User equipment (UE) indication of known or unknown transmission configuration indicator (TCI) states for ai-based beam management

Abstract

A method, system and apparatus for user equipment (UE) indication of known or unknown transmission configuration indicator (TCI) states for artificial intelligence (AI)-based beam management are disclosed According to one aspect, a method implemented in a UE (22) that is configured to communicate with a network node (16), is disclosed. The method includes determining whether a known transmission configuration indicator (TCI) state uses a known predicted receive beam to receive a transmit beam that is quasi-collocated (QCL) with a predicted transmit beam, and transmitting state information indicating support for use of the known predicted receive beam for receiving the predicted transmit beam that is QCL with the predicted transmit beam.

Description

[0001] USER EQUIPMENT (UE) INDICATION OF KNOWN OR UNKNOWN TRANSMISSION CONFIGURATION INDICATOR (TCI) STATES FOR AI- BASED BEAM MANAGEMENT

[0002] FIELD

[0003] The present disclosure relates to wireless communications, and in particular, to methods for user equipment (UE) indication of known or unknown transmission configuration indicator (TCI) states for artificial intelligence (Al)-based beam management.

[0004] BACKGROUND

[0005] The Third Generation Partnership Project (3GPP) has developed and is developing standards for Fourth Generation (4G) (also referred to as Long Term Evolution (LTE)) and Fifth Generation (5G) (also referred to as New Radio (NR)) wireless communication systems. Such systems provide, among other features, broadband communication between network nodes, such as base stations, and mobile user equipments (UE), as well as communication between network nodes and between UEs. The 3GPP is also developing standards for Sixth Generation (6G) wireless communication networks.

[0006] Beam management

[0007] Beam management procedure

[0008] In high frequency range (FR2), multiple radio frequency (RF) beams may be used to transmit and receive signals at a gNB (“network node” or “base station”) and a UE (user equipment or wireless device). For each downlink (DL) beam from a network node, there is typically an associated best UE receive (Rx) beam for receiving signals from the DL beam. The DL beam and the associated UE Rx beam forms a beam pair. The beam pair may be identified through a so-called beam management process in NR.

[0009] A DL beam is (typically) identified by an associated DL reference signal (RS) transmitted in the beam, either periodically, semi -persistently, or aperiodically. The DL RS for the purpose may be a Synchronization Signal (SS) and Physical Broadcast Channel (PBCH) block (SSB) or a Channel State Information RS (CSLRS). By measuring all the DL RSs, the UE may determine and report to the network node the best DL beam to use for DL transmissions. The network node may then transmit a burst of DL-RS using the reported best DL beam to let the UE evaluate candidate UE Rx beams.

[0010] Although not explicitly stated in the NR specification, beam management has been divided into three procedures, schematically illustrated in FIG. 1. P-1 : Purpose is to find a coarse direction for the UE using wide network node Tx beam covering the whole angular sector;

[0011] P-2: Purpose is to refine the network node Tx beam by doing a new beam search around the coarse direction found in Pl; and

[0012] P-3: Used for UE that has analog beamforming to let the UE find a suitable UE Rx beam.

[0013] P-1 is expected to utilize beams with rather large beamwidths and where the beam reference signals are transmitted periodically and are shared between all UEs of the cell. Typically, reference signals to use for P-1 are periodic CSI-RS or SSB. The UE then reports the N best beams to the network node and their corresponding reference signal received power (RSRP) values.

[0014] P-2 is expected to use aperiodic / or semi -persistent CSI-RS transmitted in narrow beams around the coarse direction found in P-1.

[0015] P-3 is expected to use aperiodic or semi -persistent CSI-RSs repeatedly transmitted in one narrow network node beam. One alternative way is to let the UE determine a suitable UE Rx beam based on the periodic SSB transmission. Since each SSB consists of four orthogonal frequency division multiplexed (OFDM) symbols, a maximum of four UE Rx beams may be evaluated during each SSB burst transmission. One benefit with using SSB instead of CSI-RS is that no extra overhead of CSI-RS transmission is needed.

[0016] Reference signal

[0017] Reference signal configurations

[0018] CSI-RS:

[0019] A CSI-RS is transmitted over each transmit (Tx) antenna port at the network node and for different antenna ports. The CSI-RS are multiplexed in time, frequency, and code domain such that the channel between each Tx antenna port at the network node and each receive antenna port at a UE may be measured by the UE. The time-frequency resource used for transmitting CSI-RS is referred to as a CSI-RS resource.

[0020] In NR, the CSI-RS for beam management is defined as a 1- or 2-port CSI-RS resource in a CSI-RS resource set where the field repetition is present. The following three types of CSI-RS transmissions are supported:

[0021] • Periodic CSI-RS: CSI-RS is transmitted periodically in certain slots. This CSI-RS transmission is semi-statically configured using radio resource control (RRC) signaling with parameters such as CSI-RS resource, periodicity, and slot offset; • Semi-Persistent CSI-RS: Similar to periodic CSI-RS, resources for semi-persistent CSI-RS transmissions are semi-statically configured using RRC signaling with parameters such as periodicity and slot offset. However, unlike periodic CSI-RS, dynamic signaling is needed to activate and deactivate the CSI-RS transmission; and

[0022] • Aperiodic CSI-RS: This is a one-shot CSI-RS transmission that may happen in any slot. Here, one-shot means that CSI-RS transmission only happens once per trigger. The CSI-RS resources (i.e., the RE locations which consist of subcarrier locations and OFDM symbol locations) for aperiodic CSI-RS are semi-statically configured. The transmission of aperiodic CSI-RS is triggered by dynamic signaling through PDCCH using the CSI request field in UL DCI, in the same DCI where the UL resources for the measurement report are scheduled. Multiple aperiodic CSI-RS resources may be included in a CSI-RS resource set and the triggering of aperiodic CSI-RS is on a resource set basis.

[0023] SSB:

[0024] In NR, an SSB consists of a pair of synchronization signals (SSs), physical broadcast channel (PBCH), and demodulation reference signal (DMRS) for PBCH. A SSB is mapped to 4 consecutive OFDM symbols in the time domain and 240 contiguous subcarriers (20 RBs) in the frequency domain.

[0025] To support beamforming and beam-sweeping for SSB transmission, in NR, a cell may transmit multiple SSBs in different narrow-beams in a time multiplexed fashion. The transmission of these SSBs is confined to a half frame time interval (5 ms). It is also possible to configure a cell to transmit multiple SSBs in a single wide-beam with multiple repetitions. The design of beamforming parameters for each of the SSBs within a half frame is up to network implementation. The SSBs within a half frame are broadcasted periodically from each cell. The periodicity of the half frames with SS / PBCH blocks is referred to as SSB periodicity, which is indicated by SIB1.

[0026] The maximum number of SSBs within a half frame, denoted by L, depends on the frequency band, and the time locations for these L candidate SSBs within a half frame depends on the subcarrier spacing (SCS) of the SSBs. The L candidate SSBs within a half frame are indexed in an ascending order in time from 0 to L-l. By successfully detecting PBCH and its associated DMRS, a UE knows the SSB index. A cell does not necessarily transmit SS / PBCH blocks in all L candidate locations in a half frame, and the resource of the un-used candidate positions may be used for the transmission of data or control signaling instead. It is up to network implementation to decide which candidate time locations to select for SSB transmission within a half frame, and which beam to use for each SSB transmission.

[0027] Measurement resource configurations

[0028] In NR, a UE may be configured with N>1 CSI reporting settings (i.e., alternatively referred to as CSI-ReportConfig), M>1 resource settings (i.e., alternatively referred to as CSI-ResourceConfig), where each CSI reporting setting is linked to one or more resource setting for channel and / or interference measurement. The CSI framework is modular, meaning that several CSI reporting settings may be associated with the same Resource Setting.

[0029] The measurement resource configurations for beam management are provided to the UE by RRC IES CSI-ResourceConfigs. One CSI-ResourceConfig contains several non-zero power (NZP)-CSI-RS-ResourceSets and / or CSI-SSB-ResourceSets.

[0030] A UE may be configured to perform measurement on CSI-RSs. Here the RRC information element (IE) NZP-CSI-RS-ResourceSet is used. A NZP CSI-RS resource set contains the configuration of Ks >1 CSI-RS resources, where the configuration of each CSI-RS resource includes at least: mapping to resource elements (REs), the number of antenna ports, time-domain behavior, etc. Up to 64 CSI-RS resources may be grouped to an NZP-CSI-RS-ResourceSet. A UE may also be configured to perform measurements on SSBs. Here, the RRC IE CSI-SSB-ResourceSet is used. Resource sets comprising SSB resources are defined in a similar manner.

[0031] In the case of aperiodic CSI-RS and / or aperiodic CSI reporting, the network node configures the UE with ScCSI triggering states. Each triggering state contains the aperiodic CSI report setting to be triggered along with the associated aperiodic CSI-RS resource sets.

[0032] Periodic and semi-persistent Resource Settings may only comprise a single resource set (i.e. S=l) while S>=1 for aperiodic Resource Settings. This is because in the aperiodic case, one out of the S resource sets comprised in the Resource Setting is indicated by the aperiodic triggering state that triggers a CSI report.

