Beam management method and apparatus

Abstract

Provided in the embodiments of the present application are a beam management method and apparatus. The method comprises: a terminal device receiving, from a network device, configuration information used for beam management; and the terminal device performing spatial beam prediction or temporal beam prediction on the basis of the configuration information by using an AI / ML model / function.

Description

Beam management method and device Technical Field

[0001] The embodiments of this application relate to the field of communication technology. Background Technology

[0002] In NR Rel-18, artificial intelligence / machine learning (AI / ML) for the air interface was studied. AI / ML can be used for the following use cases: Channel State Information (CSI) feedback enhancement, beam management, and positioning enhancement. CSI feedback enhancement can include CSI prediction and CSI compression; beam management can include spatial beam prediction (BM case-1) and temporal beam prediction (BM case-2); positioning enhancement can include direct positioning and AI / ML-assisted positioning.

[0003] In some sub-use cases, a two-sided model can be used, meaning the AI / ML model is on both the terminal device side and the network device side. In other sub-use cases, a one-sided model can be used, meaning the AI / ML model is on either the terminal device side or the network device side. For beam management, the AI / ML model can be on both the terminal device side and / or the network device side.

[0004] It should be noted that the above introduction to the technical background is only for the purpose of providing a clear and complete explanation of the technical solutions of this application and facilitating understanding by those skilled in the art. It should not be assumed that these technical solutions are known to those skilled in the art simply because they have been described in the background section of this application.

[0005] Summary of the Invention

[0006] The inventors discovered that terminal devices and / or network devices can perform beam management using AI / ML functions / models. However, current AI / ML-based beam management is not accurate enough and requires enhancements such as the configuration and / or measurement of reference signals. Further research is needed on how to perform beam management in detail.

[0007] To address at least one of the above-mentioned problems, embodiments of this application provide a beam management method and apparatus.

[0008] According to one aspect of the embodiments of this application, a beam management method is provided, comprising:

[0009] The terminal device receives configuration information for beam management from the network device;

[0010] The terminal device performs spatial beam prediction or temporal beam prediction based on the configuration information, using AI / ML models / functions.

[0011] According to another aspect of the embodiments of this application, a beam management device is provided, comprising:

[0012] The receiver receives configuration information for beam management from the network device;

[0013] The processor, based on an AI / ML model / function, performs spatial beam prediction or temporal beam prediction according to the configuration information.

[0014] According to another aspect of the embodiments of this application, a beam management method is provided, comprising:

[0015] The network device sends configuration information for beam management to the terminal device;

[0016] The configuration information is used by the terminal device to perform spatial beam prediction or temporal beam prediction based on AI / ML models / functions.

[0017] According to another aspect of the embodiments of this application, a beam management device is provided, comprising:

[0018] A transmitter that sends configuration information for beam management to terminal devices;

[0019] The configuration information is used by the terminal device to perform spatial beam prediction or temporal beam prediction based on AI / ML models / functions.

[0020] According to another aspect of the embodiments of this application, a communication system is provided, comprising:

[0021] Network devices that send configuration information for beam management;

[0022] The terminal device receives configuration information for beam management from the network device; based on the AI / ML model / function, it performs spatial beam prediction or temporal beam prediction according to the configuration information.

[0023] The beneficial effects of this application's embodiments include: the terminal device receiving configuration information from the network device; and performing spatial beam prediction and / or temporal beam prediction based on the configuration information using AI / ML functions / models. This improves the accuracy of beam management and enhances the performance and efficiency of AI / ML.

[0024] Specific embodiments of this application are disclosed in detail with reference to the following description and accompanying drawings, indicating how the principles of this application can be adopted. It should be understood that the embodiments of this application are not limited in scope. Within the spirit and scope of the appended claims, embodiments of this application include many changes, modifications, and equivalents.

[0025] Features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, combined with features in other embodiments, or substituted for features in other embodiments.

[0026] It should be emphasized that the term "including / comprises" as used herein refers to the presence of a feature, whole, step, or component, but does not exclude the presence or addition of one or more other features, wholes, steps, or components. Attached Figure Description

[0027] The elements and features described in one drawing or embodiment of this application may be combined with elements and features shown in one or more other drawings or embodiments. Furthermore, in the drawings, similar reference numerals denote corresponding parts in several drawings and can be used to indicate corresponding parts used in more than one embodiment.

[0028] Figure 1 is a schematic diagram of a communication system according to an embodiment of this application;

[0029] Figure 2 is a schematic diagram of AI / ML used for beam management;

[0030] Figure 3 is a schematic diagram of a beam management method according to an embodiment of this application;

[0031] Figure 4 is another schematic diagram of the beam management method according to an embodiment of this application;

[0032] Figure 5 is a schematic diagram of the measurement window and prediction window according to an embodiment of this application;

[0033] Figure 6 is an example of a reasoning result report being cancelled according to an embodiment of this application;

[0034] Figure 7 is an example diagram showing that the reasoning results of an embodiment of this application are still reported;

[0035] Figure 8 is an example diagram of the QCL relationship in an embodiment of this application;

[0036] Figure 9 is a schematic diagram of a beam management method according to an embodiment of this application;

[0037] Figure 10 is a schematic diagram of a beam management device according to an embodiment of this application;

[0038] Figure 11 is a schematic diagram of a beam management device according to an embodiment of this application;

[0039] Figure 12 is a schematic diagram of a terminal device according to an embodiment of this application;

[0040] Figure 13 is a schematic diagram of a network device according to an embodiment of this application. Detailed Implementation

[0041] Referring to the accompanying drawings, the foregoing and other features of this application will become apparent from the following description. Specific embodiments of this application are specifically disclosed in the description and drawings, illustrating partial implementations in which the principles of this application may be employed. It should be understood that this application is not limited to the described embodiments; rather, it includes all modifications, variations, and equivalents falling within the scope of the appended claims.

[0042] In the embodiments of this application, the terms "first," "second," etc., are used to distinguish different elements by name, but do not indicate the spatial arrangement or chronological order of these elements, and these elements should not be limited by these terms. The term "and / or" includes any one or more of the terms listed in association and all combinations thereof. The terms "comprising," "including," "having," etc., refer to the presence of the stated features, elements, components, or assemblies, but do not exclude the presence or addition of one or more other features, elements, components, or assemblies.

[0043] In the embodiments of this application, the singular forms "a," "the," etc., including the plural forms, should be broadly understood as "a kind" or "a class" rather than limited to the meaning of "an." Furthermore, the term "the" should be understood to include both the singular and plural forms, unless the context explicitly indicates otherwise. Additionally, the term "according to" should be understood as "at least partially based on…," and the term "based on" should be understood as "at least partially based on…," unless the context explicitly indicates otherwise.

[0044] In the embodiments of this application, the term "communication network" or "wireless communication network" may refer to a network that conforms to any of the following communication standards, such as Long Term Evolution (LTE), LTE-Advanced (LTE-A), Wideband Code Division Multiple Access (WCDMA), High-Speed ​​Packet Access (HSPA), etc.

[0045] Furthermore, communication between devices in a communication system can be carried out according to communication protocols at any stage, including but not limited to the following communication protocols: 1G (generation), 2G, 2.5G, 2.75G, 3G, 4G, 4.5G and 5G, New Radio (NR), future 6G, etc., and / or other currently known or future communication protocols.

[0046] In the embodiments of this application, the term "network device" refers, for example, to a device in a communication system that connects a terminal device to a communication network and provides services to that terminal device. Network devices may include, but are not limited to, the following devices: base station (BS), access point (AP), transmission reception point (TRP), broadcast transmitter, mobile management entity (MME), gateway, server, radio network controller (RNC), base station controller (BSC), etc.

[0047] Base stations can include, but are not limited to: NodeBs (or NBs), evolved NodeBs (eNodeBs or eNBs), and 5G base stations (gNBs), IAB hosts, etc. They can also include Remote Radio Heads (RRHs), Remote Radio Units (RRUs), relays, or low-power nodes (e.g., femeto, pico, etc.). The term "base station" can encompass some or all of their functions, and each base station can provide communication coverage to a specific geographic area. The term "cell" can refer to a base station and / or its coverage area, depending on the context in which the term is used.

[0048] In the embodiments of this application, the terms "User Equipment" (UE) or "Terminal Equipment" (TE) refer, for example, to a device that accesses a communication network and receives network services through a network device. A terminal device can be fixed or mobile, and may also be referred to as a mobile station (MS), terminal, subscriber station (SS), access terminal (AT), station, etc.

[0049] The terminal device may include, but is not limited to, the following devices: cellular phone, personal digital assistant (PDA), wireless modem, wireless communication device, handheld device, machine-type communication device, laptop computer, cordless phone, smartphone, smartwatch, digital camera, etc.

[0050] For example, in scenarios such as the Internet of Things (IoT), terminal devices can also be machines or devices for monitoring or measurement, such as including but not limited to: machine-type communication (MTC) terminals, vehicle communication terminals, device-to-device (D2D) terminals, machine-to-machine (M2M) terminals, and so on.

[0051] Furthermore, the terms "network side" or "network equipment side" refer to one side of the network, which can be a base station or include one or more network devices as described above. The terms "user side," "terminal side," or "terminal equipment side" refer to the side of the user or terminal, which can be a UE or include one or more terminal devices as described above. Unless otherwise specified, "equipment" can refer to either network equipment or terminal equipment.

[0052] The following examples illustrate the scenarios of embodiments of this application, but this application is not limited thereto.

[0053] Figure 1 is a schematic diagram of a communication system according to an embodiment of this application, illustrating the case of a terminal device and a network device as examples. As shown in Figure 1, the communication system 100 may include a network device 101 and terminal devices 102 and 103. For simplicity, Figure 1 only illustrates the case of two terminal devices and one network device, but the embodiments of this application are not limited to this.

