Communication method and apparatus

Abstract

A communication method and apparatus, which relate to the field of communications, and are compatible with basic requirements, such as cell resource management, and prediction-based mobility management, thereby ensuring system performance. The method comprises: receiving first indication information from a network device, and predicting a first measurement object on the basis of a correspondence between the first measurement object and a first AI function, so as to obtain a first prediction result, wherein the first indication information is used for indicating the correspondence between the first measurement object and the first AI function.

Description

Communication method and apparatus

[0001] The present application claims priority from the Chinese patent application No. 202411012241.8 filed on July 24, 2024, and entitled "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, in particular to a communication method and apparatus. BACKGROUND

[0003] In new radio (NR), intelligent collection and analysis of data using artificial intelligence (AI) / machine learning (ML) can improve network performance and user experience. In the life cycle management (LCM) decided by the network, the AI function of the terminal device is controlled by the network, such as the network sending activation / deactivation / switching / backoff management instructions to the terminal device according to the AI function reported by the terminal device, and when the AI function is activated, the terminal device uses the measurement result as the AI input to obtain the prediction result, wherein the measurement result is obtained by the terminal device according to the measurement configuration issued by the network.

[0004] However, the control flow of the AI function and the measurement flow are independent of each other, and when the network activates a certain AI function of the terminal device during mobility management, the terminal device will perform corresponding prediction on all measurement objects in the measurement configuration issued by the network, but not all measurement objects need to perform prediction for mobility management. Therefore, the prediction result reported by the terminal device will cause the decision of other management (such as cell resource management) on the network side to be unreasonable, resulting in a decline in system performance. Therefore, how to solve the problem of incompatibility between basic needs such as cell resource management and prediction-based mobility management is an urgent problem to be solved. SUMMARY

[0005] The present application provides a communication method and apparatus, which can be compatible with basic needs such as cell resource management and prediction-based mobility management, and ensure system performance.

[0006] To achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0007] In a first aspect, a communication method is provided, which can be applied to a terminal device side, such as a terminal device or a communication module in the terminal device, or a circuit or chip (such as a modem chip, also known as a baseband chip, or a system on chip (SoC) chip or a system in package (SIP) chip containing a modem core) responsible for communication functions in the terminal device. Taking the case where the method is applied to a terminal device, in the method: first indication information is received from a network device, the first indication information being used to indicate a correspondence between a first measurement object and a first artificial intelligence (AI) function. According to the correspondence between the first measurement object and the first AI function, the first measurement object is predicted to obtain a first prediction result.

[0008] In the method, the terminal device determines which measurement objects need to be predicted and which measurement objects need to be measured according to the first indication information indicating the correspondence between the AI function and the measurement object sent by the network device, which can avoid the terminal device predicting all the measurement objects in the received measurement configuration after receiving the AI function activation signaling. In addition, the correspondence between different measurement objects and AI functions can be flexibly configured through the first indication information, which can enable the network device to obtain the prediction result or the measurement result of different measurement objects, and further enable the network device to perform mobility management based on the prediction result and perform cell resource management based on the measurement result, which can be compatible with basic requirements such as cell resource management and prediction-based mobility management, and ensure the performance of the system.

[0009] In a possible design, the first indication information can include a correspondence between an identifier of the first measurement object and an identifier of the first AI function, or can include a correspondence between a measurement identifier associated with the first measurement object and an identifier of the first AI function. In this way, the first indication information can directly indicate the identifier of the first measurement object associated with the first AI function, or can indicate the measurement identifier associated with the first AI function, and further determine the first measurement object associated with the first AI function according to the measurement identifier, so as to enable the terminal device to know which measurement objects in the measurement configuration are used for prediction and which measurement objects are used for measurement.

[0010] In a possible design, receiving the first indication information from the network device can include: receiving a measurement configuration from the network device, the measurement configuration including the first indication information. In this way, in order to simplify the signaling process, the first indication information can be sent in the measurement configuration.

[0011] In a possible design, the receiving the first indication information from the network device can include: receiving first activation signaling from the network device, the first activation signaling being used to activate the first AI function, and the first activation signaling including the first indication information. In this way, in order to simplify the signaling process, the first indication information can also be carried in the first activation signaling.

[0012] In a possible design, the predicting the first measurement object according to the correspondence between the first measurement object and the first AI function to obtain the first prediction result can include: starting the first AI function in a case where the measurement configuration including the first measurement object and the first activation signaling are received, the first activation signaling being used to activate the first AI function. The first measurement object is predicted according to the correspondence between the first measurement object and the first AI function to obtain the first prediction result. That is, the terminal device starts the first AI function when it is determined that the measurement configuration including the first measurement object and the first activation signaling have been received; and the first AI function is not started during a period when the terminal device receives the measurement configuration but does not receive the first activation signaling or during a period when the terminal device receives the first activation signaling but does not receive the measurement configuration. In this way, the energy consumption of the terminal device can be reduced.

[0013] In a possible design, the method in the first aspect can further include: sending the first prediction result to the network device. In this way, after obtaining the first prediction result, the terminal device can report the first prediction result to the network device, so that the network device can perform corresponding decision and management according to the first prediction result.

[0014] In a possible design, the method in the first aspect can further include: receiving second indication information from the network device, the second indication information being used to indicate that the correspondence between the first measurement object and the first AI function is updated. In this way, the terminal device can obtain the correspondence between the measurement object and the AI function updated by the network device according to the reported prediction result, so as to guarantee system performance.

[0015] In a possible design, the method in the first aspect can further include: receiving third indication information from the network device, the third indication information being used to indicate an expected handover time. Performing radio link failure (RLF) prediction on a neighbor cell according to the third indication information to obtain a first RLF prediction result. Sending the first RLF prediction result. In this way, the terminal device can also perform RLF prediction on the neighbor cell according to the expected handover time indicated by the third indication information sent by the network device according to the reported prediction result, to obtain the RLF prediction result of the neighbor cell, so that the network device can determine a suitable target cell for handover according to the RLF prediction result, and can further determine whether the expected handover time determined according to the prediction result is suitable, to improve the success rate of cell handover of the terminal device.

[0016] In a possible design, the first RLF prediction result can include a probability that the neighbor cell will have an RLF within the expected handover time or whether the neighbor cell will have an RLF within the expected handover time.

[0017] In a possible design, the method in the first aspect can further include: sending, to the network device, fourth indication information, where the fourth indication information is used to indicate a recommended handover time and / or a recommended target cell. In this way, the terminal device can further recommend a handover time and a target cell to the network device according to the RLF prediction result of the neighbor cell, and can assist the network device in optimizing a handover decision.

[0018] In a possible design, the method in the first aspect can further include: receiving fifth indication information from the network device, where the fifth indication information is used to indicate an expected handover time and a target cell. Performing RLF prediction on the target cell according to the fifth indication information to obtain a second RLF prediction result. Sending the second RLF prediction result. In this way, the terminal device can perform RLF prediction on the target cell according to the expected handover time and the target cell indicated by the network device according to the reported prediction result, to obtain an RLF prediction result of the target cell, so that the network device can determine whether the expected handover time and the target cell determined according to the first prediction result are appropriate according to the RLF prediction result, to improve a success rate of cell handover of the terminal device.

[0019] In a possible design, the second RLF prediction result can include a probability that the target cell will have an RLF within the expected handover time or whether the target cell will have an RLF within the expected handover time.

[0020] In a possible design, the method in the first aspect can further include: sending, to the network device, fourth indication information, where the fourth indication information is used to indicate a recommended handover time and / or a recommended target cell. In this way, the terminal device can further recommend a handover time and a target cell to the network device according to the RLF prediction result of the neighbor cell, and can assist the network device in optimizing a handover decision.

[0021] In a possible design, the sending of the fourth indication information to the network device can include: sending the fourth indication information to the network device in a case where the target cell satisfies a first condition, and the first condition can be that a probability that the target cell will have an RLF within the expected handover time is greater than a first threshold, or that the target cell will have an RLF within the expected handover time. In this way, the terminal device can determine whether to recommend a handover time and a target cell to the network device according to the RLF prediction result of the target cell when performing RLF prediction on the target cell indicated by the network device.

[0022] In a possible design, the method of the first aspect can further include: receiving information for indicating the first threshold from the network device.

[0023] In a second aspect, a communication method is provided. The method can be applied to a network side, for example, a network device of the network side, a module (for example, a circuit, a processor, a chip or a chip system, etc.) in the network device, or a logic node, a logic module or software capable of implementing all or part of the functions of the network device. Taking the case that the method is applied to the network device, in the method: first indication information is generated, and the first indication information is used to indicate a correspondence between a first measurement object and a first AI function. The first indication information is sent to a terminal device.

[0024] In a possible design, the first indication information can include a correspondence between an identifier of the first measurement object and an identifier of the first AI function, or can include a correspondence between a measurement identifier associated with the first measurement object and the identifier of the first AI function.

[0025] In a possible design, the sending of the first indication information to the terminal device can include: sending, to the terminal device, a measurement configuration, and the measurement configuration includes the first indication information.

[0026] In a possible design, the sending of the first indication information to the terminal device can include: sending, to the terminal device, first activation signaling, and the first activation signaling is used to activate the first AI function, and the first activation signaling includes the first indication information.

[0027] In a possible design, the method of the second aspect can further include: receiving a first prediction result from the terminal device, and the first prediction result is determined according to the correspondence between the first measurement object and the first AI function.

[0028] In a possible design, the method of the second aspect can further include: sending, to the terminal device according to the first prediction result, second indication information, and the second indication information is used to indicate an update of the correspondence between the first measurement object and the first AI function.

[0029] In a possible design, the method of the second aspect can further include: sending, to the terminal device according to the first prediction result, third indication information, and the third indication information is used to indicate an expected handover time. The first RLF prediction result is received from the terminal device.

[0030] In a possible design, the first RLF prediction result can include a probability of an RLF of a neighbor cell occurring within the expected handover time or whether the RLF of the neighbor cell occurs within the expected handover time.

[0031] In a possible design, the method in the second aspect further includes: receiving fourth indication information from the terminal device, where the fourth indication information is used to indicate the recommended handover time and / or the recommended target cell.

[0032] In a possible design, the method in the second aspect further includes: sending fifth indication information to the terminal device according to the first prediction result, where the fifth indication information is used to indicate the expected handover time and the target cell; and receiving the second RLF prediction result from the terminal device.

[0033] In a possible design, the second RLF prediction result can include a probability that the target cell has an RLF within the expected handover time or whether the target cell has an RLF within the expected handover time.

[0034] In a possible design, the method in the second aspect further includes: receiving fourth indication information from the terminal device, where the fourth indication information is used to indicate the recommended handover time and / or the recommended target cell.

[0035] In a possible design, the method in the second aspect further includes: sending information used to indicate a first threshold to the terminal device, where the first threshold is a threshold compared with the probability that the target cell has an RLF within the expected handover time.

