Beam management configuration method and apparatus

Abstract

The embodiments of the present application provide a beam management configuration method and apparatus. The beam management configuration method comprises: a terminal device receiving configuration information from a network device, wherein the configuration information is used for AI / ML functionality / model-based spatial beam prediction and temporal beam prediction.

Description

Beam management configuration method and device Technical Field

[0001] The embodiments of the present application relate to the field of communication technologies. Background Art

[0002] NR Release 18 investigates artificial intelligence / machine learning (AI / ML) over the air interface. 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 and temporal beam prediction; and positioning enhancement can include direct positioning and AI / ML-assisted positioning.

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

[0004] It should be noted that the above introduction to the technical background is merely intended to provide a clear and complete description of the technical solutions of this application and facilitate understanding by those skilled in the art. Simply because these solutions are described in the background technology section of this application, it should not be assumed that the above technical solutions are well known to those skilled in the art.

[0005] Summary of the Invention

[0006] The inventors discovered that terminal devices and / or network devices can utilize AI / ML functionality / models to predict beams based on beam measurement results. However, there is currently no clear solution for whether spatial beam prediction and temporal beam prediction can be configured or enabled simultaneously.

[0007] To address at least one of the above problems, an embodiment of the present application provides a beam management configuration method and apparatus.

[0008] According to one aspect of an embodiment of the present application, a beam management configuration method is provided, including:

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

[0010] The configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model.

[0011] According to another aspect of an embodiment of the present application, a beam management configuration device is provided, including:

[0012] a receiving unit, configured to receive configuration information from a network device;

[0013] The configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model.

[0014] According to another aspect of an embodiment of the present application, a beam management configuration method is provided, including:

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

[0016] The configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model.

[0017] According to another aspect of an embodiment of the present application, a beam management configuration device is provided, including:

[0018] a sending unit, configured to send configuration information to a terminal device;

[0019] The configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model.

[0020] According to another aspect of an embodiment of the present application, a communication system is provided, including:

[0021] A network device that sends configuration information to a terminal device;

[0022] A terminal device receives the configuration information; wherein the configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model.

[0023] One of the beneficial effects of the embodiments of the present application is that: the terminal device receives configuration information from the network device; the configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model; thereby, the performance and efficiency of beam management can be improved, and the accuracy and reliability of beam management can be improved.

[0024] With reference to the following description and accompanying drawings, specific embodiments of the present application are disclosed in detail, indicating the manner in which the principles of the present application can be employed. It should be understood that the embodiments of the present application are not limited in scope. Within the spirit and scope of the appended claims, the embodiments of the present application include many variations, modifications and equivalents.

[0025] Features described and / or illustrated with respect to 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 "include / comprising" when used herein refers to the presence of features, integers, steps or components, but does not exclude the presence or addition of one or more other features, integers, steps or components. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The elements and features described in one figure or one embodiment of the present application can be combined with the elements and features shown in one or more other figures or embodiments. In addition, in the accompanying drawings, similar reference numerals represent corresponding parts in several figures and can be used to indicate corresponding parts used in more than one embodiment.

[0028] FIG1 is a schematic diagram of a communication system according to an embodiment of the present application;

[0029] FIG2 is a schematic diagram of a beam management configuration method according to an embodiment of the present application;

[0030] FIG3 is a schematic diagram of a beam management method according to an embodiment of the present application;

[0031] FIG4 is another schematic diagram of a beam management configuration method according to an embodiment of the present application;

[0032] FIG5 is a schematic diagram of a beam management configuration device according to an embodiment of the present application;

[0033] FIG6 is another schematic diagram of a beam management configuration apparatus according to an embodiment of the present application;

[0034] FIG7 is a schematic diagram of a terminal device according to an embodiment of the present application;

[0035] FIG8 is a schematic diagram of a network device according to an embodiment of the present application. DETAILED DESCRIPTION

[0036] The above and other features of the present application will become apparent through the following description with reference to the accompanying drawings. In the description and the accompanying drawings, specific embodiments of the present application are disclosed in detail, which illustrate some embodiments in which the principles of the present application can be adopted. It should be understood that the present application is not limited to the described embodiments. On the contrary, the present application includes all modifications, variations and equivalents that fall within the scope of the appended claims.

[0037] In the embodiments of the present application, the terms "first", "second", etc. are used to distinguish different elements from the name, but do not indicate the spatial arrangement or temporal order of these elements, and these elements should not be limited by these terms. The term "and / or" includes any one and all combinations of one or more of the associated listed terms. The terms "comprising", "including", "having", etc. refer to the presence of the stated features, elements, components or components, but do not exclude the presence or addition of one or more other features, elements, components or components.

