Method and device for performing communication by using artificial intelligence and machine learning

Abstract

The present embodiments relate to a method and device for performing communication by using artificial intelligence and machine learning, and provide the method comprising the steps of: receiving, from a base station, conditional handover configuration information configured on the basis of a prediction result inferred via an AI / ML model; measuring a signal strength and / or signal quality for a target base station on the basis of the conditional handover configuration information; and transmitting a measurement report message to the base station when the measurement result is not higher than a prescribed threshold value.

Description

Method and device for performing communication using artificial intelligence and machine learning

[0001] The present embodiments propose a method and apparatus for performing communication using artificial intelligence and machine learning in a next-generation wireless access network (in this disclosure, “5G,” “NR [New Radio],” “5G-Advanced,” “6G,” or a subsequent 3GPP wireless access network).

[0002] Next-generation wireless communication technology is evolving beyond 5G to 6G, aiming to achieve faster data transmission speeds and ultra-low latency compared to 5G in ultra-high frequency ranges such as the terahertz (THz) band. Therefore, technology is advancing toward incorporating artificial intelligence (AI) and machine learning (ML) technologies from the communication system design stage. Consequently, wireless communication systems are establishing a technological foundation to support new services and applications in ultra-high-performance, ultra-low latency, and hyper-connected environments.

[0003] In particular, AI / ML technologies are being introduced in wireless communication networks to optimize network operations and ensure real-time quality. AI / ML can perform a variety of roles, including situational awareness through big data analysis, adaptive utilization of network resources and data, and intelligent, data-driven system optimization. These capabilities can enable efficient resource management and improved service quality in complex wireless environments, where conventional methods have proven limited.

[0004] As part of this aspect, a specific design is needed to enable wireless communication using AI / ML models.

[0005] Embodiments of the present disclosure can provide a method and device for performing communication using artificial intelligence and machine learning in a next-generation wireless access network.

[0006] In one aspect, the present embodiments may provide a method for a user equipment (UE) to perform communication using artificial intelligence and machine learning (AI / ML), the method including: receiving conditional handover configuration information set based on a prediction result inferred through an AI / ML model from a base station; measuring a signal strength and / or signal quality for a target base station based on the conditional handover configuration information; and transmitting a measurement report message to the base station when the measurement result is not higher than a predetermined threshold.

[0007] In another aspect, the present embodiments may provide a method in which a base station performs communication using artificial intelligence and machine learning (AI / ML), the method including the steps of transmitting conditional handover configuration information set based on a prediction result inferred through an AI / ML model to a terminal, receiving a measurement report message from the terminal when a handover according to the conditional handover configuration information fails, and transmitting a handover cancellation message to a target base station.

[0008] In another aspect, the present embodiments provide a user equipment (UE) that performs communication using artificial intelligence and machine learning (AI / ML), including a transmitter, a receiver, and a control unit that controls operations of the transmitter and the receiver, wherein the control unit receives conditional handover configuration information set based on a prediction result inferred through an AI / ML model from a base station, measures a signal strength and / or signal quality for a target base station based on the conditional handover configuration information, and transmits a measurement report message to the base station when the measurement result is not higher than a predetermined threshold value.

[0009] In another aspect, the present embodiments provide a base station that performs communication using artificial intelligence and machine learning, including a transmitter, a receiver, and a control unit that controls operations of the transmitter and the receiver, wherein the control unit transmits conditional handover configuration information set based on a prediction result inferred through an AI / ML model to a terminal, and when a handover according to the conditional handover configuration information fails, a measurement report message is received from the terminal, and a handover cancellation message is transmitted to a target base station.

[0010] According to the present embodiments, a method and device for performing communication using artificial intelligence and machine learning in a next-generation wireless access network can be provided.

[0011] Additionally, if the predicted information is inaccurate and causes conditional handover failure / cancellation, unnecessary handover of the terminal can be prevented, and a method for monitoring the accuracy of the AI / ML model used for conditional handover can be provided, thereby improving the overall system performance.

[0012] FIG. 1 is a schematic diagram illustrating the structure of an NR wireless communication system to which the present embodiment can be applied.

[0013] FIG. 2 is a drawing for explaining a frame structure in an NR system to which the present embodiment can be applied.

[0014] FIG. 3 is a diagram for explaining a resource grid supported by a wireless access technology to which the present embodiment can be applied.

[0015] FIG. 4 is a diagram for explaining a bandwidth part supported by a wireless access technology to which the present embodiment can be applied.

[0016] FIG. 5 is a diagram illustrating an example of a synchronization signal block in a wireless access technology to which the present embodiment can be applied.

[0017] FIG. 6 is a diagram for explaining a random access procedure in a wireless access technology to which the present embodiment can be applied.

[0018] Figure 7 is a drawing for explaining CORESET.

[0019] FIG. 8 is a diagram illustrating a procedure in which a terminal performs communication using artificial intelligence and machine learning according to one embodiment.

[0020] FIG. 9 is a diagram illustrating a procedure in which a base station performs communication using artificial intelligence and machine learning according to one embodiment.

[0021] FIG. 10 is a diagram illustrating an example of temporal cell / beam level surrounding / serving cell quality / intensity prediction using AI / ML according to one embodiment.

[0022] FIG. 11 and FIG. 12 are drawings for explaining an example of a point in time of operation according to one embodiment.

[0023] FIG. 13 is a diagram for explaining an example of the operation of a terminal and a base station performing handover according to one embodiment.

[0024] FIG. 14 is a diagram for explaining an example of operations of a terminal and a base station when a conditional handover fails according to one embodiment.

[0025] Fig. 15 is a drawing showing the configuration of a terminal according to another embodiment.

[0026] Fig. 16 is a drawing showing the configuration of a base station according to another embodiment.

[0027] Hereinafter, some embodiments of the present disclosure will be described in detail with reference to exemplary drawings. When adding reference numerals to components in each drawing, identical components may have the same numerals as much as possible even if they are shown in different drawings. In addition, when describing the present embodiments, if it is determined that a detailed description of a related known configuration or function may obscure the gist of the technical idea of ​​the present invention, the detailed description may be omitted. When "includes," "has," "consists of," etc. are used in this specification, other parts may be added unless "only" is used. When a component is expressed in the singular, it may include a case in which the plural is included unless specifically stated otherwise.

[0028] Additionally, terms such as first, second, A, B, (a), (b), etc. may be used to describe components of the present disclosure. These terms are only intended to distinguish the components from other components, and the nature, order, sequence, or number of the components are not limited by the terms.

[0029] In a description of the positional relationship of components, when it is described that two or more components are "connected," "combined," or "connected," it should be understood that the two or more components may be directly "connected," "combined," or "connected," but that the two or more components may also be further "interposed" with another component to be "connected," "combined," or "connected." Here, the other component may be included in one or more of the two or more components that are "connected," "combined," or "connected" to each other.

[0030] In the description of the temporal flow relationship related to components, operation methods, or manufacturing methods, for example, when the temporal or flow relationship is described as “after”, “following”, “next to”, “before”, etc., it may also include cases where it is not continuous, unless “immediately” or “directly” is used.

[0031] Meanwhile, when numerical values ​​or corresponding information (e.g., levels, etc.) for components are mentioned, even without separate explicit description, the numerical values ​​or corresponding information may be interpreted as including an error range that may occur due to various factors (e.g., process factors, internal or external impact, noise, etc.).

[0032] The wireless communication system in this specification refers to a system for providing various communication services such as voice, data packets, etc. using wireless resources, and may include a terminal, a base station, or a core network.

[0033] The embodiments disclosed below can be applied to wireless communication systems using various wireless access technologies. For example, the embodiments can be applied to various wireless access technologies such as CDMA (code division multiple access), FDMA (frequency division multiple access), TDMA (time division multiple access), OFDMA (orthogonal frequency division multiple access), SC-FDMA (single carrier frequency division multiple access), or NOMA (non-orthogonal multiple access). In addition, the wireless access technology may not only refer to a specific access technology, but also to each generation of communication technology established by various communication agreement organizations such as 3GPP, 3GPP2, WiFi, Bluetooth, IEEE, and ITU. For example, CDMA can be implemented with wireless technologies such as UTRA (universal terrestrial radio access) or CDMA2000. TDMA can be implemented with wireless technologies such as GSM (global system for mobile communications) / GPRS (general packet radio service) / EDGE (enhanced data rates for GSM evolution). OFDMA can be implemented in wireless technologies such as IEEE (Institute of Electrical and Electronics Engineers) 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802-20, and E-UTRA (evolved UTRA). IEEE 802.16m is an evolution of IEEE 802.16e and provides backward compatibility with systems based on IEEE 802.16e.UTRA is part of UMTS (universal mobile telecommunications system). 3GPP (3rd generation partnership project) LTE (long term evolution) is part of E-UMTS (evolved UMTS) that uses E-UTRA (evolved-UMTSterrestrial radio access), employing OFDMA in the downlink and SC-FDMA in the uplink. Thus, the present embodiments can be applied to currently disclosed or commercialized wireless access technologies, as well as wireless access technologies currently under development or to be developed in the future.

[0034] Meanwhile, the term "terminal" in this specification is a comprehensive concept that refers to a device that includes a wireless communication module that performs communication with a base station in a wireless communication system, and should be interpreted as a concept that includes not only UE (User Equipment) in WCDMA, LTE, NR, HSPA, and IMT-2020 (5G or New Radio), but also MS (Mobile Station), UT (User Terminal), SS (Subscriber Station), and wireless device in GSM. In addition, the terminal may be a user portable device such as a smartphone depending on the usage type, and in a V2X communication system, it may mean a vehicle, a device including a wireless communication module in the vehicle, etc. In addition, in the case of a Machine Type Communication system, it may mean an MTC terminal, M2M terminal, URLLC terminal, etc. that is equipped with a communication module to perform machine type communication.

[0035] The base station or cell in this specification refers to an end that communicates with a terminal in terms of a network, and includes various coverage areas such as Node-B, eNB (evolved Node-B), gNB (gNode-B), LPN (Low Power Node), Sector, Site, various types of antennas, BTS (Base Transceiver System), Access Point, Point (e.g., Transmission Point, Reception Point, Transmission / Reception Point), Relay Node, Mega Cell, Macro Cell, Micro Cell, Pico Cell, Femto Cell, RRH (Remote Radio Head), RU (Radio Unit), and Small Cell. In addition, a cell may mean including a BWP (Bandwidth Part) in the frequency domain. For example, a serving cell may mean an Activation BWP of a terminal.

[0036] Since the various cells listed above have a base station that controls one or more cells, the base station can be interpreted in two meanings. 1) It can be a device itself that provides a mega cell, macro cell, micro cell, pico cell, femto cell, or small cell in relation to a wireless area, or 2) it can indicate the wireless area itself. In 1), all devices that provide a given wireless area are controlled by the same entity or that interact to cooperatively configure the wireless area are all indicated as a base station. Depending on how the wireless area is configured, a point, a transceiver point, a transmission point, a reception point, etc. can be an embodiment of a base station. In 2), the wireless area itself that receives or transmits a signal from the perspective of a user terminal or a neighboring base station can also be indicated as a base station.

[0037] In this specification, a cell may mean a component carrier having coverage of a signal transmitted from a transmission / reception point or a transmission / reception point itself.

[0038] Uplink (UL, or uplink) refers to a method of transmitting and receiving data from a terminal to a base station, and downlink (DL, or downlink) refers to a method of transmitting and receiving data from a base station to a terminal. Downlink may refer to communication or a communication path from multiple transmission / reception points to a terminal, and uplink may refer to communication or a communication path from a terminal to multiple transmission / reception points. In this case, in the downlink, the transmitter may be part of the multiple transmission / reception points, and the receiver may be part of the terminal. In addition, in the uplink, the transmitter may be part of the terminal, and the receiver may be part of the multiple transmission / reception points.

[0039] Uplink and downlink transmit and receive control information through control channels such as PDCCH (Physical Downlink Control CHannel) and PUCCH (Physical Uplink Control CHannel), and transmit and receive data by configuring data channels such as PDSCH (Physical Downlink Shared CHannel) and PUSCH (Physical Uplink Shared CHannel). Hereinafter, the situation in which signals are transmitted and received through channels such as PUCCH, PUSCH, PDCCH, and PDSCH is also expressed in the form of 'transmitting and receiving PUCCH, PUSCH, PDCCH, and PDSCH'.

[0040] For clarity of explanation, the technical idea of ​​this invention is described below mainly with reference to the 3GPP LTE / LTE-A / NR (New RAT) communication system, but the technical features of this invention are not limited to the communication system.

[0041] After researching 4G (4th-Generation) communication technology, 3GPP develops 5G (5th-Generation) communication technology to meet the requirements of the next-generation wireless access technology of the ITU-R. Specifically, 3GPP develops LTE-A pro, which enhances LTE-Advanced technology to meet the requirements of the ITU-R, and NR, a new communication technology separate from 4G communication technology. Both LTE-A pro and NR refer to 5G communication technology, and in the following, 5G communication technology will be explained with NR as the focus, unless a specific communication technology is specifically mentioned.

