Beam failure recovery method and apparatus

Abstract

Provided in the embodiments of the present application are a beam failure recovery (BFR) method and apparatus. The method comprises: a terminal device receiving BFR configuration information from a network device; and the terminal device performing BFR on the basis of the BFR configuration information, wherein a candidate beam for BFR is determined on the basis of an AI / ML functionality / model.

Description

Beam failure recovery 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 leverage AI / ML functionality / models to predict future beams based on beam measurement results. However, there is currently no clear solution for configuring and instructing beam failure recovery.

[0007] To address at least one of the above problems, embodiments of the present application provide a beam failure recovery method and apparatus.

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

[0009] The terminal device receives beam failure recovery (BFR) configuration information from the network device;

[0010] The terminal device performs beam failure recovery according to the beam failure recovery (BFR) configuration information; wherein the candidate beams for beam failure recovery are determined based on AI / ML functionality / model.

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

[0012] a receiving unit configured to receive beam failure recovery (BFR) configuration information from a network device;

[0013] A processing unit is configured to perform beam failure recovery (BFR) according to the beam failure recovery (BFR) configuration information; wherein candidate beams for the beam failure recovery are determined based on AI / ML functionality / model.

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

[0015] The network device sends beam failure recovery (BFR) configuration information to the terminal device;

[0016] The terminal device performs beam failure recovery according to the beam failure recovery (BFR) configuration information; wherein the candidate beams for beam failure recovery are determined based on AI / ML functionality / model.

[0017] According to one aspect of an embodiment of the present application, a beam failure recovery device is provided, including:

[0018] a sending unit, configured to send beam failure recovery (BFR) configuration information to a terminal device;

[0019] The terminal device performs beam failure recovery according to the beam failure recovery (BFR) configuration information; wherein the candidate beams for beam failure recovery are determined based on AI / ML functionality / model.

[0020] One of the beneficial effects of the embodiments of the present application is that candidate beams for beam failure recovery are determined based on AI / ML functionality / model, and the terminal device can perform AI / ML-based beam failure recovery, thereby improving the accuracy and reliability of beam failure recovery.

[0021] 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.

[0022] 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.

[0023] 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

[0024] 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.

[0025] FIG1 is a schematic diagram of a communication system according to an embodiment of the present application;

[0026] FIG2 is a schematic diagram of a beam failure recovery method according to an embodiment of the present application;

[0027] FIG3 is a schematic diagram of AI / ML according to an embodiment of the present application;

[0028] FIG4 is another schematic diagram of a beam failure recovery method according to an embodiment of the present application;

[0029] FIG5 is another schematic diagram of a beam failure recovery method according to an embodiment of the present application;

[0030] FIG6 is a schematic diagram of a beam failure recovery device according to an embodiment of the present application;

[0031] FIG7 is another schematic diagram of a beam failure recovery device according to an embodiment of the present application;

[0032] FIG8 is a schematic diagram of a terminal device according to an embodiment of the present application;

[0033] FIG9 is a schematic diagram of a network device according to an embodiment of the present application. DETAILED DESCRIPTION

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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.

[0044] 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.

[0045] The following describes the scenarios of the embodiments of the present application through examples, but the present application is not limited thereto.

[0046] 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.

[0047] 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.

[0048] 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.

[0049] 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, 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.

[0050] In NR Rel-15, beam failure recovery operations were introduced. Beam failure recovery operations include beam failure detection, new candidate beam identification, and a beam failure recovery request. For new candidate beam identification, the gNB can configure a candidate beam list for the UE. When a beam failure occurs, the UE selects a candidate beam for communication, and the new beam information is sent to the gNB via a dedicated physical random access channel (PRACH).

[0051] In NR Rel-16, beam failure recovery is extended to secondary cells (SCells). That is, if a beam failure occurs on an SCell, communication through the primary cell (PCell) can be maintained. In this case, new beam information can be sent via MAC-CE on the PCell.

