WO2025210845A1 - Terminal, wireless base station, and wireless communication method - Google Patents

Abstract

This terminal performs intra-frequency measurement in a serving cell and transmits the results of the intra-frequency measurement to a network. The terminal performs intra-frequency measurement in a neighboring cell of the serving cell, and uses a learning model to predict, from the results of the intra-frequency measurement of the neighboring cell, a result of inter-frequency measurement in the neighboring cell for a frequency that differs from the frequency of the intra-frequency measurement.

Description

Terminal, wireless base station, and wireless communication method

This disclosure relates to a terminal, a wireless base station, and a wireless communication method that utilizes an AI/ML model.

The 3rd Generation Partnership Project (3GPP: registered trademark) is developing specifications for Long Term Evolution (LTE) and 5th generation mobile communication systems (5G, also known as New Radio (NR) or Next Generation (NG)), and is also developing specifications for the next generation, known as Beyond 5G, 5G Evolution, or 6G.

3GPP Release 19 has established a work item (WI) on artificial intelligence/machine learning models (AI/ML Models) (Non-Patent Document 1).

For example, it is planned to consider using AI/ML models to predict cell quality measurement results, including intra-frequency and inter-frequency measurements.

"Revised SID on AIML for mobility in NR", RP-240082, 3GPP TSG RAN Meeting #103, 3GPP, March 2024

In the existing 3GPP specifications for LTE/NR, in the case of intra-frequency measurements, the terminal (User Equipment, UE) can measure cell quality without setting up a measurement gap. On the other hand, in the case of inter-frequency measurements (and inter-radio access technology (RAT) measurements), the UE must temporarily stop transmission and reception to change the radio frequency (RF) settings, which requires a measurement gap.

When a measurement gap is set, scheduling on the uplink (UL) and downlink (DL) is suspended for the duration of the measurement gap (e.g., 6 ms), which also affects the throughput between the UE and the radio base station (gNB).

Therefore, efforts are being made to use AI/ML models to predict the results of inter-frequency measurements from the results of intra-frequency measurements. However, simply using an AI/ML model presents the problem of difficulty in obtaining valid predicted results for inter-frequency measurements (as well as inter-RAT measurements).

The following disclosure has been made in light of this situation, and aims to provide a terminal, wireless base station, and wireless communication method that can predict appropriate inter-frequency measurement results from intra-frequency measurement results using an AI/ML model.

One aspect of the present disclosure is a terminal (UE200) that includes a control unit (control unit 240) that performs intra-frequency measurements in a serving cell, and a transmission unit (measurement processing unit 220) that transmits the results of the intra-frequency measurements to a network, and the control unit performs the intra-frequency measurements in cells neighboring the serving cell, and predicts, using a learning model, the results of inter-frequency measurements in the neighboring cells that target frequencies different from those of the intra-frequency measurements, based on the results of the intra-frequency measurements in the neighboring cells.

One aspect of the present disclosure is a radio base station (gNB100) that includes a receiver (radio communication unit 110) that receives from a terminal the results of intra-frequency measurements in cells neighboring a serving cell, and a control unit (control unit 140) that uses a learning model to predict, from the results of the intra-frequency measurements in the neighboring cells, the results of inter-frequency measurements in the neighboring cells that target frequencies different from those of the intra-frequency measurements.

One aspect of the present disclosure is a wireless communication method in a terminal that includes the steps of: performing intra-frequency measurements in a neighboring cell of a serving cell; and predicting, using a learning model, the results of inter-frequency measurements in the neighboring cell, the inter-frequency measurements being for a frequency different from that of the intra-frequency measurements, based on the results of the intra-frequency measurements in the neighboring cell.

FIG. 1 is a diagram showing the overall configuration of a wireless communication system 10. Figure 2 is a functional block diagram of gNB100. FIG. 3 is a functional block diagram of the UE 200. Figure 4 shows an example of the functional architecture of an AI/ML model. Figure 5 shows an example sequence for predicting the results of inter-frequency measurements. FIG. 6 is a diagram showing an example of frequencies (bands) used by the own cell (beam) and neighboring cells (beams) and predicted values of offsets. FIG. 7 is a diagram illustrating an example of the configuration of a RIC based on the O-RAN architecture. Figure 8 is a diagram showing an example of the hardware configuration of gNB100 and UE200. FIG. 9 is a diagram showing an example of the configuration of a vehicle 2001.

The following describes embodiments based on the drawings. Note that identical or similar reference symbols are used to designate identical functions and configurations, and descriptions of these will be omitted where appropriate.

(1) Overall Schematic Configuration of Wireless Communication System Fig. 1 is a diagram showing the overall schematic configuration of a wireless communication system 10 according to this embodiment. The wireless communication system 10 is a wireless communication system conforming to 5G New Radio (NR) and includes a Next Generation-Radio Access Network 20 (hereinafter, NG-RAN 20) and a terminal 200 (User Equipment 200, hereinafter, UE 200).

The wireless communication system 10 may be a wireless communication system conforming to a method called Beyond 5G, 5G Evolution, or 6G, or may include a wireless communication system conforming to a method called Long Term Evolution (LTE) or 4G. The wireless communication system 10 may support functions related to the Industrial Internet of Things (IIoT) and URLLC (Ultra-Reliable and Low Latency Communications). The wireless communication system 10 may also be configured using multiple radio access technologies (RATs), for example, 4G/LTE and 5G.

NG-RAN 20 includes a radio base station 100 (hereinafter, gNB 100). Note that the specific configuration of the radio communication system 10, including the number of gNBs (or eNBs, etc.) and UEs, is not limited to the example shown in Figure 1.

The gNB100 may also employ a fronthaul (FH) interface specified by the Open Radio Access Network Alliance (O-RAN). The gNB100 may include an O-DU (O-RAN Distributed Unit) and an O-RU (O-RAN Radio Unit). The gNB100 can function as a type of NG-RAN node.

NG-RAN20 actually includes multiple NG-RAN nodes, specifically gNBs (or ng-eNBs), and is connected to a 5G-compliant core network (5GC, not shown). 5GC may introduce the concept of CUPS (Control and User Plane Separation), which clearly separates the functions of the user plane and the control plane.

NG-RAN20 may be connected to OAM/RIC40 and NF50 via 5GC or directly from NG-RAN20. OAM/RIC40 can provide functions related to operation and maintenance of the wireless communication system 10 (OAM). OAM/RIC40 can also provide functions related to control of NG-RAN20 (RIC: RAN Intelligent Controller). The specific functions of the RIC are defined by the O-RAN specifications (e.g., O-RAN Architecture-Description 6.0). In this embodiment, OAM/RIC40 may constitute an entity that performs operation, maintenance, or control.

NF50 may be interpreted as a logical node that provides network functions. NF50 may include the Access and Mobility Management Function (AMF), which is included in the 5G system architecture and provides access and mobility management functions for UE200, the Session Management Function (SMF), which provides session management functions, and the Location Management Function (LMF), which is responsible for communication control related to location information services specified in 5GC. Furthermore, UDM/UDR (Unified Data Management/User Data Repository) may be connected to the AMF and/or SMF. NG-RAN20 and 5GC may also be simply referred to as "networks."

In addition, NG-RAN20 may be connected to a server managed by a 3GPP service provider or a server managed by a party other than that provider (3GPP or non-3GPP server).

gNB100 is a radio base station that complies with NR and performs radio communication with UE200 that complies with NR. Note that gNB100 may be composed of a CU (Central Unit) and a DU (Distributed Unit), and the DU may be separated from the CU and installed in a different geographical location. One or more DUs may be connected to a CU. Furthermore, gNB100 (gNB-CU) may be connected to each other via an Xn interface, and CUs and DUs may be connected via an F1 interface.

