Method for connection failure prediction, and apparatus

Abstract

The present application discloses a method for connection failure prediction, and an apparatus. A communication node receives first signaling, wherein the first signaling indicates a first threshold; and a first statistics unit is maintained, wherein the maintaining the first statistics unit comprises: if the first statistics unit reaches the first threshold, determining a connection failure, and the maintaining the first statistics unit comprises: if the first statistics unit reaches a second threshold, performing connection failure prediction. The first statistics unit is a counter, or the first statistics unit is a timer, and the first threshold is different from the second threshold. The solution provided in the present application reduces the overhead of a UE while improving mobility performance.

Description

A method and apparatus for connection failure prediction

[0001] The present application claims priority from the Chinese patent application No. 202410686470.1 filed on May 29, 2024, and entitled "A method and apparatus for connection failure prediction", the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0002] The present application relates to a transmission method and apparatus in a wireless communication system, and in particular to a method and apparatus for connection failure prediction. BACKGROUND

[0003] For existing services or future services (e.g., XR), when the mobility of a UE (User Equipment) is high or moves between high-density cells, it will cause more unexpected problems such as HOF (Handover Failure), RLF (Radio Link Failure), ping-pong phenomenon, throughput loss, or early / late handover. Considering that the mechanism based on AI (Artificial Intelligence) / ML (Machine Learning) algorithm has the potential to implement the proactive scheme and based on the related progress of RAN1 and RAN3 in AI / ML, the 3GPP (the 3rd Generation Partnership Project) has passed the SI (Study Item) of "Study on AI / ML for mobility in NR (New Radio)", which studies and evaluates the potential benefits and gains of AI / ML assisted mobility for network triggered L3 based handover, including RLF prediction or HOF prediction. SUMMARY

[0004] The inventors have found that, since RLF prediction or HOF prediction is performed at the UE (User Equipment) side, RLF prediction or HOF prediction improves the mobility performance while also bringing additional overhead in terms of power consumption, signaling, etc. to the UE. Therefore, how to reduce the impact of RLF prediction or HOF prediction on the UE needs to be further enhanced.

[0005] To solve the above problems, the present application provides a solution. In the description of the above problems, the NR system is taken as an example, and the present application is also applicable to scenarios such as LTE (Long-Term Evolution) or LTE-A (Long-Term Evolution Advanced) or 5G+ or 6G system, and similar technical effects of the NR system are obtained; further, although the present application gives a specific implementation for RLF, the present application can also be used in scenarios such as HOF, and similar technical effects of RLF are obtained. Further, the unified design scheme for different scenarios also helps to reduce hardware complexity and cost. Further, although the original intention of the present application is to target the Uu air interface, the present application can also be used for the PC5 interface, and similar technical effects of the Uu air interface are obtained. Further, although the original intention of the present application is to target the terminal and base station scenario, the present application is also applicable to the V2X (Vehicle-to-Everything) scenario, the communication scenario between the terminal and the relay, and the communication scenario between the relay and the base station, and similar technical effects in the terminal and base station scenario are obtained. Further, although the original intention of the present application is to target the terminal and base station scenario, the present application is also applicable to the IAB (Integrated Access and Backhaul) communication scenario, and similar technical effects in the terminal and base station scenario are obtained. Further, although the original intention of the present application is to target the TN (Terrestrial Network) scenario, the present application is also applicable to the NTN (Non-Terrestrial Network) communication scenario, and similar technical effects in the TN scenario are obtained. In addition, the unified solution for different scenarios also helps to reduce hardware complexity and cost.

[0006] As an embodiment, the explanation of the terminology in the present application refers to the definition of the specification agreement TS36 series of 3GPP.

[0007] As an embodiment, the explanation of the terminology in the present application refers to the definition of the specification agreement TS38 series of 3GPP.

[0008] As an embodiment, the explanation of the terminology in the present application refers to the definition of the specification agreement TS37 series of 3GPP.

[0009] As an embodiment, the explanation of the terminology in the present application refers to the definition of the specification agreement 6G series of 3GPP.

[0010] It should be noted that the embodiments in any node and the features in the embodiments of the present application can be applied to any other node without conflict. The embodiments and the features in the embodiments of the present application can be combined with each other without conflict.

[0011] The present application discloses a method used in a terminal, characterized in that comprising:

[0012] receiving first signaling; wherein the first signaling indicates a first threshold; if a first statistic reaches the first threshold, determining a connection failure;

[0013] wherein if the first statistic reaches a second threshold, performing a connection failure prediction; the first statistic is a counter, or the first statistic is a timer; the first threshold and the second threshold are different.

[0014] As an embodiment, the first statistic is a counter.

[0015] As an embodiment, the first statistic is a timer.

[0016] As an embodiment, the candidate of the first statistic is a counter.

[0017] As an embodiment, the candidate of the first statistic is a timer.

[0018] As an embodiment, the candidate of the first statistic includes a counter and a timer.

[0019] As an embodiment, the connection failure prediction is RLF prediction.

[0020] As an embodiment, the connection failure prediction is HOF prediction.

[0021] As an embodiment, the problem to be solved by the present application includes: how to reduce the influence of connection failure prediction on UE; the above method solves the above problem by introducing the execution condition of connection failure prediction.

[0022] As an embodiment, the problem to be solved by the present application includes: how to trigger connection failure prediction; the above method solves the above problem by triggering the execution of connection failure prediction when the first statistic reaches the second threshold.

[0023] As an embodiment, the problem to be solved by the present application includes: what features the first statistic has; in the above method, if the first statistic reaches the first threshold, a connection failure is determined, thereby solving the above problem.

[0024] As an embodiment, the problem to be solved by the present application includes: what features the first statistic has; in the method, the first statistic is a counter, thereby solving the above problem.

[0025] As an embodiment, the problem to be solved by the present application includes: what features the first statistic has; in the method, the first statistic is a timer, thereby solving the above problem.

[0026] As an embodiment, the method uses a timer that determines connection failure to trigger connection failure prediction.

[0027] As an embodiment, the method uses a counter that determines connection failure to trigger connection failure prediction.

[0028] As an embodiment, the method uses a threshold of a counter that is different from the counter that determines connection failure to trigger connection failure prediction.

[0029] As an embodiment, the method uses a threshold of a timer that is different from the timer that determines connection failure to trigger connection failure prediction.

[0030] As an embodiment, the method is simple to implement.

[0031] As an embodiment, the method reduces standardization work.

[0032] As an embodiment, the method reduces the impact of connection failure prediction on the UE.

[0033] As an embodiment, the method makes the triggering condition more reasonable.

[0034] According to an aspect of the present application, when the first statistic reaches the second threshold, a first notification is sent; the first notification is received;

[0035] The first notification triggers the execution of connection failure prediction.

[0036] As an embodiment, the problem to be solved by the present application includes: how to trigger the execution of connection failure prediction when the first statistic reaches the second threshold; in the method, the terminal sends and receives a first notification, thereby solving the above problem.

[0037] As an embodiment, the method introduces a first notification inside the terminal, which is simple to implement.

[0038] As an embodiment, the method is conducive to standardization.

[0039] As an embodiment, the method is conducive to the separation of connection failure detection and connection failure prediction.

[0040] According to one aspect of the present application, it features that

[0041] The method comprises:

[0042] Aborting the connection failure prediction in response to the first condition being met;

[0043] Wherein, the first condition depends on at least one of measurement or prediction.

[0044] As one embodiment, the first condition depends on measurement.

[0045] As one embodiment, the first condition depends on prediction.

[0046] As one embodiment, the first condition depends on both measurement and prediction.

[0047] As one embodiment, the problem to be solved by the present application includes how to reduce unnecessary connection failure prediction; the above method solves the above problem by aborting the connection failure prediction.

[0048] As one embodiment, the problem to be solved by the present application includes how to abort the connection failure prediction; the above method solves the above problem by aborting the connection failure prediction in response to the first condition being met.

[0049] As one embodiment, the problem to be solved by the present application includes how to determine the first condition; in the above method, the first condition depends on measurement or prediction, thereby solving the above problem.

[0050] As one embodiment, the above method allows aborting the connection failure prediction according to the first condition during the connection failure prediction process.

[0051] As one embodiment, the above method further reduces the impact of connection failure prediction on the UE.

[0052] As one embodiment, the above method determines the first condition by at least one of measurement or prediction, so that the condition for aborting the connection failure prediction is more reasonable.

[0053] According to one aspect of the present application, it features that

[0054] The method comprises:

[0055] When the first condition is met, sending a second notification; receiving the second notification;

[0056] Wherein, the second notification triggers the aborting of the connection failure prediction.

[0057] As one embodiment, the problem to be solved by the application includes: how to trigger the aborting of the connection failure prediction when the first condition is met; in the above method, the terminal sends and receives the second notification, thereby solving the above problem.

[0058] As one embodiment, the above method introduces the second notification inside the terminal, and is simple to implement.

[0059] As one embodiment, the above method is conducive to standardization.

[0060] As one embodiment, the above method is conducive to the separation of connection failure detection and connection failure prediction.

[0061] According to one aspect of the application, it is characterized in that,

[0062] The method comprises:

[0063] As a response to predicting a connection failure, a second statistic is operated; the second statistic is a counter, or the second statistic is a timer.

[0064] As one embodiment, the problem to be solved by the application includes: how to operate after predicting a connection failure; the above method solves the above problem by operating the first statistic.

[0065] As one embodiment, the operation of the first statistic makes it easier to detect a connection failure.

[0066] As one embodiment, the above method avoids detecting a connection failure too late by operating the first statistic.

[0067] As one embodiment, the operation of the first statistic makes it more difficult to detect a connection failure.

[0068] As one embodiment, the above method avoids detecting a connection failure too early by operating the first statistic.

[0069] As one embodiment, the operation of the first statistic makes it impossible to detect a connection failure by the first statistic.

[0070] As one embodiment, the above method avoids the first statistic triggering the detection of a connection failure by operating the first statistic.

[0071] According to one aspect of the application, it is characterized in that,

[0072] The method comprises:

[0073] As a response to predicting a connection failure, starting RRC connection reestablishment.

[0074] As one embodiment, the problem addressed by the present application includes how to operate after predicting a connection failure; the above method solves the problem by initiating RRC connection reestablishment.

[0075] As one embodiment, the above method avoids detecting a connection failure too late by initiating RRC connection reestablishment.

[0076] As one embodiment, the above method improves mobile robustness.

[0077] As one embodiment, the above method improves service continuity.

[0078] As one embodiment, the above method shortens interruption latency.

[0079] According to one aspect of the present application, a feature is that,

[0080] The method comprises:

[0081] As a response to predicting a connection failure, operating the second statistic or initiating RRC connection reestablishment depends on the predicted time of occurrence of the connection failure; the second statistic is a counter, or the second statistic is a timer.

[0082] As one embodiment, the problem addressed by the present application includes how to operate after predicting a connection failure; the above method solves the problem by operating the first statistic or initiating RRC connection reestablishment.

[0083] As one embodiment, the problem addressed by the present application includes how to determine whether to operate the first statistic or initiate RRC connection reestablishment after predicting a connection failure; the above method solves the problem by operating the first statistic or initiating RRC connection reestablishment depending on the predicted time of occurrence of the connection failure.

[0084] As one embodiment, the above method adaptively adjusts the UE behavior after predicting a connection failure, i.e., it can avoid detecting a connection failure too early and can also avoid detecting a connection failure too late.

[0085] As one embodiment, the above method takes into account the impact of the predicted time of occurrence of the connection failure, thereby selecting a more appropriate UE behavior.

[0086] According to one aspect of the present application, a feature is that,

[0087] The method comprises:

[0088] Receiving at least a first reference signal;

[0089] The connection failure prediction depends on the at least first reference signal.

[0090] As an embodiment, the problem to be solved by the present application includes: how to perform connection failure prediction; in the method, the connection failure prediction relies on the at least first reference signal, thereby solving the above problem.

[0091] As an embodiment, the method is beneficial to the combination of connection failure prediction and connection failure detection.

[0092] As an embodiment, the method reduces the standardization work.

[0093] As an embodiment, the method is simple to implement.

[0094] According to an aspect of the present application, it is characterized in that,

[0095] The predicted connection failure relies on at least one of the number of predicted synchronization indications or the number of predicted out-of-sync indications within a first time window; the predicted synchronization indication or the predicted out-of-sync indication relies on the at least first reference signal.

[0096] As an embodiment, the problem to be solved by the present application includes: how to determine to predict connection failure; in the method, the predicted connection failure relies on at least one of the number of predicted synchronization indications or the number of predicted out-of-sync indications within a first time window, thereby solving the above problem.

[0097] As an embodiment, the method improves the accuracy of prediction.

[0098] The present application discloses a method used in a base station, characterized in that, comprising:

[0099] sending first signaling; wherein the first signaling indicates a first threshold value; if a first statistic reaches the first threshold value, a receiver of the first signaling determines connection failure;

[0100] Wherein, if the first statistic reaches a second threshold value, the receiver of the first signaling performs connection failure prediction; the first statistic is a counter, or the first statistic is a timer; the first threshold value and the second threshold value are different.

[0101] According to an aspect of the present application, it is characterized in that, when the first statistic reaches a second threshold value, the receiver of the first signaling sends a first notification; the receiver of the first signaling receives the first notification; wherein the first notification triggers the execution of connection failure prediction.

[0102] According to an aspect of the present application, it is characterized in that,

[0103] In response to the first condition being met, the receiver of the first signaling suspends the connection failure prediction; wherein the first condition depends on at least one of a measurement or a prediction.

[0104] According to an aspect of the present application, there is provided a method for a terminal,

[0105] In response to the first condition being met, the receiver of the first signaling sends a second notification; the receiver of the first signaling receives the second notification; wherein the second notification triggers the suspension of the connection failure prediction.

[0106] According to an aspect of the present application, there is provided a method for a terminal,

[0107] In response to the connection failure being predicted, the receiver of the first signaling operates a second statistic; the second statistic is a counter, or the second statistic is a timer.

[0108] According to an aspect of the present application, there is provided a method for a terminal,

[0109] In response to the connection failure being predicted, the receiver of the first signaling initiates a RRC connection reestablishment.

[0110] According to an aspect of the present application, there is provided a method for a terminal,

[0111] sending at least a first reference signal;

[0112] wherein the connection failure prediction depends on the at least first reference signal.

[0113] According to an aspect of the present application, there is provided a method for a terminal,

[0114] the first signaling indicates the second threshold.

[0115] According to an aspect of the present application, there is provided a method for a terminal,

[0116] the first condition comprises the first statistic reaching a third threshold; the first signaling indicates the third threshold.

[0117] The present application discloses a terminal, characterized in that comprising:

[0118] the terminal comprises one or more processors and a memory;

[0119] the memory is coupled with the one or more processors, the memory is configured to store computer program codes, the computer program codes comprise computer instructions, the one or more processors invoke the computer instructions to make the terminal execute the method.

