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WO2025136207A1 - Data collection stop based on ue event - Google Patents

Data collection stop based on ue event Download PDF

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Publication number
WO2025136207A1
WO2025136207A1 PCT/SE2024/051117 SE2024051117W WO2025136207A1 WO 2025136207 A1 WO2025136207 A1 WO 2025136207A1 SE 2024051117 W SE2024051117 W SE 2024051117W WO 2025136207 A1 WO2025136207 A1 WO 2025136207A1
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WO
WIPO (PCT)
Prior art keywords
data collection
channel condition
channel
wireless device
measurement
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
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Application number
PCT/SE2024/051117
Other languages
French (fr)
Inventor
Johan AXNÄS
Yufei Blankenship
Chunhui Li
Henrik RYDÉN
Siva Muruganathan
Marco BELLESCHI
Reem KARAKI
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Telefonaktiebolaget LM Ericsson AB
Original Assignee
Telefonaktiebolaget LM Ericsson AB
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Publication of WO2025136207A1 publication Critical patent/WO2025136207A1/en
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Anticipated expiration legal-status Critical

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/318—Received signal strength
    • H04B17/328—Reference signal received power [RSRP]; Reference signal received quality [RSRQ]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0686—Hybrid systems, i.e. switching and simultaneous transmission
    • H04B7/0695—Hybrid systems, i.e. switching and simultaneous transmission using beam selection
    • H04B7/06952—Selecting one or more beams from a plurality of beams, e.g. beam training, management or sweeping
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00—Arrangements affording multiple use of the transmission path
    • H04L5/003—Arrangements for allocating sub-channels of the transmission path
    • H04L5/0048—Allocation of pilot signals, i.e. of signals known to the receiver
    • H04L5/005—Allocation of pilot signals, i.e. of signals known to the receiver of common pilots, i.e. pilots destined for multiple users or terminals

Definitions

  • the present disclosure generally relates to communication networks, and more specifically to stopping data collection based on a user equipment (UE) event.
  • UE user equipment
  • analog beamforming To reduce hardware costs, large antenna arrays for high frequencies use time-domain analog beamforming.
  • the core idea of analog beamforming is to share a single radio frequency chain between many (or potentially all) of the antenna elements.
  • a limitation of analog beamforming is that it is only possible to transmit radio energy using one beam (in one direction) at a given time.
  • the above limitation requires the network (NW) and user equipment (UE) to perform beam management procedures to establish and maintain suitable transmitter (Tx)/receiver (Rx) beam-pairs.
  • beam management procedures can be used by a transmitter to sweep a geographic area by transmitting reference signals on different candidate beams during nonoverlapping time intervals using a predetermined pattern. By measuring the quality of the reference signals at the receiver side, the best transmit and receive beams can be identified.
  • Beam management procedures in NR are defined by a set of layer one (Ll)/layer two (L2) procedures that establish and maintain suitable beam pairs for both transmitting and receiving data.
  • a beam management procedure can include the following sub procedures: beam determination, beam measurements, beam reporting, and beam sweeping.
  • the Pl procedure enables UE measurement on different transmission/reception point (TRP) Tx beams to support selection of TRP Tx beams/UE Rx beam(s).
  • TRP transmission/reception point
  • the gNB transmits synchronization signal (SS)/physical broadcast channel (PBCH) block (SSB) beams in different directions to cover the entire cell.
  • SS synchronization signal
  • PBCH physical broadcast channel
  • SSB synchronization signal
  • PBCH physical broadcast channel block
  • Figure 1 illustrates SSB beam selection as part of initial access procedure according to Pl scenario. Random access is then transmitted on the random access channel (RACH) resources indicated by the selected SSB. The corresponding beam will be used by both the UE and the network to communicate until connected mode beam management is active. The network infers which SSB beam was chosen by the UE without any explicit signaling.
  • RACH random access channel
  • Beamforming at a TRP typically includes an intra/inter-TRP Tx beam sweep from a set of different beams.
  • Beamforming at a UE typically includes a UE Rx beam sweep from a set of different beams.
  • the P2 procedure enables UE measurement on different TRP Tx beams to possibly change inter/intra-TRP Tx beam(s).
  • the network can use the SSB beam as an indication of which (narrow) channel state information reference signal (CSI-RS) beams to try; that is, the selected SSB beam can be used to define a candidate set of narrow CSI-RS beams for beam management.
  • CSI-RS channel state information reference signal
  • the UE measures the reference signal receive power (RSRP) and reports the result to the network.
  • RSRP reference signal receive power
  • the network If the network receives a CSI-RSRP report from the UE where a new CSI-RS beam is better than the old beam used to transmit physical downlink control channel (PDCCH)/physical downlink shared channel (PDSCH), the network updates the serving beam for the UE accordingly, and possibly also modifies the candidate set of CSI-RS beams.
  • the network can also instruct the UE to perform measurements on SSB s. If the network receives a report from the UE where a new SSB beam is better than the previous best SSB beam, a corresponding update of the candidate set of CSI-RS beams for the UE may be motivated.
  • the P2 procedure is performed on a possibly smaller set of beams for beam refinement than in Pl.
  • P2 can be a special case of Pl.
  • gNB configures the UE with different CSI-RSs and transmits each CSI-RS on a corresponding beam.
  • the UE measures the quality of each CSI-RS beam on its current RX beam and sends feedback about the quality of the measured beams. Thereafter, based on this feedback, the gNB will determine and possibly indicate to the UE which beam will be used in future transmissions.
  • An example is illustrated in Figure 2.
  • Figure 2 illustrates CSI-RS Tx beam selection in downlink according to P2 scenario.
  • P3 can be used by the UE to find the best Rx beam for a corresponding Tx beam.
  • the gNB keeps one CSI-RS Tx beam at a time, and the UE performs the sweeping and measurements on its own Rx beams for that specific Tx beam. The UE then finds the best corresponding Rx beam based on the measurements and will use it in future for reception when gNB indicates the use of that Tx beam.
  • reportQuantity Defines the reported CSI parameters — the CSI content; for example, the precoding matrix indicator (PMI), channel quality indicator (CQI), rank indicator (RI), layer indicator (LI), CSLRS resource index (CRI) and Ll-RSRP. Only certain combinations are possible, for example, ‘cri-RI-PMI-CQI’ is one possible value and ‘cri- RSRP’ is another) and each value of reportQuantity could be said to correspond to a certain CSI mode.
  • PMI precoding matrix indicator
  • CQI channel quality indicator
  • RI rank indicator
  • LI layer indicator
  • CSLRS resource index CSLRS resource index
  • Ll-RSRP Ll-RSRP
  • reportFrequencyConfiguration Define the frequency granularity of PMI and CQI (wideband or subband), if reported, along with the CSI reporting band, which is a subset of subbands of the bandwidth part (BWP) that the CSI corresponds to.
  • 3GPP has also studied using artificial intelligence (AI)/machine learning (ML) based spatial beam prediction, the core idea of which is as follows: predict the “best” beam (or beams) from a Set A of beams using measurement results from another Set B of beams.
  • AI artificial intelligence
  • ML machine learning
  • Figure 4 illustrates a grid-of-beam type radiation pattern. Each row (resp. column) depicts a certain zenith (resp. azimuth) angle from the antenna array. Set A has 8 beams and Set B has 4 beams (indicated by dark circles).
  • Set A and Set B correspond to two different sets of beams.
  • Set A is a set of 30 narrow CSI-RS beams
  • Set B is a set of 8 wide SSB beams.
  • the UE measures beams in Set B and the AI/ML model should predict the best beam(s) from Set A.
  • Figure 5 illustrates an example where Set A is a set of narrow beams and Set B is a set of wide beams.
  • the spatial beam prediction can be performed in the gNB or the UE.
  • 3 GPP will study AI/ML model training both at the NW and UE side. Which side performs the training is expected to impact how data collection is performed, where 3GPP will also study the aspect of data collection for beam management. 3GPP will also study the aspect of model monitoring and the standard impact on AI/ML model inference (e.g., reporting of predicted values).
  • Link quality related KPIs e.g., throughput, Ll-RSRP, Ll-SINR, hypothetical BLER
  • UE calculates performance metric(s), either reports it to NW or reports an event to NW based on the performance metric(s)
  • the indication/request/report may be not needed in some case(s)
  • a key part of AI/ML-based prediction is data collection. Data collection is performed in several stages of the life-cycle management (LCM). [0042] First, the model must be trained by collecting measurement data for a large set of UE locations/channel conditions representative for the UE locations/channel conditions that may be encountered during use of the model (i.e., inference). For each UE, preferably all possible narrow Tx beam directions should be swept, i.e., a fairly large set of beams.
  • the NW transmits a signal (e.g., CSI-RS or SSB) using a set of several different Tx beams on the downlink.
  • a signal e.g., CSI-RS or SSB
  • the UE measures the RSRP (or some other reporting quantity) of the different transmissions.
  • the measurements by the UE are subject to measurement errors.
  • the relative error i.e., the difference in reported measurement value for two measurements that were performed under the same nominal conditions and should thus ideally be identical
  • the relative error can be substantial, up to 6.5 dB under normal condition, see Table 10.1.20.1.2-1 of 3GPP TS 38.133, reproduced below for convenience.
  • the measurement error is a combination of several different sources, including the fact that different receive chains in the UE may have different absolute error. As a consequence, assuming for example that each antenna panel in the UE uses a different receive chain, the relative measurement error between two measurement occasions may on average be smaller if both measurements were made using the same antenna panel. Furthermore, it is possible that the relative error between two measurements is affected by other circumstances, e.g. the time interval between the two measurements, whether the UE has to switch temporarily to another Rx beam to listen to another signal between the two measurements, or if the UE has to temporarily stop listening to transmit between the two measurements.
  • Table 10.1.20.1.2-1 SSB based L1-RSRP relative accuracy in FR2
  • TRS tracking reference signal
  • TDCP time domain channel property
  • the TDCP feature defines UE estimation and reporting of the ‘wideband normalized correlation’ (WNC) between two TRS symbols separated by D symbols. This should be interpreted as an estimate of the normalized channel correlation in time as given by where h n (t) is the channel for subcarrier n at time t and At corresponds to the D symbols separating the two TRS symbols.
  • the correlation delay At is configurable and can take the values 4 OFDM symbols, 1 slot, 2 slots, 3 slots, 4 slots, 5 slots, 6 slots and 10 slots (10 slots is applicable only to 30kHz subcarrier spacing).
  • the maximum correlation delay a UE supports is subject to UE capability.
  • a UE that supports TDCP supports at least correlation delays up to 1 slot.
  • the UE can be configured to report both the amplitude (e.g., wideband normalized correlation amplitude (WNCA)) and the phase (e.g., wideband normalized correlation phase (WNCP)) of the correlation A(t, At). Reporting of the phase is, however, subject to UE capability.
  • WNCA wideband normalized correlation amplitude
  • WNCP wideband normalized correlation phase
  • the UE measurement has to be performed across the TRS bursts of two different TRSs.
  • the two TRSs should have a relative slot offset corresponding to the correlation lag At .
  • the TRS which is anyway configured for tracking purposes may be reused also for TDCP, but one additional TRS needs to be configured.
  • the extra TRS could have a longer periodicity than the TRS used for tracking to save overhead, as illustrated in Figure 6.
  • Figure 6 is a time/frequency diagram illustrating TRS bursts.
  • the horizontal axis represents time, and the vertical axis represents frequency.
  • the UE measurement can be made within one two-slot TRS burst. This means that only the TRS that is already configured for tracking purposes is needed.
  • the gNB-UE channel can change over time.
  • the channel change can be due to movement, either of the UE or things in its environment.
  • rotational movement of the UE may potentially be quite fast even in an indoor environment.
  • the UE is free to select the Rx beam and/or the UE panel it uses for reception, effectively changing the gNB-UE channel, possibly quite abruptly, even in absence of physical movement of the UE or its surroundings.
  • the changing channel is a problem for several reasons, especially for collection of Set A (prediction set) during training.
  • Set A is large and thus collecting Set A may take significant time, making the risk of substantial channel changes during its collection large.
  • Tx beam B may result in a better measured RSRP value, even if Tx beam A is a better Tx beam to reach the UE. This will mislead the training.
  • a UE stops measurements when a channel changes beyond a threshold value (or the UE suspects that the channel has changed beyond a threshold value) such that the artificial intelligence (AI)/machine learning (ML) model is not expected to work.
  • AI artificial intelligence
  • ML machine learning
  • the UE may choose among several different actions, e.g. informing network about the stop but resume sweep, restarting the sweep, informing the network about the stopped sweep and await further instructions from the network, etc.
  • a method is performed by a wireless device.
  • the method comprises: measuring one or more reference signals for data collection (e.g., for use with a machine learning model); determining that a change to a channel condition associated with the one or more reference signals impacts the data collection; and based on the determination, stopping the data collection.
  • determining that a change to a channel condition associated with the one or more reference signals impacts the data collection comprises determining that the channel condition has changed beyond a threshold value during the data collection.
  • the method further comprises reporting to a network node an indication that the data collection was stopped.
  • the indication that the data collection was stopped may comprise an indication of the channel condition that caused the data collection to stop. Reporting the indication that the data collection was stopped may comprise reporting data collected prior to determining that the channel condition changed.
  • TDCP time domain channel property
  • the threshold value is dependent on a purpose of the data collection.
  • a purpose of the data collection may be for machine learning model inference and the threshold value may be based on a value used for training the machine learning model.
  • a wireless device comprises processing circuitry operable to perform any of the wireless device methods described above.
  • a method is performed by a network node. The method comprises: configuring a wireless device to measure one or more reference signals for data collection; and receiving an indication from the wireless device that the data collection was stopped based on a determination that a change to a channel condition associated with the one or more reference signals impacted the data collection.
  • configuring the wireless device to measure the one or more reference signals for data collection comprises determining the channel condition associated with the one or more reference signals has not changed beyond a threshold value for a time duration.
  • the method further comprises, in response to receiving the indication, stopping use of a machine learning model.
  • a network node comprises processing circuitry operable to perform any of the network node methods described above.
  • a computer program product comprising a non-transitory computer readable medium storing computer readable program code, the computer readable program code operable, when executed by processing circuitry to perform any of the methods performed by the wireless device described above.
  • Another computer program product comprises a non-transitory computer readable medium storing computer readable program code, the computer readable program code operable, when executed by processing circuitry to perform any of the methods performed by the network node described above.
  • Certain embodiments may provide one or more of the following technical advantages.
  • benefits from the UE stopping a sweep such as: the network will not train an AI/ML model incorrectly due to changes in channel conditions during training; the network will not waste radio resources on a beam sweep that will not be useful; and a UE may save energy from not performing measurements that will not be useful.
  • FIG. 1 illustrates synchronization signal block (SSB) beam selection as part of initial access procedure according to Pl scenario
  • Figure 2 illustrates channel state information reference signal (CSI-RS) Tx beam selection in downlink according to P2 scenario;
  • SSB synchronization signal block
  • CSI-RS channel state information reference signal
  • Figure 3 illustrates user equipment (UE) Rx beam selection for a corresponding CSI-RS Tx beam in downlink according to P3 scenario
  • Figure 4 illustrates a grid-of-beam type radiation pattern
  • Figure 5 illustrates an example where Set A is a set of narrow beams and Set B is a set of wide beams;
  • FIG. 6 is a time/frequency diagram illustrating tracking reference signal (TRS) bursts
  • Figure 7 is a flowchart illustrating the general steps of particular embodiments.
  • Figure 8 illustrates three examples of reference signal configuration for channel change estimation using time domain channel property (TDCP) measurements
  • Figure 9 illustrates three measurement groups
  • Figure 10 shows an example of a communication system, according to certain embodiments.
  • FIG 11 shows a user equipment (UE), according to certain embodiments.
  • Figure 12 shows a network node, according to certain embodiments.
  • Figure 13 is a block diagram of a host, according to certain embodiments.
  • Figure 14 is a block diagram illustrating a virtualization environment in which functions implemented by some embodiments may be virtualized
  • Figure 16 is a flowchart illustrating an example method in a wireless device, according to certain embodiments.
  • Figure 17 is a flowchart illustrating an example method in a network node, according to certain embodiments.
  • a UE stops measurements when a channel changes beyond a threshold value (or the UE suspects that the channel has changed beyond a threshold value) such that the artificial intelligence (AI)/machine learning (ML) model is not expected to work.
