Measurement method and apparatus for wireless communication

Abstract

The present application discloses a measurement method and apparatus for wireless communication. The method comprises: a communication node sending a first message; and as a response to sending the first message, receiving a second message by means of a target radio bearer, the second message comprising at least a portion of target measurement information in a first memory cell, candidates of the target radio bearer comprising at least a first candidate and a second candidate, the second candidate being different from the first candidate, the first candidate being an SRB, and an identifier of the first candidate being Q1, Q1 being 4, or Q1 being an integer greater than 5. The method provided in the present application addresses the transmission of measurement information in a first memory cell, wherein candidates of a target radio bearer comprise at least a first candidate and a second candidate, which improve the transmission flexibility of measurement information in the first memory cell.

Description

A method and apparatus for measurement used in wireless communication Technical Field

[0001] This application relates to transmission methods and apparatus in wireless communication systems, and more particularly to measurement methods and apparatus. Background Technology

[0002] The 3GPP (3rd Generation Partnership Project) protocol supports SON (Self-Organizing Networks) / MDT (Minimization of Drive Test), including Immediate MDT and Logged MDT. For Logged MDT, to reduce the reporting of measurement information, the UE (User Equipment) can store measurement information in UE variables. Whenever the UE performs RRC (Radio Resource Control) connection reconfiguration, reestablishment, resume, or establishment, it can indicate the storage of the corresponding measurement information in the message confirming the successful completion of the RRC reconfiguration, reestablishment, resume, or establishment. Based on this indication, the base station requests the UE to report the corresponding measurement information via a UEInformationRequest message. In response, the UE sends the corresponding measurement information to the base station via a UEInformationResponse message.

[0003] 3GPP Release 19 launched WI: "For AI (Artificial Intelligence) / ML (Machine Learning) of NR Air Interface". Currently, the following consensus has been reached regarding data collection for network-side models: UEInformationRequest messages / UEInformationResponse messages are used for on-demand AI / ML training data collection, and a low-priority SRB (Signalling Radio Bearer) is used.

[0004] Since the specifications of AI models may extend beyond the scope of 3GPP (except for reference models used for performance calibration), the specific implementation of AI / ML training and AI / ML inference may be determined by the hardware equipment vendors themselves. It may be based on classic models such as Transformer architecture, RNN (Recurrent Neural Network), CNN (Conventional Neural Networks), or a hybrid model composed of multiple models. Summary of the Invention

[0005] The inventors discovered through research that, on the one hand, with the continuous development of AI / ML technology, the number of network-side AI / ML models / functions will increase, leading to different data collection needs; on the other hand, data collected for network-side models may be reported in the same message as existing data collection for purposes such as MRO (Mobility Robustness Optimisation) / MLB (Mobility Load Balancing) / RACH. For on-demand AI / ML training data collection, using only a low-priority SRB can impact some network-side AI / ML models / functions or existing data collection. Therefore, it is necessary to study the data transmission method for data collection of network-side models.

[0006] To address the aforementioned problems, this application provides a solution. While AI / ML is used as an example in the problem description, this application is also applicable to non-AI / ML scenarios, achieving similar technical effects. Similarly, while network-side AI / ML training is used as an example, this application is also applicable to scenarios where AI / ML training is performed on the UE side, achieving similar technical effects. Furthermore, adopting a unified design scheme for different scenarios helps reduce hardware complexity and cost. It should be noted that, without conflict, embodiments and features in any node of this application can be applied to any other node. Without conflict, embodiments and features in any embodiment of this application can be arbitrarily combined.

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

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

[0009] This application discloses a method used in a first node of wireless communication, characterized by comprising:

[0010] Receive the first message;

[0011] In response to receiving the first message, a second message is transmitted via the target wireless bearer; wherein the second message includes at least a portion of the target measurement information in the first storage unit;

[0012] The candidate target radio bearer includes at least a first candidate and a second candidate; the second candidate is different from the first candidate; the first candidate is an SRB, and the identifier of the first candidate is Q1;

[0013] Wherein, Q1 is 4, or Q1 is an integer greater than 5.

[0014] The above method is for the transmission of measurement information in the first storage unit. The candidates for the target wireless bearer include at least a first candidate and a second candidate, which improves the flexibility of the transmission of measurement information in the first storage unit.

[0015] According to one aspect of this application, it is characterized by comprising:

[0016] Receive third message;

[0017] Whether the target wireless bearer is the first candidate or the second candidate depends on the third message.

[0018] When the candidates for the target radio bearer include at least a first candidate and a second candidate, determining the target radio bearer is a problem that needs to be solved. The above method solves this problem by relying on the received third message to determine whether the target radio bearer is the first candidate or the second candidate, which is beneficial for network control and mutual understanding between the UE and the network.

[0019] According to one aspect of this application, the target wireless bearer being the first candidate or the second candidate depends on whether the second message includes measurement information in the second storage unit; the first storage unit and the second storage unit are different.

[0020] When the candidates for the target wireless bearer include at least a first candidate and a second candidate, determining the target wireless bearer is a problem that needs to be solved. The above method solves this problem by relying on whether the second message includes measurement information in the second storage unit to determine whether the target wireless bearer is the first candidate or the second candidate. This helps to improve data transmission efficiency and reduce the impact on the transmission of data in the second storage unit.

[0021] According to one aspect of this application, the characteristic that whether the target radio bearer is the first candidate or the second candidate depends on whether the first candidate is supported.

[0022] When the candidates for the target radio bearer include at least a first candidate and a second candidate, determining the target radio bearer is a problem that needs to be solved. The above method solves this problem by relying on whether the first candidate is supported to determine whether the target radio bearer is the first candidate or the second candidate. This is beneficial for sending a second message through the second candidate when the first candidate is not supported, thus avoiding the situation where the second message cannot be sent.

[0023] According to one aspect of this application, it is characterized by comprising:

[0024] Receive a fourth message; wherein the fourth message includes a first measurement configuration;

[0025] The target measurement information is stored in the first storage unit;

[0026] The storage of the target measurement information in the first storage unit depends on the first measurement configuration.

[0027] According to one aspect of this application, the priority of the second candidate is different from that of the first candidate.

[0028] The above method is beneficial for adjusting the priority of target measurement information transmission.

[0029] As a non-limiting embodiment, the above method takes into account the differences in priority of different measurement information and adaptively selects the SRB for sending the target measurement information according to the priority of the target measurement information. For example, when the priority of the target measurement information is low, the SRB with lower priority is selected to send the second message, and when the priority of the target measurement information is high, the SRB with higher priority is selected to send the second message, thereby balancing the transmission of the target measurement information and the transmission of other signaling or data.

[0030] According to one aspect of this application, the first candidate is used for MCG (Master Cell Group) and the second candidate is used for SCG (Secondary Cell Group).

[0031] The above method is beneficial for adjusting the priority of target measurement information transmission.

[0032] The above method avoids affecting the transmission of MCG by utilizing SCG.

[0033] According to one aspect of this application, it is characterized by comprising:

[0034] In response to the sending of the second message, at least one candidate measurement information in the first storage unit is deleted; wherein the second message includes at least a portion of each of the at least one candidate measurement information in the first storage unit;

[0035] The first storage unit stores multiple candidate measurement information, including at least one candidate measurement information, which in turn includes the target measurement information.

[0036] The above method takes into account the large size of AI / ML training data. After the second message is sent, only the candidate measurement information sent in the first storage unit is deleted, which helps to free up the storage space of the first storage unit and reduce unnecessary reporting and signaling overhead.

[0037] This application discloses a method used in a second node for wireless communication, characterized by comprising:

[0038] Send the first message;

[0039] In response to sending the first message, a second message is received via the target wireless bearer; wherein the second message includes at least a portion of the target measurement information in the first storage unit;

[0040] The candidate target radio bearer includes at least a first candidate and a second candidate; the second candidate is different from the first candidate; the first candidate is an SRB, and the identifier of the first candidate is Q1;

[0041] Wherein, Q1 is 4, or Q1 is an integer greater than 5.

[0042] According to one aspect of this application, it is characterized by comprising:

[0043] Send a third message;

[0044] Whether the target wireless bearer is the first candidate or the second candidate depends on the third message.

[0045] According to one aspect of this application, the target wireless bearer being the first candidate or the second candidate depends on whether the second message includes measurement information in the second storage unit; the first storage unit and the second storage unit are different.

[0046] According to one aspect of this application, the characteristic that whether the target radio bearer is the first candidate or the second candidate depends on whether the first candidate is supported.

[0047] According to one aspect of this application, it is characterized by comprising:

[0048] Send a fourth message; wherein the fourth message includes the first measurement configuration;

[0049] The recipient of the first message stores the target measurement information in the first storage unit; the storage of the target measurement information in the first storage unit depends on the first measurement configuration.

[0050] According to one aspect of this application, the priority of the second candidate is different from that of the first candidate.

[0051] According to one aspect of this application, the first candidate is used for MCG, and the second candidate is used for SCG.

[0052] According to one aspect of this application, it is characterized by comprising:

[0053] In response to the receipt of the second message, at least one of training or inference is performed based on at least a portion of the target measurement information.

[0054] This application discloses a first node used for wireless communication, characterized in that it comprises:

[0055] The first receiver receives the first message;

[0056] In response to receiving the first message, the first transmitter transmits a second message via a target wireless bearer; wherein the second message includes at least a portion of the target measurement information stored in the first storage unit.

[0057] The candidate target radio bearer includes at least a first candidate and a second candidate; the second candidate is different from the first candidate; the first candidate is an SRB, and the identifier of the first candidate is Q1;

[0058] Wherein, Q1 is 4, or Q1 is an integer greater than 5.

[0059] This application discloses a second node used for wireless communication, characterized in that it comprises:

[0060] The second transmitter sends the first message;

[0061] A second receiver, in response to sending the first message, receives a second message via a target radio bearer; wherein the second message includes at least a portion of the target measurement information in the first storage unit;

[0062] The candidate target radio bearer includes at least a first candidate and a second candidate; the second candidate is different from the first candidate; the first candidate is an SRB, and the identifier of the first candidate is Q1;

[0063] Wherein, Q1 is 4, or Q1 is an integer greater than 5. Attached Figure Description

[0064] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0065] Figure 1 shows a flowchart of a first node according to an embodiment of this application;

[0066] Figure 2 shows a schematic diagram of a network architecture according to an embodiment of this application;

[0067] Figure 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for the user plane and control plane according to an embodiment of this application;

[0068] Figure 4 shows a schematic diagram of a first communication device and a second communication device according to an embodiment of this application;

[0069] Figure 5 shows a flowchart of wireless signal transmission according to an embodiment of this application;

[0070] Figure 6 illustrates whether the target wireless bearer is a first candidate or a second candidate according to an embodiment of this application;

[0071] Figure 7 illustrates whether the target wireless bearer is a first candidate or a second candidate according to another embodiment of this application;

[0072] Figure 8 shows a flowchart of a first node according to an embodiment of this application;

[0073] Figure 9 illustrates a schematic diagram of the priorities of a second candidate and a first candidate according to an embodiment of this application;

[0074] Figure 10 shows a schematic diagram of a first candidate being used for MCG and a second candidate being used for SCG according to an embodiment of this application;

[0075] Figure 11 shows a schematic diagram of a first storage unit storing multiple candidate measurement information according to an embodiment of this application;

[0076] Figure 12 shows a structural block diagram of a processing apparatus for a first node according to an embodiment of the present application;

[0077] Figure 13 shows a structural block diagram of a processing apparatus for a second node according to an embodiment of this application;

[0078] Figure 14 shows a flowchart of a second node according to an embodiment of this application;

[0079] Figure 15 shows a schematic diagram of an AI / ML model according to an embodiment of this application;

[0080] Figure 16 illustrates a flowchart based on artificial intelligence or machine learning according to an embodiment of this application;

[0081] Figure 17 illustrates a schematic diagram of the deployment of intelligent functions in a RAN domain according to an embodiment of this application;

[0082] Figure 18 shows a schematic diagram of UE smart function deployment according to an embodiment of this application;

[0083] Figure 19 shows a schematic diagram of the processing of target measurement information according to an embodiment of this application. Detailed Implementation

[0084] The technical solution of this application will be further described in detail below with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other.

