the measurement result.

[0068] The periodic reference signal means that after the signaling (such as radio resource control (RRC)) signaling configures the measurement resource, the device (such as a terminal device) starts to periodically measure and report the measurement result of the reference signal. The semi-periodic reference signal means that after the signaling (such as RRC) configures the measurement resource, it needs to be triggered by separate signaling (such as downlink control information (DCI)) to start to periodically measure and report the measurement result of the reference signal. The non-periodic reference signal means that each time the device measures and reports the CSI, it needs to be triggered by separate signaling of the network side.

[0069] As the reference signal is CSI-RS, the CSI-RS includes periodic CSI-RS, semi-periodic CSI-RS and aperiodic CSI-RS. The measurement result of the CSI-RS is CSI, and the corresponding CSI reporting includes periodic (P-CSI) reporting, semi-persistent (or semi-static, or semi-persistent) CSI (SP-CSI) reporting and aperiodic (A-CSI) reporting.

[0070] 6、time unit

[0071] The time unit belongs to a time domain resource. The unit of the time unit can be a slot, a symbol, a subframe, a half frame, a frame, a mini subframe, a mini slot, or a transmission occasion (TO), and the like, without limitation.

[0072] The first time unit, the second time unit and the third time unit involved in the embodiments of the present application are used to execute the time domain resources corresponding to the corresponding processes, and the units of the first time unit, the second time unit and the third time unit can be the same or different, without limitation. For example, the units of the first time unit, the second time unit and the third time unit are all symbols.

[0073] In various embodiments of the present application, the number of nouns, unless otherwise specified, represents "a singular noun or a plural noun", that is, "one or more". "At least one" means one or more, and "multiple" means two or more. "And / or" describes the association relationship of the associated objects, which means that there can be three kinds of relationships, for example, A and / or B can represent: A exists alone, A and B exist together, and B exists alone, where A and B can be singular or plural. The character " / " generally represents that the associated objects before and after are in an "or" relationship. For example, A / B means: A or B. "At least one of the following" or the like means any combination of these items, including any combination of single item or multiple items. For example, at least one of a, b, or c means: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0074] In embodiments of the present application, "indication" can include direct indication, indirect indication, display indication, and implicit indication. When describing that certain indication information is used to indicate A, it can be understood that the indication information carries A, directly indicates A, or indirectly indicates A. In the present application, the information indicated by the indication information is referred to as to-be-indicated information. In the specific implementation process, there are many ways to indicate the to-be-indicated information, for example, but not limited to, the to-be-indicated information can be directly indicated, such as the to-be-indicated information itself or the index of the to-be-indicated information. The to-be-indicated information can also be indirectly indicated by indicating other information, where the other information and the to-be-indicated information have an association relationship. The to-be-indicated information can also be indicated only by a part of the to-be-indicated information, and the other part of the to-be-indicated information is known or agreed in advance. For example, the indication of a specific information can also be achieved by means of the arrangement order of each information agreed in advance (for example, a protocol), thereby reducing the indication overhead to a certain extent. In addition, the to-be-indicated information can be sent as a whole, or can be sent separately as multiple sub-information, and the sending period and / or sending time of the sub-information can be the same or different.

[0075] In embodiments of the present application, "sending" and "receiving" represent the direction of signal transmission. For example, "sending information to XX" can be understood as that the destination of the information is XX, which can include direct sending through the air interface, or indirect sending through the air interface by other units or modules. "Receiving information from YY" can be understood as that the source of the information is YY, which can include direct receiving from YY through the air interface, or indirect receiving from YY through the air interface from other units or modules. "Sending" can also be understood as "output" of a chip interface, and "receiving" can also be understood as "input" of a chip interface. In other words, sending and receiving can be performed between devices, for example, between network devices and terminal devices, or can be performed within a device, for example, between components, between modules, between chips, between software modules or hardware modules in a device through a bus, a wire or an interface.

[0076] The scheme provided by the embodiments of the present application can be applied to various communication systems including a first communication device and a second communication device. The first communication device and the second communication device both have communication functions. The communication device can also be replaced by an entity, a network entity, a device, a communication device, a communication module, a node or a communication node, etc., which is not limited.

[0077] For example, the first communication device is a terminal device, or a chip system (such as a chip) or other functional modules or components in the terminal device. The second communication device is a network device, or a chip system (such as a chip) or other functional modules or components in the network device.

[0078] The terminal device can be a device with wireless transceiver function, which can be a fixed device, a mobile device, a handheld device, a wearable device, a vehicle-mounted device, or a wireless device (for example, a communication module or a chip system, etc.) built in the above devices. The terminal device is used to connect people, things, machines, etc., and can be widely used in various scenarios, for example, including but not limited to the following scenarios: cellular communication, device-to-device (D2D) communication, vehicle to everything (V2X) communication, machine-to-machine / machine-type communications (M2M / MTC), internet of things (IoT), virtual reality (VR), augmented reality (AR), industrial control, self driving, remote medical, smart grid, smart furniture, smart office, smart wear, smart transportation, smart city, unmanned aerial vehicle, robot, etc. The terminal device can be sometimes referred to as user equipment (UE), terminal, access station, UE station, remote station, wireless communication device, or user apparatus, etc.