[0120] A base station is disclosed, characterized by comprising:

[0121] The base station comprises one or more processors and a memory;

[0122] The memory is coupled to the one or more processors, and the memory is configured to store computer program codes including computer instructions, and the one or more processors are configured to invoke the computer instructions to cause the base station to perform the method. BRIEF DESCRIPTION OF DRAWINGS

[0123] Other features, objects, and advantages of the application will become more apparent from the following detailed description of non-limiting embodiments thereof, read in conjunction with the accompanying drawings:

[0124] Fig. 1 shows a flowchart of a terminal according to one embodiment of the present application;

[0125] Fig. 2 shows a schematic diagram of a network architecture according to one embodiment of the present application;

[0126] Fig. 3 shows a schematic diagram of an embodiment of a radio protocol architecture for the user and control planes according to one embodiment of the present application;

[0127] Fig. 4 shows a schematic diagram of a first communication device and a second communication device according to one embodiment of the present application;

[0128] Fig. 5 shows a flowchart of a wireless signal transmission according to one embodiment of the present application;

[0129] Fig. 6 shows a flowchart of a wireless signal transmission according to another embodiment of the present application;

[0130] Fig. 7 shows a flowchart of a wireless signal transmission according to yet another embodiment of the present application;

[0131] Fig. 8 shows a flowchart of a wireless signal transmission according to still another embodiment of the present application;

[0132] Fig. 9 shows a schematic diagram of a first counter according to one embodiment of the present application;

[0133] Fig. 10 shows a schematic diagram of predicting a connection failure according to one embodiment of the present application;

[0134] Fig. 11 shows a structural block diagram of a processing device for use in a terminal according to one embodiment of the present application;

[0135] Fig. 12 shows a structural block diagram of a processing device for use in a base station according to one embodiment of the present application;

[0136] FIG. 13 shows a flowchart of a first state according to an embodiment of the present application;

[0137] FIG. 14 shows a schematic diagram of transmission of a first notification and a second notification according to an embodiment of the present application;

[0138] FIG. 15 shows a schematic diagram of an intelligent model according to an embodiment of the present application;

[0139] FIG. 16 shows a schematic diagram of intelligent function deployment of a RAN (Radio Access Network) domain according to an embodiment of the present application;

[0140] FIG. 17 shows a schematic diagram of UE intelligent function deployment according to an embodiment of the present application;

[0141] FIG. 18 shows a flowchart based on artificial intelligence or machine learning according to an embodiment of the present application. DETAILED DESCRIPTION

[0142] The technical solutions of the present application will be further described in detail below with reference to the accompanying drawings. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other arbitrarily without conflict.

[0143] Embodiment 1

[0144] Embodiment 1 shows a flowchart of a terminal according to an embodiment of the present application, as shown in FIG. 1. In FIG. 1, each block represents a step, and it is particularly emphasized that the order of the blocks in the figure does not represent the time sequence between the steps represented.

[0145] In embodiment 1, the terminal in the present application receives a first signaling in step 101; wherein the first signaling indicates a first threshold value; if a first statistic reaches the first threshold value, it is determined that the connection fails; wherein if the first statistic reaches a second threshold value, a connection failure prediction is performed; the first statistic is a counter, or the first statistic is a timer; the first threshold value and the second threshold value are different.

[0146] As an embodiment, the first signaling indicating the first threshold value means that the first signaling explicitly indicates the first threshold value.

[0147] As an embodiment, the first signaling indicating the first threshold value means that the first signaling implicitly indicates the first threshold value.

[0148] As an embodiment, the first signaling indicating the first threshold value means that the first signaling configures the first threshold value.

[0149] As an embodiment, the first signaling indicates the first threshold by enabling the first threshold.

[0150] As an embodiment, the first signaling is cell common.

[0151] As an embodiment, the first signaling is UE specific.

[0152] As an embodiment, the first signaling is RRC (Radio Resource Control) signaling.

[0153] As an embodiment, the first signaling comprises RRC signaling and MAC (Medium Access Control) CE (Control Element).

[0154] As an embodiment, the first signaling comprises RRC signaling and DCI (Downlink Control Information).

[0155] As an embodiment, the first signaling comprises one RRC signaling, the one RRC signaling configuring the first threshold.

[0156] As an embodiment, the first signaling comprises one RRC signaling and one MAC CE, the one RRC signaling configuring a plurality of thresholds, the one MAC CE indicating the first threshold from the plurality of thresholds.

[0157] As an embodiment, the first signaling comprises one RRC signaling and one DCI, the one RRC signaling configuring a plurality of thresholds, the one DCI indicating the first threshold from the plurality of thresholds.

[0158] As an embodiment, one t310 in the first signaling indicates the first threshold; the first statistic is T310.

[0159] As an embodiment, one t304 in the first signaling indicates the first threshold; the first statistic is T304.

[0160] As an embodiment, one T312-r16 in the first signaling indicates the first threshold; the first statistic is T312.

[0161] As an embodiment, one T316-r16 in the first signaling indicates the first threshold; the first statistic is T316.

[0162] As one embodiment, a preambleTransMax in the first signaling indicates the first threshold; the first statistic is PREAMBLE_TRANSMISSION_COUNTER.

[0163] As one embodiment, a preambleTransMax-r16 in the first signaling indicates the first threshold; the first statistic is PREAMBLE_TRANSMISSION_COUNTER.

[0164] As one embodiment, a maxRetxThreshold in the first signaling indicates the first threshold; the first statistic is RETX_COUNT.

[0165] As one embodiment, the first statistic is for a PCell (Primary Cell) or a MCG (Master Cell Group); connection failure prediction is performed for the PCell or the MCG.

[0166] As one embodiment, the first statistic is for a PCell or a MCG; connection failure prediction is performed for a PSCell (Primary SCG Cell) or a SCG (Secondary Cell Group).

[0167] As one embodiment, the first statistic is for a PSCell or a SCG; connection failure prediction is performed for the PSCell or the SCG.

[0168] As one embodiment, the first statistic is for a target PCell or a target MCG; connection failure prediction is performed for the target PCell or the target MCG.

[0169] As one embodiment, the first statistic is incrementally counted.

[0170] As one embodiment, the first statistic is decrementally counted.

[0171] As one embodiment, the first statistic is incrementally timed.

[0172] As one embodiment, the first statistic is decrementally timed.

[0173] As one embodiment, the first statistic reaching the first threshold means that the first statistic is not less than the first threshold.

[0174] As one embodiment, the first statistic reaching the first threshold means that the first statistic equals the first threshold.

[0175] As one embodiment, the first statistic reaching the first threshold means that the first statistic is not greater than the first threshold.

[0176] As one embodiment, the first statistic is a timer.

[0177] As one embodiment, the first statistic is a timer; the first statistic is decremented.

[0178] As one embodiment, the first statistic is T310.

[0179] As one embodiment, the first statistic is T312.

[0180] As one embodiment, the first statistic is T316.

[0181] As one embodiment, the first statistic is T304.

[0182] As one embodiment, the first statistic is a counter.

[0183] As one embodiment, the first statistic is a counter; the first statistic is incremented.

[0184] As one embodiment, the first statistic is PREAMBLE_TRANSMISSION_COUNTER.

[0185] As one embodiment, the first statistic is RETX_COUNT.

[0186] As one embodiment, the candidates of the first statistic only include timers.

[0187] As one embodiment, the candidates of the first statistic only include counters.

[0188] As one embodiment, the candidates of the first statistic include timers and counters.

[0189] As one embodiment, the candidates of the first statistic include LBT_COUNTER.

[0190] As one embodiment, the above method increases the execution probability of link failure prediction.

[0191] As one embodiment, in any case, the candidates of the first statistic do not include LBT_COUNTER.

[0192] As one embodiment, the above method takes into account the uncertain nature of unlicensed spectrum, avoiding prediction errors.

[0193] As one embodiment, the first statistic is a counter; the candidate of the first statistic includes at least one of PREAMBLE_TRANSMISSION_COUNTER or RETX_COUNT.

[0194] As one embodiment, the candidate of the first statistic includes at least one of T310 or T312 or T304 or T316.

[0195] As one embodiment, the candidate of the first statistic depends on RRC configuration.

[0196] As one embodiment, the candidate of the first statistic depends on UE implementation of the terminal.

[0197] As one embodiment, the candidate of the first statistic is determined by the terminal itself.

[0198] As one embodiment, the first statistic reaching the first threshold means that the first statistic expires; wherein the first statistic is a timer.

[0199] As one sub-embodiment of the above embodiment, the first threshold is 0; the second threshold is greater than 0; the first statistic is decremented.

[0200] As one sub-embodiment of the above embodiment, the first threshold is greater than 0; the second threshold is greater than 0; the first threshold is greater than the second threshold; the first statistic is incremented.

[0201] As one embodiment, the first statistic reaching the second threshold means that the first statistic is not greater than the second threshold.

[0202] As one sub-embodiment of the above embodiment, the first statistic is decremented.

[0203] As one sub-embodiment of the above embodiment, the first statistic reaching the first threshold means that the first statistic expires; wherein the first statistic is a timer.

[0204] As one sub-embodiment of the above embodiment, the first statistic reaching the first threshold means that the first statistic is not greater than the first threshold; wherein the first statistic is a timer.

[0205] As one sub-embodiment of the above embodiment, the first statistic reaching the first threshold means that the first statistic is not greater than the first threshold; wherein the first statistic is a counter.

[0206] As one sub-example of the above embodiment, the not less than is less than.

[0207] As one sub-example of the above embodiment, the not less than is equal to.

[0208] As one sub-example of the above embodiment, the not less than is equal to or less than.

[0209] As one sub-example of the above embodiment, the first threshold is 0; the second threshold is greater than 0.

[0210] As one sub-example of the above embodiment, the first threshold is greater than 0; the second threshold is greater than 0; the first threshold is less than the second threshold.

[0211] As one embodiment, the first statistic reaching the second threshold means that the first statistic is not less than the second threshold.

[0212] As one sub-example of the above embodiment, the first statistic is incremental.

[0213] As one sub-example of the above embodiment, the first statistic reaching the first threshold means that the first statistic expires; wherein the first statistic is a timer.

[0214] As one sub-example of the above embodiment, the first statistic reaching the first threshold means that the first statistic is not less than the first threshold; wherein the first statistic is a timer.

[0215] As one sub-example of the above embodiment, the first statistic reaching the first threshold means that the first statistic is not less than the first threshold; wherein the first statistic is a counter.

[0216] As one sub-example of the above embodiment, the not less than is greater than.

[0217] As one sub-example of the above embodiment, the not less than is equal to.

[0218] As one sub-example of the above embodiment, the not less than is equal to or greater than.

[0219] As one sub-example of the above embodiment, the first threshold is greater than 0; the second threshold is greater than 0; the first threshold is greater than the second threshold.

[0220] As one embodiment, the first statistic prefers to reach the second threshold of the second threshold and the first threshold.

[0221] As an embodiment, the second threshold is indicated by RRC signaling.

[0222] As an embodiment, the second threshold is indicated by the predicted information related to the connection failure.

[0223] As an embodiment, the second threshold is determined by the terminal.

[0224] As an embodiment, the second threshold is default.

[0225] As an embodiment, the second threshold is dedicated for the connection failure prediction.

[0226] As an embodiment, the second threshold is dedicated for the intelligent model used for the connection failure prediction.

[0227] As an embodiment, the second threshold is equal to the product of the maximum value of the first statistic and the first ratio.

[0228] As an embodiment, the second threshold is equal to the product of the first threshold and the first ratio.

[0229] As an embodiment, the first ratio is configurable.

[0230] As an embodiment, the first ratio is greater than 0 and less than 1.

[0231] As an embodiment, the first ratio is greater than 1.

[0232] As an embodiment, the first ratio is fixed.

[0233] As an embodiment, the first ratio is indicated by RRC signaling.

[0234] As an embodiment, the first ratio is indicated by the predicted information related to the connection failure.

[0235] As an embodiment, the first ratio is determined by the terminal.

[0236] As an embodiment, the first ratio is default.

[0237] As an embodiment, the first offset is dedicated for the connection failure prediction.

[0238] As an embodiment, the first offset is dedicated for the intelligent model used for the connection failure prediction.

[0239] As an embodiment, the first offset is equal to the difference between the first threshold and the first offset.

[0240] As an embodiment, the first offset is equal to a difference between a maximum value of the first statistic and the first offset.

[0241] As an embodiment, the first offset is configurable.

[0242] As an embodiment, the first offset is fixed.

[0243] As an embodiment, the first offset is indicated by RRC signaling.

[0244] As an embodiment, the first offset is indicated by the predicted connection failure related information.

[0245] As an embodiment, the first offset is determined by the terminal.

[0246] As an embodiment, the first offset is default.

[0247] As an embodiment, the first offset is dedicated for the connection failure prediction.

[0248] As an embodiment, the first offset is dedicated for an intelligent model for the connection failure prediction.

[0249] As an embodiment, the connection failure is a radio connection failure.

[0250] As an embodiment, the connection failure is a connection failure at RRC layer.

[0251] As an embodiment, the connection failure is RLF.

[0252] As an embodiment, the connection failure is HOF.

[0253] As an embodiment, the connection failure is a connection recovery failure.

[0254] As an embodiment, the determining connection failure means considering that MCG is detected with radio link failure; and the first statistic is a timer.

[0255] As an embodiment, the determining connection failure means considering that MCG is detected with radio link failure; and the first statistic is a counter.

[0256] As an embodiment, the determining connection failure means determining MCG synchronization reconfiguration failure; and the first statistic is T304.

[0257] As an embodiment, the determining connection failure means determining MCG HOF; and the first statistic is T304.

[0258] As one embodiment, the determining the connection failure refers to determining a MCG fast recovery failure; and the first statistic is T316.

[0259] As one embodiment, how the terminal determines the performing the connection failure prediction when the first statistic reaches the second threshold depends on UE implementation.

[0260] As one embodiment, how the terminal notifies the smart module 1501 in embodiment 14 when the first statistic reaches the second threshold depends on UE implementation.

[0261] As one embodiment, the connection failure prediction is performed by a smart model of the terminal for the connection failure prediction.

[0262] As one embodiment, the connection failure prediction is performed by the terminal based on UE implementation.

[0263] As one embodiment, the connection failure prediction is performed by the terminal based on network configuration.

[0264] As one embodiment, the connection failure prediction is performed by the terminal based on UE implementation and network configuration.

[0265] As one embodiment, the connection failure prediction is based on recent measurement results.

[0266] As one embodiment, the connection failure prediction is based on previous measurement results.

[0267] As one embodiment, the connection failure prediction is based on information stored by the terminal.

[0268] As one embodiment, the connection failure prediction is based on information provided by the network.

[0269] As one embodiment, the connection failure prediction is RLF prediction.

[0270] As one embodiment, the connection failure prediction is HOF prediction.

[0271] As one embodiment, the connection failure prediction includes inference.

[0272] As one embodiment, the connection failure prediction includes training.

[0273] As one embodiment, the connection failure prediction includes training and inference.

[0274] As one embodiment, the connection failure prediction includes predicting link quality.

[0275] As one embodiment, the connection failure prediction comprises predicting a synchronization indication.

[0276] As one embodiment, the connection failure prediction comprises predicting an out-of-sync indication.

[0277] As one embodiment, the connection failure prediction comprises predicting whether a timer expires.

[0278] As one embodiment, the connection failure prediction refers to predicting whether a connection failure occurs.

[0279] As one embodiment, the connection failure prediction refers to predicting a probability of a connection failure occurring.

[0280] As one embodiment, the connection failure prediction refers to predicting a time of a connection failure occurring.

[0281] As one embodiment, the connection failure prediction refers to predicting a time interval in which no connection failure occurs.

[0282] As one embodiment, the connection failure prediction refers to predicting a probability of a connection failure occurring over time.

[0283] As one embodiment, for the terminal, AS security is activated, and at least one of SRB2 or at least one DRB or at least one multicast MRB is configured; the performing the connection failure prediction is for the MCG.

[0284] As one embodiment, for the terminal, T316 is not configured, or SCG transmission is suspended, or SCG is deactivated; the performing the connection failure prediction is for the MCG.

