Method and device used in wireless link failure prediction of wireless communication

Abstract

The invention discloses a method and a device used in wireless link failure prediction of wireless communication. The communication terminal triggers a first process, and as a response that any condition in the first condition set is met, the first process is stopped; wherein the first condition set comprises at least a first condition; wherein the first process depends on wireless link failure prediction; the first condition depends on at least one of measurement or prediction; wherein the first process depends on the wireless link failure prediction, and the first process comprises the following steps: the first process is to execute the wireless link failure prediction, or the first process is predicted to be triggered by the wireless link failure.

Description

Technical Field

[0001] The present application relates to a transmission method and device in a wireless communication system, and in particular to a method and device for predicting wireless link failure. Background Art

[0002] As wireless communications gradually evolve towards intelligence in the future, artificial intelligence (AI) and machine learning (ML) are introduced and studied by 3GPP (the 3rd Generation Partnership Project) for integration, which can be used to optimize mobility performance. In NR R (release) 18, the research on AI / ML technology was established to explore its impact on system performance and system design. Compared with traditional processing methods, AI / ML has characteristics such as training-based and deployment-required. According to 3GPP standard TS38.300, AI / ML models and algorithms are beyond the scope of 3GPP. At the 103rd meeting of the RAN Plenary Session, 3GPP specifically proposed the need to study how to use AI / ML to assist mobility enhancement in the RRC_CONNECTED state to further reduce communication delays and enhance the communication quality of wireless links, and avoid sudden wireless link failures as much as possible. Summary of the invention

[0003] In the traditional scheme, the detection of wireless link failure is based on RRM measurement. When the measurement result meets certain conditions, it is considered that the wireless link failure is detected and subsequent behavior is triggered. On the one hand, after the AI ​​model is introduced into 3GPP, the UE can use the AI ​​model to predict wireless link failure in advance, which can avoid certain wireless link failures and improve communication quality. However, frequent wireless link failure predictions will inevitably lead to high energy consumption of the UE, which is not conducive to power saving. On the other hand, if the prediction of wireless link failure triggers a process, the execution of this process will have an impact on the legal (legacy) behavior of the UE. Therefore, how to reduce unnecessary wireless link failure predictions or reduce the impact on the legal behavior of the UE is a problem that needs to be studied.

[0004] In response to the above problems, the present application provides a solution for when the prediction of wireless link failure is cancelled. In the description of the above problems, the NR system is used as an example. The present application is also applicable to scenarios such as LTE (Long-Term Evolution) or LTE-A (Long-Term Evolution Advanced) systems or future 6G systems, achieving technical effects similar to those of the NR system; further, although the present application provides a specific implementation method for the mobility of the RRC_CONNECTED state involved in the switching, the present application can also be used in scenarios such as the RRC_IDLE state or the RRC_INACTIVE state to achieve technical effects similar to the mobility of the RRC connection state. Furthermore, adopting a unified design scheme for different scenarios can also help reduce hardware complexity and cost. Furthermore, although the original intention of the present application is for the Uu air interface, the present application can also be used for the PC5 port to achieve technical effects similar to those of the Uu air interface. Furthermore, although the original intention of this application is for the terminal and base station scenario, this application is also applicable to the V2X (Vehicle-to-Everything) scenario, the communication scenario between the terminal and the relay, and the relay and the base station, to achieve similar technical effects in the terminal and base station scenario. Further, although the original intention of this application is for the terminal and base station scenario, this application is also applicable to the IAB (Integrated Access and Backhaul) communication scenario, to achieve similar technical effects in the terminal and base station scenario. Further, although the original intention of this application is for the terrestrial network (Terrestrial Network, TN) scenario, this application is also applicable to the non-terrestrial network (Non-Terrestrial Network, NTN) communication scenario, to achieve similar technical effects in the TN scenario. Further, although a large number of embodiments of this application are developed for AI / ML, this application is also applicable to other scenarios, such as traditional wireless communications. Although the description of some AI / ML models and algorithms is involved in the specification of this application, those skilled in the art know that these descriptions are not necessary or irreplaceable for solutions related to wireless cellular communications. In addition, the use of a unified solution for different scenarios (including but not limited to AI / ML-based solutions and traditional CSI reporting solutions) can also help reduce hardware complexity and costs. In addition, the use of a unified solution for different scenarios can also help reduce hardware complexity and costs.

[0005] As an example, the interpretation of the terms in the present application refers to the definition of the TS38 series of specification protocols of 3GPP.

[0006] As an example, the interpretation of the terms in the present application refers to the definition of the TS37 series of specification protocols of 3GPP.

[0007] As an example, the interpretation of the terms in the present application refers to the definitions of the TS28 series of specification protocols of 3GPP.

[0008] It should be noted that, in the absence of conflict, the embodiments and features in any node of the present application can be applied to any other node. In the absence of conflict, the embodiments and features in the embodiments of the present application can be arbitrarily combined with each other.

[0009] The present application discloses a method used in a terminal, characterized in that:

[0010] include:

[0011] triggering a first process; terminating the first process in response to any condition in a first set of conditions being satisfied; wherein the first set of conditions includes at least the first condition;

[0012] The first process depends on the prediction of radio link failure; the first condition depends on at least one of measurement or prediction;

[0013] The first process being dependent on radio link failure prediction includes: the first process is executing radio link failure prediction, or the first process is predicted to be triggered by radio link failure.

[0014] As an embodiment, the problem to be solved by the present application includes: when to terminate the first process.

[0015] As an embodiment, the problems to be solved by the present application include: how to reduce unnecessary wireless link failure predictions; wherein, the first process is to perform wireless link failure predictions; the above method solves the above problem by terminating the first process in response to any condition in the first condition set being met.

[0016] As an embodiment, the problems to be solved by the present application include: how to reduce the impact on the legitimate behavior of the UE; wherein the first process is predicted to be triggered by a wireless link failure; the above method solves the above problem by terminating the first process in response to any condition in the first condition set being met.

[0017] As an embodiment, the characteristics of the above method include: terminating the first process in response to any condition in the first set of conditions being met.

[0018] As an embodiment, the problem to be solved by the present application includes: how to define the first process.

[0019] As an embodiment, the characteristics of the above method include: the first process depends on the prediction of wireless link failure; the first process depends on the prediction of wireless link failure including: the first process is to perform wireless link failure prediction, or the first process is predicted to be triggered by wireless link failure.

[0020] As an embodiment, the problem to be solved by the present application includes: how to define the first condition set.

[0021] As an embodiment, the characteristics of the above method include: the first condition set includes at least a first condition; the first condition depends on at least one of measurement or prediction;

[0022] As an embodiment, the benefits of the present application include: being facilitating protocol implementation.

[0023] As an embodiment, the benefits of the present application include: facilitating the coexistence of traditional wireless link failure detection and wireless link failure prediction.

[0024] As an embodiment, the benefits of the present application include: being helpful in saving UE power.

[0025] As an embodiment, the benefits of the present application include: helping to reduce unnecessary wireless link failure predictions.

[0026] As an embodiment, the benefits of the present application include: helping to reduce the impact on the legitimate behavior of the UE.

[0027] According to one aspect of the present application, it is characterized in that

[0028] The first condition includes that a predicted radio link failure is eliminated; wherein the first process is triggered by a predicted radio link failure.

[0029] As an embodiment, the problem to be solved by the present application includes: how to define the first condition.

[0030] As an embodiment, the characteristics of the above method include: the first condition includes that the predicted radio link failure is eliminated; wherein the first process is predicted to be triggered by the radio link failure.

[0031] As an embodiment, the benefits of the present application include: being helpful in reducing subsequent actions performed by the UE.

[0032] As an embodiment, the benefits of the present application include: being conducive to improving UE autonomy.

[0033] According to one aspect of the present application, it is characterized in that

[0034] The method comprises:

[0035] In response to any one of the conditions in the first set of conditions being satisfied, stopping a first timer;

[0036] The first timer is for the first process; the first timer is configurable or the first timer is a default or the first timer is determined by the terminal itself.

[0037] As an embodiment, the problem to be solved by the present application includes: terminating the behavior that needs to be executed by the first process.

[0038] As an embodiment, the characteristics of the above method include: stopping the first timer in response to any condition in the first condition set being met.

[0039] As an embodiment, the problem to be solved by the present application includes: how to define the first timer.

[0040] As an embodiment, the characteristics of the above method include: the first timer is for the first process; the first timer is configurable or the first timer is a default or the first timer is determined by the terminal itself.

[0041] As an embodiment, the benefits of the present application include: facilitating the reuse of existing protocols.

[0042] As an embodiment, the benefits of the present application include: being conducive to limiting the effectiveness of the first process.

[0043] According to one aspect of the present application, it is characterized in that

[0044] The method comprises:

[0045] In response to the first indicator satisfying the first threshold, triggering the first process;

[0046] The first indicator depends on prediction; the first threshold is configurable or the first threshold is a default or the first threshold is determined by the terminal itself.

[0047] As an embodiment, the problem to be solved by the present application includes: when to trigger the first process.

[0048] As an embodiment, the characteristics of the above method include: triggering the first process in response to the first indicator satisfying the first threshold;

[0049] As an embodiment, the problem to be solved by the present application includes: how to define the first indicator and the first threshold.

[0050] As an embodiment, the characteristics of the above method include: the first indicator relies on prediction; the first threshold is configurable or the first threshold is a default or the first threshold is determined by the terminal itself.

[0051] As an embodiment, the benefits of the present application include: being helpful in improving the effectiveness of the first process.

[0052] According to one aspect of the present application, it is characterized in that

[0053] The first process includes sending a first message; the first message includes at least one of a measurement result or a prediction result; wherein the first process is triggered by predicting a radio link failure.

[0054] As an embodiment, the problem to be solved by the present application includes: a specific definition of the first process.

[0055] As an embodiment, the characteristics of the above method include: the first process includes sending a first message; the first message includes at least one of a measurement result or a prediction result; wherein the first process is predicted to be triggered by a wireless link failure.

[0056] As an embodiment, the benefits of the present application include: facilitating the network side to indicate UE behavior.

[0057] As an embodiment, the benefits of the present application include: facilitating data collection.

[0058] According to one aspect of the present application, it is characterized in that

[0059] The first condition set includes a second condition, and the second condition includes triggering a cell handover.

[0060] As an embodiment, the problem to be solved by the present application includes: which conditions are included in the first condition set.

[0061] As an embodiment, the characteristics of the above method include: the first condition set includes a second condition, and the second condition includes triggering a cell handover.

[0062] As an embodiment, the benefits of the present application include: helping to reduce signaling interactions.

[0063] As an embodiment, the benefits of the present application include: helping to save costs.

[0064] According to one aspect of the present application, it is characterized in that

[0065] The first condition set includes a third condition, and the third condition includes that the intelligent model is updated; wherein the wireless link failure prediction depends on the intelligent model.

[0066] As an embodiment, the problem to be solved by the present application includes: which conditions are included in the first condition set.

[0067] As an embodiment, the characteristics of the above method include: the first condition set includes a third condition, and the third condition includes that the intelligent model is updated; wherein the wireless link failure prediction depends on the intelligent model.

[0068] As an embodiment, the benefits of the present application include: being helpful in improving the accuracy of prediction.

[0069] As an embodiment, the benefits of the present application include: facilitating improving the flexibility of terminating the first process.

[0070] The present application discloses a method used in a base station, characterized in that:

[0071] include:

[0072] Sending a first configuration message, wherein the first configuration message includes an intelligent model; wherein the wireless link failure prediction depends on the intelligent model;

[0073] Among them, the recipient of the first configuration message triggers a first process; as a response to any condition in a first condition set being met, the first process is terminated; the first condition set includes at least the first condition; the first process depends on wireless link failure prediction; the first condition depends on at least one of measurement or prediction; the first process depends on wireless link failure prediction including: the first process is to perform wireless link failure prediction, or the first process is predicted to be triggered by wireless link failure.

[0074] According to one aspect of the present application, it is characterized in that

[0075] The first condition includes that a predicted radio link failure is eliminated; wherein the first process is triggered by a predicted radio link failure.

[0076] According to one aspect of the present application, it is characterized in that

[0077] In response to any one of the conditions in the first set of conditions being met, the receiver of the first configuration message stops a first timer;

[0078] The first timer is for the first process; the first timer is configurable or the first timer is a default or the first timer is determined by the terminal itself.

[0079] According to one aspect of the present application, it is characterized in that

[0080] In response to the first indicator satisfying the first threshold, the recipient of the first configuration message triggers the first process;

[0081] The first indicator depends on prediction; the first threshold is configurable or the first threshold is a default or the first threshold is determined by the terminal itself.

[0082] According to one aspect of the present application, it is characterized in that

[0083] The method comprises:

[0084] receiving a first message, wherein the first message includes at least one of a measurement result or a prediction result;

[0085] The first process includes the receiver of the first configuration message sending the first message, and the first process is predicted to be triggered by a radio link failure.

[0086] According to one aspect of the present application, it is characterized in that

[0087] The first condition set includes a second condition, and the second condition includes triggering a cell handover.

[0088] According to one aspect of the present application, it is characterized in that

[0089] The first condition set includes a third condition, and the third condition includes that the intelligent model is updated.

[0090] The present application discloses a terminal, characterized in that:

[0091] The terminal includes: one or more processors and a memory;

[0092] The memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the terminal to execute the method according to any one of claims 1 to 7. The present application discloses a base station, characterized in that:

[0093] The base station includes: one or more processors and a memory;

[0094] The memory is coupled to the one or more processors, and the memory is used to store computer program codes, where the computer program codes include computer instructions, and the one or more processors call the computer instructions to enable the base station to perform the method according to any one of claims 9 to 15.