  • AI artificial intelligence
  • ML machine learning
  • Figure 7 is a flowchart illustrating the general steps of particular embodiments.
  • a UE during a data collection procedure consisting of the UE performing radio measurements related to inference/training/monitoring of an AI/ML model estimates that a channel condition has changed beyond a certain threshold
  • the UE takes an action that impacts the data collection procedure.
  • Some embodiments include how to detect a channel change (e.g., step 130) where the channel condition change is based on one or more measurement quantities, e.g., UE sensors (e.g., gyroscope or temperature sensor); UE channel measurements (including time domain channel property (TDCP) measurements); UE historical information, for example the UE has historically experienced a certain channel environment (e.g., coherence time of x ms), and/or the UE making a change in its setting/configuration (e.g., due to hardware error, energy savings, or other reason) that affects the effective channel conditions, e.g. switching Rx beam/panel/Rx RF chain (e.g.. due to hardware error, energy saving, etc.).
  • UE sensors e.g., gyroscope or temperature sensor
  • UE channel measurements including time domain channel property (TDCP) measurements
  • UE historical information for example the UE has historically experienced a certain channel environment (e.g., coherence time of
  • Some embodiments include a triggering event (e.g., step 130) where “channel conditions have changed beyond some threshold” (CCCBT) is that the UE has moved more than one channel coherence length (or a signaled/configure/predefined factor times the channel coherence length) for UE channel measurements, where CCCBT is that one or more WNCA(s) in the TDCP measurement are below one or more predefined threshold(s), where the channel conditions in form of interference have changed beyond some maximum allowed threshold, where CCCBT is that the UE has rotated more than a certain angle, where the angle is an absolute angle in azimuth and or elevation, and/or where the angle is relative to the UE Rx beam width.
  • CCCBT channel conditions have changed beyond some threshold
  • Some embodiments include channel condition evaluation granularity, wherein the channel condition is evaluated: per beam, i.e. SSB/CSI-RS resource; per set of beams, i.e. SSB/CSI-RS resource; per cell, or per UE.
  • the radio measurements consist of determining per channel radio measurement results, such as reference signal receive power (RSRP), reference signal receive quality (RSRQ), signal to interface and noise ratio (SINR), reference signal strength indicator (RS SI), etc.
  • RSRP reference signal receive power
  • RSRQ reference signal receive quality
  • SI reference signal strength indicator
  • Some embodiments include triggering event fulfillment.
  • the fulfillment of one or more of the triggering events implies determining that the channel conditions have changed.
  • the unfulfillment of one or more of the triggering events implies determining that the channel conditions have not changed, i.e. the channel is stable.
  • all the triggering events should be unfulfilled to determine that the channel conditions have not changed, i.e. the channel is stable.
  • Some embodiments include threshold configuration (e.g., step 120), where the threshold is preconfigured in the standards (e.g. 3 GPP defined); and/or information configured by or signaled from the network.
  • the standards e.g. 3 GPP defined
  • Some embodiments include multiple thresholds, where there are multiple thresholds combined, e.g. via “logical or” or “logical and,” or a more complicated function.
  • the action to take is prescribed in the specifications, or configured/ signaled by the network, and/or depends on whether the data being collected is for training, inference, or monitoring, and/or depends on whether partial sweeps are allowed (based on configuration by the network).
  • the type of action performed comprises one or more of the following actions: the UE informs the network and reports (appropriately processed) measurement results related to measurements performed prior to the channel condition change (e.g., under the condition that the channel is stable); the UE stops radio measurements related to measurements performed prior to the channel condition change; the UE restarts the radio measurements (possibly by continuing from the current point in the sweep); aborts the measurement (without reporting measurements so far, but informing the network about the abort) related to measurements performed prior to the channel condition change; and/or the UE logs and stores, e.g. in a variable allocated in the UE memory, the measurement results related to measurements performed prior to the channel condition change. The measurement results are stored until they are reported to the network.
  • Some embodiments include reporting of radio measurements results to the network (e.g., step 150), comprising the UE reporting the radio measurements including one or more of the following information associated to radio measurements: one or more radio measurement results (e.g., RSRP, RSRQ, SINR, RSSI) performed under the conditions that the channel is stable; the one or more triggering events that were fulfilled determining that channel conditions are changed; the amount of time (e.g., in terms of consecutive radio resources such as orthogonal frequency division multiplexing (OFDM) symbols or slots, or in terms of milliseconds or seconds) the channel was determined as stable; an indication of the one or more beams, e.g. SSB/CSI-RS index, for which the radio measurement results were performed; and/or an indication of the cell in which the radio measurements were performed.
  • one or more radio measurement results e.g., RSRP, RSRQ, SINR, RSSI
  • the amount of time e.g., in terms of consecutive radio resources such as orthogonal frequency division multiplexing
  • the report may comprise radio measurements performed in different channels and performed at different points in time.
  • the above information may be associated to radio measurements performed in a first channel in a given point in time, and the report may include the above information for each radio measurement performed in a channel at a given point in time.
  • Some embodiments include capability reporting (e.g., step 100).
  • the network configuration on the channel condition change event is based on the UE capability information, where the UE can indicate one or more of: support for estimating the channel coherence time; support for estimating channel condition change (or channel variation) based on TDCP measurement; and/or support for external sensors such as inertial measurement units (IMUs).
  • IMUs inertial measurement units
  • the UE informs the network about current channel stability (according to any type of measurements, etc., listed in other embodiments, e.g. TDCP measurements)
  • Some embodiments include a determination of when to initiate data collection (e.g., step 110).
  • the network decision on whether to collect data is based on a UE signaling that it currently is experiencing stable channel conditions. For example: the UE is stationary and not rotating (based on external sensors); UE speed is less than X km/h; UE observes a long channel coherence time (e.g., via measurements on SSB beams); UE observes that one or more WNCA(s) in the TDCP measurement are above one or more predefined threshold(s) (for example, UE observes WNCAs closer to 1); and/or the UE estimates how many beams the UE can measure before channel conditions have changed beyond some threshold, and informs the network about it. The network then decides on whether to initiate data collection.
  • the network configures and/or signals to the UE to start data collection when the channel is deemed stable enough according to some criterion, e.g. based on TDCP measurements, or measurements based on the same quantities as TDCP.
  • the configuration/signaling includes an indication of a time interval (expressed in seconds, slots, OFDM symbols, or other system time-domain-related quantity) of when the collection is allowed to start, or must start (i.e., overriding the start criterion based on stable channel).
  • the UE starts measurements even when the criterion of stable channel is not fulfilled, and in some embodiments, the UE does not start measurements for the data collection until the channel stability criterion is fulfilled (but still makes measurements needed to check or estimate if the criterion is fulfilled).
  • the channel stability criterion is configured/signaled by the network. In some embodiments, the channel stability criterion is based on the channel conditions for a certain amount of time/slots, potentially configured or signaled by the network.
  • channel may refer to the channel from gNB antenna elements to UE antenna elements, or the effective channel, where aspects such as beamforming, UE radio frequency (RF) chain configuration or properties, etc., are considered.
  • RF radio frequency
  • a method includes the following steps.
  • a UE is configured for data collection.
  • no channel condition change estimation is explicitly configured; the channel condition change may be specified in 3 GPP specifications without explicit configuration or up to UE implementation.
  • the UE measures beam data.
  • the UE checks if the channel conditions have changed with a certain amount. If yes, the data collection is stopped.
  • the UE performs certain actions in response to determining that the channel conditions have changed.
  • the UE reports information on the beam data collection, including information on the channel condition change if present (e.g., that the UE stopped the data collection in time instance N due to channel condition change).
  • What action to take may also be configured/signaled by the network. Examples of actions are given in embodiments below.
  • Some embodiments include UE capabilities reporting (e.g., step 100).
  • the UE may, prior to the data collection step, indicate to the network its capabilities for estimating a channel condition change.
  • the UE may indicate its capabilities for support of: estimating the channel coherence time; estimating channel condition change (or channel variation) based on TDCP measurement; and/or external sensors, such as IMUs.
  • Some embodiments include initiating data collection (e.g., step 110).
  • the initiation of data collection may be purely network-based, for example for low network load or good UE channel signal quality.
  • the data collection may also be UE-assisted in another embodiment.
  • a UE for example estimates how many beams the UE can measure before channel conditions have changed beyond some threshold and informs the network about it. The network determines whether to initiate data collection.
  • the data collection is initiated by the UE when the UE experiences stable (non-varying) channel conditions.
  • the UE may experience a nonvarying channel under one or more of the following conditions: UE is stationary and not rotating (based on external sensors), e.g., UE speed is less than X km/h; observes a long channel coherence time (e.g., via measurements on SSB beams); and/or observes a TDCP wideband normalized correlation between two CSI-RSs (or TRSs) is above a threshold; a threshold value close to 1 may be used as the wideband normalized correlation is closer to 1 when the channel is not varying over time.
  • Some embodiments include determining changed channel conditions and/or implementation error (e.g., step 130b).
  • the determination of whether channel conditions have changed beyond a threshold value is based on whether the UE determines that the TDCP measurement performed by the UE indicates a wideband normalized correlation amplitude (WNCA) between two reference signals (RSs) is smaller than a threshold T tr .
  • the threshold T tr may be configured to the UE by the network or may be specified or pre-defined in 3 GPP specifications.
  • Figure 8 illustrates three examples of reference signal configuration for channel change estimation using TDCP measurements.
  • Example 1 of Figure 8 shows two periodic RSs where RS2 is delayed from RSi by Di symbols or slots.
  • the UE measures TDCP corresponding to a correlation delay of Di.
  • the UE compares the WNCA associated with the TDCP measurement corresponding to correlation delay Di to the threshold T tr . If the WNCA corresponding to correlation delay Di is larger than the threshold T tr (i.e., if WNCA > T tr ), then the UE determines that the channel conditions have changed. Otherwise, the UE determines that the channel conditions have not changed.
  • the condition WNCA > T tr may be used for determining the channel conditions have changed instead of using WNCA > T tr -
  • TDCP measurements with two or more WNCAs may be used to determine whether channel conditions have changed.
  • Example 2 of Figure 8 shows three periodic RSs used for TDCP measurements where RS2 is delayed from RSi by Di symbols or slots, and RS3 is delayed from RSi by D2 symbols or slots.
  • RS2 is delayed from RSi by Di symbols or slots
  • RS3 is delayed from RSi by D2 symbols or slots.
  • WNCAs associated with correlation delays Di and D2 via WNCA and WNCA 2 , respectively.
  • Two threshold values T tr l and T tr 2 may be configured to the UE by the network or may be specified pre-defined in 3GPP specifications.
  • the threshold values may be specific to the value of the correlation delays (i.e., a first pre-defined threshold value for correlation delay of 4 symbols, a second pre-defined threshold value for correlation delay of 1 slot, a third pre-defined threshold value for correlation delay of 2 slots, etc.).
  • the UE measures TDCP corresponding to correlation delays of Di and D2.
  • the UE compares the WNCAs associated with correlation delays Di and D2 to the thresholds T tr l and T tr 2 .
  • the UE determines that the channel conditions have changed if the following conditions are met: WNCA r > T Tr l , WNCA 2 > T Tr 2 .
  • the UE determines that the channel conditions have not changed.
  • the conditions WNCA > T tr l and WNCA 2 > T tr 2 may be used for determining the channel conditions have changed instead of using WNCA > T tr l and WNCA 2 > T tr 2 .
  • TDCP measurements with two or more WNCAs may be used to determine whether channel conditions have changed with only a single periodic RS.
  • different integer multiples of the periodicity of the RS are used as the correlation delays.
  • Example 3 of Figure 8 shows a single periodic RS used for TDCP measurements where the first correlation delay Di is set to one times the periodicity of the RS, and the second correlation delay D2 is set to two times the periodicity of the RS.
  • the UE measures WNCA and WNCA 2 associated with correlation delays Di and D2 , respectively.
  • the conditions for UE determining the channel conditions have changed are similar to those of Example 2 of Figure 8 above.
  • the RSs in the above embodiments may be one of tracking reference signals (TRSs), CSI-RSs, or SSBs.
  • TRSs tracking reference signals
  • the UE uses the TDCP measurements only for the purpose of determining whether the channel conditions have changed, and the UE does not report the TDCP measurements to the network.
  • the UE may report the TDCP measurements to the network, and the network may also determine whether the channel conditions have changed for the UE by comparing the WNCAs with the respective thresholds.
  • the determination of whether channel conditions have changed beyond a threshold value is based on whether the UE estimates whether the UE has moved more than one channel coherence length since the start of the measurement set.
  • the channel coherence time may for example be estimated via the network reports the same beam over multiple time occasions.
  • the channel coherence time may also be estimated by the UE via measuring the delay spread of the channel in each time-instance. A large delay spread typically indicates a shorter channel coherence time.
  • the determination of whether channel conditions have changed beyond a threshold value is based on how much the UE has rotated.
  • the threshold in terms of angles or other quantity representing UE rotation may be based on UE beam width and may be different for different axis of rotation if the UE has different beam widths in different dimensions.
  • the UE rotation may be estimated, e.g., based on a gyroscope in the UE.
  • the determination of whether channel conditions have changed beyond a threshold value is based on UE changing the UE panel with which it performs the measurements during a training or inference sweep.
  • both UE linear movement and rotation are considered in determining if the channel conditions have changed beyond a threshold value.
  • there are separate thresholds for linear movement and rotation and the channel conditions are considered to have changed beyond a threshold value if any of the thresholds have been exceeded.
  • both linear movement and rotation are considered by computing a pre-defined function of the two quantities and comparing it with a single threshold.
  • a UE might stop, restart and/or drop measurements when the interference levels from neighboring cell are higher than the threshold configured by the network via RRC or DCI, where the threshold may also be determined by UE based on UE implementation. For example, the UE might get reference values by previously monitoring periodic reference signals, i.e., multiple occasions of SSB burst. In one embodiment, the UE might stop, restart and/or drop measurements when the UE is changing the surrounding environment which might cause the significant variations of channel conditions. For example, if the UE is moving from the outdoor scenario to the indoor scenario, the UE might stop the measurement for a time. In another example, if the UE is waiting for a coming high-speed train and is ready to onboard the high speed train, the UE might stop the measurement for a time due to the transition.
  • the AI/ML model is trained with measurement data that takes into account a certain range of implementation imperfection, measured signal quality, and/or measurement errors of the gNB or the UE.
  • implementation related measurement or measurement errors may include, for example: network synchronization error; UE/gNB RX and TX timing error; channel estimation error; estimated channel quality such as SINR, RSRP (Reference Signal Received Power), RSRQ (Signal Reference Signal Received Quality), RSRPP (reference signal received path power), Es/Iot .
  • Es Received energy per RE (power normalized to the subcarrier spacing) during the useful part of the symbol, i.e. excluding the cyclic prefix, at the UE antenna connector or radiated interface boundary.
  • the received power spectral density of the total noise and interference for a certain RE power integrated over the RE and normalized to the subcarrier spacing
  • the model is likely to fail if the corresponding value experienced during model inference is outside the designed range. This is especially true if the actual quality or error is worse than the designed range.
  • the model is not expected to generate useful model output.
  • the model is designed to handle UE timing error in the range of -10ns to 10ns (e.g., the training dataset contains measurement data with UE timing error in the range of -10ns to 10ns), while the actual UE timing error in model inference is -20 ns, then the model is not expected to generate useful output.
  • the quality of measurement data should be monitored to determine if the measurement data is acceptable to be used as model input. The determination is with reference to the designed measurement quality range or measurement error range of the model input for the trained model. This implies that the trained model should be stored together with the information on the applicability condition of the model input, including the measurement quality range or measurement error range of the model input for the trained model. [0122] When the quality of measurement data for model input is determined to be worse than the acceptable quality, then actions are to be taken to avoid using the corresponding AI/ML model output which is likely to degrade the system performance.
  • the fulfillment of one or more of the triggering events implies determining that the channel conditions have changed.
  • the unfulfillment of one or more of the triggering events implies determining that the channel conditions have not changed, i.e. the channel is stable.
  • all the triggering events should be unfulfilled to determine that the channel conditions have not changed, i.e. the channel is stable.