[0285] As one embodiment, for the terminal, MCG transmission is suspended; the performing the connection failure prediction is for the SCG.

[0286] Embodiment 2

[0287] Embodiment 2 illustrates a diagram of a network architecture according to one embodiment of the application, as shown in FIG. 2. FIG. 2 illustrates a network architecture 200. The network architecture 200 is a 5G NR (New Radio) / LTE (Long-Term Evolution) / LTE-A (Long-Term Evolution Advanced) system, or the network architecture 200 is a 5G+ network architecture, or the network architecture 200 is a 6G network architecture, or the network architecture 200 is a network architecture of future continued evolution of 3GPP; the network architecture 200 can be referred to as a 5GS (5G System) / EPS (Evolved Packet System), or the network architecture 200 can be referred to as a 6GS (6G System); the network architecture 200 includes a UE (User Equipment) 201, a RAN (Radio Access Network) 202, a core network 210, a HSS (Home Subscriber Server) / UDM (Unified Data Management) 220, and at least one of an Internet service 230. The network architecture 200 can be interconnected 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 appreciate that the various concepts presented throughout this application are amenable to use with networked or other cellular networked environments providing circuit-switched services. The RAN includes a node 203 and other nodes 204. The node 203 provides user and control plane protocol terminations toward the UE 201. The node 203 can be connected to the other nodes 204 via an Xn interface (e.g., backhaul) / X2 interface. The node 203 can also be referred to as a base station, a base transceiver station, a radio base station, a radio transceiver, a transceiver function, a basic service set (BSS), an extended service set (ESS), a TRP (Transmit Receive Point), or some other suitable terminology. The core network 210 is a 5GC (5G Core Network) / EPC (Evolved Packet Core), or the core network 210 is a 6GC; the node 203 provides an access point to the core network 210 for the UE 201.Examples of a UE 201 include a cellular phone, a smart phone, a session initiation protocol (SIP) phone, a laptop, a personal digital assistant (PDA), a satellite radio, a non-tower based station communication, satellite mobile communication, global positioning system, a multimedia device, a video device, a digital audio player (e.g., MP3 player), a camera, a game console, a drone, a flying vehicle, a narrowband internet of things device, a machine type communication device, a land vehicle, a car, a wearable device, or any other similar functional device. Those skilled in the art will also The node 203 is connected by an S1 / NG interface to the core network 210. The core network 210 includes a MME (Mobility Management Entity) / AMF (Authentication Management Field) / SMF (Session Management Function) 211, other MME / AMF / SMF 214, a S-GW (Service Gateway) / UPF (User Plane Function) 212, and a P-GW (Packet Data Network Gateway) / UPF 213. The MME / AMF / SMF 211 is a control node that handles signaling between the UE 201 and the core network 210. Generally, the MME / AMF / SMF 211 provides bearer and connection management. All user IP (Internet Protocal) packets are transferred through the S-GW / UPF 212, which itself is connected to the P-GW / UPF 213. The P-GW provides UE IP address allocation as well as other functions. The P-GW / UPF 213 is connected to the Internet services 230. The Internet services 230 include operator corresponding Internet protocol services, which can specifically include the Internet, an intranet, an IMS (IP Multimedia Subsystem), and a packet switched streaming service.

[0288] As one embodiment, the UE 201 corresponds to the terminal in the present application.

[0289] As one embodiment, the UE 201 is a user equipment (UE).

[0290] As one embodiment, the UE 201 is a base station device (Base Station, BS).

[0291] As one embodiment, the UE 201 is a relay device.

[0292] As one embodiment, the UE 201 is a gateway device.

[0293] As one embodiment, the node 203 corresponds to the base station in the present application.

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

[0295] As one embodiment, the node 203 is a relay device.

[0296] As one embodiment, the node 203 is a gateway device.

[0297] As one embodiment, the user equipment supports intelligent functions.

[0298] As one embodiment, the user equipment supports intelligent modules.

[0299] As one embodiment, the user equipment supports intelligent models.

[0300] As one embodiment, the user equipment supports intelligent models for connection failure prediction.

[0301] As one embodiment, the user equipment supports connection failure prediction.

[0302] As one embodiment, the user equipment supports RLF prediction and HOF prediction.

[0303] As one embodiment, the user equipment supports only one of the two of RLF prediction and HOF prediction.

[0304] As one embodiment, the user equipment supports 3GPP Release 19.

[0305] As one embodiment, the user equipment supports 5G.

[0306] As one embodiment, the user equipment supports 6G.

[0307] As one embodiment, the user equipment supports radio link monitoring (RLM).

[0308] As one embodiment, the user equipment supports handover.

[0309] As an embodiment, the user equipment supports CHO.

[0310] As an embodiment, the user equipment supports cell selection.

[0311] As an embodiment, the user equipment supports transmission of Non-Terrestrial Network (NTN).

[0312] As an embodiment, the user equipment supports transmission of Terrestrial Network (TN).

[0313] As an embodiment, the user equipment supports Dual Connection (DC) transmission.

[0314] As an embodiment, the user equipment comprises a device supporting low latency and high reliability transmission.

[0315] As an embodiment, the user equipment can be a mobile terminal, which can be a mobile phone or an iPad or a computer or a watch or a ring; the user equipment can also be a wearable device, which can be a watch or a ring or shoes or a hat or clothing or glasses, etc.; the user equipment can also be a flying device; the user equipment can also be a vehicle terminal; the user equipment can also be a ship terminal; the user equipment can also be an Internet of Things terminal; the user equipment can also be an industrial Internet of Things terminal; the user equipment can also be a test device; the user equipment can also be a signaling tester; the user equipment can also be an Integrated Access and Backhaul (IAB)-MT.

[0316] As an embodiment, the base station device supports an intelligent model.

[0317] As an embodiment, the base station device supports an intelligent function.

[0318] As an embodiment, the base station device supports selection of an intelligent model.

[0319] As an embodiment, the base station device supports configuration of an intelligent model.

[0320] As an embodiment, the base station device supports configuration of connection failure prediction.

[0321] As an embodiment, the base station device supports transmission of Non-Terrestrial Network (NTN).

[0322] As an embodiment, the base station device supports transmission of a terrestrial network.

[0323] As an embodiment, the base station device comprises a Base Transceiver Station (BTS).

[0324] As an embodiment, the base station device comprises a NodeB (NB); the NodeB can be a gNB or an eNB or an ng-eNB or an en-gNB; the base station device can comprise a CU (Centralized Unit); the base station device can further comprise a DU (Distributed Unit); the base station device can further comprise a TRP (Transmitter Receiver Point).

[0325] As an embodiment, the base station device can be a Macro Cellular base station or a Micro Cell base station or a Pico Cell base station or a Femtocell; the base station device can further be a flight platform device or a satellite device; the base station device can further be a test device or a signaling tester; the base station device can further be a gateway device; the base station device can further be an IAB device; the IAB device comprises at least one of an IAB-node or an IAB-donor or an IAB-donor-CU or an IAB-donor-DU or an IAB-DU or an IAB-MT.

[0326] As an embodiment, the relay device can comprise a relay; the relay can be a L3 relay or a L2 relay; the relay device can further comprise a router; the relay device can further comprise a switch; the relay device can further comprise a gateway device; the relay device can further comprise at least part of a user equipment; the relay device can further comprise at least part of a base station device.

[0327] Embodiment 3

[0328] Figure 3 is a diagram illustrating an embodiment of a radio protocol architecture for the user plane 350 and the control plane 300. Figure 3 shows three layers for the radio protocol architecture for the control plane 300: Layer 1, Layer 2, and Layer 3. Layer 1 (LI layer) is the lowest layer and implements various PHY (Physical layer) signal processing functions. The LI layer will be referred to as the PHY 301 herein. Layer 2 (L2 layer) 305 is above the PHY 301 and includes a MAC (Medium Access Control) sublayer 302, a RLC (Radio Link Control) sublayer 303, and a PDCP (Packet Data Convergence Protocol) sublayer 304. The PDCP sublayer 304 provides multiplexing between different radio bearers and logical channels. The PDCP sublayer 304 also provides security functions, such as ciphering of the data packets, and header compression. The RLC sublayer 303 provides segmentation and reassembly of upper layer data packets, retransmission of lost data packets, and reordering of data packets to compensate for out-of-order reception due to HARQ. The MAC sublayer 302 provides multiplexing between logical and transport channels. The MAC sublayer 302 is also responsible for allocating the various radio resources (e.g., resource blocks) in one cell. The MAC sublayer 302 is also responsible for HARQ operations. The RRC (Radio Resource Control) sublayer 306 in Layer 3 (L3 layer) in the control plane 300 is responsible for obtaining radio resources (i.e., radio bearers) and using RRC signaling to configure the lower layers. The radio protocol architecture for the user plane 350 includes Layer 1 (LI layer) and Layer 2 (L2 layer), which are substantially the same as the corresponding layers and sublayers in the control plane 300 for the physical layer 351, the PDCP sublayer 354 in the L2 layer 355, the RLC sublayer 353 in the L2 layer 355, and the MAC sublayer 352 in the L2 layer 355, but the PDCP sublayer 354 also provides header compression for upper layer data packets to reduce radio transmission overhead. Also included in the L2 layer 355 in the user plane 350 is the SDAP (Service Data Adaptation Protocol) sublayer 356, which is responsible for mapping between QoS flows and data radio bearers (DRBs) to support diverse service

[0329] As one example, the wireless protocol architecture in FIG. 3 is applicable to the terminal in the present application.

[0330] As one example, the wireless protocol architecture in FIG. 3 is applicable to the base station in the present application.

[0331] As one example, the first signaling in the present application is generated at the RRC 306.

[0332] As one example, the first signaling in the present application is generated at the MAC 302 or the MAC 352.

[0333] As one example, the first signaling in the present application is generated at the PHY 301 or the PHY 351.

[0334] As one example, the at least first reference signal in the present application is generated at the PHY 301 or the PHY 351.

[0335] As one example, the first notification is transmitted at a first designated protocol layer of the terminal.

[0336] As one example, the second notification is transmitted at a first designated protocol layer of the terminal.

[0337] As one example, the third notification is received at a first designated protocol layer of the terminal.

[0338] As one example, the fourth notification is received at a first designated protocol layer of the terminal.

[0339] As one example, the first designated protocol layer is one of the protocol layers shown in FIG. 3.

[0340] As one example, the first designated protocol layer is the RRC 306.

[0341] As one example, the first notification is received at a second designated protocol layer of the terminal.

[0342] As one example, the second notification is received at a second designated protocol layer of the terminal.

[0343] As one example, the third notification is transmitted at a second designated protocol layer of the terminal.

[0344] As one example, the fourth notification is transmitted at a second designated protocol layer of the terminal.

[0345] As one example, the second designated protocol layer is one of the protocol layers shown in FIG. 3.

[0346] As an embodiment, the second designated protocol layer is a protocol layer other than the protocol layers shown in Figure 3 (not included in Figure 3).

[0347] Embodiment 4

[0348] Embodiment 4 shows a schematic diagram of a first communication device and a second communication device according to the present application, as shown in Figure 4. Figure 4 is a block diagram of a first communication device 450 and a second communication device 410 communicating with each other in an access network.

[0349] The first communication device 450 comprises a controller / processor 459, a memory 460, a data source 467, a transmit processor 468, a receive processor 456, a multi-antenna transmit processor 457, a multi-antenna receive processor 458, a transmitter / receiver 454 and an antenna 452.

[0350] The second communication device 410 comprises a controller / processor 475, a memory 476, a receive processor 470, a transmit processor 416, a multi-antenna receive processor 472, a multi-antenna transmit processor 471, a transmitter / receiver 418 and an antenna 420.

[0351] In the transmission from the second communication device 410 to the first communication device 450, at the second communication device 410, upper layer packets from the core network are provided to the controller / processor 475. The controller / processor 475 implements functionality of the L2 layer. In the transmission from the second communication device 410 to the first communication device 450, the controller / processor 475 provides header compression, ciphering, packet segmentation and reordering, multiplexing between logical and transport channels, and radio resource allocations for the first communication device 450 based on various priority metrics. The controller / processor 475 is also responsible for retransmission of lost packets, and signaling to the first communication device 450. The transmit processor 416 and the multiple antenna transmit processor 471 implement various signal processing functions for the LI layer (i.e., physical layer). The transmit processor 416 implements coding and interleaving to facilitate forward error correction (FEC) at the second communication device 410, and mapping of coded bits to modulation symbols based on various modulation schemes (e.g., binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), M-phase shift keying (M-PSK), M-quadrature amplitude modulation (M-QAM)). The multiple antenna transmit processor 471 performs digital spatial pre-coding of the coded and modulated symbols, including codebook-based and non-codebook-based pre-coding, and beamforming processing, to generate one or more spatial streams. The transmit processor 416 then maps to each spatial stream to the subcarriers, multiplexes with reference signals (e.g., pilot) in the time and / or frequency domain, and then performs an inverse fast Fourier transform (IFFT) to generate a time-domain multicarrier symbol stream for the physical channel carrying the data. The multiple antenna transmit processor 471 then performs transmit analog pre-coding / beamforming operations on the time-domain multicarrier symbol stream. Each transmitter 418 converts the baseband multicarrier symbol stream provided by the multiple antenna transmit processor 471 into a radio frequency stream, and then provides the radio frequency stream to the corresponding antenna 420.

[0352] In transmissions 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 respective antenna 452. Each receiver 454 recovers information modulated onto an RF carrier and provides the recovered information at baseband as a stream of symbols to a receive processor 456. The receive processor 456 and a multiple access receiver processor 458 implement various signal processing functions of the Ll layer. The multiple access receiver processor 458 performs receive analog precoding / beamforming operations on the baseband multiple access symbol streams from the receivers 454. The receive processor 456 converts the baseband multiple access symbol streams from the time-domain to the frequency domain using a Fast Fourier Transform (FFT). In the frequency domain, the physical layer data signals and the reference signals are demultiplexed from the received symbol streams, with the reference signals to be used for channel estimation and the data signals to be recovered after multiple access detection in the multiple access receiver processor 458 for any spatial streams destined for the first communication device 450. The symbols on each spatial stream are demodulated and recovered by the receive processor 456 and used to generate soft decisions. The receive processor 456 then decodes and de-interleaves the soft decisions to recover the upper layer data and control signals transmitted by the second communication device 410 on the physical channel. The upper layer data and control signals are then provided to a controller / processor 459. The controller / processor 459 implements the functions of the L2 layer. The controller / processor 459 can be associated with a memory 460 that stores program codes and data. The memory 460 can be referred to as a computer-readable medium. In transmissions from the second communication device 410 to the first communication device 450, the controller / processor 459 provides demultiplexing between transport and logical channels, packet reassembly, deciphering, header decompression, control signal processing to recover upper layer data packets from the core network. The upper layer data packets are then provided to all protocol layers above the L2 layer. Various control signals can also be provided to the L3 for L3 processing.

[0353] 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 a controller / processor 459. The data source 467 represents all protocol layers above the L2 layer. Similar to the transmit function at the second communication device 410 described in the transmission from the second communication device 410 to the first communication device 450, the controller / processor 459 implements header compression, ciphering, packet segmentation and reordering, and multiplexing between logical and transport channels based on radio resource allocations, implements L2 layer functionality for the user plane and control plane. The controller / processor 459 is also responsible for error detection, retransmission of lost packets, and signaling to the second communication device 410. A transmit processor 468 performs modulation mapping, channel coding processing, and a multi-antenna transmit processor 457 performs digital multi-antenna spatial precoding, including codebook-based precoding and non-codebook-based precoding, and beamforming processing, and then the transmit processor 468 modulates the resulting spatial streams into multi-carrier / single-carrier symbol streams, which are then provided to different antennas 452 via transmitters 454 after analog precoding / beamforming operations in the multi-antenna transmit processor 457. Each transmitter 454 first converts the baseband symbol stream provided by the multi-antenna transmit processor 457 into a radio frequency signal, and then provides the radio frequency signal to the antenna 452.

