Methods and apparatus for wireless communication

Abstract

Methods and apparatuses for wireless communication are disclosed. A first node receives a first information block, the first information block comprising a first inference configuration or configuration information of the first inference configuration; transmits a second information block, the second information block comprising measurement results on at least one cell; transmits a third information block in conjunction with the transmitting the second information block; wherein the third information block indicates whether the first inference configuration is available in the at least one cell. The present application is beneficial to assist a receiver of the third information block to manage radio resource configuration of the first node, and provides a possibility to improve performance of the first inference configuration.

Description

Technical Field

[0001] This application relates to methods and apparatus in wireless communication systems, and more particularly to schemes and apparatus related to whether the configuration of the accompanying measurement report indication inference is available in wireless communication systems. Background Technology

[0002] In traditional wireless communication, the UE (User Equipment) reports various auxiliary information obtained through measurements of downlink signals and / or channels, such as channel status information, beam management-related auxiliary information, and positioning-related auxiliary information. With the adoption of new technologies, the increase in the number of antennas, the diversification of application scenarios, and the increasing demands on system performance, traditional measurement and reporting methods incur significant redundancy overhead. Therefore, in NR (New Radio) Rel-18 (Release-18), research on AI (Artificial Intelligence) / ML (Machine Learning) technologies was initiated to explore their impact on system performance and system design. AI / ML technologies may also play an important role in future 6G communications. According to 3GPP (3rd Generation Partnership Project) standard TS (Technical Specification) 38.300, AI / ML models and algorithms extend beyond the scope of 3GPP.

[0003] Compared to traditional processing methods, AI / ML offers advantages such as training-based and deployment-required features. Based on current research advancements, UEs can report available AI / ML models or functions within the current network (e.g., serving cell) coverage area according to the inference configuration indicated by the network, thus assisting the network in managing the UE's AI / ML functions. In other words, the UE's inference configuration can be associated with a specific AI / ML model or function. Furthermore, in beam management scenarios, the UE can report the availability of AI / ML models or functions to the target base station after handover, based on the inference configuration indicated by the target base station in the handover command message during the handover process. Summary of the Invention

[0004] The applicant's research revealed that existing measurement and reporting mechanisms may not be able to meet the functional requirements of AI / ML when AI / ML functions are introduced.

[0005] To address the aforementioned issues, this application discloses a solution. Although the specification of this application involves descriptions of some AI / ML models, those skilled in the art will understand that these descriptions are not essential or irreplaceable for solutions related to wireless cellular communication. Furthermore, employing a unified solution across different scenarios helps reduce hardware complexity and cost. Where there is no conflict, the embodiments and features in the first node of this application can be applied to the second node, and vice versa. Where there is no conflict, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other.

[0006] Where necessary, the interpretation of terms in this application shall refer to the definitions of the 3GPP TS38 series of specifications; or, the definitions of the 3GPP TS37 series of specifications; or, the definitions of the 3GPP TS28 series of specifications; or, the definitions of the 3GPP TS23 series of specifications; or, the definitions of the 3GPP TS24 series of specifications; or, the definitions of the 3GPP TS22 series of specifications.

[0007] This application discloses a method used in a first node for wireless communication, characterized by comprising:

[0008] Receive a first information block, the first information block including a first inference configuration or configuration information of the first inference configuration;

[0009] A second information block is sent, the second information block including measurement results on at least one cell; accompanied by the sending of the second information block, a third information block is sent.

[0010] The third information block indicates whether the first inference configuration is available in the at least one cell.

[0011] The above method enables the receiver of the third information block to know the measurement results of at least one cell while also understanding the availability of the first inference configuration in the at least one cell. This helps the receiver of the third information block to manage the radio resource configuration of the first node according to the instructions of the third information block, and provides the possibility of improving the performance of the first inference configuration.

[0012] Specifically, according to one aspect of this application, the above method is characterized in that at least one neighboring cell in the at least one cell is associated with the first inference configuration.

[0013] The above aspects help the recipient of the third information block to perform subsequent configuration of the first node based on the availability of inference configuration associated with neighboring cells.

[0014] Specifically, according to one aspect of this application, the above method is characterized in that the third information block indicates whether the first inference configuration is available in the at least one neighboring cell of the at least one cell.

[0015] The above aspects help to improve the relevance of the instructions in the third information block.

[0016] Specifically, according to one aspect of this application, the above method is characterized in that the first information block includes the cell identifier of each of the at least one neighboring cell in the at least one cell.

[0017] In the above aspects, the indication of the first information block helps the first node to filter out the neighboring cells associated with the first inference configuration when multiple neighboring cells are measured, which helps to reduce the processing complexity of the first node in generating the third information block and reduce the signaling overhead of the third information block.

[0018] Specifically, according to one aspect of this application, the above method is characterized in that the first information block includes multiple inference configurations or configuration information of multiple inference configurations; the third information block indicates whether each of the multiple inference configurations is available in the at least one cell.

[0019] The above aspects help the sender of the first information block to understand the availability of other inference configurations of the first node besides the first inference configuration in at least one cell, and provide the possibility to improve the flexibility of the sender of the first information block in managing the radio resource configuration of the first node.

[0020] Specifically, according to one aspect of this application, the above method is characterized by comprising:

[0021] Receive the fourth information block, wherein the transmission of the third information block accompanies the transmission of the second information block and depends on the fourth information block;

[0022] The fourth information block includes the event that triggers the second information block.

[0023] In the above aspects, the first node sends the third information block according to the instruction of the fourth information block, which can avoid the possibility of the first node frequently sending the third information block and is conducive to reducing the power consumption of the first node.

[0024] Specifically, according to one aspect of this application, the above method is characterized by comprising:

[0025] Receive a fifth information block, which indicates a handover command or configuration information of the secondary cell;

[0026] The indication of the fifth information block depends on the third information block.

[0027] In the above aspects, the third information block can assist the recipient of the third information block in managing the mobility of the first node or managing the cells serving the first node, which is conducive to ensuring the availability of the first inference configuration in different cells before and after the first node moves or in multiple cells serving the first node, thereby improving the service continuity and performance stability of the first inference configuration.

[0028] This application discloses a method used in a second node for wireless communication, characterized by comprising:

[0029] Send a first information block, the first information block including a first inference configuration or configuration information of the first inference configuration;

[0030] Receive a second information block, which includes measurement results on at least one cell; receive a third information block;

[0031] The third information block indicates whether the first inference configuration is available in the at least one cell.

[0032] Specifically, according to one aspect of this application, the above method is characterized in that at least one neighboring cell in the at least one cell is associated with the first inference configuration.

[0033] Specifically, according to one aspect of this application, the above method is characterized in that the third information block indicates whether the first inference configuration is available in the at least one neighboring cell of the at least one cell.

[0034] Specifically, according to one aspect of this application, the above method is characterized in that the first information block includes the cell identifier of each of the at least one neighboring cell in the at least one cell.

[0035] Specifically, according to one aspect of this application, the above method is characterized in that the first information block includes multiple inference configurations or configuration information of multiple inference configurations; the third information block indicates whether each of the multiple inference configurations is available in the at least one cell.

[0036] Specifically, according to one aspect of this application, the above method is characterized by comprising:

[0037] Send a fourth information block, wherein the receipt of the third information block depends on the fourth information block;

[0038] The fourth information block includes the event that triggers the second information block.

[0039] Specifically, according to one aspect of this application, the above method is characterized by comprising:

[0040] Send a fifth information block, which indicates a handover command or configuration information for the secondary cell;

[0041] The indication of the fifth information block depends on the third information block.

[0042] This application discloses a first node used for wireless communication, characterized in that it includes:

[0043] A first receiver receives a first information block, the first information block including a first inference configuration or configuration information of the first inference configuration;

[0044] A first transmitter transmits a second information block, the second information block including measurement results on at least one cell; accompanied by the transmission of the second information block, a third information block is transmitted;

[0045] The third information block indicates whether the first inference configuration is available in the at least one cell.

[0046] This application discloses a second node used for wireless communication, characterized by comprising:

[0047] The second transmitter sends a first information block, the first information block including a first inference configuration or configuration information of the first inference configuration;

[0048] The second receiver receives a second information block, which includes measurement results from at least one cell; and receives a third information block.

[0049] The third information block indicates whether the first inference configuration is available in the at least one cell. Attached Figure Description

[0050] 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:

[0051] Figure 1 A flowchart illustrating the communication of a first node according to an embodiment of this application is shown;

[0052] Figure 2 A schematic diagram of a network architecture according to an embodiment of this application is shown;

[0053] Figure 3 A schematic diagram of an embodiment of a wireless protocol architecture for the user plane and control plane according to an embodiment of this application is shown;

[0054] Figure 4 A schematic diagram of a first communication device and a second communication device according to an embodiment of this application is shown;

[0055] Figure 5 A transmission flowchart between a first node N1 and a second node N2 according to an embodiment of this application is shown;

[0056] Figure 6 A schematic diagram illustrating at least one cell associated with a first inference configuration according to an embodiment of this application is shown;

[0057] Figure 7 A transmission flowchart illustrating the first node N1 receiving the fourth information block according to an embodiment of this application is shown;

[0058] Figure 8 A transmission flowchart illustrating the first node N1 receiving the fifth information block according to an embodiment of this application is shown;

[0059] Figure 9 A schematic diagram illustrating the deployment of RAN domain AI / ML functions according to an embodiment of this application is shown;

[0060] Figure 10 A schematic diagram illustrating the deployment of AI / ML functions in a UE according to an embodiment of this application is shown;

[0061] Figure 11 A schematic diagram of an artificial intelligence or machine learning-based processing system according to an embodiment of this application is shown;

[0062] Figure 12 A schematic diagram based on artificial intelligence or machine learning according to an embodiment of this application is shown;

[0063] Figure 13 A structural block diagram of a processing apparatus for a first node according to an embodiment of this application is shown;

[0064] Figure 14 A structural block diagram of a processing apparatus for a second node according to an embodiment of this application is shown. Detailed Implementation

[0065] The technical solutions 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. Considering performance, flexibility, complexity, overhead, and compatibility, those skilled in the art are motivated to flexibly combine the embodiments in different drawings without conflict, including but not limited to the accompanying drawings. Figure 1 Examples and appendices Figure 5 - Appendix Figure 14 The embodiments in the appendix Figure 5 Examples and appendices Figure 6 - Appendix Figure 14Examples, etc.