  • Some embodiments determine various actions to take (e.g., step 140 in Figure 7). In some embodiments, the action comprises at least that the UE informs the network that it has stopped measurements (e.g., step 150 in Figure 7).
  • the action comprises at least that the UE reports the (possibly pre-processed) measurements so far, prior to the channel condition changing, i.e. under the condition that the channel is stable.
  • the pre-processing may, e.g., be selecting the N best measurements.
  • the action is pre-defined in the standard/specifications (step 140b in Figure 7 is not needed). In some embodiments, the action is based on RRC configuration. In some embodiments, the action is based on DCI signaling.
  • the UE stops the measurement during the measurement occasion, as soon as it is determined that the channel condition has changed.
  • the UE when the UE stops the measurement during the measurement occasion, the UE might drop the measurements and immediately indicate to the network that no valid measurement could be reported in the scheduled uplink resource.
  • the network may perform the reconfiguration of resources that are previously scheduled for such UE to report the measurements.
  • the UE when the UE stops the measurements during the measurement occasion, the UE might resume the measurements based on some predetermined or configured time offset, where the time offset is agreed between the network and UE. After the measurement period, the UE only reports the valid measurements with additional 1 -bit indication for network to know that some measurements are dropped. In some embodiments, the UE reports the valid measurements with additional bits for the network to know more detailed information of the dropped measurements.
  • the UE when the UE stops the measurement during the measurement occasion, the UE might drop the measurements and indicate to the network on the scheduled uplink resource that the measurements are stopped and dropped. The UE may skip the indication because the network may implicitly know that the measurements might be stopped or dropped or skipped by the UE.
  • the UE upon determining that the channel conditions have changed, the UE logs and stores, e.g. in a variable allocated in the UE memory, the measurement results related to measurements performed prior the channel condition changing, i.e. under the condition that the channel is stable. For example, the UE stops the radio measurement collection upon determining that the channel conditions have changed and logs the radio measurements collected so far. The measurement results are stored until they are reported to the network.
  • the UE may store in the UE memory radio measurements collected at different points in time, wherein each stored radio measurement (comprising RSRP, RSRQ, SINR, RSSI) are associated to radio measurements performed in radio channel under the condition that the radio channel was stable.
  • each stored radio measurement comprising RSRP, RSRQ, SINR, RSSI
  • the network may configure the UE if reporting partial sweeps is allowed or not. The action taken by the UE may then depend on this configuration. For example, if reporting partial sweeps is allowed, the UE may log the partial sweep in the Al data report, and if not allowed, the UE may discard the sample and restart the sweep.
  • the entity that performs the measurement for AI/ML model input does not provide the unavailable or unacceptable measurements for AI/ML model.
  • the entity that performs the measurement provides measurements as possible AI/ML model input, while attaching a message regarding the measurement quality, particularly if the measurement quality is poorer than acceptable.
  • Entity-A the entity that performs the measurement
  • Entity-B the same entity that performs AI/ML model inference
  • Entity -B Entity -A in this case.
  • Entity-A may take one of the following actions to address the problem of unavailable or unacceptable measurements.
  • Entity-A stops performing AI/ML model inference with the current AI/ML model and uses a different AI/ML model to generate the desired model output, where the different AI/ML model is capable of accepting this type of measurement as model input (e.g., capable of accepting measurements with worse measurement error).
  • Entity-A stops performing AI/ML model inference, and uses a fallback method (i.e., non-AI/ML based) to generate the desired model output to fulfill the functionality of the AI/ML model (e.g., beam prediction, UE position estimation, etc.).
  • a fallback method i.e., non-AI/ML based
  • Entity-A stops performing AI/ML model inference and sends an indicator to the entity that receives the model output (denoted as Entity-C) that an error has occurred with the AI/ML model.
  • the indicator may include an error code, for example, “Unexpected error with model input measurement.”
  • the entity that performs the measurement (denoted as Entity-A) is different from the entity that performs AI/ML model inference (denoted as Entity-B, and Entity- B ⁇ Entity-A in this case).
  • Entity A may take one of the following actions to address the problem of unavailable or unacceptable measurements.
  • Entity-A sends the measurement(s) as is to Entity-B, together with an indicator of the measurement quality.
  • the measurement quality indicator may notify Entity-B one or more of the following: (a) channel estimation error level (e.g., in-range, out-of-range) experienced when performing the measurement; (b) timing error level (e.g., in-range, out-of-range) of the circuit performing the measurement; (c) noise and/or inference level (e.g., in-range, out-of-range) associated with the measurement.
  • Entity-B decides whether to use the measurement as model input to its AI/ML model or discard the measurement (e.g., due to unacceptable measurement quality) and take actions similar to (l.a)-(l.c).
  • Entity-A sends a substitute measurement(s) to Entity-B, together with an indicator of the measurement quality.
  • the substitute measurement may be a historical value, or calculated based on historical value(s) (e.g., weighted average of previous N measurements).
  • the measurement quality indicator may notify Entity-B, e.g., “Reported measurement is replaced with a historical value due to larger-than-expected receiver error”.
  • Entity-B decides whether to use the substitute measurement as model input to its AI/ML model or discard the substitute measurement (e.g., due to unacceptable measurement quality) and take actions similar to (l.a)-(l .c).
  • Entity-A does not send the measurement(s) to Entity-B. Instead, Entity-A sends Entity -
  • Entity-B can take actions similar to (l.b)-(l.c).
  • the network awaits information from the UE about how stable its channel conditions are.
  • the information may be binary (stable/unstable) or more fine-granular.
  • the network may receive a TDCP report from the UE, and the network compares the WNCA(s) in the TDCP report to one or more thresholds to determine if the channel conditions are stable. If the network deems the channel conditions stable enough, the network may trigger measurements and/or request a measurement report from the UE. In some embodiments, the network selects the duration of the time interval covered by a measurement report based on how stable the channel is. For example, the network may request many measurements (e.g.
  • the network may request fewer measurements (e.g., sweeping just a few Tx beams) if the channel is unstable, and larger number of measurements if the channel is stable (e.g. sweeping many Tx beams).
  • the network may also configure/signal the extent of time-domain averaging over measurements the UE should perform, e.g. if the channel is very stable, the network may request that the UE averages over multiple measurements to improve accuracy, whereas if channel conditions vary rapidly, the network may request that the UE does not average at all.
  • the UE informs the network about measurement grouping. In some embodiments, the UE does not immediately inform the network about stopping of measurements, but rather immediately resumes or restarts measurements and at a later time instance and reports measurement results spanning over one or more stops along with information about where the stops occurred or information about which set of measurements can be considered to have been performed under approximately same channel conditions.
  • Figure 9 illustrates three measurement groups, containing measurements ⁇ 1, 2, 3 ⁇ , ⁇ 4, 5, 6 ⁇ , and ⁇ 7 ⁇ , respectively.
  • the UE informs about the groups in terms of group start and group duration (where start and duration may be expressed in terms of seconds, slots, OFDM symbols, and/or number of measurements).
  • the groups may be overlapping.
  • the UE reports a group identifier (e.g., a channel stability group identifier) for each measurement it reports to the network. The measurements that have the same group identifier are considered to have been performed under similar channel conditions. In the example of Figure 9, measurements 1-3 are reported along with a first group identifier, measurements 4-6 are reported along with a second group identifier, and measurement 7 is reported along with a third group identifier.
  • the UE aggregates/combines/merges measurements within each group (e.g., finding the best RSRP value within the group) before reporting. In this case it might not be necessary to indicate the group boundaries to the network.
  • the UE switches Rx beam only between groups, not within groups. This may be useful, because relative measurement errors between measurements with same Rx beam may be smaller than relative measurement errors between measurements using different Rx beams, and thus it may be valuable to stay on the same Rx beam while channel conditions are stable, while if the channel conditions have changed dramatically (i.e., at a group boundary), it may not matter much if there is some extra error from a beam switch at that point.
  • Rx panel or Rx RF chain rather than Rx beam is considered. The examples described are not necessarily applicable only if “groups” have been defined but may also be used in more general cases of stops in the measurements.
  • Some embodiments include reporting of radio measurements results to the network (e.g., step 150).
  • the UE reports the radio measurement results including one or more of the following information: one or more radio measurement results (e.g. RSRP, RSRQ, SINR, RSSI) performed under the conditions that the channel is stable; one or more triggering events that were fulfilled determining that channel conditions are changed; the amount of time (e.g., in terms of consecutive radio resources such as OFDM symbols or slots, or in terms of milliseconds or seconds) the channel was determined as stable; an indication of the one or more beams, e.g. SSB/CSI-RS index, for which the radio measurement results were performed; and/or an indication of the cell in which the radio measurements were performed.
  • one or more radio measurement results e.g. RSRP, RSRQ, SINR, RSSI
  • the amount of time e.g., in terms of consecutive radio resources such as OFDM symbols or slots, or in terms of milliseconds or seconds
  • the channel was determined as stable
  • the above set of information may be reported to the network upon determining that one or more of the triggering events for channel condition change are fulfilled.
  • the above set of information may be reported to the network periodically, or based on events different than the events used for determining that the channel conditions are changed, or upon network request, e.g. the UE signals to the network the availability of collected measurements results and the network requests the UE to transmit the collected radio measurement results.
  • the report consists of more than one radio measurement collection, wherein each radio measurement collection is performed under the condition that the channel is stable.
  • Each radio measurement collection included in the report comprises one or more of the information above. For example, while the channel conditions are determined to be stable in a first channel, the UE performs radio measurement on the first channel; upon determining that the channel conditions on the first channel are changed, the UE logs and stores in the UE memory the radio measurements including one or more of the information above associated to the first channel. Then, the UE may start performing radio measurements in a second channel (which could be the same channel, i.e. same SSB/CSI-RS resources, as the first channel or a different channel) upon determining that the channel conditions in the second channel are stable.
  • a second channel which could be the same channel, i.e. same SSB/CSI-RS resources, as the first channel or a different channel
  • the UE Upon determining that the channel conditions in the second channel are changed, the UE logs and stores in the UE memory the radio measurements including one or more of the information above associated to the second channel. This operation may be repeated for a plurality of radio measurements performed in a plurality of channels, wherein each radio measurement is performed under the condition that the channel conditions in the concerned channel are stable.
  • This method implies that the report to the network may consist of a list of radio measurements, wherein each entry in the list may comprise one of more of the information above associated to radio measurements performed in a given channel.
  • the report Upon transmitting to the network the report, the information associated to each radio measurement reported may be cleared from the UE memory.
  • measurement may be e.g. RSRP or RSRQ measurement, or some other type of beam/channel quality measurement. Also, it is to be understood that where RSRP is explicitly mentioned, one may typically derive a related embodiment by replacing it with e.g. RSRQ or other type of beam/channel quality measurement.
  • 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.
  • 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.
  • 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).
  • MSC Mobile Switching Center
  • MME Mobility Management Entity
  • HSS Home Subscriber Server
  • AMF Access and Mobility Management Function
  • SMF Session Management Function
  • AUSF Authentication Server Function
  • SIDF Subscription Identifier De-concealing function
  • UDM Unified Data Management
  • SEPP Security Edge Protection Proxy
  • NEF Network Exposure Function
  • UPF User Plane Function
  • 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.
  • the telecommunication network 102 is a cellular network that implements 3 GPP 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.
  • URLLC Ultra Reliable Low Latency Communication
  • eMBB Enhanced Mobile Broadband
  • mMTC Massive Machine Type Communication
  • the UEs 112 are configured to transmit and/or receive information without direct human interaction.
  • 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.
  • a UE may be configured for operating in single- or multi -RAT or multi -standard mode.
  • 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).
  • MR-DC multi-radio dual connectivity
  • 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).
  • the hub 114 may be a controller, router, content source and analytics, or any of the other communication devices described herein regarding UEs.
  • the hub 114 may be a broadband router enabling access to the core network 106 for the UEs.
  • the hub 114 may be a controller that sends commands or instructions to one or more actuators in the UEs.
  • 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.
  • 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.
  • 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.
  • the hub 114 is connected to the core network 106 and/or one or more UEs via a wired connection.
  • 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.
  • UEs may establish a wireless connection with the network nodes 110 while still connected via the hub 114 via a wired or wireless connection.
  • 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.
  • 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.
  • FIG 11 shows a UE 200 in accordance with some embodiments.
  • 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.
  • VoIP voice over IP
  • LME laptop-embedded equipment
  • LME laptop-mounted equipment
  • CPE wireless customer-premise equipment
  • UEs 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.
  • 3GPP 3rd Generation Partnership Project
  • NB-IoT narrow band internet of things
  • MTC machine type communication
  • eMTC enhanced MTC
  • a UE may support device-to-device (D2D) communication, for example by implementing a 3 GPP standard for sidelink communication, Dedicated Short-Range Communication (DSRC), vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), or vehicle-to- everything (V2X).
  • D2D device-to-device
  • DSRC Dedicated Short-Range Communication
  • V2V vehicle-to-vehicle
  • V2I vehicle-to-infrastructure
  • V2X vehicle-to- everything
  • a UE may not necessarily have a user in the sense of a human user who owns and/or operates the relevant device.
  • 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).
  • a UE may represent a device that is not intended for sale to, or operation
  • 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 2. 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.
  • the processing circuitry 202 may include multiple central processing units (CPUs).
  • 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.
  • USB Universal Serial Bus
  • 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.
  • 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.
  • RAID redundant array of independent disks
  • HD-DVD high-density digital versatile disc
  • HDDS holographic digital data storage
  • DIMM external mini-dual in-line memory module
  • SDRAM synchronous dynamic random access memory
  • SDRAM synchronous dynamic random access memory
  • the UICC may for example be an embedded UICC (eUICC), integrated UICC (iUICC) or a removable UICC commonly known as ‘SIM card.’
  • eUICC embedded UICC
  • iUICC integrated UICC
  • SIM card 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).
  • 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.
  • 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.
  • GPS global positioning system
  • 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.
  • CDMA Code Division Multiplexing Access
  • WCDMA Wideband Code Division Multiple Access
  • WCDMA Wideband Code Division Multiple Access
  • GSM Global System for Mobile communications
  • LTE Long Term Evolution
  • NR New Radio
  • UMTS Worldwide Interoperability for Microwave Access
  • WiMax Ethernet
  • TCP/IP transmission control protocol/intemet protocol
  • SONET synchronous optical networking
  • ATM Asynchronous Transfer Mode
  • QUIC Hypertext Transfer Protocol
  • HTTP Hypertext Transfer Protocol
  • 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.
  • the UE may implement the 3GPP NB-IoT standard.
  • 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.
  • 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).
  • MSR multi -standard radio
  • RNCs radio network controllers
  • BSCs base station controllers
  • BTSs base transceiver stations
  • OFDM Operation and Maintenance
  • OSS Operations Support System
  • SON Self-Organizing Network
  • positioning nodes e.g., Evolved Serving Mobile Location Centers (E-SMLCs)
  • 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.
  • 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.
  • 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.
  • 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 12 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.
  • 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.
  • FIG. 13 is a block diagram of a host 400, which may be an embodiment of the host 116 of Figure 1, in accordance with various aspects described 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.
  • 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 10 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., FLAC, 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.
  • 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.
  • HLS HTTP Live Streaming
  • RTMP Real-Time Messaging Protocol
  • RTSP Real-Time Streaming Protocol
  • MPEG-DASH Dynamic Adaptive Streaming over HTTP
  • FIG 14 is a block diagram illustrating a virtualization environment 500 in which functions implemented by some embodiments may be virtualized.
  • virtualizing means creating virtual versions of apparatuses or devices which may include virtualizing hardware platforms, storage devices and networking resources.
  • 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.
  • VMs virtual machines
  • 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.
  • 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.
  • 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.
  • 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.
  • 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 15 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.
  • UE such as a UE 112a of Figure 10 and/or UE 200 of Figure 2
  • network node such as network node 110a of Figure 10 and/or network node 300 of Figure 3
  • host such as host 116 of Figure 10 and/or host 400 of Figure 4
  • 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.
  • OTT over-the-top
  • 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 1) and/or one or more other intermediate networks, such as one or more public, private, or hosted networks.
  • a core network like core network 106 of Figure 1
  • one or more other intermediate networks such as one or more public, private, or hosted networks.
  • 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.
  • 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.
  • an executing host application may communicate with the executing client application via the OTT connection 650 terminating at the UE 606 and host 602.
