Monitoring method, device, equipment, medium and program product

Abstract

The invention provides a monitoring method and device, equipment, a medium and a program product, and aims to solve the problem that the switching performance of a terminal cannot be guaranteed in related technologies. The monitoring method is applied to a network device, and the method comprises: performing function and / or model performance monitoring on first information, the first information comprising at least one of radio resource management (RRM) measurement prediction information, failure event prediction information and measurement event prediction information. According to the invention, the cell switching performance of the terminal can be improved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a monitoring method, device, equipment, medium and program product. Background Art

[0002] Mobility Optimization is one of the typical scenarios combining the fifth generation mobile communication technology (5G) with artificial intelligence (AI) technology. The specific prediction scenarios can be divided into the following two categories: prediction of the movement trajectory of user equipment (UE); prediction of UE's radio resource management (RRM measurement), handover failure (HOF) / radio link failure (RLF) or measurement events. Through the analysis of the above two AI-based mobility prediction scenarios, it can be seen that the interaction between prediction information and feedback information is more complicated for the scenarios of prediction of RRM measurement, HOF / RLF or measurement events. In particular, when the AI / machine learning (ML) model is located on the terminal side, the UE can use the AI / ML model to predict its own RRM measurement, HOF / RLF, measurement events, etc. For different types of predictions, the prediction information reported by the UE to the network device is different. However, for each type of prediction information, the network device does not evaluate the prediction accuracy, resulting in the inability to guarantee the terminal switching performance. Summary of the invention

[0003] The embodiments of the present application provide a monitoring method, apparatus, device, medium and program product to solve the problem that terminal switching performance cannot be guaranteed in the related art.

[0004] To solve the above technical problems, this application is implemented as follows:

[0005] In a first aspect, an embodiment of the present application provides a monitoring method, which is applied to a network device, and the method includes:

[0006] Functional and / or model performance monitoring is performed on first information, where the first information includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information.

[0007] Optionally, the method further comprises:

[0008] A first message sent by a receiving terminal is received, where the first message includes the first information.

[0009] Optionally, the performing function and / or model performance monitoring on the first information includes:

[0010] Collecting performance indicator information and determining whether the prediction accuracy meets the performance requirements based on the performance indicator information;

[0011] When it is determined that the prediction accuracy does not meet the preset requirement, a second message is sent to the terminal, where the second message is used to instruct the terminal to adjust the mobility prediction function and / or model.

[0012] Optionally, the method further comprises:

[0013] generating a first mobility decision based on the first information, where the first mobility decision is used to determine a target handover cell of the terminal;

[0014] A third message is sent to the terminal, where the third message is used to indicate the target switching cell.

[0015] Optionally, the generating a first mobility decision based on the first information includes:

[0016] Comparing RRM measurement prediction results of the serving cell and the candidate target cell within a first preset time period based on the RRM measurement prediction information in the first information;

[0017] In a case where the RRM measurement prediction result of the candidate target cell within the first preset time period is greater than or equal to the RRM measurement prediction result of the serving cell, or in a case where the RRM measurement prediction result of the candidate target cell within the first preset time period is greater than or equal to a first preset value, a first mobility decision is determined, and the first mobility decision is used to determine the candidate target cell as a target switching cell.

[0018] Optionally, the generating a first mobility decision based on the first information includes:

[0019] Based on the failure event prediction information in the first information, calculating the time until the failure event is expected to occur;

[0020] In a case where the duration is greater than the cell switching preparation duration, a first mobility decision is generated.

[0021] Optionally, the generating a first mobility decision based on the first information includes:

[0022] Based on the measurement event prediction information in the first information, determining whether a failure event will occur in the terminal;

[0023] In case that it is determined that a failure event will occur to the terminal, a first mobility decision is generated.

[0024] Optionally, the statistical performance indicator information and determining whether the prediction accuracy meets the performance requirement based on the performance indicator information includes:

[0025] Performing statistics on the performance indicators within the second preset time period to obtain a first performance indicator value, wherein the performance indicator information includes the first performance indicator value;

[0026] When the first performance indicator value is less than a second preset value and the first mobility decision is generated based on a predicted value, it is determined that the prediction accuracy does not meet the performance requirement.

[0027] Optionally, the statistical performance indicator information and determining whether the prediction accuracy meets the performance requirement based on the performance indicator information includes:

[0028] generating a second mobility decision based on the predicted value in the RRM measurement prediction information;

[0029] generating a third mobility decision based on the measured value in the RRM measurement prediction information;

[0030] Counting a second performance indicator value corresponding to the second mobility decision and a third performance indicator value corresponding to the third mobility decision, wherein the performance indicator information includes the second performance indicator value and the third performance indicator value;

[0031] When the difference between the second performance indicator value and the third performance indicator value is greater than a third preset value, it is determined that the prediction accuracy does not meet the performance requirement.

[0032] Optionally, the second message includes at least one of the following:

[0033] third indication information, where the third indication information is used to indicate a type of prediction information;

[0034] fourth indication information, where the fourth indication information is used to instruct the terminal to improve the mobility prediction accuracy;

[0035] fifth indication information, the fifth indication information being used to indicate a type of prediction information for improving prediction accuracy by the terminal;

[0036] Sixth indication information, where the sixth indication information is used to instruct the terminal to perform at least one of stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0037] seventh indication information, the seventh indication information being used to indicate a prediction information type of at least one of the following: stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0038] Eighth indication information, wherein the eighth indication information is used to indicate prediction configuration information.

[0039] Optionally, the RRM measurement prediction information includes at least one of the following:

[0040] Wireless information quality indicator information, the wireless information quality indicator information including measured values ​​and predicted values;

[0041] first indication information, where the first indication information is used to indicate that the wireless information quality indicator information is a measured value or a predicted value;

[0042] second indication information, where the second indication information is used to indicate a time domain, frequency domain or spatial domain pattern corresponding to measurement reduction;

[0043] prediction related information of the terminal;

[0044] prediction confidence, prediction accuracy, or prediction precision;

[0045] The time or period of time when the predicted value in the wireless information quality indicator information is generated;

[0046] The predicted time or time period corresponding to the predicted value in the wireless information quality indicator information.

[0047] Optionally, the failure event prediction information includes at least one of the following:

[0048] The expected time or time period of occurrence of the failure event; the event type of the failure event; the location information of the failure event; the RRM measurement information corresponding to the failure event; the time or time period of generation of the failure event prediction information.

[0049] Optionally, the measurement event prediction information includes at least one of the following:

[0050] The estimated time or time period of the measurement event; the type of the measurement event; and the time or time period of generating the prediction information of the measurement event.

[0051] In a second aspect, an embodiment of the present application provides a monitoring method, which is applied to a terminal, and the method includes:

[0052] Sending a first message to a network device, wherein the first message includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information;

[0053] The first message is used by the network device to perform function and / or model performance monitoring.

[0054] Optionally, the method further comprises:

[0055] A second message sent by the network device is received, where the second message is used to instruct the terminal to adjust a mobility prediction function and / or model.

[0056] Optionally, the second message includes at least one of the following:

[0057] third indication information, where the third indication information is used to indicate a type of prediction information;

[0058] fourth indication information, where the fourth indication information is used to instruct the terminal to improve prediction accuracy;

[0059] fifth indication information, the fifth indication information being used to indicate a type of prediction information for improving prediction accuracy by the terminal;

[0060] Sixth indication information, where the sixth indication information is used to instruct the terminal to perform at least one of stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0061] seventh indication information, the seventh indication information being used to indicate a prediction information type of at least one of the following: stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0062] Eighth indication information, wherein the eighth indication information is used to indicate prediction configuration information.

[0063] Optionally, the method further comprises:

[0064] adjusting configuration information and / or model input information of mobility prediction based on the second message;

[0065] Alternatively, determining a prediction information type for improving prediction accuracy based on the second message;

[0066] Alternatively, the prediction information type for stopping prediction, suspending prediction, or deactivating prediction is determined based on the second message.

[0067] Optionally, the method further comprises:

[0068] A third message sent by the network device is received, where the third message is used to indicate a target switching cell of the terminal.

[0069] Optionally, the RRM measurement prediction information includes at least one of the following:

[0070] Wireless information quality indicator information, the wireless information quality indicator information including measured values ​​and predicted values;

[0071] First indication information, where the first indication information is used to indicate that the wireless information quality indicator information is a measured value or a predicted value;

[0072] second indication information, where the second indication information is used to indicate a time domain, frequency domain or spatial domain pattern corresponding to measurement reduction;

[0073] prediction related information of the terminal;

[0074] prediction confidence, prediction accuracy, or prediction precision;

[0075] The time or period of time when the predicted value in the wireless information quality indicator information is generated;

[0076] The predicted time or time period corresponding to the predicted value in the wireless information quality indicator information.

[0077] Optionally, the failure event prediction information includes at least one of the following:

[0078] The expected time or time period of occurrence of the failure event; the event type of the failure event; the location information of the failure event; the RRM measurement information corresponding to the failure event; the time or time period of generation of the failure event prediction information.

[0079] Optionally, the measurement event prediction information includes at least one of the following:

[0080] The estimated time or time period of the measurement event; the type of the measurement event; and the time or time period of generating the prediction information of the measurement event.

[0081] In a third aspect, an embodiment of the present application provides a monitoring device, including:

[0082] The monitoring module is used to perform function and / or model performance monitoring on the first information, wherein the first information includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information.

[0083] Optionally, the device further comprises:

[0084] The first receiving module is used to receive a first message sent by a terminal, where the first message includes the first information.

[0085] Optionally, the monitoring module includes:

[0086] A statistical unit, used to collect statistical performance indicator information and determine whether the prediction accuracy meets the performance requirements based on the performance indicator information;

[0087] The sending unit is used to send a second message to the terminal when it is determined that the prediction accuracy does not meet the preset requirement, wherein the second message is used to instruct the terminal to adjust the mobility prediction function and / or model.

[0088] Optionally, the device further comprises:

[0089] A generating module, configured to generate a first mobility decision based on the first information, wherein the first mobility decision is used to determine a target switching cell of the terminal;

[0090] The sending module is used to send a third message to the terminal, where the third message is used to indicate the target switching cell.

[0091] Optionally, the generating module includes:

[0092] A comparing unit, configured to compare the RRM measurement prediction results of the serving cell and the candidate target cell within a first preset time period based on the RRM measurement prediction information in the first information;

[0093] A determination unit is used to determine a first mobility decision when the RRM measurement prediction result of the candidate target cell within the first preset time period is greater than or equal to the RRM measurement prediction result of the serving cell, or when the RRM measurement prediction result of the candidate target cell within the first preset time period is greater than or equal to a first preset value, and the first mobility decision is used to determine the candidate target cell as a target switching cell.