[0036] The technical effects of the method in the second aspect can refer to the related descriptions of the technical effects of the method in the first aspect, which are not repeated here.

[0037] In a third aspect, a communication apparatus is provided for implementing the methods described above. The communication apparatus can be the terminal device in the first aspect, or an apparatus including the terminal device, or an apparatus included in the terminal device, such as a chip. The communication apparatus includes corresponding modules, units, or means for implementing the methods in the first aspect, which can be implemented by hardware, by software, or by a combination of hardware and software. The hardware or software includes one or more modules or units corresponding to the functions described above.

[0038] In some possible designs, the communication apparatus includes a processing module and a transceiver module. The transceiver module is configured to receive first indication information from a network device, where the first indication information is used to indicate a correspondence between a first measurement object and a first artificial intelligence (AI) function. The processing module is configured to perform prediction on the first measurement object according to the correspondence between the first measurement object and the first AI function, to obtain a first prediction result.

[0039] In a possible design, the first indication information can include a correspondence between an identifier of the first measurement object and an identifier of the first AI function, or can include a correspondence between a measurement identifier associated with the first measurement object and the identifier of the first AI function.

[0040] In a possible design, the transceiver configured to receive the first indication information from the network device can include: a transceiver configured to receive, from the network device, a measurement configuration, the measurement configuration including the first indication information.

[0041] In a possible design, the transceiver configured to receive the first indication information from the network device can include: a transceiver configured to receive, from the network device, first activation signaling, the first activation signaling being used to activate the first AI function, and the first activation signaling including the first indication information.

[0042] In a possible design, the processing module configured to perform prediction on the first measurement object according to the correspondence between the first measurement object and the first AI function to obtain the first prediction result can include: a processing module configured to, in a case where a measurement configuration and first activation signaling are received, start the first AI function, the measurement configuration including the first measurement object, and the first activation signaling being used to activate the first AI function. The processing module is configured to perform prediction on the first measurement object according to the correspondence between the first measurement object and the first AI function to obtain the first prediction result.

[0043] In a possible design, the transceiver is further configured to send, to the network device, the first prediction result.

[0044] In a possible design, the transceiver is further configured to receive, from the network device, second indication information, the second indication information being used to indicate an update of the correspondence between the first measurement object and the first AI function.

[0045] In a possible design, the transceiver is further configured to receive, from the network device, third indication information, the third indication information being used to indicate an expected handover time. The processing module is further configured to perform radio link failure (RLF) prediction on a neighbor cell according to the third indication information to obtain a first RLF prediction result. The transceiver is further configured to send the first RLF prediction result.

[0046] In a possible design, the first RLF prediction result can include a probability of the neighbor cell having an RLF within the expected handover time or whether the neighbor cell has an RLF within the expected handover time.

[0047] In a possible design, the transceiver is further configured to send, to the network device, fourth indication information, the fourth indication information being used to indicate a recommended handover time and / or a recommended target cell.

[0048] In a possible design, the transceiver module is further configured to receive fifth indication information from the network device, where the fifth indication information is used to indicate the expected handover time and the target cell; the processing module is further configured to perform RLF prediction on the target cell according to the fifth indication information, to obtain a second RLF prediction result; and the transceiver module is further configured to send the second RLF prediction result.

[0049] In a possible design, the second RLF prediction result can include a probability of the target cell experiencing RLF within the expected handover time or whether the target cell will experience RLF within the expected handover time.

[0050] In a possible design, the transceiver module is further configured to send fourth indication information to the network device, where the fourth indication information is used to indicate the recommended handover time and / or the recommended target cell.

[0051] In a possible design, the transceiver module is further configured to send the fourth indication information to the network device, which can include that, in a case where the target cell satisfies a first condition, the transceiver module is further configured to send the fourth indication information to the network device, where the first condition can be that the probability of the target cell experiencing RLF within the expected handover time is greater than a first threshold, or the target cell will experience RLF within the expected handover time.

[0052] In a possible design, the transceiver module is further configured to receive information used to indicate the first threshold from the network device.

[0053] In a possible design, the transceiver module can include a receiving module and a sending module. The sending module is configured to implement the sending function of the communication apparatus in the third aspect, and the receiving module is configured to implement the receiving function of the communication apparatus in the third aspect.

[0054] In a possible design, the communication apparatus in the third aspect can further include a storage module that stores programs or instructions. When the processing module executes the programs or instructions, the communication apparatus in the third aspect can perform the method in the first aspect.

[0055] In a fourth aspect, a communication apparatus is provided to implement the above-described methods. The communication apparatus can be the network device in the second aspect, or an apparatus including the network device, or an apparatus included in the network device, such as a chip. The communication apparatus includes corresponding modules, units, or means for implementing the methods in the second aspect, which can be implemented by hardware, software, or by executing corresponding software by hardware. The hardware or software includes one or more modules or units corresponding to the above-described functions.

[0056] In some possible design, the communication apparatus includes a processing module and a transceiver module. The processing module generates first indication information, the first indication information being used to indicate a correspondence between a first measurement object and a first AI function. The transceiver module is configured to send the first indication information to a terminal device.

[0057] In a possible design, the first indication information can include a correspondence between an identifier of the first measurement object and an identifier of the first AI function, or can include a correspondence between a measurement identifier associated with the first measurement object and the identifier of the first AI function.

[0058] In a possible design, the transceiver module configured to send the first indication information to the terminal device can include that the transceiver module is configured to send, to the terminal device, a measurement configuration, the measurement configuration including the first indication information.

[0059] In a possible design, the transceiver module configured to send the first indication information to the terminal device can include that the transceiver module is configured to send, to the terminal device, first activation signaling, the first activation signaling being used to activate the first AI function, and the first activation signaling including the first indication information.

[0060] In a possible design, the transceiver module is further configured to receive, from the terminal device, a first prediction result, the first prediction result being determined according to the correspondence between the first measurement object and the first AI function.

[0061] In a possible design, the transceiver module is further configured to send, to the terminal device, second indication information according to the first prediction result, the second indication information being used to indicate an update of the correspondence between the first measurement object and the first AI function.

[0062] In a possible design, the transceiver module is further configured to send, to the terminal device, third indication information according to the first prediction result, the third indication information being used to indicate an expected handover time. The transceiver module is further configured to receive, from the terminal device, a first RLF prediction result.

[0063] In a possible design, the first RLF prediction result can include a probability of an RLF of a neighbor cell occurring within the expected handover time or whether the RLF of the neighbor cell occurs within the expected handover time.

[0064] In a possible design, the transceiver module is further configured to receive, from the terminal device, fourth indication information, the fourth indication information being used to indicate a recommended handover time and / or a recommended target cell.

[0065] In a possible design, the transceiver module is further configured to send, to the terminal device, fifth indication information according to the first prediction result, where the fifth indication information is used to indicate the expected handover time and the target cell.

[0066] In a possible design, the second RLF prediction result can include a probability of the target cell experiencing an RLF within the expected handover time or whether the target cell will experience an RLF within the expected handover time.

[0067] In a possible design, the transceiver module is further configured to receive, from the terminal device, fourth indication information, where the fourth indication information is used to indicate a recommended handover time and / or a recommended target cell.

[0068] In a possible design, the transceiver module is further configured to send, to the terminal device, information used to indicate a first threshold value, where the first threshold value is a threshold value compared with a probability of the target cell experiencing an RLF within the expected handover time.

[0069] In a possible design, the transceiver module can include a receiving module and a sending module. The sending module is configured to implement the sending function of the communication apparatus in the fourth aspect, and the receiving module is configured to implement the receiving function of the communication apparatus in the fourth aspect.

[0070] In a possible design, the communication apparatus in the fourth aspect can further include a storage module, which stores a program or an instruction. When the processing module executes the program or the instruction, the communication apparatus in the fourth aspect can execute the method in the second aspect.

[0071] In the fifth aspect, a communication apparatus is provided, which includes an interface circuit and one or more processors. The one or more processors are coupled with a memory. The memory is used to store part or all of necessary computer programs or instructions for implementing the functions involved in the first aspect. The one or more processors can execute the computer programs or instructions, and when the computer programs or instructions are executed, the communication apparatus implements the method in any possible design or implementation manner in the first aspect. The interface circuit is used to implement the communication function within the communication apparatus and / or the communication function of the communication apparatus with other devices or components.

[0072] In a possible design, the processor is configured to communicate with other devices or components through the interface circuit.

[0073] In a possible design, the communication apparatus can further include the memory.

[0074] The communication device can be a terminal device, a communication module in the terminal device, or a chip responsible for communication functions in the terminal device, such as a modem chip (also known as a baseband chip) or a SoC or SIP chip containing a modem module.

[0075] In a sixth aspect, a communication device is provided, which includes an interface circuit and one or more processors. The one or more processors are coupled with a memory. The memory is configured to store part or all of the necessary computer programs or instructions for implementing the functions described in the second aspect. The one or more processors can execute the computer programs or instructions, which, when executed, cause the communication device to implement the method in any possible design or implementation manner of the second aspect. The interface circuit is configured to implement the communication function within the communication device and / or the communication function of the communication device with other devices or components.

[0076] In a seventh aspect, a communication system is provided, which includes a terminal device for executing the method described in the first aspect, and a network device for executing the method described in the second aspect.

[0077] In an eighth aspect, a chip is provided, in which instructions are stored, which, when the chip is running on a communication device, cause the method described in the first aspect or the second aspect to be implemented.

[0078] In a ninth aspect, a computer readable storage medium is provided, in which computer readable instructions are stored, which, when read and executed by a computer, cause the computer to execute the method in any possible design of the first aspect to the second aspect.

[0079] In a tenth aspect, a computer program product containing instructions is provided, which, when read and executed by a computer, cause the computer to execute the method in any possible design of the first aspect to the second aspect. BRIEF DESCRIPTION OF DRAWINGS

[0080] FIG. 1 is a schematic diagram of an architecture of a communication system according to an embodiment of the present application;

[0081] FIG. 2 is a schematic diagram of a structure of a network device based on an O-RAN architecture according to an embodiment of the present application;

[0082] FIG. 3 is a schematic diagram of a framework of an AI application;

[0083] FIG. 4 is a schematic diagram of a management process of an AI function / AI model;

[0084] FIG. 5 is a schematic diagram of a scenario of AI-based RRM measurement prediction;

[0085] FIG. 6 is a flow diagram of a communication method according to an embodiment of the present application;

[0086] FIG. 7 is a flow diagram of another communication method according to an embodiment of the present application;

[0087] FIG. 8 is a flow diagram of another communication method according to an embodiment of the present application;

[0088] FIG. 9 is a flow diagram of a communication method applied to an O-RAN architecture according to an embodiment of the present application;

[0089] FIG. 10 is a structural diagram of a communication apparatus according to an embodiment of the present application;

[0090] FIG. 11 is a structural diagram of another communication apparatus according to an embodiment of the present application. DETAILED DESCRIPTION

[0091] In order to better understand the embodiments of the present application, the following points are explained before the embodiments of the present application are introduced.

