WO2024168592A1

WO2024168592A1 - Accuracy requirements for user equipment-based signal strength predictions

Info

Publication number: WO2024168592A1
Application number: PCT/CN2023/076206
Authority: WO
Inventors: Qiaoyu Li; Wooseok Nam; Mahmoud Taherzadeh Boroujeni; Hamed Pezeshki; Changhwan Park
Original assignee: Qualcomm Incorporated
Priority date: 2023-02-15
Filing date: 2023-02-15
Publication date: 2024-08-22

Abstract

Methods, systems, and devices for wireless communications are described. An accuracy requirement 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 for a beam of a set of beams with respect 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

ACCURACY REQUIREMENTS FOR USER EQUIPMENT-BASED SIGNAL STRENGTH PREDICTIONS

FIELD OF TECHNOLOGY

The following relates to wireless communications, including accuracy requirements for user equipment-based signal strength predictions.

BACKGROUND

Wireless communications systems are widely deployed to provide various types of communication content such as voice, video, packet data, messaging, broadcast, and so on. These systems may be capable of supporting communication with multiple users by sharing the 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, LTE-Advanced (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 communications system may include one or more network entities, each supporting wireless communication for communication devices, which may be known as user equipment (UE) .

In some wireless communications systems, a network entity and a user equipment (UE) may support beamforming techniques and may communicate using one or more directional beams. To maintain reliable communications between the network entity and the UE, the network entity and the UE may perform a beam management procedure. In performing the beam management procedure, the UE may measure one or more reference signals transmitted by the network entity, corresponding to one or more beams, and report channel conditions for the one or more beams back to the network entity.

SUMMARY

The described techniques relate to improved methods, systems, devices, and apparatuses that support accuracy requirements for user equipment (UE) -based signal strength predictions. For example, the described techniques provide definitions for signal strength accuracy requirements when the signal strengths are predicted by a UE. The UE may receive an indication of one or more resources (e.g., time-frequency resources) associated with UE prediction of one or more signal strength characteristics, such as a reference signal received power (RSRP) , a signal-to-interference-plus-noise ratio (SINR) , or the like. The UE may predict the one or more signal strength characteristics for a beam of a set of beams with respect to the one or more resources in accordance with an accuracy requirement. The accuracy requirement may be defined as a tolerance range with respect 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. The one or more resources may, in some examples, be synchronization signal block (SSB) resources or channel state information (CSI) reference signal (CSI-RS) resources, or may be virtual resources that indicate beam information for the set of beams.

The UE may transmit an indication of the predicted one or more signal strength requirements in accordance with 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, a second set of beams, or the like. Additionally, in some examples, the UE may transmit an indication of the one or more capabilities of the UE for the accuracy requirement and based on the one or more signal strength characteristics.

A method for wireless communications 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, where an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE, predicting, in accordance with the accuracy requirement, the one or more signal strength characteristics for a beam of a set of beams with respect to the one or more time-frequency resources, and transmitting an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement.

An apparatus for wireless communications at a UE is described. The apparatus may include a processor, memory coupled with 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 predicting one or more signal strength characteristics by the UE, where an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE, predict, in accordance with the accuracy requirement, the one or more signal strength characteristics for a beam of a set of beams with respect to the one or more time-frequency resources, and transmit an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement.

Another apparatus for wireless communications at a UE is described. The apparatus may include means for receiving an indication of one or more time-frequency resources associated with predicting one or more signal strength characteristics by the UE, where an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE, means for predicting, in accordance with the accuracy requirement, the one or more signal strength characteristics for a beam of a set of beams with respect to the one or more time-frequency resources, and means for transmitting an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement.

A non-transitory computer-readable medium storing code for wireless communications 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, where an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE, predict, in accordance with the accuracy requirement, the one or more signal strength characteristics for a beam of a set of beams with respect to the one or more time-frequency resources, and transmit an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement.

Some examples of the method, apparatuses, and non-transitory computer-readable medium described herein may further include operations, features, means, or instructions for receiving, via a second set of beams corresponding to a second one or more time-frequency resources, one or more downlink reference signals and measuring the one or more downlink reference signals to obtain a second one or more signal strength characteristics, where the predicting may be based on the second one or more signal strength characteristics.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, the accuracy requirement may be based on the second one or more signal strength characteristics, a numerical quantity 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.

Some examples of the method, apparatuses, and non-transitory computer-readable medium described herein may further include operations, features, means, or instructions for transmitting a message indicating a confidence level associated with predicting the one or more signal strength characteristics, where 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.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, the accuracy requirement may be based on the one or more signal strength characteristics, a numerical quantity of beams of 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 of the method, apparatuses, and non-transitory computer-readable medium described herein, the accuracy requirement may be based on a time duration between the one or more time-frequency resources and transmitting the indication.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, the accuracy requirement may be based on a reference value for the one or more signal strength characteristics, the reference value associated with the one or more time-frequency resources.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, the accuracy requirement defines a tolerance range extending above and below the reference value for the one or more signal strength characteristics and the predicted one or more signal strength characteristics fall within the tolerance range.

In some examples of the method, apparatuses, and non-transitory computer-readable medium 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.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, a lower portion of the tolerance range extending below the reference value may be asymmetric with respect to an upper portion of the tolerance range extending above the reference value.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, the reference value includes an ideal value for the one or more signal strength characteristics or a measured value of the one or more signal strength characteristics.

Some examples of the method, apparatuses, and non-transitory computer-readable medium described herein may further include operations, features, means, or instructions for transmitting a capability message indicating a support for a set of one or more accuracy requirements at the UE with respect to the predicted signal strength characteristics.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, the support for the set of one or more accuracy requirements may be based on the one or more signal strength characteristics, a numerical quantity of beams of the set of beams, a beam type of the set of beams, a numerical quantity 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 of the method, apparatuses, and non-transitory computer-readable medium 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.

Some examples of the method, apparatuses, and non-transitory computer-readable medium described herein may further include operations, features, means, or instructions for receiving a request for the capability message, where transmitting the capability message may be based on the request.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, the one or more time-frequency resources may be associated with an SSB, a CSI-RS, or a combination thereof.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, the one or more time-frequency resources include one or more virtual resources that may be associated with a beam shape of the set of beams, a beam direction of the set of beams, or a combination thereof.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, the one or more virtual resources indicate a correspondence between one or more downlink reference signals and a beam shape of the set of beams, a correspondence between the one or more downlink reference signals and a beam direction of the set of beams, or a quasi co-location (QCL) correspondence between the one or more downlink reference signals and the set of beams.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, the one or more signal strength characteristics include an RSRP, an SINR, or a combination thereof.

In some examples of the method, apparatuses, and non-transitory computer-readable medium described herein, the predicting may include operations, features, means, or instructions for predicting the one or more signal strength characteristics using a predictive model associated with beam management.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example of a wireless communications system that supports accuracy requirements for user equipment (UE) -based signal strength predictions in accordance with one or more aspects of the present disclosure.

FIG. 2 illustrates an example of a beam management procedure that supports accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure.

FIGs. 3A and 3B illustrate examples of signal strength prediction procedures that support accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure.

FIGs. 4A, 4B, and 4C illustrate examples of accuracy requirement diagrams that support accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure.

FIGs. 5 and 6 illustrate block diagrams of devices that support accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure.

FIG. 7 illustrates a block diagram of a communications manager that supports accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure.

FIG. 8 illustrates a diagram of a system including a device that supports accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure.

FIGs. 9 through 11 illustrate flowcharts showing methods that support accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure.

DETAILED DESCRIPTION

In some wireless communications systems, such as systems that support millimeter wave (mmW) communications (e.g., new radio (NR) systems) , wireless communication devices (e.g., network entities, transmission/reception points (TRPs) , user equipments (UEs) ) may communicate via directional transmissions (e.g., beams) . For example, communications between wireless devices operating within a wireless communications system may be carried out via beamforming. In such cases, some wireless devices (e.g., the network entities and the 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.

To support reliable communications between wireless devices, the wireless devices may perform beam management, which may refer to a set of Layer 1 (L1) and Layer 2 (L2) procedures used to establish and maintain an optimal or best available beam pair (e.g., a transmit beam and a receive beam) . Such procedures may include, for example, beam switching, beam failure recovery, and beam sweeping. For example, a network entity may transmit one or more reference signals (e.g., channel state information (CSI) reference signals (CSI-RSs) , 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, such as signal strength characteristics (e.g., reference signal received power (RSRP) , signal-to-interference-plus-noise ratio (SINR) ) , channel state parameters, and the like, associated with the one or more beams. The network entity and the UE may determine one or more best beams to use for communications based on the measurements and the CSI report. For example, at initial access, the network entity and the UE may establish communications by selecting a best beam pair. After a connection has been established, the network entity and the UE may perform beam refinement and beam switching to switch to a best beam.

In some examples, the UE may utilize a predictive model (e.g., a machine learning algorithm, an artificial intelligence algorithm) to proactively predict a best one or more beams, a beam event (e.g., a beam switch event, a beam failure event) , or measurements or characteristics of one or more beams for which the UE does not have resources (e.g., time resources, frequency resources, or processing resources) to physically measure. Using a predictive model in this way may reduce or eliminate overhead and latencies associated with beam management procedures. The predictive model may take as input one or more parameters, such as real-time channel measurements, past channel measurements, and side information (different from and in addition to the channel measurements) , or a combination of these. 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 an ideal value of the one or more signal strength characteristics.

Determination and prediction of such signal strength characteristics may depend on a frequency bandwidth and a time duration in which the signal strength characteristics are calculated by the UE. Further, various accuracy requirements may be defined such that the UE calculates a signal strength characteristic in accordance with a corresponding accuracy requirement. The techniques described herein support accuracy requirements for UE-predicted signal strength characteristics, such as RSRP, SINR, and the like. For instance, a UE may predict a signal strength characteristic for a first set of one or more beams and a first set of resources (e.g., time-frequency resources) with respect to a reference value associated with the first set of resources and according to a corresponding accuracy requirement. The accuracy requirement may be defined as a tolerance range in decibels (dB) with respect to the reference value. In some cases, the reference value may be an ideal value, also referred to as a genie value, for the signal strength characteristic. In other cases, the reference value may be a measured value obtained by the UE, e.g., 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.

In some examples, the accuracy requirement may be based on conditions associated with the first set of one or more beams, conditions associated with the second set of one or more beams, or a combination thereof. In some cases, the UE may transmit a capability message (e.g., to a network entity) to indicate a set of accuracy requirements achievable by the UE, for example, based on the conditions and on predictive models supported by the UE. Further, the UE may determine a confidence level associated with a given accuracy requirement, where the confidence level may indicate a likelihood that a predicted signal strength characteristic satisfies the accuracy requirement.

Particular aspects of the subject matter described herein may be implemented to realize one or more potential advantages by facilitating improved beam management procedures between the network entity and the UE. As such, the network entity may more optimally select a beam to use for communications between the network entity and the UE. The network entity and the UE may experience a greater likelihood for successful communications based on a more optimal beam selection, which may lead to 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 a network entity, or the UE, or both, to proactively switch active beams (e.g., one or more of a transmit beam or 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 decreased communications latency, among other benefits.

Aspects of the disclosure are initially described in the context of wireless communications systems. Aspects of the disclosure are then discussed with reference to a beam management procedure, signal strength prediction procedures, and accuracy requirement diagrams. Aspects of the disclosure are further illustrated by and described with reference to apparatus diagrams, system diagrams, and flowcharts that relate to accuracy requirements for UE-based signal strength predictions.

FIG. 1 illustrates an example of a wireless communications system 100 that supports accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure. The wireless communications 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 communications 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 in accordance with other systems and radio technologies, including future systems and radio technologies not explicitly mentioned herein.