[0085] Example 1

[0086] Example 1 illustrates a flowchart of a first node according to an embodiment of this application, as shown in Figure 1. In Figure 1, each box represents a step, and it is particularly important to emphasize that the order of the boxes in the figure does not represent the temporal sequence of the steps represented.

[0087] In Embodiment 1, the first node in this application receives a first message in step 101; in step 102, in response to receiving the first message, it sends a second message through a target radio bearer; wherein the second message includes at least a portion of the target measurement information in the first storage unit; wherein the candidates for the target radio bearer include at least a first candidate and a second candidate; the second candidate is different from the first candidate; the first candidate is an SRB, and the identifier of the first candidate is Q1; wherein Q1 is 4, or Q1 is an integer greater than 5.

[0088] As an example, the first message is a MAC (Medium Access Control) CE (Control Element).

[0089] As an example, the first message is a DCI (Downlink Control Information).

[0090] As an example, the first message is an RRC message.

[0091] As one embodiment, the first message includes a first information block.

[0092] As one embodiment, the second message includes at least a portion of the target measurement information in the first storage unit that depends on the first message including the first information block.

[0093] As an example, in response to receiving the first message and the first message including the first information block, the second message includes at least a portion of the target measurement information in the first storage unit.

[0094] As an example, when the first message includes the first information block, the second message includes at least a portion of the target measurement information in the first storage unit.

[0095] As an example, provided that the first message includes the first information block, the second message includes at least a portion of the target measurement information in the first storage unit.

[0096] As an example, the name of the first information block includes Req, and the value of the first information block is true.

[0097] As an example, the first information block is a code point, and the code point is set to true.

[0098] As an example, the first information block is a bit, and the bit is set to 1.

[0099] As an example, the first information block is a bit in a bitmap, and the bit is set to 1.

[0100] As an example, each bit in the bitmap corresponds to a measurement configuration.

[0101] As an example, each bit in the bitmap corresponds to a measurement identifier.

[0102] As an example, each bit in the bitmap corresponds to a measurement object.

[0103] As an example, each bit in the bitmap corresponds to an AI / ML model.

[0104] As an example, one bit in the bitmap corresponds to the target measurement information.

[0105] As an example, the second message is an RRC message.

[0106] As one embodiment, the second message is used to provide at least one of training data or inference data to the second node N02.

[0107] As an example, an RRC container in the second message includes at least a portion of the target measurement information in the first storage unit.

[0108] As an example, at least one RRC IE in the second message includes at least a portion of the target measurement information in the first storage unit.

[0109] As an example, at least one RRC field in the second message includes at least a portion of the target measurement information in the first storage unit.

[0110] As an example, the at least part of the target measurement information is the entirety of the target measurement information.

[0111] As an example, the at least part of the target measurement information is a portion of the target measurement information.

[0112] As an example, at least a portion of the target measurement information is used by the second node N02 to perform at least one of training or inference of an AI / ML model.

[0113] As an example, at least a portion of the target measurement information is used by the second node N02 for reinforcement learning.

[0114] As an example, the first message is a request message, and the second message is a response message.

[0115] As an example, the first message is a UEInformationRequest message, and the second message is a UEInformationResponse message.

[0116] As an example, the first message belongs to a UEInformationRequest message, and the second message belongs to a UEInformationResponse message.

[0117] As an example, when the first message is set, the first storage unit stores the target measurement information.

[0118] As an example, the target measurement information includes L1 measurement results of at least one cell to be measured.

[0119] As an example, the target measurement information includes L3 measurement results of at least one cell to be measured.

[0120] As an example, the target measurement information includes measurement results for at least one SSB (Synchronization Signal Block).

[0121] As an example, the target measurement information includes measurement results for at least one CSI-RS (Channel State Information Reference Signal).

[0122] As an example, the target measurement information includes a reason, which indicates why the target measurement information is stored in the first storage unit.

[0123] The above method helps the network understand why the target measurement information is stored, and makes more effective use of the target measurement information, thereby improving training efficiency.

[0124] As an example, the stated cause is one of a plurality of candidate causes.

[0125] As an example, one of the candidate causes includes a wireless link problem.

[0126] As an example, the radio link problem includes RLF (Radio Link Failure).

[0127] As an example, the wireless link problem includes HOF (Handover Failure).

[0128] As one example, the wireless link problem includes T310 reaching a threshold.

[0129] As one example, the wireless link problem includes T312 reaching a threshold.

[0130] As an example, the wireless link problem includes a performance metric monitored by the first node reaching a threshold.

[0131] As an example, one of the plurality of candidate reasons includes a cache state that depends on the first storage unit.

[0132] As a sub-example of the above embodiment, one of the candidate reasons is that the cache of the first storage unit is less than a threshold.

[0133] As an example, one of the multiple candidate reasons depends on the number of switching attempts.

[0134] As a sub-example of the above embodiment, one of the candidate reasons is that the number of switching times reaches a threshold.

[0135] As one embodiment, the target measurement information includes the time during which the target measurement information is stored in the first storage unit.

[0136] As one embodiment, the first storage unit stores a first identifier; wherein the first identifier is associated with at least one cell, the at least one cell including at least one current serving cell.

[0137] As one embodiment, the target measurement information is stored in the first storage unit, and the first identifier is also stored in the first storage unit.

[0138] As one embodiment, the target measurement information includes the first identifier.

[0139] As an example, the at least one cell to be measured is associated with the first identifier.

[0140] As one embodiment, the first measurement configuration includes the first identifier.

[0141] As one embodiment, the target measurement information includes the first identifier.

[0142] As an example, the first identifier is configured for the at least one cell.

[0143] As an example, the at least one cell is the current at least one serving cell.

[0144] As an example, the at least one cell includes the current at least one serving cell and the current at least one neighboring cell.

[0145] As an example, the at least one cell includes the current at least one serving cell and the current at least one candidate cell.

[0146] As an example, the first identifier is a logical identifier.

[0147] As an example, the first identifier is a physical identifier.

[0148] As an example, the first identifier is a configuration identifier.

[0149] As an example, the first identifier is a measurement identifier.

[0150] As an example, the first identifier is an assimilated ID.

[0151] As an example, the first identifier is a measurement report identifier.

[0152] As an example, the second node in this application uses at least one identical AI / ML model for the at least one cell.

[0153] As an example, the second node in this application uses at least one of the same AI / ML functions for the at least one cell.

[0154] As an example, the second node in this application uses at least partially the same AI / ML training data for the at least one cell.

[0155] As an example, the at least one serving cell belongs to the current MCG.

[0156] As an example, the current at least one serving cell is the current PCell (Primary Cell).

[0157] As an example, the at least one serving cell currently belongs to the current SCG.

[0158] As an example, the current at least one serving cell is the current PSCell (Primary SCG Cell).

[0159] As an example, the current at least one serving cell and the previous at least one serving cell are both associated with the first identifier.

[0160] As one embodiment, the second message including at least a portion of the target measurement information in the first storage unit includes setting at least one field in the second message as the at least portion of the target measurement information in the first storage unit.

[0161] As one embodiment, the second message includes a portion of the target measurement information in the first storage unit.

[0162] As one embodiment, the second message includes all of the target measurement information in the first storage unit.

[0163] As one embodiment, the target measurement information in the first storage unit is used for at least one of network-side training or inference.

[0164] As an example, the first storage unit is a UE variable, and the first storage unit is represented by ASN.1.

[0165] As an example, the first storage unit is a UE variable of an RRC sublayer.

[0166] As an example, the first storage unit is a UE variable of the protocol layer above an RRC sublayer.

[0167] As an example, the first storage unit is an AS (Access Stratum) buffer.

[0168] As one embodiment, the first storage unit is a NAS (Non-Access Stratum) buffer.

[0169] As one embodiment, the first storage unit is a memory.

[0170] As one embodiment, the first storage unit is a register.

[0171] As one example, the first storage unit is implemented in software.

[0172] As one example, the first storage unit is implemented in hardware.

[0173] As one embodiment, the first storage unit is readable and writable.

[0174] As one embodiment, the first storage unit is erasable.

[0175] As one embodiment, the first storage unit is used to store at least one of training data or inference data.

[0176] As an example, the first storage unit is used to store at least one of the training data or inference data for the network-side model.

[0177] As an example, the at least first candidate and the second candidate are at least three candidates, and the at least three candidates include the first candidate and the second candidate.

[0178] As an example, the at least first candidate and the second candidate are the first candidate and the second candidate.

[0179] As an example, any one of the first and second candidates is used for the reporting of the target measurement information.

[0180] As an example, any one of the at least first candidate and second candidate is used to provide at least one of training data or inference data for the network-side model.

[0181] As an example, any one of the first candidate and the second candidate is used for reporting the measurement information in the first storage unit.

[0182] As an example, the first candidate is used only for MCG.

[0183] As an example, the first candidate is used only for SCG.

[0184] As an example, the first candidate supports split SRBs.

[0185] As an example, the first candidate does not support split SRBs.

[0186] As an example, the first candidate was used for MCG, and the second candidate was used for SCG.

[0187] As an example, the first candidate was used for SCG, and the second candidate was used for MCG.

[0188] As an example, both the first candidate and the second candidate are used in MCG.

[0189] As an example, the identifier of the first candidate is indicated by an srb-Identity field.

[0190] As an example, the identifier of the first candidate is indicated by an SRB-Identity IE.

[0191] As an example, the identifier of the first candidate is indicated by an SRB-Identity-v1700 field; wherein, Q1 is 4.

[0192] As an example, the identifier of the first candidate is indicated by an SRB-Identity-v1900 field; wherein, Q1 is an integer greater than 5.

[0193] As an example, the first candidate can only be configured by the network after AS security activation.

[0194] As an example, the first candidate can only be configured by the MN after AS security activation.

[0195] As an example, the first candidate can only be configured by the SN after AS security activation.

[0196] As an example, the identifier of the second candidate is indicated by an srb-Identity field.

[0197] As an example, the identifier of the second candidate is indicated by an SRB-Identity IE.

[0198] As an example, the identifier of the second candidate is indicated by an SRB-Identity field; wherein, Q2 is an integer less than 4.

[0199] As an example, the identifier of the second candidate is indicated by an SRB-Identity-v1800 field; wherein, Q2 is 5.

[0200] As an example, the identifier of the second candidate is indicated by an SRB-Identity-v1900 field; wherein, Q2 is an integer greater than 5.

[0201] As an example, the difference between the second candidate and the first candidate is that the second candidate is not the first candidate.

[0202] As an example, the difference between the second candidate and the first candidate means that the type of the second candidate is different from the type of the first candidate.

[0203] As an example, the difference between the second candidate and the first candidate is that the second candidate is a DRB (Data Radio Bearer).

[0204] As a sub-implementation of the above embodiments, the identifier of the second candidate is pre-configured.

[0205] As a sub-implementation of the above embodiments, the identifier of the second candidate is a positive integer.

[0206] As a sub-implementation of the above embodiments, the identifier of the second candidate is a non-negative integer.

[0207] As an example, the difference between the second candidate and the first candidate is that the second candidate is an SRB; the identifier of the second candidate is Q2, where Q2 is a positive integer, and Q2 is not equal to Q1.

[0208] As a sub-implementation of the above embodiments, the identifier of the second candidate and the identifier of the first candidate are predefined.

[0209] As a sub-implementation of the above embodiments, the identifier of the second candidate and the identifier of the first candidate are pre-configured.

[0210] As a sub-example of the above embodiment, Q1 is 4, and Q2 is less than 4.

[0211] As a sub-implementation of the above embodiment, Q1 is 4 and Q2 is 1.

[0212] As a sub-example of the above embodiment, Q1 is 4 and Q2 is 2.

