Event-triggered measurement reporting method and apparatus, event-triggered measurement reporting configuration method and apparatus, reporting method, device, and medium

Abstract

The present application relates to the technical field of communications, and discloses an event-triggered measurement reporting method and apparatus, an event-triggered measurement reporting configuration method and apparatus, a reporting method, a device, and a medium. The event-triggered measurement reporting method in embodiments of the present application comprises: a terminal acquires first configuration information from a network side device, the first configuration information being used for configuring the terminal to perform measurement reporting when triggered by a target event; and on the basis of the first configuration information, the terminal determines whether to perform measurement reporting, wherein the target event comprises predicting, on the basis of artificial intelligence (AI), whether a radio link failure occurs.

Description

Event-triggered measurement reporting method, event-triggered measurement reporting configuration method, reporting method, device, equipment, and medium

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to Chinese Patent Application No. 202410171080.0 filed in China on February 6, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The present application belongs to the field of communication technology, and specifically relates to an event-triggered measurement reporting method, an event-triggered measurement reporting configuration method, a reporting method, an apparatus, a device, and a medium. Background Art

[0004] Currently, network-side devices can configure terminals to perform measurements and reports based on measurement configurations. After performing measurements and generating measurement results, terminals can trigger the reporting of measurement reports based on measurement events configured by the network-side devices.

[0005] In related technologies, if the measurement meets the reporting conditions, the terminal will report the corresponding measurement report to the network-side device. The network-side device can refer to the measurement report and send reconfiguration information to the terminal, including new measurement configuration or switching instructions. However, the terminal may experience radio link failure (RLF), resulting in the terminal being unable to report the measurement report to the network in a timely manner, making it impossible for the network-side device to reasonably reconfigure the terminal based on the measurement situation. In addition, radio link failure will cause a long delay in the interruption of terminal services, resulting in poor communication continuity for the terminal. Summary of the Invention

[0006] The embodiments of the present application provide an event-triggered measurement reporting method, an event-triggered measurement reporting configuration method, a reporting method, an apparatus, a device, and a medium, which can reduce the delay of cell reconfiguration of a terminal and improve the stability of terminal communication.

[0007] In a first aspect, a measurement reporting method based on event triggering is provided, which is executed by a terminal, and includes: the terminal obtaining first configuration information from a network-side device, the first configuration information being used to configure the terminal to be triggered to perform measurement reporting based on a target event; the terminal determines whether to perform measurement reporting based on the first configuration information; wherein the target event includes whether RLF occurs based on artificial intelligence AI prediction.

[0008] In the second aspect, a measurement reporting configuration method based on event triggering is provided, which is executed by a network side device. The method includes: the network side device sends first configuration information to the terminal, and the first configuration information is used to configure the terminal to be triggered to perform measurement reporting based on a target event. The target event includes whether RLF occurs based on artificial intelligence AI prediction.

[0009] According to a third aspect, a reporting method is provided, which is executed by a network-side device. The method includes: the network-side device receives a first report from a terminal, and the first report includes at least one of the following: a measurement result and a prediction result; wherein the measurement result includes at least one of the following: a measurement result of a service cell of the terminal, and a measurement result of a neighboring cell of the service cell of the terminal; the prediction result includes at least one of the following: a prediction result of whether an RLF occurs by an AI prediction of the service cell of the terminal, and a prediction result of whether an RLF occurs by an AI prediction of a neighboring cell of the service cell of the terminal.

[0010] In a fourth aspect, a measurement reporting device based on event triggering is provided, which includes: a receiving module and an execution module, wherein: the receiving module is used to obtain first configuration information from a network side device, and the first configuration information is used to configure the terminal to be triggered to perform measurement reporting based on a target event; the execution module is used to determine whether to perform measurement reporting based on the first configuration information received by the receiving module; wherein the target event includes whether a radio link failure RLF occurs based on artificial intelligence AI prediction.

[0011] In the fifth aspect, a measurement reporting configuration device based on event triggering is provided, which includes: a sending module; a sending module for sending first configuration information to the terminal, the first configuration information is used to configure the terminal to be triggered to perform measurement reporting based on a target event, and the target event includes whether a wireless link failure RLF occurs based on artificial intelligence AI prediction.

[0012] In the sixth aspect, a reporting device is provided, which includes: a receiving module; a receiving module for receiving a first report from a terminal, the first report including at least one of the following: a measurement result, a prediction result; wherein the measurement result includes at least one of the following: a measurement result of the terminal's service cell, and a measurement result of a neighboring cell of the terminal's service cell; the prediction result includes at least one of the following: a prediction result of whether RLF occurs by the AI ​​prediction of the terminal's service cell, and a prediction result of whether RLF occurs by the AI ​​prediction of the neighboring cell of the terminal's service cell.

[0013] In a seventh aspect, a terminal is provided, comprising a processor and a memory, wherein the memory stores a program or instruction that can be run on the processor, and when the program or instruction is executed by the processor, the steps of the method described in the first aspect are implemented.

[0014] In an eighth aspect, a terminal is provided, comprising a processor and a communication interface, wherein the communication interface is used to obtain first configuration information from a network side device, and the first configuration information is used to configure the terminal to be triggered to perform measurement reporting based on a target event; the processor is used to determine whether to perform measurement reporting based on the first configuration information; wherein the target event includes whether a radio link failure RLF occurs based on artificial intelligence AI prediction.

[0015] In the ninth aspect, a network side device is provided, which includes a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the program or instructions are executed by the processor, the steps of the method described in the second aspect or the third aspect are implemented.

[0016] In the tenth aspect, a network side device is provided, including a processor and a communication interface, wherein the communication interface is used to send first configuration information to the terminal, and the first configuration information is used to configure the terminal to be triggered to perform measurement reporting based on a target event, and the target event includes whether a radio link failure RLF occurs based on artificial intelligence AI; or, the communication interface is used to receive a first report from the terminal, and the first report includes at least one of the following: measurement results, prediction results; wherein the measurement results include at least one of the following: the measurement results of the terminal's service cell, and the measurement results of the neighboring cells of the terminal's service cell; the prediction results include at least one of the following: the prediction results of the terminal's service cell's AI prediction of whether RLF occurs, and the prediction results of the neighboring cells of the terminal's service cell's AI prediction of whether RLF occurs.

[0017] In the eleventh aspect, a readable storage medium is provided, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented, or the steps of the method described in the second aspect are implemented, or the steps of the method described in the third aspect are implemented.

[0018] In the twelfth aspect, a wireless communication system is provided, including: a terminal and a network side device, wherein the terminal can be used to execute the steps of the method described in the first aspect, and the network side device can be used to execute the steps of the method described in the second aspect or the third aspect.

[0019] In the thirteenth aspect, a chip is provided, which includes a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the method as described in the first aspect, or the method as described in the second aspect, or the method as described in the third aspect.

[0020] In the fourteenth aspect, a computer program / program product is provided, which is stored in a storage medium and is executed by at least one processor to implement the steps of the method described in the first aspect, or the steps of the method described in the second aspect, or the steps of the method described in the third aspect.

[0021] In an embodiment of the present application, a terminal receives first configuration information from a network-side device, where the first configuration information is used to configure the terminal to be triggered to perform measurement reporting based on a target event. The terminal determines whether to perform measurement reporting based on the first configuration information, where the target event includes whether an RLF occurs based on AI prediction. Through this method, the terminal can determine whether to perform measurement reporting based on the AI ​​prediction of the likelihood of RLF occurring, thereby being able to promptly report a measurement report to the network-side device based on the AI ​​prediction of whether an RLF occurs before the RLF actually occurs, allowing the network-side device to reasonably reconfigure the terminal based on the measurement report, thereby reducing the delay in the terminal's cell reconfiguration, improving the terminal's communication quality, and ensuring communication continuity. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] FIG1 is a block diagram of a wireless communication system provided in an embodiment of the present application;

[0023] FIG2 is a flow chart of a method for reporting measurement data based on event triggering according to an embodiment of the present application;

[0024] FIG3 is a flow chart of a reporting method according to an embodiment of the present application;

[0025] FIG4 is a second flow chart of the event-triggered measurement reporting method according to an embodiment of the present application;

[0026] FIG5 is a schematic structural diagram of an event-triggered measurement reporting device according to an embodiment of the present application;

[0027] FIG6 is a schematic structural diagram of an event-triggered measurement reporting configuration apparatus according to an embodiment of the present application;

[0028] FIG7 is a schematic diagram of the structure of a reporting device provided in an embodiment of the present application;

[0029] FIG8 is a schematic diagram of the structure of a communication device provided in an embodiment of the present application;

[0030] FIG9 is a schematic diagram of the hardware structure of a terminal provided in an embodiment of the present application;

[0031] FIG10 is a schematic diagram of the hardware structure of the network side device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] The following will be combined with the accompanying drawings in the embodiments of this application to clearly describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0033] The terms "first", "second", etc. in this application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms used in this way are interchangeable where appropriate, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of the same type, and do not limit the number of objects, for example, the first object can be one or more. In addition, "or" in this application represents at least one of the connected objects. For example, "A or B" covers three options, namely, Option 1: including A but not including B; Option 2: including B but not including A; Option 3: including both A and B. The character " / " generally indicates that the objects associated before and after are in an "or" relationship.

[0034] The term "indication" in this application can be either a direct indication (or explicit indication) or an indirect indication (or implicit indication). A direct indication can be understood as the sender explicitly informing the receiver of specific information, the operation to be performed, or the requested result, etc. in the instruction sent; an indirect indication can be understood as the receiver determining the corresponding information based on the instruction sent by the sender, or making a judgment and determining the operation to be performed or the requested result, etc. based on the judgment result.

[0035] It is worth noting that the technology described in the embodiments of the present application is not limited to the Long Term Evolution (LTE) / LTE-Advanced (LTE-A) system, but can also be used in other wireless communication systems, such as Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Frequency Division Multiple Access (FDMA), Orthogonal Frequency Division Multiple Access (OFDMA), Single-carrier Frequency-Division Multiple Access (SC-FDMA) or other systems. The terms "system" and "network" in the embodiments of the present application are often used interchangeably, and the technology described can be used for the systems and radio technologies mentioned above, as well as for other systems and radio technologies. The following description describes a New Radio (NR) system for illustrative purposes, and NR terminology is used in most of the following description, but these technologies can also be applied to systems other than NR systems, such as 6th generation (6G) systems. th Generation, 6G) communication system.