[0079] The network device includes, for example, an access network device (or, an access network apparatus / access network network element), and / or a core network device (or, a core network apparatus / core network network element).

[0080] The access network device is a device with wireless transceiver function, which is used to communicate with the terminal device. The access network device includes but is not limited to the base station (BTS, Node B, eNodeB / eNB, or gNodeB / gNB), transmission reception point (TRP), base station of subsequent evolution of 3GPP, access node in wireless fidelity (WiFi) system, wireless relay node, wireless backhaul node, satellite or unmanned aerial vehicle, etc. in the communication system. The base station can be a macro base station, a micro base station, a pico base station, a small station, a relay station, etc. Multiple base stations can support the network of the same access technology mentioned above, or support the network of different access technologies mentioned above. The base station can contain one or more co-sited or non-co-sited transmission reception points. The access network device can also be a wireless controller in a cloud radio access network (C(R)AN) scenario, a centralized unit (CU), which can also be called a convergence unit, and / or a distributed unit (DU), etc. The access network device can also be a server, a wearable device, or a vehicle-mounted device, etc. For example, the access network device in vehicle to everything (V2X) technology can be a road side unit (RSU). The following describes the access network device as an example of a base station. Multiple access network devices in the communication system can be the same type of base station, or different types of base stations. The base station can communicate with the terminal device, or communicate with the terminal device through the relay station. The terminal device can communicate with multiple base stations in different access technologies.

[0081] In the case that the access network device includes a CU and / or a DU. The CU and the DU can be understood as a division of the access network device from a logical function perspective. The CU and the DU can be physically separated or deployed together, and embodiments of the present application do not make specific limitations thereon. One CU can be connected with one DU, or multiple DUs can share one CU. The CU and the DU can be divided according to a protocol stack, and one possible way is to deploy the RRC, service data adaptation protocol (SDAP), and packet data convergence protocol (PDCP) layers in the CU, and deploy the remaining radio link control (RLC) layer, media access control (MAC) layer, and physical layer in the DU. The embodiments of the present application do not completely limit the CU and the DU to be divided according to the above protocol stack, and other division manners can also be used, for example, division according to service types.

[0082] The access network device in the embodiments of the present application can also refer to a centralized unit control plane (CU-CP) node or a centralized unit user plane (CU-UP) node, or include the CU-CP and the CU-UP. The CU-CP is responsible for control plane functions, mainly including the RRC and the PDCP-C. The PDCP-C is mainly responsible for encryption and decryption of control plane data, integrity protection, data transmission, and the like. The CU-UP is responsible for user plane functions, mainly including the SDAP and the PDCP-U. The SDAP is mainly responsible for processing data of the core network and mapping the flow to a bearer. The PDCP-U is mainly responsible for encryption and decryption of the data plane, integrity protection, header compression, sequence number maintenance, data transmission, and the like.

[0083] In different systems, the CU (including the CU-CP or the CU-UP) or the DU can also have different names, but those skilled in the art can understand the meanings thereof. For example, in an open radio access network (O-RAN) system, the CU can also be referred to as an O-CU (open CU), the DU can also be referred to as an O-DU, the CU-CP can also be referred to as an O-CU-CP, and the CU-UP can also be referred to as an O-CU-UP.

[0084] The core network device is used to implement at least one of the following functions: mobility management, data processing, session management, policy and billing. The names of the devices that implement core network functions in systems with different access technologies may be different, and this embodiment of the present application is not limited to this. Taking the 5G system as an example, the core network device includes: access and mobility management function (AMF), session management function (SMF), or user plane function (UPF).

[0085] Various communication systems applicable to the embodiments of the present application include long term evolution (LTE) system, LTE frequency division duplex (FDD) system, LTE time division duplex (TDD) system, fifth generation (5G) system, th Generation, 5G) (such as new radio (NR) system), wireless local area network (WLAN) system, satellite communication system, side link (SL) communication system, future evolved communication system, or a fusion system of multiple systems, etc., without limitation. SL can also be called side communication link, side link, side link, direct link, side link or auxiliary link, etc. SL includes vehicle-to-everything (V2X) communication, etc. V2X communication may include: vehicle-to-vehicle (V2V) communication, vehicle-to-roadside infrastructure (V2I) communication, vehicle-to-pedestrian (V2P) communication, vehicle-to-network (V2N) communication, etc., without specific limitation.

[0086] The following is an example of a schematic diagram of a communication system applicable to the embodiments of the present application, with reference to the accompanying drawings.

[0087] Please refer to FIG. 1, which is a schematic diagram of a communication system applicable to an embodiment of the present application. As shown in FIG. 1, the communication system includes terminal devices and network devices. FIG. 1 takes an example of 2 terminal devices and 1 network device, and the number of terminal devices and network devices is not limited in practice. Any terminal device in FIG. 1 can be taken as an example of a first communication device, and the network device can be taken as an example of a second communication device.

[0088] The network device can send a downlink signal to the terminal device, and / or the terminal device can send an uplink signal to the network device. Optionally, the terminal device can deploy a model, and the network device can monitor the model through interaction with the terminal device. Alternatively, the model can also be deployed in other devices in communication with the terminal device. In this way, the network device can also monitor the model through interaction with the terminal device.