[0095] As an embodiment, compared with the traditional solution, this application has the following advantages:

[0096] -. It is conducive to the collection of big data;

[0097] -. It is conducive to improving the reliability and flexibility of wireless link connection;

[0098] -.It is helpful to improve the accuracy of AI prediction;

[0099] -. It is beneficial to user-side power saving;

[0100] -. It is helpful to save signaling overhead;

[0101] -.It is conducive to AI model training. BRIEF DESCRIPTION OF THE DRAWINGS

[0102] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments with reference to the following drawings:

[0103] Figure 1 A flow chart showing communication of a terminal according to an embodiment of the present application is shown;

[0104] Figure 2 A schematic diagram of a network architecture according to an embodiment of the present application is shown;

[0105] Figure 3 A schematic diagram showing an embodiment of a wireless protocol architecture of a user plane and a control plane according to an embodiment of the present application;

[0106] Figure 4 A schematic diagram showing a first communication device and a second communication device according to an embodiment of the present application is shown;

[0107] Figure 5 A wireless signal transmission flow chart according to an embodiment of the present application is shown;

[0108] Figure 6 A schematic diagram showing that the first condition according to an embodiment of the present application includes that the predicted radio link failure is eliminated;

[0109] Figure 7 A schematic diagram showing stopping a first timer according to an embodiment of the present application is shown;

[0110] Figure 8 A schematic diagram showing triggering the first process according to an embodiment of the present application is shown;

[0111] Fig. 9 A schematic diagram showing that the first message includes at least one of a measurement result or a prediction result according to an embodiment of the present application;

[0112] Fig.10A schematic diagram showing that the first condition set includes a second condition according to an embodiment of the present application;

[0113] Fig.11 A schematic diagram showing that the first condition set includes a third condition according to an embodiment of the present application;

[0114] Fig.12 A schematic diagram of RAN (Radio Access Network) domain (Domain) AI / ML function deployment according to an embodiment of the present application is shown;

[0115] Fig.13 A schematic diagram showing the deployment of AI / ML functions of a UE according to an embodiment of the present application is shown;

[0116] Fig.14 A schematic diagram of a processing system based on artificial intelligence or machine learning according to an embodiment of the present application is shown;

[0117] Fig.15 A schematic diagram of a processing system based on artificial intelligence or machine learning according to another embodiment of the present application is shown;

[0118] Fig.16 A structural block diagram of a processing device used in a terminal according to an embodiment of the present application is shown;

[0119] Fig.17 A structural block diagram of a processing device used in a base station according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0120] The technical solution of the present application will be further described in detail below in conjunction with the accompanying drawings. It should be noted that, unless there is a conflict, the embodiments in the present application and the features in the embodiments can be combined with each other arbitrarily.

[0121] Example 1

[0122] Embodiment 1 illustrates a flow chart of communication of a terminal according to an embodiment of the present application, as shown in the attached Figure 1 Attached Figure 1 In the figure, each box represents a step. It should be emphasized that the order of the boxes in the figure does not represent the temporal relationship between the steps represented.

[0123] In Example 1, the terminal in the present application triggers a first process in step 101, and the first process depends on the prediction of wireless link failure; in step 102, as a response to any condition in a first condition set being met, the first process is terminated; wherein the first condition set includes at least a first condition, and the first condition depends on at least one of measurement or prediction; the first process depends on the prediction of wireless link failure, including: the first process is to perform wireless link failure prediction, or the first process is predicted to be triggered by wireless link failure.

[0124] As an embodiment, triggering the first process refers to: starting the first process.

[0125] As an embodiment, triggering the first process refers to: executing the first process.

[0126] As an embodiment, triggering the first process refers to: activating the first process.

[0127] As an embodiment, triggering the first process refers to: restarting the first process.

[0128] As an embodiment, when any condition in the first condition set is met, the first process is terminated.

[0129] As an embodiment, when at least any one of the first condition set is satisfied, the first process is terminated.

[0130] As an embodiment, the first process is terminated as long as any condition in the first condition set is met.

[0131] As an embodiment, once any condition in the first condition set is met, the first process is terminated.

[0132] As an embodiment, the suspension is a stop.

[0133] As an embodiment, the suspension is a suspend.

[0134] As an embodiment, the suspension is a cancel.

[0135] As an embodiment, the suspension is a release.

[0136] As an embodiment, the first condition set is the first condition.

[0137] As an embodiment, the first condition set includes only the first condition.

[0138] As an embodiment, the first condition set is a plurality of conditions, and the first condition is one of the plurality of conditions.

[0139] As an embodiment, one of the conditions in the first condition set is RRC connection state transition.

[0140] As an embodiment, the RRC connection state transition refers to: entering the RRC_INACTIVE state.

[0141] As an embodiment, the RRC connection state transition refers to: entering the RRC_IDLE state.

[0142] As an embodiment, the RRC connection state transition refers to: leaving the RRC_CONNECTED state.

[0143] As an embodiment, the RRC connection state transition refers to: re-entering the RRC_CONNECTED state.

[0144] As an embodiment, the RRC connection state transition refers to: entering another RRC connection state from one RRC connection state.

[0145] As an embodiment, one of the conditions in the first set of conditions is receiving a network indication.

[0146] As an embodiment, the one network indication instructs to terminate the first process.

[0147] As an embodiment, the one network indication implicitly indicates to terminate the first process.

[0148] As an embodiment, the first process depends on the prediction of radio link failure, which means that when the prediction of radio link failure occurs, the first process is triggered.

[0149] As an embodiment, the first process depends on the prediction of radio link failure, which means that the first process is triggered when at least the prediction of radio link failure occurs.

[0150] As an embodiment, the first process relies on the prediction of radio link failure, which means that once the prediction of radio link failure occurs, the first process is triggered.

[0151] As an embodiment, the first process relies on radio link failure prediction, which means that the first process includes radio link failure prediction.

[0152] As an embodiment, the first process relying on the radio link failure prediction means that: the first process is the radio link failure prediction.

[0153] As an embodiment, the first process being dependent on the radio link failure prediction means that: the first process belongs to the radio link failure prediction.

[0154] As an embodiment, the first condition-dependent measurement or at least one of the prediction refers to: the first condition-dependent measurement.

[0155] As an embodiment, the first condition being dependent on measurement means that the first condition is obtained based on a measurement result.

[0156] As an embodiment, the first condition being dependent on measurement means that the first condition is a measurement result.

[0157] As an embodiment, the measurement is a measurement of a timer.

[0158] As an embodiment, the measurement is a measurement of a counter.

[0159] As an embodiment, the measurement is a measurement of channel quality.

[0160] As an embodiment, the measurement is an L3 filtered measurement.

[0161] As an embodiment, the measurement is an L1 filtered measurement.

[0162] As an embodiment, the measurement is a measurement at least in the time domain.

[0163] As an embodiment, the measurement is a measurement only in the time domain.

[0164] As an embodiment, the measurement is a measurement at a point in time.

[0165] As an embodiment, the measurement is a measurement within a period of time.

[0166] As an embodiment, the measurement is a measurement of a downlink reference signal.

[0167] As an embodiment, the downlink reference signal is SSB.

[0168] As an embodiment, the downlink reference signal is CSI (Channel State Information)-RS.

[0169] As an embodiment, the downlink reference signal is CSI-RS and SSB.

[0170] As an embodiment, the downlink reference signal is a CRS (Cell-Specific Reference Signal).

[0171] As an embodiment, the downlink reference signal is a PRS (Positioning Reference Signal).

[0172] As an embodiment, the measurement includes: obtaining a measurement result of a downlink reference signal.

[0173] As an embodiment, the measurement result of the downlink reference signal is RSRP (Reference Signal Received Power).

[0174] As an embodiment, the measurement result of the downlink reference signal is RSRQ (Reference Signal Received Quality).

[0175] As an embodiment, the measurement result of the downlink reference signal is RSSI (Received Signal Strength Indicator).

[0176] As an embodiment, the measurement result of the downlink reference signal is SINR (Signal to Interference plus Noise Ratio).

[0177] As an embodiment, the measurement includes: storing a measurement result of a downlink reference signal.

[0178] As an embodiment, the measurement includes: measuring a moving speed of the terminal.

[0179] As an embodiment, the measurement includes: measuring a moving direction of the terminal.

[0180] As an embodiment, the measurement includes: measuring a moving path of the terminal.

[0181] As an embodiment, the measurement includes: measuring the position of the terminal.

[0182] As an embodiment, the first conditionally dependent at least one of measurement or prediction refers to: the first conditionally dependent prediction.

[0183] As an embodiment, the first condition dependence on prediction means that the first condition is based on a prediction result.

[0184] As an embodiment, the first condition dependence prediction means that: the first condition is a prediction result.

[0185] As an embodiment, the prediction is a prediction for a period of time in the future.

[0186] As an embodiment, the prediction is a prediction for a certain time point in the future.

[0187] As an embodiment, the prediction is a prediction while the first process is running.

[0188] As an embodiment, the prediction is a prediction for a downlink reference signal.

[0189] As an embodiment, the prediction is a prediction of a measurement result of a downlink reference signal.

[0190] As an embodiment, the prediction is a prediction for an event.

[0191] As an embodiment, the prediction is a prediction for an event type.

[0192] As an embodiment, the prediction is a prediction of whether an event will occur.

[0193] As an embodiment, the first condition depends on at least one of measurement or prediction, which refers to: the first condition depends on measurement and prediction.

[0194] As an embodiment, the first condition depends on at least one of measurement or prediction: the first condition depends on prediction, otherwise the first condition depends on measurement.

[0195] As an embodiment, the first condition depends on at least one of measurement or prediction: the first condition depends on measurement, otherwise the first condition depends on prediction.

[0196] As an embodiment, the radio link failure prediction refers to: RLF prediction.

[0197] As an embodiment, the wireless link failure prediction refers to: HOF prediction.

[0198] As an embodiment, the radio link failure prediction refers to: HOF prediction and RLF prediction.

[0199] As an embodiment, the first process is the wireless link failure prediction.

[0200] As an embodiment, the performing of the radio link failure prediction is based on an intelligent model. As an embodiment, the performing of the radio link failure prediction includes performing a ML reasoning (also referred to as AI / ML reasoning) process.

[0201] As an embodiment, the performing of the wireless link failure prediction includes performing an ML training process.

[0202] As an embodiment, the performing of the wireless link failure prediction includes performing an ML testing process.

[0203] As an embodiment, the performing of the wireless link failure prediction includes performing an ML deployment process.

[0204] As an embodiment, the first process is triggered by a first signaling.

[0205] As an embodiment, the first signaling includes an intelligent model ID. As an embodiment, the intelligent model ID indexes the ML model (also referred to as AI model) used for the ML reasoning.

[0206] As an embodiment, the intelligent model ID activates the ML model (also called AI model) used for the ML reasoning.

[0207] As an embodiment, the intelligent model ID deploys an ML model (also called an AI model) used for the ML reasoning.

[0208] As an embodiment, the ML model is based on a neural network.

[0209] As an embodiment, the ML model is based on Convolutional Neural Networks (CNN).

[0210] As an embodiment, the ML model is based on a Transformer architecture.

[0211] As an embodiment, the first signaling is a RRC sublayer signaling.

[0212] As an embodiment, the first signaling is signaling of a sublayer below the RRC sublayer.

[0213] As an embodiment, the first signaling is a MAC CE.

[0214] As an embodiment, the first signaling is a PDCCH Order.

[0215] As an embodiment, the first process is triggered by the terminal.

[0216] As an embodiment, the terminal triggers the first process by itself.

[0217] As an embodiment, the execution condition of the first process is met, and the terminal triggers the first process by itself.

[0218] As an embodiment, the signaling includes the first UE capability and the terminal triggers the first process by itself after receiving the first signaling.

[0219] As an embodiment, the signaling includes the first UE capability and the execution condition of the first process is met, and the terminal triggers the first process by itself.

[0220] The above method avoids the influence of UEs that do not have the first UE capability.

[0221] As an embodiment, the first UE capability is based on network configuration.

[0222] As an embodiment, the first UE capability is configured by UECapabilityInformation IE.

[0223] As an embodiment, the first UE capability supports at least AI / ML.

[0224] As an embodiment, the first UE capability supports at least model reasoning.

[0225] As an embodiment, the first UE capability supports at least model training.

[0226] As an embodiment, the first UE capability supports at least data collection.

[0227] As an embodiment, the first UE capability supports at least information storage and reporting.

[0228] As an embodiment, the first UE capability depends on the hardware configuration of the terminal.

[0229] As an embodiment, the executing of the wireless link failure prediction process includes: predicting a measurement result, and the terminal determining the wireless link failure according to the measurement result.

[0230] As an embodiment, the executing of the wireless link failure prediction process includes predicting that a wireless link failure will occur, and the terminal determining that the wireless link has failed.

[0231] As an embodiment, the first process is triggered by predicted radio link failure.

[0232] As a sub-embodiment of the above embodiment, the first process is for predicting wireless link failure.

[0233] As a sub-embodiment of the above embodiment, the first process is to avoid wireless link failure.

[0234] As a sub-embodiment of the above embodiment, the first process includes wireless link failure detection.

[0235] As a sub-embodiment of the above embodiment, the first process includes wireless link recovery.

[0236] As a sub-embodiment of the above embodiment, the first process includes early radio link recovery.

[0237] As a sub-embodiment of the above embodiment, the first process is a radio link update.

[0238] As a sub-embodiment of the above embodiment, the first process is early radio link update.

[0239] As a subsidiary embodiment of the above sub-embodiment, the early radio link update means that a condition for the radio link update is not met.

[0240] As a subsidiary embodiment of the above sub-embodiment, the radio link update includes cell switching.

[0241] As a subsidiary embodiment of the above sub-embodiment, the radio link update includes LTM cell switching.