[0052] In an embodiment 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 model may be used for various signal processing functions of wireless communications, such as CSI prediction, CSI compression, beam prediction, positioning management, and the like; the present application is not limited thereto. Hereinafter, the beam predicted (inferred) or selected by the AI / ML model is referred to as a candidate beam or a new beam; the present application is not limited thereto, and the terms "inference" and "prediction" are interchangeable, and the terms "candidate beam" and "new beam" are interchangeable.

[0053] Embodiments of the first aspect

[0054] An embodiment of the present application provides a beam failure recovery method, which is described from the perspective of a network device.

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

[0056] 201, the terminal device receives beam failure recovery (BFR) configuration information from the network device; and

[0057] 202. The terminal device performs beam failure recovery according to beam failure recovery (BFR) configuration information; wherein candidate beams for beam failure recovery are determined 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, beam failure recovery (BFR) configuration information may include configuration information of one or more reference signals used for beam failure recovery, such as a CSI-RS list for BFR. In addition, the terminal device may also be configured with information for beam management, which may include information of one or more reference signals used for beam management or beam measurement, such as CSI-RS configuration information. The present application is not limited thereto, and reference may be made to related technologies for specific configuration information.

[0063] In some embodiments, the AI / ML functionality / model used to determine candidate beams can be the same as the AI / ML functionality / model used for beam management. For example, a single AI / ML can be used for both beam management and for determining (identifying) candidate beams for beam failure recovery.

[0064] In other embodiments, the AI / ML functionality / model used to determine candidate beams may be different from the AI / ML functionality / model used for beam management. For example, two AI / MLs may be used: one for beam management and another for determining (identifying) candidate beams for beam failure recovery.

[0065] Figure 3 is a schematic diagram of AI / ML in an embodiment of the present application, which can be used for both beam management and BFR, for example. As shown in Figure 3, one or more reference signals in the second reference signal resource set (set B) can be received and measured by a terminal device, and the measurement results can be used as input for AI / ML. One or more reference signals in the first reference signal resource set (set A) can be used by the terminal device for output of AI / ML, for example, the measurement results can be used as label data or ground truth data for AI / ML. For the specific content of AI / ML and set A and set B, please refer to the relevant technology and will not be repeated here.

[0066] In some embodiments, the AI / ML functionality / model is located on the terminal device side, which may be referred to as a UE-side model. The present application is not limited thereto and may also be applicable to network-side models or hybrid models.

[0067] In some embodiments, when a beam failure occurs, the terminal device sends a beam failure recovery request and / or candidate beam information to the network device. The following description takes the beam failure of the primary cell (PCell) as an example, but the present application is not limited thereto. For example, it can also be applied to the case where a beam failure occurs in the secondary cell (SCell).

[0068] FIG4 is another schematic diagram of a beam failure recovery method according to an embodiment of the present application. As shown in FIG4 , the method includes:

[0069] 401, the network device sends a periodic reference signal for beam failure detection;

[0070] 402: The terminal device detects a beam failure.

[0071] 403. The terminal device performs inference based on AI / ML functionality / model to select a candidate beam.

[0072] 404. The terminal device sends a beam failure recovery request and / or candidate beam information to the network device.

[0073] 405. The terminal device receives confirmation information from the network device.

[0074] It is worth noting that FIG4 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 FIG4 above.

[0075] In some embodiments, the beam failure recovery request and / or the candidate beam information is sent via a physical uplink control channel (PUCCH) resource.

[0076] For example, for beam failure recovery operations (e.g., BFR on PCell), the UE can identify candidate beams through UE-side AI / ML functions / models. After a beam failure occurs, the UE can send a beam failure recovery request to the gNB, indicating the beam failure and also indicating candidate beam information, such as which beam (SSB or CSI-RS) has been identified as a candidate beam. The beam failure recovery request and candidate beam information can be conveyed via the PUCCH. In one example, a candidate beam can be selected from set A.

[0077] Therefore, the transmission of candidate beam information through PUCCH will not be affected by the limited dedicated PRACH resources, thereby realizing AI / ML-based BFR operation.

[0078] In some embodiments, the terminal device is configured with multiple PUCCH resources for sending the beam failure recovery request and / or the candidate beam information; each PUCCH resource is associated with an SSB / CSI-RS, and the time-frequency domain resources of the PUCCH resources are pre-configured.

