Method and device for reducing cell measurement load of user equipment in mobile communication system

Abstract

The present disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. Disclosed are a method and device for reducing a cell measurement load of a user equipment by using artificial intelligence and machine learning in a mobile communication system.

Description

Method and apparatus for reducing cell measurement load of a terminal in a mobile communication system

[0001] The present disclosure relates to a method and apparatus for reducing the cell measurement load of a terminal using artificial intelligence and machine learning in a mobile communication system.

[0002] 5G mobile communication technology defines a wide frequency band to enable fast transmission speeds and new services, and can be implemented not only in frequency bands below 6 GHz ('Sub 6 GHz'), such as 3.5 gigahertz (3.5 GHz), but also in ultra-high frequency bands called millimeter waves (mmWave), such as 28 GHz and 39 GHz ('Above 6 GHz'). In addition, for 6G mobile communication technology, which is referred to as a system beyond 5G, implementation in the terahertz band (e.g., the 3 terahertz (3 THz) band at 95 GHz) is being considered to achieve transmission speeds 50 times faster and ultra-low latency reduced to one-tenth compared to 5G mobile communication technology.

[0003] In the early stages of 5G mobile communication technology, aiming to satisfy service support and performance requirements for enhanced Mobile BroadBand (eMBB), Ultra-Reliable Low-Latency Communications (URLLC), and massive Machine-Type Communications (mMTC), technologies such as beamforming and Massive MIMO to mitigate path loss and increase transmission distance in ultra-high frequency bands, support for various numerologies (such as the operation of multiple subcarrier spacings) and dynamic operation of slot formats for the efficient utilization of ultra-high frequency resources, initial access techniques to support multi-beam transmission and broadband, definition and operation of Band-Width Parts (BWP), Low Density Parity Check (LDPC) codes for high-volume data transmission, new channel coding methods such as Polar Codes for the reliable transmission of control information, and L2 pre-processing (L2 Standardization has been carried out for pre-processing, network slicing which provides a dedicated network specialized for specific services, and other methods.

[0004] Currently, discussions are underway to improve and enhance the performance of the initial 5G mobile communication technology, taking into account the services that the 5G mobile communication technology was intended to support. Additionally, standardization of the physical layer is in progress for technologies such as V2X (Vehicle-to-Everything), which helps autonomous vehicles make driving decisions and enhance user convenience based on their own location and status information transmitted by the vehicle; NR-U (New Radio Unlicensed), which aims for system operation in unlicensed bands to comply with various regulatory requirements; NR terminal low power consumption technology (UE Power Saving); Non-Terrestrial Network (NTN), which is direct terminal-satellite communication for securing coverage in areas where communication with the terrestrial network is impossible; and positioning.

[0005] In addition, standardization is underway in the field of wireless interface architecture / protocols for technologies such as the Industrial Internet of Things (IIoT) to support new services through linkage and convergence with other industries, Integrated Access and Backhaul (IAB) which provides nodes to expand network service areas by integrating wireless backhaul links and access links, Mobility Enhancement including Conditional Handover and Dual Active Protocol Stack (DAPS) Handover, and 2-step Random Access (2-step RACH for NR) which simplifies random access procedures. Standardization is also underway in the field of system architecture / services for 5G baseline architectures (e.g., Service based Architecture, Service based Interface) to incorporate Network Functions Virtualization (NFV) and Software-Defined Networking (SDN) technologies, and Mobile Edge Computing (MEC), which provides services based on the location of the terminal.

[0006] When such 5G mobile communication systems are commercialized, connected devices, which are increasing explosively, will be connected to communication networks. Accordingly, it is expected that there will be a need to enhance the functionality and performance of 5G mobile communication systems and to integrate the operation of connected devices. To this end, new research is planned to be conducted on 5G performance improvement and complexity reduction, support for AI services, support for metaverse services, and drone communication using eXtended Reality (XR), Artificial Intelligence (AI), and Machine Learning (ML) to efficiently support Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR).

[0007] Furthermore, the advancement of these 5G mobile communication systems encompasses multi-antenna transmission technologies such as new waveforms, Full Dimensional MIMO (FD-MIMO), array antennas, and large-scale antennas to guarantee coverage in the terahertz band of 6G mobile communication technology; metamaterial-based lenses and antennas; high-dimensional spatial multiplexing technology using Orbital Angular Momentum (OAM); and Reconfigurable Intelligent Surface (RIS) technology to improve terahertz band signal coverage; as well as full-duplex technology for enhancing frequency efficiency and system networks in 6G mobile communication technology; AI-based communication technologies that realize system optimization by utilizing satellites and Artificial Intelligence (AI) from the design stage and internalizing end-to-end AI support functions; and the realization of services of complexity exceeding the limits of terminal computing capabilities by utilizing ultra-high-performance communication and computing resources. It could serve as a foundation for the development of next-generation distributed computing technologies.

[0008] In next-generation wireless communication systems, the network can perform operations such as instructing terminals to measure specific cells to effectively provide services, acquiring measurement results therefrom, and subsequently setting and adaptively adjusting parameters for scheduling or transmission / reception operations. Depending on the base station's configuration, the terminal can measure all beams operated by a specific cell and derive cell measurement results to report to the base station based on the measured beam results. However, the load on the terminal may increase when performing measurements on all beams and deriving results in this manner.

[0009] Accordingly, the present disclosure provides an apparatus and method capable of reducing the load generated during the process in which a terminal derives cell measurement results.

[0010] In a wireless communication system according to an example of the present disclosure for solving the above-mentioned problems, a method of a terminal comprises: receiving a first radio resource control (RRC) message from a base station, the message including first information indicating a load reduction operation for a radio resource management (RRM) measurement and second information related to an RRM measurement beam setting, wherein the second information includes an associated ID (identity) for identifying a beam setting of similar characteristics; determining the applicability of an artificial intelligence (AI) model for the RRM measurement based on the associated ID; and transmitting a second RRC message to the base station based on the first RRC message, the second RRC message including information indicating the determined applicability, wherein the associated ID may be indicated for a measurement object (MO) set to perform the RRM measurement.

[0011] Additionally, in a wireless communication system according to one example of the present disclosure, a method of a base station comprises: transmitting a first radio resource control (RRC) message to a terminal, the message including first information indicating a load reduction operation for a radio resource management (RRM) measurement and second information related to an RRM measurement beam setting, wherein the second information includes an associated ID (identity) for identifying a beam setting of similar characteristics; and receiving a second RRC message from the terminal, the second information including information indicating the applicability of an artificial intelligence (AI) model for the RRM measurement based on the first RRC message, wherein the associated ID may be indicated for a measurement object (MO) set to perform the RRM measurement.

[0012] Additionally, in a wireless communication system according to one example of the present disclosure, a terminal comprises: a transceiver; and a control unit that controls the transceiver to receive a first radio resource control (RRC) message from a base station, the first information indicating a load reduction operation for a radio resource management (RRM) measurement and second information related to an RRM measurement beam setting, wherein the second information includes an associated ID (identity) for identifying a beam setting of similar characteristics, the control unit that checks the applicability of an artificial intelligence (AI) model for the RRM measurement based on the associated ID, and the control unit that controls the transceiver to transmit a second RRC message to the base station, the second information including information indicating the checked applicability based on the first RRC message, wherein the associated ID may be indicated for a measurement object (MO) set to perform the RRM measurement.Additionally, in a wireless communication system according to one example of the present disclosure, a base station comprises: a transceiver; and a control unit that controls the transceiver to transmit a first radio resource control (RRC) message to a terminal, the first information indicating a load reduction operation for a radio resource management (RRM) measurement and second information related to an RRM measurement beam setting, wherein the second information includes an associated ID (identity) for identifying a beam setting of similar characteristics, and controls the transceiver to receive a second RRC message from the terminal, the second information including information indicating the applicability of an artificial intelligence (AI) model for the RRM measurement based on the first RRC message, wherein the associated ID may be indicated for a measurement object (MO) set to perform the RRM measurement.

[0013] According to one example of the present disclosure, by utilizing an AI model, the terminal can obtain highly accurate measurement results for a cell even while performing measurements on only some beams, thus having the effect of reducing the load associated with signaling and analysis operations involved in deriving cell measurement results.

[0014] FIG. 1 is a drawing illustrating the structure of an NR system according to one embodiment of the present disclosure.

[0015] FIG. 2 is a diagram showing a wireless protocol structure in an LTE and NR system according to one embodiment of the present disclosure.

[0016] FIG. 3 is a diagram illustrating the process of deriving cell measurement results in a mobile communication system according to one embodiment of the present disclosure.

[0017] FIG. 4 is a diagram illustrating a method of utilizing an AI / ML model to predict cell measurement results in order to reduce the cell measurement load in a mobile communication system according to one embodiment of the present disclosure.

[0018] FIG. 5 is a flowchart of a process in which a base station instructs a terminal to perform a cell measurement load reduction operation according to one embodiment of the present disclosure, and the terminal performs a cell measurement load reduction operation according to the base station's instruction.

[0019] FIG. 6 is a drawing illustrating a terminal device according to one embodiment of the present disclosure.

[0020] FIG. 7 is a drawing illustrating a base station device according to one embodiment of the present disclosure.

[0021] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. Furthermore, in describing the present disclosure, if it is determined that a detailed description of related known functions or configurations may unnecessarily obscure the essence of the present invention, such detailed description will be omitted. Additionally, the terms described below are defined considering their functions in the present disclosure, and these may vary depending on the intentions or conventions of the user or operator. Therefore, their definitions should be based on the content throughout this specification.