[0094] Optionally, the generating module includes:

[0095] a calculation unit, configured to calculate a time period from an expected occurrence time of a failure event based on the failure event prediction information in the first information;

[0096] The first generating unit is configured to generate a first mobility decision when the duration is greater than the cell switching preparation duration.

[0097] Optionally, the generating module includes:

[0098] a judging unit, configured to judge whether a failure event will occur in the terminal based on the measurement event prediction information in the first information;

[0099] The second generating unit is configured to generate a first mobility decision when it is determined that a failure event will occur to the terminal.

[0100] Optionally, the statistical unit is specifically used for:

[0101] Performing statistics on the performance indicators within the second preset time period to obtain a first performance indicator value, wherein the performance indicator information includes the first performance indicator value;

[0102] When the first performance indicator value is less than a second preset value and the first mobility decision is generated based on a predicted value, it is determined that the prediction accuracy does not meet the performance requirement.

[0103] Optionally, the statistical unit is specifically used for:

[0104] generating a second mobility decision based on the predicted value in the RRM measurement prediction information;

[0105] generating a third mobility decision based on the measured value in the RRM measurement prediction information;

[0106] Counting a second performance indicator value corresponding to the second mobility decision and a third performance indicator value corresponding to the third mobility decision, wherein the performance indicator information includes the second performance indicator value and the third performance indicator value;

[0107] When the difference between the second performance indicator value and the third performance indicator value is greater than a third preset value, it is determined that the prediction accuracy does not meet the performance requirement.

[0108] Optionally, the second message includes at least one of the following:

[0109] third indication information, where the third indication information is used to indicate a type of prediction information;

[0110] fourth indication information, where the fourth indication information is used to instruct the terminal to improve the mobility prediction accuracy;

[0111] fifth indication information, the fifth indication information being used to indicate a type of prediction information for improving prediction accuracy by the terminal;

[0112] Sixth indication information, where the sixth indication information is used to instruct the terminal to perform at least one of stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0113] seventh indication information, the seventh indication information being used to indicate a prediction information type of at least one of the following: stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0114] Eighth indication information, wherein the eighth indication information is used to indicate prediction configuration information.

[0115] Optionally, the RRM measurement prediction information includes at least one of the following:

[0116] Wireless information quality indicator information, the wireless information quality indicator information including measured values ​​and predicted values;

[0117] First indication information, where the first indication information is used to indicate that the wireless information quality indicator information is a measured value or a predicted value;

[0118] second indication information, where the second indication information is used to indicate a time domain, frequency domain or spatial domain pattern corresponding to measurement reduction;

[0119] prediction related information of the terminal;

[0120] prediction confidence, prediction accuracy, or prediction precision;

[0121] The time or period of time when the predicted value in the wireless information quality indicator information is generated;

[0122] The predicted time or time period corresponding to the predicted value in the wireless information quality indicator information.

[0123] Optionally, the failure event prediction information includes at least one of the following:

[0124] The expected time or time period of occurrence of the failure event; the event type of the failure event; the location information of the failure event; the RRM measurement information corresponding to the failure event; the time or time period of generation of the failure event prediction information.

[0125] Optionally, the measurement event prediction information includes at least one of the following:

[0126] The estimated time or time period of the measurement event; the type of the measurement event; and the time or time period of generating the prediction information of the measurement event.

[0127] In a fourth aspect, an embodiment of the present application provides a network device, including a processor, wherein the processor is configured to:

[0128] Functional and / or model performance monitoring is performed on first information, where the first information includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information.

[0129] Optionally, the network device further includes a transceiver, and the transceiver is used to:

[0130] A first message sent by a receiving terminal is received, where the first message includes the first information.

[0131] Optionally, the processor is specifically configured to:

[0132] Collecting performance indicator information and determining whether the prediction accuracy meets the performance requirements based on the performance indicator information;

[0133] When it is determined that the prediction accuracy does not meet the preset requirement, a second message is sent to the terminal, where the second message is used to instruct the terminal to adjust the mobility prediction function and / or model.

[0134] Optionally, the processor is further configured to:

[0135] generating a first mobility decision based on the first information, where the first mobility decision is used to determine a target handover cell of the terminal;

[0136] The transceiver is further used to send a third message to the terminal, where the third message is used to indicate the target switching cell.

[0137] Optionally, the processor is specifically configured to:

[0138] Comparing RRM measurement prediction results of the serving cell and the candidate target cell within a first preset time period based on the RRM measurement prediction information in the first information;

[0139] In a case where the RRM measurement prediction result of the candidate target cell within the first preset time period is greater than or equal to the RRM measurement prediction result of the serving cell, or in a case where the RRM measurement prediction result of the candidate target cell within the first preset time period is greater than or equal to a first preset value, a first mobility decision is determined, and the first mobility decision is used to determine the candidate target cell as a target switching cell.

[0140] Optionally, the processor is specifically configured to:

[0141] Based on the failure event prediction information in the first information, calculating the time until the failure event is expected to occur;

[0142] In a case where the duration is greater than the cell switching preparation duration, a first mobility decision is generated.

[0143] Optionally, the processor is specifically configured to:

[0144] Based on the measurement event prediction information in the first information, determining whether a failure event will occur in the terminal;

[0145] In case that it is determined that a failure event will occur to the terminal, a first mobility decision is generated.

[0146] Optionally, the processor is specifically configured to:

[0147] Performing statistics on the performance indicators within the second preset time period to obtain a first performance indicator value, wherein the performance indicator information includes the first performance indicator value;

[0148] When the first performance indicator value is less than a second preset value and the first mobility decision is generated based on a predicted value, it is determined that the prediction accuracy does not meet the performance requirement.

[0149] Optionally, the processor is specifically configured to:

[0150] generating a second mobility decision based on the predicted value in the RRM measurement prediction information;

[0151] generating a third mobility decision based on the measured value in the RRM measurement prediction information;

[0152] Counting a second performance indicator value corresponding to the second mobility decision and a third performance indicator value corresponding to the third mobility decision, wherein the performance indicator information includes the second performance indicator value and the third performance indicator value;

[0153] When the difference between the second performance indicator value and the third performance indicator value is greater than a third preset value, it is determined that the prediction accuracy does not meet the performance requirement.

[0154] Optionally, the second message includes at least one of the following:

[0155] third indication information, where the third indication information is used to indicate a type of prediction information;

[0156] fourth indication information, where the fourth indication information is used to instruct the terminal to improve the mobility prediction accuracy;

[0157] fifth indication information, the fifth indication information being used to indicate a type of prediction information for improving prediction accuracy by the terminal;

[0158] Sixth indication information, where the sixth indication information is used to instruct the terminal to perform at least one of stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0159] seventh indication information, the seventh indication information being used to indicate a prediction information type of at least one of the following: stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0160] The eighth indication information is used to indicate prediction configuration information. Optionally, the RRM measurement prediction information includes at least one of the following:

[0161] Wireless information quality indicator information, the wireless information quality indicator information including measured values ​​and predicted values;

[0162] first indication information, where the first indication information is used to indicate that the wireless information quality indicator information is a measured value or a predicted value;

[0163] second indication information, where the second indication information is used to indicate a time domain, frequency domain or spatial domain pattern corresponding to measurement reduction;

[0164] prediction related information of the terminal;

[0165] prediction confidence, prediction accuracy, or prediction precision;

[0166] The time or period of time when the predicted value in the wireless information quality indicator information is generated;

[0167] The predicted time or time period corresponding to the predicted value in the wireless information quality indicator information.

[0168] Optionally, the failure event prediction information includes at least one of the following:

[0169] The expected time or time period of occurrence of the failure event; the event type of the failure event; the location information of the failure event; the RRM measurement information corresponding to the failure event; the time or time period of generation of the failure event prediction information.

[0170] Optionally, the measurement event prediction information includes at least one of the following:

[0171] The estimated time or time period of the measurement event; the type of the measurement event; and the time or time period of generating the prediction information of the measurement event.

[0172] In a fifth aspect, an embodiment of the present application provides a monitoring device, including:

[0173] A sending module, configured to send a first message to a network device, wherein the first message includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information;

[0174] The first message is used by the network device to perform function and / or model performance monitoring.

[0175] Optionally, the device further comprises:

[0176] The second receiving module is used to receive a second message sent by the network device, where the second message is used to instruct the terminal to adjust the mobility prediction function and / or model.

[0177] Optionally, the second message includes at least one of the following:

[0178] third indication information, where the third indication information is used to indicate a type of prediction information;

[0179] fourth indication information, where the fourth indication information is used to instruct the terminal to improve prediction accuracy;

[0180] fifth indication information, the fifth indication information being used to indicate a type of prediction information for improving prediction accuracy by the terminal;

[0181] Sixth indication information, where the sixth indication information is used to instruct the terminal to perform at least one of stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0182] seventh indication information, the seventh indication information being used to indicate a prediction information type of at least one of the following: stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0183] Eighth indication information, the eighth indication information is used to indicate prediction configuration information. Optionally, the device further includes:

[0184] An adjustment module, configured to adjust configuration information and / or model input information of mobility prediction based on the second message;

[0185] Alternatively, a first determining module is used to determine the type of prediction information for improving prediction accuracy based on the second message;

[0186] Alternatively, the second determination module is used to determine the prediction information type for stopping prediction, suspending prediction or deactivating prediction based on the second message.

[0187] Optionally, the method further comprises:

[0188] The third receiving module is used to receive a third message sent by the network device, where the third message is used to indicate a target switching cell of the terminal.

[0189] Optionally, the RRM measurement prediction information includes at least one of the following:

[0190] Wireless information quality indicator information, the wireless information quality indicator information including measured values ​​and predicted values;

[0191] first indication information, where the first indication information is used to indicate that the wireless information quality indicator information is a measured value or a predicted value;

[0192] second indication information, where the second indication information is used to indicate a time domain, frequency domain or spatial domain pattern corresponding to measurement reduction;

[0193] prediction related information of the terminal;

[0194] prediction confidence, prediction accuracy, or prediction precision;

[0195] The time or period of time when the predicted value in the wireless information quality indicator information is generated;

[0196] The predicted time or time period corresponding to the predicted value in the wireless information quality indicator information.

[0197] Optionally, the failure event prediction information includes at least one of the following:

[0198] The expected time or time period of occurrence of the failure event; the event type of the failure event; the location information of the failure event; the RRM measurement information corresponding to the failure event; the time or time period of generation of the failure event prediction information.

[0199] Optionally, the measurement event prediction information includes at least one of the following:

[0200] The estimated time or time period of the measurement event; the type of the measurement event; and the time or time period of generating the prediction information of the measurement event.