[0092] First, in the embodiments of the present application, the first, second and various numbers are only distinguished for convenience of description, and do not limit the scope of the embodiments of the present application. For example, different indication information is distinguished. For another example, the first network area and the second network area are only distinguished for different areas, and do not limit the order. Those skilled in the art can understand that the words "first", "second" and the like do not limit the number and execution order, and the words "first", "second" and the like do not necessarily mean different.

[0093] Second, in the embodiments of the present application, the descriptions such as "when", "in the case of", "if" and "if" all refer to the objective situation that the device (such as a terminal device or a network device) will make corresponding processing, which is not limited by time, and does not require the device (such as a terminal device or a network device) to have a judgment action when implemented, and does not mean that there are other limitations.

[0094] Third, in the embodiments of the present application, the words "exemplary" or "for example" are used to indicate an example, illustration or description. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the words "exemplary" or "for example" are intended to present the relevant concept in a specific manner for understanding.

[0095] Fourth, in the embodiments of the present application, "at least one" means one or more, and "multiple" means two or more. The "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 the following three cases: 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 an "or" relationship between the associated objects before and after it. "At least one of the following" or similar expressions means any combination of multiple items, including any combination of single item or multiple items. For example, at least one of a, b, or c can represent a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, and c can be single or multiple.

[0096] Finally, the network architecture and service scenarios described in the embodiments of the present application are used to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that, with the evolution of network architecture and the appearance of new service scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0097] The embodiments of the present application will present various aspects, embodiments or features around a system that can include multiple devices, components, modules, etc. It should be understood and appreciated that each system can include additional devices, components, modules, etc., and / or can not include all the devices, components, modules, etc. discussed in conjunction with the drawings. In addition, combinations of these solutions can also be used.

[0098] The technical solutions of the embodiments of the present application can be applied to various communication systems, such as a wireless fidelity (Wi-Fi) system, a vehicle to everything (V2X) communication system, a device-to-device (D2D) communication system, a vehicle networking communication system, a 4th generation (4G) mobile communication system such as a long term evolution (LTE) system, a worldwide interoperability for microwave access (WiMAX) communication system, a 5th generation (5G) mobile communication system such as an NR system, and a future communication system.

[0099] Please refer to FIG. 1, which is a schematic diagram of a possible and non-restrictive communication system. As shown in FIG. 1, the communication system 1000 includes a radio access network (RAN) 100 and a core network (CN) 200. Optionally, the communication system 1000 can also include the Internet 300. The RAN 100 includes at least one RAN node (e.g., 110a and 110b in FIG. 1, collectively referred to as 110) and at least one terminal (e.g., 120a-120j in FIG. 1, collectively referred to as 120). The RAN 100 can also include other RAN nodes, such as wireless relay devices and / or wireless backhaul devices (not shown in FIG. 1), etc. The terminal 120 is connected to the RAN node 110 in a wireless manner. The RAN node 110 is connected to the core network 200 in a wireless or wired manner. The core network device in the core network 200 and the RAN node 110 in the RAN 100 can be different physical devices respectively, or can be the same physical device integrated with the logical functions of the core network and the logical functions of the radio access network.

[0100] The RAN 100 can be a 3rd generation partnership project (3GPP) related cellular system, such as a 4G, 5G mobile communication system, or a future-oriented evolved system. The RAN 100 can also be an open radio access network (O-RAN or ORAN), a cloud radio access network (CRAN), or a Wi-Fi system. The RAN 100 can also be a communication system that combines two or more of the above systems.

[0101] The RAN node 110, which can also be referred to as a network device, an access network device, a RAN entity, or an access node, etc., constitutes a part of the communication system to help the terminal to implement wireless access. The multiple RAN nodes 110 in the communication system 1000 can be nodes of the same type or nodes of different types. In some scenarios, the roles of the RAN node 110 and the terminal 120 are relative, for example, the network element 120i in FIG. 1 can be a helicopter or a drone, which can be configured as a mobile base station. For those terminals 120j that access the RAN 100 through the network element 120i, the network element 120i is a base station; but for the base station 110a, the network element 120i is a terminal. The RAN node 110 and the terminal 120 are sometimes collectively referred to as communication apparatuses, for example, the network elements 110a and 110b in FIG. 1 can be understood as communication apparatuses with base station functions, and the network elements 120a-120j can be understood as communication apparatuses with terminal functions.

[0102] In a possible scenario, the RAN node can be a base station, an evolved NodeB (eNodeB), an access point (AP), a transmission reception point (TRP), a next generation NodeB (gNB), a base station in a future mobile communication system, or an access node in a Wi-Fi system, etc. The RAN node can be a macro base station (such as 110a in FIG. 1), a micro base station or an indoor station (such as 110b in FIG. 1), a relay node or a donor node, or a wireless controller in a CRAN scenario. Optionally, the RAN node can also be a server, a wearable device, a vehicle or a vehicle-mounted device, etc. For example, the access network device in the V2X technology can be a road side unit (RSU). All or part of the functions of the RAN node in this application can also be implemented by software functions running on hardware, or by virtualized functions instantiated on a platform (such as a cloud platform). The RAN node can also be provided with a communication module, circuit or chip for performing corresponding communication functions, and program instructions for performing corresponding communication functions. The RAN node in this application can also be a logical node, a logical module or software that can implement all or part of the functions of the RAN node.

[0103] In another possible scenario, multiple RAN nodes cooperate to assist a terminal to implement wireless access, and different RAN nodes respectively implement part of the functions of a base station. For example, the RAN node can be a central unit (CU), a distributed unit (DU), a CU-control plane (CP), a CU-user plane (UP), or a radio unit (RU), etc. The CU and the DU can be separately arranged, or can be included in the same network element, such as a baseband unit (BBU). The RU can be included in a radio frequency device or a radio frequency unit, such as a radio frequency remote unit (RRU), an active antenna processing unit (AAU), or a remote radio head (RRH).

[0104] In different systems, the CU (or CU-CP and CU-UP), DU or RU can also have different names, but those skilled in the art can understand their meanings. For example, in an 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, the CU-UP can also be referred to as an O-CU-UP, and the RU can also be referred to as an O-RU. For the convenience of description, the CU, CU-CP, CU-UP, DU and RU are taken as examples for description in this application. Any one of the CU (or CU-CP, CU-UP), DU and RU in this application can be implemented by a software module, a hardware module, or a combination of a software module and a hardware module.

[0105] A terminal can access the above communication system and has a corresponding communication function. The terminal can also be referred to as a terminal device, a user equipment (UE), a mobile station, a mobile terminal, etc. The terminal can be widely used in various scenarios, such as D2D, V2X communication, machine-type communication (MTC), internet of things (IoT), virtual reality, augmented reality, industrial control, autonomous driving, remote medical treatment, smart power grid, smart furniture, smart office, smart wear, smart transportation, smart city, etc. The terminal can be a mobile phone, a tablet computer, a computer with wireless transceiver function, a wearable device, a vehicle, a drone, a helicopter, an airplane, a ship, a robot, a mechanical arm, a smart home device, a transport vehicle with wireless communication function, a communication module, etc. Embodiments of the present application do not limit the device form of the terminal. The terminal usually has a communication module, circuit or chip for executing corresponding communication functions. The terminal also has a program instruction for executing corresponding communication functions.

[0106] In addition, the structure diagram of a network device based on an O-RAN architecture provided by an embodiment of the present application is shown in FIG. 2. The network device includes an intelligent controller (RAN intelligent controller, RIC), a CU and a DU. The RIC and the CU communicate through an E2 interface, the RIC and the DU also communicate through an E2 interface, and the CU and the DU communicate through an F1 interface.

[0107] The RIC can include a near real-time RIC (near real-time RIC, NRT-RIC) and a non-real-time RIC (non-real-time RIC, Non-RT RIC). For example, the RIC can be an AI module for implementing AI-related functions.

[0108] The NRT-RIC is configured to perform model training and inference. For example, the NRT-RIC is configured to train an AI model and perform inference using the AI model. The NRT-RIC can obtain network side and / or terminal device side information from network devices (e.g., CUs, CU-CPs, CU-UPs, DUs, and / or RUs) and / or terminal devices. The information can be used as training data or inference data. The NRT-RIC can provide inference results to the network devices and / or the terminal devices. The inference results can be exchanged between CUs and DUs, and / or between DUs and RUs. For example, the NRT-RIC provides inference results to a DU, and the DU provides the inference results to RUs.

[0109] The Non-RT RIC is configured to perform model training and inference. For example, the Non-RT RIC is configured to train an AI model and perform inference using the AI model. The Non-RT RIC can obtain network side and / or terminal device side information from network devices (e.g., CUs, CU-CPs, CU-UPs, DUs, and / or RUs) and / or terminal devices. The information can be used as training data or inference data. The inference results can be provided to the network devices and / or the terminal devices. The inference results can be exchanged between CUs and DUs, and / or between DUs and RUs. For example, the Non-RT RIC provides inference results to a DU, and the DU provides the inference results to RUs.

[0110] The NRT-RIC and the Non-RT RIC can also be implemented as separate network elements. Alternatively, the NRT-RIC and the Non-RT RIC can also be implemented as part of other devices. For example, the NRT-RIC can be implemented in a network device (e.g., a CU or a DU), and the Non-RT RIC can be implemented in an operation, administration and maintenance (OAM) device, a cloud server, a core network device, or another network device.

[0111] In some implementations, the RIC can also be replaced by a service unit (SU), without limitation.

[0112] It should be noted that the solutions in the embodiments of the present application can also be applied to other communication systems, and the corresponding names can also be replaced by the names of corresponding functions in other communication systems. In the present application, the RAN nodes are expressed as network devices, and the terminals are expressed as terminal devices, unless otherwise specified.

[0113] It should be understood that the names of nodes, modules, devices or network elements in different scenarios or architectures or systems, and the names of communication interfaces between two nodes, modules, devices or network elements in the embodiments of the present application are exemplarily given, and the possibility of name changes in future communication systems or scenarios or architectures is not excluded.

[0114] The related terms or technologies involved in the embodiments of the present application are introduced below.

[0115] 1、AI

[0116] AI is a technology that performs complex calculations by simulating the human brain. With the improvement of data storage and computing power, AI has been more and more used. The protocol release (R) 17 of 3GPP passed a study item (SI) to apply AI to NR, to improve network performance and user experience by intelligently collecting and analyzing data. As shown in FIG. 3, the AI application framework in NR can include the following modules:

[0117] The data collection module is used to collect and store data from next generation Node-B (gNB), gNB-central unit (CU), gNB-distributed unit (DU), UE or other management entities, as a database for AI model training and data analysis inference; the model training module gives the optimal AI model by analyzing the training data provided by the data collection module. The model inference module uses the AI model to give reasonable prediction based on the inference data provided by the data collection module, or to guide the network to make policy adjustment. The decision / actor module executes the related policy adjustment output by the model inference module, and feeds back the specific performance (such as various performance parameters) of the network after applying the related policy to the data collection module for storage.

