Method and apparatus for measuring cell quality on basis of artificial intelligence and / or machine learning

Abstract

A method and an apparatus for measuring cell quality on the basis of artificial intelligence (AI) / machine learning (ML) are provided. This terminal receives, from a base station, information about a first cell list and information about a second cell list associated with the first cell list, and measures the quality of at least one first cell belonging to the first cell list. In addition, the terminal predicts quality information of at least one second cell belonging to the second cell list, wherein the quality information of the at least one second cell is predicted using an AI / ML model on the basis of the measured quality of the at least one first cell.

Description

Method and device for measuring cell quality based on artificial intelligence and / or machine learning

[0001] This specification relates to wireless communications applicable to 5G NR, 5G-Advanced and 6G.

[0002] As more and more communication devices demand ever-increasing communication traffic, the need for next-generation 5G systems, which offer enhanced wireless broadband communication capabilities over existing LTE systems, is growing. This next-generation 5G system, known as NewRAT, differentiates communication scenarios into Enhanced Mobile BroadBand (eMBB), Ultra-reliability and low-latency communication (URLLC), and Massive Machine-Type Communications (mMTC).

[0003] Here, eMBB is a next-generation mobile communication scenario with characteristics such as High Spectrum Efficiency, High User Experienced Data Rate, and High Peak Data Rate; URLLC is a next-generation mobile communication scenario with characteristics such as Ultra Reliable, Ultra Low Latency, and Ultra High Availability (e.g., V2X, Emergency Service, and Remote Control); and mMTC is a next-generation mobile communication scenario with characteristics such as Low Cost, Low Energy, Short Packet, and Massive Connectivity (e.g., IoT).

[0004] An object of the present specification is to provide a method and device for enabling a terminal to perform cell measurement, particularly, measurement of surrounding cells, using an AI / ML model to manage movement in a wireless communication system, and to report the measured cell quality results.

[0005] One embodiment of the present specification provides a method for a wireless communication system, wherein a terminal receives information of a first cell list and information of a second cell list associated with the first cell list from a base station, and measures the quality of at least one first cell belonging to the first cell list. In addition, the terminal predicts quality information of at least one second cell belonging to the second cell list, wherein the quality information of the at least one second cell is predicted using an artificial intelligence (AI) / machine learning (ML) model based on the measured quality of the at least one first cell.

[0006] In addition, one embodiment of the present specification provides a method for, in a wireless communication system, a base station transmits information of a first cell list and information of a second cell list associated with the first cell list to a terminal. Thereafter, the base station receives a measurement report based on quality information of at least one second cell belonging to the second cell list from the terminal, wherein the quality information of at least one second cell is predicted using an artificial intelligence (AI) / machine learning (ML) model based on measured quality of at least one first cell belonging to the first cell list.

[0007] In addition, one embodiment of the present invention provides a wireless communication system, comprising at least one processor, and at least one memory storing instructions and being operably electrically connectable to the at least one processor, wherein the operations performed based on the instructions being executed by the at least one processor are: receiving information of a first cell list and information of a second cell list associated with the first cell list from a base station, and measuring the quality of at least one first cell belonging to the first cell list. In addition, predicting quality information of at least one second cell belonging to the second cell list, wherein the quality information of the at least one second cell is predicted using an artificial intelligence (AI) / machine learning (ML) model based on the measured quality of the at least one first cell.

[0008] In addition, one embodiment of the present invention provides a wireless communication system comprising at least one processor, and at least one memory storing instructions and being operably electrically connectable to the at least one processor, wherein the operations performed based on the instructions being executed by the at least one processor include: transmitting information of a first cell list and information of a second cell list associated with the first cell list to a terminal. Thereafter, receiving a measurement report based on quality information of at least one second cell belonging to the second cell list from the terminal, wherein the quality information of the at least one second cell provides a base station predicted using an artificial intelligence (AI) / machine learning (ML) model based on measured quality of at least one first cell belonging to the first cell list.

