Method and apparatus for use in communication node for wireless communication

Abstract

The present application discloses a method and apparatus for use in a communication node for wireless communication. A terminal receives a first RRC message, wherein the first RRC message configures at least one reference signal resource and a first event, the first event depends on the measurement for the at least one reference signal resource, the first event depends on a first threshold, and the first threshold changes with time. The solution provided in the present application facilitates triggering of a dynamic threshold, thereby reducing frequent high-layer signaling interactions. The design of a dynamic event threshold is conducive to selecting appropriate UE behaviors on the basis of different channel environments, thereby balancing robustness and network optimization efficiency.

Description

Method and apparatus in a communication node used for wireless communication

[0001] This application claims priority to the Chinese Patent Application No. 202411296553.6, filed on September 14, 2024, and entitled “Method and apparatus in a communication node used for wireless communication”, 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 of threshold. BACKGROUND

[0003] With the continuous development of wireless communication, the requirements for mobility, transmission delay and system capacity are becoming higher and higher. At the 94e meeting of 3GPP RAN (Radio Access Network), it was decided to study L1 / L2 triggered mobility (LTM) in the “Further NR mobility enhancements” research project (Work Item, WI) in the NR (New Radio) mobility enhancement.

[0004] To enhance the measurement reporting process of LTM, 3GPP will introduce event-triggered L1 measurement reporting in Rel-19, including configuration methods, event definitions, filtering methods, etc.

[0005] With the continuous development of wireless communication, the demand is gradually diversified. Therefore, in the future evolution, 3GPP will further enhance some key technologies, for example, applying AI (Artificial Intelligence) or ML (Machine Learning) to mobility management, and reporting measurement and prediction information in advance to help the network optimize mobility. SUMMARY

[0006] The inventors found that the existing threshold of the event relying on the measurement of the reference signal resource configured by the RRC signaling is static or semi-static, and the existing configuration method of the threshold is not suitable for some specific scenarios, for example, in the case of dynamic changes in channel state, if the threshold cannot be adjusted in time, it will lead to early or late switching or even switching failure, therefore, it is necessary to enhance the determination of the threshold of the event relying on the measurement of the reference signal resource.

[0007] To solve the above problems, the present application provides a solution. In the description of the above problems, the threshold of the event dependent on the measurement of the reference signal resource is taken as an example, and the present application is also applicable to the threshold of the event not dependent on the measurement of the reference signal resource, and similar threshold of the event dependent on the measurement of the reference signal resource is obtained.

[0008] As an embodiment, the explanation of the terminology in the present application refers to the definition of the specification agreement TS36 series of 3GPP.

[0009] As an embodiment, the explanation of the terminology in the present application refers to the definition of the specification agreement TS38 series of 3GPP.

[0010] As an embodiment, the explanation of the terminology in the present application refers to the definition of the specification agreement TS37 series of 3GPP.

[0011] It should be noted that the embodiments in any node of the present application and the features in the embodiments can be applied to any other node without conflict. The embodiments of the present application and the features in the embodiments can be arbitrarily combined with each other without conflict.

[0012] The present application discloses a method used in a terminal, characterized in that, comprising:

[0013] receiving a first RRC message, the first RRC message configuring at least one reference signal resource and a first event;

[0014] The first event is dependent on the measurement of the at least one reference signal resource, and the first event is dependent on a first threshold, and the first threshold changes over time.

[0015] As an embodiment, the problem to be solved by the present application includes: how to enhance the existing event triggering mechanism.

[0016] As an embodiment, the problem to be solved by the present application includes: how to enhance the existing event triggered measurement reporting process.

[0017] As an embodiment, the problem to be solved by the present application includes: how to enhance the existing event triggered prediction reporting process.

[0018] As an embodiment, the problem to be solved by the present application includes: how to design the event triggering mechanism based on dynamic threshold.

[0019] As an embodiment, the characteristics of the above method include: the first threshold changes over time.

[0020] As an embodiment, benefits of the above method include facilitating triggering events for dynamic threshold, facilitating reducing frequent high layer signaling interaction.

[0021] As an embodiment, benefits of the above method include facilitating adapting protocol flexibly to different measurement results, facilitating balancing network interaction delay and reliability.

[0022] As an embodiment, benefits of the above method include that the design of dynamic event threshold facilitates selecting appropriate UE behavior according to different channel environment, balancing robustness and network optimization efficiency.

[0023] As an embodiment, benefits of the above method include that the above method considers the design of dynamic event threshold in multiple cases, facilitating improving signaling interaction efficiency in different cases.

[0024] As an embodiment, benefits of the above method include that the above method facilitates implementing network optimizing subsequent mobility decision according to measurement report.

[0025] According to an aspect of the present application, the first event is dependent on the measurement for the at least one reference signal resource satisfying the first threshold.

[0026] As an embodiment, benefits of the above method include facilitating reducing modification to existing protocol.

[0027] As an embodiment, benefits of the above method include facilitating reducing signaling interaction.

[0028] According to an aspect of the present application, the first event comprises predicting a second event; the predicting the second event is dependent on the measurement for the at least one reference signal resource.

[0029] As an embodiment, benefits of the above method include facilitating implementing dynamic adjustment of threshold for event prediction.

[0030] As an embodiment, benefits of the above method include facilitating optimizing sending timing of event prediction report.

[0031] As an embodiment, benefits of the above method include facilitating optimizing sending timing of event prediction report.

[0032] As an embodiment, benefits of the above method include facilitating reducing signaling interaction.

[0033] According to an aspect of the present application, the first threshold varies with time comprises that the first threshold is dependent on a length of a first time window; the predicting the second event comprises predicting the second event occurring within the first time window.

[0034] As an embodiment, benefits of the above method include facilitating reducing modification to existing protocol.

[0035] As an embodiment, the above method has the benefit of facilitating dynamic threshold for predicted event.

[0036] According to an aspect of the present application, a method is provided, including:

[0037] The predicting the second event includes predicting a metric value of the second event is greater than or not less than the first threshold.

[0038] As an embodiment, the above method has the benefit of facilitating dynamic confidence or probability threshold for event prediction.

[0039] As an embodiment, the above method has the benefit of facilitating load balancing of the network.

[0040] As an embodiment, the above method has the benefit of facilitating reduction of signaling interaction.

[0041] According to an aspect of the present application, a method is provided, including:

[0042] The first threshold changing over time includes that the first threshold depends on a first time length and a target threshold, and the first threshold depending on the first time length and the target threshold includes:

[0043] If the first time length is less than the target threshold, the first threshold adopts a first value;

[0044] If the first time length is greater than the target threshold, the first threshold adopts a second value;

[0045] The first time length depends on a predicted time of the second event, and the first value and the second value are different.

[0046] As an embodiment, the above method has the benefit of facilitating dynamic configuration of triggering threshold for predicted event.

[0047] As an embodiment, the above method has the benefit of facilitating reduction of complexity of protocol implementation.

[0048] As an embodiment, the above method has the benefit of facilitating reduction of modification to existing protocol.

[0049] As an embodiment, the above method has the benefit of facilitating reduction of signaling interaction.

[0050] According to an aspect of the present application, a method is provided, including:

[0051] In response to the first event being triggered, performing a first operation, and wherein

[0052] The first operation comprises sending a first report.

[0053] Or,

[0054] The first operation comprises updating the RRC connection by itself.

[0055] As one embodiment, the benefits of the above method include facilitating triggering of a measurement report.

[0056] As one embodiment, the benefits of the above method include facilitating triggering of a prediction report.

[0057] As one embodiment, the benefits of the above method include facilitating triggering of conditional mobility.

[0058] As one embodiment, the benefits of the above method include facilitating reduction of signaling interactions.

[0059] The present application discloses a method used in a base station, characterized in that comprising:

[0060] sending a first RRC message, the first RRC message configuring at least one reference signal resource and a first event;

[0061] The first event depends on the measurement of the at least one reference signal resource, and the first event depends on a first threshold value, which changes over time.

[0062] According to one aspect of the present application, the first event depends on the measurement of the at least one reference signal resource satisfying the first threshold value.

[0063] According to one aspect of the present application, the first event includes predicting a second event; the predicted second event depends on the measurement of the at least one reference signal resource.

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

[0065] The first threshold value changing over time means that the first threshold value depends on the length of a first time window; the predicted second event includes predicting that the second event occurs within the first time window.

[0066] According to one aspect of the present application, the predicted second event includes predicting that the metric value of the second event occurring is greater than or not less than the first threshold value.

[0067] According to one aspect of the present application, characterized in that,

[0068] The first threshold value changing over time means that the first threshold value depends on a first time length and a target threshold value; wherein the first threshold value depending on the first time length and the target threshold value comprises:

[0069] If the first time length is less than the target threshold value, the first threshold value adopts a first value;

[0070] If the first time length is greater than the target threshold value, the first threshold value adopts a second value;

[0071] Wherein the first time length depends on a predicted time of the second event; the first value and the second value are different.

[0072] According to an aspect of the present application, it is characterized in that,

[0073] In response to the first event being triggered, a first operation is performed; wherein,

[0074] The first operation comprises receiving a first report;

[0075] Or,

[0076] The first operation comprises the receiver of the first RRC message updating the RRC connection by itself.

[0077] The present application discloses a terminal, characterized in that, comprising:

[0078] The terminal comprises one or more processors and a memory;

[0079] The memory is coupled with the one or more processors, and the memory is configured to store computer program code, the computer program code comprising computer instructions, and the one or more processors are configured to invoke the computer instructions to cause the terminal to perform the method for the terminal.

[0080] The present application discloses a base station, characterized in that, comprising:

[0081] The base station comprises one or more processors and a memory;

[0082] The memory is coupled with the one or more processors, and the memory is configured to store computer program code, the computer program code comprising computer instructions, and the one or more processors are configured to invoke the computer instructions to cause the base station to perform the method for the base station.

[0083] As an embodiment, compared with the conventional scheme, the present application has the following advantages:

[0084] The triggering event is conducive to achieving a dynamic threshold, and is conducive to reducing frequent high-layer signaling interaction processes.

[0085] The protocol is conducive to being flexibly adapted to different measurement results, and is conducive to balancing network interaction delay and reliability.

[0086] The design of the dynamic event threshold is conducive to selecting a suitable UE behavior according to different channel environments, so as to balance robustness and network optimization efficiency.

[0087] The above method considers the design of the dynamic event threshold in multiple cases, and is conducive to improving signaling interaction efficiency in different cases.

