Method and device for reducing cell measurement load of terminal by using artificial intelligence and machine learning in wireless communication system

Abstract

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

Description

Method and device for reducing cell measurement load of terminals using artificial intelligence and machine learning in wireless communication systems

[0001] The present disclosure relates to a method and device for reducing 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 the sub-6GHz frequency band such as 3.5 gigahertz (3.5GHz), but also in the ultra-high frequency band called millimeter wave (mmWave) such as 28GHz and 39GHz ('Above 6GHz'). In addition, for 6G mobile communication technology, which is called the system after 5G communication (Beyond 5G), implementation in the terahertz band (for example, the 3 terahertz (3THz) band at 95GHz) is being considered to achieve a transmission speed that is 50 times faster than 5G mobile communication technology and an ultra-low latency time that is reduced to one-tenth.

[0003] In the early stages of 5G mobile communication technology, the goal is to support services and satisfy performance requirements for enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communications (URLLC), and massive Machine-Type Communications (mMTC). These include beamforming and massive MIMO to mitigate path loss of radio waves in ultra-high frequency bands and increase the transmission distance of radio waves, support for various numerologies (such as operation of multiple subcarrier intervals) and dynamic operation of slot formats for efficient use of ultra-high frequency resources, initial access technology to support multi-beam transmission and wideband, definition and operation of BWP (Bidth Part), new channel coding methods such as LDPC (Low Density Parity Check) codes for large-capacity data transmission and Polar Code for reliable transmission of control information, and L2 pre-processing (L2). Standardization has been made for network slicing, which provides dedicated networks specialized for specific services, and pre-processing.

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

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

[0006] Once these 5G mobile communication systems are commercialized, an explosive increase in connected devices will be connected to the communication network, necessitating enhanced functionality and performance of 5G mobile communication systems and integrated operation of these connected devices. To this end, new research will be conducted on improving 5G performance and reducing complexity, supporting AI services, supporting metaverse services, and drone communications by utilizing eXtended Reality (XR), Artificial Intelligence (AI), and Machine Learning (ML) to efficiently support Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR).

[0007] In addition, the development of these 5G mobile communication systems includes new waveforms to ensure coverage in the terahertz band of 6G mobile communication technology, multi-antenna transmission technologies such as Full Dimensional MIMO (FD-MIMO), Array Antenna, and Large Scale Antenna, metamaterial-based lenses and antennas to improve the coverage of terahertz band signals, high-dimensional spatial multiplexing technology using Orbital Angular Momentum (OAM), Reconfigurable Intelligent Surface (RIS) technology, as well as full duplex technology to improve the frequency efficiency and system network of 6G mobile communication technology, satellite, AI (Artificial Intelligence) from the design stage and AI-based communication technology that realizes system optimization by internalizing end-to-end AI support functions, and ultra-high-performance communication and computing resources to provide services with complexity that exceeds the limits of terminal computing capabilities. It can serve as a basis for the development of next-generation distributed computing technologies that can be realized by utilizing them.

[0008] Based on the discussion described above, the present disclosure provides a device and method capable of effectively providing a service in a next-generation wireless communication system.

[0009] In addition, the present disclosure provides a method and device for reducing cell measurement load of a terminal by using artificial intelligence and machine learning in a mobile communication system.

[0010] In order to solve the above problem, the present disclosure provides a method performed by a terminal in a wireless communication system, the method comprising: receiving a first message including an RRM (radio resource management) prediction setting from a base station; the RRM prediction setting including configuration information for a cell for predicting a cell measurement result; transmitting a second message including information on a prediction model applicable for predicting the cell measurement result to the base station based on the first message; receiving a third message including an indicator for activating prediction of the cell measurement result from the base station based on the second message; and performing an RRM operation using prediction of the cell measurement result based on the third message.

[0011] In addition, one embodiment of the present disclosure provides a method performed by a base station in a wireless communication system, the method comprising: transmitting a first message including an RRM (radio resource management) prediction setting to a terminal; the RRM prediction setting including configuration information for a cell for predicting a cell measurement result; receiving a second message from the terminal including information on a prediction model applicable for predicting the cell measurement result based on the first message; and transmitting a third message including an indicator for activating prediction of the cell measurement result based on the second message to the terminal, wherein an RRM operation is performed using prediction of the cell measurement result based on the third message.

[0012] In addition, one embodiment of the present disclosure provides a terminal in a wireless communication system, comprising: a memory storing instructions for receiving, from a base station, a first message including an RRM (radio resource management) prediction configuration, the RRM prediction configuration including configuration information for a cell for prediction of a cell measurement result, transmitting to the base station a second message including information for a prediction model applicable for prediction of the cell measurement result based on the first message, receiving, from the base station, a third message including an indicator for activating prediction of the cell measurement result, and performing an RRM operation using prediction of the cell measurement result based on the third message.

[0013] In addition, one embodiment of the present disclosure provides a base station of a wireless communication system, comprising: a memory storing instructions for causing a terminal to transmit a first message including an RRM (radio resource management) prediction configuration to the terminal, the RRM prediction configuration including configuration information for a cell for prediction of a cell measurement result, and to receive a second message from the terminal including information for a prediction model applicable for prediction of the cell measurement result based on the first message, and to transmit a third message including an indicator for activating prediction of the cell measurement result based on the second message to the terminal, wherein the base station performs an RRM operation using prediction of the cell measurement result based on the third message.

[0014] The present disclosure provides a device and method capable of effectively providing a service in a next-generation wireless communication system.

[0015] According to various embodiments of the present disclosure, an improved method of operating a terminal and a base station in a wireless communication system can be provided.

[0016] Additionally, various embodiments of the present disclosure may provide a method for reducing cell measurement load using artificial intelligence and machine learning.

[0017] FIG. 1 is a diagram illustrating the structure of an NR system according to one embodiment of the present disclosure.

[0018] FIG. 2 is a diagram illustrating a wireless protocol structure in an LTE and NR system according to one embodiment of the present disclosure.

[0019] FIG. 3 is a diagram illustrating a use case of utilizing an AI / ML model to predict cell measurement results in a next-generation mobile communication system according to one embodiment of the present disclosure.

[0020] FIG. 4 is a diagram illustrating a specific method for utilizing an AI / ML model to predict cell measurement results in a next-generation mobile communication system according to one embodiment of the present disclosure.

[0021] FIG. 5 is a flowchart of a process in which a base station instructs a terminal to predict a cell measurement result and the terminal performs a cell measurement result prediction operation according to the base station instruction, according to one embodiment of the present disclosure.

[0022] FIG. 6 is a diagram illustrating a method for a terminal to utilize cell measurement prediction results in RRM (radio resource management) operations to reduce cell measurement load, according to one embodiment of the present disclosure.

[0023] FIG. 7 is a diagram illustrating a terminal according to one embodiment of the present disclosure.

[0024] FIG. 8 is a diagram illustrating a base station according to one embodiment of the present disclosure.

[0025] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the attached drawings. Furthermore, detailed descriptions of related known functions or configurations will be omitted if they are deemed to unnecessarily obscure the gist of the present disclosure. Furthermore, the terms described below are defined based on their functions in the present disclosure and may vary depending on the intent or custom of the user or operator. Therefore, their definitions should be based on the overall content of this specification.

[0026] The advantages and features of the present disclosure, and methods for achieving them, will become clearer with reference to the embodiments described in detail below together with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below and may be implemented in various different forms. These embodiments are provided solely to ensure that the disclosure of the present 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. Like reference numerals refer to like elements throughout the specification.

[0027] At this time, it will be understood that each block of the processing flowchart drawings and combinations of the flowchart drawings can be performed by computer program instructions. These computer program instructions can be installed in a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing equipment, so that the instructions executed by the processor of the computer or other programmable data processing equipment create a means for performing the functions described in the flowchart block(s). These computer program instructions can also be stored in a computer-available or computer-readable memory that can direct a computer or other programmable data processing equipment to implement the functions in a specific manner, so that the instructions stored in the computer-available or computer-readable memory can also produce a manufactured item that includes an instruction means for performing the functions described in the flowchart block(s). Since the computer program instructions may be installed on a computer or other programmable data processing device, a series of operational steps may be performed on the computer or other programmable data processing device to create a computer-executable process, and the instructions that cause the computer or other programmable data processing device to perform the steps for performing the functions described in the flowchart block(s) may also provide steps for performing the functions described in the flowchart block(s).