[0042] The operating scenario in NR defines various operation scenarios by adding considerations for satellites, automobiles, and new verticals to the existing 4G LTE scenario, and in terms of service, it supports the eMBB (Enhanced Mobile Broadband) scenario, the mMTC (Massive Machine Communication) scenario that has high terminal density but is deployed over a wide area and requires low data rate and asynchronous access, and the URLLC (Ultra Reliability and Low Latency) scenario that requires high responsiveness and reliability and can support high-speed mobility.

[0043] To meet these scenarios, NR introduces a wireless communication system that incorporates new waveform and frame structure technologies, low latency technologies, support for ultra-high frequency bands (mmWave), and forward compatibility technologies. In particular, NR systems offer various technological changes in terms of flexibility to ensure forward compatibility. The key technical features of NR are described below with reference to the drawings.

[0044]

[0045] <NR 시스템 일반>

[0046] Figure 1 is a schematic diagram illustrating the structure of an NR system to which the present embodiment can be applied.

[0047] Referring to Fig. 1, the NR system is divided into 5GC (5G Core Network) and NR-RAN parts, and the NG-RAN is composed of gNBs and ng-eNBs that provide user plane (SDAP / PDCP / RLC / MAC / PHY) and control plane (RRC) protocol termination for UE (User Equipment). gNBs or gNBs and ng-eNBs are interconnected via the Xn interface. gNBs and ng-eNBs are each connected to the 5GC via the NG interface. The 5GC can be configured to include an AMF (Access and Mobility Management Function) that is responsible for the control plane such as terminal access and mobility control functions, and an UPF (User Plane Function) that is responsible for the control function for user data. NR includes support for both frequency bands below 6 GHz (FR1, Frequency Range 1) and frequency bands above 6 GHz (FR2, Frequency Range 2).

[0048] gNB refers to a base station that provides NR user plane and control plane protocol termination to terminals, and ng-eNB refers to a base station that provides E-UTRA user plane and control plane protocol termination to terminals. The base station described in this specification should be understood to encompass both gNB and ng-eNB, and may also be used to refer to gNB or ng-eNB separately as needed.

[0049] <NR 웨이브 폼, 뉴머롤러지 및 프레임 구조>

[0050]

[0051] *NR uses the CP-OFDM waveform with a cyclic prefix for downlink transmission, and CP-OFDM or DFT-s-OFDM for uplink transmission. OFDM technology is easily combined with MIMO (Multiple Input Multiple Output) and has the advantage of enabling the use of low-complexity receivers with high frequency efficiency.

[0052] Meanwhile, in NR, the requirements for data rates, latency, and coverage differ across the three scenarios mentioned above. Therefore, it is necessary to efficiently satisfy these requirements across the frequency bands that comprise any NR system. To this end, technologies have been proposed to efficiently multiplex radio resources based on multiple different numerologies.

[0053] Specifically, the NR transmission numerator is determined based on the sub-carrier spacing and the cyclic prefix (CP), and is changed exponentially with the μ value being an exponent value of 2 based on 15 kHz, as shown in Table 1 below.

[0054] μ서브캐리어 간격Cyclic prefixSupported for dataSupported for synch015NormalYesYes130NormalYesYes260Normal, ExtendedYesNo3120NormalYesYes4240NormalNoYes

[0055] As shown in Table 1 above, the numerology of NR can be divided into five types according to the subcarrier spacing. This is different from the fixed subcarrier spacing of LTE, one of the 4G communication technologies, at 15 kHz. Specifically, the subcarrier spacing used for data transmission in NR is 15, 30, 60, and 120 kHz, and the subcarrier spacing used for synchronization signal transmission is 15, 30, 12, and 240 kHz. In addition, the extended CP is applied only to the 60 kHz subcarrier spacing. Meanwhile, the frame structure in NR is defined as a 10 ms frame consisting of 10 subframes with the same length of 1 ms. One frame can be divided into half frames of 5 ms, and each half frame contains 5 subframes. In the case of a 15 kHz subcarrier spacing, one subframe consists of one slot, and each slot consists of 14 OFDM symbols. FIG. 2 is a diagram for explaining the frame structure in an NR system to which the present embodiment can be applied. Referring to FIG. 2, a slot is fixedly composed of 14 OFDM symbols in the case of a normal CP, but the length of the slot in the time domain may vary depending on the subcarrier spacing. For example, in the case of a numerology with a 15 kHz subcarrier spacing, a slot is composed of 1 ms, which is the same length as a subframe. In contrast, in the case of a numerology with a 30 kHz subcarrier spacing, a slot is composed of 14 OFDM symbols, but two slots may be included in one subframe with a length of 0.5 ms. That is, a subframe and a frame are defined with a fixed time length, and a slot is defined by the number of symbols, so the time length may vary depending on the subcarrier spacing.Meanwhile, NR defines slots as the basic scheduling unit and also introduces mini-slots (or sub-slots, or non-slot-based scheduling) to reduce transmission delay in the wireless section. Using wider subcarrier spacing reduces transmission delay in the wireless section by shortening the length of each slot inversely. Mini-slots (or sub-slots) are designed to efficiently support URLLC scenarios and allow scheduling in units of 2, 4, or 7 symbols.

[0056] Furthermore, unlike LTE, NR defines uplink and downlink resource allocation at the symbol level within a single slot. To reduce HARQ delay, a slot structure was defined that allows HARQ ACK / NACKs to be transmitted directly within the transmission slot. This slot structure is referred to as a self-contained structure and will be described in detail.

[0057] NR is designed to support a total of 256 slot formats, of which 62 are used in 3GPP Rel-15. It also supports a common frame structure that configures FDD or TDD frames through various combinations of slots. For example, it supports a slot structure in which all symbols in a slot are set to downlink, a slot structure in which all symbols are set to uplink, and a slot structure in which downlink and uplink symbols are combined. NR also supports data transmission being distributed and scheduled across one or more slots. Therefore, a base station can use a slot format indicator (SFI) to inform a UE whether a slot is a downlink slot, an uplink slot, or a flexible slot. The base station can indicate the slot format by indicating an index of a table configured through UE-specific RRC signaling using the SFI, and can also indicate it dynamically through DCI (Downlink Control Information) or statically or semi-statically through RRC.

[0058] <NR 물리 자원 >

[0059] In relation to physical resources in NR, antenna ports, resource grids, resource elements, resource blocks, and bandwidth parts are considered.

[0060] Antenna ports are defined such that the channel through which a symbol on an antenna port is carried can be inferred from the channel through which another symbol on the same antenna port is carried. Two antenna ports are said to be quasi co-located (or quasi co-located) if the large-scale properties of the channel through which a symbol on one antenna port is carried can be inferred from the channel through which a symbol on the other antenna port is carried. Here, the large-scale properties include one or more of delay spread, Doppler spread, frequency shift, average received power, and received timing.

[0061] FIG. 3 is a diagram for explaining a resource grid supported by a wireless access technology to which the present embodiment can be applied.

[0062] Referring to Figure 3, a resource grid may exist for each numeral, as NR supports multiple numerals on the same carrier. Furthermore, resource grids may exist based on antenna ports, subcarrier spacing, and transmission direction.

[0063] A resource block (RB) consists of 12 subcarriers and is defined solely in the frequency domain. Furthermore, a resource element (RE) consists of one OFDM symbol and one subcarrier. Therefore, as shown in Figure 3, the size of a single RB can vary depending on the subcarrier spacing. NR also defines "Point A," which serves as a common reference point for the RB grid, as well as common RBs and virtual RBs.

[0064] FIG. 4 is a diagram for explaining a bandwidth part supported by a wireless access technology to which the present embodiment can be applied.

[0065] Unlike LTE, where the carrier bandwidth is fixed at 20 MHz, NR sets the maximum carrier bandwidth from 50 MHz to 400 MHz for each subcarrier interval. Therefore, it is not assumed that all terminals will use the entire carrier bandwidth. Accordingly, NR allows terminals to designate bandwidth parts (BWPs) within the carrier bandwidth, as illustrated in Figure 4. Furthermore, bandwidth parts are associated with a single numerology, consist of a subset of consecutive common resource blocks, and can be dynamically activated over time. Each terminal is configured with up to four bandwidth parts for both the uplink and downlink, and data is transmitted and received using the bandwidth parts activated at a given time.

[0066] In the case of a paired spectrum, the uplink and downlink bandwidth parts are set independently, and in the case of an unpaired spectrum, the downlink and uplink bandwidth parts are set in pairs so that they can share a center frequency to prevent unnecessary frequency re-tuning between downlink and uplink operations.

[0067] <NR 초기 접속>

[0068] In NR, a terminal performs cell search and random access procedures to connect to a base station and perform communication.

[0069] Cell search is a procedure in which a terminal synchronizes to the cell of a corresponding base station, obtains a physical layer cell ID, and obtains system information using a synchronization signal block (SSB) transmitted by the base station.

[0070] FIG. 5 is a diagram illustrating an example of a synchronization signal block in a wireless access technology to which the present embodiment can be applied.

[0071] Referring to FIG. 5, SSB is composed of a primary synchronization signal (PSS) and a secondary synchronization signal (SSS), each occupying 1 symbol and 127 subcarriers, and a PBCH spanning 3 OFDM symbols and 240 subcarriers.

[0072] The terminal receives SSB by monitoring SSB in the time and frequency domain.

[0073] SSB can be transmitted up to 64 times in 5ms. Multiple SSBs are transmitted in different transmission beams within 5ms, and the terminal performs detection assuming that SSBs are transmitted every 20ms based on a specific beam used for transmission. The number of beams that can be used for SSB transmission within 5ms can increase as the frequency band increases. For example, up to 4 SSB beams can be transmitted below 3GHz, up to 8 in the frequency band between 3GHz and 6GHz, and up to 64 different beams can be used for SSB transmission in the frequency band above 6GHz.

[0074] SSB contains two symbols in one slot, and the starting symbol and number of repetitions within the slot are determined as follows depending on the subcarrier spacing.

[0075] Meanwhile, unlike SS in conventional LTE, SSB is not transmitted at the center frequency of the carrier bandwidth. This means that SSB can be transmitted even in locations other than the center of the system bandwidth, and when supporting wideband operation, multiple SSBs can be transmitted in the frequency domain. Accordingly, the terminal monitors SSB using the synchronization raster, which is a candidate frequency location for monitoring SSB. The carrier raster, which is the center frequency location information of the channel for initial access, and the synchronization raster are newly defined in NR. The synchronization raster has a wider frequency interval than the carrier raster, which can support the terminal's fast SSB search.

[0076] A UE can obtain the MIB through the PBCH of the SSB. The MIB (Master Information Block) includes the minimum information required for the UE to receive the remaining system information (RMSI, Remaining Minimum System Information) broadcast by the network. In addition, the PBCH may include information on the position of the first DM-RS symbol in the time domain, information for the UE to monitor SIB1 (e.g., SIB1 numerology information, information related to SIB1 CORESET, search space information, PDCCH-related parameter information, etc.), offset information between the common resource block and the SSB (the absolute position of the SSB within the carrier is transmitted through SIB1), etc. Here, the SIB1 numerology information is also applied equally to some messages used in the random access procedure for the UE to access the base station after completing the cell search procedure. For example, the numerology information of SIB1 may be applied to at least one of messages 1 to 4 for the random access procedure.

[0077] The aforementioned RMSI may refer to SIB1 (System Information Block 1), and SIB1 is broadcast periodically (e.g., every 160 ms) in the cell. SIB1 contains information necessary for the UE to perform the initial random access procedure and is periodically transmitted via PDSCH. In order for the UE to receive SIB1, it must receive numerology information used for SIB1 transmission and CORESET (Control Resource Set) information used for SIB1 scheduling via PBCH. The UE checks scheduling information for SIB1 using SI-RNTI in CORESET and acquires SIB1 on PDSCH according to the scheduling information. The remaining SIBs, excluding SIB1, may be transmitted periodically or upon request of the UE.

[0078] FIG. 6 is a diagram for explaining a random access procedure in a wireless access technology to which the present embodiment can be applied.

[0079] Referring to FIG. 6, once cell search is complete, the terminal transmits a random access preamble for random access to the base station. The random access preamble is transmitted via the PRACH. Specifically, the random access preamble is transmitted to the base station via the PRACH, which consists of consecutive radio resources in a specific slot that is periodically repeated. Generally, when a terminal initially accesses a cell, a contention-based random access procedure is performed, and when performing random access for beam failure recovery (BFR), a non-contention-based random access procedure is performed.

[0080] The terminal receives a random access response to the transmitted random access preamble. The random access response may include a random access preamble identifier (ID), an UL Grant (uplink radio resource), a temporary C-RNTI (Temporary Cell - Radio Network Temporary Identifier), and a TAC (Time Alignment Command). Since one random access response may include random access response information for one or more terminals, the random access preamble identifier may be included to indicate which terminal the included UL Grant, temporary C-RNTI, and TAC are valid for. The random access preamble identifier may be an identifier for the random access preamble received by the base station. The TAC may be included as information for the terminal to adjust uplink synchronization. The random access response may be indicated by a random access identifier on the PDCCH, i.e., an RA-RNTI (Random Access - Radio Network Temporary Identifier).