[0089] Please refer to FIG. 2, which is a schematic diagram of a communication system applicable to an embodiment of the present application. Compared with the communication system shown in FIG. 1, the communication system shown in FIG. 2 further includes an AI network element. The AI network element is used to perform AI-related operations, such as constructing a training data set or training an AI model. The terminal device involved in FIG. 2 can be taken as an example of a first communication device, and the network device can be taken as an example of a second communication device.

[0090] For example, the network device can send data related to the training of the AI model to the AI network element, and the AI network element can construct a training data set and train the model. For example, the data related to the training of the model can include data reported by the terminal device. The AI network element can send the result of the operation related to the AI model to the network device and forward it to the terminal device through the network device. For example, the result of the operation related to the model can include at least one of the following: a trained model, an evaluation result or a test result of the model, etc.

[0091] Optionally, part of the trained AI model can be deployed on the network device, and the other part can be deployed on the terminal device. Alternatively, the trained AI model can be deployed on the network device. Alternatively, the trained AI model can be deployed on the terminal device. Alternatively, the AI network element can also be set as a module in the network device and / or the terminal device, for example, in the network device or the terminal device shown in FIG. 2.

[0092] FIG. 2 only takes an example of the AI network element being directly connected to the network device, and in other scenarios, the AI network element can also be connected to the terminal device. Alternatively, the AI network element can be connected to both the network device and the terminal device. Alternatively, the AI network element can also be connected to the network device through a third-party network element. The connection relationship between the AI network element and other network elements is not limited in the embodiments of the present application.

[0093] FIG. 1 and FIG. 2 are merely simplified schematic diagrams for the purpose of understanding, and other devices such as wireless relay devices and / or wireless backhaul devices can also be included in the communication system, which are not shown in FIG. 1 and FIG. 2.

[0094] The architecture of the access network device is exemplarily introduced below in combination with the structure schematic diagram of the communication system shown in FIG. 3 and FIG. 4.

[0095] As shown in FIG. 3, the devices in the communication system are connected through interfaces (such as NG, Xn) or air interfaces. One or more AI modules are arranged in one or more of the devices such as the core network device, the access network node (such as the RAN device), the terminal device or one or more of the operation, administration and maintenance (OAM) devices, and the number of AI modules arranged in one device is exemplarily shown as 1 in FIG. 3, which is not limited in practice. The access network node can be a single RAN node or can include multiple RAN nodes, for example, including the CU and the DU. The CU and / or the DU can also be arranged with one or more AI modules. The terminal device involved in FIG. 3 can be exemplarily taken as a first communication device, and one or more of the CU or the DU core network device or the access network node (RAN node) can be exemplarily taken as a second communication device. Optionally, the CU can be further split into the CU-CP and the CU-UP. One or more AI models are arranged in the CU-CP and / or the CU-UP.

[0096] The AI module is used to implement the corresponding function. The AI modules deployed in any two of the one or more devices can be completely the same, partially the same or completely different, which is not specifically limited in the embodiments of the present application. The AI module is used to implement the corresponding AI function. The AI modules deployed in different devices can be the same or different. The model of the AI module can implement different functions according to different parameter configurations. The model of the AI module can be configured based on one or more of the following parameters: structural parameters (such as at least one of the number of neural network layers, the width of neural network, the connection relationship between layers, the weight of neurons, the activation function of neurons or the bias in the activation function), input parameters (such as the type of input parameters and / or the dimension of input parameters) or output parameters (such as the type of output parameters and / or the dimension of output parameters). The bias in the activation function can also be referred to as the bias of the neural network.

[0097] One AI module can include one or more models. One model can infer an output including one parameter or multiple parameters. The learning process, the training process or the inference process of different models can be deployed in different nodes or devices, or can be deployed in the same node or device.

[0098] In a possible implementation, the AI module can be a RAN intelligent controller (RIC), such as a near-real time RIC (near-RT RIC) or a non-real time RIC (Non-RT RIC). For example, the near-real time RIC is arranged in a RAN node (for example, in a CU and / or a DU), and the non-real time RIC is arranged in an OAM, a cloud server, a core network device, or another network device. The RIC can obtain, from a RAN node (for example, a CU, a CU-CP, a CU-UP, a DU, and / or a RU), a subset of data from a plurality of terminal devices, reorganize the subset of data into a training data set, and perform model training based on the training data set.

[0099] For example, the near-real time RIC and the non-real time RIC can also be separately arranged as one network element, respectively.

[0100] As shown in FIG. 4, the communication system includes a RIC. For example, the RIC can be the AI module shown in FIG. 3, and is configured to implement AI-related functions. The RIC includes a near-real time RIC and a non-real time RIC. The near-real time RIC and / or the non-real time RIC can be an example of one of the second communication devices. The near-real time RIC mainly processes near-real time information, for example, data relatively sensitive to a time delay, and the time delay of the data is tens of milliseconds. The non-real time RIC mainly processes non-real time information, for example, data not sensitive to a time delay, and the time delay of the data can be seconds.