[0242] As a sub-embodiment of the above embodiment, the first process includes continuing to perform radio link failure prediction.

[0243] As a sub-embodiment of the above embodiment, the first process includes a cell selection process.

[0244] As a sub-embodiment of the above embodiment, the first process includes an RRC connection re-establishment process.

[0245] As a sub-embodiment of the above embodiment, the first process is a cell selection process.

[0246] As a sub-embodiment of the above embodiment, the first process is an RRC connection re-establishment process.

[0247] As a sub-embodiment of the above embodiment, the first process includes a reporting process.

[0248] As a sub-embodiment of the above embodiment, the first process is a reporting process.

[0249] As a subsidiary embodiment of the above sub-embodiment, the reporting process includes an MCG fast recovery process.

[0250] As a subsidiary embodiment of the above sub-embodiment, the reporting process includes a UAI process.

[0251] As a subsidiary embodiment of the above sub-embodiment, the reporting process includes a UEInformationResponse process.

[0252] As a subsidiary embodiment of the above sub-embodiment, the reporting process includes a measurement report process.

[0253] As a subsidiary embodiment of the above sub-embodiment, the reporting process includes a prediction information reporting process.

[0254] As a subsidiary embodiment of the above sub-embodiment, the reporting process is the MCG fast recovery process.

[0255] As a subsidiary embodiment of the above sub-embodiment, the reporting process is a UAI process.

[0256] As a subsidiary embodiment of the above sub-embodiment, the reporting process is a UEInformationResponse process.

[0257] As a subsidiary embodiment of the above sub-embodiment, the reporting process is a measurement report process.

[0258] As a subsidiary embodiment of the above sub-embodiment, the reporting process is a prediction information reporting process.

[0259] As an embodiment, the first process is triggered by prediction of radio link failure, and the first process is radio link failure prediction.

[0260] As an embodiment, the first process is triggered, and the first process is wireless link failure prediction; as a response to at least a first condition in the first condition set being met, the wireless link failure prediction is terminated; the first condition depends on at least one of prediction or measurement.

[0261] As an embodiment, the first process is predicted to be triggered by a radio link failure; in response to at least a first condition in the first condition set being met, the first process is terminated; and the first condition depends on at least one of prediction or measurement.

[0262] Example 2

[0263] Embodiment 2 illustrates a schematic diagram of a network architecture according to an embodiment of the present application, as shown in the attached Figure 2 Attached Figure 2The network architecture 200 of a 5G NR (New Radio) / LTE (Long-Term Evolution) / LTE-A (Long-Term Evolution Advanced) system is illustrated. The 5G NR / LTE / LTE-A network architecture 200 may be referred to as a 5GS (5G System) / EPS (Evolved Packet System) 200 or some other suitable term. The 5GS / EPS 200 includes at least one of a UE (User Equipment) 201, a RAN (Radio Access Network) 202, a 5GC (5G Core Network) / EPC (Evolved Packet Core) 210, a HSS (Home Subscriber Server) / UDM (Unified Data Management) 220, and an Internet service 230. The 5GS / EPS may be interconnected with other access networks, but these entities / interfaces are not shown for simplicity. As shown, 5GS / EPS provides packet switching services, but it will be readily understood by those skilled in the art that the various concepts presented throughout this application can be extended to networks or other cellular networks that provide circuit switching services. RAN includes node 203 and other nodes 204. Node 203 provides user and control plane protocol terminations toward UE 201. Node 203 can be connected to other nodes 204 via an Xn interface (e.g., backhaul) / X2 interface. Node 203 may also be referred to as a base station, a base transceiver station, a radio base station, a radio transceiver, a transceiver function, a basic service set (BSS), an extended service set (ESS), a TRP (transmitting receiving node) or some other suitable terminology. Node 203 provides an access point to 5GC / EPC 210 for UE 201. Examples of UE 201 include cellular phones, smart phones, session initiation protocol (SIP) phones, laptop computers, personal digital assistants (PDAs), satellite radios, non-terrestrial base station communications, satellite mobile communications, global positioning systems, multimedia devices, video devices, digital audio players (e.g., MP3 players), cameras, game consoles, drones, aircraft, narrowband Internet of Things devices, machine type communication devices, land vehicles, cars, wearable devices, or any other similar functional devices. Those skilled in the art may also refer to UE 201 as a mobile station, a subscriber station, a mobile unit, a subscriber unit, a wireless unit, a remote unit, a mobile device, a wireless device, a wireless communication device, a remote device, a mobile subscriber station, an access terminal, a mobile terminal, a wireless terminal, a remote terminal, a handset, a user agent, a mobile client, a client, or some other suitable term.Node 203 is connected to 5GC / EPC210 via an S1 / NG interface. 5GC / EPC210 includes MME (Mobility Management Entity) / AMF (Authentication Management Field) / SMF (Session Management Function) 211, other MME / AMF / SMF214, S-GW (Service Gateway) / UPF (User Plane Function) 212, and P-GW (Packet Data Network Gateway) / UPF213. MME / AMF / SMF211 is a control node that handles signaling between UE201 and 5GC / EPC210. ​​In general, MME / AMF / SMF211 provides bearer and connection management. All user IP (Internet Protocal) packets are transmitted through S-GW / UPF212, which itself is connected to P-GW / UPF213. P-GW provides UE IP address allocation and other functions. P-GW / UPF213 is connected to Internet service 230. Internet service 230 includes operator-corresponding Internet protocol services, which may specifically include Internet, Intranet, IMS (IP Multimedia Subsystem) and packet-switched streaming services.

[0264] As an embodiment, the UE201 corresponds to the terminal in this application.

[0265] As an embodiment, the UE 201 is a user equipment (User Equipment, UE).

[0266] As an embodiment, the UE 201 is a relay device.

[0267] As an embodiment, the node 203 corresponds to the base station in this application.

[0268] As an embodiment, the node 203 is a base station device.

[0269] As an embodiment, the node 203 is a relay device.

[0270] As an embodiment, the node 203 is a gateway device.

[0271] Typically, the UE 201 is a user equipment, and the node 203 is a base station device.

[0272] As an embodiment, the user equipment supports transmission of a non-terrestrial network (NTN).

[0273] As an embodiment, the user equipment supports transmission of a terrestrial network (Terrestrial Network).

[0274] As an embodiment, the user equipment supports dual connection (DC) transmission.

[0275] As an embodiment, the user equipment includes an aircraft.

[0276] As an embodiment, the user equipment includes a vehicle-mounted terminal.

[0277] As an embodiment, the user equipment includes a vessel.

[0278] As an embodiment, the user equipment includes an Internet of Things terminal.

[0279] As an embodiment, the user equipment includes a terminal of the industrial Internet of Things.

[0280] As an embodiment, the user equipment includes a device supporting low-latency and high-reliability transmission.

[0281] As an embodiment, the user equipment includes a test device.

[0282] As an embodiment, the user equipment includes a signaling tester.

[0283] As an embodiment, the user equipment includes an IAB (Integrated Access and Backhaul)-MT.

[0284] As an embodiment, the user equipment supports generating reports using AI (Artificial Intelligence) or machine learning (Machine Learning).

[0285] As an embodiment, the user equipment supports generating a trained model using training data or generating partial parameters in the trained model using trained data.

[0286] As an embodiment, the user equipment supports performing radio link update through training determination.

[0287] As an embodiment, the user equipment supports prediction of wireless link failure through training.

[0288] As an embodiment, the user equipment is a terminal supporting Massive-MIMO.

[0289] As an embodiment, the base station device supports transmission in a non-terrestrial network.

[0290] As an embodiment, the base station device supports transmission of a terrestrial network.

[0291] As an embodiment, the base station equipment includes a base transceiver station (Base Transceiver Station, BTS).

[0292] As an embodiment, the base station device includes a Node B (NodeB, NB).

[0293] As an embodiment, the base station device includes a gNB.

[0294] As an embodiment, the base station device includes an eNB.

[0295] As an embodiment, the base station device includes ng-eNB.

[0296] As an embodiment, the base station device includes en-gNB.

[0297] As an embodiment, the base station device includes a CU (Centralized Unit).

[0298] As an embodiment, the base station device includes a DU (Distributed Unit).

[0299] As an embodiment, the base station device includes a TRP (Transmitter Receiver Point).

[0300] As an embodiment, the base station device includes a macro cellular (Marco Cellular) base station.

[0301] As an embodiment, the base station device includes a micro cell base station.

[0302] As an embodiment, the base station device includes a pico cell (Pico Cell) base station.

[0303] As an embodiment, the base station device includes a home base station (Femtocell).

[0304] As an embodiment, the base station device includes a flying platform device.

[0305] As an embodiment, the base station device includes a satellite device.

[0306] As an embodiment, the base station device includes a testing device.

[0307] As an embodiment, the base station equipment includes a signaling tester.

[0308] As an embodiment, the base station device includes a gateway device.

[0309] As an embodiment, the base station device includes an IAB-node.

[0310] As an embodiment, the base station device includes an IAB-donor.

[0311] As an embodiment, the base station device includes an IAB-donor-CU.

[0312] As an embodiment, the base station device includes an IAB-donor-DU.

[0313] As an embodiment, the base station device includes an IAB-DU.

[0314] As an embodiment, the base station device includes IAB-MT.

[0315] As an embodiment, the base station device supports transmission based on Massive-MIMO.

[0316] As an embodiment, the base station device supports decompression of CSI using an AI model.

[0317] As an embodiment, the base station device supports mobility management using an AI model.

[0318] Example 3

[0319] Embodiment 3 shows a schematic diagram of an embodiment of a wireless protocol architecture of a user plane and a control plane according to the present application, as shown in the attached Figure 3 shown. Figure 3 is a schematic diagram illustrating an embodiment of a radio protocol architecture for a user plane 350 and a control plane 300, Figure 3The radio protocol architecture for the control plane 300 is shown in three layers: Layer 1, Layer 2, and Layer 3. Layer 1 (L1 layer) is the lowest layer and implements various PHY (physical layer) signal processing functions. The L1 layer will be referred to as PHY 301 in this article. Layer 2 (L2 layer) 305 is above PHY 301 and includes a MAC (Medium Access Control) sublayer 302, an RLC (Radio Link Control) sublayer 303, and a PDCP (Packet Data Convergence Protocol) sublayer 304. The PDCP sublayer 304 provides multiplexing between different radio bearers and logical channels. The PDCP sublayer 304 also provides security by encrypting data packets, and provides inter-zone mobility support. The RLC sublayer 303 provides segmentation and reassembly of upper layer data packets, retransmission of lost data packets, and reordering of data packets to compensate for out-of-order reception due to HARQ (Hybrid Automatic Repeat Request). The MAC sublayer 302 provides multiplexing between logical and transport channels. The MAC sublayer 302 is also responsible for allocating various radio resources (e.g., resource blocks) in a cell. The MAC sublayer 302 is also responsible for HARQ operations. The RRC (Radio Resource Control) sublayer 306 in layer 3 (L3 layer) in the control plane 300 is responsible for obtaining radio resources (i.e., radio bearers) and using RRC signaling to configure the lower layers. The radio protocol architecture of the user plane 350 includes layer 1 (L1 layer) and layer 2 (L2 layer). In the user plane 350, the radio protocol architecture is substantially the same as the corresponding layers and sublayers in the control plane 300 for the physical layer 351, the PDCP sublayer 354 in the L2 layer 355, the RLC sublayer 353 in the L2 layer 355, and the MAC sublayer 352 in the L2 layer 355, but the PDCP sublayer 354 also provides header compression for upper layer data packets to reduce radio transmission overhead. The L2 layer 355 in the user plane 350 also includes a SDAP (Service Data Adaptation Protocol) sublayer 356. The SDAP sublayer 356 is responsible for mapping between QoS flows and data radio bearers (DRBs) to support service diversity.

[0320] As an example, Figure 3 The wireless protocol architecture in is applicable to the terminal described in this application.

[0321] As an example, Figure 3The wireless protocol architecture in is applicable to the base station described in this application.

[0322] As an embodiment, the first message in the present application is generated in the RRC306.

[0323] As an embodiment, the first message in the present application is generated by the MAC302 or MAC352.

[0324] As an embodiment, the first message in the present application is generated by the PHY301 or PHY351.

[0325] Example 4

[0326] Embodiment 4 shows a schematic diagram of a first communication device and a second communication device according to the present application, as shown in the attached figure. Figure 4 shown. Figure 4 is a block diagram of a first communication device 450 and a second communication device 410 communicating with each other in an access network.

[0327] The first communication device 450 includes a controller / processor 459, a memory 460, a data source 467, a transmit processor 468, a receive processor 456, a multi-antenna transmit processor 457, a multi-antenna receive processor 458, a transmitter / receiver 454 and an antenna 452.

[0328] The second communication device 410 includes a controller / processor 475 , a memory 476 , a receive processor 470 , a transmit processor 416 , a multi-antenna receive processor 472 , a multi-antenna transmit processor 471 , a transmitter / receiver 418 and an antenna 420 .