[0079] For example, multiple PUCCH resources can be configured for the UE to send beam failure recovery requests and / or candidate beam information. Each PUCCH resource is associated with an SSB / CSI-RS (the associated SSB / CSI-RS can be included in set A). The time-frequency resources of the PUCCH resources can be pre-configured. In addition, the existing UCI type / PUCCH format can be reused, or a new UCI type / PUCCCH format can be introduced. In one example, the PUCCH resource can be SR-like.

[0080] In some embodiments, the terminal device is configured with a PUCCH resource for sending the beam failure recovery request and / or the candidate beam information; the one PUCCH resource is associated with an SSB / CSI-RS, and the time-frequency domain resources of the PUCCH resource are pre-configured.

[0081] For example, a PUCCH resource can be configured for the UE to transmit a beam failure recovery request and / or candidate beam information. The time-frequency resource of the PUCCH resource can be associated with an SSB / CSI-RS (the associated SSB / CSI-RS can be included in set A). For example, possible time-frequency resource occupancy patterns can be predefined. In addition, existing UCI type / PUCCH format can be reused, or a new UCI type / PUCCCH format can be introduced.

[0082] In some embodiments, the terminal device is configured with multiple PUCCH resources for sending the beam failure recovery request and / or the candidate beam information; each PUCCH resource can carry N bits and is associated with multiple SSB / CSI-RS, the N bits indicate that one SSB / CSI-RS among the multiple SSB / CSI-RS is the candidate beam, and the time-frequency domain resources of the PUCCH resources are pre-configured.

[0083] For example, multiple PUCCH resources can be configured to the UE for sending beam failure recovery requests and / or candidate beam information. Each PUCCH resource can transmit N bits of information, and each PUCCH resource can be associated with multiple (e.g., 2 N The N bits of information carried by the PUCCH resource can further indicate which SSB / CSI-RS is the candidate beam. The time-frequency resources of the PUCCH resource can be pre-configured. In addition, the existing UCI type / PUCCH format can be reused, or a new UCI type / PUCCCH format can be introduced.

[0084] In some embodiments, the terminal device is configured with a PUCCH resource for sending the beam failure recovery request and / or the candidate beam information; the one PUCCH resource can carry N bits and be associated with multiple SSB / CSI-RS, the N bits indicate that one SSB / CSI-RS among the multiple SSB / CSI-RS is the candidate beam, and the time-frequency domain resources of the PUCCH resource are pre-configured.

[0085] For example, a PUCCH resource can be configured to the UE to send a beam failure recovery request and / or candidate beam information. The PUCCH resource can transmit N bits of information. The time-frequency resources occupied by the PUCCH resource can be combined with multiple (e.g., 2 N The N bits of information carried by the PUCCH resource can further indicate which SSB / CSI-RS is the candidate beam. Possible time-frequency resource occupancy patterns can be predefined. In addition, the existing UCI type / PUCCH format can be reused, or a new UCI type / PUCCCH format can be introduced.

[0086] In some embodiments, the beam failure recovery request and / or the candidate beam information is sent via a dedicated physical random access channel (PRACH) resource.

[0087] For example, for beam failure recovery operations (e.g., BFR on PCell), the UE can identify candidate beams via UE-side AI / ML functions / models. After a beam failure occurs, the UE can send a beam failure recovery request to the gNB, indicating that a beam failure has occurred and also indicating candidate beam information, such as which beam (SSB or CSI-RS) has been identified as a candidate beam. The beam failure recovery request and candidate beam information can be delivered via a dedicated PRACH. In one example, the candidate beam can be selected from set A beams.

[0088] In some embodiments, one dedicated PRACH resource is associated with one SSB / CSI-RS; wherein the number of the dedicated PRACH resources is greater than a predetermined value.

[0089] For example, one dedicated PRACH resource is associated with one SSB / CSI-RS. The number of dedicated PRACH resources can be expanded. For example, more PRACH resources / preambles can be introduced.

[0090] In some embodiments, one dedicated PRACH resource is associated with multiple SSB / CSI-RS.