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

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

As described herein, a node of the wireless communications system 100, which may be referred to as a network node, or a 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, a node may be a UE 115. As another example, a 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 yet other aspects of this example, the first, second, and third nodes may be different relative to these examples. Similarly, reference to a UE 115, network entity 105, apparatus, device, computing system, or the like may include disclosure of the UE 115, network entity 105, apparatus, device, computing system, or the like being a node. For example, disclosure that a UE 115 is configured to receive information from a network entity 105 also discloses that a first node is configured to receive information from a second node.

In some examples, network entities 105 may communicate with the core network 130, or with one another, or both. For example, network entities 105 may communicate with the core network 130 via one or more backhaul communication links 120 (e.g., in accordance with an S1, N2, N3, or other interface protocol) . In some examples, network entities 105 may communicate with one another via a backhaul communication link 120 (e.g., in accordance with an X2, Xn, or other interface protocol) either directly (e.g., directly between network entities 105) or indirectly (e.g., via a core network 130) . In some examples, network entities 105 may communicate with one another via a midhaul communication link 162 (e.g., in accordance with a midhaul interface protocol) or a fronthaul communication link 168 (e.g., in accordance with a fronthaul interface protocol) , or any combination thereof. The backhaul communication links 120, midhaul communication links 162, or fronthaul communication links 168 may be or include one or more wired links (e.g., an electrical link, an optical fiber link) , one or more wireless links (e.g., a radio link, a wireless optical link) , among other examples or various combinations thereof. A UE 115 may communicate with the core network 130 via a communication link 155.

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 base transceiver station, a radio base station, an NR base station, an access point, a radio transceiver, a NodeB, an eNodeB (eNB) , a next-generation NodeB or a giga-NodeB (either of which may be referred to as a gNB) , a 5G NB, a next-generation eNB (ng-eNB) , a Home NodeB, a Home eNodeB, or other suitable terminology) . In some examples, a network entity 105 (e.g., a base station 140) may be implemented in an aggregated (e.g., monolithic, standalone) base station architecture, which 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 a base station 140) .

In some examples, a network entity 105 may be implemented in a disaggregated architecture (e.g., a disaggregated base station architecture, a disaggregated RAN architecture) , which may be configured to utilize a protocol stack that is physically or logically distributed among 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, a network entity 105 may include one or more of 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. An RU 170 may also be referred to as a radio head, a smart radio head, a remote radio head (RRH) , a remote radio unit (RRU) , or a transmission reception point (TRP) . One or more components of the network entities 105 in a disaggregated RAN architecture may be co-located, or one or more components of the network entities 105 may be located in distributed locations (e.g., separate physical locations) . In some examples, one or more network entities 105 of a disaggregated RAN architecture may be implemented as virtual units (e.g., a virtual CU (VCU) , a virtual DU (VDU) , a virtual RU (VRU) ) .

The split of functionality between a CU 160, a DU 165, and an RU 170 is flexible and may support different functionalities depending on which functions (e.g., network layer functions, protocol layer functions, baseband functions, RF functions, and any combinations thereof) are performed at a CU 160, a DU 165, or an RU 170. For example, a functional split of a protocol stack may be employed between a CU 160 and a DU 165 such that the CU 160 may support one or more layers of the protocol stack and the DU 165 may support one or more different layers of the protocol stack. In some examples, the CU 160 may host upper protocol layer (e.g., layer 3 (L3) , layer 2 (L2) ) functionality and signaling (e.g., Radio Resource Control (RRC) , service data adaption 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 a DU 165 and an 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 multiple different cells (e.g., via one or more RUs 170) . In some cases, a functional split between a CU 160 and a DU 165, or between a DU 165 and an RU 170 may be within a protocol layer (e.g., some functions for a protocol layer may be performed by one of a CU 160, a DU 165, or an RU 170, while other functions of the protocol layer are performed by a different one of the CU 160, the DU 165, or the RU 170) . A CU 160 may be functionally split further into CU control plane (CU-CP) and CU user plane (CU-UP) functions. A CU 160 may be connected to one or more DUs 165 via a midhaul communication link 162 (e.g., F1, F1-c, F1-u) , and a DU 165 may be connected to one or more RUs 170 via a fronthaul communication link 168 (e.g., open fronthaul (FH) interface) . In some examples, a midhaul communication link 162 or a fronthaul communication link 168 may be implemented in accordance with an interface (e.g., a channel) between layers of a protocol stack supported by respective network entities 105 that are in communication via such communication links.

In wireless communications systems (e.g., wireless communications system 100) , infrastructure and spectral resources for radio access may support wireless backhaul link capabilities to supplement wired backhaul connections, providing an IAB network architecture (e.g., to a 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 an 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) . The one or more donor network entities 105 (e.g., IAB donors) may be in communication 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) . IAB nodes 104 may include an IAB mobile termination (IAB-MT) controlled (e.g., scheduled) by DUs 165 of a coupled IAB donor. An IAB-MT may include an independent set of antennas for relay of communications with UEs 115, or may share the same antennas (e.g., of an RU 170) of an IAB node 104 used for access via the DU 165 of the IAB node 104 (e.g., referred to as virtual IAB-MT (vIAB-MT) ) . In some examples, the IAB nodes 104 may include DUs 165 that support communication links with additional entities (e.g., IAB nodes 104, UEs 115) within the relay chain or configuration of the access network (e.g., downstream) . In such cases, one or more components of the disaggregated RAN architecture (e.g., one or more IAB nodes 104 or components of IAB nodes 104) may be configured to operate according to the techniques described herein.

For instance, an access network (AN) or RAN may include communications between access nodes (e.g., an IAB donor) , IAB nodes 104, and one or more UEs 115. The IAB donor may facilitate connection between the core network 130 and the AN (e.g., via a wired or wireless connection to the core network 130) . That is, an IAB donor may refer to a RAN node with a wired or wireless connection to 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) . IAB donor and IAB nodes 104 may communicate via an F1 interface according to a protocol that defines signaling messages (e.g., an F1 AP protocol) . Additionally, or alternatively, the CU 160 may communicate with the core network via an interface, which may be an example of a portion of backhaul link, and may communicate with other CUs 160 (e.g., a CU 160 associated with an alternative IAB donor) via an Xn-C interface, which may be an example of a portion of a backhaul link.

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

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

In the case of the techniques described herein applied in the context of a disaggregated RAN architecture, one or more components of the disaggregated RAN architecture may be configured to support accuracy requirements for user equipment-based signal strength predictions 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., IAB nodes 104, DUs 165, CUs 160, RUs 170, RIC 175, SMO 180) .

A 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 the “device” may also be referred to as a unit, a station, a terminal, or a client, among other examples. A 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, a UE 115 may include or 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 communications (MTC) device, among other examples, which may be implemented in various objects such as appliances, or vehicles, meters, among other examples.

The UEs 115 described herein may be able to communicate with various types of devices, such as other UEs 115 that may sometimes act as relays as well as the network entities 105 and the network equipment including macro eNBs or gNBs, small cell eNBs or gNBs, or relay base stations, among other examples, as shown in FIG. 1.

The UEs 115 and the network entities 105 may wirelessly communicate with one another via one or more communication links 125 (e.g., an access link) using resources associated with one or more carriers. The term “carrier” may refer to a set of RF spectrum resources having a defined physical layer structure for supporting the communication links 125. For example, a carrier used for a communication link 125 may include a portion of a RF spectrum band (e.g., a bandwidth part (BWP) ) that is operated 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 that coordinates operation for the carrier, user data, or other signaling. The wireless communications system 100 may support communication with a UE 115 using carrier aggregation or multi-carrier operation. A UE 115 may be configured with multiple downlink component carriers and one or more uplink component carriers according to a carrier aggregation configuration. Carrier aggregation may be used with both frequency division duplexing (FDD) and time division duplexing (TDD) component carriers. Communication between a network entity 105 and other devices may refer to communication between the devices and any portion (e.g., entity, sub-entity) of a network entity 105. For example, the terms “transmitting, ” “receiving, ” or “communicating, ” when referring to a network entity 105, may refer to any portion of a network entity 105 (e.g., a base station 140, a CU 160, a DU 165, a RU 170) of a RAN communicating with another device (e.g., directly or via one or more other network entities 105) .

In some examples, such as in a carrier aggregation configuration, a carrier may also have acquisition signaling or control signaling that coordinates operations for other carriers. A carrier may be associated with a frequency channel (e.g., an evolved universal mobile telecommunication system terrestrial radio access (E-UTRA) absolute RF channel number (EARFCN) ) and may be identified according to a channel raster for discovery by the UEs 115. A carrier may be operated in a standalone mode, in which case initial acquisition and connection may be conducted by the UEs 115 via the carrier, or the carrier may be operated in a non-standalone mode, in which case a connection is anchored using a different carrier (e.g., of the same or a different radio access technology) .

The communication links 125 shown in the wireless communications system 100 may include downlink transmissions (e.g., forward link transmissions) from a network entity 105 to a UE 115, uplink transmissions (e.g., return link transmissions) from a UE 115 to a network entity 105, or both, among other configurations of transmissions. Carriers may carry downlink or uplink communications (e.g., in an FDD mode) or may be configured to carry downlink and uplink communications (e.g., in a TDD mode) .

A carrier may be associated with a particular bandwidth of the RF spectrum and, in some examples, the carrier bandwidth may be referred to as a “system bandwidth” of the carrier or the wireless communications system 100. For example, the carrier bandwidth may be one of a set of bandwidths for carriers of a particular radio access technology (e.g., 1.4, 3, 5, 10, 15, 20, 40, or 80 megahertz (MHz) ) . Devices of the wireless communications system 100 (e.g., the network entities 105, the UEs 115, or both) may have hardware configurations that support communications using a particular carrier bandwidth or may be configurable to support communications using one of a set of carrier bandwidths. In some examples, the wireless communications system 100 may include network entities 105 or UEs 115 that support concurrent communications using carriers associated with multiple carrier bandwidths. In some examples, each served UE 115 may be configured for operating using portions (e.g., a sub-band, a BWP) or all of a carrier bandwidth.

Signal waveforms transmitted via a carrier may be made up of multiple subcarriers (e.g., using multi-carrier modulation (MCM) techniques 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 resources of one symbol period (e.g., a duration of one modulation symbol) and one subcarrier, in which case the symbol period and subcarrier spacing may be inversely related. The quantity 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 higher quantity of resource elements (e.g., in a transmission duration) and a relatively higher order of a modulation scheme may correspond to a relatively higher rate of communication. A wireless communications resource may refer to a combination of an RF spectrum resource, a time resource, and a spatial resource (e.g., a spatial layer, a beam) , and the use of multiple spatial resources may increase the data rate or data integrity for communications with a UE 115.

One or more numerologies for a carrier may be supported, and a numerology may include a subcarrier spacing (Δf) and a cyclic prefix. A carrier may be divided into one or more BWPs having the same or different numerologies. 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 for the UE 115 may be restricted to one or more active BWPs.

The time intervals for the network entities 105 or the UEs 115 may be expressed in multiples of a basic time unit which may, for example, refer to a sampling period of T_s=1/ (Δf_max·N_f) seconds, for which Δf_max may represent a supported subcarrier spacing, and N_f may represent a supported discrete Fourier transform (DFT) size. Time intervals of a communications resource 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., ranging from 0 to 1023) .

Each frame may include multiple consecutively-numbered subframes or slots, and each subframe or 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 quantity of slots. Alternatively, each frame may include a variable quantity of slots, and the quantity of slots may depend on subcarrier spacing. Each slot may include a quantity of symbol periods (e.g., depending on the length of the cyclic prefix prepended to each symbol period) . In some wireless communications systems 100, a slot may further be divided into multiple mini-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) sampling periods. The duration of a symbol period may depend on the subcarrier spacing or frequency band of operation.