[0329] In transmission from the second communication device 410 to the first communication device 450, at the second communication device 410, upper layer data packets from the core network are provided to the controller / processor 475. The controller / processor 475 implements the functionality of the L2 layer. In transmission from the second communication device 410 to the first communication device 450, the controller / processor 475 provides header compression, encryption, packet segmentation and reordering, multiplexing between logical and transport channels, and radio resource allocation to the first communication device 450 based on various priority metrics. The controller / processor 475 is also responsible for retransmission of lost packets and signaling to the first communication device 450. The transmit processor 416 and the multi-antenna transmit processor 471 implement various signal processing functions for the L1 layer (i.e., the physical layer). The transmit processor 416 implements coding and interleaving to facilitate forward error correction (FEC) at the second communication device 410, as well as mapping of signal constellations based on various modulation schemes (e.g., binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), M-phase shift keying (M-PSK), M-quadrature amplitude modulation (M-QAM)). The multi-antenna transmit processor 471 performs digital spatial precoding, including codebook-based precoding and non-codebook-based precoding, and beamforming processing on the coded and modulated symbols to generate one or more spatial streams. The transmit processor 416 then maps each spatial stream to a subcarrier, multiplexes it with a reference signal (e.g., a pilot) in the time domain and / or frequency domain, and then uses an inverse fast Fourier transform (IFFT) to generate a physical channel carrying a time-domain multi-carrier symbol stream. The multi-antenna transmit processor 471 then performs a transmit analog precoding / beamforming operation on the time-domain multi-carrier symbol stream. Each transmitter 418 converts the baseband multi-carrier symbol stream provided by the multi-antenna transmit processor 471 into a radio frequency stream, and then provides it to a different antenna 420.

[0330] In the transmission from the second communication device 410 to the first communication device 450, at the first communication device 450, each receiver 454 receives a signal through its corresponding antenna 452. Each receiver 454 recovers the information modulated onto the RF carrier and converts the RF stream into a baseband multi-carrier symbol stream and provides it to the receiving processor 456. The receiving processor 456 and the multi-antenna receiving processor 458 implement various signal processing functions of the L1 layer. The multi-antenna receiving processor 458 performs a receiving analog precoding / beamforming operation on the baseband multi-carrier symbol stream from the receiver 454. The receiving processor 456 uses a fast Fourier transform (FFT) to convert the baseband multi-carrier symbol stream after the receiving analog precoding / beamforming operation from the time domain to the frequency domain. In the frequency domain, the physical layer data signal and the reference signal are demultiplexed by the receiving processor 456, wherein the reference signal will be used for channel estimation, and the data signal is recovered after multi-antenna detection in the multi-antenna receiving processor 458 to any spatial stream destined for the first communication device 450. The symbols on each spatial stream are demodulated and recovered in the receiving processor 456, and soft decisions are generated. The receiving processor 456 then decodes and deinterleaves the soft decisions to recover the upper layer data and control signals transmitted by the second communication device 410 on the physical channel. The upper layer data and control signals are then provided to the controller / processor 459. The controller / processor 459 implements the functions of the L2 layer. The controller / processor 459 may be associated with a memory 460 that stores program codes and data. The memory 460 may be referred to as a computer-readable medium. In the transmission from the second communication device 410 to the second communication device 450, the controller / processor 459 provides multiplexing between transport and logical channels, packet reassembly, decryption, header decompression, and control signal processing to recover the upper layer data packets from the core network. The upper layer data packets are then provided to all protocol layers above the L2 layer. Various control signals may also be provided to L3 for L3 processing.

[0331] In the transmission from the first communication device 450 to the second communication device 410, at the first communication device 450, a data source 467 is used to provide upper layer data packets to the controller / processor 459. The data source 467 represents all protocol layers above the L2 layer. Similar to the transmission function at the second communication device 410 described in the transmission from the second communication device 410 to the first communication device 450, the controller / processor 459 implements header compression, encryption, packet segmentation and reordering, and multiplexing between logical and transport channels based on radio resource allocation, and implements L2 layer functions for user plane and control plane. The controller / processor 459 is also responsible for the retransmission of lost packets and signaling to the second communication device 410. The transmit processor 468 performs modulation mapping and channel coding processing, and the multi-antenna transmit processor 457 performs digital multi-antenna spatial precoding, including codebook-based precoding and non-codebook-based precoding, and beamforming processing. Then, the transmit processor 468 modulates the generated spatial stream into a multi-carrier / single-carrier symbol stream, which is then provided to different antennas 452 via the transmitter 454 after analog precoding / beamforming operations in the multi-antenna transmit processor 457. Each transmitter 454 first converts the baseband symbol stream provided by the multi-antenna transmit processor 457 into a radio frequency symbol stream, and then provides it to the antenna 452.

[0332] In the transmission from the first communication device 450 to the second communication device 410, the function at the second communication device 410 is similar to the reception function at the first communication device 450 described in the transmission from the second communication device 410 to the first communication device 450. Each receiver 418 receives a radio frequency signal through its corresponding antenna 420, converts the received radio frequency signal into a baseband signal, and provides the baseband signal to the multi-antenna reception processor 472 and the reception processor 470. The reception processor 470 and the multi-antenna reception processor 472 jointly implement the functions of the L1 layer. The controller / processor 475 implements the L2 layer functions. The controller / processor 475 can be associated with a memory 476 storing program codes and data. The memory 476 can be referred to as a computer-readable medium. In the transmission from the first communication device 450 to the second communication device 410, the controller / processor 475 provides multiplexing between transport and logical channels, packet reassembly, decryption, header decompression, control signal processing to recover the upper layer data packets from the UE 450. Upper layer packets from controller / processor 475 may be provided to the core network.

[0333] As an embodiment, the first communication device 450 includes: at least one processor and at least one memory, the at least one memory including computer program code; the at least one memory and the computer program code are configured to be used together with the at least one processor, and the first communication device 450 at least: triggers a first process; terminates the first process in response to any condition in a first condition set being met; wherein the first condition set includes at least a first condition; wherein the first process depends on wireless link failure prediction; the first condition depends on at least one of measurement or prediction; wherein the first process depends on wireless link failure prediction including: the first process is to perform wireless link failure prediction, or the first process is predicted to be triggered by wireless link failure.

[0334] As an embodiment, the first communication device 450 includes: a memory storing a computer-readable instruction program, wherein the computer-readable instruction program generates an action when executed by at least one processor, the action including: triggering a first process; terminating the first process in response to any condition in a first condition set being satisfied; wherein the first condition set includes at least a first condition; wherein the first process depends on a prediction of a wireless link failure; the first condition depends on at least one of measurement or prediction; wherein the first process depends on a prediction of a wireless link failure including: the first process is to perform a prediction of a wireless link failure, or the first process is predicted to be triggered by a wireless link failure.

[0335] As an embodiment, the second communication device 410 includes: at least one processor and at least one memory, the at least one memory including computer program code; the at least one memory and the computer program code are configured to be used with the at least one processor. The second communication device 410 at least: sends a first configuration message, the first configuration message includes an intelligent model; wherein the radio link failure prediction depends on the intelligent model; wherein the receiver of the first configuration message triggers a first process; as a response to any condition in a first condition set being met, the first process is terminated; the first condition set includes at least a first condition; the first process depends on radio link failure prediction; the first condition depends on at least one of measurement or prediction; the first process depends on radio link failure prediction including: the first process is to perform radio link failure prediction, or the first process is predicted to be triggered by radio link failure.

[0336] As an embodiment, the second communication device 410 includes: a memory storing a computer-readable instruction program, wherein the computer-readable instruction program generates an action when executed by at least one processor, the action including: sending a first configuration message, the first configuration message including an intelligent model; wherein the wireless link failure prediction depends on the intelligent model; wherein the recipient of the first configuration message triggers a first process; as a response to any condition in a first condition set being met, terminating the first process; the first condition set includes at least a first condition; the first process depends on wireless link failure prediction; the first condition depends on at least one of measurement or prediction; the first process depends on wireless link failure prediction including: the first process is to perform wireless link failure prediction, or the first process is predicted to be triggered by wireless link failure.

[0337] As an embodiment, at least one of the antenna 452, the transmitter 454, the transmit processor 468, and the controller / processor 459 is used to send a first message.

[0338] As an embodiment, at least one of the antenna 420, the receiver 418, the receiving processor 470, and the controller / processor 475 is used to receive a first message.

[0339] As an embodiment, the first communication device 450 corresponds to the terminal in this application.

[0340] As an embodiment, the first communication device 410 corresponds to the base station in this application.

[0341] As an embodiment, the first communication device 450 is a user equipment.

[0342] As an embodiment, the first communication device 450 is a relay device.

[0343] As an embodiment, the second communication device 410 is a base station device.

[0344] As an embodiment, the second communication device 410 is a relay device.

[0345] Example 5

[0346] Embodiment 5 illustrates a wireless signal transmission flow chart according to an embodiment of the present application, as shown in the attached Figure 5 It is particularly noted that the order in this example does not limit the signal transmission order and implementation order in this application.

[0347] for Terminal U01In step S5101, a first process is triggered; in step S5102, a first message is sent, the first message includes at least one of a measurement result or a prediction result; in step S5103, the predicted wireless link failure is eliminated; in step S5104, a first configuration message is received, the first configuration message includes at least an intelligent model; in step S5105, as a response to any condition in the first condition set being met, the first process is terminated.

[0348] for Base Station N02 In step S5201, the first message is received; in step S5202, the first configuration message is sent.

[0349] In Example 5, the first process is terminated in response to any condition in a first condition set being met; wherein the first condition set includes at least a first condition; wherein the first process depends on a prediction of a wireless link failure; the first condition depends on at least one of measurement or prediction; wherein the first process depends on a prediction of a wireless link failure including: the first process is to perform a prediction of a wireless link failure, or the first process is predicted to be triggered by a wireless link failure.

[0350] As an embodiment, the terminal is a UE.

[0351] As an embodiment, the terminal is a UE supporting 3GPP R19.

[0352] As an embodiment, the terminal is a UE supporting 6G.

[0353] As an embodiment, the terminal is a UE that supports an AI model.

[0354] As an embodiment, the terminal is a UE supporting ML reasoning.

[0355] As an embodiment, the terminal is not a UE.

[0356] As an embodiment, the terminal U01 and the base station N02 are connected wirelessly.

[0357] As an embodiment, the terminal U01 and the base station N02 are connected via a wired connection.

[0358] As an embodiment, the terminal U01 and the base station N02 are connected via a Uu port.

[0359] As an embodiment, the terminal U01 and the base station N02 are connected via an IAB interface.

[0360] As an embodiment, the base station N02 is a maintaining base station of the current service cell of the terminal U01.

[0361] As an embodiment, the base station N02 is a maintenance base station of the cell served by the terminal U01.

[0362] As an embodiment, the ML training is reinforcement learning.

[0363] As an embodiment, the base station N02 receives the AI ​​model obtained after ML training and determines whether it needs to be transmitted to the terminal U01.

[0364] As an embodiment, the terminal U01 triggers the first process.

[0365] As an embodiment, the terminal U01 is instructed by the network to trigger the first process.

[0366] As an embodiment, triggering the first process depends on a condition being satisfied.

[0367] As an embodiment, when the one condition is met, the terminal U01 triggers the first process by itself.

[0368] As an embodiment, when at least one of the conditions is met, the terminal U01 triggers the first process by itself.

[0369] As an embodiment, the one condition is preconfigured.

[0370] As an embodiment, the one condition is obtained based on ML reasoning.

[0371] As an embodiment, the terminal U01 triggering the first process depends on the terminal U01 having at least the first UE capability.

[0372] As an embodiment, the dotted box F5.1 is optional.

[0373] As an embodiment, the dashed box F5.1 exists.

[0374] As an embodiment, in response to the first process being triggered, the terminal sends the first message; the first message includes at least one of a measurement result or a prediction result; and the first process is predicted to be triggered by a radio link failure.

[0375] As an embodiment, the first process is sending the first message; the first message includes at least one of a measurement result or a prediction result; and the first process is predicted to be triggered by a radio link failure.

[0376] As an embodiment, the first process is a reporting process, and the reporting process includes sending the first message; the first message includes at least one of a measurement result or a prediction result; and the first process is predicted to be triggered by a wireless link failure.

[0377] As an embodiment, the dotted box F5.1 does not exist.

[0378] As an embodiment, the first process does not include sending the first message.

[0379] As an embodiment, step S5103 is optional.

[0380] As an embodiment, step S5103 exists.

[0381] As an embodiment, the radio link failure predicted by the terminal U01 is eliminated, and the first process is predicted to be triggered by the radio link failure.

[0382] As an embodiment, the terminal U01 does not send any uplink message before the predicted radio link failure is eliminated.

[0383] As an embodiment, the reporting process is not performed before the radio link failure predicted by the terminal U01 is eliminated.

[0384] As an embodiment, the first process is not completed before the wireless link failure predicted by the terminal U01 is eliminated.

[0385] As an embodiment, step S5103 does not exist.

[0386] As an embodiment, the predicted radio link failure is not eliminated before the first process is terminated.

[0387] As an embodiment, during the execution of the first process, the predicted radio link failure is not eliminated.

[0388] For AI / ML, ML training is also called training, AI training, etc., which is an operation relative to ML inference (Inference), which is used to determine the parameters of the AI ​​model; the inference using the determined AI model can be executed in the base station N02, or in the terminal U01.

[0389] If ML reasoning is performed by the terminal U01, the base station N02 can transmit the AI ​​model obtained after ML training to the terminal U01, so that the terminal U01 can improve the quality of ML reasoning.

[0390] As an embodiment, the AI ​​model performs ML deployment in the base station N02.

[0391] As an embodiment, the AI ​​model performs ML training in the base station N02.

[0392] As an embodiment, the AI ​​model performs ML deployment in the terminal U01.

[0393] As an embodiment, the AI ​​model performs ML training in the terminal U01.

[0394] As an embodiment, the AI ​​model performs ML training on other nodes.

[0395] As an embodiment, the intelligent model in the present application is the AI ​​model.

[0396] As an embodiment, the intelligent model in the present application is at least one of the AI ​​models.

[0397] As an embodiment, the intelligent model in the present application includes the AI ​​model.

[0398] As an embodiment, the dotted box F5.2 is optional.

[0399] As an embodiment, the dashed box F5.2 exists.

[0400] As an embodiment, the terminal U01 receives a first configuration message.

[0401] As an embodiment, the first configuration message is forwarded via the base station N02.

[0402] As an embodiment, the first configuration message is an RRC message.

