WO2023211350A1 - User equipment assistance information for improved network beam predictions - Google Patents

Abstract

A method (700) by a user equipment, UE, (112) includes receiving (702) at least one beam from a network node (110) and transmitting (704), to the network node, beam prediction assistance information, BPAI, associated with the at least one beam. For example, the BPAI may include any one or more of: an index of an Rx beam; an indication of whether the at least one measurement was subject of or to blockage; and at least one uncertainty estimate associated with the at least one measurement.

Description

USER EQUIPMENT ASSISTANCE INFORMATION FOR IMPROVED NETWORK BEAM

PREDICTIONS

TECHNICAL FIELD

The present disclosure relates, in general, to wireless communications and, more particularly, systems and methods including User Equipment (UE) assistance information for improved network beam predictions.

BACKGROUND

As justification for the Further Enhanced Multiple Input-Multiple Output (FeMIMO) for Release 17, it was highlighted that “FR2 require more aggressive reduction in latency and overhead - not only for intra-cell, but also for L1/L2 centric inter-cell mobility. This also includes reducing the occurrence of beam failure events.” The goal of reducing the overhead and robustness were also reflected in the objective of the System Information (SI). As an outcome of the Release 17 SI, for example, a unified Transmission Configuration Indication (TCI) state is one improvement solution for reducing the signaling overhead. However, the potential for further improving on robustness or overhead reduction using Artificial Intelligence (AI)/Machine Learning (ML) is currently explored in the Release 17 Study item for Al for air-interface.

One example AI/ML-model outlined in the Al for air-interface includes predicting the channel in respect to a beam for a certain time-frequency resource. The expected performance of such predictor depends on several different aspects, for example time/frequency variation of channel due to UE mobility or changes in the environment. Due to the inherit correlation in time, frequency and the spatial domain of the channel, an ML-model can be trained to exploit such correlations. The spatial domain can comprise of different beams, where the correlation properties partly depend on how the antennas of the gNodeB (gNB) forms the different beams and how the UE forms the receiver beams.

For the robustness use case, coverage outage is typically an effect by large number of transitions from Line-of-Sight (LOS)-> Non-Line-of-Sight (NLOS) (for example, turning around comers) or blockers in the environment (both fixed blockers and dynamic blockers such as moving objects). Previously, a method was disclosed for enabling a UE to predict future beam values based on historical values. See, WO2020226542 (Al), NETWORK NODE, USER EQUIPMENT AND METHODS FOR HANDLING SIGNAL QUALITY VARIATIONS, November 12, 2020. Based on received device data from measurement reports, the network can leam, for example, which sequences of signal quality measurements (e.g., Reference Signal Received Power (RSRP) measurements) lead to large signal quality drop events. For example, FIGURE 1 illustrates a signal quality drop event where two UEs moving on similar paths turn around the same comer. Specifically, in an example scenario, a first UE (UE1), marked by dashed line, is the first to turn around the comer and experience a large signal quality drop. The main idea is to mitigate the drop of the second UE (UE2), which is marked by a solid line, by using learning from the first UE’s experiences.

A learning procedure can be enabled, for example, by dividing periodically reported RSRP data into a training and prediction window. More specifically, the learning can be done by feeding RSRP in ti, ... , t_n into a machine learning model (e.g. neural network), and then leam the RSRP in t_n+i, t_n+2. After the model is trained, the network can then predict future signal quality values, the signal quality prediction can then be used to avoid radio-link failure, or beam failure, by: initiating inter-frequency handover, setting handover/reselection parameters, pre-emptively performing candidate beam selection to avoid beam failure, and hanging device scheduler priority such as, for example, scheduling a device when the expected signal quality is good.

There currently exist certain challenge(s), however. For example, according to previous techniques, method(s) for a network node (NW) to predict signal quality values associated to a certain reference signal (e.g., Channel State Information-Reference Signal (CSI-RS), Synchronization Signal Block (SSB)) have been made by using the reported radio measurements from the UEs. Then, the NW can utilize learnings from one device reported measurements for a subsequent second device so as, for example, to predict an upcoming beam outage (i.e., beam failure) or radio link failure. However, with the increased capabilities in advanced antennas at the UE, the UE can now be equipped with multiple receive antenna panels and/or form receiver beams in a certain direction, leading to increased challenges in creating a trajectory fingerprint for the UE that can be representative for subsequent UEs in order to mitigate a beam failure or radio link failure. Another challenge in creating a representative trajectory of radio fingerprints is the presence of dynamic blockers (moving objects or human body), these blockers will not be present for subsequent UEs and can create a non-representative trajectory fingerprint. Moreover, there is no known information relating to what the UE is using as its receiver beam, making it hard to do such predictions also for the same UE-vendor.

In an example scenario that includes UEs with various capabilities in receiver beam reception, a UE with a more advanced antenna (such as, for example, an antenna with 16 dual polarized virtual antenna ports) may be able to achieve a higher antenna gain in comparison to a UE with a less advanced antenna (such as, for example, an antenna with 2 dual polarized virtual antenna ports). As a result, the signal quality values from the more advanced antenna cannot be directly used for beam predictions for the less advanced antenna. This could include the example of the two UEs moving along the trajectory as shown in FIGURE 1.

FIGURE 2 shows an example signal quality curve for UEs of FIGURE 1 where UE1 and an additional UE (UE3) are assumed to be equipped with a low-end antenna and UE 2 is equipped with a high-end antenna. FIGURE 2 shows the almost constant higher signal quality for UE2, and that all UEs experience an outage at tZ, due to turning around the comer as shown in FIGURE 1.

Another challenge in creating a representative trajectory of radio fingerprints is the presence of dynamic blockers (e.g., moving objects or human body), which may be experienced by UE 2 at tl as shown in FIGURE 2. This would not be present for subsequent UEs, which can create an inaccurate trajectory fingerprint, leading to bad prediction performance. However, capable devices can be able to estimate the presence of dynamic blockers in the environment, such as the human body for handheld devices. Such information is, however, not disclosed to the network node.

SUMMARY

Certain aspects of the disclosure and their embodiments may provide solutions to these or other challenges. For example, according to certain embodiments, methods and systems are provided for configuring the UE to include a beam prediction assistance information (BP Al) when reporting one or more signal quality value(s) associated to one or more beam measurement(s). The BPAI is used by the NW to create a representative radio fingerprint trajectory (compensated for blockers of antenna gain, for example), enabling the NW to perform improved beam predictions and mitigate potential beam failures.

According to certain embodiments, a method by a UE includes receiving at least one beam from a network node and transmitting, to the network node, BPAI associated with the at least one beam. According to certain embodiments, a UE is adapted to receive at least one beam from a network node and transmit, to the network node, BPAI associated with the at least one beam

According to certain embodiments, a method by a network node includes transmitting, to a UE, at least one beam and receiving, from the UE, BPAI associated with the at least one beam.

According to certain embodiments, a network node is adapted to transmit, to a UE, at least one beam and receive, from the UE, BPAI associated with the at least one beam.

Certain embodiments may provide one or more of the following technical advantage(s). For example, certain embodiments may provide a technical advantage of enabling the gNB to develop more general algorithms or leam more general ML models for beam predictions. Without the addition of the disclosed techniques and methods, the gNB would need to develop more algorithms or train more models, possibly for each unique UE-vendor or for each UE beamforming capability. Thus, a technical advantage of certain embodiments may include reducing the number of algorithms/models needed at the gNB.

Another technical advantage of certain embodiments may include enabling faster training of such algorithm/model. For example, certain embodiments may exhibit one or more of the following technical advantages:

The beam prediction algorithm or ML-model can be valid both for one UE-chipset with a first antenna design and to another UE-chipset with a second antenna design by, for example, receiving information of the UE antenna gain associated to the beam measurement report(s).

The algorithm/model can compensate for UE orientation information in the radio measurement, to create similar radio fingerprint trajectories for UEs moving on the same path.

Certain embodiments compensate for dynamic blockers (i.e. information that is not static and cannot be used to leam any representative fingerprint trajectories) by including such information in the UE reported BPAI.

Another technical advantage of certain embodiments may include improving the performance for UE-vendor specific beam predictions by introducing beam information such as the used Receiver-beam (RX-beam) identifier in the UE report.

Another technical advantage of certain embodiments may include enabling the network to train more accurate algorithms/models that can perform beam predictions and forecast a future beam outage/failure that can be used for improving radio performance such as: mitigating beam failure by initiating an inter-frequency handover prior to expected beam outage; buffering more UE data prior to predicted outage - for example by increase the UE scheduling priority; and/or mitigating beam failure by beam management configurations (such as allocate more CSI-RS resources to prevent such beam failure)

Other advantages may be readily apparent to one having skill in the art. Certain embodiments may have none, some, or all of the recited advantages.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the disclosed embodiments and their features and advantages, reference is now made to the following description, taken in conjunction with the accompanying drawings, in which:

FIGURE 1 illustrates two devices moving on similar paths;

FIGURE 2 illustrates an example on the various capabilities in RX-beam reception;

FIGURE 3 illustrates an example signal quality curve demonstrating compensation for signal quality for improved prediction, according to certain embodiments;

FIGURE 4 illustrates example signal quality curves and for single TRP and multiple TRPs, respectively, according to certain embodiments;

FIGURE 5 illustrates an example communication system, according to certain embodiments;

FIGURE 6 illustrates an example UE, according to certain embodiments;

FIGURE 7 illustrates an example network node, according to certain embodiments;

FIGURE 8 illustrates a block diagram of a host, according to certain embodiments;

FIGURE 9 illustrates a virtualization environment in which functions implemented by some embodiments may be virtualized, according to certain embodiments;

FIGURE 10 illustrates a host communicating via a network node with a UE over a partially wireless connection, according to certain embodiments;

FIGURE 11 illustrates an example method by a UE, according to certain embodiments; and

FIGURE 12 illustrates an example method by a network node, according to certain embodiments. DETAILED DESCRIPTION

Some of the embodiments contemplated herein will now be described more fully with reference to the accompanying drawings. Embodiments are provided by way of example to convey the scope of the subject matter to those skilled in the art.

As used herein, ‘node’ can be a network node or a UE. Examples of network nodes are NodeB, base station (BS), multi-standard radio (MSR) radio node such as MSR BS, eNodeB (eNB), gNodeB (gNB), Master eNB (MeNB), Secondary eNB (SeNB), integrated access backhaul (IAB) node, network controller, radio network controller (RNC), base station controller (BSC), relay, donor node controlling relay, base transceiver station (BTS), Central Unit (e.g. in a gNB), Distributed Unit (e.g. in a gNB), Baseband Unit, Centralized Baseband, C-RAN, access point (AP), transmission points, transmission nodes, Remote Radio Unit (RRU), Remote Radio Head (RRH), nodes in distributed antenna system (DAS), core network node (e.g. Mobile Switching Center (MSC), Mobility Management Entity (MME), etc.), Operations & Maintenance (O&M), Operations Support System (OSS), Self Organizing Network (SON), positioning node (e.g. E- SMLC), etc.

Another example of a node is user equipment (UE), which is a non-limiting term and refers to any type of wireless device communicating with a network node and/or with another UE in a cellular or mobile communication system. Examples of UE are target device, device to device (D2D) UE, vehicular to vehicular (V2V), machine type UE, MTC UE or UE capable of machine to machine (M2M) communication, Personal Digital Assistant (PDA), Tablet, mobile terminals, smart phone, laptop embedded equipment (LEE), laptop mounted equipment (LME), Unified Serial Bus (USB) dongles, etc.

In some embodiments, generic terminology, “radio network node” or simply “network node (NW node)”, is used. It can be any kind of network node which may comprise base station, radio base station, base transceiver station, base station controller, network controller, evolved Node B (eNB), Node B, gNodeB (gNB), relay node, access point, radio access point, Remote Radio Unit (RRU) Remote Radio Head (RRH), Central Unit (e.g., in a gNB), Distributed Unit (e.g., in a gNB), Baseband Unit, Centralized Baseband, C-RAN, access point (AP), etc.

The term radio access technology (RAT), may refer to any RAT such as, for example, Universal Terrestrial Radio Access Network (UTRA), Evolved Universal Terrestrial Radio Access Network (E-UTRA), narrow band internet of things (NB-IoT), WiFi, Bluetooth, next generation RAT, New Radio (NR), 4^th Generation (4G), 5^th Generation (5G), etc. Any of the equipment denoted by the terms node, network node or radio network node may be capable of supporting a single or multiple RATs.