[0201] In a sixth aspect, an embodiment of the present application provides a terminal, including a transceiver, wherein the transceiver is used to:

[0202] Sending a first message to a network device, wherein the first message includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information;

[0203] The first message is used by the network device to perform function and / or model performance monitoring.

[0204] Optionally, the transceiver is further used for:

[0205] A second message sent by the network device is received, where the second message is used to instruct the terminal to adjust a mobility prediction function and / or model.

[0206] Optionally, the second message includes at least one of the following:

[0207] third indication information, where the third indication information is used to indicate a type of prediction information;

[0208] fourth indication information, where the fourth indication information is used to instruct the terminal to improve prediction accuracy;

[0209] fifth indication information, the fifth indication information being used to indicate a type of prediction information for improving prediction accuracy by the terminal;

[0210] Sixth indication information, where the sixth indication information is used to instruct the terminal to perform at least one of stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0211] seventh indication information, the seventh indication information being used to indicate a prediction information type of at least one of the following: stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0212] Eighth indication information, the eighth indication information is used to indicate prediction configuration information. Optionally, the terminal further includes a processor, the processor being used to:

[0213] adjusting configuration information and / or model input information of mobility prediction based on the second message;

[0214] Alternatively, determining a prediction information type for improving prediction accuracy based on the second message;

[0215] Alternatively, the prediction information type for stopping prediction, suspending prediction, or deactivating prediction is determined based on the second message.

[0216] Optionally, the transceiver is further used for:

[0217] A third message sent by the network device is received, where the third message is used to indicate a target switching cell of the terminal.

[0218] Optionally, the RRM measurement prediction information includes at least one of the following:

[0219] Wireless information quality indicator information, the wireless information quality indicator information including measured values ​​and predicted values;

[0220] first indication information, where the first indication information is used to indicate that the wireless information quality indicator information is a measured value or a predicted value;

[0221] second indication information, where the second indication information is used to indicate a time domain, frequency domain or spatial domain pattern corresponding to measurement reduction;

[0222] prediction related information of the terminal;

[0223] prediction confidence, prediction accuracy, or prediction precision;

[0224] The time or period of time when the predicted value in the wireless information quality indicator information is generated;

[0225] The predicted time or time period corresponding to the predicted value in the wireless information quality indicator information.

[0226] Optionally, the failure event prediction information includes at least one of the following:

[0227] The expected time or time period of occurrence of the failure event; the event type of the failure event; the location information of the failure event; the RRM measurement information corresponding to the failure event; the time or time period of generation of the failure event prediction information.

[0228] Optionally, the measurement event prediction information includes at least one of the following:

[0229] The estimated time or time period of the measurement event; the type of the measurement event; and the time or time period of generating the prediction information of the measurement event.

[0230] In the seventh aspect, an embodiment of the present application provides an electronic device, comprising: a processor, a memory, and a program stored in the memory and executable on the processor, wherein when the program is executed by the processor, the steps of the monitoring method described in the first aspect are implemented; or, when the program is executed by the processor, the steps of the monitoring method described in the second aspect are implemented.

[0231] In an eighth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the monitoring method described in the first aspect are implemented; or, when the computer program is executed by a processor, the steps of the monitoring method described in the second aspect are implemented.

[0232] In the ninth aspect, an embodiment of the present application provides a computer program product, comprising computer instructions, which, when executed by a processor, implement the steps of the monitoring method described in the first aspect above; or, when executed by a processor, implement the steps of the monitoring method described in the second aspect above.

[0233] In an embodiment of the present application, the above-mentioned monitoring method is applied to a network device, and function and / or model performance monitoring is performed based on at least one of the wireless resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information included in the first information, so that the predicted performance of the terminal can be monitored in real time according to the first information to avoid problems such as terminal switching performance degradation due to insufficient prediction accuracy, thereby improving the cell switching performance and user experience of the terminal. BRIEF DESCRIPTION OF THE DRAWINGS

[0234] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments of the present application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0235] Figure 1 It is a schematic diagram of an AI / ML model functional framework provided in an embodiment of the present application;

[0236] Figure 2 This is one of the flow charts of a monitoring method provided in an embodiment of the present application;

[0237] Figure 3This is the second flow chart of a monitoring method provided in an embodiment of the present application;

[0238] Figure 4 This is one of the structural schematic diagrams of a monitoring device provided in an embodiment of the present application;

[0239] Figure 5 It is a structural diagram of a network device provided in an embodiment of the present application;

[0240] Figure 6 This is a second structural diagram of a monitoring device provided in an embodiment of the present application;

[0241] Figure 7 It is a structural diagram of a terminal provided in an embodiment of the present application. DETAILED DESCRIPTION

[0242] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0243] For ease of understanding, some contents involved in the embodiments of the present application are described below:

[0244] AI technology can extract the rules and features of massive data in complex scenarios and train and derive models to achieve prediction and optimize decision-making. Therefore, it is increasingly valued and applied by various industries. 5G mobile communication systems are also actively exploring the use of AI technology to build intelligent wireless access networks to solve problems such as the traditional methods that are prone to errors, high complexity, and inability to model complex problems, accelerate network automation and intelligence, and improve user experience.

[0245] 5G access network introduces AI / ML model, and the general functional framework is as follows Figure 1As shown in the figure, Data Collection (DataCollection): provides input data for model training (Model training) and model inference (Model inference); Model Training: is responsible for the training, testing and verification of AI / ML models, and generates metrics for model performance; Model Inference: provides the reasoning output (prediction or decision) of the AI / ML model, and can feedback the Model Performance Feedback (model performance feedback) results to the ModelTraining module; Actor: after receiving the reasoning output (prediction or decision) of the ModelInference module, initiates corresponding actions.

[0246] Mobility optimization is one of the typical scenarios for the combination of 5G and AI technology. The specific prediction scenarios can be divided into the following two categories:

[0247] (1) Predicting UE movement trajectory: The source node uses the AI / ML model Inference module to predict the movement trajectory of a specific UE and sends the predicted UE movement trajectory to the target node. The target node can directly use the prediction information to reserve transmission resources in advance. On the other hand, the source node also needs to obtain the actual movement trajectory of the UE or UE performance from the target node as feedback information to monitor the AI / ML model output performance, retrain the AI / ML model in a timely manner, and continuously improve the prediction and decision-making performance of the AI / ML model.

[0248] (2) Predict the UE's RRM measurement, HOF / RLF or measurement events: The AI / ML model can be located on the network side or the terminal side, and the prediction information can assist the network node in making decisions on UE cell switching. For example, the network node uses the AI / ML model Inference module to predict the UE's RRM measurement based on the measurement results reported by the UE; or, the UE uses the AI / ML model to predict its own RRM measurement, HOF / RLF, measurement events, etc. based on the measurement results and terminal location data. On the one hand, the prediction can reduce the measurements required on the terminal side. On the other hand, the prediction information is reported to the network, which can also assist the network node in making decisions on UE cell switching and improve the UE's switching performance.

[0249] Through the analysis of the above two AI-based mobility prediction scenarios, it can be seen that for the scenarios of prediction of RRM measurements, HOF / RLF or measurement events, the interaction between prediction information and feedback information is more complicated. In particular, when the AI / ML model is located on the terminal side, the UE can use the AI / ML model to predict its own RRM measurements, HOF / RLF, measurement events, etc. For different types of predictions, the prediction information reported by the UE to the network device is different; and for each type of prediction, the network side cannot directly feedback the same type of real information to the UE for training and performance optimization of the AI / ML model on the terminal side. For example, for RRM measurements, the UE usually measures the downlink reference signal and reports the RRM measurement results to the network side for mobility management and network resource management. The network side cannot directly obtain the RRM measurement results; similarly, for the RRM measurement prediction of the AI / ML model located on the terminal, the network side cannot directly obtain the real RRM measurement results and feedback them to the terminal. On the other hand, from the perspective of the current working framework of the wireless access network, the behavior of the terminal needs to be managed and controlled by the network side. Even if the AI / ML model is located on the terminal side, the network equipment (such as the NG-RAN node, i.e. the base station) still needs corresponding means to evaluate whether the prediction accuracy of the AI / ML model meets the requirements of mobility management such as switching decisions, and to promptly notify the terminal to adjust the prediction function of the AI / ML model or temporarily / deactivate / disable the prediction behavior of the terminal when the prediction accuracy is not met, so as to ensure that the terminal switching performance is not affected.

[0250] However, at present, there is no solution in the relevant technology to support the monitoring of the mobility prediction performance of the AI / ML model on the terminal side. The lack of relevant mechanisms may result in: the network side or the terminal side cannot timely evaluate whether the prediction accuracy of the model meets the needs of mobility management such as switching decisions on the network side, especially whether the prediction made to reduce terminal measurements can ensure that the UE's switching performance is not affected; if the prediction accuracy cannot be evaluated, the network or the terminal will not be able to take timely measures to adjust the AI / ML model prediction function or temporarily / deactivate / disable the terminal's prediction behavior, and the terminal switching performance cannot be guaranteed, affecting the user experience.

[0251] In the embodiments of the present application, the term "and / or" describes the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0252] In the embodiments of the present application, a monitoring method, device, equipment, medium and program product are proposed to solve the problem that the terminal switching performance cannot be guaranteed in the related technology.

[0253] See also Figure 2 , Figure 2 This is one of the flow charts of a monitoring method provided in an embodiment of the present application, which is applied to a network device, such as Figure 2 As shown, the method comprises the following steps:

[0254] Step 201: Perform function and / or model performance monitoring on first information, where the first information includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information.

[0255] Specifically, the above-mentioned radio resource management RRM measurement prediction information may include the radio information quality indicator information, prediction accuracy, prediction related information of the terminal measured or predicted by the terminal, etc. The above-mentioned failure event prediction information may be related information obtained by predicting the failure event, including the occurrence time of the failure event, the event type, location information, etc. The above-mentioned failure event may specifically include a radio link failure (Radio Link Failure, RLF) and a handover failure (Handover Failure, HOF) event, that is, the failure event prediction information may include RLF / HOF prediction information.

[0256] The above-mentioned measurement event prediction information (Measurement event prediction) may be relevant information obtained by predicting the measurement event, and the above-mentioned measurement event may be a conditional event that triggers a specific report or operation, such as event A3: the signal quality of the candidate target cell is higher than the signal quality of the serving cell minus an offset, event A5: the signal quality of the serving cell is lower than a certain threshold, and the signal quality of the candidate cell exceeds another different threshold.

[0257] It is understandable that the mobility prediction on the terminal side can be a specific function or an independent model execution, such as the mobility prediction scenario where the AI / ML model is located on the terminal side (UE sided model). Therefore, the detection of the terminal's mobility prediction performance can be either functional performance monitoring or model performance monitoring.