[0033] The RRC IEs described above are defined in 3GPP Technical Standard (TS) 38.331 V18.0.0 Measurement Reporting

[0034] Three types of CSI reporting are supported in NR as follows: • Periodic CSI Reporting on physical uplink control channel (PUCCH): CSI is reported periodically by a UE. Parameters such as periodicity and slot offset are configured semi-statically by higher layer RRC signaling from the network node to the UE;

[0035] • Semi-Persistent CSI Reporting on physical uplink shared channel (PUSCH) or PUCCH: similar to periodic CSI reporting, semi-persistent CSI reporting has a periodicity and slot offset which may be semi-statically configured. However, a dynamic trigger from network node to UE may be needed to allow the UE to begin semi-persistent CSI reporting. A dynamic trigger from network node to UE is needed to request the UE to stop the semi-persistent CSI reporting; and

[0036] • Aperiodic CSI Reporting on PUSCH: This type of CSI reporting involves a single-shot (i.e., one time) CSI report by a UE which is dynamically triggered by the network node using downlink control information (DCI). Some of the parameters related to the configuration of the aperiodic CSI report is semi-statically configured by RRC but the triggering is done dynamically via DCI.

[0037] In each CSI reporting setting, the content and time-domain behavior of the report is defined, along with the linkage to the associated Resource Settings. The CSI-ReportConfig IE comprises the following configurations:

[0038] • reportConfigType o Defines the time-domain behavior, i.e., periodic CSI reporting, semi-persistent CSI reporting, or aperiodic CSI reporting, along with the periodicity and slot offset of the report for periodic CSI reporting;

[0039] • reportQuantity o Defines the reported CSI param eter(s) (i.e. the CSI content), such as Precoding Matrix Indicator (PMI), Channel Quality Indicator (CQI), Rank Indicator (RI), Layer Indicator (LI), CRI (CSLRS resource index) and Ll-RSRP. Only a certain number of combinations are possible (e.g., ‘cri-RI-PMI-CQI’ is one possible value and ‘cri-RSRP’ is another) and each value of reportQuantity may be said to correspond to a certain CSI mode.

[0040] • The IE CSI-ReportConfig is used to configure a periodic or semi-persistent report sent on PUCCH on the cell in which the CSI-ReportConfig is included, or to configure a semi-persistent or aperiodic report sent on PUSCH triggered by DCI received on the cell in which the CSI- ReportConfig is included (in this case, the cell on which the report is sent is determined by the received DCI). See 3GPP TS 38.214

[0019] , clause 5.2.1.

[0041] CSI-ReportConfig information element

[0042] - ASN1 START

[0043] - TAG-CSLREPORTCONFIG-START

[0044] CSI-ReportConfig ::= SEQUENCE { reportConfigld CSI-ReportConfigld, carrier ServCelllndex OPTIONAL, — Need S resourcesForChannelMeasurement CSI-ResourceConfigld, csi-IM-ResourcesForlnterference CSI-ResourceConfigld OPTIONAL,

[0045] -- Need R nzp -CSLRS-ResourcesForlnterference CSI-ResourceConfigld

[0046] OPTIONAL, — Need R reportConfigType CHOICE { periodic SEQUENCE { reportSlotConfig CSLReportPeriodicityAndOffset, pucch-C Si-Re sourceLi st SEQUENCE (SIZE (L.maxNrofBWPs))

[0047] OF PUCCH-CSLResource

[0048] }, semiPersistentOnPUCCH SEQUENCE { reportSlotConfig CSLReportPeriodicityAndOffset, pucch-C Si-Re sourceLi st SEQUENCE (SIZE (L.maxNrofBWPs))

[0049] OF PUCCH-CSLResource

[0050] }, semiPer si stentOnPU S CH SEQUENCE { reportSlotConfig ENUMERATED {sl5, si 10, sl20, sl40, sl80,

[0051] S1160, sl320}, reportSlotOffsetList SEQUENCE (SIZE (L. maxNrofUL-

[0052] Allocations)) OF INTEGER(0..32), pOalpha PO-PUSCH-AlphaSetld

[0053] }, aperiodic SEQUENCE { reportSlotOffsetList SEQUENCE (SIZE (1..maxNrofUL-

[0054] Allocations)) OF INTEGER(0..32)

[0055] } reportQuantity CHOICE { none NULL, cri-RI-PMI-CQI NULL, cri-RI-il NULL, cri-RI-il-CQI SEQUENCE { pdsch-Bundle SizeF orC SI ENUMERATED {n2, n4}

[0056] OPTIONAL - Need S

[0057] }, cri-RI-CQI NULL, cri-RSRP NULL, ssb-Index-RSRP NULL, cri-RI-LI-PMI-CQI NULL

[0058] }, reportQuantity -r 16 CHOICE { cri-SINR-rl6 NULL, ssb-Index-SINR-r!6 NULL

[0059] } OPTIONAL, -

[0060] Need R

[0061] OPTIONAL, — Need R reportQuantity-rl7 CHOICE { cri-RSRP-Index-rl7 NULL, ssb-Index-RSRP -Index-r 17 NULL, cri-SINR-Index-rl7 NULL, ssb-Index-SINR-Index-r!7 NULL reportQuantity-rl8 TDCP-rl8

[0062] OPTIONAL, - Need R

[0063] Portlndex4::= INTEGER (0 .3)

[0064] Portlndex2: := INTEGER (0 .1) TDCP-rl8 ::= SEQUENCE { delayDSetofLengthY-rl8 SEQUENCE (SIZE (L. maxNrofdelayD-rl8)) OF

[0065] DelayD, phaseReporting-rl8 ENUMERATED {enable}

[0066] OPTIONAL - Need R

[0067] DelayD ::= ENUMERATED { symb4, slotl, slot2, slot3, slot4, slot5, slot6, slotlO } CSI-ReportSubConfig-rl8 ::= SEQUENCE { reportSubConfigld-r 18 CSLReportSubConfigld-r 18, reportSubConfigParams-r 18 CHOICE { al -parameters SEQUENCE { codebookSubConfig-r 18 CodebookConfig OPTIONAL, — Need R portSubsetlndicator-r 18 CHOICE { p2 BIT STRING (SIZE (2)), p4 BIT STRING (SIZE (4)), p8 BIT STRING (SIZE (8)), pl2 BIT STRING (SIZE (12)), pl6 BIT STRING (SIZE (16)), p24 BIT STRING (SIZE (24)), p32 BIT STRING (SIZE (32)) OPTIONAL,

[0068] Need R non-PMI-Portlndication-r 18 SEQUENCE (SIZE (1..maxNrofNZP-CSL

[0069] RS-ResourcesPerConfig)) OF PortIndexFor8Ranks

[0070] OPTIONAL

[0071] Need R

[0072] }, a2 -parameters SEQUENCE { nzp-CSLRS-ResourceList-rl 8 SEQUENCE (SIZE (1..maxNrofNZP-CSL

[0073] RS-ResourcesPerSet)) OF NZP-CSI-RS-ResourceIndex-rl8

[0074] } } OPTIONAL,

[0075] Need R powerOffset-rl8 INTEGER(0..23)

[0076] OPTIONAL - Need R }

[0077] NZP-CSLRS-Resourcelndex-r 18 : := INTEGER (0..maxNrofNZP-CSLRS-

[0078] ResourcesPerSet- 1 -r 18)

[0079] - TAG-CSLREPORTCONFIG-STOP

[0080] - ASN1STOP

[0081] • codebookConfig o Defines the codebook used for PMI reporting, along with possible codebook subset restriction (CBSR). Two “Types” of PMI codebook are defined in NR, Type I CSI and Type II CSI, each codebook type further has two variants each;

[0082] • reportFrequencyConfiguration o Define the frequency granularity of PMI and CQI (wideband or subband), if reported, along with the CSI reporting band, which is a subset of subbands of the bandwidth part (BWP) which the CSI corresponds to;

[0083] • Measurement restriction in time domain (ON / OFF) for channel and interference respectively.

[0084] For beam management, a UE may be configured to report LI -RSRP for up to four different CSLRS / SSB resource indicators. The reported RSRP value corresponding to the first (best) CRI / SSBRI requires 7 bits, using absolute values, while the remainder require 4 bits using encoding relative to the first. In 3 GPP Rel-16, the report of LI -signal to interference plus noise ratio (SINR) for beam management has already been supported. QCL and TCI states

[0085] In NR, several signals may be transmitted from different antenna ports of a same base station. These signals may have the same large-scale properties such as Doppler shift / spread, average delay spread, or average delay. These antenna ports are then said to be quasi co-located (QCL).

[0086] If the UE knows that two antenna ports are QCL with respect to a certain parameter (e.g., Doppler spread), the UE may estimate that parameter based on one of the antenna ports and apply that estimate for receiving signal on the other antenna port.

[0087] For example, there may be a QCL relation between a CSLRS for tracking RS (TRS) and the physical downlink shared channel (PDSCH) DMRS. When the UE receives the PDSCH DMRS, it may use the measurements already made on the TRS to assist the DMRS reception.