[0403] As an embodiment, the first configuration message is an RRCReconfiguration message.

[0404] As an embodiment, the first configuration message is a RRCResume message.

[0405] As an embodiment, the first configuration message is an RRCReestablishment message.

[0406] As an embodiment, the first configuration message includes information of the intelligent model.

[0407] As an embodiment, the first configuration message only includes information of the intelligent model.

[0408] As an embodiment, the information of the intelligent model includes the intelligent model ID.

[0409] As an embodiment, the information of the intelligent model includes configuration information of the intelligent model.

[0410] As an embodiment, the first configuration message is received before the step S5101.

[0411] As an embodiment, the first configuration message includes the first UE capability.

[0412] As an embodiment, the first configuration message is received after the step S5101.

[0413] As an embodiment, the first configuration message includes information about the intelligent model, and the information about the intelligent model is different from information about the intelligent model used to perform the wireless link prediction in the terminal U01.

[0414] As an embodiment, the first configuration message includes the information of the intelligent model to indicate that the intelligent model of the terminal U01 is updated.

[0415] As an embodiment, the dotted frame F5.2 does not exist.

[0416] As an embodiment, the terminal U01 terminates the first process.

[0417] As an embodiment, in response to any condition in the first condition set being met, the terminal U01 terminates the first process.

[0418] As an embodiment, when any condition in the first condition set is met, the terminal U01 terminates the first process.

[0419] As an embodiment, when at least any one of the first condition set is satisfied, the terminal U01 terminates the first process.

[0420] Example 6

[0421] Embodiment 6 illustrates a schematic diagram in which the first condition according to the present application includes that the predicted radio link failure is eliminated.

[0422] In Embodiment 6, the first condition includes that a predicted radio link failure is eliminated; wherein the first process is predicted to be triggered by a radio link failure.

[0423] As an embodiment, the first condition only includes that the predicted radio link failure is eliminated.

[0424] As an embodiment, the first condition at least includes that the predicted radio link failure is eliminated.

[0425] As an embodiment, the predicted radio link failure being eliminated means: determining based on measurement that the predicted radio link failure is eliminated.

[0426] As a sub-embodiment of the above embodiment, the predicted radio link failure is not detected based on the measurement.

[0427] As a sub-embodiment of the above embodiment, the measurement-based method refers to a measurement result based on L1 filtering.

[0428] As a sub-embodiment of the above embodiment, the measurement-based method refers to a measurement result based on L3 filtering.

[0429] As a sub-embodiment of the above embodiment, the measurement-based method refers to the method based on an average of measurement results within a period of time.

[0430] As a sub-embodiment of the above embodiment, the measurement-based method refers to the method based on the measurement result at the predicted time of radio link failure.

[0431] As a sub-embodiment of the above embodiment, the radio link failure not being detected means that the radio link failure does not occur.

[0432] As a sub-embodiment of the above embodiment, if the predicted radio link failure is not detected, it is considered that the predicted radio link failure is eliminated.

[0433] As a sub-embodiment of the above embodiment, when the predicted radio link failure is not detected, it is considered that the predicted radio link failure is eliminated.

[0434] As a sub-embodiment of the above embodiment, when at least the predicted radio link failure is not detected, it is considered that the predicted radio link failure is eliminated.

[0435] As a sub-embodiment of the above embodiment, the predicted radio link failure is not detected means that the predicted radio link failure is not detected within a predicted time period.

[0436] As a sub-embodiment of the above embodiment, the predicted radio link failure is not detected means that: at the predicted time point, the predicted radio link failure is not detected.

[0437] As a sub-embodiment of the above embodiment, the output of the predicted radio link failure is the time when the radio link failure occurs.

[0438] As a sub-embodiment of the above embodiment, the predicted radio link failure not being detected means that: the actual measurement result is better than the configured radio link quality threshold, the radio link quality threshold is Qout; and the measurement result is L1 SINR.

[0439] As a sub-embodiment of the above embodiment, the output of the predicted radio link failure is L1SINR.

[0440] As a sub-embodiment of the above embodiment, the predicted radio link failure is not detected means that the actual measurement result does not reach the configured counter threshold, and the configured counter is N310.

[0441] As a sub-embodiment of the above embodiment, the output of the predicted radio link failure is the number of measurement results whose measurement results are better than a configured radio link quality threshold.

[0442] As an embodiment, the predicted radio link failure being eliminated means: determining based on the prediction that the predicted radio link failure is eliminated.

[0443] As a sub-embodiment of the above embodiment, the prediction-based method refers to the prediction of wireless link failure.

[0444] As a sub-embodiment of the above embodiment, the prediction-based method refers to prediction of wireless link failure within a period of time.

[0445] As a sub-embodiment of the above embodiment, the prediction-based is triggered by the predicted radio link failure.

[0446] As a sub-embodiment of the above embodiment, if the prediction information indicates that the predicted radio link failure does not exist, the predicted radio link failure is eliminated.

[0447] As a sub-embodiment of the above embodiment, the prediction information indicating that the predicted radio link failure does not exist means that before the predicted radio link failure occurs, the radio link failure prediction predicts that the previous radio link failure does not exist.

[0448] As a sub-embodiment of the above embodiment, the prediction information indicating that the predicted radio link failure does not exist means that before the predicted radio link failure occurs, the radio link failure prediction does not predict the last radio link failure.

[0449] As an embodiment, the predicted radio link failure being eliminated means: determining that the predicted radio link failure is eliminated based on expiration of a timer.

[0450] As a sub-embodiment of the above embodiment, if the one timer expires, it is determined that the predicted radio link failure is eliminated.

[0451] As a sub-embodiment of the above embodiment, once the one timer expires, it is determined that the predicted radio link failure is eliminated.

[0452] As a sub-embodiment of the above embodiment, starting the timer depends on the prediction of radio link failure.

[0453] As a sub-embodiment of the above embodiment, when the wireless link failure is predicted, the timer is started.

[0454] As a sub-embodiment of the above embodiment, when at least the wireless link failure is predicted, the one timer is started.

[0455] As a sub-embodiment of the above embodiment, stopping the one timer depends on the prediction that a radio link failure occurs.

[0456] As a sub-embodiment of the above embodiment, when the wireless link failure is predicted to occur, the one timer is stopped.

[0457] As a sub-embodiment of the above embodiment, when at least the wireless link failure is predicted, the one timer is stopped.

[0458] As a sub-embodiment of the above embodiment, the one timer is for predicting the failure of the wireless link.

[0459] As a sub-embodiment of the above embodiment, the value of the timer is a default value.

[0460] As a sub-embodiment of the above embodiment, the value of the timer is configured.

[0461] As a sub-embodiment of the above embodiment, the value of the timer is predicted.

[0462] As a sub-embodiment of the above embodiment, during the operation of the timer, the first process is not completed; wherein the first process is predicted to be triggered by a wireless link failure.

[0463] As a sub-embodiment of the above embodiment, the stopping of a timer depends on the first process.

[0464] As a sub-embodiment of the above embodiment, once the first process is triggered, the one timer is stopped.

[0465] As a sub-embodiment of the above embodiment, once the first process is terminated, the one timer is stopped.

[0466] As a sub-embodiment of the above embodiment, once the first process is successfully completed, the one timer is stopped.

[0467] As an embodiment, the predicted radio link failure being eliminated means: the first process is successfully completed, and the predicted radio link failure is eliminated; the first process is predicted to be triggered by the radio link failure.

[0468] As a sub-embodiment of the above embodiment, the first process is a radio link update or an early radio link update; the successful completion of the first process refers to: successful switching to a target cell.

[0469] As a sub-embodiment of the above embodiment, the first process is an RRC connection re-establishment process, and the successful completion of the first process means: reconnecting to the target cell.

[0470] Example 7

[0471] Example 7 illustrates a schematic diagram of stopping the first timer according to an embodiment of the present application.

[0472] In Example 7, in the terminal in the present application, in step S7101, any condition in the first condition set is met; in step S7102, the first timer is stopped; the first timer is for the first process; the first timer is configurable or the first timer is default or the first timer is determined by the terminal itself.

[0473] As an embodiment, the first timer is started along with triggering the first process.

[0474] As an embodiment, in the first process, the first timer is started.

[0475] As an embodiment, the first timer is started during the reporting process; the reporting process is not the MCGFailureInformation process.

[0476] As an embodiment, when the first process is triggered, the first timer is started.

[0477] As an embodiment, the first process is to perform radio link failure prediction; in response to the radio link prediction being performed, a first timer is started.

[0478] As an embodiment, when the first process is terminated, the first timer is stopped.

[0479] As an embodiment, when the RRC connection re-establishment process is triggered, the first timer is stopped; the first process is not the RRC connection re-establishment process.

[0480] As an embodiment, when a radio link update or a radio link advance update process is triggered, the first timer is stopped; the first process is not a radio link update or a radio link advance update process.

[0481] As an embodiment, when the MCGFailureInformation process is triggered, the first timer is stopped; the first process is not the MCGFailureInformation process.

[0482] As an embodiment, the first process is started and the first timer is started when a radio link failure is predicted; the first process is triggered by the prediction of the radio link failure.

[0483] As an embodiment, the first process is started and the first timer is started when a radio link failure is predicted; the first process is to perform radio link failure prediction.

[0484] As an embodiment, while the first timer is running, wireless link failure prediction is not performed.

[0485] As an embodiment, the accompanying means: at the same time.

[0486] As an embodiment, the accompanying refers to: after.

[0487] As an embodiment, the accompanying means: only.

[0488] As an embodiment, the first timer is for the first process, and the first process is to perform radio link failure prediction.

[0489] As an embodiment, the first timer is for the first process, and the first process is predicted to be triggered by a radio link failure.

[0490] As an embodiment, the first timer is configurable.

[0491] As an embodiment, the first timer is configured separately by an RRC signaling.

[0492] As an embodiment, the first timer is configured along with the configuration information of the radio link failure prediction.

[0493] As an embodiment, the first timer is configured along with configuration information of the first process.

[0494] As an embodiment, the first timer is configured along with switching to the current serving cell.

[0495] As an embodiment, the first timer is a default timer.

[0496] As an embodiment, the value of the first timer is a default value.

[0497] As an embodiment, the start and stop conditions of the first timer are default.

[0498] As an embodiment, the first timer is determined by the terminal itself.

[0499] As an embodiment, the first timer is determined by the terminal itself and depends on whether the terminal has the first UE capability.

[0500] As an embodiment, the first timer is determined by the terminal itself and relies on the terminal to perform the radio link failure prediction.

[0501] As an embodiment, the first timer is determined by the terminal itself and relies on the terminal predicting a radio link failure.

[0502] As an embodiment, the first timer is configured, otherwise the first timer is default.

[0503] As an embodiment, the first timer is configured, otherwise the first timer is determined by the terminal itself.

[0504] Example 8

[0505] Embodiment 8 illustrates a schematic diagram of triggering the first process according to an embodiment of the present application.

[0506] In Example 8, in the terminal in the present application, in step S8101, the first indicator satisfies the first threshold; in step S8102, the first process is triggered; the first indicator depends on the prediction; the first threshold is configurable or the first threshold is default or the first threshold is determined by the terminal itself.

[0507] As an embodiment, the prediction of radio link failure depends on the first indicator satisfying a first threshold; the first process is triggered by the prediction of radio link failure.

[0508] As an embodiment, once the first indicator meets the first threshold, it is considered that the wireless link failure is predicted.

[0509] As an embodiment, when the first indicator meets a first threshold, it is considered that a wireless link failure is predicted.

[0510] As an embodiment, when at least the first indicator satisfies a first threshold, it is considered that a wireless link failure is predicted.

[0511] As an embodiment, the first indicator is the output of performing the wireless link failure prediction; as a response to the first indicator satisfying the first threshold, it is considered that the wireless link failure is predicted; triggering the first process, the first process is to perform the wireless link failure prediction.

[0512] As an embodiment, the first indicator is the output of performing the wireless link failure prediction; as a response to the first indicator satisfying a first threshold, it is considered that the wireless link failure is predicted; triggering the first process, the first process is predicted to be triggered by the wireless link.

[0513] As an embodiment, the first indicator is the output of performing the wireless link failure prediction; as a response to the first indicator satisfying the first threshold, it is considered that the wireless link failure is predicted; triggering the first process, the first process is to perform a wireless link update or an early wireless link update process.

[0514] As an embodiment, the first indicator is the output of the execution of the wireless link failure prediction; as a response to the first indicator satisfying the first threshold, it is considered that the wireless link failure is predicted; triggering the first process, the first process is to execute the RRC connection re-establishment process.

[0515] As an embodiment, the first indicator is the output of the execution of the wireless link failure prediction; as a response to the first indicator satisfying the first threshold, it is considered that the wireless link failure is predicted; triggering the first process, the first process is a reporting process.

[0516] As an embodiment, the predicting of radio link failure refers to: predicting the occurrence of radio link failure.

[0517] As an embodiment, the radio link failure occurs on the current serving cell, and the radio link failure is RLF.

[0518] As an embodiment, the radio link failure occurs on the target cell, and the radio link failure is RLF.

[0519] As an embodiment, the first radio link failure occurs on at least one candidate cell, and the radio link failure is RLF.

[0520] As an embodiment, the first radio link failure occurs on the target cell, and the radio link failure is HOF.

[0521] As an embodiment, the first radio link failure occurs on at least one candidate cell, and the radio link failure is HOF.

[0522] As an embodiment, the first indicator is the probability of occurrence of the wireless link failure predicted by AI.

[0523] As an embodiment, the first indicator satisfying a first threshold means that: the probability of occurrence of the wireless link failure is higher than the first threshold; the first indication is the probability of occurrence of the first wireless link failure, and the first threshold is a constant.

