Method and apparatus used in node for wireless communication mobility management

Abstract

The present application discloses a method and apparatus used in a node for wireless communication mobility management. A first node sending a first measurement report in a first cell, and then sending a first signal; the first measurement report comprises at least one of channel quality of the first cell or channel quality of a second cell; the second cell is a cell external to the first node; the first signal is intended for the second cell; a transmission power value of the first signal depends on a generation manner of the first measurement report; and the generation manner of the first measurement report is either an AI-based generation manner or a non-AI-based generation manner. The present application supports the fusion of AI and communications, enhances the level of intelligence of networks, optimizes mobility management, improves signal mobility support, and increases the quality of service of a system.

Description

A method and apparatus for use in a node for wireless communication mobility management Technical Field

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

[0002] The application scenarios of future wireless communication systems are becoming increasingly diversified. In order to meet the different performance requirements of different scenarios, 3GPP (3rd Generation Partner Project) is actively researching how to combine AI (Artificial Intelligence) / ML (Machine Learning) technologies with mobile communications. The main application scenarios involve multiple aspects such as network automation, optimizing resource allocation, and improving service continuity for mobile users.

[0003] User equipment (UE) mobility is an important feature of wireless networks. To further enhance UE mobility performance, L1 / L2 Triggered Mobility (LTM), introduced in 3GPP Rel-18 (Release-18), is an important research direction for reducing latency, overhead, and downtime. Rel-19 will further investigate support for inter-cell handover (HO) across centralized units and explore the feasibility of using AI / ML for beam prediction and UE mobility prediction.

[0004] Furthermore, AI / ML can achieve load balancing and energy savings by analyzing measured and predicted resource status information (such as physical resource block utilization of neighboring and serving cells, number of active UEs, etc.). In addition, AI / ML can optimize radio resource management strategies by predicting UE movement trajectories, enabling the network to make resource allocation and handover decisions based on the UE's expected movement path. AI / ML-based mobility management not only helps improve handover accuracy and efficiency but also reduces handover downtime and enhances user experience. In the future, 3GPP will further deepen the application of AI / ML in mobility management, promoting the deep integration of AI / ML with communication networks to improve network intelligence, optimize mobility management, improve spectrum and energy efficiency, and provide users with more stable and efficient mobile communication services. Summary of the Invention

[0005] In NR (New Radio) systems, network-controlled mobility can be applied to UEs in the RRC_CONNECTED state. Specifically, the network configures measurement and reporting parameters for the UE through higher-layer signaling. The RRC_CONNECTED UE performs measurements according to the measurement configuration and sends a measurement report when the conditions are met. After receiving the measurement report, the base station decides whether to hand over the UE to another cell based on the measurement report. In AI / ML scenarios, AI / ML models can predict the UE's movement path through massive amounts of data, helping the base station to make better resource allocation and handover decisions. Therefore, enhancing mobility management based on AI / ML is a problem worth studying.

[0006] To address the aforementioned issues, this application discloses a solution. It should be noted that while the NR system is used as an example in the above description, this application is also applicable to scenarios such as future 6G systems, achieving similar technical effects. Furthermore, although this application is initially intended for AI / ML scenarios, it can also be applied to other non-AI / ML scenarios. Furthermore, adopting a unified design scheme for different scenarios (such as other non-AI / ML scenarios, including but not limited to Vehicle to Everything (V2X), capacity enhancement systems, short-range communication systems, NTN (Non-Terrestrial Network), IoT (Internet of Things), and URLLC (Ultra-Reliable Low-Latency Communication) networks) helps reduce hardware complexity and cost. Unless otherwise specified, embodiments and features in any node of this application can be applied to any other node. Unless otherwise specified, embodiments and features in any node of this application can be arbitrarily combined.

[0007] In particular, the interpretation of terms, nouns, functions, and variables in this application (unless otherwise specified) can be found in the definitions of the TS38 and TS37 series of 3GPP (3rd Generation Partnership Project) Technical Specifications (TS). Where necessary, reference can be made to TS38.211, TS38.212, TS38.213, TS38.214, TS38.215, TS38.300, TS38.304, TS38.305, TS38.321, TS38.331, TS37.355, and TS38.423 in the 3GPP technical specifications to aid in understanding this application.

[0008] As an example, the interpretation of terms in this application is based on the definitions in the 3GPP specification protocol TS38 series.

[0009] As an example, the interpretation of terms in this application is based on the definitions in the 3GPP specification protocol TS37 series.

[0010] As an example, the interpretation of the terms in this application is based on the definitions in the 3GPP specification protocol TS40 series.

[0011] As an example, the interpretation of terms in this application is based on the definitions in the 3GPP specification protocol TS39 series.

[0012] As an example, the interpretation of the terms used in this application is based on the definitions in 3GPP specification protocol Rel-17.

[0013] As an example, the interpretation of the terms used in this application is based on the definitions in 3GPP specification protocol Rel-18.

[0014] As an example, the interpretation of the terms used in this application is based on the definitions in 3GPP specification protocol Rel-19.

[0015] As an example, the interpretation of the terms used in this application is based on the definitions in 3GPP specification protocol Rel-20.

[0016] This application discloses a method used in a first node for wireless communication mobility management, comprising:

[0017] Send the first measurement report in the first cell, followed by the first signal;

[0018] Wherein, the first measurement report includes at least one of the channel quality of the first cell or the channel quality of the second cell; the second cell is a cell other than the first node; the first signal is directed to the second cell; the transmit power value of the first signal depends on the generation method of the first measurement report; the generation method of the first measurement report is one of AI-based generation or not based on AI generation.

[0019] As an example, the problem this application aims to solve includes: how to determine the transmission power value of the first signal in an AI / ML scenario.

[0020] As an example, the problem this application aims to solve includes power control in AI / ML scenarios.

[0021] As an example, the problem this application aims to solve includes: how to determine the transmission power value for sending signals to the destination cell in AI / ML-based mobility management.

[0022] As an example, the features of the above method include: in this application, the first node determines the transmission power value of the signal sent to the target cell according to the generation method of the measurement report, thereby solving the above problem.

[0023] As an example, the features of the above method include: the first cell is the source cell of the first node, and the second cell is the destination cell of the first node.

[0024] As an example, the features of the above method include: the generation method of the first measurement report includes the generation method of the channel quality included in the first measurement report.

[0025] As an example, the features of the above method include: the generation of the first measurement report includes an event that triggers the generation of the first measurement report.

[0026] As an example, the features of the above method include: this application is applicable to mobility management under RRC_CONNECTED.

[0027] As an example, the advantages of the above method include: this application supports the application of AI / ML in mobility management, promotes the deep integration of AI / ML with communication networks, improves the intelligence level of the network, optimizes mobility management, improves spectrum and energy efficiency, and provides users with more stable and efficient mobile communication services.

[0028] As an example, the advantages of the above method include: enhanced power control of uplink wireless signals, ensuring reliable signal transmission while reducing terminal power consumption.

[0029] As an example, the advantages of the above method include: improving signal mobility support and enhancing the quality of service of the system.

[0030] As an example, the benefits of the above method include: generating measurement reports based on AI helps to predict changes in channel quality in advance, reduces the probability of beam failure or connection interruption, optimizes radio resource management strategies, and enables the network to make resource allocation and handover decisions based on the UE's expected movement path.

[0031] According to one aspect of this application, the above method is characterized in that, when the generation method of the first measurement report is based on AI generation, the transmission power value of the first signal depends on the first path loss and the second path loss; when the generation method of the first measurement report is not based on AI generation, the transmission power value of the first signal depends on the second path loss; the first path loss and the second path loss are respectively for the first cell and the second cell.

[0032] As an example, the problem this application aims to solve includes: how to determine the transmission power value of the signal sent to the destination cell in AI / ML-based mobility management.

[0033] As an example, the features of the above method include: in this application, the first node determines the path loss on which it sends a signal to the target cell based on the generation method of the measurement report, thereby solving the above problem.

[0034] As an example, the features of the above method include: the first path loss is the downlink path loss of the first cell, and the second path loss is the downlink path loss of the second cell.

[0035] As an example, the advantages of the above method include: the generation method of the first measurement report is not based on AI and is compatible with the current standard, with minimal changes to the standard and good compatibility.

[0036] As an example, the advantages of the above method include achieving a balance between reducing signal interference and improving cell coverage.

[0037] As an example, the advantages of the above method include: ensuring the stability of the handover or LTM process and reducing the probability of communication interruption due to handover failure.

[0038] According to one aspect of this application, the above method is characterized in that the generation method of the first measurement report is based on AI generation, which means at least one of the following:

[0039] - The first measurement report is generated through prediction;

[0040] - The first measurement report was generated through inference;

[0041] - The first measurement report is generated by a model, which is at least one of AI or ML.

[0042] As an example, the features of the above method include: the first measurement report is the output of an AI and / or ML model, or the first measurement report includes the output of an AI and / or ML model.

[0043] As an example, the features of the above method include: the first measurement report is a prediction or inference of channel quality by the first node based on AI.

[0044] As an example, the advantages of the above method include: it facilitates the deep integration of mobile communication networks and AI.

[0045] As an example, the benefits of the above method include: improving system performance and increasing the efficiency and reliability of the communication system.

[0046] According to one aspect of this application, the above method is characterized in that, when the generation method of the first measurement report is based on AI generation, the transmission power value of the first signal is not greater than the smaller of a first power value and a second power value, wherein the first power value depends on the first path loss and the second power value depends on the second path loss; when the generation method of the first measurement report is not based on AI generation, the transmission power value of the first signal is not greater than a third power value, wherein the third power value depends on the second path loss.

[0047] As an example, the features of the above method include: the first power value is linearly correlated with the first path loss, and the second power value is linearly correlated with the second path loss.

[0048] As an example, the features of the above method include: when the generation method of the first measurement report is not based on AI generation, the second power value is compatible with current standards.

[0049] As an example, the features of the above method include: when the generation method of the first measurement report is based on AI generation, the second power value is compatible with the current standard when it is not greater than the first power value.

[0050] As an example, the feature of the above method includes: the third power value is equal to the second power value.

[0051] As an example, the advantages of the above method include: reducing the interference of the first signal to the first cell, ensuring reliable signal transmission while reducing terminal power consumption.

[0052] As an example, the advantages of the above method include: ensuring the stability of the handover or LTM process and reducing the probability of communication interruption due to handover failure.

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

[0054] Receive the first reference signal and the second reference signal;

[0055] Wherein, the channel quality of the first cell depends on the reception of the first reference signal, and the channel quality of the second cell depends on the reception of the second reference signal; the channel quality of the second cell is better than the channel quality of the first cell.

[0056] As an example, the problem this application aims to solve includes: how to determine the channel quality of the first cell and the second channel quality of the second cell.

[0057] As an example, the features of the above method include: in this application, the first node receives a first reference signal and a second reference signal, and determines the channel quality of the first cell and the second channel quality of the second cell based on the first reference signal and the second reference signal, respectively, thereby solving the above problem.

[0058] As an example, the features of the above method include: when the channel quality of the first cell is generated based on AI, the input of the AI ​​model inference stage includes the first reference signal, and the output includes part or all of the channel quality of the first cell; when the channel quality of the second cell is generated based on AI, the input of the AI ​​model inference stage includes the second reference signal, and the output includes part or all of the channel quality of the second cell.

[0059] As an example, the features of the above method include: the first measurement report is event-triggered, the event including that the channel quality of the second cell is better than the channel quality of the first cell.

[0060] As an example, the features of the above method include: the first measurement report indicates that the channel quality of the second cell is better than the channel quality of the first cell.

[0061] As an example, the features of the above method include: the first measurement report is generated based on AI, and the output of the AI ​​includes an indication that the channel quality of the second cell is better than the channel quality of the first cell.

[0062] As an example, the advantages of the above method include: compatibility with mobility management in the current RRC_CONNECTED state, with minimal changes to the current standard.

[0063] According to one aspect of this application, the above method is characterized by comprising:

[0064] Receive the first signaling;

[0065] The transmission of the first signal depends on the first signaling.

[0066] As an example, the features of the above method include: in response to receiving the first signaling, the first node sends the first signal.

[0067] As an example, the features of the above method include: the first signal instructing the first node to correctly receive the first signaling.

[0068] As an example, the features of the above method include: the first signaling instructs the first node to send the first signal.

[0069] As an example, the advantages of the above method include: good compatibility.

[0070] As an example, the advantages of the above method include: increasing the probability of successful handover.

[0071] According to one aspect of this application, the above method is characterized by comprising:

[0072] Receive a second signaling message, which configures the measurement object and measurement time for the first cell and the second cell, respectively;

[0073] Specifically, at least one channel measurement value for the first cell is obtained by measuring the measurement object for the first cell during the measurement time, and at least one channel measurement value for the second cell is obtained by measuring the measurement object for the second cell during the measurement time; when the first measurement report is generated based on AI, at least one of the at least one channel measurement value for the first cell or the at least one channel measurement value for the second cell is used to generate the first measurement report.

[0074] As an example, the features of the above method include: when the generation method of the first measurement report is based on AI generation, it means that the content of the first measurement report is generated based on AI.

[0075] As an example, the features of the above method include: the first measurement report includes at least one of the channel measurement values ​​for the first cell or at least one of the channel measurement values ​​for the second cell.

[0076] As an example, the features of the above method include: the input to the AI ​​model that generates the first measurement report includes at least one of the channel measurement values ​​for the first cell or at least one of the channel measurement values ​​for the second cell.

[0077] As an example, the benefits of the above method include reducing the impact of the ping-pong effect during handover or LTM.

[0078] As an example, the advantages of the above method include: promoting the convergence of AI and mobile networks while reducing the impact on current standards.

[0079] According to one aspect of this application, the above method is characterized in that the first node is a user equipment.

[0080] According to one aspect of this application, the above method is characterized in that the first node is a relay node.

[0081] According to one aspect of this application, the above method is characterized in that the first node has AI / ML capabilities.

[0082] According to one aspect of this application, the above method is characterized in that the first node supports AI / ML-based measurement reports.

[0083] According to one aspect of this application, the above method is characterized in that the first node supports AI / ML-based mobility management.

[0084] This application discloses a method used in a second node for wireless communication mobility management, comprising:

[0085] Receive the first measurement report in the first cell, and then receive the first signal;

[0086] Wherein, the first measurement report includes at least one of the channel quality of the first cell or the channel quality of the second cell; the second cell is a cell other than the sender of the first measurement report; the first signal is directed to the second cell; the transmission power value of the first signal depends on the generation method of the first measurement report; the generation method of the first measurement report is one of AI-based generation or not based on AI generation.