Herein, measurements on one or more downlink (DL) beams corresponds to measurements of one or more measurement quantities, e.g. RSRP, and/or Reference Signal Received Quality (RSRQ), and/or Received Signal Strength Indicator (RSSI), and/or Signal Interference to Noise Ratio (SINR), measured on one or more Reference Signal(s) (RS(s)), e.g., Synchronization Signal Block (SSB), CSI-RS, Cell-specific Reference Signal (CRS), Discovery Reference Signal (DRS), Demodulation Reference Signal (DMRS), wherein the one or more measured RS(s) may be transmitted in different spatial direction(s), which may be referred as different beams. For example, a measurement on a beam may correspond to a Synchronization Signal Reference Signal Received Power (SS-RSRP) on an SSB resource index X of a cell Y, wherein the SSB is transmitted on SSB resource index X in a beam/ spatial direction. More examples of measurements may be the ones in 3GPP TS 38.215, such a SS-RSRQ, SS-SINR, CSI-RSRP, CSI-RSRQ, CSI- SINR. Measurements on one or more beams may be obtained during a measurement period or evaluation period, as defined in 3GPP TS 38.133.

According to certain embodiments, methods and systems at the network (e.g., by the network node) may include one or more of the following:

• receiving a capability indication from the UE comprising if the UE is capable of providing BP Al related to its beam measurement report, where the BP Al is used for the NW to predict future beam quality values for the UE by e.g., using an ML- model, or for the NW to develop/train/improve the beam prediction algorithm (e.g., training/r etraining the ML-model);

• configuring a request for the UE to report BPAI related to one or more beam measurement(s);

• receiving the BPAI from the UE;

• in case a beam prediction algorithm/ML-model is developed/trained at the NW side: o performing prediction associated to future signal quality values of one or more beams for the UE using a beam prediction algorithm/ML-model; and/or o setting network parameters associated to the model prediction (e.g., transmitting an indication/configuration for the UE to take some actions in the future time slot(s), e.g., intra/inter-frequency handover, or setting scheduling priorities for the UE); and/or

• performing training/updating of the beam prediction algorithm/ML-model using the received BPAI and observed UE radio fingerprint trajectory;

According to certain embodiments, methods and systems at or by the UE may include one or more of the following:

• indicating its capability of providing BPAI associated to one or more beam measurement(s);

• receiving configuration/request from the NW to provide BPAI associated to one or more beam measurement report(s);

• performing beam measurements, and estimate BPAI;

• reporting beam measurements and BPAI; and/or

• optionally, receiving a new network event related to the transmitted BPAI (e.g., receiving a parameter initiating an inter-frequency handover).

Measurement Event

According to certain embodiments, UEs in LTE and NR are required to monitor the DL link quality based on the RS(s), perform measurements on the RSs (e.g., SS-RSRP, SS-RSRQ, SS- SINR for NR cells) of the identified cells, and report the measured samples to the NW, according to the requirements specified in the 3GPP TS 36.133 for LTE and 3GPP TS 38.133 for NR, respectively.

In a particular embodiment, the UE can report RSRP/SINR/RSRQ using existing NR measurement events, described in the Section 9 in 3GPP TS 38.133, for example, using periodic reporting, or event triggered reporting.

In a particular embodiment, the UE sends a measurement report when the condition(s) as configured by the network are fulfilled. These conditions can be time-based (e.g., periodic reporting) or measurement-based (e.g., event triggered reporting). The event triggered reporting is associated with RSRP, RSRQ, or SINR related measurements. The measurements used for evaluating the event triggering criterion are Layer 3 (L3) filtered.

One type of measurement report is the report of beam measurement information. The reportType can be set to eventTriggered or periodical. According to certain embodiments, the measurement information to be included can be is based on SS/PBCH block (SSB) or CSI-RS. In a particular embodiment, L3 (RRC) beam measurement information is expanded to include BPAI so that beam failure can be anticipated and avoided as much as possible.

According to certain embodiments, for beam management, a UE can be configured to report Layer 1-RSRP (Ll-RSRP) or/and Layer 1-SINR (Ll-SINR) for each one of up to four different CSI-RS/SSB beams. In particular embodiments, the UE measurement report is sent either over Physical Uplink Control Channel (PUCCH) or Physical Uplink Shared Channel (PUSCH) to the NW, depending on the CSI reporting types (periodic CSI reporting, semi-persistent CSI reporting, or aperiodic CSI reporting.)

In a particular embodiment, the CSI report for beam management is expanded to include at least part of the BPAI (e.g., the BPAI that changes dynamically). For beam failure recovery, a UE may transmit a Beam Failure Report (BFR) Medium Access Control-Control Element (MAC CE), which contains beam failure recovery related information (e.g., index of the cell where the UE detected a beam failure and suggested candidate beam/RS Identifier (RS ID)). In a particular embodiment, the BFR MAC CE for beam failure recovery is expanded to include at least part of the BPAI (e.g., the presence of blockers).

BPAI

According to various embodiments, the UE includes the BPAI when reporting according to the higher layer measurement configuration, beam management reporting configuration, or/and beam failure reporting procedure. The BPAI could include one or more of: o Antenna Gain'. For example, the UE reports the estimated antenna gain component of the signal quality measurement. More specifically, the UE may translate the estimated value into what it had been if it were using an omnidirectional antenna. Thus, the UE deduces the antenna gain component of the signal quality value.

■ In one particular embodiment, for example, during UE capability signaling, the UE indicates the support for N different beam types, and each beam type is associated with a maximum antenna gain and a beam type index. Then, for each reported beam (Dl-RS index) in a beam report, the UE indicates the beam type index associated with the UE spatial filter used to receive the reported DL-RS. ■ In one particular embodiment, the UE reports a “UE antenna gain compensated RSRP” for each reported beam (DL-RS index) in a beam report. The “UE antenna gain compensated RSRP” can, for example, be calculated as “normal RSRP” (as specified in 3GPP TS 38.133) minus the maximum antenna gain for the spatial filter used when receiving the indicated DL-RS. In one further particular embodiment, the “UE antenna gain compensated RSRP” can be used instead of the normal RSRP. In a further particular embodiment, other factors such as, for example, estimated hand/body blockage loss is also included in the “UE antenna gain compensated RSRP”. In this case, the “UE antenna gain compensated RSRP” can be calculated as “normal RSRP” (as specified in 3GPP TS 38.133) minus the maximum antenna gain for the spatial filter used when receiving the indicated DL-RS minus the estimated hand/body blockage loss. The signal quality translated to a certain reference direction'. For example, the UE may report the estimated quality if the UE was facing north/south or towards the sky direction in an earth-bounded coordinate system. The UE RX-angle for the measurement event, and the expected antenna gain for such angle'.

■ The UE may report both horizontal and vertical beamforming (i.e., fulldimensional MIMO). For example, the UE may report the angle and related info (e.g., main lobe, beam width), where azimuth angle indicates the horizontal beam direction, and elevation angle indicates the vertical beam direction.

■ The UE may, in one particular embodiment, indicate its antenna diagram upon connection. The NW can then deduce the antenna gain given the UE reported RX-angle. Estimate of whether the measurement was subject of blockage'.

■ In a particular embodiment, the UE may report the probability that the blockage that is expected to be static (wall or fixed object).

■ In a particular embodiment, the UE may report the probability of dynamic blockage, such as the blocking due to body (face/hand) for smartphones. • The UE may additionally or alternatively indicate, if capable, a forecast of how long such blockage is expected.

• In a particular embodiment, estimated hand/body blockage loss for the UE is signaled during UE capability signaling. In this case, a single flag could be included in the beam report to indicate if hand/body blockage has occurred or not, and the gNB can then compensate for that when receiving the reported RSRP included in the beam report. Estimate of the signal quality of the measurement event if the UE was not subject to dynamic blockage at the given location Estimate of probability that the UE is located indoors

■ Using radio-measurements (e.g. analyze delay spread)

■ Non-radio measurements such as light sensors, which can be used to detect whether the UE is indoors. For example, the UE uses the light sensor/camera to measure the ambient light, which is used to classify whether the UE is indoors or outdoors. The sensor may, for example, measure the light intensity, but it may also analyze the spectral properties of the ambient light to identify characteristics of light bulbs, LEDs, fluorescent light, halogen lights, or other light sources typically found indoors. Thus, an indication of whether the UE has moved from outdoor to indoor or vice versa may be estimated using the light sensors. Time stamp of the measurement UE uncertainty estimates for the measurement For example, some UEs may estimate a certain reference signal better than what is required by the 3 GPP specification The set of predicted SS/PBCH block indexes or CSI-RS indexes in order of decreasing sorting quantity : It’s noted that in the existing specification the reported SS/PBCH block indexes or CSI-RS indexes are based on link quality measurement (LI -RSRP) of previously transmitted DL signal, not based on prediction. For each reported SSB index or CSI-RS index: ■ A set of actual measurement quantities (e.g., RSRP, RSRQ, SINR) in Ni evaluation periods that occurred right before the reporting time, where /Vz>= I . That is, measurement based on previously transmitted signal.

■ A set of predicted measurement quantities (e.g., RSRP, RSRQ, SINR) in N2 projected evaluation periods that are right after the reporting time, where N2>=1. That is, hypothetical measurement values predicted by the UE.nnel information (such as doppler information or delay spread)

■ In a particular embodiment, when the UE is configured to include doppler and/or delay information for an SSB/CSI-RS in a beam report, the UE uses the TRS that is QCL with the SSB/CSI-RS to derive the doppler and/or delay information. ice orientation in earth-bounded coordinates

■ The orientation of the device can be estimated using the accelerometer and the magnetometer. The accelerometer gives the device’s acceleration in X. Y, and Z coordinates (in respect to the device coordinate system). Since the accelerometer measures gravity as acceleration, an estimate of the z- component (in earth-bounded coordinates) can be extracted using the accelerometer. The earth-bounded x/y- orientation can be estimated using the magnetometer, where the magnetometer’s measurements are based on the earth’s magnetic field. ice received antenna panel configuration

■ In a particular embodiment, during UE capability signaling, the UE indicates the number of UE panels supported by the UE, where each UE panel is associated with a set of UE panel capabilities and a UE panel identifier (UE panel ID). In this case, the UE includes a UE panel ID for each beam in a beam report, and the gNB then knows the associated UE panel properties for the reported beam. The UE panel properties can for example be one or more of:

• number TX chains,

• number RX chains,

• number antenna elements, max gam, maximum output power, • single-polarize or dual-polarized, and/or

• pointing direction of the UE panel (relative a UEs local coordination system). o Device transmit antenna panel configuration o Device location o Mobility information (e.g. speed, velocity, rotation) o Information relating to whether the RSRP has been filtered over more than one time instances or not (number of filtered time instances used when calculating the RSRP can also be indicated) o The age of the SRSP measurements'. For example, the UE may indicate if the reported RSRP measurement is from the last SSB transmission or from a previous older SSB transmission (and potentially how many SSB transmissions ago)

In a particular embodiment, a new beam report is introduced in NR, where the beam report indicates to the UE to include (per reported SSB) one RSRP for each of the N UE panels that UE is equipped with. In a particular embodiment, the UE is mandated to use a wide beam per UE panel when calculating the RSRP per UE panel. For example, assume that the UE is equipped with three UE panels and is triggered with the new beam report. Then the UE will perform measurements using a wide beam per UE panel during three different SSB bursts (assuming the UE can receive with one UE panel at a time), and then report the N best SSBs, where each reported SSB is associated with one RSRP for each UE panel. In this way, the gNB can get reliable information about the channel between the gNB and the UE from all possible direction of the UE.

In a particular embodiment, the BPAI could also include information, that would enable improved learning also when training a model for a device-vendor specific model, for example: o For example, in a particular embodiment, the UE may indicate an index of its RX- beam. This would allow the NW to optimize for a certain chips et/firmware version, but not provide any general adaptation o As another example, in a particular embodiment, the UE may indicate a state identifier that comprises a compressed version of UE properties. The state identifier is used by the NW to use ML techniques for learning the how such state can be utilized in the beam predictor. The NW has no prior knowledge of the meaning of said state (it is not human interpretable), other than it relates to information that the NW can use to learn to perform beam predictions Measurement Reporting of BPAI

RRC based measurement reporting of BPAI

In a particular embodiment, the BPAI is reported via RRC message.

For RRC in connected mode (RRC CONNECTED), the following is an example of describing the reporting procedure. In the following, value of Ni and N2 can be: (a) a predefined value; or (b) a configured value via a RRC parameter.

The parameter TBMR provides the time period for estimating measurements for reporting beam measurement. According to various particular embodiments, the value of parameter TBMR is:

(a) A time period (in ms) defined as a function of SSB periodicity (TSSB) if the beam measurement is SSB based, or a function of the periodicity (TCSI-RS) of the periodic CSI with the given CSI index if the beam measurement is CSI based.

