Radio network node, user equipment and method performed therein

Abstract

Embodiments herein relate to a method performed by a UE (10) for handling communication in a wireless communications network. The UE (10) transmits to a radio network node (12), a second indication indicating a performance metric of a first beam, wherein a format of the performance metric is based on a value of the5 performance metric, a number of beams reported, a beam ID, and / or relative to another beam. (Fig. 6)

Description

[0001] RADIO NETWORK NODE, USER EQUIPMENT AND METHOD PERFORMED THEREIN

[0002] TECHNICAL FIELD

[0003] Embodiments herein relate to a user equipment (UE), a radio network node and methods performed therein for communication. Furthermore, a computer program and a computer readable storage medium are also provided herein. In particular, embodiments herein relate to beam handling in a wireless communications network.

[0004] BACKGROUND

[0005] In a typical wireless communications network, UEs, also known as wireless communication devices, mobile stations, stations (STA) and / or wireless devices, communicate via for example a Radio Access Network (RAN) with one or more core networks (CN). The RAN covers a geographical area which is divided into service areas or cell areas, with each service area or cell area being served by radio network node such as an access node e.g. a Wi-Fi access point or a radio base station (RBS), which in some networks may also be called, for example, a NodeB, a gNodeB, or an eNodeB. The service area or cell area is a geographical area where radio coverage is provided by the radio network node. The radio network node operates on radio frequencies to communicate over an air interface with the UEs within range of the radio network node. The radio network node communicates over a downlink (DL) to the UE and the UE communicates over an uplink (UL) to the radio network node.

[0006] A Universal Mobile Telecommunications System (UMTS) is a third-generation telecommunications network, which evolved from the second generation (2G) Global System for Mobile Communications (GSM). The UMTS terrestrial radio access network (UTRAN) is essentially a RAN using wideband code division multiple access (WCDMA) and / or High-Speed Packet Access (HSPA) for communication with user equipment. In a forum known as the Third Generation Partnership Project (3GPP), telecommunications suppliers propose and agree upon standards for present and future generation networks and UTRAN specifically and investigate enhanced data rate and radio capacity. In some RANs, e.g. as in UMTS, several radio network nodes may be connected, e.g., by landlines or microwave, to a controller node, such as a radio network controller (RNC) or a base station controller (BSC), which supervises and coordinates various activities of the plural radio network nodes connected thereto. The RNCs are typically connected to one or more core networks.

[0007] Specifications for the Evolved Packet System (EPS) have been completed within the 3GPP and this work continues in the coming 3GPP releases, such as 5G, for example New Radio (NR), and beyond networks. The EPS comprises the Evolved Universal Terrestrial Radio Access Network (E-UTRAN), also known as the Long-Term Evolution (LTE) radio access network, and the Evolved Packet Core (EPC), also known as System Architecture Evolution (SAE) core network. E-UTRAN / LTE is a 3GPP radio access technology wherein the radio network nodes are directly connected to the EPC core network. As such, the Radio Access Network (RAN) of an EPS has an essentially “flat” architecture comprising radio network nodes connected directly to one or more core networks.

[0008] With the 5G technologies such as NR, focus is on a set of features such as the use of very many transmit- and receive-antenna elements that make it possible to utilize beamforming, such as transmit-side and receive-side beamforming. Transmit-side beamforming means that the transmitter can amplify the transmitted signals in a selected direction or directions, while suppressing the transmitted signals in other directions. Similarly, on the receive-side, a receiver can amplify signals from a selected direction or directions, while suppressing unwanted signals from other directions.

[0009] Beam management procedure.

[0010] In high frequency range such as Frequency Range two (FR2), multiple radio frequency (RF) beams may be used to transmit and receive signals at a gNB and a UE. For each DL beam from a gNB, there is typically an associated best UE reception (Rx) beam for receiving signals from the DL beam. The DL beam and the associated UE Rx beam form a beam pair. The beam pair can be identified through a so-called beam management process in NR.

[0011] 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 can be a Synchronization Signal (SS) and Physical Broadcast Channel (PBCH) block (SSB) or a Channel State Information RS (CSI-RS). By measuring all the DL RSs, the UE can determine and report to the gNB the best DL beam to use for DL transmissions. The gNB can then transmit a burst of DL-RS in the reported best DL beam to let the UE evaluate candidate UE RX beams.

[0012] 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 gNB transmit (Tx) beam covering the whole angular sector

[0013] P-2: Purpose is to refine the gNB TX beam by doing a new beam search around the coarse direction found in P-1.

[0014] P-3: Used for UE that has analog beamforming to let them find a suitable UE RX

[0015] 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 synchronization signal block (SSB). The UE then reports the N best beams to the gNB and their corresponding Reference Signal Received Power (RSRP) values.

[0016] P-2 is expected to use aperiodic / or semi-persistent CSI-RS transmitted in narrow beams around the coarse direction found in P-1.

[0017] P-3 is expected to use aperiodic or semi-persistent CSI-RSs repeatedly transmitted in one narrow gNB 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 Multiplexing (OFDM) symbols, a maximum of four UE RX beams can be evaluated during each SSB burst transmission. One benefit of using SSB instead of CSI-RS is that no extra overhead of CSI-RS transmission is needed.

[0018] Reference signal configurations for different types of reference signals:

[0019] A CSI-RS is transmitted over each 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 can 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 filed 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.

[0022] • 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.

[0023] • Aperiodic CSI-RS: This is a one-shot CSI-RS transmission that can happen in any slot. Here, one-shot means that CSI-RS transmission only happens once per trigger. The CSI-RS resources, i.e. , the Resource Element (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 physical downlink control channel (PDCCH) using the CSI request field in UL downlink control information (DCI), in the same DCI where the UL resources for the measurement report are scheduled. Multiple aperiodic CSI-RS resources can be included in a CSI-RS resource set and the triggering of aperiodic CSI-RS is on a resource set basis.

[0024] In NR, an SSB consists of a pair of synchronization signals (SS), 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 Resource Blocks (RB), in the frequency domain.

[0025] To support beamforming and beam-sweeping for SSB transmission, in NR, a cell can 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, such as 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 broadcast periodically from each cell. The periodicity of the half frames with SS / PBCH blocks is referred to as SSB periodicity, which is indicated by System Information Block one (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 depend 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-1. 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 can 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. Measurement resource configurations.

[0027] In NR, a UE can be configured with N>1 CSI reporting settings, i.e. , CSI- ReportConfig, M>1 resource settings, i.e., CSI-ResourceConfig, where each CSI reporting setting is linked to one or more resource settings 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.

[0028] The measurement resource configurations for beam management are provided to the UE by RRC Information Elements (IE) CSI-ResourceConfigs. One CSI- ResourceConfig contains several Non-Zero-Power (NZP)-CSI-RS-ResourceSets and / or CSI-SSB-ResourceSets.

[0029] A UE can be configured to perform measurements on CSI-RSs. Here the RRC 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 REs, the number of antenna ports, time-domain behavior, etc. Up to 64 CSI-RS resources can be grouped to a NZP-CSI-RS- ResourceSet. A UE can 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.

[0030] 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.

[0031] Periodic and semi-persistent Resource Settings can only comprise a single resource set, i.e., S=1 , 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.

[0032] Three types of CSI reporting are supported in NR as follows:

[0033] • 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

[0034] • 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 the UE may be needed to allow the UE to begin semi-persistent CSI reporting. A dynamic trigger from network node to the UE may be needed to request the UE to stop the semi-persistent CSI reporting.

[0035] • Aperiodic CSI Reporting on PUSCH: This type of CSI reporting involves a singleshot, i.e. , one time, CSI report by a UE which is dynamically triggered by the network node using Donwlink Control Information (DCI). Some of the parameters related to the configuration of the aperiodic CSI report are semi-statically configured by RRC but the triggering is dynamic.

[0036] 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: reportConfigType

[0037] 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. reportQuantity

[0038] Defines the reported CSI parameter(s), i.e., the CSI content, such as Precoding Matrix Indicator (PMI), Channel Quality Indicator (CQI), Rank Indicator (Rl), Layer Indicator (LI), CSI-RS resource index (CRI) and L1-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 could be said to correspond to a certain CSI mode. codebookConfig

[0039] Defines the codebook used for PMI reporting, along with possible codebook subset restriction (CBSR). Two “Types” of PMI codebooks are defined in NR, Type I CSI and Type II CSI, each codebook type further has two variants each. reportFrequencyConfiguration

[0040] 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

[0041] Measurement restriction in time domain (ON / OFF) for channel and interference respectively For beam management, a UE can be configured to report L1-RSRP for up to four different CSI-RS / SSB resource indicators. The reported RSRP value corresponding to the first (best) CSI-RS resource indicator (CRI) and / or SS / PBCH Block Resource Indicator (SSBRI) requires 7 bits, using absolute values, while the others require 4 bits using encoding relative to the first. In NR release 16, the report of L1-SINR for beam management has already been supported.

[0042] SUMMARY

[0043] As part of developing embodiments herein one or more problems were first identified.

[0044] During the 3GPP meeting RAN1#109-e it was agreed to study Artificial Intelligence (Al) and / or Machine Learning (ML) based spatial beam prediction for a Set A of beams based on measurement results of Set B of beams. The Set B of beams could either be a subset of the Set A of beams, or the Set A of beams could consist of different beams compared to the Set B of beams. For example, the Set A may consist of narrow beams and Set B may consist of wide beams. The spatial beam prediction could either be made at the network (NW) side or at the UE side.

[0045] During the 3GPP meeting RAN1#109-e it was also agreed to study AI / ML based temporal beam prediction for a Set A of beams based on measurement results of Set B of beams, where the Set A of beams and Set B of beams can be the same set of beams or different set of beams. For AI / ML based temporal beam prediction, it was also agreed that the measurement results of K (K>=1) latest measurement instances during a time window T1 of the Set B beams are used for AI / ML model input. Furthermore, it was agreed that one or more beams from the Set A beams will be used as AI / ML model output, where the AI / ML model output should be F predictions for F future time instances, where all F future time instances are located within a time window T2.

[0046] It is noted that as beam is something that is formed on the NW side the UE can only measure the result of this. This can for example be that the narrow beams are measured by CSI-RS resources and the wide beams are measured by SSBs at the UE side. This would be how the UE could see the beams.

[0047] Set B is different from Set A:

[0048] Fig. 2 illustrates a schematic example of the Set A of beams and the Set B of beams. The top illustration shows all the narrow gNB beams, which constitutes the Set A of beams, and the lower illustrations show all the wide gNB beams, which constitutes the Set B of beams. It is thus shown a schematic example of Set A and Set B of beams, where Set B is different from Set A.

[0049] Set B is a subset of Set A:

[0050] Fig. 3 illustrates another example of the Set A of beams and the Set B of beams, wherein Set A contains narrow gNB beams and Set B is subset of Set A containing some narrow beams from the gNB, marked as grey beams. Fig.3 shows a schematic example of Set A and Set B of beams, where Set B is a subset of Set A of beams. Both Set B and Set A of beams are the narrow gNB beams.

[0051] Based on model output, e.g., probability of each beam in Set A to be the Top-1 beam, predicted L1-RSRPs, Top-1 / N beam(s) among Set A of beams can be predicted and / or potentially with predicted L1-RSRPs, depending on the labeling. In the evaluation, for Beam Management (BM)-Case 1 , the measurements of Set B, otherwise stated, are used as model input to predict Top-1 / N beams from Set A, and for BM-Case2, the measurements from historic time instance(s) are used as model input for temporal DL beam prediction of beams from Set A.

[0052] For both BM-Case1 and BM-Case2, the UE may report the prediction result to NW based on the output of a UE-side model, or NW can predict the Top-1 / N beam(s) based on the reported measurements of Set B for a NW-side model.

[0053] Fig. 4 shows an example of the inference procedure for beam management for probability estimation of an AI / ML model.

[0054] In the field of AI / ML, a classifier model can provide an estimate of the probability of the class label, such as the best beam probability. Examples of how such probability can be estimated depend on the selected AI / ML model, for example:

[0055] Logistic Regression: This model directly outputs probabilities. The output is the probability that a given input point belongs to a certain class.

[0056] Decision Trees and Random Forests: These may estimate probabilities by the proportion of training samples of each class in a leaf node.

[0057] Neural Networks: The output layer often uses a SoftMax function for multiclass classification, which gives the probability of each class.