[0118] The LCM of the AI model is the management of the whole process of the AI model from beginning to end. In the LCM of the AI function / AI model decided by the network (NW), as shown in FIG. 4, it includes:

[0119] S401, the UE sends the capability and / or assistance information to the NW. Correspondingly, the NW receives the capability and / or assistance information from the UE.

[0120] Among them, the capability information is used to indicate the features supported by the UE, such as the application scenarios supported by the UE, the AI functions supported by the UE, etc.; the assistance information is used to indicate the AI / ML model supported by the UE and the related information about the AI / ML function, such as the conditions suitable for the model / function or whether the model / function is suitable for the current scenario.

[0121] S402, the NW makes a decision according to the capability and / or assistance information.

[0122] S403, the NW sends a management instruction to the UE. Correspondingly, the UE receives the management instruction from the NW.

[0123] The management instruction is, for example, an AI model / AI function activation / deactivation / switching / update / backoff instruction. For example, the NW determines that there is a suitable model / function according to the capability and / or assistance information reported by the UE, and sends an AI model / function activation instruction to the UE.

[0124] S404, the UE sends performance / actual measurement results to the NW. Correspondingly, the NW receives the performance / actual measurement results from the UE.

[0125] The UE reports the AI model performance monitored by it or the actual measurement results to the NW, which is used to assist the NW in monitoring.

[0126] S405, the NW monitors according to the performance / actual measurement results.

[0127] For example, the NW monitors that the AI model / function performance of the current UE is too poor, and can send an AI model / function deactivation or switching instruction to the UE.

[0128] 2, AI-based application scenarios

[0129] Currently, 3GPP respectively studies the application of AI at the RAN side from the working groups of RAN3 and RAN1. The application scenarios (use cases) of AI technology mainly studied by RAN1 include: 1) channel state information (CSI) feedback enhancement; 2) beam management (BM); 3) positioning accuracy enhancement. The application scenarios of AI technology mainly studied by RAN3 include: 1) energy saving (ES); 2) load balancing; 3) mobility optimization.

[0130] And the AI mobility is a subject in RAN2, and the application scenarios of the research include the following:

[0131] • AI / ML based radio resource management (RRM) measurement and events

[0132] • Cell level measurement prediction, including intra-frequency and inter-frequency (considering UE side and NW side models)

[0133] • Inter-cell beam level L3 mobility measurement prediction (UE side and NW side models)

[0134] • Handover failure (HOF) / radio link failure (RLF) prediction (considering UE side models)

[0135] • Measurement event prediction (considering UE side models)

[0136] Currently, in the AI-based RRM measurement prediction, including time domain prediction, space domain prediction, and frequency domain prediction. Among them, the time domain prediction is to predict the future measurement information by using the historical measurement information of the cell, as shown in (a) of FIG. 5, the measured results of each measurement instance in the observation time window are taken as the input of the AI model / function, and the predicted results of each predicted instance in the prediction time window are predicted.

[0137] The space domain prediction is to predict the measurement results of all beams by using the measurement results of part of the beams of the cell, and then obtain the measurement results of the cell, as shown in (b) of FIG. 5, the beam measurement results of beams a1 and a3 of cell a are taken as the input of the AI model / function, and the beam measurement results of beams a1-a4 of cell a can be predicted, or the beam measurement results of beams b1 and b3 of cell b are taken as the input of the AI model / function, and the beam measurement results of beams b1-b4 of cell b can be predicted.

[0138] In the time domain prediction and the space domain prediction, the cell can be a serving cell of a terminal device, or a neighbor cell of the serving cell.

[0139] The frequency domain prediction is to predict the measurement results of the inter-frequency neighbor cell by using the measurement results of the serving cell, as shown in (c) of FIG. 5, the measurement results of the serving cell with frequency point Fa are taken as the input of the AI model / function, and the measurement results of the neighbor cell with frequency point Fb can be predicted.

[0140] And the measurement result input as the AI model / function is realized based on the measurement mechanism, that is, the network sends a measurement configuration to the terminal device, the measurement configuration includes a measurement object, a measurement identity and a reporting configuration, the measurement identity (denoted as measId) associates the measurement object and the reporting configuration together.

[0141] The measurement object includes an identification of the measurement object (denoted as measObjectId), a frequency point of a reference signal, a measurement occasion configuration, and a reference information type, etc., the reporting configuration includes an event triggered report and a periodic triggered report, and the reporting configuration also has a corresponding reporting configuration identification (denoted as reportConfigId). When the terminal device reports the measurement result to the network, the measurement identity is carried, so that the network can know which measurement object and reporting configuration the measurement result corresponds to according to the measurement identity.

[0142] However, the control flow of the AI model / function and the measurement flow are independent of each other. When the network activates a certain AI model / function of the terminal device during mobility management, the terminal device will perform corresponding prediction on all measurement objects in the measurement configuration issued by the network, that is, the measurement result obtained based on each measurement object is predicted, which causes the terminal device to report all prediction results corresponding to the measurement objects, for the network to perform prediction-based mobility management, thereby causing the decision of other management (such as cell resource management) on the network side to be unreasonable, resulting in a decline in system performance. Therefore, how to solve the problem of incompatibility between basic requirements such as cell resource management and prediction-based mobility management is an urgent problem to be solved.

[0143] Therefore, the embodiments of the present application provide a communication method and device, by indicating the correspondence between the AI function and the measurement object, the basic requirements such as cell resource management and the prediction-based mobility management can be compatible, so that the network can obtain the measured or predicted results of different measurement objects, and the performance of the system is ensured.

[0144] The communication method provided by the embodiments of the present application will be described in detail below with reference to FIGS. 6 and 7.

[0145] Exemplarily, FIG. 6 is a flow diagram of a communication method provided by an embodiment of the present application. It can be understood that the network device and the terminal device shown in FIG. 1 are taken as an example to illustrate the execution subject of the interaction, but the present application does not limit the execution subject of the interaction. For example, the method executed by the network device in the present application can also be implemented by a module (such as a circuit, a processor, a chip or a chip system, etc.) in the network device, or a logic node, a logic module or software capable of realizing all or part of the functions of the network device; the method executed by the terminal device in the present application can also be implemented by a communication module in the terminal device or a circuit or chip (such as a modem chip (also known as a baseband chip), or a SoC chip containing a modem core, or a SIP chip) responsible for communication functions in the terminal device.

[0146] As shown in FIG. 6, the communication method comprises:

[0147] S601, the network device sends first indication information to the terminal device. Correspondingly, the terminal device receives the first indication information from the network device.

[0148] The first indication information is used to indicate the correspondence between the first measurement object and the first AI function. It can be understood that the first indication information is used to indicate that the first AI function is used to predict the first measurement object, that is, the terminal device can use the measurement result measured according to the first measurement object as the input of the first AI function to predict, and the obtained prediction result can be used for mobility management. Alternatively, the first indication information can also be used to indicate the correspondence between the first measurement object and the first AI model. It can be understood that the first indication information is used to indicate that the first AI model is used to predict the first measurement object, that is, the terminal device can use the measurement result measured according to the first measurement object as the input of the first AI model to predict, and the obtained prediction result can be used for mobility management.

[0149] In the embodiment of the present application, the AI function can be replaced by the AI model, different AI functions / AI models are used to perform different functions and / or types of prediction or reasoning, and each AI function / AI model can correspond to a function / model identifier, which can be represented as functionality / model ID. It should be understood that the model identifier can be used to identify the model, and the model identifier can be assigned by the terminal device, the network device or the core network element, and is not limited. In some implementations, the model identifier can be the identifier of a data set, and the data set is a data set used to train the corresponding model.

[0150] The measurement object is configured and sent by the network device. During measurement, the network device sends one or more measurement object configurations to the terminal device through the measurement configuration, which includes measurement identification, measurement object, and report configuration. One measurement identification is used to associate one measurement object and one report configuration, and the measurement identification can be represented as measld. Different measurement objects can correspond to different types of measurements, and each measurement object (which can be represented as measObject) corresponds to an identification, which can be referred to as a measurement object identification and represented as measObjectId. The report configuration is used to configure the measurement report reporting mode of the measurement object, such as periodic reporting or event-triggered reporting, and each report configuration (which can be represented as reportConfig) corresponds to an identification, which can be referred to as a report configuration identification and represented as reportConfigld.

[0151] The configuration of the measurement object containing different measurement identifications can associate the same measurement object and / or the same report configuration, and this is not limited. That is, different measurement identifications can associate the same measurement object but different report configurations, or different measurement identifications can associate different measurement objects but the same report configuration.

[0152] For example, measld#1 is associated with measObject#1 and reportConfig#1, the identification of measObject#1 is measObjectId#1, the identification of reportConfig#1 is reportConfigld#1, and the configuration of measld#1, measObject#1, and reportConfig#1 in the measurement configuration can be considered as the configuration#1 of measurement object#1. Measld#2 is associated with measObject#1 and reportConfig#2, the identification of measObject#1 is measObjectId#1, the identification of reportConfig#2 is reportConfigld#2, and the configuration of measld#2, measObject#1, and reportConfig#2 in the measurement configuration can be considered as the configuration#2 of measurement object#1. Measld#3 is associated with measObject#2 and reportConfig#2, the identification of measObject#2 is measObjectId#2, the identification of reportConfig#2 is reportConfigld#2, and the configuration of measld#3, measObject#2, and reportConfig#2 in the measurement configuration can be considered as the configuration#1 of measurement object#2.

[0153] It should be understood that the configuration containing multiple measurement objects in the measurement configuration, the same measurement object can correspond to multiple different configurations.

[0154] In some possible implementations, the measurement configuration can be carried in a radio resource control (RRC) message, such as an RRC reconfiguration message or an RRC resume message.

[0155] In the embodiments of the present application, the measurement object for which prediction is made according to the first AI function is referred to as the first measurement object, and correspondingly, the configuration in the measurement configuration containing the first measurement object is the configuration for making prediction according to the first AI function. For the configurations of multiple measurement objects issued by the network device, which of the configurations of the measurement objects are used to make prediction according to the first AI function by the terminal device, and which of the configurations of the measurement objects are used to directly report the actual measurement results (hereinafter referred to as actual measurement results) obtained by the configurations, that is, which of the measurement objects in the measurement configuration are used to report the prediction results, and which of the measurement objects in the measurement configuration are used to report the actual measurement results, can be indicated by the first indication information.