The gNB100 and UE200 are capable of supporting Massive MIMO, which generates a more directional beam (BM) by controlling the radio signals transmitted from multiple antenna elements; Carrier Aggregation (CA), which aggregates multiple component carriers (CCs); and Dual Connectivity (DC), which enables simultaneous communication between the UE and multiple NG-RAN nodes. The UE200 may also perform handover (HO) to a different RAT. The UE200 may also perform handover between cells A and B (serving cells or neighboring cells).

In the wireless communication system 10, artificial intelligence (AI)/machine learning (ML) may be applied in the NG-RAN 20. Specifically, a learning model (herein referred to as an AI/ML model) may be used to optimize the mobility or handover (which may also be interpreted as transition, cell transition, cell selection, etc.) of the UE 200.

AI/ML Model may also be expressed as other terms that refer to AI or ML, such as artificial intelligence (AI) model or machine learning (ML) model.

In a broad sense, the mobility of UE200 may refer to the ease of movement and maneuverability of UE200, but in this embodiment, it may also refer to the minimization of call drops, radio link (including beam) failures, unnecessary handovers, ping-pong states, etc.

UE200 may periodically perform measurement reporting. UE200 may also perform measurement reporting for each event. An entering condition for starting measurement reporting and a leaving condition for ending measurement reporting may be defined for each event. Existing events may include the events shown below (see 3GPP TS38.331). Note that the entering condition may be interpreted as a condition for determining whether or not to include a measurement report, and the leaving condition may be interpreted as a condition for determining whether or not to exclude a measurement report from the measurement report.

(i)Event A1 (Serving becomes better than threshold)
Event A1 is an event in which the reception quality of the serving cell becomes better than a threshold. For example, the entering condition is Ms - Hys > Thresh, and the leaving condition is Ms + Hys < Thresh.

Here, Ms is the reception quality of the serving cell, Hys is the hysteresis parameter, and Thresh is the threshold value.

(ii) Event A2 (Serving becomes worse than threshold)
Event A2 is an event in which the reception quality of the serving cell becomes worse than a threshold. For example, the entering condition is Ms + Hys < Thresh, and the leaving condition is Ms - Hys > Thresh.

Here, Ms is the reception quality of the serving cell, Hys is the hysteresis parameter, and Thresh is the threshold value.

(iii) Event A3 (Neighbor becomes offset better than SpCell)
Event A3 is an event in which the reception quality of the neighboring cell is better than the reception quality of the serving cell by an offset. For example, the entering condition is Mn + Ofn + Ocn - Hys > Mp + Ofp + Ocp + Off, and the leaving condition is Mn + Ofn + Ocn + Hys < Mp + Ofp + Ocp + Off.

Here, Mn is the reception quality of the neighboring cell, Ofn is an offset specific to the measurement target, and Ocn is an offset specific to the cell. Mp is the reception quality of the serving cell, Ofp is an offset specific to the measurement target, and Ocp is an offset specific to the cell. Hys is the hysteresis parameter, and Off is the parameter used in Event A3.

(iv) Event A4 (Neighbor becomes better than threshold)
Event A4 is an event in which the reception quality of a neighboring cell becomes better than a threshold. For example, the entering condition is Mn + Ofn + Ocn - Hys > Thresh, and the leaving condition is Mn + Ofn + Ocn + Hys < Thresh.

Here, Mn is the reception quality of the neighboring cell, Ofn is the offset specific to the measurement target, and Ocn is the offset specific to the cell. Hys is the hysteresis parameter, and Thresh is the threshold value.

(v)Event A5 (SpCell becomes worse than threshold1 and neighbor becomes better than threshold2)
Event A5 is an event in which the reception quality of the serving cell becomes worse than a threshold and the reception quality of the neighboring cell becomes better than a threshold. For example, the entering condition is Mp + Hys < Thresh1 and Mn + Ofn + Ocn - Hys > Thresh2, and the leaving condition is Mp - Hys > Thresh1 and Mn + Ofn + Ocn + Hys < Thresh2.

Here, Ms is the reception quality of the serving cell, Hys is the hysteresis parameter, and Thresh1 is the threshold value. Mn is the reception quality of the neighboring cell, Ofn is an offset specific to the measurement target, and Ocn is an offset specific to the cell. Hys is the hysteresis parameter, and Thresh2 is the threshold value.

(vi)Event A6 (Neighbor becomes offset better than SCell)
Event A6 is an event in which the reception quality of a neighboring cell is better than the reception quality of a SCell (Secondary Cell) by an offset. For example, the entering condition is Mn + Ocn - Hys > Ms + Ocs + Off, and the leaving condition is Mn + Ocn + Hys < Ms + Ocs + Off.

In addition to the events mentioned above, events related to inter-RAT (Radio Access Technology) (e.g., B1 (Inter RAT neighbor becomes better than threshold), B2 (Serving becomes worse than threshold1 and inter RAT neighbor becomes better than threshold2)) may also be included.

Here, Mn is the reception quality of the neighboring cell, and Ocn is an offset specific to the cell. Ms is the reception quality of the SCell, and Ocs is an offset specific to the cell. Hys is the hysteresis parameter, and Off is the parameter used in Event A6.

In the wireless communication system 10, such an AI/ML model can be used to optimize the mobility or handover of the UE 200. The AI/ML model may be provided in the OAM/RIC 40 or in the gNB 100. The AI/ML model may also be provided in the UE 200.

Next, the functional block configuration of the wireless communication system 10 will be described. Specifically, the functional block configuration of the gNB 100 and UE 200 will be described. Figure 2 is a functional block configuration diagram of the gNB 100. Figure 3 is a functional block configuration diagram of the UE 200.

(2.1) gNB100
As shown in FIG. 2, the gNB 100 includes a wireless communication unit 110, a handover processing unit 120, an AI/ML model unit 130, and a control unit 140.

The wireless communication unit 110 transmits downlink signals (DL signals) conforming to NR. The wireless communication unit 110 also receives uplink signals (UL signals) conforming to NR. The wireless communication unit 110 may transmit DL signals and receive UL signals using one or more transmit/receive points (TRPs). In this embodiment, a TRP may be interpreted as meaning multiple DL transmit antennas.

The wireless communication unit 110 may receive the results of intra-frequency measurements in cells neighboring the serving cell from the UE 200. In this embodiment, the wireless communication unit 110 may constitute a receiving unit. The serving cell may correspond to, for example, cell A in FIG. 1. A neighboring cell is a cell formed near the serving cell, and may correspond to, for example, cell B in FIG. 1. A neighboring cell may also be called an adjacent cell or a peripheral cell. A neighboring cell does not necessarily have to overlap geographically with the serving cell, or may overlap geographically with part or all of the serving cell.

The handover processing unit 120 executes handover of the UE 200. Specifically, the handover processing unit 120 executes handover from the serving cell of the UE 200 to another nearby cell.

Note that the serving cell may be interpreted simply as the cell to which UE 200 is connected, but more precisely, in the case of an RRC_CONNECTED UE (connected state in the radio resource control layer) in which carrier aggregation (CA) is not configured, there is only one serving cell that constitutes the primary cell. In the case of an RRC_CONNECTED UE configured using CA, the serving cell may be interpreted as indicating a set of one or more cells including the primary cell and all secondary cells.

