Accuracy requirements for user equipment based signal strength prediction

Abstract

Methods, systems, and devices for wireless communication are described. Accuracy requirements may be defined for user equipment (UE) predicted signal strength characteristics. A UE may receive an indication of a set of time-frequency resources associated with predicting one or more signal strength characteristics by the UE. The UE may predict the one or more signal strength characteristics of a beam of the set of beams relative to the set of time-frequency resources according to the accuracy requirement. The UE may transmit an indication of the predicted one or more signal strength characteristics. In some examples, the UE may receive one or more downlink reference signals via a second set of beams corresponding to a second set of time-frequency resources, and may predict the one or more signal strength characteristics based on the second set of beams, measurements of the one or more downlink reference signals, or a combination thereof.

Description

Technical Field

[0001] The following relates to wireless communications, including accuracy requirements for user equipment-based signal strength prediction. Background Art

[0002] Wireless communication systems are widely deployed to provide various types of communication content, such as voice, video, packet data, messaging, broadcast, etc. These systems may be able to support communication with multiple users by sharing available system resources (e.g., time, frequency, and power). Examples of such multiple-access systems include fourth-generation (4G) systems (such as long-term evolution (LTE) systems, advanced LTE (LTE-A) systems, or LTE-A Pro systems) and fifth-generation (5G) systems (which may be referred to as new radio (NR) systems). These systems may employ technologies such as code division multiple access (CDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), orthogonal FDMA (OFDMA), or discrete Fourier transform spread orthogonal frequency division multiplexing (DFT-S-OFDM). A wireless multiple-access communication system may include one or more network entities, each of which supports wireless communication for communication devices, which may be referred to as user equipment (UE).

[0003] In some wireless communication systems, network entities and user equipment (UE) may support beamforming technology and may communicate using one or more directional beams. To maintain reliable communication between the network entity and the UE, the network entity and the UE may perform beam management procedures. When performing beam management procedures, the UE may measure one or more reference signals corresponding to one or more beams transmitted by the network entity and report channel conditions of the one or more beams back to the network entity. Summary of the Invention

[0004] The described techniques relate to methods, systems, devices, and apparatuses that support improved accuracy requirements for user equipment (UE)-based signal strength predictions. For example, the described techniques provide for defining accuracy requirements for signal strength when a UE predicts signal strength. The UE may receive an indication of one or more resources (e.g., time-frequency resources) associated with a UE prediction of one or more signal strength characteristics, such as reference signal received power (RSRP), signal-to-interference-plus-noise ratio (SINR), etc. The UE may predict the one or more signal strength characteristics for beams in a set of beams relative to the one or more resources based on the accuracy requirements. The accuracy requirements may be defined as a tolerance range relative to a reference value for the one or more signal strength characteristics and associated with the one or more resources. In some cases, the reference value may be an ideal value, while in other cases, the reference value may be a measured value associated with one or more received reference signals. In some examples, the one or more resources may be synchronization signal block (SSB) resources or channel state information (CSI) reference signal (CSI-RS) resources, or may be virtual resources indicating beam information for the set of beams.

[0005] The UE may send an indication of one or more signal strength requirements predicted based on the accuracy requirement. In some cases, the UE may determine (e.g., and indicate) a confidence level associated with the prediction. The confidence level may be based on the accuracy requirement, one or more capabilities of the UE, the set of beams, the second set of beams, etc. Additionally, in some examples, the UE may send an indication of one or more capabilities of the UE for the accuracy requirement and based on the one or more signal strength characteristics.

[0006] A method for wireless communication at a UE is described. The method may include receiving an indication of one or more time-frequency resources associated with predicting one or more signal strength characteristics by the UE, wherein an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE; predicting the one or more signal strength characteristics for beams in a set of beams relative to the one or more time-frequency resources according to the accuracy requirement; and sending an indication of the predicted one or more signal strength characteristics according to the accuracy requirement.

[0007] An apparatus for wireless communication at a UE is described. The apparatus may include: a processor; a memory coupled to the processor; and instructions stored in the memory. The instructions may be executable by the processor to cause the apparatus to: receive an indication of one or more time-frequency resources associated with prediction of one or more signal strength characteristics by the UE, wherein an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE; predict the one or more signal strength characteristics for beams in a set of beams relative to the one or more time-frequency resources according to the accuracy requirement; and send an indication of the predicted one or more signal strength characteristics according to the accuracy requirement.

[0008] Another apparatus for wireless communication at a UE is described. The apparatus may include: means for receiving an indication of one or more time-frequency resources associated with prediction of one or more signal strength characteristics by the UE, wherein an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE; means for predicting the one or more signal strength characteristics for beams in a set of beams relative to the one or more time-frequency resources in accordance with the accuracy requirement; and means for transmitting an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement.

[0009] A non-transitory computer-readable medium storing code for wireless communication at a UE is described. The code may include instructions executable by a processor to: receive an indication of one or more time-frequency resources associated with predicting one or more signal strength characteristics by the UE, wherein an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE; predict the one or more signal strength characteristics for beams in a set of beams relative to the one or more time-frequency resources according to the accuracy requirement; and send an indication of the predicted one or more signal strength characteristics according to the accuracy requirement.

[0010] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may also include operations, features, components, or instructions for: receiving one or more downlink reference signals via a second set of beams corresponding to a second one or more time-frequency resources; and measuring the one or more downlink reference signals to obtain second one or more signal strength characteristics, wherein the predicting may be based on the second one or more signal strength characteristics.

[0011] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the accuracy requirement may be based on the second one or more signal strength characteristics, the number of values ​​of the second set of beams, the beamwidth associated with the second set of beams, the beam type associated with the second set of beams, the periodicity of the second set of beams at the UE, or a combination thereof.

[0012] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may also include operations, features, components, or instructions for sending a message indicating a confidence level associated with predicting the one or more signal strength characteristics, wherein the confidence level may be based on the accuracy requirement, one or more capabilities of the UE, the set of beams, a second set of beams different from the set of beams, or a combination thereof.

[0013] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the accuracy requirement may be based on the one or more signal strength characteristics, the numerical number of beams in the set of beams, the beamwidth of the beams, the beam type of the set of beams, the periodicity of the set of beams at the UE, or a combination thereof.

[0014] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the accuracy requirement may be based on the one or more time-frequency resources and a time duration between sending the indication.

[0015] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the accuracy requirement may be based on a reference value of the one or more signal strength characteristics, the reference value associated with the one or more time-frequency resources.

[0016] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the accuracy requirement defines a tolerance range extending above and below the reference value of the one or more signal strength characteristics, and the predicted one or more signal strength characteristics fall within the tolerance range.

[0017] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, a lower portion of the tolerance range extending below the reference value may be symmetric with respect to an upper portion of the tolerance range extending above the reference value.

[0018] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, a lower portion of the tolerance range extending below the reference value may be asymmetric relative to an upper portion of the tolerance range extending above the reference value.

[0019] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the reference value includes an ideal value of the one or more signal strength characteristics or a measured value of the one or more signal strength characteristics.

[0020] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may also include operations, features, components, or instructions for sending a capability message indicating support at the UE for a set of one or more accuracy requirements relative to the predicted signal strength characteristic.

[0021] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the support for the set of one or more accuracy requirements may be based on the one or more signal strength characteristics, the numerical number of beams in the set of beams, the beam type of the set of beams, the numerical number of a second set of beams associated with the set of beams, the beam type associated with the second set of beams, one or more signal strength characteristics associated with the second set of beams, or a combination thereof.

[0022] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the support for the set of one or more accuracy requirements may be based on a tolerance level associated with the set of one or more accuracy requirements, a confidence level associated with the set of one or more accuracy requirements, or both.

[0023] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may also include operations, features, components, or instructions for receiving a request for the capabilities message, wherein sending the capabilities message may be based on the request.

[0024] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the one or more time-frequency resources may be associated with an SSB, a CSI-RS, or a combination thereof.

[0025] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the one or more time-frequency resources include one or more virtual resources that can be associated with a beam shape of the set of beams, a beam direction of the set of beams, or a combination thereof.

[0026] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the one or more virtual resources indicate a correspondence between one or more downlink reference signals and the beam shapes of the set of beams, a correspondence between the one or more downlink reference signals and the beam directions of the set of beams, or a quasi-co-site (QCL) correspondence between the one or more downlink reference signals and the set of beams.

[0027] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the one or more signal strength characteristics include RSRP, SINR, or a combination thereof.

[0028] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the predicting may include operations, features, components, or instructions for predicting the one or more signal strength characteristics using a prediction model associated with beam management. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 An example of a wireless communication system that supports accuracy requirements for user equipment (UE) based signal strength prediction in accordance with one or more aspects of the present disclosure is illustrated.

[0030] Figure 2 An example of a beam management process supporting accuracy requirements for UE-based signal strength prediction according to one or more aspects of the present disclosure is illustrated.

[0031] 3A and 3B illustrate examples of a signal strength prediction process that supports accuracy requirements for UE-based signal strength prediction according to one or more aspects of the present disclosure.

[0032] Figure 4A 、 Figure 4B and Figure 4C An example of an accuracy requirement graph supporting accuracy requirements for UE-based signal strength prediction in accordance with one or more aspects of the present disclosure is illustrated.

[0033] Figure 5 and Figure 6 A block diagram illustrating a device supporting accuracy requirements for UE-based signal strength prediction according to one or more aspects of the present disclosure is illustrated.

[0034] Figure 7 A block diagram illustrating a communications manager that supports accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure is illustrated.

[0035] Figure 8 A diagram illustrating a system including a device that supports accuracy requirements for UE-based signal strength prediction in accordance with one or more aspects of the present disclosure is illustrated.

[0036] Figures 9 to 11 A flow chart illustrating a method of supporting accuracy requirements for UE-based signal strength prediction according to one or more aspects of the present disclosure is illustrated. DETAILED DESCRIPTION

[0037] In some wireless communication systems, such as systems supporting millimeter wave (mmW) communication (e.g., New Radio (NR) systems), wireless communication devices (e.g., network entities, transmit / receive points (TRPs), user equipment (UEs)) may communicate via directional transmissions (e.g., beams). For example, communication between wireless devices operating within the wireless communication system may be performed via beamforming. In such cases, some wireless devices (e.g., network entities and UEs) may support beamforming operations, in which antenna elements (e.g., of an antenna array) may be used to generate directional beams for transmitting or receiving communications.

[0038] To support reliable communication between wireless devices, wireless devices may perform beam management, which may refer to a collection of Layer 1 (L1) and Layer 2 (L2) procedures used to establish and maintain optimal or best available beam pairs (e.g., transmit and receive beams). Such procedures may include, for example, beam switching, beam failure recovery, and beam scanning. For example, a network entity may send one or more reference signals (e.g., channel state information (CSI) reference signals (CSI-RS), synchronization signal blocks (SSBs)) to a UE as part of beam management, such that the one or more reference signals correspond to one or more beams. The UE may measure the one or more reference signals. In some cases, the UE may generate a CSI report based on the measurements. The CSI report may include beam management information associated with one or more beams, such as signal strength characteristics (e.g., reference signal received power (RSRP), signal to interference plus noise ratio (SINR)), channel state parameters, etc. The network entity and the UE may determine the best beam or beams to use for communication based on the measurements and the CSI report. For example, upon initial access, the network entity and the UE may establish communication by selecting the best beam pair. After the connection has been established, the network entity and the UE may perform beam refinement and beam switching to switch to the best beam.

[0039] In some examples, the UE may utilize a prediction model (e.g., a machine learning algorithm, an artificial intelligence algorithm) to proactively predict the optimal one or more beams, beam events (e.g., a beam switching event, a beam failure event), or measurements or characteristics of one or more beams that the UE does not have resources (e.g., time resources, frequency resources, or processing resources) to physically measure. Using the prediction model in this manner can reduce or eliminate the overhead and latency associated with the beam management process. The prediction model can take one or more parameters (such as real-time channel measurements, past channel measurements, and side information (different from and in addition to channel measurements) or a combination of these) as input. For example, the UE may predict one or more signal strength characteristics (e.g., RSRP, SINR) of a first set of beams based on previously obtained measurements of a second set of beams or based on ideal values ​​of the one or more signal strength characteristics.

[0040] The determination and prediction of such signal strength characteristics may depend on the frequency bandwidth and time duration over which the UE calculates the signal strength characteristics. In addition, various accuracy requirements may be defined such that the UE calculates the signal strength characteristics according to the corresponding accuracy requirements. The techniques described herein support accuracy requirements for signal strength characteristics (such as RSRP, SINR, etc.) predicted by the UE. For example, the UE may predict the signal strength characteristics of a first set of one or more beams and a first set of resources (e.g., time-frequency resources) relative to a reference value associated with a first set of resources and according to a corresponding accuracy requirement. The accuracy requirement may be defined as a tolerance range in decibels (dB) relative to the reference value. In some cases, the reference value may be an ideal value of the signal strength characteristic, also referred to as a spirit value. In other cases, the reference value may be a measurement value obtained by the UE, for example, based on a reference signal received via the first set of resources. Here, the reference signal may be associated with a second set of one or more beams.

[0041] In some examples, the accuracy requirement may be based on a condition associated with a first set of one or more beams, a condition associated with a second set of one or more beams, or a combination thereof. In some cases, the UE may send a capability message (e.g., to a network entity) to indicate a set of accuracy requirements that can be achieved by the UE, for example, based on the condition and a prediction model supported by the UE. In addition, the UE may determine a confidence level associated with a given accuracy requirement, where the confidence level may indicate a likelihood that the predicted signal strength characteristic meets the accuracy requirement.

[0042] Certain aspects of the subject matter described herein may be implemented to achieve one or more potential advantages by facilitating an improved beam management process between a network entity and a UE. As a result, the network entity may more optimally select a beam for communication between the network entity and the UE. Based on the more optimal beam selection, the network entity and the UE may experience a greater likelihood of successful communication, which may result in greater system throughput, capacity, and spectral efficiency, as well as reduced signaling overhead between the network entity and the UE. In some examples, the described techniques may enable the network entity or the UE, or both, to proactively switch active beams (e.g., one or more of a transmit beam or a receive beam) in advance of a beam event (e.g., a beam failure event). In such cases, the network entity and the UE may experience reduced occurrences of beam failure recovery, as well as improved operational characteristics, such as reduced overhead signaling and reduced communication latency, among other benefits.

[0043] Various aspects of the present disclosure are first described in the context of a wireless communication system. Then, various aspects of the present disclosure are discussed with reference to a beam management process, a signal strength prediction process, and an accuracy requirement diagram. Various aspects of the present disclosure are further illustrated and described with reference to apparatus diagrams, system diagrams, and flow diagrams related to accuracy requirements for UE-based signal strength prediction.

[0044] Figure 1 An example of a wireless communication system 100 that supports accuracy requirements for UE-based signal strength prediction according to one or more aspects of the present disclosure is illustrated. The wireless communication system 100 may include one or more network entities 105, one or more UEs 115, and a core network 130. In some examples, the wireless communication system 100 may be a Long Term Evolution (LTE) network, an LTE-Advanced (LTE-A) network, an LTE-A Pro network, a New Radio (NR) network, or a network operating according to other systems and radio technologies, including future systems and radio technologies not explicitly mentioned herein.

[0045] The network entities 105 may be dispersed throughout a geographic area to form the wireless communication system 100 and may include devices in different forms or with different capabilities. In various examples, the network entities 105 may be referred to as network elements, mobility elements, radio access network (RAN) nodes, or network equipment, among other nomenclature. In some examples, the network entities 105 and the UEs 115 may communicate wirelessly via one or more communication links 125 (e.g., radio frequency (RF) access links). For example, the network entities 105 may support a coverage area 110 (e.g., a geographic coverage area) within which the UEs 115 and the network entities 105 may establish one or more communication links 125. The coverage area 110 may be an example of a geographic area within which the network entities 105 and the UEs 115 may support signal communication according to one or more radio access technologies (RATs).

[0046] The UEs 115 may be dispersed throughout the coverage area 110 of the wireless communication system 100, and each UE 115 may be stationary or mobile or both stationary and mobile at different times. The UEs 115 may be devices that take different forms or have different capabilities. Figure 1 Some example UEs 115 are illustrated in FIG. The UEs 115 described herein may be capable of supporting communication with various types of devices, such as Figure 1 105 or other UEs 115 or network entities 105 as shown.

[0047] As described herein, a node of the wireless communication system 100 (which may be referred to as a network node or wireless node) may be a network entity 105 (e.g., any network entity described herein), a UE 115 (e.g., any UE described herein), a network controller, an apparatus, a device, a computing system, one or more components, or another suitable processing entity configured to perform any of the techniques described herein. For example, the node may be a UE 115. As another example, the node may be a network entity 105. As another example, a first node may be configured to communicate with a second node or a third node. In one aspect of this example, the first node may be a UE 115, the second node may be a network entity 105, and the third node may be a UE 115. In another aspect of this example, the first node may be a UE 115, the second node may be a network entity 105, and the third node may be a network entity 105. In other aspects of this example, the first node, the second node, and the third node may be different relative to these examples. Similarly, references to UE 115, network entity 105, apparatus, device, computing system, etc. may include disclosure of UE 115, network entity 105, apparatus, device, computing system, etc. as nodes. For example, a disclosure that UE 115 is configured to receive information from network entity 105 also discloses that the first node is configured to receive information from the second node.