[0087] According to one aspect of this application, the above method is characterized in that, when the generation method of the first measurement report is based on AI generation, the transmission power value of the first signal depends on a first path loss and a second path loss; when the generation method of the first measurement report is not based on AI generation, the transmission power value of the first signal depends on a second path loss; the first path loss and the second path loss are respectively for the first cell and the second cell.

[0088] According to one aspect of this application, the above method is characterized in that the generation method of the first measurement report is based on AI generation, which means at least one of the following:

[0089] - The first measurement report is generated through prediction;

[0090] - The first measurement report was generated through inference;

[0091] - The first measurement report is generated by a model, which is at least one of AI or ML.

[0092] According to one aspect of this application, the above method is characterized in that, when the generation method of the first measurement report is based on AI generation, the transmission power value of the first signal is not greater than the smaller of a first power value and a second power value, wherein the first power value depends on the first path loss and the second power value depends on the second path loss; when the generation method of the first measurement report is not based on AI generation, the transmission power value of the first signal is not greater than a third power value, wherein the third power value depends on the second path loss.

[0093] According to one aspect of this application, the above method is characterized by comprising:

[0094] Send the first reference signal and the second reference signal;

[0095] Wherein, the channel quality of the first cell depends on the reception of the first reference signal, and the channel quality of the second cell depends on the reception of the second reference signal; the channel quality of the second cell is better than the channel quality of the first cell.

[0096] According to one aspect of this application, the above method is characterized by comprising:

[0097] Send the first signaling;

[0098] The transmission of the first signal depends on the first signaling.

[0099] According to one aspect of this application, the above method is characterized by comprising:

[0100] Send a second signaling message, which configures the measurement object and measurement time for the first cell and the second cell, respectively;

[0101] Specifically, at least one channel measurement value for the first cell is obtained by measuring the measurement object for the first cell during the measurement time, and at least one channel measurement value for the second cell is obtained by measuring the measurement object for the second cell during the measurement time; when the first measurement report is generated based on AI, at least one of the at least one channel measurement value for the first cell or the at least one channel measurement value for the second cell is used to generate the first measurement report.

[0102] According to one aspect of this application, the method described above is characterized in that the second node is a base station.

[0103] According to one aspect of this application, the above method is characterized in that the second node is a user equipment.

[0104] According to one aspect of this application, the above method is characterized in that the second node is a TRP.

[0105] According to one aspect of this application, the method is characterized in that the second node is associated with multiple cells, the multiple cells including the first cell and the second cell.

[0106] According to one aspect of this application, the above method is characterized in that the second node manages the first cell and the second cell.

[0107] According to one aspect of this application, the above method is characterized in that the first signal is received in the second cell.

[0108] According to one aspect of this application, the above method is characterized in that the second reference signal is transmitted in the second cell.

[0109] This application discloses a first node used for wireless communication mobility management, comprising:

[0110] The first transmitter sends the first measurement report in the first cell, and then sends the first signal;

[0111] Wherein, the first measurement report includes at least one of the channel quality of the first cell or the channel quality of the second cell; the second cell is a cell other than the first node; the first signal is directed to the second cell; the transmit power value of the first signal depends on the generation method of the first measurement report; the generation method of the first measurement report is one of AI-based generation or not based on AI generation.

[0112] This application discloses a second node used for wireless communication mobility management, comprising:

[0113] The second receiver receives the first measurement report in the first cell, and then receives the first signal;

[0114] Wherein, the first measurement report includes at least one of the channel quality of the first cell or the channel quality of the second cell; the second cell is a cell other than the sender of the first measurement report; the first signal is directed to the second cell; the transmission power value of the first signal depends on the generation method of the first measurement report; the generation method of the first measurement report is one of AI-based generation or not based on AI generation.

[0115] As an example, compared with conventional solutions, this application has the following advantages, but is not limited to:

[0116] This application supports the application of AI / ML in mobility management, promotes the deep integration of AI / ML with communication networks, improves the intelligence level of the network, optimizes mobility management, improves spectrum and energy efficiency, and provides users with more stable and efficient mobile communication services.

[0117] It helps improve signal mobility support and enhance the system's service quality;

[0118] Enhance uplink wireless signal power control to ensure reliable signal transmission while reducing terminal power consumption. Attached Figure Description

[0119] 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:

[0120] Figure 1 illustrates a flowchart of the first node transmission according to an embodiment of this application;

[0121] Figure 2 shows a schematic diagram of a network architecture according to an embodiment of this application;

[0122] Figure 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for the user plane and control plane according to an embodiment of this application;

[0123] Figure 4 shows a schematic diagram of a first communication device and a second communication device according to an embodiment of this application;

[0124] Figure 5 shows a first flowchart of the transmission between a first node and a second node according to an embodiment of this application;

[0125] Figure 6 illustrates a second flowchart of the transmission between a first node and a second node according to an embodiment of this application;

[0126] Figure 7 shows a first schematic diagram of the transmission power value of a first signal according to an embodiment of the present application depending on the generation method of a first measurement report;

[0127] Figure 8 shows a second schematic diagram of the transmission power value of the first signal according to an embodiment of the present application depending on the generation method of the first measurement report;

[0128] Figure 9 illustrates a schematic diagram of RAN domain AI / ML function deployment according to an embodiment of this application;

[0129] Figure 10 shows a schematic diagram of the deployment of AI / ML functions of a UE according to an embodiment of this application;

[0130] Figure 11 shows a schematic diagram of a processing system based on artificial intelligence or machine learning according to an embodiment of this application;

[0131] Figure 12 illustrates a schematic diagram based on artificial intelligence or machine learning according to an embodiment of this application;

[0132] Figure 13 shows a structural block diagram of a processing apparatus for a first node according to an embodiment of this application;

[0133] Figure 14 shows a structural block diagram of a processing apparatus for a second node according to an embodiment of the present application. Detailed Implementation

[0134] 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 embodiments in Figure 1 and the embodiments in Figures 5-14, the embodiments in Figure 5 and the embodiments in Figures 6-14, etc.

[0135] Example 1

[0136] Example 1 illustrates a flowchart of the first node transmission according to an embodiment of this application, as shown in Figure 1. In Figure 1, each block represents a step. In particular, the order of the steps in the blocks does not represent a specific temporal relationship between the steps.

[0137] In step 101, the first node sends a first measurement report in the first cell, and then sends a first signal.

[0138] In Example 1, the first measurement report includes at least one of the channel quality of the first cell or the channel quality of the second cell; the second cell is a cell other than the first node; the first signal is directed to the second cell; the transmit power value of the first signal depends on the generation method of the first measurement report; the generation method of the first measurement report is one of AI-based generation or not based on AI generation.

[0139] As an example, the first node is the first node in this application.

[0140] As an example, AI refers to Artificial Intelligence.

[0141] As one example, the AI ​​includes: Machine Learning.

[0142] As one example, the AI ​​includes: Deep Learning.

[0143] As an example, the first node sends the first measurement report in the first cell.

[0144] As an example, the first measurement report is carried by a baseband signal.

[0145] As an example, the first measurement report is carried by a radio frequency signal.

[0146] As an example, the first measurement report is carried by a wireless signal.

[0147] As an example, the first measurement report is transmitted via an RRC (Radio Resource Control) message.

[0148] As an example, the first measurement report includes one or more RRC messages.

[0149] As an example, the first measurement report includes one or more fields in an RRC message.

[0150] As an example, the first measurement report includes one or more portions of an RRC message.

[0151] As an example, the first measurement report includes a Measurement Report.

[0152] As an example, the first measurement report includes a MeasurementReport message.

[0153] As an example, the first measurement report includes one or more fields of a MeasResults IE (Information Element).

[0154] As an example, the first measurement report is carried by SRB1 (Signal Radio Bearer 1).

[0155] As an example, the first measurement report is carried by SRB3 (Signal Radio Bearer 3).

[0156] As an example, the logical channel occupied by the first measurement report includes DCCH (Dedicated Control Channel).

[0157] As an example, the transmission channel occupied by the first measurement report includes UL-SCH (UpLink-Shared Channel).

[0158] As an example, sending the first measurement report in the first cell means: sending the first measurement report using the air interface resources of the first cell.

[0159] As an example, sending the first measurement report in the first cell means sending the first measurement report in the air interface resources corresponding to the first cell.

[0160] As an example, sending the first measurement report in the first cell means sending the first measurement report in the air interface resources configured for the first cell.

[0161] As an example, the air interface resources described in this application include some or all of the time domain resources, frequency domain resources, spatial domain resources, and code domain resources.

[0162] As an example, the air interface resources described in this application include some or all of the following: PUSCH (Physical Uplink Shared CHannel) occasion, PUCCH (Physical Uplink Control CHannel) occasion, and PRACH (Physical Random Access CHannel) occasion.

[0163] As an example, the first cell is the cell where the first node is currently camped.

[0164] As an example, the first cell is the source cell of the first node.

[0165] As an example, the first cell corresponds to one carrier.

[0166] As an example, the first cell corresponds to one PCI.

[0167] As an example, the first cell corresponds to one ServCellIndex.

[0168] As an example, the first cell corresponds to a ServCellId.

[0169] As an example, the first cell corresponds to one SCellIndex.

[0170] As an example, the first cell corresponds to one ServCellIdentity.

[0171] As an example, the second cell is a cell other than the first node.

[0172] As an example, the second cell is a neighbor cell of the cell where the first node is currently based.

[0173] As one example, the second cell is a neighboring cell of the serving cell of the first node.

[0174] As an example, the second cell is the target cell of the first node.

[0175] As an example, the second cell corresponds to one carrier.

[0176] As an example, the second cell corresponds to one PCI.

[0177] As an example, PCI in this application refers to Physical Cell Identifier.

[0178] As an example, PCI in this application refers to Physical Cell Identity.

[0179] As an example, PCI in this application refers to Physical-layer Cell Identity.

[0180] As an example, PCI in this application refers to physCellId.

[0181] As an example, the ServCellIndex described in this application is a non-negative integer not greater than 31.

[0182] As an example, the SCellIndex described in this application is a positive integer not greater than 31.

[0183] As an example, the PhysCellId described in this application is a non-negative integer not greater than 1007.

[0184] As an example, the first measurement report indicates the second cell.

[0185] As an example, the first measurement report includes the PCI corresponding to the second cell.

[0186] As an example, the first measurement report is used to trigger a cell handover from the first cell to the second cell.

[0187] As an example, the recipient of the first measurement report decides to configure LTM (L1 / L2-Triggered Mobility) based on the first measurement report and initiates LTM preparation, wherein the candidate cells for LTM include the second cell.

[0188] As an example, the recipient of the first measurement report decides to switch the cell to the second cell based on the first measurement report.

[0189] As an example, the recipient of the first measurement report decides to switch the first node from the first cell to the second cell based on the first measurement report.

[0190] As an example, the first measurement report includes at least one of the channel quality of the first cell or the channel quality of the second cell.

[0191] As an example, the first measurement report includes the channel quality of the first cell.

[0192] As an example, the first measurement report includes the channel quality of the second cell.

[0193] As an example, the first measurement report includes both the channel quality of the first cell and the channel quality of the second cell.

[0194] As an example, the channel quality described in this application includes: cell channel quality ranking.

[0195] As an example, the channel quality described in this application includes one or more fields in the MeasResults IE.

[0196] As an example, the channel quality described in this application includes: MeasQuantityResults.

[0197] As an example, the channel quality described in this application includes RSRP (Reference Signal Received Power).

[0198] As an example, the channel quality described in this application includes: RSRQ (Reference Signal Received Quality).

[0199] As an example, the channel quality described in this application includes SINR (Signal to Noise and Interference Ratio).

[0200] As an example, the channel quality described in this application includes: SSB-Index.

[0201] As an example, the channel quality described in this application includes: CSI-RS-Index.

[0202] As an example, the channel quality described in this application includes RSSI (Received Signal Strength Indication).

[0203] As an example, the channel quality described in this application includes channel Occupancy.

[0204] As an example, the channel quality described in this application includes: SRS-ResourceId.

[0205] As an example, the channel quality described in this application includes: SRS (Sounding Resource Signal) - RSRP.

[0206] As an example, the channel quality described in this application includes: RSSI-ResourceId.

[0207] As an example, the channel quality described in this application includes CLI (Cross Link Interference) - RSSI.

[0208] As an example, the channel quality described in this application includes: Delay.

[0209] As an example, the channel quality described in this application includes averageDelay.

[0210] As an example, the channel quality described in this application includes: excessDelay.

[0211] As an example, the first node sends the first signal.

[0212] As an example, the first signal is a baseband signal.

[0213] As an example, the first signal is a radio frequency signal.

[0214] As an example, the first signal is a wireless signal.

[0215] As an example, the first signal is transmitted via an RRC message.

[0216] As one example, the first signal includes one or more RRC messages.

[0217] As an example, the first signal includes one or more fields in an RRC message.

[0218] As an example, the first signal includes one or more portions of an RRC message.

[0219] As one example, the first signal is transmitted through a physical layer channel.

[0220] As an example, the first node sends the first signal after sending the first measurement report.

[0221] As an example, the first node receives a signal transmitted by the receiver of the first measurement report before sending the first signal.

[0222] As an example, the first node receives the signal transmitted by the receiver of the first measurement report after sending the first measurement report and before sending the first signal.

[0223] As an example, the first signal is directed to the second cell.

[0224] As an example, the meaning of the first signal being directed to the second cell includes: the first node transmitting the first signal on the second cell.

[0225] As an example, the meaning of the first signal being directed to the second cell includes: the first node using the air interface resources of the second cell to send the first signal.

[0226] As an example, the meaning of the first signal being directed to the second cell includes: the first node sending the first signal in the air interface resources configured in the second cell.

[0227] As one embodiment, the meaning of the first signal being directed to the second cell includes: the first node sending the first signal in the air interface resources corresponding to the second cell.

[0228] As an example, the meaning of the first signal being directed to the second cell includes: the first signal is a PRACH sent to the second cell.

[0229] As an example, the meaning of the first signal being directed to the second cell includes: the first signal is a PUSCH sent to the second cell.

[0230] As an example, the meaning of the first signal being directed to the second cell includes: the first signal is a PUCCH sent to the second cell.