[0036] FIG1 is a block diagram of a wireless communication system applicable to an embodiment of the present application. The wireless communication system includes a terminal 11 and a network-side device 12. The terminal 11 may be a mobile phone, a tablet computer (Tablet Personal Computer), a laptop computer (Laptop Computer), a notebook computer, a personal digital assistant (PDA), a handheld computer, a netbook, an ultra-mobile personal computer (UMPC), a mobile internet device (MID), an augmented reality (AR), a virtual reality (VR) device, a robot, a wearable device (Wearable Device), an aircraft (Flight Vehicle), a vehicle-mounted device (VUE), a ship-mounted device, a pedestrian user equipment (PUE), a smart home (home appliances with wireless communication capabilities, such as refrigerators, televisions, washing machines, or furniture), a game console, a personal computer (PC), an ATM, or a self-service machine, or other terminal-side devices. Wearable devices include: smart watches, smart bracelets, smart headphones, smart glasses, smart jewelry (smart bracelets, smart bracelets, smart rings, smart necklaces, smart anklets, smart anklets, etc.), smart wristbands, smart clothing, etc. Among them, the vehicle-mounted device can also be called a vehicle-mounted terminal, a vehicle-mounted controller, a vehicle-mounted module, a vehicle-mounted component, a vehicle-mounted chip or a vehicle-mounted unit, etc. It should be noted that the specific type of the terminal 11 is not limited in the embodiment of the present application. The network side device 12 may include an access network device or a core network device, wherein the access network device may also be called a radio access network (Radio Access Network, RAN) device, a radio access network function or a radio access network unit. The access network device may include a base station, a wireless local area network (WLAN) access point (AP) or a wireless fidelity (WiFi) node, etc.Among them, the base station can be referred to as Node B (NB), Evolved Node B (eNB), the next generation Node B (gNB), New Radio Node B (NR Node B), access point, Relay Base Station (RBS), Serving Base Station (SBS), Base Transceiver Station (BTS), radio base station, radio transceiver, Basic Service Set (BSS), Extended Service Set (ESS), Home Node B (HNB), Home Evolved Node B (home evolved Node B), Transmission Reception Point (TRP) or other appropriate terms in the field. As long as the same technical effect is achieved, the base station is not limited to specific technical vocabulary. It should be noted that in the embodiment of the present application, only the base station in the NR system is used as an example for introduction, and the specific type of the base station is not limited.

[0037] The core network equipment may include but is not limited to at least one of the following: core network node, core network function, mobility management entity (MME), access mobility management function (AMF), session management function (SMF), user plane function (UPF), policy control function (PCF), policy and charging rules function unit (PCRF), edge application service discovery function (EASDF), unified data management (UDM), unified data repository (UDR), home user server (HSS), centralized network configuration (CNC), network storage function (NRF), network exposure function (NEF), local NEF (L-NEF), binding support function (BSF), application function ( It should be noted that in the embodiments of the present application, only the core network device in the NR system is introduced as an example, and the specific type of the core network device is not limited.But not limited to at least one of the following: core network node, core network function, Mobility Management Entity (MME), Access and Mobility Management Function (AMF), Session Management Function (SMF), User Plane Function (UPF), Policy Control Function (PCF), Policy and Charging Rules Function (PCRF), Edge Application Server Discovery Function (EASDF), Unified Data Management (UDM), Unified Data Repository (UDR), Home Subscriber Server (HSS), Centralized Network Configuration (CNC), Network Repository Function (NRF), Network Exposure Function (NEF), Local NEF (L-NEF), Binding Support Function (BSF), Application Function (AF), etc. It should be noted that in the embodiments of this application, only the core network equipment in the NR system is introduced as an example, and the specific type of the core network equipment is not limited.

[0038] The following explains the nouns, terms and concepts involved in the embodiments of this application.

[0039] 1. Artificial Intelligence (AI)

[0040] AI is currently widely used in various fields. Integrating artificial intelligence into wireless communication networks to significantly improve technical indicators such as throughput, latency, and user capacity is a key task for future wireless communication networks. AI modules can be implemented in a variety of ways, such as neural networks, decision trees, support vector machines, and Bayesian classifiers. This application uses neural networks as an example, but does not limit the specific type of AI module.

[0041] A neural network consists of neurons, with a1, a2, …aK as inputs, w as weights (multiplicative coefficients), b as biases (additive coefficients), and σ(.) as activation functions. Common activation functions include sigmoid, tanh, and ReLU (Rectified Linear Unit).

[0042] Neural network parameters are optimized using a gradient optimization algorithm. Gradient optimization algorithms are a class of algorithms that minimize or maximize an objective function (sometimes called a loss function), which is often a mathematical combination of model parameters and data. For example, given data X and its corresponding label Y, we construct a neural network model f(.). With this model, we can obtain the predicted output f(x) based on the input x, and calculate the difference between the predicted value and the true value (f(x) - Y). This is the loss function. Our goal is to find the appropriate W and b to minimize the value of this loss function. The smaller the loss value, the closer our model is to the true value.

[0043] 2. AI Unit

[0044] An AI unit may also be referred to as an AI model, an ML (machine learning) model, an ML unit, an AI structure, an AI function, an AI feature, a machine learning model, a neural network, a neural network function, a neural network function, etc., or an AI unit may refer to a processing unit capable of implementing specific AI-related algorithms, formulas, processing flows, capabilities, etc., or an AI unit may be a processing method, algorithm, function, module, or unit for a specific data set, or an AI unit may be a processing method, algorithm, function, module, or unit running on AI / ML-related hardware such as a GPU, NPU, TPU, or ASIC, etc. Optionally, the specific data set includes the input and / or output of the AI ​​unit / AI model.

[0045] Optionally, the identifier of the AI ​​unit / AI model may be an AI model identifier, an AI structure identifier, an AI algorithm identifier, or an identifier of a specific data set associated with the AI ​​unit / AI model, or an identifier of a specific scenario, environment, channel feature, or device related to AI / ML, or an identifier of an AI / ML-related function, feature, capability, or module, etc.

[0046] 3. Radio Link Failure (RLF)

[0047] Based on the measurement of the reference signal and the reference signal quality threshold configured by the network, the RRC_CONNECTED UE performs radio link monitoring (RLM). When the UE meets the following conditions, it can declare that RLF has occurred:

[0048] The T310 timer started after the physical layer indicates that the radio link is out of synchronization (indicates N310 times "out-of-sync") times out;

[0049] When T310 is running, a measurement report is triggered, and the timer T312 configured with the measurement identifier corresponding to the measurement report times out;

[0050] The Media Access Control (MAC) layer random access procedure fails;

[0051] The maximum number of retransmissions at the Radio Link Control (RLC) layer has reached the upper limit, causing RLC failure.

[0052] When RLF occurs, the UE maintains the Radio Resource Control (RRC) connected (RRC_CONNECTED) state and selects a suitable cell to trigger the RRC re-establishment procedure; if the UE does not find a suitable cell before T311 times out, the UE enters the RRC idle state (RRC_IDLE).

[0053] In related technologies, the wireless link environment is relatively complex. When a terminal experiences RLF in the serving cell, it is easy for the terminal to not receive network control instructions for a period of time or fail to successfully execute processes such as RRC connection re-establishment, resulting in service interruption, increased transmission delay, and wasted power consumption of the terminal. Existing networks configure counters and timers for terminals based on statistics to perform terminal mobility management and RRC connection re-establishment processes. However, since statistical configuration cannot directly refer to the individual differences in the terminal's environment, from the terminal's perspective, the process of waiting for the timer to time out or the counter to reach the threshold will also somewhat prolong the time to execute the next action.

[0054] The event-triggered measurement reporting method provided in the embodiment of the present application mainly focuses on the AI ​​prediction of wireless link failure by the terminal. By defining the measurement event corresponding to the AI ​​prediction of wireless link failure, the relevant measurement report is reported together with the prediction result for reference by the network side device, thereby reducing redundant interaction processes and enabling the network side device to quickly make reasonable decisions based on the content of the measurement report.

[0055] The event-triggered measurement reporting method provided by the embodiment of the present application is described in detail below with reference to the accompanying drawings through some embodiments and their application scenarios.

[0056] FIG2 is a flow chart of a measurement reporting method based on event triggering according to an embodiment of the present application. As shown in FIG2 , the measurement reporting method based on event triggering may include the following steps S201 to S203:

[0057] Step S201: The network-side device sends first configuration information to the terminal.

[0058] The first configuration information is used to configure the terminal to be triggered to perform measurement reporting based on a target event.

[0059] In some embodiments of the present application, the above-mentioned network side device may include at least one of an access network device and a core network device, and the access network device may include a base station, a transmission and receiving point (TRP), etc.

[0060] In some embodiments of the present application, the above-mentioned target event may include whether a radio link failure (EventRLFPrediction) occurs based on AI prediction.

[0061] It should be noted that in some embodiments of the present application, whether a wireless link failure occurs based on AI prediction can be understood as whether a wireless link failure occurs based on AI prediction, whether a wireless link failure will not occur based on AI prediction, or whether a wireless link failure occurs based on AI prediction.

[0062] In some embodiments of the present application, predicting whether RLF occurs based on AI may include: predicting whether RLF occurs in the serving cell of the terminal based on AI. Exemplarily, the target event may include predicting whether radio link failure occurs in the serving cell of the terminal based on AI.

[0063] In some embodiments of the present application, an AI model is deployed in the terminal, and the AI ​​model can predict whether the terminal has an RLF in the cell, or whether the probability of the terminal having an RLF in the cell is greater than or equal to a threshold.

[0064] In some embodiments of the present application, the first configuration information may be used to configure the terminal to be triggered to perform conditional switching based on a target event.

[0065] In some embodiments of the present application, the target event may serve as a conditional measurement event, and become a target execution condition (CondEventRLFPrediction) triggered by a measurement report in a conditional handover.