[0022] The advantages and features of the present disclosure and the methods for achieving them will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below but may be implemented in various different forms. The embodiments provided are merely to ensure that the disclosure is complete and to fully inform those skilled in the art of the scope of the invention, and the present disclosure is defined only by the scope of the claims. Throughout the specification, the same reference numerals refer to the same components.

[0023] At this point, it will be understood that each block of the process flow diagrams and combinations of the flow diagrams can be executed by computer program instructions. Since these computer program instructions can be loaded into the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing equipment, the instructions executed through the processor of the computer or other programmable data processing equipment create means to perform the functions described in the flow diagram block(s). Since these computer program instructions can also be stored in computer-available or computer-readable memory that can be directed toward the computer or other programmable data processing equipment to implement the function in a specific way, the instructions stored in computer-available or computer-readable memory can also produce a manufactured item containing instruction means to perform the function described in the flow diagram block(s). Since computer program instructions can be loaded onto a computer or other programmable data processing equipment, instructions that perform a series of operation steps on the computer or other programmable data processing equipment to create a process executed by the computer can also provide steps for executing the functions described in the flowchart block(s).

[0024] Additionally, each block may represent a module, segment, or part of code containing one or more executable instructions for executing a specific logical function(s). It should also be noted that in some alternative execution examples, the functions mentioned in the blocks may occur out of order. For example, two blocks described in succession may actually be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order according to their corresponding functions.

[0025] In this embodiment, the term "part" refers to a software or hardware component such as an FPGA (Field Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit), and the "part" performs certain roles. However, the meaning of "part" is not limited to software or hardware. The "part" may be configured to reside in an addressable storage medium or configured to run one or more processors. Thus, as an example, the "part" includes components such as software components, object-oriented software components, class components, and task components, as well as processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functions provided within the components and "parts" may be combined into a smaller number of components and "parts" or further separated into additional components and "parts." In addition, the components and 'parts' may be implemented to utilize one or more CPUs within the device or secure multimedia card. Also, in the embodiments, 'parts' may include one or more processors.

[0026] In describing the present disclosure below, specific descriptions of related known functions or configurations will be omitted if it is determined that such detailed descriptions would unnecessarily obscure the essence of the present disclosure. Embodiments of the present disclosure will be described below with reference to the attached drawings.

[0027] Terms used in the following description to identify connection nodes, terms referring to network entities, terms referring to messages, terms referring to interfaces between network entities, terms referring to various identification information, etc., are examples provided for the convenience of explanation. Accordingly, the present disclosure is not limited to the terms described below, and other terms referring to objects having equivalent technical meanings may be used.

[0028] In the following description, the terms "physical channel" and "signal" may be used interchangeably with "data" or "control signal." For example, PDSCH (physical downlink shared channel) is a term referring to a physical channel through which data is transmitted, but PDSCH may also be used to refer to data. That is, in this disclosure, the expression "transmits a physical channel" may be interpreted as equivalent to the expression "transmits data or a signal through a physical channel."

[0029] In the present disclosure, upper signaling refers to a signal transmission method transmitted from a base station to a terminal using a physical layer downlink data channel, or from a terminal to a base station using a physical layer uplink data channel. Upper signaling may be understood as radio resource control (RRC) signaling or a media access control (MAC) control element (CE).

[0030] For convenience of explanation, the present disclosure uses terms and names defined in the 3GPP NR (3rd Generation Partnership Project NR (New Radio)) or 3GPP LTE (3rd Generation Partnership Project Long Term Evolution) standards. However, the present disclosure is not limited by the above terms and names and may be applied equally to systems conforming to other standards. In the present disclosure, gNB may be used interchangeably with eNB for convenience of explanation. That is, a base station described as an eNB may represent a gNB. Additionally, the term terminal may refer to mobile phones, MTC devices, NB-IoT devices, sensors, as well as other wireless communication devices.

[0031] Hereinafter, the base station is an entity that performs resource allocation for terminals and may be at least one of a gNodeB (gNB), eNode B (eNB), NodeB, BS (Base Station), wireless access unit, base station controller, or a node on a network. The terminal may include a UE (User Equipment), MS (Mobile Station), cellular phone, smartphone, computer, or a multimedia system capable of performing communication functions. Of course, it is not limited to the above examples.

[0032] FIG. 1 is a drawing illustrating the structure of an NR system according to one embodiment of the present disclosure.

[0033] Referring to FIG. 1, a wireless communication system may be composed of multiple base stations (e.g., gNB (105), ng-eNB (110), ng-eNB (115), gNB (120)), an Access and Mobility Management Function (AMF) (125), and a User Plane Function (UPF) (130). A user terminal (User Equipment, hereinafter UE or terminal) (135) can connect to an external network through the base stations (e.g., gNB (105), ng-eNB (110), ng-eNB (115), gNB (120)) and the UPF (130).

[0034] In FIG. 1, base stations (e.g., gNB (105), ng-eNB (110), ng-eNB (115), gNB (120)) can provide wireless access to terminals connected to the network as access nodes of a cellular network. That is, the base stations (e.g., gNB (105), ng-eNB (110), ng-eNB (115), gNB (120)) can support the connection between the terminals and the core network (CN, Core network; specifically, the CN of NR is referred to as 5GC) by collecting state information such as the buffer state, available transmission power state, and channel state of the terminals to service the traffic of the users and performing scheduling. Meanwhile, in communication, the User Plane (UP), which is related to the transmission of actual user data, and the Control Plane (CP), which is related to connection management, can be configured separately. In this drawing, gNB (105) and gNB (120) use the UP and CP technologies defined in NR technology, and ng-eNB (110) and ng-eNB (115), although connected to 5GC, can use the UP and CP technologies defined in LTE technology.

[0035] The above AMF (125) is a device responsible for various control functions as well as mobility management functions for the terminal and is connected to multiple base stations, and the UPF (130) may refer to a type of gateway device that provides data transmission. Although not shown in FIG. 1, the NR wireless communication system may further include a Session Management Function (SMF). The SMF can manage packet data network connections, such as protocol data unit (PDU) sessions provided to the terminal.

[0036] FIG. 2 is a diagram showing a wireless protocol structure in an LTE and NR system according to one embodiment of the present disclosure.

[0037] Referring to FIG. 2, the wireless protocols of the LTE and NR systems can be composed of PDCP (Packet Data Convergence Protocol) (205)(240), RLC (Radio Link Control) (210)(235), and MAC (Medium Access Control) (215)(230) at the terminal and eNB / gNB, respectively.

[0038] PDCP (205)(240) is responsible for operations such as IP (internet protocol) header compression / decompression, and Wireless Link Control (RLC) (210)(235) reconstructs PDCP PDU (Protocol Data Unit) into an appropriate size. MAC (215)(230) is connected to multiple RLC layer devices configured in a terminal and performs the operation of multiplexing RLC PDUs into MAC PDUs and demultiplexing RLC PDUs from MAC PDUs.

[0039] The physical (PHY) layer (220) (225) performs the operation of channel coding and modulating upper layer data, creating OFDM (orthogonal frequency division multiplexing) symbols to transmit to the wireless channel, or demodulating OFDM symbols received through the wireless channel and channel decoding to transmit to the upper layer. In addition, the physical layer also uses HARQ (Hybrid ARQ (automatic repeat request)) for additional error correction, and the receiving end transmits 1 bit indicating whether the packet transmitted by the transmitting end has been received. This is called HARQ ACK (acknowledgement) / NACK (negative ACM) information. In the case of LTE, downlink HARQ ACK / NACK information for uplink data transmission is transmitted through the physical channel of the PHICH (Physical Hybrid-ARQ Indicator Channel), while in the case of NR, it is possible to determine whether retransmission is required or if a new transmission can be performed through the scheduling information of the terminal in the PDCCH (Physical Dedicated Control Channel), which is the channel where downlink / uplink resource allocation is transmitted. This is because asynchronous HARQ is applied in NR. Uplink HARQ ACK / NACK information for downlink data transmission can be transmitted through the physical channels of the PUCCH (Physical Uplink Control Channel) or PUSCH (Physical Uplink Shared Channel). The above PUCCH is generally transmitted in the uplink of the PCell described later, but if the terminal supports it, the base station may additionally transmit it to the SCell described later to the terminal, which is referred to as the PUCCH SCell.

[0040] Although not shown in this drawing, a Radio Resource Control (RRC) layer exists above the PDCP layer of the terminal and the base station, respectively, and the RRC layer can exchange connection and measurement-related setting control messages for wireless resource control.

[0041] Meanwhile, the above PHY layer can be composed of one or more frequencies / carriers, and the technology of setting and using multiple frequencies simultaneously is called carrier aggregation (hereinafter referred to as CA). CA technology allows for a significant increase in transmission capacity by the number of secondary carriers by using one or more secondary carriers in addition to the main carrier, whereas previously only one carrier was used for communication between a terminal (or User Equipment, UE) and a base station (E-UTRAN NodeB, eNB). Meanwhile, in LTE, a cell within a base station that uses the main carrier is called a primary cell or PCell (Primary Cell), and a cell within a base station that uses a secondary carrier is called a secondary cell or SCell (Secondary Cell).

[0042] FIG. 3 is a diagram illustrating the process of deriving cell measurement results in a mobile communication system according to one embodiment of the present disclosure.