[0354] In the transmission from the first communication device 450 to the second communication device 410, the functions at the second communication device 410 are similar to the receive functions at the first communication device 450 described in the transmission from the second communication device 410 to the first communication device 450. Each receiver 418 receives a radio frequency signal through its respective antenna 420, converts the received radio frequency signal into a baseband signal, and provides the baseband signal to a multi-antenna receive processor 472 and a receive processor 470. The receive processor 470 and the multi-antenna receive processor 472 collectively implement the functionality of the L1 layer. A controller / processor 475 implements the functionality of the L2 layer. The controller / processor 475 can be associated with a memory 476 that stores program codes and data. The memory 476 can be referred to as a computer readable medium. In the transmission from the first communication device 450 to the second communication device 410, the controller / processor 475 provides demultiplexing between transport and logical channels, packet reassembly, deciphering, header decompression, control signal processing to recover upper layer data packets from the UE 450. Upper layer data packets from the controller / processor 475 can be provided to a core network.

[0355] As one embodiment, the first communication device 450 comprises: at least one processor and at least one memory including a computer program code; the at least one memory and the computer program code are configured to, with the at least one processor, cause the first communication device 450 at least to: receive first signaling; wherein the first signaling indicates a first threshold; determine a connection failure if a first statistic reaches the first threshold; wherein a connection failure prediction is performed if the first statistic reaches a second threshold; the first statistic is a counter, or the first statistic is a timer; the first threshold and the second threshold are different.

[0356] As one embodiment, the first communication device 450 comprises: a memory storing a computer readable program of instructions which, when executed by at least one processor, causes actions comprising: receiving first signaling; wherein the first signaling indicates a first threshold; determining a connection failure if a first statistic reaches the first threshold; wherein a connection failure prediction is performed if the first statistic reaches a second threshold; the first statistic is a counter, or the first statistic is a timer; the first threshold and the second threshold are different.

[0357] As one embodiment, the second communication device 410 comprises: at least one processor and at least one memory including a computer program code; the at least one memory and the computer program code are configured to, with the at least one processor, cause the second communication device 410 at least to: send first signaling; wherein the first signaling indicates a first threshold; a receiver of the first signaling determines a connection failure if a first statistic reaches the first threshold; wherein a connection failure prediction is performed by the receiver of the first signaling if the first statistic reaches a second threshold; the first statistic is a counter, or the first statistic is a timer; the first threshold and the second threshold are different.

[0358] As one embodiment, the second communication device 410 comprises: a memory storing a computer readable program of instructions which, when executed by at least one processor, causes actions comprising: sending first signaling; wherein the first signaling indicates a first threshold; a receiver of the first signaling determines a connection failure if a first statistic reaches the first threshold; wherein a connection failure prediction is performed by the receiver of the first signaling if the first statistic reaches a second threshold; the first statistic is a counter, or the first statistic is a timer; the first threshold and the second threshold are different.

[0359] As an embodiment, at least one of the antenna 452, the receiver 454, the receive processor 456, the controller / processor 459 is configured to receive the first signaling.

[0360] As an embodiment, at least one of the antenna 420, the transmitter 418, the transmit processor 416, the controller / processor 475 is configured to transmit the first signaling.

[0361] As an embodiment, at least one of the antenna 452, the transmitter 454, the transmit processor 468, the controller / processor 459 is configured to transmit at least the first reference signal.

[0362] As an embodiment, at least one of the antenna 420, the receiver 418, the receive processor 470, the controller / processor 475 is configured to receive at least the first reference signal.

[0363] As an embodiment, the first communication device 450 corresponds to the terminal in the present application.

[0364] As an embodiment, the second communication device 410 corresponds to the base station in the present application.

[0365] As an embodiment, the first communication device 450 is a user equipment.

[0366] As an embodiment, the first communication device 450 is a base station device.

[0367] As an embodiment, the first communication device 450 is a relay device.

[0368] As an embodiment, the first communication device 450 performs the connection failure prediction.

[0369] As an embodiment, optionally, the first communication device 450 comprises the intelligent module 1501 in the attached Figure 14 (not included in Figure 4).

[0370] As an embodiment, optionally, the first communication device 450 comprises the third module in the attached Figure 15 (not included in Figure 4).

[0371] As an embodiment, optionally, the first communication device 450 comprises the inference function 1806 in the attached Figure 17 (not included in Figure 4).

[0372] As an embodiment, the second communication device 410 is a user equipment.

[0373] As an embodiment, the second communication device 410 is a base station device.

[0374] As one embodiment, the second communication device 410 is a relay device.

[0375] As one embodiment, optionally, the second communication device 410 assists in performing the connection failure prediction.

[0376] As one embodiment, optionally, the second communication device 410 includes an inference function (not included in FIG. 4) of FIG. 16.

[0377] As one embodiment, optionally, the second communication device 410 includes a RAN domain training function 1805 (not included in FIG. 4) of FIG. 17.

[0378] Embodiment 5

[0379] Embodiment 5 illustrates a wireless signal transmission flowchart according to one embodiment of the present application, as shown in FIG. 5. It is particularly pointed out that the sequence in this example does not limit the sequence of signal transmission and implementation in the present application.

[0380] For terminal U01, in step S5101, a first signaling is received; wherein the first signaling indicates a first threshold; in step S5102, at least a first reference signal is received; in step S5103, it is determined whether the first statistic reaches a second threshold; if the first statistic reaches the second threshold, step S5106 is executed, otherwise, step S5106 is not executed; in step S5104, when the first statistic reaches the second threshold, a first notification is sent; in step S5105, the first notification is received; wherein the first notification triggers the execution of the connection failure prediction; in step S5106, the connection failure prediction is executed; in step S5107, it is determined whether a first condition is met; in response to the first condition being met, step S5110 is executed, otherwise, step S5110 is not executed; wherein the first condition depends on at least one of measurement or prediction; in step S5108, when the first condition is met, a second notification is sent; in step S5109, the second notification is received; wherein the second notification triggers the suspension of the connection failure prediction; in step S5110, the connection failure prediction is suspended; in step S5111, it is determined whether the first statistic reaches the first threshold; if the first statistic reaches the first threshold, step S5112 is executed, otherwise, step S5112 is not executed; in step S5112, a connection failure is determined.

[0381] For base station N02, in step S5201, a first signaling is sent; in step S5202, at least a first reference signal is sent.

[0382] In embodiment 5, the first statistic is a counter, or, the first statistic is a timer; the first threshold and the second threshold are different.

[0383] As one embodiment, the base station N02 is a base station to which a serving cell of the terminal U01 belongs.

[0384] As one embodiment, the base station N02 is a base station to which a PCell of the terminal U01 belongs.

[0385] As one embodiment, the base station N02 is a base station to which a PSCell of the terminal U01 belongs.

[0386] As one embodiment, the base station N02 is a Master Node (MN).

[0387] As one embodiment, the base station N02 is a Secondary Node (SN).

[0388] As one embodiment, the terminal U01 and the base station N02 are connected through a wireless connection.

[0389] As one embodiment, the terminal U01 and the base station N02 are connected through a wired connection.

[0390] As one embodiment, the terminal U01 and the base station N02 are connected through a Uu interface.

[0391] As one embodiment, the terminal U01 and the base station N02 are connected through an IAB interface.

[0392] As one embodiment, the terminal U01 and the base station N02 are connected through a PC5 interface.

[0393] As one embodiment, the first notification is an indication.

[0394] As one embodiment, the first notification is a notification.

[0395] As one embodiment, the first notification is a cross-layer indication.

[0396] As one embodiment, the first notification is a cross-entity indication.

[0397] As one embodiment, the first notification is within the terminal U01.

[0398] As one embodiment, the first notification is transmitted and received within the terminal U01.

[0399] As one embodiment, the first notification activates a smart model for the connection failure prediction.

[0400] As one embodiment, the first notification enables a smart model for the connection failure prediction.

[0401] As one embodiment, the first notification indicates a parameter of a smart model for the connection failure prediction.

[0402] As one embodiment, the parameter of the smart model for the connection failure prediction comprises an identification of a smart model for the connection failure prediction.

[0403] As one embodiment, the parameter of the smart model for the connection failure prediction comprises a type of a smart model for the connection failure prediction.

[0404] As one embodiment, the parameter of the smart model for the connection failure prediction comprises a current value of the first statistic.

[0405] As one embodiment, the first notification triggering the performing the connection failure prediction means that the first notification requests the performing the connection failure prediction.

[0406] As one embodiment, the first notification triggering the performing the connection failure prediction means that the first notification indicates the performing the connection failure prediction.

[0407] As one embodiment, the first notification triggering the performing the connection failure prediction means that the connection failure prediction is performed when the first notification is received.

[0408] As one embodiment, how the terminal U01 determines to abort the connection failure prediction when the first condition is met depends on UE implementation.

[0409] As one embodiment, how the terminal U01 notifies the smart module 1501 in embodiment 14 when the first condition is met depends on UE implementation.

[0410] As one embodiment, the aborting is stopping.

[0411] As one embodiment, the aborting is terminating.

[0412] As one embodiment, the aborting is suspending.

[0413] As one embodiment, the aborting is suspending.

[0414] As one embodiment, the first condition depends on the first statistic means that the first condition depends on the first statistic.

[0415] As one embodiment, the first condition depends on the first statistic means that the first condition includes the first statistic not reaching the second threshold.

[0416] As one embodiment, the first condition depends on the first statistic means that the first condition includes the first statistic reaching a third threshold.

[0417] As one embodiment, the third threshold is greater than the second threshold.

[0418] As one embodiment, the third threshold is less than the second threshold.

[0419] As one embodiment, the third threshold is the first threshold.

[0420] As one embodiment, the first condition depends on a prediction means that the first condition depends on an intelligent model for the connection failure prediction.

[0421] As one embodiment, the first condition depends on an intelligent model for the connection failure prediction means that the first condition includes the intelligent model for the connection failure prediction being updated.

[0422] As one embodiment, the first condition depends on an intelligent model for the connection failure prediction means that the first condition includes the intelligent model for the connection failure prediction being reconfigured.

[0423] As one embodiment, the first condition depends on an intelligent model for the connection failure prediction means that the first condition includes the intelligent model for the connection failure prediction being deactivated.

[0424] As one embodiment, the first condition depends on a measurement means that the first condition includes considering that a MCG is detected with radio link failure.

[0425] As one embodiment, the first condition depends on a measurement means that the first condition includes T310 being stopped.

[0426] As one embodiment, the first condition depends on a measurement means that the first condition includes T312 being stopped.

[0427] As one embodiment, the first condition depends on a measurement means that the first condition includes handover failure.

[0428] As one embodiment, the first condition depends on a measurement means that the first condition includes T304 being stopped.

[0429] As one embodiment, the second notification is an indication.

[0430] As one embodiment, the second notification is a notification.

[0431] As one embodiment, the second notification is a cross-layer indication.

[0432] As one embodiment, the second notification is a cross-entity indication.

[0433] As one embodiment, the second notification is within the terminal U01.

[0434] As one embodiment, the second notification is transmitted and received within the terminal U01.

[0435] As one embodiment, the second notification deactivates a smart model for the connection failure prediction.

[0436] As one embodiment, the second notification disables a smart model for the connection failure prediction.

[0437] As one embodiment, the second notification indicates an identity of a smart model for the connection failure prediction.

[0438] As one embodiment, the second notification indicates a type of a smart model for the connection failure prediction.

[0439] As one embodiment, the second notification triggering the aborting the connection failure prediction means that the second notification requests aborting the performing connection failure prediction.

[0440] As one embodiment, the second notification triggering the aborting the connection failure prediction means that the second notification indicates aborting the performing connection failure prediction.

[0441] As one embodiment, the second notification triggering the aborting the connection failure prediction means that the connection failure prediction is aborted when the second notification is received.

[0442] As one embodiment, resetting a smart model of the connection failure prediction is accompanied with the aborting the connection failure prediction.

[0443] As one embodiment, clearing at least part of information of the connection failure prediction is accompanied with the aborting the connection failure prediction.

[0444] As one embodiment, clearing at least part of cache of the connection failure prediction is accompanied with the aborting the connection failure prediction.

[0445] As one embodiment, the above method avoids the impact on the subsequent connection failure prediction.

[0446] As one embodiment, the receiving the at least first reference signal comprises receiving the first reference signal at each available reception occasion of each reference signal in the at least first reference signal.

[0447] As one embodiment, the receiving the at least first reference signal comprises receiving the first reference signal at at least one available reception occasion of each reference signal in the at least first reference signal.

[0448] As one embodiment, the available reception occasion of one reference signal is a time-frequency resource configured to the one reference signal.

[0449] As one embodiment, the available reception occasion of one reference signal is a time-frequency resource configured to the one reference signal and non-overlapping with a specified time-frequency resource.

[0450] As one sub-embodiment of the above embodiment, the specified time-frequency resource comprises an active measurement gap.

[0451] As one sub-embodiment of the above embodiment, the transmission on the specified time-frequency resource has a higher priority than the one reference signal.

[0452] As one embodiment, the transmitter of the at least first reference signal is a cell to which the connection failure prediction is directed.

[0453] As one embodiment, the at least first reference signal is a physical layer signal.

[0454] As one embodiment, the at least first reference signal is a Reference Signal.

[0455] As one embodiment, any reference signal in the at least first reference signal is used for connection failure prediction.

[0456] As one embodiment, any reference signal in the at least first reference signal is used for Radio Link Monitoring (RLM).

[0457] As one embodiment, any reference signal in the at least first reference signal is used for RLM and connection failure prediction.

[0458] As one embodiment, the at least first reference signal is Downlink (DL).

[0459] As one embodiment, the at least first reference signal is a Sidelink (SL).

[0460] As one embodiment, the at least first reference signal is periodic.

[0461] As one embodiment, the at least first reference signal is semi-persistent.

[0462] As one embodiment, the at least first reference signal comprises a Synchronization Signal.

[0463] As one embodiment, each of the at least first reference signal is one SSB (Synchronization Signal Block, or SS / PBCH).

[0464] As one embodiment, the at least first reference signal is a Synchronization Signal.

[0465] As one embodiment, each of the at least first reference signal is one CSI-RS (Channel State Information Reference Signal).

[0466] As one embodiment, the at least first reference signal is indicated by RRC signaling.

[0467] As one embodiment, the at least first reference signal is determined by the terminal U01.

[0468] As one embodiment, the at least first reference signal is the first reference signal.

[0469] As one embodiment, the at least first reference signal is a plurality of reference signals; the plurality of reference signals comprises at least the first reference signal.

[0470] As one embodiment, the at least first reference signal is no more than M1 reference signals; the M1 is a positive integer.

[0471] As one embodiment, the M1 depends on L max in TS 38.213.

[0472] As one embodiment, the M1 is N RLM in TS 38.213.

[0473] As one embodiment, the M1 is 2 or 4 or 8.

[0474] As one embodiment, the M1 is no more than 8.

[0475] As one embodiment, the M1 is no more than 16.

[0476] As one embodiment, the connection failure prediction comprises predicting a link quality for the at least first reference signal.