[0066] In some embodiments of the present application, the first configuration information includes configuration information related to RLF prediction by the terminal through AI, and the first configuration information includes at least one of the following:

[0067] A first measurement object (MeaObject), where the first measurement object includes a serving cell of the terminal, or the first measurement object includes a serving cell of the terminal and a neighboring cell of the serving cell;

[0068] A first reporting configuration (ReportConfig), the first reporting configuration including an event-triggered reporting type and an identifier of a target event, and the first reporting configuration is used by the terminal to perform event-triggered measurement reporting according to the target event;

[0069] A measurement identifier (measID), where the measurement identifier is used to associate the first measurement object with the first reporting configuration.

[0070] Exemplarily, the first measurement object may include the frequency of the terminal's serving cell, or the first measurement object may include the frequency of the neighboring cell of the terminal's serving cell. In other words, the terminal may perform at least one of RLF prediction and radio resource management (RRM) measurement on the serving cell, or the terminal may perform at least one of RLF prediction and RRM measurement on the serving cell and the neighboring cell.

[0071] It can be understood that the neighboring cell may also be referred to as an adjacent cell.

[0072] Exemplarily, when the first configuration information includes a first reporting configuration, and the first reporting configuration includes a reporting type based on event triggering, the manner in which the terminal reports the measurement report or prediction result to the network side device may be event-triggered reporting.

[0073] In an embodiment of the present application, the measurement objects for which the terminal is configured to perform measurement reporting include at least the serving cell of the terminal, so that the terminal can predict whether RLF occurs in the serving cell through AI, thereby being able to know in advance whether there is a possibility that the terminal will experience RLF in the serving cell; by configuring the terminal to perform measurement reporting based on event triggering, the terminal can perform or not perform measurement reporting according to the prediction result of the AI ​​prediction of RLF, thereby being able to obtain measurement reports in a timely manner.

[0074] In some embodiments of the present application, the above-mentioned first configuration information also includes first indication information, and the above-mentioned first indication information is used to instruct the terminal to report second information in the measurement report, where the second information includes at least one of the measurement results of the neighboring cells of the terminal's serving cell and the AI ​​prediction result of whether RLF occurs.

[0075] Exemplarily, the network side device carries first indication information in the first configuration information, which is used to indicate that the terminal needs to report at least one of the measurement results of the neighboring cells of the terminal's service cell and the prediction results of the RLF prediction in the measurement report, indicating that the network side device hopes to obtain the measurement of the neighboring cells through the measurement report triggered by the target event, thereby further providing subsequent switching configuration for the UE.

[0076] It should be noted that in the case where a measurement identifier is associated with only one measurement object, the measurement object is the frequency of the terminal's service cell. If the terminal needs to report the measurement of the neighboring cells of the terminal's service cell in the measurement report, it can be carried out according to the protocol provisions or in the report configuration. An indication information is used to indicate whether to report the measurement results or prediction results of the neighboring cells.

[0077] In some embodiments of the present application, the first configuration information further includes at least one of the following:

[0078] The first time includes at least one of the following: the time point when the terminal starts to perform the model reasoning of the AI ​​prediction of whether RLF occurs, the time period during which the terminal continues to perform the model reasoning of the AI ​​prediction of whether RLF occurs, the time point when the terminal outputs the model reasoning result of the AI ​​prediction of whether RLF occurs, and the time period during which the terminal outputs the model reasoning result of the AI ​​prediction of whether RLF occurs;

[0079] A second time, where the second time is a time point or time period at which AI predicts whether RLF will occur;

[0080] The first threshold is used to determine whether the model reasoning result of the AI ​​prediction of whether RLF occurs meets the entry conditions of the target event;

[0081] The second threshold is used to determine whether the model reasoning result of the AI ​​prediction of whether RLF occurs meets the exit condition of the target event;

[0082] a third time, where the third time is a duration (timetoTrigger) during which the terminal meets the entry condition of the target event;

[0083] Second indication information (reportOnLeave), the second indication information is used to indicate whether measurement reporting is supported when a leaving condition of a target event is met;

[0084] In some embodiments of the present application, when the first configuration information includes a first time, the terminal can perform model inference within the time according to the configured first time, or the result of data model inference within the time, so as to predict whether the terminal will experience RLF at a certain time point or time period later than the first time.

[0085] Exemplarily, the above-mentioned model inference result may be that the terminal will experience RLF or that the terminal will not experience RLF, or the above-mentioned model inference result may be the probability of the terminal experiencing RLF.

[0086] In some embodiments of the present application, when the first configuration information includes a second time, the terminal can output the model inference result of AI predicting RLF at any time earlier than the second time according to the configured second time, thereby being able to predict whether the terminal will experience RLF at the second time.

[0087] Exemplarily, the above-mentioned model reasoning result may be whether the terminal will experience RLF or not, or the above-mentioned model reasoning result may be the probability of the terminal experiencing RLF. In some embodiments of the present application, when the first configuration information includes a first threshold, the terminal may determine whether the model reasoning result of the AI-predicted RLF meets the entry conditions of the target event based on the configured first threshold, thereby performing measurement result reporting when the entry conditions of the target event are met.

[0088] Exemplarily, if the probability of the AI ​​prediction outputting whether an RLF has occurred is greater than or equal to a first threshold, the terminal is considered to have experienced an RLF. Exemplarily, the first threshold is 85%, 90%, or 95%, etc. The first threshold can be determined based on actual needs and is not limited in this embodiment of the present application.

[0089] Exemplarily, satisfying the entry condition of the target event includes: a model inference result of the AI-predicted RLF of the serving cell of the terminal satisfies at least one of the following:

[0090] The model reasoning results include that the terminal will experience RLF;

[0091] The model reasoning results include that the terminal will experience RLF at the first time point;

[0092] The model reasoning result includes that the probability of the terminal experiencing RLF at the second time point is greater than or equal to the first threshold.

[0093] Exemplarily, the above-mentioned first time point is determined based on the above-mentioned second time. When the second time is a time point, the first time point is the second time; or, when the second time is a time period, the first time point is any time point within the second time.

[0094] It can be understood that when the entry condition of the target event is met, the terminal is triggered to perform measurement reporting based on the target event.

[0095] In some embodiments of the present application, when the first configuration information includes a second threshold, the terminal can determine whether the model inference result of the AI ​​prediction of whether RLF occurs meets the exit condition of the target event based on the configured second threshold, thereby not performing the reporting of the measurement result when the exit condition of the target event is met, or performing the reporting of the measurement result according to the second indication information of the network side device.

[0096] Exemplarily, if the probability of the AI ​​predicting whether an RLF will occur is less than or equal to a second threshold, the terminal is deemed to be unlikely to experience an RLF. Exemplarily, the second threshold is 40%, 45%, or 50%, etc. The second threshold can be determined based on actual needs and is not limited in this embodiment of the present application. Exemplarily, the first threshold and the second threshold can be the same or different.

[0097] Exemplarily, satisfying the exit condition of the target event includes: a model inference result of the AI ​​prediction RLF of the serving cell of the terminal satisfies at least one of the following:

[0098] The model reasoning results include that RLF will not occur in the terminal;

[0099] The model reasoning results include that the terminal will not experience RLF at the third time point;

[0100] The model reasoning result includes that the probability of the terminal experiencing RLF at the fourth time point is less than or equal to the second threshold.

[0101] Exemplarily, the third time point is determined based on the second time. When the second time is a time point, the third time point is the second time; or, when the second time is a time period, the third time point is any time point within the second time.

[0102] In some embodiments of the present application, when the first configuration information includes a third time, the terminal can determine whether the duration of the entry condition of the target event is met based on the configured third time (i.e., duration), and thereby perform measurement reporting when the duration of the entry condition of the target event is met.

[0103] In some embodiments of the present application, when the first configuration information includes the second indication information, the terminal can determine whether to perform measurement reporting when the departure condition of the target event is met based on the second indication information carried in the first configuration information, thereby being able to flexibly perform measurement reporting based on the target event.

[0104] Step S202: The terminal obtains first configuration information from the network-side device.

[0105] In some embodiments of the present application, the terminal may receive first configuration information from a network-side device.

[0106] Step S203: The terminal determines whether to perform measurement reporting according to the first configuration information.

[0107] In some embodiments of the present application, the terminal may perform at least one of AI prediction of whether RLF occurs and cell measurement based on the first configuration information, and report at least one of the measurement report and the prediction result of the AI ​​predicted RLF to the network side device when the entry condition of the target event is met, or, when the exit condition of the target event is met, not perform measurement reporting or perform measurement reporting according to the second indication information of the network side device.

[0108] In some embodiments of the present application, when the prediction of wireless link failure can be used as a target execution condition triggered by a measurement report in conditional switching, the network side device pre-configures multiple candidate cells for the terminal, and the terminal evaluates the target execution conditions of the candidate cells. That is, if the candidate cell meets the entry conditions of the target event within timeToTrigger, the terminal will use the candidate cell that meets the conditions as the target cell and perform conditional reconfiguration. If there are multiple candidate cells that meet the target execution conditions, the terminal selects one of them to perform conditional reconfiguration based on the implementation.

[0109] In the event-triggered measurement reporting method provided in an embodiment of the present application, a terminal receives first configuration information from a network-side device, where the first configuration information is used to configure the terminal to be triggered to perform measurement reporting based on a target event. The terminal determines whether to perform measurement reporting based on the first configuration information, where the target event includes whether RLF occurs based on AI prediction. Through this method, the terminal can determine whether to perform measurement reporting based on the probability of RLF occurrence predicted by AI, thereby being able to report the measurement report to the network-side device in a timely manner based on the AI ​​prediction of whether RLF occurs before the RLF actually occurs, so that the network-side device can reasonably reconfigure the terminal based on the measurement report, thereby reducing the delay of the terminal's cell reconfiguration, improving the communication quality of the terminal, and ensuring communication continuity.

[0110] In some embodiments of the present application, the above step S202 may be implemented by the following step S202a:

[0111] Step S202a: When the entry conditions of the target event are met, the terminal performs measurement reporting.

[0112] In some embodiments of the present application, the terminal may determine whether the entry conditions of the target event are met based on the model inference result of AI predicting whether RLF occurs, and perform measurement reporting if the entry conditions of the target event are met.