[0054] In this embodiment of the application, network device 101 and terminal devices 102 and 103 can transmit existing services or services that can be implemented in the future. For example, these services may include, but are not limited to: enhanced mobile broadband (eMBB), massive machine-type communication (mMTC), and ultra-reliable and low-latency communication (URLLC), etc.

[0055] It is worth noting that Figure 1 shows that both terminal devices 102 and 103 are within the coverage area of ​​network device 101, but this application is not limited to this. Both terminal devices 102 and 103 may be outside the coverage area of ​​network device 101, or one terminal device 102 may be within the coverage area of ​​network device 101 while the other terminal device 103 may be outside the coverage area of ​​network device 101.

[0056] In the embodiments of this application, higher-layer signaling may be, for example, Radio Resource Control (RRC) signaling; for example, referred to as an RRC message, including MIB, system information, dedicated RRC messages; or referred to as an RRC information element. Higher-layer signaling may also be, for example, Medium Access Control (MAC) signaling; or referred to as a MAC control element. However, this application is not limited to these.

[0057] Since Rel-15, NR 5G has introduced beam management. The beam management process is based on beam sweeping. For example, the gNB needs to send beams to the UE in sequence, and the UE can select the best one or more beams and provide feedback.

[0058] The gNB can configure reference signals for the UE, such as Channel State Information Reference Signal (CSI-RS) / Synchronization Signal Block (SSB) for beam scanning and beam measurement. To indicate which beam to select for communication, the gNB configures Transmission Configuration Indication (TCI) states and indicates which TCI states are used. For example, the gNB can configure a list of TCI states via RRC, and then select a subset of the configured TCI states (e.g., 8 TCI states) to be active via MAC CE, and indicate the active TCI state to the UE via DCI (e.g., via the TCI indication field in the DCI).

[0059] In Rel-19, AI / ML-based beam management was introduced. AI / ML-based beam management in Rel-19 (BM Case-1 and BM Case-2, with NW-side and / or UE-side models) can reduce overhead.

[0060] Figure 2 is a schematic diagram of AI / ML used for beam management. As shown in Figure 2, one or more reference signals (which may be referred to as RS for measurement or RS for inference) in the second reference signal resource set (set B) can be received and measured by the terminal device. The measurement results can be used as input to AI / ML. One or more reference signals (which may be referred to as RS for prediction) in the first reference signal resource set (set A) can be used by the terminal device as output to AI / ML, for example, the measurement results can be used as labeled data or ground truth data for AI / ML. For details regarding AI / ML and sets A and B, please refer to relevant technologies, which will not be elaborated here.

[0061] As shown in Figure 2, for example, AI / ML-based beam management can predict the information corresponding to set A (a larger number of reference signals) based on the measurement results of set B (a smaller number of reference signals), and can perform beam prediction in the spatial / temporal domains.

[0062] The above provides an illustrative description of beam management, but this application is not limited thereto. Furthermore, the above embodiments can be considered as part of the embodiments of this application, applicable to this application, and can also be implemented in combination with one or more of the following embodiments.

[0063] In the embodiments of this application, one or more AI / ML models can be configured and run in network devices and / or terminal devices. AI / ML models can be used for various signal processing functions in wireless communication, such as CSI prediction, CSI compression, beam prediction, positioning management, etc.; this application is not limited thereto.

[0064] First aspect of the embodiments

[0065] This application provides a beam management method, which is described from the perspective of the terminal device.

[0066] Figure 3 is a schematic diagram of a beam management method according to an embodiment of this application. As shown in Figure 3, the method includes:

[0067] 301. The terminal device receives configuration information for beam management from the network device;

[0068] 302, the terminal device performs spatial beam prediction or temporal beam prediction based on the configuration information, using an AI / ML model / function.

[0069] It is worth noting that Figure 3 above is only an illustrative description of the embodiments of this application, but this application is not limited thereto. For example, the execution order between various operations can be appropriately adjusted, and other operations can be added or some operations can be removed. Those skilled in the art can make appropriate modifications based on the above content, and are not limited to the description in Figure 3 above.

[0070] In some embodiments, a functionality refers to an AI / ML feature / feature group enabled by a configuration, wherein the configuration is supported based on conditions indicated by UE capabilities.

[0071] For example, an AL / ML function can be one or more functions, or one or more logical models, or one or more sub-functions, or one or more features, or one or more feature groups.

[0072] For example, the function could be to use AI / ML for spatial beam prediction, or to use AI / ML for temporal beam prediction, or to use AI / ML for CSI prediction, or to use AI / ML for direct positioning, or to use AI / ML for assisted positioning, and so on.

[0073] In some embodiments, the AI / ML function / model can be used for beam management. One or more reference signals are used for measurement, and the measurement results are input to the AI / ML function / model. Another one or more reference signals are used to input the output of the AI / ML function / model for inference.

[0074] For ease of description, beam management based on AI / ML functionality / model will be referred to as model inference or inference operation, training data collection based on AI / ML functionality / model will be referred to as training data collection (training data collection can also use non-AI / ML methods), and performance monitoring based on AI / ML functionality / model will be referred to as performance monitoring.

[0075] In some embodiments, the configuration information may include configuration information for one or more reference signals, such as CSI-RS configuration information, etc. This application is not limited thereto; further details regarding specific configuration information can be found in related technologies. The configuration information may include configuration information for training data collection, and / or configuration information for model inference, and / or configuration information for performance monitoring.

[0076] Figure 4 is another schematic diagram of the beam management method according to an embodiment of this application, illustrated using a terminal device configured with AI / ML as an example. As shown in Figure 4, the method includes:

[0077] 401. The terminal device receives configuration information from the network device; for example, the configuration information includes a second set of reference signal resources (set B) for measurement and a first set of reference signal resources (set A) for prediction.

[0078] 402, The terminal device receives the reference signal;

[0079] 403. The terminal device performs reference signal measurements and inputs the measurement results into the AI / ML function / model; for example, the measurement results of the reference signal in set B are used as input to AI / ML, and the reference signal in set A is used for prediction (or inference); and

[0080] 404, the terminal device sends the prediction result to the network device.

[0081] For example, the AI / ML function resides on the terminal device side. After enabling or activating the AI / ML function, the terminal device performs measurements based on reference signals from the network side, uses AI / ML to perform beam prediction based on the measurement results, and sends the prediction results to the network device.

[0082] It is worth noting that Figure 4 above is only an illustrative description of the embodiments of this application, but this application is not limited thereto. For example, the execution order between various operations can be appropriately adjusted, and other operations can be added or some operations can be removed. Those skilled in the art can make appropriate modifications based on the above content, and are not limited to the description in Figure 4 above.

[0083] The above illustrations demonstrate AI / ML-based beam management, but this application is not limited thereto.

[0084] In some embodiments, for BM case-2 with a terminal-side model, the terminal device can measure reference signals transmitted over one or more time instances within a measurement / observation window. The terminal-side AI / ML model / function can predict the beam quality of one or more future time instances (i.e., the prediction window).

[0085] Figure 5 is a schematic diagram of the measurement window and prediction window according to an embodiment of this application. As shown in Figure 5, the measurement window may include multiple time instances (T1 to T4), on which CSI-RS can be sent. The terminal device can measure these CSI-RS and input the measurement results into an AI / ML model / function for inference, thereby predicting the beam quality of multiple time instances (T5 to T8) in the prediction window. As shown in Figure 5, the terminal device can report the inference results to the network device.

[0086] However, for BM case-2, in certain situations, such as due to discontinuous transmission (DTX) or discontinuous reception (DRX), the reference signal used for measurement may not be transmitted on one or more time instances within the measurement window. In this case, the input dimension of the AI / ML model will change, thus affecting the performance of inference operations. The following explains these issues.

[0087] In some embodiments, for time beam prediction with a terminal-side model, if at least some reference signals are not received on one or more time instances in the measurement window (or observation window) used for inference, the corresponding model inference and / or inference result report is cancelled; or, the terminal device still performs the corresponding model inference and reports the inference result.

[0088] For example, in BM case-2 with a UE-side model, in the measurement / observation window, if the reference signal (e.g., CSI-RS) on one or more time instances or all time instances is not sent by the gNB, or if a portion of the reference signal (e.g., CSI-RS) on one or more time instances or all time instances is not sent by the gNB, the inference result report is cancelled / dropped.

[0089] Figure 6 is an example of an inference result report being cancelled according to an embodiment of this application. As shown in Figure 6, if the CSI-RS of time instance T3 in the measurement window is not received by the UE (or not sent by the gNB), the inference result report is cancelled or discarded.

[0090] For example, in BM case-2 with a UE-side model, in the measurement / observation window, if the reference signal (e.g., CSI-RS) on one or more time instances or all time instances is not sent by the gNB, or if a portion of the reference signal (e.g., CSI-RS) on one or more time instances or all time instances is not sent by the gNB, then the inference result report is not cancelled / dropped.

[0091] In some embodiments, the measurement results corresponding to at least a portion of the reference signals that were not received are set to a specific value (e.g., zero or null).

[0092] For example, in BM case-2 with a UE-side model, during the measurement / observation window, if a reference signal (e.g., CSI-RS) on one or more time instances or all time instances is not transmitted by the gNB, or if a portion of the reference signals (e.g., CSI-RS) on one or more time instances or all time instances is not transmitted by the gNB, the inference operation is still performed and the inputs of the untransmitted reference signals are set to 0 or null. Furthermore, the terminal device still reports the inference results to the network device.

[0093] In some embodiments, the measurement results corresponding to at least a portion of the unreceived reference signals are set as the most recent measurement results prior to the one or more time instances.