(b) A time period (in ms) defined as a function of the evaluation period of beam failure detection (BFD), i.e., TEvaiuate_BFD_ssB (ms) for SSB based beam measurement report and TEvaluate_BFD_CSI-RS (ms) for CSI-RS based, as defined in 3GPP TS 38.133.

(c) A time period (in ms) defined as a function of the evaluation period of candidate beam detection (CBD), i.e., TEvaiuate_CBD_ssB (ms) for SSB based beam measurement report and TEvaiuate_CBD_csi-RS (ms) for CSI-RS based.

It is noted that parameter TBMR value may vary with other parameters, including: frequency range (e.g., Frequency Range 1 (FR1) vs Frequency Range 2 (FR2)), Subcarrier Spacing (SCS) of the carrier, presence/absence of measurement gap when the beam measurement is performed.

For the Ni periods of TBMR (ms) before the timing of the measurement report, these can be Ni consecutive periods in time, or Ni periods in time which are consecutive except that the UE skips certain gaps when valid measurement is not feasible (e.g., measurement gaps).

In a particular embodiment, Section 5.5.5.2 of3GPP TS 38.133 may be modified as follows (with modifications shown with underlining):

5.5.5.2 Reporting of beam measurement information

For beam measurement information to be included in a measurement report the UE shall:

1 > if reportType is set to eventTriggered'.

2> consider the trigger quantity as the sorting quantity if available, otherwise RSRP as sorting quantity if available, otherwise RSRQ as sorting quantity if available, otherwise SINR as sorting quantity;

1 > if reportType is set to periodical. 2> if a single reporting quantity is set to true in reportQuantityRS-Indexes,'

3> consider the configured single quantity as the sorting quantity;

2>else:

3> if rsrp is set to true,'

4> consider RSRP as the sorting quantity;

3>else:

4> consider RSRQ as the sorting quantity; l>set rsIndexResults to include up to maxNrofRS-IndexesToReport SS/PBCH block indexes or CSI-RS indexes in order of decreasing sorting quantity as follows:

2> if the measurement information to be included is based on SS/PBCH block:

3> include within resultsSSB-Indexes the index associated to the best beam for that SS/PBCH block sorting quantity and if absThreshSS- BlocksConsolidation is included in the VarMeasConflg for the measObject associated to the cell for which beams are to be reported, the remaining beams whose sorting quantity is above absThreshSS- BlocksConsolidatiorr,

3> if includeBeamMeasurements is set to true, include the SS/PBCH based measurement results for the quantities in reportQuantityRS-Indexes for each SS/PBCH block index;

3>if includeMultipleBeamMeasurements is set to true, include Ni SS/PBCH based measurement results for the quantities in reportQuantityRS-Indexes for each SS/PBCH block index, where the Ni measurement results are obtained from the Ni periods of TBMR (ms) before the timing of the measurement report;

3> if includeBeamMeasurementsPrediction is set to true, include N2 SS/PBCH based measurement results for the quantities in reportQuantityRS-Indexes for each SS/PBCH block index, where the N2 measurement results are the prediction by UE for the N2 periods of TBMR (ms) after the timing of the measurement report;

2>else if the beam measurement information to be included is based on CSI- RS: 3> include within resultsCSI-RS-Indexes the index associated to the best beam for that CSI-RS sorting quantity and, if absThreshCSI-RS- Consolidation is included in the VarMeasConflg for the measObject associated to the cell for which beams are to be reported, the remaining beams whose sorting quantity is above absThreshCSI-RS-Consolidatiorr,

3> if includeBeamMeasurements is set to true, include the CSI-RS based measurement results for the quantities in reportQuantityRS-Indexes for each CSI-RS index.

3>if includeMultipleBeamMeasurements is set to true, include Ni CSI-RS based measurement results for the quantities in reportOuantityRS-Indexes for each CSI-RS index, where the Ni measurement results are obtained from the Ni periods of TBMR (ms) before the timing of the measurement report;

3> if includeBeamMeasurementsPrediction is set to true, include N2 CSI-RS based measurement results for the quantities in reportOuantityRS-Indexes for each CSI-RS index, where the N2 measurement results are the prediction by UE for the N2 periods of TBMR (ms) after the timing of the measurement report;

In a particular embodiment, for RRC in idle or inactive mode (RRC IDLE or RRC INACTIVE), the reporting procedure described in Section 5.7.8.2a of 3GPP TS 38.331 may be modified as follows (with modifications shown with underlining):

5.7.8.2a Performing measurements

When performing measurements on NR carriers according to this clause, the UE shall derive the cell quality as specified in 5.5.3.3 and consider the beam quality to be the value of the measurement results of the concerned beam, where each result is averaged as described in TS 38.215 [9],

While in RRC IDLE or RRC INACTIVE, and T331 is running, the UE shall:

1> perform the measurements in accordance with the following: >if beamMeasConflgldle is included in the associated entry in measIdleCarrierListNR and if UE supports idlelnactiveNR- MeasBeamReport for the FR of the carrier frequency indicated by carrierFreq within the associated entry, for each cell in the measurement results:

6> derive beam measurements based on SS/PBCH block for each measurement quantity indicated in reportQuantityRS-Indexes , as described in TS 38.215 [9];

6> if the reportQuantityRS-Indexes is set to rsrq:

7> consider RSRQ as the beam sorting quantity;

6>else:

7> consider RSRP as the beam sorting quantity;

6> set resultsSSB-Indexes to include up to maxNrofRS- IndexesToReport SS/PBCH block indexes in order of decreasing beam sorting quantity as follows:

7> include the index associated to the best beam for the sorting quantity and if absThreshSS-BlocksConsolidation is included, the remaining beams whose sorting quantity is above absThreshSS-BlocksConsolidation,'

6> if the includeBeamMeasurements is set to true'.

7> include the beam measurement results as indicated by reportQuanti tyRS-Indexes ;

6> if includeMultipleBeamMeasurements is set to true, include Ni SS/PBCH based measurement results for the quantities in reportQuantityRS-Indexes for each SS/PBCH block index, where the Ni measurement results are obtained from the Ni periods of TBMR (ms) before the timing of the measurement report; 6>if includeBeamMeasurementsPrediction is set to true, include N2 SS/PBCH based measurement results for the quantities in reportQuantityRS-Indexes for each SS/PBCH block index, where the N2 measurement results are the prediction by UE for the N2 periods of TBMR (ms) after the timing of the measurement report; > if, as a result of the procedure in this subclause, the UE performs measurements in one or more carrier frequency indicated by measIdleCarrierListNR or measIdleCarrierListEUTRA'.

3> store the cell measurement results for RSRP and RSRQ for the serving cell within measResultServingCell in the measReportldleNR in VarMeasIdleReport .

3> if the VarMeasIdleConflg includes the measIdleCarrierListNR and it contains an entry with carrierFreq set to the value of the serving frequency:

4> if beamMeasConflgldle is included in that entry, and if the UE supports idlelnactiveNR- MeasBeamReport for the FR of the serving cell:

5> derive beam measurements based on SS/PBCH block for each measurement quantity indicated in reportQuantityRS-Indexes, as described in TS 38.215 [9];

5>if the reportQuantityRS-Indexes is set to rsrq:

6> consider RSRQ as the beam sorting quantity;

5>else:

6> consider RSRP as the beam sorting quantity; 5>set resultsSSB-Indexes to include up to maxNrofRS- IndexesToReport SS/PBCH block indexes in order of decreasing beam sorting quantity as follows:

6> include the index associated to the best beam for the sorting quantity and if absThreshSS-BlocksConsolidation is included in SIB2 of serving cell, the remaining beams whose sorting quantity is above absThreshSS-BlocksConsolidation,'

5> if the includeBeamMeasurements is set to true:

6> include the beam measurement results as indicated by reportQuanti tyRS-Indexes ;

6> if includeMultipleBeamMeasurements is set to true, include Ni SS/PBCH based measurement results for the quantities in reportQuantityRS-Indexes for each SS/PBCH block index, where the Ni measurement results are obtained from the Ni periods of TBMR (ms) before the timing of the measurement report;

6>if includeBeamMeasurementsPrediction is set to true, include N2 SS/PBCH based measurement results for the quantities in reportQuantityRS-Indexes for each SS/PBCH block index, where the N2 measurement results are the prediction by UE for the N2 periods of TBMR (ms) after the timing of the measurement report;

Network Node Actions upon BP Al Reception

In a particular embodiment, after receiving a certain number of samples including the BPAI, the NW starts training a model or develops/updates an algorithm, capable of predicting a channel associated to a certain beam. Training samples heavily subject to dynamic blockers as part of the BPAI may be set to a lower importance while training since such samples are not representative for a subsequent UE and may lead to suboptimal training.

Example ML models to predict the future signal quality value can comprise of decision trees, random forest, feed forward neural networks, autoregressive models, or convolutional neural networks. The input for the model can comprise of feeding signal quality values in //.... . t_n into a machine learning model (e.g. Neural network), and then learn the signal quality in t_n+i,t_n+2..

Based on the predicted value, the NW may, for example, set one or more of the following parameters related to one or more of: o handover decision (i.e., configure inter-freq, handovers); o scheduling decision (i.e., schedule UE earlier based on the predicted quality drop, ask UE to skip monitoring PDCCH in the future from

due to the blockage or entering the comer if UE includes its location info or other related info within BPAI); o link-adaptation (i.e., set more restrictive parameters in case of a forecasted signal quality drop); and/or o change beam management parameters (i.e., for example allocate more CSI-RS resources for a UE expecting a large drop in quality and/or allocate CSI-RS resources transmitted from another transmission point).

Capability Indication

According to certain embodiments, the UE indicates to the NW its capabilities in including one or more of the BPAI information elements listed above.

In a particular embodiment, a BPAI reporting parameter is introduced as a new UE capability parameter to enable a NW to request the information from a UE about its capability of reporting the BPAI to the NW. This BPAI reporting parameter that is contained in UE capability reporting may further include part of the BPAI information that is relatively static (e.g., transmit/receive antennal panel configuration, maximum number of predicted values that are supported by the UE, the maximum number of perdition time horizon, etc.). For the part of the BPAI information that may change dynamically, the info can be reported over RRC message, PUCCH/PUSCH, MAC CE, etc., as descripted in the precious sections.

In one example, multiple UEs are moving along a similar trajectory (similar to that described above with respect to FIGURE 1) but on different occasions and are subject to a large signal quality drop at time t2. The NW node is interested in training an ML model to predict such occurrences. The UE 2 is equipped with a more advanced antenna in relation to UE 1 or 3, but it is pruned to a dynamic blocker at time tl. By using a UE reported BPAI, the network can estimate a compensated signal quality value and use the learning to prevent the drop of this UE at time t2. For example, the NW may use learnings for UE 1 and 2 to predict for UE3. UE 2 could for instance estimate and report in the BP Al its predicted signal quality if there was no blocker, or the NW can use information from the UE2 that was blocked at tl, and instead interpolate quality values for a non-blocked signal. Moreover, the NW can compensate for the larger antenna gain for UE 2 in comparison to UE 1 and 3 by having such gain included in the BP Al.

FIGURE 3 illustrates an example signal quality curve 50 demonstrating network compensation for signal quality for improved prediction, according to certain embodiments. Specifically, the NW compensation performed for the larger antenna gain for UE 2 in comparison to UE 1 and 3 makes their trajectory more similar in the signal quality domain as depicted in FIGURE 3, leading improved prediction potential of the large quality drop at t2, thereby, preventing a potential beam failure.

Multiple Transmission/Reception Points (TRPs) at NW Node

When the NW node (e.g., gNB) is equipped with multiple TRPs, the network node needs to perform beam management for each TRP individually. In general, the gNB may have M TRPs, where M>=2. In the following discussion, it is assumed that M=2 TRPs (i.e., TRP1 and TRP2), with the understanding that the same principles apply if there are more than 2 TRPs.

For the beam measurement report, the gNB ensures that a first set of SSB indices are associated with TRP1 and a second set of SSB indices are associated with TRP2 when the beam measurement is SSB-based. When the beam measurement is CSI-RS-based, a first set of periodic CSI-RS resource indices are associated with TRP1, and a second set of periodic CSI-RS resource indices are associated with TRP2. Thus, the UE performs beam quality measurement and beam measurement report for beams of both TRPs. Using the BP Al described above, the gNB keeps track of the best candidate beams for both TRPs and performs beam prediction for beams of both TRPs.