[0113] Exemplarily, when the model inference result of the AI ​​prediction RLF of the terminal's serving cell includes that the terminal will experience RLF, the terminal will experience RLF at a first time point, or the probability of the terminal experiencing RLF at a second time point is greater than or equal to a first threshold, it is considered that the entry conditions of the target event are met, and the terminal is triggered to perform measurement reporting based on the target event.

[0114] In an embodiment of the present application, the terminal uses AI to predict the model inference result of whether RLF occurs, and when the model inference result indicates that the terminal will experience RLF in the serving cell, the terminal reports at least one of the measurement report and the prediction result to the network side device, so that the terminal reports the measurement report to the network side device in a timely manner before the RLF occurs, so that the network side device can reasonably reconfigure the terminal according to the measurement report, such as sending a switching command to the terminal to ensure that the terminal switches to a cell with good service quality before the RLF occurs, thereby avoiding the terminal of the service.

[0115] In some embodiments of the present application, the above step S202a may include the following steps S202a1:

[0116] Step S202a1: When the entry conditions of the target event are always met within the third time period, the terminal performs measurement reporting.

[0117] The third time mentioned above is the duration for the terminal to meet the entry conditions of the target event.

[0118] In some embodiments of the present application, the above duration may be the timing time for timeToTrigger to trigger reporting.

[0119] It should be noted that the above duration can also be a newly defined timing time, which is not limited in the embodiment of the present application.

[0120] Exemplarily, when the entry conditions applicable to the target event are always met during timeToTrigger, the terminal performs measurement reporting. For example, timeToTrigger = 10s, and the entry conditions of the target event are met at 00:00, that is, at 00:00, the terminal predicts whether RLF will occur through AI and the output result is that RLF will occur in the serving cell at 00:40. During 00:00-00:10, the terminal predicts whether RLF will occur through AI and the output result is that RLF will occur in the serving cell at 00:40. Then, the terminal performs measurement reporting at 00:10 after timeToTrigger expires.

[0121] It can be understood that the model inference results output during timeToTrigger are all that RLF will occur or the probability of RLF occurring is greater than or equal to the first threshold, indicating that the terminal is very likely to experience RLF.

[0122] In an embodiment of the present application, the terminal may perform measurement reporting when the entry condition of the target event is continuously satisfied for a period of time, thereby being able to perform measurement reporting when the terminal is highly likely to experience RLF.

[0123] In some embodiments of the present application, the above step S202 can be implemented by the following step S202b. For example, after the above step S202, the event-triggered measurement reporting method provided in the embodiment of the present application may include the following steps S204 and S205:

[0124] Step S202b: When the terminal determines, based on the first configuration information, that the AI ​​predicts the occurrence of RLF or the probability of the occurrence of RLF is greater than or equal to the third threshold, the terminal submits a first report to the network side device.

[0125] Step S204: The network-side device receives the first report from the terminal.

[0126] The first report includes at least one of the following: measurement results and prediction results.

[0127] Step S205: The network-side device sends a reconfiguration message to the terminal according to the first report.

[0128] The above reconfiguration message includes the configuration related to the terminal performing cell switching.

[0129] In some embodiments of the present application, the above-mentioned reconfiguration message may be an RRC reconfiguration message.

[0130] In some embodiments of the present application, the above-mentioned measurement results include at least one of the following: the measurement result of the terminal's serving cell, and the measurement result of the neighboring cell of the terminal's serving cell; the prediction result includes at least one of the following: the prediction result of whether RLF occurs by the AI ​​prediction of the terminal's serving cell, and the prediction result of whether RLF occurs by the AI ​​prediction of the neighboring cell of the serving cell.

[0131] In some embodiments of the present application, the above prediction result is obtained by the terminal based on the model inference result of AI prediction of whether RLF occurs.

[0132] Exemplarily, the terminal may process the model inference result of the AI ​​prediction of whether RLF occurs in combination with the first configuration information to obtain a prediction result. For example, if the model inference result indicates that the probability of RLF occurring in the serving cell at 00:00 is 88%, and the first threshold in the first configuration information is equal to 75%, the terminal determines that the prediction result indicates that RLF will occur in the serving cell at 00:00.

[0133] In some embodiments of the present application, the first report may be a measurement report. Exemplarily, according to the definition of EventRLFPrediction, the terminal adds a measurement report corresponding to the configured measurement identifier to the measurement report list variable, and based on the measurement object identifier and reporting configuration identifier corresponding to the measurement identifier, the terminal sends a measurement report (MeasurementReport) to the base station.

[0134] In some embodiments of the present application, the terminal may perform RRM measurement according to the configured measurement object to obtain a measurement result, and predict whether RLF occurs through AI to obtain a prediction result, wherein the cell in which the terminal measures or predicts whether RLF occurs may include at least one of the terminal's service cell and neighboring cell.

[0135] Exemplarily, when AI predicts that RLF occurs or the probability of RLF occurs is greater than or equal to a third threshold, the terminal generates a first report based on the measurement results of the cell and reports the first report to the network side device, where the first report includes the measurement results of the cell.

[0136] Exemplarily, when the AI ​​predicts that RLF will occur or the probability of RLF occurring is greater than or equal to a third threshold, a first report is generated based on the measurement results of the cell and the prediction results of the AI ​​prediction of the occurrence of RLF, and the first report is reported to the network side device. The first report includes the measurement results of the cell and the prediction results of the AI ​​prediction of the occurrence of RLF. By reporting the prediction results of the wireless link failure and the measurement results together, redundant signaling interactions are reduced, so that the network side device can make optimized switching decisions in advance based on the measurement and prediction.

[0137] Exemplarily, when the AI ​​predicts that RLF will occur or the probability of RLF occurring is greater than or equal to a third threshold, the terminal generates a first report based on the prediction result of the AI ​​predicting the occurrence of RLF, and reports the first report to the network side device, where the first report includes the prediction result of the AI ​​predicting the occurrence of RLF.

[0138] In some embodiments of the present application, the relevant configurations for the terminal to perform cell switching may include measurement configuration information, mobility control information, wireless resource dedicated configuration information, security configuration, etc.

[0139] In an embodiment of the present application, when the AI ​​predicts that RLF occurs or the probability of RLF occurs is greater than or equal to a third threshold, the terminal reports a first report to the network side device. The first report may include at least one of the measurement results and the prediction results. After receiving the first report, the network side device can send a reconfiguration message to the terminal based on the first report. In this way, by using the prediction of wireless link failure as a measurement event to trigger the reporting of the measurement report, the terminal can report at least one of the measurement results and prediction results of itself or the neighboring cell in a timely manner, so that the network side device can make reasonable decisions based on the measurement results.

[0140] In some embodiments of the present application, the above step S202 can be implemented by the following step S202c.

[0141] Step S202c: If the exit condition of the target event is met, the terminal does not perform measurement reporting; or, if the exit condition of the target event is met and the configuration information related to the target event includes the second indication information, the terminal performs measurement reporting;

[0142] The second indication information is used to indicate whether measurement reporting is supported when an exit condition of a target event is met.

[0143] In some embodiments of the present application, the terminal can determine whether the departure condition of the target event is met based on the model inference result of AI predicting whether RLF occurs, and if the departure condition of the target event is met, not perform measurement reporting, or perform measurement reporting if the departure condition of the target event is met and the second indication information is obtained.

[0144] In some examples, when the model inference result of the AI ​​predicted RLF of the terminal's service cell includes that the terminal will not experience RLF, the terminal will not experience RLF at a third time point, or the probability of the terminal experiencing RLF at a fourth time point is less than or equal to a second threshold, it is considered that the departure condition of the target event is met, and the terminal does not perform measurement reporting.

[0145] In other examples, when the model inference result of the AI ​​prediction of RLF of the terminal's service cell includes that the terminal will not experience RLF, the terminal will not experience RLF at a third time point, or the probability of the terminal experiencing RLF at a fourth time point is less than or equal to a second threshold, it is considered that the exit condition of the target event is met. If the terminal obtains the second indication information, the terminal performs measurement reporting.

[0146] In an embodiment of the present application, the terminal uses AI to predict the model reasoning result of whether RLF occurs, and when the model reasoning result indicates that the terminal will not occur RLF in the service cell, the terminal does not perform measurement reporting, or performs measurement reporting when the second indication information of the network side device is obtained, so that the terminal can flexibly perform measurement reporting according to the model reasoning result or the indication of the network side device, so that the network side device can reasonably reconfigure the terminal according to the measurement report, such as sending a switching command to the terminal to ensure that the terminal switches to a cell with good service quality before RLF occurs, avoiding the terminal of the service.

[0147] FIG3 is a flow chart of a reporting method based on event triggering according to an embodiment of the present application. As shown in FIG3 , the reporting method may include the following steps S301 and S302:

[0148] Step S301: The terminal reports a first report to a network-side device. The first report includes at least one of the following: a measurement result and a prediction result.

[0149] Step S302: The network-side device receives a first report from the terminal.

[0150] The measurement result includes at least one of the following: a measurement result of the serving cell of the terminal, and a measurement result of a neighboring cell of the serving cell of the terminal; the prediction result includes at least one of the following: a prediction result of whether RLF occurs by the AI ​​prediction of the serving cell of the terminal, and a prediction result of whether RLF occurs by the AI ​​prediction of the neighboring cell of the serving cell of the terminal.

[0151] In some embodiments of the present application, after the above step S302, the reporting method provided in the embodiment of the present application may include the following step S303:

[0152] Step S303: The network-side device sends a reconfiguration message to the terminal according to the first report.

[0153] The above reconfiguration message includes relevant configurations for the terminal to perform cell switching.

[0154] It should be noted that the explanation of this embodiment can refer to the relevant explanation of the above embodiment, which will not be repeated here.

[0155] The following uses the network side device as a base station (gNB) and the terminal as a UE as an example to illustrate the event-triggered measurement reporting provided by the embodiment of the present application. As shown in Figure 4, the method may include the following steps S31 to S35:

[0156] Step S31: The gNB sends first configuration information to the UE.

[0157] Step S32: The AI ​​model deployed on the UE side outputs the model inference result regarding RLF prediction.