[0156] In a possible design, the first indication information can include a correspondence between the identifier of the first measurement object and the identifier of the first AI function, which can be represented as (measObjectId, functionality ID). That is, the first indication information can directly indicate the identifier of the first measurement object using the first AI function, so that the terminal device can know, according to the correspondence, which of the measurement objects in the measurement configuration are used to report the prediction results, and which of the measurement objects in the measurement configuration are used to report the actual measurement results.

[0157] For example, the identifier of the first measurement object is measObjectId#1, the identifier of the first AI function is functionality ID#1, and the first indication information can include (measObjectId#1, functionality ID#1).

[0158] It should be understood that, in the embodiments of the present application, the prediction on the measurement configuration means that the measurement result obtained by actually measuring the measurement object in the measurement configuration is used as the input of the AI function for prediction or inference.

[0159] In another possible design, the first indication information can include a correspondence between a measurement object associated measurement identity and an identifier of the first AI function, which can be represented as (measId, functionality ID). That is, the first indication information can indirectly indicate the correspondence between the first measurement object and the first AI function by indicating the correspondence between the measurement identity and the first AI function, where the measurement object associated with the measurement identity is the first measurement object.

[0160] For example, the measurement identity is measId#1, the identifier of the first AI function is functionality ID#1, and the first indication information can include (measId#1, functionality ID#1).

[0161] For the delivery of the first indication information, there are two implementations as follows:

[0162] In a possible implementation, the first indication information can be carried in a measurement configuration. That is, the network device can send the measurement configuration to the terminal device, and the terminal device receives the measurement configuration from the network device, where the measurement configuration includes the first indication information and the first measurement object. It can be understood that the first indication information is carried in the measurement configuration, so that the terminal device can determine which measurement objects in the corresponding measurement configuration are used for prediction by the terminal device according to the first indication information, that is, the measurement configuration includes the first measurement object.

[0163] In another possible implementation, the first indication information can be carried in the first activation signaling, and the first activation signaling is used to activate the first AI function. That is, the network device can send the first activation signaling to the terminal device, and the terminal device receives the first activation signaling from the network device, where the first activation signaling includes the first indication information. That is, the network device activates the first AI function while delivering the association relationship of the measurement object associated with the first AI function.

[0164] Optionally, the first activation signaling can be an RRC message or media access control (MAC) signaling, which is not limited.

[0165] S602, the terminal device performs prediction on the first measurement object according to the correspondence between the first measurement object and the first AI function, to obtain a first prediction result.

[0166] After receiving the first indication information, the terminal device can determine the correspondence between the first measurement object and the first AI function according to the first indication information, so as to obtain the first prediction result by knowing from the correspondence that the configuration containing the first measurement object in the measurement configuration needs to perform the corresponding prediction according to the first AI function.

[0167] In the case where the correspondence between the first measurement object and the first AI function is the correspondence between the identifier of the first measurement object and the identifier of the first AI function, the terminal device can determine the first measurement object according to the identifier of the measurement object associated with the identifier of the first AI function, measure the first measurement object to obtain a measured result, and apply the first AI function to obtain a prediction result according to the measured result.

[0168] Taking the identifier of the first measurement object as measObjectId#1 and the identifier of the first AI function as functionality ID#1 as an example, for the configuration of the three measurement objects in the above example, the terminal device can determine, according to the correspondence between measObjectId#1 and functionality ID#1, that the configuration#1 and configuration#2 containing measObjectId#1 in the measurement configuration are used for making prediction according to the first AI function, and the configuration#1 of measurement object#2 is used for making measurement.

[0169] In the case where the correspondence between the first measurement object and the first AI function is the correspondence between the measurement identifier associated with the first measurement object and the identifier of the first AI function, the terminal device can determine the first measurement object according to the measurement identifier associated with the identifier of the first AI function, measure the first measurement object to obtain a measured result, and apply the first AI function to obtain a prediction result according to the measured result.

[0170] Taking the measurement identifier as measId#1 and the identifier of the first AI function as functionality ID#1 as an example, for the configuration of the three measurement objects in the above example, the terminal device can determine, according to the correspondence between measId#1 and functionality ID#1, that the configuration#1 and configuration#2 containing measId#1 in the measurement configuration are used for making prediction according to the first AI function, and the configuration#1 of measurement object#2 is used for making measurement.

[0171] For when the terminal device starts the first AI function or enables the first AI function, there can be the following design:

[0172] In a case where the measurement configuration and the first activation signaling are received, the first AI function is started, wherein the measurement configuration comprises the first measurement object. That is, the terminal device starts the first AI function upon determining that the measurement configuration comprising the first measurement object and the first activation signaling have been received; neither the first AI function is started during a period when the terminal device receives the measurement configuration but does not receive the first activation signaling, nor during a period when the terminal device receives the first activation signaling but does not receive the measurement configuration. It should be understood that the present application does not limit the order of sending the measurement configuration and the first activation signaling.

[0173] After the first AI function is started, the terminal device can perform measurement according to the configuration corresponding to the first measurement object in the measurement configuration, and take the measurement result as the input of the first AI function to obtain a prediction result.

[0174] In this way, the terminal device can determine which measurement objects need to be predicted and which measurement objects need to be actually measured according to the first indication information indicating the correspondence between the AI function and the measurement object sent by the network device, which can avoid the terminal device from predicting all the measurement objects in the received measurement configuration after receiving the AI function activation signaling. In addition, the correspondence between different measurement objects and the AI function can be flexibly configured through the first indication information, which can enable the network device to obtain the prediction result or the actually measured result of different measurement objects, and further enable the network device to perform mobility management based on the prediction result and perform cell resource management according to the actually measured result, which can be compatible with basic requirements such as cell resource management and prediction-based mobility management, and ensure the performance of the system.

[0175] Further, after the terminal device obtains the first prediction result according to the first AI function, the terminal device can report the first prediction result to the network device, so that the network device can perform corresponding decision and management according to the first prediction result. In a possible design, the communication method shown in FIG. 6 can further include the following steps:

[0176] S603. The terminal device sends the first prediction result to the network device. Correspondingly, the network device receives the first prediction result from the terminal device.

[0177] In a possible implementation, the terminal device can send the first prediction result to the network device in the form of a measurement report, which can comprise the first prediction result and a measurement identifier associated with the first prediction result, the measurement identifier can be used to inform the network device which measurement object the first prediction result is obtained from. Optionally, the measurement report can further comprise an identifier of the AI function associated with the first prediction result, which is not limited in this regard.

[0178] It should be understood that there can be multiple first prediction results, and different measurement objects can correspond to different first prediction results. By associating each first prediction result with a measurement identifier, it can be determined which measurement object is used to obtain the different first prediction results.

[0179] Optionally, the terminal device can send the first prediction result through an RRC message or MAC signaling, and there is no limitation thereon.

[0180] S604, the network device sends second indication information to the terminal device according to the first prediction result. Correspondingly, the terminal device receives the second indication information from the network device.

[0181] The second indication information is used to indicate the update of the correspondence between the first measurement object and the first AI function.

[0182] The network device can determine whether the correspondence between the currently-downloaded first measurement object and the first AI function meets the requirements according to the received first prediction result, and in the case where the requirements are not met, the network device can send the second indication information to update the correspondence.

[0183] For example, the first prediction result obtained by the network device according to the correspondence between the currently-downloaded first measurement object and the first AI function does not meet the requirements for system performance gain, so the network device can reconfigure a new correspondence between the measurement object and the AI function, and send the updated correspondence to the terminal device through the second indication information. For example, the un-updated correspondence is (measObjectId#1, functionality ID#1), and the updated correspondence is (measObjectId#1, functionality ID#2). For another example, the un-updated correspondence is (measId#1, functionality ID#1), and the updated correspondence is (measId#1, functionality ID#2).

[0184] If the network device updates the AI function in the correspondence, such as updating from the first AI function to the second AI function, the network device needs to activate the second AI function through activation signaling. Optionally, the second indication information can be sent in the activation signaling.

[0185] If the network device updates the measurement object in the correspondence, such as updating from the first measurement object to the second measurement object, the second indication information can be considered as a new first indication information at this time, so that the terminal device needs to determine which measurement objects are measured according to the first AI function according to the second indication information.

[0186] If the network device updates both the AI function and the measurement object in the correspondence, such as updating from the first AI function to the second AI function and updating from the first measurement object to the second measurement object, the network device also needs to reissue activation signaling to activate the second AI function, and correspondingly, the terminal device also needs to re-determine which measurement objects are measured according to the first AI function according to the second indication information.

[0187] In addition to performing the correspondence decision of S604 according to the prediction result, the network device can also perform a mobility management decision according to the first prediction result.

[0188] In one possible design, the network device can obtain an expected handover time according to the first prediction result, and indicate the terminal device with the expected handover time to trigger the terminal device to perform RLF prediction of a neighbor cell according to the expected handover time, so as to determine a suitable target cell for handover according to the RLF prediction result of the neighbor cell fed back by the terminal device, and further determine whether the expected handover time determined according to the first prediction result is suitable, so as to improve the success rate of cell handover of the terminal device. For example, S605a-S607a can be included as follows:

[0189] S605a, the network device sends third indication information to the terminal device according to the first prediction result. Correspondingly, the terminal device receives the third indication information from the network device.

[0190] The third indication information is used to indicate the expected handover time.

[0191] Since the first prediction result can be used for mobility management, for example, the first prediction result includes the future reference signal receiving power (RSRP) of the serving cell and the future RSRP of the neighbor cell of the terminal device, or the first prediction result includes the future moving track of the terminal device, the network device can also perform a mobility management decision such as cell handover according to the first prediction result, for example, the network device can determine an expected handover time of a terminal device performing cell handover according to the first prediction result, and inform the terminal device through the third indication information.

[0192] Optionally, the expected handover time can be a time point or a time period, which is not limited. If the expected handover time is a time period, the third indication information can include the start time and the duration of the expected handover time, or the start time and the end time of the expected handover time, which is not limited.

[0193] In a possible design, the network device can further send, to the terminal device, a candidate target cell list, which can include the identification of one or more candidate target cells. Optionally, the candidate target cell list can be indicated by the third indication information, e.g., the third indication information is used to indicate the expected handover time and the candidate target cell list.

[0194] In S606a, the terminal device performs RLF prediction on the neighbor cell according to the third indication information, to obtain a first RLF prediction result.

[0195] The RLF prediction is to predict the probability of connection failure or whether connection failure occurs between the terminal device and the neighbor cell at the expected handover time after the terminal device moves to the neighbor cell.

[0196] After receiving the third indication information, the terminal device can perform RLF prediction on at least one neighbor cell according to the predicted handover time, to obtain the probability of RLF or whether RLF occurs in each neighbor cell within the predicted handover time, i.e., the probability of RLF or whether RLF occurs in each neighbor cell within the predicted handover time. By performing RLF prediction on the neighbor cell, the neighbor cell that is not suitable to be a target cell can be filtered out.