[0094] For example, in BM case-2 with a UE-side model, within the measurement / observation window, if a reference signal (e.g., CSI-RS) on one or more time instances or all time instances is not transmitted by the gNB, or if a portion of the reference signals (e.g., CSI-RS) on one or more time instances or all time instances is not transmitted by the gNB, the inference operation is still performed and the input of the untransmitted reference signal is set to the most recent measurement result. Furthermore, the terminal device still reports the inference result to the network device.

[0095] Figure 7 is an example diagram showing that the inference result is still reported according to an embodiment of this application. As shown in Figure 7, if the CSI-RS of time instance T3 in the measurement window is not received by the UE (or not sent by the gNB), the inference operation is still performed, and the measurement result of time instance T2 can still be used for time instance T3. Furthermore, the terminal device still reports the inference result to the network device.

[0096] In some embodiments, the measurement results corresponding to at least a portion of the unreceived reference signals are determined by the terminal device through interpolation based on the measurement results before and after the one or more time instances.

[0097] For example, in BM case-2 with a UE-side model, during the measurement / observation window, if a reference signal (e.g., CSI-RS) on one or more time instances or all time instances is not transmitted by the gNB, or if a portion of the reference signal (e.g., CSI-RS) on one or more time instances or all time instances is not transmitted by the gNB, the inference operation is still performed and the input of the untransmitted reference signal is determined by the UE. Furthermore, the terminal device still reports the inference results to the network device.

[0098] For example, still using Figure 7 as an example, the UE can process the existing measurement results, such as interpolating the measurement results of time instance T2 before time instance T3 and time instance T4 after time instance T3, and then using the obtained result as the measurement result of time instance T3. This application is not limited to this; for example, other related information can also be used, and / or, operations such as averaging and weighted summation can be used.

[0099] In some embodiments, for time beam prediction with an end-side model, if at least a portion of the reference signal is not received on one or more time instances in the measurement window (or observation window), and the number of said time instances exceeds a threshold, the corresponding model inference and / or inference result report is cancelled.

[0100] For example, if the number of time instances that have not transmitted a reference signal exceeds a certain threshold, which is configurable or predefined, the inference operation is canceled / abandoned, and the inference result report is canceled / discarded. Otherwise, the inference operation is still performed, and the inference result is still reported.

[0101] In some embodiments, if at least a portion of the reference signal is not received at a specific time instance (e.g., the first or last time instance) in the measurement window (or observation window), the corresponding model inference and / or inference result report is cancelled.

[0102] For example, if the reference signal is not transmitted at certain specific time instances within the measurement / observation window, such as the first or last time instance, the inference operation is canceled / abandoned, and the inference result report is canceled / discarded. Otherwise, the inference operation is still performed, and the inference result is still reported.

[0103] In some embodiments, a configured reference signal (e.g., a configured CSI-RS resource(s) or a part of a configured CSI-RS resource(s)) is not transmitted on one or more or all time instances within the measurement window, possibly for one of the following reasons:

[0104] - Cell Discontinuous Transmission (Cell DTX);

[0105] -Discontinuous reception by the terminal (UE DRX);

[0106] -CSI-RS may conflict with other reference signals or channels;

[0107] -DCI indication, such as DCI format 2_6 for energy saving.

[0108] The above are just some examples of factors that may cause the reference signal to not be transmitted, but this application is not limited to these.

[0109] In some embodiments, for time beam prediction with a terminal-side model, the terminal device expects the configured reference signal to be transmitted on one or more time instances or all time instances in the measurement window, or the network device guarantees that the configured reference signal is transmitted on one or more time instances or all time instances in the measurement window.

[0110] In some embodiments, for time beam prediction with a terminal-side model, if the received beam (Rx Beam) on one or more time instances in the measurement window (or observation window) changes in relation to the reference signal, the corresponding model inference and / or inference result report is cancelled; or, the terminal device still performs the corresponding model inference and reports the inference result.

[0111] For example, in BM case-2 with a UE-side model, if the UE Rx beam changes against a reference signal (e.g., CSI-RS) in one or more time instances during the measurement / observation window, the inference result report is canceled / discarded.

[0112] For example, in BM case-2 with a UE-side model, if the UE Rx beam changes relative to a reference signal (e.g., CSI-RS) in one or more time instances within the measurement / observation window, the UE still reports the inference result.

[0113] For example, the reason for the UE Rx beam change in CSI-RS may be due to multiplexing with other RSs or messages. These other RSs or messages may include, for example, the SS / PBCH block, CORESET, and SIB1. This application is not limited to this; for example, other signals or channels that may cause the prediction results to be inaccurate may also be involved.

[0114] In some embodiments, for time beam prediction with a terminal-side model, if at least a portion of the configured reference signal resources on a time instance in a measurement window (or observation window) are multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all configured reference signal resources for that time instance are applied with the same receive beam (quasi-co-addressed with QCL-Type D) as the specific signal or channel.

[0115] For example, for BM Case-2 with a UE-side model, in the measurement / observation window, in a time instance, if multiple configured CSI-RS resources or a portion of configured CSI-RS resources or one configured CSI-RS resource is multiplexed with other RS ​​or messages (e.g., SS / PBCH block, CORESET, SIB1), then all configured CSI-RS resources in that time instance, as well as the SS / PCCH block, CORESET, or SIB1, are quasi-co-located with QCL-Type D, i.e., the same UE Rx beam is applied.

[0116] Figure 8 is an example diagram of the QCL relationship in an embodiment of this application. As shown in Figure 8, for example, in time instance T3, if the configured CSI-RS resource(s) is multiplexed with the SSB, then the configured CSI-RS resource and the SSB on time instance T3 are QCLed with Type D.

[0117] In some embodiments, for time beam prediction with a terminal-side model, if at least a portion of the configured reference signal resources on a time instance in a measurement window (or observation window) are multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all configured reference signal resources in all time instances of the measurement window (or observation window) are applied with the same receive beam (quasi-co-addressed with QCL-Type D) as the specific signal or channel.

[0118] For example, for BM Case-2 with a UE-side model, in the measurement / observation window, in a time instance, if multiple configured CSI-RS resources or a portion of configured CSI-RS resources or one configured CSI-RS resource is multiplexed with other RS ​​or messages (e.g., SS / PBCH block, CORESET, SIB1), then all configured CSI-RS resources in all time instances of that measurement / observation window, as well as that SS / PCCH block or CORESET or SIB1, are quasi-co-located with QCL-Type D, i.e., the same UE Rx beam is applied.

[0119] Taking Figure 8 as an example, for instance, if CSI-RS resources are configured to be multiplexed with SSB in time instance T3, then all time instances (T1 to T4) in this measurement window are configured with CSI-RS resources and SSB having quasi-co-addressability with QCL-type D.

[0120] In some embodiments, for time beam prediction with a terminal-side model, the terminal device expects that the configured reference signal (e.g., CSI-RS) is not multiplexed with other RSs or messages within the measurement / observation window. These other RSs or messages include, for example, the SS / PBCH block, CORESET, and SIB1. Alternatively, the network device guarantees that the configured reference signal (e.g., CSI-RS) is not multiplexed with other RSs or messages within the measurement / observation window. These other RSs or messages also include, for example, the SS / PBCH block, CORESET, and SIB1.

[0121] The above has explained BM case-2 of model inference. The following will explain BM case-1 of model inference.

[0122] In some embodiments, for spatial beam prediction with a terminal-side model, if at least some of the reference signals used for inference are not received, the corresponding model inference and / or inference result report is cancelled; or, the terminal device still performs the corresponding model inference and reports the inference result.

[0123] For example, in BM Case-1 with a UE-side model, if the gNB does not send the configured reference signal for inference or does not send a portion of the configured reference signal for inference, such as CSI-RS, the UE cancels / discards the inference result report.

[0124] For example, in BM Case-1 with a UE-side model, if the gNB does not send the configured reference signal for inference or does not send a portion of the configured reference signal for inference, such as CSI-RS, the UE still reports the inference result.

[0125] In some embodiments, the configured reference signal (e.g., a configured CSI-RS resource or a portion thereof) may not be transmitted for one of the following reasons:

[0126] - Cell Discontinuous Transmission (Cell DTX);

[0127] -Discontinuous reception by the terminal (UE DRX);

[0128] -CSI-RS may conflict with other reference signals or channels;

[0129] -DCI indication, such as DCI format 2_6 for energy saving.

[0130] The above are just some examples of factors that may cause the reference signal to not be transmitted, but this application is not limited to these.

[0131] In some embodiments, for spatial beam prediction with a terminal-side model, the terminal device expects a configured reference signal for inference to be transmitted, or the network device guarantees that a configured reference signal for inference is transmitted.

[0132] In some embodiments, for spatial beam prediction with a terminal-side model, if the received beam changes relative to the reference signal, the corresponding model inference and / or inference result report is cancelled; or, the terminal device still performs the corresponding model inference and reports the inference result.

[0133] For example, in BM case-1 with a UE-side model, if the UE Rx beam changes in relation to the reference signal used for inference (e.g., CSI-RS), the inference result report is canceled / discarded.

[0134] For example, in BM case-1 with a UE-side model, if the UE Rx beam changes in relation to the reference signal (e.g., CSI-RS) used for inference, the UE will still report the inference result.

[0135] For example, the reason for the UE Rx beam change in CSI-RS may be due to multiplexing with other RSs or messages. These other RSs or messages may include, for example, the SS / PBCH block, CORESET, and SIB1. This application is not limited to this; for example, other signals or channels that may cause the prediction results to be inaccurate may also be involved.

[0136] In some embodiments, for spatial beam prediction with a terminal-side model, if at least a portion of the configured reference signal resources used for inference are multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all configured reference signal resources used for inference are applied with the same receive beam (quasi-co-addressable with QCL-Type D) as the specific signal or channel.