A subframe, a slot, a mini-slot, or a symbol may be the smallest scheduling unit (e.g., in the time domain) of the wireless communications system 100 and may be referred to as a transmission time interval (TTI) . In some examples, the TTI duration (e.g., a quantity of symbol periods in a TTI) may be variable. Additionally, or alternatively, the smallest scheduling unit of the wireless communications system 100 may be dynamically selected (e.g., in bursts of shortened TTIs (sTTIs) ) .

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

A network entity 105 may provide communication coverage via one or more cells, for example a macro cell, a small cell, a hot spot, or other types of cells, or any combination thereof. The term “cell” may refer to a logical communication entity used for communication with a network entity 105 (e.g., using a carrier) and may be associated with an identifier for distinguishing neighboring cells (e.g., a physical cell identifier (PCID) , a virtual cell identifier (VCID) , or others) . In some examples, a cell also may refer to a coverage area 110 or a portion of a coverage area 110 (e.g., a sector) over which the logical communication entity operates. Such cells may range from smaller areas (e.g., a structure, a subset of structure) to larger areas depending on various factors such as the capabilities of the network entity 105. For example, a cell may be or include a building, a subset of a building, or exterior spaces between or overlapping with coverage areas 110, among other examples.

A macro cell generally covers a relatively large geographic area (e.g., several kilometers in radius) and may allow unrestricted access by the UEs 115 with service subscriptions with the network provider supporting the macro cell. A small cell may be associated with a lower-powered network entity 105 (e.g., a lower-powered base station 140) , as compared with a macro cell, and a small cell may operate using the same or different (e.g., licensed, unlicensed) frequency bands as macro cells. Small cells may provide unrestricted access to the UEs 115 with service subscriptions with the network provider or may provide restricted access to the UEs 115 having an association with the small cell (e.g., the UEs 115 in a closed subscriber group (CSG) , the UEs 115 associated with users in a home or office) . A network entity 105 may support one or multiple cells and may also support communications via the one or more cells using one or multiple component carriers.

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 for different types of devices.

In some examples, a network entity 105 (e.g., a base station 140, an RU 170) may be movable and therefore provide communication coverage for a moving coverage area 110. In some examples, different coverage areas 110 associated with different technologies may overlap, but the different coverage areas 110 may be supported by the same network entity 105. In some other examples, the overlapping coverage areas 110 associated with different technologies may be supported by different network entities 105. The wireless communications system 100 may include, for example, a heterogeneous network in which different types of the network entities 105 provide coverage for various coverage areas 110 using the same or different radio access technologies.

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

Some UEs 115, such as MTC or IoT devices, may be low cost or low complexity devices and may provide for automated communication between machines (e.g., via Machine-to-Machine (M2M) communication) . M2M communication or MTC may refer to data communication technologies that allow devices to communicate with one another or a network entity 105 (e.g., a base station 140) without human intervention. In some examples, M2M communication or MTC may include communications from devices that integrate sensors or meters to measure or capture information and relay such information to a central server or application program that uses the information or presents the information to humans interacting with the application program. Some UEs 115 may be designed to collect information or enable 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 geological event monitoring, fleet management and tracking, remote security sensing, physical access control, and transaction-based business charging.

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

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

In some examples, a UE 115 may be configured to support communicating directly with other UEs 115 via a device-to-device (D2D) communication link 135 (e.g., in accordance with a peer-to-peer (P2P) , D2D, or sidelink protocol) . In some examples, one or more UEs 115 of a group that are performing D2D communications may be within the coverage area 110 of a network entity 105 (e.g., a base station 140, an RU 170) , which may support aspects of such D2D communications being configured by (e.g., scheduled by) the network entity 105. In some examples, one or more UEs 115 of such a group may be outside the coverage area 110 of a network entity 105 or may be otherwise unable to or not configured to receive transmissions from a network entity 105. In some examples, groups of the UEs 115 communicating via D2D communications may 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, a network entity 105 may facilitate the scheduling of resources for D2D communications. In some other examples, D2D communications may be carried out between the UEs 115 without an involvement of a network entity 105.

In some systems, a D2D communication link 135 may be an example of a communication channel, such as a sidelink communication channel, between vehicles (e.g., UEs 115) . In some examples, vehicles may communicate using vehicle-to-everything (V2X) communications, vehicle-to-vehicle (V2V) communications, or some combination of these. A vehicle may signal information related to traffic conditions, signal scheduling, weather, safety, emergencies, or any other information relevant to a V2X system. In some examples, vehicles in a V2X system may communicate with roadside infrastructure, such as roadside units, or with the network via one or more network nodes (e.g., network entities 105, base stations 140, RUs 170) using vehicle-to-network (V2N) communications, or with both.

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 5G core (5GC) , which may include at least one control plane entity that manages access and mobility (e.g., a mobility management entity (MME) , an access and mobility management function (AMF) ) and at least one user plane entity that routes packets or interconnects to external networks (e.g., a serving gateway (S-GW) , a Packet Data Network (PDN) gateway (P-GW) , or a user plane function (UPF) ) . The control plane entity may manage non-access stratum (NAS) functions such as mobility, authentication, and bearer management for the UEs 115 served by the network entities 105 (e.g., base stations 140) associated with the core network 130. User IP packets may be transferred through the user plane entity, which may provide IP address allocation as well as other functions. The user plane entity may be connected to IP services 150 for one or more network operators. The IP services 150 may include access to the Internet, Intranet (s) , an IP Multimedia Subsystem (IMS) , or a Packet-Switched Streaming Service.

The wireless communications system 100 may operate using one or more frequency bands, which may be in the range of 300 megahertz (MHz) to 300 gigahertz (GHz) . Generally, the region from 300 MHz to 3 GHz is known as the ultra-high frequency (UHF) region or decimeter band because the wavelengths range from approximately 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 the waves may penetrate structures sufficiently for a macro cell to provide service to the UEs 115 located indoors. Communications using UHF waves may be associated with smaller antennas and shorter ranges (e.g., less than 100 kilometers) compared to communications using the smaller frequencies and longer waves of the high frequency (HF) or very high frequency (VHF) portion of the spectrum below 300 MHz.

The wireless communications system 100 may also operate using a super high frequency (SHF) region, which may be in the range of 3 GHz to 30 GHz, also known as the centimeter band, or using an extremely high frequency (EHF) region of the spectrum (e.g., from 30 GHz to 300 GHz) , also known as the millimeter band. In some examples, the wireless communications system 100 may support millimeter wave (mmW) communications between the UEs 115 and the network entities 105 (e.g., base stations 140, RUs 170) , and EHF antennas of the respective devices may be smaller and more closely spaced than UHF antennas. In some examples, such techniques may facilitate using antenna arrays within a device. The propagation of EHF transmissions, however, may be subject to even greater attenuation and shorter range than SHF or UHF transmissions. The techniques disclosed herein may be employed across transmissions that use one or more different frequency regions, and designated use of bands across these frequency regions may differ by country or regulating body.

The wireless communications system 100 may utilize both licensed and unlicensed RF spectrum bands. For example, the wireless communications system 100 may employ License Assisted Access (LAA) , LTE-Unlicensed (LTE-U) radio access technology, or NR technology using an unlicensed band such as the 5 GHz industrial, scientific, and medical (ISM) band. While operating using unlicensed RF spectrum bands, devices such as the network entities 105 and the UEs 115 may employ carrier sensing for collision detection and avoidance. In some examples, operations using unlicensed bands may be based on a carrier aggregation configuration in conjunction with component carriers operating using a licensed band (e.g., LAA) . Operations using unlicensed spectrum may include downlink transmissions, uplink transmissions, P2P transmissions, or D2D transmissions, among other examples.

A network entity 105 (e.g., a base station 140, an RU 170) or a UE 115 may be equipped with multiple antennas, which may be used to employ techniques such as transmit diversity, receive diversity, multiple-input multiple-output (MIMO) communications, or beamforming. The antennas of a network entity 105 or a 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, antennas or antenna arrays associated with a network entity 105 may be located at diverse geographic locations. A network entity 105 may include an antenna array with a set of rows and columns of antenna ports that the network entity 105 may use to support beamforming of communications with a UE 115. Likewise, a UE 115 may include one or more antenna arrays that may support various MIMO or beamforming operations. Additionally, or alternatively, an antenna panel may support RF beamforming for a signal transmitted via an antenna port.

The network entities 105 or the UEs 115 may use MIMO communications to exploit multipath signal propagation and increase spectral efficiency by transmitting or receiving multiple signals via different spatial layers. Such techniques may be referred to as spatial multiplexing. The multiple signals may, for example, be transmitted by the transmitting device via different antennas or different combinations of antennas. Likewise, the multiple signals may be received by the 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 used for channel measurement and reporting. MIMO techniques include single-user MIMO (SU-MIMO) , for which multiple spatial layers are transmitted to the same receiving device, and multiple-user MIMO (MU-MIMO) , for which multiple spatial layers are transmitted to multiple devices.

Beamforming, which may also be referred to as spatial filtering, directional transmission, or directional reception, is a signal processing technique that may 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 may be achieved by combining the signals communicated via antenna elements of an antenna array such that some signals propagating along particular orientations with respect to an antenna array experience constructive interference while others experience destructive interference. The adjustment of signals communicated via the antenna elements may include a transmitting device or a receiving device applying amplitude offsets, phase offsets, or both to signals carried via the antenna elements associated with the device. The adjustments associated with each of the antenna elements may be defined by a beamforming weight set associated with a particular orientation (e.g., with respect to the antenna array of the transmitting device or receiving device, or with respect to some other orientation) .

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

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

In some examples, transmissions by a device (e.g., by a network entity 105 or a 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 a network entity 105 to a UE 115) . The UE 115 may report feedback that indicates precoding weights for one or more beam directions, and the feedback may correspond to a configured set of beams across a system bandwidth or one or more sub-bands. The network entity 105 may transmit a reference signal (e.g., a cell-specific reference signal (CRS) , a channel state information reference signal (CSI-RS) ) , which may be precoded or unprecoded. The 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 type codebook, a linear combination type codebook, a port selection type codebook) . Although these techniques are described with reference to signals transmitted along one or more directions by a network entity 105 (e.g., a base station 140, an RU 170) , a UE 115 may employ similar techniques for transmitting signals multiple times along different directions (e.g., for identifying a beam direction for subsequent transmission or reception by the UE 115) or for transmitting a signal along a single direction (e.g., for transmitting data to a receiving device) .

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

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

The UEs 115 and the network entities 105 may support retransmissions of data to increase the likelihood that data is received successfully. Hybrid automatic repeat request (HARQ) feedback is one technique for increasing the likelihood that data is received correctly via a communication link (e.g., a communication link 125, a 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 in poor radio conditions (e.g., low signal-to-noise conditions) . In some examples, a device may support same-slot HARQ feedback, in which case the device may provide HARQ feedback in a specific slot for data received via a previous symbol in the slot. In some other examples, the device may provide HARQ feedback in a subsequent slot, or according to some other time interval.

In the wireless communications system 100, a network entity 105 may communicate with a UE 115 using directional communications techniques. For example, the network entity 105 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 transmit and receive one or more reference signals, such as CSI-RSs or SSBs, via the communication links to aid in determining CSI, among other purposes. The network entity 105 may transmit 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 representative of characteristics of the one or more beams, which may be referred to as signal strength characteristics. For instance, the UE 115 may calculate a reference signal received power (RSRP) , a signal-to-interference-plus-noise ratio (SINR) , or the like, and transmit information, such as a CSI report or a beam report, to the network entity 105. The CSI report may include beam management information, such as signal strength characteristics, channel state parameters, and the like, associated with the one or more beams. In some examples, a beam report may include an indication of a strongest beam (e.g., based on the measurements) in terms of either a layer one RSRP (L1-RSRP) or a layer one SINR (L1-SINR) .