[0028] Additionally, each block may represent a module, segment, or portion of code that contains one or more executable instructions for performing a specific logical function(s). It should also be noted that in some alternative implementation examples, the functions described in the blocks may occur out of order. For example, two blocks depicted in succession may actually be executed substantially concurrently, or the blocks may sometimes be executed in reverse order, depending on their respective functions.

[0029] Here, the term '~ part' used in this embodiment means software or hardware components such as FPGA (Field Programmable Gate Array) or ASIC (Application Specific Integrated Circuit), and the '~ part' performs certain roles. However, the '~ part' is not limited to software or hardware. The '~ part' may be configured to be on an addressable storage medium or may be configured to play one or more processors. Therefore, as an example, the '~ part' includes components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, 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'. Additionally, the components and '~parts' may be implemented to activate one or more CPUs within a device or secure multimedia card. In addition, in an embodiment, the '~parts' may include one or more processors.

[0030] In the following description of the present disclosure, detailed descriptions of related known functions or configurations will be omitted if they are deemed to unnecessarily obscure the gist of the present disclosure. Hereinafter, embodiments of the present disclosure will be described with reference to the attached drawings.

[0031] The 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 provided as examples for convenience of explanation. Therefore, the present disclosure is not limited to the terms described below, and other terms referring to objects with equivalent technical meanings may be used.

[0032] In the following description, the terms "physical channel" and "signal" may be used interchangeably with data or control signals. For example, while PDSCH (physical downlink shared channel) refers to a physical channel through which data is transmitted, PDSCH can also be used to refer to data. That is, in the present disclosure, the expression "transmitting a physical channel" can be interpreted equivalently to the expression "transmitting data or a signal through a physical channel."

[0033] Hereinafter, in the present disclosure, upper signaling refers to a signal transmission method in which a base station transmits a signal to a terminal using a downlink data channel of the physical layer, or a terminal transmits a signal to a base station using an uplink data channel of the physical layer. Upper signaling can be understood as radio resource control (RRC) signaling or a media access control (MAC) control element (CE).

[0034] For the convenience of explanation below, this disclosure uses terms and names defined in the 3rd Generation Partnership Project NR (New Radio) or 3rd Generation Partnership Project Long Term Evolution (LTE) standards. However, this disclosure is not limited by the above terms and names, and can be equally applied to systems conforming to other standards. In this disclosure, gNB may be used interchangeably with eNB for the convenience of explanation. That is, a base station described as an eNB may represent a gNB. In addition, the term terminal may represent not only a mobile phone, an MTC device, an NB-IoT device, a sensor, but also other wireless communication devices.

[0035] Hereinafter, the base station is an entity that performs resource allocation of a terminal, and may be at least one of a gNodeB (gNB), an eNode B (eNB), a NodeB, a BS (Base Station), a wireless access unit, a base station controller, or a node on a network. The terminal may include a UE (user equipment), an MS (mobile station), a cellular phone, a smartphone, a computer, or a multimedia system capable of performing a communication function. Of course, the present invention is not limited to the above examples.

[0036] FIG. 1 is a diagram illustrating the structure of an NR system according to one embodiment of the present disclosure.

[0037] 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 equipment (hereinafter referred to as UE or terminal) (135) may access an external network through the base stations (e.g., gNB (105), ng-eNB (110), ng-eNB (115), gNB (120)) and the UPF (130).

[0038] In Fig. 1, base stations (e.g., gNB (105), ng-eNB (110), ng-eNB (115), gNB (120)) can serve as access nodes of a cellular network and provide wireless access to terminals accessing the network. That is, the base stations (e.g., gNB (105), ng-eNB (110), ng-eNB (115), gNB (120)) can collect status information such as buffer status, available transmission power status, and channel status of terminals to schedule them in order to service user traffic, thereby supporting a connection between the terminals and a core network (CN; in particular, the CN of NR is referred to as 5GC). Meanwhile, in communication, a user plane (UP) related to transmission of actual user data and a control plane (CP) such as connection management can be configured separately, and in this drawing, gNB (105) and gNB (120) use UP and CP technologies defined in NR technology, and ng-eNB (110) and ng-eNB (115) can use UP and CP technologies defined in LTE technology even though they are connected to 5GC.

[0039] The above AMF (125) is a device that handles various control functions as well as mobility management functions for terminals 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 illustrated in Fig. 1, the NR wireless communication system may also include a Session Management Function (SMF). The SMF can manage packet data network connections, such as PDU (protocol data unit) sessions provided to terminals.

[0040] FIG. 2 is a diagram illustrating a wireless protocol structure in an LTE and NR system according to one embodiment of the present disclosure.

[0041] Referring to FIG. 2, the wireless protocol of the LTE system may be composed of PDCP (packet data convergence protocol) (205)(240), RLC (radio link control) (210)(235), and MAC (medium access control) (215)(230) in the terminal and eNB, respectively. PDCP (205)(240) is responsible for operations such as IP header compression / decompression, and (RLC) (210)(235) reconfigures PDCP PDU (protocol data unit) to an appropriate size. MAC (215)(230) is connected to multiple RLC layer devices configured in one terminal, and performs operations of multiplexing RLC PDUs into MAC PDUs and demultiplexing RLC PDUs from MAC PDUs. The physical (PHY) layer (220)(225) performs an operation of channel coding and modulating upper layer data, converting it into an OFDM (orthogonal frequency division multiplexing) symbol and transmitting it through a wireless channel, or demodulating and channel decoding an OFDM symbol received through a wireless channel and transmitting it to a higher layer. In addition, the physical layer also uses HARQ (hybrid automatic repeat request) for additional error correction, and the receiver transmits 1 bit to indicate whether the packet transmitted by the transmitter has been received. This is called HARQ ACK / NACK information. In the case of LTE, the downlink HARQ ACK / NACK information for uplink data transmission is transmitted through a physical hybrid-ARQ indicator channel (PHICH) physical channel, and in the case of NR, the PDCCH (physical downlink control channel), which is a channel through which downlink / uplink resource allocation, etc. are transmitted, can determine whether retransmission is necessary or new transmission can be performed through the scheduling information of the corresponding terminal. This is because NR applies asynchronous HARQ.Uplink HARQ ACK / NACK information for downlink data transmission can be transmitted via a physical uplink control channel (PUCCH) or a physical uplink shared channel (PUSCH). The PUCCH is generally transmitted in the uplink of the PCell, which will be described later. However, if the UE supports it, the base station may additionally transmit it to the SCell, which will be described later, and this is called a PUCCH SCell.

[0042] Although not shown in this drawing, an RRC (Radio Resource Control) layer exists above the PDCP layer of each terminal and base station, and the RRC layer can exchange connection and measurement-related setting control messages for radio resource control.

[0043] 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 (CA). CA technology can dramatically increase the transmission capacity by additionally using a primary carrier and one or more secondary carriers for communication between a terminal and a base station (base station, E-UTRAN NodeB, eNB, gNB), rather than using only one carrier. Meanwhile, a cell within a base station that uses a primary 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).

[0044]

[0045] FIG. 3 is a diagram illustrating a use case of utilizing an AI / ML model to predict cell measurement results in a next-generation mobile communication system according to one embodiment of the present disclosure.

[0046] Referring to FIG. 3, the AI / ML model can be utilized to predict cell measurement results in the time domain. For reference, the cell measurement results may refer to RSRP (reference signal received power) / RSRQ (reference signal received quality) / SINR (signal-to-interference-plus-noise ratio) values ​​measured by the terminal for each cell. In addition, the cell measurement results may include RSRP / RSRQ / SINR values ​​measured by the terminal for each beam when there are multiple beams transmitted by the cell for each cell. In addition, the RSRP / RSRQ / SINR values ​​may refer to one of the following values.

[0047] - RSRP and / or RSRQ and / or SINR measured at Layer 1

[0048] - RSRP and / or RSRQ and / or SINR measured / obtained at Layer 3

[0049] - A filtered value of RSRP and / or RSRQ and / or SINR measured at Layer 1 (e.g., a (weighted) average value using the measured values ​​over a given period of time)

[0050] - A filtered value of RSRP and / or RSRQ and / or SINR measured / obtained at Layer 3 (e.g., a (weighted) average value using the measured values ​​over a given period of time)

[0051] The meaning (or definition) of the above cell measurement results can be applied to the embodiments of FIGS. 4, 5, and 6 below.