[0158] Step S33: The UE determines whether the entry condition of the target event is met.

[0159] The above entry condition is used to determine whether the UE can trigger measurement reporting based on the target event.

[0160] Step S34: The UE sends a first report to the base station.

[0161] Exemplarily, the first report is a measurement report. Exemplarily, the UE adds a measurement report corresponding to the configured measurement identifier to the measurement report list variable according to the definition of EventRLFPrediction, and based on the measurement object identifier and the reporting configuration identifier corresponding to the measurement identifier, the UE sends the measurement report to the gNB.

[0162] Step S35: The gNB sends a reconfiguration message to the UE.

[0163] For example, the gNB sends an RRC reconfiguration message to the UE based on the measurement report to provide the UE with a handover configuration through the RRC reconfiguration message.

[0164] It should be noted that the explanation of this embodiment can refer to the relevant explanation of the above embodiment, which will not be repeated here.

[0165] The event-triggered measurement reporting method provided in the embodiments of the present application uses radio link failure prediction as a measurement event to trigger the reporting of measurement reports. This enables the terminal to timely report the measurement report based on the RLF prediction result, avoiding lengthy re-establishment processes and service interruptions caused by radio link failure. Furthermore, the terminal can report the radio link failure prediction result along with the measurement result, reducing redundant signaling interactions and enabling the network to make optimized handover decisions in advance based on the measurement and prediction.

[0166] In some embodiments of the present application, the event-triggered measurement reporting method provided in the embodiments of the present application may be performed by an event-triggered measurement reporting apparatus. In the embodiments of the present application, an event-triggered measurement reporting apparatus performing the event-triggered measurement reporting method is used as an example to illustrate that the embodiment of the present application provides an event-triggered measurement reporting apparatus.

[0167] Figure 5 is a structural diagram of an event-triggered measurement reporting device provided in an embodiment of the present application. As shown in Figure 5, the event-triggered measurement reporting device 500 includes: a receiving module 501 and an execution module 502, wherein: the receiving module 501 is used to obtain first configuration information from a network-side device, and the first configuration information is used to configure the terminal to be triggered to perform measurement reporting based on a target event; the execution module 502 is used to determine whether to perform measurement reporting based on the first configuration information received by the receiving module 501; wherein the target event includes whether a radio link failure RLF occurs based on artificial intelligence AI prediction.

[0168] In some embodiments of the present application, the first configuration information includes at least one of the following: a first measurement object, the first measurement object includes the service cell of the terminal, or the first measurement object includes the service cell of the terminal and the neighboring cell of the service cell; a first reporting configuration, the first reporting configuration includes an event-triggered reporting type and an identifier of the target event, and the first reporting configuration is used for the terminal to perform event-triggered measurement reporting according to the target event; a measurement identifier, the measurement identifier is used to associate the first measurement object and the first reporting configuration.

[0169] In some embodiments of the present application, the first configuration information also includes first indication information, and the first indication information is used to instruct the terminal to report second information in the measurement report, where the second information includes at least one of the measurement results of the neighboring cells of the terminal's serving cell and the AI ​​prediction result of whether RLF occurs.

[0170] In some embodiments of the present application, the first configuration information further includes at least one of the following:

[0171] The first time includes at least one of the following: the time point when the terminal starts to perform the model reasoning of the AI ​​prediction whether RLF occurs, the time period during which the terminal continues to perform the model reasoning of the AI ​​prediction whether RLF occurs, the time point when the terminal outputs the model reasoning result of the AI ​​prediction whether RLF occurs, and the time period during which the terminal outputs the model reasoning result of the AI ​​prediction whether RLF occurs;

[0172] The second time is the time point or time period when AI predicts whether RLF will occur;

[0173] The first threshold is used to determine whether the model reasoning result of the AI ​​prediction of whether RLF occurs meets the entry conditions of the target event;

[0174] The second threshold is used to determine whether the model reasoning result of the AI ​​prediction of whether RLF occurs meets the exit condition of the target event;

[0175] A third time, the third time is the duration during which the terminal meets the entry condition of the target event;

[0176] The second indication information is used to indicate whether to support measurement reporting when the exit condition of the target event is met.

[0177] In some embodiments of the present application, the execution module is specifically configured to execute measurement reporting when an entry condition of a target event is met.

[0178] In some embodiments of the present application, the execution module is specifically configured to execute measurement reporting if the entry condition of the target event is always satisfied within the third time period;

[0179] The third time is the duration for the terminal to meet the entry condition of the target event.

[0180] In some embodiments of the present application, satisfying the entry condition of the target event includes: the model inference result of the AI ​​prediction RLF of the serving cell of the terminal satisfies at least one of the following:

[0181] The model reasoning results include that the terminal will experience RLF;

[0182] The model reasoning results include that the terminal will experience RLF at the first time point;

[0183] The model reasoning result includes that the probability of the terminal experiencing RLF at the second time point is greater than or equal to the first threshold.

[0184] In some embodiments of the present application, the execution module is specifically configured to report a first report to a network-side device when, based on the first configuration information, it is determined that the AI ​​predicts the occurrence of RLF or the probability of the occurrence of RLF is greater than or equal to a third threshold, the first report including at least one of the following: a measurement result and a prediction result; wherein the measurement result includes at least one of the following: a measurement result of the service cell of the terminal and a measurement result of a neighboring cell of the service cell of the terminal; the prediction result includes at least one of the following: a prediction result of whether the AI ​​predicts the occurrence of RLF of the service cell of the terminal and a prediction result of whether the AI ​​predicts the occurrence of RLF of the neighboring cell of the service cell.

[0185] In some embodiments of the present application, the prediction result is obtained by the terminal based on the model reasoning result of AI prediction of whether RLF occurs.

[0186] In some embodiments of the present application, the execution module is specifically used to not perform measurement reporting when the departure condition of the target event is met; or to perform measurement reporting when the departure condition of the target event is met and the configuration information related to the target event includes second indication information; wherein the second indication information is used to indicate whether measurement reporting is supported when the departure condition of the target event is met.

[0187] In some embodiments of the present application, satisfying the exit condition of the target event includes: the model inference result of the AI ​​prediction RLF of the serving cell of the terminal satisfies at least one of the following:

[0188] The model reasoning results include that RLF will not occur in the terminal;

[0189] The model reasoning results include that the terminal will not experience RLF at the third time point;

[0190] The model reasoning result includes that the probability of the terminal experiencing RLF at the fourth time point is less than or equal to the second threshold.

[0191] An event-triggered measurement reporting device provided in an embodiment of the present application receives first configuration information from a network-side device, and the first configuration information is used to configure the terminal to be triggered to perform measurement reporting based on a target event. The terminal determines whether to perform measurement reporting based on the first configuration information, wherein the target event includes whether RLF occurs based on AI prediction. Through this device, the event-triggered measurement reporting device can determine whether to perform measurement reporting based on the possibility of RLF occurrence predicted by AI, thereby being able to report the measurement report to the network-side device in a timely manner based on the AI ​​prediction of whether RLF occurs before the RLF actually occurs, so that the network-side device can reasonably reconfigure the terminal based on the measurement report, thereby reducing the delay of the terminal's cell reconfiguration, improving the communication quality of the terminal and ensuring the continuity of communication.

[0192] The event-triggered measurement reporting configuration method provided in the embodiment of the present application can be executed by an event-triggered measurement reporting configuration device. In the embodiment of the present application, the event-triggered measurement reporting configuration method is executed by an event-triggered measurement reporting configuration device as an example to illustrate that the embodiment of the present application provides an event-triggered measurement reporting configuration device.

[0193] Figure 6 is a structural diagram of an event-triggered measurement reporting configuration device provided in an embodiment of the present application. As shown in Figure 6, the event-triggered measurement reporting configuration device 600 includes: a sending module 601; the sending module 601 is used to send first configuration information to the terminal, and the first configuration information is used to configure the terminal to be triggered to perform measurement reporting based on a target event, and the target event includes whether a radio link failure RLF occurs based on artificial intelligence AI.

[0194] In some embodiments of the present application, the first configuration information includes at least one of the following:

[0195] A first measurement object, where the first measurement object includes a serving cell of the terminal, or the first measurement object includes a serving cell of the terminal and a neighboring cell of the serving cell;

[0196] A first reporting configuration, the first reporting configuration including an event-triggered reporting type and an identifier of a target event, and the first reporting configuration is used by the terminal to perform event-triggered measurement reporting according to the target event;

[0197] A measurement identifier is used to associate the first measurement object with the first reporting configuration.

[0198] In some embodiments of the present application, the first configuration information also includes first indication information, and the first indication information is used to instruct the terminal to report second information in the measurement report, where the second information includes at least one of the measurement results of the neighboring cells of the terminal's serving cell and the AI ​​prediction result of whether RLF occurs.

[0199] In some embodiments of the present application, the first configuration information further includes at least one of the following:

[0200] The first time includes at least one of the following: the time point when the terminal starts to perform AI model reasoning for AI prediction or the time period during which the AI ​​model reasoning for predicting whether RLF occurs is continuously performed, and the time point or time period during which the terminal outputs the model reasoning result of AI prediction for predicting whether RLF occurs;

[0201] The second time is the time point or time period of RLF occurrence obtained by AI prediction of whether RLF occurs;

[0202] The first threshold is used to determine whether the model reasoning result of the AI ​​prediction of whether RLF occurs meets the entry conditions of the target event;

[0203] The second threshold is used to determine whether the model reasoning result of the AI ​​prediction of whether RLF occurs meets the exit condition of the target event;

[0204] A third time, the third time is the duration during which the terminal meets the entry condition of the target event;

[0205] The second indication information is used to indicate whether to support measurement reporting when the exit condition of the target event is met.

[0206] In some embodiments of the present application, the apparatus further includes: a receiving module;

[0207] A receiving module is configured to receive a first report from a terminal, where the first report includes at least one of the following: a measurement result and a prediction result; wherein the measurement result includes at least one of the following: a measurement result of a serving cell of the terminal, and a measurement result of a neighboring cell of the serving cell of the terminal; and the prediction result includes at least one of the following: a prediction result of whether an RLF occurs by an AI prediction of the serving cell of the terminal, and a prediction result of whether an RLF occurs by an AI prediction of a neighboring cell of the serving cell of the terminal.