[0213] As a sub-example of the above embodiment, Q1 is 4 and Q2 is 3.

[0214] As a sub-example of the above embodiment, Q1 is 4, and Q2 is greater than 4.

[0215] As a sub-example of the above embodiment, Q1 is 4 and Q2 is 5.

[0216] As a sub-example of the above embodiment, Q1 is 4 and Q2 is 6.

[0217] As a sub-example of the above embodiment, Q1 is 4 and Q2 is 7.

[0218] As a sub-example of the above embodiment, Q1 is greater than 5, and Q2 is less than 5.

[0219] As a sub-example of the above embodiment, Q1 is greater than 5, and Q2 is less than Q1.

[0220] As a sub-example of the above embodiment, Q1 is greater than 5, and Q2 is greater than Q1.

[0221] As a sub-example of the above embodiment, Q1 is 6 or 7, and Q2 is 1.

[0222] As a sub-example of the above embodiment, Q1 is 6 or 7, and Q2 is 2.

[0223] As a sub-example of the above embodiment, Q1 is 6 or 7, and Q2 is 3.

[0224] As a sub-example of the above embodiment, Q1 is 6 or 7, and Q2 is 5.

[0225] As a sub-example of the above embodiment, Q1 is 6 and Q2 is 7.

[0226] As a sub-example of the above embodiment, Q1 is 7 and Q2 is 8.

[0227] As an example, the identifier of the first candidate is Q1, which means that the first candidate is SRBQ1.

[0228] As an example, the identifier of the first candidate is Q1, which can be replaced with: the first candidate is SRBQ1.

[0229] As an example, the identifier of the second candidate is Q2, which means that the second candidate is SRBQ2.

[0230] As an example, the identifier of the second candidate, Q2, can be replaced with: the second candidate is SRBQ2.

[0231] As an example, the second message is triggered by the first message and used to determine that the target radio bearer is the first candidate; the second candidate is different from the first candidate in that: the second candidate is an SRB; the identifier of the second candidate is Q2, where Q2 is a positive integer and Q2 is less than Q1.

[0232] As a sub-implementation of the above embodiments, if the second message is triggered by the first event, the target wireless bearer is the second candidate.

[0233] As a sub-implementation of the above embodiments, the above method determines the target wireless bearer based on the triggering method of the second message.

[0234] As an example, the first candidate is not supported, and measurements of the measurement information stored in the first storage unit are supported.

[0235] As an example, the first candidate is not supported, and measurements of the measurement information stored in the first storage unit are not supported.

[0236] As an example, the first candidate is supported, and measurements of the measurement information stored in the first storage unit are supported.

[0237] Example 2

[0238] Example 2 illustrates a schematic diagram of a network architecture according to an embodiment of this application, as shown in Figure 2. Figure 2 illustrates network architecture 200. The network architecture 200 is a 5G NR (New Radio) / LTE (Long-Term Evolution) / LTE-A (Long-Term Evolution Advanced) system, or a 5G+ network architecture, or a 6G network architecture, or a future 3GPP network architecture; the network architecture 200 may be referred to as 5GS (5G System) / EPS (Evolved Packet System), or 6GS (6G System); the network architecture 200 includes at least one of UE (User Equipment) 201, RAN (Radio Access Network) 202, core network 210, HSS (Home Subscriber Server) / UDM (Unified Data Management) 220, and Internet service 230. The network architecture 200 can interconnect with other access networks, but these entities / interfaces are not shown for simplicity. As shown, the network architecture 200 provides packet-switched services; however, those skilled in the art will readily understand that the various concepts presented throughout this application can be extended to networks providing circuit-switched services or other cellular networks. The RAN includes node 203 and other nodes 204. Node 203 provides user and control plane protocol termination toward UE 201. Node 203 can be connected to other nodes 204 via an Xn interface (e.g., backhaul) / X2 interface. Node 203 may also be referred to as a base station, base transceiver station, radio base station, radio transceiver, transceiver function, basic service set (BSS), extended service set (ESS), TRP (transmitter-receiver node), or some other suitable term. The core network 210 is a 5GC (5G Core Network) / EPC (Evolved Packet Core), or the core network 210 is a 6GC; node 203 provides UE 201 with an access point to the core network 210.Examples of UE201 include cellular phones, smartphones, Session Initiation Protocol (SIP) phones, laptops, personal digital assistants (PDAs), satellite radios, non-terrestrial base station communications, satellite mobile communications, global positioning systems, multimedia devices, video devices, digital audio players (e.g., MP3 players), cameras, game consoles, drones, aircraft, narrowband IoT devices, machine-type communication devices, land vehicles, automobiles, wearable devices, or any other similar functional devices. Those skilled in the art may also refer to UE201 as a mobile station, subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handheld device, user agent, mobile client, client, or any other suitable term. Node 203 is connected to the core network 210 via an S1 / NG interface. The core network 210 includes an MME (Mobility Management Entity) / AMF (Authentication Management Field) / SMF (Session Management Function) 211, other MMEs / AMFs / SMFs 214, an S-GW (Service Gateway) / UPF (User Plane Function) 212, and a P-GW (Packet Data Network Gateway) / UPF 213. The MME / AMF / SMF 211 is the control node that handles signaling between the UE 201 and the core network 210. Generally, the MME / AMF / SMF 211 provides bearer and connection management. All user IP (Internet Protocol) packets are transmitted through the S-GW / UPF 212, which is itself connected to the P-GW / UPF 213. The P-GW provides UE IP address allocation and other functions. The P-GW / UPF 213 is connected to the Internet service 230. Internet services 230 include operator-compliant Internet protocol services, which may specifically include the Internet, intranets, IMS (IP Multimedia Subsystem), and packet-switched streaming services.

[0239] As an example, the UE201 corresponds to the first node in this application.

[0240] As an example, the first node in this application includes the UE201.

[0241] As an example, the UE201 is a user equipment (UE).

[0242] As an example, the UE201 is a relay device.

[0243] As an example, the UE201 is a gateway device.

[0244] As an example, the UE201 supports AI / ML.

[0245] As an example, the UE201 supports 5G.

[0246] As an example, the UE201 supports 6G.

[0247] As an example, node 203 corresponds to the second node in this application.

[0248] As an example, the second node in this application includes node 203.

[0249] As an example, the second node in this application includes not only the node 203, but also at least one higher-level device; the higher-level device includes at least one of a core network device, an OTT (over the top) server, or an OAM device.

[0250] The above sub-examples facilitate the flexible deployment of AI models on network devices, and are particularly suitable for scenarios such as positioning.

[0251] As one embodiment, the at least one higher-level device has an intelligent module.

[0252] As an example, the at least one higher-level device supports AI / ML models.

[0253] As an example, the at least one higher-level device has at least one of inference function, training function, or reinforcement learning function.

[0254] As an example, the second node in this application includes the node 203 and the core network 210.

[0255] As an example, the second node in this application includes the node 203 and the core network 214.

[0256] As an example, UE201 is the first node in this application, and node 203 corresponds to the second node in this application.

[0257] As an example, node 203 is a base station device.

[0258] As an example, node 203 is a gNB.

[0259] As an example, node 203 is a macrocell base station.

[0260] As an example, node 203 is a microcell base station.

[0261] As an example, node 203 is a PicoCell base station.

[0262] As an example, node 203 is a femtocell.

[0263] As an example, node 203 is a base station device that supports large latency differences.

[0264] As an example, node 203 is a flight platform device.

[0265] As one example, node 203 is a satellite device.

[0266] Example 3

[0267] Example 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for a user plane and control plane according to this application, as shown in Figure 3. Figure 3 is a schematic diagram illustrating an embodiment of a radio protocol architecture for a user plane 350 and a control plane 300. Figure 3 shows the radio protocol architecture for the control plane 300 in three layers: Layer 1, Layer 2, and Layer 3. Layer 1 (L1 layer) is the lowest layer and implements various PHY (Physical Layer) signal processing functions. The L1 layer will be referred to herein as PHY 301. Layer 2 (L2 layer) 305 is above PHY 301 and includes a MAC (Medium Access Control) sublayer 302, an RLC (Radio Link Control) sublayer 303, and a PDCP (Packet Data Convergence Protocol) sublayer 304. The PDCP sublayer 304 provides multiplexing between different radio bearers and logical channels. The PDCP sublayer 304 also provides security through encrypted data packets and provides cross-area mobility support. RLC sublayer 303 provides upper-layer packet segmentation and reassembly, retransmission of lost packets, and packet reordering to compensate for out-of-order reception caused by HARQ (Hybrid Automatic Repeat Request). MAC sublayer 302 provides multiplexing between the logical and transport channels. MAC sublayer 302 is also responsible for allocating various radio resources (e.g., resource blocks) within a cell. MAC sublayer 302 is also responsible for HARQ operations. RRC (Radio Resource Control) sublayer 306 in Layer 3 (L3) of the control plane 300 is responsible for acquiring radio resources (i.e., radio bearers) and using RRC signaling to configure the lower layers. The radio protocol architecture of user plane 350 includes Layer 1 (L1 layer) and Layer 2 (L2 layer). In user plane 350, the radio protocol architecture for physical layer 351, PDCP sublayer 354 in L2 layer 355, RLC sublayer 353 in L2 layer 355, and MAC sublayer 352 in L2 layer 355 is largely the same as the corresponding layers and sublayers in control plane 300. However, PDCP sublayer 354 also provides header compression for upper layer packets to reduce radio transmission overhead. L2 layer 355 in user plane 350 also includes SDAP (Service Data Adaptation Protocol) sublayer 356. SDAP sublayer 356 is responsible for mapping between QoS streams and data radio bearers (DRBs) to support service diversity.

[0268] As an example, the wireless protocol architecture in Figure 3 is applicable to the first node in this application.

[0269] As an example, the wireless protocol architecture in Figure 3 is applicable to the second node in this application.

[0270] As an example, the first message in this application is generated in the RRC306.

[0271] As an example, the first message in this application is generated by MAC302 or MAC352.

[0272] As an example, the first message in this application is generated by the PHY301 or PHY351.

[0273] As an example, the second message in this application is generated in the RRC306.

[0274] As an example, the third message in this application is generated in the RRC306.

[0275] As an example, the third message in this application is generated by MAC302 or MAC352.

[0276] As an example, the third message in this application is generated in PHY301 or PHY351.

[0277] As an example, the fourth message in this application is generated in the RRC306.

[0278] Example 4

[0279] Embodiment 4 illustrates a schematic diagram of a first communication device and a second communication device according to this application, as shown in Figure 4. Figure 4 is a block diagram of a first communication device 450 and a second communication device 410 communicating with each other in an access network.

[0280] The first communication device 450 includes a controller / processor 459, a memory 460, a data source 467, a transmitting processor 468, a receiving processor 456, a multi-antenna transmitting processor 457, a multi-antenna receiving processor 458, a transmitter / receiver 454, and an antenna 452.

[0281] The second communication device 410 includes a controller / processor 475, a memory 476, a receiver processor 470, a transmitter processor 416, a multi-antenna receiver processor 472, a multi-antenna transmitter processor 471, a transmitter / receiver 418, and an antenna 420.