[0137] For example, in BM Case-1 with a UE-side model, if multiple configured CSI-RS resources used for inference, or a portion of configured CSI-RS resources used for inference, or one configured CSI-RS resource used for inference, are multiplexed with other RSs or messages (e.g., SS / PBCH block, CORESET, SIB1), then all configured CSI-RS resources used for inference and the SS / PCCH block, CORESET, or SIB1 are quasi-co-located with QCL-Type D, i.e., they use the same UE Rx beam.

[0138] In some embodiments, for spatial beam prediction with a terminal-side model, for periodic or semi-persistent reference signals, if at least some of the reference signal resources on a time instance are configured to be multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all the configured reference signal resources of the time instance and the specific signal or channel are applied with the same receive beam (quasi-co-addressed with QCL-Type D).

[0139] For example, for BM Case-1 with a UE-side model, for periodic / semi-persistent CSI-RS, for a time instance, if multiple configured CSI-RS resources used for inference, or a portion of configured CSI-RS resources used for inference, or one configured CSI-RS resource used for inference is multiplexed with other RSs or messages (e.g., SS / PBCH block, CORESET, SIB1), then all configured CSI-RS resources used for inference, as well as the SS / PCCH block, CORESET, or SIB1, are quasi-co-located with QCL-Type D, i.e., they apply the same UE Rx beam.

[0140] In some embodiments, for spatial beam prediction with a terminal-side model, the terminal device expects that the reference signal (e.g., CSI-RS) configured for inference is not multiplexed with other RSs or messages. These other RSs or messages include, for example, the SS / PBCH block, CORESET, and SIB1. Alternatively, the network device guarantees that the reference signal (e.g., CSI-RS) configured for inference is not multiplexed with other RSs or messages. These other RSs or messages include, for example, the SS / PBCH block, CORESET, and SIB1.

[0141] The above provides an illustrative explanation of model inference; the following section will explain performance monitoring.

[0142] In some embodiments, for time beam prediction with a terminal-side model, if at least some reference signals are not received on one or more time instances used for or associated with performance monitoring, the corresponding performance monitoring and / or monitoring result report is cancelled; or, the terminal device still performs the corresponding performance monitoring and reports the monitoring results.

[0143] In some embodiments, for time beam prediction with an end-side model, if at least a portion of the reference signal is not received on one or more time instances in the prediction window used for performance monitoring, then the one or more time instances are not used for performance metric calculation and / or the corresponding performance metrics are not reported.

[0144] For example, for UE-assisted performance monitoring in BM Case-2 using the UE-side model, if reference signals (e.g., CSI-RS) used for monitoring are not transmitted in one, multiple, or all time instances within the prediction window, or if a portion of the reference signals used for monitoring are not transmitted in one, multiple, or all time instances, then these time instances are not used for performance metric calculation. Furthermore, these performance metrics may also not be reported.

[0145] In some embodiments, for time beam prediction with an end-side model, if at least some reference signals are not received on one or more time instances in the prediction window used for performance monitoring, then all time instances of the prediction window are not used for performance metric calculation and / or the corresponding performance metrics are not reported.

[0146] For example, for UE-assisted performance monitoring in BM Case-2 using the UE-side model, if, within a prediction window, the reference signal (e.g., CSI-RS) used for monitoring is not transmitted in one, multiple, or all time instances, or if a portion of the reference signal used for monitoring is not transmitted in one, multiple, or all time instances, then all time instances in that prediction window will not be used for performance metric calculation. Furthermore, these performance metrics may also not be reported.

[0147] In some embodiments, for time-beam prediction with an end-side model, if at least a portion of the reference signal is not received on one or more time instances in the prediction window used for performance monitoring, the performance metric calculation is restarted.

[0148] For example, within a prediction window, if a reference signal (e.g., CSI-RS) used for monitoring on one, multiple, or all time instances is not transmitted, or if a portion of the reference signal used for monitoring on one, multiple, or all time instances is not transmitted, the performance metric calculation restarts. For example, if a timer and / or counter are configured for performance monitoring, the timer and / or counter are restarted. Furthermore, these performance metrics may not be reported.

[0149] In some embodiments, the configured reference signal (e.g., a configured CSI-RS resource or a portion thereof) is not transmitted on one or more time instances within the prediction window, possibly for at least one of the following reasons:

[0150] - Cell Discontinuous Transmission (Cell DTX);

[0151] -Discontinuous reception by the terminal (UE DRX);

[0152] -CSI-RS may conflict with other reference signals or channels;

[0153] -DCI indication, such as DCI format 2_6 for energy saving.

[0154] The above are just some examples of factors that may cause the reference signal to not be transmitted, but this application is not limited to these.

[0155] In some embodiments, for time beam prediction with a terminal-side model, the terminal device expects the reference signal configured for performance monitoring to be transmitted on one or more time instances or all time instances in the prediction window; or, the network device guarantees that the reference signal configured for performance monitoring is transmitted on one or more time instances or all time instances in the prediction window.

[0156] In some embodiments, for time beam prediction with an end-side model, if at least a portion of the reference signal is not received on one or more time instances in the measurement window (or observation window) associated with performance monitoring, then the one or more time instances are not used for performance metric calculations and / or the corresponding performance metrics are not reported.

[0157] For example, for UE-assisted performance monitoring in BM Case-2 using the UE-side model, if reference signals (e.g., CSI-RS) are not transmitted in one or more time instances or all time instances within the measurement / observation window, or if a portion of the reference signals are not transmitted in one or more time instances or all time instances, these time instances will not be used for performance metric calculation if the measurement / observation window is associated with performance monitoring. Furthermore, these performance metrics may also not be reported.

[0158] In some embodiments, for time beam prediction with an end-side model, if at least a portion of the reference signal is not received on one or more time instances in a measurement window (or observation window) associated with performance monitoring, then all time instances of the measurement window (or observation window) are not used for performance metric calculation and / or the corresponding performance metrics are not reported.

[0159] For example, for UE-assisted performance monitoring in BM Case-2 using the UE-side model, within a measurement / observation window, if reference signals (e.g., CSI-RS) are not transmitted in one or more time instances or all time instances, or if a portion of the reference signals are not transmitted in one or more time instances or all time instances, then all time instances of that measurement / observation window will not be used for performance metric calculation if the measurement / observation window is associated with performance monitoring. Furthermore, these performance metrics may also not be reported.

[0160] In some embodiments, for time-beam prediction with an end-side model, the performance metric calculation is restarted if at least a portion of the reference signal is not received on one or more time instances in the measurement window (or observation window) associated with performance monitoring.

[0161] For example, within a measurement / observation window, if a reference signal (e.g., CSI-RS) is not transmitted on one or more time instances or all time instances, or if a portion of the reference signal is not transmitted on one or more time instances or all time instances, the performance metric calculation restarts if the measurement / observation window is associated with performance monitoring. For example, if a timer and / or counter are configured for performance monitoring, the timer and / or counter are restarted. Furthermore, these performance metrics may not be reported.

[0162] In some embodiments, the configured reference signal (e.g., configured CSI-RS resource or a portion thereof) is not transmitted on one or more time instances within the measurement / observation window, possibly for at least one of the following reasons:

[0163] - Cell Discontinuous Transmission (Cell DTX);

[0164] -Discontinuous reception by the terminal (UE DRX);

[0165] -CSI-RS may conflict with other reference signals or channels;

[0166] -DCI indication, such as DCI format 2_6 for energy saving.

[0167] The above are just some examples of factors that may cause the reference signal to not be transmitted, but this application is not limited to these.

[0168] In some embodiments, for time beam prediction with a terminal-side model, the terminal device expects the configured reference signal to be transmitted on one or more time instances or all time instances in the measurement window (or observation window) associated with performance monitoring, or the network device guarantees that the configured reference signal is transmitted on one or more time instances or all time instances in the measurement window (or observation window) associated with performance monitoring.

[0169] In some embodiments, for time beam prediction with a terminal-side model, if at least a portion of the configured reference signal resources on a time instance in the prediction window for performance monitoring and / or the measurement window (or observation window) associated with performance monitoring are multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all configured reference signal resources for that time instance apply the same receive beam (quasi-co-addressable with QCL-Type D) to the specific signal or channel.

[0170] For example, when using a UE-side model to perform UE-assisted performance monitoring for BM Case-2, within a time instance in the prediction window and / or associated measurement / observation window, if multiple configured CSI-RS resources or a portion of configured CSI-RS resources or one configured CSI-RS resource is multiplexed with other RS ​​or messages (e.g., SS / PBCH block, CORESET, SIB1), then all configured CSI-RS resources in that time instance, as well as the SS / PCCH block, CORESET, or SIB1, have quasi-co-addressable QCL-Type D, i.e., the same UE Rx beam is applied.

[0171] In some embodiments, for time beam prediction with a terminal-side model, if at least a portion of the configured reference signal resources on a time instance in the prediction window and / or the measurement window (or observation window) associated with performance monitoring are multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all configured reference signal resources for all time instances in the prediction window and / or the measurement window (or observation window) apply the same receive beam (quasi-co-addressable with QCL-Type D) to the specific signal or channel.

[0172] For example, when using a UE-side model to perform UE-assisted performance monitoring for BM Case-2, within a prediction window and / or associated measurement / observation window, if multiple configured CSI-RS resources or a portion of configured CSI-RS resources or one configured CSI-RS resource are multiplexed with other RSs or messages (e.g., SS / PBCH block, CORESET, SIB1) within a time instance, then all configured CSI-RS resources in all time instances of that prediction window and / or associated measurement / observation window, as well as that SS / PCCH block or CORESET or SIB1, have quasi-co-addressable QCL-Type D, i.e., the same UE Rx beam is applied.