[0009] The terminal can evaluate a measurement report condition based on predicted quality information of at least one second cell, and transmit a measurement report to the base station based on satisfaction of the evaluated measurement report condition.

[0010] Meanwhile, the first cell list may be associated with the input of the AI / ML model, and the second cell list may be associated with the output of the AI / ML model. In addition, the second cell list may include the first cell list.

[0011] Additionally, the information of the first cell list and the information of the second list can be transmitted by the base station to the terminal through an RRC (radio resource control) message including measurement settings, and the terminal can receive the same.

[0012] According to the disclosure of this specification, when a terminal performs cell measurement using an AI / ML model, especially a measurement of surrounding cells, there is an effect of alleviating the cell measurement burden of the terminal by enabling measurement of a smaller number of cells than before.

[0013] Figure 1 is a diagram illustrating a wireless communication system.

[0014] Figure 2 illustrates the structure of a radio frame used in NR.

[0015] Figures 3a to 3c are exemplary diagrams showing exemplary architectures for wireless communication services.

[0016] Figure 4 illustrates the slot structure of an NR frame.

[0017] Figure 5 illustrates an example of subframe types in NR.

[0018] Figure 6 illustrates the structure of a self-contained slot.

[0019] Figure 7 illustrates an example of a handover procedure to which the disclosure of this specification applies.

[0020] Figure 8 shows an example of a high-level measurement model in NR.

[0021] Figure 9 is a flowchart illustrating a method of operating a terminal according to one embodiment of the present specification.

[0022] Figures 10a and 10b show examples of cell measurements.

[0023] Figures 11a and 11b show further examples of cell measurements.

[0024] Figure 12 shows a procedure of a terminal and a base station according to one embodiment of the present specification.

[0025] Fig. 13 is a flowchart illustrating a method of operating a terminal according to another embodiment of the present specification.

[0026] Fig. 14 is a flowchart illustrating an operation method of a base station according to one embodiment of the present specification.

[0027] Figure 15 illustrates a device according to one embodiment of the present specification.

[0028] Fig. 16 is a block diagram showing the configuration of a terminal according to one embodiment of the present specification.

[0029] Figure 17 shows a block diagram of a processor in which the disclosure of this specification is implemented.

[0030] Fig. 18 is a block diagram showing in detail the transmitter / receiver of the first device illustrated in Fig. 15 or the transmitter / receiver unit of the device illustrated in Fig. 16.

[0031] It should be noted that the technical terms used in this specification are used merely to describe specific embodiments and are not intended to limit the contents of this specification. In addition, unless specifically defined otherwise herein, the technical terms used in this specification should be interpreted as having a meaning generally understood by those skilled in the art to which this specification pertains, and should not be interpreted in an excessively broad or narrow sense. In addition, if a technical term used in this specification is an incorrect technical term that does not accurately express the contents and ideas of this specification, it should be replaced with a technical term that can be correctly understood by a person skilled in the art. In addition, general terms used in this specification should be interpreted according to their dictionary definitions or according to the preceding and following context, and should not be interpreted in an excessively narrow sense.

[0032] Additionally, the singular expressions used herein include plural expressions unless the context clearly dictates otherwise. In this application, terms such as "consist of" or "have" should not be construed to necessarily include all of the components or steps described in the specification, and should be construed to mean that some of the components or steps may not be included, or that additional components or steps may be included.

[0033] Additionally, terms including ordinal numbers, such as "first" and "second," used herein may be used to describe various components, but these components should not be limited by these terms. These terms are used solely to distinguish one component from another. For example, without departing from the scope of the present invention, a first component could be referred to as a second component, and similarly, a second component could also be referred to as a first component.

[0034] When a component is referred to as being connected or connected to another component, it may be directly connected or connected to that other component, but there may also be other components intervening. Conversely, when a component is referred to as being directly connected or connected to another component, it should be understood that there are no other components intervening.