[0058] In practice, it is challenging to ensure that the predicted probabilities correspond to the true likelihood of an event. An AI / ML model is considered well-calibrated if the predicted probabilities of outcomes reflect their true probabilities. However, in many cases, AI / ML models produce raw probabilities that are not well-calibrated. This means that the confidence of the AI / ML model in its predictions doesn't always align with the actual likelihood of those predictions being correct. Some reasons that can imply poor calibration are:

[0059] Overfitting: An AI / ML model that overfits the training data may appear to be very confident, e.g., predicting probabilities close to 0 or 1 , but its predictions may not generalize well to unseen data.

[0060] Model Complexity: Complex AI / ML models, like deep neural networks, can be powerful in terms of predictive performance but often struggle with calibration due to their layered and non-linear structures.

[0061] Data Imbalance: In cases where classes are imbalanced, AI / ML models may tend to favor the majority class and produce skewed probability estimates.

[0062] One example on how different AI / ML models can provide different type of probability estimates are shown in Fig. 5. Fig. 5 shows examples of probability calibration curve and estimated probabilities histogram for some example models. The figure shows how the probability does not exactly match the perfect likelihood of an event.

[0063] During inference of UE-sided beam prediction, spatial and / or time domain beam prediction, the UE might be configured to report beam ID(s) and associated performance metric per reported beam to the network. One example of such performance or confidence metric is the probability that a reported beam is the strongest beam, i.e. , Top-1 beam in terms of signal quality. How to report such probability in an overhead efficient way is an open issue.

[0064] The object of embodiments herein is to provide a mechanism handling beams in a resource efficient manner.

[0065] According to an aspect of embodiments herein the object is achieved by providing a method performed by a UE for handling communication in a wireless communications network. The UE transmits to a radio network node, a second indication indicating a performance metric of a first beam, wherein a format of the performance metric is based on a value of the performance metric, a number of beams reported, a beam ID and / or relative to another beam. For example, the UE may transmit to the radio network node, a first indication of the first beam and the second indication, wherein the second indication indicates the performance metric of the first beam, such as a probability that the first beam is a best beam out of a number of beams in terms of signal strength or quality, and wherein the performance metric, such as the probability, is defined with a granularity, with an interval or range, and / or relative to another performance metric, and wherein the granularity, the interval or range, and / or the performance metric is based on a value of the performance metric, a number of beams reported, beam ID and / or another beam.

[0066] According to another aspect of embodiments herein the object is achieved by providing a method performed by a radio network node for handling communication in a wireless communications network. The radio network node receives from a UE, a second indication indicating a performance metric of a first beam, wherein a format of the performance metric is based on a value of the performance metric, a number of beams reported, a beam ID and / or relative to another beam. For example, the radio network node may receive a first indication of the first beam and the second indication, wherein the second indication indicates the performance metric of the first beam, such as a probability that the first beam is a best beam out of a number of beams in terms of signal strength or quality, and wherein the performance metric, such as the probability, is defined with a granularity, with an interval or range, and / or relative to another performance metric, and wherein the granularity, the interval or range, and / or the performance metric is based on a value of the performance metric, a number of beams reported, beam ID and / or another beam.

[0067] It is furthermore provided herein a computer program product comprising instructions, which, when executed on at least one processor, cause the at least one processor to carry out the methods herein, as performed by the UE and the radio network node, respectively. It is additionally provided herein a computer-readable storage medium, having stored thereon a computer program product comprising instructions which, when executed on at least one processor, cause the at least one processor to carry out the methods herein, as performed by the UE and the radio network node, respectively.

[0068] The object is further achieved by providing a UE and a radio network node configured to perform the methods herein, respectively.

[0069] Thus, the object is achieved by providing a UE for handling communication in a wireless communications network. The UE is configured to transmit to a radio network node, a second indication indicating a performance metric of a first beam, wherein a format of the performance metric is based on a value of the performance metric, a number of beams reported, a beam ID and / or relative to another beam.

[0070] According to another aspect the object is achieved by providing a radio network node for handling communication in a wireless communications network. The radio network node is configured to receive from a UE, a second indication indicating a performance metric of a first beam, wherein a format of the performance metric is based on a value of the performance metric, a number of beams reported, a beam ID and / or relative to another beam.

[0071] It is herein disclosed ways on how to report performance metrics such as probability that a reported beam, i.e. , the first beam, is the best beam, in an overhead efficient way by using, e.g., relative values, and / or reconfigurable granularity and ranges of probability.

[0072] Thus, embodiments herein provide a beam reporting overhead during inference of UE-sided beam prediction, such as spatial and / or time domain beam prediction, that can be reduced when the UE reports the performance metric such as probability that a reported beam is the best beam. Thus, embodiments herein handle beams in a resource efficient manner.

[0073] BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Embodiments will now be described in more detail in relation to the enclosed drawings, in which:

[0075] Fig. 1 shows an example of a beam management procedure according to prior art;

[0076] Fig. 2 shows a schematic example of Set A and Set B of beams;

[0077] Fig. 3 shows a schematic example of Set A and Set B of beams;

[0078] Fig. 4 shows an example of the inference procedure for beam management;

[0079] Fig. 5 shows an example of probability calibration curves and estimated probabilities histogram;

[0080] Fig. 6 is a schematic overview depicting a wireless communications network according to embodiments herein;

[0081] Fig. 7a shows a combined flowchart and signalling scheme according to some embodiments herein;

[0082] Fig. 7b is a schematic flowchart depicting a method performed by a UE according to embodiments herein;

[0083] Fig. 7c is a schematic flowchart depicting a method performed by a radio network node according to embodiments herein;

[0084] Fig. 8 is a schematic example of CSI fields for a beam prediction report according to some embodiments herein;

[0085] Fig. 9a is a schematic illustration depicting probability index according to some embodiments herein;

[0086] Fig. 9b is a schematic illustration depicting probability index according to some embodiments herein; Fig. 9c is a schematic illustration depicting probability index according to some embodiments herein;

[0087] Fig. 9d is a schematic illustration depicting probability index according to some embodiments herein;

[0088] Fig. 10 is a schematic illustration depicting an example for reporting the probability according to some embodiments herein;

[0089] Fig. 11 is a schematic illustration depicting an example of grouping of beams according to some embodiments herein;

[0090] Fig. 12 is a block diagram depicting a UE according to embodiments herein;

[0091] Fig. 13 is a block diagram depicting a radio network node according to embodiments herein;

[0092] Fig. 14 shows an example of a communication system QQ100 in accordance with some embodiments;

[0093] Fig. 15 shows a UE QQ200 in accordance with some embodiments;

[0094] Fig. 16 shows a network node QQ300 in accordance with some embodiments;

[0095] Fig. 17 is a block diagram of a host QQ400, which may be an embodiment of the host QQ116 of Fig. 14, in accordance with various aspects described herein;

[0096] Fig. 18 is a block diagram illustrating a virtualization environment QQ500 in which functions implemented by some embodiments may be virtualized; and

[0097] Fig. 19 shows a communication diagram of a host QQ602 communicating via a network node QQ604 with a UE QQ606 over a partially wireless connection in accordance with some embodiments.

[0098] DETAILED DESCRIPTION

[0099] Embodiments herein relate to communication networks in general. Fig. 6 is a schematic overview depicting a wireless communications network 1. The wireless communications network 1 comprises one or more RANs and one or more CNs. The wireless communications network 1 may use a number of different technologies, such as Wi-Fi, Long Term Evolution (LTE), LTE-Advanced, NR, Wideband Code Division Multiple Access (WCDMA), Global System for Mobile communications / Enhanced Data rate for GSM Evolution (GSM / EDGE), Worldwide Interoperability for Microwave Access (WiMax), or Ultra Mobile Broadband (UMB), just to mention a few possible implementations.

[0100] In the wireless communications network 1, wireless devices e.g. a user equipment (UE) 10 such as an loT device, an A-loT device, a ZE device, a mobile station, a non-access point (non-AP) STA, a STA, a wireless device and / or a wireless terminal, communicate via one or more Access Networks (AN), e.g. a RAN, to one or more core networks (CN). It should be understood by those skilled in the art that “UE” is a non-limiting term which means any terminal, wireless communication terminal, internet of things (loT) capable device, Machine Type Communication (MTC) device, Device to Device (D2D) terminal, or node e.g. smart phone, laptop, mobile phone, sensor, relay, mobile tablets or even a base station communicating within a cell.

[0101] The wireless communications network 1 comprises a radio network node 12 providing radio coverage over a geographical area, e.g. a first service area, of a first radio access technology (RAT), such as NR, LTE, UMTS, Wi-Fi or similar. The radio network node 12 may be a radio access network node such as radio network controller or an access point such as a wireless local area network (WLAN) access point or an Access Point Station (AP ST A), an access controller, a base station, e.g. a radio base station such as a NodeB, an evolved Node B (eNB, eNodeB), a base transceiver station, Access Point Base Station, base station router, a transmission arrangement of a radio base station, a stand-alone access point or any other network unit capable of serving a UE within the service area served by the radio network node 12 depending e.g. on the first radio access technology and terminology used.

[0102] According to embodiments herein the UE 10 reports a second indication to the radio network node 12, wherein the second indication indicates a performance metric of a first beam. A format of the performance metric is based on a value of the performance metric, a number of beams reported, a beam ID and / or relative to another beam. Thereby, the report may be compressed and lead to a reporting that is resource efficient.

[0103] Please note that some embodiments will correspond to a fixed payload size of the report, i.e., a same payload regardless of what actual values that are reported in the report, and other embodiments may result in varying payload size of the report, i.e., the size of the payload may differ depending on the actual values that are reported in the report. In case of varying payload size, typically a two-part report may be required where a first part indicates the size of a second report, while for a fixed size report, a single part may typically be used.

[0104] The format of the performance metric, also referred to as a probability format, selected as described in subsequent section may be based on how accurate a UE-sided AI / ML model can estimate the probability of a best beam. That is, how well does the estimated probability match the true likelihood of a beam being a best beam in terms of signal strength or quality. The problem of probability calibration implies that there might be no benefit of a UE using a finer granularity of %1 due to this issue. Please note that % is used as measure herein, however, fractional number can be used instead, such that e.g. 1% means 0.01, and 100% means 1, etc. In addition, please note that in most embodiments described below, an integer is used as a reported value, however, a range may be used instead. For example, if 99% is exemplified, this may be changed to 99%- 100%, or 98.5-99.5% or similar. Furthermore a 1% granularity may be exemplified for the reported performance metric, however, other granularities may also be possible in a similar way.

[0105] • The concept “network” may refer to one of a generic network node, a gNB (or the corresponding node in a 6G network), a base station, a unit within the base station to handle at least some ML operation, a relay node, a core network node, a core network node that handle at least some ML operations, or a device supporting device to device (D2D) communication.

[0106] • An AI / ML model being a computational model may refer to an ML-based model, a configuration of an ML-based model, a non-ML-based functionality, or a configuration of a non-ML-based functionality.

[0107] • The terms “ML-model” and “Al-model” are interchangeable. An AI / ML model can be defined as a functionality or be part of a functionality that is deployed / implemented in a first node. This first node can receive a message from a second node indicating that the functionality is not performing correctly. Further, an AI / ML model can be defined as a feature or part of a feature that is implemented / supported in a first node. This first node can indicate the feature version to a second node. If the ML-model is updated, the feature version maybe changed by the first node.

[0108] Fig. 7a is a combined flowchart and signalling scheme according to some embodiments herein.

[0109] Action 701. The radio network node 12 may determine a reporting configuration for the UE 10, wherein the reporting configuration defines a format for reporting the performance metric such as probability.

[0110] Action 702. The radio network node 12 may transmit the configuration indication to the UE 10. The configuration indication may indicate the determined reporting configuration such as use of indices, granularity of probability, and / or interval / range of values.

[0111] Action 703. The UE 10 may obtain a first indication related to signal strength or quality of a first beam relative other beams. The UE 10 may measure on a set B of beams and then using a computational model, such as an AI / ML model, obtain a set A of beams and related signal strength or quality. As an example, the UE 10 may obtain that a first beam is a best beam out of a number of beams in terms of signal strength or quality.