[0282] In the transmission from the second communication device 410 to the first communication device 450, at the second communication device 410, upper-layer data packets from the core network are provided to the controller / processor 475. The controller / processor 475 implements L2 layer functionality. In the transmission from the second communication device 410 to the first communication device 450, the controller / processor 475 provides header compression, encryption, packet segmentation and reordering, multiplexing between logical and transport channels, and radio resource allocation to the first communication device 450 based on various priority metrics. The controller / processor 475 is also responsible for retransmitting lost packets and signaling to the first communication device 450. The transmit processor 416 and the multi-antenna transmit processor 471 implement various signal processing functions for the L1 layer (i.e., the physical layer). Transmit processor 416 performs encoding and interleaving to facilitate forward error correction (FEC) at the second communication device 410, and mapping of signal clusters based on various modulation schemes (e.g., Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying (QPSK), M-Phase Shift Keying (M-PSK), M-QAM). Multi-antenna transmit processor 471 performs digital spatial precoding on the encoded and modulated symbols, including codebook-based and non-codebook-based precoding, and beamforming processing, generating one or more spatial streams. Transmit processor 416 then maps each spatial stream to subcarriers, multiplexes it with a reference signal (e.g., a pilot) in the time and / or frequency domains, and subsequently uses inverse fast Fourier transform (IFFT) to generate a physical channel carrying the time-domain multicarrier symbol stream. Multi-antenna transmit processor 471 then performs transmit analog precoding / beamforming operations on the time-domain multicarrier symbol stream. Each transmitter 418 converts the baseband multicarrier symbol stream provided by the multi-antenna transmitter processor 471 into an radio frequency stream, which is then provided to different antennas 420.

[0283] In the transmission from the second communication device 410 to the first communication device 450, at the first communication device 450, each receiver 454 receives a signal through its corresponding antenna 452. Each receiver 454 recovers the information modulated onto the radio frequency carrier and converts the radio frequency stream into a baseband multicarrier symbol stream, which is then provided to the receiver processor 456. The receiver processor 456 and the multi-antenna receiver processor 458 implement various signal processing functions of the L1 layer. The multi-antenna receiver processor 458 performs receive analog precoding / beamforming operations on the baseband multicarrier symbol stream from the receiver 454. The receiver processor 456 uses a Fast Fourier Transform (FFT) to convert the baseband multicarrier symbol stream after the receive analog precoding / beamforming operations from the time domain to the frequency domain. In the frequency domain, the physical layer data signal and the reference signal are demultiplexed by the receiver processor 456, where the reference signal is used for channel estimation, and the data signal is recovered in the multi-antenna receiver processor 458 after multi-antenna detection to recover any spatial stream destined for the first communication device 450. Symbols on each spatial stream are demodulated and recovered in the receive processor 456, generating soft decisions. The receive processor 456 then decodes and deinterleaves the soft decisions to recover the upper-layer data and control signals transmitted by the second communication device 410 over the physical channel. The upper-layer data and control signals are then provided to the controller / processor 459. The controller / processor 459 implements the functions of Layer 2. The controller / processor 459 may be associated with a memory 460 storing program code and data. The memory 460 may be referred to as computer-readable media. In the transmission from the second communication device 410 to the first communication device 450, the controller / processor 459 provides multiplexing, packet reassembly, decryption, header decompression, and control signal processing between the transport and logical channels to recover upper-layer data packets from the core network. The upper-layer data packets are then provided to all protocol layers above Layer 2. Various control signals may also be provided to Layer 3 for Layer 3 processing.

[0284] In the transmission from the first communication device 450 to the second communication device 410, at the first communication device 450, a data source 467 is used to provide upper-layer data packets to the controller / processor 459. The data source 467 represents all protocol layers above the L2 layer. Similar to the transmission functions at the second communication device 410 described in the transmission from the second communication device 410 to the first communication device 450, the controller / processor 459 implements header compression, encryption, packet segmentation and reordering, and multiplexing between logical and transport channels based on radio resource allocation, implementing L2 layer functions for the user plane and control plane. The controller / processor 459 is also responsible for retransmitting lost packets and signaling to the second communication device 410. Transmit processor 468 performs modulation mapping and channel coding processing, while multi-antenna transmit processor 457 performs digital multi-antenna spatial precoding, including codebook-based and non-codebook-based precoding, and beamforming processing. Subsequently, transmit processor 468 modulates the generated spatial stream into a multi-carrier / single-carrier symbol stream. After analog precoding / beamforming operations in multi-antenna transmit processor 457, the stream is provided to different antennas 452 via transmitter 454. Each transmitter 454 first converts the baseband symbol stream provided by multi-antenna transmit processor 457 into a radio frequency symbol stream before providing it to antenna 452.

[0285] In the transmission from the first communication device 450 to the second communication device 410, the function at the second communication device 410 is similar to the receiving function at the first communication device 450 described in the transmission from the second communication device 410 to the first communication device 450. Each receiver 418 receives radio frequency signals through its corresponding antenna 420, converts the received radio frequency signals into baseband signals, and provides the baseband signals to the multi-antenna receiving processor 472 and the receiving processor 470. The receiving processor 470 and the multi-antenna receiving processor 472 jointly implement the L1 layer functions. The controller / processor 475 implements the L2 layer functions. The controller / processor 475 may be associated with a memory 476 that stores program code and data. The memory 476 may be referred to as computer-readable media. In the transmission from the first communication device 450 to the second communication device 410, the controller / processor 475 provides multiplexing between the transmission and logical channels, packet reassembly, decryption, header decompression, and control signal processing to recover upper-layer data packets from the UE 450. Upper-layer packets from the controller / processor 475 can be provided to the core network.

[0286] As one embodiment, the first communication device 450 includes: at least one processor and at least one memory, the at least one memory including computer program code; the at least one memory and the computer program code are configured to be used with the at least one processor, and the first communication device 450 at least: receives a first message; and in response to receiving the first message, transmits a second message via a target radio bearer; wherein the second message includes at least a portion of target measurement information in a first storage unit; wherein the candidates for the target radio bearer include at least a first candidate and a second candidate; the second candidate is different from the first candidate; the first candidate is an SRB, and the identifier of the first candidate is Q1; wherein Q1 is 4, or, Q1 is an integer greater than 5.

[0287] As one embodiment, the first communication device 450 includes: a memory storing a computer-readable instruction program that, when executed by at least one processor, produces actions including: receiving a first message; and, in response to receiving the first message, transmitting a second message via a target radio bearer; wherein the second message includes at least a portion of target measurement information in a first storage unit; wherein the candidates for the target radio bearer include at least a first candidate and a second candidate; the second candidate is different from the first candidate; the first candidate is an SRB, and the identifier of the first candidate is Q1; wherein Q1 is 4, or Q1 is an integer greater than 5.

[0288] As one embodiment, the second communication device 410 includes: at least one processor and at least one memory, the at least one memory including computer program code; the at least one memory and the computer program code are configured to be used with the at least one processor. The second communication device 410 at least: transmits a first message; and, in response to transmitting the first message, receives a second message via a target radio bearer; wherein the second message includes at least a portion of target measurement information in a first storage unit; wherein the candidates for the target radio bearer include at least a first candidate and a second candidate; the second candidate is different from the first candidate; the first candidate is an SRB, and the identifier of the first candidate is Q1; wherein Q1 is 4, or, Q1 is an integer greater than 5.

[0289] As one embodiment, the second communication device 410 includes: a memory storing a computer-readable instruction program that, when executed by at least one processor, produces actions including: sending a first message; and receiving a second message via a target radio bearer in response to sending the first message; wherein the second message includes at least a portion of target measurement information in a first storage unit; wherein the candidates for the target radio bearer include at least a first candidate and a second candidate; the second candidate is different from the first candidate; the first candidate is an SRB, and the identifier of the first candidate is Q1; wherein Q1 is 4, or Q1 is an integer greater than 5.

[0290] As one embodiment, at least one of the antenna 452, the receiver 454, the receiving processor 456, and the controller / processor 459 is used to receive the first message; at least one of the antenna 420, the transmitter 418, the transmitting processor 416, and the controller / processor 475 is used to transmit the first message.

[0291] As one embodiment, at least one of the antenna 452, the transmitter 454, the transmitter processor 468, and the controller / processor 459 is used to transmit a second message; at least one of the antenna 420, the receiver 418, the receiver processor 470, and the controller / processor 475 is used to receive the second message.

[0292] As one embodiment, at least one of the antenna 452, the receiver 454, the receiving processor 456, and the controller / processor 459 is used to receive a third message; at least one of the antenna 420, the transmitter 418, the transmitting processor 416, and the controller / processor 475 is used to transmit a third message.

[0293] As one embodiment, at least one of the antenna 452, the receiver 454, the receiving processor 456, and the controller / processor 459 is used to receive the fourth message; at least one of the antenna 420, the transmitter 418, the transmitting processor 416, and the controller / processor 475 is used to transmit the fourth message.

[0294] As an example, the first communication device 450 corresponds to the first node in this application.

[0295] As an example, the first node in this application includes the first communication device 450.

[0296] As an example, the second communication device 410 corresponds to the second node in this application.

[0297] As an example, the second node in this application includes the second communication device 410.

[0298] As an example, the first communication device 450 is a user equipment.

[0299] As an example, the first communication device 450 is a base station device.

[0300] As an example, the first communication device 450 is a relay device.

[0301] As one embodiment, the second communication device 410 is a user equipment.

[0302] As one embodiment, the second communication device 410 is a base station device.

[0303] As one embodiment, the second communication device 410 is a relay device.

[0304] Example 5

[0305] Example 5 illustrates a wireless signal transmission flowchart according to an embodiment of this application, as shown in Figure 5. It should be noted that the order in this example does not limit the signal transmission order or the order of implementation in this application.

[0306] For the first node U01, in step S5101, a third message is received; wherein, whether the target radio bearer is the first candidate or the second candidate depends on the third message; in step S5102, a fourth message is received; wherein, the fourth message includes a first measurement configuration; in step S5103, the target measurement information is stored in the first storage unit; wherein, storing the target measurement information in the first storage unit depends on the first measurement configuration; in step S5104, a first message is received; in step S5105, in response to receiving the first message, a second message is sent through the target radio bearer; wherein, the second message includes at least a portion of the target measurement information in the first storage unit.

[0307] For the second node N02, in step S5201, the third message is sent; in step S5202, the fourth message is sent; in step S5203, the first message is sent; and in step S5204, the second message is received.

[0308] In embodiment 5, the candidates for the target radio bearer include at least a first candidate and a second candidate; the second candidate is different from the first candidate; the first candidate is an SRB, and the identifier of the first candidate is Q1; wherein, Q1 is 4, or, Q1 is an integer greater than 5.

[0309] As an example, step S5101 occurs before step S5102.

[0310] As an example, step S5101 is performed after step S5102.

[0311] As an example, the sender of the third message is the sender of the fourth message.

[0312] As an example, the sender of the third message is the sender of the first message.

[0313] As one embodiment, the first node U01 is a UE, and the second node N02 includes at least one base station device.

[0314] As one embodiment, the at least one base station device includes a gNB.

[0315] As one embodiment, the at least one base station device includes a gNB and at least one higher-level device; the higher-level device includes at least one of a core network device, an OTT (over the top) server, or an OAM device.

[0316] As an example, the dashed box F5.1 is optional.

[0317] As an example, the dashed box F5.1 does not exist.

[0318] As an example, the dashed box F5.1 is present.

[0319] As an example, the third message is at least one RRC message.

[0320] As an example, the third message is an RRCReconfiguration message.

[0321] As an example, the third message is at least one RRC IE.

[0322] As an example, the third message is at least one RRC field.

[0323] As an example, the third message is a MAC CE.

[0324] The above method balances latency and DCI overhead.

[0325] As an example, the third message is a DCI.

[0326] The above methods shorten the time.

[0327] As an example, the third message is used to determine whether the target radio bearer is the first candidate or the second candidate.

[0328] As an example, the third message indicates whether the target radio bearer is the first candidate or the second candidate.

[0329] As an example, the third message explicitly indicates whether the target radio bearer is the first candidate or the second candidate.

[0330] As an example, the third message implicitly indicates whether the target radio bearer is the first candidate or the second candidate.

[0331] As an example, the value of a field in the third message indicates whether the target radio bearer is the first candidate or the second candidate.

[0332] As an example, the name of a field in the third message indicates whether the target radio bearer is the first candidate or the second candidate.

[0333] As an example, the third message indicates from the at least first candidate and second candidate whether the target radio bearer is the first candidate or the second candidate.

[0334] As a sub-implementation of the above embodiments, if the value of the third message indicates the first candidate, the target radio bearer is the first candidate; if the value of the third message indicates the second candidate, the target radio bearer is the second candidate.