The handover may also include a conditional handover (CHO) and/or a dual active protocol stack (DAPS) handover. CHO can perform a UE200-initiated handover when certain execution conditions are met. If CHO is not applicable, a normal handover may be performed (which may be called CHO recovery). In CHO recovery, UE200 performs cell selection after a CHO failure, but if a CHO candidate cell is selected, it can directly apply conditional RRC Reconfiguration of that cell to reconnect without sending an RRC Reestablishment Request to the candidate target cell.

The execution conditions may consist of one or two trigger conditions (CHO event A3/A5 as specified in 3GPP TS38.331). A single reference signal (RS) type may be triggered, and up to two different trigger quantities (e.g., Reference Signal Received Power (RSRP) and Reference Signal Received Quality (RSRQ), RSRP and Signal-to-Interference plus Noise power Ratio (SINR), etc.) may be set simultaneously for the evaluation of the CHO execution conditions for a single candidate cell.

The AI/ML model unit 130 executes processing using a learning model (AI/ML model). Specifically, the AI/ML model unit 130 executes processing using an AI/ML model that is applied to the optimization of the mobility and/or handover of the UE 200.

In particular, in this embodiment, the AI/ML model unit 130 may predict other measurement results, specifically the results of inter-frequency measurements or inter-RAT measurements, from the results of intra-frequency measurements, in accordance with the control of the control unit 140.

Intra-frequency measurement may be interpreted as a measurement of cell quality (e.g., RSRP, RSRQ) that can be performed without changing the frequency of the radio signals transmitted and received by UE200. Inter-frequency measurement may be interpreted as a measurement of cell quality that requires a change in the frequency of the radio signals transmitted and received by UE200. Inter-RAT measurement may be interpreted as a measurement of cell quality that requires a change in the frequency of the radio signals transmitted and received by UE200 and a change in the RAT.

Inter-Frequency measurement and Inter-RAT measurement require a measurement gap, as transmission and reception must be temporarily stopped in order to change the radio frequency (RF) settings in the UE.

The control unit 140 controls each functional block that constitutes the gNB 100. In particular, in this embodiment, the control unit 140 may use the AI/ML model unit 130 to predict the results of cell quality measurements by the UE 200.

Specifically, the control unit 140 may use the AI/ML model unit 130 (learning model) to predict the results of inter-frequency measurements in neighboring cells of the UE 200 that target frequencies different from those of the intra-frequency measurements, based on the results of the intra-frequency measurements in the neighboring cells.

In addition, the control unit 140 may predict not only the results of Inter-Frequency measurements but also the results of Inter-RAT measurements.

In addition, in this embodiment, channels include control channels and data channels. Control channels include PDCCH (Physical Downlink Control Channel), PUCCH (Physical Uplink Control Channel), PRACH (Physical Random Access Channel), and PBCH (Physical Broadcast Channel), etc.

Data channels also include PDSCH (Physical Downlink Shared Channel) and PUSCH (Physical Uplink Shared Channel).

Note that reference signals include Demodulation reference signals (DMRS), Sounding Reference Signals (SRS), Phase Tracking Reference Signals (PTRS), and Channel State Information-Reference Signals (CSI-RS), and signals include channels and reference signals. Note that data may refer to data transmitted via a data channel.

(2.2) UE200
As shown in FIG. 3 , the UE 200 includes a radio communication unit 210 , an AI/ML model unit 215 , a measurement processing unit 220 , a handover execution unit 230 , and a control unit 240 .

The wireless communication unit 210 transmits uplink signals (UL signals) that comply with NR. The wireless communication unit 210 also receives uplink signals (DL signals) that comply with NR.

The AI/ML model unit 215 executes processing using a learning model (AI/ML Model). The AI/ML model unit 215 may have the same functions as the AI/ML model unit 130 of the gNB100. The AI/ML model unit may be provided in either the gNB100 or the UE200, or in both.

The AI/ML model unit 215 may predict other measurement results, specifically the results of Inter-Frequency measurements or Inter-RAT measurements, from the results of Intra-Frequency measurements, under the control of the control unit 240.

The measurement processing unit 220 can measure the quality of the serving cell of the UE 200 and the cells neighboring the serving cell, and report the measurement results to the network (Measurement Report). The measurement processing unit 220 may perform measurement reports of the source cell and target cell during handover.

The quality to be measured may be, for example, the quality included in the Measurement Report specified in 3GPP TS38.331 (e.g., RSRP, RSRQ).

In this embodiment, the measurement processing unit 220 may transmit the results of the intra-frequency measurement to the network. In this embodiment, the measurement processing unit 220 may constitute a transmitting unit.

Specifically, the measurement processing unit 220 may transmit a Measurement Report including the results of an Intra-Frequency measurement of a cell neighboring the serving cell. The measurement processing unit 220 may also transmit a Measurement Report including the results of an Inter-Frequency measurement or Inter-RAT measurement predicted from the results of the Intra-Frequency measurement.

The handover execution unit 230 executes handover of the UE 200. Specifically, the handover execution unit 230 may execute handover to the destination cell (NG-RAN node) based on control by the gNB 100.

In addition, the handover execution unit 230 can perform processing related to normal handover (legacy handover) and conditional handover (CHO).

In the case of CHO, the handover execution unit 230 may transition to a candidate cell when an execution condition is met. As described above, the execution condition may be determined based on the quality of the reference signal (RS), specifically, the RSRP, RSRQ, or SINR value.

Furthermore, the destination of a CHO may or may not involve an SCG. In other words, the destination cell of a CHO may be a single cell, or may be composed of multiple cells (which may be interpreted as a cell group) according to a DC.

Furthermore, the handover execution unit 230 can receive a handover request (handover command) for the UE 200 from the network. In this embodiment, the handover execution unit 230 may constitute a receiving unit. The handover command may include an indication to delete an AI/ML model, etc. for the source cell from which the handover originates.

The control unit 240 controls each functional block that constitutes the UE 200. Specifically, the control unit 240 may perform intra-frequency measurements in the serving cell via the measurement processing unit 220. The control unit 240 may also perform intra-frequency measurements in neighboring cells of the serving cell. There may be one or more intra-frequency measurements in neighboring cells.

The control unit 240 may use an AI/ML model to predict the results of an inter-frequency measurement in a neighboring cell that targets a frequency different from that of the intra-frequency measurement, based on the results of the intra-frequency measurement of the neighboring cell. Specifically, the control unit 240 may predict the results of the inter-frequency measurement based on the difference in the frequencies to be measured, and the difference (which may be in dB units) between the results of the intra-frequency measurement of the serving cell and the results of the intra-frequency measurement of the neighboring cell. More specific prediction methods will be described later.

The control unit 240 may apply an offset value according to the difference between the target frequency of the intra-frequency measurement and the target frequency of the inter-frequency measurement, and predict the result of the inter-frequency measurement. The size of the offset value may differ depending on the frequency band. Furthermore, the size of the offset value may basically be made larger the greater the difference between the target frequency of the intra-frequency measurement and the target frequency of the inter-frequency measurement.

The control unit 240 may perform intra-frequency measurements on the frequencies of radio signals transmitted from the same transmitting/receiving point (TRP). In other words, the control unit 240 does not need to include the frequencies of radio signals transmitted from multiple different TRPs in the prediction described above. This is because different TRPs may result in different cell quality, and the accuracy of the prediction results may not be ensured.

The control unit 240 may use an AI/ML model to predict the results of Inter-RAT measurements (measurements between radio access technologies) that target frequencies different from those of the Intra-Frequency measurements from the results of Intra-Frequency measurements of neighboring cells. Specifically, the control unit 240 can predict the results of Inter-RAT measurements using a method similar to that used to predict the results of Inter-Frequency measurements. More specific prediction methods will be described later.