[0477] As one embodiment, the connection failure prediction comprises predicting a number of synchronization indications; the synchronization indications are dependent on the at least first reference signal.

[0478] As one embodiment, the connection failure prediction comprises predicting a number of out-of-sync indications; the out-of-sync indications are dependent on the at least first reference signal.

[0479] As one embodiment, the connection failure prediction comprises predicting a link quality for the at least first reference signal.

[0480] As one embodiment, the connection failure prediction comprises predicting a number of synchronization indications; the synchronization indications are dependent on the at least first reference signal.

[0481] As one embodiment, the connection failure prediction is dependent on the at least first reference signal.

[0482] As one embodiment, the connection failure prediction is dependent on a measurement result for the at least first reference signal.

[0483] As one embodiment, an input to an intelligent model for the connection failure prediction comprises a measurement result for the at least first reference signal.

[0484] As one embodiment, an inference of an intelligent model for the connection failure prediction is dependent on a measurement result for the at least first reference signal.

[0485] As one embodiment, the measurement result for the at least first reference signal comprises at least one measurement value for the at least first reference signal.

[0486] As one embodiment, the measurement result for the at least first reference signal comprises at least one measurement value for each of the at least first reference signal.

[0487] As one embodiment, the at least one measurement value is only one measurement value.

[0488] As one embodiment, the at least one measurement value is a plurality of measurement values.

[0489] As one embodiment, the plurality of measurement values are obtained at different times.

[0490] As one embodiment, the multiple measurement values are obtained at the same time.

[0491] As one embodiment, the measurement value is RSRP (Reference Signal Receiving Power).

[0492] As one embodiment, the measurement value is RSRQ (Reference Signal Receiving Power).

[0493] As one embodiment, the measurement value is SINR (Signal to Interference plus Noise Ratio).

[0494] As one embodiment, the dashed box F5.1 is optional.

[0495] As one embodiment, the dashed box F5.1 is absent.

[0496] As one embodiment, the dashed box F5.1 is present.

[0497] As one embodiment, the step S5107 is optional.

[0498] As one embodiment, the step S5107 is absent.

[0499] As one embodiment, the step S5107 is present.

[0500] As one embodiment, the dashed box F5.2 is optional.

[0501] As one embodiment, the dashed box F5.2 depends on the step S5107.

[0502] As one embodiment, the dashed box F5.2 is absent and the step S5107 is present.

[0503] As one embodiment, the dashed box F5.2 is present and the step S5107 is present.

[0504] As one embodiment, optionally, the terminal U01 sends first UE capability information (not shown in the figure 5); wherein the first UE capability information indicates that the terminal U01 supports connection failure prediction.

[0505] As one embodiment, the “if the first statistic reaches a second threshold, perform connection failure prediction” depends on the first UE capability information indicating that the terminal U01 supports connection failure prediction.

[0506] As one embodiment, the first UE capability information indicates that the terminal U01 supports connection failure prediction; and the connection failure prediction is performed if the first statistic reaches a second threshold.

[0507] As one embodiment, the first UE capability information comprises one RRC message; and the one RRC message indicates that the terminal U01 supports connection failure prediction.

[0508] As one embodiment, the first UE capability information comprises one RRC message and one MAC CE; the one RRC message indicates a plurality of UE capabilities; and the one MAC CE indicates that the terminal U01 supports connection failure prediction from the plurality of UE capabilities.

[0509] As one embodiment, the one RRC message is a UECapabilityInformation message.

[0510] As one embodiment, the one RRC message is a UEAssistanceInformation message.

[0511] As one embodiment, the first UE capability information indicates parameters of at least one intelligent model supported by the terminal U01; optionally, the parameters can be an identification of the intelligent model, a type of the intelligent model, a function of the intelligent model, etc.

[0512] As one sub-embodiment of the above embodiment, one of the at least one intelligent model supported by the terminal U01 is an intelligent model for the connection failure prediction.

[0513] As one embodiment, the first UE capability information indicates that the terminal U01 supports connection failure prediction; and the connection failure prediction comprises RLF prediction and HOF prediction.

[0514] As one embodiment, the first UE capability information indicates that the terminal U01 supports connection failure prediction; and the connection failure prediction is RLF prediction.

[0515] As one embodiment, the first UE capability information indicates that the terminal U01 supports connection failure prediction; and the connection failure prediction is HOF prediction.

[0516] As one embodiment, the first UE capability information indicates RLF prediction from RLF prediction and HOF prediction; and the connection failure prediction is RLF prediction.

[0517] As one embodiment, the first UE capability information indicates HOF prediction from RLF prediction and HOF prediction; the connection failure prediction is HOF prediction.

[0518] As one embodiment, the first UE capability information indicates both RLF prediction and HOF prediction from RLF prediction and HOF prediction; the connection failure prediction is RLF prediction and HOF prediction.

[0519] As one embodiment, the terminal U01 receives a second message (not shown in the figure 5); wherein, the second message enables the connection failure prediction.

[0520] As one embodiment, the “if the first statistic reaches the second threshold, perform the connection failure prediction” relies on the second message to enable the connection failure prediction.

[0521] As one embodiment, if the first statistic reaches the second threshold, perform the connection failure prediction on the premise that the second message enables the connection failure prediction.

[0522] As one embodiment, the second message indicates the parameters of the enabled at least one intelligent model; optionally, the parameters can be the identification of the intelligent model, also can be the type of the intelligent model, also can be the function of the intelligent model, etc.

[0523] As one sub-embodiment of the above-mentioned embodiment, the second message indicates that one intelligent model in the enabled at least one intelligent model is the intelligent model for the connection failure prediction.

[0524] As one embodiment, the second message includes one RRC message; the one RRC message enables the connection failure prediction.

[0525] As one embodiment, the second message includes one MAC CE; the one MAC CE enables the connection failure prediction.

[0526] As one embodiment, the second message includes one DCI; the one DCI enables the connection failure prediction.

[0527] As one embodiment, the enable includes enable.

[0528] As one embodiment, the enable includes activation.

[0529] As one embodiment, the enable includes enablement.

[0530] As one embodiment, the enable includes validity.

[0531] As one embodiment, the enabling includes triggering.

[0532] Embodiment 6

[0533] Embodiment 6 illustrates a wireless signal transmission flowchart according to another embodiment of the present application, as shown in FIG. 6. It is particularly explained that the sequence in this example does not limit the sequence of signal transmission and implementation in the present application.

[0534] For the terminal U01, in step S6101, a connection failure is predicted; in step S6102, in response to predicting the connection failure, a second statistic is operated; the second statistic is a counter, or the second statistic is a timer.

[0535] As one embodiment, the second statistic is operated as long as the connection failure is predicted.

[0536] As one embodiment, the second statistic is operated if the connection failure is predicted.

[0537] As one embodiment, the second statistic is operated on the premise of at least predicting the connection failure.

[0538] As one embodiment, the second statistic is operated in response to predicting the connection failure, regardless of the time of predicting the connection failure.

[0539] As one embodiment, the connection failure is predicted by the terminal U01 based on UE implementation.

[0540] As one embodiment, the connection failure is predicted by the terminal U01 based on protocol specification.

[0541] As one embodiment, the connection failure is predicted by an intelligent model.

[0542] As one embodiment, the connection failure is predicted by an intelligent model for predicting the connection failure.

[0543] As one embodiment, the predicting the connection failure means predicting N310 consecutive out-of-sync indications; the N310 is a positive integer.

[0544] As one embodiment, the predicting the connection failure means predicting that the number of consecutive out-of-sync indications will reach N310; the N310 is a positive integer.

[0545] As one embodiment, the predicting the connection failure means predicting that the number of consecutive out-of-sync indications within the first time window will reach N310; the N310 is a positive integer.

[0546] As one embodiment, said predicting a connection failure means predicting that T310 will expire.

[0547] As one embodiment, said predicting a connection failure means predicting that T312 will expire.

[0548] As one embodiment, said predicting a connection failure means predicting that either one of T310 or T312 will expire.

[0549] As one embodiment, said predicting a connection failure means predicting that a connection failure will occur.

[0550] As one embodiment, said predicting a connection failure means predicting that a first indicator of a connection failure will reach a first threshold.

[0551] As one embodiment, said first indicator comprises a BLER (Block Error Rate).

[0552] As one embodiment, said first indicator comprises a RSRP.

[0553] As one embodiment, said first indicator comprises a RSRQ.

[0554] As one embodiment, said first indicator comprises a probability.

[0555] As one embodiment, said first indicator comprises a confidence.

[0556] As one embodiment, said response to predicting a connection failure means when said predicting a connection failure is predicted.

[0557] As one embodiment, said response to predicting a connection failure means as soon as said predicting a connection failure is predicted.

[0558] As one embodiment, said response to predicting a connection failure means at least after said predicting a connection failure is predicted.

[0559] As one embodiment, said second statistic is a counter.

[0560] As one embodiment, said second statistic is a timer.

[0561] As one embodiment, said second statistic is said first statistic.

[0562] As one embodiment, said second statistic is not said first statistic.

[0563] As one embodiment, the first statistic is not T310; the second statistic is T310.

[0564] As one sub-embodiment of the above embodiment, the first statistic is T312.

[0565] As one sub-embodiment of the above embodiment, the first statistic is T304.

[0566] As one sub-embodiment of the above embodiment, the first statistic is T316.

[0567] As one sub-embodiment of the above embodiment, the first statistic is a counter.

[0568] As one embodiment, the second statistic is N311.

[0569] As one embodiment, the second statistic is N310.

[0570] As one embodiment, the operation on the second statistic is stopping the second statistic; the second statistic is a timer.

[0571] As one embodiment, the operation on the second statistic is changing the value of the second statistic; the second statistic is a timer.

[0572] As one sub-embodiment of the above embodiment, the change is increasing.

[0573] As one sub-embodiment of the above embodiment, the change is decreasing.

[0574] As one sub-embodiment of the above embodiment, the value of the second statistic is changed according to RRC configuration.

[0575] As one sub-embodiment of the above embodiment, the value of the second statistic is changed according to the predicted information related to the connection failure.

[0576] As one sub-embodiment of the above embodiment, the changing of the value of the second statistic includes changing the current value of the second statistic.

[0577] As one sub-embodiment of the above embodiment, the changing of the value of the second statistic includes changing the value of the second statistic at the next start.

[0578] As one embodiment, the operation on the second statistic is resetting the second statistic; the second statistic is a counter.

[0579] As one embodiment, the first statistic is not started within a time interval from the predicted connection failure to a time of the predicted connection failure; the operation second statistic is stopping the second statistic; the second statistic is the first statistic; and the first statistic is T310.

[0580] As one sub-embodiment of the above embodiment, the meaning of stopping includes not continuing to count.

[0581] As one sub-embodiment of the above embodiment, the meaning of stopping includes continuing to count.

[0582] Embodiment 7

[0583] Embodiment 7 illustrates a flowchart of wireless signal transmission according to yet another embodiment of the present application, as shown in FIG. 7. It is particularly noted that the sequence in this example does not limit the sequence of signal transmission and implementation in the present application.

[0584] For terminal U01, in step S7101, a connection failure is predicted; and in step S7102, in response to the predicted connection failure, RRC connection reestablishment is started.

[0585] As one embodiment, the predicted connection failure and the meaning of response to the predicted connection failure refer to Embodiment 6, which is not repeated here.

[0586] As one embodiment, RRC connection reestablishment is started as long as a connection failure is predicted.

[0587] As one embodiment, RRC connection reestablishment is started if a connection failure is predicted.

[0588] As one embodiment, RRC connection reestablishment is started on the premise of at least predicting a connection failure.

[0589] As one embodiment, RRC connection reestablishment is started in response to the predicted connection failure regardless of a time of the predicted connection failure.

[0590] As one embodiment, a connection failure is determined after the predicted connection failure and before the RRC connection reestablishment is started.

[0591] As one embodiment, a connection failure is not determined after the predicted connection failure and before the RRC connection reestablishment is started.

[0592] As one embodiment, no legitimate event triggering the determination of a connection failure is detected within a time interval from the predicted connection failure to the RRC connection reestablishment being started.

[0593] As one embodiment, the triggering determining a legitimate event of connection failure comprises: T310 expiration of the PCell.

[0594] As one embodiment, the triggering determining a legitimate event of connection failure comprises: T312 expiration of the PCell.

[0595] As one embodiment, the triggering determining a legitimate event of connection failure comprises: receiving a Random Access problem indication from the MCG MAC and none of T300, T301, T304, T311, T316 and T319 is running and a Small Data Transmission (SDT) procedure is not ongoing.

[0596] As one embodiment, the triggering determining a legitimate event of connection failure comprises: reaching the RLC maximum retransmission number and a SDT procedure is not ongoing.

[0597] As one embodiment, the triggering determining a legitimate event of connection failure comprises: receiving a consecutive uplink LBT (Listen Before Talk) failure indication of the MCG MAC.

[0598] As one embodiment, the triggering determining a legitimate event of connection failure comprises: T304 expiration of the MCG.

[0599] Embodiment 8

[0600] Embodiment 8 illustrates a flow chart of wireless signal transmission according to yet another embodiment of the present application, as shown in FIG. 8. It is particularly noted that the sequence in this example does not limit the sequence of signal transmission and the sequence of implementation in the present application.

[0601] For the terminal U01, in step S8101, a connection failure is predicted; in step S8102, it is determined whether the occurrence time of the predicted connection failure is earlier than a first time; if the occurrence time of the predicted connection failure is earlier than the first time, step S8103(a) is executed; otherwise, step S8103(b) is executed; in step S8103(a), RRC connection reestablishment is started; in step S8103(b), a second statistic is operated.

[0602] In embodiment 8, in response to predicting a connection failure, whether to operate a second statistic or to start RRC connection reestablishment depends on the occurrence time of the predicted connection failure; the second statistic is a counter, or the second statistic is a timer.

[0603] As one embodiment, the first time is an expiry time of a first timer.

[0604] As one embodiment, the first time is an expiry time of a first timer.

[0605] As one embodiment, the first timer is the first statistic; the first statistic is a timer.

[0606] As one embodiment, the first time is an expiry time of the first statistic.

[0607] As one embodiment, the first timer is not the first statistic.

[0608] As one embodiment, the first timer is T310; the T310 is running.

[0609] As one embodiment, the first timer is T312; the T312 is running.

[0610] As one embodiment, the first timer is the smaller one of T310 and T312; both the T310 and the T312 are running.

[0611] As one embodiment, the first time is a time after a specified time interval from the time when the connection failure is predicted.

[0612] As one embodiment, the specified time interval is configurable.

[0613] As one embodiment, the specified time interval is indicated by an RRC message.

[0614] As one embodiment, the specified time interval is indicated by the related information of the predicted connection failure.

[0615] As one embodiment, as a response to the predicted connection failure, operating the second statistic, or, initiating RRC connection reestablishment.

[0616] As one embodiment, if the occurrence time of the predicted connection failure is later than the first time, operating the second statistic; if the occurrence time of the predicted connection failure is earlier than the first time, initiating RRC connection reestablishment.

[0617] As one embodiment, if the occurrence time of the predicted connection failure is later than the first time, operating the second statistic along with the time when the connection failure is predicted.

[0618] As one embodiment, if the predicted time of occurrence of the connection failure is earlier than the first time, RRC connection reestablishment is initiated along with the predicted time of occurrence of the connection failure.

[0619] As one embodiment, if the predicted time of occurrence of the connection failure is earlier than the first time, RRC connection reestablishment is initiated along with the predicted time of occurrence of the connection failure.