[0258] The network device involved in the embodiment of the present application may be a base station, which may include multiple cells providing services to the terminal. Depending on the specific application scenario, the base station may also be called an access point, or may be a device in the access network that communicates with the wireless terminal device through one or more sectors on the air interface, or other names. The network device may be used to replace the received air frame with the Internet Protocol (IP) packet, as a router between the wireless terminal device and the rest of the access network, wherein the rest of the access network may include an Internet Protocol (IP) communication network. The network device may also coordinate the attribute management of the air interface. For example, the network device involved in the embodiment of the present application may be an evolutionary network device (evolutional Node B, eNB or e-NodeB) in the long term evolution (LTE) system, a 5G base station (gNB) in the 5G network architecture (next generation system), etc., or a home evolved Node B (HeNB), a relay node, a home base station (femto), a pico base station (pico), a network test device, etc., which is not limited in the embodiment of the present application. In some network structures, the network devices may include centralized unit (CU) nodes and distributed unit (DU) nodes, and the centralized unit and the distributed unit may also be arranged geographically separately.

[0259] The terminal involved in the embodiment of the present application may be a device that provides voice and / or data connectivity to a user, a handheld device with a wireless connection function, or other processing devices connected to a wireless modem. In different systems, the name of the terminal device may also be different. For example, in a 5G system or a 6G system, the terminal device may be called a user equipment (UE). The wireless terminal device may be a USB storage device, other personal computer memory devices, and a dongle. It may also communicate with one or more core networks (CN) via a radio access network (RAN). The wireless terminal device may be a mobile terminal device, such as a mobile phone (or "cellular" phone) and a computer with a mobile terminal device. For example, it may be a portable, pocket-sized, handheld, computer-built-in or vehicle-mounted mobile device that exchanges language and / or data with a radio access network. For example, Personal Communication Service (PCS) phones, cordless phones, Session Initiated Protocol (SIP) phones, Wireless Local Loop (WLL) stations, Personal Digital Assistants (PDA), personal computers, tablet computers, Machine-type Communication (MTC) terminal devices, etc. Wireless terminal devices may also be referred to as systems, subscriber units, subscriber stations, mobile stations, mobile stations, remote stations, access points, remote terminal devices, access terminal devices, user terminal devices, user agents, user devices, and wireless access points and routers / modems that meet the limitations of this definition, which are not limited in the embodiments of the present application.

[0260] In an embodiment of the present application, the above-mentioned monitoring method is applied to a network device, and function and / or model performance monitoring is performed based on at least one of the wireless resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information included in the first information, so that the predicted performance of the terminal can be monitored in real time according to the first information to avoid problems such as terminal switching performance degradation due to insufficient prediction accuracy, thereby improving the cell switching performance and user experience of the terminal.

[0261] Optionally, the method further comprises:

[0262] A first message sent by a receiving terminal is received, where the first message includes the first information.

[0263] It should be noted that the above-mentioned first message can be one or more messages, that is, the above-mentioned terminal can send wireless resource management RRM measurement prediction information, failure event prediction information and at least one of measurement event prediction information to the network device through one or more messages.

[0264] Optionally, the performing function and / or model performance monitoring on the first information includes:

[0265] Collecting performance indicator information and determining whether the prediction accuracy meets the performance requirements based on the performance indicator information;

[0266] When it is determined that the prediction accuracy does not meet the preset requirement, a second message is sent to the terminal, where the second message is used to instruct the terminal to adjust the mobility prediction function and / or model.

[0267] Specifically, the above-mentioned performance indicator information may be indicator information obtained by statistically analyzing the cell switching performance and / or terminal performance and / or system performance, and may be used to monitor the prediction accuracy. Specifically, the above-mentioned cell switching performance may include at least one of the following: handover failure rate, for example, characterized by the ratio of the number of handover failures to the total number of handovers; wireless link failure performance index, for example, characterized by the average number of RLFs per second for a single UE; Ping-pong switching rate, for example, characterized by the ratio of the number of ping-pongs to the number of successful handovers; unnecessary switching rate such as too short residence time, for example, characterized by the ratio of the number of times the UE's residence time (time-of-stay) in a cell is less than a certain threshold to the number of successful handovers. The above-mentioned terminal performance may include but is not limited to UE downlink throughput, UE uplink throughput, data packet delay and packet loss rate. The above-mentioned system performance may include but is not limited to system throughput and resource utilization.

[0268] It should be noted that the above-mentioned function and / or model performance monitoring may be statistical monitoring performed after the terminal uses the prediction information to generate a mobility decision.

[0269] In this implementation, the above-mentioned monitoring method collects statistical performance indicator information and determines whether the prediction accuracy meets the performance requirements based on the performance indicator information. When it is determined that the prediction accuracy does not meet the preset requirements, a second message is sent to the terminal. The second message is used to instruct the terminal to adjust the mobility prediction function and / or model, so that when the prediction accuracy of the terminal does not meet the preset requirements, it can be adjusted in time, thereby improving the terminal prediction performance, thereby further ensuring the cell switching performance.

[0270] Optionally, the method further comprises:

[0271] generating a first mobility decision based on the first information, where the first mobility decision is used to determine a target handover cell of the terminal;

[0272] A third message is sent to the terminal, where the third message is used to indicate the target switching cell.

[0273] Specifically, the first mobility decision may be a cell switching decision of the terminal, and the third message may be a radio resource control (RRC) reconfiguration message, that is, the network device may use a relevant mechanism to send an RRC reconfiguration message to the UE to indicate the target cell for switching.

[0274] In this implementation, the above-mentioned monitoring method generates a first mobility decision based on the first information, the first mobility decision is used to determine the target switching cell of the terminal, and a third message is sent to the terminal, the third message is used to indicate the target switching cell, so that the network device can determine the target switching cell of the terminal according to the first message, thereby further improving the cell switching performance of the terminal.

[0275] Optionally, the generating a first mobility decision based on the first information includes:

[0276] Comparing RRM measurement prediction results of the serving cell and the candidate target cell within a first preset time period based on the RRM measurement prediction information in the first information;

[0277] In a case where the RRM measurement prediction result of the candidate target cell within the first preset time period is greater than or equal to the RRM measurement prediction result of the serving cell, or in a case where the RRM measurement prediction result of the candidate target cell within the first preset time period is greater than or equal to a first preset value, a first mobility decision is determined, and the first mobility decision is used to determine the candidate target cell as a target switching cell.

[0278] Specifically, the first preset time period may be a certain moment or a certain period in the future, for example, the observation window length may be pre-set, and the first preset time period may be a period of time within the observation window length, for example, the trigger time (Time-to-Trigger, TTT) duration in the measurement event configured by the current network for the UE may be used.

[0279] The serving cell is the current serving cell of the terminal, and the candidate target cell may be a candidate target cell determined for the terminal according to a handover decision algorithm in the related art. It is understandable that the candidate target cell may be one or more. The first preset value may be a preset threshold value.

[0280] In this embodiment, the above-mentioned monitoring method determines a first mobility decision when the RRM measurement prediction result of the candidate target cell within the first preset time period is greater than or equal to the RRM measurement prediction result of the serving cell, or when the RRM measurement prediction result of the candidate target cell within the first preset time period is greater than or equal to a first preset value. The first mobility decision is used to determine the candidate target cell as the target switching cell. By using the RRM measurement prediction information to optimize the switching decision, ping-pong switching can be effectively avoided, thereby reducing unnecessary switching, thereby reducing signaling overhead and optimizing network resource utilization.

[0281] Optionally, the generating a first mobility decision based on the first information includes:

[0282] Based on the failure event prediction information in the first information, calculating the time until the failure event is expected to occur;

[0283] In a case where the duration is greater than the cell switching preparation duration, a first mobility decision is generated.

[0284] It can be understood that the time length of the above-mentioned distance failure event is the time length from the current moment to the expected time of the failure event, and the above-mentioned cell switching preparation time length can be the time required for the UE to smoothly switch from one cell to another cell. In the case where the time length is greater than the cell switching preparation time length, it is determined that the UE performs a switching operation, and the switching is performed using a related switching mechanism. Furthermore, the target cell for cell switching can be selected for the UE based on the RRM measurement prediction information of the neighboring cell.

[0285] In this embodiment, the above-mentioned monitoring method executes terminal cell switching when the time length from the expected occurrence time of the failure event is greater than the cell switching preparation time, so as to ensure that the cell switching is completed before the predicted failure event occurs, thereby reducing the connection interruption or data loss caused by the failure event, thereby improving the robustness of the network.

[0286] Optionally, the generating a first mobility decision based on the first information includes:

[0287] Based on the measurement event prediction information in the first information, determining whether a failure event will occur in the terminal;

[0288] In case that it is determined that a failure event will occur to the terminal, a first mobility decision is generated.

[0289] Specifically, it is possible to determine whether the UE will experience a failure event such as RLF / HOF based on the time or moment when the measurement event is expected to be met and other relevant information. If it is determined that a failure event will occur, it is determined that the UE performs a handover operation in advance. It should be noted that the execution time of the handover preparation must ensure that the cell handover is completed before the failure event occurs. Furthermore, the target cell for cell handover can be selected for the UE based on the RRM measurement prediction information of the neighboring cell.

[0290] In this implementation, when the monitoring method determines that a failure event will occur at the terminal, the terminal cell switching is performed in advance to ensure that the cell switching is completed before the predicted failure event occurs, thereby reducing connection interruption or data loss caused by the failure event, thereby further improving the robustness of the network.

[0291] Optionally, the statistical performance indicator information and determining whether the prediction accuracy meets the performance requirement based on the performance indicator information includes:

[0292] Performing statistics on the performance indicators within the second preset time period to obtain a first performance indicator value, wherein the performance indicator information includes the first performance indicator value;

[0293] When the first performance indicator value is less than a second preset value and the first mobility decision is generated based on a predicted value, it is determined that the prediction accuracy does not meet the performance requirement.

[0294] Specifically, the second preset time period may be a preset window length, and may be a fixed window or a sliding window. The second preset value may be a preset threshold value, or may be the difference between the statistical index value in the previous time window and the preset threshold value.

[0295] It should be noted that the first indication information in the RRM measurement prediction information reported by the UE can be used to indicate the measured value and the predicted value, and the RLF / HOF information and measurement event information in the failure event prediction information reported by the UE can be directly identified as the predicted value.

[0296] Exemplarily, the above-mentioned network uses a fixed window or a sliding window (pre-set window length) to calculate statistical performance indicators. If the statistical indicators in a certain time window are too different from the statistical indicators in the previous time window, for example, exceeding a certain threshold value, then the information reported by the UE is combined to determine whether the switching decision is based on the prediction information. If it is based on the prediction information, it is determined that the prediction accuracy does not meet the performance requirements; or a threshold value is pre-set. If the statistical indicators in a certain time window are lower than the threshold value, then the information reported by the UE is combined to determine whether the switching decision is based on the prediction information. If it is based on the prediction information, it is determined that the prediction accuracy does not meet the performance requirements.