[0197] Therefore, the terminal device can obtain the first RLF prediction result obtained by performing RLF prediction on the neighbor cell according to the predicted handover time. The first RLF prediction result can include the probability of RLF or whether RLF occurs in the neighbor cell within the expected handover time. Whether the RLF prediction result is the probability of RLF or whether RLF occurs is based on the design of the RLF prediction model / function, and is not limited herein.

[0198] It should be understood that whether the terminal device performs RLF prediction on all neighbor cells or selects part of the neighbor cells to perform RLF prediction can be based on implementation design, and is not limited herein. Accordingly, the first RLF prediction result can correspond to multiple first RLF prediction results, or the first RLF prediction result includes the RLF prediction results of multiple neighbor cells. Each prediction result can be associated with a neighbor cell ID, and is not limited herein.

[0199] Optionally, after obtaining the first RLF prediction result, the terminal device can further determine a recommended handover time and / or a recommended target cell according to the first RLF prediction result, and send the recommended handover time and / or the recommended target cell to the network device in the form of fourth indication information, and correspondingly, the network device receives the fourth indication information from the terminal device. The fourth indication information is used to indicate the recommended handover time and / or the recommended target cell, for example, the fourth indication information includes the identifier of the recommended target cell and the recommended handover time. It should be understood that the recommended handover time can also be a time point or a time period, which is not limited.

[0200] For example, the terminal device can determine a time at which the probability of RLF is small (e.g., less than a second threshold) according to the RLF prediction result, and take the time at which the probability of RLF is small as the recommended handover time, and / or the terminal device can also take one or more neighbor cells in which the probability of RLF is small as the recommended target cell.

[0201] Optionally, in the case of the RLF prediction result being the predicted probability of RLF, after obtaining the RLF prediction result of one or more neighbor cells, the terminal device can compare the probability of RLF of each neighbor cell with a RLF probability threshold (e.g., a second threshold), take the neighbor cell in which the probability of RLF is less than the second threshold as a candidate target cell, and if there are multiple candidate target cells, the terminal device can take the candidate target cell with the smallest probability of RLF as the target cell, so that the terminal device can switch to the target cell at the expected handover time. At this time, the terminal device can not send the first RLF prediction result to the network device, that is, the terminal device can not report the first RLF prediction result, but directly determine the target cell according to the comparison result of the probability of RLF, and perform handover at the expected handover time. Alternatively, the terminal device can send the first RLF prediction result to the network device, and then determine the target cell according to the comparison result of the probability of RLF, and perform handover at the expected handover time. Therefore, the S607a described below is an optional step.

[0202] In the case that the network device sends the candidate target cell list to the terminal device, if the third indication information is used to indicate the expected handover time and the candidate target cell list, the terminal device can perform RLF prediction on each candidate target cell in the candidate target cell list to obtain the RLF prediction result of each candidate target cell, which can include the probability of RLF occurrence of the candidate target cell at the predicted handover time or whether RLF prediction occurs. At this time, S606a can be replaced by: the terminal device performs RLF prediction on the candidate target cell according to the third indication information to obtain the RLF prediction result of the candidate target cell.

[0203] Optionally, in the case that the RLF prediction result is the predicted RLF occurrence probability, after obtaining the RLF prediction result of each candidate target cell, the terminal device can compare the RLF occurrence probability of each candidate target cell with the RLF probability threshold, such as the second threshold, and take the candidate target cell with the RLF occurrence probability less than the second threshold as the target cell and switch to the target cell at the expected handover time. If there are multiple candidate target cells with the RLF occurrence probability less than the second threshold, the terminal device can select the candidate target cell with the minimum RLF occurrence probability as the target cell for switching and switch to the target cell at the preset handover time. At this time, the terminal device can not send the RLF prediction result of the candidate target cell to the network device, that is, the terminal device can directly determine the target cell according to the RLF probability comparison result and perform handover at the expected handover time without reporting the RLF prediction result. Alternatively, the terminal device can also send the RLF prediction result of the candidate target cell to the network device and determine the target cell according to the RLF probability comparison result after sending to perform handover at the expected handover time.

[0204] The second threshold described above can be configured by the network device to the terminal device, can be pre-configured or pre-defined locally in the terminal device, or can be obtained by negotiation between the network device and the terminal device, and no limitation is made in this regard. In the case that the second threshold is configured by the network device to the terminal device, the second threshold can be carried in the third indication information together with the expected handover time and / or the candidate target cell list, or can be sent separately from the expected handover time and the candidate target cell list, such as being carried in different information or messages, and no limitation is made in this regard.

[0205] S607a, the terminal device sends the first RLF prediction result to the network device. Correspondingly, the network device receives the first RLF prediction result from the terminal device.

[0206] After the terminal device obtains the first RLF prediction result according to the third indication information, the terminal device can send the first RLF prediction result to the network device.

[0207] Correspondingly, the network device can learn which neighbor cell is suitable as a target cell for the terminal device to perform handover at the expected handover time according to the received first RLF prediction result, for example, a neighbor cell with a smaller RLF prediction probability (e.g., less than a second threshold) is taken as a target cell, or a neighbor cell predicted to have no RLF is taken as a target cell. Further, the network device can send a handover command according to the first RLF prediction result to instruct the terminal device to perform handover to the target cell at the expected handover time. At this time, it should be understood that the second threshold can be pre-configured or pre-defined locally in the network device, or can be determined by negotiation between the network device and the terminal device, which is not limited.

[0208] In the case that the terminal device sends the fourth indication information, the network device can further determine the expected handover time and the target cell in combination with the fourth indication information.

[0209] In another possible design, the network device can indicate the expected handover time and the target cell determined according to the first prediction result to the terminal device to trigger the terminal device to perform RLF prediction on the target cell determined according to the first prediction result, and can further judge whether the expected handover time and the target cell determined according to the first prediction result are suitable to improve the success rate of cell handover of the terminal device. For example, S605b-S607b can be included.

[0210] S605b, the network device sends fifth indication information to the terminal device according to the first prediction result. Correspondingly, the terminal device receives the fifth indication information from the network device.

[0211] The fifth indication information is used to indicate the expected handover time and the target cell. The specific description of the expected handover time can be referred to the related description in S605a above, which is not repeated here. That is, in addition to determining an expected handover time for the terminal device to perform cell handover according to the first prediction result, the network device can also determine a target cell for the terminal device to perform handover according to the first prediction result, and send the target cell to the terminal device through the fifth indication information. For example, the fifth indication information includes the identification of the target cell and the expected handover time.

[0212] S606b, the terminal device performs RLF prediction on the target cell according to the fifth indication information to obtain a second RLF prediction result.

[0213] After receiving the fifth indication information, the terminal device can make RLF prediction on the target cell according to the expected handover time and the target cell, to obtain a second RLF prediction result, which indicates the probability of RLF occurrence of the target cell at the expected handover time or whether the target cell will have RLF at the expected handover time. Thus, the accuracy of the handover information obtained according to the first prediction result can be further verified.

[0214] Optionally, after obtaining the predicted probability of RLF occurrence of the target cell, the terminal device can compare the probability of RLF occurrence of the target cell with a RLF probability threshold, such as the second threshold described above. If the probability of RLF occurrence of the target cell is less than the second threshold, the terminal device can directly switch to the target cell at the expected handover time, without reporting the second RLF prediction result, i.e., without performing S607b described below, or the terminal device can switch to the target cell at the expected handover time after performing S607b described below, or switch to the target cell at the expected handover time based on a handover command sent by the network device. It should be understood that the size of the second threshold can be different in different scenarios.

[0215] Optionally, the terminal device can also make RLF prediction on other neighboring cells, and send fourth indication information to the network device according to the RLF prediction result. Correspondingly, the network device receives the fourth indication information from the terminal device, and the fourth indication information is used to indicate the recommended handover time and / or the recommended target cell. The specific description of the fourth indication information can be referred to the related description of the fourth indication information in S605a described above, which will not be repeated here.

[0216] In a possible implementation, in the case where the target cell meets a first condition, the terminal device can send the fourth indication information to the network device. The first condition can be that the probability of RLF occurrence of the target cell at the expected handover time is greater than a first threshold, or the target cell will have RLF at the expected handover time. That is, the terminal device can determine whether the target cell currently indicated by the network is suitable according to the second RLF prediction result. If not, the terminal device can make RLF prediction on other neighboring cells to recommend the handover time and the target cell to the network.

[0217] The first threshold can be pre-configured or pre-defined, indicated by the network device to the terminal device, or negotiated between the network device and the terminal device. For example, the network device sends information used to indicate the first threshold to the terminal device, and correspondingly, the terminal device receives the information used to indicate the first threshold from the network device. In some implementations, the first threshold can be the second threshold described above, or a threshold different from the second threshold described above, which is not limited.

[0218] S607b, the terminal device sends the second RLF prediction result to the network device. Correspondingly, the network device receives the second RLF prediction result from the terminal device.

[0219] After the terminal device obtains the second RLF prediction result, the terminal device can feed back the second RLF prediction result to the network device. Correspondingly, the network device can re-decide (such as re-determine the expected handover time and the target cell) or issue a handover command according to the received second prediction result.

[0220] For example, in the case that the probability of RLF occurring in the target cell is large (such as greater than a first threshold) or the probability of RLF not occurring, the network device can not send a handover command to the terminal device or instruct the terminal device to hand over to another cell; in the case that the probability of RLF occurring in the target cell is small (such as less than a second threshold) or the probability of RLF not occurring, the network device can issue a handover command to the terminal device, so that the terminal device hands over to the target cell at the expected handover time according to the handover command.

[0221] Thus, after obtaining the first prediction result, the network device can instruct the terminal device with the handover information obtained according to the first prediction result, so that the terminal device can timely perform RLF prediction on the handover information determined according to the first prediction result, and thus can avoid the handover failure caused by RLF occurring in the target cell after the terminal device hands over to the target cell according to the decision based on the first prediction result, and ensure the performance of the system.

[0222] In addition, the embodiment of the present application also provides a communication method, which can also be compatible with basic requirements such as cell resource management and prediction-based mobility management. For example, as shown in FIG. 7, the communication method comprises:

[0223] S701, the network device sends measurement configuration and first indication information to the terminal device. Correspondingly, the terminal device receives the measurement configuration and the first indication information from the network device.

[0224] The measurement configuration comprises a first measurement object, and the first measurement object corresponds to a measurement object identifier. The specific description of the measurement configuration can be referred to the related description in S601 above, which will not be repeated here.

[0225] The first indication information is used to instruct to report a prediction result corresponding to the first measurement object. That is, the network device instructs the terminal device to make a prediction on the first measurement object and report the prediction result through the first indication information.

[0226] In a possible implementation, the first indication information can include an identifier of the first measurement object, that is, the first indication information is used to indicate the predicted result corresponding to the reported identifier of the first measurement object. Alternatively, the first indication information can include a measurement identifier associated with the first measurement object, that is, the first indication information is used to indicate the predicted result corresponding to the reported measurement identifier associated with the first measurement object.