If both TRPs have high quality beams, then the two TRPs can be used simultaneously (e.g., TRP1 and TRP2 simultaneously transmit DL signal/channel to the UE). Alternatively, the better beam among the two TRPs is selected based on the beam prediction and used for data communication with the UE (i.e., the UE communicates with a single TRP at a time), thus, leveraging the diversity and robustness afforded by the presence of two TRPs.

FIGURE 4 illustrates example signal quality curves 60 and 70 for single TRP and multiple TRPs, respectively, according to certain embodiments.

FIGURE 5 shows an example of a communication system 100 in accordance with some embodiments. In the example, the communication system 100 includes a telecommunication network 102 that includes an access network 104, such as a radio access network (RAN), and a core network 106, which includes one or more core network nodes 108. The access network 104 includes one or more access network nodes, such as network nodes 110a and 110b (one or more of which may be generally referred to as network nodes 110), or any other similar 3^rd Generation Partnership Project (3GPP) access node or non-3GPP access point. The network nodes 110 facilitate direct or indirect connection of user equipment (UE), such as by connecting UEs 112a, 112b, 112c, and 112d (one or more of which may be generally referred to as UEs 112) to the core network 106 over one or more wireless connections.

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 100 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 100 may include and/or interface with any type of communication, telecommunication, data, cellular, radio network, and/or other similar type of system.

The UEs 112 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 110 and other communication devices. Similarly, the network nodes 110 are arranged, capable, configured, and/or operable to communicate directly or indirectly with the UEs 112 and/or with other network nodes or equipment in the telecommunication network 102 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 102.

In the depicted example, the core network 106 connects the network nodes 110 to one or more hosts, such as host 116. 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 106 includes one more core network nodes (e.g., core network node 108) 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 108. 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).

The host 116 may be under the ownership or control of a service provider other than an operator or provider of the access network 104 and/or the telecommunication network 102, and may be operated by the service provider or on behalf of the service provider. The host 116 may host a variety of applications to provide one or more service. Examples of such applications include live and pre-recorded 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.

As a whole, the communication system 100 of FIGURE 5 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.

In some examples, the telecommunication network 102 is a cellular network that implements 3GPP standardized features. Accordingly, the telecommunications network 102 may support network slicing to provide different logical networks to different devices that are connected to the telecommunication network 102. For example, the telecommunications network 102 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.

In some examples, the UEs 112 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 104 on a predetermined schedule, when triggered by an internal or external event, or in response to requests from the access network 104. 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).

In the example, the hub 114 communicates with the access network 104 to facilitate indirect communication between one or more UEs (e.g., UE 112c and/or 112d) and network nodes (e.g., network node 110b). In some examples, the hub 114 may be a controller, router, content source and analytics, or any of the other communication devices described herein regarding UEs. For example, the hub 114 may be a broadband router enabling access to the core network 106 for the UEs. As another example, the hub 114 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 110, or by executable code, script, process, or other instructions in the hub 114. As another example, the hub 114 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 114 may be a content source. For example, for a UE that is a VR headset, display, loudspeaker or other media delivery device, the hub 114 may retrieve VR assets, video, audio, or other media or data related to sensory information via a network node, which the hub 114 then provides to the UE either directly, after performing local processing, and/or after adding additional local content. In still another example, the hub 114 acts as a proxy server or orchestrator for the UEs, in particular in if one or more of the UEs are low energy loT devices.

The hub 114 may have a constant/persistent or intermittent connection to the network node 110b. The hub 114 may also allow for a different communication scheme and/or schedule between the hub 114 and UEs (e.g., UE 112c and/or 112d), and between the hub 114 and the core network 106. In other examples, the hub 114 is connected to the core network 106 and/or one or more UEs via a wired connection. Moreover, the hub 114 may be configured to connect to an M2M service provider over the access network 104 and/or to another UE over a direct connection. In some scenarios, UEs may establish a wireless connection with the network nodes 110 while still connected via the hub 114 via a wired or wireless connection. In some embodiments, the hub 114 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 110b. In other embodiments, the hub 114 may be a nondedicated hub - that is, a device which is capable of operating to route communications between the UEs and network node 110b, but which is additionally capable of operating as a communication start and/or end point for certain data channels.

FIGURE 6 shows a UE 200 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-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-IoT) UE, a machine type communication (MTC) UE, and/or an enhanced MTC (eMTC) UE.

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).

The UE 200 includes processing circuitry 202 that is operatively coupled via a bus 204 to an input/output interface 206, a power source 208, a memory 210, a communication interface 212, and/or any other component, or any combination thereof. Certain UEs may utilize all or a subset of the components shown in FIGURE 6. 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.

The processing circuitry 202 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 210. The processing circuitry 202 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 202 may include multiple central processing units (CPUs).

In the example, the input/output interface 206 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 200. 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.

In some embodiments, the power source 208 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 208 may further include power circuitry for delivering power from the power source 208 itself, and/or an external power source, to the various parts of the UE 200 via input circuitry or an interface such as an electrical power cable. Delivering power may be, for example, for charging of the power source 208. Power circuitry may perform any formatting, converting, or other modification to the power from the power source 208 to make the power suitable for the respective components of the UE 200 to which power is supplied.

The memory 210 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 210 includes one or more application programs 214, such as an operating system, web browser application, a widget, gadget engine, or other application, and corresponding data 216. The memory 210 may store, for use by the UE 200, any of a variety of various operating systems or combinations of operating systems.

The memory 210 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 in-line 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 (eUICC), integrated UICC (iUICC) or a removable UICC commonly known as ‘SIM card.’ The memory 210 may allow the UE 200 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 210, which may be or comprise a device-readable storage medium.

The processing circuitry 202 may be configured to communicate with an access network or other network using the communication interface 212. The communication interface 212 may comprise one or more communication subsystems and may include or be communicatively coupled to an antenna 222. The communication interface 212 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 218 and/or a receiver 220 appropriate to provide network communications (e.g., optical, electrical, frequency allocations, and so forth). Moreover, the transmitter 218 and receiver 220 may be coupled to one or more antennas (e.g., antenna 222) and may share circuit components, software or firmware, or alternatively be implemented separately.

In the illustrated embodiment, communication functions of the communication interface 212 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/intemet protocol (TCP/IP), synchronous optical networking (SONET), Asynchronous Transfer Mode (ATM), QUIC, Hypertext Transfer Protocol (HTTP), and so forth.

Regardless of the type of sensor, a UE may provide an output of data captured by its sensors, through its communication interface 212, 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).

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.

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. Non-limiting 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, amotion 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 itemtracking 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 200 shown in FIGURE 6.

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 3 GPP NB-IoT 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.

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.

FIGURE 7 shows a network node 300 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)).

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 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). 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).

The network node 300 includes a processing circuitry 302, a memory 304, a communication interface 306, and a power source 308. The network node 300 may be composed of multiple physically separate components (e.g., aNodeB 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 300 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 300 may be configured to support multiple radio access technologies (RATs). In such embodiments, some components may be duplicated (e.g., separate memory 304 for different RATs) and some components may be reused (e.g., a same antenna 310 may be shared by different RATs). The network node 300 may also include multiple sets of the various illustrated components for different wireless technologies integrated into network node 300, 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 300.

The processing circuitry 302 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 300 components, such as the memory 304, to provide network node 300 functionality.

In some embodiments, the processing circuitry 302 includes a system on a chip (SOC). In some embodiments, the processing circuitry 302 includes one or more of radio frequency (RF) transceiver circuitry 312 and baseband processing circuitry 314. In some embodiments, the radio frequency (RF) transceiver circuitry 312 and the baseband processing circuitry 314 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 312 and baseband processing circuitry 314 may be on the same chip or set of chips, boards, or units.

The memory 304 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 302. The memory 304 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 302 and utilized by the network node 300. The memory 304 may be used to store any calculations made by the processing circuitry 302 and/or any data received via the communication interface 306. In some embodiments, the processing circuitry 302 and memory 304 is integrated.

The communication interface 306 is used in wired or wireless communication of signaling and/or data between anetwork node, access network, and/or UE. As illustrated, the communication interface 306 comprises port(s)/terminal(s) 316 to send and receive data, for example to and from a network over a wired connection. The communication interface 306 also includes radio frontend circuitry 318 that may be coupled to, or in certain embodiments a part of, the antenna 310. Radio front-end circuitry 318 comprises filters 320 and amplifiers 322. The radio front-end circuitry 318 may be connected to an antenna 310 and processing circuitry 302. The radio frontend circuitry may be configured to condition signals communicated between antenna 310 and processing circuitry 302. The radio front-end circuitry 318 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 318 may convert the digital data into a radio signal having the appropriate channel and bandwidth parameters using a combination of filters 320 and/or amplifiers 322. The radio signal may then be transmitted via the antenna 310. Similarly, when receiving data, the antenna 310 may collect radio signals which are then converted into digital data by the radio front-end circuitry 318. The digital data may be passed to the processing circuitry 302. In other embodiments, the communication interface may comprise different components and/or different combinations of components. In certain alternative embodiments, the network node 300 does not include separate radio front-end circuitry 318, instead, the processing circuitry 302 includes radio front-end circuitry and is connected to the antenna 310. Similarly, in some embodiments, all or some of the RF transceiver circuitry 312 is part of the communication interface 306. In still other embodiments, the communication interface 306 includes one or more ports or terminals 316, the radio front-end circuitry 318, and the RF transceiver circuitry 312, as part of a radio unit (not shown), and the communication interface 306 communicates with the baseband processing circuitry 314, which is part of a digital unit (not shown).

The antenna 310 may include one or more antennas, or antenna arrays, configured to send and/or receive wireless signals. The antenna 310 may be coupled to the radio front-end circuitry 318 and may be any type of antenna capable of transmitting and receiving data and/or signals wirelessly. In certain embodiments, the antenna 310 is separate from the network node 300 and connectable to the network node 300 through an interface or port.

The antenna 310, communication interface 306, and/or the processing circuitry 302 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 310, the communication interface 306, and/or the processing circuitry 302 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.

The power source 308 provides power to the various components of network node 300 in a form suitable for the respective components (e.g., at a voltage and current level needed for each respective component). The power source 308 may further comprise, or be coupled to, power management circuitry to supply the components of the network node 300 with power for performing the functionality described herein. For example, the network node 300 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 308. As a further example, the power source 308 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. Embodiments of the network node 300 may include additional components beyond those shown in FIGURE 7 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 300 may include user interface equipment to allow input of information into the network node 300 and to allow output of information from the network node 300. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for the network node 300.

FIGURE 8 is a block diagram of a host 400, which may be an embodiment of the host 116 of FIGURE 5, in accordance with various aspects described herein. As used herein, the host 400 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 400 may provide one or more services to one or more UEs.

The host 400 includes processing circuitry 402 that is operatively coupled via a bus 404 to an input/output interface 406, a network interface 408, a power source 410, and a memory 412. 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 2 and 3, such that the descriptions thereof are generally applicable to the corresponding components of host 400.

The memory 412 may include one or more computer programs including one or more host application programs 414 and data 416, which may include user data, e.g., data generated by a UE for the host 400 or data generated by the host 400 for a UE. Embodiments of the host 400 may utilize only a subset or all of the components shown. The host application programs 414 may be implemented in a container-based architecture and may provide support for video codecs (e.g., Versatile Video Coding (VVC), High Efficiency Video Coding (HEVC), Advanced Video Coding (AVC), MPEG, VP9) and audio codecs (e.g., FL AC, 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 414 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 400 may select and/or indicate a different host for over-the-top services for a UE. The host application programs 414 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.

FIGURE 9 is a block diagram illustrating a virtualization environment 500 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 500 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.

Applications 502 (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.

Hardware 504 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 506 (also referred to as hypervisors or virtual machine monitors (VMMs)), provide VMs 508a and 508b (one or more of which may be generally referred to as VMs 508), and/or perform any of the functions, features and/or benefits described in relation with some embodiments described herein. The virtualization layer 506 may present a virtual operating platform that appears like networking hardware to the VMs 508.

The VMs 508 comprise virtual processing, virtual memory, virtual networking or interface and virtual storage, and may be run by a corresponding virtualization layer 506. Different embodiments of the instance of a virtual appliance 502 may be implemented on one or more of VMs 508, 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.

In the context ofNFV, a VM 508 may be a software implementation of a physical machine that runs programs as if they were executing on a physical, non-virtualized machine. Each of the VMs 508, and that part of hardware 504 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 ofNFV, a virtual network function is responsible for handling specific network functions that run in one or more VMs 508 on top of the hardware 504 and corresponds to the application 502.