[0043] Referring to FIG. 3, the terminal can perform measurements (300) on all (full) beams operated by the cell to obtain cell measurement results (320) for a specific cell. For reference, the cell measurement results may refer to L3 RSRP (reference signal received power) / RSRQ (reference signal received quality) / SINR (signal to interference and noise ratio) values ​​(RSRP / RSRQ / SINR values ​​after Layer 3 filtering) measured by the terminal for each cell. Additionally, the measurement results (305) for each beam may refer to L1 RSRP / RSRQ / SINR values ​​(values ​​reported to Layer 3 after filtering at Layer 1) measured for each SSB (synchronization signal block) index that the base station transmits to the beam (corresponding to the beam). The terminal can obtain the cell measurement result (320) after performing a consolidation (310) operation based on the measurement result (300) for all SSB indices transmitted by the cell.

[0044] The above consolidation operation (310) may mean an operation to derive a cell measurement result (320) from the measurement result (300) for all beams. More specifically, the terminal may perform the consolidation operation as described below.

[0045] If, within the settings of a measurement object (hereinafter referred to as MO) associated with a specific cell measurement, a specific threshold value (absThreshSS-BlocksConsolidation) or the number of average SSBs (nrofSS-BlocksToAverage) is not included, or if the beam measurement result with the highest signal strength is equal to or lower than the absThreshSS-BlocksConsolidation value, the terminal may derive the beam measurement result with the highest signal strength among all beam measurement results for that cell as the cell measurement result for that cell. Otherwise, the terminal may derive the average (linear power scale average) of the best beam measurement results, up to a maximum of nrofSS-BlocksToAverage, among beam measurement results with a signal strength higher than the absThreshSS-BlocksConsolidation, as the cell measurement result.

[0046] Therefore, when a terminal derives cell measurement results for a specific cell as described above, it may have a burden (or load) of having to measure all SSBs transmitted by the specific cell and obtain beam measurement results (300) for all beams. Accordingly, the present disclosure will explain a method in which a terminal performs beam measurement on only a partial beam and derives cell measurement results by utilizing Artificial Intelligence (AI) / Machine Learning (ML) through the embodiments of FIGS. 4 and 5 below. Furthermore, the present disclosure proposes terminal and base station operations to ultimately reduce the load incurred when the terminal derives cell measurement result values ​​through the above method.

[0047] FIG. 4 is a diagram illustrating a method of utilizing an AI / ML model to predict cell measurement results in order to reduce the cell measurement load in a mobile communication system according to one embodiment of the present disclosure.

[0048] Referring to FIG. 4, AI / ML models (410a, 410b) can be used to predict cell measurement results (420, 423) based on partial beam measurement results (401a, 401b). For reference, the beam measurement results may refer to L1 RSRP / RSRQ / SINR values ​​measured for each beam operated by the serving cell, as described in FIG. 3. Additionally, the cell measurement results may refer to L3 RSRP / RSRQ / SINR values ​​measured (predicted) for each cell, as described in FIG. 3. The meaning (or definition) of the cell measurement results and beam measurement results may be applied in the same way to the embodiment of FIG. 5 below.

[0049] A method of using an AI / ML model to predict cell measurement results based on partial beam measurement results according to one example of the present disclosure can be broadly classified into the following two cases.

[0050] - Case 1 (Direct prediction of cell measurement results based on partial beam measurement results, 400a): An AI / ML model (410a) can be trained to receive as input a partial beam measurement result (401a) obtained by measuring only a part of the beam operated by a specific cell, and to output a cell measurement result (420) of the cell. The terminal can reduce the cell measurement load by measuring some beams (405a) among the beams operated by the serving cell and not measuring the remaining beams (407a). The terminal can perform an inference operation by providing the partial beam measurement result (401a) obtained by measuring only some beams as input to the trained AI / ML model (410a), and derive a cell measurement prediction result (420) as output. Subsequently, the terminal can perform existing radio resource management (RRM) operations (e.g., checking conditions for transmitting measurement report (MR) and reporting cell measurement results through MR transmission) based on the cell measurement prediction results.

[0051] - Case 2 (Predicting all beam measurement results based on partial beam measurement results, 400b): An AI / ML model (410b) can be trained to receive a partial beam measurement result (401b) obtained by measuring only a part of the beam operated by a specific cell as input, and to output a full beam (or remaining beam) measurement result (421). The terminal can reduce the cell measurement load by measuring some beams (405b) among the beams operated by the serving cell and not measuring the remaining beams (407b). The terminal can perform an inference operation by providing the partial beam measurement result (401b) obtained by measuring only some beams as input to the trained AI / ML model (410b), and obtain a prediction result (421) of all beams (or remaining beams) as output. Subsequently, the terminal can perform a consolidation operation (423) as described in FIG. 3 based on all beam measurement / prediction results (421, measurement results for some beams and measurement prediction results for the remaining beams) and derive a cell measurement prediction result (423). Here, the measurement result for some beams (partial beam measurement quantity) and the measurement prediction result for the remaining beams (partial beam prediction quantity) described in this case 2 can be used in a sense corresponding to the beam measurement result (beam measurement quantity) in the consolidation operation described in FIG. 3. Subsequently, the terminal can perform existing RRM operations (e.g., checking MR transmission conditions and reporting cell measurement results through MR transmission) based on the cell measurement prediction result.

[0052] In common to both of the two cases described above, the Measurement Reduction Rate in Spatial domain (MRRS), which is the rate at which the measurement load of the terminal is reduced, can be defined as the ratio of beams for which measurements were not performed out of the total beams. For example, if the MRRS is 50%, the terminal can measure only the SSBs corresponding to half of the beams among the total beams operated by a specific cell, and then derive cell measurement prediction results using an AI / ML model as described above.

[0053] Additionally, as described above, the operation of predicting cell measurement results using an AI model with results obtained by measuring only a portion of the beam operated by a specific cell can be called spatial domain prediction. This is because the cell measurement results are predicted by using the beam measurement results from a portion of the beam spatial domain to predict the beam measurement results in the remaining area. For convenience of explanation, in the embodiment of FIG. 5 below, the operation of predicting cell measurement results based on spatial domain prediction and reducing the measurement load of the terminal is defined as a 'cell measurement load reduction operation' and the expression is to be used.

[0054] FIG. 5 is a flowchart of a process in which a base station instructs a terminal to perform a cell measurement load reduction operation according to one embodiment of the present disclosure, and the terminal performs a cell measurement load reduction operation according to the base station's instruction.

[0055] Referring to FIG. 5, in step 510, the terminal (500, UE) and the base station (505) can exchange terminal capability information related to cell measurement load reduction operations. Subsequently, through steps 521, 523, and 525, the base station (505) sets the cell measurement load reduction operation for the terminal (500), and the terminal (500) determines whether it can perform the cell measurement load reduction operation (e.g., whether it has an AI model to perform cell measurement result prediction), and then responds to the base station (505) with information regarding this. In step 530, the terminal (500) can predict cell measurement results based on partial beam measurement results through the cell measurement load reduction operation. Subsequently, in step 540, if the conditions for transmitting a Measurement report (MR) are satisfied based on the predicted cell measurement results, the terminal (500) can perform MR transmission to the base station (505) in step 540. The MR may include cell measurement / prediction results (in other words, cell measurement results predicted through cell measurement load reduction operations). Additionally, the terminal (500) may report to the base station (505) that a performance monitoring metric of the cell measurement load reduction operation is included within the MR. For example, the performance monitoring metric of the cell measurement load reduction operation may include information on the difference (RSRP / SINR / RSRQ difference) between the cell measurement result predicted through the cell measurement load reduction operation and the actual cell measurement result value. In step 543, the base station (505) may determine whether the terminal (500) can continue to perform the cell measurement load reduction operation based on the performance monitoring metric of the cell measurement load reduction operation reported by the terminal (500).For example, if the accuracy of the cell prediction result of the terminal (500) does not reach a certain level, the base station (505) may instruct the terminal (500) in step 545 to disable the cell measurement load reduction operation or to change the setting information related to the cell measurement load reduction operation (e.g., change MRRS).

[0056] Hereinafter, specific signaling procedures and terminal / base station operations for performing the above operations will be described in detail below.

[0057] In step 510, the base station (505) may request the terminal (500) to report terminal capability information related to cell measurement load reduction operations. To this end, the base station may include an indicator for requesting terminal capability information related to cell measurement load reduction operations in a message for requesting terminal capability (e.g., a UECapabilityEnquiry message) and transmit it to the terminal (500). The operation in step 510 is intended to prevent the terminal from unnecessarily reporting its capability information to a base station / network that does not support the function, considering that the network / base station capable of setting / supporting the terminal to perform cell measurement load reduction operations based on artificial intelligence is limited. Subsequently, the terminal (500) may report terminal capability information related to cell measurement load reduction operations in accordance with the request of the base station (505). The capability information of the above terminal can be transmitted to the base station (505) through a UECapabilityInformation message transmitted by the terminal to the base station, and the message may include at least one of the following information related to cell measurement load reduction operation.

[0058] * An indicator indicating whether it supports an operation to predict cell measurement results (cell-specific L3 RSRP / SINR / RSRQ) based on partial beam measurement results. In other words, an indicator indicating whether it supports a cell measurement load reduction operation. If the terminal supports a cell measurement load reduction operation, it may include the indicator in the UECapabilityInformation message, or include the indicator in the UECapabilityInformation message by setting it to 'True' or 'Supported'.