[0048] In some examples, network entities 105 can communicate with core network 130, with each other, or both. For example, network entities 105 can communicate with core network 130 via one or more backhaul communication links 120 (e.g., according to S1, N2, N3, or other interface protocols). In some examples, network entities 105 can communicate with each other directly (e.g., directly between network entities 105) or indirectly (e.g., via core network 130) via backhaul communication links 120 (e.g., according to X2, Xn, or other interface protocols). In some examples, network entities 105 can communicate with each other via midhaul communication links 162 (e.g., according to a midhaul interface protocol) or fronthaul communication links 168 (e.g., according to a fronthaul interface protocol), or any combination thereof. Backhaul communication links 120, midhaul communication links 162, or fronthaul communication links 168 can be or include one or more wired links (e.g., electrical links, fiber optic links), one or more wireless links (e.g., radio links, wireless optical links), etc., or various combinations thereof. UE 115 may communicate with core network 130 via communication link 155 .

[0049] One or more of the network entities 105 described herein may include or may be referred to as a base station 140 (e.g., a transceiver base station, a radio base station, an NR base station, an access point, a radio transceiver, a Node B, an eNodeB (eNB), a next-generation Node B, or a gigabit Node B (any of which may be referred to as a gNB), a 5G NB, a next-generation eNB (ng-eNB), a Home Node B, a Home eNodeB, or other suitable terminology). In some examples, the network entity 105 (e.g., a base station 140) may be implemented in a converged (e.g., monolithic, stand-alone) base station architecture that may be configured to utilize a protocol stack that is physically or logically integrated within a single network entity 105 (e.g., a single RAN node, such as the base station 140).

[0050] In some examples, the network entity 105 can be implemented in a disaggregated architecture (e.g., a disaggregated base station architecture, a disaggregated RAN architecture) that can be configured to utilize a protocol stack that is physically or logically distributed between two or more network entities 105, such as an integrated access backhaul (IAB) network, an open RAN (O-RAN) (e.g., a network configuration sponsored by the O-RAN Alliance), or a virtualized RAN (vRAN) (e.g., a cloud RAN (C-RAN)). For example, the network entity 105 can include one or more of the following: a central unit (CU) 160, a distributed unit (DU) 165, a radio unit (RU) 170, a RAN intelligent controller (RIC) 175 (e.g., a near real-time RIC (near RT RIC), a non-real-time RIC (non-RT RIC)), a service management and orchestration (SMO) 180 system, or any combination thereof. The RU 170 may also be referred to as a radio head, smart radio head, remote radio head (RRH), remote radio unit (RRU), or transmit receive point (TRP). One or more components of the network entity 105 in the disaggregated RAN architecture may be co-located, or one or more components of the network entity 105 may be located in distributed locations (e.g., separate physical locations). In some examples, one or more network entities 105 of the disaggregated RAN architecture may be implemented as virtual units (e.g., virtual CU (VCU), virtual DU (VDU), virtual RU (VRU)).

[0051] The functional split between CU 160, DU 165, and RU 170 is flexible and can support different functions depending on which functions (e.g., network layer functions, protocol layer functions, baseband functions, RF functions, and any combination thereof) are performed at CU 160, DU 165, or RU 170. For example, a functional split of the protocol stack can be employed between CU 160 and DU 165 such that CU 160 can support one or more layers of the protocol stack and DU 165 can support one or more different layers of the protocol stack. In some examples, CU 160 can host higher protocol layer (e.g., Layer 3 (L3), Layer 2 (L2)) functions and signaling (e.g., Radio Resource Control (RRC), Service Data Adaptation Protocol (SDAP), Packet Data Convergence Protocol (PDCP)). The CU 160 may be connected to one or more DUs 165 or RUs 170, and the one or more DUs 165 or RUs 170 may host lower protocol layers, such as Layer 1 (L1) (e.g., physical (PHY) layer) or L2 (e.g., radio link control (RLC) layer, medium access control (MAC) layer) functionality and signaling, and may each be at least partially controlled by the CU 160. Additionally or alternatively, a functional split of the protocol stack may be employed between the DU 165 and the RU 170, such that the DU 165 may support one or more layers of the protocol stack and the RU 170 may support one or more different layers of the protocol stack. The DU 165 may support one or more different cells (e.g., via one or more RUs 170). In some cases, the functional split between the CU 160 and the DU 165 or between the DU 165 and the RU 170 can be within the protocol layer (e.g., some functions of the protocol layer can be performed by one of the CU 160, DU 165, or RU 170, while other functions of the protocol layer are performed by a different one of the CU 160, DU 165, or RU 170). The CU 160 can be further functionally split into CU control plane (CU-CP) and CU user plane (CU-UP) functions. The CU 160 can be connected to one or more DUs 165 via midhaul communication links 162 (e.g., F1, F1-c, F1-u), and the DU 165 can be connected to one or more RUs 170 via fronthaul communication links 168 (e.g., open fronthaul (FH) interface). In some examples, midhaul communication link 162 or fronthaul communication link 168 may be implemented according to interfaces (eg, channels) between layers of a protocol stack supported by respective network entities 105 communicating via these communication links.

[0052] In some wireless communication systems (e.g., wireless communication system 100), the infrastructure and spectrum resources for radio access may support wireless backhaul link capabilities to supplement wired backhaul connections, thereby providing an IAB network architecture (e.g., to the core network 130). In some cases, in an IAB network, one or more network entities 105 (e.g., IAB nodes 104) may be partially controlled by each other. One or more IAB nodes 104 may be referred to as a donor entity or IAB donor. One or more DUs 165 or one or more RUs 170 may be partially controlled by one or more CUs 160 associated with a donor network entity 105 (e.g., a donor base station 140). One or more donor network entities 105 (e.g., IAB donors) may communicate with one or more additional network entities 105 (e.g., IAB nodes 104) via supported access and backhaul links (e.g., backhaul communication links 120). The IAB node 104 may include an IAB mobile terminal (IAB-MT) controlled (e.g., scheduled) by the DU 165 of the coupled IAB donor. The IAB-MT may include an independent set of antennas for relaying communications with the UE 115, or may share the same antennas of the IAB node 104 (e.g., RU 170) for access via the DU 165 of the IAB node 104 (e.g., referred to as a virtual IAB-MT (vIAB-MT)). In some examples, the IAB node 104 may include a DU 165 that supports communication links with additional entities (e.g., IAB node 104, UE 115) within a relay chain or configuration (e.g., downstream) of the access network. In such cases, one or more components of the decomposed RAN architecture (e.g., one or more IAB nodes 104 or components of the IAB node 104) may be configured to operate according to the techniques described herein.

[0053] For example, an access network (AN) or RAN may include an access node (e.g., an IAB donor), communications between the IAB node 104 and one or more UEs 115. The IAB donor may facilitate connectivity between the core network 130 and the AN (e.g., via a wired or wireless connection to the core network 130). That is, the IAB donor may refer to a RAN node that has a wired or wireless connection to the core network 130. The IAB donor may include a CU 160 and at least one DU 165 (e.g., and RU 170), in which case the CU 160 may communicate with the core network 130 via an interface (e.g., a backhaul link). The IAB donor and the IAB node 104 may communicate via an F1 interface according to a protocol that defines signaling messages (e.g., the F1AP protocol). Additionally or alternatively, CU 160 may communicate with the core network via an interface (which may be an example of part of a backhaul link) and may communicate with other CUs 160 (e.g., CUs 160 associated with alternative IAB donors) via an Xn-C interface (which may be an example of part of a backhaul link).

[0054] An IAB node 104 may refer to a RAN node that provides IAB functionality (e.g., access for UE 115, wireless self-backhaul capabilities, etc.). The DU 165 may act as a distributed scheduling node toward child nodes associated with the IAB node 104, and the IAB-MT may act as a scheduled node toward a parent node associated with the IAB node 104. That is, an IAB donor may be referred to as a parent node that communicates with one or more child nodes (e.g., the IAB donor may relay UE transmissions through one or more other IAB nodes 104). Additionally or alternatively, depending on the relay chain or configuration of the AN, the IAB node 104 may also be referred to as a parent node or child node of other IAB nodes 104. Thus, the IAB-MT entity of the IAB node 104 may provide a Uu interface for the child IAB node 104 to receive signaling from the parent IAB node 104, and a DU interface (e.g., DU 165) may provide a Uu interface for the parent IAB node 104 to signal to the child IAB node 104 or the UE 115.

[0055] For example, IAB node 104 may be referred to as a parent node supporting communications for child IAB nodes, or as a child IAB node associated with an IAB donor, or both. The IAB donor may include a CU 160 having a wired or wireless connection to the core network 130 (e.g., backhaul communication link 120) and may serve as a parent node for IAB node 104. For example, the DU 165 of the IAB donor may relay transmissions to UE 115 via IAB node 104, or may directly signal the transmissions to UE 115, or both. The CU 160 of the IAB donor may signal the establishment of a communication link to IAB node 104 via the F1 interface, and IAB node 104 may schedule transmissions (e.g., transmissions relayed from the IAB donor to UE 115) via the DU 165. That is, data may be relayed to and from IAB node 104 via signaling via the NR Uu interface of the MT to IAB node 104. Communications with the IAB node 104 may be scheduled by the DU 165 of the IAB donor, and communications with the IAB node 104 may be scheduled by the DU 165 of the IAB node 104 .

[0056] In the context of a disaggregated RAN architecture, one or more components of the disaggregated RAN architecture may be configured to support the accuracy requirements for user equipment-based signal strength prediction as described herein. For example, some operations described as being performed by a UE 115 or a network entity 105 (e.g., a base station 140) may additionally or alternatively be performed by one or more components of the disaggregated RAN architecture (e.g., an IAB node 104, a DU 165, a CU 160, a RU 170, a RIC 175, a SMO 180).

[0057] UE 115 may include or may be referred to as a mobile device, a wireless device, a remote device, a handheld device, or a subscriber device, or some other suitable terminology, where "device" may also be referred to as a unit, a station, a terminal, or a client, etc. UE 115 may also include or may be referred to as a personal electronic device, such as a cellular phone, a personal digital assistant (PDA), a tablet computer, a laptop computer, or a personal computer. In some examples, UE 115 may include or may be referred to as a wireless local loop (WLL) station, an Internet of Things (IoT) device, an Internet of Everything (IoE) device, or a machine type communication (MTC) device, etc., which may be implemented in various objects, such as appliances or vehicles, meters, etc.

[0058] The UE 115 described herein may be capable of communicating with various types of devices, such as other UEs 115, which may sometimes act as relays, as well as network entities 105 and network equipment including macro eNBs or gNBs, small cell eNBs or gNBs, or relay base stations, etc. Figure 1 shown.

[0059] The UE 115 and the network entity 105 may wirelessly communicate with each other via one or more communication links 125 (e.g., access links) using resources associated with one or more carriers. The term "carrier" may refer to a collection of RF spectrum resources having a physical layer structure that defines the communication link 125. For example, a carrier used for the communication link 125 may include a portion of an RF spectrum band (e.g., a bandwidth portion (BWP)) that operates according to one or more physical layer channels for a given radio access technology (e.g., LTE, LTE-A, LTE-A Pro, NR). Each physical layer channel may carry acquisition signaling (e.g., synchronization signals, system information), control signaling for coordinating carrier operation, user data, or other signaling. The wireless communication system 100 may support communications with the UE 115 using carrier aggregation or multi-carrier operation. Depending on the carrier aggregation configuration, the UE 115 may be configured with multiple downlink component carriers and one or more uplink component carriers. Carrier aggregation may be used for both frequency division duplex (FDD) and time division duplex (TDD) component carriers. Communication between the network entity 105 and other devices may refer to communication between those devices and any portion (e.g., entity, sub-entity) of the network entity 105. For example, the terms "send," "receive," or "communicate" when referring to the network entity 105 may refer to any portion of the network entity 105 (e.g., base station 140, CU 160, DU 165, RU 170) of the RAN communicating with another device (e.g., directly or via one or more other network entities 105).

[0060] In some examples, such as in a carrier aggregation configuration, a carrier may also have acquisition signaling or control signaling that coordinates the operation of other carriers. A carrier may be associated with a frequency channel (e.g., an Evolved Universal Mobile Telecommunications System Terrestrial Radio Access (E-UTRA) Absolute RF Channel Number (EARFCN)) and may be identified according to a channel raster used for discovery by UE 115. A carrier may operate in a standalone mode, in which case initial acquisition and connection by UE 115 may occur via the carrier, or a carrier may operate in a non-standalone mode, in which case a different carrier (e.g., of the same or different radio access technology) is used to anchor the connection.

[0061] The communication link 125 shown in the wireless communication system 100 may include downlink transmissions (e.g., forward link transmissions) from the network entity 105 to the UE 115, uplink transmissions (e.g., return link transmissions) from the UE 115 to the network entity 105, or both, as well as other transmission configurations. A carrier may carry downlink communications or uplink communications (e.g., in FDD mode), or may be configured to carry both downlink and uplink communications (e.g., in TDD mode).

[0062] A carrier may be associated with a particular bandwidth of RF spectrum, and in some examples, the carrier bandwidth may be referred to as the "system bandwidth" of the carrier or wireless communication system 100. For example, the carrier bandwidth may be one of a set of bandwidths of carriers for a particular radio access technology (e.g., 1.4 megahertz (MHz), 3 MHz, 5 MHz, 10 MHz, 15 MHz, 20 MHz, 40 MHz, or 80 MHz). Devices of the wireless communication system 100 (e.g., the network entity 105, the UE 115, or both) may have a hardware configuration that supports communications using a particular carrier bandwidth, or may be capable of being configured to support communications using one of a set of carrier bandwidths. In some examples, the wireless communication system 100 may include a network entity 105 or a UE 115 that supports concurrent communications using carriers associated with multiple carrier bandwidths. In some examples, each served UE 115 may be configured to operate using a portion (e.g., a subband, a BWP) or all of the carrier bandwidth.

[0063] The signal waveform transmitted via the carrier may include multiple subcarriers (e.g., using a multicarrier modulation (MCM) technique such as orthogonal frequency division multiplexing (OFDM) or discrete Fourier transform spread OFDM (DFT-S-OFDM)). In a system employing MCM techniques, a resource element may refer to the resource of one symbol period (e.g., the duration of one modulation symbol) and one subcarrier, in which case the symbol period and subcarrier spacing may be inversely related. The number of bits carried by each resource element may depend on the modulation scheme (e.g., the order of the modulation scheme, the coding rate of the modulation scheme, or both), such that a relatively high number of resource elements (e.g., in the transmission duration) and a relatively high order modulation scheme may correspond to a relatively high communication rate. Wireless communication resources may refer to a combination of RF spectrum resources, time resources, and spatial resources (e.g., spatial layers or beams), and the use of multiple spatial resources may increase the data rate or data integrity used for communication with UE 115.

[0064] One or more parameter sets for a carrier may be supported, and the parameter set may include subcarrier spacing (Δf) and cyclic prefix. A carrier may be divided into one or more BWPs with the same or different parameter sets. In some examples, a UE 115 may be configured with multiple BWPs. In some examples, a single BWP for a carrier may be active at a given time, and communications by the UE 115 may be constrained to one or more active BWPs.

[0065] The time interval for the network entity 105 or the UE 115 may be expressed as a multiple of a basic time unit, which may be, for example, a sampling period T s =1 / (Δf max ·N f ) seconds, where Δf max It can represent the supported subcarrier spacing, and N f The supported discrete Fourier transform (DFT) size may be indicated. Time intervals of communication resources may be organized according to radio frames, each having a specified duration (e.g., 10 milliseconds (ms)). Each radio frame may be identified by a system frame number (SFN) (e.g., in the range of 0 to 1023).

[0066] Each frame may include a plurality of consecutively numbered subframes or time slots, and each subframe or time slot may have the same duration. In some examples, a frame may be divided (e.g., in the time domain) into subframes, and each subframe may be further divided into a certain number of time slots. Alternatively, each frame may include a variable number of time slots, and the number of time slots may depend on the subcarrier spacing. Each time slot may include a certain number of symbol periods (e.g., depending on the length of the cyclic prefix appended in front of each symbol period). In some wireless communication systems 100, the time slot may be further divided into a plurality of mini-time slots associated with one or more symbols. Excluding the cyclic prefix, each symbol period may be associated with one or more (e.g., N f The duration of a symbol period may depend on the subcarrier spacing or the operating frequency band.