[0052] When predicting cell measurement results in the time domain, when cell measurement results (305) obtained in the past (e.g., Mt cell measurement results measured during times t_k-Mt to t_k) are input to the AI / ML model (300), the AI / ML model can be trained so that future cell measurement result prediction results (310) (e.g., Pt cell measurement results predicted during times t_k+1 to t_k+Pt) are output as the model's output.

[0053] According to an embodiment of the present disclosure, the AI / ML model for predicting cell measurement results in the aforementioned time domain can be used at the terminal and / or the base station. When the AI / ML model for predicting cell measurement results is used (or inferred) at the base station, the base station can instruct the terminal to report past cell measurement results (305) required as input to the AI / ML model (300) for predicting cell measurement results. Thereafter, the base station can perform a model inference operation using the corresponding input data and obtain a future cell measurement result prediction result (310) as an output of the model output model. Conversely, when the AI / ML model for predicting cell measurement results is used (or inferred) at the terminal, the terminal can obtain past cell measurement results (305) required as input to the AI / ML model (300) for predicting cell measurement results on its own. Thereafter, the terminal can perform a model inference operation using the input data and obtain a future cell measurement result prediction result (310) as the output of the model output model. The base station can set / instruct the terminal to perform the cell measurement result prediction operation and report the result value.

[0054] The predicted future cell measurement results in the time domain can be used for two main purposes.

[0055] The first objective is to improve the mobility (e.g., handover) performance of terminals. Based on predicted future cell measurement results, the base station can predict the optimal cell for a fast-moving terminal in advance and hand the terminal over to the optimal cell at an appropriate time. More specifically, the base station can periodically receive measurement reports from the terminal, receive cell measurement results, and hand the terminal over to the optimal cell based on these. However, depending on the cell measurement result reporting cycle (measurement report transmission cycle), the actual channel environment may change, resulting in a delay between the time the optimal cell changes and the time the base station actually receives the measurement report from the terminal and determines the change. Furthermore, if the terminal is moving rapidly, this delay in cell measurement result changes can cause a handover failure. For example, the delay between the time the base station receives the measurement report from the terminal, decides to hand the terminal over, and requests and receives approval from the neighboring base station corresponding to the handover target cell can prevent the terminal from handing over at an appropriate time, and the terminal may fall into a Radio Link Failure (RLF) state. To improve these problems, the base station can predict the optimal cell change of the terminal in advance based on the predicted cell measurement results in the time domain and prevent handover failure by handing over the terminal at an appropriate time.

[0056] The second purpose is to reduce the measurement overhead of the terminal. The terminal can reduce the cell measurement overhead while maintaining the handover performance by skipping the cell measurement performed every SSB (synchronization signal block) cycle (Tper) and replacing the cell measurement value at that point with the predicted cell measurement result. More specifically, the terminal can measure the cell signal strength every SSB cycle and perform RRM-related operations based on the measured value. The RRM operation may include operations such as RRM measurement event detection and reporting, and RLF detection. Instead of using the measured result value every SSB cycle Tper for the RRM operation, the terminal can skip the SSB measurement once in the middle and use the measured result value every 2*Tper. If the RRM operation is performed only with the measured result value every 2*Tper as described above, the cell measurement load of the terminal is reduced by 50%, but the accuracy of the RRM operation may decrease. For example, measurement events and RLFs may not be detected in a timely manner. This can ultimately lead to degraded handover performance. Therefore, to reduce the cell measurement burden while preventing handover performance degradation, the terminal can predict cell measurement results at the point where measurements were skipped and use these results for RRM operations. This allows the terminal to reduce the cell measurement load without degrading the terminal's handover performance.

[0057] In the following drawings 5 ​​and 6 of the present disclosure, specific embodiments are described regarding a method and procedure in which a base station instructs a terminal to predict cell measurement results and the terminal performs an RRM operation using the predicted results in a scenario in which an AI / ML model for predicting cell measurement results is used at the terminal end for the second purpose (reducing the measurement load of the terminal). The above-described purposes are merely representative examples of purposes that can be implemented when various embodiments of the present disclosure are applied, and the purpose of the present disclosure is not limited thereto, and various effects can be implemented based on measurement mitigation using AI / ML.

[0058] FIG. 4 is a diagram illustrating a specific method for utilizing an AI / ML model to predict cell measurement results in a next-generation mobile communication system according to one embodiment of the present disclosure.

[0059] Referring to Fig. 4, the following methods can be considered as specific cases of utilizing AI / ML models to predict cell measurement results.

[0060] - Method 1 (case 1) (400, without measurement reduction): The terminal can predict future Pt measurement results (415) in the prediction window section based on Mt measurement results (410) measured in the observation window section using an AI / ML model. At this time, the terminal can perform cell measurement every Tper through SSB or CSI-RS (channel state information - reference signal) transmitted every Tper. For every Tper, the terminal can predict the cell measurement result by sliding the observation window and prediction window by 1 Tper. In other words, the terminal performs cell measurement every Tper and can predict future cell measurement results. In this case, there is no effect of reducing the measurement load at the terminal end, but the effect of optimizing HO performance based on future cell measurement results can be expected. Since the terminal can obtain the actual measured cell measurement results for each Tper as before and use them for RRM operation, the cell measurement result prediction operation described above may not affect the RRM operation.

[0061] Method 2-1 (case 2-1) (420, with measurement reduction): The terminal can predict future Pt measurement results (435) in the prediction window based on Mt measurement results (430) measured in the observation window using an AI / ML model. At this time, the terminal can measure SSB or CSI-RS transmitted every Tper (425) only in the observation window. Unlike method 1, the terminal performs cell measurements only in the observation window and can predict cell measurement results in the prediction window without performing actual cell measurements. In other words, in the time domain, the observation window and the prediction window can alternately intersect without sliding every Tper. In this case, since the terminal does not perform actual cell measurements in the prediction window, the measurement load at the terminal can be reduced. At this time, the measurement load reduction rate of the terminal can be calculated / expressed as 'Pt / Mt+Pt'. However, unlike conventional methods, the terminal does not perform cell measurements within the prediction window instead of measuring cells every Tper. Therefore, the predicted behavior based on these cell measurement results may impact the existing RRM operation. In other words, it may degrade the handover performance of the terminal. Therefore, the terminal can prevent the handover performance degradation due to the reduced cell measurement load by using the predicted cell measurement results within the prediction window, where actual cell measurements are not performed, for the existing RRM operation.

[0062] Method 2-2 (case 2-2) (440, with measurement reduction): The terminal can predict the cell measurement result at Tper intervals (450) based on the result of performing cell measurement at Tper' intervals using an AI / ML model (445). At this time, the terminal can reduce the cell measurement load by measuring the SSB or CSI-RS transmitted at every Tper at an interval of Tper' that is a multiple of Tper. At this time, the measurement load reduction rate of the terminal can be calculated / expressed as Tper / Tper'. However, since the terminal measures the cell at every Tper' instead of every Tper, unlike the existing method, this may affect the RRM operation performed based on the result measured at every Tper. In other words, it may degrade the handover performance of the terminal. Therefore, the terminal can prevent the deterioration of handover performance due to the reduction of the cell measurement load by using the cell measurement result predicted at a time when actual cell measurement is not performed in the existing RRM operation.

[0063] In the following drawings 5 ​​and 6 of the present disclosure, specific embodiments are described for a method and procedure in which a base station instructs a terminal to predict a cell measurement result and the terminal performs an RRM operation using the predicted result in a scenario in which a cell measurement result prediction AI / ML model is used at the terminal to predict the cell measurement result of the above-described method 2-1 and method 2-2.

[0064] FIG. 5 is a flowchart of a process in which a base station instructs a terminal to predict a cell measurement result and the terminal performs a cell measurement result prediction operation according to the base station instruction, according to one embodiment of the present disclosure.

[0065] Referring to FIG. 5, the terminal (500) reports to the base station (505) whether it supports the cell measurement result prediction function, and if the terminal (500) supports the function, the base station (505) can instruct cell measurement result prediction. Thereafter, the terminal (500) can predict future cell measurement results based on past cell measurement results according to the instruction of the base station (505) and use the predicted results for RRM operation. Here, the RRM operation may mean an 'Event-triggered' or 'periodical' type Measurement Reporting operation and an operation such as RLF detection. The specific step-by-step signaling and operation between the terminal (500) and the base station (505) for the above-described operations can be described as follows.