Hardware 504 may be implemented in a standalone network node with generic or specific components. Hardware 504 may implement some functions via virtualization. Alternatively, hardware 504 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 510, which, among others, oversees lifecycle management of applications 502. In some embodiments, hardware 504 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 512 which may alternatively be used for communication between hardware nodes and radio units.

FIGURE 10 shows a communication diagram of a host 602 communicating via a network node 604 with a UE 606 over a partially wireless connection in accordance with some embodiments.

Example implementations, in accordance with various embodiments, of the UE (such as a UE 112a of FIGURE 5 and/or UE 200 of FIGURE 6), network node (such as network node 110a of FIGURE 5 and/or network node 300 of FIGURE 7), and host (such as host 116 of FIGURE 5 and/or host 400 of FIGURE 8) discussed in the preceding paragraphs will now be described with reference to FIGURE 10.

Like host 400, embodiments of host 602 include hardware, such as a communication interface, processing circuitry, and memory. The host 602 also includes software, which is stored in or accessible by the host 602 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 606 connecting via an over-the-top (OTT) connection 650 extending between the UE 606 and host 602. In providing the service to the remote user, a host application may provide user data which is transmitted using the OTT connection 650.

The network node 604 includes hardware enabling it to communicate with the host 602 and UE 606. The connection 660 may be direct or pass through a core network (like core network 106 of FIGURE 5) 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.

The UE 606 includes hardware and software, which is stored in or accessible by UE 606 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 606 with the support of the host 602. In the host 602, an executing host application may communicate with the executing client application via the OTT connection 650 terminating at the UE 606 and host 602. 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 650 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 650.

The OTT connection 650 may extend via a connection 660 between the host 602 and the network node 604 and via a wireless connection 670 between the network node 604 and the UE 606 to provide the connection between the host 602 and the UE 606. The connection 660 and wireless connection 670, over which the OTT connection 650 may be provided, have been drawn abstractly to illustrate the communication between the host 602 and the UE 606 via the network node 604, without explicit reference to any intermediary devices and the precise routing of messages via these devices.

As an example of transmitting data via the OTT connection 650, in step 608, the host 602 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 606. In other embodiments, the user data is associated with a UE 606 that shares data with the host 602 without explicit human interaction. In step 610, the host 602 initiates a transmission carrying the user data towards the UE 606. The host 602 may initiate the transmission responsive to a request transmitted by the UE 606. The request may be caused by human interaction with the UE 606 or by operation of the client application executing on the UE 606. The transmission may pass via the network node 604, in accordance with the teachings of the embodiments described throughout this disclosure. Accordingly, in step 612, the network node 604 transmits to the UE 606 the user data that was carried in the transmission that the host 602 initiated, in accordance with the teachings of the embodiments described throughout this disclosure. In step 614, the UE 606 receives the user data carried in the transmission, which may be performed by a client application executed on the UE 606 associated with the host application executed by the host 602.

In some examples, the UE 606 executes a client application which provides user data to the host 602. The user data may be provided in reaction or response to the data received from the host 602. Accordingly, in step 616, the UE 606 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 606. Regardless of the specific manner in which the user data was provided, the UE 606 initiates, in step 618, transmission of the user data towards the host 602 via the network node 604. In step 620, in accordance with the teachings of the embodiments described throughout this disclosure, the network node 604 receives user data from the UE 606 and initiates transmission of the received user data towards the host 602. In step 622, the host 602 receives the user data carried in the transmission initiated by the UE 606.

One or more of the various embodiments improve the performance of OTT services provided to the UE 606 using the OTT connection 650, in which the wireless connection 670 forms the last segment. More precisely, the teachings of these embodiments may improve one or more of, for example, data rate, latency, and/or power consumption and, thereby, provide benefits such as, for example, reduced user waiting time, relaxed restriction on file size, improved content resolution, better responsiveness, and/or extended battery lifetime.

In an example scenario, factory status information may be collected and analyzed by the host 602. As another example, the host 602 may process audio and video data which may have been retrieved from a UE for use in creating maps. As another example, the host 602 may collect and analyze real-time data to assist in controlling vehicle congestion (e.g., controlling traffic lights). As another example, the host 602 may store surveillance video uploaded by a UE. As another example, the host 602 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 602 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 650 between the host 602 and UE 606, 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 602 and/or UE 606. In some embodiments, sensors (not shown) may be deployed in or in association with other devices through which the OTT connection 650 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 650 may include message format, retransmission settings, preferred routing etc.; the reconfiguring need not directly alter the operation of the network node 604. Such procedures and functionalities may be known and practiced in the art. In certain embodiments, measurements may involve proprietary UE signaling that facilitates measurements of throughput, propagation times, latency and the like, by the host 602. The measurements may be implemented in that software causes messages to be transmitted, in particular empty or ‘dummy’ messages, using the OTT connection 650 while monitoring propagation times, errors, etc.

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.

FIGURE 11 illustrates a method 700 by a UE 112, according to certain embodiments. The method includes receiving, at step 702, at least one beam from a network node 110. At step 704, the UE transmits, to the network node 110, BP Al associated with the at least one beam.

In a particular embodiment, the UE 112 performs at least one measurement on the at least one beam received from the network node and/or estimates the BP Al based on the at least one measurement performed on the at least one beam received from the network node.

In a particular embodiment, the BPAI includes any one or more of: an index of an Rx beam; an indication of whether the at least one measurement was subject of or to blockage; and at least one uncertainty estimate associated with the at least one measurement.

In a particular embodiment, the BPAI includes any one or more of: a state identifier for machine learning, ML; at least one estimated antenna gain associated with the at least one measurement and/or the at least one beam; at least one signal quality and/or reference direction associated with the at least one measurement and/or the at least one beam; at least one UE Receiver-angle associated with the at least one measurement and/or the at least one beam; an indication of a probability that a blockage is static; an indication of a probability that a blockage is dynamic; an estimate of a measurement value without blockage; an indication of a probability that the UE is located indoors; at least one time stamp associated with the at least one measurement; at least one reliability estimate associated with the at least one measurement; one or more predicted SSB block indexes and/or one or more predicted CSI-RS indexes; for each SSB index and/or CSI- RS index, a set of actual measurement values associated with a time period before a measurement reporting time period; for each reported SSB index and/or CSI-RS index, a set of predicted measurement values for a time period subsequent to a measurement reporting time period; channel information comprising doppler information and/or delay spread; at least one orientation of the UE 112 with respect to earthbound coordinates; at least one receive antenna panel configuration; at least one transmit antenna panel configuration; a location of the UE 112; mobility information associated with the UE 112; an indication of whether the at least one measurement is filtered over more than one time instance; and an age of the at least one measurement value. In a particular embodiment, the at least one measurement includes at least one link quality measurement performed on the at least one beam. The at least one link quality measurement includes at least one of: at least one RSRP measurement; at least one RSRQ measurement; and at least one SINR measurement.

In a particular embodiment, the at least one beam includes: at least one CSI and/or at least one SSB.

In a particular embodiment, the BP Al is transmitted in or with at least one of: a measurement report; layer 3 beam measurement information; a CSI report for beam management; and a MAC CE for BFR.

In a particular embodiment, the measurement report comprises at least one value associated with at least one signal quality measurement performed by the UE 112.

In a particular embodiment, prior to transmitting the BP Al, the UE 112 performs at least one of: receiving, from the network node, a request for capability information; transmitting, to the network node, capability information indicating an ability of the UE 112 to transmit the BP Al; and receiving, from the network node, a request for the BP Al.

In a particular embodiment, the capability information further comprises a number of UE 112 panels supported by the UE 112. Each UE panel is associated with a set of UE panel capabilities, a set of UE properties, and/or a UE panel identifier, and each set of UE panel properties may include any one or more of: a number of transmitter chains, a number of receiver chains, a number of antenna elements, a max antenna gain, a maximum transmission power, singlepolarized or dual polarized, and a pointing direction.

In a particular embodiment, the capability information indicates a UE panel identifier for each beam associated with a measurement report.

In a particular embodiment, the UE 112 receives, from the network node 110, at least one transmission parameter modified by the network node 110 based on the BPAI. Based on the at least one transmission parameter that is adjusted by the network node 110, the UE 112 receives at least one beam from the network node 110.

In a particular embodiment, the at least one transmission parameter is associated with at least one of: a handover decision; a scheduling decision; link adaptation; and beam management.

In a particular embodiment, the BPAI is transmitted in a RRC message.

In a particular embodiment, the UE 112 performs at least one of: transmitting a measurement report comprising a number N1 of beam measurements, and wherein the BPAI comprises: for each SSB index and/or each CSI-RS index, a number N1 of actual measurement values associated with a time period occurring before a time period associated with a measurement report; and transmitting a measurement report comprising at least one predicted beam measurement. The BP Al comprises: for each SSB index and/or each CSI-RS index, a number N2 of predicted measurement values associated with a time period subsequent to a time period associated with the measurement report.

In a particular embodiment, the network node 110 controls multiple TRPs, and each TRP is associated with a set of SSB indices or CSI-RS resource indices. The UE 112 transmits BPAI for each one of the multiple TRPs.

FIGURE 12 illustrates a method 800 by a network node 110, according to certain embodiments. The method includes transmitting, at step 802, at least one beam to a UE 112. At step 804, the network node receives, from the UE, BPAI associated with the at least one beam.

In a particular embodiment, the network node 110 uses the BPAI to determine a predicted signal quality of at least one beam to be subsequently transmitted by the network node. Based on the BPAI and/or the predicted signal quality, the network node 110 adjusts at least one transmission parameter for the at least one beam to be subsequently transmitted by the network node 110.

In a particular embodiment, network node 110 transmits, to the UE 112, the at least one transmission parameter adjusted by the network node 110.

In a particular embodiment, based on the at least the BPAI and/or a plurality of BPAI received from a plurality of UEs 112, the network node 110 generates or updates a ML model for predicting a signal quality of at least one beam to be subsequently transmitted by the network node. Or, based on the at least the BPAI and/or a plurality of BPAI received from a plurality of UEs, the network node 110 develops or updates an algorithm for predicting a signal quality of at least one beam to be subsequently transmitted by the network node 110.

In a particular embodiment, the network node 110 uses the ML model and/or the algorithm to predict the signal quality of the at least one beam to be subsequently transmitted by the network. The signal quality includes at least one predicted value associated with a time period (e.g., tn+i,tn+2, . . . ) that is subsequent to a time period (e.g., ti,. . . ,tn) associated with the received BPAI.

In a particular embodiment, based on the predicted signal quality of the at least one beam to be subsequently transmitted, the network node 110 adjusts at least one transmission parameter. Based on the adjusted network transmission parameter, the network node 110 transmits the at least one beam. In a particular embodiment, the network node 110 transmits the adjusted transmission parameter to the UE.

In a particular embodiment, the adjusted transmission parameter comprises and/or is associated with at least one of: a handover of the UE 112, a scheduling of the UE 112, a link adaptation, and a beam management parameter.

In a particular embodiment, the BP Al comprises any one or more of: an index of an Rx beam; an indication of whether at least one measurement associated with the at least one beam was subject of or to blockage; and at least one uncertainty estimate associated with the at least one measurement associated with the at least one beam.

In a particular embodiment, the BPAI comprises any one or more of: a state identifier for ML; at least one estimated antenna gain associated with the at least one measurement and/or the at least one beam; at least one signal quality and/or reference direction associated with the at least one measurement and/or the at least one beam; at least one UE Rx-angle associated with the at least one measurement and/or the at least one beam; an indication of a probability that a blockage is static; an indication of a probability that a blockage is dynamic; an estimate of a measurement value without blockage; an indication of a probability that the UE is located indoors; at least one time stamp associated with the at least one measurement; at least one reliability estimate associated with the at least one measurement; one or more predicted SSB indexes and/or one or more predicted CSI-RS indexes; for each SSB index and/or CSI-RS index, a set of actual measurement values associated with a time period before a measurement reporting time period; for each reported SSB index and/or CSI-RS index, a set of predicted measurement values for a time period subsequent to a measurement reporting time period; channel information comprising doppler information and/or delay spread; at least one orientation of the UE with respect to earthbound coordinates; at least one receive antenna panel configuration; at least one transmit antenna panel configuration; a location of the UE 112; mobility information associated with the UE 112; an indication of whether the at least one measurement is filtered over more than one time instance; and an age of the at least one measurement value.

In a particular embodiment, the network node 110 configures the UE 112 to perform at least one measurement on the at least one beam. The at least one measurement includes at least one link quality measurement. The at least one link quality measurement comprises at least one of: at least one RSRP measurement; at least one RSRQ measurement; and at least one SINR measurement. In a particular embodiment, the at least one beam comprises: at least one CSI-RS and/or at least one SSB.