[0088] Information about what assumptions may be made regarding QCL is signaled to the UE from the network. In NR, four types of QCL relations between a transmitted source RS and transmitted target RS were defined:

[0089] Type A: {Doppler shift, Doppler spread, average delay, delay spread}

[0090] Type B: {Doppler shift, Doppler spread}

[0091] Type C: {average delay, Doppler shift}

[0092] Type D: {Spatial Rx parameter}

[0093] QCL type D was introduced to facilitate beam management with analog beamforming and is known as spatial QCL. There is currently no strict definition of spatial QCL, but the understanding is that if two transmitted antenna ports are spatially QCL, the UE may use the same Rx beam to receive them. This is helpful for a UE that uses analog beamforming to receive signals, since the UE needs to adjust its Rx beam in some direction prior to receiving a certain signal. If the UE knows that the signal is spatially QCL with some other signal it has received earlier, then it may safely use the same Rx beam to receive also this signal. Note that for beam management, the discussion mostly revolves around QCL Type D, but it is also necessary to convey a Type A QCL relation for the RSs to the UE, so that it may estimate all the relevant large-scale parameters.

[0094] Typically, this is achieved by configuring the UE with a CSLRS for tracking (TRS) for time / frequency offset estimation. To be able to use any QCL reference, the UE would have to receive it with a sufficiently good SINR. In many cases, this means that the TRS must be transmitted in a suitable beam to a certain UE. To introduce dynamics in beam and transmission point (TRP) selection, the UE may be configured through RRC signaling with up to 128 TCI (Transmission Configuration Indicator) states. The TCI state information element is as follows:

[0095] TCI-State ::= SEQUENCE ) tci-Stateld TCLStateld, qcl-Type 1 QCL-Info, qcl-Type2 QCL-Info

[0096] QCL-Info ::= SEQUENCE { cell ServCelllndex bwp-Id BWP-Id referencesignal CHOICE { csi-rs NZP-CSI-RS-Resourceld, ssb SSB -Index

[0097] }, qcl-Type ENUMERATED {typeA, typeB, typeC, typeD},

[0098] }

[0099] Each TCI state contains QCL information related to one or two RSs. For example, a TCI state may contain CSI-RS 1 associated with QCL Type A and CSI-RS2 associated with QCL TypeD. If a third RS, e.g., the physical downlink control channel (PDCCH) DMRS, has this TCI state as QCL source, it means that the UE may derive Doppler shift, Doppler spread, average delay, delay spread from CSI-RS 1 and Spatial Rx parameter (i.e. the Rx beam to use) from CSI-RS2 when performing the channel estimation for the PDCCH DMRS.

[0100] A first list of available TCI states is configured for PDSCH, and a second list of TCI states is configured for PDCCH. Each TCI state contains a pointer, known as TCI State ID, which points to the TCI state. The network then activates via medium access control (MAC) control element (CE) one TCI state for PDCCH (i.e., provides a TCI for PDCCH) and up to eight TCI states for PDSCH. The number of active TCI states the UE support is a UE capability, but the maximum is 8. Assume a UE has 4 activated TCI states (from a list of totally 64 configured TCI states). Hence, 60 TCI states are inactive for this particular UE and the UE need not be prepared to have large scale parameters estimated for those inactive TCI states. But the UE continuously tracks and updates the large scale parameters for the RSs in the 4 active TCI states. When scheduling a PDSCH to a UE, the DCI contains a pointer to one activated TCI state. The UE then knows which large scale parameter estimate to use when performing PDSCH DMRS channel estimation and thus PDSCH demodulation.

[0101] As long as the UE may use any of the currently activated TCI states, it is sufficient to use DCI signaling. However, at some point in time, none of the RSs in the currently activated TCI states may be received by the UE, i.e., when the UE moves out of the beams in which the RSs in the activated TCI states are transmitted. When this happens (or actually before this happens), the network node would have to activate new TCI states. Typically, since the number of activated TCI states is fixed, the network node would also have to deactivate one or more of the currently activated TCI states.

[0102] The two-step procedure related to TCI state update is depicted FIG. 2. In FIG. 2, the selected TCI state is selected from the activated set of TCI states using DCI, and the set of activated TCI states is updated using MAC CE.

[0103] Known conditions for TCI state

[0104] The known conditions for TCI state is defined in Clause 8.10.2 of 3GPP TS 38.133 V18.7.0, and the impact to TCI state switch delay is consequently defined in Clause 8.10.3 of 3GPP TS 38.133 V18.7.0, which are duplicated below.

[0105]

[0106] Beam prediction in 3GPP

[0107] In 3GPP Technical Release 19 (3GPP Rel-19), there is an ongoing work on specifying beam prediction both at the network node and at the UE side. The feature defines a set A of beams that is to be predicted, via measurements on a set B of beams. FIG. 3 illustrates a schematic example of the Set A of beams and the Set B of beams. The top illustration shows all the narrow network node beams, which constitutes the Set A of beams, and the lower illustration shows all the wide network node beams, which constitutes the Set B of beams.

[0108] FIG. 4 illustrates another example of the Set A of beams and the Set B of beams, wherein Set A contains narrow network node beams and set B is subset of Set A containing some narrows beams from the network node.

[0109] The feature is introduced using the existing CSI framework defined in NR. The set A and set B are transmitted / reported in respect to a resource set. The method for UE reporting of its predicted beams is in respect to such set A of beams. In order for the UE to train a model, the beam prediction feature further supports a set of associated IDs, where UE may assume the similar properties of a DL Tx beam or beam set / list associated with the same associated ID.

[0110] When the UE is using artificial intelligence / machine learning (AI / ML) to predict the set A Tx beam, some capable UEs might also during the training phase train the model to predict the best Rx beam to use for a certain set A Tx beam, where such “best” Rx beam may be in respect to:

[0111] 1. The Set A beam; and / or

[0112] 2. The beam used as QCL source to receive the set A beam.

[0113] For such UEs, during inference, the UE would be in “known TCI state” in case the network node would configure an RS with the said set A Tx beam as the source QCL (option 1 above), or in case the network node would configure an RS with the beam used as QCL source to receive the set A beam as the source QCL (option 2 above).

[0114] For other less advanced UEs that cannot predict the best Rx beam for a certain set A Tx beam, the performance in case network node would directly transmit data with such set A Tx beam would lead to a performance drop. In case the network node would assume that all UEs are in unknown TCI state, this may lead to unnecessary high signaling overhead and time-consuming measurements for ensuring that the UE is using the best Rx beam for a set A network node Tx beam. Hence, in order to reduce such high signaling overhead and time-consuming measurements, the known / unknown TCI state assumptions need to be known at the network for beam prediction using the AI / ML beam prediction feature. How the knowledge of known or unknown TCI state assumptions is acquired at the network is an open problem to be solved. SUMMARY

[0115] Some embodiments advantageously provide methods, systems, and apparatuses for UE indication of known or unknown transmission configuration indicator (TCI) states for artificial intelligence (Al)-based beam management.

[0116] Some embodiments include a method for a UE to indicate to the network node the support for known or unknown TCI state for one or more predicted set A Tx beams. In some embodiments, a method both includes providing a static indication as part of the UE capability report, as well as dynamic updating of the UE’s ability to support a known TCI state for one or more predicted set A Tx beams. The dynamic update may be achieved via one or more of uplink control information (UCI), RRC, UAI (UE assistance information) or MAC CE signaling.

[0117] Methods in a UE are provided in some embodiments to determine whether the optimal Rx beam may be predicted via its AI / ML model, and then indicate whether one or more predicted set A Tx beams at the network node have a known TCI state.

[0118] In some embodiments, for a known TCI state, the UE may determine, for a predicted Tx beam part of set A, an optimal or quasi-optimal Rx beam. Optimality may be in reference to the Rx beam that provides the highest signal quality when measuring the set A Tx beam. For quasi-optimality, when the UE may measure with a Rx beam that provides the highest signal quality when measuring a Tx beam that is QCLed with the predicted set A Tx beam.

[0119] Throughout the following disclosure, the terms Tx beam and Rx beam are used. Alternative terminologies such as ‘Tx filter’ or ‘Tx spatial filter’ may be used interchangeably in place of ‘Tx beam’. Similarly, alternative terminologies such as ‘Rx filter’ or ‘Rx spatial filter’ may be used interchangeably in place of ‘Rx beam’.

[0120] Some embodiments include a method for UE to dynamically indicate to the network node the known / unknown TCI state assumption for a predicted set A Tx beam, where the RS is associated with a certain network node Set A Tx beam.

[0121] In some embodiments, the network node only configures extra resources for enabling the UE to have a known TCI state if needed. This may reduce the overall signaling overhead. In some embodiments, the handling of known / unknown TCI state to support different UE capabilities is provided. Some embodiments are also applicable to scenarios where the UE cannot estimate the Rx beam due to UE-side conditions (e.g. blockage or certain UE speeds). In accordance with one aspect of the present disclosure, a method implemented in a user equipment (UE) that is configured to communicate with a network node is provided. The method includes determining whether a known transmission configuration indicator, (TCI) state uses a known predicted receive beam to receive a transmit beam that is quasicollocated (QCL) with a predicted transmit beam, and transmitting state information indicating support for use of the known predicted receive beam for receiving the predicted transmit beam that is QCL with the predicted transmit beam.