[0059] * An indicator indicating whether the terminal supports the operation of predicting remainder beam measurement results (beam-specific L3 RSRP / SINR / RSRQ) based on partial beam measurement results. If the terminal supports the operation of predicting remainder beam measurement results based on partial beam measurement results, it may include the indicator in the UECapabilityInformation message, or include the indicator in the UECapabilityInformation message by setting it to 'True' or 'Supported'. For reference, since the terminal's capability required to predict cell measurement results based on partial beam measurement results may differ from the terminal's capability required to predict beam measurement results, separate terminal capability information may be defined for the operation of predicting cell measurement results and the operation of predicting beam measurement results, respectively. Otherwise, the terminal may be subject to the constraint that it must always support both operations together.

[0060] * An indicator representing the type of predictable measurement result (RSRP / SINR / RSRQ). If the terminal supports one or more of the cell measurement result prediction operation and the beam measurement result prediction operation, it may report one or more supported measurement result types through the indicator.

[0061] In step 521, the base station (505) may provide the terminal (500) with configuration information required for a cell measurement load reduction operation through a predetermined RRC message (e.g., RRCReconfiguration). The configuration information required for a cell measurement load reduction operation may include at least one of the following information.

[0062] * Cell Measurement Load Reduction Operation Indicator: A base station may instruct a cell measurement load reduction operation at the level of a Measurement Object (MO), ReportConfig, or cell. For reference, the MO includes configuration information that indicates target frequency and time resource information that the terminal must measure. Additionally, the ReportConfig includes configuration information that instructs how to report the measurement / prediction results to the base station via MR transmission while performing cell / beam measurement / prediction according to the configuration information within the MO to which the terminal is connected. When a cell measurement load reduction operation is instructed at the level of the MO or ReportConfig, a 1-bit indicator indicating the cell measurement load reduction operation may be included within the MO or ReportConfig. If the indicator is included / configured, the terminal may perform a cell measurement load reduction operation for cells detected in the frequency and time resources indicated by the M (the MO containing the 1-bit indicator or the MO connected to the ReportConfig containing the 1-bit indicator via MeasID). Alternatively, when directing a cell measurement load reduction operation on a cell-by-cell basis, an indicator (e.g., a list of predicted target cells) for indicating the cell(s) on which the cell measurement load reduction operation must be performed may be included within the MO or ReportConfig. In this case, the terminal may perform the cell measurement load reduction operation for the cells indicated by the indicator.

[0063] Additionally, the base station (505) may instruct the terminal (500) to perform a cell measurement load reduction operation only for the serving cell. This is because it is easy for the terminal (500) to learn the AI ​​model required to perform the cell measurement load reduction operation for the serving cell, but it may be difficult to have the results of learning the said AI model for all other neighboring cells. To this end, the specification may include a constraint that the indicator for the cell measurement load reduction operation can be set only within the Serving cell MO for the serving cell, or if the indicator for the cell measurement load reduction operation is included at the terminal level (e.g., at the MeasConfig level), the specification may include a provision restricting the terminal to perform the cell measurement load reduction operation only for the serving cell.

[0064] In another embodiment, if the AI ​​model required to perform the cell measurement load reduction operation is not different for each cell but is the same for all, the base station may include an indicator for directing the cell measurement load reduction operation at the terminal level (e.g., at the MeasConfig level). In this case, the terminal may perform the cell measurement load reduction operation at the frequency and time resources directed by all configured MOs.

[0065] Here, as described above in FIG. 4, the following two cases can be applied as methods for performing cell measurement load reduction operations.

[0066] - Case 1 (Direct prediction of cell measurement results based on partial beam measurement results)

[0067] - Case 2 (Predicting all beam measurement results based on partial beam measurement results)

[0068] At this time, depending on which of the two cases the cell measurement load reduction operation indicator set by the base station indicates the cell measurement load reduction operation, the terminal operation associated with the consolidation setting given in the existing MO unit (e.g., absThreshSS-BlocksConsolidation, nrofSS-BlocksToAverage) may differ.

[0069] If the cell measurement load reduction operation indicator directs an operation corresponding to Case 1, when the base station directs the cell measurement load reduction operation, the terminal may no longer perform the consolidation operation described in FIG. 3. Therefore, when a cell measurement load reduction operation is directed for a specific MO, the terminal may ignore the consolidation settings set for that MO (e.g., absThreshSS-BlocksConsolidation, nrofSS-BlocksToAverage). Alternatively, considering the signaling load, if the cell measurement load reduction operation indicator is included within a specific MO, the base station may restrict the settings so that the consolidation settings are not included within that MO. Additionally, if a cell measurement load reduction operation is directed on a specific cell(s) basis, the terminal may ignore the consolidation settings set only for the measurement operation for those cells, and still perform consolidation for other cells according to the consolidation settings.

[0070] If the cell measurement load reduction operation indicator directs an operation corresponding to Case 2, the terminal can still perform the consolidation operation described in Fig. 3 when the base station directs the cell measurement load reduction operation. In other words, the terminal can obtain a full beam measurement / prediction result based on a partial beam measurement result using an AI model, and then derive a cell measurement result through a consolidation operation. Therefore, when a cell measurement load reduction operation is directed for a specific MO, the terminal can perform a consolidation operation according to the consolidation settings set for that MO (e.g., absThreshSS-BlocksConsolidation, nrofSS-BlocksToAverage).

[0071] As described above, since the terminal operation may vary depending on which Case the cell measurement load reduction operation is understood to correspond to, the base station may explicitly instruct the terminal that the operation corresponds to which of the aforementioned Cases when instructing the cell measurement load reduction operation. In this case, the cell measurement load reduction operation indicator set by the base station may indicate which case, Case 1 or Case 2, the operation corresponds to. To this end, for example, the indicator may be defined in a form such as ENUMERATE{Case 1, Case 2} to indicate one of the two cases. Additionally, when the terminal includes an indicator indicating whether the cell measurement load reduction operation is supported within the UECapabilityInformation message in step 510 to assist in the base station configuration, it may include a separate indicator indicating whether the terminal supports the corresponding operation for each of Case 1 and Case 2, or it may include an indicator that indicates only one of the two corresponding to the operation supported by the terminal.

[0072] As another example, a base station according to one example of the present disclosure may instruct a terminal to perform a cell measurement load reduction operation without distinguishing between Case 1 and Case 2, and may leave it to the terminal implementation to decide which method among Case 1 or Case 2 to perform the cell measurement load reduction operation. In this case, the terminal may have more freedom in performing the cell measurement load reduction operation, and the base station may reduce the load on setting the cell measurement load reduction operation.

[0073] The terminal (500) has an AI model necessary to perform a cell measurement load reduction operation set by the base station (505), and in a situation where the terminal (500) can perform inference through the AI ​​model and derive a result value (in other words, in a situation where there are no internal terminal issues such as memory shortage or overheating), the applicability of the operation can be determined as 'Applicable / True / Available'. In this case, the terminal (500) can report the applicability of the operation to the base station (505) through a predetermined RRC message (RRCReconfigurationComplete or UEAssistanceInformation) in step 523 below. If the terminal (500) determines that the applicability of each operation is not applicable, such as 'not Applicable / False / Unavailable', it may not start the operation and may report the applicability of the operation to the base station (505) via a predetermined RRC message (RRCReconfigurationComplete or UEAssistanceInformation) in step 523 below.

[0074] For reference, if the terminal (500) reports applicability information for each of the above operations to the base station (505) immediately after receiving the base station settings in step 521, the applicability information may be included in the RRCReconfigurationComplete message transmitted in response to the RRCReconfiguration message in step 523. On the other hand, if the applicability for a specific operation changes due to internal conditions (memory shortage and heat generation problems) regardless of the network settings in step 521, the terminal (500) may include the applicability information in the UEAssistanceInformation message and transmit it to the base station (505). To this end, the base station settings information in step 521 may include an indicator to instruct the terminal to report the applicability for the cell measurement load reduction operation via the UEAssistanceInformation (UAI) message. At this time, to prevent the terminal from reporting the applicability information too frequently via a UAI message, the base station (505) may set a prohibit timer value for the terminal (500). In this case, whenever the terminal (500) reports the applicability for a cell measurement load reduction operation via a UAI message, it starts a timer with the prohibit timer value set for that operation, and cannot report the applicability for the same operation until the timer expires.

[0075] * Associated ID: As described above, in order for a terminal to determine applicability to a cell measurement load reduction operation setting configured by a base station, the terminal must be able to determine whether it possesses an AI model necessary to perform a cell measurement load reduction operation for specific MOs or Cells (in other words, an AI model necessary to derive cell measurement result values ​​based on partial beam measurement results). For example, it can be assumed that the terminal has learned a model AI necessary for a cell measurement load reduction operation based on training data obtained by measuring a specific Cell A. In this case, whether the terminal can use the said AI model for a cell measurement load reduction operation for Cell B can be determined based on whether the Cell A and Cell B have the same beam setting (e.g., the correlation between an analog beam pattern physically facing a specific direction and an SSB having a specific index). More specifically, if Cell A and Cell B have the same beam setting described above, the direction of the physical beam transmitting SSB index 1 from Cell A and the direction of the physical beam transmitting SSB index 1 from Cell B may be the same. Therefore, the correlation between some beam measurement results (e.g., the result of measuring an SSB with an even index) and other beam measurement results or cell measurement results can also be maintained identically in Cell A and Cell B, which may mean that an AI model trained in Cell A can also be used in Cell B (in other words, applicable).