[0091] For example, a dedicated PRACH resource can be associated with multiple SSB / CSI-RS, such as a group of SSB / CSI / RS. In one example, when transmitting a dedicated PRACH, the PRACH resource can be targeted to the identified new beam. In another example, when transmitting a dedicated PRACH, the PRACH resource can be oriented toward all associated SSB / CSI-RS, and the gNB can select one as the new beam for subsequent communications.

[0092] In some embodiments, the candidate beam is selected from a candidate reference signal list (candidate RS list); a dedicated PRACH resource is associated with an SSB / CSI-RS from the candidate reference signal list.

[0093] In some embodiments, the beams in the candidate reference signal list can be dynamically changed according to the currently active beam, and the mapping mode between the beams in the candidate reference signal list and the currently active beam is predefined or configured.

[0094] For example, a candidate beam can be selected from a candidate RS list (the beams of the candidate RS list can be included in set A). The beams of the candidate RS list can change dynamically with the current active beam (current active TCI state). The mapping pattern between the beams of the candidate RS list and the current active beam can be predefined or configured. In this case, one dedicated PRACH resource can be associated with one SSB / CSI-RS (the associated SSB / CSI-RS is from the candidate RS list).

[0095] In some embodiments, the beam failure recovery request is sent via 2-step random access (2-step RA), and / or the candidate beam information is sent via a physical uplink shared channel (PUSCH) resource.

[0096] For example, for beam failure recovery operations (e.g., BFR on PCell), the UE can identify candidate beams via UE-side AI / ML functions / models. After a beam failure occurs, the UE can send a beam failure recovery request to the gNB, indicating that a beam failure has occurred and also indicating candidate beam information, such as which beam (SSB or CSI-RS) has been identified as a candidate beam. The beam failure recovery request can be delivered via a two-step PRACH, and the candidate beam information can be delivered via a PUSCH message (i.e., Msg A). In one example, a candidate beam can be selected from set A.

[0097] In some embodiments, the beam failure recovery request and / or the candidate beam information is sent via contention-based random access (CBRA).

[0098] For example, for beam failure recovery operations (e.g., BFR on the PCell), the UE can identify candidate beams via the UE-side AI / ML function / model. After a beam failure occurs, the UE can send a beam failure recovery request to the gNB, indicating that a beam failure has occurred and also indicating candidate beam information, such as which beam (SSB or CSI-RS) has been identified as a candidate beam. The beam failure recovery request and candidate beam information can be conveyed via contention-based PRACH. In one example, a candidate beam can be selected from set A.

[0099] In some embodiments, a second set of reference signals (set B) for beam management measurements is used as input to the AI / ML functionality / model to select the candidate beams.

[0100] For example, for beam failure recovery operations with AI / ML functions / models on the UE side (e.g., BFR on PCell), set B is used as the input of the AI / ML function / model for inference to select candidate beams. In the first example, the beams in the candidate RS list are used as the output of the AI / ML function / model. In the other example, the beams in set A are used as the output of the AI / ML function / model.

[0101] For another example, the beams in the candidate reference signal list can be configured to be the same as those in set B. Alternatively, the reference signals in set B can be configured to be periodic. Alternatively, if the reference signals in set B are configured to be periodic, the periodic reference signals in set B are configured / processed as candidate reference signals. Alternatively, the periodic reference signals in set B are reused for beam management.

[0102] In some examples, after each transmission of set B or candidate reference signals, the UE performs measurements and inference on set B. After a beam failure occurs, the UE can use the latest measurement and inference results of set B before the beam failure to predict / select candidate beams.

[0103] In other examples, after each set B transmission or candidate reference signal transmission, if no beam failure occurs, the UE measures the reference signals of set B but does not perform inference. After a beam failure occurs, the UE can perform inference using the latest set B measurement results before the beam failure to predict / select a candidate beam.

[0104] In some embodiments, reference signals in a candidate RS list are used as input to the AI / ML functionality / model to select the candidate beams.