[0122] In some embodiments, the state information is based at least in part on a comparison of a probability of predicting a strongest known receive beam to a threshold.

[0123] In some embodiments, the state information is based at least in part on a speed of movement of the UE.

[0124] In some embodiments, the UE transmits the state information as part of at least one of an inference report, a capability report, a radio resource control (RRC) signaling, and a UE assistance information (UAI) report.

[0125] In some embodiments, the state information includes a validity time duration for the known predicted receive beam.

[0126] In some embodiments, the state information includes an indication of whether a subsequently measured beam has a same QCL relation to the predicted transmit beam.

[0127] In accordance with another aspect of the present disclosure, a UE configured to communicate with a network node is provided. The UE is configured to determine whether a known transmission configuration indicator (TCI) state uses a known predicted receive beam to receive a transmit beam that is quasi-collocated (QCL) with a predicted transmit beam, and transmit state information indicating support for use of the known predicted receive beam for receiving the predicted transmit beam that is QCL with the predicted transmit beam.

[0128] In some embodiments, the state information is based at least in part on a comparison of a probability of predicting a strongest known receive beam to a threshold.

[0129] In some embodiments, the state information is based at least in part on a speed of movement of the UE.

[0130] In some embodiments, the UE transmits the state information as part of at least one of an inference report, a capability report, a radio resource control (RRC) signaling, and a UE assistance information (UA), report.

[0131] In some embodiments, the state information includes a validity time duration for the known predicted receive beam. In some embodiments, the state information includes an indication of whether a subsequently measured beam has a same QCL relation to the predicted transmit beam.

[0132] In accordance with another aspect of the present disclosure, a method implemented in a network node that is configured to communicate with a user equipment (UE), is provided. The method includes receiving state information indicating whether the UE is in a known or unknown transmission configuration indicator (TCI) state for a predicted and reported reference signal, and configuring a beam management process based at least in part on the received state information.

[0133] In some embodiments, the state information is based at least in part on a comparison of a probability of predicting a strongest known receive beam to a threshold.

[0134] In some embodiments, the network node receives the state information as part of at least one of an inference report, a capability report, a radio resource control (RRC) signaling, and a UE assistance information (UAI) report from the UE, the method further including adapting at least one parameter in the beam management process based on the received state information.

[0135] In some embodiments, the state information includes a UE prediction performance in estimating a known predicted receive beam, the method further including configuring subsequent measurements in case the UE prediction performance is below a threshold value.

[0136] In some embodiments, the state information includes a validity time duration for the known predicted receive beam.

[0137] In some embodiments, the state information includes an indication of whether a subsequently measured beam has a same quasi-collocation (QCL) relation to a predicted set A transmit beam.

[0138] In some embodiments, the method further includes instructing the UE to not estimate the known predicted receive beam to save UE computational resources.

[0139] In accordance with another aspect of the present disclosure, a network node configured to communicate with a user equipment (UE)), is provided. The network node is configured to receive state information indicating whether the UE is in a known or unknown transmission configuration indicator (TCI) state for a predicted and reported reference signal, and configure a beam management process based at least in part on the received state information.

[0140] In some embodiments, the state information is based at least in part on a comparison of a probability of predicting a strongest known receive beam to a threshold. In some embodiments, the network node receives the state information as part of at least one of an inference report, a capability report, a radio resource control (RRC) signaling, and a UE assistance information (UAI) report from the UE, and the network node is further configured to adapt at least one parameter in the beam management process based on the received state information.

[0141] In some embodiments, the state information includes a UE prediction performance in estimating a known predicted receive beam, and the network node is further configured to configure subsequent measurements in case the UE prediction performance is below a threshold value.

[0142] In some embodiments, the state information includes a validity time duration for the known predicted receive beam.

[0143] In some embodiments, the state information includes an indication of whether a subsequently measured beam has a same quasi-collocation (QCL) relation to a predicted set A transmit beam.

[0144] In some embodiments, the network node is further configured to instruct the UE to not estimate the known predicted receive beam to save UE computational resources.

[0145] BRIEF DESCRIPTION OF THE DRAWINGS

[0146] A more complete understanding of the present embodiments, and the attendant advantages and features thereof, will be more readily understood by reference to the following detailed description when considered in conjunction with the accompanying drawings wherein:

[0147] FIG. l is a diagram of a beam management procedure;

[0148] FIG. 2 is a diagram of a TCI update procedure;

[0149] FIG. 3 is a diagram of a first set of beams;

[0150] FIG. 4 is a diagram of another set of beams;

[0151] FIG. 5 is a schematic diagram of an example network architecture illustrating a communication system according to principles disclosed herein;

[0152] FIG. 6 is a block diagram of a network node in communication with a user equipment over a wireless connection according to some embodiments of the present disclosure;

[0153] FIG. 7 is a flowchart of an example process in a network node for UE indication of known or unknown transmission configuration indicator (TCI) states for artificial intelligence (Al)-based beam management according to some embodiments of the present disclosure; FIG. 8 is a flowchart of an example process in a user equipment for UE indication of known or unknown transmission configuration indicator (TCI) states for artificial intelligence (Al)-based beam management according to some embodiments of the present disclosure;

[0154] FIG. 9 is a flowchart of another example process in a user equipment according to some embodiments of the present disclosure;

[0155] FIG. 10 is a diagram of an example scenario for beam management according to principles disclosed herein; and

[0156] FIG. 11 is a diagram of an example process for beam management according to principles disclosed herein.

[0157] DETAILED DESCRIPTION

[0158] Before describing in detail example embodiments, it is noted that the embodiments reside primarily in combinations of apparatus components and processing steps related to UE indication of known or unknown transmission configuration indicator (TCI) states for artificial intelligence (Al)-based beam management. Accordingly, components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the embodiments so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein.

[0159] As used herein, relational terms, such as “first” and “second,” “top” and “bottom,” and the like, may be used solely to distinguish one entity or element from another entity or element without necessarily requiring or implying any physical or logical relationship or order between such entities or elements. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the concepts described herein. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and / or “including” when used herein, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0160] In embodiments described herein, the joining term, “in communication with” and the like, may be used to indicate electrical or data communication, which may be accomplished by physical contact, induction, electromagnetic radiation, radio signaling, infrared signaling or optical signaling, for example. One having ordinary skill in the art will appreciate that multiple components may interoperate and modifications and variations are possible of achieving the electrical and data communication.

[0161] In some embodiments described herein, the term “coupled,” “connected,” and the like, may be used herein to indicate a connection, although not necessarily directly, and may include wired and / or wireless connections.

[0162] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the concepts described herein. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and / or “including” when used herein, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0163] The term “network node” used herein can be any kind of network node comprised in a radio network which may further comprise any of base station (BS), radio base station, base transceiver station (BTS), base station controller (BSC), radio network controller (RNC), g Node B (gNB), evolved Node B (eNB or eNodeB), Node B, multistandard radio (MSR) radio node such as MSR BS, multi-cell / multicast coordination entity (MCE), relay node, donor node controlling relay, radio access point (AP), transmission points, transmission nodes, Remote Radio Unit (RRU) Remote Radio Head (RRH), a core network node (e.g., mobile management entity (MME), self-organizing network (SON) node, a coordinating node, positioning node, MDT node, etc.), an external node (e.g., 3rd party node, a node external to the current network), nodes in distributed antenna system (DAS), a spectrum access system (SAS) node, an element management system (EMS), etc. The network node may also comprise test equipment. The term “radio node” used herein may be used to also denote a user equipment (UE) such as a wireless device (WD) or a radio network node.

[0164] In some embodiments, the non-limiting terms wireless device (WD) or a user equipment (UE) are used interchangeably. The UE herein can be any type of user equipment capable of communicating with a network node or another UE over radio signals, such as a wireless device (WD). The UE may also be a radio communication device, target device, device to device (D2D) UE, machine type UE or UE capable of machine to machine communication (M2M), low-cost and / or low-complexity UE, a sensor equipped with UE, Tablet, mobile terminals, smart phone, laptop embedded equipped (LEE), laptop mounted equipment (LME), USB dongles, Customer Premises Equipment (CPE), an Internet of Things (loT) device, or a Narrowband loT (NB-IOT) device etc.

[0165] Also, in some embodiments the generic term “radio network node” is used. It can be any kind of a radio network node which may comprise any of base station, radio base station, base transceiver station, base station controller, network controller, RNC, evolved Node B (eNB), Node B, gNB, Multi-cell / multicast Coordination Entity (MCE), relay node, access point, radio access point, Remote Radio Unit (RRU) Remote Radio Head (RRH).

[0166] Note that although terminology from one particular wireless system, such as, for example, 3GPP LTE and / or New Radio (NR) and / or 6G, may be used in this disclosure, this should not be seen as limiting the scope of the disclosure to only the aforementioned system. It is contemplated that other 3GPP systems may make use of the concepts and arrangements disclosed herein. For example, a disclosure relating to NR may also be implementable in a 6G system and / or an LTE system, a disclosure relating to 6G may also be implementable in a NR and / or LTE system, and a disclosure relating to LTE may also be implementable in a NR and / or 6G system. Other wireless systems, including without limitation Wide Band Code Division Multiple Access (WCDMA), Worldwide Interoperability for Microwave Access (WiMax), Ultra Mobile Broadband (UMB) and Global System for Mobile Communications (GSM), may also benefit from exploiting the ideas covered within this disclosure.