In a particular embodiment, the BPAI is received in or with at least one of: a measurement report; layer 3 beam measurement information; a CSI report for beam management; and a MAC CE for BFR.

In a particular embodiment, the measurement report comprises at least one value associated with at least one signal quality measurement performed by the UE 112.

In a particular embodiment, prior to receiving the BPAI, the network node 110 performs at least one of: transmitting, to the UE 112, a request for capability information; receiving, from the UE 112, the capability information indicating an ability of the UE 112 to transmit the BPAI; and transmitting, to the UE 112, a request for the BPAI.

In a particular embodiment, the capability information indicates a number of UE panels supported by the UE 112, wherein each UE panel is associated with a set of UE panel capabilities, a set of UE properties, and/or a UE panel identifier, and wherein each set of UE panel properties may include any one or more of: a number of transmitter chains, a number of receiver chains, a number of antenna elements, a max antenna gain, a maximum transmission power, singlepolarized or dual polarized, and a pointing direction.

In a particular embodiment, the capability information indicates a UE panel identifier for each beam associated with a measurement report.

In a particular embodiment, the BPAI is received in an RRC message.

In a particular embodiment, the network node 110 configures the UE 112 to transmit a measurement report comprising a number N1 of beam measurements, and BPAI includes: for each SSB index and/or each CSI-RS index, a number N1 of actual measurement values associated with a time period occurring before a time period associated with a measurement report. Additionally or alternatively the network node 110 configures the UE 112 to include predicted beam measurements in a measurement report, and the BPAI includes: for each SSB index and/or each CSI-RS index, a number N2 of predicted measurement values associated with a time period subsequent to a time period associated with the measurement report.

In a particular embodiment, the network node comprises multiple TRPs, and each TRP is associated with a set of SSB indices or CSI-RS resource indices. The network node 110 receives a corresponding BPAI for each one of the multiple TRPs.

In a particular embodiment, the network node 110 uses the BPAI to create a representative radio fingerprint trajectory for beam predictions. In a particular embodiment, the network node 110 receives a plurality of BP Al, and each of the plurality of BPAI are associated with a corresponding one of a plurality of beams.

In a particular embodiment, the network node 110 receives a plurality of BPAI, and each of the plurality of BPAI are associated with the at least one beam.

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 functionality 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.

EXAMPLE EMBODIMENTS

Group A Example Embodiments

Example Embodiment Al . A method by a user equipment for comprising: any of the user equipment steps, features, or functions described above, either alone or in combination with other steps, features, or functions described above.

Example Embodiment A2. The method of the previous embodiment, further comprising one or more additional user equipment steps, features or functions described above.

Example Embodiment A3. The method of any of the previous embodiments, further comprising: providing user data; and forwarding the user data to a host computer via the transmission to the network node.

Group B Example Embodiments

Example Embodiment Bl. A method performed by a network node comprising: any of the network node steps, features, or functions described above, either alone or in combination with other steps, features, or functions described above.

Example Embodiment B2. The method of the previous embodiment, further comprising one or more additional network node steps, features or functions described above. Example Embodiment B3. The method of any of the previous embodiments, further comprising: obtaining user data; and forwarding the user data to a host or a user equipment.

Group C Example Embodiments

Example Embodiment Cl. A method by a user equipment (UE) comprising: transmitting, to a network node, beam prediction assistance information (BP Al).

Example Embodiment C2. The method of Example Embodiment Cl, further comprising any one or more of: receiving at least one beam from the network node, and performing at least one measurement on or associated with the at least one beam received from the network node; and estimating the BPAI based on the at least one measurement performed on or associated with the at least one beam received from the network node.

Example Embodiment C3. The method of Example Embodiment C2, wherein the BPAI comprises any one or more of: an index of an Rx beam; a state identifier for ML; at least one estimated antenna gain associated with the at least one measurement and/or the at least one beam; at least one signal quality and/or reference direction associated with the at least one measurement and/or the at least one beam; at least one UE Rx-angle associated with the at least one measurement and/or the at least one beam; an indication of whether the at least one measurement was subject of or to blockage; an indication of a probability that a blockage is static; an indication of a probability that a blockage is dynamic; an estimate of a measurement value without blockage; an indication of a probability that the UE is located indoors; at least one time stamp associated with the at least one measurement; at least one uncertainty estimate associated with the at least one measurement; at least one reliability estimate associated with the at least one measurement; one or more predicted SS/PBCH block indexes and/or one or more predicted CSI-RS indexes (optionally, in order of decreasing sorting quantity); for each SSB index and/or CSI-RS index, a set of actual measurement values associated with a time period before a measurement reporting time period; for each reported SSB index and/or CSI-RS index, a set of predicted measurement values for a time period subsequent to a measurement reporting time period; channel information comprising doppler information and/or delay spread; at least one orientation of the UE with respect to earthbound coordinates; at least one receive antenna panel configuration; at least one transmit antenna panel configuration; a location of the UE; mobility information associated with the UE; an indication of whether the at least one measurement is filtered over more than one time instance; and an age of the at least one measurement value.

Example Embodiment C4. The method of any one of Example Embodiments C2 to C3, wherein the at least one measurement comprises at least one link quality measurement performed on the at least one beam and wherein the at least one link quality measurement comprises at least one of: at least one RSRP measurement; at least one RSRQ measurement; and at least one SINR measurement.

Example Embodiment C5. The method of any one of Example Embodiments C2 to C3, wherein the at least one beam comprises: at least one CSI and/or at least one SSB.

Example Embodiment C6. The method of any one of Example Embodiments Cl to C5, wherein the BP Al is transmitted in or with at least one of: a measurement report; layer 3 beam measurement information; a CSI report for beam management; and a BFR MAC CE for beam failure recovery.

Example Embodiment C7. The method of Example Embodiment C6, wherein the measurement report comprises at least one value associated with at least one signal quality measurement performed by the UE.

Example Embodiment C8. The method of any one of Example Embodiments Cl to C7, wherein prior to transmitting the BPAI, the method further comprises at least one of: receiving, from the network node, a request for capability information; transmitting, to the network node, capability information indicating an ability of the UE to transmit the BPAI; and receiving, from the network node, a request for the BPAI.

Example Embodiment C9. The method of Example Embodiment C8, wherein the capability information further comprises a number of UE panels supported by the UE, wherein each UE panel is associated with a set of UE panel capabilities, a set of UE properties, and/or a UE panel ID, and wherein each set of UE panel properties may include any one or more of: a number of TX chains, a number of Rx chains, a number of antenna elements, a max gain, a maximum output power, single-polarized or dual polarized, and a pointing direction.

Example Embodiment CIO. The method of any one of Example Embodiments C8 to C9, wherein the capability information indicates a UE panel ID for each beam associated with a measurement report.

Example Embodiment Cl 1. The method of any one of Example Embodiments Cl to CIO, further comprising: receiving, from the network node, a parameter modified by the network node based on the BPAI, and performing at least one action based on the parameter that is modified based on the BPAI.

Example Embodiment Cl 2. The method of any one of Example Embodiments Cl to Cl 1, wherein the BPAI is transmitted in an RRC message. Example Embodiment Cl 3. The method of any one of Example Embodiments Cl to Cl 2, wherein the UE is configured to transmit a measurement report comprising a number N1 of beam measurements, and wherein the BPAI comprises: for each SSB index and/or each CSI-RS index, a number N1 of actual measurement values associated with a time period occurring before a time period associated with a measurement report.

Example Embodiment C14.The method of any one of Example Embodiments Cl to C13, wherein the UE is configured to include predicted beam measurements in a measurement report, and wherein the BPAI comprises: for each SSB index and/or each CSI-RS index, a number N2 of predicted measurement values associated with a time period subsequent to a time period associated with the measurement report.

Example Embodiment Cl 5. The method of any one of Example Embodiments Cl to Cl 4, wherein the network node comprises multiple TRPs, and wherein each TRP is associated with a set of SSB indices or CSI-RS resource indices, and wherein transmitting the BPAI comprises: transmitting BPAI for each one of the multiple TRPs.

Example Embodiment C16.The method of any one of Example Embodiments Cl to C15, further comprising receiving, from the network node, a predicted channel quality of at least one beam to be subsequently transmitted by the network.

Example Embodiment Cl 7. The method of Example Embodiment Cl 6, wherein the predicted channel quality comprises at least one predicted value associated with a time period (e.g., tn+i,tn+2, . . . ) that is subsequent to atime period (e.g., ti.... ,tn) associated with the transmitted BPAI.

Example Embodiment C18.The method of any one of Example Embodiments Cl to C17, further comprising receiving, from the network node, a network transmission parameter that is adjusted based on the BPAI.

Example Embodiment Cl 9. The method of Example Embodiment Cl 8, further comprising: based on the network transmission parameter that is adjusted, receiving at least one beam from the network node.

Example Embodiment C20. The method of Example Embodiment Cl 9, wherein the network transmission parameter that is adjusted based on the BPAI comprises and/or is associated with at least one of: handover of the UE, scheduling of the UE, link adaptation, and a beam management parameter.

Example Embodiment C21. The method of Example Embodiments Cl to C20, further comprising: providing user data; and forwarding the user data to a host via the transmission to the network node. Example Embodiment C22.A user equipment comprising processing circuitry configured to perform any of the methods of Example Embodiments Cl to C21.

Example Embodiment C23.A user equipment adapted to perform any of the methods of Example Embodiments Cl to C21.

Example Embodiment C24.A wireless device comprising processing circuitry configured to perform any of the methods of Example Embodiments Cl to C21.

Example Embodiment C25. A computer program comprising instructions which when executed on a computer perform any of the methods of Example Embodiments Cl to C21.

Example Embodiment C26. A computer program product comprising computer program, the computer program comprising instructions which when executed on a computer perform any of the methods of Example Embodiments Cl to C21.

Example Embodiment C27. A non-transitory computer readable medium storing instructions which when executed by a computer perform any of the methods of Example Embodiments Cl to C21.

Group D Example Embodiments

Example Embodiment DI. A method by a network node comprising: transmitting, to a user equipment (UE), at least one beam; and receiving, from the UE, beam prediction assistance information (BP Al) associated with the at least one beam.

Example Embodiment D2. The method of Example Embodiment DI, further comprising performing at least one action based on the BP Al received from the UE.

Example Embodiment D3. The method of any one of Example Embodiments DI to D2, wherein the BP Al comprises any one or more of: an index of an Rx beam; a state identifier for ML; at least one estimated antenna gain associated with the at least one measurement and/or the at least one beam; at least one signal quality and/or reference direction associated with the at least one measurement and/or the at least one beam; at least one UE Rx-angle associated with the at least one measurement and/or the at least one beam; an indication of whether the at least one measurement was subject of or to blockage; an indication of a probability that a blockage is static; an indication of a probability that a blockage is dynamic; an estimate of a measurement value without blockage; an indication of a probability that the UE is located indoors; at least one time stamp associated with the at least one measurement; at least one uncertainty estimate associated with the at least one measurement; at least one reliability estimate associated with the at least one measurement; one or more predicted SS/PBCH block indexes and/or one or more predicted CSI- RS indexes (optionally, in order of decreasing sorting quantity); for each SSB index and/or CSI- RS index, a set of actual measurement values associated with a time period before a measurement reporting time period; for each reported SSB index and/or CSI-RS index, a set of predicted measurement values for a time period subsequent to a measurement reporting time period; channel information comprising doppler information and/or delay spread; at least one orientation of the UE with respect to earthbound coordinates; at least one receive antenna panel configuration; at least one transmit antenna panel configuration; a location of the UE; mobility information associated with the UE; an indication of whether the at least one measurement is filtered over more than one time instance; and an age of the at least one measurement value.

Example Embodiment D4. The method of any one of Example Embodiments DI to D3, further comprising configuring the UE to perform at least one measurement on the at least one beam, wherein the at least one measurement comprises at least one link quality measurement, and wherein the at least one link quality measurement comprises at least one of: at least one RSRP measurement; at least one RSRQ measurement; and at least one SINR measurement.

Example Embodiment D5. The method of any one of Example Embodiments D2 to D4, wherein the at least one beam comprises: at least one CSI-RS and/or at least one SSB.

Example Embodiment D6. The method of any one of Example Embodiments DI to D5, wherein the BPAI is received in or with at least one of: a measurement report; layer 3 beam measurement information; a CSI report for beam management; and a BFR MAC CE for beam failure recovery.

Example Embodiment D7. The method of Example Embodiment D6, wherein the measurement report comprises at least one value associated with at least one signal quality measurement performed by the UE.