[0067] A subframe, slot, mini-slot, or symbol may be the smallest scheduling unit (e.g., in the time domain) of the wireless communication system 100 and may be referred to as a Transmit Time Interval (TTI). In some examples, the TTI duration (e.g., the number of symbol periods in a TTI) may be variable. Additionally or alternatively, the smallest scheduling unit of the wireless communication system 100 may be dynamically selected (e.g., in bursts of shortened TTIs (sTTIs)).

[0068] Physical channels may be multiplexed according to various techniques for communication using a carrier. For example, physical control channels and physical data channels may be multiplexed using one or more of time division multiplexing (TDM), frequency division multiplexing (FDM), or hybrid TDM-FDM techniques for signaling via a downlink carrier. A control region (e.g., a control resource set (CORESET)) of a physical control channel may be defined by a set of symbol periods and may extend across the system bandwidth of a carrier or a subset of that bandwidth. One or more control regions (e.g., CORESETs) may be configured for a set of UEs 115. For example, one or more of UEs 115 may monitor or search the control region for control information according to one or more search space sets, and each search space set may include one or more control channel candidates in one or more aggregation levels arranged in a cascaded manner. The aggregation level of a control channel candidate may refer to the amount of control channel resources (e.g., control channel elements (CCEs)) associated with coded information for a control information format having a given payload size. The search space sets may include a common search space set configured for transmitting control information to multiple UEs 115 and a UE-specific search space set for transmitting control information to a specific UE 115 .

[0069] The network entity 105 may provide communication coverage via one or more cells (e.g., macro cells, small cells, hotspots, or other types of cells, or any combination thereof). The term "cell" may refer to a logical communication entity used to communicate with the network entity 105 (e.g., using a carrier) and may be associated with an identifier (e.g., a physical cell identifier (PCID), a virtual cell identifier (VCID), or other identifier) ​​used to distinguish between adjacent cells. In some examples, a cell may also refer to a coverage area 110 or a portion of a coverage area 110 (e.g., a sector) within which the logical communication entity operates. Depending on various factors (such as the capabilities of the network entity 105), such cells may range from smaller areas (e.g., structures, subsets of structures) to larger areas. For example, a cell may be or may include a building, a subset of buildings, or an external space between or overlapping coverage areas 110, etc.

[0070] A macro cell generally covers a relatively large geographic area (e.g., several kilometers in radius) and may allow unrestricted access to UEs 115 that have a service subscription with a network provider that supports the macro cell. Small cells may be associated with lower-power network entities 105 (e.g., lower-power base stations 140) than macro cells, and may operate using the same or different (e.g., licensed, unlicensed) frequency bands as the macro cells. Small cells may provide unrestricted access to UEs 115 that have a service subscription with the network provider, or may provide restricted access to UEs 115 associated with the small cell (e.g., UEs 115 in a closed subscriber group (CSG), UEs 115 associated with users in a home or office). A network entity 105 may support one or more cells and may also use one or more component carriers to support communications via the one or more cells.

[0071] In some examples, a carrier may support multiple cells, and different cells may be configured according to different protocol types (e.g., MTC, narrowband IoT (NB-IoT), enhanced mobile broadband (eMBB)) that may provide access to different types of devices.

[0072] In some examples, network entities 105 (e.g., base stations 140, RUs 170) can be mobile and, therefore, provide communication coverage for mobile coverage areas 110. In some examples, different coverage areas 110 associated with different technologies can overlap, but the different coverage areas 110 can be supported by the same network entity 105. In some other examples, overlapping coverage areas 110 associated with different technologies can be supported by different network entities 105. The wireless communication system 100 can include, for example, a heterogeneous network in which different types of network entities 105 provide coverage for various coverage areas 110 using the same or different radio access technologies.

[0073] The wireless communication system 100 may support synchronous or asynchronous operation. For synchronous operation, the network entities 105 (e.g., base stations 140) may have similar frame timing, and transmissions from different network entities 105 may be approximately aligned in time. For asynchronous operation, the network entities 105 may have different frame timing, and in some examples, transmissions from different network entities 105 may not be aligned in time. The techniques described herein may be used for either synchronous or asynchronous operation.

[0074] Some UEs 115, such as MTC or IoT devices, may be low-cost or low-complexity devices and may provide automated communication between machines (e.g., via machine-to-machine (M2M) communication). M2M communication or MTC may refer to data communication technology that allows devices to communicate with each other or with a network entity 105 (e.g., base station 140) without human intervention. In some examples, M2M communication or MTC may include communication from devices that integrate sensors or meters to measure or acquire information and relay such information to a central server or application that uses the information or presents it to a person interacting with the application. Some UEs 115 may be designed to collect information or implement automated behavior of machines or other devices. Examples of applications for MTC devices include smart metering, inventory monitoring, water level monitoring, equipment monitoring, healthcare monitoring, wildlife monitoring, weather and geographic event monitoring, queue management and tracking, remote security sensing, physical access control, and transaction-based commercial charging.

[0075] Some UEs 115 may be configured to employ an operating mode that reduces power consumption, such as half-duplex communication (e.g., a mode that supports unidirectional communication via transmission or reception but does not transmit and receive concurrently). In some examples, half-duplex communication may be performed at a reduced peak rate. Other power-saving techniques for UEs 115 include entering a power-saving deep sleep mode when not engaged in active communications, operating using limited bandwidth (e.g., according to narrowband communication), or a combination of these techniques. For example, some UEs 115 may be configured to operate using a narrowband protocol type that is associated with a defined portion or range (e.g., a set of subcarriers or resource blocks (RBs)) within a carrier, within a guard band of a carrier, or outside a carrier.

[0076] The wireless communication system 100 can be configured to support ultra-reliable communication or low-latency communication or various combinations thereof. For example, the wireless communication system 100 can be configured to support ultra-reliable low-latency communication (URLLC). The UE 115 can be designed to support ultra-reliable or low-latency or critical functions. Ultra-reliable communication can include private communication or group communication and can be supported by one or more services (such as push-to-talk, video or data). Support for ultra-reliable, low-latency functions can include prioritization of services, and such services can be used for public safety or general commercial applications. The terms ultra-reliable, low-latency and ultra-reliable low-latency can be used interchangeably in this article.

[0077] In some examples, a UE 115 can be configured to support communication directly with other UEs 115 via a device-to-device (D2D) communication link 135 (e.g., according to a peer-to-peer (P2P), D2D, or sidelink protocol). In some examples, one or more UEs 115 in a group performing D2D communication can be within a coverage area 110 of a network entity 105 (e.g., a base station 140, a RU 170), which can support aspects of such D2D communication configured (e.g., scheduled) by the network entity 105. In some examples, one or more UEs 115 in such a group can be outside of the coverage area 110 of the network entity 105 or can otherwise be unable or not configured to receive transmissions from the network entity 105. In some examples, a group of UEs 115 communicating via D2D communication can support a one-to-many (1:M) system, in which each UE 115 transmits to each of the other UEs 115 in the group. In some examples, network entity 105 may facilitate scheduling of resources for D2D communications. In some other examples, D2D communications may be performed between UEs 115 without involving network entity 105.

[0078] In some systems, the D2D communication link 135 can be an example of a communication channel (such as a sidelink communication channel) between vehicles (e.g., UE 115). In some examples, the vehicles can communicate using vehicle-to-everything (V2X) communication, vehicle-to-vehicle (V2V) communication, or some combination thereof. The vehicles can signal information related to traffic conditions, signal scheduling, weather, safety, emergency situations, or any other information related to the V2X system. In some examples, the vehicles in the V2X system can communicate with roadside infrastructure (such as roadside units) or communicate with the network via one or more network nodes (e.g., network entity 105, base station 140, RU 170) using vehicle-to-network (V2N) communication, or both.

[0079] The core network 130 may provide user authentication, access authorization, tracking, Internet Protocol (IP) connectivity, and other access, routing, or mobility functions. The core network 130 may be an evolved packet core (EPC) or a 5G core (5GC), which may include at least one control plane entity (e.g., a mobility management entity (MME), an access and mobility management function (AMF)) for managing access and mobility and at least one user plane entity (e.g., a serving gateway (S-GW), a packet data network (PDN) gateway (P-GW), or a user plane function (UPF)) for routing packets or interconnecting to external networks. The control plane entities may manage non-access stratum (NAS) functions such as mobility, authentication, and bearer management for UEs 115 served by network entities 105 (e.g., base stations 140) associated with the core network 130. User IP packets may be transferred through the user plane entities, which may provide IP address allocation and other functions. The user plane entities may be connected to the IP services 150 of one or more network operators. IP services 150 may include access to the Internet, an intranet, an IP Multimedia Subsystem (IMS), or packet-switched streaming services.

[0080] The wireless communication system 100 can operate using one or more frequency bands that can range from 300 megahertz (MHz) to 300 gigahertz (GHz). Generally speaking, the region from 300 MHz to 3 GHz is referred to as the ultra-high frequency (UHF) region or decimeter band because the wavelengths range from about one decimeter to one meter in length. UHF waves may be blocked or redirected by buildings and environmental features (which may be referred to as clusters), but these waves may be sufficient to penetrate structures for macro cells to provide service to UEs 115 located indoors. Communication using UHF waves may be associated with smaller antennas and a shorter range (e.g., less than 100 kilometers) than communication using the smaller frequencies and longer wavelengths of the high frequency (HF) or very high frequency (VHF) portions of the spectrum below 300 MHz.

[0081] The wireless communication system 100 may also operate in the ultra-high frequency (SHF) region (also known as the centimeter band) using spectrum in the range of 3 GHz to 30 GHz or in the extremely high frequency (EHF) region (e.g., 30 GHz to 300 GHz) (also known as the millimeter band). In some examples, the wireless communication system 100 may support millimeter wave (mmW) communications between the UE 115 and the network entity 105 (e.g., base station 140, RU 170), and the EHF antennas of the corresponding devices may be smaller and closer together than UHF antennas. In some examples, such technology may facilitate the use of antenna arrays within the device. However, the propagation of EHF transmissions may be subject to even greater attenuation and a shorter range than SHF or UHF transmissions. The technology disclosed herein may be employed across transmissions using one or more different frequency regions, and the frequency band usage specified across these frequency regions may vary by country or regulatory agency.

[0082] The wireless communication system 100 can utilize licensed and unlicensed RF spectrum bands. For example, the wireless communication system 100 can use unlicensed bands (such as the 5 GHz Industrial, Scientific, and Medical (ISM) band) to employ license assisted access (LAA), LTE unlicensed (LTE-U) radio access technology, or NR technology. When operating using unlicensed RF spectrum bands, devices such as the network entity 105 and the UE 115 can employ carrier sensing for conflict detection and avoidance. In some examples, operations using unlicensed bands can be based on carrier aggregation configuration (e.g., LAA) in combination with component carriers operating using licensed bands. Operations performed using the unlicensed spectrum may include downlink transmissions, uplink transmissions, P2P transmissions, or D2D transmissions, among others.

[0083] A network entity 105 (e.g., a base station 140, a RU 170) or a UE 115 may be equipped with multiple antennas that can be used to employ techniques such as transmit diversity, receive diversity, multiple-input, multiple-output (MIMO) communications, or beamforming. The antennas of the network entity 105 or UE 115 may be located within one or more antenna arrays or antenna panels, which may support MIMO operations or transmit or receive beamforming. For example, one or more base station antennas or antenna arrays may be co-located at an antenna assembly, such as an antenna tower. In some examples, the antennas or antenna arrays associated with the network entity 105 may be located at different geographic locations. The network entity 105 may include an antenna array having a set of multiple rows and columns of antenna ports that the network entity 105 may use to support beamforming for communications with the UE 115. Similarly, the UE 115 may include one or more antenna arrays that may support various MIMO or beamforming operations. Additionally or alternatively, the antenna panels may support RF beamforming for signals transmitted via the antenna ports.

[0084] The network entity 105 or the UE 115 may use MIMO communication to exploit multipath signal propagation and improve spectral efficiency by sending or receiving multiple signals via different spatial layers. Such a technique may be referred to as spatial multiplexing. The multiple signals may be sent, for example, by a transmitting device via different antennas or different combinations of antennas. Similarly, the multiple signals may be received by a receiving device via different antennas or different combinations of antennas. Each of the multiple signals may be referred to as a separate spatial stream and may carry information associated with the same data stream (e.g., the same codeword) or different data streams (e.g., different codewords). Different spatial layers may be associated with different antenna ports for channel measurement and reporting. MIMO techniques include single-user MIMO (SU-MIMO), for which multiple spatial layers are sent to the same receiving device, and multi-user MIMO (MU-MIMO), for which multiple spatial layers are sent to multiple devices.

[0085] Beamforming (which may also be referred to as spatial filtering, directional transmission, or directional reception) is a signal processing technique that can be used at a transmitting device or a receiving device (e.g., a network entity 105, a UE 115) to shape or steer an antenna beam (e.g., a transmit beam, a receive beam) along a spatial path between the transmitting device and the receiving device. Beamforming can be achieved by combining signals communicated via antenna elements of an antenna array so that some signals propagating in a particular direction relative to the antenna array experience constructive interference, while other signals experience destructive interference. Adjustments to signals communicated via antenna elements can include the transmitting device or the receiving device applying an amplitude offset, a phase offset, or both to signals carried via antenna elements associated with the device. The adjustments associated with each of these antenna elements can be defined by a set of beamforming weights associated with a particular direction (e.g., relative to the antenna array of the transmitting device or the receiving device or relative to some other direction).

[0086] The network entity 105 or the UE 115 may use beam sweeping techniques as part of a beamforming operation. For example, the network entity 105 (e.g., base station 140, RU 170) may use multiple antennas or antenna arrays (e.g., antenna panels) to perform beamforming operations for directional communication with the UE 115. Some signals (e.g., synchronization signals, reference signals, beam selection signals, or other control signals) may be transmitted multiple times by the network entity 105 along different directions. For example, the network entity 105 may transmit signals according to different sets of beamforming weights associated with different transmit directions. Transmissions along different beam directions may be used to identify (e.g., by a transmitting device (such as the network entity 105) or by a receiving device (such as the UE 115)) the beam direction for later transmission or reception by the network entity 105.

[0087] Some signals, such as data signals associated with a particular receiving device, may be transmitted by a transmitting device (e.g., transmitting network entity 105, transmitting UE 115) along a single beam direction (e.g., a direction associated with a receiving device (e.g., receiving network entity 105 or receiving UE 115)). In some examples, a beam direction associated with transmission along a single beam direction may be determined based on signals transmitted along one or more beam directions. For example, UE 115 may receive one or more of the signals transmitted by network entity 105 along different directions and may report to network entity 105 an indication of the signal received by UE 115 with the highest signal quality or other acceptable signal quality.

[0088] In some examples, transmission by a device (e.g., by network entity 105 or UE 115) may be performed using multiple beam directions, and the device may use a combination of digital precoding or beamforming to generate a combined beam for transmission (e.g., from network entity 105 to UE 115). UE 115 may report feedback indicating precoding weights for one or more beam directions, and the feedback may correspond to a set of configured beams across the system bandwidth or one or more subbands. Network entity 105 may transmit reference signals (e.g., cell-specific reference signals (CRS), channel state information reference signals (CSI-RS)), which may or may not be precoded. UE 115 may provide feedback for beam selection, which may be a precoding matrix indicator (PMI) or codebook-based feedback (e.g., a multi-panel codebook, a linear combination codebook, a port-selective codebook). Although these techniques are described with reference to signals sent by a network entity 105 (e.g., base station 140, RU 170) in one or more directions, UE 115 may use similar techniques to send signals multiple times in different directions (e.g., to identify a beam direction for subsequent transmission or reception by UE 115) or to send signals in a single direction (e.g., to send data to a receiving device).

[0089] A receiving device (e.g., UE 115) may perform reception operations according to multiple reception configurations (e.g., directional listening) when receiving various signals (such as synchronization signals, reference signals, beam selection signals, or other control signals) from a receiving device (e.g., network entity 105). For example, the receiving device may perform reception according to multiple reception directions by receiving via different antenna subarrays, processing received signals according to different antenna subarrays, receiving according to different sets of receive beamforming weights applied to signals received at multiple antenna elements of an antenna array (e.g., different sets of directional listening weights), or processing received signals according to different sets of receive beamforming weights applied to signals received at multiple antenna elements of an antenna array, any of which may be referred to as "listening" according to different reception configurations or reception directions. In some examples, the receiving device may use a single reception configuration to receive along a single beam direction (e.g., when receiving a data signal). A single receive configuration may be aligned along a beam direction determined based on listening according to different receive configuration directions (e.g., a beam direction determined to have the highest signal strength, highest signal-to-noise ratio (SNR), or other acceptable signal quality based on listening according to multiple beam directions).

[0090] The wireless communication system 100 may be a packet-based network operating according to a layered protocol stack. In the user plane, communications at the bearer or PDCP layer may be IP-based. The RLC layer may perform packet segmentation and reassembly for communication via logical channels. The MAC layer may perform priority handling and multiplexing of logical channels into transport channels. The MAC layer may also support retransmission using error detection, error correction, or both to improve link efficiency. In the control plane, the RRC layer may provide for the establishment, configuration, and maintenance of RRC connections between the UE 115 and the network entity 105 or core network 130 for radio bearers supporting user plane data. The PHY layer may map transport channels to physical channels.