As an example, the UE 115 may calculate an RSRP by determining an average power of the 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 an energy received during a symbol of the resource element, excluding a 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 a quantity of resource elements, the frequency bandwidth, and a measurement period used to calculate the RSRP. The UE 115 may calculate the RSRP in accordance with a corresponding measurement accuracy requirement and may indicate the RSRP to the network entity 105, e.g., as part of a CSI report or a beam report.

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

An accuracy requirement (e.g., a measurement accuracy requirement) may be defined as a tolerance range in decibels (dB) for reference signal measurements to ensure that beam management and link adaptation procedures provide sufficient performance. Relative accuracy requirements and absolute accuracy requirements may be defined for different types of reference signals and different signal strength characteristics. For example, a first set of accuracy requirements may be defined for L1-RSRP values measured with respect to SSBs (e.g., SSB resources) . A second set of accuracy requirements may be defined for L1-RSRP values measured with respect to CSI-RSs (e.g., CSI-RS resources) . Still other sets of accuracy requirements may be defined for L1-SINR values measured with respect to SSBs and with respect to CSI-RSs. Additionally, accuracy requirements may vary based a frequency bandwidth associated with the received reference signals, which may, in turn, be associated with different capabilities of the UE 115.

For example, an absolute accuracy requirement (e.g., an absolute accuracy tolerance) may be defined as an upper limit (e.g., a maximum value) of a difference between 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 a 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 (e.g., a “genie” value) for the signal strength characteristic associated with the resource. A relative accuracy requirement (e.g., a relative accuracy tolerance) may be defined aswhereis the measured signal strength characteristic for the reference signal received via the resource, refers to a strongest (e.g., maximum) measured RSRP of all reference signals in a same serving cell as the reference signal, is an ideal value for the signal strength characteristic associated with the resource, andrefers to an ideal value for the strongest measured RSRP. Similar accuracy requirements may be defined for other signal strength characteristics, such as SINR.

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

As discussed herein, the UE 115 may predict (e.g., using a predictive model) L1-RSRP or L1-SINR values for the target beam (s) and target one or more resources according to one or more accuracy requirements defined for UE-predicted signal strength characteristics. The UE 115 may, for example, predict a signal strength characteristic for a first set of one or more beams and a first set of resources according to a corresponding accuracy requirement. The accuracy requirement may be defined as a tolerance range in dB with respect to a reference value associated with the first set of resources. In some cases, the reference value may be an ideal value, also referred to as a genie value, for the signal strength characteristic. In other cases, the reference value may be a measured value obtained by the UE 115, such as a value of a signal strength characteristic obtained by measuring a second set of one or more beams (e.g., based on a reference signal received via the second set of one or more beams via the first set of resources) . The U E115 may report the predicted signal strength requirement to the network entity 105 for use in beam management, link adaptation, or the like.

FIG. 2 illustrate an example of a beam management procedure 200 that supports accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure. In some examples, the beam management procedure 200 may implement aspects of the wireless communications system 100 or may be implemented by aspects of the wireless communications system 100. For example, the beam management procedure 200 may include a UE 115-a and a network entity 105-a, which may be examples of corresponding devices described with reference to FIG. 1.

The UE 115-a and the network entity 105-a may communicate using beamformed communications via one or more communications links, which may be examples of downlink channels (e.g., physical downlink shared channels (PDSCHs) , physical downlink control channels (PDCCHs) ) , uplink channels (e.g., physical uplink shared channels (PUSCHs) , physical uplink control channels (PUCCHs) ) , or the like. To support beamformed communications, the UE 115-a and the network entity 105-a may perform beam management. Beam management may include beam sweeping, in which the network entity 105-a may cover the UE 115-a with one or more transmission beams of a beam set (e.g., a beam set 205-a, a beam set 205-b) . More specifically, the network entity 105-a may sweep a set of transmission beams across the communication link according to a beam sweep pattern. In some examples, the beam sweeping pattern may include transmitting a set of SSBs or a set of CSI-RSs across the beam set. The UE 115-a may perform measurements of the SSBs or CSI-RSs received across the beam set and transmit a report to the network entity 105-a indicating information based on the measurements. For example, the report may indicate a strongest beam, an L1-RSRP, an L1-SINR, or the like. The UE 115-a and the network entity 105-a may select or reselect a best beam or adapt to a beam event (e.g., a beam failure event) based on the report.

Beam management procedures may be utilized during initial access procedures to establish communications over a 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 beam management procedures to maintain or update communications via the communication link. As illustrated in FIG. 2, the UE 115-a may, in some cases, operate in an RRC_IDLE or RRC_INACTIVE mode. The network entity 105-a and the UE 115-a may perform an SSB beam sweep and report procedure during an initial access procedure (e.g., as part of a random access channel (RACH) procedure) . Here, the network entity 105-a may transmit 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. Beams used for SSB beam sweeping may be wide beams (e.g., layer 1 (L1) beams) . The UE 115-a and the network entity 105-a may select a best (e.g., strongest) beam from the swept beams for the communication link based on the measurements and the report.

After initial access, the UE 115-a may operate in an RRC_CONNECTED mode and may implement beam management procedures to maintain reliable communications via the communication link. For instance, the network entity 105-a and the UE 115-a may periodically perform a CSI-RS beam sweep and report procedure while in the connected mode. The CSI-RS beam sweep may be a P1, P2, or P3 procedure. P1 may be a beam selection procedure where the network entity 105-a sweeps a beam set and the UE 115-a selects a best (e.g., strongest) beam of the beam set. The UE 115-a may report the selected beam to the network entity 105-a. P2 may be a beam refinement procedure for the network entity 105-a, where the network entity 105-a may refine a beam (e.g., by sweeping a narrower beam over a narrower range) , and UE 115-a may detect and report the best beam to the network entity 105-a. P3 may be a beam refinement procedure for the UE 115-a, where the network entity 105-a may fix a beam (e.g., transmit a same beam repeatedly) , and UE 115-a may refine its receiver 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 transmit an L1 report for beam refinement. The network entity 105-a and the UE 115-a may perform 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 sweep and report procedure as part of a beam failure recovery procedure (e.g., to facilitate fast recovery) or a radio link failure procedure (e.g., as a last resort to re-establish communications) .

The UE 115-a and the network entity 105-a may perform beam management, measurements, and reporting according to one or more accuracy requirements. An accuracy requirement may be defined for a measurement type (e.g., RSRP or SINR) , a reference signal type (e.g., SSB or CSI-RS) , and a 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 the UE 115-a measuring SSBs (e.g., received via SSB resources configured for L1-RSRP measurements) , which may be referred to as SSB-based L1-RSRP accuracy requirements. Other accuracy requirements may be defined for L1-RSRP measurements of CSI-RSs received at the UE 115-a (e.g., via CSI-RS resources configured for L1-RSRP measurements) , 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, accuracy requirements may vary based a frequency bandwidth associated with the received reference signals, which may, in turn, be associated with different capabilities of the UE 115. For example, SSB-based L1-RSRP accuracy requirements may be separately defined for SSBs configured for L1-RSRP measurements in FR1 and SSBs configured for L1-RSRP measurements in FR2.

The UE 115-a may receive and measure a reference signal based on a corresponding accuracy requirement. In some examples, the accuracy requirements may further be categorized as absolute accuracy requirements or relative accuracy requirements. For example, an absolute accuracy requirement (e.g., an absolute accuracy tolerance) may be defined as an upper limit (e.g., a maximum value) of a difference between 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 a 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 (e.g., a “genie” value) for the signal strength characteristic associated with the resource. As an example, Table 1 below illustrates absolute accuracy requirements for SSB-based L1-RSRP in FR 2.

Table 1

A relative accuracy requirement (e.g., a 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 greatest measured signal strength characteristic value among all reference signals of a cell on which the UE 115-a performs the corresponding measurements. For example, when the signal strength characteristic is an RSRP, a relative accuracy requirement may be given bywhereis the measured value of the RSRP for the reference signal received via the resource, refers to the strongest (e.g., maximum) measured RSRP of all reference signals in a same serving cell as the reference signal, is an ideal value for the RSRP associated with the resource, andrefers to an ideal value for the strongest measured RSRP. As an example, Table 2 below illustrates relative accuracy requirements for SSB-based L1-RSRP in FR 2.

Table 2

Similar absolute and relative accuracy requirements may be defined for other signal strength characteristics, such as SINR.

Further, in some examples, accuracy requirements may depend on one or more conditions associated with signal strength characteristic measurements. For example, respective accuracy requirements may correspond to respective frequency bands (e.g., operating bands) within FR1 or FR2, where each frequency band corresponds to a respective power class of the UE 115-a. In some cases, power classes of a UE 115-a may further define or be associated with one or more capabilities of the UE 115-a. Thus, the UE 115-a may achieve an accuracy requirement for a signal strength characteristic measurement (e.g., RSRP measurement, SINR measurement) of a reference signal received in a given frequency band when the one or more corresponding conditions are satisfied. Table 3 illustrates an example of such conditions for SSB-based L1-RSRP measurements for frequency bands in FR2.

Table 3

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

For example, for a target beam and a target one or more resources, the UE 115-a may utilize a predictive model to infer a signal strength characteristic that may be associated with communications via the target beam and the target one or more resources. The predictive model may be an example of a predictive model associated with beam management procedures. The UE 115-a may receive a message from the network entity 105-a that includes an indication of the target beam (s) , the target one or more resources, or a combination thereof. The network entity 105-a may (e.g., via the message) indicate that the target one or more resources are to be used by the UE 115-a in predicting the signal strength characteristic for the target beam. Based on the indication (s) , the UE 115-a may predict the signal strength characteristic for the target beam and the target one or more resources using the predictive model. In some cases, the UE 115-a may infer multiple signal strength characteristics corresponding to a target beam for a set of N future time instances. The UE 115-a may predict a respective signal strength characteristic for the beam for each future time instance.

Such predictions may utilize measurements of reference signals received via one or more other beams different from the target beam (s) . For example, the UE 115-a may perform spatial-domain downlink beam prediction for a beam set 205-a based on measurement results of one or more reference signals received via a beam set 205-b. Here, the network entity 105-a may transmit reference signals to the UE 115-a via the beam set 205-b. The UE 115-a may receive and measure the reference signals and may utilize the measurements as inputs to a predictive model to predict one or more signal strength characteristics of one or more beams of the beam set 205-a. In another example, the UE 115-a may perform time-domain beam prediction for the beam set 205-a based on historic (e.g., previously obtained) measurement results of the beam set 205-b.

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

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

The present disclosure defines accuracy requirements for signal strength characteristics when they are predicted by a UE, such as the UE 115-a. An accuracy requirement may be understood as a tolerance (e.g., a tolerance range) in dB for a predicted value of a signal strength characteristic with respect to a reference value for 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 UE-predicted L1-RSRP or L1-SINR values for the beam set 205-a with respect to the reference value. In some cases, 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 a relatively more relaxed tolerance.

As a specific example, an absolute accuracy requirement (e.g., an absolute accuracy tolerance) for an L1-RSRP prediction may be defined as RSRP_predicted-RSRP_ref, where RSRP_predicted denotes the predicted value of the L1-RSRP and RSRP_ref represents the reference value. Additionally, or alternatively, for a set of multiple target resources associated with multiple predictions, a relative accuracy requirement (e.g., a relative accuracy tolerance) for the L1-RSRP prediction may be defined asHere, denotes a predicted value associated with a target resource of the set of multiple target resources, refers to a strongest (e.g., maximum) predicted RSRP associated with a resource from among the set of multiple target resources, denotes a reference value for the target resource, andrefers to a reference value forthat is associated with the same resource from among the set of multiple target resources. Similar accuracy requirements may be defined for other predicted signal strength characteristics, such as L1-SINR.