[0112] Action 704. Furthermore, the UE 10 may also obtain the second indication indicating the performance metric of the first beam, wherein the format of the performance metric is based on the value of the performance metric, the number of beams reported, the beam ID and / or relative to another beam. The performance metric may be related to a first probability that the first indication is correct.

[0113] Action 705. The UE 10 transmits to the radio network node 12, the second indication. The UE 10 may further transmit the first indication, such as an index, a beam ID, an order of second indications, to indicate a certain beam related to the second indication.

[0114] Action 706. The radio network node 12 may then use the second indication when performing a network operation such as transmission, allocate resources, mobility and / or similar. Thus, the radio network node may perform the network operation taking into account the reported probability of the reported beam really being the best beam.

[0115] Example embodiments of a method performed by the UE 10 for handling communication in the wireless communications network 1 will now be described with reference to a flowchart depicted in Fig. 7b. The actions do not have to be taken in the order stated below but may be taken in any suitable order.

[0116] Action 711. The UE 10 may receive from the radio network node 12 a configuration indication. The configuration indication may indicate the determined reporting configuration such as use of indices, granularity of probability, and / or interval / range of values.

[0117] Action 712. The UE 10 may obtain the first indication related to signal strength or quality of the first beam relative other beams. The UE 10 may measure on a set B of beams and may use a computational model such as an AI / ML model to obtain a set A of beams and related signal strength or quality. As an example, the UE 10 may obtain that the first beam is a best beam out of a number of beams in terms of signal strength or quality.

[0118] Action 713. Furthermore, the UE 10 may also obtain the second indication indicating the performance metric of the first beam, wherein the format of the performance metric is based on the value of the performance metric, the number of beams reported, the beam ID and / or relative to another beam. The second indication may be related to a first probability that the first indication is correct. The computational model or another computational model such as an AI / ML model may be used to obtain the performance metric.

[0119] Action 714. The UE 10 transmits to the radio network node 12, the second indication indicating the performance metric of the first beam. The format of the performance metric is based on the value of the performance metric, the number of beams reported, the beam ID and / or relative the other beam.

[0120] The format of the performance metric may be defined with the granularity such a level of detailed probability e.g., whole percentage, part of percentage, tens of percentage or similar, with the interval or range, and / or relative to another performance metric. The granularity, the interval or range, and / or the performance metric may be based on the value of the performance metric, the number of beams reported, the beam ID and / or the other beam

[0121] The performance metric may comprise a probability that the first beam is a best beam out of a number of beams in terms of signal strength or quality.

[0122] The UE 10 may further transmit to the radio network node 12 the first indication indicating identity of the first beam, such as beam index, or order of beams.

[0123] Example embodiments of a method performed by the radio network node for handling communication in the wireless communications network will now be described with reference to a flowchart depicted in Fig. 7c. The actions do not have to be taken in the order stated below but may be taken in any suitable order.

[0124] Action 721. The radio network node 12 may determine the reporting configuration for the UE 10, wherein the reporting configuration defines a format for reporting the performance metric such as probability.

[0125] Action 722. The radio network node 12 may transmit configuration indication to the UE 10. The configuration indication may indicate the determined reporting configuration such as use of indices, granularity of probability, and / or interval / range of values. The radio network node 12 may further transmit the computational model such as Al model to the UE 10-

[0126] Action 723. The radio network node 12 receives from the UE 10, the second indication indicating the performance metric of the first beam. The format of the performance metric is based on the value of the performance metric, the number of beams reported, the beam ID and / or relative the other beam. The format of the performance metric may be defined with the granularity, with the interval or range, and / or relative to another performance metric. The granularity, the interval or range, and / or the performance metric may be based on the value of the performance metric, the number of beams reported, the beam ID and / or the other beam The performance metric may comprise a probability that the first beam is a best beam out of a number of beams in terms of signal strength or quality.

[0127] The radio network node 12 may further receive from the UE 10, the first indication indicating identity of the first beam.

[0128] Action 724. The radio network node 12 may then use the second indication when performing a network operation such as transmission, allocate resources, mobility and / or similar.

[0129] The format selected for reporting the second indication, such as the probability, could, on a high-level, be based on:

[0130] Standard defined:

[0131] - The format is pre-configured in the standard, e.g. the granularity, i.e. , step size of the reported performance metric, is 1% between 100->90% and 5% otherwise, i.e., between 90% and e.g. 0%.

[0132] Moreover, there will be proper testing procedures to ensure that the UE reporting will fulfil the requirements.

[0133] NW-configured:

[0134] In some embodiments, the NW configures the reporting format based on previous UE model performance monitoring procedures or historic information of the performance for a certain reporting format. The NW can also select a format based on the NW-load, for example use more low overhead formats in case of a high-load. The configuration could also be based on UE service requirements, enabling more reporting in case the UE have high service requirements, e.g., need to find the best beam.

[0135] UE-assisted:

[0136] In some embodiments, the UE 10 reports information of its recommended format based on its AI / ML model probability calibration information. Or reporting its the probability calibration plot above from its training, or the histogram of the probabilities from its training. The UE 10 may furthermore report its recommended granularity for each beam ID, or group of beam IDs. Note that the probability calibration is typically better for frequent classes / best- beams than infrequent classes. Based on the UE recommendation or other information, the NW selects and configures a reporting format.

[0137] UE-based:

[0138] In some embodiments, the UE 10 autonomously selects the reporting format based on its AI / ML model information. The UE 10 may for example in a two- part CSI report include the selected format in the first part.

[0139] Beam probability reporting embodiments:

[0140] In one embodiment the second indication is reported in a bitfield, also referred to as probability bitfield, used per reported beam in a beam prediction report, where the bitfield is used to indicate the probability that the associated first beam is the best beam relative to other beams. One example of how the reporting structure might look is illustrated in Fig. 8. Fig. 8 shows an example of CSI fields for a beam prediction report where 4 predicted beams are reported together with the probability that each of the reported beams is the best beam.

[0141] The probability bitfield may indicate a value that corresponds to a range of probabilities instead of an absolute value. The UE 10 reports index value X corresponding to range of probabilities between {Y, Z}. one example of this, a 2-bit width field is needed to index four probability ranges {P>90, 60<P<90, 40<P<60, P<40}. The probability ranges and the corresponding indices can be configured by the NW or indicated by the specification.

[0142] The probability bitfield for a certain beam being the best beam corresponds to either a range of probabilities or an absolute value depending on the actual probability value to be reported. For instance, for probabilities that are higher than 90%, the UE 10 reports the actual probability value. For probabilities lower than 90%, the UE 10 reports an index corresponding to the probability range closest to the actual probability value, as shown in Fig. 9a.

[0143] The reported beams may consist of both best beams, i.e. , highest signal strength / quality, and weakest beams. For the top-M best beam, the probability bitfield for a certain beam being the best beam corresponds to either a range of probabilities or an absolute value depending on the actual probability value to be reported. For the Top N weakest beams, the probability bitfield for a certain beam being the best beam is normally very low, i.e., lower than 1%. As such, a range of probability values might be more useful. For example, for weakest beams probabilities that are lower than 1%, the UE 10 reports the index corresponding to the probability range closest to the actual probability value, as shown in Fig. 9b.

[0144] The same probability index mapping may be used for all reported beams in one beam prediction report. This means the bit width, i.e. , number of bits, of the probability bitfield(s) may be the same for all the reported beams.

[0145] The granularity and range of the probability of each bitfield in the report may be the same. The range for a probability may be from e.g. 100% to 0 %, with 1% granularity. This would require that each bitfield is 7 bits, i.e., ceil(log2(100)). To save some overhead, the granularity may vary over the scale, such that the granularity is smaller the closer you are to 100%. One example of this is to use e.g. 1% granularity between 90% and 100% probability that the beam is the best beam, and then use 5% granularity for the probabilities between 0% and 90%, as shown in Fig. 9c. This would give a total number of candidate probabilities smaller than 32, which means that the number of bits per bitfield can be reduced from 7 bits to 5 bits. Several different granularities may be used, and the granularity may gradually be increasing the lower the probabilities are. So, for example, between 90% and 100% the granularity is 1%, between 80%and 90% the granularity is 2%, and between 0 and 80% the granularity is 5%, as shown in Fig. 9d. One reason for having larger granularity for lower probabilities, is that the lower probability that predicted beam is the best beam, the less important it is to give the exact number, since the network anyway most likely need to perform an additional beam sweep to validate if the beam is good or not, while, if the UE 10 is e.g. 99% sure that a predicted beam is the best beam, the radio network node 12 may decide to use that beam directly, without additional beam measurements to verify that the beam actually is good.

[0146] The minimum probability, maximum probability and / or granularity for each bitfield may be RRC configured. For example, for a first reported beam, which is the beam that is most likely to be the best beam, the probability granularity might be smaller compared to the remaining beams, where the exact probability might be less important compared to for the best beam. In addition, the probability that the first beam is lower than 20% is maybe not so likely, hence the minimum probability that the UE 10 can report for the first beam might be configurable to be 20%, or another number, or large, hence, skipping the possibility for the UE 10 to report that the first beam has a probability that it is best of e.g. 10%. Even if the minimum probability to indicate in a beam prediction report of a reported beam may be X%, there may be one additional codepoint of the bitfield that indicates that the probability of the reported beam is below X%, i.e., we can indicate that the probability of the report beam is below X%, but not indicate a specific value below X%.

[0147] The Xth beam in the beam report may have a maximum probability to be reported as the best beam equal to or less than 100 / X%. That is, for the first beam, the maximum probability that can be reported is 100%, for the second beam, the maximum probability that can be reported is 50%, for the third beam, the maximum probability that can be reported is 33.33%, which might be rounded to 33%, and for the fourth beam, the maximum probability that can be reported is 25%. In this way, the overhead of the second indication of the probability that a certain beam is the best beam can be reduced.

[0148] The number of beams the UE 10 may report may be fixed according to the specification or according to the configuration by the network. For example, the number of beams the UE 10 may report might always be four, corresponding to the four beams with the highest probability to be the best beam. In a related embodiment, the number of beams the UE 10 is capable of reporting is indicated by the UE 10 in a UE capability signaling.

[0149] In one embodiment, the candidate probabilities for respective beams are according to the following rule:

[0150] 100 / X : -Y : M

[0151] Where X is the beam index, i.e., 1,2,3 or 4 in this example, Y is the granularity, and M is the minimum probability that can be reported for that beam. In one example, the candidate probabilities might look like this:

[0152] • Probabilities for beaml: 100% : -1% : 30%

[0153] • Probabilities for beam2: 50% : -1% : 10%

[0154] • Probabilities for beam3: 33% : -1% : 5%

[0155] • Probabilities for beam4: 25% : -1% : 1%

[0156] In the examples above the granularity is the same for all the reported beams, i.e., Y=1%, however, this might be individually configured per beam, for example such that the granularity is smaller for the first beam compared to the last beam. For example, using a 2-bit representing a codepoint list which could be configured as [-1, -3, -5, -10]%, where codepoint 0, 1, 2, 3 corresponds to -1%, -3%, -5%, and -10%, respectively. The granularity could be configured differently based on the selected codepoint.

[0157] In the examples above,

[0158] • For reporting the probability for beaml with the granularity Y=1% and the probability threshold M=30, it needs maximum 7 bits, i.e., ceil(log2(100-30)). • For reporting the probability for beam2 with the granularity Y=1% and the probability threshold M=10, it needs maximum 6 bits, i.e., ceil(log2(50-10)).

[0159] • For reporting the probability for beam3 with the granularity Y=1% and the probability threshold M=5, it needs maximum 5 bits, i.e., ceil(log2(33-5)).

[0160] • For reporting the probability for beam4 with the granularity Y=1% and the probability threshold M=1 , it needs maximum 5 bits, i.e., ceil(log2(25-1)).

[0161] The candidate probabilities for the beams except the first beam may be relative to the actual probability reported for the first beam. For example, assume that the UE 10 may report two beams, and the first beam has a probability X1 that it is the best beam. Then the maximum probability that the second beam is the best beam is min(X1 , 100-X1), hence in one embodiment the maximum probability that the second beam can indicate starts at min(X1, 100-X1), where X1 is the probability that the first beam is the best beam. In a related embodiment, assume that the UE 10 may report more than two beams, and the first beam has a probability X1 that it is the best beam. Then the maximum probability that the additional beam (second and more) is the best beam is min(X1, 100-X1), hence in one embodiment the maximum probability that the additional beam can indicate starts at min(X1 , 100-X1), where X1 is the probability that the first beam is the best beam.

