Method and apparatus in communication node used for wireless communication

Abstract

The invention discloses a method and an apparatus in a communication node used for wireless communication. The communication node stores connection failure information in the first UE variable in response to detection of the connection failure; wherein the connection failure information is at least one of wireless link failure information or switching failure information; the first UE variable indicates whether a connection failure is predicted. According to the scheme provided by the invention, the optimization of the mobility performance of the auxiliary network is facilitated by indicating whether the connection failure is predicted in the first UE variable.

Description

Technical Field

[0001] This application relates to transmission methods and apparatus in wireless communication systems, and more particularly to methods and apparatus for setting connection failure information. Background Technology

[0002] Self-Organizing Networks (SON) include network self-configuration and self-optimization. To optimize mobility performance, existing 3GPP protocols support User Equipment (UE) to store radio link failure information or handover failure information after RLF or HOF, and report the stored radio link failure information or handover failure information based on base station scheduling.

[0003] For existing or future services (such as XR), high UE (User Equipment) mobility or movement between high-density cells can lead to more unexpected handover failures (HOF), radio link failures (RLF), ping-pong phenomena, throughput loss, or premature / late handovers. Considering the potential of AI / ML (Artificial Intelligence / Machine Learning) algorithms to implement proactive solutions and the related progress in AI / ML based on RAN1 and RAN3, 3GPP (the 3rd Generation Partnership Project) adopted the Study Item "Study on AI / ML for mobility in NR" to investigate and evaluate the potential benefits and advantages of AI / ML-assisted mobility for network-triggered L3-based handovers, including RLF prediction or HOF prediction. Summary of the Invention

[0004] The inventors discovered through research that when an RLF or HOF is detected, the UE reporting the predicted RLF or HOF-related information is beneficial for network optimization. Therefore, how the UE stores radio link failure information or handover failure information is a problem that needs to be solved.

[0005] To address the aforementioned problems, this application provides a solution. While the NR system is used as an example in the problem description, this application is also applicable to scenarios such as LTE (Long-Term Evolution), LTE-A (Long-Term Evolution Advanced), 5G+, or 6G systems, achieving similar technical effects to NR systems. Furthermore, although this application provides a specific implementation for RLF, it can also be used in scenarios such as HOF, achieving similar technical effects to RLF. Furthermore, adopting a unified design scheme for different scenarios helps reduce hardware complexity and cost. Furthermore, although this application is initially intended for the Uu air interface, it can also be used for the PC5 interface, achieving similar technical effects to the Uu air interface. Furthermore, although this application is initially intended for terminal-to-base station scenarios, it is also applicable to V2X (Vehicle-to-Everything) scenarios, communication scenarios between terminals and relays, and between relays and base stations, achieving similar technical effects to those in terminal-to-base station scenarios. Furthermore, although this application was initially intended for terminal and base station scenarios, it is also applicable to IAB (Integrated Access and Backhaul) communication scenarios, achieving similar technical effects. Furthermore, although this application was initially intended for terrestrial network (TN) scenarios, it is also applicable to non-terrestrial network (NTN) communication scenarios, achieving similar technical effects. In addition, adopting a unified solution for different scenarios helps reduce hardware complexity and cost.

[0006] As an example, the interpretation of the terminology in this application is based on the definitions in the 3GPP specification protocol TS36 series.

[0007] As an example, the interpretation of terms in this application is based on the definitions in the 3GPP specification protocol TS38 series.

[0008] As an example, the interpretation of terms in this application is based on the definitions in the 3GPP specification protocol TS37 series.

[0009] It should be noted that, unless otherwise specified, the embodiments and features in any node of this application can be applied to any other node. Furthermore, unless otherwise specified, the embodiments and features in any embodiment of this application can be arbitrarily combined with each other.

[0010] This application discloses a method used in a first node of wireless communication, characterized by comprising:

[0011] In response to detecting a connection failure, connection failure information is stored in a first UE variable; wherein the connection failure information is at least one of radio link failure information or handover failure information;

[0012] The first UE variable indicates whether a connection failure is predicted.

[0013] As an example, the problem this application aims to solve includes: how to store prediction information of connection failure; the above method uses the first UE variable to indicate whether connection failure is predicted, thereby solving the above problem.

[0014] As an example, the problem this application aims to solve includes: when to indicate prediction information of connection failure; the above method solves the above problem by detecting connection failure and triggering storage to determine whether connection failure was predicted.

[0015] As an example, the above method is compatible with existing protocols, which helps to reduce the impact of protocols.

[0016] As an example, the above method is beneficial for subsequent reporting of whether connection failure was predicted.

[0017] As an example, the above method helps the network optimize itself based on whether connection failures are predicted.

[0018] As an example, the above method helps the network optimize mobility based on whether connection failure is predicted.

[0019] According to one aspect of this application, the first UE variable indicates a predicted connection failure when a predicted connection failure exists in the first time window; the first UE variable does not indicate a predicted connection failure when no predicted connection failure exists in the first time window; the first time window depends on the time of the detected connection failure.

[0020] As an example, the problem to be solved by this application includes: how to determine whether the first UE variable indicates a predicted connection failure; the above method determines whether the first UE variable indicates a predicted connection failure based on whether there is a predicted connection failure in the first time window, thereby solving the above problem.

[0021] As an example, the above method avoids the indication of unnecessary connection failure prediction information through a first time window.

[0022] As an example, the above method associates detected connection failures with predicted connection failures through a first time window, which helps to assist the network in optimization.

[0023] As an example, the above method is advantageous for controlling the length of the first time window via a network.

[0024] As an example, the above method helps to reduce the impact of the protocol.

[0025] According to one aspect of this application, the first UE variable indicates a predicted connection failure when the detected connection failure occurs within a first time window; and the first UE variable does not indicate a predicted connection failure when the detected connection failure does not occur within the first time window; wherein the first time window depends on the predicted connection failure.

[0026] As an example, the problem to be solved by this application includes: how to determine whether the first UE variable indicates a predicted connection failure; the above method determines whether the first UE variable indicates a predicted connection failure based on whether the detected connection failure is within a first time window, thereby solving the above problem.

[0027] As an example, the above method avoids the indication of unnecessary connection failure prediction information through a first time window.

[0028] As an example, the above method associates detected connection failures with predicted connection failures through a first time window, which helps to assist the network in optimization.

[0029] As an example, the above method is helpful in determining the time interval between the predicted connection failure and the detected connection failure.

[0030] As an example, the above method helps to reduce the impact of the protocol.

[0031] According to one aspect of this application, the step of storing connection failure information in a first UE variable includes: setting a first field in the first UE variable, the first field indicating first time information; wherein, the first UE variable indicates the predicted connection failure; the first time information is related to both the predicted connection failure and the detected connection failure; the detected connection failure occurs after the predicted connection failure.

[0032] As an example, the problem this application aims to solve includes: indicating which of the predicted connection failures are; the above method solves the above problem by indicating first-time information in the first UE variable.

[0033] As an example, the above method helps the network to perform mobility optimization based on first-time information.

[0034] As an example, the above method helps the network optimize the parameters of the intelligent model based on first-time information.

[0035] As an example, the above method helps the network optimize the parameters for detecting connection failure events based on first-time information.

[0036] According to one aspect of this application, storing connection failure information in a first UE variable includes: setting a second field in the first UE variable, the second field indicating the reason for detecting the connection failure; wherein the first UE variable indicates the predicted connection failure; the second field is set to a first candidate value; the first candidate value indicates that the detected connection failure depends on the predicted connection failure; wherein the first UE variable indicates the predicted connection failure.

[0037] As an example, the problem this application aims to solve includes: indicating which of the predicted connection failures are detected; the above method solves the above problem by indicating the reason for detecting the connection failure in the first UE variable.

[0038] As an example, the above method helps the network perform mobility optimization based on the detected reasons for connection failures.

[0039] As an example, the above method helps the network optimize the parameters of the intelligent model based on the detected reasons for connection failures.

[0040] As an example, the above method helps the network optimize the parameters of the event that detects connection failure based on the cause of the connection failure.

[0041] According to one aspect of this application, storing connection failure information in a first UE variable includes: setting a third field in the first UE variable; wherein the first UE variable indicates the predicted connection failure; and the third field indicates the identifier of the smart model used to predict the connection failure.

[0042] As an example, the problem this application aims to solve includes: indicating which of the predicted connection failures are identified; the above method solves the above problem by indicating the identifier of the smart model used to predict the connection failure in the first UE variable.

[0043] As an example, the above method helps the network optimize the intelligent model used to predict connection failures.

[0044] As an example, the above method is beneficial for network optimization and connection failure prediction.

[0045] According to one aspect of this application, it is characterized by comprising:

[0046] In response to the detected connection failure, an RRC connection re-establishment procedure is executed; wherein, the execution of the RRC connection re-establishment procedure includes: selecting a first cell and setting a fourth field in the first UE variable;

[0047] The fourth field indicates whether the first cell relies on prediction.

[0048] As an example, the problem this application aims to solve includes: indicating which predicted connection failures; the above method solves the above problem by indicating in the first UE variable whether the cell selected during the RRC connection re-establishment process depends on prediction.

[0049] As an example, the above method supports selecting the first cell through prediction.

[0050] As an example, the above method supports the facilitating re-establishment of RRC connections.

[0051] As an example, the above method helps to reduce connection failures.

[0052] As an example, the above method is beneficial for optimizing cell selection parameters.

[0053] According to one aspect of this application, it is characterized by comprising:

[0054] The first processor sends a first message, the first message including at least a portion of the connection failure information in the first UE variable.

[0055] According to one aspect of this application, it is characterized by comprising:

[0056] The first processor sends the first UE capability information;

[0057] Wherein, the first UE capability information indicates that the first node supports connection failure prediction; the second message enables the connection failure prediction; the prediction of connection failure depends on the connection failure prediction.

[0058] As an example, the above method notifies the network that the first node supports the wireless connection failure prediction through the first UE capability information, so as to assist the network in configuring the wireless connection failure prediction based on the first UE capability information.

[0059] As an example, the above method facilitates network configuration of the UE.

[0060] According to one aspect of this application, it is characterized by comprising:

[0061] The first processor receives the second message;

[0062] The second message enables the connection failure prediction.

[0063] As an example, the above method is beneficial for network control.

[0064] This application discloses a method used in a second node for wireless communication, characterized by comprising:

[0065] Receive a first message, the first message including at least a portion of the connection failure information in the first UE variable;

[0066] In response to a detected connection failure, the sender of the first message stores connection failure information in a first UE variable; wherein the connection failure information is at least one of radio link failure information or handover failure information; and the first UE variable indicates whether a connection failure has been predicted.

[0067] According to one aspect of this application, the first UE variable indicates a predicted connection failure when a predicted connection failure exists in the first time window; the first UE variable does not indicate a predicted connection failure when no predicted connection failure exists in the first time window; the first time window depends on the time of the detected connection failure.

[0068] According to one aspect of this application, the step of storing connection failure information in a first UE variable includes: setting a first field in the first UE variable, the first field indicating first time information; wherein, the first UE variable indicates the predicted connection failure; the first time information is related to both the predicted connection failure and the detected connection failure; the detected connection failure occurs after the predicted connection failure.

[0069] According to one aspect of this application, storing connection failure information in a first UE variable includes: setting a second field in the first UE variable, the second field indicating the reason for detecting the connection failure; wherein the first UE variable indicates the predicted connection failure; the second field is set to a first candidate value; the first candidate value indicates that the detected connection failure depends on the predicted connection failure; wherein the first UE variable indicates the predicted connection failure.

[0070] According to one aspect of this application, storing connection failure information in a first UE variable includes: setting a third field in the first UE variable; wherein the first UE variable indicates the predicted connection failure; and the third field indicates the identifier of the smart model used to predict the connection failure.

[0071] According to one aspect of this application, in response to the detected connection failure, the sender of the first message performs an RRC connection re-establishment procedure; wherein performing the RRC connection re-establishment procedure includes: selecting a first cell and setting a fourth field in the first UE variable; the fourth field indicates whether the first cell relies on prediction.

[0072] According to one aspect of this application, it is characterized by comprising:

[0073] Receive first UE capability information;

[0074] Send a second message;

[0075] Wherein, the first UE capability information indicates that the first node supports connection failure prediction; the second message enables the connection failure prediction; the prediction of connection failure depends on the connection failure prediction.

[0076] This application discloses a method used in a third node for wireless communication, characterized by comprising:

[0077] Receive first UE capability information;

[0078] Wherein, the first UE capability information indicates that the sender of the first UE capability information supports connection failure prediction; in response to detecting a connection failure, the sender of the first UE capability information stores connection failure information in a first UE variable; the connection failure information is at least one of radio link failure information or handover failure information; the first UE variable indicates whether a connection failure has been predicted; the first UE variable indicating whether a connection failure has been predicted depends on the connection failure prediction.

[0079] According to one aspect of this application, it is characterized by comprising:

[0080] Send a second message;

[0081] The second message enables the connection failure prediction.

[0082] This application discloses a first node used for wireless communication, characterized in that it comprises:

[0083] The first processor, in response to detecting a connection failure, stores connection failure information in a first UE variable; wherein the connection failure information is at least one of radio link failure information or handover failure information;

[0084] The first UE variable indicates whether a connection failure is predicted.

[0085] This application discloses a second node used for wireless communication, characterized in that it comprises:

[0086] A second receiver receives a first message, the first message including at least a portion of the connection failure information in the first UE variable;

[0087] In response to a detected connection failure, the sender of the first message stores connection failure information in a first UE variable; wherein the connection failure information is at least one of radio link failure information or handover failure information; and the first UE variable indicates whether a connection failure has been predicted.

[0088] This application discloses a third node used for wireless communication, characterized in that it comprises:

[0089] The third receiver receives the capability information of the first UE.

[0090] Wherein, the first UE capability information indicates that the sender of the first UE capability information supports connection failure prediction; in response to detecting a connection failure, the sender of the first UE capability information stores connection failure information in a first UE variable; the connection failure information is at least one of radio link failure information or handover failure information; the first UE variable indicates whether a connection failure has been predicted; the first UE variable indicating whether a connection failure has been predicted depends on the connection failure prediction. Attached Figure Description

[0091] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0092] Figure 1 A flowchart illustrating the setting of a first UE variable according to an embodiment of this application is shown;

[0093] Figure 2 A schematic diagram of a network architecture according to an embodiment of this application is shown;

[0094] Figure 3 A schematic diagram of an embodiment of a wireless protocol architecture for the user plane and control plane according to an embodiment of this application is shown;

[0095] Figure 4 A schematic diagram of a first communication device and a second communication device according to an embodiment of this application is shown;

[0096] Figure 5 A flowchart illustrating a wireless signal transmission process according to an embodiment of this application is shown;

[0097] Figure 6 A schematic diagram illustrating a first UE variable indicating whether a connection failure is predicted, according to an embodiment of this application, is shown.