[0066] Example 1

[0067] Example 1 illustrates a flowchart of communication of a first node according to an embodiment of this application, as shown in the attached diagram. Figure 1 As shown.

[0068] In Embodiment 1, the first node 100 receives a first information block in step 101, the first information block including a first inference configuration or configuration information of the first inference configuration; in step 102, it sends a second information block, the second information block including measurement results on at least one cell; along with sending the second information block, a third information block is sent.

[0069] In Example 1, the third information block indicates whether the first inference configuration is available in the at least one cell.

[0070] As an example, the first inference configuration includes the configuration of at least one RS (Reference Signal) resource.

[0071] As a non-limiting sub-implementation of the above embodiments, the at least one RS resource includes a DMRS (Demodulation Reference Signal) resource.

[0072] As a non-limiting sub-implementation of the above embodiments, the at least one RS resource includes an SSB (SS / PBCH Block, Synchronization Signal Physical Broadcast Channel Block) resource.

[0073] As a non-limiting sub-implementation of the above embodiments, the at least one RS resource includes a PRS (Positioning Reference Signal) resource.

[0074] As a non-limiting sub-implementation of the above embodiments, the at least one RS resource includes a TRS (Tracking Reference Signal) resource.

[0075] As a non-limiting sub-implementation of the above embodiments, the at least one RS resource includes a PTRS (Phase Tracking Reference Signal) resource.

[0076] As a non-limiting sub-implementation of the above embodiments, the at least one RS resource includes a CSI-RS (Channel State Information Reference Signal) resource.

[0077] As a non-limiting sub-implementation of the above embodiments, the at least one RS resource includes an SRS (Sounding Reference Signal) resource.

[0078] As an example, the first inference configuration includes a format for the output result of executing the first inference configuration.

[0079] As a non-limiting sub-implementation of the above embodiments, the format of the output result of executing the first inference configuration includes at least one of a CSI-type compressed result and a predicted value.

[0080] As a non-limiting sub-implementation of the above embodiments, the format of the output result of executing the first inference configuration includes at least one of the predicted beam index, predicted location information, and predicted RSRP (Reference Signal Received Power).

[0081] As a non-limiting sub-implementation of the above embodiments, the format of the output result of executing the first inference configuration includes at least one of the compressed result of the precoding matrix and the predicted value.

[0082] As a non-limiting sub-implementation of the above embodiments, the format of the output result of executing the first inference configuration includes at least one of the compressed result of the feature vector and the predicted value.

[0083] As a non-limiting sub-implementation of the above embodiments, the format of the output result of performing the first inference configuration includes at least one of the compressed result of the raw channel matrix and the predicted value.

[0084] As an example, the first inference configuration is associated with at least one DataSet ID.

[0085] As a sub-example of the above embodiments, the configuration information of the first inference configuration includes at least one dataset ID.

[0086] As an example, the first inference configuration is associated with at least one associated / association ID.

[0087] As a sub-implementation of the above embodiments, the configuration information of the first inference configuration includes at least one association ID.

[0088] As an example, the first inference configuration is associated with at least one AI / ML model ID.

[0089] As a sub-example of the above embodiments, the configuration information of the first inference configuration includes at least one AI / ML model ID.

[0090] As an example, the first inference configuration is associated with at least one AI / ML functionality / feature ID.

[0091] As a sub-example of the above embodiments, the configuration information of the first inference configuration includes at least one AI / ML function ID.

[0092] As an example, the first inference configuration is used to configure at least one AI / ML model.

[0093] As an example, the first inference configuration is used to configure at least one AI / ML function.

[0094] As an example, the first inference configuration is used to activate at least one AI / ML model.

[0095] As an example, the first inference configuration is used to activate at least one AI / ML function.

[0096] As an example, the SSB mentioned in this application refers to: Synchronization Signal Block.

[0097] As an example, the SSB mentioned in this application refers to: Synchronization Signal / Physical Broadcast Channel Block (SS (Synchronization Signal) / PBCH (Physical Broadcast Channel) Block).

[0098] As an example, activation as described in this application refers to: applying AI / ML models / functions for inference.

[0099] As an example, the AI / ML functions described in this application rely on network-side additional conditions.

[0100] As an example, the AI / ML function described in this application relies on a network configuration parameter set.

[0101] As an example, the AI / ML functions described in this application include at least one of the following: CSI compression / feedback; CSI prediction; beam management; and positioning.

[0102] As an example, the AI / ML function described in this application is associated with at least one AI / ML model.

[0103] As an example, the ID mentioned in this application refers to IDentify (proof).

[0104] As an example, the ID mentioned in this application refers to: IDentification.

[0105] As an example, the ID mentioned in this application refers to: IDentity (identity or identifier).

[0106] As an example, the ID mentioned in this application refers to: Identifier.

[0107] As an example, the ID mentioned in this application refers to: InDex (index).

[0108] As an example, the ID mentioned in this application refers to: InDicator.

[0109] As an example, executing the first inference configuration as described in this application means: performing inference using the AI / ML model associated with the first inference configuration.

[0110] As an example, executing the first inference configuration as described in this application means: applying the parameters in the first inference configuration to the AI / ML model associated with the first inference configuration for inference.

[0111] As an example, the at least one cell is a single cell.

[0112] As an example, the at least one cell can be multiple cells.

[0113] As one example, the at least one cell includes at least one neighbor cell.

[0114] As a sub-implementation of the above embodiments, each of the at least one cell is a neighboring cell.

[0115] As one embodiment, the at least one cell includes the serving cell of the first node.

[0116] As a sub-implementation of the above embodiments, the at least one cell includes only the serving cell.

[0117] As a sub-implementation of the above embodiments, the serving cell includes at least one secondary cell.

[0118] As an example, the at least one cell does not include the serving cell of the first node.

[0119] As an example, the measurement results on at least one cell include at least one of the cell identifier of each cell in the at least one cell, the cell measurement results of each cell in the at least one cell, and the beam measurement results of each cell in the at least one cell.

[0120] As a sub-implementation of the above embodiments, the cell identifier includes at least one of PCI (Physical Cell Identity) and NCGI (NR Cell Global Identifier).

[0121] As a sub-example of the above embodiments, the unit of the cell measurement result or the beam measurement result is dBm (millidecibels).

[0122] As a sub-example of the above embodiments, the unit of the cell measurement result or the beam measurement result is dB (decibels).

[0123] As a sub-example of the above embodiments, the unit of the cell measurement result or the beam measurement result is W (watts).

[0124] As a sub-example of the above embodiments, the unit of the cell measurement result or the beam measurement result is mW (milliwatt).

[0125] As a sub-example of the above embodiments, the unit of the cell measurement result or the beam measurement result is μW (microwatt).

[0126] As a sub-example of the above embodiments, the cell measurement results include at least one of the cell's RSRP (Reference Signal Received Power), RSRQ (Reference Signal Received Quality), RSSI (Received Signal Strength Indicator), SNR (Signal to Noise Ratio), and SINR (Signal to Interference plus Noise Ratio).

[0127] As a sub-implementation of the above embodiments, the beam measurement results include beam indices (e.g., SSB-Index or CSI-RS-Index).

[0128] As a sub-example of the above embodiments, the beam measurement results include at least one of the beam's RSRP, RSRQ, RSSI, SNR, and SINR.

[0129] As an example, the phrase "sending a third information block along with sending the second information block" means that sending the third information block is only executed when the second information block is triggered.

[0130] As an example, the phrase "sending a third information block along with sending the second information block" means that the sending of the second information block and the sending of the third information block are triggered by the same event.

[0131] As a sub-implementation of the above embodiments, the event includes any one of events A1, A2, A3, A4, A5, A6, B1, and B2.

[0132] As a sub-implementation of the above embodiments, the sending of the second information block is executed in response to the occurrence of the first event; wherein, the sending of the second information block is in response to the occurrence of the first event.

[0133] As an example, the phrase "sending a third information block along with sending the second information block" means that sending the second information block triggers sending the third information block.

[0134] As an example, the phrase "sending a third information block along with the sending of the second information block" means that the second information block and the third information block are included in the same message or information element.

[0135] As an example, the phrase "sending a third information block along with the sending of the second information block" means that the second information block includes the third information block.

[0136] As an example, the "transmitting the third information block along with the transmission of the second information block" is performed only if at least the first inference configuration is available in at least the first cell; wherein the at least the first cell belongs to the at least one cell.

[0137] As a sub-implementation of the above embodiments, if the first inference configuration is unavailable in each of the at least one cells, the "sending a third information block along with sending a second information block" is not executed.

[0138] As an example, whether the first inference configuration is applicable in the at least one cell includes: whether the first inference configuration is suitable for inference in the at least one cell.

[0139] As one embodiment, whether the first inference configuration is available in the at least one cell includes: whether the first inference configuration is suitable for reporting inference results in the at least one cell.

[0140] As an example, whether the first inference configuration is available in the at least one cell includes whether the first inference configuration is activated in the at least one cell.

[0141] As an example, the first inference configuration may be available in the at least one cell to satisfy the UE-side conditions of the first node.

[0142] As an example, the first inference configuration may be available in the at least one cell depending on the network-side conditions satisfied by the first inference configuration.

[0143] As an example, the first inference configuration may be available in at least one cell with an AI / ML model associated with the first inference configuration that depends on the presence or availability of the first node.

[0144] As an example, the third information block indicates whether the first inference configuration is available for each of the at least one cell.

[0145] As one embodiment, the third information block indicates that the first inference configuration is available; wherein the indication of the third information block depends on the fact that the first inference configuration is available in each of the at least one cell.