[0076] As described above, the base station may map beam settings for each cell to a specific ID (e.g., associated ID) to help the terminal determine the applicability of the cell measurement load reduction operation. Additionally, an indicator for indicating the ID value at the cell / cell set / MO level may be included in the cell measurement load reduction operation setting in step 521. When the base station sets the associated ID value to 1 while instructing the cell measurement load reduction operation for a specific MO, the terminal may report applicability to the base station at the MO level depending on whether there is an AI model trained on data collected from the cell corresponding to the associated ID value 1. At this time, the terminal can understand that all cells measured in the frequency and time domain indicated by the corresponding MO have the same associated ID (in other words, the same beam setting). Alternatively, if the base station instructs a cell measurement load reduction operation for a specific cell and a set of cells and sets the associated ID value to 1, the terminal can determine whether there is an AI model trained on data collected from the cell corresponding to the associated ID value 1, and report applicability to the base station on a cell or cell set basis. Alternatively, if the base station instructs a cell measurement load reduction operation for a specific MO / cell / set of cells and sets only one associated ID value, the terminal can understand that the associated ID value corresponds to a serving cell and that all measurable cells within that serving cell have the same associated ID value. Subsequently, the terminal can determine whether there is an AI model trained on data collected from the cell having the associated ID value and report applicability to the base station on a cell measurement load reduction operation basis.

[0077] Alternatively, if the base station provides multiple Associated ID values ​​in any unit, the terminal can determine and report applicability for each Associated ID unit.

[0078] * MRRS: As described in Figure 4 above, the Measurement Reduction Rate (MRRS) in the spatial domain, which is the rate at which the measurement load of the terminal is reduced through a cell measurement load reduction operation, can be defined as the ratio of beams that do not perform measurements among all beams. When the terminal performs a cell measurement load reduction operation, a trade-off between the effect of reducing the terminal's measurement load and the accuracy of the cell measurement result can be determined depending on which MRRS value is used. For example, if a high MRRS value is used, the measurement load of the terminal is significantly reduced, but the accuracy of the cell measurement result value during the cell measurement load reduction operation may also be significantly lower. Conversely, if a low MRRS value is used, the measurement load of the terminal is slightly reduced, but the accuracy of the cell measurement result value during the cell measurement load reduction operation may also be slightly lower. Therefore, a method is required to determine an appropriate MRRS value during the cell measurement load reduction operation. To this end, the MRRS can be determined using one of the following two methods.

[0079] - Method 1 (Base station determines MRRS): When the terminal reports the applicability for the cell measurement load reduction operation to the base station in step 523 below, it may report in units of MRRS. For example, the terminal may report applicability for each case of MRRS 50%, 66%, and 80%. This is a reasonable approach considering that the AI ​​model can be trained separately for each MRRS because the magnitude of the partial beam measurement result value entering as the input value of the AI ​​model varies depending on the MRRS. To this end, the base station may provide the terminal with an indicator within the RRC message transmitted to the terminal in step 521 above to indicate one or more candidate MRRS values ​​for which the terminal should report applicability for the measurement load reduction operation. Additionally, the terminal may report applicability for each MRRS and, together with it, report the cell measurement accuracy that can be guaranteed when performing a cell measurement load reduction operation using the corresponding MRRS value (e.g., the RSRP difference, which is the difference between the actual measured RSRP value and the RSRP value predicted based on partial beam measurement results). This is to help the base station instruct the terminal on which MRRS value to use when setting / instructing the terminal to perform a cell measurement load reduction operation. For example, the cell measurement accuracy can help the base station select the MRRS value that can reduce the terminal's measurement load the most while satisfying the requirements for cell measurement accuracy necessary to support the terminal's mobility, based on the guaranteed cell measurement accuracy for each MRRS value reported by the terminal.In another embodiment, when the requirements for cell measurement accuracy necessary to support the mobility of the terminal are standardized, the terminal may report that applicability is applicable only to MRRS value(s) that can initially satisfy the requirements, such as 'Applicable / True / Available', and report that applicability is not applicable to MRRS value(s) that cannot satisfy the requirements, such as 'not Applicable / False / Unavailable'. Subsequently, in step 525, the base station may select one of the MRRS values ​​that the terminal reported as applicable in step 523 and instruct the terminal to perform a cell measurement load reduction operation with the selected MRRS value. Accordingly, within a predetermined RRC message (e.g., an RRCReconfiguration message) transmitted by the base station for setting the cell measurement load reduction operation, which will be described later in step 525, an indicator for indicating the MRRS value selected by the base station may be included.

[0080] - Method 2 (Terminal determines MRRS): While setting the cell measurement load reduction operation in step 521, the base station may also transmit minimum requirements for cell measurement accuracy necessary to support the mobility of the terminal (e.g., threshold value of cell measurement accuracy that the base station can accept, tolerable RSRP difference). To this end, an indicator representing the cell measurement accuracy threshold may be included in the RRC message in step 521. Alternatively, the minimum requirements for cell measurement accuracy necessary to support the mobility of the terminal may be standardized and included in the specifications. Subsequently, the terminal may select one of the MRRS values ​​that can satisfy the minimum requirements for cell measurement accuracy set by the base station or included in the specifications. For example, the terminal may have models trained for each of the multiple MRRS values ​​to support the cell measurement load reduction operation. In this case, the terminal can randomly select one of the models (or MRRS values) that can satisfy the minimum requirements for cell measurement accuracy (e.g., can guarantee the RSRP difference value) and start a cell measurement load reduction operation based on this. Subsequently, when reporting the applicability of the cell measurement load reduction operation in step 523 below, the applicability of the operation can be reported by setting it as applicable, such as 'Applicable / True / Available'.Conversely, if there is no model (or MRRS value) capable of satisfying the minimum requirements for cell measurement accuracy (e.g., capable of guaranteeing the RSRP difference value), the terminal may report the applicability of the cell measurement load reduction operation in step 523 below by setting the applicability of the operation to be unapplicable, such as 'Not Applicable / False / Unavailable'.

[0081] * Beam combination to be measured: As described in FIG. 4 above, when performing a cell measurement load reduction operation, the terminal can derive / predict cell measurement results based on partial beam measurement results measured for a specific beam combination. At this time, regarding how the terminal determines the beam combination for which beam measurement must be performed (in other words, the SSB index combination to be measured), at least one of the following methods may be considered.

[0082] - Method 1 (Terminal Determination): When the base station instructs a cell measurement load reduction operation in step 521 above, the terminal implementation may be left to decide which beam combination the terminal will perform beam measurements on and derive / predict the cell measurement results. In this case, the AI ​​model used to predict the remaining beam measurement results based on partial beam measurement results or to predict the cell measurement results for the cell measurement load reduction operation may be trained by the terminal (or by the terminal manufacturer's server). Therefore, the base station may not need to know which beam combination the terminal is performing partial beam measurements on. In this case, the terminal may determine the beam combination to be measured on its own when the base station instructs the cell measurement load reduction operation. If it is helpful for the base station to identify information regarding the beam combination on which the terminal is performing beam measurements, the terminal may report to the base station the beam combination to be measured that the terminal determined on its own in step 523 below, including it in the corresponding RRC message. Compared to the following methods 2, 3, and 4, method 1 may have an advantage in that it can give the terminal a degree of freedom regarding which beam combination partial beam measurement results to use as input values ​​for the AI ​​model used for cell measurement load reduction operation.

[0083] - Method 2 (Determination of partial beam measurement by terminal): When Method 1 (the base station determines the MRRS) among the MRRS determination methods described above is used, the base station may, at step 525 below, finally instruct the cell measurement load reduction operation and together instruct the MRRS value to be used by the terminal. Subsequently, the terminal can independently determine the beam combination to be measured within the range that satisfies the MRRS value set by the base station. For example, if the base station sets the MRRS value to be used by the terminal to 50%, the terminal can independently determine the combination of SSB indices corresponding to half of the SSBs transmitted by the cell that need to be measured. Compared to Method 1, Method 2 has advantages in that it provides a means to guarantee minimum accuracy for cell measurement results by giving the base station the right to select the MRRS, while simultaneously giving the terminal a degree of freedom regarding which beam combination's partial beam measurement results to use as input values ​​for the AI ​​model used for the cell measurement load reduction operation. In addition, it can have advantages in terms of signaling load compared to Method 3 below, in that the base station does not instruct the terminal on the beam combination to be measured every time. Furthermore, to simultaneously utilize the advantages of Method 1 and Method 2, the terminal can decide which of the two methods to use depending on the base station settings (MRRS settings). If the base station does not set the MRRS, the terminal can freely determine the target cell combination for measurement as in Method 1 above. On the other hand, if the base station sets the MRRS, the terminal can determine the target beam combination for measurement itself within the range satisfying the MRRS set by the base station as in Method 2 above.