[0098] Figure 7 A schematic diagram showing a first UE variable indicating first time information according to an embodiment of this application is illustrated;

[0099] Figure 8 A schematic diagram illustrating a first UE variable indicating the cause of a connection failure according to an embodiment of this application is shown;

[0100] Figure 9 A schematic diagram is shown illustrating a first UE variable indicating an identifier of the smart model used to predict a connection failure, according to an embodiment of this application;

[0101] Figure 10 A schematic diagram of a first UE variable represented by ASN.1 according to an embodiment of this application is shown;

[0102] Figure 11 A structural block diagram of a processing apparatus for a first node according to an embodiment of this application is shown;

[0103] Figure 12 A structural block diagram of a processing apparatus for a second node according to an embodiment of this application is shown;

[0104] Figure 13 A flowchart illustrating a first state according to an embodiment of this application is shown;

[0105] Figure 14 A schematic diagram of a first notification according to an embodiment of this application is shown;

[0106] Figure 15 A schematic diagram of an intelligent model according to an embodiment of this application is shown;

[0107] Figure 16 A schematic diagram illustrating the deployment of intelligent functions in a RAN domain according to an embodiment of this application is shown;

[0108] Figure 17 A schematic diagram illustrating the deployment of UE smart functions according to an embodiment of this application is shown;

[0109] Figure 18 A flowchart based on artificial intelligence or machine learning according to an embodiment of this application is shown;

[0110] Figure 19 A structural block diagram of a processing apparatus for a third node according to an embodiment of this application is shown. Detailed Implementation

[0111] The technical solution of this application will be further described in detail below with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other.

[0112] Example 1

[0113] Example 1 illustrates a flowchart of setting a first UE variable according to an embodiment of this application, as shown in the attached diagram. Figure 1 As shown. (Attached) Figure 1 In the diagram, each box represents a step. It is particularly important to emphasize that the order of the boxes does not represent the chronological order of the steps they represent.

[0114] In Embodiment 1, in step 101, the first node in this application stores connection failure information in a first UE variable as a response to detecting a connection failure; wherein the connection failure information is at least one of wireless link failure information or handover failure information; wherein the first UE variable indicates whether a connection failure is predicted.

[0115] As an example, a response to a detected connection failure refers to: when the detected connection fails.

[0116] As an example, a response to a detected connection failure refers to: if the detected connection fails.

[0117] As an example, a response to a detected connection failure refers to the situation after the connection failure is detected.

[0118] As an example, a response to a detected connection failure refers to the following: the detection of a connection failure is accompanied by the following.

[0119] As an example, the connection failure detection is directed at the first serving cell.

[0120] As an example, the connection failure detection targets the cell group to which the first serving cell belongs.

[0121] As an example, the detection of connection failure is targeted at the target cell.

[0122] As an example, the first serving cell is a PCell (Primary Cell).

[0123] As an example, the first serving cell is a PCell, and the cell group to which the first serving cell belongs is an MCG (Master Cell Group).

[0124] As an example, the first node is configured to serve only one cell.

[0125] As an example, the first node is configured to PCell only.

[0126] As an example, the first node is configured with only one CG (Cell Group).

[0127] As an example, the first node is configured with a PCell and at least one SCell (Secondary Cell).

[0128] As an example, the first node is configured with MCG and SCG (Secondary Cell Group).

[0129] As an example, the detection of connection failure and the prediction of connection failure are directed at secondary links.

[0130] As an example, the detection of connection failure and the prediction of connection failure are for the NR-Uu port.

[0131] As an example, the detection of connection failure and the prediction of connection failure are for the Uu port.

[0132] As an example, detecting a connection failure means detecting an RLF (Relational Link Failure), and predicting a connection failure means predicting an RLF.

[0133] As an example, the detection of connection failure is the detection of RLF, and the prediction of connection failure is the prediction of HOF.

[0134] As an example, the RLF mentioned in this application refers to the MCG RLF.

[0135] As an example, the RLF mentioned in this application refers to the PCell RLF.

[0136] As an example, the RLF mentioned in this application refers to the target PCell RLF.

[0137] As an example, the detection of connection failure means that the MCG is considered to have failed to connect, i.e., MCG RLF (consider radio link failure to be detected for the MCG, i.e., MCG RLF).

[0138] As an example, the detected connection failure includes: T310 expired.

[0139] As an example, the detected connection failure means that T310 has expired.

[0140] As an example, the detected connection failure includes: T312 expired.

[0141] As an example, the detected connection failure means that T312 has expired.

[0142] As one example, the detected connection failure includes: a random access problem occurring.

[0143] As an example, the detected connection failure refers to a random access problem occurring.

[0144] As an example, the detected connection failure means that a random access problem occurs and T300, T301, T304, T311, T316 and T319 are not running and the SDT process is not in progress.

[0145] As an example, the detection of connection failure refers to receiving a random access problem indication from the MCG MAC.

[0146] As an example, the detected connection failure means that a random access problem indication is received from the MCG MAC and T300, T301, T304, T311, T316 and T319 are not running and the SDT process is not in progress.

[0147] As one example, the detected connection failure includes: continuous uplink LBT failure.

[0148] As an example, the detected connection failure refers to: continuous uplink LBT failures.

[0149] As an example, the detection of connection failure refers to receiving a continuous uplink LBT failure indication from the MCG MAC.

[0150] As an example, the detection of connection failure includes: reaching the maximum number of retransmissions allowed by the RLC.

[0151] As an example, the detection of connection failure means reaching the maximum number of retransmissions allowed by the RLC.

[0152] As an example, the detection of connection failure means that the maximum number of retransmissions in the RLC has been reached and the SDT process is no longer in progress.

[0153] As an example, the detection of connection failure refers to receiving an indication from the MCG RLC that the number of retransmissions has reached its maximum value.

[0154] As an example, detecting connection failure means detecting HOF, and predicting connection failure means predicting HOF.

[0155] As an example, the detection of connection failure is the detection of HOF, and the prediction of connection failure is the prediction of RLF.

[0156] As an example, the detected connection failure includes: T304 expired.

[0157] As one example, detecting connection failure includes detecting synchronization reconfiguration failure.

[0158] As an example, the detected connection failure is: detected synchronization reconfiguration failure.

[0159] As an example, the detected connection failure means that T304 has expired.

[0160] As an example, the detection of connection failure triggers the setting of the first UE variable.

[0161] As an example, the first UE variable is for the detected connection failure.

[0162] As an example, the first UE variable records the log information of the detected connection failure.

[0163] As an example, the first UE variable is a UE variable.

[0164] As an example, the first UE variable is dedicated to radio link failure information or handover failure information.

[0165] As an example, the first UE variable is VarRLF-Report.

[0166] As an example, the first UE variable is VarConnEstFailReport.

[0167] As an example, the first UE variable is VarConnEstFailReportList.

[0168] As an example, setting the first UE variable means storing wireless link failure information in the first UE variable; the first UE variable is VarRLF-Report.

[0169] As an example, setting the first UE variable means storing handover failure information in the first UE variable; the first UE variable is VarRLF-Report.

[0170] As an example, the detected connection failure is an RLF; the connection failure information is the wireless link failure information.

[0171] As an example, the detected connection failure is HOF; the connection failure information is the handover failure information.

[0172] As an example, the detected connection failure is HOF; the connection failure information is the handover failure information and the wireless link failure information.

[0173] As an example, the detected connection failure is an RLF; the connection failure information is the wireless link failure information and the handover failure information.

[0174] As an example, the first UE variable indicates at least the identifier of the first node and the identifier of the first cell.

[0175] As an example, the detected connection failure is an RLF; when the connection failure is detected, T304 is running.

[0176] As a sub-example of the above embodiment, the detected connection failure is for the target PCell; the first serving cell is the source PCell.

[0177] As a sub-example of the above embodiments, the identifier of the first node is the C-RNTI of the first node in the first serving cell.

[0178] As an example, the detected connection failure is an RLF; when a connection failure is detected, T304 is not running.

[0179] As a sub-example of the above embodiment, the detected connection failure is directed at the first serving cell.

[0180] As a sub-implementation of the above embodiments, the identifier of the first node is the C-RNTI of the first node in the first serving cell.

[0181] As an example, the detected connection failure is HOF.

[0182] As a sub-implementation of the above embodiment, the identifier of the first node is the C-RNTI of the first node in the second cell; the second cell is the source PCell.

[0183] As an example, the first UE variable explicitly indicates whether a connection failure is predicted.

[0184] As an example, the first UE variable implicitly indicates whether a connection failure is predicted.

[0185] As an example, at least one field in the first UE variable indicates whether a connection failure is predicted.

[0186] As an example, one field in the first UE variable indicates whether a connection failure is predicted.

[0187] As a sub-implementation of the above embodiments, the first UE variable indicating a predicted connection failure means that the field is set to 1; the first UE variable not indicating a predicted connection failure means that the field is set to 0.

[0188] As a sub-implementation of the above embodiments, the first UE variable indicating a predicted connection failure means that the field is set to true; the first UE variable not indicating a predicted connection failure means that the field is set to false.

[0189] As one embodiment, the first UE variable includes a first information block; if a connection failure is predicted, the first information block indicates that a connection failure has been predicted; if a connection failure is not predicted, the first UE variable indicates that a connection failure has not been predicted.

[0190] As one embodiment, the first UE variable indicating the predicted connection failure means that: the first UE variable includes a first information block; the first UE variable not indicating the predicted connection failure means that: the first UE variable does not include the first information block; the first information block indicates the predicted connection failure.

[0191] As an example, if a connection failure is predicted, the first UE variable indicates that a connection failure has been predicted; if a connection failure is not predicted, the first UE variable does not indicate that a connection failure has been predicted; if a connection failure is predicted, the first UE variable indicates that a connection failure has been predicted; if a connection failure is not predicted, the first UE variable indicates that a connection failure has not been predicted.

[0192] As one embodiment, the prediction of connection failure includes: being instructed to predict the connection failure.

[0193] As one embodiment, the prediction of connection failure includes: prediction information related to the indicated connection failure.

[0194] As an example, predicting connection failure includes: obtaining information related to connection failure through prediction.

[0195] As one embodiment, the prediction of connection failure includes: receiving prediction information related to connection failure.

[0196] As one embodiment, the prediction of connection failure includes: receiving prediction information related to connection failure from the intelligent module.

[0197] As an example, the prediction information related to the connection failure indicates the cell group to which the connection failure occurred.

[0198] As an example, the prediction information related to the connection failure indicates the type of the connection failure; the type of connection failure is either RLF or HOF.

[0199] As an example, the prediction information related to the connection failure indicates the metric of the connection failure.

[0200] As an example, the metric for connection failure includes the probability of connection failure.

[0201] As an example, the metric for connection failure includes the likelihood of the connection failure occurring.

[0202] As an example, the metric for connection failure includes the probability of connection failure.

[0203] As an example, the metric for connection failure includes the confidence level of the connection failure.

[0204] As an example, the metric for connection failure includes the confidence level of the connection failure.

[0205] As an example, the metric for connection failure is in the time domain.

[0206] As an example, the metric for connection failure is in the spatial domain.

[0207] As an example, the metric for connection failure is in the frequency domain.

[0208] As an example, the prediction information related to the connection failure indicates a CDF, which indicates a metric of the connection failure in the time domain.

[0209] As an example, the prediction information related to connection failure indicates that a connection failure is predicted.

[0210] As an example, the prediction information related to connection failure only indicates that a connection failure is predicted.

[0211] As an example, predicting connection failure means: predicting that the connection will fail.

[0212] As an example, the prediction information related to the connection failure exists only when the connection is predicted to fail.

[0213] As an example, a prediction that a connection failure will trigger prediction information related to the connection failure is provided.

[0214] As an example, the prediction of connection failure means that the predicted connection failure will occur within a specified time interval.

[0215] As an example, the prediction of connection failure means that the predicted connection failure will occur within a specified time.

[0216] As an example, the prediction of connection failure means that the predicted connection failure will occur at the end of a specified time interval.

[0217] As an example, predicting a connection failure is triggered when the number of consecutive out-of-step indications reaches a threshold.

[0218] As an example, predicting that the wireless link quality is worse than a threshold triggers the predicted connection failure.

[0219] As an example, a predicted connection failure is triggered when a timer expires.

[0220] As an example, a prediction of a connection failure is triggered when a counter reaches a threshold.

[0221] As an example, the prediction of connection failure is triggered when a metric indicating a predicted connection failure reaches a threshold.

[0222] As one example, how the predicted connection failure is triggered depends on the UE implementation.

[0223] As an example, how the predicted connection failure is triggered depends on the network configuration.

[0224] As an example, how the prediction of connection failure is triggered depends on the smart model used for predicting connection failure.

[0225] As an example, the predicted connection failure probability is relatively high.

[0226] As an example, the predicted measure of connection failure reaches a threshold.

[0227] As an example, the measure of connection failure is probability, and reaching means greater than.

[0228] As an example, the measure of connection failure is probability, and reaching means greater than or equal to.

[0229] As an example, the metric for connection failure is confidence level, and "reaching" means greater than.

[0230] As an example, the metric for connection failure is confidence level, and "reaching" means greater than or equal to.

[0231] As an example, the connection failure-related prediction information indicates the predicted connection failure information.

[0232] As an example, the connection failure-related prediction information explicitly indicates the specified time interval.

[0233] As an example, the prediction information related to connection failure implicitly indicates the specified time interval.

[0234] As an example, the prediction information related to connection failure includes the specified time interval.

[0235] As an example, the prediction information related to connection failure includes the specified time.

[0236] As one embodiment, the connection failure-related prediction information includes a specified duration, which indicates the time interval between the predicted connection failure and the predicted connection failure.

[0237] As an example, the prediction information related to connection failure includes a specified duration, which indicates the specified time.

[0238] As an example, the prediction information related to connection failure includes a specified duration, which indicates the specified time interval.

[0239] As an example, the prediction information related to connection failure includes a specified duration, which is the duration of the specified time interval.

[0240] As an example, the specified time interval is determined by the first node itself based on the prediction information related to the connection failure.

[0241] As an example, the specified time interval is determined by the first node itself based on the connection failure in the time domain CDF indicated by the prediction information related to the connection failure.

[0242] As an example, the specified time interval is determined by the first node itself based on the specified time indicated by the prediction information related to the connection failure.

[0243] As an example, the specified time is the time when the predicted connection failure metric reaches a threshold.

[0244] As an example, the specified time is the predicted time of connection failure.