[0101] The near-real time RIC is configured to perform model training and inference. For example, the near-real time RIC is configured to train an AI model and perform inference by using the AI model. The near-real time RIC can obtain network side and / or terminal side information from a RAN node (for example, a CU, a CU-CP, a CU-UP, a DU, and / or a RU) and / or a terminal device. The information can be used as training data or inference data. Optionally, the near-real time RIC can deliver an inference result to the RAN node and / or the terminal. Optionally, the CU and the DU, and / or the DU and the RU can exchange the inference result. For example, the near-real time RIC delivers the inference result to the DU, and the DU sends the inference result to the RU.

[0102] The non-real-time RIC is also used for model training and inference. For example, the non-real-time RIC is used for training an AI model, and inference is performed using the model. The non-real-time RIC can obtain network-side and / or terminal-side information from a RAN node (for example, a CU, a CU-CP, a CU-UP, a DU, and / or a RU) and / or a terminal. The information can be used as training data or inference data, and the inference result can be delivered to the RAN node and / or the terminal. Alternatively, the inference result can be exchanged between the CU and the DU, and / or between the DU and the RU, for example, the non-real-time RIC delivers the inference result to the DU, and the DU delivers the inference result to the RU.

[0103] The near-real-time RIC and the non-real-time RIC can also be separately provided as a network element. Alternatively, the near-real-time RIC and the non-real-time RIC can also be part of other devices, for example, the near-real-time RIC is provided in a RAN node (for example, in a CU and / or a DU), and the non-real-time RIC is provided in an OAM, a cloud server, a core network device, or other network devices.

[0104] The above-mentioned FIG. 1 to FIG. 4 are examples of the communication system to which the embodiments of the present application are applied, and do not limit the communication system to which the embodiments of the present application can be applied.

[0105] The data collection scheme provided by the embodiments of the present application is described below with reference to the accompanying drawings.

[0106] In the drawings corresponding to the embodiments of the present application, the steps represented by dashed lines are optional steps. The first communication device involved in the embodiments of the present application is, for example, the terminal device involved in any one of FIG. 1 to FIG. 4. The second communication device involved in the embodiments of the present application is, for example, the network device involved in FIG. 1, the network device involved in FIG. 2, the CU, the DU, the core network device, the access network node, or the OAM involved in FIG. 3, or the non-real-time RIC, the near-real-time RIC, the CU, the DU, the CU-CP, the RU, or the access network node involved in FIG. 4. In addition, with the continuous evolution of standards, the name and / or function of the device or node may change, which is not limited.

[0107] FIG. 5 is a communication method provided by the communication method 500 of the embodiments of the present application. The steps shown in FIG. 5 are described below.

[0108] S501, the second communication device sends first indication information to the first communication device. Correspondingly, the first communication device receives the first indication information from the second communication device.

[0109] Exemplarily, the first indication information can be carried in RRC signaling, DCI, a media access control (MAC) layer control element (CE), or other signaling, which is not limited. For example, the first indication information is carried in CSI reporting configuration (CSI-ReportConfig) of RRC signaling.

[0110] The first indication information is used to indicate nominal reference signal resource set information, and the nominal reference signal resource set can be a reference signal and / or a beam, and the reference signal can be a CSI, an SSB, or the like.

[0111] S502, the second communication device sends second indication information to the first communication device. Correspondingly, the first communication device receives the second indication information from the second communication device.

[0112] Exemplarily, the second indication information can be carried in RRC signaling, DCI, a media access control (MAC) layer control element (CE), or other signaling, which is not limited. For example, the second indication information is carried in CSI reporting configuration (CSI-ReportConfig) of RRC signaling.

[0113] The second indication information is used to indicate that the first communication device receives first reference signal resource set information from the second communication device, and the first reference signal resource set information is used for the first communication device to perform AI operation on the first model, where the AI operation includes training and / or inference and / or monitoring.

[0114] Optionally, the first reference signal resource set is a subset of the nominal reference signal resource set.

[0115] S503, the second communication device sends third indication information to the first communication device. Correspondingly, the first communication device receives the third indication information from the second communication device.

[0116] Exemplarily, the third indication information can be carried in RRC signaling, DCI, a media access control (MAC) layer control element (CE), or other signaling, which is not limited. For example, the third indication information is carried in CSI reporting configuration (CSI-ReportConfig) of RRC signaling.

[0117] The third indication information indicates a first relationship, and the first relationship indicates a relationship between the nominal reference signal resource set and the first reference signal resource set.

[0118] The first relationship includes a correlation relationship and / or a mapping relationship. The correlation relationship refers to the correlation relationship between the two resource sets. For example, in the configuration information corresponding to the first resource set, an additional field is introduced to indicate the configuration of the nominal reference resource, such as CSI-reportConfig ID, resourceSet ID, resourceConfig ID, and the like. The mapping relationship refers to a subset relationship between a resource set (small set) and another resource set (large set), and each resource in the small set corresponds to a one-to-one mapping of the resource in the large set. For example, the first reference signal resource set is a subset of the nominal reference signal resource set, and each signal resource in the first reference signal resource set corresponds to the position of the signal resource in the nominal reference signal resource set.

[0119] In the embodiment of the application, the nominal reference signal resource set is used to represent the reference signal resource set corresponding to the output result of the first model of the first communication device, so that the input information is wider during AI model training and / or inference and / or monitoring, which is beneficial to the comparison of measurement results and further improves the efficiency of beam management.