[0091] UE 115 and network entity 105 may support retransmission of data to increase the likelihood of successful data reception. Hybrid Automatic Repeat Request (HARQ) feedback is a technique for increasing the likelihood of correctly receiving data via a communication link (e.g., communication link 125, D2D communication link 135). HARQ may include a combination of error detection (e.g., using a cyclic redundancy check (CRC)), forward error correction (FEC), and retransmission (e.g., automatic repeat request (ARQ)). HARQ may improve throughput at the MAC layer under poor radio conditions (e.g., low signal-to-noise ratio conditions). In some examples, a device may support same-slot HARQ feedback, in which case the device may provide HARQ feedback in a particular time slot for data received via previous symbols in that time slot. In some other examples, the device may provide HARQ feedback in subsequent time slots or based on some other time interval.

[0092] In the wireless communication system 100, the network entity 105 may communicate with the UE 115 using directional communication techniques. For example, the network entity 105-a may communicate with the UE 115 via one or more beams. The network entity 105 and the UE 115 may perform beam management procedures to establish and maintain an optimal beam pair (e.g., a transmit beam and a receive beam). For example, the network entity 105 and the UE 115 may send and receive one or more reference signals, such as CSI-RS or SSB, via a communication link to assist in determining CSI, among other purposes. The network entity 105 may send one or more reference signals to the UE 115, where the one or more reference signals correspond to one or more beams. The UE 115 may measure the one or more reference signals to determine (e.g., estimate, calculate) values ​​representing characteristics of the one or more beams, which may be referred to as signal strength characteristics. For example, the UE 115 may calculate reference signal received power (RSRP), signal to interference plus noise ratio (SINR), etc., and send information, such as a CSI report or a beam report, to the network entity 105. The CSI report may include beam management information associated with one or more beams, such as signal strength characteristics, channel state parameters, etc. In some examples, the beam report may include an indication of the strongest beam (e.g., based on measurements) in terms of layer one RSRP (L1-RSRP) or layer one SINR (L1-SINR).

[0093] As an example, the UE 115 may calculate the RSRP by determining the average power of one or more reference signals received via a set of resource elements within a given frequency bandwidth. The power per resource element may be determined based on the energy received during a symbol of the resource element (excluding the cyclic prefix (CP) of the symbol). The one or more reference signals may be cell-specific reference signals. In some cases, the UE 115 may select the number of resource elements, the frequency bandwidth, and the measurement period for calculating the RSRP. The UE 115 may calculate the RSRP based on the corresponding measurement accuracy requirements and may indicate the RSRP to the network entity 105, for example, as part of a CSI report or a beam report.

[0094] The network entity 105 and the UE 115 may determine one or more optimal beams to use for communication based on the measurements and CSI reports. For example, based on the reported information, the network entity 105 and the UE 115 may select or reselect the optimal beam or beam pair, or may adapt to beam events (e.g., beam failure). During initial access, the network entity 105 and the UE 115 may establish communication by selecting the optimal beam pair. After the connection has been established, the network entity 105 and the UE 115 may perform beam refinement and beam switching to switch to the optimal beam. Additionally or alternatively, the network entity 105 may use the reported information to perform link adaptation to improve the performance of subsequent communications with the UE 115.

[0095] Accuracy requirements (e.g., measurement accuracy requirements) can be defined as a tolerance range in decibels (dB) for reference signal measurements to ensure that beam management and link adaptation processes provide adequate performance. Relative accuracy requirements and absolute accuracy requirements can be defined for different types of reference signals and different signal strength characteristics. For example, a first set of accuracy requirements can be defined for L1-RSRP values ​​measured relative to an SSB (e.g., an SSB resource). A second set of accuracy requirements can be defined for L1-RSRP values ​​measured relative to a CSI-RS (e.g., a CSI-RS resource). Other sets of accuracy requirements can be defined for L1-SINR values ​​measured relative to an SSB and relative to a CSI-RS. Additionally, the accuracy requirements can vary based on the frequency bandwidth associated with the received reference signal, which in turn can be associated with different capabilities of the UE 115.

[0096] For example, an absolute accuracy requirement (e.g., an absolute accuracy tolerance) may be defined as the value of a measured signal strength characteristic associated with a reference signal received via a given resource (or set of resources) RSRP meas and reference value RSRP ideal That is, the absolute accuracy requirement may be equal to RSRP meas -RSRP ideal The reference value may be an ideal value (eg, a "sprite" value) of a signal strength characteristic associated with a resource. The relative accuracy requirement (eg, a relative accuracy tolerance) may be defined as in is a measured signal strength characteristic of a reference signal received via the resource, refers to the strongest (e.g., maximum) measured RSRP of all reference signals in the same serving cell as the reference signal, is the ideal value of the signal strength characteristic associated with the resource, and It refers to the ideal value of the strongest measured RSRP. Similar accuracy requirements can be defined for other signal strength characteristics such as SINR.

[0097] As part of beam management, the UE 115 may use artificial intelligence-based beam prediction to predict the best beam, beam events (e.g., beam switching events, beam failure events), etc. For example, the UE 115 may use a prediction model (e.g., a machine learning algorithm) (e.g., via a neural network, such as a convolutional neural network (CNN), a recurrent neural network (RNN), etc.) to predict the probability of a future best (e.g., top) beam index or a future best beam change. Here, the UE 115 may predict whether the best beam index may change (or change more dynamically) at a future time (or future time window). To this end, the UE 115 may predict one or more signal strength characteristics of a target beam associated with a target resource or resources (e.g., time-frequency resources), such as L1-RSRP, L1-SINR, etc.

[0098] As discussed herein, UE 115 may predict L1-RSRP or L1-SINR values ​​for a target beam and target one or more resources (e.g., using a prediction model) based on one or more accuracy requirements defined for UE-predicted signal strength characteristics. UE 115 may, for example, predict signal strength characteristics for a first set of one or more beams and a first set of resources based on the corresponding accuracy requirements. The accuracy requirement may be defined as a tolerance range in dB relative to a reference value associated with the first set of resources. In some cases, the reference value may be an ideal value of the signal strength characteristic, also referred to as a genie value. In other cases, the reference value may be a measured value obtained by UE 115, such as a value of the signal strength characteristic obtained by measuring the second set of one or more beams (e.g., based on a reference signal received via the first set of resources via the second set of one or more beams). UE 115 may report the predicted signal strength requirements to network entity 105 for beam management, link adaptation, and the like.

[0099] Figure 2 An example of a beam management process 200 that supports accuracy requirements for UE-based signal strength prediction according to one or more aspects of the present disclosure is illustrated. In some examples, the beam management process 200 may implement aspects of the wireless communication system 100 or may be implemented by aspects of the wireless communication system 100. For example, the beam management process 200 may include a UE 115-a and a network entity 105-a, which may be a reference Figure 1 Examples of corresponding devices described.

[0100] UE 115-a and network entity 105-a may communicate using beamformed communication via one or more communication links, which may be examples of downlink channels (e.g., physical downlink shared channel (PDSCH), physical downlink control channel (PDCCH)), uplink channels (e.g., physical uplink shared channel (PUSCH), physical uplink control channel (PUCCH)), etc.). To support beamformed communication, UE 115-a and network entity 105-a may perform beam management. Beam management may include beam scanning, where network entity 105-a may utilize one or more transmit beams in a beam set (e.g., beam set 205-a, beam set 205-b) to cover UE 115-a. More specifically, network entity 105-a may scan a set of transmit beams across communication links according to a beam scanning pattern. In some examples, the beam scanning pattern may include transmitting a set of SSBs or a set of CSI-RSs across the beam set. UE 115-a may perform measurements of SSBs or CSI-RS received across a set of beams and send a report to network entity 105-a indicating information based on the measurements. For example, the report may indicate the strongest beam, L1-RSRP, L1-SINR, etc. Based on the report, UE 115-a and network entity 105-a may select or reselect the best beam or adapt to beam events (e.g., beam failure events).

[0101] The beam management process may be utilized during the initial access process to establish communication over the communication link between the UE 115-a and the network entity 105-a. Additionally, the UE 115-a and the network entity 105-a may implement the beam management process to maintain or update communication over the communication link. Figure 2 As illustrated, in some cases, UE 115-a may operate in RRC_IDLE or RRC_INACTIVE mode. The network entity 105-a and the UE 115-a may perform an SSB beam scanning and reporting procedure during an initial access procedure (e.g., as part of a random access channel (RACH) procedure). Here, the network entity 105-a may send a set of SSBs across a set of beams. The UE 115-a may receive the SSBs and perform measurements to obtain beam information, such as signal strength measurements (e.g., RSRP, SINR), and may report the beam information to the network entity 105-a. The beam used for SSB beam scanning may be a wide beam (e.g., a layer 1 (L1) beam). The UE 115-a and the network entity 105-a may select the best (e.g., strongest) beam from the scanned beams of the communication link based on the measurements and reports.

[0102] After initial access, UE 115-a may operate in RRC_CONNECTED mode and may implement beam management procedures to maintain reliable communication via the communication link. For example, the network entity 105-a and UE 115-a may periodically perform CSI-RS beam scanning and reporting procedures while in connected mode. CSI-RS beam scanning may be a P1, P2, or P3 procedure. P1 may be a beam selection procedure in which the network entity 105-a scans a set of beams and the UE 115-a selects the best (e.g., strongest) beam in the set of beams. The UE 115-a may report the selected beam to the network entity 105-a. P2 may be a beam refinement procedure of the network entity 105-a in which the network entity 105-a may refine the beam (e.g., by scanning a narrower beam over a narrower range), and the UE 115-a may detect the best beam and report the best beam to the network entity 105-a. P3 may be a beam refinement process for UE 115-a, where the network entity 105-a may fix the beam (e.g., repeatedly send the same beam) and the UE 115-a may refine its receive beam. For example, the UE 115-a may set a spatial filter on the antenna array of the UE 115-a. The UE 115-a may send an L1 report for beam refinement. The network entity 105-a and the UE 115-a may perform the same process for uplink beam management (e.g., U1, U2, and U3). Additionally or alternatively, the network entity 105-a and the UE 115-a may perform a CSI-RS beam scanning and reporting process as part of a beam failure recovery process (e.g., to facilitate fast recovery) or a radio link failure process (e.g., as a last resort to reestablish communication).

[0103] UE 115-a and network entity 105-a may perform beam management, measurement, and reporting according to one or more accuracy requirements. Accuracy requirements may be defined for measurement type (e.g., RSRP or SINR), reference signal type (e.g., SSB or CSI-RS), and frequency range (e.g., frequency range 1 (FR1) or frequency range 2 (FR2)). For example, accuracy requirements may be defined for RSRP values ​​obtained by measuring SSBs by UE 115-a (e.g., received via SSB resources configured for L1-RSRP measurement), which may be referred to as SSB-based L1-RSRP accuracy requirements. Other accuracy requirements may be defined for L1-RSRP measurements of CSI-RS received at UE 115-a (e.g., via CSI-RS resources configured for L1-RSRP measurement), which may be referred to as CSI-RS-based accuracy requirements. Similarly, accuracy requirements may be defined for SSB-based L1-SINR measurements and for CSI-RS-based L1-SINR measurements. Additionally, in some cases, the accuracy requirements may vary based on the frequency bandwidth associated with the received reference signal, which in turn may be associated with different capabilities of the UE 115. For example, SSB-based L1-RSRP accuracy requirements may be defined separately for SSBs configured for L1-RSRP measurements in FR1 and for SSBs configured for L1-RSRP measurements in FR2.

[0104] UE 115-a may receive a reference signal and measure the reference signal based on a corresponding accuracy requirement. In some examples, the accuracy requirement may be further categorized as an absolute accuracy requirement or a relative accuracy requirement. For example, an absolute accuracy requirement (e.g., an absolute accuracy tolerance) may be defined as a value of a measured signal strength characteristic associated with a reference signal received via a given resource (or set of resources), RSRP. meas and reference value RSRP ideal That is, the absolute accuracy requirement may be equal to RSRP meas -RSRP ideal The reference value may be an ideal value of a signal strength characteristic associated with the resource (eg, a "sprite" value). As an example, Table 1 below illustrates the absolute accuracy requirements for SSB-based L1-RSRP in FR 2.

[0105]

[0106]

[0107] Table 1

[0108] The relative accuracy requirement (e.g., relative accuracy tolerance) may be defined in terms of the accuracy of a signal strength characteristic value as measured from a reference signal received via a resource relative to a maximum measured signal strength characteristic value among all reference signals of the cell for which UE 115-a performs corresponding measurements. For example, when the signal strength characteristic is RSRP, the relative accuracy requirement may be given by: in is the measured value of the RSRP of the reference signal received via the resource, refers to the strongest (e.g., maximum) measured RSRP of all reference signals in the same serving cell as the reference signal, is the ideal value of RSRP associated with the resource, and It refers to the ideal value of the strongest measured RSRP. As an example, the following Table 2 illustrates the relative accuracy requirements of L1-RSRP based on SSB in FR2.

[0109]

[0110]

[0111] Table 2

[0112] Similar absolute and relative accuracy requirements are defined for other signal strength characteristics such as SINR.

[0113] Furthermore, in some examples, the accuracy requirement may depend on one or more conditions associated with the signal strength characteristic measurement. For example, the respective accuracy requirement may correspond to a respective frequency band (e.g., an operating band) within FR 1 or FR2, where each frequency band corresponds to a respective power class of UE 115-a. In some cases, the power class of UE 115-a may further define or be associated with one or more capabilities of UE 115-a. Thus, when one or more corresponding conditions are met, UE 115-a may achieve the accuracy requirement for the signal strength characteristic measurement (e.g., RSRP measurement, SINR measurement) of a reference signal received in a given frequency band. Table 3 illustrates an example of such conditions for SSB-based L1-RSRP measurement for a frequency band in FR2.

[0114]

[0115]

[0116] Table 3

[0117] In some cases, UE 115-a may use artificial intelligence-based beam prediction during beam management to predict the best beam, beam events (e.g., beam switching events, beam failure events), etc. UE 115-a may use a prediction model (e.g., a machine learning algorithm) to perform beam prediction in the time domain, the spatial domain, or both to improve the accuracy of beam selection. Beam prediction may involve UE 115-a predicting the probability of the best (e.g., top) beam index in the future or the best beam changing in the future. UE 115-a may predict whether the best beam index may change (or change more dynamically) at a future time (or future time window). Additionally, UE 115-a may predict one or more signal strength characteristics of a target beam associated with a target resource or resources (e.g., time-frequency resources), such as RSRP, SINR, etc.

[0118] For example, for a target beam and a target one or more resources, UE 115-a may utilize a prediction model to infer signal strength characteristics that may be associated with communication via the target beam and the target one or more resources. The prediction model may be an example of a prediction model associated with a beam management process. UE 115-a may receive a message from network entity 105-a that includes an indication of a target beam, a target one or more resources, or a combination thereof. Network entity 105-a may indicate (e.g., via a message) that the target one or more resources are to be used by UE 115-a to predict signal strength characteristics of the target beam. Based on the indication, UE 115-a may use the prediction model to predict signal strength characteristics of the target beam and the target one or more resources. In some cases, UE 115-a may infer multiple signal strength characteristics corresponding to target beams for a set of N future time instances. UE 115-a may predict corresponding signal strength characteristics of the beam for each future time instance.

[0119] Such prediction may utilize measurements of reference signals received via one or more other beams different from the target beam. For example, UE 115-a may perform spatial domain downlink beam prediction for beam set 205-a based on measurements of one or more reference signals received via beam set 205-b. Here, network entity 105-a may send reference signals to UE 115-a via beam set 205-b. UE 115-a may receive and measure the reference signals and may utilize the measurements as input to a prediction model to predict one or more signal strength characteristics of one or more beams in beam set 205-a. In another example, UE 115-a may perform time domain beam prediction for beam set 205-a based on historical (e.g., previously obtained) measurements of beam set 205-b.

[0120] Beam set 205-a may be a beam set for downlink beam prediction, while beam set 205-b may be a beam set for downlink beam measurement (e.g., measurement of downlink reference signals received at UE 115-a). In some cases, beam set 205-a and beam set 205-b may be within the same frequency range, such as frequency range 1 (FR1) or frequency range 2 (FR2). In some examples, beam set 205-b may be a subset of beam set 205-a. In such examples, UE 115-a may select or otherwise determine beam set 205-b from beam set 205-a, for example, based on a fixed pattern or a random pattern. In other examples, beam set 205-b may be different from beam set 205-a. For example, beam set 205-b may include wide beams (e.g., beams with a wide beamwidth), while beam set 205-a may include narrow beams (e.g., beams with a narrow beamwidth). In some cases, UE 115-a may select or otherwise determine the number of beams in beam set 205-a, the number of beams in beam set 205-b, or a combination thereof. Additionally or alternatively, UE 115-a may determine a quasi-co-location (QCL) relationship between one or more beams in beam set 205-a and one or more beams in beam set 205-b.