[0088] The above method is conducive to enabling the network to optimize subsequent mobility decisions according to measurement reports.

[0089] The above method is conducive to reducing changes to existing protocols.

[0090] The above method is conducive to reducing signaling interaction.

[0091] The above method is conducive to achieving dynamic adjustment of the threshold for event prediction.

[0092] The above method is conducive to dynamic adjustment of a confidence or probability threshold for event prediction.

[0093] The above method is conducive to load balancing of the network.

[0094] The above method is conducive to reducing the complexity of protocol implementation.

[0095] The above method is conducive to triggering conditional mobility. BRIEF DESCRIPTION OF DRAWINGS

[0096] Other features, objects, and advantages of the present application will become more apparent from the following detailed description of non-limiting embodiments thereof, read in conjunction with the accompanying drawings:

[0097] FIG. 1 shows a flowchart according to one embodiment of the present application;

[0098] FIG. 2 shows a schematic diagram of a network architecture according to one embodiment of the present application;

[0099] FIG. 3 shows a schematic diagram of an embodiment of a wireless protocol architecture of a user plane and a control plane according to one embodiment of the present application;

[0100] FIG. 4 shows a schematic diagram of a first communication device and a second communication device according to one embodiment of the present application;

[0101] FIG. 5 shows a wireless signal transmission flowchart according to one embodiment of the present application;

[0102] FIG. 6 shows a schematic diagram of a first event according to an embodiment of the present application;

[0103] FIG. 7 shows a schematic diagram of a second event according to an embodiment of the present application;

[0104] FIG. 8 shows a schematic diagram of a first threshold varying over time according to an embodiment of the present application;

[0105] FIG. 9 shows a schematic diagram of predicting the second event according to an embodiment of the present application;

[0106] FIG. 10 shows a schematic diagram of a first time length according to an embodiment of the present application;

[0107] FIG. 11 shows a structural block diagram of a processing apparatus in a terminal according to an embodiment of the present application;

[0108] FIG. 12 shows a structural block diagram of a processing apparatus in a base station according to an embodiment of the present application;

[0109] FIG. 13 shows a schematic diagram of an artificial intelligence or machine learning based processing system according to an embodiment of the present application;

[0110] FIG. 14 shows a schematic diagram of RAN (Radio Access Network) domain AI / ML function deployment according to an embodiment of the present application;

[0111] FIG. 15 shows a schematic diagram of UE AI / ML function deployment according to an embodiment of the present application;

[0112] FIG. 16 shows a schematic diagram of an artificial intelligence or machine learning based processing system according to another embodiment of the present application. DETAILED DESCRIPTION

[0113] The technical solutions of the present application will be further described in detail below with reference to the accompanying drawings, and 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.

[0114] Embodiment 1

[0115] Embodiment 1 illustrates a flowchart according to an embodiment of the present application, as shown in FIG. 1. In FIG. 1, each block represents a step, and it should be particularly emphasized that the order of the blocks in the figure does not represent the time sequence between the steps represented.

[0116] In embodiment 1, the terminal in the present application receives a first RRC message in step 101, and the first RRC message configures at least one reference signal resource and a first event.

[0117] wherein the first event is dependent on the measurement of the at least one reference signal resource, and the first event is dependent on a first threshold, the first threshold being time-varying.

[0118] As one embodiment, the first event is a layer one measurement event.

[0119] As one embodiment, the first RRC message includes a CSI-MeasConfig field, the CSI-MeasConfig field configuring the measurement of the at least one reference signal resource.

[0120] As one embodiment, the first RRC message includes a CSI-ResourceConfigId field; the CSI-ResourceConfigId field indicating the at least one reference signal resource.

[0121] As one embodiment, the first event is a LTM layer one measurement event.

[0122] As one embodiment, the first RRC message includes a LTM-Config field.

[0123] As one embodiment, the first RRC message includes a LTM-CSI-MeasConfig field, the LTM-CSI-MeasConfig field configuring the measurement of the at least one reference signal resource.

[0124] As one embodiment, the first RRC message includes a LTM-CSI-ResourceConfigId field; the LTM-CSI-ResourceConfigId field indicating the at least one reference signal resource.

[0125] As one embodiment, the first event is a layer three measurement event.

[0126] As one embodiment, the first RRC includes a MeasConfig field.

[0127] As one embodiment, the first RRC message includes an EventTriggerConfig field; the EventTriggerConfig field configuring the first event.

[0128] As one embodiment, the at least one reference signal resource is configured by the first RRC message.

[0129] As an embodiment, the measurement on the at least one reference signal resource is configured by the first RRC message.

[0130] As an embodiment, the measurement is SSB measurement.

[0131] As an embodiment, the measurement is CSI-RS measurement.

[0132] As an embodiment, the first event is a measurement event.

[0133] As an embodiment, the first event is a layer three measurement event.

[0134] As an embodiment, the first event is a layer one measurement event.

[0135] As an embodiment, the first event is for LTM.

[0136] As an embodiment, the first event is for triggering conditional mobility.

[0137] As an embodiment, the first event is for triggering measurement reporting.

[0138] As an embodiment, the first event is for triggering layer one measurement reporting.

[0139] As an embodiment, the first event is for triggering layer three measurement reporting.

[0140] As an embodiment, the first event is a prediction event.

[0141] As an embodiment, the first event is for triggering prediction reporting.

[0142] As an embodiment, the at least one reference signal resource is configured to the first event.

[0143] As an embodiment, the at least one reference signal resource is determined by the terminal from a plurality of reference signal resources; the first RRC message configures the plurality of reference signal resources, and any reference signal resource in the at least one reference signal resource belongs to the plurality of reference signal resources.

[0144] As an embodiment, the plurality of reference signal resources have the same reference signal type.

[0145] As an embodiment, the plurality of reference signal resources have different reference signal types.

[0146] As an embodiment, the plurality of reference signal resources are all CSI-RS.

[0147] As an embodiment, the plurality of reference signal resources are SSBs.

[0148] As an embodiment, the at least one reference signal resource is determined by the terminal from the plurality of reference signal resources is that the at least one reference signal resource is one or more reference signal resources with the best measurement result in the plurality of reference signal resources.

[0149] As an embodiment, the best is that the RSRP is the highest.

[0150] As an embodiment, the best is that the RSRQ is the highest.

[0151] As an embodiment, the best is that the SINR is the highest.

[0152] As an embodiment, the at least one reference signal resource is determined by the terminal from the plurality of reference signal resources is that the at least one reference signal resource is dependent on the output of an AI module.

[0153] As an embodiment, the input of the AI module includes the measurement results of the plurality of reference signal resources.

[0154] As an embodiment, the one or more bests is K; the K is a positive integer.

[0155] As an embodiment, the positive integer K is configured by the first RRC message.

[0156] As an embodiment, the positive integer K is dependent on the output of the AI module.

[0157] As an embodiment, the first threshold value changes with time is that the value of the first threshold value at a first time and the value of the first threshold value at a second time are different, the first time and the second time are different.

[0158] As an embodiment, the first time and the second time are time instants.

[0159] As an embodiment, the first threshold value changes with time is that the value of the first threshold value in a first time interval and the value of the first threshold value in a second time interval are different.

[0160] As an embodiment, the first time interval and the second time interval do not overlap.

[0161] As an embodiment, the first time interval is configured by the first RRC message.

[0162] As an embodiment, the second time interval is configured by the first RRC message.

[0163] As one embodiment, the first time interval is determined by the terminal.

[0164] As one embodiment, the second time interval is determined by the terminal.

[0165] As one embodiment, the first time is an instant of time within the first time interval.

[0166] As one embodiment, the first time belongs to the first time interval.

[0167] As one embodiment, the second time is an instant of time within the second time interval.

[0168] As one embodiment, the second time belongs to the second time interval.

[0169] As one embodiment, the first threshold is constant within the first time interval or within the second time interval, and does not vary with time.

[0170] As one embodiment, the first time and the second time both belong to the first time interval.

[0171] As one sub-embodiment of the above embodiment, the first threshold corresponding to the first time and the second time can be different if and only if within the first time interval.

[0172] As one sub-embodiment of the above embodiment, the terminal decides the first threshold corresponding to the first time and the second time if and only if within the first time interval.

[0173] As one sub-embodiment of the above embodiment, the first RRC message configures the first threshold corresponding to the first time and the second time within the first time interval.

[0174] As one sub-embodiment of the above embodiment, the first threshold is not reconfigured within the first time interval.

[0175] As one embodiment, the first threshold is not reconfigured during the period in which the first threshold varies with time.

[0176] As one embodiment, the first threshold is not indicated by any RRC signaling during the period in which the first threshold varies with time.

[0177] As one embodiment, the first RRC message configures the first threshold.

[0178] As one embodiment, the first threshold is predicted.

[0179] As an embodiment, the first threshold is determined by the terminal itself.

[0180] As an embodiment, the first threshold is a constant.

[0181] As an embodiment, the first threshold is a dimension.

[0182] As an embodiment, the first threshold is a positive integer.

[0183] As an embodiment, the first threshold is a non-negative integer.

[0184] As an embodiment, the first threshold is a positive number.

[0185] As an embodiment, the first threshold is a non-negative number.

[0186] As an embodiment, the first threshold is a confidence threshold.

[0187] As an embodiment, the first threshold is a probability threshold.

[0188] As an embodiment, the first threshold is an RSRP threshold.

[0189] As an embodiment, the first threshold is an SINR threshold.

[0190] As an embodiment, the first threshold is an RSRQ threshold.

[0191] As an embodiment, the first threshold is a quantity threshold.

[0192] As an embodiment, the first threshold indicates the maximum value of the first counter.

[0193] As an embodiment, the first event depends on the measurement of the at least one reference signal resource, and the first threshold changes with time, which means that the triggering of the first event depends on the first counter; the first threshold indicates the maximum value of the first counter; the change of the first counter depends on the measurement of the at least one reference signal resource; the first threshold changes with time.

[0194] As an embodiment, the first event is triggered in response to the value of the first counter being not less than the maximum value of the first counter.

[0195] As an embodiment, the first event is RLF.

[0196] As one embodiment, the first counter is an N310 counter.

[0197] As one embodiment, the first counter is an N311 counter.

[0198] As one embodiment, the first counter is a Preamble Max Retransmission Number.

[0199] As one embodiment, the first counter is an RLC Max Retransmission Number.