[0297] In this implementation, the above-mentioned monitoring method performs statistics on the performance indicators within the second preset time period to obtain a first performance indicator value, and the performance indicator information includes the first performance indicator value. When the first performance indicator value is less than the second preset value and the first mobility decision is generated based on the predicted value, it is determined that the prediction accuracy does not meet the performance requirements, and then the terminal can be instructed to adjust the mobility prediction function and / or model, thereby avoiding problems such as terminal switching performance degradation due to insufficient prediction accuracy, thereby ensuring cell switching performance.

[0298] Optionally, the statistical performance indicator information and determining whether the prediction accuracy meets the performance requirement based on the performance indicator information includes:

[0299] generating a second mobility decision based on the predicted value in the RRM measurement prediction information;

[0300] generating a third mobility decision based on the measured value in the RRM measurement prediction information;

[0301] Counting a second performance indicator value corresponding to the second mobility decision and a third performance indicator value corresponding to the third mobility decision, wherein the performance indicator information includes the second performance indicator value and the third performance indicator value;

[0302] When the difference between the second performance indicator value and the third performance indicator value is greater than a third preset value, it is determined that the prediction accuracy does not meet the performance requirement.

[0303] Specifically, the network equipment counts the performance indicators of switching decisions based on measured values ​​and predicted values ​​respectively according to the information reported by the UE. If the difference between the statistical indicators of switching decisions based on predicted values ​​and the statistical indicators of switching decisions based on measured values ​​is too large (for example, exceeds a certain threshold value), it is judged that the prediction accuracy does not meet the performance requirements.

[0304] It should be noted that the first indication information in the RRM measurement prediction information reported by the UE can be used to indicate the measured value and the predicted value, and the RLF / HOF information and measurement event information in the failure event prediction information reported by the UE can be directly identified as the predicted value.

[0305] In this implementation manner, the monitoring method uses a network device to separately count the performance indicators of handover decisions based on measured values ​​and predicted values ​​according to the information reported by the UE, and determines whether the prediction accuracy meets the performance requirements, and then can instruct the terminal to adjust the mobility prediction function and / or model when the performance requirements are not met, thereby avoiding problems such as terminal handover performance degradation caused by insufficient prediction accuracy, and ensuring cell handover performance. Optionally, the second message includes at least one of the following:

[0306] third indication information, where the third indication information is used to indicate a type of prediction information;

[0307] fourth indication information, where the fourth indication information is used to instruct the terminal to improve the mobility prediction accuracy;

[0308] fifth indication information, the fifth indication information being used to indicate a type of prediction information for improving prediction accuracy by the terminal;

[0309] Sixth indication information, where the sixth indication information is used to instruct the terminal to perform at least one of stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0310] seventh indication information, the seventh indication information being used to indicate a prediction information type of at least one of the following: stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0311] The eighth indication information is used to indicate prediction configuration information. Specifically, the third indication information can be used to indicate a prediction information type with insufficient prediction accuracy or a prediction information type that needs to improve accuracy, such as one or more of RRM measurement prediction information, failure event prediction information, and measurement event prediction information.

[0312] The above-mentioned prediction configuration information may be prediction-related configuration information with insufficient prediction value accuracy. One way is the generation time or moment of the prediction information. The information may be used as an index to help the UE find the corresponding AI / ML model-related configuration for generating the prediction information, the relevant input information for inference, etc., so as to facilitate the configuration adjustment of the AI / ML model and improve the prediction accuracy. Another way is whether the prediction result adopts the indication information of measurement reduction and / or the actual measurement reduction (measurement reduction rates, such as MRRT, MRRF, MRRS) and / or the time-frequency, frequency domain, or spatial domain pattern used for prediction, etc. For example, the time domain pattern may be the sample point or moment information actually measured or used as input; the frequency domain pattern may be the frequency band or frequency point information actually measured or used as input; the spatial domain pattern may be the beam information actually measured or used as input; another way is prediction-related configuration information, such as the observation / observation window duration, the prediction window duration, the L1 sampling duration (sample period), the measurement period (Measurement period), and the filtering coefficient (Filtering co-efficient) used for prediction. This information can assist the UE in making configuration adjustments to the AI / ML model and measurement reduction to improve prediction accuracy.

[0313] Optionally, the RRM measurement prediction information includes at least one of the following:

[0314] Wireless information quality indicator information, the wireless information quality indicator information including measured values ​​and predicted values;

[0315] first indication information, where the first indication information is used to indicate that the wireless information quality indicator information is a measured value or a predicted value;

[0316] second indication information, where the second indication information is used to indicate a time domain, frequency domain or spatial domain pattern corresponding to measurement reduction;

[0317] prediction related information of the terminal;

[0318] prediction confidence, prediction accuracy, or prediction precision;

[0319] The time or period of time when the predicted value in the wireless information quality indicator information is generated;

[0320] The predicted time or time period corresponding to the predicted value in the wireless information quality indicator information.

[0321] Specifically, the above-mentioned wireless information quality indicator information may be various parameters of signal transmission quality in a wireless communication system, such as reference signal received power (RSRP), reference signal received quality (RSRQ) and signal to interference plus noise ratio (SINR), which may specifically include measured values ​​and / or predicted values ​​of RSRP / RSRQ / SINR at the cell level or beam level. The measured value refers to the actual measurement result of RSRP / RSRQ / SINR at the cell level or beam level of the current serving cell and / or neighboring cell; the prediction information refers to the RSRP / RSRQ / SINR prediction result at the cell level or beam level of the current serving cell and / or neighboring cell obtained by time-frequency, frequency domain, or spatial domain prediction.

[0322] In this implementation manner, the wireless information quality indicator information can be used to determine candidate target cells and avoid unnecessary handover processes such as ping-pong handover.

[0323] The above-mentioned first indication information can be used to indicate that the wireless information quality indicator information is a measured value or a predicted value, and the specific form of the indication information can be divided into two types: explicit and implicit. Among them, the explicit indication method can be to indicate which wireless information quality indicator information is obtained by actual measurement or by prediction in the form of clear bits, bitmaps, IEs, etc.; the implicit indication method can be to distinguish between the measured results and the predicted results by including them in different IE / fields or different messages.

[0324] In this implementation manner, the first indication information is useful in that the network can know on which data (actual measured value or predicted value) the mobility decision is based, and can separately count indicators such as switching performance to evaluate prediction accuracy.

[0325] The above-mentioned second indication information can be used to indicate whether the predicted value of the wireless information quality indicator information is used for the purpose of measurement reduction and / or the actual measurement reduction amount and / or the time-frequency, or frequency domain, or spatial domain pattern used for measurement reduction.

[0326] In this implementation manner, the purpose of providing the second indication information to the network device is that, when the accuracy of the prediction result can meet the mobility management requirements, the network can comprehensively consider the prediction conditions of multiple terminals and consider whether to reduce the sending of some reference signals for measurement or transmit data on the original terminal measurement resources; when the accuracy of the prediction result cannot meet the mobility management requirements, the actual measurement reduction situation can assist the network in determining whether to notify the UE to adjust the measurement reduction configuration or directly provisionally / deactivate / disable the terminal's predicted behavior.

[0327] Specifically, the prediction related information of the terminal may include information related to the prediction method such as UE power consumption and moving speed, and auxiliary information.

[0328] Optionally, the failure event prediction information includes at least one of the following:

[0329] The expected time or time period of occurrence of the failure event; the event type of the failure event; the location information of the failure event; the RRM measurement information corresponding to the failure event; the time or time period of generation of the failure event prediction information.

[0330] Specifically, the predicted time or period of the failure event may be absolute time, such as Coordinated Universal Time (UTC), or relative time, such as a period of time in the future from the time when the prediction is generated. The event type of the failure event may include HOF, RLF, etc.

[0331] The location information of the failure event may be a cell ID where the failure event is predicted to occur, or specific longitude and latitude information. In this implementation, the location information of the failure event may assist the network in determining the scene where the failure occurs and adjusting the configuration of mobility-related parameters.

[0332] The RRM measurement information corresponding to the above failure event may refer to the RRM measurement prediction information corresponding to the time when the UE failure event is expected to occur, which can be characterized as measurement quantities such as RSRP / RSRQ / SINR. In this implementation, the RRM measurement information corresponding to the above failure event can assist the network in determining the scene where the failure occurs and adjusting the configuration of mobility-related parameters.

[0333] Optionally, the measurement event prediction information includes at least one of the following:

[0334] The estimated time or time period of the measurement event; the type of the measurement event; and the time or time period of generating the prediction information of the measurement event.

[0335] Specifically, the estimated time or period of the measurement event may be absolute time, such as Coordinated Universal Time (UTC), or relative time, such as a period of time in the future from the time when the prediction is generated. The types of the measurement event may include A3, A5, and the like.

[0336] See also Figure 3 , Figure 3 This is a second flow chart of a monitoring method provided in an embodiment of the present application, which is applied to a terminal device, such as Figure 3 As shown, the method comprises the following steps:

[0337] Step 301: Send a first message to a network device, where the first message includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information;

[0338] The first message is used by the network device to perform function and / or model performance monitoring.

[0339] It should be noted that this embodiment is Figure 2 The implementation method of the corresponding terminal device in the embodiment shown in the figure can be found in the specific implementation method of the terminal device in the embodiment shown in the figure. Figure 2 To avoid repeated description, the relevant descriptions in the illustrated embodiment will not be repeated in this embodiment.

[0340] Optionally, the method further comprises:

[0341] A second message sent by the network device is received, where the second message is used to instruct the terminal to adjust a mobility prediction function and / or model.

[0342] Optionally, the second message includes at least one of the following:

[0343] third indication information, where the third indication information is used to indicate a type of prediction information;

[0344] fourth indication information, where the fourth indication information is used to instruct the terminal to improve prediction accuracy;

[0345] fifth indication information, the fifth indication information being used to indicate a type of prediction information for improving prediction accuracy by the terminal;

[0346] Sixth indication information, where the sixth indication information is used to instruct the terminal to perform at least one of stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0347] seventh indication information, the seventh indication information being used to indicate a prediction information type of at least one of the following: stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0348] Eighth indication information, the eighth indication information is used to indicate prediction configuration information. Optionally, the method further includes:

[0349] adjusting configuration information and / or model input information of mobility prediction based on the second message;

[0350] Alternatively, determining a prediction information type for improving prediction accuracy based on the second message;

[0351] Alternatively, the prediction information type for stopping prediction, suspending prediction, or deactivating prediction is determined based on the second message.