[0208] In some embodiments of the present application, the sending module is further configured to, after receiving the first report from the terminal, send a reconfiguration message to the terminal according to the first report, where the reconfiguration message includes relevant configurations for the terminal to perform cell switching.

[0209] Figure 7 is a structural diagram of a reporting device provided in an embodiment of the present application. As shown in Figure 7, the reporting device 700 includes: a receiving module 701; the receiving module 701 is used to receive a first report from the terminal, and the first report includes at least one of the following: a measurement result and a prediction result; wherein the measurement result includes at least one of the following: a measurement result of the terminal's serving cell, and a measurement result of a neighboring cell of the terminal's serving cell; the prediction result includes at least one of the following: a prediction result of whether RLF occurs in the terminal's serving cell by AI prediction, and a prediction result of whether RLF occurs in the neighboring cell of the terminal's serving cell by AI prediction.

[0210] In some embodiments of the present application, the device further includes: a sending module; a sending module configured to send a reconfiguration message to the terminal according to the first report after receiving the first report from the terminal, wherein the reconfiguration message includes relevant configurations for the terminal to perform cell switching.

[0211] The apparatus in the embodiments of the present application may be an electronic device, such as an electronic device with an operating system, or a component in an electronic device, such as an integrated circuit or chip. The electronic device may be a terminal, or may be another device other than a terminal. For example, the terminal may include but is not limited to the types of terminal 11 listed above, and the other device may be a server, a network attached storage (NAS), etc., which is not specifically limited in the embodiments of the present application.

[0212] The device provided in the embodiment of the present application can implement each process implemented in the method embodiments of Figures 1 to 4 and achieve the same technical effect. To avoid repetition, it will not be described here.

[0213] As shown in Figure 8, an embodiment of the present application further provides a communication device 800, including a processor 801 and a memory 802, wherein the memory 802 stores a program or instruction that can be run on the processor 801. For example, when the communication device 800 is a terminal, the program or instruction is executed by the processor 801 to implement the above-mentioned event-triggered measurement reporting method or the above-mentioned event-triggered measurement reporting configuration method or the various steps of the above-mentioned reporting method embodiment, and can achieve the same technical effect. When the communication device 800 is a network-side device, the program or instruction is executed by the processor 801 to implement the above-mentioned event-triggered measurement reporting method or the above-mentioned event-triggered measurement reporting configuration method or the various steps of the above-mentioned reporting method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0214] The present application also provides a terminal including a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is configured to execute a program or instruction to implement the steps of the method embodiments shown in Figures 1 to 4. This terminal embodiment corresponds to the aforementioned terminal-side method embodiment, and each implementation process and implementation method of the aforementioned method embodiment is applicable to this terminal embodiment and can achieve the same technical effects. Specifically, Figure 9 is a schematic diagram of the hardware structure of a terminal implementing an embodiment of the present application.

[0215] The terminal 100 includes but is not limited to: a radio frequency unit 101, a network module 102, an audio output unit 103, an input unit 104, a sensor 105, a display unit 106, a user input unit 107, an interface unit 108, a memory 109 and at least some of the components of the processor 110.

[0216] Those skilled in the art will appreciate that the terminal 100 may further include a power source (such as a battery) for powering various components. The power source may be logically connected to the processor 110 via a power management system, thereby enabling the power management system to manage charging, discharging, and power consumption. The terminal structure shown in FIG9 does not limit the terminal. The terminal may include more or fewer components than shown, or may combine certain components, or have different component arrangements, which will not be described in detail here.

[0217] It should be understood that in an embodiment of the present application, the input unit 104 may include a graphics processing unit (GPU) 1041 and a microphone 1042, and the graphics processor 1041 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 106 may include a display panel 1061, and the display panel 1061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 107 includes a touch panel 1071 and at least one of other input devices 1072. The touch panel 1071 is also called a touch screen. The touch panel 1071 may include two parts: a touch detection device and a touch controller. Other input devices 1072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which will not be repeated here.

[0218] In the embodiment of the present application, after receiving downlink data from a network-side device, the RF unit 101 may transmit the data to the processor 110 for processing. Furthermore, the RF unit 101 may send uplink data to the network-side device. Typically, the RF unit 101 includes, but is not limited to, an antenna, an amplifier, a transceiver, a coupler, a low-noise amplifier, a duplexer, and the like.

[0219] The memory 109 can be used to store software programs or instructions and various data. The memory 109 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, applications or instructions required for at least one function (such as a sound playback function, an image playback function, etc.). In addition, the memory 109 may include a volatile memory or a non-volatile memory. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDRSDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM), and a direct memory bus random access memory (DRRAM). The memory 109 in the embodiment of the present application includes but is not limited to these and any other suitable types of memory.

[0220] Processor 110 may include one or more processing units. Optionally, processor 110 integrates an application processor and a modem processor. The application processor primarily handles operations related to the operating system, user interface, and application programs, while the modem processor primarily processes wireless communication signals, such as a baseband processor. It is understood that the modem processor may not be integrated into processor 110.

[0221] Among them, the radio frequency unit 101 is used to obtain first configuration information from the network side device, and the first configuration information is used to configure the terminal to be triggered to perform measurement reporting based on a target event; the processor 110 is used to determine whether to perform measurement reporting according to the first configuration information received by the radio frequency unit 101; wherein the target event includes whether a radio link failure RLF occurs based on artificial intelligence AI prediction.

[0222] In some embodiments of the present application, the first configuration information includes at least one of the following: a first measurement object, the first measurement object includes the service cell of the terminal, or the first measurement object includes the service cell of the terminal and the neighboring cell of the service cell; a first reporting configuration, the first reporting configuration includes an event-triggered reporting type and an identifier of the target event, and the first reporting configuration is used for the terminal to perform event-triggered measurement reporting according to the target event; a measurement identifier, the measurement identifier is used to associate the first measurement object and the first reporting configuration.

[0223] In some embodiments of the present application, the first configuration information also includes first indication information, and the first indication information is used to instruct the terminal to report second information in the measurement report, where the second information includes at least one of the measurement results of the neighboring cells of the terminal's serving cell and the AI ​​prediction result of whether RLF occurs.

[0224] In some embodiments of the present application, the first configuration information further includes at least one of the following:

[0225] The first time includes at least one of the following: the time point when the terminal starts to perform the model reasoning of the AI ​​prediction whether RLF occurs, the time period during which the terminal continues to perform the model reasoning of the AI ​​prediction whether RLF occurs, the time point when the terminal outputs the model reasoning result of the AI ​​prediction whether RLF occurs, and the time period during which the terminal outputs the model reasoning result of the AI ​​prediction whether RLF occurs;

[0226] The second time is the time point or time period when AI predicts whether RLF will occur;

[0227] The first threshold is used to determine whether the model reasoning result of the AI ​​prediction of whether RLF occurs meets the entry conditions of the target event;

[0228] The second threshold is used to determine whether the model reasoning result of the AI ​​prediction of whether RLF occurs meets the exit condition of the target event;

[0229] A third time, the third time is the duration during which the terminal meets the entry condition of the target event;

[0230] The second indication information is used to indicate whether to support measurement reporting when the exit condition of the target event is met.

[0231] In some embodiments of the present application, the processor 110 is specifically configured to perform measurement reporting when an entry condition of a target event is met.

[0232] In some embodiments of the present application, the processor 110 is specifically configured to perform measurement reporting if the entry condition of the target event is always met within the third time;

[0233] The third time is the duration for the terminal to meet the entry condition of the target event.

[0234] In some embodiments of the present application, satisfying the entry condition of the target event includes: the model inference result of the AI ​​prediction RLF of the serving cell of the terminal satisfies at least one of the following:

[0235] The model reasoning results include that the terminal will experience RLF;

[0236] The model reasoning results include that the terminal will experience RLF at the first time point;

[0237] The model reasoning result includes that the probability of the terminal experiencing RLF at the second time point is greater than or equal to the first threshold.

[0238] In some embodiments of the present application, the processor 110 is specifically configured to report a first report to a network-side device when, based on the first configuration information, it is determined that the AI ​​predicts the occurrence of RLF or the probability of the occurrence of RLF is greater than or equal to a third threshold, where the first report includes at least one of the following: a measurement result and a prediction result; wherein the measurement result includes at least one of the following: a measurement result of the service cell of the terminal and a measurement result of a neighboring cell of the service cell of the terminal; the prediction result includes at least one of the following: a prediction result of whether the AI ​​predicts the occurrence of RLF of the service cell of the terminal and a prediction result of whether the AI ​​predicts the occurrence of RLF of the neighboring cell of the service cell.

[0239] In some embodiments of the present application, the prediction result is obtained by the terminal based on the model reasoning result of AI prediction of whether RLF occurs.

[0240] In some embodiments of the present application, the processor 110 is specifically used to not perform measurement reporting when the departure condition of the target event is met; or to perform measurement reporting when the departure condition of the target event is met and the configuration information related to the target event includes second indication information; wherein the second indication information is used to indicate whether measurement reporting is supported when the departure condition of the target event is met.

[0241] In some embodiments of the present application, satisfying the exit condition of the target event includes: the model inference result of the AI ​​prediction RLF of the serving cell of the terminal satisfies at least one of the following:

[0242] The model reasoning results include that RLF will not occur in the terminal;

[0243] The model reasoning results include that the terminal will not experience RLF at the third time point;

[0244] The model reasoning result includes that the probability of the terminal experiencing RLF at the fourth time point is less than or equal to the second threshold.

[0245] In an embodiment of the present application, a terminal is provided, wherein the terminal receives first configuration information from a network-side device, the first configuration information being used to configure the terminal to be triggered to perform measurement reporting based on a target event. The terminal determines whether to perform measurement reporting based on the first configuration information, wherein the target event includes whether an RLF occurs based on AI prediction. In this way, the terminal can determine whether to perform measurement reporting based on the probability of RLF occurrence predicted by the AI, thereby being able to timely report a measurement report to the network-side device based on the AI ​​prediction of whether an RLF occurs before the RLF actually occurs, so that the network-side device can reasonably reconfigure the terminal based on the measurement report, thereby reducing the delay of the terminal's cell reconfiguration, improving the communication quality of the terminal, and ensuring communication continuity.