In some cases, the reference value may be an ideal value, such as a genie value. For a predicted RSRP associated with a target resource, the reference value may be an ideal RSRP value associated with the target resource. For a predicted SINR associated with a target resource, the reference value may be an 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 measurements 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 a signal strength characteristic of a hypothetical reference signal, such as an SSB or a CSI-RS, that may be received (e.g., at a future time instance) via the target resource. Alternatively, the target resource may be referred to as a virtual resource that may not be used to transmit or receive, 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, such as QCL information, with another one or more resources (e.g., SSB or CSI-RS resources) .

In the example of FIG. 2, for instance, the UE 115-a may predict a signal strength characteristic, such asfor a target beam of the beam set 205-ain accordance with a relative accuracy requirement. The target beam may be associated with a target resource of a set of resources. The UE 115-a may obtain a reference value for the relative accuracy requirement by measuring a downlink reference signal received via the beam set 205-b that corresponds to the target resource. For example, the target resource may be an SSB resource. The UE 115-a may receive an SSB via a beam of the beam set 205-b corresponding to the target resource and may measure the SSB to obtainAlternatively, the target resource may be an example of a virtual resource associated with a beam shape of the target beam, a beam direction of the target beam, or a combination thereof. In some cases, the virtual resource may indicate a correspondence between the downlink reference signal (e.g., and one or more other downlink reference signals associated with the beam set 205-b) and a beam shape of the target beam, a correspondence between the downlink reference signal (e.g., and one or more other downlink reference signals associated with the beam set 205-b) and a beam direction of the target beam, or a combination thereof. In some examples, the virtual resource may indicate a QCL correspondence between the downlink reference signal (e.g., and one or more other downlink reference signals associated with the beam set 205-b) and the beam set 205-a.

The UE 115-a may predict one or more additional signal strength characteristics for one or more additional beams of the beam set 205-a associated with the set of resources. The UE 115-amay determine a maximum valueof the predicted one or more additional signal strength characteristics. Additionally, the UE 115-a may receive and measure one or more other downlink reference signals via the beam set 205-b corresponding to the set of resources, and may determine a maximum valuefrom among all downlink reference signals received via the set of resources and measured by the UE 115-a. The UE 115-a may calculate the relative accuracy requirement for the predicted signal strength characteristic in accordance withThe UE 115-a may transmit an indication of the predicted signal strength characteristic (e.g., ) to the network entity 105-ain accordance with the relative accuracy requirement.

Accuracy levels attainable by predictive models utilized for such predictions may depend on characteristics of the target beam (s) and characteristics of the beams associated with the received reference signals and the measured signal strength characteristics. For example, when the beam set 205-b includes a relatively large quantity of beams, the UE 115-a may be able to obtain sufficient measurement results such that associated predictions for the beam set 205-a have improved accuracy (e.g., compared to scenarios in which the 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, an accuracy requirement may additionally or alternatively be based on a time duration between a target resource and the report transmitted by the UE 115-a. For instance, the UE 115-a may predict a signal strength characteristic for a target resource, but may wait for a relatively long time duration before transmitting a report indicating the prediction. In this case, the accuracy requirement associated with the prediction may be less strict, as conditions may change during the time duration that may decrease the reliability and accuracy of the prediction. For shorter time durations between a prediction and a report, the accuracy requirement may be stricter.

Computational capabilities or computational resources of a UE may further affect accuracy levels that the UE is capable of achieving. For example, a first UE that has greater computational capabilities for machine learning-or artificial intelligence-based procedures may be able to predict signal strength characteristics with greater accuracy than a second UE with limited computational capabilities. As such, the first UE may be able to meet stricter accuracy requirements than the second UE.

In some cases, a UE may transmit a capability message indicating accuracy requirements that the UE is able to achieve. In some examples, the UE may receive a request for the capability message and may transmit the capability message in response to the request. In the example of FIG. 2, the UE 115-a may receive, from the network entity 105-a, a request for the UE 115-a to transmit a capability message. Based on the request, the UE 115-a may transmit, to the network entity 105-a, a capability message that includes an indication of one or more accuracy requirements supported by the UE 115-a for one or more signal strength characteristics to be predicted by the UE 115-a. For example, if the UE 115-a is to predict a set of signal strength characteristics for a target beam of the beam set 205-a corresponding to a target resource, the UE 115-a may indicate, to the network entity 105-a, that the UE 115-a supports a set of accuracy requirements with respect to the set of signal strength characteristics. In some cases, the UE 115-a’s capability to support the set of accuracy requirements may be based on the set of signal strength characteristics, a quantity of beams of the beam set 205-a, or a beam type (e.g., SSB, CSI-RS) associated with the target beam or the beam set 205-a, or a combination thereof. For instance, the 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.

Additionally, in some cases, the capability of the UE 115-a to support the set of accuracy requirements may be based on the reference value according to which the 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 the UE 115-a performs the prediction based on a measured reference value, such as a measurement associated with the beam set 205-b, the UE 115-a’s capability to support the set of accuracy requirements may be based on a quantity of beams of the beam set 205-b, a beam type associated with the beam set 205-b, one or more measured signal strength characteristics of the beam set 205-b, or a combination thereof.

Signal strength characteristic predictions by a UE may be associated with a confidence level based on the corresponding accuracy requirement. A confidence level may denote a likelihood that the prediction satisfies the accuracy requirement. For example, a 90%confidence level may indicate that a predicted signal strength requirement is 90%likely to be within a tolerance range of the accuracy requirement (e.g., 90%of predictions by the UE satisfy the accuracy requirement) . In some cases, a UE may report a confidence level along with a predicted signal strength characteristic. In the example of FIG. 2, the UE 115-a may transmit a message indicating a confidence level associated with predicting one or more signal strength characteristics for a beam (e.g., a target beam) of the beam set 205-a. The confidence level may be based on the accuracy requirement, one or more capabilities of the UE 115-a (e.g., computational capabilities) , the beam set 205-a, the beam set 205-b, or a combination thereof.

FIGs. 3A and 3B illustrate examples of signal strength prediction procedures 301 and 302, respectively, that support accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure. In some examples, the signal strength prediction procedures 301 and 302 may implement or may be implemented by aspects of a wireless communications system as described with reference to FIGs. 1 and 2. For example, the signal strength prediction procedures 301 and 302 may be implemented by a UE 115 to predict one or more signal strength characteristics, such as L1-RSRPs, L1-SINRs, or both, of a first set of beams in accordance with an accuracy requirement 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.

In FIG. 3A, for example, a UE may receive a set of reference signals 305-a via a second set of beams, which may, in some cases, 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, the reference signals 305-a may include two SSBs corresponding to two beams and received via three consecutive time occasions (e.g., time-domain resources) , which may be examples of 20 millisecond (ms) occasions. The first set of beams and the first set of resources may be referred to as prediction targets 310-a. Each beam of the first set of beams may be narrower (e.g., have a smaller beam width) than each beam of the reference signals 305-a. The UE may measure the reference signals 305-a to obtain a set of measured RSRP values and may utilize the set of measured RSRP values to predict one or more RSRP values for the prediction targets 310-a in accordance with an absolute value of an accuracy requirement 315-a. For example, the accuracy requirement 315-a may define a tolerance range of +/-6 dB with respect to a reference value 320. The absolute value of the accuracy requirement 315-a may therefore be 6 dBm. The reference value 320 may be an ideal RSRP value, an ideal SINR value, or the like, among other examples. Alternatively, the reference value 320 may be a measured RSRP value of the set of measured RSRP values associated with the reference signals 305-a.

FIG. 3A further illustrates a predictive model 325 implemented by the UE to determine a correspondence between the reference signals 305-a and the prediction targets 310-a. Thus, predicted RSRP values may be dependent on measurement results associated with downlink reference signals (e.g., the reference signals 305-a) received at the UE. The UE may input one or more measured RSRP values associated with the reference signals 305-a to the predictive model 325, which may include or be an example of a DNN, a CNN, or the like. In some examples, the predictive model 325 may include or be an example of a predictive model associated with beam management. The predictive model 325 may infer (e.g., predict) the one or more RSRP values associated with the prediction targets 310-a according to the accuracy requirement 315-a based on the input measured RSRP values. That is, each predicted RSRP value may be within the tolerance range of +/-6 dB of the one or more measured RSRP values.

In some examples, an accuracy requirement for a signal strength prediction may depend on conditions associated with a prediction target, such as a quantity, type, or characteristic of a prediction target (e.g., the first set of beams, the first set of resources) . For instance, if the beams of the first set of beams are relatively narrow, the corresponding accuracy requirement may be less strict than scenarios in which the beams of the first set of beams are relatively wide. Similarly, a relatively large quantity of beams of the first set of beams may correspond to a less strict accuracy requirement compared to a relatively small quantity of beams of the first set of beams. In some cases, the accuracy requirement may be based on a periodicity of transmission of the first set of beams, where more frequently transmitted beams may correspond to a stricter accuracy requirement. Further, an accuracy requirement for prediction targets (e.g., the first set of beams, the first set of resources) associated with SSBs may be different from an accuracy requirement for prediction targets (e.g., the first set of beams, the first set of resources) associated with CSI-RSs.

Additionally, or alternatively, the accuracy requirement for predicting signal strength characteristics of the first set of beams may be based on conditions associated with the second set of beams, such as a quantity, type, or characteristic of the second set of beams. As a quantity of beams of the second set of beams increases, for example, the accuracy requirement may become increasingly strict. When the second set of beams is associated with a narrow beam width, the accuracy requirement may be stricter than when the second set of beams is associated with a wide beam width. In some examples, the accuracy requirement may be based on a periodicity of transmission of the second set of beams, where more frequently transmitted beams may correspond to a stricter accuracy requirement. Further, the accuracy requirement may be based on whether the second set of beams (e.g., and the second set of resources) are associated with SSBs or CSI-RSs.

In some cases, if the second set of beams are relatively strong (e.g., based on the measured RSRP values being relatively large) , the UE may be able to predict signal strength characteristics for the first set of beams with improved accuracy compared to a relatively weak second set of beams. The accuracy requirement may therefore, in some cases, depend on an 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, which have a wide beam width but lower beamforming gains. The first set of beams may be associated with CSI-RSs and thus may have a narrower beam width but greater beamforming gains than the second set of beams. Additionally, CSI-RS beams are associated with relatively infrequent transmission (e.g., low periodicity) . Such a scenario may correspond to a less strict accuracy requirement. In some examples, the UE may utilize the first set of beams for other purposes, such as inputs to the predictive model 325, or to monitor performance of the prediction. For example, the UE may use the first set of beams for communication with a network entity and may obtain a measured signal strength characteristic to compare to the predicted signal strength characteristic. The UE may verify the prediction or may adjust or correct the prediction procedure based on the comparison.

FIG. 3B illustrates another example of signal strength characteristic prediction 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 20 ms time occasions (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 prediction targets 310-b. The UE may predict one or more signal strength characteristics for the prediction targets 310-b using a predictive model 335 and in accordance with an absolute value of an accuracy requirement 315-b. For example, the UE may input the one or more measured signal strength characteristics associated with the reference signals 305-b to the predictive model 335. In some examples, the predictive model 335 may include or be an example of a predictive model associated with beam management, such as a CNN, a DNN, or the like. The predictive model 335 may output (e.g., infer) the predicted one or more signal strength characteristics for the prediction targets 310-b according to the accuracy requirement 315-b. The accuracy requirement 315-b may be defined with respect to a reference value 330 associated with the reference signals 305-b, such as a measured signal strength characteristic of the one or more measured signal strength characteristics. Additionally, or alternatively, the reference value 330 may be an ideal RSRP value, an ideal SINR value, or the like, among other examples.