[0352] Specifically, the above-mentioned configuration information and / or model input information for adjusting the mobility prediction based on the second message, or the prediction information type for improving the prediction accuracy based on the second message can be determined by the terminal according to the third indication information and / or the fourth indication information in the second message, or according to the fifth indication information in the second message. The prediction type whose prediction accuracy needs to be improved can also be determined according to the generation time or time period of the prediction information or its own stored information, and the relevant configuration parameters for the prediction information whose accuracy needs to be improved can be determined based on the generation time or time period of the prediction information or the self-stored information, and adjustments can be made on this basis to improve the prediction accuracy.

[0353] Exemplarily, the terminal-side AI / ML model can obtain the relevant configuration information used for the prediction based on the generation time or time period index of the prediction information contained in the second message, or use the configuration information related to the prediction contained in the second message as input information of the AI / ML model to retrain / iterate the AI / ML model to improve the prediction performance of the AI / ML model.

[0354] Further, for the case where the prediction information type that needs to improve the prediction accuracy is RRM measurement prediction information, if it is a time domain prediction and is based on a prediction of measurement reduction (specifically, it can be determined according to the relevant information or stored information of the measurement reduction in the second message), it is determined to reduce the number of prediction sampling points, that is, to reduce the measurement reduction ratio (Measurement reduction rate), and replace the predicted value with more measured values;

[0355] If it is a time domain prediction but not a prediction based on measurement reduction, it is determined whether to increase the length of the observation window, i.e., increase the number of measured sampling points used for prediction, and / or shorten the length of the prediction window, i.e., reduce the number of sampling points of the prediction output, to avoid predicting measurement results for a longer period of time in the future;

[0356] If it is a spatial domain prediction, the previous prediction related configuration and the measurement reduction pattern may be determined according to the measurement reduction related information or the stored information in the second message, and the number of beams to be predicted may be reduced, that is, the number of beams to be predicted may be replaced by the number of beams actually measured;

[0357] If it is a frequency domain prediction, it is determined to increase the number of measured data of inter-frequency points required for prediction, such as the number of measured neighboring cells, or adjust the inter-frequency points used for prediction, such as adjusting them to frequencies that have better correlation with the frequency to be predicted.

[0358] Furthermore, in the case where the type of prediction information that needs to improve prediction accuracy is failure event prediction information, the default is time domain prediction. It can be determined whether to increase the observation window length or increase the amount of input data used for prediction, and / or shorten the prediction window length or reduce the time granularity of failure event prediction to avoid predicting the occurrence of failure events in a longer period of time in the future.

[0359] Furthermore, in the case where the type of prediction information that needs to improve prediction accuracy is measurement event prediction information, the default is time domain prediction, and it is determined whether to increase the observation window length or increase the amount of input data used for prediction, and / or shorten the prediction window length or reduce the time granularity of measurement event prediction, and avoid predicting measurement events for a longer period of time in the future.

[0360] Specifically, the prediction information type for determining to stop prediction, suspend prediction or deactivate prediction based on the second message can be that the terminal determines the prediction type that needs to be stopped / temporarily / deactivated based on the third indication information and / or the sixth indication information in the second message, or based on the seventh indication information in the second message, and the terminal falls back to measuring in the actual measurement mode and reporting RRM measurement prediction information, or stops predicting failure event prediction information or measurement event prediction information.

[0361] Optionally, the method further comprises:

[0362] A third message sent by the network device is received, where the third message is used to indicate a target switching cell of the terminal.

[0363] Optionally, the RRM measurement prediction information includes at least one of the following:

[0364] Wireless information quality indicator information, the wireless information quality indicator information including measured values ​​and predicted values;

[0365] First indication information, where the first indication information is used to indicate that the wireless information quality indicator information is a measured value or a predicted value;

[0366] second indication information, where the second indication information is used to indicate a time domain, frequency domain or spatial domain pattern corresponding to measurement reduction;

[0367] prediction related information of the terminal;

[0368] prediction confidence, prediction accuracy, or prediction precision;

[0369] The time or period of time when the predicted value in the wireless information quality indicator information is generated;

[0370] The predicted time or time period corresponding to the predicted value in the wireless information quality indicator information.

[0371] Optionally, the failure event prediction information includes at least one of the following:

[0372] The expected time or time period of occurrence of the failure event; the event type of the failure event; the location information of the failure event; the RRM measurement information corresponding to the failure event; the time or time period of generation of the failure event prediction information.

[0373] Optionally, the measurement event prediction information includes at least one of the following:

[0374] The estimated time or time period of the measurement event; the type of the measurement event; and the time or time period of generating the prediction information of the measurement event.

[0375] The above optional implementations can be found in Figure 2 To avoid repeated description, the relevant descriptions in the illustrated embodiment will not be repeated in this embodiment.

[0376] See also Figure 4 , Figure 4 is one of the structural diagrams of a monitoring device provided in an embodiment of the present application, such as Figure 4 As shown, the monitoring device 400 includes:

[0377] The monitoring module 401 is used to perform function and / or model performance monitoring on the first information, where the first information includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information.

[0378] Optionally, the device further comprises:

[0379] The first receiving module is used to receive a first message sent by a terminal, where the first message includes the first information.

[0380] Optionally, the monitoring module 402 includes:

[0381] A statistical unit, used to collect statistical performance indicator information and determine whether the prediction accuracy meets the performance requirements based on the performance indicator information;

[0382] The sending unit is used to send a second message to the terminal when it is determined that the prediction accuracy does not meet the preset requirement, wherein the second message is used to instruct the terminal to adjust the mobility prediction function and / or model.

[0383] Optionally, the device further comprises:

[0384] A generating module, configured to generate a first mobility decision based on the first information, wherein the first mobility decision is used to determine a target switching cell of the terminal;

[0385] The sending module is used to send a third message to the terminal, where the third message is used to indicate the target switching cell.

[0386] Optionally, the generating module includes:

[0387] A comparing unit, configured to compare the RRM measurement prediction results of the serving cell and the candidate target cell within a first preset time period based on the RRM measurement prediction information in the first information;

[0388] A determination unit is used to determine a first mobility decision when the RRM measurement prediction result of the candidate target cell within the first preset time period is greater than or equal to the RRM measurement prediction result of the serving cell, or when the RRM measurement prediction result of the candidate target cell within the first preset time period is greater than or equal to a first preset value, and the first mobility decision is used to determine the candidate target cell as a target switching cell.

[0389] Optionally, the generating module includes:

[0390] a calculation unit, configured to calculate a time period from an expected occurrence time of a failure event based on the failure event prediction information in the first information;

[0391] The first generating unit is configured to generate a first mobility decision when the duration is greater than the cell switching preparation duration.

[0392] Optionally, the generating module includes:

[0393] a judging unit, configured to judge whether a failure event will occur in the terminal based on the measurement event prediction information in the first information;

[0394] The second generating unit is configured to generate a first mobility decision when it is determined that a failure event will occur to the terminal.

[0395] Optionally, the statistical unit is specifically used for:

[0396] Performing statistics on the performance indicators within the second preset time period to obtain a first performance indicator value, wherein the performance indicator information includes the first performance indicator value;

[0397] When the first performance indicator value is less than a second preset value and the first mobility decision is generated based on a predicted value, it is determined that the prediction accuracy does not meet the performance requirement.

[0398] Optionally, the statistical unit is specifically used for:

[0399] generating a second mobility decision based on the predicted value in the RRM measurement prediction information;

[0400] generating a third mobility decision based on the measured value in the RRM measurement prediction information;

[0401] Counting a second performance indicator value corresponding to the second mobility decision and a third performance indicator value corresponding to the third mobility decision, wherein the performance indicator information includes the second performance indicator value and the third performance indicator value;

[0402] When the difference between the second performance indicator value and the third performance indicator value is greater than a third preset value, it is determined that the prediction accuracy does not meet the performance requirement.

[0403] Optionally, the second message includes at least one of the following:

[0404] third indication information, where the third indication information is used to indicate a type of prediction information;

[0405] fourth indication information, where the fourth indication information is used to instruct the terminal to improve the mobility prediction accuracy;

[0406] fifth indication information, the fifth indication information being used to indicate a type of prediction information for improving prediction accuracy by the terminal;

[0407] Sixth indication information, where the sixth indication information is used to instruct the terminal to perform at least one of stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0408] seventh indication information, the seventh indication information being used to indicate a prediction information type of at least one of the following: stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0409] The eighth indication information is used to indicate prediction configuration information. Optionally, the RRM measurement prediction information includes at least one of the following:

[0410] Wireless information quality indicator information, the wireless information quality indicator information including measured values ​​and predicted values;

[0411] First indication information, where the first indication information is used to indicate that the wireless information quality indicator information is a measured value or a predicted value;

[0412] second indication information, where the second indication information is used to indicate a time domain, frequency domain or spatial domain pattern corresponding to measurement reduction;

[0413] prediction related information of the terminal;

[0414] prediction confidence, prediction accuracy, or prediction precision;

[0415] The time or period of time when the predicted value in the wireless information quality indicator information is generated;

[0416] The predicted time or time period corresponding to the predicted value in the wireless information quality indicator information.

[0417] Optionally, the failure event prediction information includes at least one of the following:

[0418] The expected time or time period of occurrence of the failure event; the event type of the failure event; the location information of the failure event; the RRM measurement information corresponding to the failure event; the time or time period of generation of the failure event prediction information.

[0419] Optionally, the measurement event prediction information includes at least one of the following:

[0420] The estimated time or time period of the measurement event; the type of the measurement event; and the time or time period of generating the prediction information of the measurement event.

[0421] It should be noted that the monitoring device provided in the embodiment of the present application is a device capable of executing the above monitoring method, and all implementations in the above monitoring method embodiment are applicable to the device and can achieve the same or similar beneficial effects. To avoid repeated description, this embodiment will not be repeated.

[0422] For details, see Figure 5As shown, an embodiment of the present application further provides a network device, including a bus 501, a transceiver 502, an antenna 503, a bus interface 504, a processor 505 and a memory 506.

[0423] The processor 505 is used to perform function and / or model performance monitoring on first information, where the first information includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information.

[0424] exist Figure 5 In the embodiment, the bus architecture (represented by bus 501) is shown, and bus 501 may include any number of interconnected buses and bridges, and bus 501 links various circuits including one or more processors represented by processor 505 and memory represented by memory 506. Bus 501 may also link various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. Bus interface 504 provides an interface between bus 501 and transceiver 502. Transceiver 502 may be one element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on a transmission medium. Data processed by processor 505 is transmitted on a wireless medium via antenna 503, and further, antenna 503 also receives data and transmits the data to processor 505.