[0084] - Method 3 (Base Station Determination): The AI ​​model used for the cell measurement load reduction operation described above can be trained to predict the measurement results of the remaining beams or the cell measurement results based on the partial beam measurement results. In this case, the accuracy of the cell measurement result prediction may vary depending on which beam combination measurement results are provided as the partial beam measurement results, which are the input values ​​of the AI ​​model. For example, if measurements are performed only with beam combinations corresponding to a specific direction within the entire beam space, the partial beam measurement results for that beam combination may not be suitable or sufficient to predict the measurement results of the entire cell. Therefore, to train the AI ​​model used for the cell measurement load reduction operation more accurately or efficiently, it may be necessary to know which analog beam direction the beams used for each actual SSB transmission correspond to (map) within the entire beam space. However, while the terminal can distinguish different beam configuration information through the associated ID values ​​described above, it cannot specifically determine which beam direction each SSB transmission physically corresponds to within that beam configuration. Ultimately, only the base station can determine the mapping information regarding which analog beam direction each SSB corresponds to within the beam space. Accordingly, considering the above description, the base station may instruct the terminal to set the cell measurement load reduction technique and the measurement target beam combination together. To this end, when the base station instructs the terminal to perform the cell measurement load reduction operation through a predetermined RRC message in step 521, it may provide the terminal with an indicator representing the measurement target beam combination together.Alternatively, if the cell measurement load reduction operation is instructed at the MO level, the terminal may understand the SSB combination that the terminal is to measure, which was indicated by the existing field (ssb-ToMeasure) within the MO, as the target beam combination for measurement that the terminal must measure for the cell measurement load reduction operation. Subsequently, in step 523, the terminal receives the partial beam measurement results for the target beam combination, determines whether it has an AI model trained to predict the remaining beam measurement results or the cell measurement results, and reports the applicability reflecting the determination result to the base station. At this time, the applicability report may be made at the level of the target beam combination.

[0085] - Method 4 (Specified in Standard): To reduce the cell measurement load, the combination of target beams for which the terminal must perform measurements may be specified in the standard. For example, among all SSBs, the terminal [can...] under specific conditions specified in the standard (e.g., Index modulo Measurements can be performed on SSBs (beam combinations) that satisfy ). If the MRRS is set to 0.5 (50%), the terminal can perform beam measurements only on SSBs with even indices (beam combinations corresponding to those SSBs). By including conditions / rules for determining the beam combinations to be measured in the specification in this way, both the terminal and the base station can understand through the specification how the beam combinations to be measured are determined when a specific MRRS value is used for cell measurement load reduction operations. Through this, the base station can adjust the beam settings (the connection relationship between each SSB and the physical beam) so that the SSBs corresponding to the beam combinations to be measured correspond to physical beams that are sufficient / helpful for inferring actual cell measurement results. Furthermore, the above method 4 has the advantage of allowing the terminal to identify the beam combinations to be measured while avoiding the signaling load caused by the base station explicitly specifying the beam combinations to be measured, as in the above method 3.

[0086] * Predicted Performance Monitoring Indicator: A base station (505) may instruct a terminal (500) to calculate and report a performance monitoring metric of the cell measurement load reduction operation while performing the cell measurement load reduction operation. To this end, an indicator for instructing the operation to calculate and report the performance monitoring metric described above may be included in a predetermined RRC message (RRCReconfiguration). Here, the performance monitoring metric may refer to the difference (RSRP / SINR / RSRQ difference) between the cell measurement result predicted / derived by the terminal based on the partial beam measurement result and the cell measurement result derived by the terminal based on the actual full beam measurement result. While instructing the terminal to calculate and report the performance monitoring metric, the base station may also provide information regarding the period during which the terminal must calculate and report the metric (e.g., an indicator indicating the period). Depending on the base station configuration, the terminal may normally reduce the cell measurement load through partial beam measurement, and then perform a full beam measurement at a certain period to derive the cell measurement result and calculate the performance monitoring metric. The terminal may report the performance evaluation indicator calculated in this way to the base station through a predetermined RRC message. For example, when the terminal transmits the MR to the base station in step 540 below, it may include the calculated performance evaluation indicator in the MR and report it to the base station. By reporting the performance evaluation indicator together with the MR transmission in this way, the signaling load between the terminal and the base station can be reduced. Alternatively, if the base station is configured to report the performance evaluation indicator at a specific period, the terminal may report the performance evaluation indicator according to the specific period using a different RRC message separately from the MR transmission.

[0087] Additionally, the terminal may report to the base station, including a performance monitoring metric for the cell measurement load reduction operation within the MR. For example, the MR may include, as the performance monitoring metric, the difference (RSRP / SINR / RSRQ difference) between the cell measurement result predicted through the cell measurement load reduction operation and the actual cell measurement result value. In step 543, the base station may determine whether the terminal can continue to perform the cell measurement load reduction operation based on the performance monitoring metric for the cell measurement load reduction operation reported by the terminal. For example, if the accuracy of the terminal's cell prediction result does not reach a certain level, the base station may instruct the terminal in step 545 to disable the cell measurement load reduction operation or to change configuration information related to the cell measurement load reduction operation (e.g., change MRRS). Specific signaling procedures and terminal / base station operations for performing the above operations are as described below.

[0088] In step 523, the terminal (500) determines the applicability of the cell measurement load reduction operation according to the settings provided by the base station (505) as described in step 521, and can report this to the base station (505) through a predetermined RRC message (RRCReconfigurationComplete or UEAssistanceInformation). At this time, if the terminal (500) determines that the applicability of the cell measurement load reduction operation is applicable as 'Applicable / True / Available' and receives all the setting information necessary to perform the cell measurement load reduction operation in step 521, the terminal can immediately start performing the cell measurement load reduction operation while reporting the applicability. On the other hand, if the terminal determines that the applicability for the cell measurement load reduction operation is not applicable, such as 'NotApplicable / False / Unavailable', or if it does not receive all the configuration information required to perform the cell measurement load reduction operation in step 521 above, the terminal may report the applicability to the base station and wait for the base station configuration in step 525 below.

[0089] In step 525, the base station (505) may provide the terminal (500) with additional configuration information required for a cell measurement load reduction operation through a predetermined RRC message (RRCReconfiguration message) as described in step 521. For example, as described in step 521, if the terminal reports multiple applicable MRRS values ​​and the base station selects one of them, the base station may instruct the terminal (500) by including the MRRS value selected by the base station in the RRC message. In another embodiment, the base station (505) may provide the terminal (500) with a modified cell measurement load reduction operation setting through the RRC message. For example, when the terminal reports in step 523 that the applicability to the cell measurement load reduction operation is not applicable to a specific MO / cell / MRRS / measurement target beam combination, etc., the base station may set the cell measurement load reduction operation for the terminal with a new MO / cell / MRRS / measurement target beam combination based on the terminal report. However, if the terminal can immediately perform the cell measurement load reduction operation according to the base station setting in step 521 as described in step 523, the additional base station setting in step 525 may be omitted.

[0090] In step 530, the terminal (500) can perform a cell measurement load reduction operation according to the base station (505) settings in steps 521 and 525. In other words, the terminal (500) can predict / derive cell measurement results using AI based on partial beam measurement result values ​​obtained by performing beam measurements only on specific target beam combinations. Subsequently, the terminal (500) can check the Measurement Report (MR) transmission conditions based on the cell measurement results, and if the MR transmission conditions are satisfied, it can transmit the MR to the base station (505) in step 540 below. For example, according to the base station settings in steps 521 and 525, the terminal (500) can determine whether the MR transmission conditions are satisfied by a specific event (e.g., Event A3) defined in the RRC standard based on the cell measurement results obtained while performing the cell measurement load reduction operation, and if the MR transmission conditions are satisfied, it can transmit the MR to the base station (505) as in step 540 below.

[0091] In step 540, the terminal (500) may start MR transmission according to the base station settings as described in step 530. At this time, the terminal (500) may include the cell measurement result value obtained through the cell measurement load reduction operation within the MR and report it to the base station (505). Additionally, as described in step 521, if the base station (505) instructs the terminal (500) to report the performance evaluation indicator of the cell measurement load reduction operation, the terminal (500) may include the value of the performance evaluation indicator of the cell measurement load reduction operation (e.g., RSRP / RSRQ / SINR difference) within the MR and report it to the base station (505).

[0092] In step 543, the base station (505) may determine whether to instruct the terminal (500) to continue performing the cell measurement load reduction operation based on the performance evaluation indicator of the cell measurement load reduction operation included in the MR transmitted by the terminal (500) in step 540. Alternatively, the base station (505) may determine whether a change in the settings of the cell measurement load reduction operation (e.g., change of target cell / MO, change of MRRS, etc.) is required based on the performance evaluation indicator of the cell measurement load reduction operation. For example, if the performance evaluation indicator value reported by the terminal (500) in step 540 does not satisfy the accuracy required by the base station (505), the base station (505) may decide to disable the measurement load reduction operation of the terminal (500). Alternatively, the base station (505) may decide to change the settings of the measurement load reduction operation for the terminal so that the terminal (500) can use a lower MRRS value to improve cell measurement accuracy.

[0093] In step 545, the base station (505) may instruct the terminal (500) to disable the cell measurement load reduction operation or change the cell measurement load reduction operation setting through a predetermined RRC message (RRCReconfiguration). For example, if the base station decides to disable the measurement load reduction operation as described in step 543, the base station (505) may instruct the terminal (500) to disable / stop the operation by not including the indicator for instructing the cell measurement load reduction operation described in step 521 within the RRC message, or by setting the indicator to 'False'. As another example, if the base station (505) decides to change the measurement load reduction operation setting as described in step 543, the base station (505) may change the cell measurement load reduction operation setting information (e.g., change target cell / MO, change MRRS, etc.) as described in step 521.

[0094] FIG. 6 is a drawing illustrating a terminal device according to one embodiment of the present disclosure.