[0121] UE 115-a may report information related to beam prediction to network entity 105-a. For example, the prediction model may output a beam in beam set 205-a corresponding to an optimal beam, and UE 115-a may calculate (e.g., predict) a signal strength characteristic (e.g., RSRP, SINR) associated with the beam. UE 115-a may send an indication of the beam (e.g., a beam index), an indication of the predicted signal strength characteristic, or a combination thereof to network entity 105-a. For example, UE 115-a may report a predicted L1-RSRP value, a predicted L1-SINR value, or a combination thereof to network entity 105-a. In some cases, UE 115-a may predict and report beam information (e.g., beam index, signal strength characteristics) associated with multiple beams or multiple predictions.

[0122] The present disclosure defines accuracy requirements for signal strength characteristics when a UE, such as UE 115-a, predicts these signal strength characteristics. The accuracy requirement may be understood as a tolerance (e.g., a tolerance range) in dB of the predicted value of the signal strength characteristic relative to a reference value of the signal strength characteristic. The predicted value may be for a target beam and a target set of one or more resources, where the reference value is associated with the same target set of one or more resources. For example, an absolute or relative accuracy requirement may be defined for a UE-predicted L1-RSRP or L1-SINR value for beam set 205-a relative to a reference value. In some cases, the accuracy requirements for UE-predicted values ​​(e.g., L1-RSRP, L1-SINR) may be similar to those defined for UE-measured values ​​(e.g., L1-RSRP, L1-SINR), but may have relatively looser tolerances.

[0123] As a specific example, the absolute accuracy requirement (eg, absolute accuracy tolerance) for L1-RSRP prediction may be defined as RSRP predicted -RSRP ref , where RSRP predicted represents the predicted value of L1-RSRP, and RSRP ref Additionally or alternatively, for a set of multiple target resources associated with multiple predictions, the relative accuracy requirement (e.g., relative accuracy tolerance) for L1-RSRP prediction may be defined as here, represents a predicted value associated with a target resource in a set of multiple target resources, refers to the strongest (e.g., largest) predicted RSRP associated with a resource from the set of multiple target resources, represents the reference value of the target resource, and is associated with the same resource from a collection of multiple target resources Similar accuracy requirements can be defined for other predicted signal strength characteristics such as L1-SINR.

[0124] In some cases, the reference value may be an ideal value, such as a sap value. For the predicted RSRP associated with the target resource, the reference value may be the ideal RSRP value associated with the target resource. For the predicted SINR associated with the target resource, the reference value may be the ideal SINR value associated with the target resource. In other cases, the reference value may be an L1-RSRP value or an L1-SINR value obtained by the UE via measurement of one or more received reference signals associated with the target resource. Additionally, the target resource may be an SSB resource or a CSI-RS resource. That is, the UE may predict the signal strength characteristics of a hypothetical reference signal such as an SSB or CSI-RS that may be received via the target resource (e.g., at a future time instance). Alternatively, the target resource may be referred to as a virtual resource, which may not be used for transmission or reception but may indicate additional information associated with the target beam, such as a beam shape or beam direction. In some cases, the additional information may indicate connection information with another one or more resources (e.g., SSB or CSI-RS resources), such as QCL information.

[0125] exist Figure 2 In the example of FIG. 2 , for example, UE 115 - a may predict the signal strength characteristics of the target beam in beam set 205 - a according to a relative accuracy requirement, such as The target beam may be associated with a target resource in the set of resources. UE 115-a may obtain a reference value of the relative accuracy requirement by measuring a downlink reference signal received via the beam set 205-b corresponding to the target resource. For example, the target resource may be an SSB resource. UE 115-a may receive the SSB via a beam in beam set 205-b corresponding to the target resource and may measure the SSB to obtain Alternatively, the target resource may be an example of a virtual resource associated with the beam shape of the target beam, the beam direction of the target beam, or a combination thereof. In some cases, the virtual resource may indicate a correspondence between a downlink reference signal (e.g., and one or more other downlink reference signals associated with beam set 205-b) and the beam shape of the target beam, a correspondence between a downlink reference signal (e.g., and one or more other downlink reference signals associated with beam set 205-b) and the beam direction of the target beam, or a combination thereof. In some examples, the virtual resource may indicate a QCL correspondence between a downlink reference signal (e.g., and one or more other downlink reference signals associated with beam set 205-b) and beam set 205-a.

[0126] UE 115-a may predict one or more additional signal strength characteristics for one or more additional beams associated with the set of resources in beam set 205-a. UE 115-a may determine a maximum value of the predicted one or more additional signal strength characteristics. Additionally, UE 115-a may receive and measure one or more other downlink reference signals via beam set 205-b corresponding to the set of resources, and may determine a maximum value from all downlink reference signals received via the set of resources and measured by UE 115-a. UE 115-a may The UE 115-a may send an indication of the predicted signal strength characteristic to the network entity 105-a based on the relative accuracy requirement (e.g., ).

[0127] The level of accuracy that can be achieved by the prediction model used for such predictions may depend on the characteristics of the target beam and the characteristics of the beam associated with the received reference signal and the measured signal strength characteristics. For example, when beam set 205-b includes a relatively large number of beams, UE 115-a may be able to obtain sufficient measurements so that the associated prediction for beam set 205-a has improved accuracy (e.g., compared to a scenario where beam set 205-b includes fewer beams). Thus, the accuracy requirements for UE predictions may also depend on such characteristics or conditions. In some cases, the accuracy requirements may additionally or alternatively be based on the time duration between the target resource and the report sent by UE 115-a. For example, UE 115-a may predict the signal strength characteristics of the target resource, but may wait a relatively long time duration before sending a report indicating the prediction. In this case, the accuracy requirements associated with the prediction may be less stringent because the conditions may change during the time duration, which may reduce the reliability and accuracy of the prediction. The accuracy requirements may be more stringent for shorter time durations between the prediction and the report.

[0128] The computing power or computing resources of the UE may further affect the level of accuracy that the UE can achieve. For example, a first UE with greater computing power for a machine learning or artificial intelligence-based process may be able to predict signal strength characteristics with greater accuracy than a second UE with limited computing power. As a result, the first UE may be able to meet more stringent accuracy requirements than the second UE.

[0129] In some cases, the UE may send a capability message indicating the accuracy requirements that the UE is capable of achieving. In some examples, the UE may receive a request for a capability message and may send a capability message in response to the request. Figure 2In an example, UE 115-a may receive a request from network entity 105-a for UE 115-a to send a capabilities message. Based on the request, UE 115-a may send a capabilities message to network entity 105-a, the capabilities message including an indication of one or more accuracy requirements supported by UE 115-a for one or more signal strength characteristics to be predicted by UE 115-a. For example, if UE 115-a is to predict a set of signal strength characteristics for a target beam in beam set 205-a corresponding to a target resource, UE 115-a may indicate to network entity 105-a that UE 115-a supports a set of accuracy requirements with respect to the set of signal strength characteristics. In some cases, the ability of UE 115-a to support the set of accuracy requirements may be based on the set of signal strength characteristics, the number of beams in beam set 205-a, or a beam type (e.g., SSB, CSI-RS) associated with the target beam or beam set 205-a, or a combination thereof. For example, UE 115-a may support a first subset of accuracy requirements for SSB-based RSRP measurements, a second subset of accuracy requirements for SSB-based SINR measurements, a third subset of accuracy requirements for CSI-RS-based RSRP measurements, and a fourth subset of accuracy requirements for CSI-RS-based SINR measurements.

[0130] Additionally, in some cases, the ability of UE 115-a to support the set of accuracy requirements may be based on a reference value from which UE 115-a predicts the set of signal strength characteristics (e.g., based on whether the reference value is an ideal value or a measured value). When UE 115-a performs the prediction based on a measured reference value (such as a measurement associated with beam set 205-b), the ability of UE 115-a to support the set of accuracy requirements may be based on the number of beams in beam set 205-b, the beam type associated with beam set 205-b, one or more measured signal strength characteristics of beam set 205-b, or a combination thereof.

[0131] The prediction of the signal strength characteristic made by the UE may be associated with a confidence level based on the corresponding accuracy requirement. The confidence level may indicate the likelihood that the prediction meets the accuracy requirement. For example, a 90% confidence level may indicate that there is a 90% probability that the predicted signal strength requirement is within the tolerance range of the accuracy requirement (e.g., 90% of the predictions made by the UE meet the accuracy requirement). In some cases, the UE may report the confidence level along with the predicted signal strength characteristic. Figure 2In an example, UE 115-a may send a message indicating a confidence level associated with predicting one or more signal strength characteristics of a beam in beam set 205-a (e.g., a target beam). The confidence level may be based on an accuracy requirement, one or more capabilities of UE 115-a (e.g., computing capabilities), beam set 205-a, beam set 205-b, or a combination thereof.

[0132] 3A and 3B illustrate examples of signal strength prediction processes 301 and 302, respectively, that support accuracy requirements for UE-based signal strength prediction according to one or more aspects of the present disclosure. In some examples, the signal strength prediction processes 301 and 302 may be implemented as described in reference to FIG. Figure 1 and Figure 2 Various aspects of the wireless communication system described herein may be implemented by or in conjunction with these aspects. For example, signal strength prediction processes 301 and 302 may be implemented by UE 115 to predict one or more signal strength characteristics of a first set of beams, such as L1-RSRP, L1-SINR, or both, according to accuracy requirements as described herein. The first set of beams may be associated with a first set of resources (e.g., downlink reference signal resources) such as SSB resources, CSI-RS resources, or virtual resources.

[0133] In FIG3A , for example, a UE may receive a set of reference signals 305 - a via a second set of beams, which in some cases may be different from the first set of beams. The second set of beams may correspond to a second set of resources (e.g., downlink reference signal resources, such as SSB resources or CSI-RS resources). As a non-limiting example, reference signal 305 - a may include two SSBs corresponding to two beams and received via three consecutive opportunities (e.g., time domain resources), which may be an example of 20 millisecond (ms) opportunities. The first set of beams and the first set of resources may be referred to as prediction targets 310 - a. Each beam in the first set of beams may be narrower (e.g., have a smaller beamwidth) than each beam of reference signal 305 - a. The UE may measure reference signal 305 - a to obtain a set of measured RSRP values, and may use the set of measured RSRP values ​​to predict one or more RSRP values ​​for prediction targets 310 - a based on the absolute value of accuracy requirement 315 - a. For example, accuracy requirement 315-a may define a tolerance range of + / - 6 dB relative to reference value 320. Thus, the absolute value of accuracy requirement 315-a may be 6 dBm. Reference value 320 may be an ideal RSRP value, an ideal SINR value, or other examples. Alternatively, reference value 320 may be a measured RSRP value from a set of measured RSRP values ​​associated with reference signal 305-a.

[0134] FIG3A also illustrates a prediction model 325 implemented by a UE to determine a correspondence between a reference signal 305-a and a prediction target 310-a. Thus, the predicted RSRP value may depend on measurement results associated with a downlink reference signal (e.g., reference signal 305-a) received at the UE. The UE may input one or more measured RSRP values ​​associated with the reference signal 305-a into the prediction model 325, which may include a DNN, a CNN, or the like, or an example of a DNN, a CNN, or the like. In some examples, the prediction model 325 may include a prediction model associated with beam management or an example of such a prediction model. The prediction model 325 may infer (e.g., predict) one or more RSRP values ​​associated with the prediction target 310-a based on the input measured RSRP values ​​according to the accuracy requirement 315-a. That is, each predicted RSRP value may be within a tolerance range of + / - 6 dB of one or more measured RSRP values.

[0135] In some examples, the accuracy requirement for signal strength prediction may depend on conditions associated with the prediction target, such as the number, type, or characteristics of the prediction target (e.g., the first set of beams, the first set of resources). For example, if the beams in the first set of beams are relatively narrow, the corresponding accuracy requirement may be less stringent than a scenario where the beams in the first set of beams are relatively wide. Similarly, a relatively large number of beams in the first set of beams may correspond to a less stringent accuracy requirement than a relatively small number of beams in the first set of beams. In some cases, the accuracy requirement may be based on the periodicity of the transmission of the first set of beams, where beams that are transmitted more frequently may correspond to more stringent accuracy requirements. In addition, the accuracy requirement for prediction targets associated with SSB (e.g., the first set of beams, the first set of resources) may be different from the accuracy requirement for prediction targets associated with CSI-RS (e.g., the first set of beams, the first set of resources).

[0136] Additionally or alternatively, the accuracy requirement for predicting the signal strength characteristics of the first set of beams may be based on conditions associated with the second set of beams, such as the number, type, or characteristics of the second set of beams. For example, the accuracy requirement may become increasingly stringent as the number of beams in the second set of beams increases. The accuracy requirement may be more stringent when the second set of beams is associated with a narrow beamwidth than when the second set of beams is associated with a wide beamwidth. In some examples, the accuracy requirement may be based on the periodicity of transmission of the second set of beams, where beams that are transmitted more frequently may correspond to more stringent accuracy requirements. Furthermore, the accuracy requirement may be based on whether the second set of beams (e.g., and the second set of resources) is associated with SSB or CSI-RS.

[0137] In some cases, if the second set of beams is relatively strong (e.g., based on relatively large measured RSRP values), the UE may be able to predict the signal strength characteristics of the first set of beams with improved accuracy compared to the second set of beams, which are relatively weak. Thus, in some cases, the accuracy requirement may depend on the absolute value of one or more measured signal strength characteristics associated with the second set of beams. As another example, the second set of beams may be associated with SSBs having a wide beamwidth but lower beamforming gain. The first set of beams may be associated with CSI-RS and, therefore, may have a narrower beamwidth but greater beamforming gain than the second set of beams. Additionally, the CSI-RS beams may be associated with relatively infrequent transmissions (e.g., with low periodicity). This scenario may correspond to less stringent accuracy requirements. In some examples, the UE may use the first set of beams for other purposes, such as input to prediction model 325, or for monitoring predicted performance. For example, the UE may use the first set of beams to communicate with a network entity and may obtain measured signal strength characteristics for comparison with predicted signal strength characteristics. The UE may verify the prediction, or may adjust or correct the prediction process based on the comparison.

[0138] 3B illustrates another example of signal strength characteristic prediction performed by a UE. Here, the second set of beams may include reference signals 305-b, which may be examples of four SSBs received at the UE in four consecutive 20ms opportunities (e.g., time domain resources). The UE may perform one or more measurements of the reference signals 305-b to obtain one or more measured signal strength characteristics, such as one or more RSRP values, one or more SINR values, or a combination thereof. The first set of beams and the first set of resources may correspond to the prediction target 310-b. The UE may use a prediction model 335 and predict one or more signal strength characteristics of the prediction target 310-b based on the absolute value of the accuracy requirement 315-b. For example, the UE may input one or more measured signal strength characteristics associated with the reference signal 305-b into the prediction model 335. In some examples, the prediction model 335 may include a prediction model associated with beam management, such as a CNN, a DNN, or the like, or an example of the prediction model. Prediction model 335 may output (e.g., infer) predicted one or more signal strength characteristics of prediction target 310-b based on accuracy requirement 315-b. Accuracy requirement 315-b may be defined relative to a reference value 330 associated with reference signal 305-b (e.g., a measured signal strength characteristic from the one or more measured signal strength characteristics). Additionally or alternatively, reference value 330 may be an ideal RSRP value, an ideal SINR value, etc., among other examples.

[0139] As illustrated, reference signal 305-b includes a greater number of beams than reference signal 305-a, and each beam of reference signal 305-b has a narrower beamwidth than each beam of reference signal 305-a. Therefore, the absolute value of accuracy requirement 315-b may be smaller than the absolute value of accuracy requirement 315-a. For example, while accuracy requirement 315-a may define a tolerance range of + / - 6 dB relative to reference value 320 associated with reference signal 305-a, accuracy requirement 315-b may define a tolerance range of + / - 1 dB relative to reference value 330. The absolute value of accuracy requirement 315-a may be 6 dBm, and the absolute value of accuracy requirement 315-b may be 1 dBm. Therefore, accuracy requirement 315-b may be understood as a more stringent accuracy requirement than accuracy requirement 315-a. Thus, the predicted signal strength characteristics associated with accuracy requirement 315-b may be considered more accurate than the predicted signal strength characteristics associated with accuracy requirement 315-a. In other words, signal strength prediction process 302 may be more accurate (e.g., may be associated with a lower error) than signal strength prediction process 301.

[0140] The difference between accuracy requirement 315-a and accuracy requirement 315-b may be further reflected in a comparison between prediction model 325 and prediction model 335. As illustrated, prediction model 335 may include a neural network (e.g., a CNN, a DNN) that is wider, deeper, or both than prediction model 325, or may be an instance of such a neural network, which may enable prediction model 335 to achieve a more stringent accuracy requirement 315-b. That is, the UE may utilize a wider or deeper prediction model to achieve increased accuracy in the prediction of signal strength characteristics. Thus, the prediction model implemented by the UE may be based on the accuracy requirement associated with the prediction of signal strength characteristics. Furthermore, the accuracy requirement for a given prediction may in turn be based on the prediction models supported by the UE. For example, a UE that supports a wider or deeper prediction model may be able to predict signal strength characteristics according to more stringent accuracy requirements than a UE with limited computing power or computing resources.