[0146] As one embodiment, the third information block indicates that the first inference configuration is unavailable; wherein the indication of the third information block depends on the first inference configuration being unavailable in at least a second cell; the at least second cell belongs to the at least one cell.

[0147] As one embodiment, the first information block includes AS (Access Stratum) signaling.

[0148] As one embodiment, the first information block includes RRC (Radio Resource Control) signaling.

[0149] As an example, the first information block includes one or more RRC IEs (Information Elements).

[0150] As an example, the first information block includes one or more fields in an RRC IE.

[0151] As one embodiment, the first information block includes SIB (System Information Block) signaling.

[0152] As one embodiment, the first information block includes SIB signaling for positioning.

[0153] As one embodiment, the first information block includes non-AS signaling.

[0154] As an example, the first information block includes LPP (LTE Positioning Protocol) signaling.

[0155] As one embodiment, the first information block includes one or more LPP IEs.

[0156] As an example, the first information block includes one or more fields in an LPP IE.

[0157] As an example, the signaling / IE / domain name of the first information block includes Inference.

[0158] As an example, the signaling / IE / domain name of the first information block includes Configuration or Config.

[0159] As one embodiment, the second information block includes AS signaling.

[0160] As one embodiment, the second information block includes RRC signaling.

[0161] As one embodiment, the second information block includes one or more RRC IEs.

[0162] As one example, the second information block includes one or more fields in an RRC IE.

[0163] As one embodiment, the second information block includes MAC (Medium Access Control) and CE (Control Element).

[0164] As one embodiment, the second information block includes UCI (Uplink Control Information).

[0165] As an example, the second information block is transmitted on the PUCCH (Physical Uplink Control Channel).

[0166] As an example, the second information block is transmitted on PUSCH (Physical Uplink Shared Channel).

[0167] As an example, the signaling / IE / domain name of the second information block includes Report.

[0168] As one embodiment, the third information block includes AS signaling.

[0169] As one embodiment, the third information block includes RRC signaling.

[0170] As one example, the third information block includes one or more RRC IEs.

[0171] As an example, the third information block includes one or more fields in an RRC IE.

[0172] As an example, the third information block includes a MAC CE.

[0173] As an example, the third information block includes UCI.

[0174] As an example, the third information block is sent on the PUCCH.

[0175] As an example, the third information block is sent on the PUSCH.

[0176] As an example, the name of the signaling / IE / domain of the third information block includes Report.

[0177] As an example, the signaling / IE / domain name of the third information block includes Capability / Capabilities.

[0178] As one embodiment, the third information block includes LPP signaling.

[0179] As one example, the third information block includes one or more LPP IEs.

[0180] As an example, the third information block includes one or more fields in an LPP IE.

[0181] Example 2

[0182] Example 2 illustrates a schematic diagram of a network architecture according to an embodiment of this application, as shown in the attached diagram. Figure 2 As shown.

[0183] Appendix Figure 2The network architecture 200 is explained. 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 network architecture adopted in the future evolution of 3GPP; the network architecture 200 may be referred to as 5GS (5G System) / EPS (Evolved Packet System), or 6GS (6G System); the network architecture 200 includes at least one of UE (User Equipment) 201, RAN (Radio Access Network) 202, core network 210, HSS (Home Subscriber Server) / UDM (Unified Data Management) 220, and Internet service 230. The network architecture 200 can interconnect with other access networks, but these entities / interfaces are not shown for simplicity. As shown, the network architecture 200 provides packet-switched services; however, those skilled in the art will readily understand that the various concepts presented throughout this application can be extended to networks providing circuit-switched services or other cellular networks. The RAN includes node 203. The RAN may also include other nodes 204. Node 203 provides user and control plane protocol termination toward UE 201. Node 203 may 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, mobile terminals (MTs) in relay equipment, or any other similar functional devices. Those skilled in the art may also refer to UE201 as a mobile station, subscriber station, mobile unit, subscriber unit, radio unit, remote unit, mobile device, radio communication device, remote device, mobile subscriber station, access terminal, mobile terminal, radio terminal, remote terminal, handheld device, user agent, mobile client, client, or any other suitable term. Node 203 is connected to the core network 210 via an S1 / NG interface. The core network 210 includes MME (Mobility Management Entity) / AMF (Access and Mobility Management Function) / SMF (Session Management Function) 211, other MME / AMF / SMF 214, S-GW (Service Gateway) / UPF (User Plane Function) 212, and P-GW (Packet Data Network Gateway) / UPF 213, as well as others not listed above. Figure 2 The nodes shown are as follows. MME / AMF / SMF211 is the control node that handles signaling between UE201 and the core network 210. Generally, MME / AMF / SMF211 provides bearer and connection management. All user IP (Internet Protocol) packets are transmitted through S-GW / UPF212, which is itself connected to P-GW / UPF213. P-GW / UPF213 provides UE IP address allocation and other functions. P-GW / UPF213 is connected to Internet service 230. Internet service 230 includes operator-compliant Internet Protocol services, specifically including the Internet, intranet, IMS (IP Multimedia Subsystem), and packet switching services.

[0184] As an example, the first node includes the UE201, and the second node includes the node203.

[0185] As an example, the UE201 is a terminal.

[0186] As one example, node 203 is a base station.

[0187] As one embodiment, the node 203 is a relay node device.

[0188] As one embodiment, the core network 210 includes LMF (Location Management Function).

[0189] As an example, the wireless link between the UE201 and the node203 includes a cellular link.

[0190] As a sub-example of the above embodiment, the messages between the UE201 and the LMF in the core network 210 are transmitted through the radio link.

[0191] Example 3

[0192] Example 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, as shown in the attached diagram. Figure 3 As shown.

[0193] Example 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for a user plane and a control plane according to this application, as shown in the attached diagram. Figure 3 As shown. Figure 3 This is a schematic diagram illustrating an embodiment of a radio protocol architecture for the user plane 350 and the control plane 300. Figure 3The radio protocol architecture for the control plane 300 between the first communication device (gNB or LMF) and the second communication device (UE) is illustrated using four layers: Layer 1, Layer 2, Layer 3, and the NAS (Non-Access Stratum) layer. Layer 1 (L1 layer) is the lowest layer and implements various PHY (Physical Layer) signal processing functions. The L1 layer will be referred to as PHY301 in this document. Layer 2 (L2 layer) 305 sits above PHY301 and is responsible for the link between the first and second communication devices. L2 layer 305 includes the MAC (Medium Access Control) sublayer 302, the RLC (Radio Link Control) sublayer 303, and the PDCP (Packet Data Convergence Protocol) sublayer 304, which terminate at the first communication device. The PDCP sublayer 304 provides multiplexing between different radio bearers and logical channels. PDCP sublayer 304 also provides security through encrypted data packets and supports cross-area mobility between the first and second communication devices. RLC sublayer 303 provides upper-layer data packet segmentation and reassembly, retransmission of lost data packets, and reordering of data packets to compensate for out-of-order reception due to HARQ. 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 between the second communication devices. MAC sublayer 302 is also responsible for HARQ operations. RRC (Radio Resource Control) sublayer 306 in Layer 3 (L3) of control plane 300 is responsible for acquiring radio resources (i.e., radio bearers) and configuring the lower layers using RRC signaling between the second and first communication devices. NAS sublayer 307 in control plane 300 is used for the transmission of non-access stratum signaling between the first and second communication devices, which is transparent and invisible to the base station. The radio protocol architecture of user plane 350 includes layer 1 (L1 layer) and layer 2 (L2 layer). The radio protocol architecture for the first and second communication devices in user plane 350 is largely the same as the corresponding layers and sublayers in control plane 300 for physical layer 351, PDCP sublayer 354 in L2 layer 355, RLC sublayer 353 in L2 layer 355 and MAC sublayer 352 in L2 layer 355. However, PDCP sublayer 354 also provides header compression for upper layer data packets to reduce radio transmission overhead.The L2 layer 355 in the user plane 350 also includes an SDAP (Service Data Adaptation Protocol) sublayer 356, which is responsible for mapping between QoS streams and data radio bearers (DRBs) to support service diversity. Although not illustrated, the second communication device may have several upper layers above the L2 layer 355, including a network layer (e.g., IP layer) terminating at the P-GW / UPF on the network side and an application layer terminating at the other end of the connection (e.g., a remote UE, server, etc.).

[0194] As an example, Appendix Figure 3 The wireless protocol architecture described above is applicable to the first node.

[0195] As an example, Appendix Figure 3 The wireless protocol architecture described above is applicable to the second node.

[0196] As an example, the first information block is generated in the NAS sublayer 307, the RRC sublayer 306, the MAC sublayer 302, or the PHY sublayer 301.

[0197] As an example, the second information block is generated in at least one of the NAS sublayer 307, the RRC sublayer 306, the MAC sublayer 302, or the PHY sublayer 301.

[0198] As an example, the third information block is generated in at least one of the NAS sublayer 307, the RRC sublayer 306, the MAC sublayer 302, or the PHY sublayer 301.

[0199] As an example, the fourth information block is generated in at least one of the NAS sublayer 307, the RRC sublayer 306, the MAC sublayer 302, or the PHY sublayer 301.

[0200] As an example, the fifth information block is generated in at least one of the NAS sublayer 307, the RRC sublayer 306, the MAC sublayer 302, or the PHY sublayer 301.

[0201] Example 4

[0202] Example 4 illustrates a schematic diagram of a first communication device and a second communication device according to an embodiment of this application, as shown in the attached diagram. Figure 4 As shown. (Attached) Figure 4 This is a block diagram of a first communication device 410 and a second communication device 450 communicating with each other in an access network.

[0203] The first communication device 410 includes at least one of 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.

[0204] The second communication device 450 includes at least one of 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.

[0205] As an example, the first communication device 410 is a core network device, and the first communication device 410 includes at least one of a controller / processor 475, a memory 476, a receiver processor 470, a transmitter processor 416, and a transmitter / receiver 418.