[0095] Referring to FIG. 6, the terminal may include an RF (Radio Frequency) processing unit (610), a baseband processing unit (620), a storage unit (630), and a control unit (640). The configuration of the terminal is not limited to the exemplary configuration shown in FIG. 6 and may include fewer or more configurations than the configuration shown in FIG. 6.

[0096] The RF processing unit (610) can perform functions for transmitting and receiving signals through a wireless channel, such as signal band conversion and amplification. For example, the RF processing unit (610) can up-convert a baseband signal provided by the baseband processing unit (620) into an RF band signal and then transmit it through an antenna, and can down-convert an RF band signal received through an antenna into a baseband signal. For example, the RF processing unit (610) may include a transmission filter, a reception filter, an amplifier, a mixer, an oscillator, a DAC (digital to analog converter), an ADC (analog to digital converter), etc., but is not limited to these examples. Although only one antenna is shown in FIG. 6, the terminal may be equipped with multiple antennas. Additionally, the RF processing unit (610) may include multiple RF chains. Furthermore, the RF processing unit (610) may perform beamforming. For beamforming, the RF processing unit (610) can adjust the phase and magnitude of each of the signals transmitted and received through multiple antennas or antenna elements. Additionally, the RF processing unit (610) can perform MIMO and can receive multiple layers when performing MIMO operation.

[0097] The baseband processing unit (620) can perform conversion functions between baseband signals and bit sequences according to the physical layer specifications of the system. For example, when transmitting data, the baseband processing unit (620) can generate complex symbols by encoding and modulating the transmitted bit sequence. Additionally, when receiving data, the baseband processing unit (620) can restore the received bit sequence by demodulating and decoding the baseband signal provided by the RF processing unit (610). For example, in the case of following the orthogonal frequency division multiplexing (OFDM) method, when transmitting data, the baseband processing unit (620) can generate complex symbols by encoding and modulating the transmitted bit sequence, map the generated complex symbols to subcarriers, and then construct OFDM symbols through inverse fast Fourier transform (IFFT) operations and cyclic prefix (CP) insertion. Additionally, upon receiving data, the baseband processing unit (620) can divide the baseband signal provided by the RF processing unit (610) into OFDM symbol units, restore the signals mapped to subcarriers through a fast Fourier transform (FFT) operation, and then restore the received bit sequence through demodulation and decoding.

[0098] The baseband processing unit (620) and the RF processing unit (610) can transmit and receive signals as described above. Accordingly, the baseband processing unit (620) and the RF processing unit (610) may be referred to as a transmitting unit, a receiving unit, a transmitting and receiving unit, or a communication unit. Furthermore, at least one of the baseband processing unit (620) and the RF processing unit (610) may include a plurality of communication modules to support a plurality of different wireless access technologies. Additionally, at least one of the baseband processing unit (620) and the RF processing unit (610) may include different communication modules to process signals of different frequency bands. For example, different wireless access technologies may include wireless LAN (e.g., IEEE 802.11), cellular network (e.g., LTE), etc. In addition, different frequency bands may include super high frequency (SHF) bands (e.g., 2 NRHz, NRHz) and millimeter wave (e.g., 60 GHz) bands. The terminal can transmit and receive signals with the gNB using the baseband processing unit (620) and the RF processing unit (610), and the signals may include control information and data.

[0099] The storage unit (630) can store data such as basic programs, application programs, and setting information for the operation of the terminal. For example, the storage unit (630) can store data information such as basic programs, application programs, and setting information for the operation of the terminal. In addition, the storage unit (630) can provide the stored data upon a request from the control unit (640).

[0100] The storage unit (630) may be composed of a storage medium or a combination of storage media such as ROM, RAM, hard disk, CD-ROM, and DVD. Additionally, the storage unit (630) may be composed of a plurality of memories. According to one embodiment of the present disclosure, the storage unit (630) may store a program for performing a handover method according to the present disclosure.

[0101] The control unit (640) can control the overall operations of the terminal. For example, the control unit (640) can transmit and receive signals through the baseband processing unit (620) and the RF processing unit (610).

[0102] Additionally, the control unit (640) can write and read data to the storage unit (630). To this end, the control unit (640) may include at least one processor. For example, the control unit (640) may include a communication processor (CP) that performs control for communication and an application processor (AP) that controls upper layers such as applications. Also, according to one embodiment of the present disclosure, the control unit (640) may include a multi-connection processing unit (642) configured to process a process operating in a multi-connection mode. Additionally, at least one component within the terminal may be implemented as a single chip.

[0103] FIG. 7 is a drawing illustrating a base station device according to one embodiment of the present disclosure.

[0104] The base station of Fig. 7 may be included in the aforementioned network.

[0105] As illustrated in FIG. 7, the base station may include an RF processing unit (710), a baseband processing unit (720), a backhaul communication unit (730), a storage unit (740), and a control unit (750). The configuration of the base station is not limited to the exemplary configuration illustrated in FIG. 7, and the base station may include fewer or more configurations than the configuration illustrated in FIG. 7. The RF processing unit (710) may perform functions for transmitting and receiving signals through a wireless channel, such as signal band conversion and amplification. For example, the RF processing unit (710) may up-convert a baseband signal provided by the baseband processing unit (720) into an RF band signal and then transmit it through an antenna, and may down-convert an RF band signal received through an antenna into a baseband signal. For example, the RF processing unit (710) may include a transmission filter, a reception filter, an amplifier, a mixer, an oscillator, a DAC, an ADC, etc. In FIG. 7, only one antenna is shown, but the RF processing unit (710) may be equipped with multiple antennas. Additionally, the RF processing unit (710) may include multiple RF chains. Furthermore, the RF processing unit (710) may perform beamforming. For beamforming, the RF processing unit (710) may adjust the phase and magnitude of each of the signals transmitted and received through multiple antennas or antenna elements. The RF processing unit (710) may perform down-MIMO operation by transmitting one or more layers.

[0106] The baseband processing unit (720) can perform conversion functions between baseband signals and bit sequences according to physical layer specifications. For example, when transmitting data, the baseband processing unit (720) can generate complex symbols by encoding and modulating the transmitted bit sequence. Additionally, when receiving data, the baseband processing unit (720) can restore the received bit sequence by demodulating and decoding the baseband signal provided by the RF processing unit (710). For example, in the case of an OFDM method, when transmitting data, the baseband processing unit (720) can generate complex symbols by encoding and modulating the transmitted bit sequence, map the generated complex symbols to subcarriers, and then construct OFDM symbols through IFFT operations and CP insertion. Additionally, upon receiving data, the baseband processing unit (720) can divide the baseband signal provided by the RF processing unit (710) into OFDM symbol units, restore the signals mapped to subcarriers through FFT operations, and then restore the received bit sequence through demodulation and decoding. The baseband processing unit (720) and the RF processing unit (710) can transmit and receive signals as described above. Accordingly, the baseband processing unit (720) and the RF processing unit (710) may be referred to as a transmitting unit, a receiving unit, a transmitting and receiving unit, a communication unit, or a wireless communication unit. A base station can transmit and receive signals with a terminal using the baseband processing unit (720) and the RF processing unit (710), and the signal may include control information and data.

[0107] The backhaul communication unit (730) can provide an interface for communicating with other nodes within the network. For example, the backhaul communication unit (730) can convert a bit sequence transmitted from the main base station to another node, e.g., an auxiliary base station, a core network, etc., into a physical signal, and convert a physical signal received from another node into a bit sequence.

[0108] The storage unit (740) can store data such as basic programs, application programs, and configuration information for the operation of the main station. For example, the storage unit (740) can store information about a bearer assigned to a connected terminal, measurement results reported from the connected terminal, etc. Additionally, the storage unit (740) can store information that serves as a criterion for determining whether to provide or discontinue multiple connections to the terminal. Furthermore, the storage unit (740) can provide the stored data upon a request from the control unit (750). The storage unit (740) may be composed of a storage medium or a combination of storage media such as ROM, RAM, hard disk, CD-ROM, and DVD. Additionally, the storage unit (740) may be composed of multiple memories. According to one embodiment of the present disclosure, the storage unit (740) may store a program for performing a handover according to the present disclosure.

[0109] The control unit (750) can control the overall operations of the main station. For example, the control unit (750) can transmit and receive signals through the baseband processing unit (720) and the RF processing unit (710) or through the backhaul communication unit (730). Additionally, the control unit (750) can write and read data to and from the storage unit (740). To this end, the control unit (750) may include at least one processor. Also, according to one embodiment of the present disclosure, the control unit (750) may include a multi-connection processing unit (752) configured to process a process operating in a multi-connection mode.

[0110] Methods according to the embodiments described in the claims or specification of the present disclosure may be implemented in the form of hardware, software, or a combination of hardware and software.

[0111] When implemented in software, a computer-readable storage medium may be provided for storing one or more programs (software modules). One or more programs stored in the computer-readable storage medium are configured for execution by one or more processors within an electronic device. One or more programs include instructions that cause the electronic device to execute methods according to the embodiments described in the claims or specification of this disclosure.

[0112] Such programs (software modules, software) may be stored in random access memory, non-volatile memory including flash memory, ROM (Read Only Memory), Electrically Erasable Programmable Read Only Memory (EEPROM), magnetic disc storage devices, Compact Disc-ROM (CD-ROM), Digital Versatile Discs (DVDs), or other forms of optical storage devices, magnetic cassettes. Alternatively, they may be stored in memory composed of some or all of these. Additionally, each constituent memory may include multiple units.