[0038] In the embodiments of this application, the singular forms "a," "the," etc. include plural forms and should be broadly understood to mean "a" or "a type" rather than being limited to "one." Furthermore, the term "said" should be understood to include both singular and plural forms, unless the context clearly indicates otherwise. Furthermore, the term "according to" should be understood to mean "at least in part based on...", and the term "based on" should be understood to mean "at least in part based on...", unless the context clearly indicates otherwise.

[0039] In the embodiments of the present application, the term "communication network" or "wireless communication network" may refer to a network that complies with any of the following communication standards, such as Long Term Evolution (LTE), enhanced Long Term Evolution (LTE-A, LTE-Advanced), Wideband Code Division Multiple Access (WCDMA), High-Speed ​​Packet Access (HSPA), etc.

[0040] Furthermore, communication between devices in the communication system may be carried out according to communication protocols of any stage, for example, 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 communication protocols currently known or to be developed in the future.

[0041] In the embodiments of the present application, the term "network device" refers to, for example, a device in a communication system that connects a terminal device to the communication network and provides services to the 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.

[0042] Among them, base stations may include but are not limited to: NodeB (NodeB or NB), evolved NodeB (eNodeB or eNB) and 5G base station (gNB), IAB host, etc., and may also include remote radio head (RRH, Remote Radio Head), remote radio unit (RRU, Remote Radio Unit), relay (relay) or low-power node (such as femeto, pico, etc.). The term "base station" can include some or all of their functions. Each base station can provide communication coverage for a specific geographical 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.

[0043] In the embodiments of the present application, the term "user equipment" (UE) or "terminal equipment" (TE) refers to, for example, a device that accesses a communication network through a network device and receives network services. A terminal device can be fixed or mobile and may also be referred to as a mobile station (MS), a terminal, a subscriber station (SS), an access terminal (AT), a station, and so on.

[0044] Among them, terminal devices may include but are not limited to the following devices: cellular phones, personal digital assistants (PDAs), wireless modems, wireless communication devices, handheld devices, machine-type communication devices, laptop computers, cordless phones, smart phones, smart watches, digital cameras, etc.

[0045] For another example, in scenarios such as the Internet of Things (IoT), the terminal device can also be a machine or device for monitoring or measurement, including but not limited to: machine type communication (MTC) terminal, vehicle-mounted communication terminal, device-to-device (D2D) terminal, machine-to-machine (M2M) terminal, and so on.

[0046] In addition, the term "network side" or "network device side" refers to one side of the network, which can be a base station or one or more network devices as described above. The term "user side" or "terminal side" or "terminal device side" refers to the user or terminal side, which can be a UE or one or more terminal devices as described above. Unless otherwise specified herein, "device" can refer to either network equipment or terminal equipment.

[0047] The following describes the scenarios of the embodiments of the present application through examples, but the present application is not limited thereto.

[0048] FIG1 is a schematic diagram of a communication system according to an embodiment of the present application, schematically illustrating a situation using a terminal device and a network device as an example. As shown in FIG1 , a communication system 100 may include a network device 101 and terminal devices 102 and 103. For simplicity, FIG1 illustrates only two terminal devices and one network device as an example, but the embodiments of the present application are not limited thereto.

[0049] In the embodiment of the present application, existing services or future services can be transmitted between the network device 101 and the terminal devices 102 and 103. 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.

[0050] It is worth noting that FIG1 shows that both terminal devices 102 and 103 are within the coverage range of network device 101, but the present application is not limited thereto. Both terminal devices 102 and 103 may not be within the coverage range of network device 101, or one terminal device 102 may be within the coverage range of network device 101 while the other terminal device 103 is outside the coverage range of network device 101.

[0051] In the embodiments of the present application, the high-layer signaling may be, for example, radio resource control (RRC) signaling; for example, an RRC message, including, for example, an MIB, system information, or a dedicated RRC message; or an RRC information element (RRC IE). The high-layer signaling may also be, for example, MAC (Medium Access Control) signaling; or a MAC control element (MAC CE). However, the present application is not limited thereto.

[0052] In embodiments of the present application, one or more AI / ML models may be configured and run in a network device and / or a terminal device. The AI / ML models may be used for various signal processing functions in wireless communications, such as CSI prediction, CSI compression, beamforming, positioning management, and the like; however, the present application is not limited thereto.

[0053] Embodiments of the first aspect

[0054] An embodiment of the present application provides a beam management configuration method, which is described from the terminal device side.