[0167] Note further, that functions described herein as being performed by a user equipment or a network node may be distributed over a plurality of user equipments and / or network nodes. In other words, it is contemplated that the functions of the network node and user equipment described herein are not limited to performance by a single physical device and, in fact, can be distributed among several physical devices.

[0168] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. It will be further understood that terms used herein should be interpreted as having a meaning that is consistent with their meaning in the context of this specification and the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein. Some embodiments are directed to UE indication of known or unknown transmission configuration indicator (TCI) states for artificial intelligence (Al)-based beam management.

[0169] Referring again to the drawing figures, in which like elements are referred to by like reference numerals, there is shown in FIG. 5 a schematic diagram of a communication system 10, according to an embodiment, such as a 3 GPP -type cellular network that may support standards such as LTE and / or NR (5G) and / or 6G, which comprises an access network 12, such as a radio access network, and a core network 14. The access network 12 comprises a plurality of network nodes 16a, 16b, 16c (referred to collectively as network nodes 16), such as NBs, eNBs, gNBs or other types of wireless access points, each defining a corresponding coverage area 18a, 18b, 18c (referred to collectively as coverage areas 18). Each network node 16a, 16b, 16c is connectable to the core network 14 over a wired or wireless connection 20. A first user equipment (UE) 22a located in coverage area 18a is configured to wirelessly connect to, or be paged by, the corresponding network node 16a. A second UE 22b in coverage area 18b is wirelessly connectable to the corresponding network node 16b. While a plurality of UEs 22a, 22b (collectively referred to as user equipments 22) are illustrated in this example, the disclosed embodiments are equally applicable to a situation where a sole UE is in the coverage area or where a sole UE is connecting to the corresponding network node 16. Note that although only two UEs 22 and three network nodes 16 are shown for convenience, the communication system may include many more UEs 22 and network nodes 16.

[0170] Also, it is contemplated that a UE 22 can be in simultaneous communication and / or configured to separately communicate with more than one network node 16 and more than one type of network node 16. For example, a UE 22 can have dual connectivity with a network node 16 that supports LTE and the same or a different network node 16 that supports NR. As an example, UE 22 can be in communication with an eNB for LTE / E-UTRAN and a gNB for NR / NG-RAN.

[0171] A network node 16 (eNB or gNB) is configured to include a configuration unit 24 which may be configured to configure a beam management process based at least in part on the received state information. A user equipment 22 is configured to include a state information unit 26 which may be configured to transmit state information indicating support for use of the known predicted receive beam for receiving the predicted transmit beam that is QCL with the predicted set A transmit beam. Example implementations, in accordance with an embodiment, of the UE 22 and network node 16 discussed in the preceding paragraphs will now be described with reference to FIG. 6.

[0172] The communication system 10 includes a network node 16 provided in a communication system 10 and including hardware 28 enabling it to communicate with the UE 22. The hardware 28 may include a radio interface 30 for setting up and maintaining at least a wireless connection 32 with a UE 22 located in a coverage area 18 served by the network node 16. The radio interface 30 may be formed as or may include, for example, one or more RF transmitters, one or more RF receivers, and / or one or more RF transceivers. The radio interface 30 includes an array of antennas 34 to radiate and receive signal(s) carrying electromagnetic waves.

[0173] In the embodiment shown, the hardware 28 of the network node 16 further includes processing circuitry 36. The processing circuitry 36 may include a processor 38 and a memory 40. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 36 may comprise integrated circuitry for processing and / or control, e.g., one or more processors and / or processor cores and / or FPGAs (Field Programmable Gate Array) and / or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 38 may be configured to access (e.g., write to and / or read from) the memory 40, which may comprise any kind of volatile and / or nonvolatile memory, e.g., cache and / or buffer memory and / or RAM (Random Access Memory) and / or ROM (Read-Only Memory) and / or optical memory and / or EPROM (Erasable Programmable Read-Only Memory).

[0174] Thus, the network node 16 further has software 42 stored internally in, for example, memory 40, or stored in external memory (e.g., database, storage array, network storage device, etc.) accessible by the network node 16 via an external connection. The software 42 may be executable by the processing circuitry 36. The processing circuitry 36 may be configured to control any of the methods and / or processes described herein and / or to cause such methods, and / or processes to be performed, e.g., by network node 16. Processor 38 corresponds to one or more processors 38 for performing network node 16 functions described herein. The memory 40 is configured to store data, programmatic software code and / or other information described herein. In some embodiments, the software 42 may include instructions that, when executed by the processor 38 and / or processing circuitry 36, causes the processor 38 and / or processing circuitry 36 to perform the processes described herein with respect to network node 16. For example, processing circuitry 36 of the network node 16 may include a configuration unit 24 which may be configured to configure a beam management process based at least in part on the received state information.

[0175] The communication system 10 further includes the UE 22 already referred to. The UE 22 may have hardware 44 that may include a radio interface 46 configured to set up and maintain a wireless connection 32 with a network node 16 serving a coverage area 18 in which the UE 22 is currently located. The radio interface 46 may be formed as or may include, for example, one or more RF transmitters, one or more RF receivers, and / or one or more RF transceivers. The radio interface 46 includes an array of antennas 48 to radiate and receive signal(s) carrying electromagnetic waves.

[0176] The hardware 44 of the UE 22 further includes processing circuitry 50. The processing circuitry 50 may include a processor 52 and memory 54. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 50 may comprise integrated circuitry for processing and / or control, e.g., one or more processors and / or processor cores and / or FPGAs (Field Programmable Gate Array) and / or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 52 may be configured to access (e.g., write to and / or read from) memory 54, which may comprise any kind of volatile and / or nonvolatile memory, e.g., cache and / or buffer memory and / or RAM (Random Access Memory) and / or ROM (Read-Only Memory) and / or optical memory and / or EPROM (Erasable Programmable Read-Only Memory).

[0177] Thus, the UE 22 may further comprise software 56, which is stored in, for example, memory 54 at the UE 22, or stored in external memory (e.g., database, storage array, network storage device, etc.) accessible by the UE 22. The software 56 may be executable by the processing circuitry 50. The software 56 may include a client application 58. The client application 58 may be operable to provide a service to a human or non-human user via the UE 22.

[0178] The processing circuitry 50 may be configured to control any of the methods and / or processes described herein and / or to cause such methods, and / or processes to be performed, e.g., by UE 22. The processor 52 corresponds to one or more processors 52 for performing UE 22 functions described herein. The UE 22 includes memory 54 that is configured to store data, programmatic software code and / or other information described herein. In some embodiments, the software 56 and / or the client application 58 may include instructions that, when executed by the processor 52 and / or processing circuitry 50, causes the processor 52 and / or processing circuitry 50 to perform the processes described herein with respect to UE 22. For example, the processing circuitry 50 of the user equipment 22 may include a state information unit 26 which may be configured to transmit state information indicating support for use of the known predicted receive beam for receiving the predicted transmit beam that is QCL with the predicted set A transmit beam.

[0179] In some embodiments, the inner workings of the network node 16 and UE 22 may be as shown in FIG. 6 and independently, the surrounding network topology may be that of FIG. 5.

[0180] The wireless connection 32 between the UE 22 and the network node 16 is in accordance with the teachings of the embodiments described throughout this disclosure. More precisely, the teachings of some of these embodiments may improve the data rate, latency, and / or power consumption and thereby provide benefits such as reduced user waiting time, relaxed restriction on file size, better responsiveness, extended battery lifetime, etc. In some embodiments, a measurement procedure may be provided for the purpose of monitoring data rate, latency and other factors on which the one or more embodiments improve.

[0181] Although FIGS. 5 and 6 show various “units” such as configuration unit 24 and state information unit 26 as being within a respective processor, it is contemplated that these units may be implemented such that a portion of the unit is stored in a corresponding memory within the processing circuitry. In other words, the units may be implemented in hardware or in a combination of hardware and software within the processing circuitry.

[0182] FIG. 7 is a flowchart of an example process in a network node 16 for UE indication of known or unknown transmission configuration indicator (TCI) states for artificial intelligence (Al)-based beam management. One or more blocks described herein may be performed by one or more elements of network node 16 such as by one or more of processing circuitry 36 (including the configuration unit 24), processor 38, and / or radio interface 30. Network node 16 such as via processing circuitry 36 and / or processor 38 and / or radio interface 30 is configured to receive state information indicating whether the UE is in a known or unknown transmission configuration indicator (TCI) state for a predicted and reported reference signal (Block SI 00). The process includes configuring a beam management process based at least in part on the received state information (Block SI 02).

[0183] In some embodiments, the state information is based at least in part on a comparison of a probability of predicting a strongest known receive beam to a threshold. In some embodiments, the state information is based at least in part on a speed of movement of the UE 22. In some embodiments, the state information includes a validity time duration for the known predicted receive beam. In some embodiments, the state information includes an indication of whether a subsequently measured beam has a same quasi-collocation (QCL) relation to the predicted set A transmit beam.