[0206] As an example, the first communication device 410 is an access network device, and some specific implementation methods are given below.

[0207] In the transmission from the first communication device 410 to the second communication device 450, at the first 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 DL (Downlink), the controller / processor 475 provides header compression, encryption, packet segmentation and reordering, multiplexing between logical and transport channels, and radio resource allocation to the second communication device 450 based on various priority metrics. The controller / processor 475 is also responsible for HARQ operation, retransmission of lost packets, and signaling to the second communication device 450. The transmit processor 416 and the multi-antenna transmit processor 471 implement various signal processing functions for L1 layer (i.e., physical layer). Transmit processor 416 performs encoding and interleaving to facilitate forward error correction (FEC) at the second communication device 450, and constellation mapping based on various modulation schemes (e.g., binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), M-phase shift keying (M-PSK), and M-quadrature amplitude modulation (M-QAM). Multi-antenna transmit processor 471 performs digital spatial precoding on the encoded and modulated symbols, including codebook-based precoding and non-codebook-based precoding, and beamforming processing, generating one or more... Parallel streams. Transmit processor 416 then maps each parallel stream to a subcarrier, multiplexes the modulated symbols with a reference signal (e.g., a pilot) in the time and / or frequency domains, and then uses an inverse fast Fourier transform (IFFT) to generate a physical channel carrying the time-domain O-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 multi-antenna transmit processor 471 into an RF stream, which is then provided to different antennas 420.

[0208] In the transmission from the first communication device 410 to the second communication device 450, at the second 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 parallel stream destined for the second communication device 450. Symbols on each parallel 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 over the physical channel by the first communication device 410. 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 (L2). 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 DL (Layered Logic), the controller / processor 459 provides multiplexing, packet reassembly, decryption, header decompression, and control signal processing between the transmission and logical channels to recover upper-layer packets from the core network. The upper-layer packets are then provided to all protocol layers above Layer 2. Various control signals may also be provided to Layer 3 (L3) for L3 processing. The controller / processor 459 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operation.

[0209] In the transmission from the second communication device 450 to the first communication device 410, at the second 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 first communication device 410 described in the DL, the controller / processor 459 implements header compression, encryption, packet segmentation and reordering, and multiplexing between logical and transport channels based on the radio resource allocation of the first communication device 410, implementing L2 layer functions for the user plane and control plane. The controller / processor 459 is also responsible for HARQ operations, retransmission of lost packets, and signaling to the first 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 parallel 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.

[0210] In the transmission from the second communication device 450 to the first communication device 410, the function at the first communication device 410 is similar to the receiving function at the second communication device 450 described in the transmission from the first communication device 410 to the second 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. The controller / processor 475 provides multiplexing, packet reassembly, decryption, header decompression, and control signal processing between the transmission and logical channels to recover upper-layer data packets from the second communication device 450. The upper-layer data packets from the controller / processor 475 may be provided to the core network. The controller / processor 475 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operation.

[0211] As one embodiment, the second 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. The second communication device 450 means at least: receiving a first information block, the first information block including a first inference configuration or configuration information of the first inference configuration; transmitting a second information block, the second information block including measurement results on at least one cell; and transmitting a third information block accompanying the transmission of the second information block; wherein the third information block indicates whether the first inference configuration is available in the at least one cell.

[0212] As one embodiment, the second 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 information block, the first information block including a first inference configuration or configuration information of the first inference configuration; transmitting a second information block, the second information block including measurement results in at least one cell; and transmitting a third information block accompanying the transmission of the second information block; wherein the third information block indicates whether the first inference configuration is available in the at least one cell.

[0213] As one embodiment, the first 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 first communication device 410 means at least: transmitting a first information block, the first information block including a first inference configuration or configuration information of the first inference configuration; receiving a second information block, the second information block including measurement results on at least one cell; and receiving a third information block; wherein the third information block indicates whether the first inference configuration is available in the at least one cell.

[0214] As one embodiment, the first communication device 410 includes: a memory storing a computer-readable instruction program that generates actions when executed by at least one processor, the actions including: sending a first information block, the first information block including a first inference configuration or configuration information of the first inference configuration; receiving a second information block, the second information block including measurement results on at least one cell; and receiving a third information block; wherein the third information block indicates whether the first inference configuration is available in the at least one cell.

[0215] As an example, the first node in this application includes the second communication device 450.

[0216] As an example, the second node in this application includes the first communication device 410.

[0217] As an example, some or all of the following are used to transmit the first information block: {the antenna 420, the transmitter 418, the transmitter processor 416, the multi-antenna transmitter processor 471, the controller / processor 475, and the memory 476}.

[0218] As an example, some or all of the following are used to transmit the second information block: {the antenna 452, the transmitter 454, the transmission processor 468, the multi-antenna transmission processor 457, the controller / processor 459, the memory 460, and the data source 467}.

[0219] As an example, some or all of the following are used to transmit the third information block: {the antenna 452, the transmitter 454, the transmission processor 468, the multi-antenna transmission processor 457, the controller / processor 459, the memory 460, and the data source 467}.

[0220] As an example, some or all of the following are used to transmit the fourth information block: {the antenna 420, the transmitter 418, the transmission processor 416, the multi-antenna transmission processor 471, the controller / processor 475, and the memory 476}.

[0221] As an example, some or all of the following are used to transmit the fifth information block: {the antenna 420, the transmitter 418, the transmission processor 416, the multi-antenna transmission processor 471, the controller / processor 475, and the memory 476}.

[0222] Example 5

[0223] Example 5 illustrates a transmission flowchart between a first node N1 and a second node N2 according to an embodiment of this application, as shown in the attached diagram. Figure 5 As shown.

[0224] For the second node N2, in step S5201, a first information block is sent, the first information block including a first inference configuration or configuration information of the first inference configuration; in step S52021, a second information block is received, the second information block including measurement results on at least one cell; and in step S52022, a third information block is received.

[0225] For the first node N1, in step S5101, a first information block is received, the first information block including a first inference configuration or configuration information of the first inference configuration; in step S51021, a second information block is sent, the second information block including measurement results on at least one cell; in step S51022, a third information block is sent along with the sending of the second information block;

[0226] In Example 5, the third information block indicates whether the first inference configuration is available in the at least one cell.

[0227] As an example, the serving cell of the first node N1 is associated with the first inference configuration.

[0228] As an example, at least one neighboring cell is associated with the first inference configuration.

[0229] As an example, the serving cell of the first node N1 and at least one neighboring cell are associated with the first inference configuration.

[0230] As an example, a cell being associated with the first inference configuration includes: the cell sending the first inference configuration or the configuration information of the first inference configuration.

[0231] As a sub-example of the above embodiments, the cell is the serving cell of the first node.

[0232] As an example, a cell associated with the first inference configuration includes: the cell supporting the first inference configuration or the configuration information of the first inference configuration.

[0233] As an example, a cell associated with the first inference configuration includes: the cell allocating / reserving RS resources for performing the first inference configuration.

[0234] As an example, associating a cell with the first inference configuration includes: associating the cell with the configuration information of the first inference configuration.

[0235] As a sub-example of the above embodiments, the cell is associated with the dataset ID corresponding to the first inference configuration.

[0236] As a sub-example of the above embodiments, the cell is associated with the association ID corresponding to the first inference configuration.

[0237] As a sub-example of the above embodiments, the cell is associated with the AI / ML model ID corresponding to the first inference configuration.

[0238] As a sub-example of the above embodiments, the cell is associated with the AI / ML function ID corresponding to the first inference configuration.

[0239] As one embodiment, the first information block includes RS resources for each of the at least one cell; wherein the measurement results on the at least one cell depend on the RS resources for each of the at least one cell.

[0240] As an example, whether the first inference configuration is available in the cell depends on the performance of the first node N1 in taking the RS resources of the cell as input and executing the first inference configuration.

[0241] As a sub-implementation of the above embodiments, the RS resource of the cell is the RS resource indicated in the first inference configuration, or the RS resource of the cell is the RS resource indicated in the configuration information of the first inference configuration.

[0242] As a sub-example of the above embodiment, the RS resource of the cell is the RS resource on which the first node N1 relies to send the measurement results on the cell.

[0243] As a sub-example of the above embodiments, the RS resources of the cell are included in MeasConfigIE.

[0244] As a sub-implementation of the above embodiments, the third information block includes the performance.

[0245] As a sub-implementation of the above embodiments, if the first inference configuration is available in the cell, the third information block includes the performance.

[0246] Either of the above two sub-implementations can serve as an implementation method for the third information block to indicate whether the first inference configuration is available in the at least one cell. This helps the second node understand whether the first inference configuration is available in at least one cell and its specific performance when available, which is beneficial to improving the efficiency and rationality of the second node in managing the first inference configuration.

[0247] As an example, the performance described in this application is used to measure the quality of the AI / ML model associated with the first inference configuration.

[0248] As an example, the performance described in this application is used to measure whether the output of executing the first inference configuration meets expectations.

[0249] As an example, the performance metrics described in this application include at least one of the following: AI / ML model complexity, accuracy, precision, recall, F1 score, cosine similarity, mean square error, and mean absolute error.

[0250] As an example, the complexity includes floating-point operations.

[0251] As an example, when the AI / ML function corresponding to the AI / ML model is localization, the accuracy includes at least one of horizontal accuracy and vertical accuracy.

[0252] As an example, the cosine similarity includes at least one of generalized cosine similarity and squared generalized cosine similarity.

[0253] As an example, the mean square error includes at least one of normalized mean square error, root mean square error, and equivalent mean square error.

[0254] As an example, the performance metrics described in this application include response time.

[0255] As an example, the performance metrics described in this application include convergence speed.

[0256] As an example, the performance metrics described in this application include the Numerical Spectral Efficiency Gap.

[0257] As an example, the performance metrics described in this application include throughput.

[0258] As an example, the performance metrics described in this application include at least one of BLER (Block Error Rate) and hypothetical BLER.

[0259] As an example, the performance metrics in this application include the output of executing the first inference configuration.