[0173] In some embodiments, for spatial beam prediction with a terminal-side model, on one or more time instances within the prediction window and / or the measurement window (or observation window) associated with performance monitoring, the terminal device expects the configured reference signal (e.g., CSI-RS) not to be multiplexed with other RSs or messages. These other RSs or messages include, for example, the SS / PBCH block, CORESET, and SIB1. Alternatively, on one or more time instances within the prediction window and / or the measurement window (or observation window) associated with performance monitoring, the network device guarantees that the configured reference signal (e.g., CSI-RS) is not multiplexed with other RSs or messages. These other RSs or messages include, for example, the SS / PBCH block, CORESET, and SIB1.

[0174] The above explains BM case-2 for performance monitoring. The following explains BM case-1 for performance monitoring.

[0175] In some embodiments, for spatial beam prediction with a terminal-side model, if at least some of the reference signals used for or associated with performance monitoring are not received, the corresponding performance monitoring and / or monitoring result report is cancelled; or, the terminal device still performs the corresponding performance monitoring and reports the monitoring results.

[0176] In some embodiments, for spatial beam prediction with a terminal-side model, if at least some of the reference signals used for and / or associated with performance monitoring are not received, the corresponding monitoring results are not used for performance metric calculations and / or the corresponding performance metrics are not reported.

[0177] For example, for UE-assisted performance monitoring in BM Case-1 using the UE-side model, if the gNB does not send the configured reference signal used for monitoring or does not send a portion of the configured reference signal used for monitoring, such as CSI-RS, then the corresponding performance metric calculation may not be performed. Furthermore, the corresponding performance metric may not be reported to the gNB.

[0178] For example, in UE-assisted performance monitoring using the UE-side model in BM Case-1, if the gNB does not send the configured reference signal associated with performance monitoring for inference, or does not send a portion of the configured reference signal associated with performance monitoring for inference, such as CSI-RS, then the corresponding performance metric calculation may not be performed. Furthermore, the corresponding performance metric may not be reported to the gNB.

[0179] In some embodiments, for spatial beam prediction with an end-side model, performance metric calculation is restarted if at least some of the reference signals used for and / or associated with performance monitoring are not received.

[0180] For example, if the gNB fails to send the configured reference signal for monitoring or a portion of the configured reference signal for monitoring, such as CSI-RS, and / or if the gNB fails to send the configured reference signal for inference associated with performance monitoring or a portion of the configured reference signal for inference associated with performance monitoring, such as CSI-RS, then performance metric calculation restarts. For example, if performance monitoring is configured with a timer and / or counter, then the timer and / or counter is restarted. Furthermore, the corresponding performance metric may not be reported to the gNB.

[0181] In some embodiments, the configured reference signal used for monitoring or a portion of the configured reference signal used for monitoring (e.g., CSI-RS) is not transmitted, and / or the configured reference signal used for inference associated with performance monitoring or a portion of the configured reference signal (e.g., CSI-RS) is not transmitted, possibly for at least one of the following reasons:

[0182] - Cell Discontinuous Transmission (Cell DTX);

[0183] -Discontinuous reception by the terminal (UE DRX);

[0184] -CSI-RS may conflict with other reference signals or channels;

[0185] -DCI indication, such as DCI format 2_6 for energy saving.

[0186] The above are just some examples of factors that may cause the reference signal to not be transmitted, but this application is not limited to these.

[0187] In some embodiments, for spatial beam prediction with a terminal-side model, the terminal device expects all reference signals configured for or associated with performance monitoring to be transmitted, or the network device guarantees that all reference signals configured for or associated with performance monitoring are transmitted.

[0188] In some embodiments, for spatial beam prediction with a terminal-side model, if at least a portion of the configured reference signal resources used for performance monitoring and / or associated with performance monitoring are multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all the configured reference signal resources used for performance monitoring and / or associated with performance monitoring are applied to the same receive beam (quasi-co-addressed with QCL-Type D) as the specific signal or channel.

[0189] For example, for UE auxiliary performance monitoring in BM Case-1 with a UE-side model, if the configured CSI-RS resources used for monitoring or a portion of the configured CSI-RS resources, and / or the configured CSI-RS resources used for inference associated with monitoring or a portion of the configured CSI-RS resources, are multiplexed with other RS ​​or messages (e.g., SS / PBCH block, CORESET, SIB1), then all the configured CSI-RS resources used for monitoring and / or all the configured CSI-RS resources used for inference associated with monitoring, as well as the SS / PBCH block or CORESET or SIB1, have QCL-Type D quasi-co-address, i.e., they apply the same UE Rx beam.

[0190] In some embodiments, for spatial beam prediction with a terminal-side model, the terminal device expects that the reference signals configured for and / or associated with performance monitoring (e.g., CSI-RS) are not multiplexed with other RSs or messages. These other RSs or messages include, for example, the SS / PBCH block, CORESET, and SIB1. Alternatively, the network device guarantees that the reference signals configured for and / or associated with performance monitoring (e.g., CSI-RS) are not multiplexed with other RSs or messages. These other RSs or messages include, for example, the SS / PBCH block, CORESET, and SIB1.

[0191] The above provides an illustrative explanation of performance monitoring; the following section will explain the collection of training data.

[0192] In some embodiments, for temporal beam prediction with terminal-side and / or network-side models, or for spatial beam prediction with terminal-side and / or network-side models, if at least a portion of the reference signals used for data collection are not received, the corresponding data sample or dataset is dropped or marked.

[0193] For example, regarding the collection of training data for BM Case-2 using the UE-side model, if the configured reference signal or a portion thereof is not transmitted, the corresponding data sample is discarded, or the corresponding data sample is marked with a specific indicator, such as null, or the corresponding data set is deleted.

[0194] For example, regarding the collection of training data for BM Case-1 using the UE-side model, if the configured reference signal or a portion thereof is not transmitted, the corresponding data sample is discarded, or the corresponding data sample is marked with a specific indicator, such as null, or the corresponding data set is deleted.

[0195] For example, regarding the training data collection for BM Case-2 using a network-side model, if the configured reference signal or a portion thereof is not transmitted, the corresponding data sample is discarded, or the corresponding data sample is marked with a specific indicator, such as null, or the corresponding dataset is deleted.

[0196] For example, regarding the training data collection for BM Case-1 using a network-side model, if the configured reference signal or a portion thereof is not transmitted, the corresponding data sample is discarded, or the corresponding data sample is marked with a specific indicator, such as null, or the corresponding dataset is deleted.

[0197] In some embodiments, the configured reference signal or a portion of the configured reference signal used for training data collection is not transmitted, possibly for at least one of the following reasons:

[0198] - Cell Discontinuous Transmission (Cell DTX);

[0199] -Discontinuous reception by the terminal (UE DRX);

[0200] -CSI-RS may conflict with other reference signals or channels;

[0201] -DCI indication, such as DCI format 2_6 for energy saving.

[0202] The above are just some examples of factors that may cause the reference signal to not be transmitted, but this application is not limited to these.

[0203] In some embodiments, for temporal beam prediction with a terminal-side model and / or a network-side model, or for spatial beam prediction with a terminal-side model and / or a network-side model, the terminal device expects all configured reference signals for data collection to be transmitted, or the network device guarantees that all configured reference signals for data collection are transmitted.

[0204] The embodiments of this application can be applied to both the UE-side model and the gNB-side model, but this application is not limited thereto. Furthermore, the AI / ML in the embodiments of this application can be used for beam management, such as temporal beam prediction and / or spatial beam prediction, but this application is not limited thereto; for example, non-AI / ML methods can also be used for data collection.

[0205] The above embodiments are merely illustrative examples of embodiments of this application, but this application is not limited thereto, and appropriate modifications can be made based on the above embodiments. For example, the above embodiments can be used alone, or one or more of the above embodiments can be combined.

[0206] As can be seen from the above embodiments, the terminal device receives configuration information from the network device; based on AI / ML functions / models, it performs spatial beam prediction and / or temporal beam prediction according to the configuration information. This improves the accuracy of beam management and enhances the performance and efficiency of AI / ML.

[0207] Second aspect of the embodiments

[0208] This application provides a beam management method, described from the perspective of a network device. Embodiments of the second aspect can be combined with embodiments of the first aspect, and details identical to those in the first aspect will not be repeated.

[0209] Figure 9 is a schematic diagram of a beam management method according to an embodiment of this application. As shown in Figure 9, the method includes:

[0210] 901. The network device sends configuration information for beam management to the terminal device.

[0211] As shown in Figure 9, the method may further include:

[0212] 902, the terminal device performs spatial beam prediction or temporal beam prediction based on the configuration information, using an AI / ML model / function.

[0213] It is worth noting that Figure 9 above is only an illustrative description of the embodiments of this application, but this application is not limited thereto. For example, the execution order between various operations can be appropriately adjusted, and other operations can be added or some operations can be removed. Those skilled in the art can make appropriate modifications based on the above content, and are not limited to the description in Figure 9 above.

[0214] In some embodiments, for time beam prediction with a terminal-side model,

[0215] If at least some reference signals are not received on one or more time instances in the measurement window (or observation window) used for inference, the corresponding model inference and / or inference result reporting is cancelled; or, the terminal device still performs the corresponding model inference and reports the inference results.

[0216] In some embodiments, the measurement results corresponding to the unreceived at least portion of the reference signals are set to a specific value (zero or null).

[0217] Alternatively, the measurement results corresponding to the unreceived at least portion of the reference signals are set as the most recent measurement results prior to the one or more time instances.

[0218] Alternatively, the measurement results corresponding to the unreceived at least part of the reference signals may be determined by the terminal device through interpolation based on the measurement results before and after the one or more time instances.

[0219] In some embodiments, for time beam prediction with a terminal-side model,

[0220] If at least some reference signals are not received on one or more time instances in the measurement window (or observation window), and the number of time instances exceeds a threshold, the corresponding model inference and / or inference result reporting is cancelled.

[0221] or,

[0222] If at least some of the reference signals are not received at a specific time instance (e.g., the first or last time instance) in the measurement window (or observation window), the corresponding model inference and / or inference result reporting is cancelled.