[0105] For example, for beam failure recovery operations with AI / ML functions / models on the UE side (e.g., BFR on PCell), the candidate RS list is used as input to the AI / ML functions / models for reasoning to select candidate beams. In one example, candidate beams are selected from set A.

[0106] For another example, the beams in the candidate reference signal list may be configured to be different from set B. For example, the beams in the candidate reference signal list may be configured as a subset of set B. For another example, the beams in the candidate reference signal list may be configured to be the same as set B. Alternatively, if the reference signals in set B are configured to be periodic, the periodic reference signals in set B are configured / processed as candidate reference signals.

[0107] In some examples, after candidate reference signals are transmitted, the UE performs measurements and inference on the candidate reference signal list. After a beam failure occurs, the UE can use the most recent inference results before the beam failure to predict / select a candidate beam.

[0108] In other examples, after candidate reference signal transmission, if beam failure does not occur, the UE measures reference signals in the candidate reference signal list but does not perform inference. After beam failure occurs, the UE can perform inference using the most recent measurement results before the beam failure to predict / select a candidate beam.

[0109] The embodiments of the present application can be applied to the terminal device side model (UE-side model) or the network device side model (gNB-side model), but the present application is not limited thereto. In addition, the AI / ML of the embodiments of the present application can be used for beam management, such as time beam prediction and / or spatial beam prediction. In addition, the embodiments of the present application can also be applied to SR-based beam failure recovery operations in multi-TRP scenarios (including single-DCI multi-TRP and multi-DCI multi-TRP), but the present application is not limited thereto.

[0110] 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.

[0111] It can be seen from the above embodiments that the candidate beams for beam failure recovery are determined based on the AI / ML functionality / model, and the terminal device can perform AI / ML-based beam failure recovery, thereby improving the accuracy and reliability of beam failure recovery.

[0112] Embodiments of the second aspect

[0113] The embodiment of the present application provides a beam failure recovery 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.

[0114] FIG5 is a schematic diagram of a beam failure recovery method according to an embodiment of the present application. As shown in FIG5 , the method includes:

[0115] 501. The network device sends beam failure recovery (BFR) configuration information to the terminal device.

[0116] As shown in FIG5 , the method may further include:

[0117] 502. The terminal device performs beam failure recovery according to the beam failure recovery (BFR) configuration information; wherein the candidate beams for the beam failure recovery are determined based on AI / ML functionality / model.

[0118] It is worth noting that FIG5 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 FIG5 above.

[0119] 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.

[0120] It can be seen from the above embodiments that the candidate beams for beam failure recovery are determined based on the AI / ML functionality / model, and the terminal device can perform AI / ML-based beam failure recovery, thereby improving the accuracy and reliability of beam failure recovery.

[0121] Embodiments of the third aspect

[0122] The embodiment of the present application provides a beam failure recovery device, which can be, for example, a terminal device, or one or more components or assemblies configured in the terminal device, and the same contents as those in the first and second aspects of the embodiment are not repeated here.

[0123] FIG6 is a schematic diagram of a beam failure recovery device according to an embodiment of the present application. As shown in FIG6 , the beam failure recovery device 600 according to the embodiment of the present application includes:

[0124] a receiving unit 601 configured to receive beam failure recovery (BFR) configuration information from a network device;

[0125] The processing unit 602 performs beam failure recovery according to the beam failure recovery (BFR) configuration information; wherein candidate beams for beam failure recovery are determined based on AI / ML functionality / model.

[0126] In some embodiments, as shown in FIG6 , the beam failure recovery apparatus 600 may further include:

[0127] The sending unit 603 sends a beam failure recovery request and / or candidate beam information to the network device when a beam failure occurs.

[0128] In some embodiments, the beam failure recovery request and / or the candidate beam information is sent via a physical uplink control channel (PUCCH) resource.

[0129] In some embodiments, the terminal device is configured with multiple PUCCH resources for sending the beam failure recovery request and / or the candidate beam information; each PUCCH resource is associated with an SSB / CSI-RS, and the time-frequency domain resources of the PUCCH resources are pre-configured.