As illustrated, the reference signals 305-b include a greater quantity of beams than the reference signals 305-a, and each beam of the reference signals 305-b has a narrower beam width than each beam of the reference signals 305-a. Accordingly, the absolute value of the accuracy requirement 315-b may be less than the absolute value of the accuracy requirement 315-a. For example, while the accuracy requirement 315-a may define a tolerance range of +/-6 dB with respect to the reference value 320 associated with the reference signals 305-a, the accuracy requirement 315-b may define a tolerance range of +/-1 dB with respect to the reference value 330. The absolute value of the accuracy requirement 315-a may be 6 dBm and the absolute value of the accuracy requirement 315-b may be 1 dBm. As such, the accuracy requirement 315-b may be understood as being a stricter accuracy requirement compared to the accuracy requirement 315-a. Predicted signal strength characteristics associated with the accuracy requirement 315-b may therefore be considered to be more accurate than predicted signal strength characteristics associated with the accuracy requirement 315-a. Put another way, the signal strength prediction procedure 302 may be more accurate (e.g., may be associated with lower error) than the signal strength prediction procedure 301.

Differences between the accuracy requirement 315-a and the accuracy requirement 315-b may further be reflected in a comparison between the predictive model 325 and the predictive model 335. As illustrated, the predictive model 335 may include or be an example of a neural network (e.g., a CNN, a DNN) that is wider, deeper, or both, than the predictive model 325, which may enable the predictive model 335 to realize the stricter accuracy requirement 315-b. That is, a wider or deeper predictive model may be utilized by the UE to obtain increased accuracy in signal strength characteristic predictions. Thus, a predictive model implemented by a UE may be based on an accuracy requirement associated with a signal strength characteristic prediction. Further, the accuracy requirement for a given prediction may, in turn, be based on predictive models supported by the UE. For instance, a UE that supports wider or deeper predictive models may be capable of predicting signal strength characteristics in accordance with stricter accuracy requirements than a UE with limited computational capabilities or computational resources.

FIGs. 4A, 4B and 4C illustrates examples of accuracy requirement diagrams 401, 402, and 403, respectively, that support accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure. In some examples, the accuracy requirement diagrams 401, 402, and 403 may implement or may be implemented by aspects of a wireless communications system as described with reference to FIGs. 1 and 2. For example, the accuracy requirement diagrams 401, 402, and 403 may be implemented by a UE 115 to predict one or more signal strength characteristics, such as L1-RSRPs, L1-SINRs, or both, of a first set of beams in accordance with an accuracy requirement 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. The accuracy requirement may be defined with respect to a reference value, such as a measured signal strength characteristic 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) or an ideal value.

In the example of FIG. 4A, the UE may predict a signal strength characteristic for a beam of the first set of beams associated with a resource of the first set of resources based on a reference signal strength characteristic 405-a associated with the resource. The reference signal strength characteristic 405-a may be an example of the 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 (e.g., an error tolerance range) in dB. 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 denotes the UE-predicted signal strength characteristic and L₀ denotes the reference signal strength characteristic 405-a (e.g., the reference value) . Values of signal strength characteristics predicted by the UE according to the accuracy requirement 415-a may fall within the tolerance range T₀.

The portion of T₀ above the reference value may be referred to an upper portion and may be expressed in positive dB (+ dB) , while the portion of T₀ below the reference value may be referred to as a lower portion and may be expressed in negative dB (-dB) . When an absolute value of the lower portion of the tolerance range is equal to an absolute value of the upper portion of the tolerance range, as illustrated in FIG. 4A, the accuracy requirement 415-a may be referred to as a symmetric accuracy requirement. Put another way, for a symmetric accuracy requirement, the lower portion of the tolerance range may be symmetric to the upper portion of the tolerance range with respect to the reference value.

An accuracy requirement may be associated with a confidence level, which may, in turn, be based on conditions associated with the first set of beams, the second set of beams, or both. A confidence level may be represented by a percentage value denoting a likelihood that the prediction satisfies the accuracy requirement. Additionally, a confidence level for an accuracy requirement may indicate how strict the accuracy requirement is, for instance, relative to another accuracy requirement. For example, when the tolerance ranges for each accuracy requirement are the same, a stricter accuracy requirement may have a greater confidence value than a less strict accuracy requirement. In some cases, a 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 transmit an indication of a confidence level together with a reported signal strength prediction, e.g., based on an accuracy requirement associated with the signal strength prediction.

As a specific example, a first accuracy requirement associated with a relatively large quantity of beams of the second set of beams may have a 95%confidence level, while a second accuracy requirement associated with a relatively small quantity of beams of the second set of beams may be associated with a 75%confidence level. The first accuracy requirement and the second accuracy requirement may both correspond to a same tolerance range of +/-6 dB. The UE may be more confident that a prediction associated with the first accuracy requirement is correct compared to a prediction associated with the second accuracy requirement. The first accuracy requirement may therefore be understood as being stricter than the second accuracy requirement. Put another way, the UE may achieve the first accuracy requirement for 95%of the predictions and may meet the second accuracy requirement for 75%of the predictions.

In cases where the first accuracy requirement and the second accuracy requirement are associated with different tolerance ranges, respective confidence levels may be determined (e.g., by the UE) based on a quantity of beams of the first set of beams, a quantity of beams of the second set of beams, a beam type associated with the first set of beams, a beam type associated with the second set of beams, the signal strength characteristic (s) 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 strictness associated with each accuracy requirement. For example, a strictness metric A₂ may be defined by Equation 1 below.
A₂=P×A₁+ (1-P) × (βA₁) (1)

The UE may, for example, calculate a respective value of A₂ for each of the first accuracy requirement and the second accuracy requirement. In Equation 1, P may denote the confidence level (as a percentage value) , A₁ may denote the tolerance range in +/-dB, and β may be a predefined coefficient that is based on P and A₁. An absolute value of the resulting A₂ may indicate a relative strictness of the corresponding accuracy requirement. For example, a greater value of |A₂| may correspond to a stricter accuracy requirement. Thus, the first accuracy requirement and the second accuracy requirement may be qualitatively compared based on corresponding confidence levels and tolerance ranges.

FIG. 4B illustrates an example of an asymmetric accuracy requirement in which an upper portion of a tolerance range is asymmetric with respect to a lower portion of the tolerance range. An 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 the reference value. In FIG. 4B, a lower portion of the tolerance range extending below the reference value may be smaller than an upper portion of the tolerance range extending above the reference value (e.g., the lower portion may have an absolute value that is less than an absolute value of the upper portion) . For example, the accuracy requirement 415-b may be defined as -6 dB<T₀<20 dB. A value of a signal strength characteristic predicted by the UE may thus be within 6 dBm below the reference value (e.g., may be up to 6 dB less than the reference signal strength characteristic 405-b) and within 20 dBm above the reference value (e.g., may be up to 20 dB greater than the reference signal strength characteristic 405-b) .

In some cases, the accuracy requirement 415-b may be associated with different tolerance ranges based on a value or range of values of the reference signal strength characteristic 405-b (e.g., the reference value) . For example, when the reference signal strength characteristic 405-b, denoted by L₀, falls within a range of values given by {L₀<-110 dBm, -110 dBm≤L₀<-90 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 range of values of L₀ and T₀.

Alternatively, in some examples, respective confidence levels may be defined for each portion of a tolerance range T₀, such that a confidence level for a value of a signal strength characteristic that falls within a lower portion of T₀ may be different from a confidence level for a value of a signal strength characteristic that falls within an upper portion of T₀. In the example of FIG. 3B, T₀ may be associated with asymmetric confidence levels, where the upper portion of T₀ may have a confidence level of 95%while the lower portion of T₀ may have a confidence level of 75%.

FIG. 4C illustrates an example of an accuracy requirement 415-c that is associated with a symmetric tolerance range and asymmetric confidence levels. The accuracy requirement 415-c may correspond to a tolerance range T₀ defined with respect 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 confidence level of 75%and the upper portion may be associated with a confidence level of 95%.

In a second example, T₀ may remain symmetric with respect to the reference signal strength characteristic 405-c (e.g., the reference value) such that -6 dB<T₀< 6 dB, but the values 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, denoted by L₀, may fall within a range of values given by {L₀<-110 dBm, -110 dBm≤L₀<-90 dBm, L₀≥-90 dBm} . Additionally, each range of values 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, a predicted signal strength characteristic having a value that is within the lower portion of T₀ may be associated with a confidence level of 90%, while a predicted signal strength characteristic having a value that is within the upper portion of T₀ may be associated with a confidence level of 65%. When L₀ is between -110 dBm and -90 dBm, a predicted signal strength characteristic having a value that is within the lower portion of T₀ may be associated with a confidence level of 95%, while a predicted signal strength characteristic having a value that is within the upper portion of T₀ may be associated with a confidence level of 80%. When L₀ is greater than or equal to -90 dBm, a predicted signal strength characteristic may be associated with a 95%confidence level for any value within T₀.

In some other cases, however, the ranges of T₀ and the corresponding confidence levels may each be asymmetric for different values of L₀. For instance, when {L₀<-110 dBm, -110 dBm≤L₀<-90 dBm, L₀≥-90 dBm} , the respective tolerance ranges may be defined as {-6 dB<T₀<20 dB, -6 dB<T₀< 9 dB, -3 dB<T₀<3 dB} , and the respective confidence levels for each tolerance range and value of L₀ may 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 may be -6 dB<T₀<20 dB, where a predicted signal strength characteristic having a value that is within the lower portion of T₀ may be associated with a confidence level of 90%, while a predicted signal strength characteristic having a value that is within the upper portion of T₀ may be associated with a confidence level of 65%. The tolerance range T₀ may therefore change based on the value (s) of L₀, and each tolerance range, or each portion of a tolerance range, may further be associated with a respective confidence level.

In some cases, accuracy requirements supported by a UE may be based on associated confidence levels and tolerance ranges, as well as conditions or characteristics associated with the first set of beams and the second set of beams. That is, a UE may be capable of achieving a set of accuracy requirements defined by a set of respective tolerance ranges and corresponding to a set of confidence levels based on a quantity of beams of the first set of beams, a quantity of beams of the second set of beams, a beam type associated with the first set of beams, a beam type associated with the second set of beams, the signal strength characteristic (s) 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. For example, when the second set of beams includes a greater quantity of beams, is transmitted with increased frequency, or is associated with a narrower beam width, the UE may support accuracy requirements associated with increased confidence levels and smaller tolerance ranges (e.g., lower dB values) compared to when the second set of beams includes fewer beams, has a reduced frequency of transmission, or is associated with a wider beam width.

The UE may transmit a capability message indicating a set of accuracy requirements supported by the UE for predicting signal strength characteristics and, in some cases, may additionally indicate (e.g., within the capability message) a corresponding set of confidence levels, a corresponding set of tolerance ranges, or both. 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 is to report capabilities associated with symmetric accuracy requirements, capabilities associated with asymmetric accuracy requirements, or both.

FIG. 5 illustrates a block diagram 500 of a device 505 that supports accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure. The device 505 may be an example of aspects of a UE 115 as described herein. The device 505 may include a receiver 510, a transmitter 515, and a communications manager 520. The device 505 may also include a processor. Each of these components may be in communication with one another (e.g., via one or more buses) .

The receiver 510 may provide a 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 predictions) . Information may be passed on to other components of the device 505. The receiver 510 may utilize a single antenna or a set of multiple antennas.

The transmitter 515 may provide a 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 predictions) . In some examples, the transmitter 515 may be co-located with a receiver 510 in a transceiver module. The transmitter 515 may utilize a single antenna or a set of multiple antennas.

The communications 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 accuracy requirements for UE-based signal strength predictions as described herein. For example, the communications manager 520, the receiver 510, the transmitter 515, or various combinations or components thereof may support a method for performing one or more of the functions described herein.

In some examples, the communications manager 520, the receiver 510, the transmitter 515, or various combinations or components thereof may be implemented in hardware (e.g., in communications management circuitry) . 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, discrete hardware components, or any combination thereof configured as or otherwise supporting a means for performing the functions described in the present disclosure. In some examples, a processor and memory coupled with the processor may be configured to perform one or more of the functions described herein (e.g., by executing, by the processor, instructions stored in the memory) .