[0223] In some embodiments, for time beam prediction with a terminal-side model,

[0224] If the received beam (Rx Beam) on one or more time instances in the measurement window (or observation window) changes in relation to the reference signal, the corresponding model inference and / or inference result reporting is cancelled; otherwise, the terminal device still performs the corresponding model inference and reports the inference result.

[0225] In some embodiments, for time beam prediction with a terminal-side model,

[0226] If at least a portion of the reference signal resources configured on a time instance within the measurement window (or observation window) are multiplexed with a specific signal or channel (SSB, CORESET, SIB1),

[0227] Then, for all configured reference signal resources of the time instance, the same receiving beam (quasi-co-addressable with QCL-Type D) is applied to the specific signal or channel; or, for all configured reference signal resources of all time instances in the measurement window (or observation window), the same receiving beam (quasi-co-addressable with QCL-Type D) is applied to the specific signal or channel.

[0228] In some embodiments, for spatial beam prediction with a terminal-side model,

[0229] If at least some of the reference signals used for inference are not received, the corresponding model inference and / or inference result reporting is cancelled; or, the terminal device still performs the corresponding model inference and reports the inference result.

[0230] In some embodiments, for spatial beam prediction with a terminal-side model,

[0231] If the received beam changes in relation to the reference signal, the corresponding model inference and / or inference result reporting is cancelled; alternatively, the terminal device may still perform the corresponding model inference and report the inference results.

[0232] In some embodiments, for spatial beam prediction with a terminal-side model,

[0233] If at least a portion of the configured reference signal resources used for inference are multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all configured reference signal resources used for inference are applied with the same receive beam (quasi-co-addressed with QCL-Type D) as the specific signal or channel.

[0234] In some embodiments, for spatial beam prediction with a terminal-side model,

[0235] For periodic or semi-persistent reference signals, if at least some of the reference signal resources on a time instance are configured to be multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all the configured reference signal resources of the time instance and the specific signal or channel are applied with the same receive beam (quasi-co-addressed with QCL-Type D).

[0236] In some embodiments, for time beam prediction with a terminal-side model,

[0237] If at least some reference signals are not received on one or more time instances used for or associated with performance monitoring, the corresponding performance monitoring and / or monitoring result reporting is cancelled; otherwise, the terminal device still performs the corresponding performance monitoring and reports the monitoring results.

[0238] In some embodiments, for time beam prediction with a terminal-side model,

[0239] If at least some reference signals are not received on one or more time instances in the prediction window used for performance monitoring, then the one or more time instances are not used for performance metric calculation and / or the corresponding performance metrics are not reported; or, all time instances in the prediction window are not used for performance metric calculation and / or the corresponding performance metrics are not reported.

[0240] And / or,

[0241] If at least some reference signals are not received on one or more time instances in the prediction window used for performance monitoring, the performance metric calculation is restarted.

[0242] In some embodiments, for time beam prediction with a terminal-side model,

[0243] If at least some reference signals are not received on one or more time instances in the measurement window (or observation window) associated with performance monitoring, then the one or more time instances are not used for performance metric calculation and / or the corresponding performance metrics are not reported; or, all time instances in the measurement window (or observation window) are not used for performance metric calculation and / or the corresponding performance metrics are not reported.

[0244] And / or,

[0245] If at least some reference signals are not received on one or more time instances in the measurement window (or observation window) associated with performance monitoring, the performance metric calculation is restarted.

[0246] In some embodiments, for time beam prediction with a terminal-side model,

[0247] If at least a portion of the reference signal resources configured on a time instance of the prediction window and / or the measurement window (or observation window) associated with performance monitoring are multiplexed with a specific signal or channel (SSB, CORESET, SIB1),

[0248] Then, for all configured reference signal resources of the time instance, the same receive beam (quasi-co-addressable with QCL-Type D) is applied to the specific signal or channel; or, for all configured reference signal resources of all time instances in the prediction window and / or the measurement window (or observation window), the same receive beam (quasi-co-addressable with QCL-Type D) is applied to the specific signal or channel.

[0249] In some embodiments, for spatial beam prediction with a terminal-side model,

[0250] If at least some of the reference signals used for or associated with performance monitoring are not received, the corresponding performance monitoring and / or monitoring result reporting is cancelled; or, the terminal device still performs the corresponding performance monitoring and reports the monitoring results.

[0251] In some embodiments, for spatial beam prediction with a terminal-side model,

[0252] If at least some of the reference signals used for and / or associated with performance monitoring are not received, the corresponding monitoring results are not used for performance metric calculations and / or the corresponding performance metrics are not reported, and / or the performance metric calculations are restarted.

[0253] In some embodiments, for spatial beam prediction with a terminal-side model,

[0254] If at least a portion of the configured reference signal resources used for and / or associated with performance monitoring are multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all the configured reference signal resources used for and / or associated with performance monitoring apply the same receive beam (quasi-co-addressable with QCL-Type D) to the specific signal or channel.

[0255] In some embodiments, for temporal beam prediction with terminal-side model and / or network-side model, or for spatial beam prediction with terminal-side model and / or network-side model,

[0256] If at least some of the reference signals used for data collection are not received, the corresponding data sample or data set is dropped or marked.

[0257] In some embodiments, the network device may receive feedback information and / or report information sent by the terminal device. For example, the terminal device may report inference results and / or performance monitoring results and / or training data collection results to the network device, but this application is not limited thereto.

[0258] The above embodiments are merely illustrative examples of embodiments of this application, but this application is not limited thereto, and appropriate modifications can be made based on the above embodiments. For example, the above embodiments can be used alone, or one or more of the above embodiments can be combined.

[0259] As can be seen from the above embodiments, the terminal device receives configuration information from the network device; based on AI / ML functions / models, it performs spatial beam prediction and / or temporal beam prediction according to the configuration information. This improves the accuracy of beam management and enhances the performance and efficiency of AI / ML.

[0260] Third aspect of the embodiments

[0261] This application provides a beam management device. This device may be, for example, a terminal device, or one or more components or parts configured within a terminal device; details identical to those in the first and second aspects will not be repeated.

[0262] Figure 10 is a schematic diagram of a beam management device according to an embodiment of this application. As shown in Figure 10, the beam management device 1000 according to an embodiment of this application includes:

[0263] Receiver 1001 receives configuration information for beam management from network devices;

[0264] The processor 1002 performs spatial beam prediction or temporal beam prediction based on the configuration information, using an AI / ML model / function.

[0265] In some embodiments, as shown in FIG10, the beam management device 1000 may further include a transmitter 1003, which sends report information / feedback information to network devices, but this application is not limited thereto.

[0266] In some embodiments, for time beam prediction with an end-side model, if at least some reference signals are not received on one or more time instances in the measurement window (or observation window) used for inference, the corresponding model inference and / or inference result reporting is cancelled.

[0267] In some embodiments, for time beam prediction with a terminal-side model, if at least some reference signals are not received on one or more time instances in the measurement window (or observation window) used for inference, the terminal device still performs the corresponding model inference and reports the inference results.

[0268] In some embodiments, the measurement results corresponding to the unreceived at least part of the reference signal are set to a specific value (zero or null).

[0269] In some embodiments, the measurement results corresponding to the at least partial reference signals that were not received are set as the most recent measurement results prior to the one or more time instances.

[0270] In some embodiments, the measurement results corresponding to the unreceived at least part of the reference signals are determined by the terminal device by interpolation based on the measurement results before and after the one or more time instances.

[0271] In some embodiments, for time beam prediction with an end-side model, if at least some reference signals are not received on one or more time instances in the measurement window (or observation window), and the number of time instances exceeds a threshold, the corresponding model inference and / or inference result reporting is cancelled.

[0272] In some embodiments, for time beam prediction with a terminal-side model, if at least some reference signals are not received at a specific time instance (e.g., the first or last time instance) in the measurement window (or observation window), the corresponding model inference and / or inference result reporting is cancelled.

[0273] In some embodiments, for time beam prediction with a terminal-side model, if the received beam (Rx Beam) on one or more time instances in the measurement window (or observation window) changes in relation to the reference signal, the corresponding model inference and / or inference result reporting is cancelled.

[0274] In some embodiments, for time beam prediction with a terminal-side model, if the received beam (Rx Beam) on one or more time instances in the measurement window (or observation window) changes relative to the reference signal, the terminal device still performs the corresponding model inference and reports the inference results.

[0275] In some embodiments, for time beam prediction with a terminal-side model, if at least a portion of the configured reference signal resources on a time instance in the measurement window (or observation window) are multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all configured reference signal resources for that time instance are applied with the same receive beam (quasi-co-addressed with QCL-Type D) as the specific signal or channel.

[0276] In some embodiments, for time beam prediction with a terminal-side model, if at least a portion of the configured reference signal resources on a time instance in the measurement window (or observation window) are multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all configured reference signal resources in all time instances of the measurement window (or observation window) are applied with the same receive beam (quasi-co-addressable with QCL-Type D) as the specific signal or channel.

[0277] In some embodiments, for spatial beam prediction with a terminal-side model, if at least some of the reference signals used for inference are not received, the corresponding model inference and / or inference result reporting is cancelled.

[0278] In some embodiments, for spatial beam prediction with a terminal-side model, if at least some of the reference signals used for inference are not received, the terminal device still performs the corresponding model inference and reports the inference results.

[0279] In some embodiments, for spatial beam prediction with a terminal-side model, if the received beam changes relative to the reference signal, the corresponding model inference and / or inference result reporting is cancelled.

[0280] In some embodiments, for spatial beam prediction with a terminal-side model, if the received beam changes relative to the reference signal, the terminal device still performs the corresponding model inference and reports the inference results.