  • 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
  • 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.
  • the host 602 provides user data, which may be performed by executing a host application.
  • the user data is associated with a particular human user interacting with the UE 606.
  • the user data is associated with a UE 606 that shares data with the host 602 without explicit human interaction.
  • 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.
  • 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.
  • the UE 606 may provide user data, which may be performed by executing the client application.
  • 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.
  • the network node 604 receives user data from the UE 606 and initiates transmission of the received user data towards the host 602.
  • 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 the data rate and latency and thereby provide benefits such as reduced user waiting time, better responsiveness, and better QoE.
  • factory status information may be collected and analyzed by the host 602.
  • the host 602 may process audio and video data which may have been retrieved from a UE for use in creating maps.
  • the host 602 may collect and analyze real-time data to assist in controlling vehicle congestion (e.g., controlling traffic lights).
  • the host 602 may store surveillance video uploaded by a UE.
  • 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.
  • 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.
  • the wireless device may measure one or more reference signals according to any of the embodiments and examples described herein.
  • the wireless device may determine that a change to a channel condition associated with the one or more reference signals impacts the data collection according to any of the embodiments and examples described herein.
  • the wireless device may take additional actions upon determining that the change to the channel condition impacted the data collection. In some embodiments, the wireless device may take any of the actions described with respect to the embodiments and examples described herein.
  • the wireless device may report to a network node an indication that the data collection was stopped.
  • the indication that the data collection was stopped may comprise an indication of the channel condition that caused the data collection to stop. Reporting the indication that the data collection was stopped may comprise reporting data collected prior to determining that the channel condition changed.
  • the wireless device may report the indication according to any of the embodiments and examples described herein.
  • configuring the wireless device to measure the one or more reference signals for data collection comprises determining the channel condition associated with the one or more reference signals has not changed beyond a threshold value for a time duration.
  • the network node receives an indication from the wireless device that the data collection was stopped based on a determination that a change to a channel condition associated with the one or more reference signals impacted the data collection.
  • the indication and the determination of the changed channel conditions are described in more detail with respect to Figure 16 and with respect to the embodiments and examples above.
  • references in the specification to “one embodiment,” “an embodiment,” “an example embodiment,” etc., indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to implement such feature, structure, or characteristic in connection with other embodiments, whether or not explicitly described.
  • reporting the indication that the data collection was stopped comprises reporting an indication of the channel condition that caused the data collection to stop.
  • reporting the indication that the data collection was stopped comprises reporting data collected prior to determining the channel condition changed beyond a threshold value.
  • determining the channel condition has changed beyond a threshold value comprises evaluating one or more measurement quantities.
  • the measurement quantity includes one or more of: sensors, channel measurements including TDCP measurements, and historical information.
  • determining the channel condition has changed beyond a threshold value comprises determining the wireless device made a change in its setting/configuration that affects the channel conditions.
  • determining the channel condition has changed beyond a threshold value comprises determining one or more of:
  • - one or more WNCA(s) in the TDCP measurement are below one or more predefined threshold(s);
  • a method performed by a wireless device comprising:
  • any of the wireless device steps, features, or functions described above either alone or in combination with other steps, features, or functions described above.
  • the method of the previous embodiment further comprising one or more additional wireless device steps, features or functions described above.
  • a method performed by a base station comprising:
  • the measurement quantity includes one or more of: sensors, channel measurements including TDCP measurements, and historical information.
  • the wireless device has moved more than a threshold channel coherence length
  • - one or more WNCA(s) in the TDCP measurement are below one or more predefined threshold(s);
  • the wireless device has rotated more than a certain angle.

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Abstract

According to some embodiments, a method is performed by a wireless device. The method comprises: measuring one or more reference signals for data collection; determining that a change to a channel condition associated with the one or more reference signals impacts the data collection; and based on the determination, stopping the data collection.

Description

DATA COLLECTION STOP BASED ON UE EVENT
TECHNICAL FIELD
[0001] The present disclosure generally relates to communication networks, and more specifically to stopping data collection based on a user equipment (UE) event.
BACKGROUND
[0002] One of the key features of Third Generation Partnership Project (3 GPP) New Radio (NR) compared to previous generation of wireless networks is the ability to operate in higher frequencies (e.g., above 10 GHz). The available large transmission bandwidths in these frequency ranges can potentially provide large data rates. However, as carrier frequency increases, both pathloss and penetration loss increase. To maintain the coverage at the same level, highly directional beams are used to focus the radio transmitter energy in a particular direction on the receiver. However, large radio antenna arrays - at both receiver and transmitter sides - are needed to create such highly direction beams.
[0003] To reduce hardware costs, large antenna arrays for high frequencies use time-domain analog beamforming. The core idea of analog beamforming is to share a single radio frequency chain between many (or potentially all) of the antenna elements. A limitation of analog beamforming is that it is only possible to transmit radio energy using one beam (in one direction) at a given time.
[0004] The above limitation requires the network (NW) and user equipment (UE) to perform beam management procedures to establish and maintain suitable transmitter (Tx)/receiver (Rx) beam-pairs. For example, beam management procedures can be used by a transmitter to sweep a geographic area by transmitting reference signals on different candidate beams during nonoverlapping time intervals using a predetermined pattern. By measuring the quality of the reference signals at the receiver side, the best transmit and receive beams can be identified.
[0005] Beam management procedures in NR are defined by a set of layer one (Ll)/layer two (L2) procedures that establish and maintain suitable beam pairs for both transmitting and receiving data. A beam management procedure can include the following sub procedures: beam determination, beam measurements, beam reporting, and beam sweeping.
[0006] For downlink transmission from the NW to the UE, P1/P2/P3 beam management procedures can be performed to overcome the challenges of establishing and maintaining the beam pairs when, for example, a UE moves or a blockage in the environment requires changing the beams. Although these scenarios are not directly mentioned in specifications, there are relevant procedures defined that enables the realization of these scenarios. Examples of such realization are depicted in corresponding figures.
[0007] The Pl procedure enables UE measurement on different transmission/reception point (TRP) Tx beams to support selection of TRP Tx beams/UE Rx beam(s). During initial access, for example, the gNB transmits synchronization signal (SS)/physical broadcast channel (PBCH) block (SSB) beams in different directions to cover the entire cell. The UE measures signal quality on corresponding SSB signals to detect and select an appropriate SSB beam. An example is illustrated in Figure 1.
[0008] Figure 1 illustrates SSB beam selection as part of initial access procedure according to Pl scenario. Random access is then transmitted on the random access channel (RACH) resources indicated by the selected SSB. The corresponding beam will be used by both the UE and the network to communicate until connected mode beam management is active. The network infers which SSB beam was chosen by the UE without any explicit signaling.
[0009] Beamforming at a TRP typically includes an intra/inter-TRP Tx beam sweep from a set of different beams. Beamforming at a UE typically includes a UE Rx beam sweep from a set of different beams.
[0010] The P2 procedure enables UE measurement on different TRP Tx beams to possibly change inter/intra-TRP Tx beam(s). The network can use the SSB beam as an indication of which (narrow) channel state information reference signal (CSI-RS) beams to try; that is, the selected SSB beam can be used to define a candidate set of narrow CSI-RS beams for beam management. Once CSI-RS is transmitted, the UE measures the reference signal receive power (RSRP) and reports the result to the network. If the network receives a CSI-RSRP report from the UE where a new CSI-RS beam is better than the old beam used to transmit physical downlink control channel (PDCCH)/physical downlink shared channel (PDSCH), the network updates the serving beam for the UE accordingly, and possibly also modifies the candidate set of CSI-RS beams. The network can also instruct the UE to perform measurements on SSB s. If the network receives a report from the UE where a new SSB beam is better than the previous best SSB beam, a corresponding update of the candidate set of CSI-RS beams for the UE may be motivated.
[0011] The P2 procedure is performed on a possibly smaller set of beams for beam refinement than in Pl. Note that P2 can be a special case of Pl. For example, in connected mode gNB configures the UE with different CSI-RSs and transmits each CSI-RS on a corresponding beam. The UE then measures the quality of each CSI-RS beam on its current RX beam and sends feedback about the quality of the measured beams. Thereafter, based on this feedback, the gNB will determine and possibly indicate to the UE which beam will be used in future transmissions. An example is illustrated in Figure 2.
[0012] Figure 2 illustrates CSI-RS Tx beam selection in downlink according to P2 scenario.
[0013] P3 is used to enable UE measurement on the same TRP Tx beam to change UE Rx beam when the UE uses beamforming. Once in connected mode, the UE is configured with a set of reference signals. Based on measurements, the UE determines which Rx beam is suitable to receive each reference signal in the set. The network then indicates which reference signals are associated with the beam that will be used to transmit PDCCH/PDSCH, and the UE uses this information to adjust its Rx beam when receiving PDCCH/PDSCH.
[0014] In connected mode, P3 can be used by the UE to find the best Rx beam for a corresponding Tx beam. In this case the gNB keeps one CSI-RS Tx beam at a time, and the UE performs the sweeping and measurements on its own Rx beams for that specific Tx beam. The UE then finds the best corresponding Rx beam based on the measurements and will use it in future for reception when gNB indicates the use of that Tx beam.
[0015] Figure 3 illustrates UE Rx beam selection for a corresponding CSI-RS Tx beam in downlink according to P3 scenario.
[0016] For beam management, a UE can be configured to report RSRP or/and signal to interference and noise ratio (SINR) for each one of up to four beams, either on CSI-RS or SSB. UE measurement reports can be sent either over physical uplink control channel (PUCCH) or physical uplink shared channel (PUSCH) to the network node, e.g., gNB.
[0017] A CSI-RS is transmitted over each transmit (Tx) antenna port at the network node and for different antenna ports. The CSI-RS are multiplexed in time, frequency, and code domain such that the channel between each Tx antenna port at the network node and each receive antenna port at a UE can be measured by the UE. The time-frequency resource used for transmitting CSI-RS is referred to as a CSI-RS resource.
[0018] In NR, the CSI-RS for beam management is defined as a 1- or 2-port CSI-RS resource in a CSI-RS resource set where the field repetition is present. The following three types of CSI- RS transmissions are supported:
• Periodic CSI-RS: CSI-RS is transmitted periodically in certain slots. This CSI-RS transmission is semi-statically configured using Radio Resource Control (RRC) signaling with parameters such as CSI-RS resource, periodicity, and slot offset.
• Semi -Persistent CSI-RS: Similar to periodic CSI-RS, resources for semi-persistent CSI- RS transmissions are semi-statically configured using RRC signaling with parameters such as periodicity and slot offset. However, unlike periodic CSI-RS, dynamic signaling is needed to activate and deactivate the CSI-RS transmission.
• Aperiodic CSI-RS: This is a one-shot CSI-RS transmission that can happen in any slot. One-shot means that CSI-RS transmission only happens once per trigger. The CSI-RS resources (i.e., the resource element (RE) locations that consist of subcarrier locations and orthogonal frequency division multiplexing (OFDM) symbol locations) for aperiodic CSI- RS are semi-statically configured. The transmission of aperiodic CSI-RS is triggered by dynamic signaling through PDCCH using the CSI request field in uplink downlink control information (DCI), in the same DCI where the uplink resources for the measurement report are scheduled. Multiple aperiodic CSI-RS resources can be included in a CSI-RS resource set and the triggering of aperiodic CSI-RS is on a resource set basis.
[0019] In NR, an SSB consists of a pair of synchronization signals (SSs), physical broadcast channel (PBCH), and demodulation reference signal (DMRS) for PBCH. An SSB is mapped to 4 consecutive OFDM symbols in the time domain and 240 contiguous subcarriers (20 resource blocks (RBs)) in the frequency domain.
[0020] NR supports beamforming and beam-sweeping for SSB transmission by enabling a cell to transmit multiple SSBs in different narrow-beams multiplexed in time. The transmission of these SSBs is confined to a half frame time interval (5 ms). It is also possible to configure a cell to transmit multiple SSBs in a single wide beam with multiple repetitions. The design of beamforming parameters for each of the SSBs within a half frame is up to network implementation. The SSBs within a half frame are broadcasted periodically from each cell. The periodicity of the half frames with SS/PBCH blocks is referred to as SSB periodicity, which is indicated by system information block one (SIB1).
[0021] The maximum number of SSBs within a half frame, denoted by L, depends on the frequency band, and the time locations for the L candidate SSBs within a half frame depends on the subcarrier spacing (SCS) of the SSBs. The L candidate SSBs within a half frame are indexed in an ascending order in time from 0 to L-l. By successfully detecting PBCH and its associated DMRS, a UE knows the SSB index. A cell does not necessarily transmit SS/PBCH blocks in all L candidate locations in a half frame, and the resources of the unused candidate positions can be used for the transmission of data or control signaling instead. It is up to network implementation to decide which candidate time locations to select for SSB transmission within a half frame, and which beam to use for each SSB transmission.
[0022] A UE can be configured with N>1 CSI reporting settings (CSI-ReportConfig) and M>1 resource settings (CSI-ResourceConfig). Each CSI reporting setting is linked to one or more resource setting for channel and/or interference measurement. The CSI framework is modular in the sense that several CSI reporting settings may be associated with the same resource setting.
[0023] The measurement resource configurations for beam management are provided to the UE by RRC information element (IE) (CSI-ResourceConfigs). One CSI-ResourceConfig contains several NZP-CSI-RS-ResourceSets and/or CSI-SSB-ResourceSets.
[0024] A UE can be configured to measure CSI-RSs using the RRC IE NZP-CSI-RS- ResourceSet. A NZP CSI-RS resource set contains the configurations of Ks >1 CSI-RS resources. Each CSI-RS resource configuration resource includes at least the following: mapping to REs, the number of antenna ports, and time-domain behavior. Up to 64 CSI-RS resources can be grouped together in an NZP-CSI-RS-ResourceSet.
[0025] A UE can be configured to measure SSBs using the RRC IE CSI-SSB-ResourceSet. Resource sets comprising SSB resources are defined in a similar manner to the CSI-RS resources defined above.
[0026] For aperiodic CSI-RS and/or aperiodic CSI reporting, the network node configures the UE with Sc CSI triggering states. Each triggering state contains the aperiodic CSI report setting to be triggered along with the associated aperiodic CSI-RS resource sets.
[0027] Periodic and semi-persistent resource settings can only comprise a single resource set (i.e., S=l). Aperiodic resource settings can have many resources sets (S>=1), because one out of the S resource sets defined in the resource setting is indicated by the aperiodic triggering state that triggers a CSI report.
[0028] Three types of CSI reporting are supported in NR as follows:
• Periodic CSI Reporting on physical uplink control channel (PUCCH): CSI is reported periodically by a UE. Parameters such as periodicity and slot offset are configured semi- statically by higher layer RRC signaling from the network node to the UE.
• Semi -Persistent CSI Reporting on physical uplink shared channel (PUSCH) or PUCCH: similar to periodic CSI reporting, semi-persistent CSI reporting has a periodicity and slot offset which may be semi-statically configured. However, a dynamic trigger from network node to UE may be needed to enable the UE to begin semi-persistent CSI reporting. A dynamic trigger from network node to UE is needed to request the UE to stop the semi- persistent CSI reporting.
• Aperiodic CSI Reporting on PUSCH: This type of CSI reporting involves a single-shot (i.e., one time) CSI report by a UE which is dynamically triggered by the network node using DCI. Some of the parameters related to the configuration of the aperiodic CSI report is semi-statically configured by RRC but the triggering is dynamic. [0029] In each CSI reporting setting, the content and time-domain behavior of the report is defined, along with the linkage to the associated Resource Settings.
[0030] The CSI-ReportConfig IE comprises the following configurations:
• reportConfigType - Defines the time-domain behavior (periodic CSI reporting, semi- persistent CSI reporting, or aperiodic CSI reporting) along with the periodicity and slot offset of the report for periodic CSI reporting.
• reportQuantity - Defines the reported CSI parameters — the CSI content; for example, the precoding matrix indicator (PMI), channel quality indicator (CQI), rank indicator (RI), layer indicator (LI), CSLRS resource index (CRI) and Ll-RSRP. Only certain combinations are possible, for example, ‘cri-RI-PMI-CQI’ is one possible value and ‘cri- RSRP’ is another) and each value of reportQuantity could be said to correspond to a certain CSI mode.