[0081] Upon receiving a valid random access response, the terminal processes the information contained in the random access response and performs scheduled transmission to the base station. For example, the terminal applies TAC and stores a temporary C-RNTI. Furthermore, using the UL Grant, the terminal transmits data stored in its buffer or newly generated data to the base station. In this case, information that identifies the terminal must be included.

[0082] Finally, the terminal receives a downlink message for contention resolution.

[0083] <NR CORESET>

[0084] The downlink control channel in NR is transmitted in a CORESET (Control Resource Set) with a length of 1 to 3 symbols, and transmits uplink / downlink scheduling information, SFI (Slot format Index), and TPC (Transmit Power Control) information.

[0085] To ensure system flexibility, NR introduced the CORESET concept. CORESET (Control Resource Set) refers to time-frequency resources for downlink control signals. A terminal can decode control channel candidates using one or more search spaces within the CORESET time-frequency resources. A QCL (Quasi CoLocation) assumption is established for each CORESET, which is used to inform the characteristics of analog beam direction in addition to the delay spread, Doppler spread, Doppler shift, and average delay assumed by the conventional QCL.

[0086] Figure 7 is a drawing for explaining CORESET.

[0087] Referring to Figure 7, a CORESET can exist in various forms within the carrier bandwidth within a single slot, and in the time domain, a CORESET can consist of up to three OFDM symbols. In addition, a CORESET is defined as a multiple of six resource blocks up to the carrier bandwidth in the frequency domain.

[0088] The first CORESET is indicated via the MIB as part of the initial bandwidth part configuration, allowing the terminal to receive additional configuration and system information from the network. After establishing a connection with the base station, the terminal can receive and configure one or more CORESET information via RRC signaling.

[0089] In this specification, the terms frequency, frame, subframe, resource, resource block, region, band, subband, control channel, data channel, synchronization signal, various reference signals, various signals or various messages related to NR (New Radio) may be interpreted in the past or present meaning or in various meanings used in the future.

[0090] Wider bandwidth operations

[0091] Existing LTE systems supported scalable bandwidth operation for any LTE Component Carrier (CC). That is, depending on the deployment scenario, any LTE operator could configure a single LTE CC with a bandwidth ranging from a minimum of 1.4 MHz to a maximum of 20 MHz, and a normal LTE terminal supported transmission and reception capabilities of 20 MHz bandwidth for a single LTE CC.

[0092] However, in the case of NR, the design is made to support NR terminals with different transmission and reception bandwidth capabilities through a single wideband NR CC, and accordingly, it is required to configure one or more bandwidth parts (BWP, bandwidth part(s)) consisting of segmented bandwidths for any NR CC, and to support flexible wider bandwidth operation through different bandwidth part configurations and activations for each terminal.

[0093] Specifically, in NR, one or more bandwidth parts can be configured through one serving cell configured from the terminal's perspective, and the terminal is defined to activate one downlink bandwidth part (DL bandwidth part) and one uplink bandwidth part (UL bandwidth part) in the serving cell to use them for uplink / downlink data transmission and reception. In addition, when multiple serving cells are configured in the terminal, that is, for the terminal to which CA is applied, it is defined to activate one downlink bandwidth part and / or uplink bandwidth part for each serving cell to use the radio resources of the serving cell to use them for uplink / downlink data transmission and reception.

[0094] Specifically, an initial bandwidth part for an initial access procedure of a terminal in an arbitrary serving cell is defined, one or more UE-specific bandwidth part(s) are configured for each terminal through dedicated RRC signaling, and a default bandwidth part for a fallback operation can also be defined for each terminal.

[0095] However, it can be defined that multiple downlink and / or uplink bandwidth parts can be activated and used simultaneously depending on the capability and bandwidth part(s) configuration of the terminal in any serving cell, but in NR rel-15, it is defined that only one downlink bandwidth part (DL bandwidth part) and one uplink bandwidth part (UL bandwidth part) can be activated and used in any terminal at any time.

[0096]

[0097] The present disclosure relates to a method for efficiently performing conditional handover of a terminal based on prediction results of surrounding cells derived by the terminal or base station for a terminal managing movement using AI / ML.

[0098] The following terms can be defined for AI / ML-based wireless communications:

[0099] Data collection refers to the process by which network nodes, management entities, or UEs collect data for the purpose of AI / ML model training, data analysis, and inference.

[0100] An AI / ML model (hereinafter also referred to as a "model") is a data-driven algorithm that applies AI / ML technology to generate a series of outputs based on a series of inputs. AI / ML model training refers to the process of training an AI / ML model in a data-driven manner by learning input / output relationships and obtaining a trained AI / ML model for inference. AI / ML model inference refers to the process of using a trained AI / ML model to generate a series of outputs based on a series of inputs. AI / ML model validation refers to the subprocess of training that evaluates the quality of an AI / ML model using a dataset different from the one used for model training. AI / ML model testing refers to the subprocess of training that evaluates the performance of the final AI / ML model using a dataset different from the one used for model training and validation. Unlike AI / ML model validation, testing does not assume subsequent adjustments to the model.

[0101] The UE-side (AI / ML) model refers to an AI / ML model where inference is performed entirely in the UE. The Network-side (AI / ML) model refers to an AI / ML model where inference is performed entirely in the network. The One-sided (AI / ML) model refers to either the UE-side (AI / ML) model or the network-side (AI / ML) model. The Two-sided (AI / ML) model refers to a pair of AI / ML models where joint inference is performed. Here, joint inference consists of AI / ML inference where inference is performed jointly across the UE and the network. That is, the first part of inference is performed first by the UE and the remaining part by the gNB or vice versa.

[0102] AI / ML model transfer refers to the transmission of an AI / ML model over a wireless interface, either with parameters of a model structure known to the receiver or with a new model with parameters. The transfer may include a complete model or a partial model. Model download refers to the transmission of a model from the network to the UE. Model upload refers to the transmission of a model from the UE to the network.

[0103] Federated learning / federated training refers to a machine learning technique that trains AI / ML models on multiple distributed edge nodes (e.g., UEs, gNBs), each performing local model training using local data samples. This requires multiple model interactions but does not require the exchange of local data samples. Offline field data refers to data collected in the field and used for offline training of AI / ML models. Online field data refers to data collected in the field and used for online training of AI / ML models.

[0104] Model monitoring refers to the process of monitoring the inference performance of AI / ML models.

[0105] Supervised learning refers to the process of training a model using inputs and their corresponding labels. Unsupervised learning refers to the process of training a model without labeled data. Semi-supervised learning refers to the process of training a model using a mixture of labeled and unlabeled data. Reinforcement learning (RL) refers to the process of training an AI / ML model from inputs (i.e., states) and feedback signals (i.e., rewards) resulting from the model's outputs (i.e., actions) in an environment in which the model interacts.

[0106] Model activation refers to activating an AI / ML model for a specific function. Model deactivation refers to deactivating an AI / ML model for a specific function. Model switching refers to deactivating the currently activated AI / ML model and activating a different AI / ML model for a specific function.

[0107] When applying AI / ML models, the following network-UE collaboration levels are considered.

[0108] 1. Level x: No collaboration.

[0109] 2. Level y: Signaling-based collaboration without model transfer.

[0110] 3. Level z: Signal-based collaboration through model transfer.

[0111] In relation to life cycle management (LCM) procedures for AI / ML models, an AI / ML model may have a model ID with relevant information and / or model functionality for at least some AI / ML operations.

[0112] Model selection, activation, deactivation, switching, and replacement for both UE-side and bilateral models may be initiated by the network, if determined by the network, or initiated by the UE and requested by the network. If determined by the UE, the UE's decision may be reported to the network based on events configured by the network.

[0113] For AI / ML-based features / FGs (feature groups), additional conditions refer to all aspects assumed for model learning, but are not part of the terminal capabilities (UE) for the AI / ML-based features / FGs. This does not necessarily mean that additional conditions are explicitly specified. Additional conditions can be divided into two categories: network-side additional conditions and UE-side additional conditions.

[0114] For the inference of the UE-side model, the following options can be taken as possible approaches to ensure consistency between learning and inference with respect to additional NW-side conditions (if identified):

[0115] - Identification of a model to achieve alignment for additional conditions on the NW side between the NW side and the UE side.

[0116] - The model learned under additional conditions is trained in NW and transferred to UE.

[0117] - Provide information and / or instructions to the UE regarding additional conditions on the NW side.

[0118] - Consistency is supported by monitoring (model / feature selection through performance of candidate models / features on UE side by UE and / or NW).

[0119] - Other approaches are not ruled out.

[0120] - It is not denied that different approaches can achieve the same function.

[0121] In relation to data collection, it can be defined as follows:

[0122] For the UE-side AI / ML model on the UE side, the UE reports to the NW its support / preference configuration for downlink reference signal (DL RS) transmission. Regarding data collection trigger / start, data collection can be initiated / triggered by the NW's configuration or by the UE's request for data collection.

[0123] Signaling aspects for data collection, for example, signaling aspects relate to assistance information (if supported), reference signals, content / type of data collected, configuration related to Set A and / or Set B, and information about the association / mapping of Set A and Set B.

[0124] Support information (if available) provided by the network to the UE for UE data collection to classify data for the purpose of differentiating data characteristics. Support information must protect privacy / proprietary information.

[0125] For NW-side AI / ML models on the NW side, reporting-related mechanisms, additional information about the report content, reporting overhead reduction, signals / configuration / measurement / reporting for data collection, e.g., signal aspects are related to support information (if supported), reference signals.

[0126] Regarding data collection for the NW-side AI / ML models of BM-Case1 and BM-Case2, the following approaches for overhead reduction are identified:

[0127] - Omission / selection of collected data

[0128] - Compression of collected data

[0129] - If the purpose of data collection is different, the overhead reduction mechanism and the resulting specification impact may be different.

[0130] - For each LCM purpose, which mechanisms are supported (if any) and their potential specification implications (if any) are the subject of separate discussion.

[0131] Regarding data collection for the NW-side AI / ML models of BM-Case1 and BM-Case2, the following reporting signals for beam-specific aspects may be applied:

[0132] - L1 signal to report collected data

[0133] - Higher-layer signals to report collected data

[0134] - At least not applicable to AI / ML model inference

[0135] - Existing signaling principles (e.g. RSRP reporting on L1) can be reused.

[0136] RAN1 studies model identification type A, including more details related to use cases.

[0137] RAN1 explores the following options for model identification type B as a starting point, including more details relevant to all use cases:

[0138] - MI-Option 1: Model identification along with data collection related configuration and / or instructions.

[0139] - MI-Option 2: Model Identification with Dataset Transfer

[0140] - MI-Option 3: Model identification in model transfer from NW to UE

[0141] - The names (MI-Option 1, MI-Option 2, MI-Option 3) are used for discussion purposes only.

[0142] - Other options are proposed for model identification type B:

[0143] - MI-Option 4: Model Identification through Standardization of Reference Models (for CSI Compression)

[0144] - MI-Option 5: Model Identification through Model Monitoring

[0145] Regarding MI-Option 1 (Model Identification with Data Collection Related Configuration and / or Instructions) of Model Identification Type B, RAN1 further explores the following aspects:

[0146] - Relationship between model ID and data collection related configuration and / or instructions.

[0147] - Information transmitted from NW to UE (if any)

[0148] - Information transmitted from UE to NW (if any)

[0149] - Related procedures

[0150] - Use cases / applicable uses of MI-Option 1

[0151] For Model Identification Type B of MI-Option 1 (including data collection configuration and / or instructions related to model identification), RAN1 further studies the following aspects:

[0152] - Relationship between model ID and data collection related configuration and / or instructions.

[0153] - Information transmitted from the network (NW) to the UE (if any)

[0154] - Information transmitted from UE to network (NW) (if any)

[0155] - Use cases where MI-Option 1 is used or applicable

[0156] From a RAN1 perspective, for a UE-side model developed (e.g., trained, updated) on the UE side, the following procedure is an example (AI-Example 1) for further study (including feasibility / necessity) of MI-Option 1.

[0157] - A: For data collection, NW signals the data collection related configuration and its / their associated ID.

[0158] An association ID for each sub-use case associated with the NW-side additional conditions.

[0159] - B: UE collects data corresponding to the associated ID.

[0160] - C: AI / ML models are developed (e.g., trained, updated) on the UE side based on collected data corresponding to the associated ID.

[0161] - D: The UE reports its AI / ML model information corresponding to the associated ID to the NW. A model ID is determined / assigned for each AI / ML model.

[0162] Relationship between Model ID and Association ID

[0163] How the model ID is determined / assigned, for example, NW assigns the model ID, UE assigns / reports the model ID, or the association ID is considered as the model ID, and D's "model ID is determined / assigned for each AI / ML model" is not required, and the model ID is determined according to predefined rules.

[0164] D is to facilitate AI / ML model inference.

[0165] Additional interactions of steps A / B / C and association IDs between UE and NW can be considered as other solutions for consistency resolution without model identification.