(3) Operation of the Wireless Communication System Next, the operation of the wireless communication system 10 will be described. Specifically, the operation of predicting the measurement results of cell quality using an AI/ML model will be described. Note that, although the following operation example will be mainly described with respect to a cell, a similar operation may also be performed with respect to a beam BM (see FIG. 1).

(3.1) Example of AI/ML Model Configuration Figure 4 shows an example of the functional architecture of an AI/ML model. As shown in Figure 4, the architecture may include the following functions:

Data collection: Providing input data for model training and model inference functions.

- Model training: Train, validate, and test ML models. As part of the model testing procedure, model performance metrics may be generated.

The model training function may also be responsible for data preparation (data preprocessing and cleaning, formatting, conversion, etc.).

- Model inference: Provides inference output (such as predictions or decisions). The model inference function may also provide control of model inference to the model management/performance monitoring function.

・Model management/performance monitoring: Manage ML models and monitor model performance.

(3.2) Assumptions and Issues In the existing 3GPP specifications for LTE/NR, when a UE performs intra-frequency measurements, the measurements can be performed without setting measurement gaps. On the other hand, in the case of inter-frequency measurements and inter-RAT measurements, transmission and reception must be temporarily stopped to change the radio frequency (RF) settings, and measurement gaps (e.g., per UE gap, per FR1 gap, per FR2 gap) are required.

Note that FR1 is the frequency range of 410 MHz to 7.125 GHz, and FR2 is the frequency range of 24.25 GHz to 52.6 GHz. FR2-2 (above 52.6 GHz to 71 GHz) and FR3 (above 7.125 GHz to 24.25 GHz) may also be included.

When a measurement gap is set, scheduling is suspended for a period equivalent to the length of the measurement gap (e.g., 6 ms), which halts transmission and reception between the UE and the gNB and negatively impacts the UE's throughput.

If it is possible to predict the results of inter-frequency and inter-RAT measurements from the results of intra-frequency measurements using an AI/ML model, it will be possible to obtain inter-frequency and inter-RAT measurement results without setting up measurement gaps, which has the advantage of allowing cell quality (or beam quality) to be measured without adversely affecting UE throughput.

(3.3) Example of Operation Below, an example of operation will be described in which the result of Inter-Frequency measurement or Inter-RAT measurement is predicted from the result of Intra-Frequency measurement using an AI/ML model.

Figure 5 shows an example sequence for predicting the results of inter-frequency measurements. As shown in Figure 5, the UE may perform cell quality measurement configuration and intra-frequency measurements based on the MeasConfig (measurement configuration) received from the network (gNB). The intra-frequency measurements here may target the serving cell and neighboring cells.

The UE may use an AI/ML model to predict the results of the inter-frequency measurement from the results of the intra-frequency measurement. The UE may send a measurement report including the predicted inter-frequency measurement results to the network.

More specifically, the UE may perform intra-frequency measurements on neighboring cells. Based on the measurement results of the neighboring cells (or beams), the results of the inter-frequency measurements may be predicted using an AI/ML model.

Figure 6 shows an example of the frequencies (bands) used by the own cell (beam) and neighboring cells (beams) and predicted offset values. Here, it is assumed that the measurement difference between the results of the intra-frequency measurement (e.g., RSRP) and the results of the inter-frequency measurement is X dB. The center frequency of the own cell (beam) (which can also be ARFCN: Absolute Radio-Frequency Channel Number) is "Frequency 1," and the center frequency of the neighboring cell is "Frequency 2."

The differences (SS-RSRP, SS-RSRQ, SS-SINR) between the measurement results for frequency 1 (ARFCN-ValueNR1) and frequency 2 (ARFCN-ValueNR2) are defined as offset1 (X1 dB), offset2 (X2 dB), and offset3 (X3 dB), respectively. The AI/ML model may predict these offset values.

In addition, if the frequency of a neighboring cell has an intra-frequency relationship with the frequency of the cell in question, that is, if the same frequency band is used, the frequency characteristics are similar and the same offset may be used.

Similarly, if the frequency of neighboring cell 1 and the frequency of neighboring cell 2 are in an intra-frequency relationship, the frequency characteristics are similar, so the same offset may be used.

As shown in Figure 6, a new unit called delta-freq may be defined. If the difference between the frequency of a neighboring cell and the frequency of the own cell is within delta-freq, offset1 (X1 dB), offset2 (X2 dB), and offset3 (X3 dB) may be added to the intra-frequency measurement results (SS-RSRP, SS-RSRQ, SS-SINR). Note that the offset value may differ for each quality type.

If the frequency of the neighboring cell and the frequency of the own cell are, for example, within the same frequency range (e.g., FR1), this offset may be applied. X may be a positive or negative value.

On the other hand, if the frequency of the neighboring cell and the frequency of the own cell are in different frequency ranges (e.g., own cell = FR1, neighboring cell = FR3) and the difference between the frequency of the neighboring cell and the frequency of the own cell exceeds a predetermined difference (delta-freq2), a new, separate offset may be applied. For example, offset1 (Y1 dB), offset2 (Y2 dB), and offset3 (Y3 dB) may be added to the intra-frequency measurement results (SS-RSRP, SS-RSRQ, SS-SINR).

A specified frequency offset may be added to a specified difference (delta-freq2) between the frequency of a neighboring cell and the frequency of the own cell. The same quality differences offset1 (Y1 dB), offset2 (Y2 dB), and offset3 (Y3 dB) may be applied to neighboring cells within a specified frequency range.

On the other hand, if the frequency of the neighboring cell and the frequency of the own cell are in different frequency ranges (e.g., own cell = FR1, neighboring cell = FR2) and the difference between the frequency of the neighboring cell and the frequency of the own cell exceeds a predetermined difference (delta-freq3), a new, separate offset may be applied. For example, offset1 (Z1 dB), offset2 (Z2 dB), and offset3 (Z3 dB) may be added to the intra-frequency measurement results (SS-RSRP, SS-RSRQ, SS-SINR).

A specified frequency offset may be added to a specified difference (delta-freq3) between the frequency of a neighboring cell and the frequency of the own cell. The same quality differences offset1 (Z1 dB), offset2 (Z2 dB), and offset3 (Z3 dB) may be applied to neighboring cells within a specified frequency range.

Furthermore, the above-mentioned prediction operation may be conditioned on the frequency of the radio signal (beam) transmitted from the same TRP. To enable the UE to identify that radio signals of multiple frequencies are being transmitted from the same TRP, a list of cells (beams) of the same TRP may be broadcast by broadcast information. Even if the frequencies used are close to each other, the quality may vary depending on the radio wave propagation environment of the cells (beams). However, if the frequencies are the same TRP, it can be assumed that the propagation environments are similar, so setting such conditions may be effective.

The above-mentioned prediction operation may be applied to measurements when the UE is in the CONNECTED state, or to measurements when the UE is in the IDLE state. The above-mentioned prediction operation may also be applied to CSI-RS measurements.

Furthermore, in the case of inter-RAT measurements, new offsets may be added to the intra-frequency measurement results (SS-RSRP, SS-RSRQ, SS-SINR). For example, offset1 (M1 dB), offset2 (M2 dB), and offset3 (M3 dB) may be added. The offset value added to the measurement results may be changed depending on the difference between the frequency of the own cell and the frequency of the other RAT.

The frequency of the own cell may refer to the center frequency of the own cell, and the frequency of a neighboring cell may refer to the center frequency of the neighboring cell.

In the case of intra-frequency measurement, a band number is defined, and the frequency characteristics within a band may be similar. For example, the same offset may be applied to 3.5 GHz and 3.7 GHz within the band. Here too, transmission from the same TRP may be a condition. In this case, the same offset may be applied, just like for frequencies within the band. Alternatively, a new offset value may be defined.