[0055] FIG2 is a schematic diagram of a beam management configuration method according to an embodiment of the present application. As shown in FIG2 , the method includes:

[0056] 201, the terminal device receives configuration information from the network device;

[0057] The configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model.

[0058] It is worth noting that FIG2 above is merely a schematic illustration of an embodiment of the present application, and the present application is not limited thereto. For example, the execution order of the various operations may be appropriately adjusted, and other operations may be added or some operations may be reduced. Those skilled in the art may make appropriate modifications based on the above description, and are not limited to the description of FIG2 above.

[0059] In some embodiments, functionality refers to an AI / ML feature / feature group enabled by a configuration, where the configuration is supported based on conditions indicated by UE capabilities.

[0060] For example, the AL / ML function may 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.

[0061] For another example, the function can be to use AI / ML for spatial beam prediction, or to use AI / ML for time 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.

[0062] In some embodiments, the configuration information for beam management may include configuration information of one or more reference signals used for beam management or beam measurement, such as CSI-RS configuration information, etc. The present application is not limited thereto, and reference may be made to related technologies for specific configuration information.

[0063] In some embodiments, one or more reference signals are used for measurement and the measurement results are input into the AI / ML functionality / model, and another one or more reference signals are used for the output of the AI / ML functionality / model for inference.

[0064] FIG3 is another schematic diagram of the beam management method according to an embodiment of the present application, which is illustrated by taking a terminal device configured with AIML as an example. As shown in FIG3 , the method includes:

[0065] 301. A terminal device receives configuration information from a network device; for example, the configuration information includes a second reference signal resource set (set B) for beam measurement and a first reference signal resource set (set A) for beam prediction.

[0066] 302. The terminal device performs beam measurement and inputs the beam measurement results into the AI / ML functionality / model. For example, the measurement results of the reference signals in set B are used as input to the AI / ML, and the reference signals in set A are used for prediction (or inference).

[0067] 303. The terminal device sends the beam prediction result to the network device.

[0068] For example, the AI / ML function is located on the terminal device side. After the AI / ML function is enabled or activated, the terminal device performs beam measurement based on the reference signal from the network side, uses AI / ML to perform beam prediction based on the beam measurement results, and sends the prediction results to the network device.

[0069] It is worth noting that FIG3 above is merely a schematic illustration of an embodiment of the present application, and the present application is not limited thereto. For example, the execution order of the various operations may be appropriately adjusted, and other operations may be added or some operations may be reduced. Those skilled in the art may make appropriate modifications based on the above description, and are not limited to the description of FIG3 above.

[0070] The above schematically illustrates AI / ML-based beam management. The following describes the beam management configuration.

[0071] In some embodiments, the spatial beam prediction is configured in the terminal device and the temporal beam prediction is configured in the network device; and / or, the spatial beam prediction is configured in the network device and the temporal beam prediction is configured in the terminal device; and / or, the spatial beam prediction is configured in the terminal device and the temporal beam prediction is configured in the terminal device; and / or, the spatial beam prediction is configured in the network device and the temporal beam prediction is configured in the network device.

[0072] For example, the following AI / ML for beam management operations can be configured simultaneously:

[0073] -BM Case-1 (spatial beam prediction) on the UE side and BM Case-2 (temporal beam prediction) on the gNB side;

[0074] -BM Case-2 (temporal beam prediction) on the UE side and BM Case-1 (spatial beam prediction) on the gNB side;

[0075] -BM Case-1 (spatial beam prediction) on the UE side and BMCase-2 (temporal beam prediction) on the UE side;

[0076] -BM Case-1 (spatial beam prediction) on the gNB side and BM Case-2 (temporal beam prediction) on the gNB side.

[0077] The above schematically illustrates four situations. The above four situations can be implemented separately or in combination of two or more situations. This application does not limit this.

[0078] In some embodiments, the second reference signal set (set B) for measurement and the first reference signal set (set A) for prediction are configured separately for the time beam prediction and the spatial beam prediction; wherein the time beam prediction and the spatial beam prediction are configured separately.

[0079] For example, separate set A and set B can be configured for BM Case 1 and BM Case 2. For example, two set A and two set B are configured; one set A and one set B are used for BM Case 1, and the other set A and another set B are used for BM Case 2. In signaling, BM Case 1 and BM Case 2 can be configured separately.

[0080] In some embodiments, the second reference signal set (set B) for measurement and the first reference signal set (set A) for prediction are configured separately for the time beam prediction and the spatial beam prediction; wherein the time beam prediction and the spatial beam prediction are configured together.