[0620] As one embodiment, if the predicted time of occurrence of the connection failure is the first time, the second statistic is operated.

[0621] As one embodiment, if the predicted time of occurrence of the connection failure is the first time, RRC connection reestablishment is initiated.

[0622] Embodiment 9

[0623] Embodiment 9 illustrates a diagram of a first statistic according to one embodiment of the present application, as shown in FIG. 9. In the diagram 9, the horizontal axis represents the value of the first statistic; the difference between the second threshold and the initial value is not greater than the difference between the first threshold and the initial value.

[0624] As one embodiment, the initial value is greater than the second threshold, and the second threshold is greater than the first threshold.

[0625] As one embodiment, the initial value is less than the second threshold, and the second threshold is less than the first threshold.

[0626] As one embodiment, the initial value is 0; and the second threshold is not greater than the first threshold.

[0627] As one embodiment, the initial value is the maximum value of the first statistic; and the second threshold is not less than the first threshold.

[0628] As one embodiment, if the first statistic is reset, the first statistic starts from the initial value again.

[0629] As one embodiment, if the first statistic is stopped, the first statistic does not change before starting or restarting.

[0630] As one embodiment, if the first statistic is started, the first statistic starts timing or counting.

[0631] As one embodiment, if the first statistic is not started, the first statistic does not time or count.

[0632] As one embodiment, whether the first threshold and the second threshold are equal is configurable.

[0633] As one embodiment, the first threshold and the second threshold are not equal by default.

[0634] As one embodiment, the first threshold and the second threshold are equal.

[0635] As one embodiment, the above method reduces the impact on existing connection failure detection mechanisms.

[0636] As one embodiment, the first threshold and the second threshold are not equal.

[0637] As one embodiment, the above method avoids triggering connection failure too early.

[0638] Embodiment 10

[0639] Embodiment 10 illustrates an example of predicting connection failure according to one embodiment of the present application, as shown in FIG. 10. In the FIG. 10, the horizontal axis represents time, t10.1 is the start time of the first time window, t10.2 is the end time of the first time window, the solid single-headed arrow represents a predicted in-sync indication, the dashed single-headed arrow represents a predicted out-of-sync indication, and every other predicted indication period corresponds to a prediction evaluation occasion.

[0640] In embodiment 10, the predicting connection failure relies on at least one of a number of predicted in-sync indications or a number of predicted out-of-sync indications within a first time window; the predicted in-sync indication or the predicted out-of-sync indication relies on the at least first reference signal.

[0641] As one embodiment, the predicted out-of-sync indication relies on a predicted link quality for the at least first reference signal.

[0642] As one embodiment, the predicted link quality is RSRP.

[0643] As one embodiment, the predicted link quality is RSRQ.

[0644] As one embodiment, the predicted link quality is BLER.

[0645] As one embodiment, the predicted link quality is filtered by L1 or L3.

[0646] As one embodiment, the predicted link quality is unfiltered.

[0647] As one embodiment, the predicted link quality is a new quantity.

[0648] As one embodiment, a predicted out-of-sync indication is predicted if the predicted link quality for each of the at least first reference signals is worse than a first predicted out-of-sync threshold for a predicted out-of-sync evaluation period.

[0649] As one embodiment, the first predicted out-of-sync threshold is Qout configured by rlmInSyncOutOfSyncThreshold.

[0650] As one embodiment, the first predicted out-of-sync threshold is not Qout configured by rlmInSyncOutOfSyncThreshold.

[0651] As one embodiment, the predicted in-sync indication depends on the predicted link quality for the at least first reference signals.

[0652] As one embodiment, a predicted in-sync indication is predicted if the predicted link quality for at least one of the at least first reference signals is better than a first predicted in-sync threshold for a predicted in-sync evaluation period.

[0653] As one embodiment, the first predicted in-sync threshold is Qin configured by rlmInSyncOutOfSyncThreshold.

[0654] As one embodiment, the first predicted in-sync threshold is not Qin configured by rlmInSyncOutOfSyncThreshold.

[0655] As one embodiment, the predicted evaluation occasion can not exist in practice for clarity.

[0656] As one embodiment, at each predicted evaluation occasion, there is either a predicted in-sync indication or a predicted out-of-sync indication.

[0657] As one embodiment, at a predicted evaluation occasion, there can be neither a predicted in-sync indication nor a predicted out-of-sync indication.

[0658] As one embodiment, the length of the predicted in-sync evaluation period is equal to the length of the predicted out-of-sync evaluation period.

[0659] As one embodiment, the length of the predicted in-sync evaluation period is not equal to the length of the predicted out-of-sync evaluation period.

[0660] As an embodiment, the length of the predicted synchronization evaluation period is the length of the synchronization evaluation period.

[0661] As an embodiment, the length of the predicted synchronization evaluation period is not the length of the synchronization evaluation period.

[0662] As an embodiment, the length of the predicted indication period is equal to the length of the indication period.

[0663] As an embodiment, the length of the synchronization evaluation period refers to TEvaluate_in_SSB of TS 38.133.

[0664] As an embodiment, the length of the out-of-synchronization evaluation period refers to TEvaluate_out_SSB of TS 38.133.

[0665] As an embodiment, the length of the synchronization evaluation period is equal to the length of the out-of-synchronization evaluation period.

[0666] As an embodiment, the length of the synchronization evaluation period is not equal to the length of the out-of-synchronization evaluation period.

[0667] As an embodiment, the above method can maintain the continuity of the predicted synchronization indication and / or the predicted out-of-synchronization indication based on the synchronization indication and / or the out-of-synchronization indication.

[0668] As an embodiment, the length of the predicted indication period is not equal to the length of the indication period.

[0669] As an embodiment, the above method makes the prediction more flexible independently of the synchronization indication and / or the out-of-synchronization indication.

[0670] As an embodiment, the present embodiment does not limit the position of the evaluation occasion in the predicted indication period.

[0671] As an embodiment, the predicted evaluation occasion is only for the sake of clarity to evaluate every other predicted indication period to determine whether there is a predicted out-of-synchronization indication or a predicted synchronization indication, and in actual application, no specific limitation is made.

[0672] As an embodiment, the predicted out-of-connection failure depends on the number of the predicted synchronization indications in a first time window.

[0673] As an embodiment, the absence of at least P2 consecutive predicted synchronization indications in the first time window triggers the predicted out-of-connection failure; P2 is a positive integer.

[0674] As an embodiment, the above method is simple to implement.

[0675] As one embodiment, the P2 is N311 minus R2; the R2 is a number of consecutive synchronization indications received by the time the connection failure is predicted.

[0676] As one embodiment, the P2 is less than N311.

[0677] As one embodiment, the method reduces the probability of predicting connection failure by using a P2 less than N311.

[0678] As one embodiment, the P2 is greater than N311.

[0679] As one embodiment, the method provides a fault tolerance rate of prediction by using a P2 greater than N311.

[0680] As one embodiment, the P2 is N321.

[0681] As one embodiment, the prediction of connection failure is triggered by a ratio of the predicted synchronization indications within the first time window not being higher than a threshold.

[0682] As one sub-embodiment of the above embodiment, the not higher than is less than.

[0683] As one sub-embodiment of the above embodiment, the not higher than is less than or equal to.

[0684] As one sub-embodiment of the above embodiment, the threshold is configurable.

[0685] As one sub-embodiment of the above embodiment, the threshold is default.

[0686] As one sub-embodiment of the above embodiment, the ratio of the predicted synchronization indications within the first time window refers to a ratio of a number of the predicted synchronization indications within the first time window to a number of prediction indication periods within the first time window.

[0687] As one sub-embodiment of the above embodiment, the ratio of the predicted synchronization indications within the first time window refers to a ratio of a number of the predicted synchronization indications within the first time window to a number of the predicted out-of-sync indications within the first time window.

[0688] As one embodiment, the prediction of connection failure depends on a number of the predicted out-of-sync indications within a first time window.

[0689] As an embodiment, the prediction of the connection failure is triggered when there are at least P1 consecutive predicted out-of-sync indications within the first time window; the P1 is a positive integer.

[0690] As an embodiment, the P1 is smaller than N310.

[0691] As an embodiment, the method with P1 smaller than N310 helps to predict the connection failure earlier.

[0692] As an embodiment, the P1 is larger than N310.

[0693] As an embodiment, the method with P1 larger than N310 avoids the impact of prediction error.

[0694] As an embodiment, the P1 is N310.

[0695] As an embodiment, the method is simple.

[0696] As an embodiment, the P1 is the difference between N310 and R1; the R1 is the number of consecutive out-of-sync indications received by the time of the prediction of the connection failure.

[0697] As an embodiment, the P1 is N320.

[0698] As an embodiment, the prediction of the connection failure is triggered when the proportion of the predicted out-of-sync indications within the first time window is not lower than a threshold.

[0699] As a sub-embodiment of the above embodiment, the not lower than is greater than.

[0700] As a sub-embodiment of the above embodiment, the not lower than is greater than or equal to.

[0701] As a sub-embodiment of the above embodiment, the threshold is configurable.

[0702] As a sub-embodiment of the above embodiment, the threshold is default.

[0703] As a sub-embodiment of the above embodiment, the proportion of the predicted out-of-sync indications within the first time window refers to the ratio of the number of the predicted out-of-sync indications within the first time window to the number of prediction indication periods within the first time window.

[0704] As a sub-embodiment of the above-mentioned embodiment, the ratio of the predicted out-of-sync indications in the first time window refers to a ratio of a number of the predicted out-of-sync indications in the first time window to a number of the predicted in-sync indications in the first time window.

[0705] As an embodiment, the predicting a connection failure depends on a number of the predicted in-sync indications and a number of the predicted out-of-sync indications in a first time window.

[0706] As an embodiment, the predicting a connection failure is triggered by a presence of at least P1 consecutive predicted out-of-sync indications in a second time window and a non-presence of at least P2 consecutive predicted in-sync indications in a first time window; the P1 is a positive integer; the P2 is a positive integer; a start time of the first time window depends on an end time of the second time window.

[0707] As an embodiment, the first time window is implemented by a timer.

[0708] As an embodiment, a length of the first time window is indicated by a network.

[0709] As an embodiment, the length of the first time window is determined by the terminal.

[0710] As an embodiment, the first time window includes at least the P1 predicted indication periods.

[0711] As an embodiment, the length of the first time window is not less than (the P1-1) predicted indication periods.

[0712] As an embodiment, the length of the first time window is not less than (the P1-1) predicted indication periods and not more than the P1 predicted indication periods.

[0713] As an embodiment, the first time window includes at least the P2 predicted indication periods.

[0714] As an embodiment, the length of the first time window is not less than (the P2-1) predicted indication periods.

[0715] As an embodiment, the length of the first time window is not less than (the P2-1) predicted indication periods and not more than the P2 predicted indication periods.

[0716] As an embodiment, the first time window includes at least (the P1+the P2) predicted indication periods.

[0717] As one embodiment, the first time window is not less than a remaining time of the first statistic; the first statistic is a timer.

[0718] As one embodiment, the first time window is a remaining time of the first statistic; the first statistic is a timer.

[0719] As one embodiment, the first time window is greater than a remaining time of the first statistic; the first statistic is a timer.

[0720] As one embodiment, the first time window comprises a remaining time of the first statistic and at least one predicted indication period after a time of expiration of the first statistic; the first statistic is a timer.

[0721] As one embodiment, a length of the first time sub-window is equal to a value of T310.

[0722] As one embodiment, the first time sub-window is a predicted time of T310 running.

[0723] As one embodiment, the P2 consecutive in-sync indications correspond to P2 consecutive in-sync evaluation periods.

[0724] As one embodiment, the P1 consecutive out-of-sync indications correspond to P1 consecutive out-of-sync evaluation periods.

[0725] Embodiment 11

[0726] Embodiment 11 illustrates a structure block diagram of a processing apparatus in a terminal according to one embodiment of the present application, as shown in FIG. 11. In FIG. 11, the processing apparatus in the terminal 1100 comprises a first receiver 1101, a first processor 1102.

[0727] The first receiver 1101 receives a first signaling; wherein the first signaling indicates a first threshold; if a first statistic reaches the first threshold, determines a connection failure.

[0728] In embodiment 11, if the first statistic reaches a second threshold, performs a connection failure prediction; the first statistic is a counter, or the first statistic is a timer; the first threshold and the second threshold are different.

[0729] As one embodiment, the first processor 1102 determines a connection failure if the first statistic reaches a first threshold.

[0730] As one embodiment, the first processor 1102 performs a connection failure prediction if the first statistic reaches a second threshold.

[0731] As one embodiment, the first processor 1102 sends a first notification when the first statistic reaches the second threshold; receives the first notification; wherein the first notification triggers the performing the connection failure prediction.

[0732] As one embodiment, the first processor 1102, in response to the first condition being met, suspends the connection failure prediction; wherein the first condition depends on at least one of a measurement or a prediction.

[0733] As one embodiment, the first processor 1102 sends a second notification when the first condition is met; receives the second notification; wherein the second notification triggers the suspending the connection failure prediction.

[0734] As one embodiment, the first processor 1102, in response to predicting the connection failure, operates a second statistic; the second statistic is a counter, or the second statistic is a timer.

[0735] As one embodiment, the first processor 1102, in response to predicting the connection failure, initiates a RRC connection reestablishment.

[0736] As one embodiment, the first processor 1102, in response to predicting the connection failure, operates a second statistic and initiates a RRC connection reestablishment depends on a time of the predicted connection failure; the second statistic is a counter, or the second statistic is a timer.

[0737] As one embodiment, the first receiver 1101 receives at least a first reference signal; wherein the connection failure prediction depends on the at least first reference signal.

[0738] As one embodiment, the predicting the connection failure depends on at least one of a number of predicted in-sync indications or a number of predicted out-of-sync indications within a first time window; the predicted in-sync indications or the predicted out-of-sync indications depend on the at least first reference signal.

[0739] As one embodiment, the first processor 1102 comprises a first transmitter.

[0740] As one embodiment, the first processor 1102 comprises the third module in FIG. 15; the third module performs the connection failure prediction.

[0741] As one embodiment, the first processor 1102 comprises the intelligent module 1501 in FIG. 14; the intelligent module 1501 performs the connection failure prediction.

[0742] As an embodiment, the first processor 1102 comprises the inference function 1806 in Figure 17; the inference function 1806 performs the connection failure prediction.

[0743] As an embodiment, the first receiver 1102 comprises at least one of the antenna 452 or the receiver 454 or the multi-antenna reception processor 458 or the reception processor 456 or the controller / processor 459 or the memory 460 or the data source 467 in Figure 4.

[0744] As an embodiment, the first receiver 1101 comprises at least the antenna 452 and the receiver 454 in Figure 4.

[0745] As an embodiment, the first transmitter comprises at least one of the antenna 452 or the transmitter 454 or the multi-antenna transmission processor 457 or the transmission processor 468 or the controller / processor 459 or the memory 460 or the data source 467 in Figure 4.

[0746] As an embodiment, the first transmitter comprises at least the antenna 452 and the transmitter 454 in Figure 4.

[0747] As an embodiment, the terminal comprises one or more processors and a memory; the memory is coupled to the one or more processors; the memory is configured to store computer program codes; the computer program codes comprise computer instructions; the one or more processors invoke the computer instructions to cause the terminal to perform the method in the present application which is used in the terminal; the one or more processors and the memory comprise the first receiver and the first processor.

[0748] Embodiment 12

[0749] Embodiment 12 illustrates a structural block diagram of a processing apparatus used in a base station according to an embodiment of the present application, as shown in Figure 12. In Figure 12, the processing apparatus 1200 in the base station comprises a second transmitter 1201.