[0066] In step 510, the base station (505) and the terminal (500) can exchange terminal capability information related to cell measurement result prediction. Upon receiving a terminal capability information report request from the base station, the terminal can report the terminal capability information to the base station. For example, the terminal (500) can transmit to the base station (505) a combination of at least one of the following indicators indicating terminal capability information related to cell measurement prediction (i.e., RRM measurement prediction) within an RRC message (e.g., a UECapabilityInformation message).

[0067] - Indicator indicating whether RRM measurement prediction (without measurement reduction) is supported: If the terminal (500) supports the cell measurement result prediction operation corresponding to method 1 (400) of the above-mentioned FIG. 4, the terminal (500) may include the corresponding indicator in the RRC message (or set it to a True / Supported value) and transmit it to the base station (505). For reference, the cell measurement result prediction operation may mean an operation of predicting RSRP / SINR / RSRQ measurement results for each cell / beam. More specifically, the indicator may indicate whether the terminal (500) can predict future cell measurement results and report them to the base station (505).

[0068] - Indicator indicating whether RRM measurement prediction (with measurement reduction) is supported: If the terminal (500) supports the cell measurement result prediction operation corresponding to the method 2-1 (420) and method 2-2 (440) of FIG. 4, the terminal (500) may include the corresponding indicator in the RRC message (or set it to a True / Supported value) and transmit it to the base station (505). For reference, the cell measurement result prediction operation may mean an operation of predicting RSRP / SINR / RSRQ measurement results for each cell / beam. More specifically, the indicator may indicate whether the terminal (500) can predict future cell measurement results and use them for the existing RRM operation.

[0069] Additionally, a common indicator may be used to indicate whether the terminal capabilities indicated by the two indicators above are combined to support operations of predicting future cell measurement results and reporting them to the base station (500) and using the predicted results in existing RRM operations.

[0070] For reference, the terminal (500) can report the terminal capability information described above to the base station (505) in units of terminal, frequency range, frequency band, or feature set combination.

[0071] By predicting cell measurement information using methods 2-1 and 2-2 of the above-described FIG. 4, the terminal (500) can reduce the cell measurement load. However, even if the terminal (500) skips cell measurement, which was previously performed at every Tper, and replaces the cell measurement result at that point with the predicted result, if the accuracy of the AI / ML-based cell measurement result prediction is not guaranteed to be above a certain level, the handover performance of the terminal (500) may deteriorate. At this time, the cell measurement load reduction rate (R) of the terminal (500) and the cell measurement result prediction accuracy may have a complementary (trade-off) relationship. For example, as the cell measurement load reduction rate of the terminal (500) increases, the terminal (500) must predict future cell measurement results based on more intermittently measured results, and thus the cell measurement result prediction accuracy may decrease. At this time, the accuracy of the cell measurement result can be expressed as RSRP / RSRQ / SINR difference (the difference between the actually measured value and the predicted value at the same point in time). Considering this complementary relationship, the terminal (500) can ensure the accuracy of the cell measurement result above a certain level (e.g., ensure that the RSRP difference is lower than a specific threshold) and maintain the handover performance by using a model with an appropriate level of cell measurement load reduction ratio. For reference, the cell measurement load reduction ratio and the guaranteeable prediction accuracy (i.e., RSRP difference) can be determined by the AI / ML model that the terminal will use to predict the corresponding cell measurement result. According to an embodiment of the present disclosure, the terminal (500) may have multiple available AI / ML models for predicting the cell measurement result.In order to enable the terminal (500) to use a model having an appropriate level of cell measurement load reduction ratio to predict cell measurement results, one of the following two methods may be considered.

[0072] - Method 1 (120, the method in which the base station determines the measurement reduction rate R)

[0073] In step 521, the base station (505) can transmit the initial settings for method 2-1 or method 2-2 of FIG. 4 to the terminal (500). The base station (505) can transmit an RRM prediction configuration including the initial settings to the terminal (500). The initial settings can include a target cell setting for predicting cell measurement results, a reporting setting for cell measurement prediction results, a prediction window length, etc. In addition, the base station (505) can include multiple cell measurement result prediction settings for multiple cells. In this case, each prediction setting can be linked to a specific ID value for indicating it. A predetermined RRC message (e.g., RRCReconfiguration) can be used for the settings.

[0074] In step 523, the terminal (500) can report to the base station (505) information about AI / ML models that can be used to perform the cell measurement result prediction operation according to the cell prediction setting in step 521. More specifically, the terminal (500) can report to the base station (505) the measurement reduction rate and the guaranteed RSRP / RSRQ / SINR difference value for each AI / ML model (or option) that can be used to perform the cell measurement result prediction operation. When the terminal (500) has a plurality of AI / ML models that can be used to perform the cell measurement result prediction operation, the terminal (500) can report to the base station (505) a list including the measurement reduction rate and the guaranteed RSRP / RSRQ / SINR difference value for each of the plurality of models (or options). Each item of the list can include the measurement reduction rate and the guaranteed RSRP / RSRQ / SINR difference value for each model. When the terminal (500) reports information on multiple models (or options) to the base station (505) in a list format, the list may include information corresponding to each model in order of preference for each model. At this time, a model (option) ID may be used to indicate each model (or option) within the list. A predetermined RRC message (e.g., UEAssistanceInformation) may be used for the above reporting.

[0075] In step 525, the base station (505) can set / activate a cell measurement result prediction operation for reducing the cell measurement load for the terminal (500) based on the information reported by the terminal (500) in step 523. To this end, an indicator for activating the cell measurement result prediction operation (or cell measurement load reduction operation) can be included / set in a message that the base station (505) transmits to the terminal (500). At this time, the base station (505) can select one of the available models (or options) reported by the terminal (500) in step 523 and instruct the terminal (500) to use the corresponding model (or option). The base station (505) can select a model (or option) with the largest measurement reduction rate R among models with a prediction accuracy that does not degrade handover performance (e.g., among models with an RSRP difference value below a specific level). A predetermined RRC message (e.g., RRCReconfiguration) or MAC CE may be used to set / activate the above cell measurement result prediction operation. When the terminal (500) is instructed to activate the above cell measurement result prediction operation (or cell measurement load reduction operation), the terminal (500) may determine a period in which it will not perform the cell measurement operation and perform the RRM operation with the predicted cell measurement result value for the period.

[0076] - Method 2 (530, method in which the terminal determines the measurement reduction rate R):

[0077] In step 531, the base station (505) may transmit the initial settings for method 2-1 or method 2-2 of FIG. 4 to the terminal (500). The base station (505) may transmit an RRM prediction configuration including the initial settings to the terminal (500). The initial settings may include a target cell setting for predicting cell measurement results, a reporting setting for cell measurement prediction results, a prediction window length, etc. In addition, the base station (505) may include a plurality of cell measurement result prediction settings for a plurality of cells. In this case, each prediction setting may be linked to a specific ID value for indicating it. In addition, the base station (505) may set a threshold value (e.g., tolerable RSRP difference threshold) of cell measurement result prediction accuracy that must be guaranteed at a minimum to prevent handover performance degradation of the terminal (500) to the terminal (500). Additionally, the base station (505) can indicate to the terminal (500) the range of the measurement load reduction rate (R) (e.g., the minimum and maximum values ​​of the R value) that is allowable for the terminal (500) when performing the cell measurement result prediction operation. The aforementioned prediction accuracy threshold and measurement load reduction rate range can be set in multiple numbers according to the location and movement speed of the terminal (500). For example, the terminal (500) can be divided into several sections based on the serving cell signal strength and movement speed, and a separate prediction accuracy threshold and measurement load reduction rate range can be set for each section. This is because the measurement load reduction rate and prediction accuracy threshold that the base station (505) can allow can be different depending on the status of the terminal (500). A predetermined RRC message (e.g., RRCReconfiguration) can be used for the above setting.