[0335] As a sub-implementation of the above embodiments, if the value of the third message is the name of the first candidate, the target radio bearer is the first candidate; if the value of the third message is the name of the second candidate, the target radio bearer is the second candidate.

[0336] As an example, the third message may include a second information block indicating whether the target radio bearer is the first candidate or the second candidate.

[0337] As a sub-implementation of the above embodiments, if the third message includes the second information block, the target radio bearer is the first candidate; if the third message does not include the second information block, the target radio bearer is the second candidate.

[0338] As a sub-implementation of the above embodiments, if the third message does not include the second information block, the target radio bearer is the first candidate; if the third message includes the second information block, the target radio bearer is the second candidate.

[0339] As an example, the third message indicates the priority of the target measurement information in the first storage unit.

[0340] As an example, the dashed box F5.2 is optional.

[0341] As an example, the dashed box F5.2 does not exist.

[0342] As an example, the dashed box F5.2 is present.

[0343] As an example, the fourth message is received when the PCell of the first node U01 is the current PCell.

[0344] As an example, the fourth message is received when the PCell of the first node U01 is the previous PCell; the previous PCell and the current PCell are different.

[0345] As an example, the fourth message is received via SRB1.

[0346] As an example, the fourth message is received via SRB3.

[0347] As an example, the fourth message is at least one RRC message.

[0348] As an example, the fourth message is an RRCReconfiguration message.

[0349] As an example, the fourth message is an RRCRelease message.

[0350] As an example, the fourth message is at least one RRC IE.

[0351] As an example, the fourth message includes at least one MeasId.

[0352] As an example, the fourth message includes at least one MeasObjectNR.

[0353] As an example, the fourth message includes at least one MeasConfig.

[0354] As an example, at least one MeasConfig in the fourth message includes the first measurement configuration.

[0355] As an example, the first measurement configuration includes at least one MeasConfig.

[0356] As an example, the fourth message is at least one RRC field.

[0357] As one embodiment, the first measurement configuration includes at least one measurement object.

[0358] As an example, the fourth message includes multiple measurement configurations, and the first measurement configuration is any one of the multiple measurement configurations.

[0359] As an example, the plurality of measurement configurations correspond one-to-one with the plurality of bits.

[0360] As an example, the plurality of measurement configurations correspond one-to-one with the plurality of entries in the list.

[0361] As an example, the fourth message is the first measurement configuration.

[0362] As an example, the first measurement configuration indicates synchronous measurement.

[0363] As an example, the first measurement configuration indicates inter-frequency measurement.

[0364] As an example, the first measurement configuration indicates the cell identifier of the cell being measured.

[0365] As an example, the first measurement configuration indicates the RS resources of the cell being measured, wherein the RS resources are SSB resources or CSI-RS resources.

[0366] As an example, the cell being measured is indicated by the first measurement configuration.

[0367] As an example, the measured cell is associated with the first measurement identifier.

[0368] As an example, the cell being measured is the serving cell of the first node.

[0369] As one example, the measured cell includes the serving cell and neighboring cells of the first node.

[0370] As an example, the cell being measured is a single cell.

[0371] As one example, the measured cell is a plurality of cells.

[0372] As one example, the number of cells being measured is configurable.

[0373] As one embodiment, the fourth message includes a first measurement configuration and a first measurement identifier, the first measurement identifier being used to identify the first measurement configuration.

[0374] As an example, the fourth message includes multiple measurement configurations and multiple measurement identifiers, the multiple measurement identifiers being used to identify the multiple measurement configurations, wherein the first measurement configuration is any one of the multiple measurement configurations.

[0375] As an example, the plurality of measurement identifiers and the plurality of bits correspond one-to-one.

[0376] As an example, the plurality of measurement identifiers correspond one-to-one with the plurality of entries in the list.

[0377] As an example, one of the MeasIds in the fourth message includes the first measurement identifier.

[0378] As an example, when the PCell of the first node U01 is the current PCell, the target measurement information is stored in the first storage unit.

[0379] As an example, when the PCell of the first node U01 is the previous PCell, the target measurement information is stored in the first storage unit; the previous PCell and the current PCell are different.

[0380] As one embodiment, storing the target measurement information in the first storage unit includes: setting at least one field in the first storage unit, the at least one field indicating the target measurement information.

[0381] As one embodiment, storing the target measurement information in the first storage unit includes: setting at least one field in the first storage unit, wherein the at least one field is set as the target measurement information.

[0382] As one embodiment, storing the target measurement information in the first storage unit includes setting the target measurement information in the first storage unit.

[0383] As an example, storing the target measurement information in the first storage unit depends on the first measurement configuration, meaning that the first measurement configuration instructs the first node to store the target measurement information in the first storage unit.

[0384] As an example, storing the target measurement information in the first storage unit depends on the first measurement configuration, meaning that the second message includes the first measurement configuration used to determine whether to store the target measurement information in the first storage unit.

[0385] As an example, the first measurement configuration indicates whether the first node U01 stores the target measurement information in the first storage unit periodically or in an event-triggered manner.

[0386] As an example, the first measurement configuration indicates that the first node U01 stores the target measurement information in the first storage unit periodically.

[0387] As one embodiment, the first measurement configuration includes a period of storing the target measurement information in the first storage unit.

[0388] As an example, the first node periodically stores the target measurement information in the first storage unit.

[0389] As an example, the first measurement configuration instructs the first node U01 to store the target measurement information in the first storage unit in an event-triggered manner.

[0390] As one embodiment, the first measurement configuration includes a trigger event that stores the target measurement information in the first storage unit.

[0391] As an example, the storage of the target measurement information in the first storage unit by the first node is triggered by an event.

[0392] As one embodiment, the target measurement information includes the first measurement identifier.

[0393] As one example, the target measurement information includes measurement results for the first measurement configuration.

[0394] As one example, the target measurement information includes measurement results obtained by performing measurements according to the first measurement configuration.

[0395] Example 6

[0396] Example 6 illustrates a schematic diagram of whether the target wireless bearer is a first candidate or a second candidate according to an embodiment of this application.

[0397] In embodiment 6, whether the target wireless bearer is the first candidate or the second candidate depends on whether the second message includes measurement information in the second storage unit; the first storage unit and the second storage unit are different.

[0398] As an example, if the second message does not include the measurement information in the second storage unit, the target radio bearer is the first candidate; if the second message includes the measurement information in the second storage unit, the target radio bearer is the second candidate.

[0399] As an example, the difference between the second candidate and the first candidate is that the second candidate is an SRB; the identifier of the second candidate is Q2, where Q2 is a positive integer and is less than Q1.

[0400] As a sub-example of the above embodiment, Q1 is 4 and Q2 is 2.

[0401] As a sub-implementation of the above embodiment, Q1 is 4 and Q2 is 1.

[0402] As a sub-implementation of the above embodiment, Q1 is an integer greater than 5, and Q2 is 2.

[0403] As a sub-implementation of the above embodiment, Q1 is an integer greater than 5, and Q2 is 1.

[0404] As an example, the second candidate has a higher priority than the first candidate.

[0405] As an example, the fact that Q2 is less than Q1 is used to determine that the priority of the second candidate is higher than that of the first candidate.

[0406] As one embodiment, the second storage unit is a UE variable.

[0407] As one embodiment, the second storage unit is a VarRLF-Report.

[0408] As one embodiment, the second storage unit is a VarRA-Report.

[0409] As one embodiment, the second storage unit is a VarConnEstFailReport.

[0410] As one embodiment, the second storage unit is a VarLogMeasReport.

[0411] As one embodiment, the second storage unit is a VarMobilityHistoryReport.

[0412] As one embodiment, the second storage unit is a VarSuccessHO-Report.

[0413] As one embodiment, the second storage unit is a VarSuccessPSCell-Report.

[0414] Example 7

[0415] Example 7 illustrates a schematic diagram of whether the target wireless bearer is a first candidate or a second candidate according to another embodiment of this application.

[0416] In Embodiment 7, whether the target radio bearer is the first candidate or the second candidate depends on whether the first candidate is supported; wherein, when the first candidate is supported, the target radio bearer is the first candidate; when the first candidate is not supported, the target radio bearer is the second candidate.

[0417] As one embodiment, whether the target radio bearer is the first candidate or the second candidate depends on whether the first candidate is supported, and whether the target radio bearer is the first candidate or the second candidate depends on whether the second message includes measurement information in the second storage unit; the first storage unit and the second storage unit are different.

[0418] As an example, when the first candidate is supported and the second message does not include measurement information in the second storage unit, the target radio bearer is the first candidate; when the first candidate is not supported or the second message includes measurement information in the second storage unit, the target radio bearer is the second candidate.

[0419] As an example, the first candidate being supported includes: the current at least one serving cell supporting the first candidate.

[0420] As an example, the first candidate being supported includes: the current at least one serving cell supporting the configuration of the first candidate.

[0421] As an example, the first candidate being supported includes: the current at least one serving cell supporting the establishment of the first candidate.

[0422] As one embodiment, the first candidate being supported includes: the first node being configured with the first candidate.

[0423] As an example, the first candidate being supported includes: the first node being established as the first candidate.

[0424] As one embodiment, supporting the first candidate includes: the first candidate being indicated.

[0425] As one embodiment, supporting the first candidate includes: the first candidate being configured.

[0426] As one embodiment, supporting the first candidate includes: the first candidate being established.

[0427] As one example, supporting the first candidate includes: the first candidate being activated.

[0428] As one embodiment, the first candidate being supported includes: the first candidate not being suspended.

[0429] As an example, the first candidate being supported includes: the current at least one serving cell supporting a function, and the current at least one serving cell supporting the function being used to determine that the current at least one serving cell supports the first candidate.

[0430] As an example, the current at least one serving cell supports a function including: the current at least one serving cell supports 3GPP Release 19.

[0431] As an example, the current at least one serving cell supports a function including: the current at least one serving cell supports AI / ML models.

[0432] As an example, the current at least one serving cell supports a function including: the current at least one serving cell supports the measurement and reporting of AI / ML models on the network side.

[0433] As an example, the aforementioned function refers to an AI / ML function.

[0434] As one example, one of the functions includes training.

[0435] As one example, one of the functions includes reasoning.

[0436] As one embodiment, whether the target radio bearer is the first SRB or the second radio bearer depends on whether the first SRB has been established.

[0437] As one embodiment, whether the target radio bearer is the first SRB or the second radio bearer depends on whether the first SRB is supported.

[0438] Example 8

[0439] Example 8 illustrates a flowchart of a first node according to an embodiment of this application, as shown in Figure 8.

[0440] For the first node U01, in response to the sending of the second message, at least one candidate measurement information in the first storage unit is deleted; wherein, the second message includes at least a portion of each candidate measurement information in the at least one candidate measurement information in the first storage unit; the first storage unit stores a plurality of candidate measurement information, the plurality of candidate measurement information including the at least one candidate measurement information, the at least one candidate measurement information including the target measurement information.

[0441] As an example, in response to the sending of the second message, any candidate measurement information in the first storage unit is deleted.

[0442] As an example, in response to the sending of the second message, the candidate measurement information included in the second message is deleted from the first storage unit.

[0443] As an example, the at least one candidate measurement information is one of the plurality of candidate measurement information.

[0444] As an example, the plurality of candidate measurement information includes one or more candidate measurement information other than the at least one candidate measurement information.

[0445] As an example, the target measurement information is any one of the at least one candidate measurement information.

[0446] As one embodiment, the second message includes each candidate measurement information in the at least one candidate measurement information in the first storage unit that is at least partially dependent on the indication of the first message.

[0447] As one embodiment, the second message includes each candidate measurement information in the at least one candidate measurement information in the first storage unit that is at least partially dependent on the order of the plurality of candidate measurement information in the first storage unit.

[0448] As an example, the second message includes each candidate measurement information in the at least one candidate measurement information in the first storage unit that is at least partially dependent on the priority of the plurality of candidate measurement information.