[0141] Figure 4A 、 Figure 4B and Figure 4C 4. Examples of accuracy requirement diagrams 401, 402, and 403 respectively illustrating accuracy requirements for UE-based signal strength prediction according to one or more aspects of the present disclosure are shown. In some examples, the accuracy requirement diagrams 401, 402, and 403 may be implemented as shown in FIG. Figure 1 and Figure 2Aspects of the wireless communication system described herein may be implemented by or in conjunction with these aspects. For example, accuracy requirement graphs 401, 402, and 403 may be implemented by UE 115 to predict one or more signal strength characteristics, such as L1-RSRP, L1-SINR, or both, for a first set of beams based on the accuracy requirements as described herein. The first set of beams may be associated with a first set of resources (e.g., downlink reference signal resources) (e.g., SSB resources, CSI-RS resources, or virtual resources). The accuracy requirements may be defined relative to a reference value, such as a measured signal strength characteristic value, or an ideal value, associated with a second set of beams and a second set of resources (e.g., downlink reference signal resources, such as SSB resources or CSI-RS resources).

[0142] exist Figure 4A In an example, the UE may predict the signal strength characteristics of a beam associated with a resource in the first set of resources based on a reference signal strength characteristic 405-a associated with the resource in the first set of resources. The reference signal strength characteristic 405-a may be an example of a reference value. The UE may perform the prediction according to an accuracy requirement 415-a, which may define or be defined as a tolerance range T0 in dB (e.g., an error tolerance range). For example, the reference value may be within the tolerance range T0 such that the tolerance range T0 extends above and below the reference value. That is, T0=L-L0, where L represents the signal strength characteristic predicted by the UE, and L0 represents the reference signal strength characteristic 405-a (e.g., the reference value). The value of the signal strength characteristic predicted by the UE according to the accuracy requirement 415-a may fall within the tolerance range T0.

[0143] The portion where T0 is higher than the reference value may be referred to as the upper portion and may be expressed in positive dB (+dB), while the portion where T0 is lower than the reference value may be referred to as the lower portion and may be expressed in negative dB (-dB). When the absolute value of the lower portion of the tolerance range is equal to the absolute value of the upper portion of the tolerance range, as Figure 4A As illustrated, the accuracy requirement 415 - a may be referred to as a symmetrical accuracy requirement. In other words, for the symmetrical accuracy requirement, the lower portion of the tolerance range may be symmetrical to the upper portion of the tolerance range with respect to the reference value.

[0144] The accuracy requirement may be associated with a confidence level, which in turn may be based on conditions associated with the first set of beams, the second set of beams, or both. The confidence level may be represented by a percentage value representing the likelihood that the prediction meets the accuracy requirement. Additionally, the confidence level of the accuracy requirement may indicate how stringent the accuracy requirement is, for example, relative to another accuracy requirement. For example, when the tolerance range for each accuracy requirement is the same, a more stringent accuracy requirement may have a greater confidence value than a less stringent accuracy requirement. In some cases, the confidence level may be defined based on conditions or characteristics associated with the first set of beams and the second set of beams. The UE may send an indication of the confidence level along with the reported signal strength prediction, for example, based on the accuracy requirement associated with the signal strength prediction.

[0145] As a specific example, a first accuracy requirement associated with a relatively large number of beams in the second set of beams may have a 95% confidence level, while a second accuracy requirement associated with a relatively small number of beams in the second set of beams may be associated with a 75% confidence level. Both the first accuracy requirement and the second accuracy requirement may correspond to the same tolerance range of + / - 6 dB. The UE may be more confident that the prediction associated with the first accuracy requirement is correct than the prediction associated with the second accuracy requirement. Therefore, the first accuracy requirement can be understood as being stricter than the second accuracy requirement. In other words, the UE may achieve the first accuracy requirement for 95% of predictions and may meet the second accuracy requirement for 75% of predictions.

[0146] In the case where the first accuracy requirement and the second accuracy requirement are associated with different tolerance ranges, the respective confidence levels may be determined (e.g., by the UE) based on the number of beams in the first set of beams, the number of beams in the second set of beams, the beam type associated with the first set of beams, the beam type associated with the second set of beams, the signal strength characteristics associated with the first set of beams, one or more signal strength characteristics associated with the second set of beams (e.g., as measured by the UE), or a combination thereof. Here, the respective confidence levels may indicate a relative degree of stringency associated with each accuracy requirement. For example, the stringency metric A2 may be defined by the following equation 1.

[0147] A2=P×A1+(1-P)×(βA1) (1)

[0148] The UE may calculate, for example, the respective values of A2 for each of the first accuracy requirement and the second accuracy requirement. In Equation 1, P may represent the confidence level (as a percentage value), A1 may represent the tolerance range in + / - dB, and β may be a predefined coefficient based on P and A1. The absolute value of the resulting A2 may indicate the relative strictness of the corresponding accuracy requirement. For example, a larger value of |A2| may correspond to a more strict accuracy requirement. Thus, the first accuracy requirement and the second accuracy requirement may be qualitatively compared based on the corresponding confidence level and tolerance range.

[0149] Figure 4B An example of an asymmetric accuracy requirement is illustrated, where the upper part of the tolerance range is asymmetric with respect to the lower part of the tolerance range. The accuracy requirement 415-b may define a tolerance range T0 with respect to a reference signal strength characteristic 405-b, which may be an example of a reference value. In Figure 4B it, the lower part of the tolerance range that extends below the reference value may be smaller than the upper part of the tolerance range that extends above the reference value (e.g., the lower part may have an absolute value that is less than the absolute value of the upper part). For example, the accuracy requirement 415-b may be defined as -6 dB < T0 < 20 dB. Thus, the value of the signal strength characteristic predicted by the UE may be within 6 dBm below the reference value (e.g., may be at most 6 dB smaller than the reference signal strength characteristic 405-b) and within 20 dBm above the reference value (e.g., may be at most 20 dB larger than the reference signal strength characteristic 405-b).

[0150] In some cases, based on the value or range of values of the reference signal strength characteristic 405-b (e.g., the reference value), the accuracy requirement 415-b may be associated with different tolerance ranges. For example, when the reference signal strength characteristic 405-b represented by L0 falls within the value ranges given by {L0 < -110 dBm, -110 dBm ≤ L0 < -9 dBm, L0 ≥ -90 dBm}, the corresponding tolerance ranges T0 may be given by {-6 dB < T0 < 20 dB, -6 dB < T0 < 9 dB, -3 dB < T0 < 3 dB}, respectively. Here, the confidence level may remain the same for each value range of L0 and T0.

[0151] Alternatively, in some examples, a respective confidence level may be defined for each part of the tolerance range T0 such that the confidence level of the values of the signal strength characteristic that fall within the lower part of T0 may be different from the confidence level of the values of the signal strength characteristic that fall within the upper part of T0. In the example of Figure 3B, T0 may be associated with asymmetric confidence levels, where the upper part of T0 may have a 95% confidence level, while the lower part of T0 may have a 75% confidence level.

[0152] Figure 4CAn example of an accuracy requirement 415-c associated with a symmetric tolerance range and an asymmetric confidence level is illustrated. The accuracy requirement 415-c may correspond to a tolerance range T0 defined relative to a reference signal strength characteristic 405-c. In a first example, T0 may include a lower portion and an upper portion such that -6 dB < T0 < 6 dB. The lower portion may be associated with a 75% confidence level, and the upper portion may be associated with a 95% confidence level.

[0153] In a second example, T0 may be symmetric with respect to a reference signal strength characteristic 405-c (e.g., a reference value) such that -6 dB < T0 < 6 dB, but the value of the reference signal strength characteristic 405-c and the corresponding confidence levels may vary and may be asymmetric. For example, the reference signal strength characteristic 405-c represented by L0 may fall within a value range given by {L0 < -110 dBm, -110 dBm ≤ L0 < -90 dBm, L0 ≥ -90 dBm}. Additionally, each value range of L0 may correspond to a respective set of asymmetrically defined confidence levels given by {{90%, 65%}, {95%, 80%}, {95%, 95%}}. More specifically, when L0 is less than -110 dBm, the predicted signal strength characteristic having a value within the lower portion of T0 may be associated with a 90% confidence level, while the predicted signal strength characteristic having a value within the upper portion of T0 may be associated with a 65% confidence level. When L0 is between -110 dBm and -90 dBm, the predicted signal strength characteristic having a value within the lower portion of T0 may be associated with a 95% confidence level, while the predicted signal strength characteristic having a value within the upper portion of T0 may be associated with an 80% confidence level. When L0 is greater than or equal to -90 dBm, for any value within T0, the predicted signal strength characteristic may be associated with a 95% confidence level.

[0154] However, in some other cases, the ranges of T0 and the corresponding confidence levels can each be asymmetric for different values of L0. For example, when {L0 < -110 dBm, -110 dBm ≤ L0 < -90 dBm, L0 ≥ -90 dBm}, the corresponding tolerance ranges can be defined as {-6 dB < T0 < 20 dB, -6 dB < T0 < 9 dB, -3 dB < T0 < 3 dB}, and the corresponding confidence levels for each tolerance range and the value of L0 can be given by {{90%, 65%}, {95%, 80%}, {95%, 95%}}. Thus, when L0 is less than -110 dBm, the tolerance range associated with the accuracy requirement 415-c can be -6 dB < T0 < 20 dB, where the predicted signal strength characteristics with values in the lower portion of T0 can be associated with a 90% confidence level, and the predicted signal strength characteristics with values in the upper portion of T0 can be associated with a 65% confidence level. Thus, the tolerance range T0 can vary based on the value of L0, and each tolerance range or each portion of the tolerance range can further be associated with a corresponding confidence level.

[0155] In some cases, the accuracy requirements supported by the UE can be based on the associated confidence levels and tolerance ranges, and conditions or characteristics associated with a first set of beams and a second set of beams. That is, the UE may be able to achieve a set of accuracy requirements defined by a set of corresponding tolerance ranges and corresponding to a set of confidence levels based on the number of beams in the first set of beams, the number of beams in the second set of beams, the beam type associated with the first set of beams, the beam type associated with the second set of beams, the signal strength characteristics associated with the first set of beams, one or more signal strength characteristics (e.g., as measured by the UE) associated with the second set of beams, or a combination thereof. For example, when the second set of beams includes a greater number of beams, is transmitted at an increased frequency, or is associated with a narrower beam width, the UE may support accuracy requirements associated with an increased confidence level and a smaller tolerance range (e.g., a lower dB value) compared to when the second set of beams includes a smaller number of beams, has a reduced transmission frequency, or is associated with a wider beam width.

[0156] The UE may transmit a capability message indicating the set of accuracy requirements supported by the UE for predicted signal strength characteristics, and in some cases, may additionally indicate the corresponding set of confidence levels, the corresponding set of tolerance ranges, or both (e.g., within the capability message). In some examples, the UE may transmit the capability message based on receiving a request for the capability message. In such examples, the request may indicate that the UE will report the capability associated with symmetric accuracy requirements, the capability associated with asymmetric accuracy requirements, or both.

[0157] Figure 5 A block diagram 500 illustrates a device 505 that supports accuracy requirements for UE-based signal strength prediction according to one or more aspects of the present disclosure. The device 505 can be an example of aspects of the UE 115 as described herein. The device 505 can include a receiver 510, a transmitter 515, and a communication manager 520. The device 505 can also include a processor. Each of these components can communicate with each other (e.g., via one or more buses).

[0158] The receiver 510 may provide means for receiving information (such as packets, user data, control information, or any combination thereof) associated with various information channels (e.g., control channels, data channels, information channels related to accuracy requirements for UE-based signal strength prediction). The information may be passed to other components of the device 505. The receiver 510 may utilize a single antenna or a collection of multiple antennas.

[0159] The transmitter 515 may provide means for transmitting signals generated by other components of the device 505. For example, the transmitter 515 may transmit information (such as packets, user data, control information, or any combination thereof) associated with various information channels (e.g., control channels, data channels, information channels related to accuracy requirements for UE-based signal strength prediction). In some examples, the transmitter 515 may be co-located with the receiver 510 in a transceiver module. The transmitter 515 may utilize a single antenna or a collection of multiple antennas.

[0160] The communication manager 520, the receiver 510, the transmitter 515, or various combinations thereof, or various components thereof, may be examples of means for performing various aspects of the accuracy requirements for UE-based signal strength prediction as described herein. For example, the communication manager 520, the receiver 510, the transmitter 515, or various combinations thereof, or components thereof, may support methods for performing one or more of the functions described herein.

[0161] In some examples, the communication manager 520, the receiver 510, the transmitter 515, or various combinations or components thereof may be implemented in hardware (e.g., in a communication management circuit). The hardware may include a processor, a digital signal processor (DSP), a central processing unit (CPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a microcontroller, discrete gate or transistor logic components, discrete hardware components, or any combination thereof configured as or otherwise supporting components for performing the functions described herein. In some examples, the processor and a memory coupled to the processor may be configured to perform one or more of the functions described herein (e.g., by executing instructions stored in the memory by the processor).

[0162] Additionally or alternatively, in some examples, the communication manager 520, receiver 510, transmitter 515, or various combinations or components thereof may be implemented in code executed by a processor (e.g., as communication management software or firmware). If implemented in code executed by a processor, the functionality of the communication manager 520, receiver 510, transmitter 515, or various combinations or components thereof may be performed by a general-purpose processor (e.g., configured as or otherwise supporting means for performing the functions described herein), a DSP, a CPU, an ASIC, an FPGA, a microcontroller, or any combination of these or other programmable logic devices.

[0163] In some examples, communication manager 520 can be configured to perform various operations (e.g., receive, obtain, monitor, output, transmit) using or otherwise cooperating with receiver 510, transmitter 515, or both. For example, communication manager 520 can receive information from receiver 510, transmit information to transmitter 515, or be integrated with receiver 510, transmitter 515, or both to obtain information, output information, or perform various other operations as described herein.

[0164] According to examples disclosed herein, the communication manager 520 can support wireless communications at a UE. For example, the communication manager 520 can be configured as or otherwise support means for receiving an indication of one or more time-frequency resources associated with prediction of one or more signal strength characteristics by the UE, wherein an accuracy requirement is defined for the prediction of the one or more signal strength characteristics by the UE. The communication manager 520 can be configured as or otherwise support means for predicting one or more signal strength characteristics of a beam in a set of beams relative to the one or more time-frequency resources in accordance with the accuracy requirement. The communication manager 520 can be configured as or otherwise support means for sending an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement.

[0165] By including or configuring the communication manager 520 according to the examples described herein, the device 505 (e.g., a processor controlling the receiver 510, the transmitter 515, the communication manager 520, or a combination thereof or otherwise coupled thereto) can support techniques for improving the accuracy of beam management predictions, which can also increase the reliability of the beam management process. Consequently, the device 505 can potentially communicate more successfully with a network entity or other wireless device based on the use of a more optimal beam, which can reduce the number of potential retransmissions or monitoring opportunities that the device 505 can decode, and in turn, reduce processing, reduce power consumption, and improve efficiency of resource utilization.

[0166] Figure 6A block diagram 600 illustrates a device 605 that supports accuracy requirements for UE-based signal strength prediction according to one or more aspects of the present disclosure. The device 605 can be an example of aspects of the device 505 or UE 115 as described herein. The device 605 can include a receiver 610, a transmitter 615, and a communication manager 620. The device 605 can also include a processor. Each of these components can communicate with each other (e.g., via one or more buses).

[0167] The receiver 610 may provide means for receiving information (such as packets, user data, control information, or any combination thereof) associated with various information channels (e.g., control channels, data channels, information channels related to accuracy requirements for UE-based signal strength prediction). The information may be passed to other components of the device 605. The receiver 610 may utilize a single antenna or a collection of multiple antennas.

[0168] The transmitter 615 may provide means for transmitting signals generated by other components of the device 605. For example, the transmitter 615 may transmit information (such as packets, user data, control information, or any combination thereof) associated with various information channels (e.g., control channels, data channels, information channels related to accuracy requirements for UE-based signal strength prediction). In some examples, the transmitter 615 may be co-located with the receiver 610 in a transceiver module. The transmitter 615 may utilize a single antenna or a collection of multiple antennas.

[0169] Device 605 or its various components may be examples of means for performing various aspects of accuracy requirements for UE-based signal strength prediction as described herein. For example, communication manager 620 may include time-frequency resource component 625, prediction component 630, or any combination thereof. Communication manager 620 may be an example of aspects of communication manager 520 as described herein. In some examples, communication manager 620 or its various components may be configured to perform various operations (e.g., receive, obtain, monitor, output, transmit) using or otherwise cooperating with receiver 610, transmitter 615, or both. For example, communication manager 620 may receive information from receiver 610, transmit information to transmitter 615, or be integrated with receiver 610, transmitter 615, or both to obtain information, output information, or perform various other operations as described herein.