[0227] Optionally, the first indication information and the measurement configuration can be carried in different messages or in the same message, which is not limited.

[0228] It should be understood that, in addition to the configuration of the first measurement object, the measurement configuration sent by the network device can also include the configuration of other measurement objects.

[0229] S702, the network device sends first activation signaling to the terminal device. Correspondingly, the terminal device receives the first activation signaling from the network device.

[0230] The first activation signaling is used to activate the first AI function, and the specific description of the first activation signaling can be referred to the related description in S601, which will not be described here.

[0231] S703, the terminal device determines, according to the measurement configuration, the first indication information and the first activation signaling, to use the first AI function to predict the first measurement object, to obtain the first predicted result.

[0232] The terminal device determines, according to the obtained first indication information and the first activation signaling, that the AI function used to predict the first measurement object is the first AI function, so that the terminal device can measure according to the configuration of the first measurement object in the measurement configuration, and take the measurement result as the input of the first AI function to obtain the first predicted result. It can be understood that the first indication information and the first activation signaling jointly indicate the object of the first measurement object and the first AI function, which is equivalent to an implicit indication mode.

[0233] For example, the first indication information is used to indicate the predicted result corresponding to the reported identifier of the first measurement object, so that the terminal device can determine which measurement objects in the measurement configuration are the first measurement object according to the identifier of the first measurement object, and measure the first measurement object, so as to predict according to the measurement result and the first AI function.

[0234] For another example, the first indication information is used to indicate the predicted result corresponding to the reported measurement identifier associated with the first measurement object, so that the terminal device can determine which measurement objects in the measurement configuration are associated with the measurement identifier according to the measurement identifier, determine the measurement objects associated with the measurement identifier as the first measurement object, and measure the first measurement object, so as to predict according to the measurement result and the first AI function.

[0235] At this time, the terminal device can also start the first AI function after receiving the measurement configuration and the first activation signaling, and make a prediction on the first measurement object according to the first AI function to obtain a first prediction result.

[0236] S704, the terminal device sends the first prediction result and the second indication information to the network device. Correspondingly, the network device receives the first prediction result and the second indication information from the terminal device.

[0237] The second indication information is used to indicate the correspondence between the first measurement object and the first AI function. In a possible implementation, the second indication information can include the correspondence between the identifier of the first measurement object and the identifier of the first AI function, or the second indication information can include the correspondence between the measurement identifier associated with the first measurement object and the identifier of the first AI function. For specific description of the second indication information, refer to the related description of the first indication information in S601 above, which will not be repeated here.

[0238] The first prediction result is associated with the second indication information, that is, the terminal device can feed back the correspondence between the measurement object used by the first prediction result and the AI function to the network device through the second indication information in addition to reporting the first prediction result.

[0239] Optionally, the first prediction result and the associated second indication information can also be reported together in the form of a report, or the first prediction result and the second indication information are sent separately, which is not limited.

[0240] Therefore, the network device can also indicate the correspondence between the first measurement object and the identifier of the first AI function through the first indication information and the first activation signaling, so that the terminal device can determine which measurement objects need to be predicted and which measurement objects need to be measured, and the terminal device can avoid making a prediction on all measurement objects in the received measurement configuration after receiving the activation signaling.

[0241] Further, in the scenario shown in FIG. 7, after the network device receives the first prediction result, it can also perform S604, S605a-S607a or S605b-S607b as described above, which will not be repeated here.

[0242] The embodiments of the present application also provide a communication method, in which the terminal device can make RLF prediction on a cell and feed back the RLF prediction result to the network device, which can assist the network device to optimize the handover decision, so as to avoid the handover failure caused by the RLF of the terminal device after being handed over to a target cell, and ensure the performance of the system.

[0243] Exemplarily, FIG. 8 is a flow diagram of a communication method provided by the embodiments of the present application. As shown in FIG. 8, the communication method comprises the following steps.

[0244] S801, the terminal device sends the first prediction result to the network device. Correspondingly, the network device receives the first prediction result from the terminal device.

[0245] The implementation of the terminal device obtaining the first prediction result can refer to the related description in S601-S603 or S701-S703, and details are not described herein.

[0246] S802, the network device sends the sixth indication information to the terminal device. Correspondingly, the terminal device receives the sixth indication information from the network device.

[0247] The sixth indication information is used to indicate the expected handover time, and the specific description of the expected handover time can refer to the related description in S605a, and details are not described herein.

[0248] In a possible design, the sixth indication information can be the third indication information, and the specific description of the third indication information can refer to the related description in S605a, and details are not described herein. In a possible design, the sixth indication information can be the fifth indication information, and the specific description of the fifth indication information can refer to the related description in S605b, and details are not described herein.

[0249] S803, the terminal device performs RLF prediction on the cell according to the sixth indication information, and obtains the third RLF prediction result.

[0250] In the case that the sixth indication information is the third indication information, the cell can refer to the neighboring cell of the serving cell of the terminal device, and the third RLF prediction result is the RLF prediction result of the neighboring cell, i.e., the first RLF prediction result, or the cell can refer to the candidate target cell indicated by the network device, and the third RLF prediction result is the RLF prediction result of the candidate target cell, and the specific implementation process can refer to the related description in S606a, and details are not described herein.

[0251] In the case that the sixth indication information is the fifth indication information, the cell can be the target cell indicated by the network device, and the third RLF prediction result is the RLF prediction result of the target cell, i.e., the second RLF prediction result, and the specific implementation process can refer to the related description in S606b, and details are not described herein.

[0252] S804, the terminal device sends the third RLF prediction result to the network device. Correspondingly, the network device receives the third RLF prediction result from the terminal device.

[0253] The specific implementation process of S804 can be referred to the related description in S607a or S607b described above, which will not be repeated here. As described above in S606a or S606b, S804 is an optional step.

[0254] The above describes the scheme provided by the embodiments of the application by taking the network device as an example. In the network device of the O-RAN architecture as shown in FIG. 2, the interaction between the network device and the terminal device can also be converted into the processing between the RIC, the CU / DU and the terminal device:

[0255] For example, S601 can specifically include that the RIC sends first indication information to the CU, and correspondingly, the CU receives the first indication information from the RIC. Further, the CU sends the first indication information to the DU, and correspondingly, the DU receives the first indication information from the CU, so as to send the first indication information to the terminal device by the CU again. Alternatively, the RIC directly sends the first indication information to the DU, and correspondingly, the DU receives the first indication information from the CU. S605a, S605b, S701, S702, S802 and the like also perform similar processing as S601 in the network device of the O-RAN architecture, which will not be repeated here.

[0256] For another example, S603 can specifically include that the terminal device sends the first prediction result to the DU, and correspondingly, the DU receives the first prediction result from the terminal device. Further, the DU sends the first prediction result to the CU, and correspondingly, the CU receives the first prediction result from the DU, so as to send the first prediction result to the RIC by the CU again. S607a, S607b, S704, S801, S803 and the like also perform similar processing as S603 in the network device of the O-RAN architecture, which will not be repeated here. In some embodiments, the internal processing of the network device can also be performed in the CU or the DU, for example, S604 can be performed in the RIC or the CU or the DU, which is not limited.

[0257] For example, FIG. 9 is a flow diagram of a communication method applied to the O-RAN architecture. As shown in FIG. 9, the network device includes a CU and a first node, which can be a RIC or a SU. The communication method includes:

[0258] S901, the terminal device sends capability information to the CU. Correspondingly, the CU receives the capability information from the terminal device.

[0259] The capability information is used to indicate the AI function / AI model available to the terminal device, for example, the capability information can include the identifier of the terminal device, the identifier of the AI function / AI model, the applicable scenario of the AI function / AI model, the input / output format of the AI function / AI model and the like.

[0260] S902, the CU sends capability information to the first node. Correspondingly, the first node receives the capability information from the CU.

[0261] That is, after the CU obtains the capability information, the CU sends the capability information to the first node, so that the first node performs the following steps.

[0262] S903, the CU sends the identifier of the terminal device and the measurement configuration to the first node. Correspondingly, the first node receives the identifier of the terminal device and the measurement configuration from the CU.

[0263] After the CU obtains the capability information, the CU can configure the measurement configuration for the terminal device and send the measurement configuration to the first node.

[0264] S904, the first node sends first activation signaling and first indication information to the CU. Correspondingly, the CU receives the first activation signaling and the first indication information from the first node.

[0265] The first activation signaling is used to activate the first AI function, and the first indication information is used to indicate the correspondence between the first measurement object and the first AI function or to indicate the reporting of the prediction result corresponding to the first measurement object. The specific description of the first activation signaling and the first indication information can be referred to the related description in S601 or S701 described above, and will not be repeated here.

[0266] The first node can determine the first indication information and the first activation signaling according to the capability information and the measurement configuration, and send the first indication information and the first activation signaling to the CU.

[0267] S905, the CU sends the first activation signaling and the first indication information to the terminal device. Correspondingly, the terminal device receives the first activation signaling and the first indication information from the CU.

[0268] After the CU obtains the first activation signaling and the first indication information, the CU can indicate the terminal device based on the implementation manner shown in FIG. 6 or FIG. 7, and the corresponding implementation of the terminal device can also be referred to the implementation manner shown in FIG. 6 or FIG. 7 described above, and will not be repeated here.

[0269] In the scenario shown in FIG. 9, the first node such as RIC or SU can know the AI function available for the terminal device and the measurement configuration, so as to flexibly control the correspondence between the AI function and the measurement object in the measurement configuration, and can be compatible with basic requirements such as cell resource management and prediction-based mobility management, thereby ensuring the performance of the system.

[0270] It can be understood that, in each of the above embodiments, the method and / or steps implemented by the network device can also be implemented by components (such as a processor, a chip, a chip system, a circuit, a logic module, or software) available for the network device; the method and / or steps implemented by the terminal device can also be implemented by components (such as a processor, a chip, a chip system, a circuit, a logic module, or software) available for the terminal device.

[0271] The above mainly introduces the schemes provided in the application. Accordingly, the application also provides a communication apparatus, which is used to implement various methods in the above method embodiments. The communication apparatus can be a network device in the above method embodiments, or an apparatus containing a network device, or a component available for a network device, such as a chip or a chip system. Alternatively, the communication apparatus can be a terminal device in the above method embodiments, or an apparatus containing a terminal device, or a component available for a terminal device, such as a chip or a chip system.

[0272] It can be understood that, in order to implement the above functions, the communication apparatus contains corresponding hardware structures and / or software modules for executing various functions. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of the examples described in the embodiments disclosed herein, the application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the application.

[0273] The embodiments of the application can divide the communication apparatus into functional modules according to the above method embodiments, for example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or software functional module. It should be noted that the division of modules in the embodiments of the application is illustrative, and is only a logical function division. There can be another division manner when actually implemented.