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

In some examples, the communications manager 520 may be configured to perform various operations (e.g., receiving, obtaining, monitoring, outputting, transmitting) using or otherwise in cooperation with the receiver 510, the transmitter 515, or both. For example, the communications manager 520 may receive information from the receiver 510, send information to the transmitter 515, or be integrated in combination with the receiver 510, the transmitter 515, or both to obtain information, output information, or perform various other operations as described herein.

The communications manager 520 may support wireless communications at a UE in accordance with examples as disclosed herein. For example, the communications manager 520 may be configured as or otherwise support a means for receiving an indication of one or more time-frequency resources associated with predicting one or more signal strength characteristics by the UE, where an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE. The communications manager 520 may be configured as or otherwise support a means for predicting, in accordance with the accuracy requirement, the one or more signal strength characteristics for a beam of a set of beams with respect to the one or more time-frequency resources. The communications manager 520 may be configured as or otherwise support a means for transmitting an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement.

By including or configuring the communications manager 520 in accordance with examples as described herein, the device 505 (e.g., a processor controlling or otherwise coupled with the receiver 510, the transmitter 515, the communications manager 520, or a combination thereof) may support techniques for improved accuracy in beam management predictions, which may likewise increase the reliability of beam management procedures. As such, the device 505 may potentially communicate with a network entity or other wireless device more successfully based on using a more optimal beam, which may decrease a number of potential retransmissions or a number of monitoring occasions that the device 505 may decode and, in turn, reduce processing, reduce power consumption, and improve efficiency in resource utilization.

FIG. 6 illustrates a block diagram 600 of a device 605 that supports accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure. The device 605 may be an example of aspects of a device 505 or a UE 115 as described herein. The device 605 may include a receiver 610, a transmitter 615, and a communications manager 620. The device 605 may also include a processor. Each of these components may be in communication with one another (e.g., via one or more buses) .

The receiver 610 may provide a 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 predictions) . Information may be passed on to other components of the device 605. The receiver 610 may utilize a single antenna or a set of multiple antennas.

The transmitter 615 may provide a 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 predictions) . In some examples, the transmitter 615 may be co-located with a receiver 610 in a transceiver module. The transmitter 615 may utilize a single antenna or a set of multiple antennas.

The device 605, or various components thereof, may be an example of means for performing various aspects of accuracy requirements for UE-based signal strength predictions as described herein. For example, the communications manager 620 may include a time-frequency resource component 625 a predicting component 630, or any combination thereof. The communications manager 620 may be an example of aspects of a communications manager 520 as described herein. In some examples, the communications manager 620, or various components thereof, may be configured to perform various operations (e.g., receiving, obtaining, monitoring, outputting, transmitting) using or otherwise in cooperation with the receiver 610, the transmitter 615, or both. For example, the communications manager 620 may receive information from the receiver 610, send information to the transmitter 615, or be integrated in combination with the receiver 610, the transmitter 615, or both to obtain information, output information, or perform various other operations as described herein.

The communications manager 620 may support wireless communications at a UE in accordance with examples as disclosed herein. The time-frequency resource component 625 may be configured as or otherwise support a means for receiving an indication of one or more time-frequency resources associated with predicting one or more signal strength characteristics by the UE, where an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE. The predicting component 630 may be configured as or otherwise support a means for predicting, in accordance with the accuracy requirement, the one or more signal strength characteristics for a beam of a set of beams with respect to the one or more time-frequency resources. The predicting component 630 may be configured as or otherwise support a means for transmitting an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement.

FIG. 7 illustrates a block diagram 700 of a communications manager 720 that supports accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure. The communications manager 720 may be an example of aspects of a communications manager 520, a communications manager 620, or both, as described herein. The communications manager 720, or various components thereof, may be an example of means for performing various aspects of accuracy requirements for UE-based signal strength predictions as described herein. For example, the communications manager 720 may include a time-frequency resource component 725, a predicting 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 may communicate, directly or indirectly, with one another (e.g., via one or more buses) .

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

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

In some examples, the accuracy requirement is based on the second one or more signal strength characteristics, a numerical quantity 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.

In some examples, the confidence level component 740 may be configured as or otherwise support a means for transmitting a message indicating a confidence level associated with predicting the one or more signal strength characteristics, where the confidence level is 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.

In some examples, the accuracy requirement is based on the one or more signal strength characteristics, a numerical quantity of beams of 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 transmitting the indication. In some examples, the accuracy requirement is based on a reference value for the one or more signal strength characteristics, the reference value associated with the one or more time-frequency resources.

In some examples, the accuracy requirement defines a tolerance range extending above and below the 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.

In some examples, a lower portion of the tolerance range extending below the reference value is symmetric with respect to an upper portion of the tolerance range extending above the reference value. In some examples, 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. In some examples, the reference value includes an ideal value for the one or more signal strength characteristics or a measured value of the one or more signal strength characteristics.

In some examples, the capability message component 745 may be configured as or otherwise support a means for transmitting a capability message indicating a support for a set of one or more accuracy requirements at the UE with respect to the predicted signal strength characteristics. In some examples, the support for the set of one or more accuracy requirements is based on the one or more signal strength characteristics, a numerical quantity of beams of the set of beams, a beam type of the set of beams, a numerical quantity 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.

In some examples, the capability message component 745 may be configured as or otherwise support a means for receiving a request for the capability message, where transmitting the capability message is based on the request.

In some examples, the 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 that are associated with a beam shape of the set of beams, a beam direction of the 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 the set of beams, a correspondence between the one or more downlink reference signals and a beam direction of the set of beams, or a QCL correspondence between the one or more downlink reference signals and the set of beams.

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

In some examples, to support predicting, the predicting component 730 may be configured as or otherwise support a means for predicting the one or more signal strength characteristics using a predictive model associated with beam management.

FIG. 8 illustrates a diagram of a system 800 including a device 805 that supports accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure. The device 805 may be an example of or include the 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 bi-directional voice and data communications including components for transmitting and receiving communications, such as a communications 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) .

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

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 bi-directionally, via the one or more antennas 825, wired, or wireless links as described herein. For example, the transceiver 815 may represent a wireless transceiver and may communicate bi-directionally with another wireless transceiver. The transceiver 815 may also include a modem to modulate the packets, to provide the modulated packets to one or more antennas 825 for transmission, and to demodulate packets received from the one or more antennas 825. The transceiver 815, or the transceiver 815 and one or more antennas 825, may be an example of a transmitter 515, a transmitter 615, a receiver 510, a receiver 610, or any combination thereof or component thereof, as described herein.

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 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 cause a computer (e.g., when compiled and executed) to perform functions described herein. In some cases, the memory 830 may contain, among other things, a basic I/O system (BIOS) which may control basic hardware or software operation such as the interaction with peripheral components or devices.

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, a 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., the memory 830) to cause the device 805 to perform various functions (e.g., functions or tasks supporting accuracy requirements for UE-based signal strength predictions) . For example, the device 805 or a component of the device 805 may include a processor 840 and memory 830 coupled with or to the processor 840, the processor 840 and memory 830 configured to perform various functions described herein.

The communications manager 820 may support wireless communications at a UE in accordance with examples as disclosed herein. For example, the communications manager 820 may be configured as or otherwise support a means for receiving an indication of one or more time-frequency resources associated with predicting one or more signal strength characteristics by the UE, where an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE. The communications manager 820 may be configured as or otherwise support a means for predicting, in accordance with the accuracy requirement, the one or more signal strength characteristics for a beam of a set of beams with respect to the one or more time-frequency resources. The communications manager 820 may be configured as or otherwise support a means for transmitting an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement.

By including or configuring the communications manager 820 in accordance with examples as described herein, the device 805 may support techniques for improved accuracy in beam management predictions, which may likewise increase the reliability of beam management procedures. As such, the device 805 may potentially communicate with a network entity or other wireless device more successfully based on using a more optimal beam, which may, in turn, improve communications reliability and efficiency, reduce communications latency, and improve coordination between the device 805 and other wireless devices.

In some examples, the communications manager 820 may be configured to perform various operations (e.g., receiving, monitoring, transmitting) using or otherwise in cooperation with the transceiver 815, the one or more antennas 825, or any combination thereof. Although the communications manager 820 is illustrated as a separate component, in some examples, one or more functions described with reference to the communications manager 820 may be supported by or performed by the processor 840, the memory 830, the code 835, or any combination thereof. For example, the code 835 may include instructions executable by the processor 840 to cause the device 805 to perform various aspects of accuracy requirements for UE-based signal strength predictions as described herein, or the processor 840 and the memory 830 may be otherwise configured to perform or support such operations.

FIG. 9 illustrates a flowchart showing a method 900 that supports accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure. The operations of the method 900 may be implemented by a UE or its components as described herein. For example, the operations of the method 900 may be performed by a UE 115 as described with reference to FIGs. 1 through 8. In some examples, a UE may execute a set of instructions to control the functional elements of the UE to perform the described functions. Additionally, or alternatively, the UE may perform aspects of the described functions using special-purpose hardware.

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, where an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE. The operations of 905 may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of 905 may be performed by a time-frequency resource component 725 as described with reference to FIG. 7.

At 910, the method may include predicting, in accordance with the accuracy requirement, the one or more signal strength characteristics for a beam of a set of beams with respect to the one or more time-frequency resources. The operations of 910 may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of 910 may be performed by a predicting component 730 as described with reference to FIG. 7.

At 915, the method may include transmitting an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement. The operations of 915 may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of 915 may be performed by a predicting component 730 as described with reference to FIG. 7.

FIG. 10 illustrates a flowchart showing a method 1000 that supports accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure. The operations of the method 1000 may be implemented by a UE or its components as described herein. For example, the operations of the method 1000 may be performed by a UE 115 as described with reference to FIGs. 1 through 8. In some examples, a UE may execute a set of instructions to control the functional elements of the UE to perform the described functions. Additionally, or alternatively, the UE may perform aspects of the described functions using special-purpose hardware.

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, where an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE. The operations of 1005 may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of 1005 may be performed by a time-frequency resource component 725 as described with reference to FIG. 7.

At 1010, the method may include receiving, via a second set of beams corresponding to a second one or more time-frequency resources, one or more downlink reference signals. The operations of 1010 may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of 1010 may be performed by a reference signal component 735 as described with reference to FIG. 7.

At 1015, the method may include measuring the one or more downlink reference signals to obtain a second one or more signal strength characteristics. The operations of 1015 may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of 1015 may be performed by a reference signal component 735 as described with reference to FIG. 7.

At 1020, the method may include predicting, in accordance with the accuracy requirement and using a predictive model associated with beam management, the one or more signal strength characteristics for a beam of a set of beams with respect to the one or more time-frequency resources, where the predicting is based on the second one or more signal strength characteristics. The operations of 1020 may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of 1020 may be performed by a predicting component 730 as described with reference to FIG. 7.

At 1025, the method may include transmitting an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement. The operations of 1025 may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of 1025 may be performed by a predicting component 730 as described with reference to FIG. 7.

FIG. 11 illustrates a flowchart showing a method 1100 that supports accuracy requirements for UE-based signal strength predictions in accordance with one or more aspects of the present disclosure. The operations of the method 1100 may be implemented by a UE or its components as described herein. For example, the operations of the method 1100 may be performed by a UE 115 as described with reference to FIGs. 1 through 8. In some examples, a UE may execute a set of instructions to control the functional elements of the UE to perform the described functions. Additionally, or alternatively, the UE may perform aspects of the described functions using special-purpose hardware.

At 1105, the method may include receiving a request for a capability message indicating a support for a set of one or more accuracy requirements at the UE. The operations of 1105 may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of 1105 may be performed by a capability message component 745 as described with reference to FIG. 7.