Example Embodiment D8. The method of any one of Example Embodiments DI to D7, wherein prior to receiving the BPAI, the method further comprises at least one of: transmitting, to the UE, a request for capability information; receiving, from the UE, the capability information indicating an ability of the UE to transmit the BPAI; and transmitting, to the UE, a request for the BPAI.

Example Embodiment D9. The method of Example Embodiment D8, wherein the capability information indicates a number of UE panels supported by the UE, wherein each UE panel is associated with a set of UE panel capabilities, a set of UE properties, and/or a UE panel ID, and wherein each set of UE panel properties may include any one or more of: a number of TX chains, a number of Rx chains, a number of antenna elements, a max gain, a maximum output power, single-polarized or dual polarized, and a pointing direction.

Example Embodiment DIO. The method of any one of Example Embodiments D8 to D9, wherein the capability information indicates a UE panel ID for each beam associated with a measurement report.

Example Embodiment Dl l. The method of any one of Example Embodiments D 1 to D 10, further comprising: transmitting, to the UE, a parameter modified by the network node based on the BP Al.

Example Embodiment D12. The method of any one of Example Embodiments DI to DI 1, wherein the BP Al is received in an RRC message.

Example Embodiment D13. The method of any one of Example Embodiments DI to DI 2, wherein the UE is configured to transmit a measurement report comprising a number N1 of beam measurements, and wherein the BPAI comprises: for each SSB index and/or each CSI-RS index, a number N1 of actual measurement values associated with a time period occurring before a time period associated with a measurement report.

Example Embodiment DI 4. The method of any one of Example Embodiments DI to DI 3, wherein the UE is configured to include predicted beam measurements in a measurement report, and wherein the BPAI comprises: for each SSB index and/or each CSI-RS index, a number N2 of predicted measurement values associated with a time period subsequent to a time period associated with the measurement report.

Example Embodiment D15. The method of any one of Example Embodiments DI to DI 4, wherein the network node comprises multiple TRPs, and wherein each TRP is associated with a set of SSB indices or CSI-RS resource indices, and wherein receiving the BPAI comprises: receiving a corresponding BPAI for each one of the multiple TRPs.

Example Embodiment DI 6. The method of any one of Example Embodiments DI to DI 5, further comprising configuring the UE to perform at least one measurement on or associated with the at least one beam received from the network node and estimate the BPAI based on the at least one measurement performed on or associated with the at least one beam transmitted from the network node.

Example Embodiment DI 7. The method of any one of Example Embodiments D2 to DI 6, wherein performing the at least one action based on the BPAI comprises using the BPAI to create a representative radio fingerprint trajectory for beam predictions.

Example Embodiment D18. The method of any one of Example Embodiments D2 to D17, wherein performing the at least one action based on the BPAI comprises: using the BPAI to determine a predicted signal quality of at least one beam to be subsequently transmitted; and based on the BP Al and/or a predicted signal quality, adjusting at least one network transmission parameter for the at least one beam to be subsequently transmitted.

Example Embodiment DI 9. The method of any one of Example Embodiments D2 to DI 8, wherein performing the at least one action based on the BP Al comprises storing the BP Al.

Example Embodiment D20. The method of any one of Example Embodiments DI to DI 9, further comprising receiving a plurality of BPAI, wherein each of the plurality of BP Al are associated with a corresponding one of a plurality of beams.

Example Embodiment D21. The method of any one of Example Embodiments DI to DI 9, further comprising receiving a plurality of BPAI, wherein each of the plurality of BPAI are associated with the at least one beam.

Example Embodiment D22. The method of any one of Example Embodiments D2 to D218, wherein performing the at least one action comprises: based on the at least the BPAI and/or the plurality of BPAI, generating or updating a machine learning (ML) model for predicting a channel quality of at least one beam to be subsequently transmitted by the network node; or based on the at least the BPAI and/or the plurality of BPAI, developing or updating an algorithm for predicting a channel quality of at least one beam to be subsequently transmitted by the network node.

Example Embodiment D23. The method of Example Embodiment D22, further comprising using the ML model and/or the algorithm to predict a channel quality of at least one beam to be subsequently transmitted by the network.

Example Embodiment D24. The method of Example Embodiment D23, wherein the channel quality comprises at least one predicted value associated with a time period (e.g., tn+i,tn+2, ... ) that is subsequent to a time period (e.g., ti,... ,tn) associated with the received BPAI.

Example Embodiment D25. The method of any one of Example Embodiments D22 to D24, wherein performing the at least one action comprises: based on the predicted channel quality of the at least one beam to be subsequently transmitted, adjusting at least one network transmission parameter; and based on the adjusted network transmission parameter, transmitting the at least one beam.

Example Embodiment D26. The method of Example Embodiment D25, further comprising transmitting the adjusted network transmission parameter to the UE.

Example Embodiment D27. The method of any one of Example Embodiments D22 to D26, wherein performing the at least one action comprises at least one of: adjusting at least one parameter; and transmitting the at least one adjusted parameter to the UE.

Example Embodiment D28. The method of Example Embodiment D27, wherein the adjusted parameter comprises and/or is associated with at least one of: handover of the UE, scheduling of the UE, link adaptation, and a beam management parameter.

Example Embodiment D29. The method of any one of Example Embodiments DI to D28, wherein the network node comprises a gNodeB (gNB).

Example Embodiment D30. The method of any of the previous Example Embodiments, further comprising: obtaining user data; and forwarding the user data to a host or a user equipment.

Example Embodiment D31. A network node comprising processing circuitry configured to perform any of the methods of Example Embodiments DI to D30.

Example Embodiment D32. A network node adapted to perform any of the methods of Example Embodiments DI to D30.

Example Embodiment D33. A computer program comprising instructions which when executed on a computer perform any of the methods of Example Embodiments DI to D30.

Example Embodiment D34. A computer program product comprising computer program, the computer program comprising instructions which when executed on a computer perform any of the methods of Example Embodiments DI to D30.

Example Embodiment D35. A non-transitory computer readable medium storing instructions which when executed by a computer perform any of the methods of Example Embodiments DI to D30.

Group E Example Embodiments

Example Embodiment El. A user equipment comprising: processing circuitry configured to perform any of the steps of any of the Group A and C Example Embodiments; and power supply circuitry configured to supply power to the processing circuitry.

Example Embodiment E2. A network node comprising: processing circuitry configured to perform any of the steps of any of the Group B and D Example Embodiments; power supply circuitry configured to supply power to the processing circuitry.

Example Embodiment E3. A user equipment (UE) comprising: an antenna configured to send and receive wireless signals; radio front-end circuitry connected to the antenna and to processing circuitry, and configured to condition signals communicated between the antenna and the processing circuitry; the processing circuitry being configured to perform any of the steps of any of the Group A and C Example Embodiments; an input interface connected to the processing circuitry and configured to allow input of information into the UE to be processed by the processing circuitry; an output interface connected to the processing circuitry and configured to output information from the UE that has been processed by the processing circuitry; and a battery connected to the processing circuitry and configured to supply power to the UE.

Example Embodiment E4. A host configured to operate in a communication system to provide an over-the-top (OTT) service, the host comprising: processing circuitry configured to provide user data; and a network interface configured to initiate transmission of the user data to a cellular network for transmission to a user equipment (UE), wherein the UE comprises a communication interface and processing circuitry, the communication interface and processing circuitry of the UE being configured to perform any of the steps of any of the Group A and C Example Embodiments to receive the user data from the host.

Example Embodiment E5. The host of the previous Example Embodiment, wherein the cellular network further includes a network node configured to communicate with the UE to transmit the user data to the UE from the host.

Example Embodiment E6. The host of the previous 2 Example Embodiments, wherein: the processing circuitry of the host is configured to execute a host application, thereby providing the user data; and the host application is configured to interact with a client application executing on the UE, the client application being associated with the host application.

Example Embodiment E7. A method implemented by a host operating in a communication system that further includes a network node and a user equipment (UE), the method comprising: providing user data for the UE; and initiating a transmission carrying the user data to the UE via a cellular network comprising the network node, wherein the UE performs any of the operations of any of the Group A embodiments to receive the user data from the host.

Example Emboidment E8. The method of the previous Example Embodiment, further comprising: at the host, executing a host application associated with a client application executing on the UE to receive the user data from the UE.

Example Embodiment E9. The method of the previous Example Embodiment, further comprising: at the host, transmitting input data to the client application executing on the UE, the input data being provided by executing the host application, wherein the user data is provided by the client application in response to the input data from the host application.

Example Emboidment E10. A host configured to operate in a communication system to provide an over-the-top (OTT) service, the host comprising: processing circuitry configured to provide user data; and a network interface configured to initiate transmission of the user data to a cellular network for transmission to a user equipment (UE), wherein the UE comprises a communication interface and processing circuitry, the communication interface and processing circuitry of the UE being configured to perform any of the steps of any of the Group A and C Example Embodiments to transmit the user data to the host.

Example Emboidment Ell. The host of the previous Example Embodiment, wherein the cellular network further includes a network node configured to communicate with the UE to transmit the user data from the UE to the host.

Example Embodiment El 2. The host of the previous 2 Example Embodiments, wherein: the processing circuitry of the host is configured to execute a host application, thereby providing the user data; and the host application is configured to interact with a client application executing on the UE, the client application being associated with the host application.

Example Embodiment El 3. A method implemented by a host configured to operate in a communication system that further includes a network node and a user equipment (UE), the method comprising: at the host, receiving user data transmitted to the host via the network node by the UE, wherein the UE performs any of the steps of any of the Group A and C Example Embodiments to transmit the user data to the host.

Example Embodiment E14. The method of the previous Example Embodiment, further comprising: at the host, executing a host application associated with a client application executing on the UE to receive the user data from the UE.

Example Embodiment El 5. The method of the previous Example Embodiment, further comprising: at the host, transmitting input data to the client application executing on the UE, the input data being provided by executing the host application, wherein the user data is provided by the client application in response to the input data from the host application.

Example Embodiment E16. A host configured to operate in a communication system to provide an over-the-top (OTT) service, the host comprising: processing circuitry configured to provide user data; and a network interface configured to initiate transmission of the user data to a network node in a cellular network for transmission to a user equipment (UE), the network node having a communication interface and processing circuitry, the processing circuitry of the network node configured to perform any of the operations of any of the Group B and D Example Embodiments to transmit the user data from the host to the UE.

Example Embodiment El 7. The host of the previous Example Embodiment, wherein: the processing circuitry of the host is configured to execute a host application that provides the user data; and the UE comprises processing circuitry configured to execute a client application associated with the host application to receive the transmission of user data from the host.

Example Embodiment El 8. A method implemented in a host configured to operate in a communication system that further includes a network node and a user equipment (UE), the method comprising: providing user data for the UE; and initiating a transmission carrying the user data to the UE via a cellular network comprising the network node, wherein the network node performs any of the operations of any of the Group B and D Example Embodiments to transmit the user data from the host to the UE.

Example Embodiment E19. The method of the previous Example Embodiment, further comprising, at the network node, transmitting the user data provided by the host for the UE.

Example Emboidment E20. The method of any of the previous 2 Example Embodiments, wherein the user data is provided at the host by executing a host application that interacts with a client application executing on the UE, the client application being associated with the host application.

Example Embodiment E21. A communication system configured to provide an over-the- top service, the communication system comprising: a host comprising: processing circuitry configured to provide user data for a user equipment (UE), the user data being associated with the over-the-top service; and a network interface configured to initiate transmission of the user data toward a cellular network node for transmission to the UE, the network node having a communication interface and processing circuitry, the processing circuitry of the network node configured to perform any of the operations of any of the Group B and D Example Embodiments to transmit the user data from the host to the UE.

Example Embodiment E22. The communication system of the previous Example Embodiment, further comprising: the network node; and/or the user equipment.

Example Embodiment E23. A host configured to operate in a communication system to provide an over-the-top (OTT) service, the host comprising: processing circuitry configured to initiate receipt of user data; and a network interface configured to receive the user data from a network node in a cellular network, the network node having a communication interface and processing circuitry, the processing circuitry of the network node configured to perform any of the operations of any of the Group B and D Example Embodiments to receive the user data from a user equipment (UE) for the host.

Example Embodiment E24. The host of the previous 2 Example Embodiments, wherein: the processing circuitry of the host is configured to execute a host application, thereby providing the user data; and the host application is configured to interact with a client application executing on the UE, the client application being associated with the host application.

Example Embodiment E25.The host of the any of the previous 2 Example Embodiments, wherein the initiating receipt of the user data comprises requesting the user data.