[0078] In step 533, the terminal (500) can report to the base station (505) whether or not the cell measurement result prediction operation can be performed according to the cell prediction setting in step 531. For this purpose, a 1-bit indicator indicating whether or not the cell measurement result prediction operation can be performed can be used. More specifically, if there is a model available for cell measurement result prediction according to the setting from the base station (505) received in step 531, the terminal (500) can report to the base station (505) including a 1-bit indicator indicating whether or not the cell measurement result prediction operation can be performed (or set to 'True' / 'Available' / 'Supported'). The terminal (500) can determine that there is a model available for cell measurement result prediction if at least one or more combinations of the following conditions are satisfied.

[0079] - Condition 1: The terminal must have a model that can be used to predict cell measurement results according to the cell prediction settings in step 531 above (e.g., target cell for cell measurement result prediction).

[0080] - Condition 2: If the base station sets a threshold value (e.g., tolerable RSRP difference threshold) for the cell measurement result prediction accuracy in step 531, at least one of the models possessed by the terminal must be able to guarantee an RSRP / RSRQ / SINR difference lower than the threshold value.

[0081] - Condition 3: If the base station sets a range of allowable measurement load reduction rates in step 531 above, at least one of the models possessed by the terminal must have a measurement reduction rate within that range.

[0082] If there is no model available for predicting cell measurement results according to the setting from the base station (505) in step 531, the terminal (500) may report to the base station (505) by omitting (or setting to 'False' / 'NotAvailable' / 'NotSupported') a 1-bit indicator indicating whether or not cell measurement result prediction operation can be performed.

[0083] Additionally, when the terminal (500) reports to the base station (505) a 1-bit indicator indicating whether the cell measurement result prediction operation can be performed (or set to 'True' / 'Available' / 'Supported'), it may also include additional information about the available model (e.g., measurement reduction rate and RSRP / RSRQ / SINR difference). A predetermined RRC message (e.g., UEAssistanceInformation) may be used for the report. Additionally, when the terminal (500) reports that the cell measurement result prediction operation cannot be performed, the base station (505) may return to step 531 and instruct the terminal (500) again with a threshold value for a new cell measurement result prediction accuracy (e.g., tolerable RSRP difference threshold). Thereafter, the terminal (500) may determine whether the cell measurement result prediction can be performed again based on the threshold value and report the result to the base station (505). Accordingly, the base station (505) and the terminal (500) can repeat the operations in steps 531 and 533 and discuss an appropriate model (or option) available for cell measurement result prediction operation.

[0084] In step 535, the base station (505) can set / activate a cell measurement result prediction operation for reducing the cell measurement load for the terminal (500) based on the information reported by the terminal (500) in step 533. To this end, an indicator for activating the cell measurement result prediction operation (or cell measurement load reduction operation) may be included / set in a message that the base station (505) transmits to the terminal (500). If multiple cell measurement result prediction settings are made in step 531, multiple indicators may be included / set for each setting to indicate activation for each setting. Alternatively, if multiple cell measurement result prediction settings are made in step 531 and each setting is associated with a specific ID value, an indicator defined in the form of a list or bit stream for indicating multiple setting IDs to be activated may be included / set to indicate activation for each setting. A predetermined RRC message (e.g., RRCReconfiguration) or MAC CE may be used to set / activate the cell measurement result prediction operation. When the terminal (500) is instructed to activate the cell measurement result prediction operation (or cell measurement load reduction operation), it can determine a section in which it will not perform the cell measurement operation and perform the RRM operation with the predicted cell measurement result value for that section.

[0085] When the terminal (500) performs cell measurement result prediction as in the method 2-1 and method 2-2 of the above-mentioned FIG. 4, the terminal (500) may not perform cell measurement every Tper (e.g., SSB cycle). When the terminal (500) performs the cell measurement result prediction operation, the cell measurement pattern may be determined by the model that the terminal (500) uses to predict the cell measurement result. Therefore, the base station (505) cannot know what pattern the terminal (500) actually has to measure the cell (in other words, at what point the cell measurement is actually performed and at what point the cell measurement is not performed). If the base station (505) can know the cell measurement pattern of the terminal (500), the base station (505) can use the information to optimize the cell measurement settings of the terminal (500), thereby improving the performance of the terminal (500) or reducing unnecessary base station transmission operations.

[0086] In an embodiment of the present disclosure, the base station (505) can optimize the measurement gap setting for the terminal (500) based on the cell measurement pattern information of the terminal (500). If the terminal (500) cannot hear the signal of the current serving cell in order to perform neighboring cell measurement, the base station (505) can set a measurement gap so that the terminal (500) can perform the necessary cell measurement operation without hearing the serving cell signal during a specific period (e.g., measurement gap). Therefore, the terminal (500) and the serving cell cannot exchange data during the measurement gap period. If the base station (505) can identify the cell measurement pattern information of the terminal (500), the measurement gap can be not set in the period in which the actual terminal (500) does not perform cell measurement, thereby minimizing the period in which data cannot be transmitted and received and improving the data transmission speed of the terminal (500).

[0087] In another embodiment, the base station (505) can minimize the number of transmissions of reference signals (e.g., CSI-RS) that the base station (505) must transmit to assist cell measurement of the terminal (500) based on the cell measurement pattern information of the terminal (500). For example, if the terminal (500) performs a cell measurement result prediction operation in a manner of reducing cell measurement load, such as methods 2-1 and 2-2 of FIG. 4, the base station (505) may not transmit CSI-RS every Tper. If the base station (505) can identify the cell measurement pattern information of the terminal (500), the transmission resources of the base station (505) can be saved by not transmitting CSI-RS when the terminal (500) does not perform cell measurement.

[0088] In order for the base station (505) to optimize the measurement gap setting and reference signal setting based on the cell measurement pattern information of the terminal (500) as in the above-described embodiments, the terminal (500) may report / provide cell measurement pattern information when performing the cell measurement result prediction operation to the base station (505). More specifically, the base station (505) may instruct the terminal (500) to report cell measurement pattern information while setting the cell measurement result prediction operation in steps 521 and 531. To this end, an indicator for instructing the cell measurement pattern information reporting operation may be included in the RRC message in steps 521 and 531. Thereafter, in steps 523 and 533, the terminal (500) may report actual cell measurement pattern information to the base station (505) when performing the cell measurement result prediction operation according to the setting of the base station (505). At this time, the cell measurement pattern information may mean information for reporting the section / time point at which the terminal (500) performs actual cell measurement when the terminal (500) performs a cell measurement result prediction operation according to methods 2-1 and 2-2 of the above-described FIG. 4. In addition, the cell measurement pattern information may be reported to the base station (505) in each cell measurement result prediction setting unit provided by the base station (505) in steps 521 and 531. The cell measurement pattern information may be composed of a combination of at least one of the following pieces of information.

[0089] - Tper: Information indicating the time interval during which actual cell measurement and cell measurement result prediction are performed in method 2-1 of the above-mentioned FIG. 4. It may be indicated in units such as subframe, slot, symbol, ms, etc. Alternatively, it may indicate the time interval during which cell measurement result prediction is performed in method 2-2 of the above-mentioned FIG. 4.

[0090] - Mt: Information indicating the length of the observation window in method 2-1 of the above-mentioned Fig. 4. It can be indicated by the number of cell measurement results included within the actual observation window.

[0091] - Pt: Information indicating the length of the prediction window in method 2-1 of the above-mentioned Fig. 4. It can be indicated by the number of cell measurement result predictions included within the actual prediction window.

[0092] - Tper': Or information indicating the time interval at which cell measurement is performed in method 2-2 of the above-mentioned FIG. 4. It can be indicated in units such as subframe, slot, symbol, ms, etc.

[0093] - Observation periodicity: Information indicating the period of the observation window in method 2-1 of the above-mentioned Figure 4. It can be indicated in units such as subframe, slot, symbol, and ms.

[0094] The base station (505) can provide the terminal (500) with a separate measurement gap setting and measurement setting (SMTC setting and CSI-RS setting) that can be used only when the cell measurement result prediction setting for reducing the cell measurement load is activated in steps 525 and 535 based on the cell measurement pattern information reported by the terminal (500). At this time, the measurement gap setting and the measurement setting can be linked to the cell measurement result prediction report setting for reducing the cell measurement load. When a specific cell measurement result prediction setting is activated, the terminal (500) can perform cell measurement according to the measurement gap setting and the measurement setting (SMTC setting and CSI-RS setting) linked to the setting, thereby reducing the cell measurement load.