[0246] It can be understood that the implementation process of each implementation method mentioned in this embodiment can refer to the relevant description of the method embodiment and achieve the same or corresponding technical effects. To avoid repetition, it will not be described here.

[0247] The present application also provides a network-side device, including a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is configured to execute a program or instruction to implement the steps of the method embodiments shown in Figures 1 to 4. This network-side device embodiment corresponds to the aforementioned network-side device method embodiment, and each implementation process and implementation method of the aforementioned method embodiment are applicable to this network-side device embodiment and can achieve the same technical effects.

[0248] Specifically, an embodiment of the present application also provides a network-side device. As shown in Figure 10, the network-side device 1000 includes: an antenna 1001, a radio frequency device 1002, a baseband device 1003, a processor 1004, and a memory 1005. Antenna 1001 is connected to radio frequency device 1002. In the uplink direction, radio frequency device 1002 receives information via antenna 1001 and sends the received information to baseband device 1003 for processing. In the downlink direction, baseband device 1003 processes the information to be transmitted and sends it to radio frequency device 1002. Radio frequency device 1002 processes the received information and sends it through antenna 1001.

[0249] The method executed by the network-side device in the above embodiment may be implemented in the baseband device 1003 , which includes a baseband processor.

[0250] The baseband device 1003 may, for example, include at least one baseband board, on which multiple chips are arranged, as shown in Figure 10, one of which is, for example, a baseband processor, which is connected to the memory 1005 through a bus interface to call the program in the memory 1005 and execute the network device operations shown in the above method embodiment.

[0251] The network side device may further include a network interface 1006, which is, for example, a Common Public Radio Interface (CPRI).

[0252] Specifically, the network side device 1000 of the embodiment of the present application also includes: instructions or programs stored in the memory 1005 and can be run on the processor 1004. The processor 1004 calls the instructions or programs in the memory 1005 to execute the method of execution of each module shown in Figure 6 or Figure 7, and achieves the same technical effect. To avoid repetition, it will not be repeated here.

[0253] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the above-mentioned method embodiment are implemented and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0254] The processor is the processor in the terminal described in the above embodiment. The readable storage medium includes a computer-readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk. In some examples, the readable storage medium may be a non-transitory readable storage medium.

[0255] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned method embodiment and achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0256] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0257] An embodiment of the present application further provides a computer program / program product, which is stored in a storage medium. The computer program / program product is executed by at least one processor to implement the various processes of the above-mentioned method embodiment and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0258] An embodiment of the present application also provides a communication system, including: a terminal and a network-side device, wherein the terminal can be used to execute the steps of the event-triggered measurement reporting method as described above, and the network-side device can be used to execute the event-triggered measurement reporting configuration method as described above or execute the steps of the reporting method as described above.

[0259] It should be noted that, in this article, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may also be added, omitted or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0260] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of a computer software product plus a necessary general-purpose hardware platform, or of course, by hardware. The computer software product is stored in a storage medium (such as ROM, RAM, magnetic disk, optical disk, etc.) and includes a number of instructions for enabling a terminal or network-side device to execute the methods described in each embodiment of the present application.

[0261] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms of implementation methods without departing from the purpose of this application and the scope of protection of the claims. These implementation methods are all within the protection of this application.

Claims

1. A measurement reporting method based on event triggering, the method comprising: The terminal obtains first configuration information from a network-side device, where the first configuration information is used to configure the terminal to be triggered to perform measurement reporting based on a target event; Determining, by the terminal, whether to perform measurement reporting according to the first configuration information; The target event includes predicting whether a radio link failure (RLF) occurs based on artificial intelligence (AI).

2. The method according to claim 1, wherein The predicting whether RLF occurs based on AI includes: predicting whether RLF occurs in the serving cell of the terminal based on AI.

3. The method according to claim 1, wherein The first configuration information includes at least one of the following: a first measurement object, where the first measurement object includes a serving cell of the terminal, or the first measurement object includes a serving cell of the terminal and a neighboring cell of the serving cell; a first reporting configuration, the first reporting configuration including an event-triggered reporting type and an identifier of the target event, the first reporting configuration being configured for the terminal to perform event-triggered measurement reporting according to the target event; A measurement identifier, where the measurement identifier is used to associate the first measurement object with the first reporting configuration.

4. The method according to claims 1 to 3, wherein: The first configuration information also includes first indication information, where the first indication information is used to instruct the terminal to report second information in a measurement report, where the second information includes at least one of a measurement result of a neighboring cell of the serving cell of the terminal and an AI prediction result of whether RLF occurs.

5. The method according to any one of claims 1 to 4, wherein The first configuration information further includes at least one of the following: a first time, the first time including at least one of the following: a time point when the terminal starts to perform model reasoning for AI prediction of whether RLF occurs, a time period during which the terminal continues to perform model reasoning for AI prediction of whether RLF occurs, a time point when the terminal outputs a result of model reasoning for AI prediction of whether RLF occurs, and a time period during which the terminal outputs a result of model reasoning for AI prediction of whether RLF occurs; A second time, where the second time is a time point or time period at which AI predicts whether RLF will occur; A first threshold value is used to determine whether the model reasoning result of the AI prediction of whether RLF occurs meets the entry conditions of the target event; A second threshold value is used to determine whether the model reasoning result of the AI prediction of whether RLF occurs meets the exit condition of the target event; a third time, the third time being a duration for the terminal to meet the entry condition of the target event; Second indication information, where the second indication information is used to indicate whether measurement reporting is supported when an exit condition of the target event is met.

6. The method according to any one of claims 1 to 5, wherein The terminal determining, according to the first configuration information, whether to perform measurement reporting, includes: When an entry condition of the target event is met, the terminal performs measurement reporting.

7. The method according to claim 6, wherein: When the entry condition of the target event is met, the terminal performing measurement reporting includes: If the entry condition of the target event is always met within the third time, the terminal performs measurement reporting; The third time is the duration for the terminal to meet the entry condition of the target event.

8. The method according to claim 6 or 7, wherein: The entry condition of the target event is satisfied, including: the model inference result of the AI prediction RLF of the serving cell of the terminal satisfies at least one of the following: The model reasoning result includes that the terminal will have RLF; The model inference result includes that the terminal will experience RLF at a first time point; The model inference result includes that a probability of the terminal experiencing RLF at the second time point is greater than or equal to a first threshold.

9. The method according to any one of claims 1 to 8, wherein The terminal determining, according to the first configuration information, whether to perform measurement reporting, includes: When the terminal determines, based on the first configuration information, that the AI predicts that an RLF occurs or that the probability of an RLF occurs is greater than or equal to a third threshold, reporting a first report to the network side device, where the first report includes at least one of the following: a measurement result and a prediction result; The measurement result includes at least one of the following: a measurement result of the serving cell of the terminal, and a measurement result of a neighboring cell of the serving cell of the terminal; the prediction result includes at least one of the following: a prediction result of whether RLF occurs by the AI prediction of the serving cell of the terminal, and a prediction result of whether RLF occurs by the AI prediction of the neighboring cell of the serving cell.

10. The method according to claim 9, wherein: The prediction result is obtained by the terminal based on the model inference result of AI prediction of whether RLF occurs.

11. The method according to any one of claims 1 to 5, wherein The terminal determining, according to the first configuration information, whether to perform measurement reporting, includes: When the exit condition of the target event is met, the terminal does not perform measurement reporting; or, when the exit condition of the target event is met and the configuration information related to the target event includes second indication information, the terminal performs measurement reporting; The second indication information is used to indicate whether measurement reporting is supported when an exit condition of the target event is met.

12. The method according to claim 11, wherein The leaving condition of the target event is satisfied, wherein the model inference result of the AI prediction RLF of the serving cell of the terminal satisfies at least one of the following: The model reasoning result includes that the terminal will not have RLF; The model reasoning result includes that the terminal will not have RLF at a third time point; The model inference result includes that the probability of the terminal experiencing RLF at the fourth time point is less than or equal to the second threshold.

13. A method for configuring measurement reporting based on event triggering, the method comprising: The network side device sends first configuration information to the terminal, where the first configuration information is used to configure the terminal to be triggered to perform measurement reporting based on a target event, where the target event includes whether a radio link failure RLF occurs based on artificial intelligence AI.

14. The method according to claim 13, wherein The predicting whether RLF occurs based on AI includes: predicting whether RLF occurs in the serving cell of the terminal based on AI.

15. The method according to claim 13 or 14, wherein: The first configuration information includes at least one of the following: a first measurement object, where the first measurement object includes a serving cell of the terminal, or the first measurement object includes a serving cell of the terminal and a neighboring cell of the serving cell; a first reporting configuration, the first reporting configuration including an event-triggered reporting type and an identifier of a target event, the first reporting configuration being configured for the terminal to perform event-triggered measurement reporting according to the target event; A measurement identifier, where the measurement identifier is used to associate the first measurement object with the first reporting configuration.

16. The method according to any one of claims 13 to 15, wherein The first configuration information also includes first indication information, where the first indication information is used to instruct the terminal to report second information in a measurement report, where the second information includes at least one of a measurement result of a neighboring cell of the serving cell of the terminal and an AI prediction result of whether RLF occurs.

17. The method according to any one of claims 13 to 16, wherein The first configuration information further includes at least one of the following: A first time, the first time including at least one of the following: a time point when the terminal starts to perform AI model reasoning for AI prediction or a time period during which the AI model reasoning for predicting whether RLF occurs is continuously performed, and a time point or time period during which the terminal outputs a result of the model reasoning for predicting whether RLF occurs; A second time, where the second time is a time point or time period at which RLF occurs, obtained by predicting whether RLF occurs through AI; A first threshold value is used to determine whether the model reasoning result of the AI prediction of whether RLF occurs meets the entry conditions of the target event; A second threshold value is used to determine whether the model reasoning result of the AI prediction of whether RLF occurs meets the exit condition of the target event; a third time, the third time being a duration for the terminal to meet the entry condition of the target event; Second indication information, where the second indication information is used to indicate whether measurement reporting is supported when an exit condition of the target event is met.