[0081] For example, separate set A and set B can be configured for BM Case-1 and BM Case-2 operations. For example, two set A and two set B are configured; one set A and one set B are used for BM Case-1, and the other set A and another set B are used for BM Case-2. In signaling, BM Case-1 and BM Case-2 can be configured together.

[0082] In some embodiments, for the time beam prediction and the spatial beam prediction, the second reference signal set (set B) for measurement and / or the first reference signal set (set A) for prediction are shared by the time beam prediction and the spatial beam prediction.

[0083] For example, if both BM case-1 and BM case-2 are configured or enabled at the same time, set A and / or set B can be shared between BM case-1 and BM case-2. For example, if both BM case-1 and BM case-2 are configured on the UE side, only one set A and one set B can be configured, and these two sets are used for both BM case-1 and BM case-2.

[0084] In some embodiments, separate reporting is configured for temporal beam prediction and spatial beam prediction.

[0085] For example, if both BM case-1 and BM case-2 are configured or enabled simultaneously, reporting (reporting) is configured for BM case-1 and BM case-2 respectively. For example, if both BM case-1 and BM case-2 are configured on the UE side, reporting (e.g., reporting#1) can be configured for BM case-1 and reporting (e.g., reporting#2) can be configured for BM case-2.

[0086] In some embodiments, the same reporting is configured for temporal beam prediction and spatial beam prediction.

[0087] For example, if both BM case-1 and BM case-2 are configured or enabled at the same time, reporting is configured for each of BM case-1 and BM case-2. For example, if both BM case-1 and BM case-2 are configured on the UE side, one reporting (e.g., reporting#1) can be configured for both BM case-1 and BM case-2.

[0088] In some embodiments, with respect to the time beam prediction and the space beam prediction, the time beam prediction is configured in the terminal device, and beam reporting of multiple time instances is also configured to the terminal device.

[0089] For example, for simultaneous configuration or activation of BM case-1 operation and BM case-2 operation, if BM case-2 is configured on the UE side, beam reporting of multiple time instances is also configured for the UE.

[0090] In some embodiments, respective performance monitoring is configured for the temporal beam prediction and the spatial beam prediction.

[0091] For example, if BM case-1 and BM case-2 are configured or enabled at the same time, separate performance monitoring processes can be configured for BM case-1 and BM case-2. For example, two performance monitoring processes are configured; one performance monitoring process is used for BM case-1, and the other performance monitoring process is used for BM case-2.

[0092] In some embodiments, shared performance monitoring is configured for the temporal beam prediction and the spatial beam prediction.

[0093] For example, if BM case-1 and BM case-2 are configured or enabled at the same time, BM case-1 and BM case-2 can share a performance monitoring process. For example, a performance monitoring process is configured; the performance monitoring process is used for both BM case-1 and BM case-2.

[0094] In some embodiments, the spatial beam prediction is configured in the terminal device and the time beam prediction is configured in the terminal device, and a shared performance monitoring process is configured for the time beam prediction and the spatial beam prediction;

[0095] And / or, the spatial beam prediction is configured in the network device and the temporal beam prediction is configured in the network device, and a shared performance monitoring process is configured for the temporal beam prediction and the spatial beam prediction.

[0096] For example, if BM case-1 and BM case-2 are configured on one side (UE side), a performance monitoring process can be configured, which can be configured on the UE side (or on the eNB side) and shared by BM case-1 and BM case-2.

[0097] For another example, if BM case-1 and BM case-2 are configured on one side (eNB side), a performance monitoring process can be configured. The performance monitoring process can be configured on the eNB side (or on the UE side) and shared by BM case-1 and BM case-2.

[0098] For another example, if BM Case-1 and BM Case-2 are configured on both sides (e.g., BM Case-1 at the gNB and BM Case-2 at the UE, or BM Case-1 at the UE and BM Case-2 at the gNB), separate performance monitoring procedures are configured for BM Case-1 and BM Case-2 respectively.

[0099] In some embodiments, for the time beam prediction and the spatial beam prediction, a performance monitoring process is configured in the terminal device, or the performance monitoring process is configured in the network device, or the performance monitoring process is configured in the network device and the terminal device.

[0100] For example, for simultaneously configuring or enabling BM case-1 operation and BM case-2 operation, the performance monitoring process can be configured on one side (UE side or eNB side), or the performance monitoring process can be configured on both sides (UE side and eNB side).

[0101] For another example, if BM Case-1 and BM Case-2 are configured on the gNB side, the performance monitoring process is also configured on the gNB side. If BM Case-1 and BM Case-2 are configured on the UE side, the performance monitoring process is also configured on the UE side, or hybrid performance monitoring is configured.