[0162] In a similar way, in one embodiment, the third best beam cannot report a probability larger than min(X2, 100 - (X1+X2)), where X1 is the probability that the first beam is best and X2 is the probability that the second beam is best, assuming that the UE 10 may report the beams in order according to the probability to be best beam.

[0163] In a similar way, in one embodiment, the fourth best beam cannot report a probability larger than min(X3, 100 - (X1+X2+X3)), where X1 is the probability that the first beam is best, X2 is the probability that the second beam is best and the X3 is the probability that the third beam is best.

[0164] In a related embodiment, the candidate probabilities for the beams except the first beam are relative to the actual probability reported for the first beam and the granularity of the reported probabilities for the additional beams is controlled by a preconfigured bitfield width for each of the probability bitfield(s). For example, assume that the UE 10 may report three beams, and the first, second, and third beam have a respective probability X1 = 70 %, X2 = 20 %, and X3 = 10% that it is the best beam and a preconfigured width of probabilities for the additional beams to 3 bits each. Then the maximum probability that the second beam is the best beam is min(X1, 100-X1) i.e. 30. With 3 bits, the granularity reported for the second beam is 3.75, i.e., 30 / (2A3). Then the maximum probability that the third beam is the best beam is min(X1+X2, 100-(X1+X2)) i.e. 10. With 3 bits, the granularity reported for the third beam is 1.25, i.e., 10 / (2A3). Please note that the granularities may be rounded up or down to e.g. even percentage numbers.

[0165] In a related embodiment, the number of bits allocated for each of the probability bitfields is configured separately for each beam, i.e. can be different for each beam. As an example, assume that the UE 10 may report three beams, and the first, second, and third beam has a respective probability X1 = 70 %, X2 = 20 %, and X3 = 10% that it is the best beam and a preconfigured width of probabilities for the second and third beam is 3 bits and 1 bits respectively. Then the maximum probability that the second beam is the best beam is min(X1, 100-X1) i.e. 30. With 3 bits, the granularity reported for the second beam is 3.75. Then the maximum probability that the third beam is the best beam is min (X1+X2, 100-(X1+X2)) i.e. 10. With 1 bits, the granularity reported for the third beam is 5, i.e., 10 / (2A1). In a related embodiment, the probability for the first beam is in absolute value, while the probabilities for the rest of the beams are reported in relative values. The relative values can be with reference to the first reported beam, i.e., (X1 , X1-X2, X1-X3, X1-X4, ...). Alternatively, the relative values can be with reference to the earlier adjacent beam, i.e., (X1 , X1-X2, X2-X3, X3-X4, ...). Using the earlier example of reporting three beams and the first, second, and third beam has a probability value X1 = 70 %, X2 = 20 %, and X3 = 10%, respectively, that the associated beam is the best beam.

[0166] • If the relative values are reported with reference to the first reported beam: the probability of the first beam may be reported as absolute value X1 (=70% in this example), while the probability of the 2ndand the 3rdbeams may be reported as (X1-X2) and (X1-X3), which are 50% and 60%, respectively, in this example. If the relative values are reported with reference to the earlier adjacent beam: the probability of the first beam may be reported as absolute value X1 (=70% in this example), while the probability of the 2ndand the 3rdbeams may be reported as (X1-X2) and (X2-X3), which are 50% and 10%, respectively, in this example.

[0167] For time-domain beam prediction, one or more predicted beams and associated performance metric, may be reported for each of F future time instances. The performance metric used in the 1-st future time instance may be used as the anchor value for the remaining future time instances, which might reduce some overhead for reporting. One example is shown in Fig. 10.

[0168] • In one embodiment, for each future time instance starting from future time instance #2, same bits (same granularity) used for reporting the relative probability comparing to the value in Future Time Instance #1 • In another embodiment, for each future time instance starting from future time instance #2, different bits (different granularities) used for reporting the relative probability comparing to the value in Future Time Instance #1

[0169] • where in this example shown in Fig. 10, same minimum probability that may be reported for that beam M=30%, same maximum probability difference between any future time instance and future time instance #1 is 50%, and the number of future time instance N=4 are considered when calculating the required bits for reporting the probability of beam to be the best beam for 4 considered future time instances.

[0170] Thus, Fig. 10 shows an example for reporting the probability of beam to be the best beam in time-domain beam prediction.

[0171] The probability of beam to be the best beam in future time instance #K (K>1) may be the relative probability based on the probability in the previous future time instance #(K-1) rather than always comparing to the anchor / reference probability in the future time instance #1. As such, the reporting overhead may be further reduced.

[0172] The probability format, e.g. granularity, may be dependent on the beam ID. For example, the beams in ID range 1-10 will use granularity of 1%, while beams in range 11- 32 will use granularity of 5%. This can be used in scenarios when the beams in ID range 11-32 are very infrequent, e.g., pointing to the sky, and are hence expected to have much less training data available than beams pointing towards the ground. This is due to the problem of calibrating the probability estimate, that it is hard to match the true likelihood. That is, there is no point in using a finer probability granularity than 1% due to the probability calibration issue. One example of such statistics is shown in Fig. 11 for an outdoor scenario, described in R1-2206938, illustrating that the best beam statistics can be highly biased, e.g., beams pointing near the horizon.

[0173] The probability format may support a grouping of beams into a summed probability. For example, the format enables summarizing the probability of a set of beams. The probability could then be reported for such a set of beams using any of the methods described above. In one example, the format supports that the UE 10 may report the summed probability of a beam being best in the 69-degree zenith direction in figure above. This can enable the NW to understand the likelihood of the UE 10 being in a certain direction. The beam IDs for grouping the summed probability could be based on the pointing direction, beam statistics of being strongest, or the beams scanned in a previous time instance. Fig. 12 shows a block diagram depicting the UE 10 for handling communication in the wireless communications network.

[0174] The UE 10 may comprise processing circuitry 901 , e.g. one or more processors, configured to perform the methods herein.

[0175] The UE 10 and / or the processing circuitry 901 may be configured to receive from the radio network node 12 the configuration indication. The configuration indication may indicate the determined reporting configuration such as use of indices, granularity of probability, and / or interval / range of values.

[0176] The UE 10 and / or the processing circuitry 901 may be configured to obtain the first indication related to signal strength or quality of the first beam relative other beams. The UE 10 may measure on a set B of beams and then using a computational model such as an AI / ML model obtain a set A of beams and related signal strength or quality. As an example, the UE 10 may obtain that the first beam is a best beam out of a number of beams in terms of signal strength or quality.

[0177] The UE 10 and / or the processing circuitry 901 may be configured to obtain the second indication indicating the performance metric of the first beam, wherein the format of the performance metric is based on the value of the performance metric, the number of beams reported, the beam ID and / or relative to another beam. The second indication may be related to a first probability that the first indication is correct. The computational model or another computational model such as an AI / ML model may be used to obtain the performance metric.

[0178] The UE 10 and / or the processing circuitry 901 is configured to transmit to the radio network node 12, the second indication indicating the performance metric of the first beam. The format of the performance metric is based on the value of the performance metric, the number of beams reported, the beam ID and / or relative the other beam.

[0179] The format of the performance metric may be defined with the granularity such a level of detailed probability e.g., whole percentage, part of percentage, tens of percentage or similar, with the interval or range, and / or relative to another performance metric. The granularity, the interval or range, and / or the performance metric may be based on the value of the performance metric, the number of beams reported, the beam ID and / or the other beam

[0180] The performance metric may comprise a probability that the first beam is a best beam out of a number of beams in terms of signal strength or quality. The UE 10 and / or the processing circuitry 901 may be configured to transmit to the radio network node 12 the first indication indicating identity of the first beam, such as beam index, or order of beams.

[0181] The UE 10 further comprises a memory 905. The memory comprises one or more units to be used to store data on, such as indications, computational model, performance metrics, reconfiguration, applications to perform the methods disclosed herein when being executed, and similar. The UE 10 comprises a communication interface 906 comprising transmitter, receiver, transceiver and / or one or more antennas. Thus, it is herein provided the UE 10 for handling communication in a wireless communications network, wherein the UE 10 comprises processing circuitry and a memory, said memory comprising instructions executable by said processing circuitry whereby said UE 10 is operative to perform any of the methods herein.

[0182] The methods according to the embodiments described herein for the UE 10 are respectively implemented by means of e.g. a computer program product 907 or a computer program product, comprising instructions, i.e. , software code portions, which, when executed on at least one processor, cause the at least one processor to carry out the actions described herein, as performed by the UE 10. The computer program product 907 may be stored on a computer-readable storage medium 908, e g. a universal serial bus (USB) stick, a disc or similar. The computer-readable storage medium 908, having stored thereon the computer program product, may comprise the instructions which, when executed on at least one processor, cause the at least one processor to carry out the actions described herein, as performed by the UE 10. In some embodiments, the computer-readable storage medium may be a non-transitory or transitory computer- readable storage medium.

[0183] Fig. 13 shows a block diagram depicting the radio network node 12 for handling communication in the wireless communications network.

[0184] The radio network node 12 may comprise processing circuitry 1001 , e.g. one or more processors, configured to perform the methods herein.

[0185] The radio network node 12 and / or the processing circuitry 1001 may be configured to determine the reporting configuration for the UE 10, wherein the reporting configuration defines a format for reporting the performance metric such as probability.

[0186] The radio network node 12 and / or the processing circuitry 1001 may be configured to transmit configuration indication to the UE 10. The configuration indication may indicate the determined reporting configuration such as use of indices, granularity of probability, and / or interval / range of values. The radio network node 12 and / or the processing circuitry 1001 may be configured to further transmit the computational model such as Al model to the UE 10-

[0187] The radio network node 12 and / or the processing circuitry 1001 is configured to receive from the UE 10, the second indication indicating the performance metric of the first beam. The format of the performance metric is based on the value of the performance metric, the number of beams reported, the beam ID and / or relative the other beam.

[0188] The format of the performance metric may be defined with the granularity, with the interval or range, and / or relative to another performance metric. The granularity, the interval or range, and / or the performance metric may be based on the value of the performance metric, the number of beams reported, the beam ID and / or the other beam.

[0189] The performance metric may comprise a probability that the first beam is a best beam out of a number of beams in terms of signal strength or quality.

[0190] The radio network node 12 and / or the processing circuitry 1001 may be configured to receive from the UE 10, the first indication indicating identity of the first beam.

[0191] The radio network node 12 and / or the processing circuitry 1001 may be configured to use the second indication when performing a network operation such as transmission, allocate resources, mobility and / or similar.

[0192] The radio network node 12 further comprises a memory 1005. The memory comprises one or more units to be used to store data on, such as indications, computational model, performance metrics, reconfiguration, applications to perform the methods disclosed herein when being executed, and similar. The radio network node 12 comprises a communication interface 1006 comprising transmitter, receiver, transceiver and / or one or more antennas. Thus, it is herein provided the radio network node 12 for handling communication in a wireless communications network, wherein the radio network node 12 comprises processing circuitry and a memory, said memory comprising instructions executable by said processing circuitry whereby said radio network node 12 is operative to perform any of the methods herein.

[0193] The methods according to the embodiments described herein for the radio network node 12 are respectively implemented by means of e.g. a computer program product 1007 or a computer program product, comprising instructions, i.e. , software code portions, which, when executed on at least one processor, cause the at least one processor to carry out the actions described herein, as performed by the radio network node 12. The computer program product 1007 may be stored on a computer-readable storage medium 1008, e.g. a universal serial bus (USB) stick, a disc or similar. The computer- readable storage medium 1008, having stored thereon the computer program product, may comprise the instructions which, when executed on at least one processor, cause the at least one processor to carry out the actions described herein, as performed by the radio network node 12. In some embodiments, the computer-readable storage medium may be a non-transitory or transitory computer-readable storage medium.

[0194] As will be readily understood by those familiar with communications design, that functions means or modules may be implemented using digital logic and / or one or more microcontrollers, microprocessors, or other digital hardware. In some embodiments, several or all of the various functions may be implemented together, such as in a single application-specific integrated circuit (ASIC), or in two or more separate devices with appropriate hardware and / or software interfaces between them. Several of the functions may be implemented on a processor shared with other functional components of a radio network node, for example.