The prediction of the offset value using the AI/ML model mentioned above may be performed on the UE side (UE sided model) or on the network (gNB) side (network sided model).

In the case of the network-sided model, the predicted offset may be notified to the UE via an RRC message. The UE may support UE capability signaling, which indicates that it has the ability to predict the results of inter-frequency measurements from the results of the above-mentioned intra-frequency measurements, and may report this capability to the network.

In addition, in the case of a network-sided model, the prediction results of the AI/ML model generated by the O-RAN Non-Real Time RIC may be notified to the O-CU-CP or O-DU via the O1 interface.

Figure 7 shows an example configuration of a RIC based on the O-RAN architecture. As shown in Figure 7, the RIC may include a Near-Real Time RIC and/or a Non-Real Time RIC. The Near-Real Time RIC may be connected to the O-DU and the Non-Real Time RIC via interfaces (A1, E2).

The Near-Real Time RIC may be connected to the O-eNB (radio base station) via an interface (E2). The RIC included in such an O-RAN architecture may constitute an OAM/RIC40.

In such a RIC architecture, feedback on the performance of the AI/ML model may be provided to the Near-Real Time RIC or the Non-Real Time RIC.

In addition, in the case of a network-sided model, the prediction results of the AI/ML model generated by the O-RAN Near-Real Time RIC may be notified to the O-CU-CP or O-DU via the E2 interface.

According to the above-mentioned operational example, the UE (and gNB) can use an AI/ML model to predict the results of inter-frequency measurements in neighboring cells that target frequencies different from those of the intra-frequency measurements, based on the results of the intra-frequency measurements of the neighboring cells. Specifically, the results of the inter-frequency measurements can be predicted based on the difference in the frequencies to be measured and the difference (which may be in dB units) between the results of the intra-frequency measurements of the serving cell and the results of the intra-frequency measurements of the neighboring cells.

As a result, an AI/ML model can be used to predict valid inter-frequency measurement results from the results of intra-frequency measurements. This reduces the number of inter-frequency measurements (and inter-RAT measurements) performed and also eliminates the need for measurement gaps, so there is no impact on throughput between the UE and gNB.

(4) Other Embodiments Although the embodiments have been described above, it will be obvious to those skilled in the art that the present invention is not limited to the description of the embodiments, and that various modifications and improvements are possible.

For example, in the example operation described above, the results of the inter-frequency measurement were predicted from the results of the intra-frequency measurement that measures cell quality, but as described above, similar prediction operations may also be applied to measurements of other reference signals, such as CSI-RS measurements.

In the above description, configure, activate, update, indicate, enable, specify, and select may be read as interchangeable. Similarly, link, associate, correspond, and map may be read as interchangeable, and allocate, assign, monitor, and map may also be read as interchangeable.

Furthermore, specific, dedicated, UE-specific, and UE-individual may be read as interchangeable. Similarly, common, shared, group-common, UE-common, and UE-shared may be read as interchangeable.

In this disclosure, terms such as "precoding," "precoder," "weight (precoding weight)," "Quasi-Co-Location (QCL)," "Transmission Configuration Indication state (TCI state)," "spatial relation," "spatial domain filter," "transmit power," "phase rotation," "antenna port," "antenna port group," "layer," "number of layers," "rank," "resource," "resource set," "resource group," "beam," "beam width," "beam angle," "antenna," "antenna element," and "panel" may be used interchangeably.

Furthermore, the block diagrams (Figures 2 and 3) used to explain the above-mentioned embodiments show functional blocks. These functional blocks (components) are realized by any combination of hardware and/or software. Furthermore, there are no particular limitations on how each functional block is realized. That is, each functional block may be realized using a single device that is physically or logically coupled, or may be realized using two or more physically or logically separated devices that are connected directly or indirectly (for example, using wires, wirelessly, etc.) and these multiple devices. A functional block may also be realized by combining software with the single device or multiple devices.

Functions include, but are not limited to, judgment, determination, assessment, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, regard, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assignment. For example, a functional block (component) that performs transmission functions is called a transmitting unit or transmitter. As mentioned above, there are no particular limitations on how these functions are implemented.

Furthermore, the above-mentioned gNB100 and UE200 (the device) may function as a computer that performs processing of the wireless communication method of the present disclosure. Figure 8 is a diagram showing an example of the hardware configuration of the device. As shown in Figure 8, the device may be configured as a computer device including a processor 1001, memory 1002, storage 1003, a communication device 1004, an input device 1005, an output device 1006, and a bus 1007.

In the following explanation, the term "apparatus" can be interpreted as a circuit, device, unit, etc. The hardware configuration of the apparatus may be configured to include one or more of the devices shown in the diagram, or may be configured to exclude some of the devices.

Each functional block of the device (see Figures 2 and 3) is realized by one of the hardware elements of the computer device, or a combination of those hardware elements.

Furthermore, each function of the device is realized by loading specific software (programs) onto hardware such as the processor 1001 and memory 1002, causing the processor 1001 to perform calculations, control communications via the communications device 1004, and control at least one of reading and writing data from and to the memory 1002 and storage 1003.

The processor 1001, for example, runs an operating system to control the entire computer. The processor 1001 may be configured as a central processing unit (CPU) that includes an interface with peripheral devices, a control unit, an arithmetic unit, registers, etc.

Furthermore, the processor 1001 reads programs (program code), software modules, data, etc. from at least one of the storage 1003 and the communication device 1004 into the memory 1002, and executes various processes in accordance with these. The programs used are those that cause a computer to execute at least some of the operations described in the above-mentioned embodiments. Furthermore, the various processes described above may be executed by a single processor 1001, or may be executed simultaneously or sequentially by two or more processors 1001. The processor 1001 may be implemented by one or more chips. The programs may also be transmitted from a network via telecommunications lines.

Memory 1002 is a computer-readable recording medium and may be composed of, for example, at least one of Read Only Memory (ROM), Erasable Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), Random Access Memory (RAM), etc. Memory 1002 may also be called a register, cache, main memory (primary storage device), etc. Memory 1002 can store a program (program code), software module, etc. that can execute a method according to one embodiment of the present disclosure.

Storage 1003 is a computer-readable recording medium, and may be composed of, for example, at least one of an optical disk such as a Compact Disc ROM (CD-ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray (registered trademark) disc), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy (registered trademark) disk, a magnetic strip, etc. Storage 1003 may also be referred to as an auxiliary storage device. The above-mentioned recording medium may be, for example, a database, a server, or other suitable medium including at least one of memory 1002 and storage 1003.

The communication device 1004 is hardware (transmission/reception device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as a network device, network controller, network card, communication module, etc.

The communication device 1004 may be configured to include high-frequency switches, duplexers, filters, frequency synthesizers, etc. to realize, for example, at least one of Frequency Division Duplex (FDD) and Time Division Duplex (TDD).

The input device 1005 is an input device (e.g., a keyboard, mouse, microphone, switch, button, sensor, etc.) that accepts input from the outside. The output device 1006 is an output device (e.g., a display, speaker, LED lamp, etc.) that outputs to the outside. Note that the input device 1005 and the output device 1006 may be integrated into one device (e.g., a touch panel).

Furthermore, each device, such as the processor 1001 and memory 1002, is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or may be configured using different buses between each device.

Furthermore, the device may be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA), and some or all of the functional blocks may be realized by the hardware. For example, the processor 1001 may be implemented using at least one of these pieces of hardware.