[0524] As an embodiment, the first indicator is the occurrence time of the wireless link failure predicted by AI.

[0525] As an embodiment, the first indicator satisfying the first threshold means that: the duration of the first time interval is less than the first time length; the first indication is the first time interval, and the first threshold is the first time length.

[0526] As an embodiment, the first indicator is the credibility of the wireless link failure predicted by AI.

[0527] As an embodiment, the first indicator satisfying a first threshold means that: the credibility of the failure of the wireless link is higher than the first threshold; the first indication is the credibility of the failure of the first wireless link, and the first threshold is a constant.

[0528] As an embodiment, the first indicator is the accuracy of the wireless link failure predicted by AI.

[0529] As an embodiment, the first indicator satisfying a first threshold means that: the accuracy of the radio link failure is higher than the first threshold; the first indication is the accuracy of the first radio link failure, and the first threshold is a constant.

[0530] As an embodiment, the first indicator is the quality of the wireless link within a period of time predicted by AI.

[0531] As an embodiment, the first indicator satisfying the first threshold means that: the quality of the wireless link within a period of time is lower than the first threshold; the first indication is the quality of the wireless link within a period of time, and the first threshold is a constant.

[0532] As an embodiment, the first threshold is configured by the network.

[0533] As an embodiment, the first threshold is inferred by ML.

[0534] As an embodiment, the first threshold is the output result of the AI ​​module.

[0535] As an embodiment, the first threshold is determined by the UE itself.

[0536] Example 9

[0537] Embodiment 9 illustrates a schematic diagram in which the first message includes at least one of a measurement result or a prediction result according to an embodiment of the present application.

[0538] In Example 9, the first process includes sending a first message; the first message includes at least one of a measurement result or a prediction result; wherein the first process is predicted to be triggered by a wireless link failure.

[0539] As an embodiment, the first process is a reporting process.

[0540] As an embodiment, when the first process is triggered, the first message is sent.

[0541] As an embodiment, the first message is sent when at least the first process is triggered.

[0542] As an embodiment, the first process includes a reporting process.

[0543] As an embodiment, the reporting process includes sending the first message.

[0544] As an embodiment, the first process is sending the first message.

[0545] As an embodiment, the first process includes sending the first message.

[0546] As an embodiment, in the first process, a condition is met to trigger the sending of the first message.

[0547] As an embodiment, the first timer is started along with sending the first message.

[0548] As an embodiment, the accompanying sending of the first message refers to: accompanying setting of the first message.

[0549] As an embodiment, the accompanying sending of the first message refers to: accompanying the transmission of the first message.

[0550] As an embodiment, the first message is dedicated to performing radio link failure prediction.

[0551] As an embodiment, the first message is for prediction.

[0552] As an embodiment, the first message is an RRC message.

[0553] As an embodiment, the first message is a MeasurementReport message.

[0554] As an embodiment, the first message is a MCGFailureInformation message.

[0555] As an embodiment, the first message is a UEInformationResponse message.

[0556] As an embodiment, the first message is a UEAssistanceInformation message.

[0557] As an embodiment, the first message is a MAC CE.

[0558] As an embodiment, the first message is a MAC sublayer message.

[0559] As an embodiment, the first message is a UCI.

[0560] As an embodiment, the first message includes a measurement result.

[0561] As an embodiment, the measurement result includes: the measurement result when the first message is sent.

[0562] As an embodiment, the measurement result includes: a measurement result of a period of time from predicting the failure of the wireless link to sending the first message.

[0563] As an embodiment, the measurement result includes: a measurement result of a period of time from starting the first process to sending the first message.

[0564] As an embodiment, the first message includes a prediction result.

[0565] As an embodiment, the prediction result includes the prediction of wireless link failure.

[0566] As an embodiment, the prediction result includes the prediction that the wireless link failure is eliminated.

[0567] As an embodiment, the prediction result includes the time when the wireless link failure occurs.

[0568] As an embodiment, the prediction result includes the quality of the wireless channel when the wireless link failure occurs.

[0569] As an embodiment, the prediction result includes the reception strength of the reference signal when the wireless link failure occurs.

[0570] As an embodiment, the prediction result includes the signal quality of the reference signal when the wireless link failure occurs.

[0571] As an embodiment, the first message only includes measurement results and prediction results.

[0572] As an embodiment, the first message includes at least a measurement result and a prediction result.

[0573] Example 10

[0574] Embodiment 10 illustrates a schematic diagram in which the first condition set includes a second condition according to an embodiment of the present application.

[0575] In Embodiment 10, the first condition set includes a second condition, and the second condition includes triggering a cell switching.

[0576] As an embodiment, the first condition set includes only the first condition and the second condition.

[0577] As an embodiment, the first condition set includes at least a first condition and a second condition.

[0578] As an embodiment, the second condition includes at least triggering a cell handover.

[0579] As an embodiment, the second condition is to trigger a cell switching.

[0580] As an embodiment, the triggering of cell switching is receiving a command to trigger cell switching.

[0581] As a sub-embodiment of the above embodiment, the command is an RRC message.

[0582] As a sub-embodiment of the above embodiment, the RRC message is an RRCReconfiguration message.

[0583] As a sub-embodiment of the above embodiment, the RRC message is an RRCResume message.

[0584] As a sub-embodiment of the above embodiment, the RRC message is an RRCSetup message.

[0585] As a sub-embodiment of the above embodiment, the RRC message is an RRCReestablishment message.

[0586] As a sub-embodiment of the above embodiment, the RRC message includes a reconfigurationWithSync field.

[0587] As a sub-embodiment of the above embodiment, the one command is MAC CE.

[0588] As a sub-embodiment of the above embodiment, the MAC CE is an LTM Cell switch MAC CE.

[0589] As a sub-embodiment of the above embodiment, the MAC CE is not LTM Cell Switch CommandMAC CE.

[0590] As a sub-embodiment of the above embodiment, the MAC CE is a MAC CE dedicated to the first process.

[0591] As a sub-embodiment of the above embodiment, the MAC CE is a MAC CE dedicated to triggering cell switching.

[0592] As a sub-embodiment of the above embodiment, the command indicates a target cell.

[0593] As a sub-embodiment of the above embodiment, the one command indicates at least one candidate cell.

[0594] As a sub-embodiment of the above embodiment, the one command indicates a cell identity.

[0595] As a subsidiary embodiment of the above sub-embodiment, the cell identity is a configuration index.

[0596] As a sub-embodiment of the above embodiment, the one command only indicates the cell identity.

[0597] As a sub-embodiment of the above embodiment, the cell identity includes a physical cell identity (Physical Cell identity, PCI) of the cell.

[0598] As a sub-embodiment of the above embodiment, the cell identity includes a global cell identity (Global Cell Identity, CGI) of the cell.

[0599] As a sub-embodiment of the above embodiment, the cell identity includes a public land mobile network (PLMN) of the cell.

[0600] As a sub-embodiment of the above embodiment, the cell identity includes a stand-alone non-public network (SNPN) of the cell.

[0601] As a sub-embodiment of the above embodiment, the cell identity includes the cellIdentity of the cell.

[0602] As a sub-embodiment of the above embodiment, the cell identity includes the CellIndex of the cell.

[0603] As a sub-embodiment of the above embodiment, the cell identity includes a reference signal frequency of the cell.

[0604] As a sub-embodiment of the above embodiment, the cell identity includes a reference signal frequency and PCI of the cell.

[0605] As a sub-embodiment of the above embodiment, the cell identity includes a carrier frequency of the cell.

[0606] As a sub-embodiment of the above embodiment, the cell identity includes the carrier frequency and PCI of the cell.

[0607] As a sub-embodiment of the above embodiment, the cell identity includes the servingCellId of the cell.

[0608] As a sub-embodiment of the above embodiment, the cell identity includes one of the cell's NCGI (NR Cell Global Identifier), CGI, PLMN, and SNPN.

[0609] As a sub-embodiment of the above embodiment, the cell identity includes the PLMN of the cell and the CGI of the third cell.

[0610] As a sub-embodiment of the above embodiment, the cell identity includes the SNPN of the cell and the CGI of the third cell.

[0611] As a sub-embodiment of the above embodiment, the cell identity includes the CGI of the cell and the Tracking Area Code (TAC) of the cell.

[0612] As a sub-embodiment of the above embodiment, if the GCI and TAC of the cell are available, the cell identity is the GCI and TAC of the cell; otherwise, the cell identity is the cell PCI.

[0613] As an embodiment, if the GCI and TAC of the cell are available, the cell identity is the GCI and TAC of the cell; otherwise, the cell identity is the PCI and carrier frequency of the cell.

[0614] As a sub-embodiment of the above embodiment, the command starts the evaluation of execution conditions for triggering cell switching.

[0615] As an embodiment, the triggering of cell switching is that the execution condition of triggering cell switching is met.

[0616] As an embodiment, when the execution condition for triggering cell switching is met, cell switching is triggered.

[0617] As an embodiment, when at least an execution condition for triggering cell switching is met, cell switching is triggered.

[0618] As an embodiment, when the execution condition for triggering cell switching is met and the first timer is running, cell switching is triggered.

[0619] As an embodiment, when at least the execution condition for triggering cell switching is met and the first timer is running, the cell switching is triggered.

[0620] As an embodiment, when the execution condition for triggering cell switching is met and the first process is not terminated, cell switching is triggered.

[0621] As an embodiment, when at least the execution condition for triggering the cell switching is met and the first process is not terminated, the cell switching is triggered.

[0622] As an embodiment, when the execution condition for triggering the cell switching is met and the predicted radio link failure has not occurred, the cell switching is triggered.

[0623] As an embodiment, when at least an execution condition for triggering a cell handover is satisfied and the predicted radio link failure has not occurred, the cell handover is triggered.

[0624] As an embodiment, when the execution condition for triggering cell switching is met and the predicted radio link failure is detected to occur, cell switching is triggered.

[0625] As an embodiment, when at least the execution condition for triggering the cell switching is met and the predicted radio link failure is detected to occur, the cell switching is triggered.

[0626] Embodiment 11

[0627] Embodiment 11 illustrates a schematic diagram in which the first condition set includes a third condition according to an embodiment of the present application.

[0628] In Embodiment 11, the first condition set includes a third condition, and the third condition includes that the intelligent model is updated; wherein the wireless link failure prediction depends on the intelligent model.

[0629] As an embodiment, the first condition set only includes the first condition and the third condition.

[0630] As an embodiment, the first condition set only includes the second condition and the third condition.

[0631] As an embodiment, the first condition set only includes the first condition, the second condition and the third condition.

[0632] As an embodiment, the third condition is that the intelligent model is updated.

[0633] As an embodiment, the updating of the intelligent model means that the intelligent model is cancelled.

[0634] As an embodiment, updating the intelligent model means that the intelligent model is deactivated.

[0635] As an embodiment, the updating of the intelligent model means that the intelligent model is overwritten.

[0636] As an embodiment, the intelligent model being updated means that the intelligent model is considered invalid.

[0637] As an embodiment, the network indicates that the intelligent model is updated.

[0638] As an embodiment, the network sends a first configuration message, wherein the first configuration message includes an intelligent model index; the intelligent model index is not the current intelligent model index.

[0639] As an embodiment, the smart model index is a smart model ID.

[0640] As an embodiment, the smart model index includes a smart model ID.

[0641] As an embodiment, the smart model index is a smart model configuration ID.

[0642] As an embodiment, the smart model index includes a smart model configuration ID.

[0643] As an embodiment, the first configuration message includes configuration information related to the ML training module.

[0644] As an embodiment, the first configuration message includes at least one intelligent model index.

[0645] As an embodiment, the first configuration message includes only one smart model index.

[0646] As an embodiment, the first configuration message includes multiple intelligent model indexes.

[0647] As an embodiment, the intelligent model index is network configured.

[0648] As an embodiment, the intelligent model index is configured by RAN.

[0649] As an embodiment, the intelligent model index is configured by the core network.

[0650] As an embodiment, the intelligent model index is generated by the terminal.

[0651] As an embodiment, the smart model index is used to identify a smart model.

[0652] As an embodiment, the smart model index is used to select a smart model.

[0653] As an embodiment, the smart model index is used to activate a smart model.

[0654] As an embodiment, the smart model index is used to switch a smart model.

[0655] As an embodiment, the intelligent model index is used for model pairing.

[0656] As an embodiment, the intelligent model index is a positive integer.

[0657] As an embodiment, the smart model index is a non-negative integer.

[0658] As an embodiment, the intelligent model index is based on LCM (lifecycle Management, LCM) .

[0659] As an embodiment, the intelligent model index is an identifier on the network side.

[0660] As an embodiment, the intelligent model index is an identifier on the UE side.

[0661] As an embodiment, the smart model index is a two-sided identification.

[0662] As an embodiment, the intelligent model index includes an identifier of the network side and an identifier of the UE side.

[0663] As an embodiment, the smart model index is pre-defined.

[0664] As an embodiment, the intelligent model index is optional.

[0665] As an embodiment, the smart model index is globally unique.

[0666] As an embodiment, the smart model index is indicated by a PLMN ID.

[0667] As an embodiment, the intelligent model index is indicated by combining multiple basic fields.

[0668] As an embodiment, the first configuration information message includes at least one intelligent model index list; the intelligent model to which any cell among the multiple cells belongs is indexed by an intelligent model in the at least one intelligent model index list.

[0669] As an embodiment, the UE decides on its own whether the intelligent model is updated.

[0670] As an embodiment, when a condition is met, the UE decides on its own that the intelligent model is updated.

[0671] As an embodiment, the one condition is a timer; the one timer is for the smart model; in response to the expiration of the one timer, the UE decides that the smart model is updated.

[0672] As an embodiment, the one condition is a threshold, and when the output of the intelligent model is lower than a certain threshold, the UE decides that the intelligent model is updated.