• codebookConfig - Defines the codebook used for PMI reporting, along with possible codebook subset restriction (CBSR). NR supported the following two types of PMI codebooks: Type I CSI and Type II CSI. Additionally, the Type I and Type II codebooks each have two different variants: regular and port selection.
• reportFrequencyConfiguration - Define the frequency granularity of PMI and CQI (wideband or subband), if reported, along with the CSI reporting band, which is a subset of subbands of the bandwidth part (BWP) that the CSI corresponds to.
• Measurement restriction in time domain (ON/OFF) for channel and interference respectively
[0031] For beam management, a UE can be configured to report Ll-RSRP for up to four different CSI-RS/SSB resource indicators. The reported RSRP value corresponding to the first (best) CRI/SSBRI requires 7 bits, using absolute values, while the others require 4 bits using encoding relative to the first. In NR release 16, the report of Ll-SINR for beam management has already been supported.
[0032] 3GPP has also studied using artificial intelligence (AI)/machine learning (ML) based spatial beam prediction, the core idea of which is as follows: predict the “best” beam (or beams) from a Set A of beams using measurement results from another Set B of beams.
[0033] Set A and Set B of beams have not been defined yet; however, the following two examples illustrate some scenarios that will likely be studied in Release 18.
[0034] In a first example, Set B is a subset of a Set A, as illustrated in Figure 4. For example, Set A is a set of 8 SSB/CSLRS beams shown in Figure 4 (both light and dark circles). The UE measures Set B (the 4 beams indicated by dark circles). The AI/ML model should predict the best beam (or beams) in Set A using only measurements from Set B.
[0035] Figure 4 illustrates a grid-of-beam type radiation pattern. Each row (resp. column) depicts a certain zenith (resp. azimuth) angle from the antenna array. Set A has 8 beams and Set B has 4 beams (indicated by dark circles).
[0036] In a second example, Set A and Set B correspond to two different sets of beams. For example, Set A is a set of 30 narrow CSI-RS beams, and Set B is a set of 8 wide SSB beams. The UE measures beams in Set B and the AI/ML model should predict the best beam(s) from Set A.
[0037] Figure 5 illustrates an example where Set A is a set of narrow beams and Set B is a set of wide beams.
[0038] The spatial beam prediction can be performed in the gNB or the UE. Thus, 3 GPP will study AI/ML model training both at the NW and UE side. Which side performs the training is expected to impact how data collection is performed, where 3GPP will also study the aspect of data collection for beam management. 3GPP will also study the aspect of model monitoring and the standard impact on AI/ML model inference (e.g., reporting of predicted values).
[0039] The following text is captured in the TR 38.843 regarding performance monitoring.
Performance monitoring:
For the performance monitoring of BM-Casel and BM-Case2:
- Performance metric(s) with the following alternatives:
- Alt.l : Beam prediction accuracy related KPIs, e.g., Top-K/1 beam prediction accuracy
- Alt.2: Link quality related KPIs, e.g., throughput, Ll-RSRP, Ll-SINR, hypothetical BLER
- Alt.3 : Performance metric based on input/output data distribution of AI/ML
- Alt.4: The Ll-RSRP difference evaluated by comparing measured RSRP and predicted RSRP
- Benchmark/reference for the performance comparison, including:
- Alt.1 : The best beam(s) obtained by measuring beams of a set indicated by gNB (e.g., Beams from Set A)
- Alt.4: Measurements of the predicted best beam(s) corresponding to model output (e.g., Comparison between actual Ll-RSRP and predicted RSRP of predicted Top-l/K Beams)
- Signalling/configuration/measurement/report for model monitoring, e.g., signalling aspects related to assistance information (if supported), Reference signals For BM-Casel and BM-Case2 with a UE-side AI/ML model:
- Typel performance monitoring:
- Configuration/Signalling from gNB to UE for measurement and/or reporting
- UE may have different operations
- Optionl : UE sends reporting to NW (e.g., for the calculation of performance metric at NW)
- Option2: UE calculates performance metric(s), either reports it to NW or reports an event to NW based on the performance metric(s)
- Indication from NW for UE to do LCM operations
- Note: At least the performance and reporting overhead of model monitoring mechanism should be considered
- Type2 performance monitoring (UE-side performance monitoring):
- Indication/request/report from UE to gNB for performance monitoring
- Note: The indication/request/report may be not needed in some case(s)
- Configuration/Signalling from gNB to UE for performance monitoring measurement and/or reporting
- UE calculates performance metric(s), either reports it to NW or reports an event to NW based on the performance metric(s)
- If it is for UE-side model monitoring, UE makes decision(s) of model selection/activation/ deactivation/switching/fallback operation
- Indication from NW to UE to do LCM operation
- UE reporting of beam measurement(s) based on a set of beams indicated by gNB
- Signalling, e.g., RRC -based, LI -based
- Note: Performance and UE complexity, power consumption should be considered
Mechanism that facilitates the UE to detect whether the functionality/model is suitable or no longer suitable
Table 7.2.3-1 summarizes applicability of various alternatives for performance metric(s) of AI/ML model monitoring for BM-Casel and BM-Case2.
Table 7.2.3-1: Alternatives for Performance metric(s) of AI/ML model monitoring for BM-Case 1 and BM-Case 2
Figure imgf000011_0001
Notel : The above analysis shall not give an indication about whether/which metric is supported or specified.
Note2: Monitoring performance of the above alternatives are not addressed in the table.
[0040] As mentioned above, the AI/ML model for beam prediction may be NW-sided or UE- sided (i.e., execute in the gNB or in the UE). If the model is NW-sided, the UE makes RSRP measurements and reports the measurement results to the NW for input into the AI/ML model. If the model is UE-sided, the UE both makes the measurements and the AI/ML-model-based prediction, and thus no reporting of the measurements is needed (only reporting of the final predicted beam(s)).
[0041] A key part of AI/ML-based prediction is data collection. Data collection is performed in several stages of the life-cycle management (LCM). [0042] First, the model must be trained by collecting measurement data for a large set of UE locations/channel conditions representative for the UE locations/channel conditions that may be encountered during use of the model (i.e., inference). For each UE, preferably all possible narrow Tx beam directions should be swept, i.e., a fairly large set of beams.
[0043] Second, when using the model for prediction (i.e., inference), measurement data for any UE to predict beams for must be collected and fed to the AI/ML model. The set of beams to sweep for a UE is here much smaller than during training, because not all narrow beams are swept, only a few wide (or possibly narrow) beams.
[0044] Finally, measurements are needed to monitor that the model functions well, or otherwise disable the model or update the model.
[0045] For a NW-sided model, all three types of data collection (training, inference, monitoring) follow the same general procedure:
• The NW transmits a signal (e.g., CSI-RS or SSB) using a set of several different Tx beams on the downlink.
• The UE measures the RSRP (or some other reporting quantity) of the different transmissions.
• The UE here typically does Rx beamforming; this beamforming is, however, an implementation detail that it is up to the UE to decide on.
• The UE reports the measured RSRP (or other reporting quantity) values to the NW.
[0046] The measurements by the UE are subject to measurement errors. According to 3 GPP specifications, the relative error (i.e., the difference in reported measurement value for two measurements that were performed under the same nominal conditions and should thus ideally be identical) can be substantial, up to 6.5 dB under normal condition, see Table 10.1.20.1.2-1 of 3GPP TS 38.133, reproduced below for convenience.
[0047] The measurement error is a combination of several different sources, including the fact that different receive chains in the UE may have different absolute error. As a consequence, assuming for example that each antenna panel in the UE uses a different receive chain, the relative measurement error between two measurement occasions may on average be smaller if both measurements were made using the same antenna panel. Furthermore, it is possible that the relative error between two measurements is affected by other circumstances, e.g. the time interval between the two measurements, whether the UE has to switch temporarily to another Rx beam to listen to another signal between the two measurements, or if the UE has to temporarily stop listening to transmit between the two measurements. Table 10.1.20.1.2-1: SSB based L1-RSRP relative accuracy in FR2
Figure imgf000013_0002
[0048] In NR Rel. 18, tracking reference signal (TRS) based time domain channel property (TDCP) reporting is specified where the UE reports the TDCP measurements to the network.
[0049] The TDCP feature defines UE estimation and reporting of the ‘wideband normalized correlation’ (WNC) between two TRS symbols separated by D symbols. This should be interpreted as an estimate of the normalized channel correlation in time as given by
Figure imgf000013_0001
where hn(t) is the channel for subcarrier n at time t and At corresponds to the D symbols separating the two TRS symbols. The correlation delay At is configurable and can take the values 4 OFDM symbols, 1 slot, 2 slots, 3 slots, 4 slots, 5 slots, 6 slots and 10 slots (10 slots is applicable only to 30kHz subcarrier spacing). The maximum correlation delay a UE supports is subject to UE capability. A UE that supports TDCP supports at least correlation delays up to 1 slot.
[0050] The UE can be configured to report both the amplitude (e.g., wideband normalized correlation amplitude (WNCA)) and the phase (e.g., wideband normalized correlation phase (WNCP)) of the correlation A(t, At). Reporting of the phase is, however, subject to UE capability. [0051] For correlation delays longer than one slot, the UE measurement has to be performed across the TRS bursts of two different TRSs. The two TRSs should have a relative slot offset corresponding to the correlation lag At . The TRS which is anyway configured for tracking purposes may be reused also for TDCP, but one additional TRS needs to be configured. The extra TRS could have a longer periodicity than the TRS used for tracking to save overhead, as illustrated in Figure 6.
[0052] Figure 6 is a time/frequency diagram illustrating TRS bursts. The horizontal axis represents time, and the vertical axis represents frequency.
[0053] As illustrated in Figure 6, to support estimation of the channel correlation over a delay of 4 OFDM symbols or 1 slot, it is sufficient to configure a single dual slot TRS. To support a longer correlation delay it is, however, necessary to configure two TRSs with a relative time offset corresponding to the wanted correlation delay.
[0054] For the correlation lags 4 OFDM symbols, and 1 slot, the UE measurement can be made within one two-slot TRS burst. This means that only the TRS that is already configured for tracking purposes is needed.
[0055] There currently exist certain challenges. For example, a problem with existing methods for data collection is that the gNB-UE channel can change over time. The channel change can be due to movement, either of the UE or things in its environment. In particular, rotational movement of the UE may potentially be quite fast even in an indoor environment. Furthermore, the UE is free to select the Rx beam and/or the UE panel it uses for reception, effectively changing the gNB-UE channel, possibly quite abruptly, even in absence of physical movement of the UE or its surroundings.
[0056] The changing channel is a problem for several reasons, especially for collection of Set A (prediction set) during training. Set A is large and thus collecting Set A may take significant time, making the risk of substantial channel changes during its collection large.
[0057] Consider for example a case where the channel change is due to UE beam change. If the UE changes from a poor Rx beam 1 (e.g., pointing away from the gNB) used when gNB transmitted Tx beam A to a good Rx beam 2 (pointing more towards the gNB) used when gNB transmitted Tx beam B, then Tx beam B may result in a better measured RSRP value, even if Tx beam A is a better Tx beam to reach the UE. This will mislead the training.
SUMMARY
[0058] As described above, certain challenges currently exist with data collection when the gNB-user equipment (UE) channel can change over time. Certain aspects of the disclosure and their embodiments may provide solutions to these or other challenges. For example, in particular embodiments a UE stops measurements when a channel changes beyond a threshold value (or the UE suspects that the channel has changed beyond a threshold value) such that the artificial intelligence (AI)/machine learning (ML) model is not expected to work. Several different criteria, including methods for the network to control the criteria and methods for UE reporting capabilities in detecting a channel change, are described with respect to particular embodiments.
[0059] Once the UE has stopped the measurements, the UE may choose among several different actions, e.g. informing network about the stop but resume sweep, restarting the sweep, informing the network about the stopped sweep and await further instructions from the network, etc.
[0060] According to some embodiments, a method is performed by a wireless device. The method comprises: measuring one or more reference signals for data collection (e.g., for use with a machine learning model); determining that a change to a channel condition associated with the one or more reference signals impacts the data collection; and based on the determination, stopping the data collection.
[0061] In particular embodiments, determining that a change to a channel condition associated with the one or more reference signals impacts the data collection comprises determining that the channel condition has changed beyond a threshold value during the data collection.
[0062] In particular embodiments, the method further comprises reporting to a network node an indication that the data collection was stopped. The indication that the data collection was stopped may comprise an indication of the channel condition that caused the data collection to stop. Reporting the indication that the data collection was stopped may comprise reporting data collected prior to determining that the channel condition changed.
[0063] In particular embodiments, the determining that the channel condition has changed comprises evaluating one or more measurement quantities, such as one or more of: measurement output of a speed, position, or inertia sensor; time domain channel property (TDCP) measurements; a measurement of a signal strength or interference; and historical measurements of channel coherence time. Determining that the channel condition has changed may comprise determining that the wireless device made a change in a configuration of the wireless device that affects the channel condition.
[0064] In particular embodiments, the threshold value is dependent on a purpose of the data collection. For example, a purpose of the data collection may be for machine learning model inference and the threshold value may be based on a value used for training the machine learning model.
[0065] In particular embodiments, the measuring of the one or more reference signals for data collection is initiated when the channel condition associated with the one or more reference signals has not changed beyond a threshold value for a time duration. [0066] According to some embodiments, a wireless device comprises processing circuitry operable to perform any of the wireless device methods described above.
[0067] According to some embodiments, a method is performed by a network node. The method comprises: configuring a wireless device to measure one or more reference signals for data collection; and receiving an indication from the wireless device that the data collection was stopped based on a determination that a change to a channel condition associated with the one or more reference signals impacted the data collection.
[0068] In particular embodiments, configuring the wireless device to measure the one or more reference signals for data collection comprises determining the channel condition associated with the one or more reference signals has not changed beyond a threshold value for a time duration.
[0069] In particular embodiments, the method further comprises, in response to receiving the indication, stopping use of a machine learning model.
[0070] According to some embodiments, a network node comprises processing circuitry operable to perform any of the network node methods described above.
[0071] Also disclosed is a computer program product comprising a non-transitory computer readable medium storing computer readable program code, the computer readable program code operable, when executed by processing circuitry to perform any of the methods performed by the wireless device described above.
[0072] Another computer program product comprises a non-transitory computer readable medium storing computer readable program code, the computer readable program code operable, when executed by processing circuitry to perform any of the methods performed by the network node described above.
[0073] Certain embodiments may provide one or more of the following technical advantages. For example, particular embodiments include benefits from the UE stopping a sweep, such as: the network will not train an AI/ML model incorrectly due to changes in channel conditions during training; the network will not waste radio resources on a beam sweep that will not be useful; and a UE may save energy from not performing measurements that will not be useful.
[0074] BRIEF DESCRIPTION OF THE DRAWINGS
[0075] The present disclosure may be best understood by way of example with reference to the following description and accompanying drawings that are used to illustrate embodiments of the present disclosure. In the drawings:
Figure 1 illustrates synchronization signal block (SSB) beam selection as part of initial access procedure according to Pl scenario; Figure 2 illustrates channel state information reference signal (CSI-RS) Tx beam selection in downlink according to P2 scenario;
Figure 3 illustrates user equipment (UE) Rx beam selection for a corresponding CSI-RS Tx beam in downlink according to P3 scenario;
Figure 4 illustrates a grid-of-beam type radiation pattern;
Figure 5 illustrates an example where Set A is a set of narrow beams and Set B is a set of wide beams;
Figure 6 is a time/frequency diagram illustrating tracking reference signal (TRS) bursts;
Figure 7 is a flowchart illustrating the general steps of particular embodiments;
Figure 8 illustrates three examples of reference signal configuration for channel change estimation using time domain channel property (TDCP) measurements;
Figure 9 illustrates three measurement groups;
Figure 10 shows an example of a communication system, according to certain embodiments;
Figure 11 shows a user equipment (UE), according to certain embodiments;
Figure 12 shows a network node, according to certain embodiments;
Figure 13 is a block diagram of a host, according to certain embodiments;
Figure 14 is a block diagram illustrating a virtualization environment in which functions implemented by some embodiments may be virtualized;
Figure 15 shows a communication diagram of a host communicating via a network node with a UE over a partially wireless connection in accordance with some embodiments;
Figure 16 is a flowchart illustrating an example method in a wireless device, according to certain embodiments; and
Figure 17 is a flowchart illustrating an example method in a network node, according to certain embodiments.