Furthermore, the notification of information is not limited to the aspects/embodiments described in the present disclosure, and may be performed using other methods. For example, the notification of information may be performed by physical layer signaling (e.g., Downlink Control Information (DCI), Uplink Control Information (UCI)), higher layer signaling (e.g., RRC signaling, Medium Access Control (MAC) signaling, broadcast information (Master Information Block (MIB), System Information Block (SIB))), other signals, or a combination of these. Furthermore, RRC signaling may be referred to as an RRC message, and may be, for example, an RRC Connection Setup message, an RRC Connection Reconfiguration message, etc.

Each aspect/embodiment described in this disclosure may be applied to Long Term Evolution (LTE), LTE-Advanced (LTE-A), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 6th generation mobile communication system (6G), xth generation mobile communication system ( xG) (x is, for example, an integer or decimal point), Future Radio Access (FRA), New Radio (NR), W-CDMA (registered trademark), GSM (registered trademark), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, Ultra-WideBand (UWB), Bluetooth (registered trademark), or other appropriate systems, and may be applied to at least one of next-generation systems that are extended based on these. Also, multiple systems may be combined (for example, a combination of at least one of LTE and LTE-A with 5G).

The order of the processing steps, sequences, flowcharts, etc. of each aspect/embodiment described in this disclosure may be changed unless inconsistent. For example, the methods described in this disclosure present elements of various steps using an example order, and are not limited to the particular order presented.

In this disclosure, certain operations that are described as being performed by a base station may in some cases be performed by its upper node. In a network consisting of one or more network nodes that have base stations, it is clear that various operations performed for communication with terminals may be performed by at least one of the base station and other network nodes other than the base station (such as, but not limited to, an MME or S-GW). While the above example shows a case where there is one other network node other than the base station, it may also be a combination of multiple other network nodes (for example, an MME and an S-GW).

Information, signals (information, etc.) can be output from a higher layer (or lower layer) to a lower layer (or higher layer). They may also be input and output via multiple network nodes.

Input and output information may be stored in a specific location (e.g., memory) or may be managed using a management table. Input and output information may be overwritten, updated, or appended. Output information may be deleted. Input information may be sent to another device.

The determination may be made based on a value represented by a single bit (0 or 1), a Boolean value (true or false), or a numerical comparison (for example, comparison with a predetermined value).

Each aspect/embodiment described in this disclosure may be used alone, in combination, or switched between depending on the implementation. Furthermore, notification of specified information (e.g., notification that "X is true") is not limited to being done explicitly, but may also be done implicitly (e.g., not notifying the specified information).

Software shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise.

Software, instructions, information, etc. may also be transmitted and received via a transmission medium. For example, if software is transmitted from a website, server, or other remote source using wired technologies (such as coaxial cable, fiber optic cable, twisted pair, or Digital Subscriber Line (DSL)) and/or wireless technologies (such as infrared or microwave), then these wired and/or wireless technologies are included within the definition of a transmission medium.

The information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

Note that terms explained in this disclosure and terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings. For example, at least one of a channel and a symbol may be a signal (signaling). Furthermore, a signal may be a message. Furthermore, a component carrier (CC) may be called a carrier frequency, a cell, a frequency carrier, etc.

As used in this disclosure, the terms "system" and "network" are used interchangeably.

Furthermore, the information, parameters, etc. described in this disclosure may be expressed using absolute values, relative values from a predetermined value, or other corresponding information. For example, radio resources may be indicated by an index.

The names used for the parameters described above are not intended to be limiting in any way. Furthermore, the mathematical formulas using these parameters may differ from those explicitly disclosed in this disclosure. The various channels (e.g., PUCCH, PDCCH, etc.) and information elements may be identified by any suitable names, and therefore the various names assigned to these various channels and information elements are not intended to be limiting in any way.

In this disclosure, terms such as "base station (BS)," "radio base station," "fixed station," "NodeB," "eNodeB (eNB)," "gNodeB (gNB)," "access point," "transmission point," "reception point," "transmission/reception point," "cell," "sector," "cell group," "carrier," and "component carrier" may be used interchangeably. Base stations may also be referred to by terms such as macrocell, small cell, femtocell, and picocell.

A base station can accommodate one or more (e.g., three) cells (also called sectors). When a base station accommodates multiple cells, the base station's overall coverage area can be divided into multiple smaller areas, and each smaller area can be provided with communication services by a base station subsystem (e.g., a small indoor base station (Remote Radio Head: RRH)).

The terms "cell" or "sector" refer to part or all of the coverage area of a base station and/or a base station subsystem that provides communication services within that coverage area.

In this disclosure, a base station transmitting information to a terminal may be interpreted as the base station instructing the terminal to control or operate based on the information.

In this disclosure, terms such as "Mobile Station (MS)," "user terminal," "User Equipment (UE)," and "terminal" may be used interchangeably.

A mobile station may also be referred to by those skilled in the art as a subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, or some other suitable terminology.

At least one of the base station and the mobile station may be referred to as a transmitting device, a receiving device, a communication device, etc. At least one of the base station and the mobile station may be a device mounted on a mobile object, the mobile object itself, etc. The mobile object refers to an object that can move at any speed. Naturally, this also includes cases where the mobile object is stationary. Examples of the mobile object include, but are not limited to, vehicles, transport vehicles, automobiles, motorcycles, bicycles, connected cars, excavators, bulldozers, wheel loaders, dump trucks, forklifts, trains, buses, handcars, rickshaws, ships and other watercraft, airplanes, rockets, satellites, drones (registered trademark), multicopters, quadcopters, balloons, and objects mounted thereon. The mobile object may also be a mobile object that moves autonomously based on an operation command. It may be a vehicle (e.g., a car, an airplane, etc.), an unmanned mobile object (e.g., a drone, an autonomous vehicle, etc.), or a robot (manned or unmanned). Note that at least one of the base station and the mobile station may be a device that does not necessarily move during communication operations. For example, at least one of the base station and the mobile station may be an IoT (Internet of Things) device such as a sensor.

Furthermore, the base station in the present disclosure may be interpreted as a mobile station (user terminal, the same applies hereinafter). For example, the aspects/embodiments of the present disclosure may be applied to a configuration in which communication between a base station and a mobile station is replaced with communication between multiple mobile stations (which may be called, for example, Device-to-Device (D2D) or Vehicle-to-Everything (V2X)). In this case, the mobile station may be configured to have the functions of a base station. Furthermore, terms such as "uplink" and "downlink" may be interpreted as terms corresponding to communication between terminals (for example, "side"). For example, terms such as uplink channel and downlink channel may be interpreted as side channel (or side link).

Similarly, the mobile station in this disclosure may be interpreted as a base station. In this case, the base station may be configured to have the functions of a mobile station.

A radio frame may be composed of one or more frames in the time domain. Each of the one or more frames in the time domain may be called a subframe. A subframe may further be composed of one or more slots in the time domain. A subframe may have a fixed time length (e.g., 1 ms) that is independent of numerology.

Numerology may be a communication parameter that applies to at least one of the transmission and reception of a signal or channel. Numerology may indicate, for example, at least one of the following: subcarrier spacing (SCS), bandwidth, symbol length, cyclic prefix length, transmission time interval (TTI), number of symbols per TTI, radio frame structure, specific filtering operations performed by the transmitter and receiver in the frequency domain, and specific windowing operations performed by the transmitter and receiver in the time domain.

A slot may consist of one or more symbols in the time domain (such as Orthogonal Frequency Division Multiplexing (OFDM) symbols or Single Carrier Frequency Division Multiple Access (SC-FDMA) symbols). A slot may also be a numerology-based time unit.