[0035] Hereinafter, embodiments will be described in detail with reference to the attached drawings. Regardless of the drawing reference numerals, identical or similar components will be given the same reference numerals, and redundant descriptions thereof will be omitted. In addition, when describing the contents of this specification, if a detailed description of a related known technology is judged to obscure the gist of this specification, the detailed description thereof will be omitted. In addition, it should be noted that the attached drawings are only intended to make the contents and ideas of this specification easily understandable, and should not be construed as limiting the contents and ideas of this specification by the attached drawings. The contents and ideas of this specification should be construed to extend to all changes, equivalents, and substitutes other than the attached drawings.

[0036] In this specification, “A or B” can mean “only A,” “only B,” or “both A and B.” In other words, “A or B” in this specification can be interpreted as “A and / or B.” For example, “A, B or C” in this specification can mean “only A,” “only B,” “only C,” or “any combination of A, B, and C.”

[0037] As used herein, a slash ( / ) or a comma can mean "and / or." For example, "A / B" can mean "A and / or B." Accordingly, "A / B" can mean "only A," "only B," or "both A and B." For example, "A, B, C" can mean "A, B, or C."

[0038] In this specification, “at least one of A and B” may mean “only A,” “only B,” or “both A and B.” Additionally, in this specification, the expressions “at least one of A or B” or “at least one of A and / or B” may be interpreted identically to “at least one of A and B.”

[0039] Additionally, in this specification, “at least one of A, B and C” can mean “only A,” “only B,” “only C,” or “any combination of A, B and C.” Additionally, “at least one of A, B or C” or “at least one of A, B and / or C” can mean “at least one of A, B and C.”

[0040] Additionally, parentheses used in this specification may mean “for example.” Specifically, when “control information (PDCCH)” is indicated, “PDCCH (Physical Downlink Control Channel)” may be suggested as an example of “control information.” In other words, “control information” in this specification is not limited to “PDCCH,” and “PDDCH” may be suggested as an example of “control information.” Furthermore, even when indicated as “control information (i.e., PDCCH),” “PDCCH” may be suggested as an example of “control information.”

[0041] Technical features individually described in a single drawing in this specification may be implemented individually or simultaneously.

[0042] Although the attached drawing illustrates a UE (User Equipment) as an example, the illustrated UE may also be referred to as a terminal, ME (Mobile Equipment), etc. In addition, the UE may be a portable device such as a laptop, mobile phone, PDA, smart phone, multimedia device, etc., or a non-portable device such as a PC or vehicle-mounted device.

[0043] Hereinafter, the term "UE" is used as an example of a device capable of wireless communication (e.g., a wireless communication device, a wireless device, or a wireless device). The operations performed by the UE can be performed by any device capable of wireless communication. A device capable of wireless communication may also be referred to as a wireless communication device, a wireless device, or a wireless device.

[0044] The term base station used below generally refers to a fixed station that communicates with wireless devices, and can be used as a comprehensive term that includes eNodeB (evolved-NodeB), eNB (evolved-NodeB), BTS (Base Transceiver System), Access Point, gNB (Next generation NodeB), RRH (remote radio head), TP (transmission point), RP (reception point), relay, etc.

[0045] Although this specification describes embodiments using LTE systems, LTE-A systems, and NR systems, these embodiments may be applied to any communication system falling within the above definitions.

[0046] Wireless Communication System

[0047] Building on the success of LTE (long term evolution) / LTE-Advanced (LTE-A) for 4th generation mobile communications, commercialization of the next generation, or 5th generation (so-called 5G) mobile communications, and follow-up research are also ongoing.

[0048] The International Telecommunication Union (ITU) defines 5G mobile communications as providing data transfer speeds of up to 20 Gbps and a perceived transmission speed of at least 100 Mbps everywhere. Its official name is "IMT-2020."

[0049] ITU proposes three usage scenarios: eMBB (enhanced Mobile BroadBand), mMTC (massive Machine Type Communication), and URLLC (Ultra Reliable and Low Latency Communications).