[0166] With respect to the association ID, the UE assumes that the NW-side additional conditions with the same association ID are consistent at least within the cell. Further research is needed to determine whether and how the UE's assumption can be applied across multiple cells (including feasibility studies).

[0167] To ensure consistency of NW-side additional conditions throughout the learning and inference of the UE-side models for BM-Case 1 and BM-Case 2, either association ID-based or performance monitoring-based methods can be defined.

[0168] Mobility in RRC_CONNECTED

[0169] Network-controlled mobility in the RRC_CONNECTED state is divided into cell-level mobility and beam-level mobility for the terminal (UE). Beam-level mobility includes intra-cell beam mobility and inter-cell beam mobility.

[0170] Cell-level mobility requires explicit RRC signaling (handover). For example, handover between gNBs involves the following procedure:

[0171] 1. The source gNB initiates the handover by sending a HANDOVER REQUEST through the Xn interface.

[0172] 2. The target gNB performs admission control and responds by including new RRC configuration information in the HANDOVER REQUEST ACKNOWLEDGE.

[0173] 3. The source gNB forwards the RRCReconfiguration message received from the target gNB to the UE. This message contains the target cell identifier and access information, allowing the UE to access the target cell without separately reading system information. In some cases, it may also include random access-related information and beam-related information.

[0174] 4. The UE moves the RRC connection to the target gNB and responds with an RRCReconfigurationComplete message.

[0175] In case of DAPS (Dual Active Protocol Stack) handover, the UE continues to receive downlink data from the source gNB until the source cell is released, and continues to transmit uplink data to the source gNB until random access to the target gNB is successful. During DAPS handover, only the source and target PCells are used, and CA, DC, SUL, multi-TRP, EHC, CHO, UDC, NR sidelink, V2X sidelink, etc. are released before the handover command from the source gNB, and are not re-established in the target gNB until the DAPS handover is completed.

[0176] In RRC-based handovers, the UE must reset at least the MAC entity and RLC, while separate procedures apply for DAPS handovers. Depending on the RLC mode (AM / UM) of the DRB and the SRB, procedures such as PDCP entity reset, security key change, and data recovery are supported.

[0177] In case of handover failure, timer-based procedures and RRC connection re-establishment procedures are applied, and exceptions related to DAPS or CHO (Conditional Handover) are also defined.

[0178] Beam-level mobility (LBM) does not require explicit RRC signaling and can occur within a cell or between cells (Inter-cell Beam Management, ICBM). In ICBM, UEs can transmit and receive UE-dedicated channels / signals via TRPs with different PCIs (cell identifiers). The gNB provides SSB / CSI resources and measurement settings to the UE via RRC signaling, and beam mobility itself is handled through physical layer and MAC layer control signals.

[0179] SSB-based beam-level mobility is based on the SSB associated with the initial DL BWP and can only be configured for that DL BWP and DL BWPs that include the SSB. In other DL BWPs, only CSI-RS-based beam mobility is possible.

[0180] Conditional Handover

[0181] Conditional Handover (CHO) is a handover performed by the UE when one or more handover execution conditions are met. The UE begins evaluating execution conditions upon receiving the CHO configuration and ceases evaluation once the actual handover is executed.

[0182] A CHO configuration includes the configuration of a CHO candidate cell generated by a candidate gNB and the execution conditions generated by the source gNB. The execution conditions can consist of one or two trigger conditions (CHO events A3 / A5). Only one type of RS is supported at a time, and up to two different trigger indicators (such as RSRP, RSRQ, and SINR) can be set simultaneously for evaluating the execution conditions of a candidate cell.

[0183] If a HO command is received without CHO configuration before the CHO execution conditions are met, the UE follows the existing handover procedure.

[0184] From the time of CHO execution (UE starts synchronizing with the target cell), the UE does not monitor the source cell.

[0185] With regard to C-plane handling, it is stipulated as follows:

[0186] As with intra-NR RAN handovers, the preparation and execution phases of intra-NR RAN CHO are performed through direct message exchange between gNBs without 5GC intervention.

[0187] Upon completion of CHO, resource release from the source gNB is triggered by the target gNB.

[0188] The basic procedure is as follows:

[0189] 0 / 1. Mobility control information is provided by AMF, and measurement control and reporting are performed.

[0190] 2. The source gNB determines the use of CHO.

[0191] 3. The source gNB sends a CHO request message to one or more candidate gNBs for each candidate cell.

[0192] 4. The target gNB and candidate gNB perform admission control.

[0193] 5. The candidate gNB transmits the candidate cell configuration to the source gNB in ​​a CHO response (HO REQUEST ACKNOWLEDGE) message for each candidate cell.

[0194] 6. The source gNB sends an RRCReconfiguration message containing the CHO candidate cell configuration and execution conditions to the UE.

[0195] 7. The UE responds with an RRCReconfigurationComplete message.

[0196] 7a. When early data forwarding is applied, the source gNB transmits an EARLY STATUS TRANSFER message.

[0197] 8. After receiving the CHO configuration, the UE maintains a connection with the source gNB and evaluates the execution conditions of the candidate cells. If one or more candidate cells meet the execution conditions, the UE disconnects from the source gNB and completes the RRC handover procedure by applying the synchronized and stored configuration to the candidate cells (sending RRCReconfigurationComplete to the target gNB). After the handover is complete, the stored CHO configuration is deleted.

[0198] The target gNB notifies the source gNB of the UE's successful target cell access with a HANDOVER SUCCESS message. The source gNB responds with an SN STATUS TRANSFER message.

[0199] The source gNB cancels the CHO by sending a HANDOVER CANCEL message to other candidate gNBs.

[0200] Regarding U-plane handling, early data forwarding follows the same principles as DAPS handover. However, in the case of Full Configuration, after the SN assignment is transferred to the target gNB, the HFN and PDCP SN are reset on the target gNB.

[0201] When forwarding late data, the RLC-AM or RLC-UM bearer principle is followed.

[0202] For delayed data forwarding, the source NG-RAN node initiates data forwarding after identifying the target NG-RAN node to which the UE is actually connected, following the same principles as intra-system handover (except for the DAPS handover configuration DRB).

[0203] For early data forwarding, before the UE initiates a handover, the source NG-RAN node initiates data forwarding to the candidate target node of interest, following the same principles as intra-system DAPS handover.

[0204]

[0205] 3GPP has been researching the application of AI / ML models to beam management (BM), positioning, and CSI feedback use cases, and has decided to begin full-scale work on AI / ML specifications to improve beam management and positioning accuracy. Based on these research findings, efforts to apply AI / ML to communications technology are underway in various fields, and new research has begun on the topic of AI / ML-based mobility.

[0206] In the case of conventional BM, research on AI / ML for BM was conducted with the goal of reducing the burden / delay of beam measurement for mobility between beams set within a cell, as well as the overhead for reference signal resources allocated for beam measurement. NR experiences frequent link failures due to beamforming technology in high frequency bands. This also affects the decision to handover (HO) between cells, and beam link failures can result in frequent HO or HO failures. Therefore, NR mobility enhancement has been continuously discussed to solve this problem, and the following new features have been defined.

[0207] - CHO (Conditional HO)

[0208] - ICBM (Inter-Cell Beam Management)

[0209] - LTM (Lower-layer Triggered Mobility)

[0210] That is, not only HO but also BM can be considered as one of the key elements for mobility, and similar to AI / ML for beam management, various methods are being studied to improve HO performance by applying AI / ML models as a new method to ensure seamless mobility between cells, thereby predicting the strength of surrounding cells at a future point in time as well as reducing the measurement burden through measuring only some surrounding cells. This can be done not only by measuring some cells instead of all surrounding cells, but also by predicting the signal strength / quality of a cell through measuring only some beams of surrounding cells. Alternatively, by measuring surrounding cells at the current point in time and predicting the timing of reporting the measurement results and executing the handover (HO) in advance, interruption time can be minimized and HO accuracy can be improved.

[0211] To ensure link connectivity for mobile terminals, 3GPP requires continuous measurements of not only the serving cell but also surrounding cells. However, with the evolution of network architecture, cells of various sizes are emerging, leading to a burgeoning environment with a large number of cells. Consequently, terminals must measure an ever-increasing number of cells, resulting in significant overhead and increased complexity. Various technologies have been proposed for 5G to reduce this measurement burden, and measurement relaxation and mobility enhancement are currently being studied as key issues.

[0212] However, conventional measurement relaxation, which is performed based on base station settings, can lead to problems such as inability to perform HO in a timely manner, which ultimately leads to handover delay and link disconnection. Furthermore, while CHO, introduced to enhance handover reliability, reduces HO failures for terminals, it also requires preemptive handover requests and admission control for one or more cells, resulting in signaling overhead and resource waste between base stations.

[0213] With the recent application of AI / ML technologies across various communications fields, many AI / ML-based approaches are being proposed to address the high overhead and complexity of 5G. Specifically, utilizing an AI / ML model that predicts the timing of movement to a target cell by predicting the future signal strength / quality of neighboring cells can improve handover success rates and reduce handover delays by ensuring that the terminal performs inter-cell movement at the optimal time.

[0214] By applying a method to predict the signal strength of surrounding cells at a future point in time based on an AI / ML model to CHO technology, a technique for moving to the optimal cell at the optimal time needs to be defined.

[0215]

[0216] Below, a method of performing communication using artificial intelligence and machine learning will be described with reference to relevant drawings.

[0217] FIG. 8 is a diagram illustrating a procedure (800) in which a terminal performs communication using artificial intelligence and machine learning according to one embodiment.

[0218] Referring to FIG. 8, the terminal can receive conditional handover configuration information set based on the prediction result inferred through the AI / ML model from the base station (S810).

[0219] A base station, i.e., a serving base station to which a terminal is wirelessly connected, may decide to use Conditional Handover (CHO) for the terminal based on a predetermined prediction result. In one example, the prediction result may include a predicted signal strength and / or signal quality for at least one neighboring base station.

[0220] In this case, the prediction results may be acquired at the terminal and transmitted to the base station, or may be acquired at the base station based on measurement results for at least one surrounding base station transmitted by the terminal. In other words, the acquisition location of the prediction results may vary depending on whether the AI / ML model used for conditional handover is located at the terminal or the base station.

[0221] When the AI / ML model is located in the terminal, the terminal can measure the signal strength and / or signal quality of at least one surrounding base station based on preset measurement report configuration information. In this case, it can be assumed that the terminal can obtain a prediction result including the predicted signal strength and / or signal quality of at least one surrounding base station through inference of the AI / ML model based on the measurement result. The terminal can report the obtained prediction result to the base station. Alternatively, the terminal can obtain at least one predicted target base station and handover time point and report it to the base station. As long as the above-mentioned prediction results can be obtained, the AI / ML model is not limited to a specific model, and any current or future AI / ML model can be applied.

[0222] When the AI / ML model is located at the base station, the terminal can measure the signal strength and / or signal quality of at least one surrounding base station and report the measurement to the base station. Similarly, it can be assumed that the base station can use the information received from the terminal about the past serving base station and / or surrounding base stations through inference of the AI / ML model to predict the quality of the serving base station and / or surrounding base stations at a specific point in the future, or at least one target base station and the handover point.

[0223] That is, the base station can determine the target base station and the expected time of handover to the target base station based on the predicted surrounding cell quality received from the terminal or the predicted surrounding cell quality of the terminal obtained by the base station through inference. If the base station predicts / determines that the terminal will perform a handover within a specific predicted future time, it can transmit conditional handover configuration information including the execution conditions related thereto to the terminal.

[0224] For example, conditional handover configuration information may include at least one of target base station information, target time information, and threshold information. The threshold information may be set to a value that serves as a criterion for determining whether a condition for conditional handover is met. For example, the threshold may be set to a value for one of RSRP, RSRQ, and SINR, similar to the conventional MeasTriggerQuantity.

[0225] The target time information may include a target time set as either a conditional handover determination time or a conditional handover execution time, or may include information regarding the target time and a predetermined time period during which the conditional handover determination is performed. In one example, the target time information may only include information regarding the target time set as the handover execution time or the conditional handover evaluation time. Alternatively, the target time information may also include information regarding the target time and a specific time period during which measurements or conditional handover evaluations are performed for the target base station.

[0226] For example, the time period included in the target time information may represent the valid time period for a conditional handover. That is, if the handover conditions are not met within the time period, the conditional handover may be deemed to have failed. In this case, the terminal may transmit a message to the base station indicating the failure of the conditional handover.

[0227] For example, the target time can be set as the start of a set time interval, i.e., the conditional handover evaluation time. In this case, the terminal can perform a conditional handover evaluation while measuring the signal strength / quality of the target base station during the set time interval starting from the target time. If the set CHO event is satisfied during the time interval, the terminal can perform a handover to the target base station.

[0228] In another example, the target time can be set to the end of a set time interval, i.e., the handover execution time. In this case, the terminal can measure the signal strength / quality of the target base station from the time corresponding to (target time - time interval). If the set CHO event is satisfied during the time interval, the terminal can perform a handover to the target base station.