[0231] As an example, the meaning of the first signal being directed to the second cell includes: the first signal is for accessing the second cell.

[0232] As an example, the meaning of "the first signal is directed to the second cell" includes: the first signal is a wireless signal transmitted during the synchronization process with the second cell.

[0233] As an example, the meaning of "the first signal is directed to the second cell" includes: the first signal is a radio signal in the RACH (Random Access Channel) process initiated by the second cell.

[0234] As an example, the meaning of the first signal being directed to the second cell includes: the first signal is a RACH sent to the second cell.

[0235] As an example, the meaning of the first signal being directed to the second cell includes: the first signal is for establishing an RRC connection with the second cell.

[0236] As an example, the meaning of the first signal being directed to the second cell includes: the first signal is an RRCReconfigurationComplete message sent to the second cell.

[0237] As an example, the meaning of the first signal being directed to the second cell includes: the first signal being an uplink signal sent by the first node to the second cell within a given time window, wherein the given time window is located after the first measurement report, the given time window is fixed, or the given time window is configured via RRC signaling.

[0238] As an example, the transmission power value of the first signal depends on the generation method of the first measurement report.

[0239] As an example, the upper limit of the transmission power value of the first signal is the maximum transmission power value of the first wireless signal configured by the first node.

[0240] As an example, the upper limit of the transmission power value of the first signal is the maximum output power configured for the first node.

[0241] As an example, the upper limit of the transmission power value of the first signal is the maximum output power of the second cell configured by the first node for one carrier.

[0242] As an example, the upper limit of the transmission power value of the first signal is the maximum output power of the first cell configured by the first node for one carrier.

[0243] As an example, the upper limit of the transmission power value of the first signal is the maximum output power of the first cell configured by the first node for the kth indicated TCI (Transmission Configuration Indicator) state of a carrier, where k is equal to 1 or 2.

[0244] As an example, the upper limit of the transmission power value of the first signal is the maximum output power of the second cell configured by the first node for the kth indicated TCI state of a carrier, where k is equal to 1 or 2.

[0245] As an example, the upper limit of the transmission power value of the first signal is related to the capability of the first node.

[0246] As an example, the upper limit of the transmission power value of the first signal is related to the Category of the first node.

[0247] As an example, the upper limit of the transmission power value of the first signal corresponds to P in the 3GPP (3rd Generation Partner Project) specification protocol. CMAX .

[0248] As an example, the method of generating the first measurement report is used to determine the transmission power value of the first signal.

[0249] As an example, the transmission power value of the first signal depends on the second power information, and whether the transmission power value of the first signal depends on the first power information depends on the generation method of the first measurement report.

[0250] As a sub-implementation of this embodiment, the first power information and the second power information correspond to the expected power value of the first signal transmitted in the first cell and the expected power value of the first signal transmitted in the second cell, respectively.

[0251] As a sub-example of this embodiment, the first power information and the second power information correspond to the path loss of the active BWP (Bandwidth Part) of the first cell and the path loss of the active BWP of the second cell, respectively.

[0252] As a sub-example of this embodiment, the first power information and the second power information correspond to the road loss compensation coefficient of the first cell and the road loss compensation coefficient of the second cell, respectively.

[0253] As a sub-example of this embodiment, the first power information and the second power information correspond to the power adjustment state of the first cell and the power adjustment state of the second cell, respectively.

[0254] As an example, the first measurement report is generated either based on AI or not based on AI.

[0255] As an example, the first measurement report is generated based on AI.

[0256] As an example, the generation method of the first measurement report based on AI means that the first measurement report is generated through prediction.

[0257] As an example, the generation method of the first measurement report based on AI means that the content of the first measurement report is generated through prediction.

[0258] As an example, the generation method of the first measurement report based on AI means that the first measurement report is generated through inference.

[0259] As an example, the generation method of the first measurement report based on AI means that the content of the first measurement report is generated through reasoning.

[0260] As an example, the generation method of the first measurement report based on AI means that the first measurement report is generated by a model, which is for AI.

[0261] As an example, the generation method of the first measurement report based on AI means that the content of the first measurement report is generated by a model, and the model is AI.

[0262] As an example, the generation method of the first measurement report based on AI means that the first measurement report is generated by a model, and the model is for ML.

[0263] As an example, the generation method of the first measurement report based on AI means that the content of the first measurement report is generated by a model, and the model is for machine learning.

[0264] As an example, the generation method of the first measurement report based on AI means that the first measurement report is generated based on AI based on the measurement.

[0265] As an example, the generation method of the first measurement report based on AI means that the content of the first measurement report is generated based on AI based on the measurement.

[0266] As an example, the generation method of the first measurement report based on AI means that the first node predicts the content of the first measurement report based on the measurement results using an AI model, and then sends the first measurement report.

[0267] As an example, the generation method of the first measurement report based on AI means that the first node predicts and sends the first measurement report based on the measurement results using an AI model, and then sends the first measurement report.

[0268] As an example, the generation method of the first measurement report based on AI means that: the first node predicts the current measurement results of the first cell and the second cell based on the previous measurement results of the first cell and the measurement results of the second cell using an AI model, and then generates the first measurement report and sends the first measurement report.

[0269] As an example, the generation method of the first measurement report based on AI means that: the first node predicts the future measurement results of the first cell and the second cell based on the current measurement results of the first cell and the measurement results of the second cell using an AI model, thereby generating the first measurement report and sending the first measurement report.

[0270] As an example, the generation method of the first measurement report being based on AI means that the first measurement report includes the channel quality of the first cell, and the channel quality of the first cell is generated based on AI.

[0271] As an example, the generation method of the first measurement report being based on AI means that the first measurement report includes the channel quality of the second cell, and the channel quality of the second cell is generated based on AI.

[0272] As an example, the generation method of the first measurement report being based on AI means that the first measurement report includes the channel quality of the first cell and the channel quality of the second cell, and at least one of the channel quality of the first cell and the channel quality of the second cell is generated based on AI.

[0273] As an example, the generation method of the first measurement report based on AI means that the first measurement report is triggered by a single event, and the event that triggers the first node to send the first measurement report is based on AI.

[0274] As an example, the first measurement report is generated in a manner that is not based on AI.

[0275] As an example, the generation method of the first measurement report not based on AI means that the generation of the first measurement report depends on the measurement results for the first cell and the measurement results for the second cell, and does not depend on the prediction of the AI ​​model.

[0276] As an example, the generation method of the first measurement report not based on AI means that the transmission of the first measurement report depends on the measurement results for the first cell and the measurement results for the second cell, and does not depend on the prediction of the AI ​​model.

[0277] As an example, the generation method of the first measurement report not based on AI means that the first measurement report is triggered by a single event, and the event that triggers the first node to send the first measurement report is not based on AI.

[0278] Example 2

[0279] Example 2 illustrates a schematic diagram of a network architecture according to an embodiment of this application, as shown in Figure 2.

[0280] Figure 2 illustrates network architecture 200. Network architecture 200 is the network architecture for LTE (Long-Term Evolution), LTE-A (Long-Term Evolution Advanced), 5G systems, 5G-Advanced, and future 6G systems. The network architecture for LTE, LTE-A, 5G systems, 5G-Advanced, and future 6G systems is referred to as EPS (Evolved Packet System). The 5G NR or LTE network architecture may be referred to as 5GS (5G System) / EPS or some other suitable terminology; the 6G network architecture may be referred to as 6GS (6G System) / EPS or some other suitable terminology. Network architecture 200 may include one or more UEs 201, RAN (Next Generation Radio Access Network) 202, core network 210, HSS (Home Subscriber Server) / UDM (Unified Data Management) 220, and Internet services 230. Network architecture 200 can interconnect with other access networks, but these entities / interfaces are not shown for simplicity. As shown in Figure 2, 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. RAN 202 includes node B 203 and other nodes 204. Node 203 provides user and control plane protocol termination toward UE 201. Node 203 can be connected to other nodes 204 via an Xn interface (e.g., backhaul). Node 203 may also be referred to as a base station, base transceiver station, wireless base station, wireless transceiver, transceiver function, Basic Service Set (BSS), Extended Service Set (ESS), TRP (Transmitter Receiver Point), or some other suitable term. Node 203 provides UE 201 with an access point to core network 210; core network 210 is 5GC (5G Core Network) / EPC (Evolved Packet Core), or core network 210 is 6GC.Examples of UE 201 include cellular phones, smartphones, Session Initiation Protocol (SIP) phones, laptops, personal digital assistants (PDAs), satellite radios, GPS devices, multimedia devices, video devices, digital audio players (e.g., MP3 players), cameras, game consoles, drones, aircraft, narrowband physical network devices, machine-type communication devices, land vehicles, automobiles, wearable devices, or any other similar functional devices. Those skilled in the art may also refer to UE 201 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 core network 210 via an S1 / NG interface. The core network 210 includes the MME (Mobility Management Entity) / AMF (Authentication Management Field) / SMF (Session Management Function) 211, other MMEs / AMFs / SMFs 214, the S-GW (Service Gateway) / UPF (User Plane Function) 212, and the P-GW (Packet Data Network Gateway) / UPF 213. The MME / AMF / SMF 211 is the control node that handles signaling between the UE 201 and the 5G-CN / EPC 210. Generally, the MME / AMF / SMF 211 provides bearer and connection management. All user IP (Internet Protocol) packets are transmitted through the S-GW / UPF 212, which is itself connected to the P-GW / UPF 213. The P-GW provides UE IP address allocation and other functions. The P-GW / UPF 213 connects to Internet service 230. Internet service 230 includes carrier-compliant Internet protocol services, specifically including the Internet, intranet, IMS (IP Multimedia Subsystem), and packet switching services.

[0281] As an example, the first node in this application includes the UE 201.

[0282] As an example, the second node in this application includes the node 203.

[0283] As an example, node 203 is a macrocell base station.

[0284] As an example, node 203 is a microcell base station.

[0285] As an example, node 203 is a pico cell base station.

[0286] As an example, node 203 is a femtocell.

[0287] As an example, node 203 is a base station device that supports large latency differences.

[0288] As an example, node 203 is a flight platform device.

[0289] As one example, node 203 is a satellite device.

[0290] As one embodiment, the node 203 is a test device (e.g., a transceiver device simulating part of the functions of a base station, a signaling tester).

[0291] As an example, the UE 201 includes a mobile phone.

[0292] As an example, the UE 201 is a vehicle including a car.

[0293] As an example, the wireless link from the UE 201 to the node 203 is an uplink, which is used to perform uplink transmissions.

[0294] As an example, the radio link from node 203 to UE 201 is a downlink, which is used to perform downlink transmissions.

[0295] As an example, the wireless link between the node 203 and the UE 201 includes a cellular link.

[0296] As an example, the node 203 and the UE 201 are connected via the Uu air interface.

[0297] As an example, the sender of the first measurement report includes the UE 201.

[0298] As an example, the recipient of the first measurement report includes the node 203.

[0299] As an example, the sender of the first signal includes the UE 201.

[0300] As an example, the receiver of the first signal includes the node 203.

[0301] As an example, the sender of the first signal includes the UE 201.

[0302] As an example, the receiver of the first signal includes the node 204.

[0303] As an example, the UE 201 supports generating reports using AI / ML.

[0304] As an example, the UE 201 supports generating a trained model or some parameters of the model using training data.

[0305] As an example, the UE 201 supports AI / ML-based measurement reporting.

[0306] As an example, the UE 201 supports measurement reporting based on NN (Neural Networks).

[0307] As an example, the UE 201 supports measurement reporting based on ANN (Artificial Neural Networks).

[0308] As an example, the UE 201 supports measurement reporting based on CNN (Convolutional Neural Networks).

[0309] As an example, the UE 201 supports measurement reporting based on Transformer.

[0310] As an example, the UE 201 supports measurement reporting based on LSTM (Long Short-Term Memory) network.

[0311] As an example, the UE 201 supports measurement reporting based on MLP (MultiLayer Perceptron).

[0312] As an example, the UE 201 supports measurement reporting based on GAN (Generative Adversarial Nets).

[0313] As an example, the UE 201 supports measurement reporting based on a lightweight neural network.

[0314] As a sub-example of this embodiment, the lightweight neural network includes one or more of MobileNet, ShuffleNet, and SqueezeNet.

[0315] As an example, the UE 201 supports a 5G system.

[0316] As one example, the node 203 supports a 5G system.

[0317] As an example, the UE 201 supports at least a 6G system.

[0318] As an example, the node 203 supports at least a 6G system.

[0319] Example 3

[0320] 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 Figure 3.

[0321] Figure 3 is a schematic diagram illustrating an embodiment of the wireless protocol architecture for the user plane 350 and the control plane 300. Figure 3 shows the wireless protocol architecture for the control plane 300 between a first communication node device (UE or RSU in V2X, onboard equipment or onboard communication module) and a second node device (gNB, RSU in UE or V2X, onboard equipment or onboard communication module), or between two UEs, using three layers: Layer 1 (L1), Layer 2 (L2), and Layer 3 (L3). L1 is the lowest layer and implements various PHY (Physical layer) signal processing functions. L1 will be referred to herein as PHY 301. L2 305 is above PHY 301 and is responsible for the link between the first node device and the second node device, or between two UEs, through PHY 301. L2 305 includes a MAC (Medium Access Control) sublayer 302, an RLC (Radio Link Control) sublayer 303, and a PDCP (Packet Data Convergence Protocol) sublayer 304, which terminate at the second node device. The PDCP sublayer 304 provides multiplexing between different radio bearers and logical channels. It also provides security through encrypted data packets and supports cross-cell mobility between the second communication node devices and the first communication node device. The RLC sublayer 303 provides upper-layer packet segmentation and reassembly, retransmission of lost packets, and packet reordering to compensate for out-of-order reception due to HARQ (Hybrid Automatic Repeat reQuest). The MAC sublayer 302 provides multiplexing between logical and transport channels. It is also responsible for allocating various radio resources (e.g., resource blocks) within a cell between the first communication node devices. The MAC sublayer 302 is also responsible for HARQ operations. The RRC (Radio Resource Control) sublayer 306 in L3 of the control plane 300 is responsible for obtaining radio resources (i.e., radio bearers) and using RRC signaling between the second communication node device and the first communication node device to configure the lower layer.The wireless protocol architecture of user plane 350 includes Layer 1 (L1) and Layer 2 (L2). The wireless protocol architecture for the first and second communication node 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 355, RLC sublayer 353 in L2 355, and MAC sublayer 352 in L2 355. However, PDCP sublayer 354 also provides header compression for upper-layer packets to reduce wireless transmission overhead. L2 355 in user plane 350 also includes SDAP (Service Data Adaptation Protocol) sublayer 356. SDAP sublayer 356 is responsible for mapping between QoS (Quality of Service) streams and Data Radio Bearers (DRBs) to support service diversity. Although not illustrated, the first communication node device may have several upper layers above L2 355, including a network layer (e.g., IP (Internet Protocol) layer) terminating at the P-GW on the network side and an application layer terminating at the other end of the connection (e.g., remote UE, server, etc.).