[0095] In step 540, the terminal (500) performs a cell measurement result prediction operation (or a cell measurement load reduction operation) according to the instructions of the base station (505) in steps 525 and 535, and may perform an RRM operation by using both the actual cell measurement result and the predicted cell measurement result. Here, the RRM operation may mean an 'Event-triggered' or 'periodical' type Measurement Reporting operation and an operation such as RLF (Radio Link Failure) detection.

[0096] In an embodiment of the present disclosure, the base station (505) may set a 'periodical' measurement reporting operation in steps 525 and 535. In this case, the terminal (500) may be triggered to periodically transmit a measurement report.

[0097] In another embodiment, in steps 525 and 535, the base station (505) can set the measurement reporting operation in an 'Event-triggered' manner. In this case, the terminal (500) can determine whether the condition for a specific event (e.g., A2 event) set by the base station is satisfied based on the cell measurement result. If the cell measurement result prediction operation (or cell measurement load reduction operation) is set / activated together in steps 525 and 535, the terminal (500) can use the predicted cell measurement result as well as the actual cell measurement result to determine whether the condition for the event is satisfied. The specific operation of the terminal (500) using the predicted cell measurement result as well as the actual cell measurement result to determine whether the condition for a specific RRM measurement event (e.g., A2) set by the base station (505) is satisfied is described in the embodiment of FIG. 6 below, and reference is made thereto.

[0098] As described above, the terminal (500) can trigger measurement report transmission in a 'periodical' manner or an 'Event-triggered' manner at step 540.

[0099] In step 545, the terminal (500) can transmit a measurement report message to the base station (505). The measurement report message can include cell measurement results for serving and neighboring cells. If the cell measurement result prediction operation is not set in steps 525 and 535, the terminal (500) can report the last (recently) actually measured RSRP / RSRQ / SINR values ​​for each cell on a cell and beam basis. If the cell measurement result prediction operation (or cell measurement load reduction operation) is set / activated together in steps 525 and 535, the terminal (500) can include at least one combination of the following information in the measurement report for each cell and beam and report the result to the base station (505).

[0100] - Latest measurement: The most recent (or most recent) measured RSRP / RSRQ / SINR values ​​for each cell and beam can be included and reported to the base station based on the time of measurement report transmission.

[0101] - Latest prediction: The most recent (or latest) predicted RSRP / RSRQ / SINR values ​​for past points in time based on the time of measurement report transmission can be included for each cell and beam and reported to the base station.

[0102] - Future prediction: The predicted RSRP / RSRQ / SINR value(s) for future time(s) based on the time of measurement report transmission can be included for each cell and beam and reported to the base station.

[0103] In steps 525 and 535, the base station (505) can explicitly instruct the terminal (500) which of the above information (Latest measurement, Latest prediction, future prediction) should be included when transmitting the measurement report. For this purpose, an indicator for indicating whether each piece of information should be included can be included in the RRC message that the base station (505) transmits to the terminal (500) in steps 525 and 535. Additionally, the terminal (500) can include only reportable values ​​among the above information in the measurement report. For example, even if the base station (505) explicitly instructs in steps 525 and 535 to include future prediction in the measurement report, if the terminal (500) cannot actually report the value, the terminal (500) may not include the corresponding information in the measurement report.

[0104] FIG. 6 is a diagram illustrating a method for a terminal to utilize cell measurement prediction results in RRM operation to reduce cell measurement load according to an embodiment of the present disclosure.

[0105] Referring to FIG. 6, if the base station sets the cell measurement result prediction operation (or cell measurement load reduction operation) to the terminal in steps 525 and 535 of FIG. 5, the terminal can utilize the predicted cell measurement result (605) together with the cell measurement result (600) for the RRM operation. Here, the RRM operation may mean a Measurement Report triggering operation and an RLF detection operation, an RRM relaxation operation, an RLM (radio link monitoring) / BFD (beam failure detection) relaxation operation, a random access operation, etc.

[0106] In one embodiment of the present disclosure, a terminal may use a predicted cell measurement result (605) for a measurement report triggering operation. More specifically, a base station may set an 'event triggered' type measurement report operation for the terminal. At this time, the terminal may perform cell measurement on a serving cell and neighboring cells according to the base station settings, and may determine whether a measurement report triggering condition for a specific RRM measurement event (e.g., A2) set by the base station is satisfied based on the cell measurement result. If the base station sets a cell measurement result prediction operation (or cell measurement load reduction operation) for the terminal, the terminal may use the predicted cell measurement result (605) together with the cell measurement result (600) to determine whether the measurement report triggering condition is satisfied. For example, the base station may instruct the terminal to transmit a measurement report when the measurement report triggering condition for the A2 event is satisfied. At this time, one of the following methods may be used to determine whether the measurement report triggering condition for the above Event A2 is satisfied by using the cell measurement prediction result (605) together with the cell measurement result (600).

[0107] - Method 1 (610): If the entering condition of the A2 event is satisfied for all cell measurement results (600) during the TimeToTrigger period, the transmission of the measurement report for the A2 event can be triggered. Here, the entering condition of the A2 event means that the measured RSRP / RSRQ / SINR (100) for the serving cell must be lower than the base station set threshold value (607).

[0108] - Method 2 (620): If the entering condition of the A2 event is satisfied for all cell measurement results (600) and predicted cell measurement results (605) during the TimeToTrigger period, the transmission of the measurement report for the A2 event can be triggered. Here, the entering condition of the A2 event means that the measured / predicted RSRP / RSRQ / SINR (600, 605) for the serving cell must be lower than the base station set threshold value (607).

[0109] - Method 3 (630): If it is predicted that the entering condition of the A2 event will be satisfied for all cell measurement results (600) and predicted cell measurement results (605) during the TimeToTrigger period, the transmission of the measurement report for the A2 event can be triggered. Here, the entering condition of the A2 event means that the measured / predicted RSRP / RSRQ / SINR (100, 105) for the serving cell must be lower than the base station set threshold value (607).

[0110] Methods 1 / 2 / 3 of using cell measurement prediction results (605) together with cell measurement results (600) to determine whether measurement report triggering conditions for the above-described specific event are satisfied can be described in the standard as shown in Table 1 below.

[0111] <Method 1>2> else if thereportTypeis set toeventTriggered, and if the correspondingreportConfigdoes not includenumberOfTriggeringCells,andif the entry condition applicable for this event, i.e. the event corresponding with theeventIdof the correspondingreportConfigwithinVarMeasConfig,is fulfilledfor one or more applicable cells not included in thecellsTriggeredListfor all measurements after layer 3 filtering taken duringtimeToTriggerdefined for this event within theVarMeasConfig(a subsequent cell triggers the event):<Method 2>2> else if thereportTypeis set toeventTriggered, and if the correspondingreportConfigdoes not includenumberOfTriggeringCells,andif the entry condition applicable for this event, i.e.the event corresponding with theeventIdof the correspondingreportConfigwithinVarMeasConfig,is fulfilledfor one or more applicable cells not included in thecellsTriggeredListfor all measurements and predicted measurements after layer 3 filtering taken duringtimeToTriggerdefined for this event within theVarMeasConfig(a subsequent cell triggers the event):<Method 3>2> else if thereportTypeis set toeventTriggered, and if the correspondingreportConfigdoes not includenumberOfTriggeringCells,andif the entry condition applicable for this event, i.e. the event corresponding with theeventIdof the correspondingreportConfigwithinVarMeasConfig,is predicted to be fulfilledfor one or more applicable cells not included in thecellsTriggeredListfor all measurements and predicted measurements after layer 3 filtering taken duringtimeToTriggerdefined for this event within theVarMeasConfig(a subsequent cell triggers the event):.

[0112] In one embodiment of the present disclosure, the terminal may use the predicted cell measurement result (605) together with the cell measurement result (100) to determine whether the relaxation criterion is satisfied in the RRM relaxation operation and the RLM / BFD relaxation operation. This may be described in the specification as shown in Tables 2 and 3 below.

[0113] [Table 2]

[0114]

[0115]

[0116] [Table 3]

[0117]

[0118] In the embodiments of FIGS. 3, 4, 5, and 6 above, the cell measurement result may mean a combination of one or more of the following values ​​measured per cell or per beam of a specific cell.