[0229] However, the description of the target time information described above is an example and is not limited thereto, and may be set differently according to various modifications and variations within a scope that does not contradict the technical idea of ​​the present disclosure.

[0230] Referring again to FIG. 8, the terminal may measure the signal strength and / or signal quality for the target base station based on the conditional handover configuration information (S820), and if the measurement result is not higher than a predetermined threshold value, may transmit a measurement report message to the base station (S830).

[0231] When conditional handover configuration information is received, the terminal can transmit a response message according to the reception of conditional handover configuration information.

[0232] Based on the conditional handover configuration information, the terminal may measure at least one of the signal strength and / or quality, for example, RSRP, RSRQ, or SINR, for the target base station according to the configured target time information. If the target time is set as the conditional handover evaluation time, the terminal may start measurement from the target time. If the target time is set as the handover execution time, the terminal may start measurement from the time corresponding to (target time - time interval).

[0233] If the measured result for the target base station is not higher than the threshold set by the conditional handover configuration information, the terminal may determine that the event condition is unsatisfied. In this case, according to an example, the terminal may transmit a measurement report message including the measured signal quality / strength result of the target base station to the serving base station. Alternatively, the terminal may transmit a message notifying the serving base station of a conditional handover failure. Alternatively, in the case of a UE-sided model, the terminal may transmit a message reporting the model performance result to the serving base station.

[0234] In this case, the measurement report message may include at least one of target base station information, measurement results, AI / ML model accuracy, and a conditional handover failure indicator. This may also apply to messages notifying conditional handover failure or reporting model performance results.

[0235] For example, as described above, the terminal may transmit a model performance result message. This may be applied when the terminal transmits the prediction result obtained using the UE-sided model to the base station. In this case, if the handover condition is not satisfied, the terminal may determine that the performance of the AI / ML model performed in the terminal is poor. Accordingly, the terminal that determines that the set condition is not satisfied may transmit a message to the base station containing information indicating poor performance of the AI / ML model / function, such as CHO failure / cancellation and the measurement result value for the target base station (cause of failure), or model accuracy (e.g., the difference between the RSRP according to the measurement result and the predicted RSRP). This may cause the terminal to expect to receive a new RRC reconfiguration message from the base station. Furthermore, the base station that received the message may transmit a handover cancellation message to the target base station.

[0236] In another example, as described above, the terminal may transmit a measurement report (MR) message. This may be applied when using a network-side model (NW-sided model) or when the model performance is calculated in the network even for the terminal-side model. By defining a MR trigger event that triggers a measurement report when a handover event condition is not satisfied, the failure / cancellation of the conditional handover can be implicitly notified to the serving base station. The measurement report message may include at least one of the actual measured target base station information, the actual measurement result value for the target base station, and an indicator indicating that the message is triggered and reported due to a failure to satisfy the conditional handover evaluation result event condition. This may be implicitly configured to be triggered by the failure / cancellation of a new execution condition for the conditional handover.

[0237] Alternatively, by explicitly defining a new event that triggers a measurement report from the terminal, the following MR-related events can be additionally set along with the execution conditions for the conditional handover, so that a measurement report can be set to be reported upon failure of the conditional handover. That is, if the set event is not satisfied within the target handover time, a measurement report including the measurement results for the target base station can be set to be triggered.

[0238] In another example, as described above, the terminal may transmit a new conditional handover failure message. This is a newly defined message that may be configured as one of the PHY / MAC / RRC control information. This is a message transmitted by the terminal to notify the base station of the conditional handover failure / cancellation when the terminal can determine whether the conditional handover has failed / cancelled. When only conditional handover evaluations performed within a specific time period are configured as valid handovers, the message may be configured to be triggered by the terminal after a configured time period when the conditional handover evaluation result performed by the terminal is not satisfied within the specified time period. In this case, the conditional handover failure message may include at least one of the target base station information that failed / cancelled the conditional handover and the cell quality / strength result value actually measured for the target base station.

[0239] Upon receiving any of the aforementioned messages, the base station can instruct Life Cycle Management (LCM) operations for the terminal's AI / ML model, such as deactivation / fallback / switching. Additionally, the base station can transmit a handover cancellation (CANCEL) message to the target base station.

[0240] Accordingly, if the predicted information is inaccurate and conditional handover fails / cancels, unnecessary handover of the terminal can be prevented, and a method for monitoring the accuracy of the AI / ML model used for conditional handover can be provided, thereby improving the overall system performance.

[0241] FIG. 9 is a diagram illustrating a procedure (900) for a base station to perform communication using artificial intelligence and machine learning according to one embodiment. The descriptions previously described in FIG. 8 may be omitted to avoid redundant explanations. In this case, the omitted content may be substantially equally applied to the base station, as long as it does not conflict with the technical spirit of the invention.

[0242] Referring to FIG. 9, the base station can transmit conditional handover configuration information set based on the target base station and handover prediction time to the terminal (S910).

[0243] The base station can determine a target base station and a predicted handover time based on a prediction result obtained from the terminal and transmitted to the base station or a measurement result for at least one surrounding base station transmitted by the terminal. The base station can decide to use a conditional handover (CHO) for the terminal based on a predetermined prediction result. In one example, the prediction result may include a predicted signal strength and / or signal quality for at least one surrounding base station.

[0244] In this case, the prediction results may be acquired at the terminal and transmitted to the base station, or may be acquired at the base station based on measurement results for at least one surrounding base station transmitted by the terminal. In other words, the acquisition location of the prediction results may vary depending on whether the AI / ML model used for conditional handover is located at the terminal or the base station.

[0245] When the AI / ML model is located in the terminal, the terminal can measure the signal strength and / or signal quality of at least one surrounding base station based on preset measurement report configuration information. In this case, it can be assumed that the terminal can obtain a prediction result including the predicted signal strength and / or signal quality of at least one surrounding base station through inference of the AI / ML model based on the measurement results. The base station can receive the obtained prediction result from the terminal. Alternatively, the base station can receive at least one predicted target base station and handover time point from the terminal.

[0246] When the AI / ML model is located at the base station, the terminal can measure the signal strength and / or signal quality of at least one surrounding base station and report the measurement to the base station. Similarly, it can be assumed that the base station can use the information received from the terminal about the past serving base station and / or surrounding base stations through inference of the AI / ML model to predict the quality of the serving base station and / or surrounding base stations at a specific point in the future, or at least one target base station and the handover point.

[0247] That is, the base station can determine the target base station of the terminal and the expected time of handover to the target base station based on the predicted surrounding cell quality received from the terminal or the predicted surrounding cell quality of the terminal obtained by the base station through inference. In other words, the base station can predict / determine that the terminal will perform a handover within a certain predicted future time.

[0248] The base station can transmit a handover request message including handover prediction time information to a target base station, and receive a handover request ACK message from the target base station.

[0249] If a base station predicts / determines that a terminal will perform a handover within a specific time in the predicted future, the base station can perform an admission control procedure for the terminal with at least one target base station in advance. That is, the base station can transmit a handover request (HO request) message containing information about the terminal to at least one target base station. In this case, the handover request message can include information about the predicted handover time. The base station can receive a response message to the handover request from the target base station that allows / denies the terminal's cell entry. If the serving base station receives a handover request acknowledgment (HO request ACK) message from the target base station allowing the terminal's entry, the following procedure can be performed.

[0250] If a base station predicts / determines that a terminal will perform a handover within a certain point in time in the predicted future, conditional handover configuration information including execution conditions related thereto may be transmitted to the terminal. In one example, the conditional handover configuration information may include at least one of target base station information, target time information, and threshold information. The threshold information may be set to a value that serves as a criterion for determining whether a condition for a conditional handover is met. In one example, the threshold may be set to a value for one of RSRP, RSRQ, and SINR, similar to the conventional MeasTriggerQuantity.

[0251] The target time information may include a target time set as either a conditional handover determination time or a conditional handover execution time, or may include information regarding the target time and a predetermined time period during which the conditional handover determination is performed. In one example, the target time information may only include information regarding the target time set as the handover execution time or the conditional handover evaluation time. Alternatively, the target time information may also include information regarding the target time and a specific time period during which measurements or conditional handover evaluations are performed for the target base station.

[0252] For example, the target time can be set as the start of a set time interval, i.e., the conditional handover evaluation time. In this case, the terminal can perform a conditional handover evaluation while measuring the signal strength / quality of the target base station during the set time interval starting from the target time. If the set CHO event is satisfied during the time interval, the terminal can perform a handover to the target base station.

[0253] In another example, the target time can be set to the end of a set time interval, i.e., the handover execution time. In this case, the terminal can measure the signal strength / quality of the target base station from the time corresponding to (target time - time interval). If the set CHO event is satisfied during the time interval, the terminal can perform a handover to the target base station.

[0254] The terminal may measure the signal strength and / or signal quality for the target base station based on conditional handover configuration information, and if the measurement result is higher than a predetermined threshold, perform a conditional handover from the base station to the target base station.

[0255] When conditional handover configuration information is transmitted, the base station can receive a response message from the terminal according to the transmission of conditional handover configuration information.

[0256] Based on the conditional handover configuration information, the terminal may measure at least one of the signal strength and / or quality, for example, RSRP, RSRQ, or SINR, for the target base station according to the configured target time information. If the target time is set as the conditional handover evaluation time, the terminal may start measurement from the target time. If the target time is set as the handover execution time, the terminal may start measurement from the time corresponding to (target time - time interval).

[0257] Again, referring to FIG. 9, the base station can receive a measurement report message from the terminal when handover fails according to conditional handover configuration information (S920).

[0258] Based on the conditional handover configuration information, the terminal may measure at least one of the signal strength and / or quality, for example, RSRP, RSRQ, or SINR, for the target base station according to the configured target time information. If the target time is set as the conditional handover evaluation time, the terminal may start measurement from the target time. If the target time is set as the handover execution time, the terminal may start measurement from the time corresponding to (target time - time interval).

[0259] If the measured result for the target base station is not higher than the threshold set by the conditional handover configuration information, the terminal may determine that the event condition is unsatisfied. In this case, according to an example, the base station may receive a measurement report message from the terminal to the serving base station, including the measured signal quality / strength result of the target base station. Alternatively, the base station may receive a message from the terminal to the serving base station notifying that the conditional handover has failed. Alternatively, the base station may receive a message from the terminal to the serving base station reporting the model performance result in the case of a UE-sided model.

[0260] In this case, the measurement report message may include at least one of target base station information, measurement results, AI / ML model accuracy, and a conditional handover failure indicator. This may also apply to messages notifying conditional handover failure or reporting model performance results.

[0261] For example, as described above, the base station may receive a model performance result message from the terminal. This may be applicable when the terminal transmits the prediction result obtained using the UE-sided model to the base station. In this case, if the handover condition is not satisfied, the terminal may determine that the performance of the AI / ML model performed on the terminal is poor. Accordingly, the terminal that determines that the set condition is not satisfied may transmit a message to the base station containing information indicating that the performance of the AI / ML model / function is poor, such as a CHO failure / cancellation and a measurement result value for the target base station (cause of failure), or model accuracy (e.g., a difference value between the RSRP according to the measurement result and the predicted RSRP). This may cause the terminal to expect to receive a new RRC reconfiguration message from the base station. Furthermore, the base station that received the message may transmit a handover cancellation message to the target base station.

[0262] In another example, as described above, the base station can receive a measurement report (MR) message from the terminal. This can be applied when using a network-side model (NW-sided model) or when the model performance is calculated in the network even for the terminal-side model. By defining a MR trigger event that triggers a measurement report when a handover event condition is not satisfied, the serving base station can implicitly notify of the failure / cancellation of the conditional handover. The measurement report message can include at least one of the target base station information that was actually measured, the actual measurement result value for the target base station, and an indicator indicating that the message is triggered and reported due to a failure to satisfy the conditional handover evaluation result event condition. This can be set implicitly, such as to be triggered by the failure / cancellation of a new execution condition for the conditional handover.

[0263] Alternatively, by explicitly defining a new event that triggers a measurement report from the terminal, the following MR-related events can be additionally set along with the execution conditions for the conditional handover, so that a measurement report can be set to be reported upon failure of the conditional handover. That is, if the set event is not satisfied within the target handover time, a measurement report including the measurement results for the target base station can be set to be triggered.

[0264] In another example, as described above, the base station may receive a new conditional handover failure message from the terminal. This is a newly defined message that may be configured as one of the PHY / MAC / RRC control information. This is a message transmitted by the terminal to notify the base station of the conditional handover failure / cancellation when the terminal can determine whether the conditional handover has failed / cancelled. When only conditional handover evaluations performed within a specific time period are configured as valid handovers, the message may be configured to be triggered by the terminal after a configured time period when the conditional handover evaluation result performed by the terminal is not satisfied within the specified time period. In this case, the conditional handover failure message may include at least one of the target base station information that failed / cancelled the conditional handover and the cell quality / strength result value actually measured for the target base station.

[0265] Referring again to FIG. 9, the base station can transmit a handover cancellation message to the target base station (S930).

[0266] Upon receiving any of the aforementioned messages, the base station can instruct Life Cycle Management (LCM) operations for the terminal's AI / ML model, such as deactivation / fallback / switching. Additionally, the base station can transmit a handover cancellation (CANCEL) message to the target base station.