[0673] As an embodiment, the output of the intelligent model refers to the output within a period of time.

[0674] As an embodiment, the output of the intelligent model refers to credibility.

[0675] As an embodiment, the output of the intelligent model refers to accuracy.

[0676] As an embodiment, the wireless failed link prediction can be performed only if the UE is configured with the intelligent model.

[0677] As an embodiment, when the UE is configured with the intelligent model, the wireless failed link prediction is performed.

[0678] As an embodiment, when at least the UE is configured with the intelligent model, the wireless failed link prediction is performed.

[0679] As an embodiment, the UE being configured with the intelligent model means that the UE is deployed with the intelligent model.

[0680] As an embodiment, the UE being configured with the intelligent model means that the UE is deployed with the intelligent model and activated.

[0681] As an embodiment, the UE being configured with the intelligent model means that the UE is able to perform reasoning using the intelligent model.

[0682] As an embodiment, the input of the intelligent model is historical measurement results.

[0683] As an embodiment, the input of the intelligent model is the historical SINR.

[0684] As an embodiment, the output of the intelligent model is a predicted SINR.

[0685] As an embodiment, the output of the intelligent model is a prediction of the occurrence of the wireless link failure.

[0686] As an embodiment, the output of the intelligent model is a predicted time point when the wireless link failure occurs.

[0687] As an embodiment, the output of the intelligent model is a time period in which the wireless link failure is predicted to occur.

[0688] Example 12

[0689] Embodiment 12 illustrates a schematic diagram of RAN (Radio Access Network) domain (Domain) AI / ML function deployment according to an embodiment of the present application; as shown in the attached Fig.12 As shown. The gNB in ​​Example 12 can be replaced by network equipment such as eNB or 6G base station.

[0690] AI / ML related functions include ML training function (also called AI training, or AI / ML training), ML testing function, ML reasoning (also called AI reasoning, or AI / ML reasoning) function, etc. ML training function, ML testing function, and ML reasoning function can be deployed independently or co-located. The deployment of AI / ML related functions can be achieved through software, such as downloading and / or running executable files; it can also be achieved through a combination of software and hardware, such as accelerating specific computing units through hardware to increase computing speed or save power consumption.

[0691] For ML training functions, they can be deployed in a cross-domain management system or a domain-specific management system; the domain-specific management system is used to manage the RAN domain or the CN (Core Network) domain. For example, the ML training function for MDA (Management Data Analytics) can be deployed in MDAF (MDA function); ML training for network data analysis can be deployed in NWDAF (Network Data Analytics Function), that is, the ML training function is MTLF (Model Training logical function).

[0692] The ML reasoning function can also be deployed in a cross-domain management system or a domain-specific management system; for example, the ML reasoning function is MDAF, or the ML reasoning function is AnLF (Analytics logical function) located in NWDAF.

[0693] Similarly, ML testing capabilities can also be deployed in cross-domain management systems, or domain-specific management systems.

[0694] In Example 12, the RAN domain ML training function 1402 is located in the RAN domain management function 1403; and the ML reasoning function is located in the base station, that is, the AI / ML reasoning function 1404 is located in the gNB1405, the AI / ML reasoning function 1406 is located in the gNB1407, and so on.

[0695] Attached Fig.12In the example, the management of the ML inference functions of multiple base stations is completed by the RAN domain management function 1403, that is, data interaction with the RAN domain MnS (Management Service) consumer / cross-domain management 1401 (see attached Fig.12 ).

[0696] Optionally, the management of the ML reasoning function may also be performed by the base station itself, that is, each base station may independently interact with the RAN domain MnS consumer / cross-domain management 1401 for data.

[0697] It should be noted that Example 12 is merely a non-restrictive implementation method; optionally, the ML training function of the RAN domain may also be deployed in the base station; or optionally, some base stations deploy the ML reasoning function and the ML training function of the RAN domain, while some base stations only deploy the ML reasoning function.

[0698] As an embodiment, a gNB (or base station) in Embodiment 2 is the base station described in the present application.

[0699] As an embodiment, the second transmitter includes an attached Fig.12 An AL / ML reasoning function, namely 1404 or 1406.

[0700] As an embodiment, the second receiver includes an attached Fig.12 An AL / ML reasoning function, namely 1404 or 1406.

[0701] As an example, Fig.12 An AL / ML inference function in performs ML training based on the collected wireless link failure data.

[0702] Embodiment 13

[0703] Embodiment 13 illustrates a schematic diagram of the AI / ML function deployment of a UE according to an embodiment of the present application; Fig.13 Attached Fig.13 The RAN domain ML training functionality 1505 is optional.

[0704] The UE function 1504 is deployed in the terminal of the present application, and the UE function 1504 includes an AI / ML reasoning function 1506; the AI / ML reasoning function 1506 uses an ML model (also called an AI model) for reasoning; an ML model is usually trained before being used for AI / ML reasoning.

[0705] As an embodiment, the UE function 1504 includes a RAN domain ML training function 1505, and the RAN domain ML training function 1505 runs the training data through the ML model to derive relevant losses, and adjusts the parameters of the ML model based on the calculated losses; the ML training includes at least one of ML initial training, ML re-training, and reinforcement learning.

[0706] The above embodiments can reduce the complexity of the base station, or save air interface resources caused by reporting training data; however, the above embodiments place high demands on the processing capability of the UE side.

[0707] Optionally, the UE function 1504 also includes a CN domain ML training function ( Fig.13 not included).

[0708] Optionally, the UE function 1504 also includes an AI / ML deployment function: Fig.13 Not included, used to load ML models and data.

[0709] As an embodiment, the terminal indicates whether it supports the ML training function (RAN domain or CN domain) through capability reporting, and the capability reporting is RRC signaling, or NAS (Non-Access Stratum) signaling.

[0710] As an embodiment, the ML model and related metadata are loaded by the terminal from a network device or a remote server.

[0711] Optionally, the UE function 1504 is a MnS (Management Service) producer, providing data to the CN domain MnF (Management Function) 1501, and / or the RAN domain MnF 1502, and / or the cross-domain management system 1503 for management or analysis (as shown by the double arrow 1507).

[0712] Optionally, the UE function 1504 is an MnS consumer, which loads data from the CN domain MnF (Management Function) 1501, and / or the RAN domain MnF 1502, and / or the cross-domain management system 1503 for AI / ML related management, such as management data requests, ML model activation, and / or ML training, etc. (as shown by the double arrow 1507).

[0713] As an embodiment, the prediction of wireless link failure in the present application is obtained through reasoning by the AI / ML reasoning function 1506.

[0714] As an embodiment, the first processor includes an attached Fig.13 An AL / ML reasoning function 1506 in.

[0715] As an embodiment, the ML model is based on a neural network.

[0716] As an embodiment, the ML model is based on CNN (Conventional Neural Networks).

[0717] As an embodiment, the ML model is based on the Transformer architecture.

[0718] Embodiment 14

[0719] Embodiment 14 illustrates a schematic diagram of a processing system based on artificial intelligence or machine learning according to an embodiment of the present application; Fig.14 Attached Fig.14 Includes a third processor, a fourth processor, a fifth processor and a sixth processor.

[0720] In Example 14, the third processor sends a first data set to the fourth processor and a second data set to the fifth processor; the fourth processor generates a target first-category parameter group based on the first data set, and the fourth processor sends the generated target first-category parameter group to the fifth processor; the fifth processor processes the second data set using the target first-category parameter group to obtain a first-category output, and (optionally) the fifth processor sends the first-category output to the sixth processor. Fig.14 In the embodiment, the first type of feedback and the second type of feedback are optional; the fourth processor includes ML training function; and the fifth processor includes ML reasoning function.

[0721] As an embodiment, the sixth processor includes ML testing functionality.

[0722] As an embodiment, the sixth processor includes performance monitoring / evaluation of the ML model.

[0723] As an embodiment, the fifth processor sends the first type of feedback to the fourth processor, and the first type of feedback is used to trigger recalculation or updating of the target first type parameter group, that is, triggering ML initial training or ML retraining.

[0724] As an embodiment, the sixth processor sends a second type of feedback to the third processor, and the second type of feedback is used to generate the first data set or the second data set, or the second type of feedback is used to trigger the sending of the first data set or the sending of the second data set.

[0725] As an embodiment, the third processing machine generates the first data set and the second data set according to measurements.

[0726] As an embodiment, the fifth processor belongs to the terminal, and the sixth processor belongs to the base station.

[0727] As an embodiment, the first type of output includes the prediction of wireless link failure.

[0728] As an embodiment, the first type of output includes the predicted measurement results.

[0729] As an embodiment, the second data set includes measurements for a reference signal.

[0730] As an embodiment, the first data set includes training data (Training Data).

[0731] As an embodiment, the fourth processor is used to train the ML model, and the trained model is described by the target first-category parameter group.

[0732] As an embodiment, the fourth processor belongs to the terminal.

[0733] The above embodiment avoids transmitting the first data set to the base station.

[0734] As an embodiment, the fourth processor belongs to the base station.

[0735] The above embodiments support joint training and optimize system performance.

[0736] As an embodiment, the fourth processor belongs to the core network.

[0737] The above embodiments support joint training of the entire network, further optimizing system performance.

[0738] As an embodiment, the second data set includes inference data.

[0739] As an embodiment, the fifth processor belongs to the terminal.

[0740] As an embodiment, the fifth processing machine constructs a model according to the target first-category parameter group, and then inputs the second data set into the constructed model to obtain the first-category output.

[0741] As an embodiment, the fifth processing machine generates a restored data set according to the first type of output, and an error between the restored data set and the second data set is used to generate the first type of feedback.

[0742] As an embodiment, the first type of feedback is used to reflect the performance of the trained model; when the performance of the trained model cannot meet the requirements, the fourth processor will recalculate the target first type parameter group.

[0743] As an embodiment, when the error is too large or has not been updated for too long, the performance of the trained model is considered to be unable to meet the requirements.

[0744] As an embodiment, the target first category parameter group includes: one or more of: convolution kernel size, number of convolution layers, convolution step size, pooling kernel size, pooling kernel step size, pooling function, activation function, or number of feature maps.

[0745] As an embodiment, the target first-category parameter group includes: one or more of a convolution kernel, a pooling kernel, a pooling function, an activation function, parameters of a pooling function, or parameters of an activation function.

[0746] Embodiment 15

[0747] Embodiment 15 illustrates a schematic diagram of artificial intelligence or machine learning according to another embodiment of the present application, as shown in the attached Fig.15 Attached Fig.15 It includes a first module, a second module, a third module, a fourth module and a fifth module.

[0748] In Example 15, the first module sends a first data set to the second module, the first module sends a second data set to the third module, the first module sends a third data set to the fifth module, the fifth module sends a first type of parameter group to the second module, the fifth module sends a second type of parameter group to the third module, the fifth module sends a third type of parameter group to the fourth module, the second module sends a fourth type of parameter group to the fourth module, and the fourth module sends a fifth type of parameter group to the third module.

[0749] As an embodiment, the first module, the second module, the third module, the fourth module and the fifth module all belong to the terminal.

[0750] The above method avoids air interface signaling interaction and shortens transmission delay.

[0751] As an embodiment, any one of the first module, the second module, the third module, the fourth module and the fifth module does not belong to the terminal.

[0752] The above method reduces the hardware complexity of the terminal.

[0753] As an embodiment, at least the first module among the first module, the second module, the third module, the fourth module and the fifth module belongs to the terminal; and at least one module among the first module, the second module, the third module, the fourth module and the fifth module does not belong to the terminal.

[0754] The above method balances the hardware complexity and transmission delay of the terminal.

[0755] As an embodiment, the first module is used for data collection.

[0756] As an embodiment, the first module is responsible for data collection.

[0757] As an embodiment, the first module has a data collection function.

[0758] As an embodiment, the second module is used for model training (Model Training).

[0759] As an embodiment, the second module is responsible for model training.

[0760] As an embodiment, the second module has a model training function.

[0761] As an embodiment, the second module performs AI / ML model training.

[0762] As an embodiment, the second module performs validation.

[0763] As an embodiment, the second module performs testing.

[0764] As an embodiment, the second module generates model performance metrics.

[0765] As an embodiment, the second module is responsible for data preparation.

[0766] As an embodiment, the data preparation includes at least one of data pre-processing, cleaning, formatting, or transformation.

[0767] As an embodiment, the third module is used for inference.

[0768] As an embodiment, the third module has a reasoning function.

[0769] As an embodiment, the third module is responsible for reasoning.

[0770] As an embodiment, the fourth module is used for model storage (Model Storage).

[0771] As an embodiment, the fourth module has a model storage (Model Storage) function.

[0772] As an embodiment, the fourth module is responsible for storing the trained model.

[0773] As an embodiment, the fourth module is responsible for storing the trained model that can be used to perform reasoning processing.

[0774] As an embodiment, the fifth module is used for management.

[0775] As an embodiment, the fifth module is responsible for management.

[0776] As an embodiment, the fifth module has a management function.

[0777] As an embodiment, the first data set is training data (Training Data).

[0778] As an embodiment, the second data set is inference data.

[0779] As an embodiment, the third data set is monitoring data.

[0780] As an embodiment, the first parameter group includes monitoring output.

[0781] As an embodiment, the second type of parameter group includes management instructions.

[0782] As an embodiment, the second type of parameter group is used for fine-tuning operation of the inference function.

[0783] As an embodiment, the second parameter group includes an identifier of the model.

[0784] As an embodiment, the second type of parameter group is used to select a model.

[0785] As an embodiment, the second type of parameter group is used for switching models.

[0786] As an embodiment, the second type of parameter group is used to activate / deactivate the model.

[0787] As an embodiment, the second type of parameter group is used to fall back from AI-ML operation to non-AI-ML operation.