[0245] As an example, the first node predicts connection failure based on the UE.

[0246] As an example, the first node anticipates connection failures based on intelligent prediction.

[0247] As an example, the intelligence is AI.

[0248] As one example, the intelligence is ML.

[0249] As an example, the intelligence is AI / ML.

[0250] As one example, the intelligence includes at least one of training or inference.

[0251] As one example, the intelligence includes prediction.

[0252] As an example, the first node predicts connection failure based on at least one intelligent model.

[0253] As an example, the at least one smart model is indicated by RRC signaling.

[0254] As an example, the at least one smart model is selected by the UE itself.

[0255] As an example, the at least one smart model is implemented based on the UE.

[0256] As an example, the at least one smart model is activated by MAC CE.

[0257] As an example, the at least one smart model is activated by DCI.

[0258] As an example, the at least one smart model is a smart model.

[0259] As an example, the at least one smart model is a plurality of smart models.

[0260] As an example, the RRC signaling indicates the identifier of the at least one smart model.

[0261] As an example, an intelligent model is indexed by an identifier.

[0262] As an example, the identifier of a smart model is a non-negative integer.

[0263] As an example, the identifier of a smart model includes a region identifier.

[0264] As an example, the identifier of a smart model includes a region identifier and a non-negative integer; the non-negative integer indicates the smart model within the range indicated by the region identifier.

[0265] As an example, the identifier of a smart model includes a region identifier and a type identifier; the non-negative integer indicates the smart model within the range indicated by the region identifier.

[0266] As an example, the smart module predicts a connection failure.

[0267] As an example, part of the smart module predicts connection failure.

[0268] As an example, the intelligent module predicts connection failure through inference.

[0269] As one embodiment, the intelligent module has at least one of the following: training function or inference function.

[0270] As one example, the intelligent module carries an intelligent model.

[0271] As an example, the intelligent module is a carrier of the intelligent model.

[0272] As one example, the intelligent module processes intelligent models.

[0273] As an example, the intelligent module runs an intelligent model.

[0274] As an example, the intelligent module runs an intelligent model.

[0275] As one embodiment, the first node receives a first notification indicating that a connection failure was predicted.

[0276] As a sub-implementation of the above embodiments, the RRC protocol entity of the first processor receives the first notification.

[0277] As a sub-implementation of the above embodiment, the first node receives the first notification in the RRC sublayer.

[0278] As a sub-implementation of the above embodiment, the second node sends the first notification.

[0279] As a sub-implementation of the above embodiments, the intelligent module of the first processor sends the first notification.

[0280] As a sub-implementation of the above embodiment, the network-side node sends the first notification.

[0281] As a sub-implementation of the above embodiment, the first node sends the first notification.

[0282] As a sub-implementation of the above embodiments, the first notification indicates prediction information related to the connection failure.

[0283] As a sub-implementation of the above embodiment, the first notification is sent by a protocol layer outside the RRC sublayer of the first node.

[0284] As a sub-implementation of the above embodiment, a protocol layer outside the RRC sublayer is a layer lower than the RRC sublayer.

[0285] As a sub-implementation of the above embodiment, a protocol layer outside the RRC sublayer is a higher layer than the RRC sublayer.

[0286] Example 2

[0287] Example 2 illustrates a schematic diagram of a network architecture according to an embodiment of this application, as shown in the attached diagram. Figure 2 As shown. (Attached) Figure 2The network architecture 200 is described. The network architecture 200 is a 5G NR (New Radio) / LTE (Long-Term Evolution) / LTE-A (Long-Term Evolution Advanced) system, or a 5G+ network architecture, or a 6G network architecture, or a future evolution network architecture of 3GPP; the network architecture 200 may be referred to as 5GS (5G System) / EPS (Evolved Packet System), or 6GS (6G System); the network architecture 200 includes at least one of UE (User Equipment) 201, RAN (Radio Access Network) 202, core network 210, HSS (Home Subscriber Server) / UDM (Unified Data Management) 220, and Internet service 230. The network architecture 200 can interconnect with other access networks, but these entities / interfaces are not shown for simplicity. As shown, the network architecture 200 provides packet-switched services; however, those skilled in the art will readily understand that the various concepts presented throughout this application can be extended to networks providing circuit-switched services or other cellular networks. The RAN includes node 203 and other nodes 204. Node 203 provides user and control plane protocol termination 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, base transceiver station, radio base station, radio transceiver, transceiver function, basic service set (BSS), extended service set (ESS), TRP (transmitter-receiver node), or some other suitable term. The core network 210 is a 5GC (5G Core Network) / EPC (Evolved Packet Core), or the core network 210 is a 6GC; node 203 provides UE 201 with an access point to the core network 210. Examples of UE201 include cellular phones, smartphones, Session Initiation Protocol (SIP) phones, laptops, 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 IoT devices, machine-type communication devices, land vehicles, automobiles, wearable devices, or any other similar functional devices.Those skilled in the art may also refer to UE201 as a mobile station, subscriber station, mobile unit, subscriber unit, radio unit, remote unit, mobile device, radio device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, radio terminal, remote terminal, handheld device, user agent, mobile client, client, or any other suitable term. Node 203 is connected to the core network 210 via the S1 / NG interface. The core network 210 includes MME (Mobility Management Entity) / AMF (Authentication Management Field) / SMF (Session Management Function) 211, other MME / AMF / SMF 214, S-GW (Service Gateway) / UPF (User Plane Function) 212, and P-GW (Packet Data Network Gateway) / UPF 213. MME / AMF / SMF 211 is the control node that handles signaling between UE201 and the core network 210. In general, the MME / AMF / SMF211 provides bearer and connection management. All user IP (Internet Protocol) packets are transmitted through the S-GW / UPF212, which is itself connected to the P-GW / UPF213. The P-GW provides UE IP address allocation and other functions. The P-GW / UPF213 connects to Internet service 230. Internet service 230 includes operator-compliant Internet Protocol services, specifically including the Internet, intranet, IMS (IP Multimedia Subsystem), and packet-switched streaming services.

[0288] As an example, the UE201 corresponds to the first node in this application.

[0289] As an example, the UE201 is a user equipment (UE).

[0290] As an example, the UE201 is a base station (BS).

[0291] As an example, the UE201 is a relay device.

[0292] As an example, the UE201 is a gateway device.

[0293] As an example, node 203 corresponds to the second node in this application.

[0294] As one example, node 203 is a base station device.

[0295] As an example, node 203 is a user equipment.

[0296] As one example, node 203 is a relay device.

[0297] As one example, node 203 is a gateway device.

[0298] Typically, UE201 is a user equipment and node203 is a base station device.

[0299] Typically, UE201 is a user equipment, and node203 is a user equipment.

[0300] Typically, UE201 is a base station device, and node203 is a base station device.

[0301] As one example, the user equipment is configured with an intelligent module.

[0302] As an example, the user equipment supports intelligent functions.

[0303] As one example, the user equipment supports intelligent modules.

[0304] As an example, the user equipment supports intelligent models.

[0305] As an example, the user equipment supports an intelligent model for predicting connection failures.

[0306] As an example, the user equipment supports connection failure prediction.

[0307] As an example, the user equipment supports RLF prediction and HOF prediction.

[0308] As an example, the user equipment supports only one of RLF prediction and HOF prediction.

[0309] As an example, the user equipment supports 3GPP Release 19.

[0310] As one example, the user equipment supports 5G.

[0311] As one example, the user equipment supports 6G.

[0312] As an example, the user equipment supports Radio Link Monitoring (RLM).

[0313] As one example, the user equipment supports handover.

[0314] As an example, the user equipment supports CHO.

[0315] As one example, the user equipment supports cell selection.

[0316] As one example, the user equipment supports transmission over a non-terrestrial network (NTN).

[0317] As an example, the user equipment supports terrestrial network transmission.

[0318] As an example, the user equipment supports dual connection (DC) transmission.

[0319] As one embodiment, the user equipment includes devices that support low-latency, high-reliability transmission.

[0320] As one embodiment, the user equipment can be a mobile terminal, such as a mobile phone, iPad, computer, watch, or ring; the user equipment can also be a wearable device, such as a watch, ring, shoes, hat, clothing, or glasses; the user equipment can also be an aircraft; the user equipment can also be a vehicle-mounted terminal; the user equipment can also be a shipborne terminal; the user equipment can also be an Internet of Things (IoT) terminal; the user equipment can also be an industrial IoT terminal; the user equipment can also be a testing device; the user equipment can also be a signaling tester; the user equipment can also be an IAB (Integrated Access and Backhaul)-MT.

[0321] As one example, the base station equipment includes an intelligent module.

[0322] As an example, the base station equipment supports a smart model.

[0323] As an example, the base station equipment supports intelligent functions.

[0324] As an example, the base station equipment supports the selection of intelligent models.

[0325] As an example, the base station equipment supports the configuration of intelligent models.

[0326] As an example, the base station equipment supports configuration for connection failure prediction.

[0327] As an example, the base station equipment supports transmission over non-terrestrial networks.

[0328] As one example, the base station equipment supports transmission over a terrestrial network.

[0329] As one embodiment, the base station equipment includes a Base Transceiver Station (BTS).

[0330] As one embodiment, the base station equipment includes a NodeB (NB); the NodeB can be a gNB, an eNB, an ng-eNB, or an en-gNB; the base station equipment can include a CU (Centralized Unit); the base station equipment can also include a DU (Distributed Unit); the base station equipment can also include a TRP (Transmitter Receiver Point).

[0331] As one embodiment, the base station equipment may be a macrocell base station, a microcell base station, a picocell base station, or a femtocell base station; the base station equipment may also be a flight platform equipment or a satellite equipment; the base station equipment may also be a testing equipment or a signaling tester; the base station equipment may also be a gateway equipment; the base station equipment may also be an IAB device; the IAB device includes at least one of IAB-node, IAB-donor, IAB-donor-CU, IAB-donor-DU, IAB-DU, or IAB-MT.

[0332] As one embodiment, the relay device may include a relay; the relay may be an L3 relay or an L2 relay; the relay device may also include a router; the relay device may also include a switch; the relay device may also include a gateway device; the relay device may also include at least a portion of user equipment; the relay device may also include at least a portion of base station equipment.

[0333] Example 3

[0334] Example 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for a user plane and a control plane according to this application, as shown in the attached diagram. Figure 3As shown. Figure 3 This is a schematic diagram illustrating an embodiment of a radio protocol architecture for the user plane 350 and the control plane 300. Figure 3 The radio protocol architecture for control plane 300 is illustrated using 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. L1 layer will be referred to as PHY301 in this document. Layer 2 (L2 layer) 305 sits above PHY301 and includes the MAC (Medium Access Control) sublayer 302, the RLC (Radio Link Control) sublayer 303, and the PDCP (Packet Data Convergence Protocol) sublayer 304. The PDCP sublayer 304 provides multiplexing between different radio bearers and logical channels. It also provides security through encrypted data packets and cross-area mobility support. The RLC sublayer 303 provides segmentation and reassembly of upper-layer packets, retransmission of lost packets, and packet reordering to compensate for out-of-order reception due to HARQ (Hybrid Automatic Repeat Request). MAC sublayer 302 provides multiplexing between the logical and transport channels. MAC sublayer 302 is also responsible for allocating various radio resources (e.g., resource blocks) within a cell. MAC sublayer 302 is also responsible for HARQ operations. The RRC (Radio Resource Control) sublayer 306 in Layer 3 (L3) of the control plane 300 is responsible for acquiring 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) and Layer 2 (L2). The radio protocol architecture in the user plane 350 is substantially the same as the corresponding layers and sublayers in the control plane 300 for Physical Layer 351, PDCP sublayer 354 in L2 Layer 355, RLC sublayer 353 in L2 Layer 355, and MAC sublayer 352 in L2 Layer 355. However, PDCP sublayer 354 also provides header compression for upper layer packets to reduce radio transmission overhead. The L2 layer 355 in the user plane 350 also includes the SDAP (Service Data Adaptation Protocol) sublayer 356. The SDAP sublayer 356 is responsible for the mapping between QoS streams and data radio bearers (DRBs) to support service diversity.

[0335] As an example, Appendix Figure 3The wireless protocol architecture described herein is applicable to the first node in this application.

[0336] As an example, Appendix Figure 3 The wireless protocol architecture described herein is applicable to the second node in this application.

[0337] As an example, a connection failure is predicted at a protocol layer.

[0338] As an example, the protocol layer is the... Figure 3 This is a protocol layer shown.

[0339] As an example, the protocol layer is the... Figure 3 A protocol layer outside of the protocol layer shown.

[0340] As one example, the intelligent module is the protocol entity corresponding to the protocol layer.

[0341] As one example, the smart module is located at a protocol layer.

[0342] As an example, the first message in this application is generated in the RRC306.

[0343] As an example, the first message in this application is generated by MAC302 or MAC352.

[0344] As an example, the first message in this application is generated by the PHY301 or PHY351.

[0345] As an example, the first UE capability information in this application is generated in the RRC306.

[0346] As an example, the first UE capability information in this application is generated by MAC302 or MAC352.

[0347] As an example, the first UE capability information in this application is generated in the PHY301 or PHY351.

[0348] As an example, the second message in this application is generated in the RRC306.

[0349] As an example, the second message in this application is generated by MAC302 or MAC352.

[0350] As an example, the second message in this application is generated in the PHY301 or PHY351.

[0351] Example 4

[0352] Example 4 shows schematic diagrams of a first communication device and a second communication device according to this application, as shown in the appendix. Figure 4 As shown. Figure 4 This is a block diagram of a first communication device 450 and a second communication device 410 communicating with each other in the access network.

[0353] The first communication device 450 includes a controller / processor 459, a memory 460, a data source 467, a transmitting processor 468, a receiving processor 456, a multi-antenna transmitting processor 457, a multi-antenna receiving processor 458, a transmitter / receiver 454, and an antenna 452.

[0354] The second communication device 410 includes a controller / processor 475, a memory 476, a receiver processor 470, a transmitter processor 416, a multi-antenna receiver processor 472, a multi-antenna transmitter processor 471, a transmitter / receiver 418, and an antenna 420.