[0130] In some embodiments, the terminal device is configured with a PUCCH resource for sending the beam failure recovery request and / or the candidate beam information; the one PUCCH resource is associated with an SSB / CSI-RS, and the time-frequency domain resources of the PUCCH resource are pre-configured.

[0131] In some embodiments, the terminal device is configured with multiple PUCCH resources for sending the beam failure recovery request and / or the candidate beam information; each PUCCH resource can carry N bits and is associated with multiple SSB / CSI-RS, the N bits indicate that one SSB / CSI-RS among the multiple SSB / CSI-RS is the candidate beam, and the time-frequency domain resources of the PUCCH resources are pre-configured.

[0132] In some embodiments, the terminal device is configured with a PUCCH resource for sending the beam failure recovery request and / or the candidate beam information; the one PUCCH resource can carry N bits and be associated with multiple SSB / CSI-RS, the N bits indicate that one SSB / CSI-RS among the multiple SSB / CSI-RS is the candidate beam, and the time-frequency domain resources of the PUCCH resource are pre-configured.

[0133] In some embodiments, the beam failure recovery request and / or the candidate beam information is sent via a dedicated physical random access channel (PRACH) resource.

[0134] In some embodiments, one dedicated PRACH resource is associated with one SSB / CSI-RS; wherein the number of the dedicated PRACH resources is greater than a predetermined value.

[0135] In some embodiments, one dedicated PRACH resource is associated with multiple SSB / CSI-RS.

[0136] In some embodiments, the candidate beam is selected from a candidate reference signal list (candidate RS list); a dedicated PRACH resource is associated with an SSB / CSI-RS from the candidate reference signal list.

[0137] In some embodiments, the beams in the candidate reference signal list can be dynamically changed according to the currently active beam, and the mapping mode between the beams in the candidate reference signal list and the currently active beam is predefined or configured.

[0138] In some embodiments, the beam failure recovery request is sent via a 2-step random access, and / or the candidate beam information is sent via a physical uplink shared channel (PUSCH) resource.

[0139] In some embodiments, the candidate beams are selected from a first set of reference signals (set A) for beam management prediction.

[0140] In some embodiments, the beam failure recovery request and / or the candidate beam information is sent via contention-based random access (CBRA).

[0141] In some embodiments, the candidate beams are selected from a first set of reference signals (set A) for beam management prediction.

[0142] In some embodiments, a second set of reference signals (set B) for beam management measurements is used as input to the AI / ML functionality / model to select the candidate beams.

[0143] In some embodiments, reference signals in a candidate RS list are used as input to the AI / ML functionality / model to select the candidate beams.

[0144] 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.

[0145] 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 failure recovery 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.

[0146] 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.

[0147] It can be seen from the above embodiments that the candidate beams for beam failure recovery are determined based on the AI / ML functionality / model, and the terminal device can perform AI / ML-based beam failure recovery, thereby improving the accuracy and reliability of beam failure recovery.

[0148] Embodiments of the fourth aspect

[0149] The embodiment of the present application provides a beam failure recovery device. The device may 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.

[0150] FIG7 is another schematic diagram of a beam failure recovery device according to an embodiment of the present application. As shown in FIG7 , a beam failure recovery device 700 includes:

[0151] a sending unit 701, which sends beam failure recovery (BFR) configuration information to a terminal device;

[0152] The terminal device performs beam failure recovery according to the beam failure recovery (BFR) configuration information; wherein the candidate beams for beam failure recovery are determined based on AI / ML functionality / model.

[0153] In some embodiments, as shown in FIG7 , the beam failure recovery apparatus 700 may further include:

[0154] The receiving unit 702 receives data / information fed back by the terminal device.

[0155] 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.

[0156] 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 failure recovery device 700 may also include other components or modules. For the specific contents of these components or modules, reference may be made to the relevant art.

[0157] In addition, for the sake of simplicity, FIG7 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.

[0158] It can be seen from the above embodiments that the candidate beams for beam failure recovery are determined based on the AI / ML functionality / model, and the terminal device can perform AI / ML-based beam failure recovery, thereby improving the accuracy and reliability of beam failure recovery.

[0159] Embodiments of the fifth aspect

[0160] 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.