[0281] In some embodiments, for spatial beam prediction with a terminal-side model, if at least a portion of the configured reference signal resources used for inference are multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all configured reference signal resources used for inference are applied with the same receive beam (quasi-co-addressable with QCL-Type D) as the specific signal or channel.

[0282] In some embodiments, for spatial beam prediction with a terminal-side model, for periodic or semi-persistent reference signals, if at least some of the reference signal resources on a time instance are configured to be multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all the configured reference signal resources of the time instance and the specific signal or channel are applied with the same receive beam (quasi-co-addressed with QCL-Type D).

[0283] In some embodiments, for time beam prediction with an end-side model, if at least some reference signals are not received on one or more time instances used for or associated with performance monitoring, the corresponding performance monitoring and / or monitoring result reporting is cancelled.

[0284] In some embodiments, for time beam prediction with a terminal-side model, if at least some reference signals are not received on one or more time instances used for or associated with performance monitoring, the terminal device still performs the corresponding performance monitoring and reports the monitoring results.

[0285] In some embodiments, for time beam prediction with a terminal-side model, if at least some reference signals are not received on one or more time instances in the prediction window used for performance monitoring, then the one or more time instances are not used for performance metric calculation and / or the corresponding performance metrics are not reported.

[0286] In some embodiments, for time beam prediction with a terminal-side model, if at least some reference signals are not received on one or more time instances in the prediction window used for performance monitoring, then all time instances of the prediction window are not used for performance metric calculation and / or the corresponding performance metrics are not reported.

[0287] In some embodiments, for time-beam prediction with an end-side model, if at least a portion of the reference signal is not received on one or more time instances in the prediction window used for performance monitoring, the performance metric calculation is restarted.

[0288] In some embodiments, for time beam prediction with an end-side model, if at least a portion of the reference signal is not received on one or more time instances in the measurement window (or observation window) associated with performance monitoring, then the one or more time instances are not used for performance metric calculation and / or the corresponding performance metrics are not reported.

[0289] In some embodiments, for time beam prediction with an end-side model, if at least a portion of the reference signal is not received on one or more time instances in a measurement window (or observation window) associated with performance monitoring, then all time instances of the measurement window (or observation window) are not used for performance metric calculation and / or the corresponding performance metrics are not reported.

[0290] In some embodiments, for time beam prediction with an end-side model, if at least a portion of the reference signal is not received on one or more time instances in the measurement window (or observation window) associated with performance monitoring, the performance metric calculation is restarted.

[0291] In some embodiments, for time beam prediction with a terminal-side model, if at least a portion of the configured reference signal resources on a time instance in the prediction window for performance monitoring and / or the measurement window (or observation window) associated with performance monitoring are multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all configured reference signal resources for that time instance apply the same receive beam (quasi-co-addressable with QCL-Type D) to the specific signal or channel.

[0292] In some embodiments, for time beam prediction with a terminal-side model, if at least a portion of the configured reference signal resources on a time instance in the prediction window and / or the measurement window (or observation window) associated with performance monitoring are multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all configured reference signal resources for all time instances in the prediction window and / or the measurement window (or observation window) apply the same receive beam (quasi-co-addressable with QCL-Type D) to the specific signal or channel.

[0293] In some embodiments, for spatial beam prediction with a terminal-side model, if at least some of the reference signals used for or associated with performance monitoring are not received, the corresponding performance monitoring and / or monitoring result reporting is cancelled.

[0294] In some embodiments, for spatial beam prediction with a terminal-side model, if at least some of the reference signals used for or associated with performance monitoring are not received, the terminal device still performs the corresponding performance monitoring and reports the monitoring results.

[0295] In some embodiments, for spatial beam prediction with a terminal-side model, if at least some of the reference signals used for performance monitoring and / or associated with performance monitoring are not received, the corresponding monitoring results are not used for performance metric calculations and / or the corresponding performance metrics are not reported.

[0296] In some embodiments, for spatial beam prediction with a terminal-side model, the performance metric calculation is restarted if at least some of the reference signals used for and / or associated with performance monitoring are not received.

[0297] In some embodiments, for spatial beam prediction with a terminal-side model, if at least a portion of the configured reference signal resources used for performance monitoring and / or associated with performance monitoring are multiplexed with a specific signal or channel (SSB, CORESET, SIB1), then all the configured reference signal resources used for performance monitoring and / or associated with performance monitoring are applied to the same receive beam (quasi-co-addressed with QCL-Type D) as the specific signal or channel.

[0298] In some embodiments, for temporal beam prediction with terminal-side and / or network-side models, or for spatial beam prediction with terminal-side and / or network-side models, if at least a portion of the reference signals used for data collection are not received, the corresponding data sample or dataset is dropped or marked.

[0299] The above embodiments are merely illustrative examples of embodiments of this application, but this application is not limited thereto, and appropriate modifications can be made based on the above embodiments. For example, the above embodiments can be used alone, or one or more of the above embodiments can be combined.

[0300] It is worth noting that the above description only covers the components or modules relevant to this application, but this application is not limited thereto. The beam management device 1000 may also include other components or modules, and for details regarding these components or modules, please refer to relevant technologies.

[0301] Furthermore, for simplicity, Figure 10 only illustrates the connection relationships or signal flow between the various components or modules, but those skilled in the art should understand that various related technologies such as bus connections can be used. The aforementioned components or modules can be implemented using hardware facilities such as processors, memory, transmitters, and receivers; this application does not limit this implementation.

[0302] As can be seen from the above embodiments, the terminal device receives configuration information from the network device; based on AI / ML functions / models, it performs spatial beam prediction and / or temporal beam prediction according to the configuration information. This improves the accuracy of beam management and enhances the performance and efficiency of AI / ML.

[0303] Fourth aspect of the embodiment

[0304] This application provides a beam management device. This device may be, for example, a network device, or one or more components or parts configured within a network device; details identical to those in the embodiments of the first to third aspects will not be repeated.

[0305] Figure 11 is another schematic diagram of a beam management device according to an embodiment of this application. As shown in Figure 11, the beam management device 1100 includes:

[0306] Transmitter 1101 sends configuration information for beam management to the terminal device;

[0307] The terminal device, based on AI / ML models / functions, performs spatial beam prediction or temporal beam prediction according to the configuration information.

[0308] In some embodiments, as shown in FIG11, the beam management device 1100 may further include:

[0309] Receiver 1102 receives report information / feedback information sent by terminal equipment, but this application is not limited thereto.

[0310] The above embodiments are merely illustrative examples of embodiments of this application, but this application is not limited thereto, and appropriate modifications can be made based on the above embodiments. For example, the above embodiments can be used alone, or one or more of the above embodiments can be combined.

[0311] It is worth noting that the above description only covers the components or modules relevant to this application, but this application is not limited thereto. The beam management device 1100 may also include other components or modules, and for details regarding these components or modules, please refer to relevant technologies.

[0312] Furthermore, for simplicity, Figure 11 only illustrates the connection relationships or signal flow between the various components or modules, but those skilled in the art should understand that various related technologies such as bus connections can be used. The aforementioned components or modules can be implemented using hardware facilities such as processors, memory, transmitters, and receivers; this application does not limit this implementation.

[0313] As can be seen from the above embodiments, the terminal device receives configuration information from the network device; based on AI / ML functions / models, it performs spatial beam prediction and / or temporal beam prediction according to the configuration information. This improves the accuracy of beam management and enhances the performance and efficiency of AI / ML.

[0314] Fifth aspect of the embodiment

[0315] This application also provides a communication system, which can be referred to FIG1. ​​The contents that are the same as those in the embodiments of the first to fourth aspects will not be repeated.

[0316] In some embodiments, the communication system 100 may include at least:

[0317] Network devices that send configuration information for beam management;

[0318] The terminal device receives configuration information for beam management from the network device; based on the AI / ML model / function, it performs spatial beam prediction or temporal beam prediction according to the configuration information.

[0319] This application also provides a terminal device, but the application is not limited thereto and may also include other devices.

[0320] Figure 12 is a schematic diagram of a terminal device according to an embodiment of this application. As shown in Figure 12, the terminal device 1200 may include a processor 1210 and a memory 1220; the memory 1220 stores data and programs and is coupled to the processor 1210. It is worth noting that this figure is exemplary; other types of structures may also be used to supplement or replace this structure to implement telecommunications functions or other functions.

[0321] For example, processor 1210 may be configured to execute a program to implement the beam management method as described in the embodiments of the first aspect. For example, processor 1210 may be configured to perform the following control: receive configuration information for beam management from a network device; and perform spatial beam prediction or temporal beam prediction based on the configuration information according to an AI / ML model / function.

[0322] As shown in Figure 12, the terminal device 1200 may further include: a communication module 1230, an input unit 1240, a display 1250, and a power supply 1260. The functions of these components are similar to those in the prior art and will not be described in detail here. It is worth noting that the terminal device 1200 does not necessarily include all the components shown in Figure 12; these components are not essential. Furthermore, the terminal device 1200 may also include components not shown in Figure 12, which can be referred to in the prior art.

[0323] This application also provides a network device, such as a base station, but this application is not limited to this and may also include other network devices.

[0324] Figure 13 is a schematic diagram of the network device according to an embodiment of this application. As shown in Figure 13, the network device 1300 may include: a processor 1310 (e.g., a central processing unit CPU) and a memory 1320; the memory 1320 is coupled to the processor 1310. The memory 1320 can store various data; in addition, it also stores an information processing program 1330, and executes the program 1330 under the control of the processor 1310.

[0325] For example, processor 1310 may be configured to execute a program to implement the beam management method as described in the embodiments of the second aspect. For example, processor 1310 may be configured to control the following: sending configuration information for beam management to a terminal device; wherein the configuration information is used by the terminal device to perform spatial beam prediction or temporal beam prediction based on an AI / ML model / function.