[0050] URLLC addresses usage scenarios that require high reliability and low latency. For example, services such as autonomous driving, factory automation, and augmented reality require high reliability and low latency (e.g., sub-1ms). Current 4G (LTE) latency is statistically 21-43ms (best 10%) and 33-75ms (median). This is insufficient to support services requiring sub-1ms latency. Next, eMBB usage scenarios address usage scenarios that require mobile ultra-wideband.

[0051] In other words, the 5th generation mobile communication system can support higher capacity than the current 4G LTE, increase the density of mobile broadband users, and support D2D (Device to Device), high reliability, and MTC (Machine-type communication). 5G research and development also aims for lower latency and lower battery consumption than 4G mobile communication systems to better implement the Internet of Things. For this 5G mobile communication, a new radio access technology (New RAT or NR) may be proposed.

[0052] The NR frequency band can be defined by two types of frequency ranges (FR1, FR2). The numerical values ​​of the frequency ranges can be changed, and for example, the two types of frequency ranges (FR1, FR2) can be as shown in Table 1 below. For convenience of explanation, among the frequency ranges used in the NR system, FR1 can mean the “sub 6 GHz range”, and FR2 can mean the “above 6 GHz range” and can be called millimeter wave (mmW).

[0053] Frequency Range designationCorresponding frequency rangeSubcarrier SpacingFR1410MHz - 7125MHz15, 30, 60kHzFR224250MHz - 52600MHz60, 120, 240kHz

[0054] The numerical value of the frequency range of the NR system can be changed. For example, FR1 can include a band from 410 MHz to 7125 MHz, as shown in Table 1. That is, FR1 can include frequency bands above 6 GHz (or 5850, 5900, 5925 MHz, etc.). For example, the frequency bands above 6 GHz (or 5850, 5900, 5925 MHz, etc.) included within FR1 can include unlicensed bands. Unlicensed bands can be used for various purposes, such as for vehicle communications (e.g., autonomous driving).

[0055] Meanwhile, 3GPP-based communication standards define downlink physical channels corresponding to resource elements that carry information originating from upper layers, and downlink physical signals corresponding to resource elements that are used by the physical layer but do not carry information originating from upper layers. For example, the physical downlink shared channel (PDSCH), physical broadcast channel (PBCH), physical multicast channel (PMCH), physical control format indicator channel (PCFICH), physical downlink control channel (PDCCH), and physical hybrid ARQ indicator channel (PHICH) are defined as downlink physical channels, and reference signals and synchronization signals are defined as downlink physical signals. A reference signal (RS), also referred to as a pilot, is a signal with a special predefined waveform known to the gNB and the UE. For example, cell specific RS, UE-specific RS (UE-RS), positioning RS (PRS), and channel state information RS (CSI-RS) are defined as downlink reference signals. The 3GPP LTE / LTE-A standard defines uplink physical channels corresponding to resource elements carrying information originating from higher layers, and uplink physical signals corresponding to resource elements used by the physical layer but not carrying information originating from higher layers.For example, a physical uplink shared channel (PUSCH), a physical uplink control channel (PUCCH), and a physical random access channel (PRACH) are defined as uplink physical channels, and a demodulation reference signal (DMRS) for uplink control / data signals and a sounding reference signal (SRS) used for uplink channel measurement are defined.

[0056] In this specification, PDCCH (Physical Downlink Control CHannel) / PCFICH (Physical Control Format Indicator CHannel) / PHICH ((Physical Hybrid automatic retransmit request Indicator CHannel) / PDSCH (Physical Downlink Shared CHannel) mean a set of time-frequency resources or a set of resource elements that carry DCI (Downlink Control Information) / CFI (Control Format Indicator) / downlink ACK / NACK (ACKnowlegement / Negative ACK) / downlink data, respectively. In addition, PUCCH (Physical Uplink Control CHannel) / PUSCH (Physical Uplink Shared CHannel) / PRACH (Physical Random Access CHannel) mean a set of time-frequency resources or a set of resource elements that carry UCI (Uplink Control Information) / uplink data / random access signals, respectively.