[0449] Example 9

[0450] Example 9 illustrates a schematic diagram of the priority of a second candidate and the priority of a first candidate according to an embodiment of this application, as shown in Figure 9.

[0451] In Example 9, the priority of the second candidate is different from that of the first candidate.

[0452] As an example, the priority of the second candidate is higher than the priority of the first candidate.

[0453] As an example, the priority of the second candidate is lower than the priority of the first candidate.

[0454] As an example, the difference between the second candidate and the first candidate is that the second candidate is a DRB.

[0455] As an example, the difference between the second candidate and the first candidate is that the second candidate is an SRB; the identifier of the second candidate is Q2, where Q2 is a positive integer, and Q2 is not equal to Q1.

[0456] As one embodiment, the priority of the second candidate is higher than the priority of the first candidate; wherein, Q2 is less than Q1.

[0457] As one embodiment, the priority of the second candidate is lower than the priority of the first candidate; wherein, Q2 is greater than Q1.

[0458] As an example, it is the default that the priority of the second candidate is different from that of the first candidate.

[0459] As an example, the priority of the second candidate is configured to be different from that of the first candidate.

[0460] As an example, an RRC message indicates the priority value of the second candidate and the priority value of the first candidate.

[0461] As an example, at least one of the priorities of the second candidate and the first candidate is assigned a default priority.

[0462] As an example, the first candidate is not assigned a default priority, while the second candidate is assigned a default priority.

[0463] As an example, neither the first candidate nor the second candidate is assigned a default priority.

[0464] As an example, the first candidate is assigned a default priority greater than 3.

[0465] As an example, the first candidate is not assigned a default priority, while the second candidate is assigned a default priority of 1.

[0466] As an example, the first candidate is not assigned a default priority, while the second candidate is assigned a default priority of 2.

[0467] As an example, the first candidate is not assigned a default priority, while the second candidate is assigned a default priority of 3.

[0468] Example 10

[0469] Example 10 illustrates a schematic diagram of a first candidate being used for MCG and a second candidate being used for SCG according to an embodiment of this application, as shown in Figure 10.

[0470] In Example 10, the first candidate was used for MCG and the second candidate was used for SCG.

[0471] As an example, the first node is configured with a DC.

[0472] As an example, the first node is configured with MR-DC.

[0473] As an example, the MCG and the SCG belong to the same RAT.

[0474] As an example, the MCG and the SCG belong to different RATs.

[0475] As an example, the difference between the second candidate and the first candidate is that the second candidate is an SRB; the identifier of the second candidate is Q2, where Q2 is a positive integer, and Q2 is not equal to Q1.

[0476] As an example, Q1 is an integer greater than 5, and Q2 is an integer greater than Q1.

[0477] As an example, Q1 is 4 and Q2 is 5.

[0478] As an example, Q1 is 4 and Q2 is 2.

[0479] As an example, the second candidate is split SRB2.

[0480] As an example, neither the second candidate nor the first candidate supports a split SRB.

[0481] As an example, the second candidate supports a split SRB.

[0482] As an example, the second candidate is a split SRB, which is used in the SCG.

[0483] Example 11

[0484] Example 11 illustrates a schematic diagram of a first storage unit storing multiple candidate measurement information according to an embodiment of the present application; as shown in Figure 11.

[0485] In embodiment 11, the first storage unit stores multiple candidate measurement information, and the target measurement information is one of the multiple candidate measurement information.

[0486] As an example, the target measurement information is any one of the plurality of candidate measurement information.

[0487] As one embodiment, the first message includes at least one information block, each of which indicates that at least one candidate measurement information is available; the first information block is one of the at least one information block; the plurality of candidate measurement information includes the at least one candidate measurement information.

[0488] As an example, the first information block is any one of the plurality of information blocks.

[0489] As an example, the number of the at least one information block is less than the number of the plurality of candidate measurement information.

[0490] As an example, the first information block indicates the identifier of the target measurement information.

[0491] As an example, the first information block indicates the identifier of each candidate measurement information among the at least one candidate measurement information.

[0492] As one embodiment, the second message includes the plurality of candidate measurement information.

[0493] As an example, the plurality of identifiers and the plurality of bits correspond one-to-one.

[0494] As an example, the plurality of identifiers correspond one-to-one with the plurality of entries in the list.

[0495] As an example, the plurality of candidate measurement information correspond one-to-one with a plurality of identifiers, and the first identifier is one of the plurality of identifiers.

[0496] As an example, any one of the plurality of identifiers is associated with the at least one cell.

[0497] As an example, any two of the plurality of identifiers are associated with different AI / ML models.

[0498] As an example, any two of the plurality of identifiers may be associated with different AI / ML functions.

[0499] As one embodiment, the first storage unit stores the plurality of identifiers.

[0500] Example 12

[0501] Example 12 illustrates a structural block diagram of a processing apparatus for a first node according to an embodiment of the present application; as shown in Figure 12. In Figure 12, the processing apparatus 1200 in the first node includes a first receiver 1201, a first transmitter 1202, and a first processor 1203.

[0502] First receiver 1201 receives the first message;

[0503] In response to receiving the first message, the first transmitter 1202 transmits a second message via a target wireless bearer; wherein the second message includes at least a portion of the target measurement information in the first storage unit;

[0504] In Example 12, the candidates for the target radio bearer include at least a first candidate and a second candidate; the second candidate is different from the first candidate; the first candidate is an SRB, and the identifier of the first candidate is Q1; wherein, Q1 is 4, or, Q1 is an integer greater than 5.

[0505] As one embodiment, the first receiver 1201 receives a third message; wherein, whether the target radio bearer is the first candidate or the second candidate depends on the third message.

[0506] As one embodiment, whether the target wireless bearer is the first candidate or the second candidate depends on whether the second message includes measurement information in the second storage unit; the first storage unit and the second storage unit are different.

[0507] As one embodiment, whether the target radio bearer is the first candidate or the second candidate depends on whether the first candidate is supported.

[0508] As one embodiment, the first receiver 1201 receives a fourth message; wherein the fourth message includes a first measurement configuration; the first processor 1203 stores the target measurement information in the first storage unit; wherein storing the target measurement information in the first storage unit depends on the first measurement configuration.

[0509] As one example, the priority of the second candidate is different from that of the first candidate.

[0510] As an example, the first candidate was used for MCG, and the second candidate was used for SCG.

[0511] As one embodiment, the first processor 1203, in response to the sending of the second message, deletes at least one candidate measurement information from the first storage unit; wherein the second message includes at least a portion of each candidate measurement information in the at least one candidate measurement information in the first storage unit; wherein the first storage unit stores a plurality of candidate measurement information, the plurality of candidate measurement information including the at least one candidate measurement information, the at least one candidate measurement information including the target measurement information.

[0512] As one embodiment, the first receiver 1201 receives a fourth message; wherein the fourth message includes a first measurement configuration; a first processor stores the target measurement information in the first storage unit; the first processor 1203, in response to the sending of the second message, deletes at least one candidate measurement information in the first storage unit; wherein the second message includes at least a portion of each candidate measurement information in the at least one candidate measurement information in the first storage unit; wherein storing the target measurement information in the first storage unit depends on the first measurement configuration; the first storage unit stores a plurality of candidate measurement information, the plurality of candidate measurement information including the at least one candidate measurement information, the at least one candidate measurement information including the target measurement information.

[0513] As one embodiment, the first receiver 1201 includes at least one of the following in Figure 4 of this application: antenna 452, receiver 454, multi-antenna receiver processor 458, receiver processor 456, controller / processor 459, memory 460, or data source 467.

[0514] As one embodiment, the first receiver 1201 includes at least an antenna 452 and a receiver 454 as shown in Figure 4 of this application.

[0515] As one embodiment, the first transmitter 1202 includes at least one of the following in Figure 4 of this application: antenna 452, transmitter 454, multi-antenna transmitter processor 457, transmitter processor 468, controller / processor 459, memory 460, or data source 467.

[0516] As one embodiment, the first transmitter 1202 includes at least an antenna 452 and a transmitter 454 as shown in Figure 4 of this application.

[0517] As an example, the first node is a UE.

[0518] As an example, the first node is a terminal.

[0519] As an example, the first node is an IoT device.

[0520] As an example, the first node is a relay.

[0521] Example 13

[0522] Example 13 illustrates a structural block diagram of a processing apparatus for a second node according to an embodiment of the present application; as shown in Figure 13. In Figure 13, the processing apparatus 1300 in the second node includes a second transmitter 1301, a second receiver 1302, and a second processor 1303.

[0523] The second transmitter, 1301, sends the first message;

[0524] The second receiver 1302, in response to sending the first message, receives a second message via a target radio bearer; wherein the second message includes at least a portion of the target measurement information in the first storage unit;

[0525] In Example 13, the candidates for the target radio bearer include at least a first candidate and a second candidate; the second candidate is different from the first candidate; the first candidate is an SRB, and the identifier of the first candidate is Q1; wherein, Q1 is 4, or, Q1 is an integer greater than 5.

[0526] As one embodiment, the second transmitter 1301 sends a third message; wherein, whether the target radio bearer is the first candidate or the second candidate depends on the third message.

[0527] As one embodiment, whether the target wireless bearer is the first candidate or the second candidate depends on whether the second message includes measurement information in the second storage unit; the first storage unit and the second storage unit are different.

[0528] As one embodiment, whether the target radio bearer is the first candidate or the second candidate depends on whether the first candidate is supported.

[0529] As one embodiment, the second transmitter 1301 sends a fourth message; wherein the fourth message includes a first measurement configuration; wherein the recipient of the first message stores the target measurement information in the first storage unit; the storage of the target measurement information in the first storage unit depends on the first measurement configuration.

[0530] As one example, the priority of the second candidate is different from that of the first candidate.

[0531] As an example, the first candidate was used for MCG, and the second candidate was used for SCG.

[0532] As one embodiment, the second processor 1303, in response to the receipt of the second message, performs at least one of training or inference based on at least a portion of the target measurement information.

[0533] As one embodiment, the second transmitter 1301 includes at least one of the following in Figure 4 of this application: antenna 420, transmitter 418, multi-antenna transmitter processor 471, transmitter processor 416, controller / processor 475, or memory 476.

[0534] As one embodiment, the second transmitter 1301 includes at least an antenna 420 and a transmitter 418 as shown in Figure 4 of this application.

[0535] As one embodiment, the second receiver 1302 includes at least one of the following in Figure 4 of this application: antenna 420, receiver 418, multi-antenna receiver processor 472, receiver processor 470, controller / processor 475, or memory 476.

[0536] As one embodiment, the second receiver 1302 includes at least an antenna 420 and a receiver 418 as shown in Figure 4 of this application.

[0537] As one embodiment, the second node includes a base station device.

[0538] As one embodiment, the second node includes at least one base station device and at least one higher-level device.

[0539] As one example, the second node is a base station device.

[0540] Example 14

[0541] Example 14 illustrates a flowchart of a second node according to an embodiment of this application, as shown in Figure 14.

[0542] For the second node N02, in response to the receipt of the second message, at least one of training or inference is performed based on at least a portion of the target measurement information.

[0543] As an example, at least one of the training or the inference is based on an AI / ML model.

[0544] As an example, the training refers to AI / ML model training.

[0545] As an example, the training refers to AI / ML function training.

[0546] As an example, the inference refers to AI / ML model inference.

[0547] As an example, the inference refers to AI / ML functional inference.

[0548] As an example, at least a portion of the target measurement information is the input to an AI / ML model.

[0549] As an example, at least a portion of the target measurement information is input to the training function of the AI / ML model.

[0550] As an example, at least a portion of the target measurement information is input to the inference function of the AI / ML model.

[0551] As an example, the second processor in this application performs at least one of training or inference based on at least a portion of the target measurement information.

[0552] As an example, the second processor in this application includes the second module in embodiment 15, which performs training based on at least a portion of the target measurement information.