[0102] If both BM Case-1 and BM Case-2 are configured on both sides, performance monitoring of AI / ML for beam management on the gNB side can be performed on the gNB side. Performance monitoring of AI / ML for beam management on the UE side can also be performed on the UE side, or hybrid performance monitoring can be configured.

[0103] The above embodiments are merely exemplary of the present invention, but the present invention is not limited thereto. Appropriate modifications may be made based on the above embodiments. For example, the above embodiments may be used alone, or one or more of the above embodiments may be combined.

[0104] It can be seen from the above embodiments that the terminal device receives configuration information from the network device; the configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model; thereby, the performance and efficiency of beam management can be improved, and the accuracy and reliability of beam management can be improved.

[0105] Embodiments of the second aspect

[0106] The embodiment of the present application provides a beam management configuration method, which is described from the perspective of a network device. The embodiment of the second aspect can be combined with the embodiment of the first aspect, and the same contents as the embodiment of the first aspect will not be repeated.

[0107] FIG4 is another schematic diagram of a beam management configuration method according to an embodiment of the present application. As shown in FIG4 , the method includes:

[0108] 401. A network device sends configuration information to a terminal device, wherein the configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model.

[0109] The above embodiments are merely exemplary of the present invention, but the present invention is not limited thereto. Appropriate modifications may be made based on the above embodiments. For example, the above embodiments may be used alone, or one or more of the above embodiments may be combined.

[0110] It can be seen from the above embodiments that the terminal device receives configuration information from the network device; the configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model; thereby, the performance and efficiency of beam management can be improved, and the accuracy and reliability of beam management can be improved.

[0111] Embodiments of the third aspect

[0112] The embodiment of the present application provides a beam management configuration device. The device can be, for example, a terminal device, or one or more components or assemblies configured in the terminal device. The contents that are the same as those in the first and second aspects of the embodiment are not repeated here.

[0113] FIG5 is a schematic diagram of a beam management configuration apparatus according to an embodiment of the present application. As shown in FIG5 , the beam management configuration apparatus 500 according to an embodiment of the present application includes:

[0114] The receiving unit 501 receives configuration information from a network device; the configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model.

[0115] In some embodiments, the spatial beam prediction is configured at the terminal device and the temporal beam prediction is configured at the network device.

[0116] In some embodiments, the spatial beam prediction is configured at the network device and the temporal beam prediction is configured at the terminal device.

[0117] In some embodiments, the spatial beam prediction is configured at the terminal device and the temporal beam prediction is configured at the terminal device.

[0118] In some embodiments, the spatial beam prediction is configured at the network device and the temporal beam prediction is configured at the network device.

[0119] In some embodiments, the second reference signal set (set B) for measurement and the first reference signal set (set A) for prediction are configured for the time beam prediction and the spatial beam prediction, respectively.

[0120] In some embodiments, the temporal beam prediction and the spatial beam prediction are configured separately.

[0121] In some embodiments, the temporal beam prediction and the spatial beam prediction are configured together.

[0122] In some embodiments, for the time beam prediction and the spatial beam prediction, the second reference signal set (set B) for measurement and / or the first reference signal set (set A) for prediction are shared by the time beam prediction and the spatial beam prediction.

[0123] In some embodiments, separate reporting is configured for the temporal beam prediction and the spatial beam prediction.

[0124] In some embodiments, the same reporting is configured for the temporal beam prediction and the spatial beam prediction.

[0125] In some embodiments, with respect to the time beam prediction and the space beam prediction, the time beam prediction is configured in the terminal device, and beam reporting of multiple time instances is also configured to the terminal device.

[0126] In some embodiments, respective performance monitoring is configured for the temporal beam prediction and the spatial beam prediction.

[0127] In some embodiments, shared performance monitoring is configured for the temporal beam prediction and the spatial beam prediction.

[0128] In some embodiments, the spatial beam prediction is configured in the terminal device and the temporal beam prediction is configured in the terminal device, and a shared performance monitoring process is configured for the temporal beam prediction and the spatial beam prediction.

[0129] In some embodiments, the spatial beam prediction is configured in the network device and the temporal beam prediction is configured in the network device, and a shared performance monitoring process is configured for the temporal beam prediction and the spatial beam prediction.

[0130] In some embodiments, a performance monitoring process is configured in the terminal device for the time beam prediction and the spatial beam prediction.

[0131] In some embodiments, the performance monitoring process is configured in the network device for the temporal beam prediction and the spatial beam prediction.