[0355] In the 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 L2 layer functionality. In the 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 retransmitting 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). Transmit processor 416 performs encoding and interleaving to facilitate forward error correction (FEC) at the second communication device 410, and mapping of signal clusters based on various modulation schemes (e.g., Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying (QPSK), M-Phase Shift Keying (M-PSK), M-QAM). Multi-antenna transmit processor 471 performs digital spatial precoding on the encoded and modulated symbols, including codebook-based and non-codebook-based precoding, and beamforming processing, generating one or more spatial streams. Transmit processor 416 then maps each spatial stream to subcarriers, multiplexes it with a reference signal (e.g., a pilot) in the time and / or frequency domains, and subsequently uses inverse fast Fourier transform (IFFT) to generate a physical channel carrying the time-domain multicarrier symbol stream. Multi-antenna transmit processor 471 then performs transmit analog precoding / beamforming operations on the time-domain multicarrier symbol stream. Each transmitter 418 converts the baseband multicarrier symbol stream provided by the multi-antenna transmitter processor 471 into an radio frequency stream, which is then provided to different antennas 420.

[0356] 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 radio frequency carrier and converts the radio frequency stream into a baseband multicarrier symbol stream, which is then provided to the receiver processor 456. The receiver processor 456 and the multi-antenna receiver processor 458 implement various signal processing functions of the L1 layer. The multi-antenna receiver processor 458 performs receive analog precoding / beamforming operations on the baseband multicarrier symbol stream from the receiver 454. The receiver processor 456 uses a Fast Fourier Transform (FFT) to convert the baseband multicarrier symbol stream after the receive analog precoding / beamforming operations 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 receiver processor 456, where the reference signal is used for channel estimation, and the data signal is recovered in the multi-antenna receiver processor 458 after multi-antenna detection to recover any spatial stream destined for the first communication device 450. Symbols on each spatial stream are demodulated and recovered in the receive processor 456, generating soft decisions. The receive 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 over 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 Layer 2. The controller / processor 459 may be associated with a memory 460 storing program code and data. The memory 460 may be referred to as computer-readable media. In the transmission from the second communication device 410 to the first communication device 450, the controller / processor 459 provides multiplexing, packet reassembly, decryption, header decompression, and control signal processing between the transport and logical channels to recover upper-layer data packets from the core network. The upper-layer data packets are then provided to all protocol layers above Layer 2. Various control signals may also be provided to Layer 3 for Layer 3 processing.

[0357] 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 functions 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, implementing L2 layer functions for the user plane and control plane. The controller / processor 459 is also responsible for retransmitting lost packets and signaling to the second communication device 410. Transmit processor 468 performs modulation mapping and channel coding processing, while multi-antenna transmit processor 457 performs digital multi-antenna spatial precoding, including codebook-based and non-codebook-based precoding, and beamforming processing. Subsequently, transmit processor 468 modulates the generated spatial stream into a multi-carrier / single-carrier symbol stream. After analog precoding / beamforming operations in multi-antenna transmit processor 457, the stream is provided to different antennas 452 via transmitter 454. Each transmitter 454 first converts the baseband symbol stream provided by multi-antenna transmit processor 457 into a radio frequency symbol stream before providing it to antenna 452.

[0358] 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 receiving 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 radio frequency signals through its corresponding antenna 420, converts the received radio frequency signals into baseband signals, and provides the baseband signals to the multi-antenna receiving processor 472 and the receiving processor 470. The receiving processor 470 and the multi-antenna receiving processor 472 jointly implement the L1 layer functions. The controller / processor 475 implements the L2 layer functions. The controller / processor 475 may be associated with a memory 476 that stores program code and data. The memory 476 may be referred to as computer-readable media. In the transmission from the first communication device 450 to the second communication device 410, the controller / processor 475 provides multiplexing between the transmission and logical channels, packet reassembly, decryption, header decompression, and control signal processing to recover upper-layer data packets from the UE 450. Upper-layer packets from the controller / processor 475 can be provided to the core network.

[0359] As one 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 with the at least one processor, and the first communication device 450 at least: stores connection failure information in a first UE variable in response to detecting a connection failure; wherein the connection failure information is at least one of radio link failure information or handover failure information; wherein the first UE variable indicates whether a connection failure is predicted.

[0360] As one embodiment, the first communication device 450 includes: a memory storing a computer-readable instruction program that generates actions when executed by at least one processor, the actions including: storing connection failure information in a first UE variable in response to detecting a connection failure; wherein the connection failure information is at least one of radio link failure information or handover failure information; wherein the first UE variable indicates whether a connection failure is predicted.

[0361] As one 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: receives a first message, the first message including at least a portion of connection failure information in a first UE variable; wherein, in response to detecting a connection failure, the sender of the first message stores the connection failure information in the first UE variable; wherein the connection failure information is at least one of radio link failure information or handover failure information; the first UE variable indicates whether a connection failure has been predicted.

[0362] As one embodiment, the second communication device 410 includes: a memory storing a computer-readable instruction program that, when executed by at least one processor, produces actions including: receiving a first message, the first message including at least a portion of connection failure information in a first UE variable; wherein, as a response to detecting a connection failure, the sender of the first message stores the connection failure information in the first UE variable; wherein the connection failure information is at least one of radio link failure information or handover failure information; the first UE variable indicates whether a connection failure has been predicted.

[0363] As an example, the first communication device 450 predicts the predicted connection failure.

[0364] As one embodiment, the first communication device 450 includes the intelligent module.

[0365] As an example, the second communication device 410 predicts the predicted connection failure.

[0366] As an example, at least one of the antenna 452, the receiver 454, the receiving processor 456, and the controller / processor 459 is used to receive the second message.

[0367] As one embodiment, at least one of the antenna 420, the transmitter 418, the transmission processor 416, and the controller / processor 475 is used to transmit a second message.

[0368] As an example, at least one of the antenna 452, the transmitter 454, the transmission processor 468, and the controller / processor 459 is used to transmit the first message.

[0369] As an example, at least one of the antenna 420, the receiver 418, the receiving processor 470, and the controller / processor 475 is used to receive the first message.

[0370] As an example, at least one of the antenna 452, the transmitter 454, the transmission processor 468, and the controller / processor 459 is used to transmit first UE capability information.

[0371] As an example, at least one of the antenna 420, the receiver 418, the receiving processor 470, and the controller / processor 475 is used to receive first UE capability information.

[0372] As an example, the first communication device 450 corresponds to the first node in this application.

[0373] As an example, the second communication device 410 corresponds to the second node in this application.

[0374] As an example, the first communication device 450 is a user equipment.

[0375] As an example, the first communication device 450 is a base station device.

[0376] As an example, the first communication device 450 is a relay device.

[0377] As one embodiment, the second communication device 410 is a user equipment.

[0378] As one embodiment, the second communication device 410 is a base station device.

[0379] As an example, the second communication device 410 is a relay device.

[0380] Example 5

[0381] Example 5 illustrates a wireless signal transmission flowchart according to an embodiment of this application, as shown in the attached diagram. Figure 5 As shown. It should be noted that the order in this example does not limit the order of signal transmission and implementation in this application.

[0382] for First node U01 In step S5101, first UE capability information is sent; in step S5102, a second message is received; in step S5103, as a response to detecting a connection failure, connection failure information is stored in a first UE variable; wherein, the connection failure information is at least one of radio link failure information or handover failure information; in step S5104, a first cell is selected; in step S5105, a first message is sent, the first message including at least a portion of the connection failure information in the first UE variable.

[0383] for Second node N02 In step S5201, the first message is received.

[0384] for Third node N03 In step S5301, the first UE capability information is received; in step S5302, the second message is sent.

[0385] In Embodiment 5, the first UE capability information indicates that the first node U01 supports connection failure prediction; the second message enables the connection failure prediction; the prediction of connection failure depends on the connection failure prediction.

[0386] As one example, the first node U01 and the second node N02 are connected wirelessly.

[0387] As an example, the first node U01 and the second node N02 are connected by a wire.

[0388] As one example, the first node U01 and the second node N02 are connected via a Uu port.

[0389] As an example, the first node U01 and the second node N02 are connected via an IAB port.

[0390] As an example, the first node U01 and the second node N02 are connected via a PC5 interface.

[0391] As one example, the second node N02 is the sustaining base station of the first cell.

[0392] As one example, the second node N02 is a maintenance base station for a serving cell of the first node U01.

[0393] As an example, the second node N02 is a cell following the RRC connection re-establishment process.

[0394] As an example, the third node N03 is the sustaining base station of the first serving cell.

[0395] As an example, the third node N03 is a sustaining base station of a PCell following the first serving cell.

[0396] As an example, the third node N03 is the sustaining base station of the source PCell.

[0397] As an example, the third node N03 is the second node N02.

[0398] As an example, the third node N03 is not the second node N02.

[0399] As one embodiment, the third node N03 and the second node N02 are connected via a wireless interface.

[0400] As an example, the third node N03 and the second node N02 are connected via a wired interface.

[0401] As an example, the third node N03 and the second node N02 are connected via an Xn interface.

[0402] As one embodiment, the third node N03 and the second node N02 are connected via an X2 interface.

[0403] As an example, the third node N03 and the second node N02 have an ideal backhaul.

[0404] As an example, the backhaul between the third node N03 and the second node N02 is non-ideal.

[0405] As an example, the third node N03 and the second node N02 belong to the same CU.

[0406] As an example, the third node N03 and the second node N02 belong to the same DU.

[0407] As an example, the third node N03 and the second node N02 belong to different CUs.

[0408] As an example, the third node N03 and the second node N02 belong to different DUs.

[0409] As an example, the dashed box F5.1 is optional.

[0410] As an example, the dashed box F5.1 does not exist.

[0411] As an example, the dashed box F5.1 is present.

[0412] As an example, the first UE capability information is a UECapabilityInformation message.

[0413] As an example, the first UE capability information is a UEAssistanceInformation message.

[0414] As an example, the first UE capability information is triggered by the network.

[0415] As an example, the first UE capability information is triggered by the first node U01.

[0416] As an example, the first UE capability information is triggered by the first node U01 based on measurement.

[0417] As an example, the first UE capability information is obtained by the first node U01 based on measurements of the wireless signal.

[0418] As an example, the first UE capability information is obtained by the first node U01 based on measurements of wireless link quality.

[0419] As an example, the first UE capability information is obtained by the first node U01 based on measurements of cell link quality.

[0420] As an example, the first UE capability information indicates the smart model supported by the first node U01.

[0421] As an example, the first UE capability information indicates the index of the smart models supported by the first node U01.

[0422] As an example, the first UE capability information indicates the type of smart model supported by the first node U01.

[0423] As an example, the first UE capability information indicates the functionality of the smart model supported by the first node U01.

[0424] As an example, the first UE capability information indicates that the first node U01 supports an intelligent model for predicting connection failures.

[0425] As an example, the first UE capability information indicates that the first node U01 supports connection failure prediction, which includes RLF prediction and HOF prediction.

[0426] As an example, the first UE capability information indicates that the first node U01 supports connection failure prediction, and the connection failure prediction is RLF prediction.

[0427] As an example, the first UE capability information indicates that the first node U01 supports connection failure prediction, and the connection failure prediction is HOF prediction.

[0428] As an example, the first UE capability information indicates the RLF prediction from the RLF prediction and the HOF prediction; the connection failure prediction is the RLF prediction.

[0429] As an example, the first UE capability information indicates the HOF prediction from the RLF prediction and the HOF prediction; the connection failure prediction is the HOF prediction.

[0430] As an example, the first UE capability information indicates both the RLF prediction and the HOF prediction from the RLF prediction and the HOF prediction; the connection failure prediction is the RLF prediction and the HOF prediction.

[0431] As an example, the first UE capability information indicates that the first node U01 supports reporting connection failure information for connection failure prediction.

[0432] As an example, the connection failure information reporting is wireless link failure information reporting.

[0433] As an example, the connection failure information reporting is a handover failure information reporting.

[0434] As an example, the connection failure information is reported as an RLF-Report.

[0435] As an example, provided that the first UE capability information is sent, the first UE variable indicates whether a connection failure is predicted.

[0436] As an example, if the first node U01 supports connection failure prediction, the first UE variable indicates whether a connection failure is predicted.

[0437] As an example, if the first node U01 supports reporting connection failure information for connection failure prediction, the first UE variable indicates whether a connection failure is predicted.

[0438] As an example, the dashed box F5.2 is optional.

[0439] As an example, the dashed box F5.2 does not exist.

[0440] As an example, the dashed box F5.2 is present.

[0441] As an example, the prediction of connection failure is based on the prediction of connection failure.

[0442] As an example, the first node U01 performs the connection failure prediction based on the indication of the second message.

[0443] As an example, connection failure is predicted if the second message enables the connection failure prediction.

[0444] As an example, connection failure is predicted if the second message is received.

[0445] As an example, if the connection failure prediction is not enabled, the first UE variable does not indicate a predicted connection failure at any time.

[0446] As an example, if the second message is received, the first UE variable indicates whether a connection failure is predicted.

[0447] As an example, if the second message enables the connection failure prediction, the first UE variable indicates whether a connection failure is predicted.

[0448] As an example, if the second message enables the connection failure prediction, the first UE variable indicates that a connection failure has been predicted.

[0449] As an example, if the second message enables the reporting of connection failure information for connection failure prediction, the first UE variable indicates whether a connection failure is predicted.

[0450] As an example, if the second message enables the connection failure prediction and enables the reporting of connection failure information for connection failure prediction, the first UE variable indicates that a connection failure has been predicted.

[0451] As an example, the second message indicates the enabled smart model.

[0452] As an example, the second message indicates the index of the enabled smart model.

[0453] As an example, the second message indicates the type of smart model that is enabled.

[0454] As an example, the second message indicates the functionality of the enabled smart model.

[0455] As an example, the second message indicates that the smart model for predicting connection failures is enabled.

[0456] As one embodiment, the second information block indicates an RLF prediction; the connection failure prediction is an RLF prediction.

[0457] As an example, the second information block indicates the RLF prediction from the RLF prediction and the HOF prediction; the connection failure prediction is the RLF prediction.

[0458] As one embodiment, the second information block indicates HOF prediction; the connection failure prediction is HOF prediction.

[0459] As an example, the second information block indicates the HOF prediction from the RLF prediction and the HOF prediction; the connection failure prediction is the HOF prediction.

[0460] As an example, the second information block indicates both the RLF prediction and the HOF prediction from the RLF prediction and the HOF prediction; the connection failure prediction is both the RLF prediction and the HOF prediction.

[0461] As an example, the dashed box F5.3 is optional.

[0462] As an example, the dashed box F5.3 does not exist.

[0463] As a sub-example of the above embodiment, the RRC connection re-establishment process was not executed.

[0464] As an example, the dashed box F5.3 is present.

[0465] As a sub-implementation of the above embodiment, the RRC connection re-establishment process is executed.

[0466] As a sub-example of the above embodiment, the second node N02 is the maintenance base station of a serving cell after the completion of the RRC connection re-establishment process.

[0467] As a sub-implementation of the above embodiment, the second node N02 is the sustaining base station of the first cell.