At 1110, the method may include transmitting the capability message indicating the support for a set of one or more accuracy requirements at the UE with respect to one or more predicted signal strength characteristics, where transmitting the capability message is based on the request. The operations of 1110 may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of 1110 may be performed by a capability message component 745 as described with reference to FIG. 7.

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, where an accuracy requirement is defined for predicting the one or more signal strength characteristics by the UE. The operations of 1115 may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of 1115 may be performed by a time-frequency resource component 725 as described with reference to FIG. 7.

At 1120, the method may include predicting, in accordance with the accuracy requirement, the one or more signal strength characteristics for a beam of a set of beams with respect to the one or more time-frequency resources. The operations of 1120 may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of 1120 may be performed by a predicting component 730 as described with reference to FIG. 7.

At 1125, the method may include transmitting an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement. The operations of 1125 may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of 1125 may be performed by a predicting component 730 as described with reference to FIG. 7.

At 1125, the method may include transmitting a message indicating a confidence level associated with predicting the one or more signal strength characteristics, where the confidence level is 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. The operations of 1125 may be performed in accordance with examples as disclosed herein. In some examples, aspects of the operations of 1125 may be performed by a confidence level component 740 as described with reference to FIG. 7.

The following provides an overview of aspects of the present disclosure:

Aspect 1: A method for wireless communications at a UE, comprising: 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, in accordance with the accuracy requirement, the one or more signal strength characteristics for a beam of a set of beams with respect to the one or more time-frequency resources; and transmitting an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement.

Aspect 2: The method of aspect 1, further comprising: receiving, via a second set of beams corresponding to a second one or more time-frequency resources, one or more downlink reference signals; and measuring the one or more downlink reference signals to obtain a 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.

Aspect 3: The method of aspect 2, wherein the accuracy requirement is based at least in part on the second one or more signal strength characteristics, a numerical quantity 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.

Aspect 4: The method of any of aspects 1 through 3, further comprising: transmitting 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.

Aspect 5: The method of any of aspects 1 through 4, wherein the accuracy requirement is based at least in part on the one or more signal strength characteristics, a numerical quantity of beams of 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.

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

Aspect 7: The method of any of aspects 1 through 6, wherein the accuracy requirement is based at least in part on a reference value for the one or more signal strength characteristics, the reference value associated with the one or more time-frequency resources.

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

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

Aspect 10: The method of 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.

Aspect 11: The method of any of aspects 8 through 10, wherein the reference value comprises an ideal value for the one or more signal strength characteristics or a measured value of the one or more signal strength characteristics.

Aspect 12: The method of any of aspects 1 through 11, further comprising: transmitting a capability message indicating a support for a set of one or more accuracy requirements at the UE with respect to the predicted signal strength characteristics.

Aspect 13: The method of 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, a numerical quantity of beams of the set of beams, a beam type of the set of beams, a numerical quantity 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.

Aspect 14: The method of any of aspects 12 through 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.

Aspect 15: The method of any of aspects 12 through 14, further comprising: receiving a request for the capability message, wherein transmitting the capability message is based at least in part on the request.

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

Aspect 17: The method of any of aspects 1 through 16, wherein the one or more time-frequency resources comprise one or more virtual resources that are associated with a beam shape of the set of beams, a beam direction of the set of beams, or a combination thereof.

Aspect 18: The method of aspect 17, wherein the one or more virtual resources indicate a correspondence between one or more downlink reference signals and a beam shape of the set of beams, a correspondence between the one or more downlink reference signals and a beam direction of the set of beams, or a QCL correspondence between the one or more downlink reference signals and the set of beams.

Aspect 19: The method of any of aspects 1 through 18, wherein the one or more signal strength characteristics comprise an RSRP, an SINR, or a combination thereof.

Aspect 20: The method of any of aspects 1 through 19, wherein the predicting comprises: predicting the one or more signal strength characteristics using a predictive model associated with beam management.

Aspect 21: An apparatus for wireless communications at a UE, comprising a processor; memory coupled with the processor; and instructions stored in the memory and executable by the processor to cause the apparatus to perform a method of any of aspects 1 through 20.

Aspect 22: An apparatus for wireless communications at a UE, comprising at least one means for performing a method of any of aspects 1 through 20.

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

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

Although aspects of an LTE, LTE-A, LTE-A Pro, or NR system may be described for purposes of example, and LTE, LTE-A, LTE-A Pro, or NR terminology may be used in much of the description, the techniques described herein are applicable beyond LTE, LTE-A, LTE-A Pro, or NR networks. For example, the described techniques may be applicable to various other wireless communications 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, as well as other systems and radio technologies not explicitly mentioned herein.

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

The various illustrative blocks and components described in connection with the disclosure herein may be implemented or performed using a general-purpose processor, a DSP, an ASIC, a CPU, an FPGA or other programmable logic device, discrete gate or transistor logic, 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, multiple microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration) .

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 or transmitted using one or more instructions or code of a computer-readable medium. Other examples and implementations are within the scope of the disclosure and appended claims. For example, due to the nature of software, functions described herein may be implemented using software executed by a processor, hardware, firmware, hardwiring, or combinations of any of these. Features implementing functions may also be physically located at various positions, including being distributed such that portions of functions are implemented at different physical locations.

Computer-readable media includes both non-transitory computer storage media and communication media including any medium that facilitates transfer of a computer program from one location to another. A non-transitory storage medium may be any available medium that may be accessed by a general-purpose or special-purpose computer. By way of example, and not limitation, non-transitory computer-readable media may include RAM, ROM, electrically erasable programmable ROM (EEPROM) , flash memory, compact disk (CD) ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that may be used to carry or store desired program code means in the form of instructions or data structures and that may be accessed by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor. Also, any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL) , or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of computer-readable medium. Disk and disc, as used herein, include CD, laser disc, optical disc, digital versatile disc (DVD) , floppy disk and Blu-ray disc. Disks may reproduce data magnetically, and discs may reproduce data optically using lasers. Combinations of the above are also included within the scope of computer-readable media.

As used herein, including in the claims, “or” as used in a list of items (e.g., a list of items prefaced by a phrase such as “at least one of” or “one or more of” ) indicates an inclusive list such 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) . Also, as used herein, the phrase “based on” shall not be construed as a reference to a closed set of conditions. For example, an example step that is described as “based on condition A” may be based on both a condition A and a condition B without departing from the scope of the present disclosure. In other words, as used herein, the phrase “based on” shall be construed in the same manner as the phrase “based at least in part on. ”

The term “determine” or “determining” encompasses a variety of actions and, therefore, “determining” can include calculating, computing, processing, deriving, investigating, looking up (such as via looking up in a table, a database or another data structure) , ascertaining and the like. Also, “determining” can include receiving (e.g., receiving information) , accessing (e.g., accessing data stored in memory) and the like. Also, “determining” can include resolving, obtaining, selecting, choosing, establishing, and other such similar actions.

In the appended figures, similar components or features may have the same reference label. Further, various components of the same type may be distinguished by following the reference label by a dash and a second label that distinguishes among the similar components. If just the first reference label is used in the specification, the description is applicable to any one of the similar components having the same first reference label irrespective of the second reference label, or other subsequent reference label.

The description set forth herein, in connection with the appended drawings, describes example configurations and does not represent all the examples that may be implemented or that are within the scope of the claims. The term “example” used herein means “serving as an example, instance, or illustration, ” and not “preferred” or “advantageous over other examples. ” The detailed description includes specific details for the purpose of providing an understanding of the described techniques. These techniques, however, may be practiced without these specific details. In some instances, known structures and devices are shown in block diagram form in order to avoid obscuring the concepts of the described examples.

The description herein is provided to enable a person having ordinary skill in the art to make or use the disclosure. Various modifications to the disclosure will be apparent to a person having ordinary skill in the art, and the generic principles defined herein may be applied to other variations without departing from the scope of the disclosure. Thus, the disclosure is not limited to the examples and designs described herein but is to be accorded the broadest scope consistent with the principles and novel features disclosed herein.

Claims

An apparatus for wireless communications at a user equipment (UE) , comprising:

a processor;

memory coupled with the processor; and

instructions stored in the memory and executable by the processor to cause the apparatus 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, in accordance with the accuracy requirement, the one or more signal strength characteristics for a beam of a set of beams with respect to the one or more time-frequency resources; and

transmit an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement.
The apparatus of claim 1, wherein the instructions are further executable by the processor to cause the apparatus to:

receive, via a second set of beams corresponding to a second one or more time-frequency resources, one or more downlink reference signals; and

measure the one or more downlink reference signals to obtain a 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.
The apparatus of claim 2, wherein the accuracy requirement is based at least in part on the second one or more signal strength characteristics, a numerical quantity 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.
The apparatus of claim 1, wherein the instructions are further executable by the processor to cause the apparatus to:

transmit 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.
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 quantity of beams of 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.
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 transmitting the indication.
The apparatus of claim 1, wherein the accuracy requirement is based at least in part on a reference value for the one or more signal strength characteristics, the reference value associated with the one or more time-frequency resources.
The apparatus of claim 7, wherein:

the accuracy requirement defines a tolerance range extending above and below the reference value for the one or more signal strength characteristics, and

the predicted one or more signal strength characteristics fall within the tolerance range.
The apparatus of claim 8, wherein a lower portion of the tolerance range extending below the reference value is symmetric with respect to an upper portion of the tolerance range extending above the reference value.
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.
The apparatus of claim 8, wherein the reference value comprises an ideal value for the one or more signal strength characteristics or a measured value of the one or more signal strength characteristics.
The apparatus of claim 1, wherein the instructions are further executable by the processor to cause the apparatus to:

transmit a capability message indicating a support for a set of one or more accuracy requirements at the UE with respect to the predicted signal strength characteristics.
The apparatus of 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, a numerical quantity of beams of the set of beams, a beam type of the set of beams, a numerical quantity 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.
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.
The apparatus of claim 12, wherein the instructions are further executable by the processor to cause the apparatus to:

receive a request for the capability message, wherein transmitting the capability message is based at least in part on the request.
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.
The apparatus of claim 1, wherein the one or more time-frequency resources comprise one or more virtual resources that are associated with a beam shape of the set of beams, a beam direction of the set of beams, or a combination thereof.
The apparatus of claim 17, wherein the one or more virtual resources indicate a correspondence between one or more downlink reference signals and a beam shape of the set of beams, a correspondence between the one or more downlink reference signals and a 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.
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.
The apparatus of claim 1, wherein the instructions to predict are executable by the processor to cause the apparatus to:

predict the one or more signal strength characteristics using a predictive model associated with beam management.
A method for wireless communications at a user equipment (UE) , comprising:

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, in accordance with the accuracy requirement, the one or more signal strength characteristics for a beam of a set of beams with respect to the one or more time-frequency resources; and

transmitting an indication of the predicted one or more signal strength characteristics in accordance with the accuracy requirement.
The method of claim 21, further comprising:

receiving, via a second set of beams corresponding to a second one or more time-frequency resources, one or more downlink reference signals; and

measuring the one or more downlink reference signals to obtain a 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.
The method of claim 22, wherein the accuracy requirement is based at least in part on the second one or more signal strength characteristics, a numerical quantity 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.
The method of claim 21, further comprising:

transmitting 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.
The method of claim 21, wherein the accuracy requirement is based at least in part on the one or more signal strength characteristics, a numerical quantity of beams of 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.
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 transmitting the indication.
The method of claim 21, wherein the accuracy requirement is based at least in part on a reference value for the one or more signal strength characteristics, the reference value associated with the one or more time-frequency resources.
The method of claim 27, wherein:

the accuracy requirement defines a tolerance range extending above and below the reference value for the one or more signal strength characteristics; and

the predicted one or more signal strength characteristics fall within the tolerance range.
The method of claim 28, wherein a lower portion of the tolerance range extending below the reference value is symmetric with respect to an upper portion of the tolerance range extending above the reference value.
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.