[0200] Embodiment 2

[0201] 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 for a 5G NR (New Radio) / LTE (Long-Term Evolution) / LTE-A (Long-Term Evolution Advanced) system. The 5G NR / LTE / LTE-A network architecture 200 can be referred to as a 5GS (5G System) / EPS (Evolved Packet System) 200 or some other suitable terminology. The 5GS / EPS 200 includes a UE (User Equipment) 201, a RAN (Radio Access Network) 202, a 5GC (5G Core Network, 5G Core) / EPC (Evolved Packet Core) 210, a HSS (Home Subscriber Server) / UDM (Unified Data Management) 220, and at least one of an Internet service 230. The 5GS / EPS can interconnect with other access networks, but these entities / interfaces are not shown for simplicity. As shown, the 5GS / EPS provides packet-switched services, however, one of skill in the art will readily appreciate that the various concepts presented throughout this application can be extended to networks providing circuit-switched services or other cellular networks. 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 node 203 provides an access point to the 5GC / EPC 210 for a UE 201. Examples of UEs 201 include a cellular phone, a smart phone, a session initiation protocol (SIP) phone, a laptop, a personal digital assistant (PDA), a satellite radio, non-terrestrial base 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, an automobile, a wearable device, or any other similar functional device.Those skilled in the art will also refer to the UE 201 as a mobile station, a subscriber station, a mobile unit, a subscriber unit, a wireless unit, a remote unit, a mobile device, a wireless device, a wireless communication device, a remote device, a mobile subscriber station, an access terminal, a mobile terminal, a wireless terminal, a remote terminal, a handset, a user agent, a mobile client, a client, or some other suitable terminology. The node 203 is connected to the 5GC / EPC 210 over an S1 / NG interface. The 5GC / EPC 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 Date Network Gateway) / UPF 213. The MME / AMF / SMF 211 is the control node that processes the signaling between the UE 201 and the 5GC / EPC 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 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.

[0202] As an embodiment, the UE 201 corresponds to the terminal in the present application.

[0203] As an embodiment, the UE 201 is a user equipment (UE).

[0204] As an embodiment, the UE 201 is a base station (BS).

[0205] As an embodiment, the UE 201 is a relay device.

[0206] As an embodiment, the UE 201 is a gateway device.

[0207] As an embodiment, the node 203 corresponds to the base station in the present application.

[0208] As an embodiment, the node 203 is a base station device.

[0209] As an embodiment, the node 203 is a user equipment.

[0210] As an embodiment, the node 203 is a relay device.

[0211] As an embodiment, the node 203 is a gateway device.

[0212] Typically, the UE 201 is a user equipment and the node 203 is a base station device.

[0213] Typically, the UE 201 is a user equipment and the node 203 is a user equipment.

[0214] Typically, the UE 201 is a base station device and the node 203 is a base station device.

[0215] As an embodiment, the user equipment supports transmission of Non-Terrestrial Network (NTN).

[0216] As an embodiment, the user equipment supports transmission of Terrestrial Network (TN).

[0217] As an embodiment, the user equipment supports Dual Connection (DC) transmission.

[0218] As an embodiment, the user equipment comprises an aerial vehicle.

[0219] As an embodiment, the user equipment comprises a vehicular terminal.

[0220] As an embodiment, the user equipment comprises a ship.

[0221] As an embodiment, the user equipment comprises an Internet of Things terminal.

[0222] As an embodiment, the user equipment comprises an Industrial Internet of Things terminal.

[0223] As an embodiment, the user equipment comprises a device supporting low latency and high reliability transmission.

[0224] As an embodiment, the user equipment comprises a test device.

[0225] As one embodiment, the user equipment comprises a signaling tester.

[0226] As one embodiment, the user equipment comprises an IAB (Integrated Access and Backhaul)-MT (Mobile Termination).

[0227] As one embodiment, the base station equipment supports transmission in a non-terrestrial network.

[0228] As one embodiment, the base station equipment supports transmission in a terrestrial network.

[0229] As one embodiment, the base station equipment comprises a BTS (Base Transceiver Station).

[0230] As one embodiment, the base station equipment comprises a NodeB (NB).

[0231] As one embodiment, the base station equipment comprises a gNB.

[0232] As one embodiment, the base station equipment comprises an eNB.

[0233] As one embodiment, the base station equipment comprises an ng-eNB.

[0234] As one embodiment, the base station equipment comprises an en-gNB.

[0235] As one embodiment, the base station equipment comprises a CU (Centralized Unit).

[0236] As one embodiment, the base station equipment comprises a DU (Distributed Unit).

[0237] As one embodiment, the base station equipment comprises a TRP (Transmitter Receiver Point).

[0238] As one embodiment, the base station equipment comprises a Marco Cellular base station.

[0239] As one embodiment, the base station equipment comprises a Micro Cell base station.

[0240] As one embodiment, the base station equipment comprises a Pico Cell base station.

[0241] As one embodiment, the base station device comprises a femtocell.

[0242] As one embodiment, the base station device comprises a flight platform device.

[0243] As one embodiment, the base station device comprises a satellite device.

[0244] As one embodiment, the base station device comprises a test device.

[0245] As one embodiment, the base station device comprises a signaling tester.

[0246] As one embodiment, the base station device comprises a gateway device.

[0247] As one embodiment, the base station device comprises an IAB-node.

[0248] As one embodiment, the base station device comprises an IAB-donor.

[0249] As one embodiment, the base station device comprises an IAB-donor-CU.

[0250] As one embodiment, the base station device comprises an IAB-donor-DU.

[0251] As one embodiment, the base station device comprises an IAB-DU.

[0252] As one embodiment, the base station device comprises an IAB-MT.

[0253] As one embodiment, the relay device comprises a relay.

[0254] As one embodiment, the relay device comprises an L3 relay.

[0255] As one embodiment, the relay device comprises an L2 relay.

[0256] As one embodiment, the relay device comprises a router.

[0257] As one embodiment, the relay device comprises a switch.

[0258] As one embodiment, the relay device comprises a gateway device.

[0259] As one embodiment, the relay device comprises a user equipment.

[0260] As one embodiment, the relay device comprises a base station device.

[0261] Embodiment 3

[0262] Embodiment 3 shows a diagram of an embodiment of a radio protocol architecture for a user plane and a control plane according to this application, as shown in Figure 3. Figure 3 is a diagram illustrating an embodiment of a radio protocol architecture for a user plane 350 and a control plane 300, which shows the radio protocol architecture for the control plane 300 with three layers: 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 through encryption of 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 (Hybrid Automatic Repeat Request). 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 generally the same as the corresponding layers and sublayers in the control plane 300 for the physical layer 351, the PDCP sublayer 354 in the L2 layer 355, the RLC sublayer 353 in the L2 layer 355, and the MAC sublayer 352 in the L2 layer 355, but the PDCP sublayer 354 also provides header compression for upper layer data packets to reduce radio transmission overhead. The SDAP (Service Data Adaptation Protocol) sublayer 356 is also included in the L2 layer 355 in the user plane 350, which is responsible for mapping between QoS flows and data radio bearers (DRBs) to support diverse traffic.

[0263] As one embodiment, the wireless protocol architecture in FIG. 3 is applicable to the terminal in the present application.

[0264] As one embodiment, the wireless protocol architecture in FIG. 3 is applicable to the base station in the present application.

[0265] As one embodiment, the first RRC message in the present application is generated at the RRC 306.

[0266] As one embodiment, the first report in the present application is generated at the RRC 306.

[0267] As one embodiment, the first report in the present application is generated at the MAC 302 or the MAC 352.

[0268] As one embodiment, the first report in the present application is generated at the PHY 301 or the PHY 351.

[0269] Embodiment 4

[0270] Embodiment 4 shows a schematic diagram of a first communication device and a second communication device according to the present application, as shown in FIG. 4. FIG. 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.

[0271] The first communication device 450 includes a controller / processor 459, a memory 460, a data source 467, a transmit processor 468, a receive processor 456, a multi-antenna transmit processor 457, a multi-antenna receive processor 458, a transmitter / receiver 454, and an antenna 452.

[0272] The second communication device 410 includes a controller / processor 475, a memory 476, a receive processor 470, a transmit processor 416, a multi-antenna receive processor 472, a multi-antenna transmit processor 471, a transmitter / receiver 418, and an antenna 420.

[0273] 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 the stream 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. 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.

[0274] 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 symbol streams from the receivers 454. The receive processor 456 converts the baseband symbol streams from the multiple access receiver processor 458 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 multi-antenna 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.

[0275] 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.

[0276] 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.

[0277] As one embodiment, the first communication device 450 includes at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the first communication device 450 at least to receive a first RRC message, the first RRC message configuring at least one reference signal resource and a first event; the first event depending on the measurement for the at least one reference signal resource, and the first event depending on a first threshold, the first threshold varying over time.

[0278] As one embodiment, the first communication device 450 includes a memory storing a program of computer readable instructions to produce actions when executed by at least one processor, the actions comprising receiving a first RRC message, the first RRC message configuring at least one reference signal resource and a first event; the first event depending on the measurement for the at least one reference signal resource, and the first event depending on a first threshold, the first threshold varying over time.

[0279] As one embodiment, the second communication device 410 includes at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the second communication device 410 at least to transmit a first RRC message, the first RRC message configuring at least one reference signal resource and a first event; the first event depending on the measurement for the at least one reference signal resource, and the first event depending on a first threshold, the first threshold varying over time.

[0280] As one embodiment, the second communication device 410 includes a memory storing a program of computer readable instructions to produce actions when executed by at least one processor, the actions comprising transmitting a first RRC message, the first RRC message configuring at least one reference signal resource and a first event; the first event depending on the measurement for the at least one reference signal resource, and the first event depending on a first threshold, the first threshold varying over time.

[0281] As one 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 RRC message.

[0282] 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 RRC message.

[0283] 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 the first report.

[0284] 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 the first report.

[0285] As an embodiment, the first communication device 450 corresponds to a terminal in the present application.

[0286] As an embodiment, the second communication device 410 corresponds to a base station in the present application.

[0287] As an embodiment, the first communication device 450 is a user equipment.

[0288] As an embodiment, the first communication device 450 is a base station device.

[0289] As an embodiment, the first communication device 450 is a relay device.

[0290] As an embodiment, the second communication device 410 is a user equipment.

[0291] As an embodiment, the second communication device 410 is a base station device.

[0292] As an embodiment, the second communication device 410 is a relay device.