[0468] As a sub-implementation of the above embodiment, in response to the detected connection failure, an RRC connection re-establishment process is executed; wherein, the execution of the RRC connection re-establishment process includes: selecting a first cell and setting a fourth field in the first UE variable; wherein, the fourth field indicates whether the first cell depends on prediction.

[0469] As a sub-implementation of the above embodiment, the execution of the RRC connection re-establishment process includes: sending an RRCReestablishmentRequest message.

[0470] As a sub-implementation of the above embodiments, the execution of the RRC connection re-establishment process includes: receiving an RRCReestablishment message as a response to the sending of the RRCReestablishmentRequest message.

[0471] As a sub-implementation of the above embodiment, the execution of the RRC connection re-establishment process includes: sending an RRCReestablishmentComplete message as a response to the receipt of the RRCReestablishment message.

[0472] As a sub-implementation of the above embodiment, in response to the selection of the first cell, the first cell is selected as the current PCell.

[0473] As a sub-implementation of the above embodiments, selecting the first cell means: performing cell selection; selecting the first cell during the cell selection process.

[0474] As a sub-implementation of the above embodiments, selecting the first cell means: selecting a suitable cell; the suitable cell is the first cell.

[0475] As a sub-example of the above embodiment, T311 is running when the first cell is selected.

[0476] As a sub-implementation of the above embodiments, the first cell is an NR cell.

[0477] As a sub-example of the above embodiment, the first cell is a 6G cell.

[0478] As a sub-example of the above embodiments, the first cell is a cell that supports connection failure prediction.

[0479] As a sub-example of the above embodiments, the RAT to which the first cell belongs is the same as the RAT to which the first serving cell belongs.

[0480] As a sub-implementation of the above embodiment, when setting the RRCReestablishmentRequest message, the fourth field is set in the first UE variable.

[0481] As a sub-implementation of the above embodiment, during the process of initiating and sending the RRCReestablishmentRequest message, the fourth field is set in the first UE variable.

[0482] As a sub-implementation of the above embodiments, when the first cell depends on prediction, the fourth field includes the fifth field; when the first cell does not depend on prediction, the fourth field does not include the fifth field; wherein, the fourth field includes reestablishmentCellId-r16; and the fifth field indicates the first cell depends on prediction.

[0483] As an additional embodiment of the above sub-example, the reestablishmentCellId-r16 indicates the cell that performs a re-establishment attempt after the connection failure.

[0484] As an additional embodiment of the above sub-example, when the first cell dependency prediction is performed, the reestablishmentCellId-r16 in the first UE variable is set to the global cell identifier of the first cell and the fifth field is set; when the first cell dependency prediction is performed, the reestablishmentCellId-r16 is set to the global cell identifier of the first cell.

[0485] As a sub-implementation of the above embodiment, when the first cell depends on prediction, a first subdomain in the fourth domain is set in the first UE variable; when the first cell does not depend on prediction, a second subdomain in the fourth domain is set in the first UE variable; the second subdomain is reestablishmentCellId-r16; the first subdomain and the second subdomain are different.

[0486] As an additional embodiment of the above sub-example, one of the first subdomain and the second subdomain is set.

[0487] As an additional embodiment of the above sub-example, the second subdomain indicates the cell that performs a re-establishment attempt after the connection failure.

[0488] As an additional embodiment of the above sub-example, the first subdomain indicates the cell that makes a re-establishment attempt after the connection fails and the cell depends on prediction.

[0489] As a supplementary embodiment of the above sub-example, the name of the first subdomain does not include reestablishmentCellId.

[0490] As a supplementary embodiment of the above sub-example, the name of the first subdomain includes reestablishmentCellId.

[0491] As a supplementary embodiment of the above sub-example, the first sub-domain is reestablishmentCellId-r19.

[0492] As a supplementary embodiment of the above sub-example, the first sub-domain is reestablishmentCellId-r1900.

[0493] As an additional embodiment of the above sub-example, setting the first subdomain in the fourth domain in the first UE variable means: setting the first subdomain in the fourth domain of the first UE variable to the global cell identifier of the first cell.

[0494] As an additional embodiment of the above sub-example, setting the first sub-domain in the fourth domain in the first UE variable means: setting the first sub-domain in the fourth domain of the first UE variable to the physical cell identity (PCI) of the first cell and the carrier frequency of the first cell.

[0495] As an additional embodiment of the above sub-example, setting the second subdomain in the fourth domain in the first UE variable means: setting the second subdomain in the fourth domain of the first UE variable to the global cell identifier of the first cell.

[0496] As an example, the dashed box F5.4 is optional.

[0497] As an example, the dashed box F5.4 is not present.

[0498] As a sub-example of the above embodiments, the first message was not sent.

[0499] As a sub-implementation of the above embodiment, the connection failure information in the first UE variable is discarded.

[0500] As a sub-example of the above embodiment, the connection failure information in the first UE variable is not scheduled.

[0501] As an example, the dashed box F5.4 is present.

[0502] As a sub-implementation of the above embodiments, the first message is sent.

[0503] As a sub-implementation of the above embodiments, the first message is an RRC message.

[0504] As a sub-implementation of the above embodiment, the first message is sent via the Uu port.

[0505] As a sub-implementation of the above embodiments, the first message is sent via the sidelink (SL).

[0506] As a sub-implementation of the above embodiments, the first message is an MCGFailureInformation message.

[0507] As a supplementary embodiment of the above sub-example, the first message includes the predicted cell.

[0508] As a supplementary embodiment of the above sub-example, the first message includes the measured cell.

[0509] As a supplementary embodiment of the above sub-example, the first message includes cells that meet the cell selection criteria.

[0510] As a supplementary embodiment of the above sub-example, the above method is beneficial for rapid recovery from connection failure.

[0511] As a sub-implementation of the above embodiments, the first message is a UEAssistanceInformation message.

[0512] As a supplementary embodiment of the above sub-example, the above method does not rely on network scheduling, which is beneficial for timely reporting of at least part of the connection failure information.

[0513] As an additional embodiment of the above sub-example, optionally, the first message is sent when a condition is met; this method is beneficial for reducing information reporting; optionally, the condition is related to measurement; optionally, the condition is related to prediction; optionally, the condition includes a timer not running; optionally, the condition is related to a timer.

[0514] As a sub-implementation of the above embodiment, a UEInformationRequest message is received; the UEInformationRequest message includes an rlf-ReportReq, which is set to true; as a response to the receipt of the UEInformationRequest message, a first message is sent; the first message is a UEInformationResponse message; the first message includes an rlf-Report, which includes at least a portion of the connection failure information in the first UE variable.

[0515] As a supplementary embodiment of the above sub-example, the above method reduces the impact of the protocol and helps to avoid unnecessary information reporting.

[0516] As an additional embodiment of the above sub-example, when the first message is sent, the connection failure information in the first UE variable is not cleared.

[0517] As a sub-implementation of the above embodiments, at least a portion of the connection failure information is the connection failure information.

[0518] As a sub-implementation of the above embodiments, at least a portion of the connection failure information is a part of the connection failure information.

[0519] Example 6

[0520] Example 6 illustrates a schematic diagram of a first UE variable indicating whether a connection failure is predicted according to an embodiment of this application. In the appendix... Figure 6 In the middle, the horizontal axis represents time, and box 601 represents the first time window.

[0521] As an example, the duration of the first time window is pre-configured.

[0522] As an example, the duration of the first time window is configurable.

[0523] As an example, the duration of the first time window is configured by an RRC message.

[0524] As an example, the duration of the first time window is configured by MAC CE.

[0525] As an example, the duration of the first time window is predicted.

[0526] As an example, the duration of the first time window is indicated by the prediction information related to the connection failure.

[0527] As an example, the duration of the first time window is a positive integer multiple of the first time length.

[0528] As an example, the first time length is configurable.

[0529] As an example, the first time length is configured by RRC.

[0530] As an example, the first time length is determined by the first node itself.

[0531] As an example, the first time length is indicated by the prediction information related to the connection failure.

[0532] As an example, the first time length is a measurement period.

[0533] As an example, the above method takes into account the impact of the measurement period on the first time window.

[0534] As an example, the above method avoids the impact of excessively long or short measurement periods on detected or predicted connection failures.

[0535] As an example, the measurement period is the shortest monitoring periodicity of RLM (Radio Link Monitoring).

[0536] As an example, the measurement period is the minimum monitoring period of BLM (Beam link monitoring).

[0537] As an example, the measurement period is the indication period of the RLM.

[0538] As an example, the measurement period is the indication period of the BLM.

[0539] As an example, the indication period is the maximum of the minimum monitoring period and 10 milliseconds.

[0540] As an example, at least one of the start time, end time, and duration of the first time window is indicated by the prediction information related to the connection failure.

[0541] In Example 6, when a predicted connection failure exists in the first time window, the first UE variable indicates that a connection failure has been predicted; when no predicted connection failure exists in the first time window, the first UE variable does not indicate that a connection failure has been predicted; the first time window depends on the time of the detected connection failure.

[0542] As a sub-implementation of the above embodiments, the first time window depending on the detected connection failure time means that the first time window includes the time of the detected connection failure.

[0543] As an additional embodiment of the above sub-example, the first time window is a time interval between a time before the time of the detected connection failure and a time after the time of the detected connection failure.

[0544] As an additional embodiment of the above sub-example, the above method is advantageous for determining whether a predicted connection failure exists before or after the detection of a connection failure.

[0545] As a supplementary embodiment of the above sub-example, the above method is helpful in determining whether there is a prediction that is too late or too early.

[0546] As a sub-implementation of the above embodiments, the first time window depends on the detected connection failure time, which means that the start time of the first time window depends on the detected connection failure time.

[0547] As an additional embodiment of the above sub-example, the above method is advantageous in determining whether a predicted connection failure exists after a connection failure is detected.

[0548] As a supplementary embodiment of the above sub-example, the above method is advantageous for its simplicity.

[0549] As a supplementary embodiment of the above sub-example, the above method is helpful in determining whether there is premature prediction.

[0550] As a sub-implementation of the above embodiments, the first time window depends on the detected connection failure time, which means that the cutoff time of the first time window depends on the detected connection failure time.

[0551] As an additional embodiment of the above sub-example, the first time window is a period of time before the detected connection failure.

[0552] As an additional embodiment of the above sub-example, the above method is advantageous in determining whether a predicted connection failure exists before a connection failure is detected.

[0553] As a supplementary embodiment of the above sub-example, the above method is advantageous for its simplicity.

[0554] As a supplementary embodiment of the above sub-example, the above method is helpful in determining whether there is premature prediction.

[0555] As an additional embodiment of the above sub-example, the cutoff time of the first time window is the time of the detected connection failure.

[0556] As an additional embodiment of the above sub-example, the cutoff time of the first time window is the time after which the detected connection failure has been offset.

[0557] As a supplementary embodiment of the above sub-example, the offset is pre-configured.

[0558] As a supplementary embodiment to the above sub-example, the offset is configurable.

[0559] As a supplementary embodiment of the above sub-example, the offset is determined by the first node itself.

[0560] As a sub-implementation of the above embodiments, the existence of predicted connection failures in the first time window means that the time of the predicted connection failures overlaps with the first time window.

[0561] As an additional embodiment of the above sub-example, the absence of predicted connection failures in the first time window includes: the time of the predicted connection failures and the first time window do not overlap.

[0562] As an additional embodiment of the above sub-example, the absence of predicted connection failures in the first time window includes: no connection failures were predicted.

[0563] As a sub-implementation of the above embodiments, the existence of predicted connection failures in the first time window means that the time of the predicted connection failures belongs to the first time window.

[0564] As an additional embodiment of the above sub-example, the absence of predicted connection failures in the first time window includes: the time of the predicted connection failure does not belong to the first time window.

[0565] As an additional embodiment of the above sub-example, the absence of predicted connection failures in the first time window includes: no connection failures were predicted.

[0566] In Example 6, when the detected connection failure occurs within a first time window, the first UE variable indicates a predicted connection failure; when the detected connection failure does not occur within the first time window, the first UE variable does not indicate a predicted connection failure; wherein, the first time window depends on the predicted connection failure.

[0567] As a sub-implementation of the above embodiments, the first time window is the specified time interval.

[0568] As a sub-implementation of the above embodiments, the start time of the first time window depends on the predicted connection failure.

[0569] As a sub-implementation of the above embodiments, the starting time of the first time window is the time when the connection failure is predicted.

[0570] As a sub-implementation of the above embodiments, the start time of the first time window is the time when the prediction information related to the connection failure is received.

[0571] As a sub-implementation of the above embodiments, the start time of the first time window is the time predicted to be the connection failure, as indicated by the prediction information related to the connection failure.

[0572] As a sub-implementation of the above embodiment, at the start time of the first time window, the predicted connection failure is stored in a UE variable; the first time window is the time interval in which the predicted connection failure is stored in a UE variable.

[0573] As an additional embodiment of the above sub-example, the detection of connection failure in the first time window means that when the connection failure is detected, the predicted connection failure is stored in a UE variable.

[0574] As an additional embodiment of the above sub-example, the detection of connection failure not in the first time window means that when the connection failure is detected, the predicted connection failure is not stored in a UE variable.

[0575] As a supplementary embodiment of the above sub-example, the UE variable is the first UE variable.

[0576] As a supplementary embodiment of the above sub-example, the UE variable is not the first UE variable.

[0577] As a sub-implementation of the above embodiment, a first timer is started at the beginning of the first time window; the first time window is the running time of the first timer.

[0578] As an additional embodiment of the above sub-example, the first timer is stopped at the end of the first time window.

[0579] As an additional embodiment of the above sub-example, the detection of connection failure in the first time window means that when the connection failure is detected, the first timer is running; the first time window is the time during which the first timer is running.

[0580] As an additional embodiment of the above sub-example, the statement that the connection failure is not detected in the first time window means that when the connection failure is detected, the first timer is not running.

[0581] As a sub-implementation of the above embodiments, the detection of connection failure in the first time window means that when the connection is detected as failed, there is an unresolved first state.

[0582] As an additional embodiment of the above sub-example, the detection of connection failure is not included in the first time window: when the connection failure is detected, there is no pending first state.

[0583] As an additional embodiment of the above sub-example, the first time window is the time interval between the first state being triggered and the first state being canceled.

[0584] As an additional embodiment of the above sub-example, the first time window is the time interval during which the first state is unresolved.

[0585] Example 7

[0586] Example 7 illustrates a schematic diagram of a first UE variable indicating first-time information according to an embodiment of this application. (See attached diagram.) Figure 7 In the diagram, the horizontal axis represents time. The first time and the second time are two separate times, with the second time occurring after the first time.