[0120] The first model herein can be an AI model, which is a function model that maps a certain dimension of input to a certain dimension of output, and the model parameters are obtained through machine learning training. The type of AI model can be a neural network, a linear regression model, a decision tree model, a support vector machine (SVM), a Bayesian network, a Q learning model, or other machine learning models; or it can be a first function, which can be a set of AI configurations, such as reference signal configurations and / or CSI report configurations corresponding to model input / output.

[0121] Please refer to FIG. 6, which provides another communication method for the communication method 600 of the embodiment of the application. The steps shown in FIG. 6 are introduced as follows.

[0122] S601, the second communication device sends first indication information to the first communication device. Correspondingly, the first communication device receives the first indication information from the second communication device.

[0123] For example, the first indication information can be carried in RRC signaling, DCI, media access control (MAC) layer control element (CE), or other signaling, which is not limited. For example, the first indication information is carried in the CSI report configuration (CSI-ReportConfig) of the RRC signaling.

[0124] The first indication information is used for indicating nominal reference signal resource set information. The nominal reference signal resource set can be a reference signal and / or a beam. The reference signal can be a CSI, an SSB, and the like.

[0125] S602, the second communication device sends second indication information to the first communication device. Correspondingly, the first communication device receives the second indication information from the second communication device.

[0126] For example, the second indication information is carried in CSI reporting configuration (CSI-ReportConfig) of RRC signaling.

[0127] The second indication information is used for indicating first reference signal resource set information received by the first communication device from the second communication device. The first reference signal resource set information is used for the first communication device to perform AI operation on the first model. The AI operation herein includes training and / or inference and / or monitoring.

[0128] Optionally, the first reference signal resource set is a subset of the nominal reference signal resource set.

[0129] S603, the second communication device sends third indication information to the first communication device. Correspondingly, the first communication device receives the third indication information from the second communication device.

[0130] For example, the third indication information is carried in CSI reporting configuration (CSI-ReportConfig) of RRC signaling.

[0131] The third indication information indicates a first relationship. The first relationship indicates a relationship between the nominal reference signal resource set and the first reference signal resource set.

[0132] The first relationship includes a correlation relationship and / or a mapping relationship. The correlation relationship refers to the correlation relationship between the two resource sets. For example, in the configuration information corresponding to the first resource set, an additional field is introduced to indicate the configuration of the nominal reference resource, such as CSI-reportConfig ID, resourceSet ID, resourceConfig ID, etc. The mapping relationship refers to a subset relationship between a resource set (small set) and another resource set (large set), and each resource in the small set corresponds to a one-to-one mapping of the resource in the large set, such as: the first reference signal resource set is a subset of the nominal reference signal resource set, and each signal resource in the first reference signal resource set corresponds to the position of the signal resource in the nominal reference signal resource set.

[0133] S604, the first communication device measures the first reference signal resource set to obtain a first measurement result.

[0134] The first measurement result contains the label determined by the first communication device through the first model training or monitoring, that is, the first measurement result is used as the label used for training or monitoring of the first model, such as the first measurement result is directly used or used after processing as the label used for training or monitoring of the first model.

[0135] S605, the second communication device sends fourth indication information to the first communication device. Correspondingly, the first communication device receives the fourth indication information from the second communication device.

[0136] For example, the fourth indication information can be carried in RRC signaling, DCI, media access control (MAC) layer control element (CE), or other signaling, which is not limited. For example, the fourth indication information is carried in the CSI report configuration (CSI-ReportConfig) of the RRC signaling.

[0137] The fourth indication information indicates that the first communication device receives the second reference signal resource set information from the second communication device; the second reference signal resource set is used for the first communication device to perform AI operation on the first model, and the AI operation includes training and / or inference and / or monitoring.

[0138] S606, the second communication device sends fifth indication information to the first communication device. Correspondingly, the first communication device receives the fifth indication information from the second communication device.

[0139] Exemplarily, the fifth indication information can be carried in RRC signaling, DCI, a media access control (MAC) layer control element (CE), or other signaling, which is not limited. For example, the fifth indication information is carried in CSI-ReportConfig of RRC signaling.

[0140] The fifth indication information indicates the second relationship.

[0141] The second relationship includes an association relationship between the first reference signal resource set and the second reference signal resource set and / or a mapping relationship between the first reference signal resource set and the second reference signal resource set. The association relationship includes a second field in configuration information of the second reference signal resource set, and the second field is used for first reference signal resource set configuration information. The configuration information of the first reference signal resource set includes a configuration ID of the first reference signal resource set. The mapping relationship indicates that the second reference signal resource set is a subset of the first reference signal resource set, and includes a position of each signal resource in the second reference signal resource set corresponding to a signal resource in the first reference signal resource set.

[0142] S607, the first device measures the second reference signal resource set to obtain a second measurement result, and the second measurement result contains an input of the first communication device for first model inference.

[0143] Please refer to FIG. 7, which provides another beam management method for the communication method 700 of the embodiment of the present application. The steps shown in FIG. 7 will be introduced as follows.

[0144] S701-S707 are consistent with steps S601-S607 of embodiment 600.