[0170] According to examples disclosed herein, the communication manager 620 can support wireless communications at a UE. The time-frequency resource component 625 can be configured as or otherwise support means for receiving an indication of one or more time-frequency resources associated with prediction of one or more signal strength characteristics by the UE, wherein an accuracy requirement is defined for the prediction of the one or more signal strength characteristics by the UE. The prediction component 630 can be configured as or otherwise support means for predicting one or more signal strength characteristics of a beam in a set of beams relative to the one or more time-frequency resources in accordance with the accuracy requirement. The prediction component 630 can be configured as or otherwise support means for sending an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement.

[0171] Figure 7 A block diagram 700 illustrates a communication manager 720 that supports accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure. The communication manager 720 can be an example of aspects of the communication manager 520, the communication manager 620, or both as described herein. The communication manager 720 or its various components can be examples of means for performing various aspects of accuracy requirements for UE-based signal strength predictions as described herein. For example, the communication manager 720 can include a time-frequency resource component 725, a prediction component 730, a reference signal component 735, a confidence level component 740, a capability message component 745, or any combination thereof. Each of these components can communicate with each other directly or indirectly (e.g., via one or more buses).

[0172] According to examples disclosed herein, the communication manager 720 can support wireless communications at a UE. The time-frequency resource component 725 can be configured as or otherwise support means for receiving an indication of one or more time-frequency resources associated with predicting one or more signal strength characteristics by the UE, wherein an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE. The prediction component 730 can be configured as or otherwise support means for predicting one or more signal strength characteristics of a beam in a set of beams relative to the one or more time-frequency resources in accordance with the accuracy requirement. In some examples, the prediction component 730 can be configured as or otherwise support means for sending an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement.

[0173] In some examples, reference signal component 735 can be configured as or otherwise support means for receiving one or more downlink reference signals via a second set of beams corresponding to a second one or more time-frequency resources. In some examples, reference signal component 735 can be configured as or otherwise support means for measuring one or more downlink reference signals to obtain second one or more signal strength characteristics, wherein the prediction is based on the second one or more signal strength characteristics.

[0174] In some examples, the accuracy requirement is based on a second one or more signal strength characteristics, a numerical number of the second set of beams, a beam width associated with the second set of beams, a beam type associated with the second set of beams, a periodicity of the second set of beams at the UE, or a combination thereof.

[0175] In some examples, the confidence level component 740 may be configured as or otherwise support a component for sending a message indicating a confidence level associated with predicting one or more signal strength characteristics, where the confidence level is based on an accuracy requirement, one or more capabilities of the UE, a set of beams, a second set of beams different from the set of beams, or a combination thereof.

[0176] In some examples, the accuracy requirement is based on one or more signal strength characteristics, a numerical number of beams in the set of beams, a beam width of the beam, a beam type of the set of beams, a periodicity of the set of beams at the UE, or a combination thereof. In some examples, the accuracy requirement is based on a time duration between the one or more time-frequency resources and the sending of the indication. In some examples, the accuracy requirement is based on a reference value generated by the one or more signal strength characteristics, the reference value being associated with the one or more time-frequency resources.

[0177] In some examples, the accuracy requirement defines a tolerance range extending above and below a reference value for the one or more signal strength characteristics. In some examples, the predicted one or more signal strength characteristics fall within the tolerance range.

[0178] In some examples, a lower portion of the tolerance range extending below the reference value is symmetrical relative to an upper portion of the tolerance range extending above the reference value. In some examples, the lower portion of the tolerance range extending below the reference value is asymmetrical relative to an upper portion of the tolerance range extending above the reference value. In some examples, the reference value includes an ideal value of one or more signal strength characteristics or a measured value of one or more signal strength characteristics.

[0179] In some examples, the capability message component 745 can be configured as or otherwise support means for sending a capability message indicating support at the UE for a set of one or more accuracy requirements relative to a predicted signal strength characteristic. In some examples, the support for the set of one or more accuracy requirements is based on one or more signal strength characteristics, a numerical number of beams in the set of beams, a beam type for the set of beams, a numerical number of a second set of beams associated with the set of beams, a beam type associated with the second set of beams, one or more signal strength characteristics associated with the second set of beams, or a combination thereof. In some examples, the support for the set of one or more accuracy requirements is based on a tolerance level associated with the set of one or more accuracy requirements, a confidence level associated with the set of one or more accuracy requirements, or both.

[0180] In some examples, capability message component 745 can be configured as or otherwise support means for receiving a request for a capability message, where sending the capability message is based on the request.

[0181] In some examples, one or more time-frequency resources are associated with an SSB, a CSI-RS, or a combination thereof. In some examples, the one or more time-frequency resources include one or more virtual resources associated with a beam shape of a set of beams, a beam direction of a set of beams, or a combination thereof. In some examples, the one or more virtual resources indicate a correspondence between one or more downlink reference signals and a beam shape of a set of beams, a correspondence between one or more downlink reference signals and a beam direction of a set of beams, or a QCL correspondence between one or more downlink reference signals and a set of beams.

[0182] In some examples, the one or more signal strength characteristics include RSRP, SINR, or a combination thereof.

[0183] In some examples, to support prediction, prediction component 730 can be configured as or otherwise support means for predicting one or more signal strength characteristics using a prediction model associated with beam management.

[0184] Figure 8A diagram illustrating a system 800 including a device 805 that supports accuracy requirements for UE-based signal strength prediction according to one or more aspects of the present disclosure is shown. The device 805 may be an example of, or include components of, a device 505, a device 605, or a UE 115 as described herein. The device 805 may communicate (e.g., wirelessly) with one or more network entities 105, one or more UEs 115, or any combination thereof. The device 805 may include components for two-way voice and data communication, including components for sending and receiving communications, such as a communication manager 820, an input / output (I / O) controller 810, a transceiver 815, an antenna 825, a memory 830, code 835, and a processor 840. These components may be in electronic communication or otherwise coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more buses (e.g., a bus 845).

[0185] I / O controller 810 can manage input and output signals for device 805. I / O controller 810 can also manage peripheral devices that are not integrated into device 805. In some cases, I / O controller 810 can represent a physical connection or port to an external peripheral device. In some cases, I / O controller 810 can utilize an operating system such as or another known operating system. Additionally or alternatively, I / O controller 810 may represent or interact with a modem, keyboard, mouse, touch screen, or similar device. In some cases, I / O controller 810 may be implemented as part of a processor, such as processor 840. In some cases, a user may interact with device 805 via I / O controller 810 or via hardware components controlled by I / O controller 810.

[0186] In some cases, the device 805 may include a single antenna 825. However, in some other cases, the device 805 may have more than one antenna 825, which may be capable of concurrently transmitting or receiving multiple wireless transmissions. The transceiver 815 may communicate bidirectionally via one or more antennas 825, a wired link, or a wireless link as described herein. For example, the transceiver 815 may represent a wireless transceiver and may communicate bidirectionally with another wireless transceiver. The transceiver 815 may also include a modem for modulating packets; providing the modulated packets to the one or more antennas 825 for transmission; and demodulating packets received from the one or more antennas 825. The transceiver 815, or the transceiver 815 and the one or more antennas 825, may be examples of the transmitter 515, the transmitter 615, the receiver 510, the receiver 610, or any combination thereof, or components thereof, as described herein.

[0187] The memory 830 may include random access memory (RAM) and read-only memory (ROM). The memory 830 may store computer-readable, computer-executable code 835 including instructions that, when executed by the processor 840, cause the device 805 to perform the various functions described herein. The code 835 may be stored in a non-transitory computer-readable medium such as system memory or another type of memory. In some cases, the code 835 may not be directly executable by the processor 840, but may (e.g., when compiled and executed) cause the computer to perform the functions described herein. In some cases, among other things, the memory 830 may also contain a basic I / O system (BIOS) that controls basic hardware or software operations, such as interaction with peripheral components or devices.

[0188] The processor 840 may include an intelligent hardware device (e.g., a general-purpose processor, a DSP, a CPU, a microcontroller, an ASIC, an FPGA, a programmable logic device, a discrete gate or transistor logic component, a discrete hardware component, or any combination thereof). In some cases, the processor 840 may be configured to operate a memory array using a memory controller. In some other cases, the memory controller may be integrated into the processor 840. The processor 840 may be configured to execute computer-readable instructions stored in a memory (e.g., a memory 830) to cause the device 805 to perform various functions (e.g., functions or tasks that support accuracy requirements for UE-based signal strength prediction). For example, the device 805 or a component of the device 805 may include a processor 840 and a memory 830 coupled to or coupled to the processor 840, the processor 840 and the memory 830 being configured to perform the various functions described herein.

[0189] According to examples disclosed herein, the communication manager 820 can support wireless communications at a UE. For example, the communication manager 820 can be configured as or otherwise support means for receiving an indication of one or more time-frequency resources associated with prediction of one or more signal strength characteristics by the UE, wherein an accuracy requirement is defined for prediction of the one or more signal strength characteristics by the UE. The communication manager 820 can be configured as or otherwise support means for predicting one or more signal strength characteristics of a beam in a set of beams relative to the one or more time-frequency resources in accordance with the accuracy requirement. The communication manager 820 can be configured as or otherwise support means for sending an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement.

[0190] By including or configuring the communication manager 820 according to the examples described herein, the device 805 can support techniques for improving the accuracy of beam management predictions, which can also increase the reliability of the beam management process. As a result, the device 805 can potentially communicate more successfully with network entities or other wireless devices based on the use of more optimal beams, which can in turn improve communication reliability and efficiency, reduce communication latency, and improve coordination between the device 805 and other wireless devices.

[0191] In some examples, the communication manager 820 can be configured to perform various operations (e.g., receive, monitor, transmit) using or otherwise coordinating with the transceiver 815, one or more antennas 825, or any combination thereof. Although the communication manager 820 is illustrated as a separate component, in some examples, one or more functions described with reference to the communication manager 820 can be supported or performed by the processor 840, the memory 830, the code 835, or any combination thereof. For example, the code 835 can include instructions that can be executed by the processor 840 to cause the device 805 to perform various aspects of the accuracy requirements for UE-based signal strength prediction as described herein, or the processor 840 and the memory 830 can be otherwise configured to perform or support such operations.

[0192] Figure 9 A flowchart illustrating a method 900 for supporting accuracy requirements for UE-based signal strength prediction according to one or more aspects of the present disclosure is illustrated. The operations of the method 900 may be implemented by a UE or components thereof as described herein. For example, the operations of the method 900 may be implemented by a UE or components thereof as described herein. Figures 1 to 8 The described functions may be performed by the UE 115. In some examples, the UE may execute an instruction set to control the functional elements of the UE to perform the described functions. Additionally or alternatively, the UE may use dedicated hardware to perform various aspects of the described functions.

[0193] At 905, the method may include receiving an indication of one or more time-frequency resources associated with predicting one or more signal strength characteristics by the UE, wherein an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE. The operations of 905 may be performed according to examples as disclosed herein. In some examples, aspects of the operations of 905 may be performed as described in reference to Figure 7 The described time-frequency resource component 725 is performed.

[0194] At 910, the method may include predicting one or more signal strength characteristics of beams in the set of beams relative to one or more time-frequency resources according to an accuracy requirement. The operations of 910 may be performed according to examples disclosed herein. In some examples, aspects of the operations of 910 may be performed as described in reference to Figure 7The prediction component 730 is described to perform.

[0195] At 915, the method may include sending an indication of the predicted one or more signal strength characteristics according to the accuracy requirement. The operations of 915 may be performed according to the examples disclosed herein. In some examples, aspects of the operations of 915 may be performed by reference to Figure 7 The prediction component 730 is described to perform.

[0196] Figure 10 A flowchart illustrating a method 1000 for supporting accuracy requirements for UE-based signal strength prediction according to one or more aspects of the present disclosure is illustrated. The operations of the method 1000 may be implemented by a UE or components thereof as described herein. For example, the operations of the method 1000 may be implemented by a UE or components thereof as described herein. Figures 1 to 8 The described functions may be performed by the UE 115. In some examples, the UE may execute an instruction set to control the functional elements of the UE to perform the described functions. Additionally or alternatively, the UE may use dedicated hardware to perform various aspects of the described functions.

[0197] At 1005, the method may include receiving an indication of one or more time-frequency resources associated with predicting one or more signal strength characteristics by the UE, wherein an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE. The operations of 1005 may be performed according to examples as disclosed herein. In some examples, aspects of the operations of 1005 may be performed as described in reference to Figure 7 The described time-frequency resource component 725 is performed.

[0198] At 1010, the method may include receiving one or more downlink reference signals via a second set of beams corresponding to a second one or more time-frequency resources. The operations of 1010 may be performed according to examples disclosed herein. In some examples, aspects of the operations of 1010 may be performed by reference to Figure 7 The described reference signal component 735 is performed.

[0199] At 1015, the method may include measuring one or more downlink reference signals to obtain a second one or more signal strength characteristics. The operations of 1015 may be performed according to examples disclosed herein. In some examples, aspects of the operations of 1015 may be performed by reference to Figure 7 The described reference signal component 735 is performed.

[0200] At 1020, the method may include predicting one or more signal strength characteristics of beams in the set of beams relative to one or more time-frequency resources according to an accuracy requirement and using a prediction model associated with beam management, wherein the prediction is based on the second one or more signal strength characteristics. The operations of 1020 may be performed according to examples as disclosed herein. In some examples, aspects of the operations of 1020 may be performed as described in reference to Figure 7 The prediction component 730 is described to perform.

[0201] At 1025, the method may include sending an indication of the predicted one or more signal strength characteristics according to the accuracy requirement. The operations of 1025 may be performed according to the examples disclosed herein. In some examples, aspects of the operations of 1025 may be performed by reference to Figure 7 The prediction component 730 is described to perform.

[0202] Figure 11 A flowchart illustrating a method 1100 for supporting accuracy requirements for UE-based signal strength prediction according to one or more aspects of the present disclosure is illustrated. The operations of the method 1100 may be implemented by a UE or components thereof as described herein. For example, the operations of the method 1100 may be implemented by a UE or components thereof as described herein. Figures 1 to 8 The described functions may be performed by the UE 115. In some examples, the UE may execute an instruction set to control the functional elements of the UE to perform the described functions. Additionally or alternatively, the UE may use dedicated hardware to perform various aspects of the described functions.

[0203] At 1105, the method may include receiving a request for a capability message indicating support for a set of one or more accuracy requirements at the UE. The operations of 1105 may be performed according to examples as disclosed herein. In some examples, aspects of the operations of 1105 may be performed as described in reference to Figure 7 The described capability message component 745 is executed.

[0204] At 1110, the method may include sending a capability message indicating support at the UE for a set of one or more accuracy requirements relative to one or more predicted signal strength characteristics, wherein sending the capability message is based on the request. The operations of 1110 may be performed according to examples as disclosed herein. In some examples, aspects of the operations of 1110 may be performed as described in reference to Figure 7 The described capability message component 745 is executed.

[0205] At 1115, the method may include receiving an indication of one or more time-frequency resources associated with predicting one or more signal strength characteristics by the UE, wherein an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE. The operations of 1115 may be performed according to examples as disclosed herein. In some examples, aspects of the operations of 1115 may be performed as described in reference to Figure 7 The described time-frequency resource component 725 is performed.

[0206] At 1120, the method may include predicting one or more signal strength characteristics of beams in the set of beams relative to one or more time-frequency resources according to an accuracy requirement. The operations of 1120 may be performed according to examples disclosed herein. In some examples, aspects of the operations of 1120 may be performed as described in reference to Figure 7 The prediction component 730 is described to perform.

[0207] At 1125, the method may include sending an indication of the predicted one or more signal strength characteristics according to the accuracy requirement. The operations of 1125 may be performed according to the examples disclosed herein. In some examples, aspects of the operations of 1125 may be performed by the reference Figure 7 The prediction component 730 is described to perform.

[0208] At 1125, the method may include sending a message indicating a confidence level associated with predicting one or more signal strength characteristics, wherein the confidence level is based on an accuracy requirement, one or more capabilities of the UE, a set of beams, a second set of beams different from the set of beams, or a combination thereof. The operations of 1125 may be performed according to examples as disclosed herein. In some examples, aspects of the operations of 1125 may be performed by a method as described in reference to Figure 7 The described confidence level component 740 is performed.

[0209] The following provides an overview of various aspects of the disclosure:

[0210] Aspect 1: A method for wireless communication at a UE, the method comprising: receiving an indication of one or more time-frequency resources associated with one or more signal strength characteristics predicted by the UE, wherein an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE; predicting the one or more signal strength characteristics of beams in a set of beams relative to the one or more time-frequency resources based on the accuracy requirement; and sending an indication of the predicted one or more signal strength characteristics based on the accuracy requirement.