[0260] As an example, the performance described in this application is calculated based on the output of executing the first inference configuration and the label / ground truth of the output.

[0261] As an example, the performance described in this application is obtained during the inference phase when the first node N1 executes the first inference configuration.

[0262] As an example, the conditions under which the first inference configuration is available in the cell include: the first node N1 takes the RS resources of the cell as input and the performance metric for executing the first inference configuration is better than a first threshold.

[0263] As a sub-example of the above embodiments, the performance measure value being better than the first threshold means that the magnitude of the performance measure value is greater than the first threshold.

[0264] As a sub-example of the above embodiments, the performance measure value being better than the first threshold means that the magnitude of the performance measure value is less than the first threshold.

[0265] As an example, the conditions under which the first inference configuration is available in the cell include: the performance metric of the first node N1 performing the first inference configuration using the cell's RS resources as input is not worse than a first threshold.

[0266] As a sub-example of the above embodiments, the performance measurement value being no worse than the first threshold means that the magnitude of the performance measurement value is no greater than the first threshold.

[0267] As a sub-example of the above embodiments, the performance measurement value being no worse than the first threshold means that the magnitude of the performance measurement value is not less than the first threshold.

[0268] As a sub-implementation of either of the two embodiments described above, the first threshold is pre-configured to the first node N1.

[0269] As a sub-implementation of either of the two embodiments described above, the first threshold is indicated to the first node N1.

[0270] As a sub-implementation of either of the two embodiments described above, the first threshold is included in the first information block.

[0271] Furthermore, some non-limiting implementations of the first inference configuration and the performance of executing the first inference configuration are given below for the purpose of understanding. These different implementations may be applicable to different application scenarios.

[0272] As an example, the first inference configuration includes at least one CSI-RS configuration.

[0273] As an example, the first inference configuration is CSI-Reportconfig IE.

[0274] As an example, the first inference configuration is OtherConfig IE.

[0275] As an example, the first inference configuration includes at least one associated ID and at least one of the report types of the output of executing the first inference configuration.

[0276] As a sub-example of the above embodiments, the report type of the output of the first inference configuration includes at least one of aperiodic report, periodic report, and semi-persistent report.

[0277] As an example, the performance is the squared generalized cosine similarity (SGCS) or the normalized mean square error (NMSE).

[0278] The above embodiments are particularly suitable for CSI compression or CSI prediction scenarios.

[0279] As one embodiment, the first inference configuration includes at least a first CSI-RS resource configuration and a second CSI-RS resource configuration, wherein the measurement results on the first CSI-RS resource are used as inputs for executing the first inference configuration to predict the measurement results on the second CSI-RS resource.

[0280] As a sub-implementation of the above embodiments, the prediction includes at least one of spatial-domain correlation and temporal-domain correlation.

[0281] As an example, the first inference configuration is CSI-Reportconfig.

[0282] As an example, the first inference configuration includes at least one of the following: an associated ID, a report type of the output of executing the first inference configuration, and a time instance of measurement or prediction.

[0283] As an example, please refer to the example in the previous embodiment for an example of the report type of the output of the first inference configuration.

[0284] As an example, the first performance is CRI (Resource Indicator) or SSBRI.

[0285] The above embodiments are particularly suitable for beam management scenarios.

[0286] As an example, the first inference configuration includes at least one DL PRS resource configuration.

[0287] As an example, the first inference configuration is NR-DL-PRS-Assistance Data.

[0288] As an example, the first inference configuration is NR-DL-PRS-BeamInfo.

[0289] As an example, the first inference configuration is NR-DL-PRS-Info.

[0290] As an example, the first performance includes at least one of horizontal accuracy and vertical accuracy.

[0291] The above embodiments are particularly suitable for positioning scenarios.

[0292] As an example, the conditions under which the first inference configuration is available in the cell include: the first timer has not expired; wherein the activation of the first timer depends on the first node N1 receiving the first information block.

[0293] As a sub-implementation of the above embodiment, the first timer is pre-configured for the first node N1.

[0294] As a sub-implementation of the above embodiment, the first timer is indicated to the first node N1.

[0295] As a sub-implementation of the above embodiments, the first timer is included in the first information block.

[0296] As a sub-implementation of the above embodiments, the start of the first timer depends on the first node N1 receiving the first information block, including: the start time of the first timer corresponds to the time when the first information block is received.

[0297] As a sub-implementation of the above embodiments, the start of the first timer depends on the first node N1 receiving the first information block, including: the start time of the first timer corresponds to the time when the first node N1 starts executing the first inference configuration after receiving the first information block.

[0298] As a sub-implementation of the above embodiments, the expiration of the first timer means that the initial value of the first timer is 0, and the first timer increments to the first time value.

[0299] As a sub-implementation of the above embodiments, the expiration of the first timer means that the initial value of the first timer is a first time value, and the first timer counts down to 0.

[0300] The above embodiments can avoid the situation where the storage and computing resources of the first node are occupied due to the long execution of the first inference configuration, improve the resource utilization of the first node, and help reduce the latency and complexity of the first node sending the third information block.

[0301] As an example, the third information block includes the output result of the first node N1 taking the RS resources on the at least one cell as input and executing the first inference configuration.

[0302] As a sub-example of the above embodiment, when the first inference configuration is available in at least a third cell, the third information block includes the output result of the first node N1 taking the RS resources on the at least third cell as input and executing the first inference configuration.

[0303] As one embodiment, the first information block includes multiple inference configurations or configuration information of multiple inference configurations; the third information block indicates whether each of the multiple inference configurations is available in the at least one cell.

[0304] As a sub-implementation of the above embodiments, when the first inference configuration is unavailable in each of the at least one cell, the third information block does not include the first inference configuration or the configuration information of the first inference configuration, and can be regarded as an implementation in which the third information block indicates that the first inference configuration is unavailable in the at least one cell.

[0305] As a sub-implementation of the above embodiment, the third information block includes priority information of at least one inference configuration among a plurality of inference configurations available in the at least one cell; wherein, if no priority information is indicated for the inference configuration available in the at least one cell, the inference configuration is regarded as having the lowest priority among the plurality of inference configurations available in the at least one cell.

[0306] The above sub-implementation is beneficial for assisting the second node in managing the first node based on the priority information of the inference configuration when multiple inference configurations are available in at least one cell, thereby reducing the processing complexity of the second node.

[0307] As one embodiment, the first node N1 and the second node N2 are a user equipment and an access network device, respectively.

[0308] As a sub-implementation of the above embodiment, the second node N2 is the service access network device of the first node N1.

[0309] As one embodiment, the first information block is an RRC Reconfiguration message; or, the first information block is one or more IEs / domains in an RRC Reconfiguration message.

[0310] As a sub-implementation of the above embodiments, the first information block is CSI-MeasConfig IE.

[0311] As a sub-implementation of the above embodiments, the first inference configuration includes at least one CSI-ReportConfig IE.

[0312] As a sub-implementation of the above embodiments, the first inference configuration is a CSI-ReportConfigIE.

[0313] As a sub-implementation of the above embodiments, the first inference configuration is an OtherConfig IE.

[0314] As one embodiment, the first information block is a Provide Assistance Data message; or, the first inference configuration is one or more IEs / domains in the Provide Assistance Data message.

[0315] As one embodiment, the first information block is a RequestLocationInformation message; or, the first inference configuration is one or more IEs / domains in a RequestLocationInformation message.

[0316] As a sub-implementation of either of the two embodiments described above, the first information block is transmitted (Transport / Transfer) from the second node N2 to the first node N1 via LPP signaling / IE / domain.

[0317] As a sub-implementation of any of the two embodiments described above, the first information block is included in NAS (Non-Access Stratum) - PDU (Protocol Data Unit).

[0318] As a sub-implementation of any of the two embodiments described above, the first inference configuration includes part or all of the contents of NR-DL-TDOA-ProvideAssistanceData IE.

[0319] As a sub-implementation of either of the two embodiments described above, the first inference configuration is NR-DL-PRS-Assistance Data IE.

[0320] As a sub-implementation of either of the two embodiments described above, the first inference configuration is NR-DL-PRS-BeamInfo IE.

[0321] As a sub-implementation of either of the two embodiments described above, the first inference configuration is NR-DL-PRS-Info IE.

[0322] As an example, the second information block and the third information block are included in the same MeasurementReport message.

[0323] As an example, the second information block and the third information block are included in the same UCI.

[0324] As one embodiment, the second information block is included in a measurement report message, and the third information block is included in a UE Assistance Information message.

[0325] As an example, the second information block is included in a UCI, and the third information block is included in a UE assistance information message.

[0326] As one embodiment, the second information block is included in a measurement report message, and the third information block is included in a Provide Capabilities message.

[0327] As an example, the second information block is included in a UCI, and the third information block is included in a capability provision message.

[0328] As a sub-implementation of either of the above two embodiments, the third information block is the LPP signaling / IE / domain that is transparently transmitted (Transport / Transfer) from the first node N1 to the second node N2.

[0329] As a sub-implementation of either of the two embodiments described above, the third information block is included in NAS (Non-Access Stratum)-PDU ​​(Protocol Data Unit).

[0330] As an example, step S5022 includes: the third information block and the second message block are included in the same message or the same IE and received by the second node N2.

[0331] As an example, step S5022 includes: the third information block being included in the second message block and received by the second node N2.

[0332] As one example, how the second node N2 applies the third information block is typically implementation-related or determined by the supplier of the second node N2; some non-limiting implementation methods are given below in conjunction with other subsequent embodiments.

[0333] Typically, but not limitingly, the second node N2 indicates to the first node N1 at least one RS resource used for data collection in the first inference configuration; wherein the at least one RS resource depends on the third information block.

[0334] As a sub-implementation of the above embodiments, the at least one RS resource depending on the third information block includes: the at least one RS resource is an RS resource in at least one cell available in the first inference configuration.