[0119] - RSRP and / or RSRQ and / or SINR measured at Layer 1

[0120] - RSRP and / or RSRQ and / or SINR measured / obtained at Layer 3

[0121] - A filtered value of RSRP and / or RSRQ and / or SINR measured at Layer 1 (e.g., a weighted average value using the measured values ​​over a given period of time)

[0122] - A filtered value of RSRP and / or RSRQ and / or SINR measured / obtained at Layer 3 (e.g., a (weighted) average value using the measured values ​​over a given period of time)

[0123] FIG. 7 is a diagram illustrating a terminal according to one embodiment of the present disclosure.

[0124] Referring to FIG. 7, the terminal may include an RF (radio frequency) processing unit (710), a baseband processing unit (720), a storage unit (730), and a control unit (740). The configuration of the terminal is not limited to the exemplary configuration illustrated in FIG. 7, and may include fewer or more configurations than the configuration illustrated in FIG. 7.

[0125] 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 from the baseband processing unit (720) into an RF band signal and transmit it through an antenna, and may down-convert an RF band signal received through the 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 digital to analog convertor (DAC), an analog to digital convertor (ADC), etc., but is not limited to these examples. In FIG. 7, only one antenna is illustrated, but the terminal may be equipped with multiple antennas. In addition, 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) can adjust the phase and magnitude of each signal transmitted and received through multiple antennas or antenna elements. In addition, the RF processing unit (710) can perform MIMO and receive multiple layers when performing MIMO operations.

[0126] The baseband processing unit (720) can perform a conversion function between a baseband signal and a bit stream according to the physical layer specifications of the system. For example, when transmitting data, the baseband processing unit (720) can generate complex symbols by encoding and modulating a transmission bit stream. In addition, when receiving data, the baseband processing unit (720) can restore a reception bit stream by demodulating and decoding a baseband signal provided from the RF processing unit (710). For example, in the case of following the OFDM (orthogonal frequency division multiplexing) method, when transmitting data, the baseband processing unit (720) can generate complex symbols by encoding and modulating a transmission bit stream, map the generated complex symbols to subcarriers, and then configure OFDM symbols through an inverse fast Fourier transform (IFFT) operation and a cyclic prefix (CP) insertion. In addition, when receiving data, the baseband processing unit (720) divides the baseband signal provided from the RF processing unit (710) into OFDM symbol units, restores signals mapped to subcarriers through an FFT (fast Fourier transform) operation, and then restores the received bit string through demodulation and decoding.

[0127] 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 transmitter, a receiver, a transceiver, or a communication unit. Furthermore, at least one of the baseband processing unit (720) and the RF processing unit (710) may include a plurality of communication modules to support a plurality of different wireless access technologies. In addition, at least one of the baseband processing unit (720) and the RF processing unit (710) may include different communication modules to process signals of different frequency bands. For example, the different wireless access technologies may include wireless LAN (e.g., IEEE 802.11), a cellular network (e.g., LTE), etc. Additionally, different frequency bands may include super high frequency (SHF) (e.g., 2.NRHz, NRhz) bands and millimeter wave (mm wave) (e.g., 60GHz) bands. The terminal may transmit and receive signals with the gNB using the baseband processing unit (720) and the RF processing unit (710), and the signals may include control information and data.

[0128] The storage unit (730) can store data such as basic programs, application programs, and setting information for the operation of the terminal. For example, the storage unit (730) can store data information such as basic programs, application programs, and setting information for the operation of the terminal. In addition, the storage unit (730) can provide the stored data upon request of the control unit (740). The storage unit (730) can be configured as a storage medium or a combination of storage media such as a ROM, a RAM, a hard disk, a CD-ROM, and a DVD. In addition, the storage unit (730) can be configured as a plurality of memories. According to one embodiment of the present disclosure, the storage unit (730) can also store a program for performing a handover method according to the present disclosure.

[0129] The control unit (740) can control the overall operations of the terminal. For example, the control unit (740) can transmit and receive signals through the baseband processing unit (720) and the RF processing unit (710). In addition, the control unit (740) can record and read data in the storage unit (730). To this end, the control unit (740) can include at least one processor. For example, the control unit (740) can include a communication processor (CP) that performs control for communication and an application processor (AP) that controls upper layers such as application programs. In addition, according to one embodiment of the present disclosure, the control unit (740) can include a multi-connection processing unit (742) configured to process a process operating in a multi-connection mode. In addition, at least one component within the terminal can be implemented as a single chip.

[0130] FIG. 8 is a diagram illustrating a base station according to one embodiment of the present disclosure.

[0131] The base station of Fig. 8 may be included in the aforementioned network.

[0132] As illustrated in FIG. 8, the base station may include an RF processing unit (810), a baseband processing unit (820), a backhaul communication unit (830), a storage unit (840), and a control unit (850). The configuration of the base station is not limited to the exemplary configuration illustrated in FIG. 8, and the base station may include fewer or more configurations than the configuration illustrated in FIG. 8. The RF processing unit (810) 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 (810) may up-convert a baseband signal provided from the baseband processing unit (820) into an RF band signal and then transmit it through an antenna, and may down-convert an RF band signal received through the antenna into a baseband signal. For example, the RF processing unit (810) may include a transmission filter, a reception filter, an amplifier, a mixer, an oscillator, a DAC, an ADC, and the like. In FIG. 8, only one antenna is illustrated, but the RF processing unit (810) may be equipped with multiple antennas. In addition, the RF processing unit (810) may include multiple RF chains. Furthermore, the RF processing unit (810) may perform beamforming. For beamforming, the RF processing unit (810) may adjust the phase and magnitude of each signal transmitted and received through the multiple antennas or antenna elements. The RF processing unit (810) may perform a downlink MIMO operation by transmitting one or more layers.

[0133] The baseband processing unit (820) can perform a conversion function between a baseband signal and a bit stream according to the physical layer standard. For example, when transmitting data, the baseband processing unit (820) can generate complex symbols by encoding and modulating a transmission bit stream. In addition, when receiving data, the baseband processing unit (820) can restore the reception bit stream by demodulating and decoding the baseband signal provided from the RF processing unit (810). For example, in the case of following the OFDM method, when transmitting data, the baseband processing unit (820) can generate complex symbols by encoding and modulating a transmission bit stream, map the generated complex symbols to subcarriers, and then configure OFDM symbols through an IFFT operation and CP insertion. In addition, when receiving data, the baseband processing unit (820) can divide the baseband signal provided from the RF processing unit (810) into OFDM symbol units, restore the signals mapped to subcarriers through FFT operation, and then restore the received bit string through demodulation and decoding. The baseband processing unit (820) and the RF processing unit (810) can transmit and receive signals as described above. Accordingly, the baseband processing unit (820) and the RF processing unit (810) may be referred to as a transmitter, a receiver, a transceiver, a communication unit, or a wireless communication unit. The base station can transmit and receive signals with the terminal using the baseband processing unit (820) and the RF processing unit (810), and the signals may include control information and data.

[0134] The backhaul communication unit (830) may provide an interface for communicating with other nodes within the network. For example, the backhaul communication unit (830) may convert a bit stream transmitted from the primary base station to another node, such as an auxiliary base station or core network, into a physical signal, and may convert a physical signal received from another node into a bit stream.

[0135] The storage unit (840) can store data such as basic programs, application programs, and setting information for the operation of the main base station. For example, the storage unit (840) can store information on bearers assigned to connected terminals, measurement results reported from connected terminals, etc. In addition, the storage unit (840) can store information that serves as a basis for determining whether to provide or terminate multiple connections to the terminals. In addition, the storage unit (840) can provide the stored data at the request of the control unit (850). The storage unit (840) can be configured as a storage medium or a combination of storage media such as a ROM, a RAM, a hard disk, a CD-ROM, and a DVD. In addition, the storage unit (840) can be configured as a plurality of memories. According to one embodiment of the present disclosure, the storage unit (840) can also store a program for performing a handover according to the present disclosure.

[0136] The control unit (850) can control the overall operations of the base station. For example, the control unit (850) can transmit and receive signals through the baseband processing unit (820) and the RF processing unit (810) or through the backhaul communication unit (830). In addition, the control unit (850) can record and read data in the storage unit (840). For this purpose, the control unit (850) can include at least one processor. In addition, according to one embodiment of the present disclosure, the control unit (850) can include a multi-connection processing unit (852) configured to process a process operating in a multi-connection mode.

[0137] The 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.

[0138] When implemented in software, a computer-readable storage medium storing one or more programs (software modules) may be provided. The one or more programs stored in the computer-readable storage medium are configured for execution by one or more processors within an electronic device. The 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 the present disclosure.