[0293] Embodiment 5

[0294] Embodiment 5 illustrates a wireless signal transmission flow chart according to an embodiment of the present application, as shown in FIG. 5. It is particularly stated that the sequence in this example does not limit the signal transmission sequence and the implementation sequence in the present application.

[0295] For the terminal U01:

[0296] In step S5101, a first RRC message is received, the first RRC message configuring at least one reference signal resource and a first event;

[0297] In step S5102, as a response to the first event being triggered, a first operation is performed;

[0298] In step S5103, the first report is transmitted;

[0299] In step S5104, the RRC connection is updated by itself;

[0300] For the base station N02:

[0301] In step S5201, the first RRC message is transmitted;

[0302] In step S5202, the first report is received;

[0303] In embodiment 5, the first event depends on the measurement for the at least one reference signal resource, and the first event depends on a first threshold, which varies over time.

[0304] As one embodiment, the terminal U01 and the base station N02 are connected through a wireless connection.

[0305] As one embodiment, the terminal U01 and the base station N02 are connected through a wired connection.

[0306] As one embodiment, the terminal U01 and the base station N02 are connected through a Uu interface.

[0307] As one embodiment, the terminal U01 and the base station N02 are connected through an IAB interface.

[0308] As one embodiment, the terminal U01 and the base station N02 are connected through a PC5 interface.

[0309] As one embodiment, the dashed box F5.1 is optional.

[0310] As one embodiment, the dashed box F5.1 exists.

[0311] As one embodiment, the dashed box F5.1 does not exist.

[0312] As one embodiment, the dashed box F5.2 is optional.

[0313] As one embodiment, the dashed box F5.2 exists.

[0314] As one embodiment, the dashed box F5.2 does not exist.

[0315] As one embodiment, the dashed box F5.3 is optional.

[0316] As one embodiment, the dashed box F5.3 exists.

[0317] As one embodiment, the dashed box F5.3 does not exist.

[0318] As one embodiment, when the dashed box F5.1 is present, then the dashed box F5.2 or the dashed box F5.3 can be present.

[0319] As one embodiment, when the dashed box F5.1 is present, then the dashed box F5.2 or the dashed box F5.3 can be present.

[0320] As one embodiment, the dashed box F5.2 and the dashed box F5.3 are not present at the same time.

[0321] As one embodiment, when the dashed box F5.2 is present, the dashed box F5.3 is not present.

[0322] As one embodiment, when the dashed box F5.3 is present, the dashed box F5.2 is not present.

[0323] As one embodiment, the dashed box F5.2 and the dashed box F5.3 are present at the same time.

[0324] As one embodiment, whether the dashed box F5.2 and the dashed box F5.3 are present depends on the first RRC message.

[0325] As one embodiment, the first RRC message configures whether the dashed box F5.1 is present.

[0326] As one embodiment, the first RRC message configures whether the dashed box F5.2 is present.

[0327] As one embodiment, the first RRC message configures whether the dashed box F5.3 is present.

[0328] As one embodiment, the first operation is an operation of a RRC layer.

[0329] As one embodiment, the first report indicates at least the first event.

[0330] As one embodiment, the first report is an event prediction report.

[0331] As one embodiment, the first report is a measurement report.

[0332] As one embodiment, the first report is a layer three measurement report.

[0333] As one embodiment, the first report is a layer one measurement report.

[0334] As one embodiment, the first report is a RRC message.

[0335] As one embodiment, the first report is a MAC PDU.

[0336] As one embodiment, the first report is a MAC CE.

[0337] As one embodiment, the first report is a UCI.

[0338] As one embodiment, the first report indicates the first event.

[0339] As one embodiment, the first report indicates the second event.

[0340] As one embodiment, the first report indicates a measurement result for the at least one reference signal.

[0341] As one embodiment, the first report indicates a prediction result for the at least one reference signal.

[0342] As one embodiment, the first report indicates a prediction result for the second event.

[0343] As one embodiment, the self-updating RRC connection comprises performing RRC connection re-establishment.

[0344] As one embodiment, the self-updating RRC connection comprises entering RRC_IDLE state.

[0345] As one embodiment, the self-updating RRC connection comprises performing cell selection.

[0346] As one embodiment, the self-updating RRC connection comprises applying configuration information of a candidate cell.

[0347] As one embodiment, the self-updating RRC connection comprises performing conditional mobility handover.

[0348] As one embodiment, the conditional mobility handover comprises conditional handover (CHO).

[0349] As one embodiment, the conditional mobility handover comprises conditional LTM.

[0350] As one embodiment, the candidate cell is a candidate cell of the conditional mobility handover.

[0351] As one embodiment, the first operation comprises sending the first report in response to the first event being triggered.

[0352] As one embodiment, the first event is associated with the one candidate cell.

[0353] As one embodiment, the first event is a conditional handover event.

[0354] As one embodiment, the first operation comprises sending the first report or comprises the self-updating RRC connection depending on the first RRC message.

[0355] As one embodiment, the first operation comprises sending the first report or comprises the self-updating RRC connection being implicitly indicated by the first RRC message.

[0356] As one embodiment, the first operation comprises sending the first report when the first RRC message configures the reporting configuration of the first report.

[0357] As one embodiment, the first operation comprises the self-updating RRC connection when the first RRC message configures the configuration of the self-updating RRC connection.

[0358] As one embodiment, the first operation comprises sending the first report or comprises the self-updating RRC connection being explicitly indicated by the first RRC message.

[0359] As one embodiment, the first RRC message indicates whether to send the first report when the first event is triggered.

[0360] As one embodiment, the first operation comprises sending the first report or comprises the self-updating RRC connection depending on the terminal self-determination.

[0361] As one embodiment, the first operation comprises the sending the first report and the self-updating RRC connection.

[0362] As one embodiment, the first operation is: sending the first report; and self-updating RRC connection in response to the successful sending of the first report.

[0363] Embodiment 6

[0364] Embodiment 6 illustrates a schematic diagram of a first event according to one embodiment of the present application, as shown in FIG. 6.

[0365] In Embodiment 6, the first event depends on the measurement for the at least one reference signal resource satisfying the first threshold.

[0366] As one embodiment, the first event depends on the measurement for the at least one reference signal resource being greater than or not less than the first threshold; wherein the at least one reference signal resource is configured on a neighboring cell of one serving cell of the terminal.

[0367] As one embodiment, the first event depends on the measurement for the at least one reference signal resource being less than or not greater than the first threshold; wherein the at least one reference signal resource is configured on one serving cell of the terminal.

[0368] As one embodiment, the one serving cell is a PCell.

[0369] As one embodiment, the one serving cell is a PSCell.

[0370] As one embodiment, the first event depends on the measurement for at least one reference signal satisfying a second threshold.

[0371] As one embodiment, the first event depends on the measurement for the at least one reference signal resource being greater than or not less than the second threshold; wherein the at least one reference signal resource is configured on one candidate cell of the terminal.

[0372] As one embodiment, the one candidate cell is an LTM candidate cell.

[0373] As one embodiment, the one candidate cell is a conditional LTM candidate cell.

[0374] As one embodiment, the one candidate cell is a conditional handover candidate cell.

[0375] As one embodiment, the first condition is deemed to be satisfied in response to the measurement for at least one reference signal resource of the one serving cell being greater than or not less than the first threshold.

[0376] As one embodiment, the first condition is deemed to be satisfied in response to the measurement for the at least one reference signal resource of the one candidate cell being greater than or not less than the second threshold.

[0377] As one embodiment, the first condition is considered fulfilled in response to the measurement for at least one reference signal resource of the first serving cell being greater than or not less than the first threshold and the measurement for the at least one reference signal resource of the one candidate cell being greater than or not less than the second threshold.

[0378] As one embodiment, the first condition is considered fulfilled in response to the measurement for at least one reference signal resource of the first serving cell being greater than or not less than the first threshold or the measurement for the at least one reference signal resource of the one candidate cell being greater than or not less than the second threshold.

[0379] As one embodiment, the first condition is considered fulfilled in response to the measurement for at least one reference signal of the first serving cell being greater than or not less than a first threshold for more than a first trigger time.

[0380] As one embodiment, the first condition is considered fulfilled in response to the measurement for at least one reference signal of the first candidate cell being greater than or not less than a first threshold for more than a second trigger time.

[0381] As one embodiment, the first condition is considered fulfilled in response to the measurement for at least one reference signal of the first serving cell being greater than or not less than a first threshold for more than a first trigger time or the measurement for at least one reference signal of the first candidate cell being greater than or not less than a first threshold for more than a second trigger time.

[0382] As one embodiment, the first condition is considered fulfilled in response to the measurement for at least one reference signal of the first serving cell being greater than or not less than a first threshold for more than a first trigger time and the measurement for at least one reference signal of the first candidate cell being greater than or not less than a first threshold for more than a second trigger time.

[0383] As one embodiment, the first trigger time is TimeToTrigger.

[0384] As one embodiment, the second trigger time is TimeToTrigger.

[0385] As one embodiment, the first trigger time is pre-configured.

[0386] As one embodiment, the second trigger time is pre-configured.

[0387] As one embodiment, the second trigger time is the first trigger time.

[0388] As one embodiment, the measurement of the at least one reference signal resource being greater than or not less than the first threshold value means that the measurement of the at least one reference signal resource is greater than or not less than the sum of the first threshold value and a first hysteresis value.

[0389] As one embodiment, the measurement of the at least one reference signal resource being less than or not greater than the second threshold value means that the measurement of the at least one reference signal resource is less than or not greater than the sum of the second threshold value and a second hysteresis value.

[0390] As one embodiment, the first hysteresis value is the first hysteresis value.

[0391] As one embodiment, the first hysteresis value is not the first hysteresis value.

[0392] As one embodiment, the first hysteresis value is pre-configured.

[0393] As one embodiment, the first hysteresis value is Hysteresis.

[0394] As one embodiment, the second hysteresis value is pre-configured.

[0395] As one embodiment, the second hysteresis value is Hysteresis.

[0396] As one embodiment, the first hysteresis value depends on the output of an AI module.

[0397] As one embodiment, the second hysteresis value depends on the output of an AI module.

[0398] As one embodiment, the first trigger time depends on the output of an AI module.

[0399] As one embodiment, the second trigger time depends on the output of an AI module.