[0335] As a sub-implementation of the above embodiments, the at least one RS resource depending on the third information block includes: the at least one RS resource is a subset of RS resources in at least one cell available in the first inference configuration.

[0336] As one example, the user equipment is a terminal.

[0337] As one example, the access network device is a base station.

[0338] As one embodiment, the access network device is a relay device.

[0339] Example 6

[0340] Example 6 illustrates a schematic diagram of at least one cell associated with a first inference configuration according to an embodiment of this application, as shown in the attached diagram. Figure 6 As shown. In Embodiment 6, the at least one cell includes the serving cell of the first node and at least one neighboring cell; wherein, at least one neighboring cell of the at least one cell is associated with the first inference configuration.

[0341] As an example, the serving cell of the first node is associated with the first inference configuration.

[0342] The above embodiments can assist the second node in making decisions based on whether the first inference configuration is available in the first node's serving cell and neighboring cells, thereby helping to ensure the user experience of the first node executing the first inference configuration.

[0343] As an example, the "transmission of a third information block along with the transmission of the second information block" depends on the at least one neighboring cell in the at least one cell being associated with the first inference configuration.

[0344] As a sub-implementation of the above embodiments, the "transmitting a third information block along with the transmission of a second information block" is only executed when at least one of the at least one neighboring cells in at least one of the at least one cells is associated with the first inference configuration.

[0345] As a sub-implementation of the above embodiments, if any neighboring cell in the at least one cell is not associated with the first inference configuration, the step of "sending a third information block along with sending a second information block" is not executed.

[0346] As a sub-implementation of the above embodiment, the "transmission of a third information block along with the transmission of the second information block" is triggered by a second event triggered by the measurement results on at least one neighboring cell of the at least one cell; wherein the second event includes any one of events A3, A4, A5, A6, B1 and B2.

[0347] The above embodiments help reduce the processing complexity of the first node sending the third information block and reduce unnecessary power consumption of the first node.

[0348] As an example, the first information block includes the cell identifier of each of the at least one neighboring cells in the at least one cell; wherein, for an example of the cell identifier, please refer to the relevant description in Example 1.

[0349] As an example, the third information block indicates whether the first inference configuration is available in the at least one neighboring cell of the at least one cell.

[0350] As a sub-implementation of the above embodiments, the third information block indicates whether the first inference configuration is available for each of the at least one neighboring cell in the at least one cell.

[0351] As a sub-implementation of the above embodiments, the third information block indicates that the first inference configuration is available in one of the neighboring cells of the at least one cell; wherein the first inference configuration is not available in the serving cell of the first node.

[0352] The above sub-implementation is beneficial for assisting the second node in managing the mobility of the first node according to the instructions of the third information block when the first inference configuration is unavailable in the first node's serving cell.

[0353] Example 7

[0354] Example 7 illustrates a transmission flowchart of a first node N1 receiving a fourth information block according to an embodiment of this application, as shown in the attached diagram. Figure 7 As shown, for ease of description, an appendix is ​​attached. Figure 7Only some steps are shown in the figure; for other steps not shown, please refer to Example 5.

[0355] For the second node N2, a fourth information block is sent in step S7200, and the receipt of the third information block depends on the fourth information block; the third information block is received in step S7202.

[0356] For the first node N1, in step S7100, a fourth information block is received, and the transmission of the third information block is accompanied by the transmission of the second information block depending on the fourth information block; in step S7102, the third information block is transmitted along with the transmission of the second information block.

[0357] In embodiment 7, the fourth information block includes an event that triggers the second information block.

[0358] As an example, for an example of the event that triggers the second information block, please refer to the example of the event described in Example 1 or the example of the second event in Example 5.

[0359] As an example, the fourth information block is used by the first node N1 to determine that the second information block is sent along with the third information block.

[0360] As an example, the fourth information block indicates whether the inference configuration of the first node's N1 is available in neighboring cells.

[0361] As an example, the fourth information block indicates whether the first inference configuration is available in neighboring cells.

[0362] As an example, the fourth information block indicates whether the inference configuration of the first node's N1 is available in the at least one cell.

[0363] As an example, the fourth information block indicates whether the first inference configuration is available in the at least one cell.

[0364] As an example, step S7200 is executed after step S5201; correspondingly, step S7100 is executed after step S5101.

[0365] As an example, the execution times of step S7200 and step S5201 overlap; correspondingly, the execution times of step S7100 and step S5101 overlap.

[0366] The above embodiments are beneficial for saving air interface signaling overhead.

[0367] As one embodiment, the fourth information block includes RRC signaling.

[0368] As one example, the fourth information block includes one or more RRC IEs.

[0369] As an example, the fourth information block includes one or more fields in an RRC IE.

[0370] As an example, the fourth information block and the first information block are included in the same RRC reconfiguration message.

[0371] As an example, the fourth information block and the first information block are included in two different RRC reconfiguration messages.

[0372] As an example, the fourth information block is included in the MeasConfig IE.

[0373] As an example, the signaling / IE / domain name of the fourth information block includes ReportConfig.

[0374] In embodiment 7, the indication to trigger the third information block is included in the trigger configuration of the second information block (i.e., the fourth information block) and sent by the second node to the first node. This is beneficial to reduce the power consumption of sending control signaling while strengthening the control of the second node over the first node.

[0375] Example 8

[0376] Example 8 illustrates a transmission flowchart of a first node N1 receiving a fifth information block according to an embodiment of this application, as shown in the attached diagram. Figure 8 As shown, the steps within the dashed lines are optional. For ease of description, see the appendix. Figure 8 Only some steps are shown in the figure; for other steps not shown, please refer to Example 5.

[0377] For the first node N1, in step S8102, a third information block is sent along with the transmission of the second information block; in step S8103, a fifth information block is received, the fifth information block indicating a handover command or configuration information of the secondary cell;

[0378] For the second node N2, a third information block is received in step S8202; and a fifth information block is sent in step S8203, wherein the fifth information block indicates a handover command or configuration information of the secondary cell.

[0379] In embodiment 8, the indication of the fifth information block depends on the third information block.

[0380] As one embodiment, the fifth information block includes RRC signaling.

[0381] As one example, the fifth information block includes one or more RRC IEs.

[0382] As an example, the fifth information block includes one or more fields in an RRC IE.

[0383] As an example, the fifth information block is an RRC reconfiguration message.

[0384] As an example, the fifth information block is a Handover Command message.

[0385] As an example, the fifth information block is CellGroupConfig IE.

[0386] As a sub-implementation of the above embodiment, the fifth information block is the sCellToAddModList field.

[0387] As an example, the statement "the indication of the fifth information block depends on the third information block" means that the fifth information block is triggered by the third information block.

[0388] As an example, the statement "the indication of the fifth information block depends on the third information block" means that: for the first node N1, the receiving of the fifth information block is executed after the sending of the third information block; correspondingly, for the second node N2, the sending of the fifth information block is executed after the receiving of the third information block.

[0389] As an example, the statement "the indication of the fifth information block depends on the third information block" means that the indication content in the fifth information block is generated based on the third information block.

[0390] As an example, the statement "the indication of the fifth information block depends on the third information block" means that the cell identifier included in the fifth information block is determined based on the third information block; wherein, for an example of the cell identifier, please refer to the relevant description in Example 1.

[0391] As a sub-implementation of the above embodiments, the cell identifier included in the fifth information block is at least one cell identifier among at least one cell available for the first inference configuration indicated in the third information block.

[0392] As a sub-implementation of the above embodiments, if the third information block includes the performance of the first inference configuration available in at least one cell, the cell identifier included in the fifth information block is the cell identifier corresponding to the best performance among the performances.

[0393] As a sub-implementation of the above embodiments, if the third information block includes the performance of the first inference configuration available in at least one cell, the cell identifier included in the fifth information block is at least one cell identifier corresponding to the performance being better than / not worse than a second threshold.

[0394] As a sub-implementation of the above embodiments, when the third information block includes the performance of the first inference configuration available in at least one cell, the cell identifier included in the fifth information block is at least one cell identifier corresponding to the Top N cells ranked from best to worst in the performance; where N is a configured positive integer.

[0395] As a sub-implementation of the above embodiments, when the third information block includes priority information of the first inference configuration available in at least one cell, the cell identifier included in the fifth information block is the cell identifier corresponding to the highest priority in the priority information.

[0396] As a sub-implementation of the above embodiments, when the third information block includes priority information of the first inference configuration available in at least one cell, the cell identifier included in the fifth information block is at least one cell identifier corresponding to a priority value (Value) in the priority information that is better than / not worse than a third threshold.

[0397] As a sub-implementation of the above embodiments, when the third information block includes priority information of the first inference configuration available in at least one cell, the cell identifier included in the fifth information block is at least one cell identifier corresponding to the top M priority ranked from high to low in the priority information; wherein, M is a configured positive integer.

[0398] As a sub-implementation of the above embodiments, if the third information block includes the CSI prediction result or beam prediction result of the output of the first inference configuration available in at least one cell, the cell identifier included in the fifth information block is the cell identifier with the best signal quality in CSI prediction or beam prediction.

[0399] As a sub-implementation of the above embodiments, if the third information block includes the CSI prediction result or beam prediction result of the output of the first inference configuration available in at least one cell, the cell identifier included in the fifth information block is at least one cell identifier whose CSI predicted signal quality or beam prediction signal quality is better than / not worse than a fourth threshold.

[0400] As a sub-implementation of the above embodiments, if the third information block includes the CSI prediction result or beam prediction result of the output of the first inference configuration available in at least one cell, the cell identifier included in the fifth information block is at least one cell identifier ranked Top O in terms of signal quality from best to worst in the CSI prediction or beam prediction; wherein, O is a configured positive integer.

[0401] As an example, step S5201 in Example 5 includes: the second node N2 receiving information block #1 from the third node N3, the information block #1 including at least one RS resource used for the first inference configuration on at least a fourth cell; wherein the at least fourth cell belongs to the at least one cell.

[0402] As a sub-implementation of the above embodiments, the at least one RS resource used for the first inference configuration includes: the at least one RS resource serving as input for executing the first inference configuration.