Example Embodiment E26. A method implemented by a host configured to operate in a communication system that further includes a network node and a user equipment (UE), the method comprising: at the host, initiating receipt of user data from the UE, the user data originating from a transmission which the network node has received from the UE, wherein the network node performs any of the steps of any of the Group B and D Example Embodiments to receive the user data from the UE for the host. Example Embodiment E27. The method of the previous Example Embodiment, further comprising at the network node, transmitting the received user data to the host.

Claims

1. A method (700) by a user equipment, UE, (112) comprising: receiving (702) at least one beam from a network node (110), and transmitting (704), to the network node, beam prediction assistance information, BP Al, associated with the at least one beam.

2. The method of Claim 1, comprising any one or more of: performing at least one measurement on the at least one beam received from the network node; and estimating the BPAI based on the at least one measurement performed on the at least one beam received from the network node.

3. The method of any one of Claims 1 to 2, wherein the BPAI comprises any one or more of: an index of an Rx beam; an indication of whether the at least one measurement was subject of or to blockage; and at least one uncertainty estimate associated with the at least one measurement.

4. The method of any one of Claims 1 to 3, wherein the BPAI comprises any one or more of: a state identifier for machine learning, ML; at least one estimated antenna gain associated with the at least one measurement and/or the at least one beam; at least one signal quality and/or reference direction associated with the at least one measurement and/or the at least one beam; at least one UE Receiver-angle associated with the at least one measurement and/or the at least one beam; an indication of a probability that a blockage is static; an indication of a probability that a blockage is dynamic; an estimate of a measurement value without blockage; an indication of a probability that the UE is located indoors; at least one time stamp associated with the at least one measurement; at least one reliability estimate associated with the at least one measurement; one or more predicted Synchronization Signal Block, SSB, indexes and/or one or more predicted Channel State Information-Reference Signal, CSI-RS, indexes; for each SSB index and/or CSI-RS index, a set of actual measurement values associated with a time period before a measurement reporting time period; for each reported SSB index and/or CSI-RS index, a set of predicted measurement values for a time period subsequent to a measurement reporting time period; channel information comprising doppler information and/or delay spread; at least one orientation of the UE with respect to earthbound coordinates; at least one receive antenna panel configuration; at least one transmit antenna panel configuration; a location of the UE; mobility information associated with the UE; an indication of whether the at least one measurement is filtered over more than one time instance; and an age of the at least one measurement value.

5. The method of any one of Claims 2 to 4, wherein the at least one measurement comprises at least one link quality measurement performed on the at least one beam and wherein the at least one link quality measurement comprises at least one of: at least one Reference Signal Received Power, RSRP, measurement; at least one Reference Signal Received Quality, RSRQ, measurement; and at least one Signal Interference to Noise Ratio, SINR, measurement.

6. The method of any one of Claims 2 to 5, wherein the at least one beam comprises: at least one Channel State Information, CSI, and/or at least one SSB.

7. The method of any one of Claims 1 to 6, wherein the BP Al is transmitted in or with at least one of: a measurement report; layer 3 beam measurement information; a CSI report for beam management; and a Medium Access Control-Control Element, MAC CE, for beam failure recovery, BFR.

8. The method of Claim 7, wherein the measurement report comprises at least one value associated with at least one signal quality measurement performed by the UE.

9. The method of any one of Claims 1 to 8, wherein prior to transmitting the BP Al, the method comprises at least one of: receiving, from the network node, a request for capability information; transmitting, to the network node, capability information indicating an ability of the UE to transmit the BPAI; and receiving, from the network node, a request for the BP Al.

10. The method of Claim 9, wherein the capability information further comprises a number of UE panels supported by the UE, wherein each UE panel is associated with a set of UE panel capabilities, a set of UE properties, and/or a UE panel identifier, and wherein each set of UE panel properties may include any one or more of: a number of transmitter chains, a number of receiver chains, a number of antenna elements, a max antenna gain, a maximum transmission power, single-polarized or dual polarized, and a pointing direction.

11. The method of any one of Claims 9 to 10, wherein the capability information indicates a UE panel identifier for each beam associated with a measurement report.

12. The method of any one of Claims 1 to 11, comprising: receiving, from the network node, at least one transmission parameter modified by the network node based on the BPAI, and based on the at least one transmission parameter that is adjusted by the network node, receiving at least one beam from the network node.

13. The method of Claim 12, wherein the at least one transmission parameter is associated with at least one of: a handover decision; a scheduling decision; link adaptation; and beam management.

14. The method of any one of Claims 1 to 13, wherein the BPAI is transmitted in a Radio Resource Control, RRC, message.

15. The method of any one of Claims 1 to 14, comprising at least one of: transmitting a measurement report comprising a number N1 of beam measurements, and wherein the BPAI comprises: for each Synchronization Signal Block, SSB, index and/or each Channel State Information-Reference Signal, CSI-RS, index, a number N1 of actual measurement values associated with a time period occurring before a time period associated with a measurement report; and transmitting a measurement report comprising at least one predicted beam measurement, and wherein the BP Al comprises: for each Synchronization Signal Block, SSB, index and/or each Channel State Information-Reference Signal, CSI-RS, index, a number N2 of predicted measurement values associated with a time period subsequent to a time period associated with the measurement report.

16. The method of any one of Claims 1 to 15, wherein the network node controls multiple Transmission Reception Points, TRPs, and wherein each TRP is associated with a set of Synchronization Signal Block, SSB, indices or Channel State Information-Reference Signal, CSI- RS resource indices, and wherein transmitting the BP Al comprises: transmitting BP Al for each one of the multiple TRPs.

17. A method (800) by a network node (110) comprising: transmitting (802), to a user equipment, UE, (112) at least one beam; and receiving (804), from the UE, beam prediction assistance information, BP Al, associated with the at least one beam.

18. The method of Claim 17, comprising at least one of: using the BP Al to determine a predicted signal quality of at least one beam to be subsequently transmitted by the network node; and based on the BP Al and/or the predicted signal quality, adjusting at least one transmission parameter for the at least one beam to be subsequently transmitted by the network node.

19. The method of Claim 18, comprising: transmitting, to the UE, the at least one transmission parameter adjusted by the network node.

20. The method of Claim 17, comprising: based on the at least the BP Al and/or a plurality of BPAI received from a plurality of UEs, generating or updating a machine learning, ML, model for predicting a signal quality of at least one beam to be subsequently transmitted by the network node; or based on the at least the BPAI and/or a plurality of BPAI received from a plurality of UEs, developing or updating an algorithm for predicting a signal quality of at least one beam to be subsequently transmitted by the network node.

21. The method of Claim 20, comprising using the ML model and/or the algorithm to predict the signal quality of the at least one beam to be subsequently transmitted by the network, and wherein the signal quality comprises at least one predicted value associated with a time period (e.g., tn+i,tn+2, ... ) that is subsequent to a time period (e.g., ti,... ,tn) associated with the received BPAI.

22. The method of any one of Claims 20 to 21, comprising: based on the predicted signal quality of the at least one beam to be subsequently transmitted, adjusting at least one transmission parameter; and based on the adjusted network transmission parameter, transmitting the at least one beam.

23. The method of Claim 22, comprising transmitting the adjusted transmission parameter to the UE.

24. The method of any one of Claims 22 to 23, wherein the adjusted transmission parameter comprises and/or is associated with at least one of: a handover of the UE, a scheduling of the UE, a link adaptation, and a beam management parameter.

25. The method of any one of Claims 17 to 24, wherein the BPAI comprises any one or more of: an index of an Rx beam; an indication of whether at least one measurement associated with the at least one beam was subject of or to blockage; and at least one uncertainty estimate associated with the at least one measurement associated with the at least one beam.

26. The method of any one of Claims 17 to 25, wherein the BPAI comprises any one or more of: a state identifier for ML; at least one estimated antenna gain associated with the at least one measurement and/or the at least one beam; at least one signal quality and/or reference direction associated with the at least one measurement and/or the at least one beam; at least one UE Rx-angle associated with the at least one measurement and/or the at least one beam; an indication of a probability that a blockage is static; an indication of a probability that a blockage is dynamic; an estimate of a measurement value without blockage; an indication of a probability that the UE is located indoors; at least one time stamp associated with the at least one measurement; at least one reliability estimate associated with the at least one measurement; one or more predicted Synchronization Signal Block, SSB, indexes and/or one or more predicted Channel State Information-Reference Signal, CSI-RS, indexes; for each Synchronization Signal Block, SSB, index and/or CSI-RS index, a set of actual measurement values associated with a time period before a measurement reporting time period; for each reported SSB index and/or CSI-RS index, a set of predicted measurement values for a time period subsequent to a measurement reporting time period; channel information comprising doppler information and/or delay spread; at least one orientation of the UE with respect to earthbound coordinates; at least one receive antenna panel configuration; at least one transmit antenna panel configuration; a location of the UE; mobility information associated with the UE; an indication of whether the at least one measurement is filtered over more than one time instance; and an age of the at least one measurement value.

27. The method of any one of Claims 17 to 26, comprising configuring the UE to perform at least one measurement on the at least one beam, wherein the at least one measurement comprises at least one link quality measurement, and wherein the at least one link quality measurement comprises at least one of: at least one Reference Signal Received Power, RSRP, measurement; at least one Reference Signal Received Quality, RSRQ, measurement; and at least one Signal Interference to Noise Ratio, SINR, measurement.

28. The method of any one of Claims 17 to 27, wherein the at least one beam comprises: at least one Channel State Information-Reference Signal, CSI-RS, and/or at least one Synchronization Signal Block, SSB.

29. The method of any one of Claims 17 to 28, wherein the BP Al is received in or with at least one of: a measurement report; layer 3 beam measurement information; a Channel State Information, CSI, report for beam management; and a Medium Access Control-Control Element, MAC CE, for beam failure recovery, BFR.

30. The method of Claim 29, wherein the measurement report comprises at least one value associated with at least one signal quality measurement performed by the UE.

31. The method of any one of Claims 17 to 39, wherein prior to receiving the BP Al, the method comprises at least one of: transmitting, to the UE, a request for capability information; receiving, from the UE, the capability information indicating an ability of the UE to transmit the BPAI; and transmitting, to the UE, a request for the BPAI.

32. The method of Claim 31, wherein the capability information indicates a number of UE panels supported by the UE, wherein each UE panel is associated with a set of UE panel capabilities, a set of UE properties, and/or a UE panel identifier, and wherein each set of UE panel properties may include any one or more of: a number of transmitter chains, a number of receiver chains, a number of antenna elements, a max antenna gain, a maximum transmission power, single-polarized or dual polarized, and a pointing direction.

33. The method of any one of Claims 31 to 32, wherein the capability information indicates a UE panel identifier for each beam associated with a measurement report.

34. The method of any one of Claims 17 to 33, wherein the BPAI is received in an Radio Resource Control, RRC, message.

35. The method of any one of Claims 17 to 34, comprising at least one of: configuring the UE to transmit a measurement report comprising a number N1 of beam measurements, and wherein the BPAI comprises: for each Synchronization Signal Block, SSB, index and/or each Channel State Information-Reference Signal, CSI-RS, index, a number N1 of actual measurement values associated with a time period occurring before a time period associated with a measurement report; and configuring the UE to include predicted beam measurements in a measurement report, and wherein the BPAI comprises: for each SSB index and/or each CSI-RS index, a number N2 of predicted measurement values associated with a time period subsequent to a time period associated with the measurement report.

36. The method of any one of Claims 17 to 35, wherein: the network node comprises multiple Transmission Reception Points, TRPs, each TRP is associated with a set of Synchronization Signal Block, SSB, indices or Channel State Information-Reference Signal, CSI-RS, resource indices, and receiving the BPAI comprises: receiving a corresponding BPAI for each one of the multiple TRPs.

37. The method of any one of Claims 17 to 36, comprising using the BPAI to create a representative radio fingerprint trajectory for beam predictions.

38. The method of any one of Claims 17 to 37, comprising receiving a plurality of BPAI, wherein each of the plurality of BPAI are associated with a corresponding one of a plurality of beams.

39. The method of any one of Claims 17 to 37, comprising receiving a plurality of BPAI, wherein each of the plurality of BPAI are associated with the at least one beam.

40. A user equipment, UE, adapted to: receive at least one beam from the network node, and transmit, to a network node, beam prediction assistance information, BPAI, associated with the at least one beam.

41. The UE of Claim 40, adapted to perform any of the methods of Claims 2 to 16.

42. A network node adapted to: transmit, to a user equipment, UE, at least one beam; and receive, from the UE, beam prediction assistance information, BPAI, associated with the at least one beam.

43. The network node of Claim 42, adapted to perform any of the methods of Claims 18 to 39.