[0400] As one embodiment, the first event depending on the measurement for the at least one reference signal resource satisfying the first threshold value means that the first event depends on the difference between the measurement for the at least one reference signal resource of the first candidate cell and the measurement for the at least one reference signal resource of the first serving cell being greater than or not less than the first threshold value.

[0401] As one embodiment, the first event depending on the difference between the measurement for the at least one reference signal resource of the first candidate cell and the measurement for the at least one reference signal resource of the first serving cell being greater than or not less than the first threshold value means that the first event depending on the difference between the measurement for the at least one reference signal resource of the first candidate cell and the measurement for the at least one reference signal resource of the first serving cell being greater than or not less than the sum of the first threshold value and the first hysteresis value.

[0402] As one embodiment, the first condition is considered to be satisfied in response to the first event depending on the difference between the measurement for the at least one reference signal resource of the first candidate cell and the measurement for the at least one reference signal resource of the first serving cell being greater than or not less than the first threshold value remaining for more than a first trigger time.

[0403] Embodiment 7

[0404] Embodiment 7 illustrates a diagram of a second event according to one embodiment of the application, as shown in FIG. 7.

[0405] In embodiment 7, the first event comprises a predicted second event; the predicted second event depending on the measurement for the at least one reference signal resource.

[0406] As one embodiment, the second event is a measurement event.

[0407] As one embodiment, the second event is a layer three measurement event.

[0408] As one embodiment, the measurement for the at least one reference signal means a layer three measurement.

[0409] As one embodiment, the second event is a layer one measurement event.

[0410] As one embodiment, the measurement for the at least one reference signal means a layer one measurement.

[0411] As one embodiment, the second event is RLF.

[0412] As one embodiment, whether the first event is satisfied depends on whether the second event is predicted.

[0413] As one embodiment, the first event is considered to be satisfied in response to the prediction of the second event.

[0414] As one embodiment, the prediction of the second event depends on an output of an AI module.

[0415] As one embodiment, the second event is a handover execution condition being met.

[0416] As one embodiment, the second event is a measurement reporting condition being met.

[0417] As one embodiment, measurement reporting is performed in response to the second event being met.

[0418] As one embodiment, conditional handover is performed in response to the second event being met.

[0419] As one embodiment, the prediction for the second event is a direct event prediction.

[0420] As one embodiment, the direct event prediction refers to the output of the AI module being a prediction for the second event.

[0421] As one embodiment, the direct event prediction refers to the output of the AI module including whether the second event will occur.

[0422] As one embodiment, the direct event prediction refers to the output of the AI module including a probability of the second event occurring.

[0423] As one embodiment, the prediction for the second event is an indirect event prediction.

[0424] As one embodiment, the indirect event prediction refers to the output of the AI module being a prediction for the measurement.

[0425] As one embodiment, the prediction for the second event relies on a prediction for the measurement.

[0426] As one embodiment, the prediction for the measurement refers to a prediction for the measurement of the at least one reference signal resource; the at least one reference signal resource being configured on the first serving cell.

[0427] As one embodiment, the prediction for the measurement refers to a prediction for the measurement of the at least one reference signal resource; the at least one reference signal resource being configured on the first candidate cell.

[0428] As one embodiment, the prediction for the measurement refers to a prediction for a measurement of one serving cell; the at least one reference signal resource being configured on the one serving cell; the one serving cell being a serving cell of the terminal.

[0429] As an embodiment, the prediction of the measurement refers to a prediction of a measurement of one candidate cell; the at least one reference signal resource is configured on the one candidate cell; the one candidate cell is a candidate cell of the terminal.

[0430] Embodiment 8

[0431] Embodiment 8 illustrates a schematic diagram of the first threshold varying over time according to an embodiment of the present application, as shown in FIG. 8.

[0432] In embodiment 8, the first threshold varying over time refers to that the first threshold depends on a length of a first time window; the predicting the second event includes predicting that the second event occurs within the first time window.

[0433] As an embodiment, the first time window is configured by a network.

[0434] As an embodiment, the first time window is configured by a first RRC message.

[0435] As an embodiment, the length of the first time window is determined by a terminal.

[0436] As an embodiment, a network configures a first coefficient value.

[0437] As an embodiment, the first RRC message configures the first coefficient value.

[0438] As an embodiment, the terminal determines the first coefficient value by itself.

[0439] As an embodiment, the first coefficient value depends on an output of the AI module.

[0440] As an embodiment, the first threshold depends on the first coefficient value and the first time window.

[0441] As an embodiment, the first threshold equals to a product of the length of the first time window and the first coefficient value.

[0442] As an embodiment, the first threshold equals to a first fixed value plus a first dynamic value.

[0443] As an embodiment, the first dynamic value equals to a product of the length of the first time window and the first coefficient value.

[0444] As an embodiment, the first fixed value does not vary over time.

[0445] As an embodiment, the first RRC message configures the first fixed value.

[0446] As an embodiment, the first coefficient value is a probability density.

[0447] As an embodiment, the first coefficient value is in unit of 1 / s.

[0448] As an embodiment, the first coefficient value is a rate of change of RSRP over time.

[0449] As an embodiment, the first coefficient value is in unit of dB / s.

[0450] As an embodiment, the start time of the first time window is current time.

[0451] As an embodiment, the end time of the first time window is pre-configured.

[0452] As an embodiment, the end time of the first time window is configured by the first RRC message.

[0453] As an embodiment, the end time of the first time window is dependent on the output of the AI module.

[0454] As an embodiment, the end time of the first time window is the time when the second event is most likely to occur.

[0455] As an embodiment, the end time of the first time window is the time when the second event is predicted to occur.

[0456] As an embodiment, the time-varying first threshold means that the first threshold is dependent on a first function; the first function is dependent on the first time window; the first time window is time-varying.

[0457] As an embodiment, within the first time window, the value of the first threshold is the function value of the first function.

[0458] As an embodiment, the first function is pre-configured.

[0459] As an embodiment, the first function is configured by the first RRC message.

[0460] As an embodiment, the input of the first function includes the length of the first time window.

[0461] As an embodiment, the first function is an AI module.

[0462] As an embodiment, the parameter of the first function includes the first coefficient value.

[0463] As an embodiment, the argument of the first function is the length of the first time window.

[0464] As one embodiment, the first function depends on a current time instant.

[0465] As one embodiment, an argument of the first function depends on a current time instant.

[0466] As one embodiment, an argument of the first function is the current time value.

[0467] As one embodiment, the first function depends on a first reference point.

[0468] As one embodiment, the first reference point is a start instant of the first time window.

[0469] As one embodiment, an argument of the first function is a time difference from the first reference point to a current time instant.

[0470] As one embodiment, an argument of the first function is a time difference from a start of the first time window to a current time instant.

[0471] As one embodiment, a unit of the time difference is millisecond.

[0472] As one embodiment, a unit of the time difference is frame number.

[0473] As one embodiment, a unit of the time difference is subframe number.

[0474] As one embodiment, a unit of the time difference is slot number.

[0475] As one embodiment, a unit of the time difference is symbol number.

[0476] As one embodiment, the first function is a monotonic function.

[0477] As one embodiment, the first function is a linear function.

[0478] As one embodiment, the first function is a positive proportion function, a coefficient of which is the first coefficient value.

[0479] As one embodiment, the first threshold value is a positive proportion function of the first time window length.

[0480] As one embodiment, the first threshold value is a linear function of the first time window length.

[0481] As one embodiment, the first threshold value is equal to a product of the first time window length and the first coefficient value.

[0482] As one embodiment, the first function depends on a first function value and a second function value.

[0483] As one embodiment, the first function value indicates a function value of the first function at a start time of the first time window.

[0484] As one embodiment, the second function value indicates a function value of the first function at an end time of the first time window.

[0485] As one embodiment, the second function value indicates a function value of the first function at a fixed time after the start time of the first time window.

[0486] As one embodiment, the first function linearly and uniformly varies over time between the first function value and the second function value.

[0487] As one embodiment, the predicting that the second event occurs within the first time window means that a probability of the second event occurring within the first time window is not less than or greater than the first threshold value.

[0488] As one embodiment, the predicting that the second event occurs within the first time window means that a predicted measurement value of the at least one reference signal resource within the first time window triggers the second event.

[0489] As one embodiment, the first report is sent in response to the predicting of the second event.

[0490] Embodiment 9

[0491] Embodiment 9 illustrates a schematic diagram of predicting the second event according to one embodiment of the present application, as shown in FIG. 9.

[0492] In embodiment 9, the predicting of the second event includes predicting that a metric value of the second event is greater than or not less than the first threshold value. As one embodiment, the predicting of the second event includes predicting that a metric value of the second event occurring within the first time window is greater than or not less than the first threshold value.

[0493] As one embodiment, the predicting of the second event includes predicting that a metric value of the second event occurring at a first time is greater than or not less than the first threshold value.

[0494] As one embodiment, the metric value refers to a probability.

[0495] As one embodiment, the metric value refers to a confidence.

[0496] As an embodiment, the metric value of the second event occurrence refers to a probability value of the second event occurrence.

[0497] As an embodiment, the metric value of the second event occurrence refers to a confidence level of the second event occurrence.

[0498] As an embodiment, the second event occurrence refers to a second event occurrence within a time window.

[0499] As an embodiment, the metric value of the second event occurrence greater than or not less than the first threshold value refers to a probability of the second event occurrence greater than or not less than the first threshold value.

[0500] As an embodiment, the metric value of the second event occurrence greater than or not less than the first threshold value refers to a confidence level of the second event occurrence greater than or not less than the first threshold value.

[0501] As an embodiment, the time window is configured by the first RRC message.

[0502] As an embodiment, the second event occurrence refers to a second event occurrence at a time point.

[0503] As an embodiment, the time point is configured by the first RRC message.

[0504] As an embodiment, the metric value refers to RSRP.

[0505] As an embodiment, the metric value refers to a predicted value of a measurement quantity.

[0506] As an embodiment, the metric value of the second event occurrence refers to a predicted value of a measurement quantity associated with the second event.

[0507] As an embodiment, the predicted value refers to a predicted value within a time window.

[0508] As an embodiment, the predicted value refers to a predicted value at a time point.

[0509] As an embodiment, the time window is configured by the first RRC message.

[0510] As an embodiment, the time point is configured by the first RRC message.

[0511] As an embodiment, the measurement quantity associated with the second event depends on at least one reference signal resource of the first candidate cell.

[0512] As one embodiment, the predicting the metric value of the second event occurrence greater than or not less than the first threshold value means the predicted value of the measurement associated with the second event greater than or not less than the first threshold value.