[0322] As an example, the wireless protocol architecture in Figure 3 is applicable to the first node in this application.

[0323] As an example, the wireless protocol architecture in Figure 3 is applicable to the second node in this application.

[0324] As an example, the first measurement report is generated in the RRC 306.

[0325] As an example, the first signal is generated in the RRC 306.

[0326] As an example, the first signaling is generated in the RRC 306.

[0327] As an example, the first signaling is generated in MAC 302 or MAC 352.

[0328] As an example, the first signaling is generated in the PHY 301 or the PHY 351.

[0329] As an example, the second signaling is generated in the RRC 306.

[0330] As an example, the higher layer mentioned in this application refers to the layer above the physical layer.

[0331] As an example, the higher layer described in this application includes the MAC layer.

[0332] As an example, the higher layer described in this application includes the RRC layer.

[0333] Example 4

[0334] 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 Figure 4. Figure 4 is a block diagram of a first communication device 410 and a second communication device 450 communicating with each other in an access network.

[0335] The first communication device 410 includes a controller / processor 475, a memory 476, a receiver processor 470, a transmitter processor 416, a multi-antenna receiver processor 472, a multi-antenna transmitter processor 471, a transmitter / receiver 418, and an antenna 420.

[0336] The second communication device 450 includes a controller / processor 459, a memory 460, a data source 467, a transmitting processor 468, a receiving processor 456, a multi-antenna transmitting processor 457, a multi-antenna receiving processor 458, a transmitter / receiver 454, and an antenna 452.

[0337] 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 functionality. In the DL, 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 (i.e., the physical layer). Transmit processor 416 performs encoding and interleaving to facilitate forward error correction (FEC) at the second communication device 450, and mapping of signal clusters based on various modulation schemes (e.g., Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying (QPSK), 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. The 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 multicarrier symbol stream. The multi-antenna transmit processor 471 then performs transmit analog precoding / beamforming operations on the time-domain multicarrier symbol stream. Each transmitter 418 converts the baseband multicarrier symbol stream provided by the multi-antenna transmit processor 471 into an RF stream, which is then provided to a different antenna 420.

[0338] 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 L1 signal processing functions. 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 by the first communication device 410 over the physical channel. The upper-layer data and control signals are then provided to the controller / processor 459. The controller / processor 459 implements L2 functionality. 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, 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 L2. Various control signals may also be provided to L3 for L3 processing. The controller / processor 459 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operation.

[0339] 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 L2. 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 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.

[0340] 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 function. The controller / processor 475 implements the L2 function. The controller / processor 475 may be associated with a memory 476 storing 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.

[0341] 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 transmits a first measurement report in at least a first cell, followed by transmitting a first signal; the first measurement report includes at least one of the channel quality of the first cell or the channel quality of a second cell; the second cell is a cell other than the first node; the first signal is directed to the second cell; the transmission power value of the first signal depends on the generation method of the first measurement report; the generation method of the first measurement report is either AI-generated or not based on AI generation.

[0342] 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: transmitting a first measurement report in a first cell; and transmitting a first signal.

[0343] 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 receives a first measurement report in at least a first cell, and subsequently receives a first signal; the first measurement report includes at least one of the channel quality of the first cell or the channel quality of a second cell; the second cell is a cell other than the sender of the first measurement report; the first signal is directed to the second cell; the transmission power value of the first signal depends on the generation method of the first measurement report; the generation method of the first measurement report is either AI-generated or not AI-generated.

[0344] As one embodiment, the first communication device 410 includes: a memory storing a computer-readable instruction program that, when executed by at least one processor, produces actions including: receiving a first measurement report in a first cell; and receiving a first signal.

[0345] As an example, the first node in this application includes the second communication device 450.

[0346] As an example, the second node in this application includes the first communication device 410.

[0347] As an example, at least one of {the antenna 452, the transmitter 454, the transmitter processor 468, the multi-antenna transmitter processor 457, the controller / processor 459, the memory 460, and the data source 467} is used to transmit a first measurement report in a first cell; at least one of {the antenna 420, the receiver 418, the receiver processor 470, the multi-antenna receiver processor 472, the controller / processor 475, and the memory 476} is used to receive a first measurement report in the first cell.

[0348] As an example, at least one of {the antenna 452, the transmitter 454, the transmitter processor 468, the multi-antenna transmitter processor 457, the controller / processor 459, the memory 460, and the data source 467} is used to transmit a first signal; at least one of {the antenna 420, the receiver 418, the receiver processor 470, the multi-antenna receiver processor 472, the controller / processor 475, and the memory 476} is used to receive the first signal.

[0349] As an example, at least one of {the antenna 420, the transmitter 418, the transmission processor 416, the multi-antenna transmission processor 471, the controller / processor 475, and the memory 476} is used to transmit the second signaling; and at least one of {the antenna 452, the receiver 454, the receiving processor 456, the multi-antenna receiving processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to receive the second signaling.

[0350] As an example, at least one of {the antenna 420, the transmitter 418, the transmission processor 416, the multi-antenna transmission processor 471, the controller / processor 475, and the memory 476} is used to transmit the first signaling; at least one of {the antenna 452, the receiver 454, the receiving processor 456, the multi-antenna receiving processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to receive the first signaling.

[0351] As an example, at least one of {the antenna 420, the transmitter 418, the transmitter processor 416, the multi-antenna transmitter processor 471, the controller / processor 475, and the memory 476} is used to transmit a first reference signal; and at least one of {the antenna 452, the receiver 454, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to receive the first reference signal.

[0352] As an example, at least one of {the antenna 420, the transmitter 418, the transmitter processor 416, the multi-antenna transmitter processor 471, the controller / processor 475, and the memory 476} is used to transmit the second reference signal; and at least one of {the antenna 452, the receiver 454, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to receive the second reference signal.

[0353] Example 5

[0354] Example 5 illustrates a first flowchart of transmission between a first node and a second node according to an embodiment of this application, as shown in Figure 5. In Figure 5, the first node U1 and the second node N2 communicate via a wireless link; the steps in blocks F51, F52, and F53 are optional. It should be noted that the order in this embodiment does not limit the signal transmission order or the order of implementation in this application.

[0355] For the first node U1, in step S5110, the second signaling is received; in step S5120, the first reference signal and the second reference signal are received; in step S510, the first measurement report is sent in the first cell; in step S5130, the first signaling is received; and in step S511, the first signal is sent.

[0356] For the second node N2, a second signaling is sent in step S5210; a first reference signal and a second reference signal are sent in step S5220; a first measurement report is received in the first cell in step S520; a first signaling is sent in step S5230; and a first signal is received in step S521.

[0357] In Example 5, the first measurement report includes at least one of the channel quality of the first cell or the channel quality of the second cell; the second cell is a cell other than the first node; the first signal is directed to the second cell; the transmit power value of the first signal depends on the generation method of the first measurement report; the generation method of the first measurement report is one of AI-based generation or not based on AI generation.

[0358] As an example, the first node U1 is the first node in this application.

[0359] As an example, the second node N2 is the second node in this application.

[0360] As one embodiment, the air interface between the second node N2 and the first node U1 includes a wireless interface between the base station equipment and the user equipment.

[0361] As one embodiment, the air interface between the second node N2 and the first node U1 includes a wireless interface between the relay node device and the user equipment.

[0362] As one embodiment, the air interface between the second node N2 and the first node U1 includes a wireless interface between user equipment and user equipment.

[0363] As one embodiment, the air interface between the second node N2 and the first node U1 includes one or more of the following: a wireless interface between a TRP (Transmitter Receiver Point) and a user equipment, a wireless interface between a CU (Centralized Unit) and a user equipment, or a wireless interface between a DU (Distributed Unit) and a user equipment.

[0364] As one example, the second node N2 and the first node U1 communicate via the Uu interface.

[0365] As one example, the second node N2 is the maintenance base station of the serving cell of the first node U1.

[0366] In one embodiment, the second node N2 is the sustaining base station of the first cell.

[0367] As one example, the second node N2 is the sustaining base station of the second cell.

[0368] As one example, the second node N2 is the sustaining base station for the first cell and the second cell.

[0369] As an example, the first cell corresponds to the source MAC (Medium Access Control) entity of the first node U1, and the second cell corresponds to the destination MAC entity of the first node N2.

[0370] As an example, the first cell is an LTM source cell of the first node U1, and the second cell is an LTM candidate cell of the first node U1.

[0371] As an example, the first cell is the source cell for cell switching, and the second cell is the candidate cell for cell switching.

[0372] As an example, the first cell is the PCell (Primary Cell) of the first node U1, and the second cell is the SCell (Secondary Cell) of the first node U1.

[0373] As a sub-implementation of this embodiment, the first measurement report triggers a change in the first node U1 PCell and SCell.

[0374] As an example, the first cell is the source PCell of the first node U1, and the second cell is the destination PCell of the first node U1.

[0375] As a sub-implementation of this embodiment, the first measurement report triggers a change in the first node U1 PCell.

[0376] As an example, the second cell corresponds to an LTM-CandidateId.

[0377] As an example, the second cell is the serving cell of the first node U1.

[0378] As an example, the second cell is not the current serving cell of the first node U1.

[0379] As an example, the first measurement report includes a Measurement Report.

[0380] As an example, the first measurement report includes a MeasurementReport message.

[0381] As an example, the first measurement report includes one or more fields of the MeasResults IE.

[0382] As one example, the transmission of the first signal depends on the first signaling.

[0383] As an example, block 53 is present in Figure 5; the method applied to the first node in this application includes: receiving a first signaling; the transmission of the first signal depends on the first signaling.

[0384] As an example, the first signal indicates that the first signaling was correctly received.

[0385] As an example, the first signal is a feedback to the first signaling.

[0386] As one embodiment, the first signaling includes an RRCReconfiguration message.

[0387] As one embodiment, the first signaling includes LTM candidate configuration.

[0388] As one example, the first signaling includes one or more domains of the ltm-Config IE.

[0389] As one example, the first signaling includes one or more domains of LTM-Candidate IE.

[0390] As an example, the first signaling is carried by SRB1.

[0391] As an example, the first signaling is carried by SRB3.

[0392] As an example, the logical channel occupied by the first signaling includes DCCH.

[0393] As an example, the first signal includes an RRCReconfigurationComplete message.

[0394] As an example, the first signal is carried by SRB1.

[0395] As an example, the first signal is carried by SRB3.

[0396] As an example, the logical channel occupied by the first signal includes DCCH.

[0397] As an example, the transmission channel occupied by the first signal includes UL-SCH.

[0398] As an example, the physical layer channel occupied by the first signal includes PUSCH.

[0399] As an example, the physical layer channel occupied by the first signal includes PUCCH.

[0400] As an example, the first signaling is physical layer signaling.

[0401] As an example, the first signaling is dynamic signaling.

[0402] As an example, the first signaling initiates the uplink TA (Timing Advance) acquisition process.

[0403] As an example, the first signaling initiates an early TA acquisition process.

[0404] As one embodiment, the transmission of the first signal is a response to the reception of the first signaling.

[0405] As one example, in response to receiving the first signaling, the first node sends the first signal.

[0406] As an example, the first signal is used to obtain uplink synchronization.

[0407] As an example, the first signal is used to obtain uplink synchronization with the second cell.

[0408] As an example, the first signal is used to establish time alignment.

[0409] As an example, the first signal is used for LTM (L1 / L2-Triggered Mobility).

[0410] As an example, the first signal is used for early TA acquisition.

[0411] As an example, the first signal is generated from a pseudo-random sequence.

[0412] As one example, the first signaling includes DCI (Downlink Control Information).

[0413] As an example, the DCI format corresponding to the first signaling is DCI format 1_0.

[0414] As an example, the CRC (Cyclic redundancy check) included in the first signaling is scrambled by C (Cell)-RNTI (Radio Network Temporary Identifier).

[0415] As an example, the FDRA (Frequency Domain Resource Assignment) field included in the first signaling is all 1s.

[0416] As an example, the first signaling is a PDCCH (Physical Downlink Control Channel) Order.

[0417] As an example, the physical layer channel occupied by the first signaling includes PDCCH.

[0418] As one embodiment, the first signal includes a ZC sequence (Zadoff-Chu sequence).

[0419] As an example, the first signal is generated by a ZC sequence.

[0420] As an example, the first signal is generated from a preamble sequence.

[0421] As one example, the first signal includes a preamble.

[0422] As an example, the first signal includes only one preamble.

[0423] As an example, the preamble included in the first signal is assigned by the sender of the first signaling.

[0424] As an example, the preamble included in the first signal is indicated by the sender of the first signaling.

[0425] As one embodiment, the first signal includes Msg1 (message 1).

[0426] As an example, Msg1 mentioned in this application refers to Massage 1, Msg 1, or MSG1.

[0427] As an example, the first signal includes RACH.

[0428] As one example, the first signal includes PRACH.

[0429] As an example, the transmission channel occupied by the first signal includes RACH.

[0430] As an example, the physical layer channel occupied by the first signal includes PRACH.

[0431] As an example, the first measurement report includes an L1 Measurement Report.

[0432] As an example, the first signaling is MAC layer signaling.

[0433] As an example, the first signaling includes a MAC CE (Control Element).

[0434] As an example, the first signaling includes LTM Cell switch command MAC CE.

[0435] As an example, the transmission channel occupied by the first signaling includes DL-SCH.

[0436] As an example, the physical layer channel occupied by the first signaling includes PDSCH (Physical Downlink Shared Channel).

[0437] As one example, the first signaling indicates the second cell.

[0438] As an example, the first signaling indicates the PCI of the second cell.

[0439] As one embodiment, the first signaling instructs the first node to perform cell switching to the second cell.

[0440] As an example, the first signal includes UCI (Uplink Control Information).

[0441] As one embodiment, the first signal includes HARQ (Hybrid Automatic Repeat reQuest) - ACK (ACKnowledgment).