[0788] As an embodiment, the third type of parameter group includes a model transfer request (Model Transfer Request).

[0789] As an embodiment, the third parameter group includes a model delivery request (Model DeliveryRequest).

[0790] As an embodiment, the fourth parameter group includes a trained model (Trained Model).

[0791] As an embodiment, the fourth parameter group includes an updated model (Updated Model).

[0792] As an embodiment, the fourth type of parameter group indicates the identification of the model.

[0793] As an embodiment, the fifth parameter group includes model transfer.

[0794] As an embodiment, the fifth parameter group includes model delivery.

[0795] As an embodiment, the fifth type of parameter group indicates the identification of the model.

[0796] As an embodiment, the first type of output includes a monitoring output.

[0797] As an embodiment, the first type of output exists.

[0798] As an embodiment, the first type of output does not exist.

[0799] As an embodiment, the second type of output includes inference output.

[0800] As an embodiment, the second type of output is used by the fifth module to monitor the performance of the AI / ML model.

[0801] As an embodiment, the second type of output is used by the fifth module to monitor the performance of the AI / ML function.

[0802] As an embodiment, the second type of output exists.

[0803] As an embodiment, the second type of output does not exist.

[0804] As an embodiment, the artificial intelligence processing system generates or assists in generating the predicted wireless link failure.

[0805] As an embodiment, the fifth module generates or assists in generating the predicted wireless link failure.

[0806] As an embodiment, the third module generates or assists in generating the predicted wireless link failure.

[0807] As an embodiment, the second type of output includes the prediction of wireless link failure.

[0808] As an embodiment, the embodiment 15 is only used to illustrate that the present application can be used in an artificial intelligence or machine learning system. The embodiment does not limit the application of the present application to a non-artificial intelligence system, and the embodiment does not limit the application of the present application to other types of artificial intelligence systems to obtain and attach Fig.15 The artificial intelligence system shown has comparable effects.

[0809] Example 16

[0810] Embodiment 16 illustrates a structural block diagram of a processing device used in a terminal according to an embodiment of the present application; Fig.16 As shown in the attached Fig.16 In the example, the processing device 1600 in the terminal includes a first processor 1601.

[0811] The first processor 1601 triggers a first process; in response to any condition in a first set of conditions being satisfied, terminates the first process; wherein the first set of conditions includes at least the first condition;

[0812] In Example 16, the first process depends on the prediction of wireless link failure; the first condition depends on at least one of measurement or prediction; wherein the first process depends on the prediction of wireless link failure including: the first process is to perform wireless link failure prediction, or the first process is predicted to be triggered by wireless link failure.

[0813] As an embodiment, the terminal includes: one or more processors and a memory;

[0814] The memory is coupled to the one or more processors, and the memory is used to store computer program codes, where the computer program codes include computer instructions. The one or more processors call the computer instructions to enable the terminal to execute the method according to any one of claims 1 to 7.

[0815] As an embodiment, the first condition includes that a predicted radio link failure is eliminated; wherein the first process is triggered by a predicted radio link failure.

[0816] As an embodiment, the first processor 1601, in response to any of the conditions in the first condition set being met, stops a first timer; wherein the first timer is for the first process; the first timer is configurable or the first timer is default or the first timer is determined by the terminal itself.

[0817] As an embodiment, the first processor 1601, in response to the first indicator satisfying a first threshold, initiates the first process; wherein the first indicator depends on prediction; the first threshold is configurable or the first threshold is a default or the first threshold is determined by the terminal itself.

[0818] As an embodiment, the first process includes sending a first message; the first message includes at least one of a measurement result or a prediction result; wherein the first process is predicted to be triggered by a wireless link failure.

[0819] As an embodiment, the first condition set includes a second condition, and the second condition includes triggering a cell switching.

[0820] As an embodiment, the first condition set includes a third condition, and the third condition includes that the intelligent model is updated; wherein the wireless link failure prediction depends on the intelligent model.

[0821] As an embodiment, the first processor 1601 includes a first receiver.

[0822] As an embodiment, the first processor 1601 includes a first transmitter.

[0823] As an embodiment, the first processor 1601 includes a first receiver and a first transmitter.

[0824] As an embodiment, the first receiver includes the attached Figure 4 At least one of the antenna 452 or the receiver 454 or the multi-antenna receive processor 458 or the receive processor 456 or the controller / processor 459 or the memory 460 or the data source 467.

[0825] As an embodiment, the first receiver includes the attached Figure 4 At least an antenna 452 and a receiver 454.

[0826] As an embodiment, the first transmitter includes the attached Figure 4 At least one of the antenna 452 or the transmitter 454 or the multi-antenna transmit processor 457 or the transmit processor 468 or the controller / processor 459 or the memory 460 or the data source 467.

[0827] As an embodiment, the first transmitter includes the attached Figure 4 At least antenna 452 and transmitter 454.

[0828] As an embodiment, the radio link failure is predicted by the first receiver.

[0829] As an embodiment, the radio link failure is predicted by the first transmitter.

[0830] As an embodiment, the radio link failure is predicted by the memory 460 in the first receiver.

[0831] As an embodiment, the radio link failure is predicted by the memory 460 in the first transmitter.

[0832] As an embodiment, the radio link failure is predicted by the controller / processor 459 in the first receiver.

[0833] As an embodiment, the radio link failure is predicted by the controller / processor 459 in the first transmitter.

[0834] As an embodiment, the first message is set by the first receiver.

[0835] As an embodiment, the first message is set by the first transmitter.

[0836] As an embodiment, the first message is set by the memory 460 in the first receiver.

[0837] As an embodiment, the first message is set by the memory 460 in the first transmitter.

[0838] As an embodiment, the first message is set by the controller / processor 459 in the first receiver.

[0839] As an embodiment, the first message is set by the controller / processor 459 in the first transmitter.

[0840] Embodiment 17

[0841] Embodiment 17 illustrates a structural block diagram of a processing device used in a base station according to an embodiment of the present application; Fig.17 As shown in the attached Fig.17 In the embodiment, the processing device 1700 in the base station includes a second transmitter 1701 and a second receiver 1702.

[0842] The second transmitter 1701 sends a first configuration message, wherein the first configuration message includes an intelligent model; wherein the wireless link failure prediction depends on the intelligent model;

[0843] In Example 17, the recipient of the first configuration message triggers a first process; in response to any condition in a first condition set being met, the first process is terminated; the first condition set includes at least the first condition; the first process depends on a prediction of a wireless link failure; the first condition depends on at least one of measurement or prediction; the first process depends on a prediction of a wireless link failure including: the first process is to perform a prediction of a wireless link failure, or the first process is predicted to be triggered by a wireless link failure.

[0844] As an embodiment, the base station includes: one or more processors and a memory;

[0845] The memory is coupled to the one or more processors, and the memory is used to store computer program codes, where the computer program codes include computer instructions, and the one or more processors call the computer instructions to enable the base station to perform the method according to any one of claims 9 to 15.

[0846] As an embodiment, the first condition includes that a predicted radio link failure is eliminated; wherein the first process is triggered by a predicted radio link failure.

[0847] As an embodiment, in response to any one of the conditions in the first set of conditions being met, the recipient of the first configuration message stops a first timer; wherein the first timer is for the first process; the first timer is configurable or the first timer is a default or the first timer is determined by the terminal itself.

[0848] As an embodiment, in response to the first indicator satisfying a first threshold, the recipient of the first configuration message triggers the first process; wherein the first indicator depends on prediction; the first threshold is configurable or the first threshold is a default or the first threshold is determined by the terminal itself.

[0849] As an embodiment, the second receiver 1702 receives a first message, where the first message includes at least one of a measurement result or a prediction result;

[0850] As an embodiment, the first process includes a recipient of the first configuration message sending the first message, and the first process is predicted to be triggered by a radio link failure.

[0851] As an embodiment, the first condition set includes a second condition, and the second condition includes triggering a cell switching.

[0852] As an embodiment, the first condition set includes a third condition, and the third condition includes that the intelligent model is updated.

[0853] As an embodiment, the second transmitter 1701 includes the attached Figure 4 At least one of the antenna 420 or the transmitter 418 or the multi-antenna transmit processor 471 or the transmit processor 416 or the controller / processor 475 or the memory 476.

[0854] As an embodiment, the second transmitter 1701 includes the attached Figure 4 At least antenna 420 and transmitter 418.

[0855] As an embodiment, the second receiver 1702 includes the attached Figure 4 At least one of the antenna 420 or the receiver 418 or the multi-antenna reception processor 472 or the reception processor 470 or the controller / processor 475 or the memory 476.

[0856] As an embodiment, the second receiver 1702 includes the attached Figure 4 At least an antenna 420 and a receiver 418.

[0857] A person of ordinary skill in the art can understand that all or part of the steps in the above method can be completed by instructing the relevant hardware through a program, and the program can be stored in a computer-readable storage medium, such as a read-only memory, a hard disk or an optical disk. Optionally, all or part of the steps in the above embodiment can also be implemented using one or more integrated circuits. Accordingly, each module unit in the above embodiment can be implemented in the form of hardware or in the form of a software function module, and the present application is not limited to any specific form of software and hardware combination. The user equipment, terminal and UE in the present application include but are not limited to drones, communication modules on drones, remote-controlled aircraft, aircraft, small aircraft, mobile phones, tablet computers, notebooks, vehicle-mounted communication equipment, wireless sensors, Internet cards, Internet of Things terminals, RFID terminals, NB-IOT terminals, MTC (Machine Type Communication, Machine Type Communication) terminals, eMTC (enhanced MTC, enhanced MTC) terminals, data cards, Internet cards, vehicle-mounted communication equipment, low-cost mobile phones, low-cost tablet computers and other wireless communication devices. The base stations or system devices in this application include but are not limited to macrocell base stations, microcell base stations, home base stations, relay base stations, gNB (NR Node B) NR Node B, TRP (Transmitter Receiver Point) and other wireless communication devices.

[0858] The above is only a preferred embodiment of the present application and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method used in a terminal, characterized in that: include: triggering a first process; terminating the first process in response to any condition in a first set of conditions being satisfied; wherein the first set of conditions includes at least the first condition; The first process depends on the prediction of radio link failure; the first condition depends on at least one of measurement or prediction; The first process being dependent on radio link failure prediction includes: the first process is executing radio link failure prediction, or the first process is predicted to be triggered by radio link failure.

2. The method according to claim 1, characterized in that The first condition includes that a predicted radio link failure is eliminated; wherein the first process is triggered by a predicted radio link failure.

3. The method according to claim 1 or 2, characterized in that: The method comprises: In response to any one of the conditions in the first set of conditions being satisfied, stopping a first timer; The first timer is for the first process; the first timer is configurable or the first timer is a default or the first timer is determined by the terminal itself.

4. The method according to any one of claims 1 to 3, characterized in that The method comprises: In response to the first indicator satisfying the first threshold, initiating the first process; The first indicator depends on prediction; the first threshold is configurable or the first threshold is a default or the first threshold is determined by the terminal itself.

5. The method according to any one of claims 1 to 4, characterized in that The first process includes sending a first message; the first message includes at least one of a measurement result or a prediction result; wherein the first process is triggered by predicting a radio link failure.

6. The method according to any one of claims 1 to 5, characterized in that The first condition set includes a second condition, and the second condition includes triggering a cell handover.

7. The method according to any one of claims 1 to 6, characterized in that The first condition set includes a third condition, and the third condition includes that the intelligent model is updated; wherein the wireless link failure prediction depends on the intelligent model.

8. A terminal, characterized in that: The terminal includes: one or more processors and a memory; The memory is coupled to the one or more processors, and the memory is used to store computer program codes, where the computer program codes include computer instructions. The one or more processors call the computer instructions to enable the terminal to execute the method according to any one of claims 1 to 7.

9. A method used in a base station, characterized in that: include: Sending a first configuration message, wherein the first configuration message includes an intelligent model; wherein the wireless link failure prediction depends on the intelligent model; Among them, the recipient of the first configuration message triggers a first process; as a response to any condition in a first condition set being met, the first process is terminated; the first condition set includes at least the first condition; the first process depends on wireless link failure prediction; the first condition depends on at least one of measurement or prediction; the first process depends on wireless link failure prediction including: the first process is to perform wireless link failure prediction, or the first process is predicted to be triggered by wireless link failure.

10. The method according to claim 9, characterized in that The first condition includes that a predicted radio link failure is eliminated; wherein the first process is triggered by a predicted radio link failure.

11. The method according to claim 9 or 10, characterized in that: In response to any one of the conditions in the first set of conditions being met, the receiver of the first configuration message stops a first timer; The first timer is for the first process; the first timer is configurable or the first timer is a default or the first timer is determined by the terminal itself.

12. The method according to any one of claims 9 to 11, characterized in that: In response to the first indicator satisfying the first threshold, the recipient of the first configuration message triggers the first process; The first indicator depends on prediction; the first threshold is configurable or the first threshold is a default or the first threshold is determined by the terminal itself.

13. The method according to any one of claims 9 to 12, characterized in that: The method comprises: receiving a first message, wherein the first message includes at least one of a measurement result or a prediction result; The first process includes a receiver of the first configuration message sending the first message, and the first process is triggered by predicting a radio link failure.

14. The method according to any one of claims 9 to 13, characterized in that: The first condition set includes a second condition, and the second condition includes triggering a cell handover.

15. The method according to any one of claims 9 to 14, characterized in that: The first condition set includes a third condition, and the third condition includes that the intelligent model is updated.

16. A base station, characterized in that: The base station includes: one or more processors and a memory; The memory is coupled to the one or more processors, and the memory is used to store computer program codes, where the computer program codes include computer instructions, and the one or more processors call the computer instructions to enable the base station to perform the method according to any one of claims 9 to 15.

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