[0513] As one embodiment, the predicting the metric value of the second event occurrence greater than or not less than the first threshold value means the predicted value of the measurement associated with the second event greater than or not less than the first threshold value.

[0514] As one embodiment, the predicting the metric value of the second event occurrence greater than or not less than the first threshold value means the predicted value of the measurement associated with the second event greater than or not less than the first threshold value.

[0515] As one embodiment, the predicting the metric value of the second event occurrence greater than or not less than the first threshold value means the predicted value of the measurement associated with the second event greater than or not less than the first threshold value.

[0516] As one embodiment, the predicting the metric value of the second event occurrence greater than or not less than the first threshold value means the predicted value of the measurement associated with the second event greater than or not less than the first threshold value.

[0517] As one embodiment, the predicting the metric value of the second event occurrence greater than or not less than the first threshold value means the predicted value of the measurement associated with the second event greater than or not less than the first threshold value.

[0518] As one embodiment, the predicting the metric value of the second event occurrence greater than or not less than the first threshold value means the predicted value of the measurement associated with the second event greater than or not less than the first threshold value.

[0519] As one embodiment, the predicting the metric value of the second event occurrence greater than or not less than the first threshold value means the predicted value of the measurement associated with the second event greater than or not less than the first threshold value.

[0520] As one embodiment, the predicting the metric value of the second event occurrence greater than or not less than the first threshold value means the predicted value of the measurement associated with the second event greater than or not less than the first threshold value.

[0521] As one embodiment, the canceling means terminating.

[0522] Embodiment 10

[0523] Embodiment 10 illustrates a schematic diagram of a first time length according to an embodiment of the present application, as shown in FIG. 10.

[0524] In Embodiment 10, the first threshold value varying with time means that the first threshold value depends on a first time length and a target threshold value; wherein the first threshold value depending on the first time length and the target threshold value comprises:

[0525] if the first time length is less than the target threshold value, the first threshold value adopts a first value;

[0526] if the first time length is greater than the target threshold value, the first threshold value adopts a second value;

[0527] wherein the first time length depends on a predicted time of occurrence of the second event; the first value and the second value are different.

[0528] As an embodiment, the first RRC message configures the first value and the second value of the first threshold value.

[0529] As an embodiment, the first threshold value is a probability threshold value.

[0530] As an embodiment, the first threshold value is a confidence threshold value.

[0531] As an embodiment, the first time length is a time length between a current time and a predicted time of occurrence of the second event.

[0532] As an embodiment, the first time length is a time length between a current time when the second event is predicted to occur and a predicted time of occurrence of the second event.

[0533] As an embodiment, the target threshold value is a time metric value.

[0534] As an embodiment, the target threshold value is preconfigured.

[0535] As an embodiment, the target threshold value is configured by the first RRC message.

[0536] As an embodiment, the target threshold value is determined by the terminal itself.

[0537] As an embodiment, the target threshold value depends on an output of the AI module.

[0538] As an embodiment, the target threshold value is fixed.

[0539] As an embodiment, the target threshold value is relative.

[0540] As one embodiment, the target threshold is in units of milliseconds.

[0541] As one embodiment, the target threshold is in units of frames.

[0542] As one embodiment, the target threshold is in units of subframes.

[0543] As one embodiment, the target threshold is in units of slots.

[0544] As one embodiment, the target threshold is in units of symbols.

[0545] As one embodiment, the first value is higher than the second value.

[0546] As one embodiment, the first value is pre-configured.

[0547] As one embodiment, the first value is configured by the first RRC message.

[0548] As one embodiment, the first value is fixed.

[0549] As one embodiment, the second value is pre-configured.

[0550] As one embodiment, the second value is configured by the first RRC message.

[0551] As one embodiment, the second value is fixed.

[0552] As one embodiment, the second value depends on the first value and a first offset value.

[0553] As one embodiment, the second value is equal to the first value plus the first offset value.

[0554] As one embodiment, the first offset value is pre-configured.

[0555] As one embodiment, the first offset value is configured by the first RRC message.

[0556] As one embodiment, the first value depends on the second value and a second offset value.

[0557] As one embodiment, the first value is equal to the second value plus the second offset value.

[0558] As one embodiment, the second offset value is pre-configured.

[0559] As one embodiment, the second offset value is configured by the first RRC message.

[0560] As one embodiment, the second value is equal to 1.

[0561] Embodiment 11

[0562] 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 terminal 1100 comprises a first transmitter 1101 and a first processor 1102.

[0563] The first processor 1102 receives a first RRC message, the first RRC message configuring at least one reference signal resource and a first event;

[0564] In embodiment 11, wherein the first event depends on the measurement for the at least one reference signal resource, and the first event depends on a first threshold, the first threshold varying over time.

[0565] As one embodiment, the first event depends on the measurement for the at least one reference signal resource satisfying the first threshold.

[0566] As one embodiment, the first event comprises a predicted second event; the predicted second event depends on the measurement for the at least one reference signal resource.

[0567] As one embodiment, the first threshold varying over time means that the first threshold depends on a length of a first time window; the predicted second event comprises predicting that the second event occurs within the first time window.

[0568] As one embodiment, the predicted second event comprises predicting that a metric value of the second event occurring is greater than or not less than the first threshold.

[0569] As one embodiment, the first threshold varying over time means that the first threshold depends on a first time length and a target threshold; wherein the first threshold depending on the first time length and the target threshold comprises:

[0570] If the first time length is less than the target threshold, the first threshold adopts a first value;

[0571] If the first time length is greater than the target threshold, the first threshold adopts a second value;

[0572] Wherein the first time length depends on a time of the predicted second event occurring; the first value and the second value are different.

[0573] As an embodiment, in response to the first event being triggered, the terminal 1100 performs a first operation; wherein

[0574] The first operation comprises sending a first report.

[0575] Or,

[0576] The first operation comprises updating the RRC connection by itself.

[0577] 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 for a terminal in the present application.

[0578] As an embodiment, the first receiver comprises at least one of the antenna 452 or the receiver 454 or the multi-antenna receiving processor 458 or the receiving processor 456 or the controller / processor 459 or the memory 460 or the data source 467 in FIG. 4 of the present application.

[0579] As an embodiment, the first receiver comprises at least the antenna 452 and the receiver 454 in FIG. 4 of the present application.

[0580] As an embodiment, the first transmitter 1101 comprises at least one of the antenna 452 or the transmitter 454 or the multi-antenna transmitting processor 457 or the transmitting processor 468 or the controller / processor 459 or the memory 460 or the data source 467 in FIG. 4 of the present application.

[0581] As an embodiment, the first transmitter 1101 comprises at least the antenna 452 and the transmitter 454 in FIG. 4 of the present application.

[0582] Embodiment 12

[0583] Embodiment 12 illustrates a structural block diagram of a processing device in a base station according to an embodiment of the present application; as shown in FIG. 12. In FIG. 12, the base station 1200 comprises a second transmitter 1201 and a second receiver 1202.

[0584] The second transmitter 1201 sends a first RRC message, wherein the first RRC message configures at least one reference signal resource and a first event.

[0585] In embodiment 12, the first event depends on the measurement for the at least one reference signal resource, and the first event depends on a first threshold value, wherein the first threshold value varies with time.

[0586] As an embodiment, the first event depends on the measurement for the at least one reference signal resource satisfying the first threshold.

[0587] As an embodiment, the first event comprises a predicted second event; the predicted second event depends on the measurement for the at least one reference signal resource.

[0588] As an embodiment, the first threshold varies with time means that the first threshold depends on a length of a first time window; the predicted second event comprises predicting that the second event occurs within the first time window.

[0589] As an embodiment, the predicted second event comprises predicting that a metric value of the second event occurring is greater than or not less than the first threshold.

[0590] As an embodiment, the first threshold varies with time means that the first threshold depends on a first time length and a target threshold; wherein the first threshold depending on the first time length and the target threshold comprises:

[0591] if the first time length is less than the target threshold, the first threshold adopts a first value;

[0592] if the first time length is greater than the target threshold, the first threshold adopts a second value;

[0593] wherein the first time length depends on a predicted time of the second event occurring; the first value and the second value are different.

[0594] As an embodiment, in response to the first event being triggered, the base station 1200 performs a first operation; wherein,

[0595] the first operation comprises receiving a first report;

[0596] or,

[0597] the first operation comprises a receiver of the first RRC message updating an RRC connection by itself.

[0598] As an embodiment, the base station comprises one or more processors and a memory; 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 base station perform the method for a base station in the present application.

[0599] As one embodiment, the second transmitter 1201 includes 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.

[0600] As one embodiment, the second transmitter 1201 includes at least the antenna 420 and the transmitter 418 in FIG.4 of this application.

[0601] As one embodiment, the second receiver 1202 includes 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.

[0602] As one embodiment, the second receiver 1202 includes at least the antenna 420 and the receiver 418 in FIG.4 of this application.

[0603] Embodiment 13

[0604] Embodiment 13 illustrates a schematic diagram of an artificial intelligence or machine learning based processing system according to an embodiment of the application, as shown in FIG.13. FIG.13 includes a first module, a second module, a third module, a fourth module and a fifth module.

[0605] In embodiment 13, the first module sends a first data set to the second module, the first module sends a second data set to the third module, the first module sends a third data set to the fifth module, the fifth module sends a first type of parameter set to the second module, the fifth module sends a second type of parameter set to the third module, the fifth module sends a third type of parameter set to the fourth module, the second module sends a fourth type of parameter set to the fourth module, and the fourth module sends a fifth type of parameter set to the third module.

[0606] As one embodiment, any one of the first module, the second module, the third module, the fourth module and the fifth module does not belong to the terminal.

[0607] The above method avoids air interface signaling interaction and shortens transmission delay.

[0608] As one embodiment, any one of the first module, the second module, the third module, the fourth module and the fifth module does not belong to the terminal.

[0609] The above method reduces the hardware complexity of the terminal.

[0610] As an embodiment, at least the first module among the first module, the second module, the third module, the fourth module, and the fifth module belongs to the terminal; and at least one module among the first module, the second module, the third module, the fourth module, and the fifth module does not belong to the terminal.

[0611] The above method balances the hardware complexity and transmission latency of the terminal.

[0612] As an embodiment, the first module is used for data collection.

[0613] As an embodiment, the first module is responsible for data collection.