[0750] The second transmitter 1201 transmits first signaling; wherein the first signaling indicates a first threshold value; if the first statistic reaches the first threshold value, the receiver of the first signaling determines a connection failure.

[0751] In Embodiment 12, if the first statistic reaches a second threshold value, the receiver of the first signaling performs a connection failure prediction; the first statistic is a counter, or the first statistic is a timer; the first threshold value and the second threshold value are different.

[0752] As one embodiment, the receiver of the first signaling sends a first notification when the first statistic reaches a second threshold; the receiver of the first signaling receives the first notification; wherein the first notification triggers the performing connection failure prediction.

[0753] As one embodiment, in response to the first condition being met, the receiver of the first signaling suspends the connection failure prediction; wherein the first condition depends on at least one of measurement or prediction.

[0754] As one embodiment, the receiver of the first signaling sends a second notification when the first condition is met; the receiver of the first signaling receives the second notification; wherein the second notification triggers the suspending the connection failure prediction.

[0755] As one embodiment, in response to predicting connection failure, the receiver of the first signaling operates a second statistic; the second statistic is a counter, or the second statistic is a timer.

[0756] As one embodiment, in response to predicting connection failure, the receiver of the first signaling initiates RRC connection reestablishment.

[0757] As one embodiment, the second transmitter 1201 transmits at least a first reference signal; wherein the connection failure prediction depends on the at least first reference signal.

[0758] As one embodiment, the first signaling indicates the second threshold.

[0759] As one embodiment, the first condition includes the first statistic reaching a third threshold; the first signaling indicates the third threshold.

[0760] As one embodiment, the processing device 1200 in the base station includes a second receiver 1202.

[0761] As one embodiment, the processing device 1200 in the base station includes the third module in FIG. 15.

[0762] As one embodiment, the processing device 1200 in the base station includes the RAN domain training function 1805 in FIG. 17.

[0763] As one embodiment, the processing device 1200 in the base station includes the inference function 1806 in FIG. 17.

[0764] As one embodiment, the processing device 1200 in the base station includes one inference function, 1704 or 1706, in FIG. 16.

[0765] As one embodiment, the second transmitter 1201 comprises at least one of the antenna 420 or the transmitter 418 or the multi-antenna transmit processor 471 or the transmit processor 416 or the controller / processor 475 or the memory 476 in FIG.4 of this application.

[0766] As one embodiment, the second transmitter 1201 comprises at least the antenna 420 and the transmitter 418 in FIG.4 of this application.

[0767] As one embodiment, the second receiver 1202 comprises at least one of the antenna 420 or the receiver 418 or the multi-antenna receive processor 472 or the receive processor 470 or the controller / processor 475 or the memory 476 in FIG.4 of this application.

[0768] As one embodiment, the second receiver 1202 comprises at least the antenna 420 and the receiver 418 in FIG.4 of this application.

[0769] As one embodiment, the base station comprises: one or more processors and a memory; the memory is coupled to the one or more processors; the memory is configured to store computer program codes; the computer program codes comprise computer instructions; the one or more processors invoke the computer instructions to cause the base station to perform the method in this application which is used in the base station; the one or more processors and the memory comprise the second transmitter 1201.

[0770] Embodiment 13

[0771] Embodiment 13 illustrates a flowchart of the first state according to one embodiment of this application, as shown in FIG.13. Embodiment 13 illustrates a schematic diagram of the intelligent model according to one embodiment of this application, as shown in FIG.13.

[0772] For the terminal U01, in step S1401, a connection failure is predicted; in step S1402, in response to the prediction of the connection failure, a first state is triggered; in step S1403, any condition in a first condition set is met; in step S1404, in response to the any condition in the first condition set being met, the triggered first state is cancelled.

[0773] As one embodiment, the first state is pending after being triggered until the first state is cancelled.

[0774] As one embodiment, the pending means: being triggered and not being cancelled.

[0775] As one embodiment, pending means: pending.

[0776] As one embodiment, pending means: being set.

[0777] As one embodiment, pending means: being stored.

[0778] As one embodiment, dashed box 14.1 is optional.

[0779] As one embodiment, dashed box 14.1 is not present.

[0780] As one sub-embodiment of the above embodiment, none of the first set of conditions is met.

[0781] As one sub-embodiment of the above embodiment, the first state is not cancelled.

[0782] As one embodiment, dashed box 14.1 is present.

[0783] As one sub-embodiment of the above embodiment, at least one of the first set of conditions is met.

[0784] As one sub-embodiment of the above embodiment, the first state is cancelled.

[0785] As one embodiment, one of the first set of conditions includes the predicted connection failure being predicted to be eliminated.

[0786] As one embodiment, one of the first set of conditions includes initiating a handover procedure.

[0787] As one embodiment, one of the first set of conditions includes entering an RRC_INACTIVE state.

[0788] As one embodiment, one of the first set of conditions includes entering an RRC_IDLE state.

[0789] As one embodiment, one of the first set of conditions includes the intelligent model being deactivated.

[0790] As one embodiment, one of the first set of conditions includes the intelligent model being deleted.

[0791] As one embodiment, one of the first set of conditions includes the intelligent model being reconfigured.

[0792] As one embodiment, one condition in the first set of conditions comprises at least one of the predicted connection failure being predicted to be eliminated or a handover procedure being initiated or an RRC connection re-establishment being initiated or an RRC_INACTIVE state being entered or an RRC_IDLE state being entered or the intelligent model being deactivated or the intelligent model being deleted or the intelligent model being reconfigured.

[0793] As one embodiment, the cancel refers to cancel.

[0794] As one embodiment, the cancel refers to Release.

[0795] As one embodiment, the cancel refers to Delete.

[0796] As one embodiment, the cancel refers to clear.

[0797] As one embodiment, the cancel refers to no longer store.

[0798] Embodiment 14

[0799] Embodiment 14 illustrates a schematic diagram of transmission of the first notification and the second notification according to one embodiment of the present application, as shown in FIG. 14. The terminal 1500 comprises an intelligent module 1501 and a legacy module 1502.

[0800] In embodiment 14, the legacy module 1502 of the terminal 1500 sends the first notification when the first statistic reaches the second threshold; the intelligent module 1501 of the terminal 1500 receives the first notification; wherein the first notification triggers the performing connection failure prediction.

[0801] In embodiment 14, the legacy module 1502 of the terminal 1500 sends the second notification when the first condition is satisfied; the intelligent module 1501 of the terminal 1500 receives the second notification; wherein the second notification triggers the aborting the connection failure prediction.

[0802] As one embodiment, the intelligent module 1501 of the terminal 1500 sends a third notification when a connection failure is predicted; the legacy module 1502 of the terminal 1500 receives the third notification; wherein the third notification indicates the predicted connection failure.

[0803] As one embodiment, the intelligent module 1501 of the terminal 1500 sends a fourth notification; the legacy module 1502 of the terminal 1500 receives the fourth notification; wherein the fourth notification indicates the predicted connection failure is eliminated.

[0804] As a sub-example of the above example, the method avoids triggering unreasonable UE behavior by updating the prediction information.

[0805] As a sub-example of the above example, the method facilitates UE decision.

[0806] As a sub-example of the above example, the predicted connection failure elimination means that a connection failure is not predicted to occur at the predicted time of the connection failure.

[0807] As an example, in response to the first notification being received, an indication is sent to a lower layer; the indication is received at an RRC sublayer.

[0808] As an example, in response to the first notification being received, an indication is sent to an upper layer; the indication is received at an RRC sublayer.

[0809] As an example, the indication indicates the first notification.

[0810] As an example, the indication includes the first notification.

[0811] As an example, the legality module is logical.

[0812] As an example, the legality module is physical.

[0813] As an example, the legality module determines a connection failure if the first statistic reaches a first threshold.

[0814] As an example, the legality module receives at least a first reference signal.

[0815] As an example, the legality module operates the first statistic in response to predicting a connection failure.

[0816] As an example, the legality module initiates RRC connection reestablishment in response to predicting a connection failure.

[0817] As an example, the legality module is a protocol entity.

[0818] As an example, the legality module is an RRC protocol entity.

[0819] As an example, the legality module is at an RRC sublayer.

[0820] As an example, the legality module is at an upper layer of an RRC sublayer.

[0821] As an embodiment, the lawful module is at a lower layer of the RRC sublayer.

[0822] As an embodiment, the lawful module supports 3GPP Release 17.

[0823] As an embodiment, the lawful module supports 3GPP Release 18.

[0824] As an embodiment, the lawful module does not have any one of a training function or an inference function.

[0825] As an embodiment, the lawful module is not an intelligent module.

[0826] As an embodiment, the intelligent module is a hardware.

[0827] As an embodiment, the intelligent module is a software.

[0828] As an embodiment, the intelligent module is a program.

[0829] As an embodiment, the intelligent module is a function.

[0830] As an embodiment, the intelligent module is a protocol entity.

[0831] As an embodiment, the intelligent module is an AI entity.

[0832] As an embodiment, the intelligent module is an ML entity.

[0833] As an embodiment, the intelligent module is an AI / ML entity.

[0834] As an embodiment, the intelligent module is logical.

[0835] As an embodiment, the intelligent module is physical.

[0836] As an embodiment, the intelligent module performs connection failure prediction.

[0837] As an embodiment, the intelligent module processes the at least one intelligent model.

[0838] As an embodiment, the intelligent module includes at least one of the second module or the third module of the intelligent model of embodiment 15.

[0839] As an embodiment, an interface between the lawful module and the intelligent module is defined by a 3GPP protocol.

[0840] As an embodiment, the interface between the lawful module and the intelligent module is implemented based on UE.

[0841] As an embodiment, the interface between the lawful module and the intelligent module is logical.

[0842] As an embodiment, the interface between the lawful module and the intelligent module is physical.

[0843] Embodiment 15

[0844] Embodiment 15 illustrates a schematic diagram of an intelligent model according to an embodiment of the present application, as shown in FIG. 15. FIG. 15 includes a first module, a second module, a third module, a fourth module and a fifth module.

[0845] In embodiment 15, in the intelligent model shown in FIG. 15, the first module sends a first data set to the second module, the first module sends a second data set to the third module, the first module sends a third data set to the fifth module, the fifth module sends a first parameter group to the second module, the fifth module sends a second parameter group to the third module, the fifth module sends a third parameter group to the fourth module, the second module sends a fourth parameter group to the fourth module, and the fourth module sends a fifth parameter group to the third module.

[0846] As an embodiment, the first module, the second module, the third module, the fourth module and the fifth module in an intelligent model all belong to the terminal.

[0847] The above method avoids air interface signaling interaction and shortens transmission delay.

[0848] As an embodiment, any one of the first module, the second module, the third module, the fourth module and the fifth module in an intelligent model does not belong to the terminal.

[0849] The above method reduces the hardware complexity of the terminal.

[0850] As an embodiment, 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 terminal; and at least one of the first module, the second module, the third module, the fourth module and the fifth module belongs to the network node.

[0851] The above method balances the hardware complexity of the terminal and the transmission delay.

[0852] As one example, the first module is for data collection.

[0853] As one example, the first module is responsible for data collection.

[0854] As one example, the first module has a data collection function.

[0855] As one example, the second module has a training function.

[0856] As one example, the training function is for model training.

[0857] As one example, the training function is responsible for model training.

[0858] As one example, the training function has a model training function.

[0859] As one example, the training function performs model training.

[0860] As one example, the second module performs validation.

[0861] As one example, the second module performs testing.

[0862] As one example, the second module generates model performance metrics.

[0863] As one example, the second module is responsible for data preparation.

[0864] As one example, the data preparation includes at least one of data pre-processing or cleaning or formatting or transformation.

[0865] As one example, the third module has an inference function.

[0866] As one example, the inference function is for inference.

[0867] As one example, the inference function is responsible for inference.

[0868] As one example, the fourth module is for model storage.

[0869] As an example, the fourth module has a model storage function.

[0870] As an example, the fourth module is responsible for storing trained models.

[0871] As an example, the fourth module is responsible for storing trained models that can be used to perform inference processing.

[0872] As an example, the fifth module is used for management.

[0873] As an example, the fifth module is responsible for management.

[0874] As an example, the fifth module has a management function.

[0875] As an example, the fifth module manages intelligent models.

[0876] As an example, the first data set is training data.

[0877] As an example, the first data set is the input of the second module.

[0878] As an example, the second data set is inference data.

[0879] As an example, the second data set is the input of the third module.

[0880] As an example, the third data set is monitoring data.

[0881] As an example, the third data set is the input of the fifth module.

[0882] As an example, the first type of parameter set includes monitoring output.

[0883] As an example, the second type of parameter set includes management instructions.

[0884] As an example, the second type of parameter set is used for fine-tuning operations of inference functions.

[0885] As an example, the second type of parameter set includes the identification of a model.

[0886] As an example, the second type of parameter set is used to select a model.

[0887] As one embodiment, the second type of parameter set is used for a switching model.

[0888] As one embodiment, the second type of parameter set is used for an activation / deactivation model.

[0889] As one embodiment, the second type of parameter set is used for a fallback intelligent model.

[0890] As one embodiment, the third type of parameter set includes a model transfer request.

[0891] As one embodiment, the third type of parameter set includes a model delivery request.

[0892] As one embodiment, the fourth type of parameter set includes a trained model.

[0893] As one embodiment, the fourth type of parameter set includes an updated model.

[0894] As one embodiment, the fourth type of parameter set indicates an identity of a model.

[0895] As one embodiment, the fifth type of parameter set includes a model transfer.

[0896] As one embodiment, the fifth type of parameter set includes a model delivery.

[0897] As one embodiment, the fifth type of parameter set indicates an identity of a model.

[0898] As one embodiment, the first type of output is absent.

[0899] As one embodiment, the first type of output is present.

[0900] As one embodiment, the second module sends the first type of output to the fifth module.

[0901] As one embodiment, the first type of output includes a monitoring output.

[0902] As one embodiment, the second type of output is absent.

[0903] As one embodiment, the second type of output is present.

[0904] As an embodiment, the third module sends the second type of output to the fifth module.

[0905] As an embodiment, the second type of output comprises Inference Output.

[0906] As an embodiment, the second type of output is used by the fifth module to monitor the performance of the AI / ML model.

[0907] As an embodiment, the second type of output indicates the result of the execution of the connection failure prediction.

[0908] As an embodiment, the second type of output indicates the predicted connection failure.

[0909] As an embodiment, the second type of output comprises relevant information of the predicted connection failure.

[0910] As an embodiment, the second type of output comprises the third notification.

[0911] As an embodiment, the second type of output comprises the fourth notification.

[0912] As an embodiment, the first data set in the intelligent model is configured by the network.

[0913] As an embodiment, the first data set in the intelligent model is determined by the terminal.

[0914] As an embodiment, the first data set in the intelligent model comprises storage data of the terminal; the storage data can be from the network, can also be from the log of the terminal, and can also be from other RAN nodes.

[0915] As an embodiment, the first data set in the intelligent model comprises measurement information of the terminal; the measurement information can be the moving state of the terminal, such as the moving speed, or the number of switched cells in a given time interval, etc.; the measurement information can also be the measurement result for the reference signal, such as the cell-level measurement result, or the beam-level measurement result, or the time-domain measurement result, or the frequency-domain measurement result, or the spatial-domain measurement result, or the combination thereof, etc.

[0916] As an embodiment, the first data set in the intelligent model comprises the measurement result for the at least first reference signal.

[0917] As an embodiment, the second data set in the intelligent model is configured by the network.