[0425] The processor 505 is responsible for managing the bus 501 and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management and other control functions. The memory 506 can be used to store data used by the processor 505 when performing operations.

[0426] Optionally, the processor 505 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or a complex programmable logic device (CPLD).

[0427] Optionally, the network device further includes a transceiver 502, and the transceiver 502 is used to:

[0428] A first message sent by a receiving terminal is received, where the first message includes the first information.

[0429] Optionally, the processor 505 is specifically configured to:

[0430] Collecting performance indicator information and determining whether the prediction accuracy meets the performance requirements based on the performance indicator information;

[0431] When it is determined that the prediction accuracy does not meet the preset requirement, a second message is sent to the terminal, where the second message is used to instruct the terminal to adjust the mobility prediction function and / or model.

[0432] Optionally, the processor 505 is further configured to:

[0433] generating a first mobility decision based on the first information, where the first mobility decision is used to determine a target handover cell of the terminal;

[0434] The transceiver is further used to send a third message to the terminal, where the third message is used to indicate the target switching cell.

[0435] Optionally, the processor 505 is specifically configured to:

[0436] Comparing RRM measurement prediction results of the serving cell and the candidate target cell within a first preset time period based on the RRM measurement prediction information in the first information;

[0437] In a case where the RRM measurement prediction result of the candidate target cell within the first preset time period is greater than or equal to the RRM measurement prediction result of the serving cell, or in a case where the RRM measurement prediction result of the candidate target cell within the first preset time period is greater than or equal to a first preset value, a first mobility decision is determined, and the first mobility decision is used to determine the candidate target cell as a target switching cell.

[0438] Optionally, the processor 505 is specifically configured to:

[0439] Based on the failure event prediction information in the first information, calculating the time until the failure event is expected to occur;

[0440] In a case where the duration is greater than the cell switching preparation duration, a first mobility decision is generated.

[0441] Optionally, the processor 505 is specifically configured to:

[0442] Based on the measurement event prediction information in the first information, determining whether a failure event will occur in the terminal;

[0443] In case that it is determined that a failure event will occur to the terminal, a first mobility decision is generated.

[0444] Optionally, the processor 505 is specifically configured to:

[0445] Performing statistics on the performance indicators within the second preset time period to obtain a first performance indicator value, wherein the performance indicator information includes the first performance indicator value;

[0446] When the first performance indicator value is less than a second preset value and the first mobility decision is generated based on a predicted value, it is determined that the prediction accuracy does not meet the performance requirement.

[0447] Optionally, the processor 505 is specifically configured to:

[0448] generating a second mobility decision based on the predicted value in the RRM measurement prediction information;

[0449] generating a third mobility decision based on the measured value in the RRM measurement prediction information;

[0450] Counting a second performance indicator value corresponding to the second mobility decision and a third performance indicator value corresponding to the third mobility decision, wherein the performance indicator information includes the second performance indicator value and the third performance indicator value;

[0451] When the difference between the second performance indicator value and the third performance indicator value is greater than a third preset value, it is determined that the prediction accuracy does not meet the performance requirement.

[0452] Optionally, the second message includes at least one of the following:

[0453] third indication information, where the third indication information is used to indicate a type of prediction information;

[0454] fourth indication information, where the fourth indication information is used to instruct the terminal to improve the mobility prediction accuracy;

[0455] fifth indication information, the fifth indication information being used to indicate a type of prediction information for improving prediction accuracy by the terminal;

[0456] Sixth indication information, where the sixth indication information is used to instruct the terminal to perform at least one of stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0457] seventh indication information, the seventh indication information being used to indicate a prediction information type of at least one of the following: stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0458] The eighth indication information is used to indicate prediction configuration information. Optionally, the RRM measurement prediction information includes at least one of the following:

[0459] Wireless information quality indicator information, the wireless information quality indicator information including measured values ​​and predicted values;

[0460] First indication information, where the first indication information is used to indicate that the wireless information quality indicator information is a measured value or a predicted value;

[0461] second indication information, where the second indication information is used to indicate a time domain, frequency domain or spatial domain pattern corresponding to measurement reduction;

[0462] prediction related information of the terminal;

[0463] prediction confidence, prediction accuracy, or prediction precision;

[0464] The time or period of time when the predicted value in the wireless information quality indicator information is generated;

[0465] The predicted time or time period corresponding to the predicted value in the wireless information quality indicator information.

[0466] Optionally, the failure event prediction information includes at least one of the following:

[0467] The expected time or time period of occurrence of the failure event; the event type of the failure event; the location information of the failure event; the RRM measurement information corresponding to the failure event; the time or time period of generation of the failure event prediction information.

[0468] Optionally, the measurement event prediction information includes at least one of the following:

[0469] The estimated time or time period of the measurement event; the type of the measurement event; and the time or time period of generating the prediction information of the measurement event.

[0470] It should be noted that the electronic device provided in the embodiment of the present application is a device capable of executing the above monitoring method, and all implementations in the above monitoring method embodiment are applicable to the electronic device and can achieve the same or similar beneficial effects. To avoid repeated description, this embodiment will not be repeated.

[0471] See also Figure 6 , Figure 6 This is a second structural diagram of a monitoring device provided in an embodiment of the present application, such as Figure 6 As shown, the monitoring device 600 includes:

[0472] A sending module 601 is configured to send a first message to a network device, wherein the first message includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information;

[0473] The first message is used by the network device to perform function and / or model performance monitoring.

[0474] Optionally, the device further comprises:

[0475] The second receiving module is used to receive a second message sent by the network device, where the second message is used to instruct the terminal to adjust the mobility prediction function and / or model.

[0476] Optionally, the second message includes at least one of the following:

[0477] third indication information, where the third indication information is used to indicate a type of prediction information;

[0478] fourth indication information, where the fourth indication information is used to instruct the terminal to improve prediction accuracy;

[0479] fifth indication information, the fifth indication information being used to indicate a type of prediction information for improving prediction accuracy by the terminal;

[0480] Sixth indication information, where the sixth indication information is used to instruct the terminal to perform at least one of stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0481] seventh indication information, the seventh indication information being used to indicate a prediction information type of at least one of the following: stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0482] Eighth indication information, the eighth indication information is used to indicate prediction configuration information. Optionally, the device further includes:

[0483] An adjustment module, configured to adjust configuration information and / or model input information of mobility prediction based on the second message;

[0484] Alternatively, a first determining module is used to determine the type of prediction information for improving prediction accuracy based on the second message;

[0485] Alternatively, the second determination module is used to determine the prediction information type for stopping prediction, suspending prediction or deactivating prediction based on the second message.

[0486] Optionally, the method further comprises:

[0487] The third receiving module is used to receive a third message sent by the network device, where the third message is used to indicate a target switching cell of the terminal.

[0488] Optionally, the RRM measurement prediction information includes at least one of the following:

[0489] Wireless information quality indicator information, the wireless information quality indicator information including measured values ​​and predicted values;

[0490] First indication information, where the first indication information is used to indicate that the wireless information quality indicator information is a measured value or a predicted value;

[0491] second indication information, where the second indication information is used to indicate a time domain, frequency domain or spatial domain pattern corresponding to measurement reduction;

[0492] prediction related information of the terminal;

[0493] prediction confidence, prediction accuracy, or prediction precision;

[0494] The time or period of time when the predicted value in the wireless information quality indicator information is generated;

[0495] The predicted time or time period corresponding to the predicted value in the wireless information quality indicator information.

[0496] Optionally, the failure event prediction information includes at least one of the following:

[0497] The expected time or time period of occurrence of the failure event; the event type of the failure event; the location information of the failure event; the RRM measurement information corresponding to the failure event; the time or time period of generation of the failure event prediction information.

[0498] Optionally, the measurement event prediction information includes at least one of the following:

[0499] The estimated time or time period of the measurement event; the type of the measurement event; and the time or time period of generating the prediction information of the measurement event.

[0500] It should be noted that the monitoring device provided in the embodiment of the present application is a device capable of executing the above monitoring method, and all implementations in the above monitoring method embodiment are applicable to the device and can achieve the same or similar beneficial effects. To avoid repeated description, this embodiment will not be repeated.

[0501] For details, see Figure 7 As shown, an embodiment of the present application also provides a terminal, including a bus 701, a transceiver 702, an antenna 703, a bus interface 704, a processor 705 and a memory 706.

[0502] The transceiver 702 is used for:

[0503] Sending a first message to a network device, wherein the first message includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information;

[0504] The first message is used by the network device to perform function and / or model performance monitoring.

[0505] exist Figure 7 In the embodiment, the bus architecture (represented by bus 701) may include any number of interconnected buses and bridges, and bus 701 links various circuits including one or more processors represented by processor 705 and memory represented by memory 706. Bus 701 may also link various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. Bus interface 704 provides an interface between bus 701 and transceiver 702. Transceiver 702 may be one element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on a transmission medium. Data processed by processor 705 is transmitted on a wireless medium via antenna 703, and further, antenna 703 also receives data and transmits the data to processor 705.

[0506] The processor 705 is responsible for managing the bus 701 and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management and other control functions. The memory 706 can be used to store data used by the processor 705 when performing operations.

[0507] Optionally, the processor 705 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or a complex programmable logic device (CPLD).

[0508] Optionally, the transceiver 702 is further configured to:

[0509] A second message sent by the network device is received, where the second message is used to instruct the terminal to adjust a mobility prediction function and / or model.

[0510] Optionally, the second message includes at least one of the following:

[0511] third indication information, where the third indication information is used to indicate a type of prediction information;

[0512] fourth indication information, where the fourth indication information is used to instruct the terminal to improve prediction accuracy;

[0513] fifth indication information, the fifth indication information being used to indicate a type of prediction information for improving prediction accuracy by the terminal;

[0514] Sixth indication information, where the sixth indication information is used to instruct the terminal to perform at least one of stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0515] seventh indication information, the seventh indication information being used to indicate a prediction information type of at least one of the following: stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction;

[0516] The eighth indication information is used to indicate the prediction configuration information. Optionally, the processor 705 is further used to:

[0517] adjusting configuration information and / or model input information of mobility prediction based on the second message;

[0518] Alternatively, determining a prediction information type for improving prediction accuracy based on the second message;

[0519] Alternatively, the prediction information type for stopping prediction, suspending prediction, or deactivating prediction is determined based on the second message.

[0520] Optionally, the transceiver 702 is further configured to:

[0521] A third message sent by the network device is received, where the third message is used to indicate a target switching cell of the terminal.