[0195] Alternatively, several of the functional elements of the processing means discussed may be provided through the use of dedicated hardware, while others are provided with hardware for executing software, in association with the appropriate software or firmware. Thus, the term “processor” or “controller” as used herein does not exclusively refer to hardware capable of executing software and may implicitly include, without limitation, digital signal processor (DSP) hardware, read-only memory (ROM) for storing software, random-access memory for storing software and / or program or application data, and non-volatile memory. Other hardware, conventional and / or custom, may also be included. Designers of communications receivers will appreciate the cost, performance, and maintenance trade-offs inherent in these design choices.

[0196] Fig. 14 shows an example of a communication system QQ100 in accordance with some embodiments.

[0197] In the example, the communication system QQ100 includes a telecommunication network QQ102 that includes an access network QQ104, such as a radio access network (RAN), and a core network QQ106, which includes one or more core network nodes QQ108. The access network QQ104 includes one or more access network nodes, such as network nodes QQ110a and QQ110b (one or more of which may be generally referred to as network nodes QQ110) being examples of the first radio network node 12 and second radio network node 13, or any other similar 3rdGeneration Partnership Project (3GPP) access nodes or non-3GPP access points. Moreover, as will be appreciated by those of skill in the art, a network node, being examples of the entities herein, is not necessarily limited to an implementation in which a radio portion and a baseband portion are supplied and integrated by a single vendor. Thus, it will be understood that network nodes include disaggregated implementations or portions thereof. For example, in some embodiments, the telecommunication network QQ102 includes one or more Open-RAN (ORAN) network nodes. An ORAN network node is a node in the telecommunication network QQ102 that supports an ORAN specification (e.g., a specification published by the O-RAN Alliance, or any similar organization) and may operate alone or together with other nodes to implement one or more functionalities of any node in the telecommunication network QQ102, including one or more network nodes QQ110 and / or core network nodes QQ108.

[0198] Examples of an ORAN network node include an open radio unit (0-Rll), an open distributed unit (0-Dll), an open central unit (O-CU), including an O-CU control plane (O-CU-CP) or an O-CU user plane (O-CU-UP), a RAN intelligent controller (near- real time or non-real time) hosting software or software plug-ins, such as a near-real time control application (e.g., xApp) or a non-real time control application (e.g., rApp), or any combination thereof (the adjective “open” designating support of an ORAN specification). The network node may support a specification by, for example, supporting an interface defined by the ORAN specification, such as an A1 , F1 , W1, E1, E2, X2, Xn interface, an open fronthaul user plane interface, or an open fronthaul management plane interface. Moreover, an ORAN access node may be a logical node in a physical node. Furthermore, an ORAN network node may be implemented in a virtualization environment (described further below) in which one or more network functions are virtualized. For example, the virtualization environment may include an O-Cloud computing platform orchestrated by a Service Management and Orchestration Framework via an 0-2 interface defined by the O-RAN Alliance or comparable technologies. The network nodes QQ110 facilitate direct or indirect connection of the user equipment (UE) 10, such as by connecting UEs QQ112a, QQ112b, QQ112c, and QQ112d (one or more of which may be generally referred to as UEs QQ112) to the core network QQ106 over one or more wireless connections.

[0199] Example wireless communications over a wireless connection include transmitting and / or receiving wireless signals using electromagnetic waves, radio waves, infrared waves, and / or other types of signals suitable for conveying information without the use of wires, cables, or other material conductors. Moreover, in different embodiments, the communication system QQ100 may include any number of wired or wireless networks, network nodes, UEs, and / or any other components or systems that may facilitate or participate in the communication of data and / or signals whether via wired or wireless connections. The communication system QQ100 may include and / or interface with any type of communication, telecommunication, data, cellular, radio network, and / or other similar type of system.

[0200] The UEs QQ112 may be any of a wide variety of communication devices, including wireless devices arranged, configured, and / or operable to communicate wirelessly with the network nodes QQ110 and other communication devices. Similarly, the network nodes QQ110 are arranged, capable, configured, and / or operable to communicate directly or indirectly with the UEs QQ112 and / or with other network nodes or equipment in the telecommunication network QQ102 to enable and / or provide network access, such as wireless network access, and / or to perform other functions, such as administration in the telecommunication network QQ102.

[0201] In the depicted example, the core network QQ106 connects the network nodes QQ110 to one or more hosts, such as host QQ116. These connections may be direct or indirect via one or more intermediary networks or devices. In other examples, network nodes may be directly coupled to hosts. The core network QQ106 includes one more core network nodes (e.g., core network node QQ108) such as network node 15 that are structured with hardware and software components. Features of these components may be substantially similar to those described with respect to the UEs, network nodes, and / or hosts, such that the descriptions thereof are generally applicable to the corresponding components of the core network node QQ108. Example core network nodes include functions of one or more of a Mobile Switching Center (MSC), Mobility Management Entity (MME), Home Subscriber Server (HSS), Access and Mobility Management Function (AMF), Session Management Function (SMF), Authentication Server Function (AUSF), Subscription Identifier De-concealing function (SIDF), Unified Data Management (UDM), Security Edge Protection Proxy (SEPP), Network Exposure Function (NEF), and / or a User Plane Function (UPF).

[0202] The host QQ116 may be under the ownership or control of a service provider other than an operator or provider of the access network QQ104 and / or the telecommunication network QQ102, and may be operated by the service provider or on behalf of the service provider. The host QQ116 may host a variety of applications to provide one or more service. Examples of such applications include live and prerecorded audio / video content, data collection services such as retrieving and compiling data on various ambient conditions detected by a plurality of UEs, analytics functionality, social media, functions for controlling or otherwise interacting with remote devices, functions for an alarm and surveillance center, or any other such function performed by a server.

[0203] As a whole, the communication system QQ100 of Fig. 14 enables connectivity between the UEs, network nodes, and hosts. In that sense, the communication system may be configured to operate according to predefined rules or procedures, such as specific standards that include, but are not limited to: Global System for Mobile Communications (GSM); Universal Mobile Telecommunications System (UMTS); Long Term Evolution (LTE), and / or other suitable 2G, 3G, 4G, 5G standards, or any applicable future generation standard (e.g., 6G); wireless local area network (WLAN) standards, such as the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standards (WiFi); and / or any other appropriate wireless communication standard, such as the Worldwide Interoperability for Microwave Access (WiMax), Bluetooth, Z-Wave, Near Field Communication (NFC) ZigBee, LiFi, and / or any low-power wide-area network (LPWAN) standards such as LoRa and Sigfox.

[0204] In some examples, the telecommunication network QQ102 is a cellular network that implements 3GPP standardized features. Accordingly, the telecommunications network QQ102 may support network slicing to provide different logical networks to different devices that are connected to the telecommunication network QQ102. For example, the telecommunications network QQ102 may provide Ultra Reliable Low Latency Communication (URLLC) services to some UEs, while providing Enhanced Mobile Broadband (eMBB) services to other UEs, and / or Massive Machine Type Communication (mMTC) / Massive loT services to yet further UEs.

[0205] In some examples, the UEs QQ112 are configured to transmit and / or receive information without direct human interaction. For instance, a UE may be designed to transmit information to the access network QQ104 on a predetermined schedule, when triggered by an internal or external event, or in response to requests from the access network QQ104. Additionally, a UE may be configured for operating in single- or multi- RAT or multi-standard mode. For example, a UE may operate with any one or combination of Wi-Fi, NR (New Radio) and LTE, i.e. being configured for multi-radio dual connectivity (MR-DC), such as E-UTRAN (Evolved-UMTS Terrestrial Radio Access Network) New Radio - Dual Connectivity (EN-DC).

[0206] In the example, the hub QQ114 communicates with the access network QQ104 to facilitate indirect communication between one or more UEs (e.g., UE QQ112c and / or QQ112d) and network nodes (e.g., network node QQ110b). In some examples, the hub QQ114 may be a controller, router, content source and analytics, or any of the other communication devices described herein regarding UEs. For example, the hub QQ114 may be a broadband router enabling access to the core network QQ106 for the UEs. As another example, the hub QQ114 may be a controller that sends commands or instructions to one or more actuators in the UEs. Commands or instructions may be received from the UEs, network nodes QQ110, or by executable code, script, process, or other instructions in the hub QQ114. As another example, the hub QQ114 may be a data collector that acts as temporary storage for UE data and, in some embodiments, may perform analysis or other processing of the data. As another example, the hub QQ114 may be a content source. For example, for a UE that is a VR headset, display, loudspeaker or other media delivery device, the hub QQ114 may retrieve VR assets, video, audio, or other media or data related to sensory information via a network node, which the hub QQ114 then provides to the UE either directly, after performing local processing, and / or after adding additional local content. In still another example, the hub QQ114 acts as a proxy server or orchestrator for the UEs, in particular if one or more of the UEs are low energy loT devices.

[0207] The hub QQ114 may have a constant / persistent or intermittent connection to the network node QQ110b. The hub QQ114 may also allow for a different communication scheme and / or schedule between the hub QQ114 and UEs (e.g., UE QQ112c and / or QQ112d), and between the hub QQ114 and the core network QQ106. In other examples, the hub QQ114 is connected to the core network QQ106 and / or one or more UEs via a wired connection. Moreover, the hub QQ114 may be configured to connect to an M2M service provider over the access network QQ104 and / or to another UE over a direct connection. In some scenarios, UEs may establish a wireless connection with the network nodes QQ110 while still connected via the hub QQ114 via a wired or wireless connection. In some embodiments, the hub QQ114 may be a dedicated hub - that is, a hub whose primary function is to route communications to / from the UEs from / to the network node QQ110b. In other embodiments, the hub QQ114 may be a non-dedicated hub - that is, a device which is capable of operating to route communications between the UEs and network node QQ110b, but which is additionally capable of operating as a communication start and / or end point for certain data channels.

[0208] Figure 15 shows a UE QQ200 in accordance with some embodiments. As used herein, a UE refers to a device capable, configured, arranged and / or operable to communicate wirelessly with network nodes and / or other UEs. Examples of a UE include, but are not limited to, a smart phone, mobile phone, cell phone, voice over IP (VoIP) phone, wireless local loop phone, desktop computer, personal digital assistant (PDA), wireless cameras, gaming console or device, music storage device, playback appliance, wearable terminal device, wireless endpoint, mobile station, tablet, laptop, laptop-embedded equipment (LEE), laptop-mounted equipment (LME), smart device, wireless customer-premise equipment (CPE), vehicle, vehicle-mounted or vehicle embedded / integrated wireless device, etc. Other examples include any UE identified by the 3rd Generation Partnership Project (3GPP), including a narrow band internet of things (NB-loT) UE, a machine type communication (MTC) UE, and / or an enhanced MTC (eMTC) UE.

[0209] A UE may support device-to-device (D2D) communication, for example by implementing a 3GPP standard for sidelink communication, Dedicated Short-Range Communication (DSRC), vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), or vehicle-to-everything (V2X). In other examples, a UE may not necessarily have a user in the sense of a human user who owns and / or operates the relevant device. Instead, a UE may represent a device that is intended for sale to, or operation by, a human user but which may not, or which may not initially, be associated with a specific human user (e.g., a smart sprinkler controller). Alternatively, a UE may represent a device that is not intended for sale to, or operation by, an end user but which may be associated with or operated for the benefit of a user (e.g., a smart power meter).

[0210] The UE QQ200 includes processing circuitry QQ202 that is operatively coupled via a bus QQ204 to an input / output interface QQ206, a power source QQ208, a memory QQ210, a communication interface QQ212, and / or any other component, or any combination thereof. Certain UEs may utilize all or a subset of the components shown in Figure 15. The level of integration between the components may vary from one UE to another UE. Further, certain UEs may contain multiple instances of a component, such as multiple processors, memories, transceivers, transmitters, receivers, etc.

[0211] The processing circuitry QQ202 is configured to process instructions and data and may be configured to implement any sequential state machine operative to execute instructions stored as machine-readable computer programs in the memory QQ210. The processing circuitry QQ202 may be implemented as one or more hardware-implemented state machines (e.g., in discrete logic, field-programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), etc.); programmable logic together with appropriate firmware; one or more stored computer programs, general-purpose processors, such as a microprocessor or digital signal processor (DSP), together with appropriate software; or any combination of the above. For example, the processing circuitry QQ202 may include multiple central processing units (CPUs).