A slot may include multiple minislots. Each minislot may consist of one or more symbols in the time domain. A minislot may also be called a subslot. A minislot may consist of fewer symbols than a slot. A PDSCH (or PUSCH) transmitted in a time unit larger than a minislot may be called PDSCH (or PUSCH) mapping type A. A PDSCH (or PUSCH) transmitted using a minislot may be called PDSCH (or PUSCH) mapping type B.

Radio frame, subframe, slot, minislot, and symbol all represent time units for transmitting signals. Other names corresponding to radio frame, subframe, slot, minislot, and symbol may also be used.

For example, one subframe may be called a transmission time interval (TTI), multiple consecutive subframes may be called a TTI, or one slot or one minislot may be called a TTI. In other words, at least one of the subframe and TTI may be a subframe (1 ms) in existing LTE, a period shorter than 1 ms (e.g., 1-13 symbols), or a period longer than 1 ms. Note that the unit representing the TTI may be called a slot, minislot, etc. instead of a subframe.

Here, TTI refers to, for example, the smallest time unit for scheduling in wireless communication. For example, in an LTE system, a base station schedules each user terminal by allocating radio resources (such as the frequency bandwidth and transmission power available for use by each user terminal) in TTI units. However, the definition of TTI is not limited to this.

The TTI may be a transmission time unit for a channel-encoded data packet (transport block), code block, code word, etc., or it may be a processing unit for scheduling, link adaptation, etc. When a TTI is given, the time interval (e.g., number of symbols) to which the transport block, code block, code word, etc. is actually mapped may be shorter than the TTI.

Note that when one slot or one minislot is referred to as a TTI, one or more TTIs (i.e., one or more slots or one or more minislots) may be the smallest time unit for scheduling. Furthermore, the number of slots (minislots) that make up the smallest time unit for scheduling may be controlled.

A TTI with a time length of 1 ms may be referred to as a regular TTI (TTI in LTE Rel. 8-12), normal TTI, long TTI, regular subframe, normal subframe, long subframe, slot, etc. A TTI shorter than a regular TTI may be referred to as a shortened TTI, short TTI, partial or fractional TTI, shortened subframe, short subframe, minislot, subslot, slot, etc.

Note that a long TTI (e.g., a normal TTI, subframe, etc.) may be interpreted as a TTI with a time length exceeding 1 ms, and a short TTI (e.g., a shortened TTI, etc.) may be interpreted as a TTI with a TTI length shorter than the TTI length of a long TTI but equal to or greater than 1 ms.

A resource block (RB) is a resource allocation unit in the time domain and frequency domain, and may include one or more consecutive subcarriers in the frequency domain. The number of subcarriers included in an RB may be the same regardless of numerology, and may be, for example, 12. The number of subcarriers included in an RB may also be determined based on numerology.

Furthermore, the time domain of an RB may include one or more symbols and may be one slot, one minislot, one subframe, or one TTI in length. One TTI, one subframe, etc. may each be composed of one or more resource blocks.

Note that one or more RBs may also be referred to as a physical resource block (PRB), sub-carrier group (SCG), resource element group (REG), PRB pair, RB pair, etc.

Furthermore, a resource block may be composed of one or more resource elements (RE). For example, one RE may be a radio resource region of one subcarrier and one symbol.

A Bandwidth Part (BWP) (which may also be referred to as a partial bandwidth) may represent a subset of contiguous common resource blocks (RBs) for a given numerology on a given carrier, where the common RBs may be identified by the RB's index relative to the carrier's common reference point. PRBs may be defined in a given BWP and numbered within that BWP.

BWPs may include a BWP for UL (UL BWP) and a BWP for DL (DL BWP). One or more BWPs may be configured for a UE within one carrier.

At least one of the configured BWPs may be active, and the UE may not expect to transmit or receive a specific signal/channel outside of the active BWP. Note that "cell," "carrier," etc. in this disclosure may be read as "BWP."

The structures of the radio frames, subframes, slots, minislots, and symbols described above are merely examples. For example, the number of subframes included in a radio frame, the number of slots per subframe or radio frame, the number of minislots included in a slot, the number of symbols and RBs included in a slot or minislot, the number of subcarriers included in an RB, as well as the number of symbols within a TTI, the symbol length, and the cyclic prefix (CP) length can be changed in various ways.

The terms "connected," "coupled," or any variation thereof, refer to any direct or indirect connection or coupling between two or more elements, and may include the presence of one or more intermediate elements between two elements that are "connected" or "coupled" to each other. The coupling or connection between elements may be physical, logical, or a combination thereof. For example, "connected" may be read as "access." As used in this disclosure, two elements may be considered to be "connected" or "coupled" to each other using at least one of one or more wires, cables, and printed electrical connections, as well as electromagnetic energy having wavelengths in the radio frequency range, microwave range, and optical (both visible and invisible) range, as some non-limiting and non-exhaustive examples.

The reference signal may also be abbreviated as Reference Signal (RS) or may be called a pilot depending on the applicable standard.

As used in this disclosure, the phrase "based on" does not mean "based only on," unless expressly stated otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."

The "means" in the configuration of each of the above devices may be replaced with "part," "circuit," "device," etc.

As used in this disclosure, any reference to an element using a designation such as "first," "second," etc. does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Thus, a reference to a first and a second element does not imply that only two elements may be employed therein, or that the first element must in some way precede the second element.

When the terms "include," "including," and variations thereof are used in this disclosure, these terms are intended to be inclusive, similar to the term "comprising." Furthermore, when the term "or" is used in this disclosure, it is not intended to be an exclusive or.

In this disclosure, where articles are added by translation, such as a, an, and the in English, this disclosure may include the noun following these articles being plural.

As used in this disclosure, the terms "determining" and "determining" may encompass a wide variety of actions. "Determining" and "determining" may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, inquiring (e.g., searching a table, database, or other data structure), and ascertaining something as a "judging" or "determining." "Determining" and "determining" may also include receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in memory), and ascertaining something as a "judging" or "determining." Furthermore, "judgment" and "decision" can include regarding resolving, selecting, choosing, establishing, comparing, etc. as having been "judged" or "decided." In other words, "judgment" and "decision" can include regarding some action as having been "judged" or "decided." Furthermore, "judgment (decision)" can be interpreted as "assuming," "expecting," "considering," etc.

In this disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "combined" may also be interpreted in the same way as "different."

Figure 9 shows an example configuration of vehicle 2001. As shown in Figure 9, vehicle 2001 is equipped with a drive unit 2002, a steering unit 2003, an accelerator pedal 2004, a brake pedal 2005, a shift lever 2006, left and right front wheels 2007, left and right rear wheels 2008, an axle 2009, an electronic control unit 2010, various sensors 2021-2029, an information service unit 2012, and a communication module 2013.

The drive unit 2002 is composed of, for example, an engine, a motor, or a hybrid of an engine and a motor.
The steering unit 2003 includes at least a steering wheel (also called a handle) and is configured to steer at least one of the front wheels and the rear wheels based on the operation of the steering wheel operated by the user.
The electronic control unit 2010 is composed of a microprocessor 2031, a memory (ROM, RAM) 2032, and a communication port (IO port) 2033. Signals are input to the electronic control unit 2010 from various sensors 2021 to 2027 provided in the vehicle. The electronic control unit 2010 may also be called an ECU (Electronic Control Unit).