[0326] In addition, as shown in Figure 13, network device 1300 may also include a transceiver 1340 and an antenna 1350, etc.; the functions of the above components are similar to those in the prior art, and will not be described in detail here. It is worth noting that network device 1300 does not necessarily have to include all the components shown in Figure 13; in addition, network device 1300 may also include components not shown in Figure 13, which can be referred to in the prior art.

[0327] This application also provides a computer program, wherein when the program is executed in a terminal device, the program causes the terminal device to perform the beam management method described in the first aspect of the embodiment.

[0328] This application also provides a storage medium storing a computer program, wherein the computer program causes a terminal device to execute the beam management method described in the first aspect of the embodiment.

[0329] This application also provides a computer program, wherein when the program is executed in a network device, the program causes the network device to perform the beam management method described in the second aspect of the embodiment.

[0330] This application also provides a storage medium storing a computer program, wherein the computer program causes a network device to perform the beam management method described in the second aspect of the embodiment.

[0331] The apparatus and methods described above in this application can be implemented in hardware or in combination with software. This application relates to a computer-readable program that, when executed by a logic component, enables the logic component to implement the apparatus or components described above, or to implement the various methods or steps described above. This application also relates to storage media for storing the above programs, such as hard disks, magnetic disks, optical disks, DVDs, flash memory, etc.

[0332] The methods / apparatus described in conjunction with the embodiments of this application can be directly embodied in hardware, software modules executed by a processor, or a combination of both. For example, one or more and / or combinations of one or more functional block diagrams shown in the figures can correspond to various software modules in a computer program flow, or to various hardware modules. These software modules can correspond to the various steps shown in the figures, respectively. These hardware modules can be implemented, for example, using a field-programmable gate array (FPGA) to embed these software modules.

[0333] The software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art. A storage medium can be coupled to the processor, enabling the processor to read information from and write information to the storage medium; or the storage medium can be an integral part of the processor. The processor and storage medium can reside in an ASIC. The software module can be stored in the memory of a mobile terminal or in a memory card that can be inserted into the mobile terminal. For example, if the device (such as a mobile terminal) uses a high-capacity MEGA-SIM card or a high-capacity flash memory device, the software module can be stored in the MEGA-SIM card or the high-capacity flash memory device.

[0334] One or more and / or one or more combinations of functional blocks described in the accompanying drawings can be implemented as a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, or any suitable combination thereof for performing the functions described herein. One or more and / or one or more combinations of functional blocks described in the accompanying drawings can also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in communication with a DSP, or any other such configuration.

[0335] The present application has been described above with reference to specific embodiments. However, those skilled in the art should understand that these descriptions are exemplary and not intended to limit the scope of protection of the present application. Those skilled in the art can make various modifications and variations to the present application based on its spirit and principles, and these modifications and variations are also within the scope of the present application.

[0336] Regarding the implementation methods including the above embodiments, the following notes are also disclosed:

[0337] 1. A beam management method, comprising:

[0338] The terminal device receives configuration information for beam management from the network device;

[0339] The terminal device performs spatial beam prediction or temporal beam prediction based on the configuration information, using AI / ML models / functions.

[0340] 2. A beam management method, comprising:

[0341] The network device sends configuration information for beam management to the terminal device;

[0342] The configuration information is used by the terminal device to perform spatial beam prediction or temporal beam prediction based on AI / ML models / functions.

[0343] 3. A terminal device comprising a memory and a processor, the memory storing a computer program and the processor being configured to execute the computer program to implement the beam management method as described in Appendix 1.

[0344] 4. A network device comprising a memory and a processor, the memory storing a computer program and the processor being configured to execute the computer program to implement the beam management method as described in Appendix 2.

[0345] 5. A computer program product comprising at least a computer program that, when executed by a processor, causes a terminal device to perform the beam management method as described in Appendix 1.

[0346] 6. A computer program product comprising at least a computer program that, when executed by a processor, causes a network device to perform the beam management method as described in Appendix 2.

Claims

1. A beam management device, comprising: The receiver receives configuration information for beam management from the network device; The processor, based on an AI / ML model / function, performs spatial beam prediction or temporal beam prediction according to the configuration information.

2. The apparatus according to claim 1, wherein, For time beam prediction with terminal-side model If at least some of the reference signals are not received at one or more time instances in the measurement window used for inference, the corresponding model inference and / or inference result reporting is cancelled, or the terminal device still performs the corresponding model inference and reports the inference results.

3. The apparatus according to claim 2, wherein, The measurement results corresponding to at least a portion of the unreceived reference signals are set to specific values. Alternatively, the measurement results corresponding to the unreceived at least portion of the reference signals may be set as the most recent measurement results prior to the one or more time instances. Alternatively, the measurement results corresponding to the unreceived at least part of the reference signals may be determined by the terminal device through interpolation based on the measurement results before and after the one or more time instances.

4. The apparatus according to claim 1, wherein, For time beam prediction with terminal-side model If at least some reference signals are not received on one or more time instances in the measurement window used for inference, and the number of said time instances exceeds a threshold, the corresponding model inference and / or inference result reporting is cancelled. or, If at least a portion of the reference signal is not received at a specific time instance within the measurement window used for inference, the corresponding model inference and / or inference result reporting is cancelled.

5. The apparatus according to claim 1, wherein, For time beam prediction with terminal-side model If the received beam changes relative to the reference signal on one or more time instances within the measurement window used for inference, the corresponding model inference and / or inference result reporting is cancelled; alternatively, the terminal device may still perform the corresponding model inference and report the inference results.

6. The apparatus according to claim 1, wherein, For time beam prediction with terminal-side model If at least a portion of the reference signal resources in a time instance of the measurement window used for inference are configured to be multiplexed with a specific signal or channel, Then all configured reference signal resources for the time instance are the same as those for the specific signal or channel application. The receiving beam, or, for all configured reference signal resources in all time instances of the measurement window, the same receiving beam is applied to the specific signal or channel.

7. The apparatus according to claim 1, wherein, For spatial beam prediction with terminal-side models If at least some of the reference signals used for inference are not received, the corresponding model inference and / or inference result reporting is cancelled, or the terminal device still performs the corresponding model inference and reports the inference result.

8. The apparatus according to claim 1, wherein, For spatial beam prediction with terminal-side models If the received beam changes in relation to the reference signal, the corresponding model inference and / or inference result reporting is cancelled; alternatively, the terminal device may still perform the corresponding model inference and report the inference results.

9. The apparatus according to claim 1, wherein, For spatial beam prediction with terminal-side models If at least a portion of the reference signal resources used for inference are configured to be multiplexed with a specific signal or channel, then all the configured reference signal resources used for inference apply the same receive beam as the specific signal or channel.

10. The apparatus according to claim 1, wherein, For spatial beam prediction with terminal-side models For periodic or semi-persistent reference signals, if at least a portion of the reference signal resources on a time instance are configured to be multiplexed with a specific signal or channel, then all the configured reference signal resources on the time instance and the specific signal or channel are applied with the same receive beam.

11. The apparatus according to claim 1, wherein, For time beam prediction with terminal-side model If at least some reference signals are not received on one or more time instances in the prediction window used for performance monitoring, then the one or more time instances are not used for performance metric calculation and / or the corresponding performance metrics are not reported; or, all time instances of the prediction window are not used for performance metric calculation and / or the corresponding performance metrics are not reported.

12. The apparatus according to claim 1, wherein, For time beam prediction with terminal-side model If at least some reference signals are not received on one or more time instances in a measurement window associated with performance monitoring, then the one or more time instances are not used for performance metric calculation and / or the corresponding performance metrics are not reported; or, all time instances of the measurement window are not used for performance metric calculation and / or the corresponding performance metrics are not reported.

13. The apparatus according to claim 1, wherein, For time beam prediction with terminal-side model If at least some reference signals are not received on one or more time instances in the prediction window used for performance monitoring, and / or if at least some reference signals are not received on one or more time instances in the measurement window associated with performance monitoring, the performance metric calculation is restarted.

14. The apparatus according to claim 1, wherein, For time beam prediction with terminal-side model If at least one time instance of the prediction window and / or measurement window used for performance monitoring... Some of the configured reference signal resources are multiplexed with specific signals or channels. Then, for all configured reference signal resources of the time instance, the same receiving beam is applied to the specific signal or channel; or, for all configured reference signal resources of all time instances in the prediction window and / or the measurement window, the same receiving beam is applied to the specific signal or channel.

15. The apparatus according to claim 1, wherein, For spatial beam prediction with terminal-side models If at least some of the reference signals used for and / or associated with performance monitoring are not received, the corresponding monitoring results will not be used for performance metric calculations and / or the corresponding performance metrics will not be reported.

16. The apparatus according to claim 1, wherein, For spatial beam prediction with terminal-side models If at least some of the reference signals used for and / or associated with performance monitoring are not received, the performance metric calculation is restarted.

17. The apparatus according to claim 1, wherein, For spatial beam prediction with terminal-side models If at least a portion of the reference signal resources used for and / or associated with performance monitoring are configured to be multiplexed with a specific signal or channel, then all the configured reference signal resources used for and / or associated with performance monitoring apply the same receiving beam to the specific signal or channel.

18. The apparatus according to claim 1, wherein, For temporal beam prediction with terminal-side and / or network-side models, or for spatial beam prediction with terminal-side and / or network-side models, If at least some of the reference signals used for data collection are not received, the corresponding data sample or data set is discarded or marked.

19. A beam management device, comprising: A transmitter that sends configuration information for beam management to terminal devices; The configuration information is used by the terminal device to perform spatial beam prediction or temporal beam prediction based on AI / ML models / functions.

20. A communication system, comprising: Network devices that send configuration information for beam management; The terminal device receives configuration information for beam management from the network device; based on the AI / ML model / function, it performs spatial beam prediction or temporal beam prediction according to the configuration information.

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