[0553] As an example, the second processor in this application includes the third module in embodiment 15, which performs inference based on at least a portion of the target measurement information.

[0554] As an example, in the first stage of Example 16, training is performed based on at least a portion of the target measurement information.

[0555] As an example, in the fourth stage of Example 16, training is performed based on at least a portion of the target measurement information.

[0556] As an example, the second processor in this application includes a training function 1702 for the RAN domain in embodiment 17, the training function 1702 for the RAN domain performing training based on at least a portion of the target measurement information.

[0557] As an example, the second processor in this application includes an inference function in embodiment 17, which performs training based on at least a portion of the target measurement information.

[0558] As an example, the second processor in this application includes a training function 1805 for the RAN domain in embodiment 17, the training function 1805 for the RAN domain performing training based on at least a portion of the target measurement information.

[0559] As one embodiment, the second processor in this application includes the smart module 1900 in embodiment 19.

[0560] As an example, the second processor in this application belongs to a base station device of the second node.

[0561] As an example, the second processor in this application belongs to a higher-level device of the second node.

[0562] Example 15

[0563] Example 15 illustrates a schematic diagram of an AI / ML model according to an embodiment of this application, as shown in Figure 15. Figure 15 includes a first module, a second module, a third module, a fourth module, and a fifth module.

[0564] In Example 15, in the AI / ML model shown in Figure 15, the first module sends a first dataset to the second module, the first module sends a second dataset to the third module, the first module sends a third dataset to the fifth module, the fifth module sends a first type of parameter group to the second module, the fifth module sends a second type of parameter group to the third module, the fifth module sends a third type of parameter group to the fourth module, the second module sends a fourth type of parameter group to the fourth module, and the fourth module sends a fifth type of parameter group to the third module.

[0565] As an example, the first module, the second module, the third module, the fourth module, and the fifth module in an AI / ML model all belong to the first node in this application.

[0566] The above method avoids air interface signaling interaction and shortens transmission latency.

[0567] As an example, any one of the first module, second module, third module, fourth module, and fifth module in an AI / ML model does not belong to the first node in this application.

[0568] The above method reduces the hardware complexity of the first node.

[0569] As an example, at least one of the first module, the second module, the third module, the fourth module, and the fifth module in an AI / ML model belongs to the first node in this application; and at least one of the first module, the second module, the third module, the fourth module, and the fifth module belongs to the second node in this application.

[0570] The above method balances the hardware complexity and transmission latency of the first node.

[0571] As an example, the third module belongs to the first node in this application.

[0572] As an example, the third module belongs to the second node in this application.

[0573] As an example, the first module is used for data collection; specifically, the first module is responsible for data collection; specifically, the first module has data collection functions.

[0574] As one embodiment, the second module has a training function, which is used for AI / ML model training; specifically, the training function is responsible for AI / ML model training; specifically, the training function has AI / ML model training capabilities; specifically, the training function performs AI / ML model training.

[0575] As one example, the second module performs validation and / or testing; specifically, the second module generates AI / ML model performance metrics.

[0576] As one embodiment, the second module is responsible for data preparation; specifically, the data preparation includes at least one of data pre-processing, cleaning, formatting, or transformation.

[0577] As an example, the third module is used for inference; specifically, the third module has inference function; specifically, the inference function is responsible for inference.

[0578] As one embodiment, the fourth module is used for AI / ML model storage; specifically, the fourth module has AI / ML model storage function; specifically, the fourth module is responsible for storing trained AI / ML models; specifically, the fourth module is responsible for storing trained AI / ML models that can be used to perform inference processing.

[0579] As an example, the fifth module is used for management; specifically, the fifth module is responsible for management; specifically, the fifth module has management functions; specifically, the fifth module manages AI / ML models.

[0580] As an example, the first dataset is training data, and the first dataset is the input of the second module.

[0581] As an example, the first dataset is configured by the network.

[0582] As an example, the first dataset is determined by the first node.

[0583] As an example, the first dataset includes the stored data of the first node; the stored data may come from the network, the logs of the first node, or other RAN nodes.

[0584] As an example, the first dataset includes measurement information of the first node; the measurement information may be the movement status of the first node, such as movement speed, or the number of cells switched within a given time interval; the measurement information may also be measurement results for a reference signal, such as cell-level measurement results, or beam-level measurement results, or time-domain measurement results, or frequency-domain measurement results, or spatial-domain measurement results, or a combination thereof.

[0585] As an example, the first dataset includes at least a portion of the target measurement information.

[0586] As an example, the second dataset is inference data, which is the input of the third module.

[0587] As an example, the second dataset is configured by the network.

[0588] As an example, the second dataset is determined by the first node.

[0589] As one embodiment, the second dataset includes the stored data of the first node; the stored data may come from the network, the logs of the first node, or other RAN nodes.

[0590] As an example, the second dataset includes measurement information of the first node; the measurement information may be the movement status of the first node, such as movement speed, or the number of cells switched within a given time interval; the measurement information may also be measurement results for a reference signal, such as cell-level measurement results, or beam-level measurement results, or time-domain measurement results, or frequency-domain measurement results, or spatial-domain measurement results, or a combination thereof.

[0591] As an example, the second dataset includes at least a portion of the target measurement information.

[0592] As an example, the third dataset is monitoring data, which is the input of the fifth module.

[0593] As an example, the third dataset is configured by the network.

[0594] As an example, the third dataset is determined by the first node.

[0595] As an example, the third dataset is determined by the second node.

[0596] As an example, the third dataset includes the stored data of the first node; the stored data may come from the network, the logs of the first node, or other RAN nodes.

[0597] As an example, the third dataset includes measurement information of the first node; the measurement information may be the movement status of the first node, such as movement speed, or the number of cells switched within a given time interval; the measurement information may also be measurement results for a reference signal, such as cell-level measurement results, or beam-level measurement results, or time-domain measurement results, or frequency-domain measurement results, or spatial-domain measurement results, or a combination thereof.

[0598] As an example, the third dataset includes at least a portion of the target measurement information.

[0599] As an example, the first type of parameter group includes monitoring output.

[0600] As one embodiment, the second type of parameter group includes management instructions; specifically, the second type of parameter group is used for fine-tuning operations of the inference function; specifically, the second type of parameter group includes the identifier of the AI / ML model; specifically, the second type of parameter group is used for selecting, and / or switching, and / or activating / deactivating, and / or reverting the AI / ML model.

[0601] As an example, the third type of parameter group includes AI / ML model transfer requests and / or AI / ML model delivery requests.

[0602] As an example, the fourth parameter group includes trained AI / ML models and / or updated AI / ML models; specifically, the fourth parameter group indicates the identifier of the AI / ML model.

[0603] As an example, the fifth parameter group includes AI / ML model transfer and / or AI / ML model delivery; specifically, the fifth parameter group indicates the identifier of the AI / ML model.

[0604] As an example, the second module sends the first type of output to the fifth module.

[0605] As an example, the first type of output includes monitoring output.

[0606] As an example, the second type of output includes inference output.

[0607] As an example, the second type of output is used by the fifth module to monitor the performance of the AI / ML model.

[0608] As an example, the third module sends the second type of output to the fifth module.

[0609] As an example, Example 15 is only intended to illustrate that this application can be used in AI / ML models. This example does not limit the application of this application to non-AI / ML operations, nor does it limit the application of this application to other types of AI / ML models to achieve effects comparable to the AI / ML model shown in Figure 15.

[0610] Example 16

[0611] Example 16 illustrates a flowchart based on artificial intelligence or machine learning according to an embodiment of this application, as shown in Figure 16. Figure 16 includes a third operation, a fourth operation, a fifth operation, a sixth operation, and a seventh operation. In Example 16, the third and fourth operations belong to a first stage, the fifth operation belongs to a second stage, the sixth operation belongs to a third stage, and the seventh operation belongs to a fourth stage. In Figure 16, the lines with arrows indicate the sequence of the process.

[0612] As an example, the third operation includes AI / ML training, the fourth operation includes AI / ML testing, the fifth operation includes AI / ML emulation, the sixth operation includes AI / ML entity loading, and the seventh operation includes AI / ML inference.

[0613] As an example, the first stage includes a training phase, the second stage includes an emulation phase, the third stage includes a deployment phase, and the fourth stage includes an inference phase.

[0614] As an example, the first stage includes AI / ML model training.

[0615] As an example, the first stage includes AI / ML model training and AI / ML testing.

[0616] As an example, the AI / ML model training includes initial training and re-training of one or a group of AI / ML entities.

[0617] As an example, the training of the AI / ML model depends on training data.

[0618] As an example, the training data includes at least a portion of the target measurement information.

[0619] As an example, the AI / ML model training includes AI / ML entity validation.

[0620] As an example, the AI / ML entity verification is used to evaluate the performance of the AI / ML entity.

[0621] As an example, the AI / ML entity verification relies on verification data.

[0622] As an example, if the AI / ML entity verification results do not meet expectations, the AI / ML model will be retrained.

[0623] As an example, the AI / ML testing includes testing the validated AI / ML entities to estimate the performance of the trained AI / ML model.

[0624] As an example, if the AI / ML test results meet expectations, the AI / ML entity proceeds to the next stage; otherwise, the AI / ML model will be retrained.

[0625] As an example, the AI / ML test relies on test data.

[0626] As an example, the test data includes at least a portion of the target measurement information.

[0627] As one embodiment, the second stage includes AI / ML simulation, which performs AI / ML entity reasoning in a simulation environment.

[0628] As an example, the AI / ML simulation estimates the performance of AI / ML entity reasoning in a simulation environment before using AI / ML entities.

[0629] As one embodiment, the second stage is optional.

[0630] As an example, the third stage includes AI / ML entity loading, which is to obtain trained AI / ML entities to obtain the desired AI / ML inference capabilities.

[0631] As an example, the third stage is optional.

[0632] As an example, the third stage is no longer needed when the training and inference functions are co-located.

[0633] As an example, the fourth stage includes AI / ML inference.

[0634] Example 17

[0635] Example 17 illustrates a schematic diagram of intelligent function deployment in a RAN (Radio Access Network) domain according to an embodiment of this application; as shown in Figure 17. The gNB in ​​Example 17 can be replaced with, for example, an eNB, or a network device such as a 6G base station.

[0636] Intelligent functions in the RAN domain include training (also known as ML training, AI training, or AI / ML training), testing (also known as ML testing, AI testing, or AI / ML testing), and inference (also known as ML inference, AI inference, or AI / ML inference), among others. Training, testing, and inference functions can be deployed independently or co-located. Deployment of intelligent functions can be achieved through software, such as downloading and / or running executable files; or through a combination of software and hardware, such as accelerating specific computing units through hardware to improve processing speed or save power.

[0637] Training functions can be deployed in a cross-domain management system or a domain-specific management system; the domain-specific management system is used to manage the RAN domain or the CN (Core Network) domain. For example, training functions for MDA (Management Data Analytics) can be deployed in MDAF (MDA Function); training functions for network data analytics can be deployed in NWDAF (Network Data Analytics Function), meaning the training function is MTLF (Model Training Logical Function).

[0638] The inference function can also be deployed in a cross-domain management system or a domain-specific management system; for example, the inference function is MDAF, or the inference function is AnLF (Analytics logical function) located in NWDAF.

[0639] Similarly, testing functionality can also be deployed in cross-domain management systems or domain-specific management systems.

[0640] In embodiment 17, the training function 1702 of the RAN domain is located in the management function 1703 of the RAN domain; while the inference function is located in the base station, that is, the inference function 1704 is located in gNB 1705, and the inference function 1706 is located in gNB 1707. The ellipsis in Figure 17 indicates other gNBs that include other inference functions but are not shown.

[0641] In Figure 17, the management of the inference function of multiple base stations is completed by the RAN domain management function 1703, that is, data interaction with the RAN domain MnS (Mangement Service) consumer / cross-domain management 1701 (as shown by the dashed arrow 1708 in Figure 17).