[0161] In some embodiments, the communication system 100 may include at least:

[0162] a network device that sends beam failure recovery (BFR) configuration information to a terminal device;

[0163] A terminal device performs beam failure recovery according to the beam failure recovery (BFR) configuration information; wherein candidate beams for the beam failure recovery are determined based on AI / ML functionality / model.

[0164] 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.

[0165] Figure 8 is a schematic diagram of a terminal device according to an embodiment of the present application. As shown in Figure 8 , terminal device 800 may include a processor 810 and a memory 820. Memory 820 stores data and programs and is coupled to processor 810. 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.

[0166] For example, the processor 810 may be configured to execute a program to implement the beam failure recovery method according to the embodiment of the first aspect. For example, the processor 810 may be configured to perform the following control: receiving beam failure recovery (BFR) configuration information from a network device; performing beam failure recovery according to the BFR configuration information; wherein candidate beams for beam failure recovery are determined based on AI / ML functionality / model.

[0167] As shown in Figure 8 , the terminal device 800 may further include: a communication module 830, an input unit 840, a display 850, and a power supply 860. 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 800 does not necessarily include all of the components shown in Figure 8 , and these components are not essential. Furthermore, the terminal device 800 may also include components not shown in Figure 8 , for which reference may be made to the prior art.

[0168] 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.

[0169] Figure 9 is a schematic diagram illustrating the structure of a network device according to an embodiment of the present application. As shown in Figure 9 , network device 900 may include a processor 910 (e.g., a central processing unit (CPU)) and a memory 920 ; the memory 920 is coupled to the processor 910 . The memory 920 may store various data and may also store an information processing program 930 , which is executed under the control of the processor 910 .

[0170] For example, the processor 910 may be configured to execute a program to implement the beam failure recovery method as described in the embodiment of the second aspect. For example, the processor 910 may be configured to perform the following control: sending beam failure recovery (BFR) configuration information to a terminal device; wherein the terminal device performs beam failure recovery according to the beam failure recovery (BFR) configuration information; wherein the candidate beams for beam failure recovery are determined based on AI / ML functionality / model.

[0171] In addition, as shown in Figure 9, network device 900 may further include: a transceiver 940 and an antenna 950; wherein, the functions of these components are similar to those in the prior art and are not further described here. It is worth noting that network device 900 does not necessarily include all the components shown in Figure 9; in addition, network device 900 may also include components not shown in Figure 9, and reference may be made to the prior art for details.

[0172] An embodiment of the present application also provides a computer program, wherein when the program is executed in a terminal device, the program causes the terminal device to execute the beam failure recovery method described in the embodiment of the first aspect.

[0173] 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 failure recovery method described in the embodiment of the first aspect.

[0174] An embodiment of the present application also provides a computer program, wherein when the program is executed in a network device, the program causes the network device to execute the beam failure recovery method described in the embodiment of the second aspect.

[0175] 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 failure recovery method described in the embodiment of the second aspect.

[0176] 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.

[0177] 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).

[0178] 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.

[0179] 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.

[0180] 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.

[0181] Regarding the implementation methods including the above embodiments, the following additional notes are also disclosed:

[0182] 1. A beam failure recovery method, comprising:

[0183] The terminal device receives beam failure recovery (BFR) configuration information from the network device;

[0184] The terminal device performs beam failure recovery according to the beam failure recovery (BFR) configuration information; wherein the candidate beams for beam failure recovery are determined based on AI / ML functionality / model.

[0185] 2. A beam failure recovery method, comprising:

[0186] The network device sends beam failure recovery (BFR) configuration information to the terminal device;

[0187] The terminal device performs beam failure recovery according to the beam failure recovery (BFR) configuration information; wherein the candidate beams for beam failure recovery are determined based on AI / ML functionality / model.

[0188] 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 failure recovery method as described in Note 1.

[0189] 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 failure recovery method as described in Note 2.

[0190] 5. A computer program product, comprising at least a computer program, which, when executed by a processor, enables a terminal device to execute the beam failure recovery method as described in Note 1.