[0211] Aspect 2: According to the method of Aspect 1, the method also includes: receiving one or more downlink reference signals via a second set of beams corresponding to a second one or more time-frequency resources; and measuring the one or more downlink reference signals to obtain a second one or more signal strength characteristics, wherein the prediction is at least partially based on the second one or more signal strength characteristics.

[0212] Aspect 3: A method according to Aspect 2, wherein the accuracy requirement is based at least in part on the second one or more signal strength characteristics, the numerical number of the second set of beams, the beam width associated with the second set of beams, the beam type associated with the second set of beams, the periodicity of the second set of beams at the UE, or a combination thereof.

[0213] Aspect 4: According to the method described in any one of Aspects 1 to 3, the method also includes: sending a message indicating a confidence level associated with predicting the one or more signal strength characteristics, wherein the confidence level is at least partially based on the accuracy requirement, one or more capabilities of the UE, the set of beams, a second set of beams different from the set of beams, or a combination thereof.

[0214] Aspect 5: A method according to any one of Aspects 1 to 4, wherein the accuracy requirement is based at least in part on the one or more signal strength characteristics, the numerical number of beams in the set of beams, the beam width of the beams, the beam type of the set of beams, the periodicity of the set of beams at the UE, or a combination thereof.

[0215] Aspect 6: The method according to any one of aspects 1 to 5, wherein the accuracy requirement is based at least in part on the one or more time-frequency resources and a time duration between sending the indication.

[0216] Aspect 7: The method according to any one of aspects 1 to 6, wherein the accuracy requirement is based at least in part on reference values ​​of the one or more signal strength characteristics, the reference values ​​being associated with the one or more time-frequency resources.

[0217] Aspect 8: The method of aspect 7, wherein the accuracy requirement defines a tolerance range extending above and below the reference value of the one or more signal strength characteristics, the predicted one or more signal strength characteristics falling within the tolerance range.

[0218] Aspect 9: The method according to aspect 8, wherein a lower portion of the tolerance range extending below the reference value is symmetrical with respect to an upper portion of the tolerance range extending above the reference value.

[0219] Aspect 10: The method according to aspect 8, wherein a lower portion of the tolerance range extending below the reference value is asymmetric with respect to an upper portion of the tolerance range extending above the reference value.

[0220] Aspect 11: The method according to any one of aspects 8 to 10, wherein the reference value comprises an ideal value of the one or more signal strength characteristics or a measured value of the one or more signal strength characteristics.

[0221] Aspect 12: The method according to any one of aspects 1 to 11, further comprising: sending a capability message indicating support at the UE for a set of one or more accuracy requirements with respect to the predicted signal strength characteristic.

[0222] Aspect 13: A method according to Aspect 12, wherein the support for the set of one or more accuracy requirements is based at least in part on the one or more signal strength characteristics, the numerical number of beams in the set of beams, the beam type of the set of beams, the numerical number of a second set of beams associated with the set of beams, the beam type associated with the second set of beams, one or more signal strength characteristics associated with the second set of beams, or a combination thereof.

[0223] Aspect 14: A method according to any one of Aspects 12 to 13, wherein the support for the set of one or more accuracy requirements is based at least in part on a tolerance level associated with the set of one or more accuracy requirements, a confidence level associated with the set of one or more accuracy requirements, or both.

[0224] Aspect 15: The method according to any one of aspects 12 to 14, further comprising: receiving a request for the capability message, wherein sending the capability message is based at least in part on the request.

[0225] Aspect 16: The method according to any one of aspects 1 to 15, wherein the one or more time-frequency resources are associated with SSB, CSI-RS, or a combination thereof.

[0226] Aspect 17: A method according to any one of Aspects 1 to 16, wherein the one or more time-frequency resources include one or more virtual resources associated with the beam shape of the set of beams, the beam direction of the set of beams, or a combination thereof.

[0227] Aspect 18: A method according to Aspect 17, wherein the one or more virtual resources indicate a correspondence between one or more downlink reference signals and the beam shape of the set of beams, a correspondence between the one or more downlink reference signals and the beam direction of the set of beams, or a QCL correspondence between the one or more downlink reference signals and the set of beams.

[0228] Aspect 19: The method according to any one of aspects 1 to 18, wherein the one or more signal strength characteristics include RSRP, SINR, or a combination thereof.

[0229] Aspect 20: The method according to any one of aspects 1 to 19, wherein the predicting comprises: predicting the one or more signal strength characteristics using a prediction model associated with beam management.

[0230] Aspect 21: An apparatus for wireless communication at a UE, the apparatus comprising: a processor; a memory coupled to the processor; and instructions stored in the memory and executable by the processor to cause the apparatus to perform a method according to any one of aspects 1 to 20.

[0231] Aspect 22: An apparatus for wireless communication at a UE, the apparatus comprising: at least one component for performing the method according to any one of aspects 1 to 20.

[0232] Aspect 23: A non-transitory computer-readable medium storing code for wireless communication at a UE, the code comprising instructions executable by a processor to perform the method according to any one of aspects 1 to 20.

[0233] It should be noted that the methods described herein describe possible implementations, and that the operations and steps may be rearranged or otherwise modified and that other implementations are possible. Furthermore, aspects from two or more methods may be combined.

[0234] Although aspects of LTE, LTE-A, LTE-A Pro, or NR systems may be described for example purposes, and the terminology of LTE, LTE-A, LTE-A Pro, or NR may be used throughout much of the description, the techniques described herein may also be applicable to networks other than LTE, LTE-A, LTE-A Pro, or NR networks. For example, the techniques described may be applicable to various other wireless communication systems, such as Ultra Mobile Broadband (UMB), Institute of Electrical and Electronics Engineers (IEEE) 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20, Flash-OFDM, and other systems and radio technologies not explicitly mentioned herein.

[0235] The information and signals described herein may be represented by any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips referred to throughout the description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

[0236] The various illustrative blocks and components described in conjunction with the disclosure herein may be implemented or executed using a general purpose processor, a DSP, an ASIC, a CPU, an FPGA or other programmable logic device, discrete gate or transistor logic components, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices (e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors combined with a DSP core, or any other such configuration).

[0237] The functions described herein may be implemented using hardware, software executed by a processor, firmware, or any combination thereof. If implemented using software executed by a processor, the functions may be stored as one or more instructions or codes of a computer-readable medium, or sent using one or more instructions or codes of a computer-readable medium. Other examples and implementations are within the scope of this disclosure and the appended claims. For example, due to the nature of software, the functions described herein may be implemented using software executed by a processor, hardware, firmware, hard wiring, or a combination of any of these. Features that implement the functions may also be physically located at different locations, including being distributed so that various parts of the functions are implemented at different physical locations.

[0238] Computer-readable media includes both non-transient computer storage media and communication media, and the communication media includes any medium that promotes a computer program to be transferred from one location to another.Non-transient storage media can be any available medium that can be accessed by a general or special-purpose computer.By way of example and not limitation, non-transient computer-readable media can include RAM, ROM, electrically erasable programmable ROM (EEPROM), flash memory, compact disc (CD) ROM or other optical disc storage devices, magnetic disk storage devices or other magnetic storage devices, or can be used for carrying or storing desired program code components and any other non-transient medium that can be accessed by a general or special-purpose computer or a general or special-purpose processor in the form of an instruction or data structure.Moreover, any connection is appropriately referred to as computer-readable media.For example, if software is sent from a website, a server or other remote source using a coaxial cable, a fiber optic cable, a twisted pair, a digital subscriber line (DSL) or a wireless technology such as infrared, radio and microwave, then the coaxial cable, the fiber optic cable, the twisted pair, the DSL or the wireless technology such as infrared, radio and microwave are included in the definition of computer-readable media. As used herein, disks and optical discs include CDs, laser discs, optical discs, digital versatile discs (DVDs), floppy disks, and Blu-ray discs. Magnetic disks can reproduce data magnetically, and optical discs can reproduce data optically using lasers. Combinations of the above are also included within the scope of computer-readable media.

[0239] As used herein (including in the claims), "or" used in a list of items (e.g., a list of items followed by a phrase such as "at least one of" or "one or more of") indicates an inclusive list, so that, for example, a list of at least one of A, B, or C means A or B or C or AB or AC or BC or ABC (i.e., A and B and C). In addition, as used herein, the phrase "based on" should not be interpreted as a reference to a closed set of conditions. For example, an example step described as "based on condition A" could be based on both condition A and condition B without departing from the scope of this disclosure. In other words, as used herein, the phrase "based on" should be interpreted in the same manner as the phrase "based at least in part on."

[0240] The term "determining" encompasses a variety of actions, and thus, "determining" may include calculating, computing, processing, deriving, investigating, looking up (such as via looking up in a table, database, or other data structure), ascertaining, and the like. Furthermore, "determining" may include receiving (e.g., receiving information), accessing (e.g., accessing data stored in a memory), etc. Furthermore, "determining" may include resolving, retrieving, selecting, choosing, establishing, and other such similar actions.

[0241] In the drawings, similar components or features may have the same reference label. In addition, various components of the same type may be distinguished by following the reference label with a dash and a second label to distinguish between similar components. If only the first reference label is used in the specification, the description can apply to any of the similar components having the same first reference label, regardless of the second reference label or other subsequent reference labels.

[0242] The description set forth herein in conjunction with the accompanying drawings describes example configurations and does not represent all examples that may be implemented or within the scope of the claims. The term "example" as used herein means "serving as an example, instance, or illustration," rather than "preferred" or "having advantages over other examples." The detailed description includes specific details to provide an understanding of the described techniques. However, these techniques can be practiced without these specific details. In some cases, known structures and devices are shown in block diagram form to avoid obscuring the concepts of the described examples.

[0243] The description herein is provided to enable one of ordinary skill in the art to make or use the present disclosure. Various modifications to the present disclosure will be apparent to those of ordinary skill in the art, and the general principles defined herein may be applied to other variations without departing from the scope of the present disclosure. Thus, the present disclosure is not limited to the examples and designs described herein, but should be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An apparatus for wireless communication at a user equipment (UE), the apparatus comprising: processor; a memory coupled to the processor; and instructions stored in the memory and executable by the processor to cause the apparatus to: receiving an indication of one or more time-frequency resources associated with predicting, by the UE, one or more signal strength characteristics, wherein an accuracy requirement is defined for predicting, by the UE, the one or more signal strength characteristics; predicting, according to the accuracy requirement, the one or more signal strength characteristics of beams in the set of beams relative to the one or more time-frequency resources; as well as An indication of the predicted one or more signal strength characteristics according to the accuracy requirement is sent.

2. The apparatus of claim 1 , wherein the instructions are further executable by the processor to cause the apparatus to: receiving one or more downlink reference signals via a second set of beams corresponding to a second one or more time-frequency resources; and The one or more downlink reference signals are measured to obtain second one or more signal strength characteristics, wherein the predicting is based at least in part on the second one or more signal strength characteristics.

3. An apparatus according to claim 2, wherein the accuracy requirement is based at least in part on the second one or more signal strength characteristics, the numerical number of the second set of beams, the beamwidth associated with the second set of beams, the beam type associated with the second set of beams, the periodicity of the second set of beams at the UE, or a combination thereof.

4. The apparatus of claim 1 , wherein the instructions are further executable by the processor to cause the apparatus to: Sending a message indicating a confidence level associated with predicting the one or more signal strength characteristics, wherein the confidence level is based at least in part on the accuracy requirement, one or more capabilities of the UE, the set of beams, a second set of beams different from the set of beams, or a combination thereof.

5. The apparatus of claim 1 , wherein the accuracy requirement is based at least in part on the one or more signal strength characteristics, a numerical number of beams in the set of beams, a beamwidth of the beams, a beam type of the set of beams, a periodicity of the set of beams at the UE, or a combination thereof.

6. The apparatus of claim 1, wherein the accuracy requirement is based at least in part on a time duration between the one or more time-frequency resources and sending the indication.

7. The apparatus of claim 1, wherein the accuracy requirement is based at least in part on reference values ​​of the one or more signal strength characteristics, the reference values ​​being associated with the one or more time-frequency resources.

8. The apparatus according to claim 7, wherein: The accuracy requirement defines a tolerance range extending above and below the reference value of the one or more signal strength characteristics, and The predicted one or more signal strength characteristics fall within the tolerance range. 9 . The apparatus of claim 8 , wherein a lower portion of the tolerance range extending below the reference value is symmetrical with respect to an upper portion of the tolerance range extending above the reference value. 10 . The apparatus of claim 8 , wherein a lower portion of the tolerance range extending below the reference value is asymmetric with respect to an upper portion of the tolerance range extending above the reference value. 11 . The apparatus of claim 8 , wherein the reference value comprises an ideal value of the one or more signal strength characteristics or a measured value of the one or more signal strength characteristics.

12. The apparatus of claim 1 , wherein the instructions are further executable by the processor to cause the apparatus to: A capability message is sent, the capability message indicating support at the UE for a set of one or more accuracy requirements relative to the predicted signal strength characteristic.

13. An apparatus according to claim 12, wherein the support for the set of one or more accuracy requirements is based at least in part on the one or more signal strength characteristics, the numerical number of beams in the set of beams, the beam type of the set of beams, the numerical number of a second set of beams associated with the set of beams, the beam type associated with the second set of beams, one or more signal strength characteristics associated with the second set of beams, or a combination thereof.

14. The apparatus of claim 12, wherein the support for the set of one or more accuracy requirements is based at least in part on a tolerance level associated with the set of one or more accuracy requirements, a confidence level associated with the set of one or more accuracy requirements, or both.

15. The apparatus of claim 12, wherein the instructions are further executable by the processor to cause the apparatus to: A request for the capabilities message is received, wherein sending the capabilities message is based at least in part on the request.

16. The apparatus of claim 1, wherein the one or more time-frequency resources are associated with a synchronization signal block, a channel state information reference signal, or a combination thereof.

17. The apparatus of claim 1, wherein the one or more time-frequency resources comprise one or more virtual resources associated with a beam shape of the set of beams, a beam direction of the set of beams, or a combination thereof.

18. An apparatus according to claim 17, wherein the one or more virtual resources indicate a correspondence between one or more downlink reference signals and the beam shape of the set of beams, a correspondence between the one or more downlink reference signals and the beam direction of the set of beams, or a quasi-co-location correspondence between the one or more downlink reference signals and the set of beams.

19. The apparatus of claim 1, wherein the one or more signal strength characteristics comprise a reference signal received power, a signal to interference plus noise ratio, or a combination thereof.

20. The apparatus of claim 1, wherein the instructions for predicting are executable by the processor to cause the apparatus to: The one or more signal strength characteristics are predicted using a prediction model associated with beam management.

21. A method for wireless communication at a user equipment (UE), the method comprising: receiving an indication of one or more time-frequency resources associated with predicting, by the UE, one or more signal strength characteristics, wherein an accuracy requirement is defined for predicting, by the UE, the one or more signal strength characteristics; predicting the one or more signal strength characteristics of beams in the set of beams relative to the one or more time-frequency resources according to the accuracy requirement; and An indication of the predicted one or more signal strength characteristics according to the accuracy requirement is sent.

22. The method according to claim 21, further comprising: receiving one or more downlink reference signals via a second set of beams corresponding to a second one or more time-frequency resources; as well as The one or more downlink reference signals are measured to obtain second one or more signal strength characteristics, wherein the predicting is based at least in part on the second one or more signal strength characteristics.

23. A method according to claim 22, wherein the accuracy requirement is based at least in part on the second one or more signal strength characteristics, the numerical number of the second set of beams, the beamwidth associated with the second set of beams, the beam type associated with the second set of beams, the periodicity of the second set of beams at the UE, or a combination thereof.

24. The method according to claim 21, further comprising: Sending a message indicating a confidence level associated with predicting the one or more signal strength characteristics, wherein the confidence level is based at least in part on the accuracy requirement, one or more capabilities of the UE, the set of beams, a second set of beams different from the set of beams, or a combination thereof.

25. The method of claim 21 , wherein the accuracy requirement is based at least in part on the one or more signal strength characteristics, the numerical number of beams in the set of beams, the beamwidth of the beams, the beam type of the set of beams, the periodicity of the set of beams at the UE, or a combination thereof.

26. The method of claim 21, wherein the accuracy requirement is based at least in part on a time duration between the one or more time-frequency resources and sending the indication.

27. The method of claim 21, wherein the accuracy requirement is based at least in part on reference values ​​of the one or more signal strength characteristics, the reference values ​​being associated with the one or more time-frequency resources.

28. The method of claim 27, wherein: the accuracy requirement defining a tolerance range extending above and below the reference value of the one or more signal strength characteristics; and The predicted one or more signal strength characteristics fall within the tolerance range. 29 . The method of claim 28 , wherein a lower portion of the tolerance range extending below the reference value is symmetrical with respect to an upper portion of the tolerance range extending above the reference value.

30. The method of claim 28, wherein a lower portion of the tolerance range extending below the reference value is asymmetric with respect to an upper portion of the tolerance range extending above the reference value.

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