[0145] S708, the first device measures the first reference signal resource set to obtain a third measurement result, and the third measurement result contains an input of the first communication device for first model inference.

[0146] In the embodiments of the present application, a beam management method is provided. The method is suitable for a scenario in which a network device configures a terminal device to perform multi-beam / resource scanning. Through the cooperation of the first relationship, the second relationship configuration, and the nominal reference signal resource information indication, the monitoring process of the terminal device on the multi-beam / resource model is supported, which is beneficial to reducing the number of times of scanning beams / resources of the terminal device and achieving energy saving effect.

[0147] It should be understood that, in order to implement the functions in the above embodiments, the base station and the terminal include hardware structures and / or software modules corresponding to the functions. Those skilled in the art should easily understand that, in combination with the units and method steps of the examples described in the embodiments disclosed in the present application, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is implemented in hardware or computer software driven hardware depends on the specific application scenarios and design constraints of the technical solutions.

[0148] FIGS. 8 to 10 are structural schematic diagrams of possible communication apparatuses provided by the embodiments of the present application. The communication apparatuses can be used to implement the functions of the first communication device or the second communication device in the above method embodiments, or to implement the functions of the terminal device or the network device in the above method embodiments, and thus can also achieve the beneficial effects possessed by the above method embodiments. In the embodiments of the present application, the communication apparatus can be the terminal device as involved in any one of FIGS. 1 to 4, or the network device as involved in FIG. 1, the network device as involved in FIG. 2, the CU, the DU, the core network device, the access network node or the OAM as involved in FIG. 3, or the non-real-time RIC, the near-real-time RIC, the CU, the DU, the CU-CP, the RU or the access network node as involved in FIG. 4, or a module (such as a chip) applied to the terminal device or the network device.

[0149] As shown in FIG. 8, the communication apparatus 800 includes a processing module 810 and a transceiver module 820.

[0150] In a possible embodiment, the communication apparatus 800 is used to implement the functions of the first communication device in the above method embodiment shown in FIG. 5, or the functions of the terminal device in the method embodiments shown in FIGS. 6 and 7.

[0151] For example, the transceiver module 820 can be used to receive the first indication information and transmit the first information, etc. under the control of the processing module 810.

[0152] The communication apparatus 800 can also implement the steps implemented by the first communication device in the method embodiment shown in FIG. 5, or the steps implemented by the terminal device in the method embodiments shown in FIGS. 6 and 7, which will not be listed one by one here.

[0153] In a possible embodiment, the communication apparatus 800 is used to implement the functions of the second communication device in the above method embodiment shown in FIG. 5, or the functions of the network device in the method embodiments shown in FIGS. 6 and 7.

[0154] For example, the transceiver module 820 can be used to transmit the first indication information and receive the first information, etc. under the control of the processing module 810.

[0155] The communication apparatus 800 can also implement the steps implemented by the second communication device in the method embodiments shown in FIG. 5, or the steps implemented by the network device in the method embodiments shown in FIG. 6 and FIG. 7, which are not listed one by one here.

[0156] As shown in FIG. 9, the communication apparatus 900 includes a processor 910 and an interface circuit 920. The processor 910 and the interface circuit 920 are coupled to each other. It can be understood that the interface circuit 920 can be a transceiver or an input / output interface. Optionally, the communication apparatus 900 can also include a memory 930 for storing instructions executed by the processor 910 or storing input data required by the processor 910 to run instructions or storing data generated after the processor 910 runs instructions.

[0157] The communication apparatus 900 can be used to implement the method embodiments shown in FIG. 5, FIG. 6 and FIG. 7.

[0158] Optionally, the communication apparatus 900 is also used to implement the functions of the communication apparatus 800 shown in FIG. 8. In this case, the processor 910 is used to implement the functions of the processing module 810 described above, and the interface circuit 920 is used to implement the functions of the transceiver module 820 described above.

[0159] When the above communication apparatus is a chip applied to a terminal device, the terminal device chip implements the functions of the terminal device in the above method embodiments. The terminal device chip receives information from other modules (such as a radio frequency module or an antenna) in the terminal device, and the information is sent by the network device to the terminal device; or the terminal device chip sends information to other modules (such as a radio frequency module or an antenna) in the terminal device, and the information is sent by the terminal device to the network device.

[0160] When the above communication apparatus is a module applied to a network device, the network device module implements the functions of the network device in the above method embodiments. The network device module receives information from other modules (such as a radio frequency module or an antenna) in the network device, and the information is sent by the terminal device to the network device; or the network device module sends information to other modules (such as a radio frequency module or an antenna) in the network device, and the information is sent by the network device to the terminal device. The network device module here can be a baseband chip of the network device, or a DU or other module, and the DU here can be a DU under the open radio access network (O-RAN) architecture.

[0161] It can be appreciated that the processor involved in various embodiments of the present application can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. The general-purpose processor can be a microprocessor or any conventional processor. In addition, the memory involved in various embodiments of the present application can include volatile memory (such as random access memory (RAM)), and can also include non-volatile memory (such as read-only memory (ROM), flash memory, mechanical hard disk drive (HDD) or solid state drive (SSD)).