[0212] In the example, the input / output interface QQ206 may be configured to provide an interface or interfaces to an input device, output device, or one or more input and / or output devices. Examples of an output device include a speaker, a sound card, a video card, a display, a monitor, a printer, an actuator, an emitter, a smartcard, another output device, or any combination thereof. An input device may allow a user to capture information into the UE QQ200. Examples of an input device include a touch-sensitive or presence-sensitive display, a camera (e.g., a digital camera, a digital video camera, a web camera, etc.), a microphone, a sensor, a mouse, a trackball, a directional pad, a trackpad, a scroll wheel, a smartcard, and the like. The presence-sensitive display may include a capacitive or resistive touch sensor to sense input from a user. A sensor may be, for instance, an accelerometer, a gyroscope, a tilt sensor, a force sensor, a magnetometer, an optical sensor, a proximity sensor, a biometric sensor, etc., or any combination thereof. An output device may use the same type of interface port as an input device. For example, a Universal Serial Bus (USB) port may be used to provide an input device and an output device.

[0213] In some embodiments, the power source QQ208 is structured as a battery or battery pack. Other types of power sources, such as an external power source (e.g., an electricity outlet), photovoltaic device, or power cell, may be used. The power source QQ208 may further include power circuitry for delivering power from the power source QQ208 itself, and / or an external power source, to the various parts of the UE QQ200 via input circuitry or an interface such as an electrical power cable. Delivering power may be, for example, for charging of the power source QQ208. Power circuitry may perform any formatting, converting, or other modification to the power from the power source QQ208 to make the power suitable for the respective components of the UE QQ200 to which power is supplied.

[0214] The memory QQ210 may be or be configured to include memory such as random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic disks, optical disks, hard disks, removable cartridges, flash drives, and so forth. In one example, the memory QQ210 includes one or more application programs QQ214, such as an operating system, web browser application, a widget, gadget engine, or other application, and corresponding data QQ216. The memory QQ210 may store, for use by the UE QQ200, any of a variety of various operating systems or combinations of operating systems.

[0215] The memory QQ210 may be configured to include a number of physical drive units, such as redundant array of independent disks (RAID), flash memory, USB flash drive, external hard disk drive, thumb drive, pen drive, key drive, high-density digital versatile disc (HD-DVD) optical disc drive, internal hard disk drive, Blu-Ray optical disc drive, holographic digital data storage (HDDS) optical disc drive, external mini-dual inline memory module (DIMM), synchronous dynamic random access memory (SDRAM), external micro-DIMM SDRAM, smartcard memory such as tamper resistant module in the form of a universal integrated circuit card (UICC) including one or more subscriber identity modules (SIMs), such as a USIM and / or ISIM, other memory, or any combination thereof. The UICC may for example be an embedded UICC (eUlCC), integrated UICC (iUICC) or a removable UICC commonly known as ‘SIM card.’ The memory QQ210 may allow the UE QQ200 to access instructions, application programs and the like, stored on transitory or non-transitory memory media, to off-load data, or to upload data. An article of manufacture, such as one utilizing a communication system may be tangibly embodied as or in the memory QQ210, which may be or comprise a device-readable storage medium.

[0216] The processing circuitry QQ202 may be configured to communicate with an access network or other network using the communication interface QQ212. The communication interface QQ212 may comprise one or more communication subsystems and may include or be communicatively coupled to an antenna QQ222. The communication interface QQ212 may include one or more transceivers used to communicate, such as by communicating with one or more remote transceivers of another device capable of wireless communication (e.g., another UE or a network node in an access network). Each transceiver may include a transmitter QQ218 and / or a receiver QQ220 appropriate to provide network communications (e.g., optical, electrical, frequency allocations, and so forth). Moreover, the transmitter QQ218 and receiver QQ220 may be coupled to one or more antennas (e.g., antenna QQ222) and may share circuit components, software or firmware, or alternatively be implemented separately.

[0217] In the illustrated embodiment, communication functions of the communication interface QQ212 may include cellular communication, Wi-Fi communication, LPWAN communication, data communication, voice communication, multimedia communication, short-range communications such as Bluetooth, near-field communication, location-based communication such as the use of the global positioning system (GPS) to determine a location, another like communication function, or any combination thereof. Communications may be implemented in according to one or more communication protocols and / or standards, such as IEEE 802.11, Code Division Multiplexing Access (CDMA), Wideband Code Division Multiple Access (WCDMA), GSM, LTE, New Radio (NR), UMTS, WiMax, Ethernet, transmission control protocol / internet protocol (TCP / IP), synchronous optical networking (SONET), Asynchronous Transfer Mode (ATM), QUIC, Hypertext Transfer Protocol (HTTP), and so forth.

[0218] Regardless of the type of sensor, a UE may provide an output of data captured by its sensors, through its communication interface QQ212, via a wireless connection to a network node. Data captured by sensors of a UE can be communicated through a wireless connection to a network node via another UE. The output may be periodic (e.g., once every 15 minutes if it reports the sensed temperature), random (e.g., to even out the load from reporting from several sensors), in response to a triggering event (e.g., when moisture is detected an alert is sent), in response to a request (e.g., a user initiated request), or a continuous stream (e.g., a live video feed of a patient).

[0219] As another example, a UE comprises an actuator, a motor, or a switch, related to a communication interface configured to receive wireless input from a network node via a wireless connection. In response to the received wireless input the states of the actuator, the motor, or the switch may change. For example, the UE may comprise a motor that adjusts the control surfaces or rotors of a drone in flight according to the received input or to a robotic arm performing a medical procedure according to the received input.

[0220] A UE, when in the form of an Internet of Things (loT) device, may be a device for use in one or more application domains, these domains comprising, but not limited to, city wearable technology, extended industrial application and healthcare. Nonlimiting examples of such an loT device are a device which is or which is embedded in: a connected refrigerator or freezer, a TV, a connected lighting device, an electricity meter, a robot vacuum cleaner, a voice controlled smart speaker, a home security camera, a motion detector, a thermostat, a smoke detector, a door / window sensor, a flood / moisture sensor, an electrical door lock, a connected doorbell, an air conditioning system like a heat pump, an autonomous vehicle, a surveillance system, a weather monitoring device, a vehicle parking monitoring device, an electric vehicle charging station, a smart watch, a fitness tracker, a head-mounted display for Augmented Reality (AR) or Virtual Reality (VR), a wearable for tactile augmentation or sensory enhancement, a water sprinkler, an animal- or item-tracking device, a sensor for monitoring a plant or animal, an industrial robot, an Unmanned Aerial Vehicle (UAV), and any kind of medical device, like a heart rate monitor or a remote controlled surgical robot. A UE in the form of an loT device comprises circuitry and / or software in dependence of the intended application of the loT device in addition to other components as described in relation to the UE QQ200 shown in Figure 15.

[0221] As yet another specific example, in an loT scenario, a UE may represent a machine or other device that performs monitoring and / or measurements and transmits the results of such monitoring and / or measurements to another UE and / or a network node. The UE may in this case be an M2M device, which may in a 3GPP context be referred to as an MTC device. As one particular example, the UE may implement the 3GPP NB-loT standard. In other scenarios, a UE may represent a vehicle, such as a car, a bus, a truck, a ship and an airplane, or other equipment that is capable of monitoring and / or reporting on its operational status or other functions associated with its operation.

[0222] In practice, any number of UEs may be used together with respect to a single use case. For example, a first UE might be or be integrated in a drone and provide the drone’s speed information (obtained through a speed sensor) to a second UE that is a remote controller operating the drone. When the user makes changes from the remote controller, the first UE may adjust the throttle on the drone (e.g. by controlling an actuator) to increase or decrease the drone’s speed. The first and / or the second UE can also include more than one of the functionalities described above. For example, a UE might comprise the sensor and the actuator, and handle communication of data for both the speed sensor and the actuators.

[0223] Figure 16 shows a network node QQ300 in accordance with some embodiments. As used herein, network node refers to equipment capable, configured, arranged and / or operable to communicate directly or indirectly with a UE and / or with other network nodes or equipment, in a telecommunication network. Examples of network nodes include, but are not limited to, access points (APs) (e.g., radio access points), base stations (BSs) (e.g., radio base stations, Node Bs, evolved Node Bs (eNBs) and NR NodeBs (gNBs)), O-RAN nodes or components of an O-RAN node (e.g., O-RU, O-DU, O-CU). Base stations may be categorized based on the amount of coverage they provide (or, stated differently, their transmit power level) and so, depending on the provided amount of coverage, may be referred to as femto base stations, pico base stations, micro base stations, or macro base stations. A base station may be a relay node or a relay donor node controlling a relay. A network node may also include one or more (or all) parts of a distributed radio base station such as centralized digital units, distributed units (e.g., in an O-RAN access node) and / or remote radio units (RRUs), sometimes referred to as Remote Radio Heads (RRHs). Such remote radio units may or may not be integrated with an antenna as an antenna integrated radio. Parts of a distributed radio base station may also be referred to as nodes in a distributed antenna system (DAS).

[0224] Other examples of network nodes include multiple transmission point (multi- TRP) 5G access nodes, multi-standard radio (MSR) equipment such as MSR BSs, network controllers such as radio network controllers (RNCs) or base station controllers (BSCs), base transceiver stations (BTSs), transmission points, transmission nodes, multi-cell / multicast coordination entities (MCEs), Operation and Maintenance (O&M) nodes, Operations Support System (OSS) nodes, Self-Organizing Network (SON) nodes, positioning nodes (e.g., Evolved Serving Mobile Location Centers (E-SMLCs)), and / or Minimization of Drive Tests (MDTs).

[0225] The network node QQ300 includes a processing circuitry QQ302, a memory QQ304, a communication interface QQ306, and a power source QQ308. The network node QQ300 may be composed of multiple physically separate components (e.g., a NodeB component and a RNC component, or a BTS component and a BSC component, etc.), which may each have their own respective components. In certain scenarios in which the network node QQ300 comprises multiple separate components (e.g., BTS and BSC components), one or more of the separate components may be shared among several network nodes. For example, a single RNC may control multiple NodeBs. In such a scenario, each unique NodeB and RNC pair may, in some instances, be considered a single separate network node. In some embodiments, the network node QQ300 may be configured to support multiple radio access technologies (RATs). In such embodiments, some components may be duplicated (e.g., separate memory QQ304 for different RATs) and some components may be reused (e.g., a same antenna QQ310 may be shared by different RATs). The network node QQ300 may also include multiple sets of the various illustrated components for different wireless technologies integrated into network node QQ300, for example GSM, WCDMA, LTE, NR, WiFi, Zigbee, Z-wave, LoRaWAN, Radio Frequency Identification (RFID) or Bluetooth wireless technologies. These wireless technologies may be integrated into the same or different chip or set of chips and other components within network node QQ300.

[0226] The processing circuitry QQ302 may comprise a combination of one or more of a microprocessor, controller, microcontroller, central processing unit, digital signal processor, application-specific integrated circuit, field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software and / or encoded logic operable to provide, either alone or in conjunction with other network node QQ300 components, such as the memory QQ304, to provide network node QQ300 functionality.

[0227] In some embodiments, the processing circuitry QQ302 includes a system on a chip (SOC). In some embodiments, the processing circuitry QQ302 includes one or more of radio frequency (RF) transceiver circuitry QQ312 and baseband processing circuitry QQ314. In some embodiments, the radio frequency (RF) transceiver circuitry QQ312 and the baseband processing circuitry QQ314 may be on separate chips (or sets of chips), boards, or units, such as radio units and digital units. In alternative embodiments, part or all of RF transceiver circuitry QQ312 and baseband processing circuitry QQ314 may be on the same chip or set of chips, boards, or units.