[0057] Figure 1 is a diagram illustrating a wireless communication system.

[0058] As can be seen from FIG. 1, the wireless communication system includes at least one base station (BS). The BS is divided into a gNodeB (or gNB) (20a) and an eNodeB (or eNB) (20b). The gNB (20a) supports 5th generation mobile communications. The eNB (20b) supports 4th generation mobile communications, i.e., long term evolution (LTE).

[0059] Each base station (20a and 20b) provides communication services for a specific geographic area (commonly referred to as a cell) (20-1, 20-2, 20-3). The cell may be further divided into multiple areas (referred to as sectors).

[0060] A UE (user equipment) typically belongs to a single cell, and the cell to which the UE belongs is called a serving cell. The base station that provides communication services for the serving cell is called a serving base station (BS). Since the wireless communication system is a cellular system, there are other cells adjacent to the serving cell. These other cells adjacent to the serving cell are called neighbor cells. The base station that provides communication services to the neighbor cell is called a neighbor BS. The serving cell and neighbor cells are determined relative to the UE.

[0061] Hereinafter, downlink refers to communication from a base station (20) to a UE (10), and uplink refers to communication from a UE (10) to a base station (20). In downlink, the transmitter may be part of the base station (20), and the receiver may be part of the UE (10). In uplink, the transmitter may be part of the UE (10), and the receiver may be part of the base station (20).

[0062] Meanwhile, wireless communication systems can be broadly divided into frequency division duplex (FDD) and time division duplex (TDD). In FDD, uplink and downlink transmissions occupy different frequency bands and occur at different times. In TDD, uplink and downlink transmissions occupy the same frequency band but occur at different times. The channel response in TDD is essentially reciprocal, meaning that the downlink and uplink channel responses are nearly identical in a given frequency range. Therefore, in TDD-based wireless communication systems, the downlink channel response can be derived from the uplink channel response, which is advantageous. In TDD, uplink and downlink transmissions are time-divided across the entire frequency band, so downlink transmission by the base station and uplink transmission by the UE cannot be performed simultaneously. In TDD systems, where uplink and downlink transmissions are divided into subframes, uplink and downlink transmissions are performed in different subframes.

[0063] Figure 2 illustrates the structure of a radio frame used in NR.

[0064] In NR, uplink and downlink transmissions are structured as frames. A radio frame is 10ms long and is defined by two 5ms half-frames (HF). Each half-frame is defined by five 1ms subframes (SF). A subframe is divided into one or more slots, and the number of slots in a subframe depends on the subcarrier spacing (SCS). Each slot contains 12 or 14 OFDM(A) symbols, depending on the cyclic prefix (CP). When a normal CP is used, each slot contains 14 symbols. When an extended CP is used, each slot contains 12 symbols. Here, the symbols may include OFDM symbols (or CP-OFDM symbols), SC-FDMA symbols (or DFT-s-OFDM symbols).

[0065] Support for various numerologies

[0066] In NR systems, multiple numerologies may be provided to terminals as wireless communication technologies advance. For example, an SCS of 15 kHz supports a wide area in traditional cellular bands. An SCS of 30 kHz / 60 kHz supports dense urban environments, lower latency, and wider carrier bandwidth. An SCS of 60 kHz or higher supports a bandwidth greater than 24.25 GHz to overcome phase noise.

[0067] The above numerology can be defined by the cycle prefix (CP) length and subcarrier spacing (SCS). A single cell can provide multiple numerologies to a terminal. When the numerology index is represented by μ, each subcarrier spacing and the corresponding CP length can be as shown in the table below.

[0068] μ△f=2 μ 15 [kHz]CP015 General 130 General 260 General, Extended 3120 General 4240 General 5480 General 6960 General

[0069] For general CP, when the index of the numerology is represented by μ, the number of OFDM symbols per slot (N slot symb ), number of slots per frame (N frame,μ slot ) and the number of slots per subframe (N subframe,μ slot ) is as shown in the table below.