[0403] As a sub-example of the above embodiments, the at least one RS resource used for the first inference configuration includes: the at least one RS resource is used for measurement on the at least fourth cell.

[0404] As a sub-implementation of the above embodiment, the first information block includes the indication content in information block #1.

[0405] As a sub-example of the above embodiment, the third node N3 is an access network device.

[0406] As a sub-example of the above embodiments, the third node N3 is the target access network device of the first node N1; typically, but not limitingly, the third node N3 is the target base station (TargetNG-RANNode).

[0407] As a sub-example of the above embodiments, the third node N3 is a secondary access network device of the first node N1; typically, but not limitingly, the third node N3 is a secondary NG-RANNode.

[0408] As a sub-example of the above embodiments, the access network device is a base station.

[0409] As a sub-example of the above embodiments, the access network device is a relay device.

[0410] As a sub-example of the above embodiment, the third node N3 is a core network device.

[0411] As a sub-example of the above embodiment, the third node N3 is an LMF in a core network device.

[0412] As a sub-example of the above embodiment, the third node N3 is the LMF in the serving core network device of the first node N1.

[0413] In existing positioning scenarios, the downlink measurement resources used by the terminal for positioning are configured by the LMF. The serving base station accessed by the terminal may not be aware of the downlink measurement resources used by neighboring stations for positioning. The above sub-example is beneficial for assisting the second node in managing the wireless resource configuration of the first node according to the third information block in AI / ML positioning scenarios.

[0414] Example 9

[0415] Example 9 illustrates a schematic diagram of the deployment of AI / ML functionality in a RAN (Radio Access Network) domain according to an embodiment of this application; as shown in the attached diagram. Figure 9 As shown. In Example 9, the gNB can be replaced with, for example, an eNB, or a network device such as a 6G base station.

[0416] AI / ML related functions include ML training (also known as AI training, or AI / ML training), ML testing, and ML inference (also known as AI inference, or AI / ML inference), etc. ML training, ML testing, and ML inference functions can be deployed independently or co-located. Deployment of AI / ML related functions can be implemented through software, such as downloading and / or running executable files; or it can be implemented through a combination of software and hardware, such as accelerating specific computing units through hardware to improve computing speed or save power.

[0417] ML 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, ML training functions for MDA (Management Data Analytics) can be deployed in MDAF (MDA Function); ML training for network data analytics can be deployed in NWDAF (Network Data Analytics Function), meaning the ML training function is an MTLF (Model Training Logical Function).

[0418] The ML inference function can also be deployed in a cross-domain management system or a domain-specific management system; for example, the ML inference function is MDAF, or the ML inference function is AnLF (Analytics logical function) located in NWDAF.

[0419] Similarly, ML testing functionality can also be deployed in cross-domain management systems or domain-specific management systems.

[0420] In Example 9, the RAN domain ML training function 902 is located in the RAN domain management function 903; while the ML inference function is located in the base station, that is, the AI / ML inference function 904 is located in gNB 905, the AI / ML inference function 906 is located in gNB 907, and so on.

[0421] Appendix Figure 9 In this context, the management of ML inference functions across multiple base stations is handled by the RAN domain management function 903, which interacts with the RAN domain MnS (Management Service) consumer / cross-domain management 901 (as shown in the attached diagram). Figure 9 (As shown by the dashed arrow in the image).

[0422] Optionally, the management of ML inference function 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 901.

[0423] It should be noted that Example 9 is merely a non-limiting implementation; optionally, the ML training function of the RAN domain may also be deployed in the base station; or optionally, some base stations may deploy both the ML inference function and the ML training function of the RAN domain, while some base stations may only deploy the ML inference function.

[0424] As an example, one of the gNBs (or base stations) in Example 9 is the second node of this application.

[0425] Example 10

[0426] Example 10 illustrates a schematic diagram of the deployment of AI / ML functions in a UE according to an embodiment of this application; as shown in the appendix. Figure 10 As shown. (Attached) Figure 10 The RAN domain ML training function 1005 is optional.

[0427] UE function 1004 is deployed in the first node of this application, and the UE function 1004 includes AI / ML inference function 1006; the AI / ML inference function 1006 uses an ML model (also called an AI model) for inference; an ML model is typically trained before being used for AI / ML inference.

[0428] As an example, the UE function 1004 includes a RAN domain ML training function 1005, which runs training data through an ML model to obtain a relevant loss and adjusts the parameters of the ML model based on the calculated loss; the ML training includes at least one of ML initial training, ML re-training, and reinforcement learning.

[0429] 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.

[0430] Optionally, the UE function 1004 also includes a CN domain ML training function. Figure 10 (Not included in the text).

[0431] Optionally, the UE function 1004 also includes an AI / ML deployment function. Figure 10 It is not included in the list, which is used to load ML models and data.

[0432] As an example, the first node indicates whether it supports ML training function (RAN domain or CN domain) through capability reporting. The capability reporting is RRC signaling or NAS (Non-Access Stratum) signaling.

[0433] As an example, the ML model and the associated metadata are loaded by the first node from a network device or a remote server.

[0434] Optionally, the UE function 1004 is an MnS (Management Service) producer that provides data to the CN domain MnF (Management Function) 1001, and / or the RAN domain MnF 1002, and / or the cross-domain management system 1003 for management or analysis (as shown by double arrow 1007).

[0435] Optionally, the UE function 1004 is an MnS consumer that loads data from the CN domain MnF (Management Function) 1001, and / or the RAN domain MnF 1002, and / or the cross-domain management system 1003 for AI / ML-related management, such as managing data requests, ML model activation, and / or ML training (as shown by double arrow 1007).

[0436] As an example, the performance of executing the first inference configuration in this application is obtained by inference using an ML model (also known as an AI model) by the AI / ML inference function 1006.

[0437] As one embodiment, at least one of the first receiver and the first transmitter includes an attachment Figure 10 One of the RAN domain ML training functions is 1005.

[0438] As one embodiment, at least one of the first receiver and the first transmitter includes an attachment Figure 10 One of the AL / ML inference functions is 1006.

[0439] As an example, the ML model is a model based on NN (Neural Networks).

[0440] As an example, the ML model is based on an ANN (Artificial Neural Networks) model.

[0441] As an example, the ML model is based on a CNN (Conventional Neural Networks) model.

[0442] As an example, the ML model is based on a GNN (Graph Neural Network) model.

[0443] As an example, the ML model is based on the LLM (Large Language Model) architecture.

[0444] As an example, the ML model is based on the Transformer architecture.

[0445] As an example, the ML model is based on the GPT (Generative Pre-Trained) architecture.

[0446] As an example, the ML model is based on an LSTM (Long Short-Term Memory) network.

[0447] As an example, the ML model is based on an MLP (MultiLayer Perceptron) model.

[0448] As an example, the ML model is based on GAN (Generative Adversarial Nets).

[0449] As an example, the ML model is based on a lightweight neural network.

[0450] As an example, the lightweight neural network includes one or more of MobileNet, ShuffleNet, and SqueezeNet.

[0451] Example 11

[0452] Example 11 illustrates a schematic diagram of a processing system based on artificial intelligence or machine learning according to an embodiment of this application, as shown in the attached diagram. Figure 11 As shown. In the appendix Figure 11 In this context, the processing system based on artificial intelligence or machine learning includes a first processor, a second processor, a third processor, and a fourth processor.

[0453] In Example 11, the first processor sends a first dataset to the second processor and a second dataset to the third processor; the second processor generates a target first-class parameter set based on the first dataset, and sends the generated target first-class parameter set to the third processor; the third processor processes the second dataset using the target first-class parameter set to obtain a first-class output, optionally, the third processor sends the first-class output to the fourth processor. (See Appendix...) Figure 11 In this configuration, the first type of feedback and the second type of feedback are optional; the second processor includes ML training functionality; and the third processor includes ML inference functionality.

[0454] As one embodiment, the fourth processor includes ML testing functionality.

[0455] As one embodiment, the fourth processor includes performance monitoring / evaluation of the ML model.

[0456] As an example, the third processor sends a first type of feedback to the second processor; the first type of feedback is used to trigger the recalculation or update of the target first type of parameter set, that is, to trigger ML initial training or ML retraining.

[0457] As one embodiment, the fourth processor sends a second type of feedback to the first processor; the second type of feedback is used to generate the first dataset or the second dataset, or the second type of feedback is used to trigger the sending of the first dataset or the sending of the second dataset.

[0458] As one embodiment, the first processor generates the first dataset and the second dataset based on the measurement of the reference signal.

[0459] As an example, both the first processor and the second processor belong to the first node.

[0460] As an example, the second processor belongs to the first node; the above method avoids passing the first dataset to the second node.

[0461] As one embodiment, the third processor belongs to the first node, and the fourth processor belongs to the second node.

[0462] As an example, both the third processor and the fourth processor belong to the first node.

[0463] As an example, the first dataset includes training data.

[0464] As one embodiment, the second processor is used to train an ML model, and the trained model is described by the target first class of parameter sets.

[0465] As an example, the second dataset includes inference data.

[0466] As an example, the third processor constructs a model based on the target first type of parameter group, and then inputs the second dataset into the constructed model to obtain the first type of output.

[0467] As an example, the target first type of parameter group includes at least one AI / ML model associated with the first inference configuration in this application.

[0468] As an example, the output of the third processor includes the performance of executing the first inference configuration as described in this application.

[0469] As an example, the output of the third processor includes the output result of executing the first inference configuration in this application.

[0470] As an example, the third processor generates a recovery dataset based on the first type of output, and the error between the recovery dataset and the second dataset is used to generate the first type of feedback.

[0471] As an example, the first type of feedback is used to reflect the performance of the trained model; when the performance of the trained model fails to meet the requirements, the second processing opportunity will recalculate the target first type of parameter set.

[0472] As an example, when the error is too large or the update has not been performed for too long, the performance of the trained model is considered to be unsatisfactory.