[0442] As an embodiment, block 52 is present in Figure 5; the method applied to the first node in this application includes: receiving a first reference signal and a second reference signal; the channel quality of the first cell depends on the reception of the first reference signal, the channel quality of the second cell depends on the reception of the second reference signal; the channel quality of the second cell is better than the channel quality of the first cell.

[0443] As an example, the first reference signal is transmitted in the first cell.

[0444] As an example, the second reference signal is transmitted in the second cell.

[0445] As one embodiment, the first reference signal includes CSI-RS (channel state information-reference signal).

[0446] As one embodiment, the first reference signal includes SSB.

[0447] As one embodiment, the second reference signal includes CSI-RS.

[0448] As one embodiment, the second reference signal includes SSB.

[0449] As an example, SSB in this application refers to Synchronization Signal Block.

[0450] As an example, the SSB mentioned in this application refers to: SS (Synchronization Signal) / PBCH (Physical Broadcast Channel) block, which is a synchronization signal / physical broadcast channel block.

[0451] Typically, the PBCH, PSS (Primary Synchronization Signal), and SSS (Secondary Synchronization Signal) are received in consecutive symbols and form an SS / PBCH block.

[0452] As an example, the channel quality of the first cell is obtained by measuring the first reference signal.

[0453] As an example, the channel quality of the second cell is obtained by measuring the second reference signal.

[0454] As an example, when the channel quality of the first cell is generated based on AI, the input of the AI ​​model inference stage includes the first reference signal, and the output includes part or all of the channel quality of the first cell.

[0455] As an example, when the channel quality of the second cell is generated based on AI, the input of the AI ​​model inference stage includes the second reference signal, and the output includes part or all of the channel quality of the second cell.

[0456] As an example, the first measurement report is event-triggered, the event including that the channel quality of the second cell is better than the channel quality of the first cell.

[0457] As an example, the first measurement report indicates that the channel quality of the second cell is better than that of the first cell.

[0458] As an example, the first measurement report is generated based on AI, and the output of the AI ​​includes an indication that the channel quality of the second cell is better than that of the first cell.

[0459] As an example, the statement that the channel quality of the second cell is better than that of the first cell means that the RSRP of the second cell is greater than that of the first cell.

[0460] As an example, the statement that the channel quality of the second cell is better than that of the first cell means that the RSRQ of the second cell is greater than that of the first cell.

[0461] As an example, the statement that the channel quality of the second cell is better than that of the first cell means that the SINR of the second cell is greater than that of the first cell.

[0462] As an example, the statement that the channel quality of the second cell is better than that of the first cell means that the sum of the RSRP of the second cell and a given offset value is greater than the RSRP of the first cell.

[0463] As an example, the statement that the channel quality of the second cell is better than that of the first cell means that the sum of the RSRQ of the second cell and a given offset value is greater than the RSRQ of the first cell.

[0464] As an example, the statement that the channel quality of the second cell is better than that of the first cell means that the sum of the SINR of the second cell and a given offset value is greater than the SINR of the first cell.

[0465] As an example, the statement that the channel quality of the second cell is better than that of the first cell means that the second cell becomes better than the first cell when considering offset, the offset including at least one of measurement-specific offset, cell-specific offset, and offset parameters for a given event.

[0466] As an example, the meaning that the channel quality of the second cell is better than that of the first cell includes: the second cell corresponds to a neighboring cell, the first cell corresponds to a SpCell (Special Cell), and the neighboring cell and the SpCell satisfy Event A3.

[0467] As an example, the meaning of the second cell having better channel quality than the first cell includes: the first cell becoming worse than a first threshold and the second cell becoming better than a second threshold.

[0468] As an example, the meaning that the channel quality of the second cell is better than that of the first cell includes: the second cell corresponds to a neighboring cell, the first cell corresponds to a SpCell, and the neighboring cell and the SpCell satisfy Event A5.

[0469] As an example, the statement that the channel quality of the second cell is better than that of the first cell means that the second cell is better than the first cell when offset is taken into account.

[0470] As an example, the meaning that the channel quality of the second cell is better than that of the first cell includes: the second cell corresponds to a neighboring cell, the first cell corresponds to an SCell, and the neighboring cell and the SCell satisfy Event A6.

[0471] As an embodiment, block 51 is present in Figure 5; the method applied to the first node in this application includes: receiving second signaling, the second signaling configuring a measurement object and a measurement time for the first cell and the second cell, respectively.

[0472] As an example, at least one channel measurement value for the first cell is obtained by measuring the measurement object for the first cell during the measurement time, and at least one channel measurement value for the second cell is obtained by measuring the measurement object for the second cell during the measurement time; when the first measurement report is generated based on AI, at least one of the at least one channel measurement value for the first cell or the at least one channel measurement value for the second cell is used to generate the first measurement report.

[0473] As one embodiment, the second signaling includes higher-layer signaling.

[0474] As one embodiment, the second signaling includes RRC signaling.

[0475] As one example, the second signaling includes one or more fields in an RRC IE.

[0476] As one embodiment, the second signaling includes multiple RRC IEs.

[0477] As one embodiment, the second signaling includes one or more fields of each of the plurality of RRC IEs.

[0478] As one example, the second signaling includes one or more fields in the MeasurementReport IE.

[0479] As one example, the second signaling includes one or more domains in the MeasConfig IE.

[0480] As one example, the second signaling includes one or more fields in MeasObjectEUTRA IE.

[0481] As one example, the second signaling includes one or more fields in the MeasObjectNR IE.

[0482] As one example, the second signaling includes one or more domains in MeasWindowConfig IE.

[0483] As an example, the unit of measurement time is milliseconds (ms).

[0484] As an example, the unit of measurement time is a time slot.

[0485] As an example, the unit of measurement time is a subframe.

[0486] As one embodiment, the measurement object includes a reference signal transmitted in a reference signal resource, which is at least one of a CSI-RS resource and an SSB.

[0487] As an example, the measurement object includes a reference signal, which is at least one of CSI-RS and SSB.

[0488] As an example, the measurement object includes a reference signal received by the first node, and the received reference signal is at least one of CSI-RS and SSB.

[0489] As an example, the measurement object includes a reference signal generated by the first node, and the generated reference signal includes at least one of CSI-RS, SSB, and SRS.

[0490] As one example, the measurement object includes DMRS (DeModulation Reference Signal).

[0491] As an example, when the first measurement report is generated based on AI, the input to the AI ​​model that generates the first measurement report includes at least one of the channel measurement values ​​for the first cell or at least one of the channel measurement values ​​for the second cell.

[0492] As an example, when the first measurement report is generated based on AI, the input to the AI ​​model that generates the first measurement report includes at least one of the channel measurement values ​​for the first cell or at least one of the channel measurement values ​​for the second cell.

[0493] As an example, step S511 is after step S510; step S521 is after step S520.

[0494] As an example, block 53 is present in Figure 5, step S5130 precedes step S511; step S5230 precedes step S521.

[0495] As an example, block 53 is present in Figure 5, step S5130 is after step S510; step S5230 is after step S520.

[0496] As an example, block 52 is present in Figure 5, step S5120 precedes step S510; step S5220 precedes step S520.

[0497] As an example, block 51 is present in Figure 5, step S5110 precedes step S510; step S5210 precedes step S520.

[0498] As an example, in Figure 5, boxes 51 and 52 exist simultaneously, with step S5120 following step S5110; and step S5220 following step S5210.

[0499] As an example, the box 51 shown in Figure 5 is not present.

[0500] As an example, the box 52 shown in Figure 5 is not present.

[0501] As an example, the box 53 shown in Figure 5 is not present.

[0502] Example 6

[0503] Example 6 illustrates a second flowchart of transmission between a first node and a second node according to an embodiment of this application, as shown in Figure 5. In Figure 6, the first node U3 communicates with the second node N4 via a wireless link, and the first node U3 communicates with the third node N5 via a wireless link; the steps in blocks F61, F62, and F63 are optional. It should be noted that the order in this embodiment does not limit the signal transmission order or the order of implementation in this application.

[0504] For the first node U3, in step S6310, the second signaling is received; in step S6320, the first reference signal and the second reference signal are received; in step S630, the first measurement report is sent in the first cell; in step S6330, the first signaling is received; and in step S631, the first signal is sent.

[0505] For the second node N4, a second signaling is sent in step S6410; a first reference signal is sent in step S6420; a first measurement report is received in the first cell in step S640; and a first signaling is sent in step S6430.

[0506] For the third node N5, a second reference signal is sent in step S6520; and a first signal is received in step S650.

[0507] In Example 6, the first measurement report includes at least one of the channel quality of the first cell or the channel quality of the second cell; the second cell is a cell other than the first node; the first signal is directed to the second cell; the transmit power value of the first signal depends on the generation method of the first measurement report; the generation method of the first measurement report is one of AI-based generation or not based on AI generation.

[0508] As an example, the first node U3 is the first node in this application.

[0509] As an example, the second node N4 is the second node in this application.

[0510] As an example, the second node in this application includes the second node N4 and the third node N5.

[0511] As one embodiment, the air interface between the second node N4 and the first node U3 includes a wireless interface between the base station equipment and the user equipment.

[0512] As one embodiment, the air interface between the third node N5 and the first node U3 includes the wireless interface between the base station equipment and the user equipment.

[0513] As one embodiment, the air interface between the second node N4 and the first node U3 includes a wireless interface between the relay node device and the user equipment.

[0514] As one embodiment, the air interface between the third node N5 and the first node U3 includes a wireless interface between the relay node device and the user equipment.

[0515] As one embodiment, the air interface between the second node N4 and the first node U3 includes a wireless interface between user equipment and user equipment.

[0516] As one embodiment, the air interface between the third node N5 and the first node U3 includes a wireless interface between user equipment and user equipment.

[0517] As one embodiment, the air interface between the second node N4 and the first node U3 includes one or more of the following: a wireless interface between the TRP and the user equipment, a wireless interface between the CU and the user equipment, or a wireless interface between the DU and the user equipment.

[0518] As one embodiment, the air interface between the third node N5 and the first node U3 includes one or more of the following: the wireless interface between the TRP and the user equipment, the wireless interface between the CU and the user equipment, or the wireless interface between the DU and the user equipment.

[0519] As one example, the second node N4 and the first node U3 communicate via the Uu interface.

[0520] As an example, the third node N5 and the first node U3 communicate via the Uu interface.

[0521] In one embodiment, the second node N4 is the sustaining base station of the first cell.

[0522] As an example, the third node N5 is the sustaining base station of the second cell.

[0523] As one example, the second node N4 and the third node N5 are two different base stations.

[0524] As an example, the second node N4 and the third node N5 are two different gNBs.

[0525] As one example, the second node N4 and the third node N5 are different DUs of the same base station.

[0526] As an example, the first cell corresponds to the source base station of the first node.

[0527] As an example, the first cell corresponds to the source gNB of the first node.

[0528] As one example, the second cell corresponds to the destination base station of the first node.

[0529] As one example, the second cell corresponds to the destination gNB of the first node.

[0530] As an example, block 63 is present in Figure 6; the method applied to the first node in this application includes: receiving a first signaling; the transmission of the first signal depends on the first signaling.

[0531] As an example, the first signaling triggers a handover of the Uu port.

[0532] As an example, the first signaling is transmitted via RRC messages.

[0533] As one example, the first signaling includes one or more RRC messages.

[0534] As an example, the first signaling includes one or more fields in an RRC message.

[0535] As one embodiment, the first signaling includes one or more portions of an RRC message.

[0536] As one embodiment, the first signaling includes an RRCReconfiguration message.

[0537] As an example, the first signal indicates that the first signaling was correctly received.

[0538] As an example, the first signal is a feedback to the first signaling.

[0539] As one embodiment, the first signaling includes information required to access the second cell.

[0540] As one example, the first signaling indicates the cell identifier of the second cell.

[0541] As an example, the first signaling indicates the C(Cell)-RNTI of the second cell.

[0542] As an example, the first signaling is carried by SRB1.

[0543] As an example, the first signaling is carried by SRB3.

[0544] As an example, the logical channel occupied by the first signaling includes DCCH.

[0545] As an example, the first signal includes an RRCReconfigurationComplete message.

[0546] As an example, the first signal is carried by SRB1.

[0547] As an example, the first signal is carried by SRB3.

[0548] As an example, the logical channel occupied by the first signal includes DCCH.

[0549] As an example, the transmission channel occupied by the first signal includes UL-SCH.

[0550] As an example, the physical layer channel occupied by the first signal includes PUSCH.

[0551] As an example, the physical layer channel occupied by the first signal includes PUCCH.

[0552] As one example, the first signaling includes a MobilityFromNRCommand message.

[0553] As an example, the first signal includes an RRCReestablishmentRequest message.

[0554] As an example, the first signal is used to initiate the re-establishment procedure.

[0555] As an example, the first signal is carried by SRB0.

[0556] As an example, the transmission channel of the first signal includes the CCCH (Common Control Channel).

[0557] As an embodiment, block 62 is present in Figure 6; the method applied to the first node in this application includes: receiving a first reference signal and a second reference signal; the channel quality of the first cell depends on the reception of the first reference signal, the channel quality of the second cell depends on the reception of the second reference signal; the channel quality of the second cell is better than the channel quality of the first cell.

[0558] As an example, block 62 in Figure 6 is present; step S6320 is step S5120 in block F52 in Figure 5.

[0559] As an example, block 62 is present in Figure 6; step S6420 precedes step S6520.

[0560] As an example, block 62 is present in Figure 6; step S6420 follows step S6520.

[0561] As an example, block 61 is present in Figure 6; the method applied to the first node in this application includes: receiving second signaling, the second signaling configuring measurement objects and measurement times for the first cell and the second cell respectively.

[0562] As an example, block 61 in Figure 6 is the step in block 51 in Figure 5.

[0563] As an example, block 61 is present in Figure 6, step S6310 precedes step S630; step S6410 precedes step S640.

[0564] As an example, block 62 is present in Figure 6, step S6320 precedes step S630; step S6420 precedes step S640; and step S6520 precedes step S650.

[0565] As an example, block 63 is present in Figure 6, and step S6330 precedes step S631.

[0566] As an example, block 63 is present in Figure 6, step S6330 is after step S630; step S6430 is after step S640.

[0567] As an example, the steps in boxes 61 and F62 of Figure 6 exist simultaneously, with step S6310 preceding step S6320; and step S6410 preceding step S6420.