[0587] In Embodiment 7, storing connection failure information in the first UE variable includes: setting a first field in the first UE variable, the first field indicating first time information; wherein, the first UE variable indicates the predicted connection failure; the first time information is related to both the predicted connection failure and the detected connection failure; the detected connection failure occurs after the predicted connection failure.

[0588] As an example, the detected connection failure is the first connection failure detected after the predicted connection failure.

[0589] As an example, no connection failure is detected between the prediction of the connection failure and the detection of the connection failure.

[0590] As an example, from the prediction of connection failure to the detection of connection failure, the first serving cell is the PCell of the first node.

[0591] As an example, the first time information is a duration.

[0592] As an example, the first time information consists of N1 time units; where N1 is a positive integer.

[0593] As an example, the time unit is milliseconds.

[0594] As an example, the time unit is seconds.

[0595] As an example, the time unit is 0.5 milliseconds.

[0596] As an example, the minimum candidate value of N1 is 0.

[0597] As an example, the minimum value of the candidate N1 is greater than 0.

[0598] As an example, the maximum value of the candidate N1 is M1; where M1 is a positive integer.

[0599] As an example, if N1 is less than M1, the first time information indicated by the first field is N1 time units.

[0600] As an example, if N1 equals M1, the first time information indicated by the first field equals M1 time units.

[0601] As an example, if N1 is equal to M1, the first time information indicated by the first field is equal to or greater than M1 time units.

[0602] As an example, the first time information being related to both the predicted connection failure and the detected connection failure means that the first time information corresponds to a time interval, and the time interval is related to both the predicted connection failure and the detected connection failure.

[0603] As an example, the first time information being related to both the predicted connection failure and the detected connection failure means that the first time information corresponds to a time interval, the start time of which depends on the predicted connection failure, and the end time of which depends on the detected connection failure.

[0604] As an example, the first time information being related to both the predicted connection failure and the detected connection failure means that: the first time information is related to both the first time and the second time; the first time depends on the predicted connection failure; and the second time depends on the detected connection failure.

[0605] As an example, the first time information being related to both the predicted connection failure and the detected connection failure means that: the first time information is the actual time elapsed between the first time and the second time; the first time depends on the predicted connection failure; and the second time depends on the detected connection failure.

[0606] As one embodiment, the first time information is the actual time elapsed between the first time and the second time; the first time depends on the predicted connection failure; the second time depends on the detected connection failure.

[0607] As an example, the first time is the time when the connection failure is predicted.

[0608] As an example, the predicted connection failure time is the time when the predicted connection failure is indicated.

[0609] As an example, the time when the connection failure is predicted is the time when the prediction information related to the connection failure is received.

[0610] As an example, the predicted time of connection failure is the predicted time of connection failure indicated by the prediction information related to the connection failure.

[0611] As an example, the first time is the predicted time of connection failure.

[0612] As an example, the second time is the time when the detected connection failure occurred.

[0613] As an example, the time of the detected connection failure refers to the time when the connection failure was detected.

[0614] As one embodiment, the second time is the time when the event triggering the detection of connection failure is satisfied.

[0615] As an example, the first time is the predicted time of connection failure; the second time is the detected time of connection failure.

[0616] As one embodiment, the first time is the predicted connection failure time; the second time is the detected connection failure time.

[0617] Example 8

[0618] Example 8 illustrates a schematic diagram of a first UE variable indicating the cause of a connection failure according to an embodiment of this application.

[0619] In embodiment 8, storing connection failure information in the first UE variable includes: setting a second field in the first UE variable, the second field indicating the reason for the detected connection failure; wherein, the first UE variable indicates the predicted connection failure; the second field is set to a first candidate value; the first candidate value indicates that the detected connection failure depends on the predicted connection failure; wherein, the first UE variable indicates the predicted connection failure.

[0620] As an example, optionally, a field is set in the first UE variable, the field indicating the value of T310 when the connection failure is detected; wherein, when the connection failure is detected, T310 is running.

[0621] As an example, optionally, a field is set in the first UE variable, the field indicating the value of T312 when the connection failure is detected; wherein, when the connection failure is detected, T312 is running.

[0622] As an example, optionally, a field is set in the first UE variable, the field indicating the value of T304 when the connection failure is detected; wherein, when the connection failure is detected, T304 is running.

[0623] As an example, optionally, a field is set in the first UE variable, the field indicating the number of times the Preamble is sent when the connection failure is detected; wherein, when the connection failure is detected, a random access procedure is in progress.

[0624] As an example, the above methods, by reporting the status information of connection failure detection, help the network obtain the gap between connection failure prediction and connection failure detection, thereby assisting the network in optimizing connection failure prediction and / or connection failure detection.

[0625] As one embodiment, the detection of connection failure relying on the predicted connection failure includes: the detection of connection failure includes the predicted connection failure.

[0626] As one embodiment, the detection of connection failure depending on the prediction of connection failure includes: the prediction of connection failure triggers the detection of connection failure.

[0627] As one embodiment, the detection of connection failure depending on the prediction of connection failure includes: the detection of connection failure occurs when at least the prediction of connection failure is made.

[0628] As a sub-implementation of the above embodiments, the detection of connection failure is determined along with the prediction of connection failure.

[0629] As a sub-implementation of the above embodiment, the connection failure is determined at the time when the connection failure is predicted.

[0630] As a sub-implementation of the above embodiment, the connection failure is determined after the time when the connection failure is predicted.

[0631] As a sub-implementation of the above embodiments, the detected connection failure is determined in conjunction with the predicted connection failure.

[0632] As a sub-implementation of the above embodiment, the detected connection failure is determined at the predicted time of connection failure.

[0633] As an example, the second field explicitly indicates the reason for the detected connection failure.

[0634] As an example, the second field implicitly indicates the reason for the detected connection failure.

[0635] As an example, the name of the second field indicates the reason for the detected connection failure.

[0636] As an example, the value of the second field indicates the reason for the detected connection failure.

[0637] As an example, the name of the second field includes rlf and Cause.

[0638] As an example, the second domain is an rlf-Cause domain.

[0639] As an example, the second field is an rlf-Cause-r16 field, and the plurality of candidate values ​​include the first candidate value and t310-Expiry. The plurality of candidate values ​​include randomAccessProblem, rlc-MaxNumRetx, beamFailureRecoveryFailure, lbtFailure-r16, bh-rlfRecoveryFailure, and t312-expiry-r17.

[0640] As an example, the second field is an rlf-Cause-r16 field, the plurality of candidate values ​​include the first candidate value and t310-Expiry, and the plurality of candidate values ​​do not include at least one of randomAccessProblem, rlc-MaxNumRetx, beamFailureRecoveryFailure, lbtFailure-r16, bh-rlfRecoveryFailure, or t312-expiry-r17.

[0641] As an example, the name of the first candidate value may include AI or ML.

[0642] As an example, the name of the first candidate value may include pre, predicted, predicted, or prediction.

[0643] Example 9

[0644] Example 9 illustrates a schematic diagram of a first UE variable indicating the identifier of the smart model used to predict connection failure according to an embodiment of this application, as shown in the attached diagram. Figure 9 As shown.

[0645] In Embodiment 9, storing connection failure information in the first UE variable includes setting a third field in the first UE variable; wherein the first UE variable indicates the predicted connection failure; and the third field indicates the identifier of the smart model used to predict the connection failure.

[0646] As an example, the third field is set as an identifier of the smart model used to predict connection failure.

[0647] As an example, the identifier of the smart model used to predict connection failure is a non-negative integer.

[0648] As an example, the non-negative integers do not include 0.

[0649] As an example, the non-negative integer includes 0.

[0650] As an example, the non-negative integer occupies at least one bit.

[0651] As an example, the non-negative integer occupies 1 bit.

[0652] As an example, the non-negative integer occupies multiple bits.

[0653] As an example, the non-negative integer occupies 3 bits.

[0654] As an example, the non-negative integer occupies 8 bits.

[0655] As an example, the identifier of the smart model used to predict connection failure includes a region identifier.

[0656] As an example, the identifier of the smart model used to predict connection failure includes a region identifier and a non-negative integer; the non-negative integer indicates the smart model used to predict connection failure within the range indicated by the region identifier.

[0657] As an example, the identifier of the smart model used to predict connection failure includes a region identifier and a type identifier; the non-negative integer indicates the smart model used to predict connection failure within the range indicated by the region identifier.

[0658] As an example, the type identifier indicates the functionality of the smart model.

[0659] As an example, the type identifier indicates the protocol layer to which the smart model belongs.

[0660] As an example, the area identifier indicates at least one PLMN.

[0661] As an example, the area identifier indicates at least one TAC.

[0662] As an example, the area identifier indicates at least one cell.

[0663] As an example, the region identifier indicates at least one server.

[0664] As an example, the area identifier indicates at least one MnF.

[0665] As an example, the area identifier indicates at least one MnS.

[0666] As an example, the region identifier is of the RAN domain.

[0667] As an example, the region identifier is a CN domain.

[0668] Example 10

[0669] Example 10 illustrates a schematic diagram of a first UE variable represented by ASN.1 according to an embodiment of this application, as shown in the attached diagram. Figure 10 As shown. In the appendix Figure 10In this context, the first UE variable is represented by ASN.1, and the first UE variable is a VarRLF-Report; the VarRLF-Report includes an RLF-Report, and the RLF-Report includes at least one of the first domain, the second domain, the third domain, or the fourth domain.

[0670] As an example, the rlf-Report includes the first domain.

[0671] As an example, the rlf-Report includes the second field.

[0672] As an example, the rlf-Report includes the third field.

[0673] As an example, the rlf-Report includes the second field and the fourth field; the first UE variable does not indicate a predicted connection failure.

[0674] As an example, the rlf-Report includes the second field and the fourth field; the first UE variable indicates a predicted connection failure.

[0675] As an example, the rlf-Report includes the second field and the third field.

[0676] As an example, the rlf-Report includes the first domain, the second domain, the third domain, and the fourth domain.

[0677] As an example, the above method, based on the existing VarRLF-Report, assists in network mobility configuration by adding at least one of the first domain, the second domain, the third domain, or the fourth domain.

[0678] As an example, the above method avoids the additional signaling overhead caused by introducing new UE variables.

[0679] As an example, this application does not limit the specific implementation of the first UE variable.

[0680] As an example, optionally, how the first UE variable is stored is implemented by the UE.

[0681] As an example, this application does not limit the specific name of the first UE variable or the supported protocol version.

[0682] Example 11

[0683] Example 11 illustrates a structural block diagram of a processing apparatus for a first node according to an embodiment of this application; as shown in the appendix. Figure 11 As shown. In the appendix Figure 11 In the first node, the processing device 1100 includes a first processor 1101.

[0684] As one embodiment, the first processor 1101 includes a first receiver.

[0685] As one embodiment, the first processor 1101 includes a first transmitter.

[0686] As one embodiment, the first processor 1101 includes an appendix Figure 15 The third module mentioned above.

[0687] As one embodiment, the first processor 1101 includes an appendix Figure 14 The intelligent module 1501 in it.

[0688] As one embodiment, the first processor 1101 includes an appendix Figure 17 The reasoning function in 1806.

[0689] The first processor 1101, in response to detecting a connection failure, stores connection failure information in a first UE variable; wherein the connection failure information is at least one of radio link failure information or handover failure information;

[0690] In Example 11, the first UE variable indicates whether a connection failure is predicted.

[0691] As an example, when a predicted connection failure exists in the first time window, the first UE variable indicates that a connection failure has been predicted; when no predicted connection failure exists in the first time window, the first UE variable does not indicate that a connection failure has been predicted; the first time window depends on the time of the detected connection failure.

[0692] As one embodiment, storing connection failure information in a first UE variable includes: setting a first field in the first UE variable, the first field indicating first time information; wherein, the first UE variable indicates the predicted connection failure; the first time information is related to both the predicted connection failure and the detected connection failure; the detected connection failure occurs after the predicted connection failure.

[0693] As one embodiment, storing connection failure information in a first UE variable includes: setting a second field in the first UE variable, the second field indicating the reason for detecting the connection failure; wherein, the first UE variable indicates the predicted connection failure; the second field is set to a first candidate value; the first candidate value indicates that the detected connection failure depends on the predicted connection failure; wherein, the first UE variable indicates the predicted connection failure.

[0694] As one embodiment, storing connection failure information in the first UE variable includes: setting a third field in the first UE variable; wherein the first UE variable indicates the predicted connection failure; and the third field indicates the identifier of the smart model used to predict the connection failure.

[0695] As one embodiment, the first processor, in response to the detected connection failure, executes an RRC connection re-establishment process; wherein, the execution of the RRC connection re-establishment process includes: selecting a first cell and setting a fourth field in the first UE variable; wherein, the fourth field indicates whether the first cell relies on prediction.

[0696] As an example, the first processor 1101 sends a first message, the first message including at least a portion of the connection failure information in the first UE variable.

[0697] As an example, the first transmitter in the first processor 1101 sends the first message.

[0698] As one embodiment, the first processor 1101 sends first UE capability information and receives a second message; wherein the first UE capability information indicates that the first node supports connection failure prediction; the second message enables the connection failure prediction; the prediction of connection failure depends on the connection failure prediction.

[0699] As one embodiment, the first processor 1101 receives a second message; wherein the second message enables the connection failure prediction.

[0700] As an example, the first transmitter in the first processor 1101 transmits the first UE capability information.

[0701] As an example, the first receiver in the first processor 1101 receives the second message.

[0702] As one embodiment, the first receiver includes the appendix to this application. Figure 4The antenna 452, receiver 454, multi-antenna receiver processor 458, receiver processor 456, controller / processor 459, memory 460, or data source 467 are at least one of these.

[0703] As one embodiment, the first receiver includes the appendix to this application. Figure 4 At least antenna 452 and receiver 454 are included.

[0704] As one embodiment, the first transmitter includes the appendix to this application. Figure 4 The antenna 452 or transmitter 454 or multi-antenna transmitter processor 457 or transmitter processor 468 or controller / processor 459 or memory 460 or data source 467 is at least one of them.

[0705] As one embodiment, the first transmitter includes the appendix to this application. Figure 4 At least antenna 452 and transmitter 454 are included.

[0706] Example 12

[0707] Example 12 illustrates a structural block diagram of a processing apparatus for a second node according to an embodiment of this application; as shown in the appendix. Figure 12 As shown. In the appendix Figure 12 In the second node, the processing device 1200 includes a second transmitter 1201 and a second receiver 1202.

[0708] The second receiver 1202 receives a first message, the first message including at least a portion of the connection failure information in the first UE variable.

[0709] In Example 12, as a response to detecting a connection failure, the sender of the first message stores connection failure information in a first UE variable; wherein the connection failure information is at least one of radio link failure information or handover failure information; the first UE variable indicates whether a connection failure is predicted.