[0139] These programs (software modules, software) may be stored in random access memory, non-volatile memory including flash memory, read only memory (ROM), electrically erasable programmable read only memory (EEPROM), magnetic disc storage device, compact disc ROM (CD-ROM), digital versatile discs (DVDs) or other forms of optical storage device, magnetic cassette. Or, they may be stored in a memory configured as a combination of some or all of these. In addition, each configuration memory may be included in multiple numbers.

[0140] Additionally, the program may be stored in an attachable storage device that is accessible via a communication network such as the Internet, an intranet, a local area network (LAN), a wide local area network (WLAN), a 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 via an external port. Additionally, a separate storage device on the communication network may be connected to a device performing an embodiment of the present disclosure.

[0141] In this disclosure, the term "computer program product" or "computer-readable medium" is used to collectively refer to media such as memory, a hard disk installed in a hard disk drive, and signals. These "computer program products" or "computer-readable mediums" are components provided in a method for reporting terminal capabilities in a wireless communication system according to the present disclosure.

[0142] A device-readable storage medium may be provided in the form of a non-transitory storage medium. Here, the term "non-transitory storage medium" simply means a tangible device that does not contain signals (e.g., electromagnetic waves). This term does not distinguish between cases where data is permanently stored in the storage medium and cases where data is temporarily stored. For example, a "non-transitory storage medium" may include a buffer in which data is temporarily stored.

[0143] According to one embodiment, the method according to various embodiments disclosed in the present document may be provided as included in a computer program product. The computer program product may be traded as a product between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., compact disc read only memory (CD-ROM)), or may be distributed online (e.g., downloaded or uploaded) via 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., a downloadable app) may be temporarily stored or temporarily generated in a machine-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or an intermediary server.

[0144] In the specific embodiments of the present disclosure described above, components included in the invention are expressed in the singular or plural form, depending on the specific embodiment presented. However, the singular or plural expressions are selected to suit the presented situation for convenience of explanation, and the present disclosure is not limited to singular or plural components. Components expressed in the plural form may be composed of singular elements, or components expressed in the singular form may be composed of plural elements.

[0145] Meanwhile, the embodiments of the present disclosure disclosed in this specification and drawings are merely specific examples to easily explain the technical contents of the present disclosure and to help understand the present disclosure, and are not intended to limit the scope of the present disclosure. In other words, it will be apparent to those skilled in the art that other modified examples based on the technical idea of ​​the present disclosure are possible. In addition, the above-described embodiments can be combined and operated as needed. For example, parts of one embodiment of the present disclosure and another embodiment can 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 modified examples based on the technical idea of ​​the embodiments may also be implemented. For example, the embodiments may be applied to LTE systems, 5G, NR systems, or 6G systems. Therefore, the scope of the present disclosure should not be limited to the described embodiments, but should be defined not only by the scope of the following claims but also by equivalents thereof.

Claims

1. In a method performed by a terminal in a wireless communication system, A step of receiving a first message including an RRM (radio resource management) prediction setting from a base station, wherein the RRM prediction setting includes setting information for a cell for predicting a cell measurement result; A step of transmitting a second message to the base station, the second message including information on an applicable prediction model for predicting the cell measurement result based on the first message; A step of receiving a third message including an indicator for activating prediction of the cell measurement result from the base station based on the second message; and A method comprising a step of performing an RRM operation using a prediction of the cell measurement result based on the third message.

2. In paragraph 1, The second message comprises a list of information about applicable prediction models, the list comprising information about at least one applicable prediction model, and The information for each applicable prediction model above includes at least one of a measurement reduction rate or a guaranteed measurement difference value, and A method wherein the third message includes information about a prediction model selected based on the list.

3. In paragraph 1, The first message includes information about a threshold value of cell measurement result prediction accuracy or information about an acceptable measurement reduction ratio, and A method in which information about the applicable prediction model is determined based on information about a threshold value of the prediction accuracy of the cell measurement results or information about the allowable measurement reduction ratio.

4. In paragraph 1, The second message includes cell measurement pattern information corresponding to information about the applicable prediction model, A method in which at least one of transmission of a reference signal or setting of a measurement gap is controlled based on the above cell measurement pattern information.

5. In paragraph 1, A step of receiving a terminal capability information report request from the base station; and Including a step of transmitting terminal capability information to the base station, A method wherein the terminal capability information includes at least one of first information indicating performance of RRM measurement prediction not based on measurement reduction or second information indicating performance of RRM measurement prediction based on measurement reduction.

6. In a method performed by a base station in a wireless communication system, A step of transmitting a first message including an RRM (radio resource management) prediction setting to a terminal, wherein the RRM prediction setting includes setting information for a cell for predicting a cell measurement result; A step of receiving a second message from the terminal that includes information about an applicable prediction model for predicting the cell measurement result based on the first message; and A step of transmitting a third message to the terminal, the third message including an indicator for activating prediction of the cell measurement result based on the second message, A method in which an RRM operation is performed using prediction of the cell measurement result based on the third message.

7. In paragraph 6, The second message comprises a list of information about applicable prediction models, the list comprising information about at least one applicable prediction model, and The information for each applicable prediction model above includes at least one of a measurement reduction rate or a guaranteed measurement difference value, and A method wherein the third message includes information about a prediction model selected based on the list.

8. In paragraph 6, The first message includes information about a threshold value of cell measurement result prediction accuracy or information about an acceptable measurement reduction ratio, and A method in which information about the applicable prediction model is determined based on information about a threshold value of the prediction accuracy of the cell measurement results or information about the allowable measurement reduction ratio.

9. In paragraph 6, The second message includes cell measurement pattern information corresponding to information about the applicable prediction model, A method in which at least one of transmission of a reference signal or setting of a measurement gap is controlled based on the above cell measurement pattern information.

10. In paragraph 6, A step of transmitting a terminal capability information report request to the terminal; and Including a step of receiving terminal capability information from the terminal, A method wherein the terminal capability information includes at least one of first information indicating performance of RRM measurement prediction not based on measurement reduction or second information indicating performance of RRM measurement prediction based on measurement reduction.

11. In a wireless communication system terminal, In the terminal, At least one transceiver; At least one processor communicatively connected to said at least one transceiver; and Communicably connected to at least one processor, and executable individually or in any combination of said at least one processor, so that said terminal Receive a first message including an RRM (radio resource management) prediction setting from a base station, wherein the RRM prediction setting includes setting information for a cell for predicting a cell measurement result; Transmitting a second message to the base station, the second message including information about an applicable prediction model for predicting the cell measurement result based on the first message; Receive a third message including an indicator for activating prediction of the cell measurement result from the base station based on the second message; and A memory storing a command to perform an RRM operation using a prediction of the cell measurement result based on the third message; A terminal including .

12. In paragraph 11, The second message comprises a list of information about applicable prediction models, the list comprising information about at least one applicable prediction model, and The information for each applicable prediction model above includes at least one of a measurement reduction rate or a guaranteed measurement difference value, and The third message is a terminal that includes information about a prediction model selected based on the list.

13. In paragraph 11, The first message includes information about a threshold value of cell measurement result prediction accuracy or information about an acceptable measurement reduction ratio, and The terminal is determined based on information about the threshold value of the cell measurement result prediction accuracy or information about the allowable measurement reduction ratio, wherein the information about the applicable prediction model is a terminal.

14. In a base station of a wireless communication system, At least one transceiver; At least one processor communicatively connected to said at least one transceiver; and Communicably connected to at least one processor, and executable individually or in any combination of said at least one processor, so that said terminal Transmitting a first message including an RRM (radio resource management) prediction setting to a terminal, wherein the RRM prediction setting includes setting information for a cell for predicting a cell measurement result; Receive a second message from the terminal that includes information about an applicable prediction model for predicting the cell measurement result based on the first message; and A memory storing a command to transmit a third message to the terminal, the third message including an indicator for activating prediction of the cell measurement result based on the second message; A base station in which an RRM operation is performed using prediction of the cell measurement result based on the third message.

15. In paragraph 14, The second message comprises a list of information about applicable prediction models, the list comprising information about at least one applicable prediction model, and The information for each applicable prediction model above includes at least one of a measurement reduction rate or a guaranteed measurement difference value, and The third message is a base station that includes information about a prediction model selected based on the list.

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