[0568] Example 7

[0569] Example 7 illustrates a first schematic diagram of the transmission power value of a first signal depending on the generation method of a first measurement report according to an embodiment of this application, as shown in Figure 7. In Figure 7, case (a) indicates that when the generation method of the first measurement report is based on AI generation, the transmission power value of the first signal depends on a first path loss and a second path loss; case (b) indicates that when the generation method of the first measurement report is not based on AI generation, the transmission power value of the first signal depends on a second path loss.

[0570] In Example 7, the first path loss and the second path loss are respectively for the first cell and the second cell.

[0571] As an example, when the first measurement report is generated based on AI, the transmission power value of the first signal depends on the first path loss and the second path loss; the first path loss and the second path loss are respectively for the first cell and the second cell.

[0572] As an example, the first path loss (PL) is downlink.

[0573] As an example, the unit of the first path loss is dB (decibel).

[0574] As an example, the first path loss is estimated through the first node.

[0575] As an example, the first node obtains the first path loss by measuring a third reference signal, which is transmitted on the first cell.

[0576] As a sub-example of this embodiment, the third reference signal is either CSI-RS or SSB.

[0577] As an example, the second path loss is downstream.

[0578] As an example, the unit of the second path loss is dB.

[0579] As an example, the second path loss is estimated through the first node.

[0580] As an example, the first node obtains the first path loss by measuring a fourth reference signal, which is transmitted on the second cell.

[0581] As a sub-implementation of this embodiment, the fourth reference signal is one of CSI-RS or SSB.

[0582] As an example, the meanings of "first path loss" and "second path loss" referring to the first cell and the second cell respectively include: the first path loss is the downlink path loss of the first cell, and the second path loss is the downlink path loss of the second cell.

[0583] As an example, the first path loss and the second path loss, respectively referring to the first cell and the second cell, mean that: the first path loss is obtained by the first node by receiving a reference signal transmitted in the first cell, and the second path loss is obtained by the second node by receiving a reference signal transmitted in the second cell; the reference signal includes at least one of CSI-RS or SSB.

[0584] As an example, the meaning of the transmission power value of the first signal depending on the first path loss and the second path loss includes: the transmission power value of the first signal depends on the larger of the first path loss and the second path loss.

[0585] As an example, the meaning of the transmission power value of the first signal depending on the first path loss and the second path loss includes: the transmission power value of the first signal depending on the smaller of the first path loss and the second path loss.

[0586] As an example, the meaning of the transmission power value of the first signal depending on the first path loss and the second path loss includes: the transmission power value of the first signal depending on the weighted average of the first path loss and the second path loss.

[0587] As an example, the meaning of the transmission power value of the first signal depending on the first path loss and the second path loss includes: the transmission power value of the first signal depending on the average of the first path loss and the second path loss.

[0588] As an example, the meaning of the transmission power value of the first signal depending on the first path loss and the second path loss includes: the transmission power value of the first signal depending on the sum of the first path loss and the second path loss.

[0589] As an example, the statement that the transmission power value of the first signal depends on the first path loss and the second path loss means that the transmission power value of the first signal is linearly related to both the first path loss and the second path loss.

[0590] As an example, the meaning that the transmission power value of the first signal depends on the first path loss and the second path loss includes: the transmission power value of the first signal depends on the third path loss, wherein the third path loss is the output value of a function, and the input values ​​of the function include the first path loss and the second path loss.

[0591] As an example, the meaning of the transmission power value of the first signal depending on the first path loss and the second path loss includes: the transmission power value of the first signal depending on the smaller of a first maximum power value and a first target power value, the first target power value being the smaller of a first power value and a second power value, the first power value depending on the first path loss, and the second power value depending on the second path loss.

[0592] As a sub-implementation of this embodiment, the first maximum power value is P. CMAX,f,c (i).

[0593] As a sub-implementation of this embodiment, the first maximum power value is P. CMAX .

[0594] As a sub-implementation of this embodiment, the first maximum power value is the maximum transmission power value of the first node.

[0595] As a sub-implementation of this embodiment, the meaning that the transmission power value of the first signal depends on the smaller of the first maximum power value and the first target power value includes: the transmission power value of the first signal is equal to the smaller of the first maximum power value and the first target power value.

[0596] As a sub-implementation of this embodiment, the meaning that the transmission power value of the first signal depends on the smaller of the first maximum power value and the first target power value includes: the transmission power value of the first signal is not greater than the smaller of the first maximum power value and the first target power value.

[0597] As a sub-implementation of this embodiment, the meaning that the transmission power value of the first signal depends on the smaller of the first maximum power value and the first target power value includes: the transmission power value of the first signal is the smaller of the first maximum power value, the first target power value and the second maximum power value, and the second maximum power value is fixed or configurable.

[0598] As a sub-example of this embodiment, the first power value and the first path loss are linearly related.

[0599] As a sub-example of this embodiment, the product of the first power value and the first path loss with the first coefficient is linearly related.

[0600] As a sub-example of this embodiment, the first power value is referenced to the uplink transmission power value determined by the first node when transmitting PUSCH in the first cell.

[0601] As a sub-example of this embodiment, the second power value and the second path loss are linearly related.

[0602] As a sub-example of this embodiment, the product of the second power value and the second path loss with the second coefficient is linearly related.

[0603] As a sub-example of this embodiment, the first power value is referenced to the uplink transmission power value determined by the first node when transmitting PUSCH in the second cell.

[0604] As an example, when the first measurement report is not generated based on AI, the transmission power value of the first signal depends on the second path loss; the second path loss is specific to the second cell.

[0605] As an example, the transmission power value of the first signal depends on the smaller of a first maximum power value and a third power value, wherein the third power value depends on the second path loss.

[0606] As a sub-implementation of this embodiment, the first maximum power value is P. CMAX,f,c (i).

[0607] As a sub-implementation of this embodiment, the first maximum power value is P. CMAX .

[0608] As a sub-implementation of this embodiment, the first maximum power value is the maximum transmission power value of the first node.

[0609] As a sub-implementation of this embodiment, the meaning that the transmission power value of the first signal depends on the smaller of the first maximum power value and the third power value includes: the transmission power value of the first signal is equal to the smaller of the first maximum power value and the third power value.

[0610] As a sub-implementation of this embodiment, the fact that the transmission power value of the first signal depends on the smaller of the first maximum power value and the third power value means that the transmission power value of the first signal is not greater than the smaller of the first maximum power value and the third power value.

[0611] As a sub-implementation of this embodiment, the meaning that the transmission power value of the first signal depends on the smaller of the first maximum power value and the third power value includes: the transmission power value of the first signal is the smaller of the first maximum power value, the third power value and the third maximum power value, and the third maximum power value is fixed or configurable.

[0612] As a sub-example of this embodiment, the third power value and the second path loss are linearly related.

[0613] As a sub-example of this embodiment, the product of the third power value and the second path loss with the second coefficient is linearly related.

[0614] As a sub-example of this embodiment, the third power value is referenced to the uplink transmission power value determined by the first node when transmitting PUSCH in the second cell.

[0615] Example 8

[0616] Example 8 illustrates a second schematic diagram of the transmission power value of a first signal according to an embodiment of this application depending on the generation method of a first measurement report, as shown in Figure 8. In Figure 8, case (a) indicates that when the generation method of the first measurement report is based on AI generation, the transmission power value of the first signal is not greater than the smaller of a first power value and a second power value; case (b) indicates that when the generation method of the first measurement report is not based on AI generation, the transmission power value of the first signal is not greater than a third power value.

[0617] In Example 8, the first power value depends on the first path loss, the second power value depends on the second path loss, and the third power value depends on the second path loss.

[0618] As an example, when the first measurement report is generated based on AI, the transmission power value of the first signal is not greater than the smaller of the first power value and the second power value, where the first power value depends on the first path loss and the second power value depends on the second path loss.

[0619] As an example, the unit of the first power value is dBm (decibel relative to one milliwatt).

[0620] As an example, the unit of the first power value is mW (milliWatt).

[0621] As an example, the unit of the first power value is W (Watt).

[0622] As an example, the first power value corresponds to the formula in 3GPP TS (Technical Specification) 38.213 used to determine the transmit power of the uplink signal, where P... CMAX,f,c (i) The value of the polynomial that takes the minimum value, wherein the uplink signal is one of PUSCH, PUCCH, or PRACH.

[0623] As an example, the first node transmits the first signal during the i-th PUSCH timing, and the first power value is equal to

[0624] Wherein, c represents the first cell, b represents the BWP activated in the first cell, f represents the carrier, j represents the parameter set configuration index, μ represents the subcarrier spacing of the first signal, and q represents the subcarrier spacing of the first signal. d This represents the reference signal index for the downlink BWP to be activated, where l represents the PUSCH power control adjustment state index; the P O_PUSCH,b,f,c (j) is the desired power value of the first signal, and P O_PUSCH,b,f,c (j) depends on the expected power value of the first cell and the expected power value of the first node; The resource bandwidth allocated to the first signal, the Represented by RB numbers; the α b,f,c (j) is the road loss compensation coefficient; the PL b,f,c (q d ) is the first path loss, and the unit of the first path loss is expressed in dB; the ΔTF,b,f,c (i) depends on the transmission format (TF) of the first signal; the f b,f,c (i,l) represents the power adjustment state.

[0625] As an example, the first node transmits the first signal during the i-th PUCCH timing, and the first power value is equal to

[0626] Wherein, c represents the first cell, b represents the BWP activated in the first cell, f represents the carrier, j represents the parameter set configuration index, μ represents the subcarrier spacing of the first signal, and q represents the subcarrier spacing of the first signal. d This indicates the reference signal index for activating the downlink BWP, where l represents the PUCCH power control adjustment state index; the P... O_PUCCH,b,f,c (j) is the desired power value of the first signal, and P O_PUCCH,b,f,c (j) depends on the expected power value of the first cell and the expected power value of the first node; The resource bandwidth allocated to the first signal, the Represented by RB numbers; the α b,f,c (j) is the road loss compensation coefficient; the PL b,f,c (q d ) is the first path loss, and the unit of the first path loss is expressed in dB; the Δ F_PUCCH (F) depends on the PUCCH format of the first signal transmission; the Δ TF,b,f,c (i) is the PUCCH transmission power adjustment component; the g b,f,c (i,l) represents the power adjustment state.

[0627] As an example, the first signal is PRACH, and the first power value is equal to P. PRACH,target,f,c +PL b,f,c ;

[0628] Wherein, c represents the first cell, b represents the BWP activated in the first cell, and f represents the carrier; P PRACH,target,f,c It is the PRACH target received power, the P PRACH,target,f,c Provided by the higher-level parameter PREAMBLE_RECEIVED_TARGET_POWER; the PL b,f,c This refers to the first path loss, which is expressed in dB.

[0629] As an example, the unit of the second power value is dBm.

[0630] As an example, the unit of the second power value is mW.

[0631] As an example, the unit of the second power value is W.

[0632] As an example, the second power value corresponds to the formula in 3GPP TS 38.213 used to determine the transmit power of the uplink signal, and P CMAX,f,c (i) The value of the polynomial that takes the minimum value, wherein the uplink signal is one of PUSCH, PUCCH, or PRACH.

[0633] As an example, the first node transmits the first signal during the i-th PUSCH timing, and the second power value is equal to

[0634] Wherein, c represents the second cell, b represents the BWP activated in the second cell, f represents the carrier, j represents the parameter set configuration index, μ represents the subcarrier spacing of the first signal, and q represents the subcarrier spacing of the first signal. d The index represents the reference signal index for activating the downlink BWP, where l represents the PUSCH power control adjustment state index; the P O_PUSCH,b,f,c (j) is the desired power value of the first signal, and P O_PUSCH,b,f,c (j) depends on the expected power value of the second cell and the expected power value of the first node; The resource bandwidth allocated to the first signal, the Represented by RB numbers; the α b,f,c (j) is the road loss compensation coefficient; the PL b,f,c (q d ) is the second path loss, and the unit of the second path loss is expressed in dB; the Δ TF,b,f,c (i) depends on the transmission format of the first signal; the f b,f,c (i,l) represents the power adjustment state.

[0635] As an example, the first node transmits the first signal during the i-th PUCCH timing, and the second power value is equal to

[0636] Wherein, c represents the second cell, b represents the BWP activated in the second cell, f represents the carrier, j represents the parameter set configuration index, μ represents the subcarrier spacing of the first signal, and q represents the subcarrier spacing of the first signal. d This indicates the reference signal index for activating the downlink BWP, where l represents the PUCCH power control adjustment state index; the P... O_PUCCH,b,f,c(j) is the desired power value of the first signal, and P O_PUCCH,b,f,c (j) depends on the expected power value of the second cell and the expected power value of the first node; The resource bandwidth allocated to the first signal, the Represented by RB numbers; the α b,f,c (j) is the road loss compensation coefficient; the PL b,f,c (q d ) is the second path loss, and the unit of the second path loss is expressed in dB; the Δ F_PUCCH (F) PUCCH format dependent on the first signal transmission; the Δ TF,b,f,c (i) is the PUCCH transmission power adjustment component; the g b,f,c (i,l) represents the power adjustment state.

[0637] As an example, the first signal is PRACH, and the second power value is equal to P. PRACH,target,f,c +PL b,f,c ;

[0638] Wherein, c represents the second cell, b represents the BWP activated in the second cell, and f represents the carrier; P PRACH,target,f,c It is the PRACH target received power, the P PRACH,target,f,c Provided by the higher-level parameter PREAMBLE_RECEIVED_TARGET_POWER; the PL b,f,c This refers to the second path loss, which is expressed in dB.

[0639] As an example, when the first measurement report is generated in a manner not based on AI, the transmission power value of the first signal is not greater than a third power value, the third power value depending on the second path loss.

[0640] As an example, the unit of the third power value is dBm.

[0641] As an example, the unit of the third power value is mW.

[0642] As an example, the unit of the third power value is W.

[0643] As an example, the third power value corresponds to the formula in 3GPP TS 38.213 used to determine the transmit power of the uplink signal, and P CMAX,f,c (i) The value of the polynomial that takes the minimum value, wherein the uplink signal is one of PUSCH, PUCCH, or PRACH.