[0267] Accordingly, if the predicted information is inaccurate and conditional handover fails / cancels, unnecessary handover of the terminal can be prevented, and a method for monitoring the accuracy of the AI / ML model used for conditional handover can be provided, thereby improving the overall system performance.

[0268]

[0269] Below, with reference to the relevant drawings, each embodiment related to a method of performing communication using artificial intelligence and machine learning will be described in detail.

[0270] Embodiments of the present disclosure propose a method in which a base station sets a new event for conditional handover to a terminal based on a result value for predicted surrounding cell information when a terminal uses an AI / ML model to predict cell / beam level quality / intensity for a future point in time of a surrounding cell, and proposes a method for performing a handover of a terminal using the same.

[0271] FIG. 10 is a diagram illustrating an example of temporal cell / beam level surrounding / serving cell quality / strength prediction using AI / ML according to one embodiment. As illustrated in FIG. 10, it is assumed that a terminal measures cell / beam level quality / strength for surrounding cells and a serving cell, and uses this as input value to predict cell / beam level quality / strength for the surrounding / serving cell for N future time instances (N time instance(s)).

[0272] In the present disclosure, the AI / ML model can be located in the terminal or the base station. If the AI / ML model is located in the terminal, it is assumed that the terminal reports predicted cell results (or target cells (target cell(s) and HO time) for neighboring cells to the base station based on measurement report information set by the base station. If the AI / ML model inference is performed in the base station, it is assumed that the base station can predict the serving / surrounding cell quality (or target cell(s) and HO time) of the future N time instances using the past serving / surrounding cell information received from the terminal. That is, the base station can determine the target cell of the terminal and the expected HO time to the target cell based on the predicted neighboring cell quality received from the terminal or the predicted neighboring cell quality of the terminal obtained by the base station through inference.

[0273] If the base station predicts / determines that the terminal will perform HO within the predicted future N time instances based on the above information, it transmits conditional handover (CHO) configuration information including execution conditions related thereto to the terminal, and the terminal, upon receiving the information, performs CHO evaluation based on the configuration information and performs HO if the condition is satisfied. However, if the CHO evaluation result of the terminal does not satisfy the set condition at the expected HO time, the terminal does not perform HO to the target cell and reports the result to the base station.

[0274] More specifically, the present disclosure defines a new execution condition that can be set to a terminal based on the predicted results, and proposes a conditional HO and AI / ML model monitoring method using the same.

[0275] A new execution condition that can be included in the conditional handover proposed in this disclosure can be defined as follows.

[0276] CondEvent A4T2 (Conditional reconfiguration target measured at a target time is higher than absolute threshold)

[0277] That is, the signal strength / quality for the target cell is measured at a set target time (future point in time), and if the measured result is higher than a threshold, the event is considered to have entered the condition.

[0278] As described above, the base station transmits a conditional reconfiguration message to the terminal, which includes at least one of the predicted HO time instance of the terminal, information about the target gNB / cell, and threshold information for the event. Here, the threshold information is preferably set to a value of one of RSRP, RSRQ, and SINR (i.e., the conventional MeasTriggerQuantity). The base station that decides to transmit the message to the terminal performs an admission control procedure for the target gNB(s) and the terminal in advance before transmitting the message to the terminal. That is, the base station transmits a handover request (HO request) message including information about the terminal to the target cell(s). This may include the predicted HO time instance. The target base station that receives this transmits a response message to the HO request, allowing / rejecting the terminal's cell entry, to the base station. If the serving base station receives a handover request ACK (HO request ACK) message from the target base station allowing the terminal to enter, the base station transmits a conditional reconfiguration message to the terminal including at least one of the predicted HO time information (target time), target cell / gNB information, and a threshold for the corresponding event based on the CondEvent A4T2. The terminal receiving the conditional reconfiguration message from the serving base station measures the signal strength / quality (i.e., the indicated RSRP or RSRQ or SINR) for the target cell received in the message at the target time indicated in the message. At this time, if the measured result value of the target cell is greater than the threshold (i.e., if the event condition is satisfied), the terminal performs HO to the target cell.That is, if the above conditions are met, the terminal disconnects from the serving base station and establishes a connection (synchronization) with the target base station. Upon recognizing the terminal's successful entry, the target base station can transmit a HO Success message to the serving base station, notifying the terminal of its successful HO.

[0279] Figures 11 and 12 are diagrams illustrating an example of a timing of an operation according to an embodiment. The target time set in the above conditions may be defined together with a time period, which means a specific time period for performing a measurement to the target gNB or starting a CHO evaluation. That is, as illustrated in Figure 11, the signal strength / quality of the target cell is measured during a set period from the target time while performing a CHO evaluation, and if the set CHO event is satisfied during this period, HO to the target cell can be performed.

[0280] Alternatively, as illustrated in Fig. 12, the target time can be defined to mean the point in time at which HO to the target gNB is performed, in which case the signal strength / quality of the target cell is measured from the point in time (target time - period) through a period defined together. If the set CHO event is satisfied during the period, HO can be performed at the target time.

[0281] The definitions of the period and predicted HO point in time proposed in this disclosure are merely illustrative of the technical idea of ​​this disclosure, and various modifications and variations of the definitions are possible without departing from the essential characteristics.

[0282]

[0283] The following describes the operation of a terminal and a base station according to the technology of the present disclosure. FIG. 13 is a diagram illustrating an example of the operation of a terminal and a base station performing a handover according to one embodiment.

[0284] [Terminal operation]

[0285] -[In case of UE-sided model] The terminal reports a measurement report message including information on surrounding cells predicted by the base station to the base station.

[0286] -[In case of NW-sided model] The terminal reports a measurement report message including surrounding cell information to the base station.

[0287] - The terminal receives an RRCreconfiguration message containing conditional reconfiguration information set based on AI / ML prediction results from the base station. The message includes at least one of the following pieces of information:

[0288] o (Predicted) Target cell / gNB information;

[0289] o (Predicted) Information on the timing of HO performance (or CHO evaluation) to the target cell / gNB;

[0290] This can be defined by specific point in time and period information, and the specific point in time can mean the point in time when CHO evaluation starts or the point in time when HO is performed based on the CHO evaluation results.

[0291] o Threshold information.

[0292] Can be directed by the base station as one of RSRP, RSRQ, and SINR

[0293] - The terminal transmits a response message for the conditional reconfiguration to the base station.

[0294] - The terminal performs CHO evaluation based on the settings of the conditional reconfiguration message received above.

[0295] o Check whether the measurement result value of the target base station at the set time is better than the threshold.

[0296] - If the evaluation result satisfies the set conditions, the terminal performs HO from the serving base station to the target base station.

[0297] o Disconnect from the Serving gNB; and

[0298] o Perform synchronization with the target gNB.

[0299] [Serving Base Station Operation]

[0300] -[In case of UE-sided model] The base station receives a measurement report message including predicted surrounding / serving cell information (i.e., surrounding / serving cell quality and strength at a future point in time) from the terminal.

[0301] -[In case of NW-sided model] The base station predicts the surrounding cell information of the terminal (i.e., surrounding / serving cell quality and strength at a future point in time) based on the surrounding / serving cell information received from the terminal.

[0302] - The base station determines / predicts the HO time point of the terminal and at least one target gNB / cell based on prediction information about the surrounding / serving cells received from the terminal or predicted by the base station.

[0303] - The serving base station requests HO of the terminal to the determined target gNB (sends a HO request message).

[0304] o This may include predicted HO timing information of the terminal.

[0305] - The serving base station receives an HO request ACK from the target base station, allowing the terminal to enter.

[0306] - The base station transmits an RRCreconfiguration message to the terminal containing conditional reconfiguration information set based on the AI / ML prediction results. The message includes at least one of the following pieces of information:

[0307] o (Predicted) target cell / gNB information;

[0308] o (Predicted) Information on the timing of HO performance (or CHO evaluation) to the target cell / gNB;

[0309] This can be defined by specific point in time and period information, and the specific point in time can mean the point in time when CHO evaluation starts or the point in time when HO is performed based on the CHO evaluation results.

[0310] o Threshold information.

[0311] Can be directed by the base station as one of RSRP, RSRQ, and SINR

[0312] - The base station receives a response message for the conditional reconfiguration from the terminal.

[0313] - The base station receives a HO success message indicating successful HO of the terminal from the target base station after the target time.

[0314]

[0315] This disclosure further defines a method for reporting the results of a CHO failure / cancellation of a UE. Assume that a conditional reconfiguration including a new event condition (execution condition, CondEvent A4T2) proposed in this disclosure is received from a base station, and a CHO evaluation is performed based on the configured information, but the event condition is not satisfied. That is, if the UE performs measurement toward a target gNB at a target time, but the measurement result is worse than a threshold, the UE proposes to transmit a message notifying the CHO failure to the serving base station, a message reporting the model performance result (i.e., in the case of a UE-sided model), or a measurement report message including the measured signal quality / strength result of the target cell.

[0316] Figure 14 is a diagram illustrating an example of the operations of a terminal and a base station when a conditional handover fails according to one embodiment. The reporting message for CHO failure / cancellation can be defined in different message formats depending on the model location and monitoring method. Upon receiving the proposed message, the base station can instruct LCM operations for the model / function, such as deactivation / fallback / switching of the terminal's AI / ML model, based on the message. This disclosure describes an embodiment of this.

[0317] First, we define a case where a model performance result message is transmitted. This can be applied when a UE uses a UE-sided model to predict the signal strength / quality of a neighboring / serving cell to a base station and transmits a measurement report including the results for the predicted neighboring / serving cell to the base station. In other words, the base station uses the predicted results of the AI / ML model performed by the UE to predict the target base station and HO timing for CHO. If the UE performs CHO evaluation through the CHO set based on this and the conditions are not met, the UE can determine that the performance of the AI / ML model performed on the UE is poor. In this way, a UE that determines that the set conditions are not met can transmit a message to the serving base station containing information indicating poor performance of its AI / ML model / function (e.g., CHO failure / cancellation and measurement result value for the target cell (cause of failure), or model accuracy (e.g., difference value between RSRP according to the measured results and the predicted RSRP)). This allows the terminal to expect to receive a new RRC reconfiguration message from the base station, and the base station receiving the proposed message notifies the target base station that the HO of the terminal is cancelled by sending a HO cancellation message.

[0318] Next, we define a case in which a measurement report (MR) message is transmitted. This method can be applied when using a network-side model (NW-sided model) or when calculating model performance in a UE-sided model at the NW. When a UE performs the CHO evaluation proposed in this disclosure but does not satisfy the event condition, this can be defined as an MR trigger event that triggers a measurement report, thereby implicitly notifying the serving base station of CHO failure / cancellation. The measurement report message can include at least one of the actual measured target cell information, the actual measurement result value for the target cell, and an indicator indicating that the message is triggered and reported due to the CHO evaluation result not satisfying the event condition. This can be defined implicitly, such as triggering by a failure / cancellation of a new execution condition (e.g., CondEvent A4T2) for the conditional handover proposed in this disclosure. Alternatively, a measurement report can be defined to be reported upon failure of conditional handover by additionally setting the following MR-related event together with the execution condition for the proposed conditional handover by explicitly defining a new event that triggers a measurement report of the terminal.

[0319] Event C1 (CondEvent A4T2 is not satisfied, ie, Conditional reconfiguration target measured at a target time is worse than absolute threshold)

[0320] If CondEvent A4T2 is set and the event set by CondEvent A4T2 is not satisfied within the target HO time point, a measurement report including the measurement result for the target cell is triggered.

[0321] That is, the signal strength / quality for the target cell is measured at the target time (e.g., the expected time of HO execution or the time of HO evaluation completion), and if the measured result is worse than the threshold, the event is considered to have entered the condition.

[0322] The event may be set up with CondEvent A4T2 proposed in this disclosure, or may be defined with target gNB / cell information, target time, and threshold identical to the parameters set in CondEvnet A4T2.

[0323] Finally, we define a case where a new CHO failure (or HO cancel) message is transmitted. This is a newly defined message and can be defined as one of the PHY / MAC / RRC control information. This is a message transmitted by the terminal to notify the base station of CHO failure / cancellation when the terminal can determine whether CHO failure / cancellation can be performed by conditional reconfiguration set by the base station. In a case where only CHO evaluations within a specific time period are defined as valid HO, such as the new conditional event (CondEvent) proposed in the present invention, this is defined as a message that can be triggered by the terminal after a set time period when the CHO evaluation result performed by the terminal is not satisfied within the specified time period. The CHO failure (or HO cancel) message proposed in the present disclosure includes at least one of the target cell information that failed / cancelled CHO and the cell quality / strength result value actually measured for the corresponding cell.

[0324] [Terminal operation]

[0325] - The terminal receives an RRCreconfiguration message containing conditional reconfiguration information set based on AI / ML prediction results from the base station. The message includes at least one of the following pieces of information:

[0326] o (Predicted) Target cell / gNB information;

[0327] o (Predicted) Information on the timing of HO performance (or CHO evaluation) to the target cell / gNB;

[0328] This can be defined by specific point in time and period information, and the specific point in time can mean the point in time when CHO evaluation starts or the point in time when HO is performed based on the CHO evaluation results.