[0132] In some embodiments, for the time beam prediction and the spatial beam prediction, the performance monitoring process is configured in the network device and the terminal device.

[0133] In some embodiments, as shown in FIG5 , the beam management configuration apparatus 500 may further include:

[0134] a processing unit 502 that performs beam measurement and / or beam prediction; and

[0135] The sending unit 503 sends beam measurement information and / or beam prediction information to the network device.

[0136] The above embodiments are merely exemplary of the present invention, but the present invention is not limited thereto. Appropriate modifications may be made based on the above embodiments. For example, the above embodiments may be used alone, or one or more of the above embodiments may be combined.

[0137] It is worth noting that the above only describes the components or modules related to the present application, but the present application is not limited thereto. The beam management configuration device 500 may also include other components or modules. For the specific contents of these components or modules, reference may be made to the relevant art.

[0138] In addition, for simplicity, FIG5 only illustrates the connection relationship or signal path between various components or modules. However, those skilled in the art should be aware that various related technologies such as bus connection can be used. The above-mentioned components or modules can be implemented by hardware facilities such as processors, memories, transmitters, and receivers; this application is not limited to this.

[0139] It can be seen from the above embodiments that the terminal device receives configuration information from the network device; the configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model; thereby, the performance and efficiency of beam management can be improved, and the accuracy and reliability of beam management can be improved.

[0140] Embodiments of the fourth aspect

[0141] The embodiment of the present application provides a beam management configuration device. The device can be, for example, a network device, or one or more components or assemblies configured in the network device. The contents that are the same as those in the first to third aspects of the embodiment are not repeated here.

[0142] FIG6 is another schematic diagram of a beam management configuration apparatus according to an embodiment of the present application. As shown in FIG6 , the beam management configuration apparatus 600 includes:

[0143] A sending unit 601 sends configuration information to a terminal device; wherein the configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model.

[0144] In some embodiments, as shown in FIG6 , the beam management configuration apparatus 600 may further include:

[0145] The receiving unit 602 receives the beam measurement information and / or beam prediction information sent by the terminal device.

[0146] The above embodiments are merely exemplary of the present invention, but the present invention is not limited thereto. Appropriate modifications may be made based on the above embodiments. For example, the above embodiments may be used alone, or one or more of the above embodiments may be combined.

[0147] It is worth noting that the above only describes the components or modules related to the present application, but the present application is not limited thereto. The beam management configuration device 600 may also include other components or modules. For the specific contents of these components or modules, reference may be made to the relevant art.

[0148] In addition, for the sake of simplicity, FIG6 only illustrates the connection relationship or signal direction between various components or modules. However, it should be clear to those skilled in the art that various related technologies such as bus connection can be used. The above-mentioned components or modules can be implemented by hardware facilities such as processors, memories, transmitters, and receivers; the implementation of this application is not limited to this.

[0149] It can be seen from the above embodiments that the terminal device receives configuration information from the network device; the configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model; thereby, the performance and efficiency of beam management can be improved, and the accuracy and reliability of beam management can be improved.

[0150] Embodiments of the fifth aspect

[0151] An embodiment of the present application also provides a communication system, and reference may be made to FIG1 . The contents that are the same as those in the first to fourth aspects of the embodiments will not be repeated.

[0152] In some embodiments, the communication system 100 may include at least:

[0153] A network device that sends configuration information to a terminal device;

[0154] A terminal device receives the configuration information, where the configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model.

[0155] The embodiment of the present application also provides a terminal device, but the present application is not limited thereto and may also be other devices.

[0156] Figure 7 is a schematic diagram of a terminal device according to an embodiment of the present application. As shown in Figure 7 , terminal device 700 may include a processor 710 and a memory 720. Memory 720 stores data and programs and is coupled to processor 710. It should be noted that this diagram is exemplary; other types of structures may be used to supplement or replace this structure to implement telecommunication or other functions.

[0157] For example, the processor 710 may be configured to execute a program to implement the beam management configuration method as described in the embodiment of the first aspect. For example, the processor 710 may be configured to perform the following control: receiving configuration information from a network device; wherein the configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model.

[0158] As shown in Figure 7 , the terminal device 700 may further include: a communication module 730, an input unit 740, a display 750, and a power supply 760. The functions of these components are similar to those in the prior art and are not described in detail here. It is worth noting that the terminal device 700 does not necessarily include all of the components shown in Figure 7 , and these components are not essential. Furthermore, the terminal device 700 may also include components not shown in Figure 7 , for which reference may be made to the prior art.