[0274] For example, the communication apparatus is the network device or the terminal device in the method embodiments, and FIG. 10 is a structural schematic diagram of the communication apparatus provided in the embodiments of the present application. As shown in FIG. 10, the communication apparatus 1000 includes a processing module 1001 and a transceiver module 1002. The processing module 1001 is configured to perform the processing functions of the network device or the terminal device in the method embodiments. The transceiver module 1002 is configured to perform the communication functions of the network device or the terminal device in the method embodiments. The related content of each step in the method embodiments can be referred to the function description of the corresponding functional module, and will not be repeated here.

[0275] In a possible design, the transceiver module 1002 can include a receiving module and a sending module (not shown in FIG. 10). The sending module and the receiving module are respectively configured to implement the sending function and the receiving function of the communication apparatus 1000.

[0276] In a possible design, the communication apparatus 1000 can further include a storage module (not shown in FIG. 10), which stores programs or instructions. When the processing module 1001 executes the programs or instructions, the communication apparatus 1000 can perform the functions of the network device or the terminal device in any of the methods shown in FIGS. 6-8.

[0277] In some embodiments, the processing module 1001 involved in the communication apparatus 1000 can be implemented by a processor or a processor-related circuit component, and can be a processor or a processing unit. The transceiver module 1002 can be implemented by a transceiver or a transceiver-related circuit component, and can be a transceiver or a transceiving unit.

[0278] For example, FIG. 11 is a structural schematic diagram of another communication apparatus provided in the embodiments of the present application. The communication apparatus can be the network device or the terminal device in the method embodiments, or can be a chip (system) or other components or assemblies that can be arranged in the network device or the terminal device. As shown in FIG. 11, the communication apparatus 1100 can include a processor 1101, a bus 1102, a communication interface 1103, and a memory 1104. The processor 1101, the memory 1104, and the communication interface 1103 communicate through the bus 1102. The communication apparatus 1100 can be the network device or the terminal device. It should be understood that the number of processors and memories in the communication apparatus 1100 is not limited in the present application.

[0279] The bus 1102 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one line is shown in FIG. 11, but it does not mean that there is only one bus or only one type of bus. The bus 1102 can include a path for transmitting information between various components (for example, the memory 1104, the processor 1101, the communication interface 1103) of the communication apparatus 1100.

[0280] The processor 1101 can include any one or more of a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP), etc.

[0281] The memory 1104 can include a volatile memory (for example, a random access memory (RAM)), and the processor 1101 can further include a non-volatile memory (for example, a read-only memory (ROM), a flash memory, a hard disk drive (HDD), or a solid state drive (SSD)).

[0282] The communication interface 1103 uses a transceiver module such as, but not limited to, a network interface card, a transceiver, etc., to implement communication between the communication apparatus 1100 and other devices or communication networks.

[0283] The memory 1104 stores executable program code, and the processor 1101 executes the executable program code to respectively implement the functions of the network device or the terminal device in the foregoing method embodiments. That is, the memory 1104 has instructions for executing the above communication method.

[0284] In yet another aspect, the embodiments of the present application also provide a computer program product containing instructions, which, when executed on a communication apparatus, enable the communication apparatus to perform the method described in any one of the above embodiments.

[0285] Furthermore, embodiments of this application also provide a computer-readable storage medium. This computer-readable storage medium stores a computer program or instructions that, when executed on a communication device, enable the communication device to perform the methods described in any of the above embodiments.

[0286] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented using software programs, implementation can be, in whole or in part, in the form of a computer program product. This computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device containing one or more servers, data centers, etc., that can be integrated with the medium. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state disks, SSDs).

[0287] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0288] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0289] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other manners. For example, the described device embodiments are merely schematic. The division of the units is merely logical function division. There can be other division manners in actual implementation. For example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between different units, can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0290] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e., can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment. In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present alone, or two or more units can be integrated in one unit.

[0291] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the parts that make contributions to the prior art, or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a ROM, a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0292] Although the present application is described herein in conjunction with various embodiments, other variations of the disclosed embodiments can be understood and implemented by those skilled in the art with reference to the attached drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "one" does not exclude a plurality. A single processor or other unit can implement several functions listed in the claims. Some measures described in mutually different dependent claims can be combined and produce good results.

[0293] Although the present application has been described in connection with certain specific features and embodiments thereof, it is to be understood that it is provided as an exemplification of the application and is not intended to limit the scope of the application, which is defined in the claims. Various modifications and changes can be made thereto without departing from the spirit and scope of the application. Accordingly, it is intended that all such modifications and changes be included within the scope of the application as claimed. Obviously, many modifications and variations of the present application are possible in light of the above teachings. It is, therefore, to be understood that within the scope of the appended claims and their equivalents, the application can be practiced otherwise than as specifically described.

Claims

1. A communication method characterized by comprising: The method comprises: receiving first indication information from a network device, the first indication information being used to indicate a correspondence relationship between a first measurement object and a first artificial intelligence (AI) function; performing prediction on the first measurement object according to the correspondence relationship between the first measurement object and the first AI function, to obtain a first prediction result.

2. The method of claim 1, wherein, The first indication information comprises a correspondence relationship between an identifier of the first measurement object and an identifier of the first AI function, or comprises a correspondence relationship between a measurement identifier associated with the first measurement object and the identifier of the first AI function.

3. The method according to claim 1 or 2, characterized in that, The receiving of the first indication information from the network device comprises: receiving a measurement configuration from the network device, the measurement configuration comprising the first indication information.

4. The method according to claim 1 or 2, characterized in that, The receiving of the first indication information from the network device comprises: receiving first activation signaling from the network device, the first activation signaling being used to activate the first AI function, and the first activation signaling comprising the first indication information.

5. The method according to any one of claims 1-4, characterized in that, The performing of the prediction on the first measurement object according to the correspondence relationship between the first measurement object and the first AI function to obtain the first prediction result comprises: starting the first AI function upon receiving a measurement configuration and first activation signaling, the measurement configuration comprising the first measurement object, and the first activation signaling being used to activate the first AI function; performing prediction on the first measurement object according to the correspondence relationship between the first measurement object and the first AI function, to obtain the first prediction result.

6. The method according to any one of claims 1-5, characterized in that, The method further comprises: sending the first prediction result to the network device.

7. The method of claim 6, wherein, The method further comprises: receiving second indication information from the network device, the second indication information being used to indicate an update of the correspondence relationship between the first measurement object and the first AI function.

8. The method according to any one of claims 1 to 7, characterized in that, The method further comprises: receiving third indication information from the network device, the third indication information being used to indicate an expected handover time; performing radio link failure (RLF) prediction on a neighbor cell according to the third indication information, to obtain a first RLF prediction result; sending the first RLF prediction result.

9. The method of claim 8, wherein, The first RLF prediction result comprises a probability of the neighbor cell experiencing RLF within the expected handover time or whether the neighbor cell will experience RLF within the expected handover time.

10. The method according to claim 8 or 9, characterized in that, The method further comprises: sending fourth indication information to the network device, the fourth indication information being used to indicate a recommended handover time and / or a recommended target cell.

11. The method according to any one of claims 1-7, characterized in that, The method further comprises: receiving fifth indication information from the network device, the fifth indication information being used to indicate an expected handover time and a target cell; performing RLF prediction on the target cell according to the fifth indication information, to obtain a second RLF prediction result; sending the second RLF prediction result.

12. The method of claim 11, wherein, The second RLF prediction result comprises a probability of the target cell experiencing RLF within the expected handover time or whether the target cell will experience RLF within the expected handover time.

13. The method according to claim 11 or 12, characterized in that, The method further comprises: sending fourth indication information to the network device, the fourth indication information being used to indicate a recommended handover time and / or a recommended target cell.

14. The method of claim 13, wherein, The fourth indication information is sent to the network device, including: In the case where the target cell meets the first condition, the fourth indication information is sent to the network device, and the first condition is that the probability of RLF of the target cell within the expected handover time is greater than a first threshold, or the target cell will have RLF within the expected handover time.

15. A method of communication, comprising: The method comprises: Generating first indication information, the first indication information being used to indicate the correspondence relationship between a first measurement object and a first artificial intelligence (AI) function; The first indication information is sent to a terminal device.

16. The method of claim 15, wherein, The first indication information comprises a correspondence relationship between an identifier of the first measurement object and an identifier of the first AI function, or comprises a correspondence relationship between a measurement identifier associated with the first measurement object and an identifier of the first AI function.

17. The method according to claim 15 or 16, characterized in that, The first indication information is sent to the terminal device, including: The measurement configuration is sent to the terminal device, and the measurement configuration comprises the first indication information.

18. The method of claim 15 or 16, wherein, The first indication information is sent to the terminal device, including: The first activation signaling is sent to the terminal device, the first activation signaling being used to activate the first AI function, and the first activation signaling comprises the first indication information.

19. The method according to any one of claims 15-18, characterized by, The method further comprises: Receiving a first prediction result from the terminal device, the first prediction result being determined according to the correspondence relationship between the first measurement object and the first AI function.

20. The method of any one of claims 15-19, wherein, The method further comprises: According to the first prediction result, second indication information is sent to the terminal device, the second indication information being used to indicate that the correspondence relationship between the first measurement object and the first AI function is updated.

21. The method of any one of claims 15-20, wherein, The method further comprises: According to the first prediction result, third indication information is sent to the terminal device, the third indication information being used to indicate an expected handover time; A first RLF prediction result is received from the terminal device.

22. The method of claim 21, wherein, The first RLF prediction result comprises the probability of RLF of a neighbor cell within the expected handover time or whether the neighbor cell will have RLF within the expected handover time.

23. The method of claim 21 or 22, wherein, The method further comprises: Fourth indication information is received from the terminal device, the fourth indication information being used to indicate a recommended handover time and / or a recommended target cell.

24. The method of any one of claims 15-20, wherein, The method further comprises: According to the first prediction result, fifth indication information is sent to the terminal device, the fifth indication information being used to indicate an expected handover time and a target cell; A second RLF prediction result is received from the terminal device.

25. The method of claim 24, wherein, The second RLF prediction result comprises the probability of RLF of the target cell within the expected handover time or whether the target cell will have RLF within the expected handover time.

26. The method of claim 24 or 25, wherein, The method further comprises: Fourth indication information is received from the terminal device, the fourth indication information being used to indicate a recommended handover time and / or a recommended target cell.

27. A communications device, characterized by The module is used to execute the method as claimed in any one of claims 1-14 or as claimed in any one of claims 15-26.

28. A communications device, characterized by The module comprises: A processor; The processor is configured to execute computer programs or instructions to cause the method of any one of claims 1-14, or any one of claims 15-26 to be implemented.

29. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer programs or instructions which, when executed by a communication device, implement the method of any one of claims 1-14, or any one of claims 15-26.

30. A computer program product, characterised in that, The computer readable storage medium stores computer programs or instructions which, when executed by a communication device, implement the method of any one of claims 1-14, or any one of claims 15-26.

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