DETAILED DESCRIPTION
[0076] As described above, certain challenges currently exist with data collection when the gNB-user equipment (UE) channel can change over time. Certain aspects of the disclosure and their embodiments may provide solutions to these or other challenges. For example, in particular embodiments a UE stops measurements when a channel changes beyond a threshold value (or the UE suspects that the channel has changed beyond a threshold value) such that the artificial intelligence (AI)/machine learning (ML) model is not expected to work. Several different criteria, including methods for the network to control the criteria and methods for UE reporting capabilities in detecting a channel change, are described with respect to particular embodiments. [0077] Particular embodiments are 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.
[0078] Figure 7 is a flowchart illustrating the general steps of particular embodiments. In general, when a UE during a data collection procedure consisting of the UE performing radio measurements related to inference/training/monitoring of an AI/ML model estimates that a channel condition has changed beyond a certain threshold, the UE takes an action that impacts the data collection procedure.
[0079] Some embodiments include how to detect a channel change (e.g., step 130) where the channel condition change is based on one or more measurement quantities, e.g., UE sensors (e.g., gyroscope or temperature sensor); UE channel measurements (including time domain channel property (TDCP) measurements); UE historical information, for example the UE has historically experienced a certain channel environment (e.g., coherence time of x ms), and/or the UE making a change in its setting/configuration (e.g., due to hardware error, energy savings, or other reason) that affects the effective channel conditions, e.g. switching Rx beam/panel/Rx RF chain (e.g.. due to hardware error, energy saving, etc.).
[0080] Some embodiments include a triggering event (e.g., step 130) where “channel conditions have changed beyond some threshold” (CCCBT) is that the UE has moved more than one channel coherence length (or a signaled/configure/predefined factor times the channel coherence length) for UE channel measurements, where CCCBT is that one or more WNCA(s) in the TDCP measurement are below one or more predefined threshold(s), where the channel conditions in form of interference have changed beyond some maximum allowed threshold, where CCCBT is that the UE has rotated more than a certain angle, where the angle is an absolute angle in azimuth and or elevation, and/or where the angle is relative to the UE Rx beam width.
[0081] Some embodiments include channel condition evaluation granularity, wherein the channel condition is evaluated: per beam, i.e. SSB/CSI-RS resource; per set of beams, i.e. SSB/CSI-RS resource; per cell, or per UE. The radio measurements consist of determining per channel radio measurement results, such as reference signal receive power (RSRP), reference signal receive quality (RSRQ), signal to interface and noise ratio (SINR), reference signal strength indicator (RS SI), etc.
[0082] Some embodiments include triggering event fulfillment. In particular embodiments, the fulfillment of one or more of the triggering events implies determining that the channel conditions have changed. In particular embodiments, the unfulfillment of one or more of the triggering events implies determining that the channel conditions have not changed, i.e. the channel is stable. In some embodiments, all the triggering events should be unfulfilled to determine that the channel conditions have not changed, i.e. the channel is stable.
[0083] Some embodiments include threshold configuration (e.g., step 120), where the threshold is preconfigured in the standards (e.g. 3 GPP defined); and/or information configured by or signaled from the network.
[0084] Some embodiments include multiple thresholds, where there are multiple thresholds combined, e.g. via “logical or” or “logical and,” or a more complicated function.
[0085] According to some embodiments, the action to take is prescribed in the specifications, or configured/ signaled by the network, and/or depends on whether the data being collected is for training, inference, or monitoring, and/or depends on whether partial sweeps are allowed (based on configuration by the network).
[0086] According to some embodiments, in response to estimating that a channel condition has changed, the type of action performed comprises one or more of the following actions: the UE informs the network and reports (appropriately processed) measurement results related to measurements performed prior to the channel condition change (e.g., under the condition that the channel is stable); the UE stops radio measurements related to measurements performed prior to the channel condition change; the UE restarts the radio measurements (possibly by continuing from the current point in the sweep); aborts the measurement (without reporting measurements so far, but informing the network about the abort) related to measurements performed prior to the channel condition change; and/or the UE logs and stores, e.g. in a variable allocated in the UE memory, the measurement results related to measurements performed prior to the channel condition change. The measurement results are stored until they are reported to the network.
[0087] Some embodiments include reporting of radio measurements results to the network (e.g., step 150), comprising the UE reporting the radio measurements including one or more of the following information associated to radio measurements: one or more radio measurement results (e.g., RSRP, RSRQ, SINR, RSSI) performed under the conditions that the channel is stable; the one or more triggering events that were fulfilled determining that channel conditions are changed; the amount of time (e.g., in terms of consecutive radio resources such as orthogonal frequency division multiplexing (OFDM) symbols or slots, or in terms of milliseconds or seconds) the channel was determined as stable; an indication of the one or more beams, e.g. SSB/CSI-RS index, for which the radio measurement results were performed; and/or an indication of the cell in which the radio measurements were performed.
[0088] The report may comprise radio measurements performed in different channels and performed at different points in time. For example, the above information may be associated to radio measurements performed in a first channel in a given point in time, and the report may include the above information for each radio measurement performed in a channel at a given point in time.
[0089] Some embodiments include capability reporting (e.g., step 100). In particular embodiments, the network configuration on the channel condition change event is based on the UE capability information, where the UE can indicate one or more of: support for estimating the channel coherence time; support for estimating channel condition change (or channel variation) based on TDCP measurement; and/or support for external sensors such as inertial measurement units (IMUs).
[0090] In some embodiments, the UE informs the network about current channel stability (according to any type of measurements, etc., listed in other embodiments, e.g. TDCP measurements)
[0091] Some embodiments include a determination of when to initiate data collection (e.g., step 110). The network decision on whether to collect data is based on a UE signaling that it currently is experiencing stable channel conditions. For example: the UE is stationary and not rotating (based on external sensors); UE speed is less than X km/h; UE observes a long channel coherence time (e.g., via measurements on SSB beams); UE observes that one or more WNCA(s) in the TDCP measurement are above one or more predefined threshold(s) (for example, UE observes WNCAs closer to 1); and/or the UE estimates how many beams the UE can measure before channel conditions have changed beyond some threshold, and informs the network about it. The network then decides on whether to initiate data collection.
[0092] According to some embodiments, the network configures and/or signals to the UE to start data collection when the channel is deemed stable enough according to some criterion, e.g. based on TDCP measurements, or measurements based on the same quantities as TDCP.
[0093] In some embodiments, the configuration/signaling includes an indication of a time interval (expressed in seconds, slots, OFDM symbols, or other system time-domain-related quantity) of when the collection is allowed to start, or must start (i.e., overriding the start criterion based on stable channel).
[0094] In some embodiments, the UE starts measurements even when the criterion of stable channel is not fulfilled, and in some embodiments, the UE does not start measurements for the data collection until the channel stability criterion is fulfilled (but still makes measurements needed to check or estimate if the criterion is fulfilled). [0095] In some embodiments, the channel stability criterion is configured/signaled by the network. In some embodiments, the channel stability criterion is based on the channel conditions for a certain amount of time/slots, potentially configured or signaled by the network.
[0096] As used herein, channel may refer to the channel from gNB antenna elements to UE antenna elements, or the effective channel, where aspects such as beamforming, UE radio frequency (RF) chain configuration or properties, etc., are considered.
[0097] The general steps described above are described in more detail in the following. When a UE performs a set of measurements requested by the network, the UE estimates how much the channel conditions have changed during the set of measurements, and if the change is large enough that a continuation of the set of measurements the UE is performing may be not useful, then the UE may take an appropriate action to avoid wasting further radio resources, UE power, etc.
[0098] In which sense the channel conditions may have changed, and the amount of change may be determined by a combination of specifications and/or configuration/signaling by the network and/or UE implementation. Examples are given in embodiments below. Particular embodiments include optional steps, as shown by dashed lines in Figure 7. According to particular embodiments, a method includes the following steps.
[0099] At step 120, a UE is configured for data collection. In some embodiments, no channel condition change estimation is explicitly configured; the channel condition change may be specified in 3 GPP specifications without explicit configuration or up to UE implementation.
[0100] At step 130a, the UE measures beam data.
[0101] At step 130b, the UE checks if the channel conditions have changed with a certain amount. If yes, the data collection is stopped.
[0102] At step 140, the UE performs certain actions in response to determining that the channel conditions have changed.
[0103] At step 150, the UE reports information on the beam data collection, including information on the channel condition change if present (e.g., that the UE stopped the data collection in time instance N due to channel condition change).
[0104] What action to take may also be configured/signaled by the network. Examples of actions are given in embodiments below.
[0105] Some embodiments include UE capabilities reporting (e.g., step 100). The UE may, prior to the data collection step, indicate to the network its capabilities for estimating a channel condition change. For example, the UE may indicate its capabilities for support of: estimating the channel coherence time; estimating channel condition change (or channel variation) based on TDCP measurement; and/or external sensors, such as IMUs. [0106] Some embodiments include initiating data collection (e.g., step 110). The initiation of data collection may be purely network-based, for example for low network load or good UE channel signal quality. The data collection may also be UE-assisted in another embodiment. A UE for example estimates how many beams the UE can measure before channel conditions have changed beyond some threshold and informs the network about it. The network determines whether to initiate data collection.
[0107] In another embodiment, the data collection is initiated by the UE when the UE experiences stable (non-varying) channel conditions. For example, the UE may experience a nonvarying channel under one or more of the following conditions: UE is stationary and not rotating (based on external sensors), e.g., UE speed is less than X km/h; observes a long channel coherence time (e.g., via measurements on SSB beams); and/or observes a TDCP wideband normalized correlation between two CSI-RSs (or TRSs) is above a threshold; a threshold value close to 1 may be used as the wideband normalized correlation is closer to 1 when the channel is not varying over time.
[0108] Some embodiments include determining changed channel conditions and/or implementation error (e.g., step 130b). In some embodiments, the determination of whether channel conditions have changed beyond a threshold value is based on whether the UE determines that the TDCP measurement performed by the UE indicates a wideband normalized correlation amplitude (WNCA) between two reference signals (RSs) is smaller than a threshold Ttr . The threshold Ttr may be configured to the UE by the network or may be specified or pre-defined in 3 GPP specifications.
[0109] Figure 8 illustrates three examples of reference signal configuration for channel change estimation using TDCP measurements. Example 1 of Figure 8 shows two periodic RSs where RS2 is delayed from RSi by Di symbols or slots. Using RSi and RS2, the UE measures TDCP corresponding to a correlation delay of Di. The UE then compares the WNCA associated with the TDCP measurement corresponding to correlation delay Di to the threshold Ttr. If the WNCA corresponding to correlation delay Di is larger than the threshold Ttr (i.e., if WNCA > Ttr), then the UE determines that the channel conditions have changed. Otherwise, the UE determines that the channel conditions have not changed. In some variants, the condition WNCA > Ttr may be used for determining the channel conditions have changed instead of using WNCA > Ttr-
[0110] In some embodiments, TDCP measurements with two or more WNCAs may be used to determine whether channel conditions have changed. Example 2 of Figure 8 shows three periodic RSs used for TDCP measurements where RS2 is delayed from RSi by Di symbols or slots, and RS3 is delayed from RSi by D2 symbols or slots. Denote the WNCAs associated with correlation delays Di and D2 via WNCA and WNCA2, respectively. Two threshold values Ttr l and Ttr 2 may be configured to the UE by the network or may be specified pre-defined in 3GPP specifications. In embodiments where the threshold values are pre-defined in 3GPP specifications, the threshold values may be specific to the value of the correlation delays (i.e., a first pre-defined threshold value for correlation delay of 4 symbols, a second pre-defined threshold value for correlation delay of 1 slot, a third pre-defined threshold value for correlation delay of 2 slots, etc.). Using RSi, RS2, and RS3, the UE measures TDCP corresponding to correlation delays of Di and D2. The UE then compares the WNCAs associated with correlation delays Di and D2 to the thresholds Ttr l and Ttr 2. The UE determines that the channel conditions have changed if the following conditions are met: WNCAr > TTr l, WNCA2 > TTr 2. Otherwise, the UE determines that the channel conditions have not changed. In some variants, the conditions WNCA > Ttr l and WNCA2 > Ttr 2 may be used for determining the channel conditions have changed instead of using WNCA > Ttr l and WNCA2 > Ttr 2.
[OlH] In some embodiments, TDCP measurements with two or more WNCAs may be used to determine whether channel conditions have changed with only a single periodic RS. In this embodiment, different integer multiples of the periodicity of the RS are used as the correlation delays. Example 3 of Figure 8 shows a single periodic RS used for TDCP measurements where the first correlation delay Di is set to one times the periodicity of the RS, and the second correlation delay D2 is set to two times the periodicity of the RS. The UE measures WNCA and WNCA2 associated with correlation delays Di and D2 , respectively. The conditions for UE determining the channel conditions have changed are similar to those of Example 2 of Figure 8 above.
[0112] The RSs in the above embodiments may be one of tracking reference signals (TRSs), CSI-RSs, or SSBs. In some embodiments, the UE uses the TDCP measurements only for the purpose of determining whether the channel conditions have changed, and the UE does not report the TDCP measurements to the network. In some embodiments, the UE may report the TDCP measurements to the network, and the network may also determine whether the channel conditions have changed for the UE by comparing the WNCAs with the respective thresholds.
[0113] In some embodiments, the determination of whether channel conditions have changed beyond a threshold value is based on whether the UE estimates whether the UE has moved more than one channel coherence length since the start of the measurement set. The channel coherence time may for example be estimated via the network reports the same beam over multiple time occasions. The channel coherence time may also be estimated by the UE via measuring the delay spread of the channel in each time-instance. A large delay spread typically indicates a shorter channel coherence time.
[0114] In one embodiment, the determination of whether channel conditions have changed beyond a threshold value is based on how much the UE has rotated. The threshold in terms of angles or other quantity representing UE rotation may be based on UE beam width and may be different for different axis of rotation if the UE has different beam widths in different dimensions. The UE rotation may be estimated, e.g., based on a gyroscope in the UE.
[0115] In one embodiment, the determination of whether channel conditions have changed beyond a threshold value is based on UE changing the UE panel with which it performs the measurements during a training or inference sweep.
[0116] In some embodiments, both UE linear movement and rotation are considered in determining if the channel conditions have changed beyond a threshold value. In a related embodiment, there are separate thresholds for linear movement and rotation, and the channel conditions are considered to have changed beyond a threshold value if any of the thresholds have been exceeded. In some embodiments, both linear movement and rotation are considered by computing a pre-defined function of the two quantities and comparing it with a single threshold.
[0117] In one embodiment, a UE might stop, restart and/or drop measurements when the RSRP values are lower than the threshold configured by the network via RRC or DCI, where the threshold may also be determined by UE based on UE implementation. For example, the UE might get reference values by previously monitoring some periodic reference signals, i.e., multiple occasions of SSB burst.
[0118] In one embodiment, a UE might stop, restart and/or drop measurements when the interference levels from neighboring cell are higher than the threshold configured by the network via RRC or DCI, where the threshold may also be determined by UE based on UE implementation. For example, the UE might get reference values by previously monitoring periodic reference signals, i.e., multiple occasions of SSB burst. In one embodiment, the UE might stop, restart and/or drop measurements when the UE is changing the surrounding environment which might cause the significant variations of channel conditions. For example, if the UE is moving from the outdoor scenario to the indoor scenario, the UE might stop the measurement for a time. In another example, if the UE is waiting for a coming high-speed train and is ready to onboard the high speed train, the UE might stop the measurement for a time due to the transition.