18. The method according to any one of claims 13 to 17, wherein The method further comprises: The network side device receives a first report from the terminal, where the first report includes at least one of the following: a measurement result and a prediction result; The measurement result includes at least one of the following: a measurement result of the serving cell of the terminal, and a measurement result of a neighboring cell of the serving cell of the terminal; the prediction result includes at least one of the following: a prediction result of whether RLF occurs by the AI prediction of the serving cell of the terminal, and a prediction result of whether RLF occurs by the AI prediction of the neighboring cell of the serving cell of the terminal.

19. The method according to claim 18, wherein After the network-side device receives the first report from the terminal, the method further includes: The network-side device sends a reconfiguration message to the terminal according to the first report, where the reconfiguration message includes relevant configurations for the terminal to perform cell switching.

20. A reporting method, comprising: The network-side device receives a first report from the terminal, where the first report includes at least one of the following: a measurement result and a prediction result; The measurement result includes at least one of the following: a measurement result of the serving cell of the terminal, and a measurement result of a neighboring cell of the serving cell of the terminal; the prediction result includes at least one of the following: a prediction result of whether RLF occurs by the AI prediction of the serving cell of the terminal, and a prediction result of whether RLF occurs by the AI prediction of the neighboring cell of the serving cell of the terminal.

21. The method according to claim 20, wherein After the network-side device receives the first report from the terminal, the method further includes: The network-side device sends a reconfiguration message to the terminal according to the first report, where the reconfiguration message includes relevant configurations for the terminal to perform cell switching.

22. A measurement reporting device based on event triggering, the device comprising: A receiving module and an execution module, wherein: The receiving module is configured to obtain first configuration information from a network-side device, where the first configuration information is used to configure the terminal to be triggered to perform measurement reporting based on a target event; The execution module is configured to determine whether to perform measurement reporting according to the first configuration information received by the receiving module; The target event includes predicting whether a radio link failure (RLF) occurs based on artificial intelligence (AI).

23. The device according to claim 22, wherein The first configuration information includes at least one of the following: a first measurement object, where the first measurement object includes a serving cell of the terminal, or the first measurement object includes a serving cell of the terminal and a neighboring cell of the serving cell; a first reporting configuration, the first reporting configuration including an event-triggered reporting type and an identifier of the target event, the first reporting configuration being configured for the terminal to perform event-triggered measurement reporting according to the target event; A measurement identifier, where the measurement identifier is used to associate the first measurement object with the first reporting configuration.

24. The device according to claim 22 or 23, wherein The first configuration information also includes first indication information, where the first indication information is used to instruct the terminal to report second information in a measurement report, where the second information includes at least one of a measurement result of a neighboring cell of the serving cell of the terminal and an AI prediction result of whether RLF occurs.

25. The device according to any one of claims 22 to 24, wherein The first configuration information further includes at least one of the following: a first time, the first time including at least one of the following: a time point when the terminal starts to perform model reasoning for AI prediction of whether RLF occurs, a time period during which the terminal continues to perform model reasoning for AI prediction of whether RLF occurs, a time point when the terminal outputs a result of model reasoning for AI prediction of whether RLF occurs, and a time period during which the terminal outputs a result of model reasoning for AI prediction of whether RLF occurs; A second time, where the second time is a time point or time period at which AI predicts whether RLF will occur; A first threshold value is used to determine whether the model reasoning result of the AI prediction of whether RLF occurs meets the entry conditions of the target event; A second threshold value is used to determine whether the model reasoning result of the AI prediction of whether RLF occurs meets the exit condition of the target event; a third time, the third time being a duration for the terminal to meet the entry condition of the target event; Second indication information, where the second indication information is used to indicate whether measurement reporting is supported when an exit condition of the target event is met.

26. The device according to any one of claims 22 to 25, wherein The execution module is specifically configured to execute measurement reporting when the entry condition of the target event is met.

27. The device according to claim 26, wherein The execution module is specifically configured to execute measurement reporting if the entry condition of the target event is always met within the third time; The third time is the duration for the terminal to meet the entry condition of the target event.

28. The device according to claim 26 or 27, wherein The entry condition of the target event is satisfied, including: the model inference result of the AI prediction RLF of the serving cell of the terminal satisfies at least one of the following: The model reasoning result includes that the terminal will have RLF; The model inference result includes that the terminal will experience RLF at a first time point; The model inference result includes that a probability of the terminal experiencing RLF at the second time point is greater than or equal to a first threshold.

29. The device according to any one of claims 22 to 28, wherein The execution module is specifically configured to report a first report to the network side device when determining, based on the first configuration information, that the AI predicts the occurrence of RLF or the probability of the occurrence of RLF is greater than or equal to a third threshold, where the first report includes at least one of the following: a measurement result and a prediction result; The measurement result includes at least one of the following: a measurement result of the serving cell of the terminal, and a measurement result of a neighboring cell of the serving cell of the terminal; the prediction result includes at least one of the following: a prediction result of whether RLF occurs by the AI prediction of the serving cell of the terminal, and a prediction result of whether RLF occurs by the AI prediction of the neighboring cell of the serving cell.

30. The apparatus according to claim 29, wherein The prediction result is obtained by the terminal based on the model inference result of AI prediction of whether RLF occurs.

31. The device according to any one of claims 22 to 25, wherein The execution module is specifically configured to not perform measurement reporting when the exit condition of the target event is met; or perform measurement reporting when the exit condition of the target event is met and the configuration information related to the target event includes the second indication information; The second indication information is used to indicate whether measurement reporting is supported when an exit condition of the target event is met.

32. The apparatus according to claim 31, wherein The leaving condition of the target event is satisfied, wherein the model inference result of the AI prediction RLF of the serving cell of the terminal satisfies at least one of the following: The model reasoning result includes that the terminal will not have RLF; The model reasoning result includes that the terminal will not have RLF at a third time point; The model inference result includes that the probability of the terminal experiencing RLF at the fourth time point is less than or equal to the second threshold.

33. A device for configuring measurement reporting based on event triggering, the device comprising: Sending module; The sending module is used to send first configuration information to the terminal, where the first configuration information is used to configure the terminal to be triggered to perform measurement reporting based on a target event, where the target event includes whether a radio link failure RLF occurs based on artificial intelligence AI.

34. The apparatus according to claim 33, wherein The first configuration information includes at least one of the following: a first measurement object, where the first measurement object includes a serving cell of the terminal, or the first measurement object includes a serving cell of the terminal and a neighboring cell of the serving cell; a first reporting configuration, the first reporting configuration including an event-triggered reporting type and an identifier of a target event, the first reporting configuration being configured for the terminal to perform event-triggered measurement reporting according to the target event; A measurement identifier, where the measurement identifier is used to associate the first measurement object with the first reporting configuration.

35. The apparatus according to claim 33 or 34, wherein The first configuration information also includes first indication information, where the first indication information is used to instruct the terminal to report second information in a measurement report, where the second information includes at least one of a measurement result of a neighboring cell of the serving cell of the terminal and an AI prediction result of whether RLF occurs.

36. The device according to any one of claims 33 to 35, wherein The first configuration information further includes at least one of the following: A first time, the first time including at least one of the following: a time point when the terminal starts to perform AI model reasoning for AI prediction or a time period during which the AI model reasoning for predicting whether RLF occurs is continuously performed, and a time point or time period during which the terminal outputs a result of the model reasoning for predicting whether RLF occurs; A second time, where the second time is a time point or time period at which RLF occurs, obtained by predicting whether RLF occurs through AI; A first threshold value is used to determine whether the model reasoning result of the AI prediction of whether RLF occurs meets the entry conditions of the target event; A second threshold value is used to determine whether the model reasoning result of the AI prediction of whether RLF occurs meets the exit condition of the target event; a third time, the third time being a duration for the terminal to meet the entry condition of the target event; Second indication information, where the second indication information is used to indicate whether measurement reporting is supported when an exit condition of the target event is met.

37. The device according to any one of claims 33 to 36, wherein The device further includes: a receiving module; The receiving module is configured to receive a first report from a terminal, where the first report includes at least one of the following: a measurement result and a prediction result; The measurement result includes at least one of the following: a measurement result of the serving cell of the terminal, and a measurement result of a neighboring cell of the serving cell of the terminal; the prediction result includes at least one of the following: a prediction result of whether RLF occurs by the AI prediction of the serving cell of the terminal, and a prediction result of whether RLF occurs by the AI prediction of the neighboring cell of the serving cell of the terminal.

38. The apparatus according to claim 37, wherein The sending module is further configured to, after receiving a first report from the terminal, send a reconfiguration message to the terminal according to the first report, where the reconfiguration message includes relevant configurations for the terminal to perform cell switching.

39. A reporting device, comprising: Receiver module; The receiving module is configured to receive a first report from a terminal, where the first report includes at least one of the following: a measurement result and a prediction result; The measurement result includes at least one of the following: a measurement result of the serving cell of the terminal, and a measurement result of a neighboring cell of the serving cell of the terminal; the prediction result includes at least one of the following: a prediction result of whether RLF occurs by the AI prediction of the serving cell of the terminal, and a prediction result of whether RLF occurs by the AI prediction of the neighboring cell of the serving cell of the terminal.

40. The apparatus according to claim 39, wherein The device further includes: a sending module; The sending module is configured to send a reconfiguration message to the terminal according to the first report after receiving the first report from the terminal, wherein the reconfiguration message includes relevant configurations for the terminal to perform cell switching.

41. A terminal comprising a processor and a memory, wherein the memory stores a program or instruction that can be run on the processor, and when the program or instruction is executed by the processor, the steps of the event-triggered measurement reporting method according to any one of claims 1 to 12 are implemented.

42. A network side device, comprising a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the program or instructions are executed by the processor, implements the steps of the event-triggered measurement reporting configuration method as described in any one of claims 13 to 19, or implements the steps of the reporting method as described in claim 20 or 21.

43. A readable storage medium storing a program or instruction, wherein the program or instruction, when executed by a processor, implements the event-triggered measurement reporting method according to any one of claims 1 to 12, or implements the steps of the event-triggered measurement reporting configuration method according to any one of claims 13 to 19, or implements the steps of the reporting method according to claim 20 or 21.

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