[0070] μ△f=2 μ 15 [kHz]N slot symb N frame,μ slot N subframe,μ slot 015141011301420226014404312014808424014160165480143203269601464064

[0071] For extended CP, when the index of the numerology is represented by μ, the number of OFDM symbols per slot (N slot symb ), number of slots per frame (N frame,μ slot ) and the number of slots per subframe (N subframe,μ slot ) is as shown in the table below.

[0072] μSCS (15*2 u )N slot symb N frame,μ slot N subframe,μslot 260KHz (u=2)12404

[0073] In an NR system, OFDM(A) numerology (e.g., SCS, CP length, etc.) may be set differently between multiple cells that are merged into a single terminal. Accordingly, the (absolute time) interval of a time resource (e.g., SF, slot, or TTI) (conveniently referred to as TU (Time Unit)) consisting of the same number of symbols may be set differently between the merged cells.

[0074] Figures 3a to 3c are exemplary diagrams showing exemplary architectures for wireless communication services.

[0075] Referring to FIG. 3a, the UE is connected to an LTE / LTE-A-based cell and an NR-based cell in a DC (dual connectivity) manner.

[0076] The above NR-based cell is connected to the core network for existing 4th generation mobile communication, i.e. Evolved Packet Core (EPC).

[0077] Referring to FIG. 3b, unlike FIG. 3a, the LTE / LTE-A-based cell is connected to a core network for 5th generation mobile communication, i.e., a 5G core network.

[0078] A service method based on an architecture as illustrated in Figures 3a and 3b above is called NSA (non-standalone).

[0079] Referring to Figure 3c, the UE is connected only to NR-based cells. A service method based on this architecture is called SA (standalone).

[0080] Meanwhile, in the above NR, it may be considered that reception from the base station utilizes a downlink subframe, and transmission to the base station utilizes an uplink subframe. This method can be applied to paired and unpaired spectrums. A pair of spectrums means that two carrier spectrums are included for downlink and uplink operations. For example, in a pair of spectrums, one carrier may include a downlink band and an uplink band that are paired with each other.

[0081] Figure 4 illustrates the slot structure of an NR frame.

[0082] A slot contains multiple symbols in the time domain. For example, in the case of a normal CP, one slot contains 14 symbols, but in the case of an extended CP, one slot contains 12 symbols. A carrier contains multiple subcarriers in the frequency domain. An RB (Resource Block) is defined as multiple (e.g., 12) consecutive subcarriers in the frequency domain. A BWP (Bandwidth Part) is defined as multiple consecutive (physical, P)RBs in the frequency domain, and can correspond to a single numerology (e.g., SCS, CP length, etc.). A terminal can be configured with up to N (e.g., 4) BWPs in the downlink and uplink, respectively. Downlink or uplink transmission is performed through an activated BWP, and at a given time, only one BWP among the BWPs configured for the terminal can be activated. In the resource grid, each element is referred to as a Resource Element (RE), to which one complex symbol can be mapped.

[0083] Figure 5 illustrates an example of subframe types in NR.

[0084] The transmission time interval (TTI) illustrated in FIG. 5 may be referred to as a subframe or slot for NR (or new RAT). The subframe (or slot) of FIG. 5 may be used in a TDD system of NR (or new RAT) to minimize data transmission delay. As illustrated in FIG. 5, a subframe (or slot) includes 14 symbols. The symbols in the front of the subframe (or slot) may be used for a downlink (DL) control channel, and the symbols in the back of the subframe (or slot) may be used for an uplink (UL) control channel. The remaining symbols may be used for DL ​​data transmission or UL data transmission. According to this subframe (or slot) structure, downlink transmission and uplink transmission may be sequentially performed in one subframe (or slot). Therefore, downlink data may be received within a subframe (or slot), and an uplink acknowledgment (ACK / NACK) may be transmitted within the subframe (or slot).

[0085] The structure of these subframes (or slots) can be called self-contained subframes (or slots).