[0522] Optionally, the RRM measurement prediction information includes at least one of the following:

[0523] Wireless information quality indicator information, the wireless information quality indicator information including measured values ​​and predicted values;

[0524] First indication information, where the first indication information is used to indicate that the wireless information quality indicator information is a measured value or a predicted value;

[0525] second indication information, where the second indication information is used to indicate a time domain, frequency domain or spatial domain pattern corresponding to measurement reduction;

[0526] prediction related information of the terminal;

[0527] prediction confidence, prediction accuracy, or prediction precision;

[0528] The time or period of time when the predicted value in the wireless information quality indicator information is generated;

[0529] The predicted time or time period corresponding to the predicted value in the wireless information quality indicator information.

[0530] Optionally, the failure event prediction information includes at least one of the following:

[0531] The expected time or time period of occurrence of the failure event; the event type of the failure event; the location information of the failure event; the RRM measurement information corresponding to the failure event; the time or time period of generation of the failure event prediction information.

[0532] Optionally, the measurement event prediction information includes at least one of the following:

[0533] The estimated time or time period of the measurement event; the type of the measurement event; and the time or time period of generating the prediction information of the measurement event.

[0534] It should be noted that the electronic device provided in the embodiment of the present application is a device capable of executing the above monitoring method, and all implementations in the above monitoring method embodiment are applicable to the electronic device and can achieve the same or similar beneficial effects. To avoid repeated description, this embodiment will not be repeated.

[0535] An embodiment of the present application also provides an electronic device, including: a processor, a memory, and a program stored in the memory and executable on the processor. When the program is executed by the processor, the various processes of the above-mentioned monitoring method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0536] The embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, each process of the above monitoring method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it is not repeated here. The computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0537] The embodiment of the present application also provides a computer program product, including computer instructions. When the computer instructions are executed by a processor, the various processes of the above-mentioned monitoring method embodiment are implemented and the same technical effect can be achieved. To avoid repetition, they are not repeated here.

[0538] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including 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 existence of other identical elements in the process, method, article or device including the element.

[0539] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0540] 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 the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A monitoring method, characterized in that: Applied to a network device, the method comprises: Functional and / or model performance monitoring is performed on first information, where the first information includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information.

2. The method according to claim 1, characterized in that The method further comprises: A first message sent by a receiving terminal is received, where the first message includes the first information.

3. The method according to claim 1, characterized in that The function and / or model performance monitoring of the first information includes: Collecting performance indicator information and determining whether the prediction accuracy meets the performance requirements based on the performance indicator information; When it is determined that the prediction accuracy does not meet the preset requirement, a second message is sent to the terminal, where the second message is used to instruct the terminal to adjust the mobility prediction function and / or model.

4. The method according to claim 1, characterized in that: The method further comprises: generating a first mobility decision based on the first information, where the first mobility decision is used to determine a target handover cell of the terminal; A third message is sent to the terminal, where the third message is used to indicate the target switching cell.

5. The method according to claim 4, characterized in that The generating a first mobility decision based on the first information includes: Comparing RRM measurement prediction results of the serving cell and the candidate target cell within a first preset time period based on the RRM measurement prediction information in the first information; In a case where the RRM measurement prediction result of the candidate target cell within the first preset time period is greater than or equal to the RRM measurement prediction result of the serving cell, or in a case where the RRM measurement prediction result of the candidate target cell within the first preset time period is greater than or equal to a first preset value, a first mobility decision is determined, and the first mobility decision is used to determine the candidate target cell as a target switching cell.

6. The method according to claim 4, characterized in that The generating a first mobility decision based on the first information includes: Based on the failure event prediction information in the first information, calculating the time until the failure event is expected to occur; In a case where the duration is greater than the cell switching preparation duration, a first mobility decision is generated.

7. The method according to claim 4, characterized in that The generating a first mobility decision based on the first information includes: Based on the measurement event prediction information in the first information, determining whether a failure event will occur in the terminal; In case that it is determined that a failure event will occur to the terminal, a first mobility decision is generated.

8. The method according to claim 3, characterized in that The statistical performance indicator information, and determining whether the prediction accuracy meets the performance requirements based on the performance indicator information, includes: Performing statistics on the performance indicators within the second preset time period to obtain a first performance indicator value, wherein the performance indicator information includes the first performance indicator value; When the first performance indicator value is less than a second preset value and the first mobility decision is generated based on the predicted value, it is determined that the prediction accuracy does not meet the performance requirement.

9. The method according to claim 3, characterized in that: The statistical performance indicator information, and determining whether the prediction accuracy meets the performance requirements based on the performance indicator information, includes: generating a second mobility decision based on the predicted value in the RRM measurement prediction information; generating a third mobility decision based on the measured value in the RRM measurement prediction information; Counting a second performance indicator value corresponding to the second mobility decision and a third performance indicator value corresponding to the third mobility decision, wherein the performance indicator information includes the second performance indicator value and the third performance indicator value; When the difference between the second performance indicator value and the third performance indicator value is greater than a third preset value, it is determined that the prediction accuracy does not meet the performance requirement.

10. The method according to claim 3, characterized in that The second message includes at least one of the following: third indication information, where the third indication information is used to indicate a type of prediction information; fourth indication information, where the fourth indication information is used to instruct the terminal to improve the mobility prediction accuracy; fifth indication information, the fifth indication information being used to indicate a type of prediction information for improving prediction accuracy by the terminal; Sixth indication information, where the sixth indication information is used to instruct the terminal to perform at least one of stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction; seventh indication information, the seventh indication information being used to indicate a prediction information type of at least one of the following: stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction; Eighth indication information, wherein the eighth indication information is used to indicate prediction configuration information.

11. The method according to any one of claims 1 to 10, characterized in that The RRM measurement prediction information includes at least one of the following: Wireless information quality indicator information, the wireless information quality indicator information including measured values ​​and predicted values; first indication information, where the first indication information is used to indicate that the wireless information quality indicator information is a measured value or a predicted value; second indication information, where the second indication information is used to indicate a time domain, frequency domain or spatial domain pattern corresponding to measurement reduction; Prediction-related information of the terminal; prediction confidence, prediction accuracy, or prediction precision; The time or period of time when the predicted value in the wireless information quality indicator information is generated; The predicted time or time period corresponding to the predicted value in the wireless information quality indicator information.

12. The method according to any one of claims 1 to 11, characterized in that The failure event prediction information includes at least one of the following: The expected time or time period of occurrence of the failure event; the event type of the failure event; the location information of the failure event; the RRM measurement information corresponding to the failure event; the time or time period of generation of the failure event prediction information.

13. The method according to any one of claims 1 to 12, characterized in that The measurement event prediction information includes at least one of the following: The estimated time or time period of the measurement event; the type of the measurement event; and the time or time period of generating the prediction information of the measurement event.

14. A monitoring method, characterized in that: Applied to a terminal, the method comprises: Sending a first message to a network device, wherein the first message includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information; The first message is used by the network device to perform function and / or model performance monitoring.

15. The method according to claim 14, characterized in that The method further comprises: A second message sent by the network device is received, where the second message is used to instruct the terminal to adjust a mobility prediction function and / or model.

16. The method according to claim 15, characterized in that The second message includes at least one of the following: third indication information, where the third indication information is used to indicate a type of prediction information; fourth indication information, where the fourth indication information is used to instruct the terminal to improve prediction accuracy; fifth indication information, the fifth indication information being used to indicate a type of prediction information for improving prediction accuracy by the terminal; Sixth indication information, where the sixth indication information is used to instruct the terminal to perform at least one of stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction; seventh indication information, the seventh indication information being used to indicate a prediction information type of at least one of the following: stopping mobility prediction, suspending mobility prediction, and deactivating mobility prediction; Eighth indication information, wherein the eighth indication information is used to indicate prediction configuration information.

17. The method according to claim 15, characterized in that The method further comprises: adjusting configuration information and / or model input information of mobility prediction based on the second message; Alternatively, determining a prediction information type for improving prediction accuracy based on the second message; Alternatively, the prediction information type for stopping prediction, suspending prediction, or deactivating prediction is determined based on the second message.

18. The method according to claim 14, characterized in that The method further comprises: A third message sent by the network device is received, where the third message is used to indicate a target switching cell of the terminal.

19. The method according to any one of claims 14 to 18, characterized in that: The RRM measurement prediction information includes at least one of the following: Wireless information quality indicator information, the wireless information quality indicator information including measured values ​​and predicted values; first indication information, where the first indication information is used to indicate that the wireless information quality indicator information is a measured value or a predicted value; second indication information, where the second indication information is used to indicate a time domain, frequency domain or spatial domain pattern corresponding to measurement reduction; prediction related information of the terminal; prediction confidence, prediction accuracy, or prediction precision; The time or period of time when the predicted value in the wireless information quality indicator information is generated; The predicted time or time period corresponding to the predicted value in the wireless information quality indicator information.

20. The method according to any one of claims 14 to 19, characterized in that The failure event prediction information includes at least one of the following: The expected time or time period of occurrence of the failure event; the event type of the failure event; the location information of the failure event; the RRM measurement information corresponding to the failure event; the time or time period of generation of the failure event prediction information.

21. The method according to any one of claims 14 to 20, characterized in that The measurement event prediction information includes at least one of the following: The estimated time or time period of the measurement event; the type of the measurement event; and the time or time period of generating the prediction information of the measurement event.

22. A monitoring device, characterized in that: include: The monitoring module is used to perform function and / or model performance monitoring on the first information, wherein the first information includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information.

23. A network device, characterized in that: comprising a processor configured to: Functional and / or model performance monitoring is performed on first information, where the first information includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information.

24. A monitoring device, characterized in that: include: A sending module, configured to send a first message to a network device, wherein the first message includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information; The first message is used by the network device to perform function and / or model performance monitoring.

25. A terminal, characterized in that: The invention comprises a transceiver, wherein the transceiver is used for: Sending a first message to a network device, wherein the first message includes at least one of radio resource management RRM measurement prediction information, failure event prediction information and measurement event prediction information; The first message is used by the network device to perform function and / or model performance monitoring.

26. An electronic device, characterized in that: include: A processor, a memory, and a program stored in the memory and executable on the processor, wherein the program, when executed by the processor, implements the steps of the monitoring method as described in any one of claims 1 to 13; or, the program, when executed by the processor, implements the steps of the monitoring method as described in any one of claims 14 to 21.

27. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements the steps of the monitoring method as described in any one of claims 1 to 13; or, when the computer program is executed by a processor, the computer program implements the steps of the monitoring method as described in any one of claims 14 to 21.

28. A computer program product, characterized in that It comprises computer instructions, which, when executed by a processor, implement the steps of the monitoring method as described in any one of claims 1 to 13; or, when executed by a processor, the computer instructions implement the steps of the monitoring method as described in any one of claims 14 to 21.

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