[0184] In some embodiments, the state information is based at least in part on a comparison of a probability of predicting a strongest known receive beam to a threshold.

[0185] In some embodiments, network node 16 receives the state information as part of at least one of an inference report, a capability report, a radio resource control (RRC) signaling, and a UE 22 assistance information (UAI) report from the UE 22, the network node 16 further configured to adapt at least one UE parameter in the beam management process based on the received state information.

[0186] In some embodiments, the state information includes a 22 prediction performance in estimating a known predicted receive beam, the network node 16 further configured to configure subsequent measurements in case the UE 22 prediction performance is below a threshold value.

[0187] In some embodiments, the state information includes a validity time duration for the known predicted receive beam.

[0188] In some embodiments, the state information includes an indication of whether a subsequently measured beam has a same quasi-collocation (QCL) relation to a predicted set A transmit beam.

[0189] In some embodiments, the network node 16 is further configured to instruct the UE (22) to not estimate the known predicted receive beam to save UE 22 computational resources.

[0190] FIG. 8 is a flowchart of an example process in a UE 22 according to some embodiments of the present disclosure. One or more blocks described herein may be performed by one or more elements of UE 22 such as by one or more of processing circuitry 50 (including the state information unit 26), processor 52, and / or radio interface 46. UE 22 such as via processing circuitry 50 and / or processor 52 and / or radio interface 46 is configured to determine (Block SI 04) whether a known transmission configuration indicator (TCI) state uses a known predicted receive beam to receive a transmit beam that is quasi-collocated (QCL) with a predicted set A transmit beam. The process also includes transmitting state information indicating support for use of the known predicted receive beam for receiving the predicted transmit beam that is QCL with the predicted set A transmit beam (Block SI 06).

[0191] In some embodiments, the state information is based at least in part on a comparison of a probability of predicting a strongest known receive beam to a threshold. In some embodiments, the state information is based at least in part on a speed of movement of the UE 22. In some embodiments, the state information includes a validity time duration for the known predicted receive beam. In some embodiments, the state information includes an indication of whether a subsequently measured beam has a same QCL relation to the predicted set A transmit beam.

[0192] FIG. 9 is a flowchart of another example process in a UE 22 according to some embodiments of the present disclosure. One or more blocks described herein may be performed by one or more elements of UE 22 such as by one or more of processing circuitry 50 (including the state information unit 26), processor 52, and / or radio interface 46. UE 22 is configured to determine (Block SI 08) whether a known transmission configuration indicator (TCI) state uses a known predicted receive beam to receive a transmit beam that is quasi-collocated (QCL) with a predicted transmit beam. The process also includes transmitting (Block SI 10) state information indicating support for use of the known predicted receive beam for receiving the predicted transmit beam that is QCL with the predicted transmit beam.

[0193] In some embodiments, the state information is based at least in part on a comparison of a probability of predicting a strongest known receive beam to a threshold.

[0194] In some embodiments, the state information is based at least in part on a speed of movement of the UE 22.

[0195] In some embodiments, the UE 22 transmits the state information as part of at least one of an inference report, a capability report, a radio resource control (RRC) signaling, and a UE 22 assistance information (UAI) report.

[0196] In some embodiments, the state information includes a validity time duration for the known predicted receive beam.

[0197] In some embodiments, the state information includes an indication of whether a subsequently measured beam has a same QCL relation to the predicted transmit beam.

[0198] Having described the general process flow of arrangements of the disclosure and having provided examples of hardware and software arrangements for implementing the processes and functions of the disclosure, the sections below provide details and examples of arrangements for UE indication of known or unknown transmission configuration indicator (TCI) states for artificial intelligence (Al)-based beam management.

[0199] One or more UE 22 functions described below may be performed by one or more of processing circuitry 50, processor 52, state information unit 26, radio interface 46, etc. One or more network node 16 functions described below may be performed by one or more of processing circuitry 36, processor 38, configuration unit 24, radio interface 30, etc.

[0200] FIG. 10 is a diagram of an example of a scenario where the UE AI / ML model predicts the CSI-RS beams 1-6. In the scenario, the CSI-RS 1,2 is QCLed with SSB-1 as part of a network node configuration. Hence, a TCI state for receiving CSI-RS beam 1 and 2 may comprise information that such beams are QCL with SSB-1 (e.g., a network node SSB beam).

[0201] Furthermore, in the scenario of FIG. 10, the UE supports 3 Rx beams. In some embodiments, a known TCI state includes when the UE 22 may for a predicted Tx beam receive such beam with a known predicted Rx beam. The known predicted Rx beam may be an optimal or quasi-optimal Rx beam, where optimal may mean the Rx beam that provides the highest signal quality when measuring the predicted Tx beam (CSI-RS beam 1-6 in the figure). Quasi-optimal may mean when the UE 22 may measure with an Rx beam that provides the highest signal quality when measuring a Tx beam that is QCLed with the predicted Tx beam (NW SSB beam 1-3 in the figure).

[0202] The referred Tx beam may include a wide SSB beam (Tx beam 1-3 FIG. 10), or a narrow CSI-RS beam (CSI-RS beam 1-6 in FIG. 10) based on how the TCI states are configured.

[0203] In FIG. 10, in a first example, when the TCI state is based on the Tx beams 1, 2, 3, for example if the UE 22 knows the Rx beam for Tx beam 1, it is said to be in known TCI state for the CSI-RS beam 1 and 2. Otherwise it is in an unknown TCI state.

[0204] In FIG. 10, in a second example, when the TCI state is based on the narrow Tx beams denoted CSI-RS 1-6, if the UE 22 for example knows only the optimal Rx beam for CSI-RS beam 1, it is said to be in known TCI state for the predicted CSI-RS beam 1, and unknown TCI state for CSI-RS 2-6. Note that the UE 22, due to its AI / ML capabilities, might only support to predict the optimal Rx beam for some of its predicted CSLRSs. UE 22 prediction ofRx beam, and i f the TCI state is known / unknown

[0205] The UE 22 may use AI / ML to train a model that learns which is the optimal predicted Rx beam to use for a certain network node Set A Tx beam. This may include a training phase where the network node transmits the beams in set A, and the beams that are QCLed with such beams. Next, the UE 22 may train one or more AI / ML models that may predict the optimal Rx beam for the set A narrow beam, or the associated QCLed beam that is indicated as part of the TCI state configuration. Note that predicting an Tx / Rx beam pair may require larger AI / ML models since the output space increases in comparison to only predicting the Tx beam. Hence, some UEs 22 might not be capable of creating such model.

[0206] During inference, the UE 22 may encounter scenarios when the Rx beam prediction is uncertain, for example, when the UE 22 is moving in certain speeds different than the speeds during training, or in new environments that are different from the environments when training was performed. In such cases, the UE 22 may indicate that the TCI state is unknown as described in subsequent sections.

[0207] Signaling state information as part of the inference report (lower layer report)

[0208] During the inference, the UE 22 is configured by the network node to report predicted beams in set A, for example by indicating one or more CRI(s) corresponding to CSLRS resources in a CSLRS Set A Resource set. Also, the UE 22 may provide the predicted RSRP(s) in this prediction report corresponding to the one or more CRI(s). In order to indicate whether the UE 22 also has a known or unknown TCI state corresponding to the reported predicted beams from set A in the inference report, the UE 22 may indicate this as part of the inference report.

[0209] In some embodiments, a simple 1 -bit indicator is included in the inference report to indicate whether the UE 22 is in known or unknown state for all of the predicted beams from set A (e.g., the predicted beams correspond to one or more CRI(s) in the inference report) included in the inference report. If the single bit indicates that the UE 22 is in known state, then it means that the TCI state(s) are known for all of the predicted beams in the inference report. If the single bit indicates that the UE 22 is in unknown state, then it means that the TCI state(s) are unknown for all of the predicted beams in the inference report.

[0210] In some embodiments, M bits are included in the inference report wherein M is the number of predicted beams from set A (i.e., the number of CRI(s) corresponding to predicted beams from set A in the inference report). In this example, the mthbit (m = 1, 2, ... , M) bit among the M bits indicate whether the UE 22 is in known or unknown state for the mthpredicted beam from set A (e.g., the predicted beam corresponding to the mthCRI in the inference report). In some embodiments, the 1 -bit indicator may be introduced:

[0211] Per-resourceSet level, e.g. the UE 22 indicates if all reported beams in the resource set have a known / unknown TCI state;

[0212] Per resource level, in case each reported resource in set A have an unknown / known state; and / or

[0213] A list of RS with known / unknown TCI state, where the list includes RSs that are not transmitted by the network node (hence only RSs that may be predicted by the network node)

[0214] The flowchart of the example of UE 22 reporting the known / unknown state(s) during inference report is outlined in FIG. 11. The figure also indicates network node actions for the beam management process given the UE report.