[0159] An embodiment of the present application further provides a network device, which may be, for example, a base station, but the present application is not limited thereto and may also be other network devices.

[0160] Figure 8 is a schematic diagram illustrating the structure of a network device according to an embodiment of the present application. As shown in Figure 8 , network device 800 may include a processor 810 (e.g., a central processing unit (CPU)) and a memory 820 ; the memory 820 is coupled to the processor 810 . The memory 820 may store various data and may also store an information processing program 830 , which is executed under the control of the processor 810 .

[0161] For example, the processor 810 may be configured to execute a program to implement the beam management configuration method as described in the embodiment of the second aspect. For example, the processor 810 may be configured to perform the following control: sending configuration information to a terminal device; wherein the configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model.

[0162] In addition, as shown in FIG8 , network device 800 may further include: a transceiver 840 and an antenna 850, etc.; wherein, the functions of the above components are similar to those in the prior art and are not described in detail here. It is worth noting that network device 800 does not necessarily include all the components shown in FIG8 ; in addition, network device 800 may also include components not shown in FIG8 , and reference may be made to the prior art for details.

[0163] An embodiment of the present application also provides a computer program, wherein when the program is executed in a terminal device, the program enables the terminal device to execute the beam management configuration method described in the embodiment of the first aspect.

[0164] An embodiment of the present application also provides a storage medium storing a computer program, wherein the computer program enables a terminal device to execute the beam management configuration method described in the embodiment of the first aspect.

[0165] An embodiment of the present application also provides a computer program, wherein when the program is executed in a network device, the program enables the network device to execute the beam management configuration method described in the embodiment of the second aspect.

[0166] An embodiment of the present application also provides a storage medium storing a computer program, wherein the computer program enables a network device to execute the beam management configuration method described in the embodiment of the second aspect.

[0167] The above devices and methods of the present application can be implemented by hardware or by a combination of hardware and software. The present application relates to such a computer-readable program that, when executed by a logic component, enables the logic component to implement the devices or components described above, or enables the logic component to implement the various methods or steps described above. The present application also relates to a storage medium for storing the above program, such as a hard disk, a magnetic disk, an optical disk, a DVD, a flash memory, etc.

[0168] The method / device described in conjunction with the embodiments of the present application can be directly embodied as hardware, a software module executed by a processor, or a combination of the two. For example, one or more of the functional block diagrams shown in the figure and / or one or more combinations of functional block diagrams can correspond to various software modules of the computer program flow or to various hardware modules. These software modules can respectively correspond to the various steps shown in the figure. These hardware modules can be implemented by solidifying these software modules, for example, using a field programmable gate array (FPGA).

[0169] The software module may be located in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. A storage medium may be coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium; or the storage medium may be an integral part of the processor. The processor and the storage medium may be located in an ASIC. The software module may be stored in the memory of the 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 large-capacity MEGA-SIM card or a large-capacity flash memory device, the software module may be stored in the MEGA-SIM card or the large-capacity flash memory device.

[0170] One or more of the functional blocks and / or one or more combinations of functional blocks described in the accompanying drawings may be implemented as a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, or any appropriate combination thereof for performing the functions described in this application. One or more of the functional blocks and / or one or more combinations of functional blocks described in the accompanying drawings may 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.

[0171] The present application has been described above in conjunction with specific embodiments. However, those skilled in the art should understand that these descriptions are merely illustrative and are not intended to limit the scope of protection of the present application. Those skilled in the art may make various modifications and variations to the present application based on the spirit and principles of the present application, and such modifications and variations are also within the scope of the present application.

[0172] Regarding the implementation methods including the above embodiments, the following additional notes are also disclosed:

[0173] 1. A beam management configuration method, comprising:

[0174] The terminal device receives configuration information from the network device;

[0175] The configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model.

[0176] 2. A beam management configuration method, comprising:

[0177] The network device sends configuration information to the terminal device;

[0178] The configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functionality / model.

[0179] 3. A terminal device comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the computer program to implement the beam management configuration method as described in Note 1.

[0180] 4. A network device comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the computer program to implement the beam management configuration method as described in Note 2.

Claims

1. A beam management configuration device, comprising: A receiving unit that receives configuration information from a network device; Wherein, the configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functions / models.

2. The device according to claim 1, wherein, The spatial beam prediction is configured in the terminal device and the temporal beam prediction is configured in the network device; and / or, The spatial beam prediction is configured in the network device and the temporal beam prediction is configured in the terminal device; and / or, The spatial beam prediction is configured in the terminal device and the temporal beam prediction is configured in the terminal device; and / or, The spatial beam prediction is configured in the network device and the temporal beam prediction is configured in the network device.