[0614] As an embodiment, the first module has a data collection function.

[0615] As an embodiment, the second module is used for model training.

[0616] As an embodiment, the second module is responsible for model training.

[0617] As an embodiment, the second module has a model training function.

[0618] As an embodiment, the second module performs AI / ML model training.

[0619] As an embodiment, the second module performs validation.

[0620] As an embodiment, the second module performs testing.

[0621] As an embodiment, the second module generates model performance metrics.

[0622] As an embodiment, the second module is responsible for data preparation.

[0623] As an embodiment, the data preparation includes at least one of data pre-processing or cleaning or formatting or transformation.

[0624] As an embodiment, the third module is used for inference.

[0625] As one embodiment, the third module has an inference function.

[0626] As one embodiment, the third module is responsible for inference.

[0627] As one embodiment, the fourth module is for Model Storage.

[0628] As one embodiment, the fourth module has a Model Storage function.

[0629] As one embodiment, the fourth module is responsible for storing trained models.

[0630] As one embodiment, the fourth module is responsible for storing trained models that can be used to perform inference processing.

[0631] As one embodiment, the fifth module is for Management.

[0632] As one embodiment, the fifth module is responsible for management.

[0633] As one embodiment, the fifth module has a management function.

[0634] As one embodiment, the first data set is Training Data.

[0635] As one embodiment, the second data set is Inference Data.

[0636] As one embodiment, the third data set is Monitoring Data.

[0637] As one embodiment, the first group of parameters includes Monitoring output.

[0638] As one embodiment, the second group of parameters includes Management Instruction.

[0639] As one embodiment, the second group of parameters is used for fine-tune operation of inference function.

[0640] As one embodiment, the second group of parameters includes the identity of the model.

[0641] As one embodiment, the second group of parameters is used to select a model.

[0642] As one embodiment, the second type of parameter set is used for a switching model.

[0643] As one embodiment, the second type of parameter set is used for an activation / deactivation model.

[0644] As one embodiment, the second type of parameter set is used for fallback from an AI-ML operation to a non-AI-ML operation.

[0645] As one embodiment, the third type of parameter set includes a model transfer request.

[0646] As one embodiment, the third type of parameter set includes a model delivery request.

[0647] As one embodiment, the fourth type of parameter set includes a trained model.

[0648] As one embodiment, the fourth type of parameter set includes an updated model.

[0649] As one embodiment, the fourth type of parameter set indicates an identity of a model.

[0650] As one embodiment, the fifth type of parameter set includes a model transfer.

[0651] As one embodiment, the fifth type of parameter set includes a model delivery.

[0652] As one embodiment, the fifth type of parameter set indicates an identity of a model.

[0653] As one embodiment, the first type of output includes a monitoring output.

[0654] As one embodiment, the first type of output is present.

[0655] As one embodiment, the first type of output is not present.

[0656] As one embodiment, the second type of output includes an inference output.

[0657] As one embodiment, the second type of output is used by the fifth module to monitor performance of an AI / ML model.

[0658] As one embodiment, the second type of output is used by the fifth module to monitor performance of an AI / ML function. As one embodiment, the second type of output exists.

[0659]

[0660] As one embodiment, the second type of output does not exist.

[0661] As one embodiment, the artificial intelligence processing system generates or assists in generating at least one of the first threshold, or the prediction of the second event, or the metric value that predicts the occurrence of the second event, or the length of the first time window, or the target threshold, or the first value, or the second value, or the first operation, or the first report, or the self-updating RRC connection.

[0662] As one embodiment, the fifth module generates or assists in generating at least one of the first threshold, or the prediction of the second event, or the metric value that predicts the occurrence of the second event, or the length of the first time window, or the target threshold, or the first value, or the second value, or the first operation, or the first report, or the self-updating RRC connection.

[0663] As one embodiment, the third module generates or assists in generating at least one of the first threshold, or the prediction of the second event, or the metric value that predicts the occurrence of the second event, or the length of the first time window, or the target threshold, or the first value, or the second value, or the first operation, or the first report, or the self-updating RRC connection.

[0664] As one embodiment, the second type of output includes at least one of the first threshold, or the prediction of the second event, or the metric value that predicts the occurrence of the second event, or the length of the first time window, or the target threshold, or the first value, or the second value, or the first operation, or the first report, or the self-updating RRC connection.

[0665] As one embodiment, at least one of the first data set or the second data set includes the measurement of the at least one reference signal resource.

[0666] As one embodiment, at least one of the first data set or the second data set includes the first RRC message.

[0667] As one embodiment, at least one of the first data set or the second data set includes the first event.

[0668] As one embodiment, at least one of the first data set or the second data set includes the second event.

[0669] ​​​​​​​​​​As one embodiment, at least one of the first data set or the second data set or the third data set comprises the measurement of the at least one reference signal resource.

[0670] As one embodiment, at least one of the first data set or the second data set or the third data set comprises the first RRC message.

[0671] As one embodiment, at least one of the first data set or the second data set or the third data set comprises the first event.

[0672] As one embodiment, at least one of the first data set or the second data set or the third data set comprises the second event.

[0673] As one embodiment, the embodiment 13 is merely for illustrating that the present application can be applied to an artificial intelligence processing system, the embodiment does not limit that the present application is applied to a non-artificial intelligence processing system, and the embodiment does not limit that the present application is applied to other types of artificial intelligence processing systems to achieve the effects equivalent to the artificial intelligence processing system shown in the figure 13.

[0674] Embodiment 14

[0675] The embodiment 14 illustrates a schematic diagram of RAN (Radio Access Network) domain AI / ML function deployment according to one embodiment of the present application; as shown in the figure 14. The gNB in the embodiment 14 can be replaced by a network device such as eNB, or 6G base station, etc.

[0676] The AI / ML related functions include ML training function (also referred to as AI training, or AI / ML training), ML testing function, ML inference function (also referred to as AI inference, or AI / ML inference), etc. The ML training function, the ML testing function, and the ML inference function can be independently deployed, or can be co-located deployed. The deployment of the AI / ML related functions can be implemented by software, such as downloading and / or running of an executable file; or can be implemented by software combined with hardware, such as accelerating the calculation by hardware to improve the operation speed or save the power consumption.

[0677] For ML training function, it can be deployed in cross-domain management system, or domain-specific management system, which is used to manage RAN domain or CN (Core Network) domain. For example, for MDA (Management Data Analytics) ML training function can be deployed in MDAF (MDA function); for network data analytics ML training can be deployed in NWDAF (Network Data Analytics Function), i.e. ML training function is MTLF (Model Training logical function).

[0678] For ML inference function, it can also be deployed in cross-domain management system, or domain-specific management system; for example, ML inference function is MDAF, or ML inference function is AnLF (Analytics logical function) in NWDAF.

[0679] Similarly, ML testing function can also be deployed in cross-domain management system, or domain-specific management system.

[0680] In embodiment 14, RAN domain ML training function 1402 is located in RAN domain management function 1403; and ML inference function is located in base station, i.e. AI / ML inference function 1404 is located in gNB 1405, AI / ML inference function 1406 is located in gNB 1407, and so on.

[0681] In FIG. 14, the management of ML inference function of multiple base stations is completed by RAN domain management function 1403, i.e. data interaction is performed with RAN domain MnS (Management Service) consumer / cross-domain management 1401 (as shown by the dashed arrow in FIG. 14).

[0682] Optionally, the management of ML inference function can also be completed by the base station itself, i.e. each base station can independently perform data interaction with RAN domain MnS consumer / cross-domain management 1401.

[0683] It should be noted that embodiment 14 is only a non-limiting implementation; optionally, RAN domain ML training function can also be deployed in base station; or optionally, part of base stations deploy ML inference function and RAN domain ML training function, and part of base stations only deploy ML inference function.

[0684] As one embodiment, one gNB (or base station) in Embodiment 2 is the base station of the present application.

[0685] As one embodiment, the first processor comprises one AL / ML inference function in FIG. 14, i.e. 1404 or 1406.

[0686] As one embodiment, the second processor comprises one AL / ML inference function in FIG. 14, i.e. 1404 or 1406.

[0687] As one embodiment, one AL / ML inference function in FIG. 14 performs ML training according to the collected measurement results of the first serving cell or the second cell.

[0688] As one embodiment, one AL / ML inference function in FIG. 14 performs ML training according to the collected measurement of the at least one reference signal resource.

[0689] As one embodiment, one AL / ML inference function in FIG. 14 performs ML training according to the collected first RRC message.

[0690] Embodiment 15

[0691] Embodiment 15 illustrates a schematic diagram of AI / ML function deployment of a UE according to one embodiment of the present application; as shown in FIG. 15. The RAN domain ML training function 1505 in FIG. 15 is optional.

[0692] The UE function 1504 is deployed in the terminal of the present application, and the UE function 1504 comprises an AI / ML inference function 1506; the AI / ML inference function 1506 uses an ML model (also referred to as an AI model) for inference; one ML model is usually trained before being used for AI / ML inference.

[0693] As one embodiment, the UE function 1504 comprises a RAN domain ML training function 1505, which runs training data through an ML model, derives relevant loss, and adjusts parameters of the ML model based on the calculated loss; the ML training comprises at least one of ML initial training, ML re-training, and reinforcement learning.

[0694] The above embodiments can reduce the complexity of the base station, or save the air interface resources caused by reporting training data; however, the above embodiments put higher requirements on the processing capability of the UE side.

[0695] Optionally, the UE function 1504 further comprises a CN domain ML training function (not included in FIG. 15).

[0696] Optionally, the UE function 1504 further comprises an AI / ML deployment function - not included in FIG. 15, for loading ML models and data.

[0697] As one embodiment, the terminal indicates whether it supports ML training function (RAN domain or CN domain) through capability reporting, and the capability reporting is RRC signaling or NAS (Non-Access Stratum) signaling.

[0698] As one embodiment, the ML model, and related metadata, are loaded by the terminal from a network device or a remote server.

[0699] Optionally, the UE function 1504 is a MnS (Management Service) producer that provides data to the CN domain MnF (Management Function) 1501, and / or the RAN domain MnF 1502, and / or the cross-domain management system 1503 for management or analysis (as indicated by double-headed arrow 1507).

[0700] Optionally, the UE function 1504 is a MnS consumer that loads data from the CN domain MnF (Management Function) 1501, and / or the RAN domain MnF 1502, and / or the cross-domain management system 1503 for AI / ML related management, such as management data request, ML model activation, and / or ML training, etc. (as indicated by double-headed arrow 1507).