Signals from the various sensors 2021-2028 include a current signal from a current sensor 2021 that senses the motor current, a front and rear wheel rotation speed signal obtained by a rotation speed sensor 2022, a front and rear wheel air pressure signal obtained by an air pressure sensor 2023, a vehicle speed signal obtained by a vehicle speed sensor 2024, an acceleration signal obtained by an acceleration sensor 2025, an accelerator pedal depression amount signal obtained by an accelerator pedal sensor 2029, a brake pedal depression amount signal obtained by a brake pedal sensor 2026, a shift lever operation signal obtained by a shift lever sensor 2027, and a detection signal for detecting obstacles, vehicles, pedestrians, etc. obtained by an object detection sensor 2028.

The information service unit 2012 is composed of various devices, such as a car navigation system, audio system, speakers, television, and radio, that provide (output) various types of information, including driving information, traffic information, and entertainment information, as well as one or more ECUs that control these devices. The information service unit 2012 uses information obtained from external devices via the communication module 2013, etc., to provide various types of multimedia information and multimedia services to the occupants of the vehicle 1.

The information service unit 2012 may include input devices (e.g., keyboards, mice, microphones, switches, buttons, sensors, touch panels, etc.) that accept input from the outside, and may also include output devices (e.g., displays, speakers, LED lamps, touch panels, etc.) that output to the outside.

The driving assistance system unit 2030 is composed of various devices that provide functions to prevent accidents and reduce the driver's driving burden, such as millimeter-wave radar, LiDAR (Light Detection and Ranging), cameras, positioning locators (e.g., GNSS, etc.), map information (e.g., high-definition (HD) maps, autonomous vehicle (AV) maps, etc.), gyro systems (e.g., IMU (Inertial Measurement Unit), INS (Inertial Navigation System), etc.), AI (Artificial Intelligence) chips, and AI processors, as well as one or more ECUs that control these devices. The driving assistance system unit 2030 also transmits and receives various information via the communication module 2013 to realize driving assistance functions or autonomous driving functions.

The communication module 2013 can communicate with the microprocessor 2031 and components of the vehicle 1 via the communication port. For example, the communication module 2013 transmits and receives data via the communication port 2033 to and from the drive unit 2002, steering unit 2003, accelerator pedal 2004, brake pedal 2005, shift lever 2006, left and right front wheels 2007, left and right rear wheels 2008, axles 2009, microprocessor 2031 and memory (ROM, RAM) 2032 in the electronic control unit 2010, and sensors 2021-2028, all of which are provided on the vehicle 2001.

The communication module 2013 is a communication device that can be controlled by the microprocessor 2031 of the electronic control unit 2010 and can communicate with external devices. For example, it transmits and receives various information to and from external devices via wireless communication. The communication module 2013 may be located either inside or outside the electronic control unit 2010. The external device may be, for example, a base station, a mobile station, etc.

The communications module 2013 may transmit, via wireless communication, to an external device at least one of the signals from the various sensors 2021-2028 described above that are input to the electronic control unit 2010, information obtained based on the signals, and information based on input from the outside (user) obtained via the information service unit 2012. The electronic control unit 2010, the various sensors 2021-2028, the information service unit 2012, etc. may also be referred to as input units that accept input. For example, the PUSCH transmitted by the communications module 2013 may include information based on the above input.

The communication module 2013 receives various information (traffic information, traffic signal information, vehicle-to-vehicle distance information, etc.) transmitted from external devices and displays it on the information service unit 2012 provided in the vehicle. The information service unit 2012 may also be called an output unit that outputs information (for example, outputs information to a device such as a display or speaker based on the PDSCH (or data/information decoded from the PDSCH) received by the communication module 2013). The communication module 2013 also stores the various information received from external devices in memory 2032 that can be used by the microprocessor 2031. Based on the information stored in memory 2032, the microprocessor 2031 may control the drive unit 2002, steering unit 2003, accelerator pedal 2004, brake pedal 2005, shift lever 2006, left and right front wheels 2007, left and right rear wheels 2008, axles 2009, sensors 2021-2028, and the like provided in the vehicle 2001.

(Additional Note)
The above disclosure may be expressed as follows: A first feature is a terminal including: a controller that performs intra-frequency measurement in a serving cell; and a transmitter that transmits a result of the intra-frequency measurement to a network, wherein the controller performs the intra-frequency measurement in a neighboring cell of the serving cell, and predicts a result of inter-frequency measurement in the neighboring cell, the inter-frequency measurement targeting a frequency different from that of the intra-frequency measurement, from the result of the intra-frequency measurement in the neighboring cell using a learning model.

The second feature is that in the first feature, the control unit applies an offset value corresponding to the difference between the target frequency of the intra-frequency measurement and the target frequency of the inter-frequency measurement, and predicts the result of the inter-frequency measurement.

A third feature is that in the first or second feature, the control unit performs the intra-frequency measurement on the frequencies of radio signals transmitted from the same transmitting and receiving point.

A fourth feature is that in any one of the first to third features, the control unit uses the learning model to predict the results of inter-radio access technology measurements targeting frequencies different from those of the intra-frequency measurements, based on the results of the intra-frequency measurements of the neighboring cells.

10 Wireless Communication Systems 20 NG-RAN
40 OAM/RIC
50 NF
100 gNB
110 wireless communication unit 120 handover processing unit 130 AI/ML model unit 140 control unit 200 UE
210 Wireless communication unit 215 AI/ML model unit 220 Measurement processing unit 230 Handover execution unit 240 Control unit 1001 Processor 1002 Memory 1003 Storage 1004 Communication device 1005 Input device 1006 Output device 1007 Bus 2001 Vehicle 2002 Drive unit 2003 Steering unit 2004 Accelerator pedal 2005 Brake pedal 2006 Shift lever 2007 Left and right front wheels 2008 Left and right rear wheels 2009 Axle 2010 Electronic control unit 2012 Information service unit 2013 Communication module 2021 Current sensor 2022 RPM sensor 2023 Air pressure sensor 2024 Vehicle speed sensor 2025 Acceleration sensor 2026 Brake pedal sensor 2027 Shift lever sensor 2028 Object detection sensor 2029 Accelerator pedal sensor 2030 Driving assistance system section 2031 Microprocessor 2032 Memory (ROM, RAM)
2033 communication port

Claims (6)

a control unit for performing intra-frequency measurements in a serving cell;
a transmitter that transmits the results of the intra-frequency measurement to a network;
The control unit
performing the intra-frequency measurements on neighboring cells of the serving cell;
A terminal that predicts, from the result of the intra-frequency measurement of the neighboring cell using a learning model, the result of an inter-frequency measurement in the neighboring cell, the inter-frequency measurement being targeted at a frequency different from that of the intra-frequency measurement. The terminal according to claim 1, wherein the control unit predicts the results of the inter-frequency measurement by applying an offset value corresponding to the difference between the target frequency of the intra-frequency measurement and the target frequency of the inter-frequency measurement. The terminal described in claim 1, wherein the control unit performs the intra-frequency measurement on the frequencies of radio signals transmitted from the same transmitting and receiving point. The terminal according to claim 1, wherein the control unit uses the learning model to predict the results of inter-radio access technology measurements targeting frequencies different from those of the intra-frequency measurements, based on the results of the intra-frequency measurements of the neighboring cells. a receiving unit that receives intra-frequency measurement results in neighboring cells of a serving cell from a terminal;
a control unit that predicts, based on a result of intra-frequency measurement of the neighboring cell, a result of inter-frequency measurement in the neighboring cell, the result of inter-frequency measurement being targeted at a frequency different from that of the intra-frequency measurement, using a learning model. performing intra-frequency measurements on neighboring cells of a serving cell;
A wireless communication method in a terminal, comprising: using a learning model to predict results of inter-frequency measurements in the neighboring cell, the inter-frequency measurements being performed on a frequency different from that of the intra-frequency measurements, from results of intra-frequency measurements in the neighboring cell.