[0473] As an example, the target first type of parameter group includes one or more of the following: convolution kernel, pooling kernel, pooling function, activation function, parameters of the pooling function, or parameters of the activation function.

[0474] As an example, the target first type of parameter group includes one or more of the following: convolution kernel size, number of convolution layers, convolution stride, pooling kernel size, pooling kernel stride, pooling function, activation function, or number of feature maps.

[0475] Example 12

[0476] Example 12 illustrates a schematic diagram based on artificial intelligence or machine learning according to an embodiment of this application, as shown in the attached diagram. Figure 12 As shown. In the appendix Figure 12 In this process, the first and second operations belong to the first stage, the third operation belongs to the second stage, the fourth operation belongs to the third stage, and the fifth operation belongs to the fourth stage; the arrowed lines indicate the sequence of the process.

[0477] As an example, the first operation includes AI / ML training, the second operation includes AI / ML testing, the third operation includes AI / ML emulation, the fourth operation includes AI / ML entity loading, and the fifth operation includes AI / ML inference.

[0478] As one embodiment, 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.

[0479] As an example, the first stage includes AI / ML model training.

[0480] As an example, the first stage includes AI / ML model training and AI / ML testing.

[0481] As an example, the AI / ML model training includes initial training and re-training of one or a group of AI / ML entities.

[0482] As an example, the training of the AI / ML model depends on training data.

[0483] As an example, the AI / ML model training includes AI / ML entity validation.

[0484] As an example, the AI / ML entity verification is used to evaluate the performance of the AI / ML entity.

[0485] As an example, the AI / ML entity verification relies on verification data.

[0486] As an example, if the AI / ML entity verification results do not meet expectations, the AI / ML model will be retrained.

[0487] As an example, the AI / ML testing includes testing the validated AI / ML entities to estimate the performance of the trained AI / ML model.

[0488] 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.

[0489] As an example, the AI / ML test relies on test data.

[0490] As one embodiment, the second stage includes AI / ML simulation, which performs AI / ML entity reasoning in a simulation environment.

[0491] As an example, the AI / ML simulation estimates the performance of AI / ML entity reasoning in a simulation environment before using AI / ML entities.

[0492] As one embodiment, the second stage is optional.

[0493] 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 function.

[0494] As an example, the third stage is optional.

[0495] As an example, the third stage is no longer needed when the training and inference functions are co-located.

[0496] As an example, the fourth stage includes AI / ML inference.

[0497] Example 13

[0498] Example 13 illustrates a structural block diagram of a processing apparatus for a first node according to an embodiment of this application; as shown in the appendix. Figure 13 As shown. In the appendix Figure 13 In the first node, the processing device 1300 includes a first receiver 1301 and a first transmitter 1302.

[0499] The first receiver 1301 receives a first information block, the first information block including a first inference configuration or configuration information of the first inference configuration; the first transmitter 1302 transmits a second information block, the second information block including measurement results on at least one cell; and a third information block is transmitted along with the transmission of the second information block.

[0500] In Example 13, the third information block indicates whether the first inference configuration is available in the at least one cell.

[0501] As an example, at least one neighboring cell in the at least one cell is associated with the first inference configuration.

[0502] As a sub-implementation of the above embodiments, the third information block indicates whether the first inference configuration is available in the at least one neighboring cell of the at least one cell.

[0503] As a sub-implementation of either of the above two embodiments, the first information block includes the cell identifier of each of the at least one neighboring cell in the at least one cell.

[0504] As one embodiment, the first information block includes multiple inference configurations or configuration information of multiple inference configurations; the third information block indicates whether each of the multiple inference configurations is available in the at least one cell.

[0505] As one embodiment, the first receiver 1301 receives a fourth information block, and the transmission of the third information block accompanies the transmission of the second information block and depends on the fourth information block; wherein, the fourth information block includes an event that triggers the second information block.

[0506] As one embodiment, the first receiver 1301 receives a fifth information block, which indicates a handover command or configuration information of a secondary cell; wherein the indication of the fifth information block depends on the third information block.

[0507] As one example, the first node is a user equipment.

[0508] As one example, the user equipment is a terminal.

[0509] As an example, the first receiver 1301 includes at least one of the following in embodiment 4: {antenna 452, receiver 454, receiver processor 456, multi-antenna receiver processor 458, controller / processor 459, memory 460, data source 467}.

[0510] As an example, the first transmitter 1302 includes at least one of the following in embodiment 4: {antenna 452, transmitter 454, transmission processor 468, multi-antenna transmission processor 457, controller / processor 459, memory 460, data source 467}.

[0511] Example 14

[0512] Example 14 illustrates a structural block diagram of a processing apparatus for a second node according to an embodiment of this application; as shown in the appendix. Figure 14 As shown. In the appendix Figure 14In the second network device, the processing unit 1400 includes a second receiver 1401 and a second transmitter 1402.

[0513] The second transmitter 1402 transmits a first information block, the first information block including a first inference configuration or configuration information of the first inference configuration; the second receiver 1401 receives a second information block, the second information block including measurement results on at least one cell; and receives a third information block.

[0514] In Example 14, the third information block indicates whether the first inference configuration is available in the at least one cell.

[0515] As an example, at least one neighboring cell in the at least one cell is associated with the first inference configuration.

[0516] As a sub-implementation of the above embodiments, the third information block indicates whether the first inference configuration is available in the at least one neighboring cell of the at least one cell.

[0517] As a sub-implementation of either of the above two embodiments, the first information block includes the cell identifier of each of the at least one neighboring cell in the at least one cell.

[0518] As one embodiment, the first information block includes multiple inference configurations or configuration information of multiple inference configurations; the third information block indicates whether each of the multiple inference configurations is available in the at least one cell.

[0519] As one embodiment, the second transmitter 1402 transmits a fourth information block, and the reception of the third information block depends on the fourth information block; wherein, the fourth information block includes an event that triggers the second information block.

[0520] As one embodiment, the second transmitter 1402 sends a fifth information block, which indicates a handover command or configuration information of a secondary cell; wherein the indication of the fifth information block depends on the third information block.

[0521] In one embodiment, the second node is an access network device.

[0522] As one example, the access network device is a base station device.

[0523] As one embodiment, the access network device is a relay node device.

[0524] As one embodiment, the second receiver 1401 includes at least one of the following in embodiment 4: {antenna 420, receiver 418, receiver processor 470, multi-antenna receiver processor 472, controller / processor 475, memory 476}.

[0525] As one embodiment, the second transmitter 1402 includes at least one of the following in embodiment 4: {antenna 420, transmitter 418, transmission processor 416, multi-antenna transmission processor 471, controller / processor 475, memory 476}.

[0526] 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 equipment, vehicles, RSUs, wireless sensors, internet access cards, IoT terminals, RFID terminals, NB-IoT terminals, MTC (Machine Type Communication) terminals, eMTC (enhanced MTC) terminals, data cards, internet access cards, vehicle-mounted communication equipment, low-cost mobile phones, low-cost tablets, and other wireless communication devices. The base stations or system equipment in this application include, but are not limited to, macrocell base stations, microcell base stations, small cell base stations, home base stations, relay base stations, eNBs, gNBs, TRPs (Transmitter Receiver Points), GNSS, relay satellites, satellite base stations, airborne base stations, RSUs (Road Side Units), drones, and testing equipment, such as transceivers or signaling testers that simulate some functions of a base station, and other wireless communication equipment.

[0527] Those skilled in the art will understand that the present invention can be practiced in other specified forms without departing from its core or essential characteristics. Therefore, the embodiments disclosed herein should in any way be considered descriptive rather than restrictive. The scope of the invention is defined by the appended claims rather than the foregoing description, and all modifications within their equivalent meaning and scope are considered to be included therein.

Claims

1. A first node used for wireless communication, characterized in that, include: A first receiver receives a first information block, the first information block including a first inference configuration or configuration information of the first inference configuration; A first transmitter transmits a second information block, the second information block including measurement results on at least one cell; accompanied by the transmission of the second information block, a third information block is transmitted; The third information block indicates whether the first inference configuration is available in the at least one cell.

2. The first node according to claim 1, characterized in that, At least one neighboring cell in the at least one cell is associated with the first inference configuration.

3. The first node according to claim 2, characterized in that, The third information block indicates whether the first inference configuration is available in the at least one neighboring cell of the at least one cell.

4. The first node according to claim 2 or 3, characterized in that, The first information block includes the cell identifier of each of the at least one neighboring cell in the at least one cell.

5. The first node according to any one of claims 1 to 4, characterized in that, The first information block includes multiple inference configurations or configuration information of multiple inference configurations; the third information block indicates whether each of the multiple inference configurations is available in the at least one cell.

6. The first node according to any one of claims 1 to 5, characterized in that, include: The first receiver receives the fourth information block, and the transmission of the third information block accompanies the transmission of the second information block and depends on the fourth information block; The fourth information block includes the event that triggers the second information block.

7. The first node according to any one of claims 1 to 6, characterized in that, include: The first receiver receives a fifth information block, which indicates a handover command or configuration information of the secondary cell; The indication of the fifth information block depends on the third information block.

8. A second node used for wireless communication, characterized in that, include: The second transmitter sends a first information block, the first information block including a first inference configuration or configuration information of the first inference configuration; A second receiver receives a second information block, which includes measurement results from at least one cell; and receives a third information block. The third information block indicates whether the first inference configuration is available in the at least one cell.

9. A method used in a first node of wireless communication, characterized in that, include: Receive a first information block, the first information block including a first inference configuration or configuration information of the first inference configuration; A second information block is sent, the second information block including measurement results on at least one cell; accompanied by the sending of the second information block, a third information block is sent. The third information block indicates whether the first inference configuration is available in the at least one cell.

10. A method used in a second node of wireless communication, characterized in that, include: Send a first information block, the first information block including a first inference configuration or configuration information of the first inference configuration; Receive a second information block, which includes measurement results on at least one cell; receive a third information block; The third information block indicates whether the first inference configuration is available in the at least one cell.

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