[0215] Signaling state information as part of a higher layer report

[0216] In some embodiments, the signaling of the UE 22 capability of estimating the best Rx beam for a certain Tx beam is indicated as part of the UAI report or RRC message. For example, the UE 22 may indicate for which of the report configurations with inference parameters it supports to predict the best Rx beam. The inference parameters may include, for example:

[0217] The network node CSI report configuration of inference related parameters; o Set A related information; o Set B related information; o Report content related information; o Time instances related information for measurements; o Time instances related information for prediction, within the prediction window; and / or o The associated ID(s), where the UE 22 assumption regarding the associated ID is that UE 22 may assume the similar properties of a DL Tx beam or beam set / list associated with the same associated ID: The AI / ML model performance related information, e.g. the performance in predicting the correct Rx beam; and / or

[0218] The AI / ML model computational related information, e.g. the number of CSI processing units required for also predicting the Rx beam NW, e.g., network node 16 actions

[0219] In case the UE 22 reports known TCI state for a predicted set A Tx beam, the network node may directly schedule the UE 22 with a data transmission on such RS, or configure a subsequent RS measurement using said TCI state. This is shown in the example of FIG. 11.

[0220] Alternative set of UE embodiments (related to the alternative set of UE embodiments in Core Essence)

[0221] In some embodiments, UE 22 indicates whether the TCI state associated with a reported Set A beam may be considered known or unknown (where UEs behavior of known and unknown TCI state during TCI state switching is defined in 3GPP TS 38.133) by UE 22 capability signaling. In a related embodiment, the support is indicated independently for each supported spatial domain beam prediction AI / ML model. In some embodiments, the support is indicated commonly across all supported spatial domain beam prediction AI / ML models.

[0222] One example of the known TCI state may be represented in the way in the below or at the least take the below conditions into account, with respect to embodiments disclosed herein:

[0223] • The TCI state switch command is received during valid inference of AI / ML mode or;

[0224] • The predicted Set A beam is the RS in target TCI state or QCLed to the target TCI state;

[0225] • The predicted Set A beam is detectable during training and inference phase, which implies the beam has been trained successfully and available in inference phase; and / or

[0226] • UE 22 indicates the state information indicating the known Rx beam for the predicted Set A beam.

[0227] In some embodiments, UE 22 indicates whether the TCI state associated with a reported Set A beam may be considered known or unknown in a beam prediction report.

[0228] In some embodiments, the beam prediction report includes a single-bit bitfield per reported Set A beam, where the single-bit bitfield may be used to indicate if the TCI state associated with the reported Set A beam may be considered known or not.

[0229] In some embodiments, the beam prediction report includes one single-bit bitfield, where the single-bit bitfield may be used to indicate if the TCI state associated with the reported Set A beam with highest predicted RSRP or highest predicted chance of being the strongest beam may be considered known or not.

[0230] In some embodiments, UE 22 may be RRC configured (e.g., in a report setting / report configuration) whether to indicate known or unknown TCI state in a beam prediction report.

[0231] In some embodiments, the RRC configuration may indicate for how many of the beams (e.g., top M beams) included in the beam prediction report the UE 22 should indicated known or unknown TCI state for.

[0232] In some embodiments, the UE 22 indicates if the UE 22 has determined a suitable UE Rx beam for the TCI state associated with a reported Set A beam. The determination of the suitable UE Rx beam may, e.g., be based on UE Rx beam sweep procedures on actual transmitted DL-RS associated with the TCI state (e.g., SSB / TRS) or the UE 22 has predicted the UE Rx beam using AI / ML models for the TCI state. This kind of information may be useful in order for the network to determine if additional P3 beam sweep procedures are required for the TCI state or not.

[0233] In some embodiments, the UE 22 indicates a validity time duration / timer during which the TCI state associated with a reported Set A beam is known. Upon expiration of the timer value, the TCI state is unknown then.

[0234] Some example embodiments may include one or more of the following:

[0235] 1. A method in a UE 22, to signal state information regarding its support for using a known predicted Rx beam for receiving a predicted set A Tx beam, a. where the state information may include information if the predicted set A Tx beam has a known or unknown TCI state in at least one of the following cases:

[0236] 1. the case where known TCI state includes if the UE 22 uses the known predicted Rx beam to receive a network node Tx beam that is QCLed with the predicted set A Tx beam

[0237] 2. the case where known TCI state includes if the UE 22 uses the known predicted Rx beam to receive the predicted set A Tx beam.

[0238] 2. Method of Example 1, where the UE 22 may indicate the state information in the inference report of the predicted set A Tx beam, wherein the state information may be based on any one of the following: a.the state information may be based on the model output, e.g., the probability of predicting the strongest known Rx beam is above a certain threshold, i.e., the known predicted Rx beam that maximizes the received signal level, b. the state information may be based on the specific set A beam, e.g., the UE 22 indicates for which beam in set A that the state is known / unknown, the network node may for example configure as part of the reportQuantity support for UE 22 to report if it is in known or unknown state for a predicted beam in set A. c. the state information may be based on UE 22 movement, for example a fastmoving UE 22 might quickly have an outdated known Rx beam. d. the state information depends on if a UE 22 has measured a beam that has the same QCL relation to the predicted set A Tx beam, e.g., a certain SSB beam. e. the state information includes whether the predicted set A Tx beam is associated with a known predicted Rx beam. f. the state information includes a validity time duration / timer for the known predicted Rx beam corresponding to the predicted set A Tx beam. Method of Example 1, where the UE 22 may indicate the state information in the UE 22 capability report, a.The state is based on whether the UE 22 has a model that may support finding the known predicted Rx beam for all scenarios, defined by the supported functionalities. Method of Example 1, where UE 22 may indicate the state information as part of one or more of the UAI, RRC, or MAC CE. Method of Example 1, where the state information is reported for a certain CSI report configuration or inference parameters, for example whether UE 22 may predict the known Rx beam for one or more of the following inference parameters, a. Set A related information b. Set B related information c. Report content related information d. Time instance related information for measurements e. Time instance related information for prediction, within the prediction window f. The associated ID(s), where the UE 22 assumption regarding the associated ID is that UE 22 may assume the similar properties of a DL Tx beam or beam set / list associated with the same associated ID. Method of any of the above Examples, where the UE 22 also indicates as part of the state information the prediction performance of estimating the known predicted Rx beam. a.For example, the UE 22 in x % of the cases finds an accurate known predicted Rx beam. Method of any of the above Examples, where the UE 22 also indicates as part of the state information the computation cost of estimating the known predicted Rx beam. Method of Example 1, where the RS may be a SSB, CSI-RS or DMRS.

[0239] Some embodiments may include one or more of the following: A method in a network node 16, to configure a beam management process based on information of whether a UE 22 is in known / unknown TCI state for a certain UE predicted and reported RS, Method of Example 9, where the network node 16 receives state information as part of the inference report, or capability, or RRC, or UAI report from the UE 22, and adapts one or more parameter in its beam management process based on the received information. Method of Example 10, where after the network node 16 receives the UE 22 inference report, the network node 16 configures subsequent measurements on the predicted set A Tx beam and / or the RS that is QCLed with the predicted set A Tx beam. Method of Example 9, where the state information includes the UE AI / ML prediction performance in estimating the known predicted Rx beam, and network node 16 then configures subsequent measurements in method 10 in case the prediction performance is below a threshold value. Method of Example 9, where the network node 16 determines state information based on its UE measurement configurations. For example, the UE 22 might already measure the beams that are QCL source for the Set A Tx beams. Any of the above Examples, where the network node 16 further instructs the UE 22 to not estimate the known predicted Rx beam to save UE computational resources 1. In this case, the network node 16 always configures subsequent measurements described in step 10.

[0240] 15. A method in a UE 22 to indicate whether the TCI state associated with a reported Set A beam may be considered known or unknown, where the indication is conveyed using one or more of the following methods:

[0241] 1. Indicated in UE capability signaling

[0242] 2. Indicated in the beam prediction report

[0243] 3. Indicated as part of one or more of the UAI, RRC, or MAC CE

[0244] 16. Method of Example 9 where the indication may be signaled independently for each supported spatial / temporal domain beam prediction AI / ML model, or commonly across all supported spatial / temporal domain beam prediction AI / ML models.

[0245] 17. Method of Example 9, where the beam prediction report includes a single-bit bitfield per reported Set A beam, where the single-bit bitfield may be used to indicate if the TCI state associated with the reported Set A beam may be considered known or unknown.

[0246] 18. Method of Example 9, where the beam prediction report includes one single-bit bitfield, where the single-bit bitfield may be used to indicate if the TCI state associate with the reported Set A beam with highest predicted RSRP or highest predicted chance of being the strongest beam may be considered known or unknown.

[0247] 19. Method of Example 9, where the UE 22 may be RRC configured (e.g. in a report setting / report configuration) whether to indicate known or unknown TCI state in a beam prediction report.

[0248] 20. Method of Example 9, where the RRC configuration may indicate for how many of the beams (e.g., top M beams) included in the beam prediction report the UE 22 should indicate known or unknown TCI state for.

[0249] 21. Method of Example 9, where the UE 22 indicates if the UE 22 has determined a suitable UE Rx beam for the TCI state associated with a reported Set A beam .

[0250] 22. Method of Example 9, where the UE 22 indicates a validity time duration / timer for the known or unknown TCI state status of the reported set A Tx beam.