[0119] In some embodiments, the AI/ML model is trained with measurement data that takes into account a certain range of implementation imperfection, measured signal quality, and/or measurement errors of the gNB or the UE. Such implementation related measurement or measurement errors may include, for example: network synchronization error; UE/gNB RX and TX timing error; channel estimation error; estimated channel quality such as SINR, RSRP (Reference Signal Received Power), RSRQ (Signal Reference Signal Received Quality), RSRPP (reference signal received path power), Es/Iot . Es: Received energy per RE (power normalized to the subcarrier spacing) during the useful part of the symbol, i.e. excluding the cyclic prefix, at the UE antenna connector or radiated interface boundary. lot: The received power spectral density of the total noise and interference for a certain RE (power integrated over the RE and normalized to the subcarrier spacing) as measured at the UE antenna connector or radiated interface boundary. [0120] If the model is designed for a certain range of implementation imperfection, measured signal quality, and/or measurement errors, then the model is likely to fail if the corresponding value experienced during model inference is outside the designed range. This is especially true if the actual quality or error is worse than the designed range. For example, if the model was trained with measurement data with SINR in the range of -20 dB to 10 dB (e.g., the training dataset contains measurement data with SINR in the range of -20 dB to 10 dB), while the actual SINR in model inference is -30 dB, then the model is not expected to generate useful model output. In another example, if the model is designed to handle UE timing error in the range of -10ns to 10ns (e.g., the training dataset contains measurement data with UE timing error in the range of -10ns to 10ns), while the actual UE timing error in model inference is -20 ns, then the model is not expected to generate useful output.
[0121] Therefore, during model inference, the quality of measurement data should be monitored to determine if the measurement data is acceptable to be used as model input. The determination is with reference to the designed measurement quality range or measurement error range of the model input for the trained model. This implies that the trained model should be stored together with the information on the applicability condition of the model input, including the measurement quality range or measurement error range of the model input for the trained model. [0122] When the quality of measurement data for model input is determined to be worse than the acceptable quality, then actions are to be taken to avoid using the corresponding AI/ML model output which is likely to degrade the system performance.
[0123] In some embodiments, the fulfillment of one or more of the triggering events implies determining that the channel conditions have changed. In some embodiments, the unfulfillment of one or more of the triggering events implies determining that the channel conditions have not changed, i.e. the channel is stable. In some embodiments, all the triggering events should be unfulfilled to determine that the channel conditions have not changed, i.e. the channel is stable. [0124] Some embodiments determine various actions to take (e.g., step 140 in Figure 7). In some embodiments, the action comprises at least that the UE informs the network that it has stopped measurements (e.g., step 150 in Figure 7).
[0125] In some embodiments, the action comprises at least that the UE reports the (possibly pre-processed) measurements so far, prior to the channel condition changing, i.e. under the condition that the channel is stable. The pre-processing may, e.g., be selecting the N best measurements.
[0126] In some embodiments, the action comprises at least that the UE restarts measurements, either from scratch, or by continuing at the point it was, in the same set of beams. In another embodiment, the UE changes the set of beams (sweep) in which to perform the radio measurements.
[0127] In some embodiments, the action is pre-defined in the standard/specifications (step 140b in Figure 7 is not needed). In some embodiments, the action is based on RRC configuration. In some embodiments, the action is based on DCI signaling.
[0128] In some embodiments, the UE stops the measurement during the measurement occasion, as soon as it is determined that the channel condition has changed.
[0129] In some embodiments, when the UE stops the measurement during the measurement occasion, the UE might drop the measurements and immediately indicate to the network that no valid measurement could be reported in the scheduled uplink resource. The network may perform the reconfiguration of resources that are previously scheduled for such UE to report the measurements.
[0130] In some embodiments, when the UE stops the measurements during the measurement occasion, the UE might resume the measurements based on some predetermined or configured time offset, where the time offset is agreed between the network and UE. After the measurement period, the UE only reports the valid measurements with additional 1 -bit indication for network to know that some measurements are dropped. In some embodiments, the UE reports the valid measurements with additional bits for the network to know more detailed information of the dropped measurements.
[0131] In some embodiments, when the UE stops the measurement during the measurement occasion, the UE might drop the measurements and indicate to the network on the scheduled uplink resource that the measurements are stopped and dropped. The UE may skip the indication because the network may implicitly know that the measurements might be stopped or dropped or skipped by the UE. [0132] In some embodiments, upon determining that the channel conditions have changed, the UE logs and stores, e.g. in a variable allocated in the UE memory, the measurement results related to measurements performed prior the channel condition changing, i.e. under the condition that the channel is stable. For example, the UE stops the radio measurement collection upon determining that the channel conditions have changed and logs the radio measurements collected so far. The measurement results are stored until they are reported to the network. According to this embodiment, the UE may store in the UE memory radio measurements collected at different points in time, wherein each stored radio measurement (comprising RSRP, RSRQ, SINR, RSSI) are associated to radio measurements performed in radio channel under the condition that the radio channel was stable.
[0133] In some embodiments, the network may configure the UE if reporting partial sweeps is allowed or not. The action taken by the UE may then depend on this configuration. For example, if reporting partial sweeps is allowed, the UE may log the partial sweep in the Al data report, and if not allowed, the UE may discard the sample and restart the sweep.
[0134] In one embodiment, the entity that performs the measurement for AI/ML model input does not provide the unavailable or unacceptable measurements for AI/ML model. In a related embodiment, the entity that performs the measurement provides measurements as possible AI/ML model input, while attaching a message regarding the measurement quality, particularly if the measurement quality is poorer than acceptable.
[0135] In one example, the entity that performs the measurement (denoted as Entity-A) is the same entity that performs AI/ML model inference (denoted as Entity -B, and Entity -B=Entity -A in this case). In this case, Entity-A may take one of the following actions to address the problem of unavailable or unacceptable measurements.
[0136] Entity-A stops performing AI/ML model inference with the current AI/ML model and uses a different AI/ML model to generate the desired model output, where the different AI/ML model is capable of accepting this type of measurement as model input (e.g., capable of accepting measurements with worse measurement error).
[0137] Entity-A stops performing AI/ML model inference, and uses a fallback method (i.e., non-AI/ML based) to generate the desired model output to fulfill the functionality of the AI/ML model (e.g., beam prediction, UE position estimation, etc.).
[0138] Entity-A stops performing AI/ML model inference and sends an indicator to the entity that receives the model output (denoted as Entity-C) that an error has occurred with the AI/ML model. Moreover, the indicator may include an error code, for example, “Unexpected error with model input measurement.” [0139] In another example, the entity that performs the measurement (denoted as Entity-A) is different from the entity that performs AI/ML model inference (denoted as Entity-B, and Entity- B^Entity-A in this case). In this case, Entity A may take one of the following actions to address the problem of unavailable or unacceptable measurements.
[0140] Entity-A sends the measurement(s) as is to Entity-B, together with an indicator of the measurement quality. For example, the measurement quality indicator may notify Entity-B one or more of the following: (a) channel estimation error level (e.g., in-range, out-of-range) experienced when performing the measurement; (b) timing error level (e.g., in-range, out-of-range) of the circuit performing the measurement; (c) noise and/or inference level (e.g., in-range, out-of-range) associated with the measurement. When Entity B receives the measurement value together with the indicator of the measurement quality, Entity-B decides whether to use the measurement as model input to its AI/ML model or discard the measurement (e.g., due to unacceptable measurement quality) and take actions similar to (l.a)-(l.c).
[0141] Entity-A sends a substitute measurement(s) to Entity-B, together with an indicator of the measurement quality. For example, the substitute measurement may be a historical value, or calculated based on historical value(s) (e.g., weighted average of previous N measurements). In this case, the measurement quality indicator may notify Entity-B, e.g., “Reported measurement is replaced with a historical value due to larger-than-expected receiver error”. Correspondingly, Entity-B decides whether to use the substitute measurement as model input to its AI/ML model or discard the substitute measurement (e.g., due to unacceptable measurement quality) and take actions similar to (l.a)-(l .c).
[0142] Entity-A does not send the measurement(s) to Entity-B. Instead, Entity-A sends Entity -
B an error message, where the error message may include an error code why the measurements are not provided, for example, “SINR of the measurement for model input is worse than X dB”, “Out-of-range UE timing error”, “Measurement not performed due to low power mode”, etc. Correspondingly, Entity-B can take actions similar to (l.b)-(l.c).
[0143] In some embodiments, the network awaits information from the UE about how stable its channel conditions are. The information may be binary (stable/unstable) or more fine-granular. In another embodiment, the network may receive a TDCP report from the UE, and the network compares the WNCA(s) in the TDCP report to one or more thresholds to determine if the channel conditions are stable. If the network deems the channel conditions stable enough, the network may trigger measurements and/or request a measurement report from the UE. In some embodiments, the network selects the duration of the time interval covered by a measurement report based on how stable the channel is. For example, the network may request many measurements (e.g. sweeping many Tx beams) rapidly after each other if channel is unstable, and spreading the measurements out in time if the channel is stable. The network may request fewer measurements (e.g., sweeping just a few Tx beams) if the channel is unstable, and larger number of measurements if the channel is stable (e.g. sweeping many Tx beams).
[0144] The network may also configure/signal the extent of time-domain averaging over measurements the UE should perform, e.g. if the channel is very stable, the network may request that the UE averages over multiple measurements to improve accuracy, whereas if channel conditions vary rapidly, the network may request that the UE does not average at all.
[0145] In some embodiments, the UE informs the network about measurement grouping. In some embodiments, the UE does not immediately inform the network about stopping of measurements, but rather immediately resumes or restarts measurements and at a later time instance and reports measurement results spanning over one or more stops along with information about where the stops occurred or information about which set of measurements can be considered to have been performed under approximately same channel conditions.
[0146] This effectively groups measurement into multiple groups, where measurements within a group may be considered to have been performed under similar channel conditions, while for measurements in different groups, this cannot be assumed. This knowledge enables the network to use the collected data appropriately in AI/ML model training. An example is illustrated in Figure 9.
[0147] Figure 9 illustrates three measurement groups, containing measurements { 1, 2, 3}, {4, 5, 6}, and {7}, respectively.
[0148] In one embodiment, the UE informs about the groups in terms of group start and group duration (where start and duration may be expressed in terms of seconds, slots, OFDM symbols, and/or number of measurements). In some embodiments, the groups may be overlapping. In another embodiment, the UE reports a group identifier (e.g., a channel stability group identifier) for each measurement it reports to the network. The measurements that have the same group identifier are considered to have been performed under similar channel conditions. In the example of Figure 9, measurements 1-3 are reported along with a first group identifier, measurements 4-6 are reported along with a second group identifier, and measurement 7 is reported along with a third group identifier.
[0149] In some embodiments, the UE aggregates/combines/merges measurements within each group (e.g., finding the best RSRP value within the group) before reporting. In this case it might not be necessary to indicate the group boundaries to the network. [0150] In some embodiments, the UE switches Rx beam only between groups, not within groups. This may be useful, because relative measurement errors between measurements with same Rx beam may be smaller than relative measurement errors between measurements using different Rx beams, and thus it may be valuable to stay on the same Rx beam while channel conditions are stable, while if the channel conditions have changed dramatically (i.e., at a group boundary), it may not matter much if there is some extra error from a beam switch at that point. In some embodiments, Rx panel or Rx RF chain rather than Rx beam is considered. The examples described are not necessarily applicable only if “groups” have been defined but may also be used in more general cases of stops in the measurements.
[0151] Some embodiments include reporting of radio measurements results to the network (e.g., step 150). In some embodiments, the UE reports the radio measurement results including one or more of the following information: one or more radio measurement results (e.g. RSRP, RSRQ, SINR, RSSI) performed under the conditions that the channel is stable; one or more triggering events that were fulfilled determining that channel conditions are changed; the amount of time (e.g., in terms of consecutive radio resources such as OFDM symbols or slots, or in terms of milliseconds or seconds) the channel was determined as stable; an indication of the one or more beams, e.g. SSB/CSI-RS index, for which the radio measurement results were performed; and/or an indication of the cell in which the radio measurements were performed.
[0152] According to some embodiments, the above set of information may be reported to the network upon determining that one or more of the triggering events for channel condition change are fulfilled. In another embodiment, the above set of information may be reported to the network periodically, or based on events different than the events used for determining that the channel conditions are changed, or upon network request, e.g. the UE signals to the network the availability of collected measurements results and the network requests the UE to transmit the collected radio measurement results.
[0153] In one embodiment, the report consists of more than one radio measurement collection, wherein each radio measurement collection is performed under the condition that the channel is stable. Each radio measurement collection included in the report comprises one or more of the information above. For example, while the channel conditions are determined to be stable in a first channel, the UE performs radio measurement on the first channel; upon determining that the channel conditions on the first channel are changed, the UE logs and stores in the UE memory the radio measurements including one or more of the information above associated to the first channel. Then, the UE may start performing radio measurements in a second channel (which could be the same channel, i.e. same SSB/CSI-RS resources, as the first channel or a different channel) upon determining that the channel conditions in the second channel are stable. Upon determining that the channel conditions in the second channel are changed, the UE logs and stores in the UE memory the radio measurements including one or more of the information above associated to the second channel. This operation may be repeated for a plurality of radio measurements performed in a plurality of channels, wherein each radio measurement is performed under the condition that the channel conditions in the concerned channel are stable. This method implies that the report to the network may consist of a list of radio measurements, wherein each entry in the list may comprise one of more of the information above associated to radio measurements performed in a given channel. Upon transmitting to the network the report, the information associated to each radio measurement reported may be cleared from the UE memory.
[0154] As used herein, “measurement” may be e.g. RSRP or RSRQ measurement, or some other type of beam/channel quality measurement. Also, it is to be understood that where RSRP is explicitly mentioned, one may typically derive a related embodiment by replacing it with e.g. RSRQ or other type of beam/channel quality measurement.
[0155] In any embodiment mentioning “Rx beam”, “Rx panel”, or “Rx RF chain”, “Rx spatial filter”, etc., one may typically derive a related embodiment by substituting any other of these terms. [0156] Figure 10 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 3rd 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.
[0157] 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.
[0158] 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.
[0159] 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).
[0160] 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.
[0161] As a whole, the communication system 100 of Figure 10 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.
[0162] In some examples, the telecommunication network 102 is a cellular network that implements 3 GPP 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.
[0163] 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).
[0164] 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.
[0165] 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.
[0166] Figure 11 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.
[0167] A UE may support device-to-device (D2D) communication, for example by implementing a 3 GPP 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).
[0168] 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 2. 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.
[0169] 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).
[0170] 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.
[0171] 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.
[0172] 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.
[0173] 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.
[0174] 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.
[0175] 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.
[0176] 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). [0177] 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.
[0178] 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, a motion detector, a thermostat, a smoke detector, a door/window sensor, a flood/moisture sensor, an electrical door lock, a connected doorbell, an air conditioning system like a heat pump, an autonomous vehicle, a surveillance system, a weather monitoring device, a vehicle parking monitoring device, an electric vehicle charging station, a smart watch, a fitness tracker, a head-mounted display for Augmented Reality (AR) or Virtual Reality (VR), a wearable for tactile augmentation or sensory enhancement, a water sprinkler, an animal- or 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 2.
[0179] As yet another specific example, in an loT scenario, a UE may represent a machine or other device that performs monitoring and/or measurements and transmits the results of such monitoring and/or measurements to another UE and/or a network node. The UE may in this case be an M2M device, which may in a 3GPP context be referred to as an MTC device. As one particular example, the UE may implement the 3GPP NB-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.
[0180] 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.
[0181] Figure 12 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)). [0182] 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).
[0183] 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).
[0184] 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., a NodeB component and a RNC component, or a BTS component and a BSC component, etc.), which may each have their own respective components. In certain scenarios in which the network node 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. [0185] 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.
[0186] 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.
[0187] 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.
[0188] The communication interface 306 is used in wired or wireless communication of signaling and/or data between a network node, access network, and/or UE. As illustrated, the communication interface 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 front-end 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 front-end 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.
[0189] 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).
[0190] 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.
[0191] 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.
[0192] 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.
[0193] Embodiments of the network node 300 may include additional components beyond those shown in Figure 12 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.
[0194] Figure 13 is a block diagram of a host 400, which may be an embodiment of the host 116 of Figure 1, 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.
[0195] 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 10 and 3, such that the descriptions thereof are generally applicable to the corresponding components of host 400.
[0196] 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., FLAC, 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.
[0197] Figure 14 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.
[0198] 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.
[0199] 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. [0200] 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.
[0201] In the context of NFV, 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 of NFV, 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.
[0202] 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.
[0203] Figure 15 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 10 and/or UE 200 of Figure 2), network node (such as network node 110a of Figure 10 and/or network node 300 of Figure 3), and host (such as host 116 of Figure 10 and/or host 400 of Figure 4) discussed in the preceding paragraphs will now be described with reference to Figure 6. [0204] 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.
[0205] 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 1) 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.
[0206] 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.