[0162] Another example of a communication device is provided in the embodiments of the present application, which includes at least one processor and at least one memory, the at least one processor and the at least one memory are coupled, the at least one memory is used to store instructions, when the instructions are executed by the at least one processor, the communication device executes the method in the above embodiments. Taking the communication device including one processor and one memory as an example, as shown in FIG. 10, the communication device 1000 includes one processor 1010 and one memory 1020. The processor 1010 and the memory 1020 are coupled, and the memory 1020 stores instructions, when the instructions stored in the memory 1020 are executed by the processor 1010, the communication device 1000 executes any one of the method embodiments shown in FIG. 5, FIG. 6 and FIG. 7.

[0163] The method steps in the various embodiments of the present application can be implemented in hardware or in software instructions executable by a processor. The software instructions can be composed of corresponding software modules, which can be stored in a random access memory, a flash memory, a read-only memory, a programmable read-only memory, an erasable programmable read-only memory, an electrically erasable programmable read-only memory, a register, a hard disk, a mobile hard disk, a CD-ROM, or any other form of storage medium well known in the art. An exemplary storage medium is coupled to the processor, so that the processor can read information from and write information to the storage medium. The storage medium can also be an integral part of the processor. The processor and the storage medium can be located in an ASIC. In addition, the ASIC can be located in a base station or a terminal. The processor and the storage medium can also exist as discrete components in the base station or the terminal.

[0164] In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware, or any combination thereof. When implemented by software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer programs or instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments are performed. The computer can be a general-purpose computer, a special-purpose computer, a computer network, a network device, a user equipment, or other programmable apparatus. The computer programs or instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another computer-readable storage medium, for example, the computer programs or instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center through a wired or wireless manner. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that integrates one or more available media. The available medium can be a magnetic medium, such as a floppy disk, a hard disk, a magnetic tape; an optical medium, such as a digital video disc; or a semiconductor medium, such as a solid-state disk. The computer-readable storage medium can be a volatile or non-volatile storage medium, or can include both volatile and non-volatile storage media.

[0165] The embodiments of the present application provide a communication system, which includes a first communication device and a second communication device. The first communication device can implement the functions of the first communication device in FIG. 5, or implement the functions of the terminal device in FIG. 6 or FIG. 7. The second communication device can implement the functions of the second communication device in FIG. 5, or implement the functions of the network device in FIG. 6 or FIG. 7.

[0166] The chip system provided in the embodiments of the present application comprises a processor and an interface. The processor is configured to call and run an instruction from the interface. When the processor executes the instruction, any method shown in FIG. 5, FIG. 6 or FIG. 7 is implemented.

[0167] The computer readable storage medium provided in the embodiments of the present application is configured to store a computer program or instruction. When the computer program or instruction is run, any method shown in FIG. 5, FIG. 6 or FIG. 7 is implemented.

[0168] The computer program product provided in the embodiments of the present application comprises an instruction. When the instruction is run on a computer, any method shown in FIG. 5, FIG. 6 or FIG. 7 is implemented.

[0169] In the embodiments of the present application, the terms and / or descriptions of different embodiments are consistent and can be referred to each other if there is no special description and logical conflict. The technical features of different embodiments can be combined to form new embodiments according to their inherent logical relationship.

[0170] It can be understood that the various numbers involved in the embodiments of the present application are only used for differentiation for convenience of description, and are not used to limit the scope of the embodiments of the present application. The size of the serial numbers of the above processes does not mean the execution order, and the execution order of the processes should be determined according to their functions and inherent logic.

Claims

1. A communication method characterized by comprising: The method is applied to a first communication device, and the method comprises: receiving first indication information, second indication information, and third indication information from a second communication device; the first indication information indicates that the first communication device receives nominal reference signal resource set information from the second communication device; the second indication information indicates that the first communication device receives first reference signal resource set information from the second communication device; and the third indication information indicates a first relationship; the nominal reference signal resource set is used to represent a reference signal resource set corresponding to an output result of a first model of the first communication device; the first reference signal resource set is used for the first communication device to perform an AI operation on the first model, and the AI operation comprises one or more of the following: training, inference, or monitoring; the first relationship indicates a relationship between the nominal reference signal resource set and the first reference signal resource set.

2. The method of claim 1, wherein the first relationship comprises one or more of the following: an association relationship between the first reference signal resource set and the nominal reference signal resource set, or a mapping relationship from the first reference signal resource set to the nominal reference signal resource set.

3. The method of claim 2, wherein the association relationship comprises a first field in configuration information of the first reference signal resource set, and the first field is used to indicate configuration information of the nominal reference signal resource set; the configuration information of the nominal reference signal resource set comprises a configuration ID of the nominal reference signal resource set; the mapping relationship indicates that the first reference signal resource set is a subset of the nominal reference signal resource set, and comprises a position of each signal resource in the first reference signal resource set corresponding to a signal resource in the nominal reference signal resource set.

4. The method according to any one of claims 1 to 3, characterized in that, The method further comprises: the first communication device performs measurement on the first reference signal resource set to obtain a first measurement result, and the first measurement result comprises a label determined by the first communication device through training or monitoring of the first model.