[0113] Additionally, the above program may be stored on an attachable storage device that can be accessed via a communication network such as the Internet, Intranet, Local Area Network (LAN), Wide LAN (WLAN), or Storage Area Network (SAN), or a combination thereof. Such a storage device may be connected to a device performing an embodiment of the present disclosure through an external port. Additionally, a separate storage device on a communication network may be connected to a device performing an embodiment of the present disclosure.

[0114] In the present disclosure, the terms “computer program product” or “computer readable medium” are used to collectively refer to media such as memory, a hard disk installed in a hard disk drive, and signals. These “computer program product” or “computer readable medium” are configurations provided in a method for reporting terminal capability in a wireless communication system according to the present disclosure.

[0115] A device-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-transitory storage medium' simply means that it is a tangible device and does not contain a signal (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently and cases where it is stored temporarily. For example, a 'non-transitory storage medium' may include a buffer in which data is stored temporarily.

[0116] According to one embodiment, the method according to the various embodiments disclosed herein may be provided by being included in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory (CD-ROM)), or distributed online (e.g., download or upload) through an application store (e.g., Play Store™) or directly between two user devices (e.g., smartphones). In the case of online distribution, at least a portion of the computer program product (e.g., downloadable app) may be temporarily stored or temporarily created on a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0117] In the specific embodiments of the present disclosure described above, the components included in the invention are expressed in a singular or plural form according to the specific embodiments presented. However, the singular or plural expression is selected to suit the situation presented for convenience of explanation, and the present disclosure is not limited to singular or plural components; even if a component is expressed in the plural, it may be composed of a singular form, and even if a component is expressed in the singular form, it may be composed of a plural form.

[0118] Meanwhile, the embodiments of the present disclosure disclosed in this specification and drawings are merely specific examples provided to facilitate the explanation of the technical content of the present disclosure and to aid in understanding the present disclosure, and are not intended to limit the scope of the present disclosure. That is, it is obvious to those skilled in the art that other variations based on the technical concept of the present disclosure are possible. Furthermore, each of the above embodiments may be combined and operated as needed. For example, parts of one embodiment of the present disclosure and another embodiment may be combined to operate a base station and a terminal. In addition, the embodiments of the present disclosure are applicable to other communication systems, and other variations based on the technical concept of the embodiments may also be possible. For example, the embodiments may be applied to LTE systems, 5G, NR systems, or 6G systems, etc. Therefore, the scope of the present disclosure should not be limited to the described embodiments, but should be defined by the claims set forth below as well as equivalents thereof.

Claims

1. In a wireless communication system, regarding the method of a terminal, A step of receiving a first radio resource control (RRC) message from a base station, comprising first information instructing a load reduction operation for a radio resource management (RRM) measurement and second information related to an RRM measurement beam setting—the second information includes an associated ID (identity) for identifying a beam setting of similar characteristics—; A step of verifying the applicability of an AI (artificial intelligence) model for RRM measurement based on the associated ID; and Based on the first RRC message, the method includes the step of transmitting a second RRC message to the base station, the second RRC message including information indicating the confirmed availability. A method of a terminal characterized in that the above-mentioned associated ID is indicated to a measurement object (MO) set to perform the above-mentioned RRM measurement.

2. In Paragraph 1, If it is confirmed that the above AI model is available, a step of obtaining measurement results for the above RRM measurement using the above AI model; and The method further includes the step of transmitting information about the measurement result to the base station based on a report setting associated with the MO, and A method of a terminal characterized in that the above measurement result is obtained by inputting measurement values ​​for at least some of the multiple beams identified based on the above RRM measurement beam setting into the AI ​​model.

3. In Paragraph 2, The above first RRC message further includes third information regarding the rate at which the load of the RRM measurement is reduced, and A method of a terminal characterized in that at least some of the beams are determined based on the third information.

4. In Paragraph 2, The method further includes the step of transmitting terminal capability information to the base station indicating whether the load reduction operation of the RRM measurement is supported. The above terminal capability information includes at least one of an indicator indicating whether to support a prediction operation of cell measurement results based on measurement values ​​for at least some beams, or an indicator indicating whether to support a prediction operation of measurement results for the remaining beams based on measurement values ​​for at least some beams. The above first RRC message includes an RRC reset message, and A method of a terminal characterized in that the above-mentioned second RRC message includes an RRC reset completion message or a UE (user equipment) assistance information message.

5. In a wireless communication system, regarding the method of a base station, A step of transmitting a first radio resource control (RRC) message to a terminal, the message comprising first information instructing a load reduction operation for a radio resource management (RRM) measurement and second information related to an RRM measurement beam setting, wherein the second information includes an associated ID (identity) for identifying a beam setting of similar characteristics; and The method includes the step of receiving a second RRC message from the terminal, which includes information indicating the applicability of an AI (artificial intelligence) model for RRM measurement based on the first RRC message. A method of a base station characterized in that the above-mentioned associated ID is indicated for a measurement object (MO) set to perform the above-mentioned RRM measurement.

6. In Paragraph 5, The method further includes the step of receiving information regarding the measurement results of the RRM measurement from the terminal based on the reporting settings associated with the MO. A method of a base station characterized by the above measurement result being obtained based on the measurement value for at least some of the beams among the plurality of beams associated with the RRM measurement beam setting and the AI ​​model.

7. In Paragraph 6, The above first RRC message further includes third information regarding the rate at which the load of the RRM measurement is reduced, and A method of a base station characterized in that at least some of the beams are determined based on the third information.

8. In Paragraph 6, The method further includes the step of receiving terminal capability information from the terminal indicating whether the load reduction operation of the RRM measurement is supported. The above terminal capability information includes at least one of information indicating whether to support a prediction operation of cell measurement results based on measurement values ​​for at least some beams, or information indicating whether to support a prediction operation of measurement results for the remaining beams based on measurement values ​​for at least some beams. The above first RRC message includes an RRC reset message, and A method of a base station characterized in that the above-mentioned second RRC message includes an RRC reset completion message or a UE (user equipment) assistance information message.

9. In a wireless communication system, regarding a terminal, Transmitter / receiver; and The control unit controls the transceiver to receive a first radio resource control (RRC) message from a base station, the first information instructing a load reduction operation for a radio resource management (RRM) measurement and the second information related to an RRM measurement beam setting, wherein the second information includes an associated ID (identity) for identifying a beam setting of similar characteristics, the control unit checks the applicability of an artificial intelligence (AI) model for the RRM measurement based on the associated ID, and the control unit to transmit a second RRC message to the base station, the second RRC message including information instructing the checked applicability based on the first RRC message. A terminal characterized in that the above-mentioned associated ID is indicated to a measurement object (MO) set to perform the above-mentioned RRM measurement.

10. In Paragraph 9, The above control unit is, When it is confirmed that the above AI model is available, the above AI model is used to obtain measurement results for the above RRM measurement, and the above transceiver is controlled to transmit information about the measurement results to the above base station based on the reporting settings associated with the above MO. A terminal characterized in that the above measurement result is obtained by inputting measurement values ​​for at least some of the multiple beams identified based on the above RRM measurement beam setting into the AI ​​model.

11. In Paragraph 9, The above first RRC message further includes third information regarding the rate at which the load of the RRM measurement is reduced, and A terminal characterized in that the control unit determines at least some of the beams based on the third information.

12. In Paragraph 9, The above control unit controls the transceiver to transmit terminal capability information to the base station indicating whether to support the load reduction operation of the RRM measurement, and The above terminal capability information includes at least one of an indicator indicating whether to support a prediction operation of cell measurement results based on measurement values ​​for at least some beams, or an indicator indicating whether to support a prediction operation of measurement results for the remaining beams based on measurement values ​​for at least some beams. The above first RRC message includes an RRC reset message, and A terminal characterized in that the above second RRC message includes an RRC reset completion message or a UE (user equipment) assistance information message.

13. In a wireless communication system, regarding a base station, Transmitter / receiver; and The apparatus comprises a control unit that controls the transceiver to transmit a first radio resource control (RRC) message to a terminal, the first information indicating a load reduction operation for RRM (radio resource management) measurement and second information related to an RRM measurement beam setting, wherein the second information includes an associated ID (identity) for identifying a beam setting of similar characteristics, and controls the transceiver to receive a second RRC message from the terminal, the second RRC message including information indicating the applicability of an AI (artificial intelligence) model for the RRM measurement based on the first RRC message. A base station characterized in that the above-mentioned associated ID is indicated for a measurement object (MO) set to perform the above-mentioned RRM measurement.

14. In Paragraph 13, The above first RRC message further includes third information regarding the rate at which the load of the RRM measurement is reduced, and The control unit controls the transceiver to receive information regarding the measurement result of the RRM measurement from the terminal based on the reporting setting associated with the MO, and The above measurement result is obtained based on the measurement values ​​for at least some of the beams among the plurality of beams associated with the RRM measurement beam setting and the AI ​​model, and A method of a base station characterized in that at least some of the beams are determined based on the third information.

15. In Paragraph 13, The above control unit controls the transceiver to receive terminal capability information from the terminal indicating whether to support a load reduction operation of the RRM measurement, and The above terminal capability information includes at least one of information indicating whether to support a prediction operation of cell measurement results based on measurement values ​​for at least some beams, or information indicating whether to support a prediction operation of measurement results for the remaining beams based on measurement values ​​for at least some beams. The above first RRC message includes an RRC reset message, and A base station characterized in that the above second RRC message includes an RRC reset completion message or a UE (user equipment) assistance information message.

Images