[0251] As will be appreciated by one of skill in the art, the concepts described herein may be embodied as a method, data processing system, computer program product and / or computer storage media storing an executable computer program. Accordingly, the concepts described herein may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects all generally referred to herein as a “circuit” or “module.” Any process, step, action and / or functionality described herein may be performed by, and / or associated to, a corresponding module, which may be implemented in software and / or firmware and / or hardware. Furthermore, the disclosure may take the form of a computer program product on a tangible computer usable storage medium having computer program code embodied in the medium that can be executed by a computer. Any suitable tangible computer readable medium may be utilized including hard disks, CD-ROMs, electronic storage devices, optical storage devices, or magnetic storage devices.

[0252] Some embodiments are described herein with reference to flowchart illustrations and / or block diagrams of methods, systems and computer program products. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer (to thereby create a special purpose computer), special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0253] These computer program instructions may also be stored in a computer readable memory or storage medium that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instruction means which implement the function / act specified in the flowchart and / or block diagram block or blocks.

[0254] The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0255] It is to be understood that the functions / acts noted in the blocks may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality / acts involved. Although some of the diagrams include arrows on communication paths to show a primary direction of communication, it is to be understood that communication may occur in the opposite direction to the depicted arrows.

[0256] Computer program code for carrying out operations of the concepts described herein may be written in an object oriented programming language such as Python, Java® or C++. However, the computer program code for carrying out operations of the disclosure may also be written in conventional procedural programming languages, such as the "C" programming language. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer. In the latter scenario, the remote computer may be connected to the user's computer through a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0257] Many different embodiments have been disclosed herein, in connection with the above description and the drawings. It will be understood that it would be unduly repetitious and obfuscating to literally describe and illustrate every combination and subcombination of these embodiments. Accordingly, all embodiments can be combined in any way and / or combination, and the present specification, including the drawings, shall be construed to constitute a complete written description of all combinations and subcombinations of the embodiments described herein, and of the manner and process of making and using them, and shall support claims to any such combination or subcombination.

[0258] Abbreviations that may be used in the preceding description include:

[0259] Abbreviation Explanation

[0260] 3 GPP 3rd Generation Partnership Project

[0261] 5G Fifth Generation

[0262] ACK Acknowledgement

[0263] Al Artificial Intelligence

[0264] AoA Angle of Arrival

[0265] CORESET Control Resource Set

[0266] CSI Channel State Information CSI-RS CSI Reference Signal

[0267] CRI CSI-RS resource indicator

[0268] DCI Downlink Control Information

[0269] DoA Direction of Arrival

[0270] DL Downlink

[0271] DMRS Downlink Demodulation Reference Signals

[0272] FDD Frequency-Division Duplex

[0273] FR2 Frequency Range 2

[0274] HARQ Hybrid Automatic Repeat Request

[0275] ID identity gNB gNodeB

[0276] MAC Medium Access Control

[0277] MAC-CE MAC Control Element

[0278] ML Machine Learning

[0279] NR New Radio

[0280] NW Network

[0281] OFDM Orthogonal Frequency Division Multiplexing

[0282] PBCH Physical Broadcast Channel

[0283] PCI Physical Cell Identity

[0284] PDCCH Physical Downlink Control Channel

[0285] PDSCH Physical Downlink Shared Channel

[0286] PRB Physical Resource Block

[0287] QCL Quasi co-located

[0288] RB Resource Block

[0289] RRC Radio Resource Control

[0290] RSRP Reference Signal Received Power

[0291] RSRQ Reference Signal Received Quality

[0292] RS SI Received Signal Strength Indicator scs Subcarrier Spacing

[0293] SINR Signal to Interference plus Noise Ratio

[0294] SSB Synchronization Signal Block

[0295] RL Reinforcement Learning

[0296] RS Reference Signal

[0297] Rx Receiver TB Transport Block

[0298] TDD Time-Division Duplex

[0299] TCI Transmission configuration indication

[0300] TRP Transmission / Reception Point

[0301] Tx Transmitter

[0302] UE User Equipment

[0303] UL Uplink

[0304] ZP-CSI-RS Zero power CSI-RS

[0305] It will be appreciated by persons skilled in the art that the embodiments described herein are not limited to what has been particularly shown and described herein above. In addition, unless mention was made above to the contrary, it should be noted that all of the accompanying drawings are not to scale. A variety of modifications and variations are possible in light of the above teachings without departing from the scope of the following claims.

Claims

CLAIMS:

1. A method implemented in a user equipment, UE, (22) that is configured to communicate with a network node (16), the method comprising: determining (SI 08) whether a known transmission configuration indicator, TCI, state uses a known predicted receive beam to receive a transmit beam that is quasicollocated, QCL, with a predicted transmit beam; and transmitting (SI 10) state information indicating support for use of the known predicted receive beam for receiving the predicted transmit beam that is QCL with the predicted transmit beam.

2. The method of Claim 1, wherein the state information is based at least in part on a comparison of a probability of predicting a strongest known receive beam to a threshold.

3. The method of any one of Claims 1 and 2, wherein the state information is based at least in part on a speed of movement of the UE (22).

4. The method of any one of Claims 2-3, wherein the UE (22) transmits the state information as part of at least one of an inference report, a capability report, a radio resource control, RRC, signaling, and a UE (22) assistance information, UAI, report.

5. The method of any one of Claims 1-4, wherein the state information includes a validity time duration for the known predicted receive beam.

6. The method of any one of Claims 1-5, wherein the state information includes an indication of whether a subsequently measured beam has a same QCL relation to the predicted transmit beam.

7. A user equipment, UE, (22) configured to communicate with a network node (16), the UE (22) is configured to: determine whether a known transmission configuration indicator, TCI, state uses a known predicted receive beam to receive a transmit beam that is quasi-collocated, QCL, with a predicted transmit beam; andtransmit state information indicating support for use of the known predicted receive beam for receiving the predicted transmit beam that is QCL with the predicted transmit beam.

8. The UE (22) of Claim 7, wherein the state information is based at least in part on a comparison of a probability of predicting a strongest known receive beam to a threshold.

9. The UE (22) of any one of Claims 7 and 8, wherein the state information is based at least in part on a speed of movement of the UE (22).

10. The UE (22) of any one of Claims 7-9, wherein the UE (22) transmits the state information as part of at least one of an inference report, a capability report, a radio resource control, RRC, signaling, and a UE (22) assistance information, UAI, report.

11. The UE (22) of any one of Claims 7-10, wherein the state information includes a validity time duration for the known predicted receive beam.

12. The UE (22) of any one of Claims 7-11, wherein the state information includes an indication of whether a subsequently measured beam has a same QCL relation to the predicted transmit beam.

13. A method implemented in a network node (16) that is configured to communicate with a user equipment, UE, (22), the method comprising: receiving (SI 00) state information indicating whether the UE (22) is in a known or unknown transmission configuration indicator, TCI, state for a predicted and reported reference signal; and configuring (SI 02) a beam management process based at least in part on the received state information.

14. The method of Claim 13, wherein the state information is based at least in part on a comparison of a probability of predicting a strongest known receive beam to a threshold.

15. The method of any one of Claims 13 and 14, wherein the network node receives the state information as part of at least one of an inference report, a capability report, a radio resource control, RRC, signaling, and a UE (22) assistance information, UAI, report from the UE (22), the method further comprising adapting at least one parameter in the beam management process based on the received state information.

16. The method of any one of Claims 13-15, wherein the state information includes a UE (22) prediction performance in estimating a known predicted receive beam, the method further comprising configuring subsequent measurements in case the UE (22) prediction performance is below a threshold value.

17. The method of Claim 16, wherein the state information includes a validity time duration for the known predicted receive beam.

18. The method of any one of Claims 13-17, wherein the state information includes an indication of whether a subsequently measured beam has a same quasicollocation, QCL, relation to a predicted set A transmit beam.

19. The method of any one of Claims 16-18, further comprising instructing the UE (22) to not estimate the known predicted receive beam to save UE (22) computational resources.

20. A network node (16) configured to communicate with a user equipment, UE (22), the network node (16) is configured to: receive state information indicating whether the UE (22) is in a known or unknown transmission configuration indicator, TCI, state for a predicted and reported reference signal; and configure a beam management process based at least in part on the received state information.

21. The network node (16) of Claim 20, wherein the state information is based at least in part on a comparison of a probability of predicting a strongest known receive beam to a threshold.

22. The network node (16) of any one of Claims 20 and 21, wherein the network node receives the state information as part of at least one of an inference report, a capability report, a radio resource control, RRC, signaling, and a UE (22) assistance information, UAI, report from the UE (22); and the network node is further configured to adapt at least one parameter in the beam management process based on the received state information.

23. The network node (16) of any one of Claims 20-22, wherein the state information includes a UE prediction performance in estimating a known predicted receive beam; and the network node is further configured to configure subsequent measurements in case the UE prediction performance is below a threshold value.

24. The network node (16) of Claim 23, wherein the state information includes a validity time duration for the known predicted receive beam.

25. The network node (16) of any one of Claims 20-24, wherein the state information includes an indication of whether a subsequently measured beam has a same quasi-collocation, QCL, relation to a predicted set A transmit beam.

26. The network node (16) of any one of Claims 23-25, wherein the network node (16) is further configured to instruct the UE (22) to not estimate the known predicted receive beam to save UE (22) computational resources.

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