5. The method of claim 1, wherein, The method further comprises: the first communication device receives fourth indication information and fifth indication information from the second communication device; the fourth indication information indicates that the first communication device receives second reference signal resource set information from the second communication device; and the fifth indication information indicates a second relationship; the second reference signal resource set is used for the first communication device to perform an AI operation on the first model, and the AI operation comprises one or more of the following: training, inference, or monitoring; the second relationship indicates a relationship between the first reference signal resource set and the second reference signal resource set.

6. The method of claim 5, wherein the second relationship comprises one or more of the following: an association relationship between the first reference signal resource set and the second reference signal resource set, or a mapping relationship between the first reference signal resource set and the second reference signal resource set. The association relationship includes a second field in configuration information of the second reference signal resource set, and the second field is used for first reference signal resource set configuration information. The configuration information of the first reference signal resource set includes a configuration ID of the first reference signal resource set. The mapping relationship indicates that the second reference signal resource set is a subset of the first reference signal resource set, and includes a position of each signal resource in the second reference signal resource set corresponding to a signal resource in the first reference signal resource set.

7. The method of claim 6, wherein, The method further includes: The first communication device measures the second reference signal resource set to obtain a second measurement result, and the second measurement result contains input of the first communication device for first model inference.

8. The method of claim 1, wherein, The method further includes: The first communication device measures the first reference signal resource set to obtain a third measurement result, and the third measurement result contains input of the first communication device for first model inference.

9. The method of claim 1, wherein: The first reference signal resource set is a proper subset of the nominal reference signal resource set.

10. A communication method characterized by comprising: The method applied to the second communication device includes: sending first indication information, second indication information, and third indication information to the first communication device; the first indication information indicates nominal reference signal resource set information; the second indication information indicates first reference signal resource set information; and the third indication information indicates a first relationship; The nominal reference signal resource set is used to represent a reference signal resource set corresponding to an output result of a first model of the first communication device; The first reference signal resource set is used for the first communication device to perform AI operation on the first model, and the AI operation includes one or more of the following: training, inference, or monitoring; The first relationship indicates a relationship between the nominal reference signal resource set and the first reference signal resource set.

11. The method of claim 10, wherein: The first relationship includes one or more of the following: An association relationship between the first reference signal resource set and the nominal reference signal resource set, or a mapping relationship from the first reference signal resource set to the nominal reference signal resource set.

12. The method of claim 11, wherein: The association relationship includes a first field in configuration information of the first reference signal resource set, and the first field is used to indicate configuration information of the nominal reference signal resource set; The configuration information of the nominal reference signal resource set includes a configuration ID of the nominal reference signal resource set; The mapping relationship indicates that the first reference signal resource set is a subset of the nominal reference signal resource set, and includes a position of each signal resource in the first reference signal resource set corresponding to a signal resource in the nominal reference signal resource set.

13. The method according to any one of claims 10 to 12, characterized in that, The first reference signal resource set is used to obtain a first measurement result, and the first measurement result contains a label determined by the first communication device through first model training or monitoring.

14. The method of claim 10, wherein, The method further includes: transmitting, to the first communication device, fourth indication information and fifth indication information; the fourth indication information indicates second reference signal resource set information; the fifth indication information indicates a second relationship; the second reference signal resource set is used for the first communication device to perform AI operation on the first model, the AI operation including one or more of the following: training, inference, or monitoring; the second relationship indicates a relationship between the first reference signal resource set and the second reference signal resource set.

15. The method of claim 14, wherein the second relationship includes one or more of the following: an association relationship between the first reference signal resource set and the second reference signal resource set, or a mapping relationship between the first reference signal resource set and the second reference signal resource set; the association relationship includes a second field in configuration information of the second reference signal resource set, the second field being used for first reference signal resource set configuration information, the first reference signal resource set configuration information including a configuration ID of the first reference signal resource set; the mapping relationship indicates that the second reference signal resource set is a subset of the first reference signal resource set, including that each signal resource in the second reference signal resource set corresponds to a position of a signal resource in the first reference signal resource set.

16. The method of claim 15, wherein, the second reference signal resource set is used to obtain a second measurement result, the second measurement result containing input for the first communication device to perform inference on the first model.

17. The method of claim 10, wherein, the first reference signal resource set is also used to obtain a third measurement result, the third measurement result containing input for the first communication device to perform inference on the first model.

18. The method of claim 10, wherein the first reference signal resource set is a proper subset of the nominal reference signal resource set.

19. A communications device, characterized by comprising: a module for performing the method of any one of claims 1-9 or a module for performing the method of any one of claims 10-18.

20. A communications device, characterized by comprising a processor and an interface circuit for receiving signals from other communication devices outside the communication device and transmitting signals to the processor or sending signals from the processor to other communication devices outside the communication device, the processor being used to implement the method of any one of claims 1-9 or claims 10-18 through logic circuit or executing code instructions.

21. A computer program, characterized in that, containing computer programs or instructions, when the computer programs or instructions are executed by a communication device, causing the communication device to perform the method of any one of claims 1-9 or claims 10-18.

22. A computer-readable storage medium, characterized in that, the storage medium is used to store computer programs or instructions, when the computer programs or instructions are executed by a communication device, implementing the method of any one of claims 1-9 or claims 10-18.

23. A communication system, characterized by comprising means for performing the method of any one of claims 1-9 and means for performing the method of any one of claims 10-18.

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