[0329] o Threshold information.

[0330] Can be directed by the base station as one of RSRP, RSRQ, and SINR

[0331] - The terminal transmits a response message for the conditional reconfiguration to the base station.

[0332] - The terminal performs CHO evaluation based on the settings of the conditional reconfiguration message received above.

[0333] o Check whether the measurement result value of the target base station at the set time is better than the threshold.

[0334] - If the evaluation result does not satisfy the set condition, the terminal transmits a message to the serving base station to notify this. This message may be one of the following, and the message may include at least one of target cell information, measured quality / strength results for the target cell, model accuracy, and an indicator indicating CHO failure / cancellation.

[0335] o Terminal model performance result message; or

[0336] o Measurement report message; or

[0337] o CHO failure (or HO cancel) message.

[0338] [Serving Base Station Operation]

[0339] - The base station determines / predicts the HO time point of the terminal and at least one target gNB / cell based on prediction information about the surrounding / serving cells received from the terminal or predicted by the base station.

[0340] - The serving base station requests HO of the terminal to the determined target gNB (sends a HO request message).

[0341] o This may include predicted HO timing information of the terminal.

[0342] - The serving base station receives an HO request ACK from the target base station, allowing the terminal to enter.

[0343] - The base station transmits an RRCreconfiguration message to the terminal containing conditional reconfiguration information set based on the AI / ML prediction results. The message includes at least one of the following pieces of information:

[0344] o Target cell / gNB information;

[0345] o Information on the timing of HO performance (or CHO evaluation) to the target cell / gNB;

[0346] o Threshold information.

[0347] - The base station receives a response message for the conditional reconfiguration from the terminal.

[0348] - If the base station receives one of the following messages from the terminal after the target time, it recognizes that the terminal's CHO has failed. The received message may include at least one of target cell information, measured quality / strength results for the target cell, model accuracy, and an indicator indicating CHO failure / cancellation.

[0349] o Terminal model performance result message; or

[0350] o Measurement report message; or

[0351] o CHO failure (or HO cancel) message.

[0352] - The base station transmits a HO cancel message to the target base station.

[0353] According to embodiments of the present disclosure, by pre-setting predicted handover timing information so that a terminal can perform handover to a target base station at an optimal timing with minimal handover delay, the burden of cell measurement on the terminal and the probability of handover failure can be minimized, and overall system performance can be improved.

[0354] Additionally, in case of CHO failure / cancellation, it can improve the overall system performance by not only preventing unnecessary HO of the terminal but also providing a way to monitor the accuracy of the AI / ML model used for HO / surrounding cell quality prediction.

[0355]

[0356] Hereinafter, the configuration of a terminal and a base station capable of performing some or all of the embodiments described with reference to FIGS. 1 to 14 will be described with reference to the drawings. The above description may be omitted to avoid redundant description, and in this case, the omitted content may be substantially equally applied to the following description, as long as it does not contradict the technical spirit of the invention.

[0357] Fig. 15 is a drawing showing the configuration of a terminal (1500) according to another embodiment.

[0358] Referring to FIG. 15, a terminal (1500) according to another embodiment includes a transmitter (1520), a receiver (1530), and a control unit (1510) that controls the transmitter and receiver.

[0359] The control unit (1510) controls the overall operation of the terminal (1500) according to the method of performing communication using artificial intelligence and machine learning necessary to perform the aforementioned embodiments.

[0360] The transmitter (1520) and receiver (1530) are used to transmit and receive signals, messages, and data necessary to perform the aforementioned embodiments with the base station.

[0361] The control unit (1510) may receive conditional handover configuration information from a base station based on the predicted results inferred through the AI / ML model. The base station, i.e., the serving base station to which the terminal is wirelessly connected, may decide to use conditional handover (CHO) for the terminal based on the predetermined predicted results. In one example, the predicted results may include predicted signal strength and / or signal quality for at least one neighboring base station.

[0362] In this case, the prediction results may be acquired at the terminal and transmitted to the base station, or may be acquired at the base station based on measurement results for at least one surrounding base station transmitted by the terminal. In other words, the acquisition location of the prediction results may vary depending on whether the AI / ML model used for conditional handover is located at the terminal or the base station.

[0363] When the AI / ML model is located in the terminal, the control unit (1510) can measure the signal strength and / or signal quality of at least one surrounding base station based on preset measurement report configuration information. In this case, it can be assumed that the control unit (1510) can obtain a prediction result including a predicted signal strength and / or signal quality of at least one surrounding base station through inference of the AI / ML model based on the measurement result. The control unit (1510) can report the obtained prediction result to the base station. Alternatively, the control unit (1510) can obtain at least one predicted target base station and handover time point and report them to the base station.

[0364] When the AI / ML model is located at the base station, the control unit (1510) can measure the signal strength and / or signal quality of at least one surrounding base station and perform measurement reporting to the base station. Similarly, it can be assumed that the base station can predict the quality of the serving base station and / or surrounding base stations at a specific point in the future, or at least one target base station and the handover point, by using information about past serving base stations and / or surrounding base stations received from the terminal through inference of the AI / ML model.

[0365] That is, the base station can determine the target base station and the expected time of handover to the target base station based on the predicted surrounding cell quality received from the terminal or the predicted surrounding cell quality of the terminal obtained by the base station through inference. If the base station predicts / determines that the terminal will perform a handover within a specific predicted future time, it can transmit conditional handover configuration information including the execution conditions related thereto to the terminal.

[0366] For example, conditional handover configuration information may include at least one of target base station information, target time information, and threshold information. The threshold information may be set to a value that serves as a criterion for determining whether a condition for conditional handover is met. For example, the threshold may be set to a value for one of RSRP, RSRQ, and SINR, similar to the conventional MeasTriggerQuantity.

[0367] The target time information may include a target time set as either a conditional handover determination time or a conditional handover execution time, or may include information regarding the target time and a predetermined time period during which the conditional handover determination is performed. In one example, the target time information may only include information regarding the target time set as the handover execution time or the conditional handover evaluation time. Alternatively, the target time information may also include information regarding the target time and a specific time period during which measurements or conditional handover evaluations are performed for the target base station.

[0368] For example, the target time may be set as the start point of a set time interval, i.e., the conditional handover evaluation time. In this case, the control unit (1510) may perform a conditional handover evaluation while measuring the signal strength / quality of the target base station during the set time interval from the target time. If the set CHO event is satisfied during the time interval, the control unit (1510) may perform a handover to the target base station.

[0369] In another example, the target time may be set to the end of a set time interval, i.e., the handover execution time. In this case, the control unit (1510) may measure the signal strength / quality of the target base station from a time corresponding to (target time - time interval). If the set CHO event is satisfied during the time interval, the control unit (1510) may perform a handover to the target base station.

[0370] The control unit (1510) measures the signal strength and / or signal quality for the target base station based on the conditional handover configuration information, and if the measurement result is higher than a predetermined threshold, can perform a conditional handover from the base station to the target base station.

[0371] When conditional handover configuration information is received, the control unit (1510) can transmit a response message according to the reception of the conditional handover configuration information.

[0372] Based on the conditional handover configuration information, the control unit (1510) can measure at least one of the signal strength and / or quality, for example, RSRP, RSRQ, or SINR, for the target base station according to the set target time information. If the target time is set as the conditional handover evaluation time, the control unit (1510) can start the measurement from the target time. If the target time is set as the handover execution time, the control unit (1510) can start the measurement from the time corresponding to (target time - time interval).

[0373] If the result value for the measured target base station is not higher than the threshold value set by the conditional handover configuration information, the control unit (1510) may determine that the event condition is unsatisfied. In this case, according to an example, the control unit (1510) may transmit a measurement report message including the measured signal quality / strength result of the target base station to the serving base station. Alternatively, the control unit (1510) may transmit a message notifying the conditional handover failure to the serving base station. Alternatively, the control unit (1510) may transmit a message reporting the model performance result to the serving base station in the case of a UE-sided model.

[0374] In this case, the measurement report message may include at least one of target base station information, measurement results, AI / ML model accuracy, and a conditional handover failure indicator. This may also apply to messages notifying conditional handover failure or reporting model performance results.

[0375] For example, as described above, the control unit (1510) may transmit a model performance result message. This may be applied when the terminal transmits the prediction result obtained using the UE-sided model to the base station. In this case, if the handover condition is not satisfied, the control unit (1510) may determine that the performance of the AI / ML model performed in the terminal is poor. Accordingly, the control unit (1510) that determines that the set condition is not satisfied may transmit a message to the base station containing information indicating that the performance of the AI / ML model / function is poor, such as a CHO failure / cancellation and a measurement result value for the target base station (cause of failure), or model accuracy (e.g., a difference value between the RSRP according to the measurement result and the predicted RSRP). This may cause the control unit (1510) to expect to receive a new RRC reconfiguration message from the base station. In addition, the base station that received the message may transmit a handover cancellation message to the target base station.

[0376] In another example, as described above, the control unit (1510) may transmit a measurement report (MR) message. This may be applied when a network-side model (NW-sided model) is used, or even when the model performance is calculated in the network for a terminal-side model. By defining this as an MR trigger event that triggers a measurement report when a handover event condition is not satisfied, the failure / cancellation of the conditional handover can be implicitly notified to the serving base station. The measurement report message may include at least one of the actual measured target base station information, the actual measurement result value for the target base station, and an indicator indicating that the message is triggered and reported due to the conditional handover evaluation result not being satisfied. This may be set implicitly, such as to be triggered by the failure / cancellation of a new execution condition for the conditional handover.

[0377] Alternatively, by explicitly defining a new event that triggers a measurement report from the terminal, the following MR-related events can be additionally set along with the execution conditions for the conditional handover, so that a measurement report can be set to be reported upon failure of the conditional handover. That is, if the set event is not satisfied within the target handover time, a measurement report including the measurement results for the target base station can be set to be triggered.

[0378] In another example, as described above, the control unit (1510) may transmit a new conditional handover failure message. This is a newly defined message that may be configured as one of the PHY / MAC / RRC control information. This is a message that the terminal transmits to the base station to notify the terminal of the conditional handover failure / cancellation when the terminal can determine whether the conditional handover has failed / cancelled. When only conditional handover evaluations performed within a specific time period are configured as valid handovers, the message may be configured to be triggered by the terminal after a configured time period when the conditional handover evaluation result performed by the terminal is not satisfied within the specified time period. In this case, the conditional handover failure message may include at least one of the target base station information that failed / cancelled the conditional handover and the cell quality / strength result value actually measured for the target base station.

[0379] Upon receiving any of the aforementioned messages, the base station can instruct Life Cycle Management (LCM) operations for the terminal's AI / ML model, such as deactivation / fallback / switching. Additionally, the base station can transmit a handover cancellation (CANCEL) message to the target base station.

[0380] Accordingly, if the predicted information is inaccurate and conditional handover fails / cancels, unnecessary handover of the terminal can be prevented, and a method for monitoring the accuracy of the AI / ML model used for conditional handover can be provided, thereby improving the overall system performance.

[0381] Fig. 16 is a drawing showing the configuration of a base station (1600) according to another embodiment.

[0382] Referring to FIG. 16, a base station (1600) according to another embodiment includes a transmitter (1620), a receiver (1630), and a control unit (1610) that controls the transmitter and receiver.

[0383] The control unit (1610) controls the overall operation of the base station (1600) and the operation of the repeater according to the method of performing communication using artificial intelligence and machine learning necessary to perform the aforementioned embodiments.

[0384] The transmitter (1620) and receiver (1630) are used to transmit and receive signals, messages, and data necessary for performing the above-described embodiments to and from the terminal.

[0385] The control unit (1610) may determine a target base station and a predicted handover time based on a prediction result obtained from the terminal and transmitted to the base station or a measurement result for at least one surrounding base station transmitted by the terminal. The control unit (1610) may determine to use a conditional handover (CHO) for the terminal based on a predetermined prediction result. In one example, the prediction result may include a predicted signal strength and / or signal quality for at least one surrounding base station.

[0386] In this case, the prediction results may be acquired at the terminal and transmitted to the base station, or may be acquired at the base station based on measurement results for at least one surrounding base station transmitted by the terminal. In other words, the acquisition location of the prediction results may vary depending on whether the AI / ML model used for conditional handover is located at the terminal or the base station.

[0387] When the AI / ML model is located in the terminal, the terminal can measure the signal strength and / or signal quality of at least one surrounding base station based on preset measurement report configuration information. In this case, it can be assumed that the terminal can obtain a prediction result including the predicted signal strength and / or signal quality of at least one surrounding base station through inference of the AI / ML model based on the measurement results. The control unit (1610) can receive the obtained prediction result from the terminal. Alternatively, the control unit (1610) can receive at least one predicted target base station and handover time point from the terminal.