[0207] 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.
[0208] 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.
[0209] 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.
[0210] 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 the data rate and latency and thereby provide benefits such as reduced user waiting time, better responsiveness, and better QoE.
[0211] 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.
[0212] 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.
[0213] 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.
[0214] 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.
[0215] FIGURE 16 is a flowchart illustrating an example method 1600 in a wireless device, according to certain embodiments. In particular embodiments, one or more steps of FIGURE 16 may be performed by UE 200 described with respect to FIGURE 11.
[0216] The method begins at step 1612, where the wireless device (e.g., UE 200) measures one or more reference signals for data collection (e.g., for use with a machine learning model).
[0217] The wireless device may be configured by a network node to measure the one or more reference signals. In particular embodiments, the measuring of the one or more reference signals for data collection is initiated when the channel condition associated with the one or more reference signals has not changed beyond a threshold value for a time duration.
[0218] In particular embodiments, the wireless device may measure one or more reference signals according to any of the embodiments and examples described herein.
[0219] At step 1614, the wireless device determines that a change to a channel condition associated with the one or more reference signals impacts the data collection. For example, the change to the channel condition may cause the collected data to no longer be useful for its intended purpose.
[0220] In particular embodiments, determining that a change to a channel condition associated with the one or more reference signals impacts the data collection comprises determining that the channel condition has changed beyond a threshold value during the data collection. [0221] In particular embodiments, the determining that the channel condition has changed comprises evaluating one or more measurement quantities, such as one or more of: measurement output of a speed, position, or inertia sensor; TDCP measurements; a measurement of a signal strength or interference; and historical measurements of channel coherence time. Determining that the channel condition has changed may comprise determining that the wireless device made a change in a configuration of the wireless device that affects the channel condition.
[0222] In particular embodiments, the threshold value is dependent on a purpose of the data collection. For example, a purpose of the data collection may be for machine learning model inference and the threshold value may be based on a value used for training the machine learning model.
[0223] In particular embodiments, the wireless device may determine that a change to a channel condition associated with the one or more reference signals impacts the data collection according to any of the embodiments and examples described herein.
[0224] At step 1616, the wireless device, based on the determination, stops the data collection. For example, if the measurements are determined to not be useful for their intended purpose, then the wireless device may conserve resources by not continuing with the measurements.
[0225] In some embodiments, the wireless device may take additional actions upon determining that the change to the channel condition impacted the data collection. In some embodiments, the wireless device may take any of the actions described with respect to the embodiments and examples described herein.
[0226] At step 1618, the wireless device may report to a network node an indication that the data collection was stopped. The indication that the data collection was stopped may comprise an indication of the channel condition that caused the data collection to stop. Reporting the indication that the data collection was stopped may comprise reporting data collected prior to determining that the channel condition changed.
[0227] In particular embodiments, the wireless device may report the indication according to any of the embodiments and examples described herein.
[0228] Modifications, additions, or omissions may be made to method 1600 of FIGURE 16. Additionally, one or more steps in the method of FIGURE 16 may be performed in parallel or in any suitable order.
[0229] FIGURE 17 is a flowchart illustrating an example method 1700 in a network node, according to certain embodiments. In particular embodiments, one or more steps of FIGURE 17 may be performed by network node 300 described with respect to FIGURE 12. [0230] The method begins at step 1712, where the network node (e.g., network node 300) configures a wireless device to measure one or more reference signals for data collection (e.g., for use with a machine learning model).
[0231] In particular embodiments, configuring the wireless device to measure the one or more reference signals for data collection comprises determining the channel condition associated with the one or more reference signals has not changed beyond a threshold value for a time duration.
[0232] In particular embodiments, the network node configures the wireless device to measure one or more reference signals for data collection according to any of the embodiments and examples described herein.
[0233] At step 1714, the network node receives an indication from the wireless device that the data collection was stopped based on a determination that a change to a channel condition associated with the one or more reference signals impacted the data collection. The indication and the determination of the changed channel conditions are described in more detail with respect to Figure 16 and with respect to the embodiments and examples above.
[0234] At step 1716, in response to receiving the indication, the network node may stop using a machine learning model. For example, because the network node knows that it will not receive data collection results to be used with the machine learning model, the network node may fallback to a different mechanism to provide a similar functionality. The network node may take additional steps in response to receiving the indication, which are described in more detail with respect to the embodiments and examples described herein.
[0235] Modifications, additions, or omissions may be made to method 1700 of FIGURE 17. Additionally, one or more steps in the method of FIGURE 17 may be performed in parallel or in any suitable order.
[0236] The foregoing description sets forth numerous specific details. It is understood, however, that embodiments may be practiced without these specific details. In other instances, well-known circuits, structures and techniques have not been shown in detail in order not to obscure the understanding of this description. Those of ordinary skill in the art, with the included descriptions, will be able to implement appropriate functionality without undue experimentation.
[0237] References in the specification to “one embodiment,” “an embodiment,” “an example embodiment,” etc., indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to implement such feature, structure, or characteristic in connection with other embodiments, whether or not explicitly described.
[0238] Although this disclosure has been described in terms of certain embodiments, alterations and permutations of the embodiments will be apparent to those skilled in the art. Accordingly, the above description of the embodiments does not constrain this disclosure. Other changes, substitutions, and alterations are possible without departing from the scope of this disclosure, as defined by the claims below.
[0239] Some example embodiments are described below.
Group A Embodiments
1. A method performed by a wireless device, the method comprising:
- measuring one or more reference signals for data collection;
- determining a channel condition associated with the one or more reference signals has changed beyond a threshold value; and
- based on the determination, stopping the data collection.
2. The method of the previous embodiment, further comprising reporting to a network node an indication that the data collection was stopped.
3. The method of the previous embodiment, wherein reporting the indication that the data collection was stopped comprises reporting an indication of the channel condition that caused the data collection to stop.
4. The method of any one of the previous two embodiments, wherein reporting the indication that the data collection was stopped comprises reporting data collected prior to determining the channel condition changed beyond a threshold value.
5. The method of the previous embodiment, wherein determining the channel condition has changed beyond a threshold value comprises evaluating one or more measurement quantities.
6. The method of the previous embodiment, wherein the measurement quantity includes one or more of: sensors, channel measurements including TDCP measurements, and historical information. The method of any one of the previous embodiments, wherein determining the channel condition has changed beyond a threshold value comprises determining the wireless device made a change in its setting/configuration that affects the channel conditions. The method of any one of the previous embodiments, wherein determining the channel condition has changed beyond a threshold value comprises determining one or more of:
- the wireless device has moved more than a threshold channel coherence length;
- one or more WNCA(s) in the TDCP measurement are below one or more predefined threshold(s);
- channel conditions in form of interference have changed beyond a threshold value; and
- the wireless device has rotated more than a certain angle. The method of any one of the previous embodiments, further comprising:
- immediately resuming the data collection after indicating the channel condition associated with the one or more reference signals changed beyond the threshold value. The method of any one of the previous embodiments, further comprising:
- determining a channel condition associated with the one or more reference signals has returned to within a threshold value; and
- based on the determination, resuming the data collection. A method performed by a wireless device, the method comprising:
- any of the wireless device steps, features, or functions described above, either alone or in combination with other steps, features, or functions described above. The method of the previous embodiment, further comprising one or more additional wireless device steps, features or functions described above. 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 base station. Group B Embodiments
14. A method performed by a base station, the method comprising:
- configuring a wireless to measure one or more reference signals for data collection; and
- receiving an indication from the wireless device that the data collection was stopped based on a determination that a channel condition associated with the one or more reference signals has changed beyond a threshold value.
15. The method of the previous embodiment, wherein the indication is based on an evaluation of one or more measurement quantities.
16. The method of the previous embodiment, wherein the measurement quantity includes one or more of: sensors, channel measurements including TDCP measurements, and historical information.
17. The method of any one of the previous three embodiments, wherein the indication is based on a determination that the wireless device made a change in its setting/configuration that affects the channel conditions.
18. The method of any one of the previous four embodiments, wherein the indication is based on one or more of:
- the wireless device has moved more than a threshold channel coherence length;
- one or more WNCA(s) in the TDCP measurement are below one or more predefined threshold(s);
- channel conditions in form of interference have changed beyond a threshold value; and
- the wireless device has rotated more than a certain angle.
19. The method of any one of the previous five embodiments, wherein the indication includes an indication of the channel condition that caused the data collection to stop.
20. The method of any one of the previous six embodiments, wherein the indication includes data collected prior to the wireless device determining the channel condition changed beyond a threshold value. 21. A method performed by a base station, the method comprising:
- any of the steps, features, or functions described above with respect to base stations, either alone or in combination with other steps, features, or functions described above.
22. The method of the previous embodiment, further comprising one or more additional base station steps, features or functions described above.
23. The method of any of the previous embodiments, further comprising:
- obtaining user data; and
- forwarding the user data to a host computer or a wireless device.
Group C Embodiments
24. A mobile terminal comprising:
- processing circuitry configured to perform any of the steps of any of the Group A embodiments; and
- power supply circuitry configured to supply power to the wireless device.
25. A base station comprising:
- processing circuitry configured to perform any of the steps of any of the Group B embodiments;
- power supply circuitry configured to supply power to the wireless device.
26. 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 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.

Claims

Claims
1. A method (1600) performed by wireless device, the method comprising: measuring (1612) one or more reference signals for data collection; determining (1614) that a change to a channel condition associated with the one or more reference signals impacts the data collection; and based on the determination, stopping (1616) the data collection.
2. The method of claim 1, wherein determining that a change to a channel condition associated with the one or more reference signals impacts the data collection comprises determining that the channel condition has changed beyond a threshold value during the data collection.
3. The method of any one of claims 1 -2, further comprising reporting (1618) to a network node an indication that the data collection was stopped.
4. The method of claim 3, wherein the indication that the data collection was stopped comprises an indication of the channel condition that caused the data collection to stop.
5. The method of any one of claims 3-4, wherein reporting the indication that the data collection was stopped comprises reporting data collected prior to determining that the channel condition changed.
6. The method of any one of claims 1-5, wherein the determining that the channel condition has changed comprises evaluating one or more measurement quantities.
7. The method of claim 6, wherein the measurement quantity includes one or more of measurement output of a speed, position, or inertia sensor; time domain channel property, TDCP, measurements; a measurement of a signal strength or interference; and historical measurements of channel coherence time.
8. The method of any one of claims 1-7, wherein determining that the channel condition has changed comprises determining that the wireless device made a change in a configuration of the wireless device that affects the channel condition.
9. The method of any one of claims 2-8, wherein the threshold value is dependent on a purpose of the data collection.
10. The method of claim 9, wherein a purpose of the data collection is for machine learning model inference and the threshold value is based on a value used for training the machine learning model.
11. The method of any one of claims 1-10, wherein the measuring of the one or more reference signals for data collection is initiated when the channel condition associated with the one or more reference signals has not changed beyond a threshold value for a time duration.
12. A wireless device (200) comprising processing circuitry (202), the processing circuitry operable to: measure one or more reference signals for data collection; determine that a change to a channel condition associated with the one or more reference signals impacts the data collection; and based on the determination, stop the data collection.
13. The wireless device of claim 12, wherein the processing circuitry is operable to determine that a change to a channel condition associated with the one or more reference signals impacts the data collection by determining that the channel condition has changed beyond a threshold value during the data collection.
14. The wireless device of any one of claims 12-13, the processing circuitry further operable to report to a network node (300) an indication that the data collection was stopped.
15. The wireless device of claim 14, wherein the indication that the data collection was stopped comprises an indication of the channel condition that caused the data collection to stop.
16. The wireless device of any one of claims 14-15, wherein the processing circuitry is operable to report the indication that the data collection was stopped by reporting data collected prior to determining that the channel condition changed.
17. The wireless device of any one of claims 12-16, wherein the processing circuitry is operable to determine that the channel condition has changed by evaluating one or more measurement quantities.
18. The wireless device of claim 17, wherein the measurement quantity includes one or more of: measurement output of a speed, position, or inertia sensor; time domain channel property, TDCP, measurements; a measurement of a signal strength or interference; and historical measurements of channel coherence time.
19. The wireless device of any one of claims 12-18, wherein the processing circuitry is operable to determine that the channel condition has changed by determining that the wireless device made a change in a configuration of the wireless device that affects the channel condition.
20. The wireless device of any one of claims 13-19, wherein the threshold value is dependent on a purpose of the data collection.
21. The wireless device of claim 20, wherein a purpose of the data collection is for machine learning model inference and the threshold value is based on a value used for training the machine learning model.
22. The wireless device of any one of claims 12-21, wherein the measuring of the one or more reference signals for data collection is initiated when the channel condition associated with the one or more reference signals has not changed beyond a threshold value for a time duration.
23. A method (1700) performed by a network node, the method comprising: configuring (1712) a wireless device to measure one or more reference signals for data collection; and receiving (1714) an indication from the wireless device that the data collection was stopped based on a determination that a change to a channel condition associated with the one or more reference signals impacted the data collection.
24. The method of claim 23, wherein the indication that the data collection was stopped comprises an indication of the channel condition that caused the data collection to stop.
25. The method of any one of claims 23-24, wherein receiving the indication that the data collection was stopped comprises receiving data collected prior to the determination that the channel condition changed.
26. The method of any one of claims 23-25, wherein the indication is based on an evaluation of one or more measurement quantities.
27. The method of claim 26, wherein the measurement quantity includes one or more of: measurement output of a speed, position, or inertia sensor; time domain channel property, TDCP, measurements; measurement of signal strength or interference; and historical measurements of channel coherence time.
28. The method of any one of claims 23-27, wherein the indication is based on a determination that the wireless device made a change in a configuration of the wireless device that affects the channel condition.
29. The method of any one of claims 23-28, wherein the determination that a change to a channel condition associated with the one or more reference signals impacted the data collection is based on a determination that the channel condition changed beyond a threshold value during the data collection.
30. The method of claim 29, wherein the threshold value is dependent on a purpose of the data collection.
31. The method of claim 30, wherein a purpose of the data collection is for machine learning model inference and the threshold value is based on a value used for training the machine learning model.
32. The method of any one of claims 23-31, wherein configuring the wireless device to measure the one or more reference signals for data collection comprises determining the channel condition associated with the one or more reference signals has not changed beyond a threshold value for a time duration.
33. The method of any one of claims 23-32, further comprising, in response to receiving the indication, stopping (1716) use of a machine learning model.
34. A network node (300) comprising processing circuitry (302), the processing circuitry operable to: configure a wireless device (200) to measure one or more reference signals for data collection; and receive an indication from the wireless device that the data collection was stopped based on a determination that a change to a channel condition associated with the one or more reference signals impacted the data collection.
35. The network node of claim 34, wherein the indication that the data collection was stopped comprises an indication of the channel condition that caused the data collection to stop.
36. The network node of any one of claims 34-35, wherein the processing circuitry is operable to receive the indication that the data collection was stopped by receiving data collected prior to the determination that the channel condition changed.
37. The network node of any one of claims 34-36, wherein the indication is based on an evaluation of one or more measurement quantities.
38. The network node of claim 37, wherein the measurement quantity includes one or more of: measurement output of a speed, position, or inertia sensor; time domain channel property, TDCP, measurements; measurement of signal strength or interference; and historical measurements of channel coherence time.
39. The network node of any one of claims 34-38, wherein the indication is based on a determination that the wireless device made a change in a configuration of the wireless device that affects the channel condition.
40. The network node of any one of claims 34-39, wherein the determination that a change to a channel condition associated with the one or more reference signals impacted the data collection is based on a determination that the channel condition changed beyond a threshold value during the data collection.
41. The network node of claim 40, wherein the threshold value is dependent on a purpose of the data collection.
42. The network node of claim 41, wherein a purpose of the data collection is for machine learning model inference and the threshold value is based on a value used for training the machine learning model.
43. The network node of any one of claims 34-42, wherein the processing circuitry is operable to configure the wireless device to measure the one or more reference signals for data collection by determining the channel condition associated with the one or more reference signals has not changed beyond a threshold value for a time duration.
44. The network node of any one of claims 34-43, the processing circuitry further operable to, in response to receiving the indication, stop using a machine learning model.
PCT/SE2024/051117 2023-12-19 2024-12-19 Data collection stop based on ue event Pending WO2025136207A1 (en)

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