3. The device according to claim 1, wherein A second set of reference signals for measurement and a first set of reference signals for prediction are respectively configured for the temporal beam prediction and the spatial beam prediction; Wherein, the temporal beam prediction and the spatial beam prediction are respectively configured, or, the temporal beam prediction and the spatial beam prediction are configured together.

4. The apparatus according to claim 1, wherein, For the temporal beam prediction and the spatial beam prediction, the second set of reference signals for measurement and / or the first set of reference signals for prediction are shared by the temporal beam prediction and the spatial beam prediction.

5. The apparatus according to claim 1, wherein Respective reports are configured for the temporal beam prediction and the spatial beam prediction, or, the same report is configured for the temporal beam prediction and the spatial beam prediction.

6. The apparatus according to claim 1, wherein, For the temporal beam prediction and the spatial beam prediction, if the temporal beam prediction is configured in the terminal device, beam reports for multiple time instances are also configured for the terminal device.

7. The apparatus according to claim 1, wherein Respective performance monitoring is configured for the temporal beam prediction and the spatial beam prediction.

8. The device according to claim 1, wherein Shared performance monitoring is configured for the temporal beam prediction and the spatial beam prediction.

9. The device according to claim 8, wherein, If the spatial beam prediction is configured in the terminal device and the temporal beam prediction is configured in the terminal device, a shared performance monitoring process is configured for the temporal beam prediction and the spatial beam prediction; and / or, if the spatial beam prediction is configured in the network device and the temporal beam prediction is configured in the network device, a shared performance monitoring process is configured for the temporal beam prediction and the spatial beam prediction.

10. The device according to claim 1, wherein, For the temporal beam prediction and the spatial beam prediction, the performance monitoring process is configured in the terminal device, or, the performance monitoring process is configured in the network device, or, the performance monitoring process is configured in the network device and the terminal device.

11. A beam management configuration device, comprising: A sending unit that sends configuration information to a terminal device; Wherein, the configuration information is used for spatial beam prediction and temporal beam prediction based on AI / ML functions / models.

12. The device according to claim 11, wherein, The spatial beam prediction is configured in the terminal device and the temporal beam prediction is configured in the network device; and / or, The spatial beam prediction is configured in the network device and the temporal beam prediction is configured in the terminal device; and / or, The spatial beam prediction is configured in the terminal device and the temporal beam prediction is configured in the terminal device; and / or, The spatial beam prediction is configured in the network device and the temporal beam prediction is configured in the network device.

13. The apparatus according to claim 11, wherein, A second reference signal set for measurement and a first reference signal set for prediction are respectively configured for the temporal beam prediction and the spatial beam prediction; wherein, the temporal beam prediction and the spatial beam prediction are respectively configured, or, the temporal beam prediction and the spatial beam prediction are configured together.

14. The apparatus according to claim 11, wherein For the temporal beam prediction and the spatial beam prediction, the second reference signal set for measurement and / or the first reference signal set for prediction are shared by the temporal beam prediction and the spatial beam prediction.

15. The apparatus according to claim 11, wherein, Respective reports are configured for the temporal beam prediction and the spatial beam prediction, or, the same report is configured for the temporal beam prediction and the spatial beam prediction; For the temporal beam prediction and the spatial beam prediction, if the temporal beam prediction is configured in the terminal device, beam reports for multiple time instances are also configured for the terminal device.

16. The device according to claim 11, wherein, Respective performance monitors are configured for the temporal beam prediction and the spatial beam prediction.

17. The apparatus according to claim 11, wherein, A shared performance monitor is configured for the temporal beam prediction and the spatial beam prediction.

18. The apparatus according to claim 17, wherein, If the spatial beam prediction is configured in the terminal device and the temporal beam prediction is configured in the terminal device, a shared performance monitoring process is configured for the temporal beam prediction and the spatial beam prediction; and / or, if the spatial beam prediction is configured in the network device and the temporal beam prediction is configured in the network device, a shared performance monitoring process is configured for the temporal beam prediction and the spatial beam prediction.

19. The device according to claim 11, wherein, For the temporal beam prediction and the spatial beam prediction, the performance monitoring process is configured in the terminal device, or, the performance monitoring process is configured in the network device, or, the performance monitoring process is configured in the network device and the terminal device.

20. A communication system, comprising: A network device that sends configuration information to a terminal device; A terminal device that receives the configuration information, wherein the configuration information is used for spatial beam prediction and temporal beam prediction based on an AI / ML function / model.

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