[0388] When the AI / ML model is located at the base station, the terminal can measure the signal strength and / or signal quality of at least one surrounding base station and perform measurement reporting to the base station. Similarly, it can be assumed that the control unit (1610) can use information about past serving base stations and / or surrounding base stations received from the terminal through inference of the AI / ML model to predict the quality of the serving base station and / or surrounding base stations at a specific point in the future, or at least one target base station and the handover point in time.

[0389] That is, the control unit (1610) can determine the target base station of the terminal and the expected time of handover to the target base station based on the predicted surrounding cell quality received from the terminal or the predicted surrounding cell quality of the terminal obtained by the base station through inference. That is, the control unit (1610) can predict / determine that the terminal will perform handover within a specific predicted time in the future.

[0390] The control unit (1610) can transmit a handover request message including handover prediction time information to the target base station and receive a handover request ACK message from the target base station.

[0391] If the base station predicts / determines that the terminal will perform a handover within a specific time in the predicted future, the control unit (1610) can perform an admission control procedure for at least one target base station and the terminal in advance. That is, the control unit (1610) can transmit a handover request (HO request) message including information about the terminal to at least one target base station. In this case, the handover request message can include information about the predicted handover time. The control unit (1610) can receive a response message to the handover request from the target base station that allows / denies the terminal's cell entry. If the control unit (1610) receives a handover request acknowledgment (HO request ACK) message from the target base station that allows the terminal's entry, the following procedure can be performed.

[0392] The control unit (1610) can transmit conditional handover configuration information set based on the target base station and handover prediction time to the terminal.

[0393] If the base station predicts / determines that the terminal will perform a handover within a specific point in time in the predicted future, the control unit (1610) may transmit conditional handover configuration information including execution conditions related thereto to the terminal. In one example, the conditional handover configuration information may include at least one of target base station information, target time information, and threshold information. The threshold information may be set to a value that serves as a criterion for whether the condition for conditional handover is met. In one example, the threshold may be set to a value for one of RSRP, RSRQ, and SINR, similar to the conventional MeasTriggerQuantity.

[0394] The target time information may include a target time set as either a conditional handover determination time or a conditional handover execution time, or may include information regarding the target time and a predetermined time period during which the conditional handover determination is performed. In one example, the target time information may only include information regarding the target time set as the handover execution time or the conditional handover evaluation time. Alternatively, the target time information may also include information regarding the target time and a specific time period during which measurements or conditional handover evaluations are performed for the target base station.

[0395] For example, the target time can be set as the start of a set time interval, i.e., the conditional handover evaluation time. In this case, the terminal can perform a conditional handover evaluation while measuring the signal strength / quality of the target base station during the set time interval starting from the target time. If the set CHO event is satisfied during the time interval, the terminal can perform a handover to the target base station.

[0396] In another example, the target time can be set to the end of a set time interval, i.e., the handover execution time. In this case, the terminal can measure the signal strength / quality of the target base station from the time corresponding to (target time - time interval). If the set CHO event is satisfied during the time interval, the terminal can perform a handover to the target base station.

[0397] The terminal may measure the signal strength and / or signal quality for the target base station based on conditional handover configuration information, and if the measurement result is higher than a predetermined threshold, perform a conditional handover from the base station to the target base station.

[0398] When conditional handover configuration information is transmitted, the control unit (1610) can receive a response message from the terminal according to the transmission of conditional handover configuration information.

[0399] The control unit (1610) can receive a measurement report message from the terminal when handover fails according to conditional handover configuration information.

[0400] Based on the conditional handover configuration information, the terminal may measure at least one of the signal strength and / or quality, for example, RSRP, RSRQ, or SINR, for the target base station according to the configured target time information. If the target time is set as the conditional handover evaluation time, the terminal may start measurement from the target time. If the target time is set as the handover execution time, the terminal may start measurement from the time corresponding to (target time - time interval).

[0401] If the measured result for the target base station is not higher than the threshold value set by the conditional handover configuration information, the terminal may determine that the event condition is unsatisfied. In this case, according to an example, the control unit (1610) may receive a measurement report message including the measured signal quality / strength result of the target base station from the terminal to the serving base station. Alternatively, the control unit (1610) may receive a message from the terminal to the serving base station notifying that the conditional handover has failed. Alternatively, the control unit (1610) may receive a message from the terminal to the serving base station reporting the model performance result in the case of a UE-sided model.

[0402] In this case, the measurement report message may include at least one of target base station information, measurement results, AI / ML model accuracy, and a conditional handover failure indicator. This may also apply to messages notifying conditional handover failure or reporting model performance results.

[0403] For example, as described above, the control unit (1610) may receive a model performance result message from the terminal. This may be applied when the terminal transmits the prediction result obtained using the terminal-side model (UE-sided model) to the base station. In this case, if the handover condition is not satisfied, the terminal may determine that the performance of the AI / ML model performed in the terminal is poor. Accordingly, the terminal that determines that the set condition is not satisfied may transmit a message to the base station containing information indicating that the performance of the AI / ML model / function is poor, such as a CHO failure / cancellation and a measurement result value for the target base station (cause of failure), or model accuracy (e.g., a difference value between the RSRP according to the measurement result and the predicted RSRP). This may allow the terminal to expect to receive a new RRC reconfiguration message from the base station. In addition, the control unit (1610) that receives the message may transmit a handover cancellation message to the target base station.

[0404] In another example, as described above, the control unit (1610) may receive a measurement report (MR) message from the terminal. This may be applied when a network-side model (NW-sided model) is used, or even when the terminal-side model has model performance calculated in the network. By defining this as an MR trigger event that triggers a measurement report when a handover event condition is not satisfied, the control unit (1610) may implicitly detect failure / cancellation of a conditional handover. The measurement report message may include at least one of actual measured target base station information, actual measurement result values ​​for the target base station, and an indicator indicating that the message is triggered and reported due to failure to satisfy the conditional handover evaluation result event condition. This may be set implicitly, such as to be triggered by failure / cancellation of a new execution condition for the conditional handover.

[0405] Alternatively, by explicitly defining a new event that triggers a measurement report from the terminal, the following MR-related events can be additionally set along with the execution conditions for the conditional handover, so that a measurement report can be set to be reported upon failure of the conditional handover. That is, if the set event is not satisfied within the target handover time, a measurement report including the measurement results for the target base station can be set to be triggered.

[0406] In another example, as described above, the base station may receive a new conditional handover failure message from the terminal. This is a newly defined message that may be configured as one of the PHY / MAC / RRC control information. This is a message transmitted by the terminal to notify the base station of the conditional handover failure / cancellation when the terminal can determine whether the conditional handover has failed / cancelled. When only conditional handover evaluations performed within a specific time period are configured as valid handovers, the message may be configured to be triggered by the terminal after a configured time period when the conditional handover evaluation result performed by the terminal is not satisfied within the specified time period. In this case, the conditional handover failure message may include at least one of the target base station information that failed / cancelled the conditional handover and the cell quality / strength result value actually measured for the target base station.

[0407] The control unit (1610) may transmit a handover cancel message to the target base station. Upon receiving any of the aforementioned messages, the base station may, based on the received message, instruct LCM (Life Cycle Management) operations for the model / function, such as deactivation / fallback / switching of the AI / ML model of the terminal. Additionally, the base station may transmit a handover cancel (CANCEL) message to the target base station.

[0408] Accordingly, if the predicted information is inaccurate and conditional handover fails / cancels, unnecessary handover of the terminal can be prevented, and a method for monitoring the accuracy of the AI / ML model used for conditional handover can be provided, thereby improving the overall system performance.

[0409] The above-described embodiments may be supported by standard documents disclosed in at least one of the wireless access systems, IEEE 802, 3GPP, and 3GPP2. That is, steps, components, and parts not described in the present embodiments to clearly illustrate the technical concepts herein may be supported by the above-described standard documents. Furthermore, all terms disclosed in this specification may be explained by the above-described standard documents.

[0410] The embodiments described above may be implemented through various means. For example, the embodiments may be implemented through hardware, firmware, software, or a combination thereof.

[0411] In the case of hardware implementation, the method according to the present embodiments may be implemented by one or more ASICs (Application Specific Integrated Circuits), DSPs (Digital Signal Processors), DSPDs (Digital Signal Processing Devices), PLDs (Programmable Logic Devices), FPGAs (Field Programmable Gate Arrays), processors, controllers, microcontrollers, or microprocessors.

[0412] When implemented using firmware or software, the methods according to the present embodiments may be implemented in the form of devices, procedures, or functions that perform the functions or operations described above. The software code may be stored in a memory unit and executed by a processor. The memory unit may be located within or outside the processor and may exchange data with the processor using various known means.

[0413] Additionally, terms such as "system," "processor," "controller," "component," "module," "interface," "model," or "unit" as described above may generally refer to a computer-related entity, such as hardware, a combination of hardware and software, software, or software in execution. For example, the aforementioned components may be, but are not limited to, a process driven by a processor, a processor, a controller, a control processor, an object, a thread of execution, a program, and / or a computer. For example, both an application running on a controller or a processor and the controller or the processor may be components. One or more components may be within a process and / or thread of execution, and the components may be located on a single device (e.g., a system, a computing device, etc.) or distributed across two or more devices.

[0414] The above description is merely an illustrative example of the technical idea of ​​the present disclosure, and those skilled in the art to which the present disclosure pertains will appreciate that various modifications and variations can be made without departing from the essential characteristics of the technical idea of ​​the present disclosure. In addition, the present embodiments are not intended to limit the technical idea of ​​the present disclosure but rather to explain it, and therefore the scope of the technical idea of ​​the present disclosure is not limited by these embodiments. The scope of protection of the present disclosure should be interpreted by the claims below, and all technical ideas within a scope equivalent thereto should be interpreted as being included within the scope of the rights of the present disclosure.

[0415]

[0416] CROSS-REFERENCE TO RELATED APPLICATION

[0417] This patent application claims priority under 35 USC §119(a) to Korean Patent Application No. 10-2024-0094040, filed in Korea on July 16, 2024, and Korean Patent Application No. 10-2025-0095317, filed in Korea on July 15, 2025, the entire contents of which are incorporated herein by reference. In addition, this patent application claims priority in countries other than the United States for the same reasons, the entire contents of which are incorporated herein by reference.

Claims

1. A method for a terminal (user equipment; UE) to perform communication using artificial intelligence and machine learning (AI / ML), A step of receiving conditional handover configuration information set based on a prediction result inferred through an AI / ML model from a base station; A step of measuring signal strength and / or signal quality for a target base station based on the above conditional handover configuration information; and A method comprising the step of transmitting a measurement report message to the base station if the result of the above measurement is not higher than a predetermined threshold value.

2. In paragraph 1, The above prediction results are, A method comprising predicting signal strength and / or signal quality for at least one surrounding base station.

3. In paragraph 1, The above conditional handover configuration information is: A method comprising at least one of the target base station information, target time information, and the threshold information.

4. In paragraph 3, The above target time information is, A method comprising a target time set as either a conditional handover determination time or a conditional handover execution time, or information on a predetermined time period during which the target time and conditional handover determination are performed.

5. In paragraph 1, The above measurement report message is, A method comprising at least one of the target base station information, the measurement result, AI / ML model accuracy, and a conditional handover failure indicator.

6. In a method in which a base station performs communication using artificial intelligence and machine learning (AI / ML), A step of transmitting conditional handover configuration information set based on the predicted results inferred through an AI / ML model to a terminal; If the handover fails according to the above conditional handover configuration information, a step of receiving a measurement report message from the terminal; and A method comprising the step of transmitting a handover cancellation message to a target base station.

7. In paragraph 6, The above prediction results are, A method comprising predicting signal strength and / or signal quality for at least one surrounding base station.

8. In paragraph 6, The above conditional handover configuration information is: A method comprising at least one of the target base station information, target time information, and threshold information.

9. In paragraph 8, The above target time information is, A method comprising a target time set as either a conditional handover determination time or a conditional handover execution time, or information on a predetermined time period during which the target time and conditional handover determination are performed.

10. In paragraph 6, The above measurement report message is, A method comprising at least one of the target base station information, the measurement result, AI / ML model accuracy, and a conditional handover failure indicator.

11. In a terminal (user equipment; UE) that performs communication using artificial intelligence and machine learning (AI / ML), Transmitter; Receiver; and Including a control unit that controls the operation of the above transmitter and receiver, The control unit is a terminal that receives conditional handover configuration information set based on a prediction result inferred through an AI / ML model from a base station, measures signal strength and / or signal quality for a target base station based on the conditional handover configuration information, and transmits a measurement report message to the base station when the measurement result is not higher than a predetermined threshold.

12. In paragraph 11, The above prediction results are, A terminal including a predicted signal strength and / or signal quality for at least one surrounding base station.

13. In paragraph 11, The above conditional handover configuration information is: A terminal including at least one of the target base station information, target time information, and the threshold information.

14. In paragraph 13, The above target time information is, A terminal including a target time set as either a conditional handover determination time or a conditional handover execution time, or including information on a predetermined time period during which the target time and conditional handover determination are performed.

15. In paragraph 11, The above measurement report message is, A terminal including at least one of the target base station information, the measurement result, AI / ML model accuracy, and a conditional handover failure indicator.

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