[0228] The memory QQ304 may comprise any form of volatile or non-volatile computer-readable memory including, without limitation, persistent storage, solid-state memory, remotely mounted memory, magnetic media, optical media, random access memory (RAM), read-only memory (ROM), mass storage media (for example, a hard disk), removable storage media (for example, a flash drive, a Compact Disk (CD) or a Digital Video Disk (DVD)), and / or any other volatile or non-volatile, non-transitory device-readable and / or computer-executable memory devices that store information, data, and / or instructions that may be used by the processing circuitry QQ302. The memory QQ304 may store any suitable instructions, data, or information, including a computer program, software, an application including one or more of logic, rules, code, tables, and / or other instructions capable of being executed by the processing circuitry QQ302 and utilized by the network node QQ300. The memory QQ304 may be used to store any calculations made by the processing circuitry QQ302 and / or any data received via the communication interface QQ306. In some embodiments, the processing circuitry QQ302 and memory QQ304 is integrated. The communication interface QQ306 is used in wired or wireless communication of signaling and / or data between a network node, access network, and / or UE. As illustrated, the communication interface QQ306 comprises port(s) / terminal(s) QQ316 to send and receive data, for example to and from a network over a wired connection. The communication interface QQ306 also includes radio frontend circuitry QQ318 that may be coupled to, or in certain embodiments a part of, the antenna QQ310. Radio front-end circuitry QQ318 comprises filters QQ320 and amplifiers QQ322. The radio front-end circuitry QQ318 may be connected to an antenna QQ310 and processing circuitry QQ302. The radio front-end circuitry may be configured to condition signals communicated between antenna QQ310 and processing circuitry QQ302. The radio front-end circuitry QQ318 may receive digital data that is to be sent out to other network nodes or UEs via a wireless connection. The radio front-end circuitry QQ318 may convert the digital data into a radio signal having the appropriate channel and bandwidth parameters using a combination of filters QQ320 and / or amplifiers QQ322. The radio signal may then be transmitted via the antenna QQ310. Similarly, when receiving data, the antenna QQ310 may collect radio signals which are then converted into digital data by the radio front-end circuitry QQ318. The digital data may be passed to the processing circuitry QQ302. In other embodiments, the communication interface may comprise different components and / or different combinations of components.

[0229] In certain alternative embodiments, the network node QQ300 does not include separate radio front-end circuitry QQ318, instead, the processing circuitry QQ302 includes radio front-end circuitry and is connected to the antenna QQ310. Similarly, in some embodiments, all or some of the RF transceiver circuitry QQ312 is part of the communication interface QQ306. In still other embodiments, the communication interface QQ306 includes one or more ports or terminals QQ316, the radio front-end circuitry QQ318, and the RF transceiver circuitry QQ312, as part of a radio unit (not shown), and the communication interface QQ306 communicates with the baseband processing circuitry QQ314, which is part of a digital unit (not shown).

[0230] The antenna QQ310 may include one or more antennas, or antenna arrays, configured to send and / or receive wireless signals. The antenna QQ310 may be coupled to the radio front-end circuitry QQ318 and may be any type of antenna capable of transmitting and receiving data and / or signals wirelessly. In certain embodiments, the antenna QQ310 is separate from the network node QQ300 and connectable to the network node QQ300 through an interface or port. The antenna QQ310, communication interface QQ306, and / or the processing circuitry QQ302 may be configured to perform any receiving operations and / or certain obtaining operations described herein as being performed by the network node. Any information, data and / or signals may be received from a UE, another network node and / or any other network equipment. Similarly, the antenna QQ310, the communication interface QQ306, and / or the processing circuitry QQ302 may be configured to perform any transmitting operations described herein as being performed by the network node. Any information, data and / or signals may be transmitted to a UE, another network node and / or any other network equipment.

[0231] The power source QQ308 provides power to the various components of network node QQ300 in a form suitable for the respective components (e.g., at a voltage and current level needed for each respective component). The power source QQ308 may further comprise, or be coupled to, power management circuitry to supply the components of the network node QQ300 with power for performing the functionality described herein. For example, the network node QQ300 may be connectable to an external power source (e.g., the power grid, an electricity outlet) via an input circuitry or interface such as an electrical cable, whereby the external power source supplies power to power circuitry of the power source QQ308. As a further example, the power source QQ308 may comprise a source of power in the form of a battery or battery pack which is connected to, or integrated in, power circuitry. The battery may provide backup power should the external power source fail.

[0232] Embodiments of the network node QQ300 may include additional components beyond those shown in Figure 16 for providing certain aspects of the network node’s functionality, including any of the functionality described herein and / or any functionality necessary to support the subject matter described herein. For example, the network node QQ300 may include user interface equipment to allow input of information into the network node QQ300 and to allow output of information from the network node QQ300. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for the network node QQ300.

[0233] Figure 17 is a block diagram of a host QQ400, which may be an embodiment of the host QQ116 of Figure 14, in accordance with various aspects described herein. As used herein, the host QQ400 may be or comprise various combinations hardware and / or software, including a standalone server, a blade server, a cloud-implemented server, a distributed server, a virtual machine, container, or processing resources in a server farm. The host QQ400 may provide one or more services to one or more UEs. The host QQ400 includes processing circuitry QQ402 that is operatively coupled via a bus QQ404 to an input / output interface QQ406, a network interface QQ408, a power source QQ410, and a memory QQ412. Other components may be included in other embodiments. Features of these components may be substantially similar to those described with respect to the devices of previous figures, such as Figures 15 and 16, such that the descriptions thereof are generally applicable to the corresponding components of host QQ400.

[0234] The memory QQ412 may include one or more computer programs including one or more host application programs QQ414 and data QQ416, which may include user data, e.g., data generated by a UE for the host QQ400 or data generated by the host QQ400 for a UE. Embodiments of the host QQ400 may utilize only a subset, or all of the components shown. The host application programs QQ414 may be implemented in a container-based architecture and may provide support for video codecs (e.g., Versatile Video Coding (WC), High Efficiency Video Coding (HEVC), Advanced Video Coding (AVC), MPEG, VP9) and audio codecs (e.g., FLAG, Advanced Audio Coding (AAC), MPEG, G.711), including transcoding for multiple different classes, types, or implementations of UEs (e.g., handsets, desktop computers, wearable display systems, heads-up display systems). The host application programs QQ414 may also provide for user authentication and licensing checks and may periodically report health, routes, and content availability to a central node, such as a device in or on the edge of a core network. Accordingly, the host QQ400 may select and / or indicate a different host for over-the-top services for a UE. The host application programs QQ414 may support various protocols, such as the HTTP Live Streaming (HLS) protocol, Real-Time Messaging Protocol (RTMP), Real-Time Streaming Protocol (RTSP), Dynamic Adaptive Streaming over HTTP (MPEG-DASH), etc.

[0235] Figure 18 is a block diagram illustrating a virtualization environment QQ500 in which functions implemented by some embodiments may be virtualized. In the present context, virtualizing means creating virtual versions of apparatuses or devices which may include virtualizing hardware platforms, storage devices and networking resources. As used herein, virtualization can be applied to any device described herein, or components thereof, and relates to an implementation in which at least a portion of the functionality is implemented as one or more virtual components. Some or all of the functions described herein may be implemented as virtual components executed by one or more virtual machines (VMs) implemented in one or more virtual environments QQ500 hosted by one or more of hardware nodes, such as a hardware computing device that operates as a network node, UE, core network node, or host. Further, in embodiments in which the virtual node does not require radio connectivity (e.g., a core network node or host), then the node may be entirely virtualized. In some embodiments, the virtualization environment QQ500 includes components defined by the O-RAN Alliance, such as an O-Cloud environment orchestrated by a Service Management and Orchestration Framework via an 0-2 interface.

[0236] Applications QQ502 (which may alternatively be called software instances, virtual appliances, network functions, virtual nodes, virtual network functions, etc.) are run in the virtualization environment Q400 to implement some of the features, functions, and / or benefits of some of the embodiments disclosed herein.

[0237] Hardware QQ504 includes processing circuitry, memory that stores software and / or instructions executable by hardware processing circuitry, and / or other hardware devices as described herein, such as a network interface, input / output interface, and so forth. Software may be executed by the processing circuitry to instantiate one or more virtualization layers QQ506 (also referred to as hypervisors or virtual machine monitors (VMMs)), provide VMs QQ508a and QQ508b (one or more of which may be generally referred to as VMs QQ508), and / or perform any of the functions, features and / or benefits described in relation with some embodiments described herein. The virtualization layer QQ506 may present a virtual operating platform that appears like networking hardware to the VMs QQ508.

[0238] The VMs QQ508 comprise virtual processing, virtual memory, virtual networking or interface and virtual storage, and may be run by a corresponding virtualization layer QQ506. Different embodiments of the instance of a virtual appliance QQ502 may be implemented on one or more of VMs QQ508, and the implementations may be made in different ways. Virtualization of the hardware is in some contexts referred to as network function virtualization (NFV). NFV may be used to consolidate many network equipment types onto industry standard high volume server hardware, physical switches, and physical storage, which can be located in data centers, and customer premise equipment.

[0239] In the context of NFV, a VM QQ508 may be a software implementation of a physical machine that runs programs as if they were executing on a physical, nonvirtualized machine. Each of the VMs QQ508, and that part of hardware QQ504 that executes that VM, be it hardware dedicated to that VM and / or hardware shared by that VM with others of the VMs, forms separate virtual network elements. Still in the context of NFV, a virtual network function is responsible for handling specific network functions that run in one or more VMs QQ508 on top of the hardware QQ504 and corresponds to the application QQ502.

[0240] Hardware QQ504 may be implemented in a standalone network node with generic or specific components. Hardware QQ504 may implement some functions via virtualization. Alternatively, hardware QQ504 may be part of a larger cluster of hardware (e.g. such as in a data center or CPE) where many hardware nodes work together and are managed via management and orchestration QQ510, which, among others, oversees lifecycle management of applications QQ502. In some embodiments, hardware QQ504 is coupled to one or more radio units that each include one or more transmitters and one or more receivers that may be coupled to one or more antennas. Radio units may communicate directly with other hardware nodes via one or more appropriate network interfaces and may be used in combination with the virtual components to provide a virtual node with radio capabilities, such as a radio access node or a base station. In some embodiments, some signaling can be provided with the use of a control system QQ512 which may alternatively be used for communication between hardware nodes and radio units.

[0241] Figure 19 shows a communication diagram of a host QQ602 communicating via a network node QQ604 with a UE QQ606 over a partially wireless connection in accordance with some embodiments. Example implementations, in accordance with various embodiments, of the UE (such as a UE QQ112a of Figure 14 and / or UE QQ200 of Figure 15), network node (such as network node QQ110a of Figure 14 and / or network node QQ300 of Figure 16), and host (such as host QQ116 of Figure 14 and / or host QQ400 of Figure 17) discussed in the preceding paragraphs will now be described with reference to Figure 19.

[0242] Like host QQ400, embodiments of host QQ602 include hardware, such as a communication interface, processing circuitry, and memory. The host QQ602 also includes software, which is stored in or accessible by the host QQ602 and executable by the processing circuitry. The software includes a host application that may be operable to provide a service to a remote user, such as the UE QQ606 connecting via an over-the-top (OTT) connection QQ650 extending between the UE QQ606 and host QQ602. In providing the service to the remote user, a host application may provide user data which is transmitted using the OTT connection QQ650.

[0243] The network node QQ604 includes hardware enabling it to communicate with the host QQ602 and UE QQ606. The connection QQ660 may be direct or pass through a core network (like core network QQ106 of Figure 14) and / or one or more other intermediate networks, such as one or more public, private, or hosted networks. For example, an intermediate network may be a backbone network or the Internet.

[0244] The UE QQ606 includes hardware and software, which is stored in or accessible by UE QQ606 and executable by the UE’s processing circuitry. The software includes a client application, such as a web browser or operator-specific “app” that may be operable to provide a service to a human or non-human user via UE QQ606 with the support of the host QQ602. In the host QQ602, an executing host application may communicate with the executing client application via the OTT connection QQ650 terminating at the UE QQ606 and host QQ602. In providing the service to the user, the UE's client application may receive request data from the host's host application and provide user data in response to the request data. The OTT connection QQ650 may transfer both the request data and the user data. The UE's client application may interact with the user to generate the user data that it provides to the host application through the OTT connection QQ650.

[0245] The OTT connection QQ650 may extend via a connection QQ660 between the host QQ602 and the network node QQ604 and via a wireless connection QQ670 between the network node QQ604 and the UE QQ606 to provide the connection between the host QQ602 and the UE QQ606. The connection QQ660 and wireless connection QQ670, over which the OTT connection QQ650 may be provided, have been drawn abstractly to illustrate the communication between the host QQ602 and the UE QQ606 via the network node QQ604, without explicit reference to any intermediary devices and the precise routing of messages via these devices.