[0644] As an example, the first node transmits the first signal during the i-th PUSCH timing, and the third power value is equal to

[0645] Wherein, c represents the second cell, b represents the BWP activated in the second cell, f represents the carrier, j represents the parameter set configuration index, μ represents the subcarrier spacing of the first signal, and q represents the subcarrier spacing of the first signal. d This represents the reference signal index for the activated downlink BWP, where l represents the PUSCH power control adjustment state index; the P O_PUSCH,b,f,c (j) is the desired power value of the first signal, and P O_PUSCH,b,f,c (j) depends on the expected power value of the second cell and the expected power value of the first node; The resource bandwidth allocated to the first signal, the Represented by RB numbers; the α b,f,c (j) is the road loss compensation coefficient; the PL b,f,c (q d ) is the second path loss, and the unit of the second path loss is expressed in dB; the Δ TF,b,f,c (i) depends on the transmission format of the first signal; the f b,f,c (i,l) represents the power adjustment state.

[0646] As an example, the first node transmits the first signal during the i-th PUCCH timing, and the third power value is equal to

[0647] Wherein, c represents the second cell, b represents the BWP activated in the second cell, f represents the carrier, j represents the parameter set configuration index, μ represents the subcarrier spacing of the first signal, and q represents the subcarrier spacing of the first signal. d This indicates the reference signal index for activating the downlink BWP, where l represents the PUCCH power control adjustment state index; the P... O_PUCCH,b,f,c (j) is the desired power value of the first signal, and P O_PUCCH,b,f,c (j) depends on the expected power value of the second cell and the expected power value of the first node; The resource bandwidth allocated to the first signal, the Represented by RB numbers; the α b,f,c (j) is the road loss compensation coefficient; the PL b,f,c (q d ) is the second path loss, and the unit of the second path loss is expressed in dB; the Δ F_PUCCH (F) PUCCH format dependent on the first signal transmission; the ΔTF,b,f,c (i) is the PUCCH transmission power adjustment component; the g b,f,c (i,l) represents the power adjustment state.

[0648] As an example, the first signal is PRACH, and the third power value is equal to P. PRACH,target,f,c +PL b,f,c ;

[0649] Wherein, c represents the second cell, b represents the BWP activated in the second cell, and f represents the carrier; P PRACH,target,f,c It is the PRACH target received power, the P PRACH,target,f,c Provided by the higher-level parameter PREAMBLE_RECEIVED_TARGET_POWER; the PL b,f,c This refers to the second path loss, which is expressed in dB.

[0650] As an example, the second power value and the third power value are the same.

[0651] Example 9

[0652] Example 9 illustrates a schematic diagram of RAN domain AI / ML function deployment according to one embodiment of this application, as shown in Figure 9. In Figure 9, the gNB can be replaced with, for example, an eNB, or a network device such as a 6G base station.

[0653] In Example 9, the management of ML inference functions of multiple base stations is completed by the RAN domain management function 902, that is, data interaction with the RAN domain MnS (Management Service) consumer / cross-domain management 901 (as shown by the dashed arrow in Figure 9). The RAN domain ML training function 903 is located in the RAN domain management function 902; 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.

[0654] 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.

[0655] 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 (Management Data Analytic 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).

[0656] 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.

[0657] Similarly, ML testing capabilities can also be deployed in cross-domain management systems or domain-specific management systems.

[0658] 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.

[0659] 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.

[0660] As an example, one of the gNBs (or base stations) in Example 9 is the second node of this application.

[0661] As an example, the second node in this application includes a gNB (or base station) in Example 9.

[0662] Example 10

[0663] 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 Figure 10. In Figure 10, the RAN domain ML training function 1004 is optional.

[0664] UE function 1003 is deployed in the first node of this application, and the UE function 1003 includes AI / ML inference function 1005; the AI / ML inference function 1005 uses an ML model (also called an AI model) for inference; an ML model is typically trained before being used for AI / ML inference.

[0665] As an example, the UE function 1003 includes a RAN domain ML training function 1004, 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.

[0666] 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.

[0667] Optionally, the UE function 1003 also includes a CN domain ML training function (not shown in Figure 10).

[0668] Optionally, the UE function 1003 also includes an AI / ML deployment function—not shown in Figure 10—for loading ML models and data.

[0669] 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.

[0670] As an example, the ML model and the associated metadata are loaded by the first node from a network device or a remote server.

[0671] Optionally, the UE function 1003 is an MnS producer that provides data to the CN domain MnF (Management Function) and / or the RAN domain MnF and / or the cross-domain management system 1001 for management or analysis (as shown by the double arrow 1002).

[0672] Optionally, the UE function 1003 is an MnS consumer that loads data from the CN domain MnF and / or RAN domain MnF and / or cross-domain management system 1001 for AI / ML-related management, such as managing data requests, ML model activation, and / or ML training (as shown by double arrow 1002).

[0673] As an example, the first measurement report is generated based on AI. The first measurement report in this application is obtained through inference by the AI / ML inference function 1005.

[0674] As an example, the ML model is based on NN.

[0675] As an example, the ML model is based on ANN.

[0676] As an example, the ML model is based on CNN.

[0677] As an example, the ML model is based on the Transformer architecture.

[0678] As an example, the ML model is based on LSTM.

[0679] As an example, the ML model is based on MLP.

[0680] As an example, the ML model is based on GAN.

[0681] As an example, the ML model is based on a lightweight neural network.

[0682] As a sub-example of this embodiment, the lightweight neural network includes one or more of MobileNet, ShuffleNet, and SqueezeNet.

[0683] Example 11

[0684] 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 Figure 11. In Figure 11, the processing system based on artificial intelligence or machine learning includes a first processor, a second processor, a third processor, and a fourth processor.

[0685] 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, and optionally, the third processor sends the first-class output to the fourth processor. In Figure 11, the first-class feedback and the second-class feedback are optional; the second processor includes ML training functionality; the third processor includes ML inference functionality.

[0686] As one embodiment, the fourth processor includes ML testing functionality.

[0687] As one embodiment, the fourth processor includes performance monitoring / evaluation of the ML model.

[0688] 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.

[0689] 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.

[0690] As one embodiment, the first processor generates the first dataset and the second dataset based on the measurement of the reference signal.

[0691] As one embodiment, the third processor belongs to the first node, and the fourth processor belongs to the second node.

[0692] As an example, the first dataset includes training data.

[0693] 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.

[0694] As an example, the second processor belongs to the first node; the above method avoids passing the first dataset to the second node.

[0695] As an example, the second processor belongs to the second node; the above method supports joint training and optimizes system performance.

[0696] As an example, the second processor belongs to the core network; the above method supports network-wide joint training, further optimizing system performance.

[0697] As an example, the second dataset includes inference data.

[0698] As an example, the first measurement report is generated based on AI, and the second dataset includes the first reference signal.

[0699] As an example, the first measurement report is generated based on AI, and the second dataset includes the second reference signal.

[0700] As an example, the first measurement report is generated based on AI, and the third processor belongs to the first node.

[0701] 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.

[0702] As an example, the first measurement report is generated based on AI, and the first type of output includes the channel quality of the first cell.

[0703] As an example, the first measurement report is generated based on AI, and the first type of output includes the channel quality of the second cell.

[0704] As an example, the first measurement report is generated based on AI, and the first type of output includes the channel quality of the first cell and the second cell.

[0705] As an example, the first measurement report is generated based on AI, and the first type of output includes the first measurement report.

[0706] As an example, the first measurement report is generated based on AI, and the first type of output triggers the first node to send the first measurement report.

[0707] As an example, the first measurement report is generated based on AI, and the first measurement report includes some or all of the first type of output.

[0708] As an example, the first measurement report is generated based on AI, and whether the first node sends the first measurement report depends on the first type of output.

[0709] 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.

[0710] 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.

[0711] 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.

[0712] 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.

[0713] 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.

[0714] Example 12

[0715] Example 12 illustrates a schematic diagram based on artificial intelligence or machine learning according to an embodiment of this application, as shown in Figure 12. In Figure 12, 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.

[0716] 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.

[0717] 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.

[0718] As an example, the first stage includes AI / ML model training.

[0719] As an example, the first stage includes AI / ML model training and AI / ML testing.

[0720] As an example, the AI / ML model training includes initial training and re-training of one or a group of AI / ML entities.

[0721] As an example, the training of the AI / ML model depends on training data.

[0722] As an example, the AI / ML model training includes AI / ML entity validation.

[0723] As an example, the AI / ML entity verification is used to evaluate the performance of the AI / ML entity.

[0724] As an example, the AI / ML entity verification relies on verification data.

[0725] As an example, if the AI / ML entity verification results do not meet expectations, the AI / ML model will be retrained.

[0726] As an example, the AI / ML testing includes testing the validated AI / ML entities to estimate the performance of the trained AI / ML model.

[0727] 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.

[0728] As an example, the AI / ML test relies on test data.

[0729] As one embodiment, the second stage includes AI / ML simulation, which performs AI / ML entity reasoning in a simulation environment.

[0730] As an example, the AI / ML simulation estimates the performance of AI / ML entity reasoning in a simulation environment before using AI / ML entities.

[0731] As one embodiment, the second stage is optional.

[0732] 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.

[0733] As an example, the third stage is optional.

[0734] As an example, the third stage is no longer needed when the training and inference functions are co-located.

[0735] As an example, the fourth stage includes AI / ML inference.

[0736] As an example, the first measurement report is generated based on AI, and some or all of the components of the first measurement report are generated in the fourth stage.

[0737] Example 13

[0738] Example 13 illustrates a structural block diagram of a processing apparatus for a first node according to an embodiment of the present application, as shown in Figure 13. In Figure 13, the processing apparatus 1300 in the first node includes a first receiver 1301 and a first transmitter 1302.

[0739] In embodiment 13, the first transmitter 1302 sends a first measurement report in the first cell, and then sends a first signal.

[0740] In Example 13, the first measurement report includes at least one of the channel quality of the first cell or the channel quality of the second cell; the second cell is a cell other than the first node; the first signal is directed to the second cell; the transmit power value of the first signal depends on the generation method of the first measurement report; the generation method of the first measurement report is one of AI-based generation or not based on AI generation.

[0741] As an example, when the first measurement report is generated based on AI, the transmission power value of the first signal depends on the first path loss and the second path loss; when the first measurement report is not generated based on AI, the transmission power value of the first signal depends on the second path loss; the first path loss and the second path loss are respectively for the first cell and the second cell.

[0742] As an example, the generation method of the first measurement report being based on AI means at least one of the following:

[0743] - The first measurement report is generated through prediction;

[0744] - The first measurement report was generated through inference;

[0745] - The first measurement report is generated by a model, which is at least one of AI or ML.

[0746] As an example, when the first measurement report is generated based on AI, the transmission power value of the first signal is not greater than the smaller of the first power value and the second power value, the first power value depends on the first path loss, and the second power value depends on the second path loss; when the first measurement report is not generated based on AI, the transmission power value of the first signal is not greater than the third power value, and the third power value depends on the second path loss.

[0747] As one embodiment, the first receiver 1301 receives a first reference signal and a second reference signal; the channel quality of the first cell depends on the reception of the first reference signal, and the channel quality of the second cell depends on the reception of the second reference signal; the channel quality of the second cell is better than the channel quality of the first cell.

[0748] As an example, the first receiver 1301 receives the first signaling; the transmission of the first signal depends on the first signaling.

[0749] As one embodiment, the first receiver 1301 receives a second signaling, which configures a measurement object and a measurement time for the first cell and the second cell, respectively; at least one channel measurement value for the first cell is obtained by measuring the measurement object for the first cell during the measurement time, and at least one channel measurement value for the second cell is obtained by measuring the measurement object for the second cell during the measurement time; when the first measurement report is generated based on AI, at least one of the at least one channel measurement value for the first cell or the at least one channel measurement value for the second cell is used to generate the first measurement report.

[0750] As an example, the first transmitter 1302 transmits the first signal on the second cell.

[0751] As an example, the physical layer channel occupied by the first signal is PUSCH.

[0752] As an example, the physical layer channel occupied by the first signal is PUCCH.

[0753] As an example, the physical layer channel occupied by the first signal is PRACH.

[0754] As an example, the first measurement report is generated based on AI. The first node predicts the content of the first measurement report based on the measurement results using an AI model and then sends the first measurement report.

[0755] As an example, the generation method of the first measurement report is based on AI. The first node predicts and sends the first measurement report based on the measurement results using an AI model.

[0756] As an example, the first measurement report is generated based on AI. The first node predicts the current measurement results of the first cell and the second cell using an AI model based on the previous measurement results of the first cell and the second cell, and then generates and sends the first measurement report.

[0757] As an example, the first measurement report is generated based on AI. The first node uses an AI model to predict the future measurement results of the first cell and the second cell based on the current measurement results of the first cell and the second cell, and then generates and sends the first measurement report.

[0758] As an example, the first measurement report is generated based on AI, and the first measurement report includes the channel quality of the first cell, which is generated based on AI.

[0759] As an example, the first measurement report is generated based on AI, and the first measurement report includes the channel quality of the second cell, which is generated based on AI.

[0760] As an example, the first measurement report is generated based on AI. The first measurement report includes the channel quality of the first cell and the channel quality of the second cell, and at least one of the channel quality of the first cell and the channel quality of the second cell is generated based on AI.

[0761] As an example, the first measurement report is generated using AI, and the first measurement report is triggered by a single event, which triggers the first node to send the first measurement report.

[0762] As one example, the first node is a user equipment.

[0763] As an example, the first node is a relay node device.

[0764] As an example, the first receiver 1301 includes at least one of the following in embodiment 4: the antenna 452, the receiver 454, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467.

[0765] As an example, the first transmitter 1302 includes at least one of the following in embodiment 4: 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.

[0766] Example 14

[0767] 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 Figure 14. In Figure 14, the processing apparatus 1400 in the second node includes a second transmitter 1401 and a second receiver 1402.

[0768] In embodiment 14, the second receiver 1402 receives a first measurement report in the first cell, and then receives a first signal.

[0769] In Example 14, the first measurement report includes at least one of the channel quality of the first cell or the channel quality of the second cell; the second cell is a cell other than the sender of the first measurement report; the first signal is directed to the second cell; the transmission power value of the first signal depends on the generation method of the first measurement report; the generation method of the first measurement report is either AI-generated or not AI-generated.

[0770] As an example, when the first measurement report is generated based on AI, the transmission power value of the first signal depends on the first path loss and the second path loss; when the first measurement report is not generated based on AI, the transmission power value of the first signal depends on the second path loss; the first path loss and the second path loss are respectively for the first cell and the second cell.