[0918] As an embodiment, the second data set in the intelligent model is determined by the terminal.

[0919] As an embodiment, the second data set in the intelligent model comprises storage data of the terminal; the storage data can be from the network, can also be from the log of the terminal, and can also be from other RAN nodes.

[0920] As an embodiment, the second data set in the intelligent model comprises measurement information of the terminal; the measurement information can be the moving state of the terminal, for example, the moving speed, or the number of switched cells in a given time interval, etc.; the measurement information can also be the measurement result for the reference signal, for example, the cell-level measurement result, or the beam-level measurement result, or the time-domain measurement result, or the frequency-domain measurement result, or the spatial-domain measurement result, or the combination thereof, etc.

[0921] As an embodiment, the second data set in the intelligent model comprises the measurement result for the at least first reference signal.

[0922] As an embodiment, the third data set in the intelligent model is configured by the network.

[0923] As an embodiment, the third data set in the intelligent model is determined by the terminal.

[0924] As an embodiment, the third data set in the intelligent model comprises storage data of the terminal; the storage data can be from the network, can also be from the log of the terminal, and can also be from other RAN nodes.

[0925] As an embodiment, the third data set in the intelligent model comprises measurement information of the terminal; the measurement information can be the moving state of the terminal, for example, the moving speed, or the number of switched cells in a given time interval, etc.; the measurement information can also be the measurement result for the reference signal, for example, the cell-level measurement result, or the beam-level measurement result, or the time-domain measurement result, or the frequency-domain measurement result, or the spatial-domain measurement result, or the combination thereof, etc.

[0926] As an embodiment, the third data set in the intelligent model comprises the measurement result for the at least first reference signal.

[0927] As an embodiment, the connection failure prediction is performed through the intelligent model.

[0928] As an embodiment, the embodiment 15 is only for illustrating that the present application can be applied to intelligent models, the embodiment does not limit that the present application is applied to non-intelligent operations, and the embodiment does not limit that the present application is applied to other types of intelligent models to achieve the effects equivalent to the intelligent models shown in the figure 15.

[0929] Embodiment 16

[0930] The embodiment 16 shows a schematic diagram of intelligent function deployment of a RAN (Radio Access Network, wireless access network) domain according to an embodiment of the present application; as shown in the figure 16. The gNB in the embodiment 16 can be replaced by a network device such as an eNB, or a 6G base station, etc.

[0931] The intelligent functions of the RAN domain include training (also referred to as ML training, or AI training, or AI / ML training) functions, testing (also referred to as ML testing, or AI testing, or AI / ML testing) functions, inference (also referred to as ML inference, or AI inference, or AI / ML inference) functions, etc. The training functions, the testing functions, and the inference functions can be independently deployed or co-located deployed. The deployment of the intelligent functions can be implemented by software, such as downloading and / or running of executable files; or can be implemented by a combination of software and hardware, such as acceleration of specific computing units by hardware to improve operation speed or save power consumption.

[0932] For the training functions, a cross-domain management system or a domain-specific management system can be deployed; the domain-specific management system is used to manage the RAN domain or the CN (Core Network, core network) domain. For example, the training function for MDA (Management Data Analytics, management data analytics) can be deployed in the MDAF (MDA function); the training for network data analysis can be deployed in the NWDAF (Network Data Analytics Function, network data function), that is, the training function is the MTLF (Model Training logical function, model training logical function).

[0933] For the inference function, it can also be deployed in the cross-domain management system or the domain-specific management system; for example, the inference function is the MDAF, or the inference function is the AnLF (Analytics logical function) located in the NWDAF.

[0934] Similarly, the test function can also be deployed in the cross-domain management system or the domain-specific management system.

[0935] In embodiment 16, the training function 1702 of the RAN domain is located in the management function 1703 of the RAN domain; and the inference function is located in the base station, i.e., the inference function 1704 is located in the gNB 1705, the inference function 1706 is located in the gNB 1707, and so on.

[0936] In FIG. 16, the management of the inference functions of multiple base stations is completed by the RAN domain management function 1703, i.e., data interaction is performed with the RAN domain MnS (Management Service) consumer / cross-domain management 1701 (as shown by the dashed arrow 1708 in FIG. 16).

[0937] Optionally, the management of the inference function can also be completed by the base station itself, i.e., each base station can independently perform data interaction with the RAN domain MnS consumer / cross-domain management 1701.

[0938] It should be noted that embodiment 16 is only one non-limiting implementation; optionally, the training function of the RAN domain can also be deployed in the base station; or optionally, part of the base stations deploy the inference function and the training function of the RAN domain, and part of the base stations only deploy the inference function.

[0939] As an example, one gNB (or base station) in embodiment 16 is the base station of the present application.

[0940] As an example, one inference function in FIG. 16 performs connection failure prediction.

[0941] Embodiment 17

[0942] Embodiment 17 illustrates a schematic diagram of UE intelligent function deployment according to one embodiment of the present application; as shown in FIG. 17. The training function 1805 of the RAN domain in FIG. 17 is optional.

[0943] The UE intelligent function 1804 is deployed in the terminal of the present application, and the UE intelligent function 1804 includes the inference function 1806; the inference function 1806 uses an intelligent model (also referred to as an AI model, or an ML model, or an AI / ML model) for inference; one intelligent model usually needs to be trained before being used for AI / ML inference.

[0944] As an embodiment, the UE intelligence function 1804 includes a RAN domain training function 1805 that runs training data through an intelligent model, derives a related loss, and adjusts parameters of the intelligent model based on the computed loss; the training includes at least one of ML initial training, ML re-training, and reinforcement learning.

[0945] The above embodiment can reduce the complexity of the base station, or save the air interface resources caused by reporting training data; however, the above embodiment puts higher requirements on the processing capability of the UE side.

[0946] Optionally, the UE intelligence function 1804 further includes a CN domain training function (not included in FIG. 18).

[0947] Optionally, the UE intelligence function 1804 further includes an intelligent deployment function (not included in FIG. 18) for loading intelligent models and data.

[0948] As an embodiment, the terminal indicates whether to support the training function (RAN domain or CN domain) through capability reporting, and the capability reporting is RRC signaling or NAS (Non-Access Stratum) signaling.

[0949] As an embodiment, the intelligent model and related metadata are loaded by the terminal from a network device or a remote server.

[0950] Optionally, the UE intelligence 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 the double-headed arrow 1507).

[0951] Optionally, the UE intelligence function 1804 is an MnS consumer that loads data from the CN domain MnF 1801, and / or the RAN domain MnF 1802, and / or the cross-domain management system 1803 for AI / ML related management, such as management data request, intelligent model activation, and / or intelligent model training, etc. (as shown by the double-headed arrow 1807).

[0952] As an embodiment, the intelligent model is based on a neural network.

[0953] As an embodiment, the intelligent model is based on a CNN (Conventional Neural Networks).

[0954] As an embodiment, the intelligent model is based on a Transformer architecture.

[0955] As an embodiment, the terminal in the present application comprises the inference function 1806 in FIG. 17.

[0956] As an embodiment, the first processor in the present application comprises the inference function 1806 in FIG. 17.

[0957] As an embodiment, the UE 201 in FIG. 2 comprises the inference function 1806 in FIG. 17.

[0958] As an embodiment, the first communication device 450 in FIG. 4 comprises the inference function 1806 in FIG. 17.

[0959] As an embodiment, the first processor 1101 in FIG. 11 comprises the inference function 1806 in FIG. 17.

[0960] As an embodiment, the intelligent module 1501 in FIG. 14 comprises the inference function 1806 in FIG. 17.

[0961] As an embodiment, the third module in FIG. 15 comprises the inference function 1806 in FIG. 17.

[0962] As an embodiment, the inference function 1806 in FIG. 17 performs connection failure prediction.

[0963] Embodiment 18

[0964] Embodiment 18 illustrates a flowchart based on artificial intelligence or machine learning according to an embodiment of the present application; as shown in FIG. 18. FIG. 18 comprises a third operation, a fourth operation, a fifth operation, a sixth operation and a seventh operation. In embodiment 18, the third operation and the fourth operation 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. In FIG. 18, the line with an arrow represents the order of the flow.

[0965] As one embodiment, the third operation comprises AI / ML training, the fourth operation comprises AI / ML testing, the fifth operation comprises AI / ML emulation, the sixth operation comprises AI / ML entity loading, and the seventh operation comprises AI / ML inference.

[0966] As one embodiment, the first phase comprises a training phase, the second phase comprises an emulation phase, the third phase comprises a deployment phase, and the fourth phase comprises an inference phase.

[0967] As one embodiment, the first phase comprises AI / ML model training.

[0968] As one embodiment, the first phase comprises AI / ML model training and AI / ML testing.

[0969] As one embodiment, the AI / ML model training comprises initial training and re-training of one or a set of AI / ML entities.

[0970] As one embodiment, the AI / ML model training relies on training data.

[0971] As one embodiment, the AI / ML model training comprises AI / ML entity validation.

[0972] As one embodiment, the AI / ML entity validation is used to evaluate the performance of the AI / ML entity.

[0973] As one embodiment, the AI / ML entity validation relies on validation data.

[0974] As one embodiment, if the result of AI / ML entity validation does not meet expectations, the AI / ML model will be re-trained.

[0975] As one embodiment, the AI / ML testing comprises testing the validated AI / ML entity to evaluate the performance of the trained AI / ML model.

[0976] As one embodiment, if the result of AI / ML testing meets expectations, the AI / ML entity proceeds to the next phase; otherwise, the AI / ML model will be re-trained.

[0977] As one embodiment, the AI / ML testing relies on test data.

[0978] As one embodiment, the second stage includes AI / ML simulation, which simulates the inference of the AI / ML entity in a simulation environment.

[0979] As one embodiment, the AI / ML simulation estimates the performance of the inference of the AI / ML entity in a simulation environment before the AI / ML entity is used.

[0980] As one embodiment, the second stage is optional.

[0981] As one embodiment, the third stage includes AI / ML entity loading, which is to obtain the trained AI / ML entity to obtain the desired AI / ML inference function.

[0982] As one embodiment, the third stage is optional.

[0983] As one embodiment, the third stage is no longer needed when the training function and the inference function are co-located.

[0984] As one embodiment, the fourth stage includes AI / ML inference.

[0985] Those skilled in the art can understand that all or part of the steps in the foregoing method can be instructed by programs to the relevant hardware to complete, and the programs can be stored in a computer readable storage medium, such as a read-only memory, a hard disk, an optical disk or the like. Alternatively, all or part of the steps of the foregoing embodiments can also be implemented using one or more integrated circuits. Correspondingly, each module unit in the foregoing embodiments can be implemented in the form of hardware or in the form of a software function module, and the present application is not limited to any specific form of combination of software and hardware. The user equipment, terminal and UE in the present application include but are not limited to unmanned aerial vehicles, communication modules on unmanned aerial vehicles, remote control aircraft, aircraft, small aircraft, mobile phones, tablet computers, notebooks, vehicle-mounted communication devices, wireless sensors, network cards, Internet of Things terminals, RFID terminals, NB-IOT terminals, MTC (Machine Type Communication) terminals, eMTC (enhanced MTC) terminals, data cards, network cards, vehicle-mounted communication devices, low-cost mobile phones, low-cost tablet computers and other wireless communication devices. The base station or system device in the present application includes but is not limited to macro cellular base stations, micro cellular base stations, home base stations, relay base stations, gNB (NR NodeB) NR NodeB, TRP (Transmitter Receiver Point) and other wireless communication devices.

[0986] The above is only a preferred embodiment of the present application, and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for connection failure prediction, the method comprising: receiving first signaling, wherein the first signaling indicates a first threshold, and determining a connection failure if a first statistic reaches the first threshold; wherein the connection failure prediction is performed if the first statistic reaches a second threshold, and the first statistic is a counter or a timer, and the first threshold and the second threshold are different. 2.The method of claim 1, wherein the method comprises: sending a first notification when the first statistic reaches the second threshold, and receiving the first notification; wherein the first notification triggers the connection failure prediction. 3.The method of claim 1 or 2, wherein the method comprises: suspending the connection failure prediction in response to a first condition being met; wherein the first condition depends on at least one of a measurement or a prediction. 4.The method of claim 3, wherein the method comprises: sending a second notification when the first condition is met, and receiving the second notification; wherein the second notification triggers the suspension of the connection failure prediction. 5.The method of any one of claims 1-4, wherein the method comprises: operating a second statistic in response to predicting a connection failure, and the second statistic is a counter or a timer. 6.The method of any one of claims 1-4, wherein the method comprises: initiating a RRC connection re-establishment in response to predicting a connection failure. 7.The method of any one of claims 1-4, wherein the method comprises: operating a second statistic or initiating a RRC connection re-establishment in response to predicting a connection failure depends on a time of occurrence of the predicted connection failure, and the second statistic is a counter or a timer. 8.The method of any one of claims 1-7, wherein the method comprises: receiving at least a first reference signal; wherein the connection failure prediction depends on the at least first reference signal. 9.The method of claim 8, wherein the predicting a connection failure depends on at least one of a number of predicted in-sync indications or a number of predicted out-of-sync indications within a first time window, and the predicted in-sync indications or the predicted out-of-sync indications depend on the at least first reference signal. 10.An apparatus for connection failure prediction, the apparatus comprising: one or more processors and a memory; the memory coupled to the one or more processors, the memory configured to store computer program code comprising computer instructions, the one or more processors configured to invoke the computer instructions to cause the apparatus to perform the method of any one of claims 1-9. 11.A method for connection failure prediction, the method comprising: ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ sending a first signaling; wherein the first signaling indicates a first threshold; and wherein a receiver of the first signaling determines a connection failure if a first statistic reaches the first threshold; wherein the receiver of the first signaling performs a connection failure prediction if the first statistic reaches a second threshold; and wherein the first statistic is a counter or the first statistic is a timer; and wherein the first threshold and the second threshold are different.

12. The method of claim 11, wherein, the receiver of the first signaling sends a first notification when the first statistic reaches the second threshold; and wherein the receiver of the first signaling receives the first notification; and wherein the first notification triggers the performing of the connection failure prediction.

13. The method of claim 11 or 12, wherein, the receiver of the first signaling aborts the connection failure prediction in response to a first condition being met; and wherein the first condition depends on at least one of a measurement or a prediction.

14. The method of claim 13, wherein, the receiver of the first signaling sends a second notification when the first condition is met; and wherein the receiver of the first signaling receives the second notification; and wherein the second notification triggers the aborting of the connection failure prediction.

15. The method of any one of claims 11-14, wherein, the receiver of the first signaling operates a second statistic in response to predicting a connection failure; and wherein the second statistic is a counter or the second statistic is a timer.

16. The method of any one of claims 11-14, wherein the method is used for wireless communication, and wherein, the receiver of the first signaling initiates a RRC connection reestablishment in response to predicting a connection failure.

17. The method of any one of claims 11-16, wherein, at least a first reference signal is sent; and wherein the connection failure prediction depends on the at least first reference signal.

18. The method of any one of claims 11-17, wherein, the first signaling indicates the second threshold.

19. The method of any one of claims 11-18, wherein, the first condition comprises the first statistic reaching a third threshold; and wherein the first signaling indicates the third threshold.

20. An apparatus for connection failure prediction, the apparatus comprising: one or more processors and memory; and wherein the memory is coupled to the one or more processors, and the memory is configured to store computer program code comprising computer instructions, and the one or more processors are configured to invoke the computer instructions to cause the apparatus to perform the method of any one of claims 11-19. ​ ​ ​

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