[0710] As an example, when a predicted connection failure exists in the first time window, the first UE variable indicates that a connection failure has been predicted; when no predicted connection failure exists in the first time window, the first UE variable does not indicate that a connection failure has been predicted; the first time window depends on the time of the detected connection failure.

[0711] As one embodiment, storing connection failure information in a first UE variable includes: setting a first field in the first UE variable, the first field indicating first time information; wherein, the first UE variable indicates the predicted connection failure; the first time information is related to both the predicted connection failure and the detected connection failure; the detected connection failure occurs after the predicted connection failure.

[0712] As one embodiment, storing connection failure information in a first UE variable includes: setting a second field in the first UE variable, the second field indicating the reason for detecting the connection failure; wherein, the first UE variable indicates the predicted connection failure; the second field is set to a first candidate value; the first candidate value indicates that the detected connection failure depends on the predicted connection failure; wherein, the first UE variable indicates the predicted connection failure.

[0713] As one embodiment, storing connection failure information in the first UE variable includes: setting a third field in the first UE variable; wherein the first UE variable indicates the predicted connection failure; and the third field indicates the identifier of the smart model used to predict the connection failure.

[0714] As an example, in response to the detected connection failure, the sender of the first message performs an RRC connection re-establishment procedure; wherein, performing the RRC connection re-establishment procedure includes: selecting a first cell and setting a fourth field in the first UE variable; the fourth field indicates whether the first cell relies on prediction.

[0715] As one embodiment, the second receiver 1202 receives first UE capability information; the second transmitter 1201 sends a second message; wherein, the first UE capability information indicates that the first node supports connection failure prediction; the second message enables the connection failure prediction; the prediction of connection failure depends on the connection failure prediction.

[0716] As one embodiment, the second transmitter 1201 includes the appendix to this application. Figure 4 The antenna 420, transmitter 418, multi-antenna transmitter processor 471, transmitter processor 416, controller / processor 475, or memory 476 are at least one of them.

[0717] As one embodiment, the second transmitter 1201 includes the appendix to this application. Figure 4 At least antenna 420 and transmitter 418 are included.

[0718] As one embodiment, the second receiver 1202 includes the appendix to this application. Figure 4The antenna 420, receiver 418, multi-antenna receiver processor 472, receiver processor 470, controller / processor 475, or memory 476 are at least one of them.

[0719] As one embodiment, the second receiver 1202 includes the appendix to this application. Figure 4 At least antenna 420 and receiver 418 are included.

[0720] Example 13

[0721] Example 13 illustrates a flowchart of a first state according to an embodiment of this application, as shown in the attached diagram. Figure 13 As shown. Example 13 illustrates a schematic diagram of an intelligent model according to an embodiment of this application, as shown in the attached diagram. Figure 13 As shown.

[0722] for First node U01 In step S1401, a connection failure is predicted; in step S1402, a first state is triggered in response to the predicted connection failure; in step S1403, any condition in the first set of conditions is satisfied; in step S1404, the triggered first state is canceled in response to the satisfaction of any condition in the first set of conditions.

[0723] As an example, predicting connection failure means: predicting that the connection will fail.

[0724] As one example, the first state remains pending after it is triggered until it is canceled.

[0725] As an example, "pending" means: triggered but not canceled.

[0726] As an example, "pending" refers to something that is still pending.

[0727] As an example, "pending" means: set.

[0728] As one example, "pending" means: stored.

[0729] As an example, dashed box 14.1 is optional.

[0730] As an example, the dashed box 14.1 is not present.

[0731] As a sub-implementation of the above embodiment, none of the conditions in the first condition set are satisfied.

[0732] As a sub-implementation of the above embodiments, the first state was not cancelled.

[0733] As an example, the dashed box 14.1 is present.

[0734] As a sub-implementation of the above embodiment, at least one condition in the first condition set is satisfied.

[0735] As a sub-implementation of the above embodiments, the first state is cancelled.

[0736] As an example, one of the conditions in the first set of conditions includes predicting that the predicted connection failure will not occur.

[0737] As an example, one of the conditions in the first set of conditions includes initiating a handover process.

[0738] As an example, one of the conditions in the first set of conditions includes initiating an RRC connection re-establishment.

[0739] As an example, one of the conditions in the first set of conditions includes entering the RRC_INACTIVE state.

[0740] As an example, one of the conditions in the first set of conditions includes entering the RRC_IDLE state.

[0741] As an example, one of the conditions in the first set of conditions includes the deactivation of the smart model.

[0742] As an example, one of the conditions in the first set of conditions includes the deletion of the smart model.

[0743] As an example, one of the conditions in the first set of conditions includes the smart model being reconfigured.

[0744] As an example, one of the conditions in the first set of conditions includes at least one of the following: predicting that the predicted connection failure will not occur, initiating a handover process, initiating an RRC connection re-establishment, entering the RRC_INACTIVE state, entering the RRC_IDLE state, or the smart model being deactivated, deleted, or reconfigured.

[0745] As an example, "cancel" means "cancel".

[0746] As an example, cancellation refers to release.

[0747] As an example, cancellation refers to deletion.

[0748] As an example, "cancel" means "clear".

[0749] As an example, cancellation means: no longer storing.

[0750] Example 14

[0751] Example 14 illustrates a schematic diagram of a first notification according to an embodiment of this application, as shown in the attached diagram. Figure 14 As shown. The first processor 1500 of the first node includes an intelligent module 1501 and a legacy module 1502.

[0752] In embodiment 14, the legitimacy module 1502 of the first processor 1500 receives a first notification indicating that a connection failure has been predicted; the intelligence module 1501 of the first processor 1500 sends the first notification; the first processor 1500 includes the legitimacy module 1502 and the intelligence module 1501; the intelligence module 1501 has at least one of the following: a training function or an inference function.

[0753] As one embodiment, the legitimacy module 1502 of the first processor receives a second notification indicating that an update predicts a connection failure; the intelligence module 1501 of the first processor sends the second notification.

[0754] As one example, the first notification includes prediction information related to the connection failure.

[0755] As an example, the legal module 1502 is logical.

[0756] As an example, the legal module 1502 is physical.

[0757] As an example, the legitimacy module 1502 triggers a legitimate event detected by connection failure.

[0758] As an example, the legitimate module 1502 detects a connection failure.

[0759] As an example, the legal module 1502 is a protocol entity.

[0760] As an example, the legal module 1502 is an RRC protocol entity.

[0761] As an example, the legal module 1502 is located in the RRC sublayer.

[0762] As one embodiment, the legal module 1502 is located at a higher level than the RRC sublayer.

[0763] As an example, the legal module 1502 is located at a lower level than the RRC sublayer.

[0764] As one embodiment, in response to the receipt of the first notification, an indication is sent to a lower layer; the indication is received at the RRC sublayer.

[0765] As one example, in response to the receipt of the first notification, an indication is sent to a higher layer; the indication is received at the RRC sublayer.

[0766] As an example, the legal module 1502 supports 3GPP Release 17.

[0767] As an example, the legal module 1502 supports 3GPP Release 18.

[0768] As an example, the legal module 1502 does not have either training or inference functions.

[0769] As an example, the legal module 1502 is not a smart module.

[0770] As one example, the smart module 1501 is a piece of hardware.

[0771] As one example, the smart module 1501 is software.

[0772] As an example, the smart module 1501 is a program.

[0773] As one embodiment, the intelligent module 1501 is a function.

[0774] As one embodiment, the smart module 1501 is a protocol entity.

[0775] As an example, the intelligent module 1501 is an AI entity.

[0776] As an example, the smart module 1501 is an ML entity.

[0777] As an example, the intelligent module 1501 is an AI / ML entity.

[0778] As one embodiment, the smart module 1501 is logical.

[0779] As one embodiment, the smart module 1501 is physical.

[0780] As an example, the smart module 1501 predicts a connection failure.

[0781] As an example, the intelligent module 1501 processes the at least one intelligent model.

[0782] As one embodiment, the intelligent module 1501 includes at least one of the second module or the third module in the intelligent model shown in embodiment 15.

[0783] As an example, the interface between the legal module 1502 and the smart module 1501 is defined by the 3GPP protocol.

[0784] As an example, the interface between the legal module 1502 and the smart module 1501 is implemented based on the UE.

[0785] As an example, the interface between the legal module 1502 and the smart module 1501 is logical.

[0786] As an example, the interface between the legal module 1502 and the smart module 1501 is physical.

[0787] Example 15

[0788] Example 15 illustrates a schematic diagram of an intelligent model according to an embodiment of this application, as shown in the attached diagram. Figure 15 As shown. (Attached) Figure 15 It includes Module 1, Module 2, Module 3, Module 4, and Module 5.

[0789] In Example 15, in the appendix Figure 15 In the intelligent model shown, the first module sends a first dataset to the second module, the first module sends a second dataset to the third module, the first module sends a third dataset 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.

[0790] As an example, the first module, the second module, the third module, the fourth module, and the fifth module in an intelligent model all belong to the first node.

[0791] The above method avoids air interface signaling interaction and shortens transmission latency.

[0792] As an example, any one of the first module, second module, third module, fourth module, and fifth module in an intelligent model does not belong to the first node.

[0793] The above method reduces the hardware complexity of the first node.

[0794] As an example, at least one of the first module, the second module, the third module, the fourth module, and the fifth module in an intelligent model belongs to the first node; and at least one of the first module, the second module, the third module, the fourth module, and the fifth module belongs to a network node.

[0795] The above method balances the hardware complexity and transmission latency of the first node.

[0796] As an example, the first module is used for data collection.

[0797] As an example, the first module is responsible for data collection.

[0798] As an example, the first module has a data collection function.

[0799] As one example, the second module has a training function.

[0800] As an example, the training function is used for model training.

[0801] As an example, the training function is responsible for model training.

[0802] As an example, the training function includes a model training function.

[0803] As an example, the training function performs model training.

[0804] As an example, the second module performs validation.

[0805] As an example, the second module performs testing.

[0806] As an example, the second module generates model performance metrics.

[0807] As one example, the second module is responsible for data preparation.

[0808] As one embodiment, the data preparation includes at least one of data pre-processing, cleaning, formatting, or transformation.

[0809] As an example, the third module has reasoning capabilities.

[0810] As an example, the inference function is used for inference.

[0811] As an example, the reasoning function is responsible for reasoning.

[0812] As one example, the fourth module is used for model storage.

[0813] As an example, the fourth module has a model storage function.

[0814] As an example, the fourth module is responsible for storing the trained model.

[0815] As an example, the fourth module is responsible for storing trained models that can be used to perform inference processing.

[0816] As one example, the fifth module is used for management.

[0817] As an example, the fifth module is responsible for management.

[0818] As one example, the fifth module has management functions.

[0819] As an example, the fifth module manages the intelligent model.

[0820] As an example, the first dataset is training data.

[0821] As an example, the first dataset is the input to the second module.

[0822] As an example, the second dataset is inference data.

[0823] As an example, the second dataset is the input to the third module.

[0824] As an example, the third dataset is monitoring data.

[0825] As an example, the third dataset is the input to the fifth module.

[0826] As an example, the first type of parameter group includes monitoring output.

[0827] As one example, the second type of parameter group includes management instructions.

[0828] As an example, the second type of parameter group is used for fine-tuning operations of the inference function.

[0829] As an example, the second type of parameter group includes the model's identifier.

[0830] As an example, the second type of parameter group is used to select the model.

[0831] As an example, the second type of parameter group is used to switch models.

[0832] As an example, the second type of parameter group is used to activate / deactivate the model.

[0833] As an example, the second type of parameter group is used to fall back to the smart model.

[0834] As an example, the third type of parameter group includes Model Transfer Request.

[0835] As an example, the third type of parameter group includes Model Delivery Request.

[0836] As an example, the fourth parameter group includes the trained model.

[0837] As an example, the fourth type of parameter group includes the updated model.

[0838] As an example, the fourth type of parameter group indicates the identifier of the model.

[0839] As an example, the fifth group of parameters includes model transfer.

[0840] As an example, the fifth parameter group includes Model Delivery.

[0841] As an example, the fifth group of parameters indicates the identifier of the model.

[0842] As an example, the first type of output does not exist.

[0843] As an example, the first type of output exists.

[0844] As an example, the second module sends the first type of output to the fifth module.

[0845] As an example, the first type of output includes monitoring output.

[0846] As an example, the second type of output does not exist.

[0847] As an example, the second type of output exists.

[0848] As an example, the third module sends the second type of output to the fifth module.

[0849] As an example, the second type of output includes inference output.

[0850] As an example, the second type of output is used by the fifth module to monitor the performance of the AI / ML model.

[0851] As an example, the second type of output indicates that a connection failure was predicted.

[0852] As an example, the second type of output includes the prediction of connection failure.

[0853] As an example, the second type of output includes prediction information related to the connection failure.

[0854] As one example, the second type of output includes the first notification.

[0855] As one example, the second type of output includes the second notification.

[0856] As an example, the second type of output includes the first time window.

[0857] As an example, the second type of output includes the first time length.

[0858] As an example, the second type of output includes the specified time.

[0859] As an example, the second type of output includes the specified time interval.

[0860] As an example, the first dataset in the intelligent model depends on network configuration.

[0861] As an example, the first dataset in the intelligent model depends on the measurement information of the first node.

[0862] As an example, the first dataset in the intelligent model depends on the historical data of the first node.

[0863] As an example, the first dataset in the intelligent model depends on the data stored by the first node.

[0864] As an example, the second dataset in the intelligent model depends on network configuration.

[0865] As an example, the second dataset in the intelligent model depends on the measurement information of the first node.

[0866] As an example, the second dataset in the intelligent model depends on the historical data of the first node.

[0867] As an example, the second dataset in the intelligent model depends on the data stored by the first node.

[0868] As an example, the third dataset in the intelligent model depends on network configuration.

[0869] As an example, the third dataset in the intelligent model depends on the measurement information of the first node.

[0870] As an example, the third dataset in the intelligent model depends on the historical data of the first node.

[0871] As an example, the third dataset in the intelligent model depends on the data stored by the first node.

[0872] As one example, the measurement information includes movement speed.

[0873] As one example, the measurement information includes cell-level measurement results.

[0874] As one example, the measurement information includes beam-level measurement results.

[0875] As one example, the measurement information includes time-domain measurement results.

[0876] As one example, the measurement information includes frequency domain measurement results.

[0877] As one example, the measurement information includes spatial measurement results.

[0878] As an example, the connection failure is predicted by the intelligent model.