[0642] Optionally, the management of inference functions can also be completed by the base station itself, that is, each base station can independently interact with the RAN domain MnS consumer / cross-domain management 1701.

[0643] It should be noted that Embodiment 17 is merely a non-limiting implementation; optionally, the RAN domain training function may also be deployed at the base station; or optionally, some base stations may deploy both inference function and RAN domain training function, while some base stations may only deploy inference function.

[0644] As one embodiment, the second node of this application includes a gNB (or base station) in embodiment 17.

[0645] As an example, the second node of this application is a gNB (or base station) in Example 17.

[0646] As an example, the current at least one serving cell belongs to gNB1705, and the previous at least one serving cell belongs to gNB1707.

[0647] As an example, the current at least one serving cell belongs to gNB1705, and the previous at least one serving cell also belongs to gNB1705.

[0648] As an example, the node 203 in Figure 2 of this application includes the RAN domain MnS consumer / cross-domain management 1701 in Figure 17.

[0649] As an example, the node 203 in Figure 2 of this application includes the training function 1702 in Figure 17.

[0650] As an example, the node 203 in Figure 2 of this application includes the management function 1703 in Figure 17.

[0651] As an example, node 203 in Figure 2 of this application includes the reasoning function 1704 in Figure 17.

[0652] As an example, the node 211 in Figure 2 of this application includes the RAN domain MnS consumer / cross-domain management 1701 in Figure 17.

[0653] As an example, the input to the training function 1702 in Figure 17 includes at least a portion of the target measurement information.

[0654] As an example, the input to the inference function 1704 in Figure 17 includes at least a portion of the target measurement information.

[0655] Example 18

[0656] Example 18 illustrates a schematic diagram of UE smart function deployment according to one embodiment of this application; as shown in Figure 18. The RAN domain training function 1805 in Figure 18 is optional.

[0657] The UE intelligent function 1804 includes an inference function 1806; the inference function 1806 is deployed in the first node of this application, and the inference function 1806 uses an AI / ML model (also known as an AI model, or an ML model, or an AI / ML model) for inference; an AI / ML model is typically trained before being used for AI / ML inference.

[0658] As an example, the UE intelligent function 1804 includes a RAN domain training function 1805, which runs training data through an AI / ML model to obtain a relevant loss and adjusts the parameters of the AI / ML model based on the calculated loss; the training includes at least one of ML initial training, ML re-training, and reinforcement learning.

[0659] As an example, the training function 1805 of the RAN domain is deployed in the first node of this application.

[0660] The above embodiments can reduce the complexity of the base station, or save air interface resources caused by reporting training data; however, the above embodiments place high demands on the processing capabilities of the UE side.

[0661] As an example, the training function 1805 of the RAN domain is deployed in the second node of this application; wherein the input of the training function 1805 in Figure 18 includes at least a portion of the target measurement information.

[0662] The above embodiments can reduce the complexity of the UE.

[0663] As an example, the UE intelligent function 1804 further includes a CN domain training function (not shown in FIG18); wherein the input of the CN domain training function includes at least a portion of the target measurement information.

[0664] Optionally, the UE intelligent function 1804 also includes an intelligent deployment function—not shown in Figure 18—for loading AI / ML models and data.

[0665] As an example, the first node indicates whether it supports training functions (RAN domain or CN domain) through capability reporting. The capability reporting is RRC signaling or NAS (Non-Access Stratum) signaling.

[0666] As an example, the AI / ML model and related metadata are loaded by the first node from a network device or a remote server.

[0667] Optionally, the UE intelligent function 1804 is an MnS (Management Service) producer that provides data to the CN domain MnF (Management Function) 1801, and / or the RAN domain MnF 1802, and / or the cross-domain management system 1803 for management or analysis (as shown by double arrow 1807).

[0668] Optionally, the UE intelligent function 1804 is an MnS consumer that loads data from the CN domain MnF1801, and / or the RAN domain MnF1802, and / or the cross-domain management system 1803 for AI / ML-related management, such as managing data requests, AI / ML model activation, and / or AI / ML model training (as shown by double arrow 1807).

[0669] As an example, the AI / ML model is based on a neural network.

[0670] As an example, the AI / ML model is based on CNN (Conventional Neural Networks).

[0671] As an example, the AI / ML model is based on the Transformer architecture.

[0672] As an example, the first communication device 450 in Figure 4 of this application includes the reasoning function 1806 in Figure 18.

[0673] As an example, the first node 1200 in Figure 12 of this application includes the reasoning function 1806 in Figure 18.

[0674] As an example, the third module in Figure 15 of this application includes the reasoning function 1806 in Figure 18.

[0675] As an example, the first node in this application includes the inference function 1806 shown in Figure 18.

[0676] As an example, the second node in this application includes the MnF1802 shown in Figure 18.

[0677] As an example, the second node in this application includes the RAN domain MnF1802 shown in Figure 18.

[0678] As an example, the UE201 in Figure 2 of this application includes the inference function 1806 in Figure 18.

[0679] As an example, node 203 in Figure 2 of this application includes MnF1801 in Figure 18.

[0680] As an example, node 203 in Figure 2 of this application includes the CN domain MnF1801 in Figure 18.

[0681] As an example, node 203 in Figure 2 of this application includes the cross-domain management system 1803 in Figure 18.

[0682] As an example, node 211 in Figure 2 of this application includes MnF1801 in Figure 18.

[0683] As an example, node 211 in Figure 2 of this application includes the CN field MnF1801 in Figure 18.

[0684] As an example, node 211 in Figure 2 of this application includes the cross-domain management system 1803 in Figure 18.

[0685] Example 19

[0686] Example 19 illustrates a schematic diagram of the processing of target measurement information according to an embodiment of this application; as shown in Figure 19. In Figure 19, when the PCell of the first node is the previous PCell 1904, the first node 1905 stores the target measurement information in the first storage unit; when the PCell of the first node is the current PCell 1902, the first node 1905 receives the first message and sends the second message; the previous PCell 1904 belongs to the second child node 1903, and the current PCell 1902 belongs to the first child node 1901; the intelligent module 1900 is used for the current PCell 1902 and the previous PCell 1904.

[0687] As an example, the second node in this application includes the first child node 1901 and the second child node 1903.

[0688] As an example, the second node in this application includes the smart module 1900.

[0689] As one embodiment, the intelligent module 1900 includes the second processor of this application.

[0690] As one embodiment, the smart module 1900 includes the second module in embodiment 15.

[0691] As one embodiment, the smart module 1900 includes the third module described in embodiment 15.

[0692] As an example, the intelligent module 1900 includes the training function 1702 of the RAN domain in Example 17.

[0693] As an example, the intelligent module 1900 includes a reasoning function as described in Example 17.

[0694] As an example, the intelligent module 1900 includes the training function 1805 of the RAN domain in Example 17.

[0695] As one embodiment, the smart module 1900 includes a core network device, an OTT server, or an OAM device.

[0696] As one embodiment, the intelligent module 1900 has at least one of a training function, an inference function, or a reinforcement learning function.

[0697] As an example, the intelligent module 1900 performs at least one of training, inference, or reinforcement learning based on at least a portion of the target measurement information.

[0698] As an example, the second child node 1903 is the first child node 1901.

[0699] As an example, the second child node 1903 is not the first child node 1901.

[0700] As an example, the second child node 1903 sends the fourth message.

[0701] As an example, the first child node 1901 sends the third message.

[0702] As an example, the first child node 1901 sends the first message and receives the second message.

[0703] As an example, in response to the receipt of the second message, at least a portion of the target measurement information is forwarded to the smart module 1900.

[0704] As an example, in response to the receipt of the second message, the second message is forwarded to the smart module 1900.

[0705] Those skilled in the art will understand that all or part of the steps in the above methods can be implemented by a program instructing related hardware, and the program can be stored in a computer-readable storage medium, such as a read-only memory, hard disk, or optical disk. Optionally, all or part of the steps in the above embodiments can also be implemented using one or more integrated circuits. Accordingly, each module unit in the above embodiments can be implemented in hardware or in the form of software functional modules. This application is not limited to any specific combination of software and hardware. The user equipment, terminal, and UE in this application include, but are not limited to, drones, communication modules on drones, remote-controlled aircraft, aircraft, small aircraft, mobile phones, tablets, laptops, vehicle-mounted communication devices, wireless sensors, internet cards, IoT terminals, RFID terminals, NB-IoT terminals, MTC (Machine Type Communication) terminals, eMTC (enhanced MTC) terminals, data cards, internet cards, vehicle-mounted communication devices, low-cost mobile phones, low-cost tablets, and other wireless communication devices. The base station or system equipment in this application includes, but is not limited to, macrocell base stations, microcell base stations, home base stations, relay base stations, gNB (NR Node B), TRP (Transmitter Receiver Point), and other wireless communication equipment.

[0706] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A first node used for wireless communication, characterized in that, include: The first receiver receives the first message; In response to receiving the first message, the first transmitter transmits a second message via a target wireless bearer; wherein the second message includes at least a portion of the target measurement information stored in the first storage unit. The candidate target radio bearer includes at least a first candidate and a second candidate; the second candidate is different from the first candidate; the first candidate is an SRB, and the identifier of the first candidate is Q1; Wherein, Q1 is 4, or Q1 is an integer greater than 5.

2. The first node according to claim 1, characterized in that, include: The first receiver receives the third message; Whether the target wireless bearer is the first candidate or the second candidate depends on the third message.

3. The first node according to claim 1 or 2, characterized in that, Whether the target wireless bearer is the first candidate or the second candidate depends on whether the second message includes measurement information in the second storage unit; the first storage unit and the second storage unit are different.

4. The first node according to claim 1 or 2, characterized in that, Whether the target radio bearer is the first candidate or the second candidate depends on whether the first candidate is supported.

5. The first node according to any one of claims 1 to 4, characterized in that, include: The first receiver receives a fourth message; wherein the fourth message includes a first measurement configuration; A first processor stores the target measurement information in the first storage unit; The storage of the target measurement information in the first storage unit depends on the first measurement configuration.

6. The first node according to any one of claims 1 to 5, characterized in that, The priority of the second candidate is different from that of the first candidate.

7. The first node according to any one of claims 1 to 6, characterized in that, The first candidate was used for MCG, and the second candidate was used for SCG.

8. The first node according to any one of claims 1 to 7, characterized in that, include: A first processor, in response to the sending of the second message, deletes at least one candidate measurement information from the first storage unit; wherein the second message includes at least a portion of each of the at least one candidate measurement information in the first storage unit; The first storage unit stores multiple candidate measurement information, including at least one candidate measurement information, which in turn includes the target measurement information.

9. A method used in a first node of wireless communication, characterized in that, include: Receive the first message; In response to receiving the first message, a second message is transmitted via the target wireless bearer; wherein the second message includes at least a portion of the target measurement information in the first storage unit; The candidate target radio bearer includes at least a first candidate and a second candidate; the second candidate is different from the first candidate; the first candidate is an SRB, and the identifier of the first candidate is Q1; Wherein, Q1 is 4, or Q1 is an integer greater than 5.

10. A second node used for wireless communication, characterized in that, include: The second transmitter sends the first message; A second receiver, in response to sending the first message, receives a second message via a target radio bearer; wherein the second message includes at least a portion of the target measurement information in the first storage unit; The candidate target radio bearer includes at least a first candidate and a second candidate; the second candidate is different from the first candidate; the first candidate is an SRB, and the identifier of the first candidate is Q1; Wherein, Q1 is 4, or Q1 is an integer greater than 5.

11. A method used in a second node for wireless communication, characterized in that, include: Send the first message; In response to sending the first message, a second message is received via the target wireless bearer; wherein the second message includes at least a portion of the target measurement information in the first storage unit; The candidate target radio bearer includes at least a first candidate and a second candidate; the second candidate is different from the first candidate; the first candidate is an SRB, and the identifier of the first candidate is Q1; Wherein, Q1 is 4, or Q1 is an integer greater than 5.

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