[0701] As one embodiment, the first threshold in the present application is obtained through inference of the AI / ML inference function 1506.

[0702] As one embodiment, the prediction of the second event in the present application is obtained through inference of the AI / ML inference function 1506.

[0703] As one embodiment, the predicted metric value of the occurrence of the second event in the present application is obtained through inference of the AI / ML inference function 1506.

[0704] As one embodiment, the length of the first time window in the present application is derived from inference by the AI / ML inference function 1506.

[0705] As one embodiment, the target threshold in the present application is not satisfied is derived from inference by the AI / ML inference function 1506.

[0706] As one embodiment, the first value in the present application is derived from inference by the AI / ML inference function 1506.

[0707] As one embodiment, the second value in the present application is derived from inference by the AI / ML inference function 1506.

[0708] As one embodiment, the first operation in the present application is derived from inference by the AI / ML inference function 1506.

[0709] As one embodiment, the first report in the present application is derived from inference by the AI / ML inference function 1506.

[0710] As one embodiment, the self-updating RRC connection in the present application is derived from inference by the AI / ML inference function 1506.

[0711] As one embodiment, at least one of the first threshold or the prediction for the second event or the metric value predicting the occurrence of the second event or the length of the first time window or the target threshold or the first value or the second value or the first operation or the first report or the self-updating RRC connection in the present application is derived from inference by the AI / ML inference function 1506.

[0712] As one embodiment, the first processor comprises an AI / ML inference function 1506 in FIG. 15.

[0713] As one embodiment, the ML model is based on a neural network (NN).

[0714] As one embodiment, the ML model is based on a CNN (Conventional Neural Networks).

[0715] As one embodiment, the ML model is based on a ResNet (Deep Residual Networks).

[0716] As one embodiment, the ML model is based on RNN (Recurrent Neural Networks).

[0717] As one embodiment, the ML model is based on LSTM (Long Short Term Memory) networks.

[0718] As one embodiment, the ML model is based on Transformer architecture.

[0719] Embodiment 16

[0720] Embodiment 16 illustrates a schematic diagram of an artificial intelligence or machine learning based processing system according to another embodiment of the present application; as shown in FIG. 16. FIG. 16 includes a third processor, a fourth processor, a fifth processor and a sixth processor.

[0721] In embodiment 16, the third processor sends a first data set to the fourth processor, and a second data set to the fifth processor; the fourth processor generates a target first group of parameters based on the first data set, and sends the generated target first group of parameters to the fifth processor; the fifth processor processes the second data set using the target first group of parameters to obtain a first output, and (optionally) sends the first output to the sixth processor. In FIG. 16, a first feedback and a second feedback are optional; the fourth processor includes an ML training function; and the fifth processor includes an ML inference function.

[0722] As one embodiment, the sixth processor includes an ML testing function.

[0723] As one embodiment, the sixth processor includes performance monitoring / evaluation of the ML model.

[0724] As one embodiment, the fifth processor sends a first feedback to the fourth processor, and the first feedback is used to trigger re-computation or update of the target first group of parameters, i.e. trigger ML initial training or ML re-training.

[0725] As one embodiment, the sixth processor sends a second feedback to the third processor, and the second feedback is used to generate the first data set or the second data set, or the second feedback is used to trigger sending of the first data set or sending of the second data set.

[0726] As one embodiment, the third processor generates the first data set and the second data set based on measurements.

[0727] As one embodiment, the fifth processing machine belongs to the terminal and the sixth processing machine belongs to the base station.

[0728] As one embodiment, the first type of output includes the first message.

[0729] As one embodiment, the first type of output includes the first threshold.

[0730] As one embodiment, the first type of output includes the first hysteresis value.

[0731] As one embodiment, the first type of output includes the first trigger time.

[0732] As one embodiment, the first type of output includes whether the first condition is met.

[0733] As one embodiment, the first type of output includes whether to switch to the second cell or send a first message on the first serving cell.

[0734] As one embodiment, the first type of output includes the second threshold.

[0735] As one embodiment, the first type of output includes the second hysteresis value.

[0736] As one embodiment, the first type of output includes the second trigger time.

[0737] As one embodiment, the first type of output includes whether the second condition is met.

[0738] As one embodiment, the first type of output includes the third threshold.

[0739] As one embodiment, the first type of output includes the first time length.

[0740] As one embodiment, the first type of output includes a prediction of a measurement of at least one reference signal resource of the first serving cell.

[0741] As one embodiment, the first type of output includes a prediction of a measurement of at least one reference signal resource of the second cell.

[0742] As one embodiment, the first type of output includes a length of the second timer.

[0743] As one embodiment, the second data set includes a measurement for a reference signal.

[0744] As one embodiment, the first data set includes training data.

[0745] As an embodiment, the fourth processor is configured to train the ML model, and the trained model is described by the target first-type parameter set.

[0746] As an embodiment, the fourth processor belongs to the terminal.

[0747] The above embodiment avoids transmitting the first data set to the base station.

[0748] As an embodiment, the fourth processor belongs to the base station.

[0749] The above embodiment supports joint training and optimizes system performance.

[0750] As an embodiment, the fourth processor belongs to the core network.

[0751] The above embodiment supports joint training across the network and further optimizes system performance.

[0752] As an embodiment, the second data set includes inference data.

[0753] As an embodiment, the fifth processor belongs to the terminal.

[0754] As an embodiment, the fifth processor constructs a model according to the target first-type parameter set, and then inputs the second data set into the constructed model to obtain the first-type output.

[0755] As an embodiment, the fifth processor generates a recovery data set according to the first-type output, and the error of the recovery data set and the second data set is used to generate the first-type feedback.

[0756] As an embodiment, the first-type feedback is used to reflect the performance of the trained model; when the performance of the trained model cannot meet the requirements, the fourth processor will recalculate the target first-type parameter set.

[0757] As an embodiment, when the error is too large or the time for updating is too long, the performance of the trained model is considered to be unable to meet the requirements.

[0758] As an embodiment, the target first-type parameter set includes one or more of the following: convolution kernel size, convolution layer number, convolution step length, pooling kernel size, pooling kernel step length, pooling function, activation function, or feature map number.

[0759] As an embodiment, the target first-type parameter group includes one or more of a convolution kernel, a pooling kernel, a pooling function, an activation function, a parameter of the pooling function, or a parameter of the activation function.

[0760] Those skilled in the art can understand that all or part of the steps in the foregoing method can be instructed to relevant hardware by a program, and the program 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 a drone, a communication module on a drone, a remote control airplane, a flying vehicle, a small airplane, a mobile phone, a tablet computer, a notebook computer, a vehicle-mounted communication device, a wireless sensor, a network card, an Internet of Things terminal, an RFID terminal, an NB-IOT terminal, an MTC (Machine Type Communication) terminal, an eMTC (enhanced MTC) terminal, a data card, a network card, a vehicle-mounted communication device, a low-cost mobile phone, a low-cost tablet computer, and the like wireless communication devices. The base station or system device in the present application includes but is not limited to a macro cellular base station, a micro cellular base station, a home base station, a relay base station, a gNB (NR Node B), an NR Node B, a TRP (Transmitter Receiver Point), and the like wireless communication devices.

[0761] The above describes only the preferred embodiments of the present application and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, and the like 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 a terminal, comprising: receiving a first RRC message, the first RRC message configuring at least one reference signal resource and a first event; wherein the first event depends on the measurement for the at least one reference signal resource, and the first event depends on a first threshold, the first threshold varies over time. the first event depends on the measurement for the at least one reference signal resource satisfying the first threshold.

2. The method of claim 1, wherein, 3.The method of claim 1, wherein: the first event comprises predicting a second event; the predicting the second event depends on the measurement for the at least one reference signal resource. 4.The method of claim 3, wherein: the first threshold varies over time means that the first threshold depends on a length of a first time window; the predicting the second event comprises predicting that the second event occurs within the first time window. 5.The method of claim 3, wherein: the predicting the second event comprises predicting that a metric value of the second event occurring is greater than or not less than the first threshold. 6.The method of claim 5, wherein: the first threshold varies over time means that the first threshold depends on a first time length and a target threshold; wherein the first threshold depending on the first time length and the target threshold comprises: if the first time length is less than the target threshold, the first threshold adopts a first value; if the first time length is greater than the target threshold, the first threshold adopts a second value; wherein the first time length depends on a time of the predicted second event occurring; the first value and the second value are different. 7.The method of any one of claims 1-6, wherein: in response to the first event being triggered, performing a first operation; wherein: the first operation comprises sending a first report; or, the first operation comprises updating an RRC connection by itself. 8.A terminal, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is configured to store computer program codes, the computer program codes comprising computer instructions, and the one or more processors are configured to invoke the computer instructions to cause the terminal to perform the method of any one of claims 1-7. 9.A method for a base station, comprising: sending a first RRC message, the first RRC message configuring at least one reference signal resource and a first event; wherein the first event depends on the measurement for the at least one reference signal resource, and the first event depends on a first threshold, the first threshold varies over time. the first event depends on the measurement for the at least one reference signal resource satisfying the first threshold. the first event comprises predicting a second event; the predicting the second event depends on the measurement for the at least one reference signal resource.

10. The method of claim 9, wherein, ​ 11. The method of claim 9, wherein, ​ 12. The method of claim 11, wherein the first threshold varies over time in that the first threshold is dependent on a length of a first time window, and wherein the predicting the second event comprises predicting that the second event occurs within the first time window.

13. The method of claim 11, wherein the predicting the second event comprises predicting that a metric value of the second event is greater than or not less than the first threshold.

14. The method of claim 13, wherein the first threshold varies over time in that the first threshold is dependent on a first time length and a target threshold, and wherein the first threshold being dependent on the first time length and the target threshold comprises: if the first time length is less than the target threshold, the first threshold adopts a first value; and if the first time length is greater than the target threshold, the first threshold adopts a second value, wherein the first time length is dependent on a predicted time of the second event, and wherein the first value and the second value are different.

15. The method of any one of claims 9-14, wherein in response to the first event being triggered, a first operation is performed, and wherein the first operation comprises receiving a first report, or wherein the first operation comprises a receiver of the first RRC message updating an RRC connection by itself.

16. A base station, comprising: one or more processors and a memory, wherein the memory is coupled with the one or more processors, and the memory is configured to store computer program code 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 of any one of claims 9-15. ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​

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