[0771] As an example, the generation method of the first measurement report being based on AI means at least one of the following:

[0772] - The first measurement report is generated through prediction;

[0773] - The first measurement report was generated through inference;

[0774] - The first measurement report is generated by a model, which is at least one of AI or ML.

[0775] As an example, when the first measurement report is generated based on AI, the transmission power value of the first signal is not greater than the smaller of the first power value and the second power value, the first power value depends on the first path loss, and the second power value depends on the second path loss; when the first measurement report is not generated based on AI, the transmission power value of the first signal is not greater than the third power value, and the third power value depends on the second path loss.

[0776] As one embodiment, the second transmitter 1401 transmits a first reference signal and a second reference signal; the channel quality of the first cell depends on the reception of the first reference signal, and the channel quality of the second cell depends on the reception of the second reference signal; the channel quality of the second cell is better than the channel quality of the first cell.

[0777] As one embodiment, the second transmitter 1401 sends a first signaling; the transmission of the first signal depends on the first signaling.

[0778] As one embodiment, the second transmitter 1401 sends a second signaling, which configures a measurement object and a measurement time for the first cell and the second cell, respectively; at least one channel measurement value for the first cell is obtained by measuring the measurement object for the first cell during the measurement time, and at least one channel measurement value for the second cell is obtained by measuring the measurement object for the second cell during the measurement time; when the first measurement report is generated based on AI, at least one of the at least one channel measurement value for the first cell or the at least one channel measurement value for the second cell is used to generate the first measurement report.

[0779] As one embodiment, the second transmitter 1401 transmits a first reference signal; the sustaining base station of the second cell transmits a second reference signal, the channel quality of the first cell depends on the reception of the first reference signal, the channel quality of the second cell depends on the reception of the second reference signal; the channel quality of the second cell is better than the channel quality of the first cell.

[0780] As one embodiment, the second receiver receives the first signal on the second cell.

[0781] As one example, the second node is the sustaining base station for the first cell and the second cell.

[0782] As one example, the second node is associated with multiple cells, including the first cell and the second cell.

[0783] As one example, the second node manages the first cell and the second cell.

[0784] As an example, the physical layer channel occupied by the first signal is PUSCH.

[0785] As an example, the physical layer channel occupied by the first signal is PUCCH.

[0786] As an example, the physical layer channel occupied by the first signal is PRACH.

[0787] As an example, the first measurement report is generated based on AI. The first node predicts the content of the first measurement report based on the measurement results using an AI model and then sends the first measurement report.

[0788] As an example, the generation method of the first measurement report is based on AI. The first node predicts and sends the first measurement report based on the measurement results using an AI model.

[0789] As an example, the first measurement report is generated based on AI. The first node predicts the current measurement results of the first cell and the second cell using an AI model based on the previous measurement results of the first cell and the second cell, and then generates and sends the first measurement report.

[0790] As an example, the first measurement report is generated based on AI. The first node uses an AI model to predict the future measurement results of the first cell and the second cell based on the current measurement results of the first cell and the second cell, and then generates and sends the first measurement report.

[0791] As an example, the first measurement report is generated based on AI, and the first measurement report includes the channel quality of the first cell, which is generated based on AI.

[0792] As an example, the first measurement report is generated based on AI, and the first measurement report includes the channel quality of the second cell, which is generated based on AI.

[0793] As an example, the first measurement report is generated based on AI. The first measurement report includes the channel quality of the first cell and the channel quality of the second cell, and at least one of the channel quality of the first cell and the channel quality of the second cell is generated based on AI.

[0794] As an example, the first measurement report is generated using AI, and the first measurement report is triggered by a single event, which triggers the first node to send the first measurement report.

[0795] In one embodiment, the second node is a base station device.

[0796] In one embodiment, the second node is a user equipment.

[0797] As an example, the second node is a TRP.

[0798] As one embodiment, the second transmitter 1401 includes at least one of the following in embodiment 4: the antenna 420, the transmitter 418, the transmission processor 416, the multi-antenna transmission processor 471, the controller / processor 475, and the memory 476.

[0799] As one embodiment, the second receiver 1402 includes at least one of the following in embodiment 4: the antenna 420, the receiver 418, the receiver processor 470, the multi-antenna receiver processor 472, the controller / processor 475, and the memory 476.

[0800] 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. Correspondingly, 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 cards, IoT terminals, RFID (Radio Frequency Identification) terminals, NB-IoT (Narrow Band Internet of Things) terminals, MTC (Machine Type Communication) terminals, eMTC (enhanced MTC) terminals, data cards, internet cards, vehicle-mounted communication equipment, low-cost mobile phones, low-cost tablets, and other wireless communication devices. The base station or system equipment in this application includes, but is not limited to, macrocell base stations, microcell base stations, small cell base stations, home base stations, relay base stations, eNB (evolved Node B), gNB, TRP, GNSS (Global Navigation Satellite System), relay satellites, satellite base stations, airborne base stations, RSUs, unmanned aerial vehicles, and test equipment, such as transceivers or signaling testers that simulate some functions of a base station, and other wireless communication equipment.

[0801] 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 for mobility management in wireless communication, the first node being configured to, Comprising: a first transmitter, transmitting a first measurement report in a first cell, followed by transmitting a first signal; wherein the first measurement report comprises at least one of a channel quality of the first cell or a channel quality of a second cell; the second cell is a cell other than the first node; the first signal is for the second cell; a transmission power value of the first signal depends on a generation manner of the first measurement report; the generation manner of the first measurement report is one of based on AI or not based on AI.

2. The first node of claim 1, characterized in that, When the generation manner of the first measurement report is based on AI, the transmission power value of the first signal depends on a first path loss and a second path loss; when the generation manner of the first measurement report is not based on AI, the transmission power value of the first signal depends on the second path loss; the first path loss and the second path loss are for the first cell and the second cell respectively.

3. The first node of claim 1 or 2, characterized by, The meaning that the generation manner of the first measurement report is based on AI includes at least one of: - the first measurement report is generated by prediction; - the first measurement report is generated by inference; - the first measurement report is generated by a model, the model is at least one of AI or ML.

4. The first node of claim 2 or 3, wherein, When the generation manner of the first measurement report is based on AI, the transmission power value of the first signal is not greater than a smaller value of a first power value and a second power value, the first power value depends on the first path loss, the second power value depends on the second path loss; when the generation manner of the first measurement report is not based on AI, the transmission power value of the first signal is not greater than a third power value, the third power value depends on the second path loss.

5. The first node of any of claims 1 to 4, wherein, Comprising: a first receiver, receiving a first reference signal and a second reference signal; wherein the channel quality of the first cell depends on reception of the first reference signal, the channel quality of the second cell depends on reception of the second reference signal; the channel quality of the second cell is better than the channel quality of the first cell.

6. The first node of any of claims 1 to 5, wherein, Comprising: a first receiver, receiving a first signaling; wherein transmission of the first signal depends on the first signaling.

7. The first node of any of claims 1-6, wherein, Comprising: a first receiver, receiving a second signaling, the second signaling configures a measurement object and a measurement time for the first cell and the second cell respectively; wherein at least one channel measurement value for the first cell is obtained by measurement of the measurement object in the measurement time for the first cell, at least one channel measurement value for the second cell is obtained by measurement of the measurement object in the measurement time for the second cell; when the generation manner of the first measurement report is based on AI, at least one of at least one of the channel measurement value for the first cell or at least one of the channel measurement value for the second cell is used to generate the first measurement report.

8. A second node for mobility management in wireless communications, characterized in that, Comprising: a second receiver, receiving a first measurement report in a first cell, followed by receiving a first signal; The first measurement report includes at least one of a channel quality of the first cell or a channel quality of a second cell; the second cell is a cell other than a sender of the first measurement report; the first signal is for the second cell; a transmission power value of the first signal depends on a generation manner of the first measurement report; the generation manner of the first measurement report is one of AI-based generation or non-AI-based generation.

9. The second node of claim 8, wherein, When the generation manner of the first measurement report is AI-based generation, the transmission power value of the first signal depends on a first path loss and a second path loss; when the generation manner of the first measurement report is non-AI-based generation, the transmission power value of the first signal depends on the second path loss; the first path loss and the second path loss are respectively for the first cell and the second cell.

10. The second node of claim 8 or 9, characterized by, The meaning that the generation manner of the first measurement report is AI-based generation includes at least one of the following: The first measurement report is generated by prediction; The first measurement report is generated by inference; The first measurement report is generated by a model, the model being at least one of AI or ML.

11. The second node of any of claims 9-10, wherein, When the generation manner of the first measurement report is AI-based generation, the transmission power value of the first signal is not greater than a smaller value of a first power value and a second power value, the first power value depending on the first path loss, and the second power value depending on the second path loss; when the generation manner of the first measurement report is non-AI-based generation, the transmission power value of the first signal is not greater than a third power value, the third power value depending on the second path loss.

12. The second node of any of claims 8-11, wherein, Comprising: The second transmitter transmits a first reference signal and a second reference signal; The channel quality of the first cell depends on reception of the first reference signal, and the channel quality of the second cell depends on reception of the second reference signal; the channel quality of the second cell is better than the channel quality of the first cell.

13. The second node of any of claims 8 to 12, wherein, Comprising: The second transmitter transmits a first signaling; transmission of the first signal depends on the first signaling.

14. The second node of any of claims 8 to 13, wherein, Comprising: The second transmitter transmits a second signaling, the second signaling configuring a measurement object and a measurement time for the first cell and the second cell respectively; At least one channel measurement value for the first cell is obtained through measurement of the measurement object in the measurement time for the first cell, and at least one channel measurement value for the second cell is obtained through measurement of the measurement object in the measurement time for the second cell; when the generation manner of the first measurement report is AI-based generation, at least one of at least one channel measurement value for the first cell or at least one channel measurement value for the second cell is used to generate the first measurement report.

15. A method for a first node in wireless communication mobility management, the method comprising: Comprising: Transmitting a first measurement report in a first cell, and then transmitting a first signal; The first measurement report includes at least one of a channel quality of the first cell or a channel quality of a second cell; the second cell is a cell other than the first node; the first signal is for the second cell; a transmission power value of the first signal depends on a generation manner of the first measurement report; the generation manner of the first measurement report is one of AI-based generation or non-AI-based generation.

16. The method of claim 15, wherein, When the generation manner of the first measurement report is AI-based generation, the transmission power value of the first signal depends on a first path loss and a second path loss; when the generation manner of the first measurement report is non-AI-based generation, the transmission power value of the first signal depends on the second path loss; the first path loss and the second path loss are respectively for the first cell and the second cell.

17. The method according to claim 15 or 16, characterized in that, The meaning that the generation manner of the first measurement report is AI-based generation includes at least one of the following: The first measurement report is generated by prediction; The first measurement report is generated by inference; The first measurement report is generated by a model, the model being at least one of AI or ML.

18. The method of any one of claims 16-17, wherein, When the generation manner of the first measurement report is AI-based generation, the transmission power value of the first signal is not greater than a smaller value of a first power value and a second power value, the first power value depending on the first path loss, and the second power value depending on the second path loss; when the generation manner of the first measurement report is non-AI-based generation, the transmission power value of the first signal is not greater than a third power value, the third power value depending on the second path loss.

19. The method of any one of claims 15-18, wherein, Comprising: Receiving a first reference signal and a second reference signal; The channel quality of the first cell depends on reception of the first reference signal, and the channel quality of the second cell depends on reception of the second reference signal; the channel quality of the second cell is better than the channel quality of the first cell.

20. The method of any one of claims 15-19, wherein, Comprising: Receiving a first signaling; Transmission of the first signal depends on the first signaling.

21. The method of any one of claims 15-20, wherein, Comprising: Receiving a second signaling, the second signaling configuring a measurement object and a measurement time for the first cell and the second cell respectively; At least one channel measurement value for the first cell is obtained by measurement of the measurement object in the measurement time for the first cell, and at least one channel measurement value for the second cell is obtained by measurement of the measurement object in the measurement time for the second cell; when the generation manner of the first measurement report is AI-based generation, at least one of at least one channel measurement value for the first cell or at least one channel measurement value for the second cell is used to generate the first measurement report.

22. A method for a second node in wireless communication mobility management, the method comprising: Comprising: Receiving a first measurement report in a first cell, and then receiving a first signal; The first measurement report includes at least one of a channel quality of the first cell or a channel quality of a second cell; the second cell is a cell other than a sender of the first measurement report; the first signal is for the second cell; a transmission power value of the first signal depends on a generation manner of the first measurement report; the generation manner of the first measurement report is one of AI-based generation or non-AI-based generation.

23. The method of claim 22, wherein, When the generation manner of the first measurement report is AI-based generation, the transmission power value of the first signal depends on a first path loss and a second path loss; when the generation manner of the first measurement report is non-AI-based generation, the transmission power value of the first signal depends on the second path loss; the first path loss and the second path loss are respectively for the first cell and the second cell.

24. The method of claim 22 or 23, wherein, The meaning that the generation manner of the first measurement report is AI-based generation includes at least one of the following: The first measurement report is generated by prediction; The first measurement report is generated by inference; The first measurement report is generated by a model, the model being at least one of AI or ML.

25. The method of any of claims 23-24, wherein, When the generation manner of the first measurement report is AI-based generation, the transmission power value of the first signal is not greater than a smaller value of a first power value and a second power value, the first power value depending on the first path loss, and the second power value depending on the second path loss; when the generation manner of the first measurement report is non-AI-based generation, the transmission power value of the first signal is not greater than a third power value, the third power value depending on the second path loss.

26. The method of any one of claims 22-25, wherein, Comprising: Transmitting a first reference signal and a second reference signal; The channel quality of the first cell depends on reception of the first reference signal, and the channel quality of the second cell depends on reception of the second reference signal; the channel quality of the second cell is better than the channel quality of the first cell.

27. The method of any one of claims 22-26, wherein, Comprising: Transmitting a first signaling; Transmission of the first signal depends on the first signaling.

28. The method of any one of claims 22-27, wherein, Comprising: Transmitting a second signaling, the second signaling configuring a measurement object and a measurement time for the first cell and the second cell respectively; At least one channel measurement value for the first cell is obtained by measurement of the measurement object in the measurement time for the first cell, and at least one channel measurement value for the second cell is obtained by measurement of the measurement object in the measurement time for the second cell; when the generation manner of the first measurement report is AI-based generation, at least one of at least one of the channel measurement value for the first cell or at least one of the channel measurement value for the second cell is used to generate the first measurement report.

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