[0191] 6. A computer program product, comprising at least a computer program, which, when executed by a processor, enables a network device to execute the beam failure recovery method as described in Note 2.

Claims

1. A beam failure recovery device, comprising: a receiving unit configured to receive beam failure recovery configuration information from a network device; A processing unit that performs beam failure recovery according to the beam failure recovery configuration information; wherein candidate beams for beam failure recovery are determined based on an AI / ML function / model.

2. The device according to claim 1, wherein The device further comprises: A sending unit, which sends a beam failure recovery request and / or candidate beam information to the network device when a beam failure occurs.

3. The device according to claim 2, wherein The beam failure recovery request and / or the candidate beam information is sent through PUCCH resources.

4. The device according to claim 3, wherein The terminal device is configured with multiple PUCCH resources for sending the beam failure recovery request and / or the candidate beam information; each PUCCH resource is associated with an SSB / CSI-RS, and the time-frequency domain resources of the PUCCH resources are pre-configured.

5. The device according to claim 3, wherein The terminal device is configured with a PUCCH resource for sending the beam failure recovery request and / or the candidate beam information; the one PUCCH resource is associated with an SSB / CSI-RS, and the time-frequency domain resources of the PUCCH resource are pre-configured.

6. The device according to claim 3, wherein The terminal device is configured with multiple PUCCH resources for sending the beam failure recovery request and / or the candidate beam information; each PUCCH resource can carry N bits and is associated with multiple SSB / CSI-RS, and the N bits indicate that one SSB / CSI-RS among the multiple SSB / CSI-RS is the candidate beam, and the time-frequency domain resources of the PUCCH resources are pre-configured.

7. The device according to claim 3, wherein The terminal device is configured with a PUCCH resource for sending the beam failure recovery request and / or the candidate beam information; the one PUCCH resource can carry N bits and be associated with multiple SSB / CSI-RSs, the N bits indicate that one SSB / CSI-RS among the multiple SSB / CSI-RSs is the candidate beam, and the time-frequency domain resources of the PUCCH resource are pre-configured.

8. The device according to claim 2, wherein The beam failure recovery request and / or the candidate beam information is sent through a dedicated PRACH resource.

9. The device according to claim 8, wherein One dedicated PRACH resource is associated with one SSB / CSI-RS; wherein the number of the dedicated PRACH resources is greater than a predetermined value.

10. The device according to claim 8, wherein One dedicated PRACH resource is associated with multiple SSB / CSI-RS.

11. The device according to claim 8, wherein The candidate beam is selected from a candidate reference signal list; a dedicated PRACH resource is associated with an SSB / CSI-RS from the candidate reference signal list.

12. The device according to claim 11, wherein The beams in the candidate reference signal list can be dynamically changed according to the current active beam, and the mapping mode between the beams in the candidate reference signal list and the current active beam is predefined or configured.

13. The device according to claim 2, wherein The beam failure recovery request is sent through 2-step random access, and / or the candidate beam information is sent through physical uplink shared channel resources.

14. The device according to claim 13, wherein The candidate beams are selected from a first set of reference signals used for beam management prediction.

15. The device according to claim 2, wherein The beam failure recovery request and / or the candidate beam information is transmitted through contention-based random access.

16. The device according to claim 15, wherein The candidate beams are selected from a first set of reference signals used for beam management prediction.

17. The device according to claim 1, wherein A second set of reference signals for beam management measurements is used as input to the AI / ML function / model to select the candidate beams.

18. The device according to claim 1, wherein The reference signals in the candidate reference signal list are used as input to the AI / ML function / model to select the candidate beams.

19. A beam failure recovery device, comprising: a sending unit, configured to send beam failure recovery configuration information to a terminal device; The terminal device performs beam failure recovery according to the beam failure recovery configuration information; wherein the candidate beam for beam failure recovery is determined based on the AI / ML function / model.

20. A communication system comprising: A network device that sends beam failure recovery configuration information to a terminal device; A terminal device performs beam failure recovery according to the beam failure recovery configuration information; wherein the candidate beams for beam failure recovery are determined based on AI / ML functions / models.

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