[0246] As an example of transmitting data via the OTT connection QQ650, in step QQ608, the host QQ602 provides user data, which may be performed by executing a host application. In some embodiments, the user data is associated with a particular human user interacting with the UE QQ606. In other embodiments, the user data is associated with a UE QQ606 that shares data with the host QQ602 without explicit human interaction. In step QQ610, the host QQ602 initiates a transmission carrying the user data towards the UE QQ606. The host QQ602 may initiate the transmission responsive to a request transmitted by the UE QQ606. The request may be caused by human interaction with the UE QQ606 or by operation of the client application executing on the UE QQ606. The transmission may pass via the network node QQ604, in accordance with the teachings of the embodiments described throughout this disclosure. Accordingly, in step QQ612, the network node QQ604 transmits to the UE QQ606 the user data that was carried in the transmission that the host QQ602 initiated, in accordance with the teachings of the embodiments described throughout this disclosure. In step QQ614, the UE QQ606 receives the user data carried in the transmission, which may be performed by a client application executed on the UE QQ606 associated with the host application executed by the host QQ602.

[0247] In some examples, the UE QQ606 executes a client application which provides user data to the host QQ602. The user data may be provided in reaction or response to the data received from the host QQ602. Accordingly, in step QQ616, the UE QQ606 may provide user data, which may be performed by executing the client application. In providing the user data, the client application may further consider user input received from the user via an input / output interface of the UE QQ606. Regardless of the specific manner in which the user data was provided, the UE QQ606 initiates, in step QQ618, transmission of the user data towards the host QQ602 via the network node QQ604. In step QQ620, in accordance with the teachings of the embodiments described throughout this disclosure, the network node QQ604 receives user data from the UE QQ606 and initiates transmission of the received user data towards the host QQ602. In step QQ622, the host QQ602 receives the user data carried in the transmission initiated by the UE QQ606.

[0248] One or more of the various embodiments improve the performance of OTT services provided to the UE QQ606 using the OTT connection QQ650, in which the wireless connection QQ670 forms the last segment. More precisely, the teachings of these embodiments may improve handling of computational models and thereby provide benefits such as reduced user waiting time, better responsiveness, and / or extended battery lifetime.

[0249] In an example scenario, factory status information may be collected and analyzed by the host QQ602. As another example, the host QQ602 may process audio and video data which may have been retrieved from a UE for use in creating maps. As another example, the host QQ602 may collect and analyze real-time data to assist in controlling vehicle congestion (e.g., controlling traffic lights). As another example, the host QQ602 may store surveillance video uploaded by a UE. As another example, the host QQ602 may store or control access to media content such as video, audio, VR or AR which it can broadcast, multicast or unicast to UEs. As other examples, the host QQ602 may be used for energy pricing, remote control of non-time critical electrical load to balance power generation needs, location services, presentation services (such as compiling diagrams etc. from data collected from remote devices), or any other function of collecting, retrieving, storing, analyzing and / or transmitting data. In some examples, 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. There may further be an optional network functionality for reconfiguring the OTT connection QQ650 between the host QQ602 and UE QQ606, in response to variations in the measurement results. The measurement procedure and / or the network functionality for reconfiguring the OTT connection may be implemented in software and hardware of the host QQ602 and / or UE QQ606. In some embodiments, sensors (not shown) may be deployed in or in association with other devices through which the OTT connection QQ650 passes; the sensors may participate in the measurement procedure by supplying values of the monitored quantities exemplified above or supplying values of other physical quantities from which software may compute or estimate the monitored quantities. The reconfiguring of the OTT connection QQ650 may include message format, retransmission settings, preferred routing etc.; the reconfiguring need not directly alter the operation of the network node QQ604. Such procedures and functionalities may be known and practiced in the art. In certain embodiments, measurements may involve proprietary UE signalling that facilitates measurements of throughput, propagation times, latency and the like, by the host QQ602. The measurements may be implemented in that software causes messages to be transmitted, in particular empty or ‘dummy’ messages, using the OTT connection QQ650 while monitoring propagation times, errors, etc.

[0250] Although the computing devices described herein (e.g., UEs, network nodes, hosts) may include the illustrated combination of hardware components, other embodiments may comprise computing devices with different combinations of components. It is to be understood that these computing devices may comprise any suitable combination of hardware and / or software needed to perform the tasks, features, functions and methods disclosed herein. Determining, calculating, obtaining or similar operations described herein may be performed by processing circuitry, which may process information by, for example, converting the obtained information into other information, comparing the obtained information or converted information to information stored in the network node, and / or performing one or more operations based on the obtained information or converted information, and as a result of said processing making a determination. Moreover, while components are depicted as single boxes located within a larger box, or nested within multiple boxes, in practice, computing devices may comprise multiple different physical components that make up a single illustrated component, and functionality may be partitioned between separate components. For example, a communication interface may be configured to include any of the components described herein, and / or the functionality of the components may be partitioned between the processing circuitry and the communication interface. In another example, non-computationally intensive functions of any of such components may be implemented in software or firmware and computationally intensive functions may be implemented in hardware.

[0251] In certain embodiments, some or all of the functionality described herein may be provided by processing circuitry executing instructions stored on in memory, which in certain embodiments may be a computer program product in the form of a non- transitory computer-readable storage medium. In alternative embodiments, some or all of the functionalities may be provided by the processing circuitry without executing instructions stored on a separate or discrete device-readable storage medium, such as in a hard-wired manner. In any of those particular embodiments, whether executing instructions stored on a non-transitory computer-readable storage medium or not, the processing circuitry can be configured to perform the described functionality. The benefits provided by such functionality are not limited to the processing circuitry alone or to other components of the computing device but are enjoyed by the computing device as a whole, and / or by end users and a wireless network generally.

[0252] Modifications and other embodiments of the disclosed embodiments will come to mind to one skilled in the art having the benefit of the teachings presented in the foregoing descriptions and the associated drawings. Therefore, it is to be understood that the embodiment(s) is / are not to be limited to the specific embodiments disclosed and that modifications and other embodiments are intended to be included within the scope of this disclosure. Although specific terms may be employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.

[0253] EMBODIMENTS

[0254] Embodiment A1

[0255] A method performed by a UE (10) for handling communication in a wireless communications network, comprising

[0256] - transmitting to a radio network node, a second indication indicating a performance metric of a first beam, wherein a format of the performance metric is based on a value of the performance metric, a number of beams reported, a beam ID and / or relative to another beam.

[0257] Embodiment A2

[0258] The method according to embodiment A1 , wherein the format of the performance metric is defined with a granularity, with an interval or range, and / or relative to another performance metric, and wherein the granularity, the interval or range, and / or the performance metric is based on the value of the performance metric, the number of beams reported, the beam ID and / or the other beam

[0259] Embodiment A3.

[0260] The method according to any of the embodiments A1-A2, wherein the performance metric comprises a probability that the first beam is a best beam out of a number of beams in terms of signal strength or quality.

[0261] Embodiment A4.

[0262] The method according to any of the embodiments A1-A3, wherein the UE further transmits a first indication indicating identity of the first beam

[0263] Embodiment B1

[0264] A method performed by a radio network node (12) for handling communication in a wireless communications network, comprising receiving from a UE (10), a second indication indicating a performance metric of a first beam, wherein a format of the performance metric is based on a value of the performance metric, a number of beams reported, a beam ID and / or relative to another beam.

[0265] Embodiment B2

[0266] The method according to embodiment B1 , wherein the format of the performance metric is defined with a granularity, with an interval or range, and / or relative to another performance metric, and wherein the granularity, the interval or range, and / or the performance metric is based on the value of the performance metric, the number of beams reported, the beam ID and / or the other beam Embodiment B3.

[0267] The method according to any of the embodiments B1-B2, wherein the performance metric comprises a probability that the first beam is a best beam out of a number of beams in terms of signal strength or quality.

[0268] Embodiment B4.

[0269] The method according to any of the embodiments B1-B3, wherein the radio network node further receives a first indication indicating identity of the first beam Embodiment B5.

[0270] The method according to any of the embodiments B1-B4, further comprising performing a network operation taking the second indication into account.

[0271] Embodiment C1

[0272] A UE (10) for handling communication in a wireless communications network, wherein the UE is configured to

[0273] - transmit to a radio network node, a second indication indicating a performance metric of a first beam, wherein a format of the performance metric is based on a value of the performance metric, a number of beams reported, a beam ID and / or relative to another beam.

[0274] Embodiment C2

[0275] The UE according to embodiment C1, wherein the UE is configured to perform the method according to any of the embodiments A2-A4.

[0276] Embodiment D1

[0277] A radio network node (12) for handling communication in a wireless communications network, wherein the radio network node is configured to receive from a UE (10), a second indication indicating a performance metric of a first beam, wherein a format of the performance metric is based on a value of the performance metric, a number of beams reported, a beam ID and / or relative to another beam.

[0278] Embodiment D2

[0279] The radio network node according to embodiment D1 , wherein the radio network node is configured to perform the method according to any of the embodiments B2-B5.

[0280] Embodiment E1 A computer program comprising instructions, which, when executed on at least one processor, cause the at least one processor to carry out the method according to any of the embodiments A1-A4, and B1-B5, as performed by the UE (10) and the radio network node (12), respectively. Embodiment F1

[0281] A computer readable storage medium, having stored thereon a computer program comprising instructions which, when executed on at least one processor, cause the at least one processor to carry out the method according to any of the embodiments A1-A4, and B1-B5, as performed by the UE (10) and the radio network node (12), respectively.

Claims

CLAIMS1. A method performed by a user equipment, UE, (10) for handling communication in a wireless communications network, comprising transmitting (714) to a radio network node (12), a second indication indicating a performance metric of a first beam, wherein a format of the performance metric is based on a value of the performance metric, a number of beams reported, a beam identity, ID, and / or relative to another beam.

2. The method according to claim 1 , wherein the format of the performance metric is defined with a granularity, with an interval or range, and / or relative to another performance metric, and wherein the granularity, the interval or range, and / or the performance metric is based on the value of the performance metric, the number of beams reported, the beam ID and / or the other beam3. The method according to any of the claims 1-2, wherein the performance metric comprises a probability that the first beam is a best beam out of a number of beams in terms of signal strength or quality.

4. The method according to any of the claims 1-3, wherein the UE (10) further transmits a first indication indicating identity of the first beam5. A method performed by a radio network node (12) for handling communication in a wireless communications network, the method comprising: receiving (723) from a user equipment, UE, (10), a second indication indicating a performance metric of a first beam, wherein a format of the performance metric is based on a value of the performance metric, a number of beams reported, a beam identity, ID, and / or relative to another beam.

6. The method according to claim 5, wherein the format of the performance metric is defined with a granularity, with an interval or range, and / or relative to another performance metric, and wherein the granularity, the interval or range, and / or the performance metric is based on the value of the performance metric, the number of beams reported, the beam ID and / or the other beam7. The method according to any of the claims 5-6, wherein the performance metric comprises a probability that the first beam is a best beam out of a number of beams in terms of signal strength or quality.

8. The method according to any of the claims 5-7, wherein the radio network node further receives a first indication indicating identity of the first beam.

9. The method according to any of the claims 5-8, further comprising:- performing (724) a network operation taking the second indication into account.

10. A user equipment, UE, (10) for handling communication in a wireless communications network, wherein the UE is configured to- transmit to a radio network node (12), a second indication indicating a performance metric of a first beam, wherein a format of the performance metric is based on a value of the performance metric, a number of beams reported, a beam identity, ID, and / or relative to another beam.

11. The UE according to claim 10, wherein the UE is configured to perform the method according to any of the claims 2-4.

12. A radio network node (12) for handling communication in a wireless communications network, wherein the radio network node is configured to receive from a user equipment, UE, (10), a second indication indicating a performance metric of a first beam, wherein a format of the performance metric is based on a value of the performance metric, a number of beams reported, a beam identity, ID, and / or relative to another beam.

13. The radio network node according to claim 12, wherein the radio network node is configured to perform the method according to any of the claims 6-9.

14. A computer program comprising instructions, which, when executed on at least one processor, cause the at least one processor to carry out the method according to any of the claims 1-4, and 5-9, as performed by the UE (10) and the radio network node (12), respectively.

15. A computer readable storage medium, having stored thereon a computer program comprising instructions which, when executed on at least one processor, cause the at least one processor to carry out the method according to any of the claims 1-4, and 5-9, as performed by the UE (10) and the radio network node (12), respectively.

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