[0879] As an example, Example 15 is merely illustrative of how this application can be used in intelligent models. This example does not limit the application to non-intelligent operations, nor does it limit the application to other types of intelligent models to achieve and supplement [the desired results]. Figure 15 The intelligent model shown has a fairly good effect.

[0880] Example 16

[0881] Example 16 illustrates a schematic diagram of intelligent function deployment in a RAN (Radio Access Network) domain according to an embodiment of this application; as shown in the appendix. Figure 16 As shown. In Example 16, the gNB can be replaced with, for example, an eNB, or a network device such as a 6G base station.

[0882] Intelligent functions in the RAN domain include training (also known as ML training, AI training, or AI / ML training), testing (also known as ML testing, AI testing, or AI / ML testing), and inference (also known as ML inference, AI inference, or AI / ML inference), among others. Training, testing, and inference functions can be deployed independently or co-located. Deployment of intelligent functions can be achieved through software, such as downloading and / or running executable files; or through a combination of software and hardware, such as accelerating specific computing units through hardware to improve processing speed or save power.

[0883] Training functions 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, training functions for MDA (Management Data Analytics) can be deployed in MDAF (MDA Function); training functions for network data analytics can be deployed in NWDAF (Network Data Analytics Function), meaning the training function is MTLF (Model Training Logical Function).

[0884] Similarly, inference functions can be deployed in cross-domain management systems or domain-specific management systems; for example, the inference function is an MDAF, or the inference function is an AnLF (Analytics logical function) located in an NWDAF.

[0885] Similarly, testing functionality can also be deployed in cross-domain management systems or domain-specific management systems.

[0886] In Example 16, the training function 1702 of the RAN domain is located in the management function 1703 of the RAN domain; while the inference function is located in the base station, that is, the inference function 1704 is located in gNB1705, the inference function 1706 is located in gNB1707, and so on.

[0887] Appendix Figure 16 In this context, the management of inference functions for multiple base stations is handled by the RAN domain management function 1703, which interacts with the RAN domain MnS (Management Service) consumer / cross-domain management 1701 (as shown in the attached diagram). Figure 16 (As shown by the dashed arrow 1708 in the image).

[0888] Optionally, the management of inference functions can also be completed by the base station itself, that is, each base station can independently interact with the RAN domain MnS consumer / cross-domain management 1701.

[0889] It should be noted that Embodiment 16 is merely a non-limiting implementation method; optionally, the training function of the RAN domain may also be deployed at the base station; or optionally, some base stations may deploy both the inference function and the training function of the RAN domain, while some base stations may only deploy the inference function.

[0890] As an example, one of the gNBs (or base stations) in Example 16 is the second node of this application.

[0891] As an example, Appendix Figure 16 One of the reasoning functions performs connection failure prediction and predicts connection failure.

[0892] Example 17

[0893] Example 17 illustrates a schematic diagram of UE smart function deployment according to an embodiment of this application; as shown in the appendix. Figure 17 As shown. (Attached) Figure 17 The training function 1805 for the RAN domain is optional.

[0894] The UE intelligent function 1804 is deployed in the first node of this application. The UE intelligent function 1804 includes an inference function 1806. The inference function 1806 uses an intelligent model (also known as an AI model, or an ML model, or an AI / ML model) for inference. An intelligent model is typically trained before being used for AI / ML inference.

[0895] As an example, the UE intelligent function 1804 includes a RAN domain training function 1805, which runs training data through an intelligent model to obtain a relevant loss and adjusts the parameters of the intelligent model based on the calculated loss; the training includes at least one of ML initial training, ML re-training, and reinforcement learning.

[0896] 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 capabilities of the UE side.

[0897] Optionally, the UE intelligent function 1804 also includes a CN domain training function. Figure 18 (Not included in the text).

[0898] Optionally, the UE intelligent function 1804 also includes an intelligent deployment function. Figure 18 It is not included in the list, which is used to load intelligent models and data.

[0899] As an example, the first node indicates whether it supports training functions (RAN domain or CN domain) through capability reporting. The capability reporting is RRC signaling or NAS (Non-Access Stratum) signaling.

[0900] As an example, the intelligent model and the associated metadata are loaded by the first node from a network device or a remote server.

[0901] Optionally, the UE intelligent function 1804 is an MnS (Management Service) producer that provides data to the CN domain MnF (Management Function) 1801, and / or the RAN domain MnF 1802, and / or the cross-domain management system 1803 for management or analysis (as shown by double arrow 1507).

[0902] Optionally, the UE intelligent function 1804 is an MnS consumer that loads data from the CN domain MnF1801, and / or the RAN domain MnF1802, and / or the cross-domain management system 1803 for AI / ML-related management, such as managing data requests, intelligent model activation, and / or intelligent model training (as shown by double arrow 1807).

[0903] As an example, the intelligent model is based on a neural network.

[0904] As an example, the intelligent model is based on CNN (Conventional Neural Networks).

[0905] As an example, the smart model is based on the Transformer architecture.

[0906] As an example, the first node in this application includes an appendix. Figure 17 The reasoning function 1806 mentioned above.

[0907] As one embodiment, the first processor in this application includes an appendix. Figure 17 The reasoning function 1806 mentioned above.

[0908] As an example, Appendix Figure 2 UE201 in the middle includes appendix Figure 17 The reasoning function 1806 mentioned above.

[0909] As an example, Appendix Figure 4 The first communication device 450 in the middle includes an attachment Figure 17 The reasoning function 1806 mentioned above.

[0910] As an example, Appendix Figure 15The third module includes appendices. Figure 17 The reasoning function 1806 mentioned above.

[0911] As an example, Appendix Figure 14 The intelligent module 1501 in the middle includes an attached Figure 17 The reasoning function 1806 mentioned above.

[0912] As an example, Appendix Figure 11 The first processor 1101 in the process includes an appendix Figure 17 The reasoning function 1806 mentioned above.

[0913] As an example, Appendix Figure 17 The inference function 1806 in the text performs connection failure prediction and predicts connection failure.

[0914] Example 18

[0915] Example 18 illustrates a flowchart based on artificial intelligence or machine learning according to an embodiment of this application; as attached. Figure 18 As shown. (Attached) Figure 18 This includes a third, fourth, fifth, sixth, and seventh operation. In Example 18, the third and fourth operations belong to the first stage, the fifth operation belongs to the second stage, the sixth operation belongs to the third stage, and the seventh operation belongs to the fourth stage. (See Appendix...) Figure 18 In the diagram, the lines with arrows indicate the sequence of processes.

[0916] As an example, the third operation includes AI / ML training, the fourth operation includes AI / ML testing, the fifth operation includes AI / ML emulation, the sixth operation includes AI / ML entity loading, and the seventh operation includes AI / ML inference.

[0917] As an example, the first stage includes a training phase, the second stage includes an emulation phase, the third stage includes a deployment phase, and the fourth stage includes an inference phase.

[0918] As an example, the first stage includes AI / ML model training.

[0919] As an example, the first stage includes AI / ML model training and AI / ML testing.

[0920] As an example, the AI / ML model training includes initial training and re-training of one or a group of AI / ML entities.

[0921] As an example, the training of the AI / ML model depends on training data.

[0922] As an example, the AI / ML model training includes AI / ML entity validation.

[0923] As an example, the AI / ML entity verification is used to evaluate the performance of the AI / ML entity.

[0924] As an example, the AI / ML entity verification relies on verification data.

[0925] As an example, if the AI / ML entity verification results do not meet expectations, the AI / ML model will be retrained.

[0926] As an example, the AI / ML testing includes testing the validated AI / ML entities to estimate the performance of the trained AI / ML model.

[0927] As an example, if the AI / ML test results meet expectations, the AI / ML entity proceeds to the next stage; otherwise, the AI / ML model will be retrained.

[0928] As an example, the AI / ML test relies on test data.

[0929] As one embodiment, the second stage includes AI / ML simulation, which performs AI / ML entity reasoning in a simulation environment.

[0930] As an example, the AI / ML simulation estimates the performance of AI / ML entity reasoning in a simulation environment before using AI / ML entities.

[0931] As one embodiment, the second stage is optional.

[0932] As an example, the third stage includes AI / ML entity loading, which is to obtain trained AI / ML entities to obtain the desired AI / ML inference capabilities.

[0933] As an example, the third stage is optional.

[0934] As an example, the third stage is no longer needed when the training and inference functions are co-located.

[0935] As an example, the fourth stage includes AI / ML inference.

[0936] Example 19

[0937] Example 19 illustrates a structural block diagram of a processing apparatus for a third node according to an embodiment of this application; as shown in the appendix. Figure 19 As shown. In the appendix Figure 19 In the second node, the processing device 1900 includes a third transmitter 1901 and a third receiver 1902.

[0938] A third receiver 1902 receives first UE capability information; wherein the first UE capability information indicates that the sender of the first UE capability information supports connection failure prediction; in response to detecting a connection failure, the sender of the first UE capability information stores connection failure information in a first UE variable; the connection failure information is at least one of radio link failure information or handover failure information; the first UE variable indicates whether a connection failure has been predicted; the first UE variable indicating whether a connection failure has been predicted depends on the connection failure prediction.

[0939] As an example, the third transmitter 1901 sends a second message; wherein the second message enables the connection failure prediction.

[0940] As one embodiment, the third receiver 1902 receives first UE capability information; the second transmitter 1201 sends a second message; wherein, the first UE capability information indicates that the first node supports connection failure prediction; the second message enables the connection failure prediction; the prediction of connection failure depends on the connection failure prediction.

[0941] As one embodiment, the third transmitter 1901 includes the appendix to this application. Figure 4 The antenna 420, transmitter 418, multi-antenna transmitter processor 471, transmitter processor 416, controller / processor 475, or memory 476 are at least one of them.

[0942] As one embodiment, the third transmitter 1901 includes the appendix to this application. Figure 4 At least antenna 420 and transmitter 418 are included.

[0943] As one embodiment, the third receiver 1902 includes the appendix to this application. Figure 4The antenna 420, receiver 418, multi-antenna receiver processor 472, receiver processor 470, controller / processor 475, or memory 476 are at least one of them.

[0944] As one embodiment, the third receiver 1902 includes the appendix to this application. Figure 4 At least antenna 420 and receiver 418 are included.

[0945] Those skilled in the art will understand that all or part of the steps in the above methods can be implemented by a program instructing related hardware, and the program can be stored in a computer-readable storage medium, such as a read-only memory, hard disk, or optical disk. Optionally, all or part of the steps in the above embodiments can also be implemented using one or more integrated circuits. Accordingly, each module unit in the above embodiments can be implemented in hardware or in the form of software functional modules. This application is not limited to any specific combination of software and hardware. The user equipment, terminal, and UE in this application include, but are not limited to, drones, communication modules on drones, remote-controlled aircraft, aircraft, small aircraft, mobile phones, tablets, laptops, vehicle-mounted communication devices, wireless sensors, internet cards, IoT terminals, RFID terminals, NB-IoT terminals, MTC (Machine Type Communication) terminals, eMTC (enhanced MTC) terminals, data cards, internet cards, vehicle-mounted communication devices, low-cost mobile phones, low-cost tablets, and other wireless communication devices. The base station or system equipment in this application includes, but is not limited to, macrocell base stations, microcell base stations, home base stations, relay base stations, gNB (NR Node B), TRP (Transmitter Receiver Point), and other wireless communication equipment.

[0946] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A first node used for wireless communication, characterized in that, include: The first processor, in response to detecting a connection failure, stores connection failure information in a first UE variable; wherein the connection failure information is at least one of radio link failure information or handover failure information; The first UE variable indicates whether a connection failure is predicted.

2. The first node according to claim 1, characterized in that, When a predicted connection failure exists in the first time window, the first UE variable indicates that a connection failure has been predicted; when no predicted connection failure exists in the first time window, the first UE variable does not indicate that a connection failure has been predicted; the first time window depends on the time of the detected connection failure.

3. The first node according to claim 1 or 2, characterized in that, The step of storing connection failure information in the first UE variable includes: setting a first field in the first UE variable, the first field indicating first time information; wherein, the first UE variable indicates the predicted connection failure; the first time information is related to both the predicted connection failure and the detected connection failure; the detected connection failure occurs after the predicted connection failure.

4. The first node according to any one of claims 1 to 3, characterized in that, Storing connection failure information in a first UE variable includes: setting a second field in the first UE variable, the second field indicating the reason for detecting the connection failure; wherein, the first UE variable indicates the predicted connection failure; the second field is set to a first candidate value; the first candidate value indicates that the detected connection failure depends on the predicted connection failure; wherein, the first UE variable indicates the predicted connection failure.

5. The first node according to any one of claims 1 to 4, characterized in that, Storing connection failure information in the first UE variable includes setting a third field in the first UE variable; wherein the first UE variable indicates the predicted connection failure; and the third field indicates the identifier of the intelligent model used to predict the connection failure.

6. The first node according to any one of claims 1 to 5, characterized in that, include: The first processor, in response to the detected connection failure, executes an RRC connection re-establishment process; wherein, the execution of the RRC connection re-establishment process includes: selecting a first cell and setting a fourth field in the first UE variable; The fourth field indicates whether the first cell relies on prediction.

7. The first node according to any one of claims 1 to 6, characterized in that, include: The first processor sends a first message, the first message including at least a portion of the connection failure information in the first UE variable.

8. The first node according to any one of claims 1 to 7, characterized in that, include: The first processor sends the first UE capability information; Receive the second message; Wherein, the first UE capability information indicates that the first node supports connection failure prediction; the second message enables the connection failure prediction; and the first UE variable indicates whether the prediction of connection failure depends on the connection failure prediction.

9. A second node used for wireless communication, characterized in that, include: A second receiver receives a first message, the first message including at least a portion of the connection failure information in the first UE variable; In response to a detected connection failure, the sender of the first message stores connection failure information in a first UE variable; wherein the connection failure information is at least one of radio link failure information or handover failure information; and the first UE variable indicates whether a connection failure has been predicted.

10. A method used in a second node for wireless communication, characterized in that, include: Receive a first message, the first message including at least a portion of the connection failure information in the first UE variable; In response to a detected connection failure, the sender of the first message stores connection failure information in a first UE variable; wherein the connection failure information is at least one of radio link failure information or handover failure information; and the first UE variable indicates whether a connection failure has been predicted.

11. A third node used for wireless communication, characterized in that, include: The third receiver receives the capability information of the first UE. Wherein, the first UE capability information indicates that the sender of the first UE capability information supports connection failure prediction; in response to detecting a connection failure, the sender of the first UE capability information stores connection failure information in a first UE variable; the connection failure information is at least one of radio link failure information or handover failure information; the first UE variable indicates whether a connection failure has been predicted; the first UE variable indicating whether a connection failure has been predicted depends on the connection failure prediction.

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