[0086] Specifically, the first N symbols in a slot are used to transmit a DL control channel (hereinafter, DL control region), and the last M symbols in the slot can be used to transmit a UL control channel (hereinafter, UL control region). N and M are each integers greater than or equal to 0. A resource region (hereinafter, data region) between the DL control region and the UL control region can be used for DL ​​data transmission or UL data transmission. For example, a physical downlink control channel (PDCCH) can be transmitted in the DL control region, and a physical downlink shared channel (PDSCH) can be transmitted in the DL data region. A physical uplink control channel (PUCCH) can be transmitted in the UL control region, and a physical uplink shared channel (PUSCH) can be transmitted in the UL data region.

[0087] Using this subframe (or slot) structure has the advantage of minimizing the final data transmission latency by reducing the time required to retransmit data that has experienced reception errors. In this self-contained subframe (or slot) structure, a time gap may be required during the transition from transmit mode to receive mode or from receive mode to transmit mode. To this end, some OFDM symbols during the transition from DL to UL in the subframe structure can be designated as a guard period (GP).

[0088] Figure 6 illustrates the structure of a self-contained slot.

[0089] In an NR system, a frame is characterized by a self-contained structure in which a DL control channel, DL or UL data, and a UL control channel can all be included within a single slot. For example, the first N symbols within a slot can be used to transmit a DL control channel (hereinafter, referred to as a DL control region), and the last M symbols within a slot can be used to transmit a UL control channel (hereinafter, referred to as a UL control region). N and M are each integers greater than or equal to 0. The resource region (hereinafter, referred to as a data region) between the DL control region and the UL control region can be used for DL ​​data transmission or UL data transmission. As an example, the following configuration can be considered. Each section is listed in chronological order.

[0090] 1. DL only configuration

[0091] 2. UL only configuration

[0092] 3. Mixed UL-DL configuration

[0093] - DL area + GP (Guard Period) + UL control area

[0094] - DL control area + GP + UL area

[0095] DL area: (i) DL data area, (ii) DL control area + DL data area

[0096] UL domain: (i) UL data domain, (ii) UL data domain + UL control domain

[0097] In the DL control region, a PDCCH can be transmitted, and in the DL data region, a PDSCH can be transmitted. In the UL control region, a PUCCH can be transmitted, and in the UL data region, a PUSCH can be transmitted. In the PDCCH, downlink control information (DCI), for example, DL data scheduling information, UL data scheduling information, etc., can be transmitted. In the PUCCH, uplink control information (UCI), for example, ACK / NACK (Positive Acknowledgement / Negative Acknowledgement) information for DL ​​data, CSI (Channel State Information) information, SR (Scheduling Request), etc., can be transmitted. GP provides a time gap when a base station and a terminal switch from transmission mode to reception mode or when switching from reception mode to transmission mode. Some symbols at the time of switching from DL to UL within a subframe can be set as GP.

[0098] Mobility in RRC_CONNECTED is described below. See section 9.2.3 of 3GPP TS 38.300 v17.6.0.

[0099] Network controlled mobility applies to terminals / UEs in RRC_CONNECTED and can be classified into two types: cell level mobility and beam level mobility. Cell level mobility requires explicit RRC signaling to be triggered.

[0100] Figure 7 illustrates an example of a handover procedure to which the disclosure of this specification applies.

[0101] Referring to FIG. 7, a source gNB initiates a handover and transmits a handover request message to a target gNB via the Xn interface (S701). The target gNB performs admission control and provides a new RRC configuration to the source gNB as part of a handover request acknowledge message (S702). The source gNB provides the RRC configuration to the UE by forwarding an RRC reconfiguration message received in the handover request acknowledge message (S703). The RRC reconfiguration message includes at least a cell ID and all information necessary to access the target cell so that the UE can access the target cell without reading system information. In some cases, information necessary for contention-based and contention-free random access may be included in the RRC reconfiguration message. Access information for the target cell may include beam-specific information, if available. Thereafter, the UE switches to a new cell, i.e., moves the RRC connection to the target base station, and transmits an RRC reconfiguration complete message (S704).

[0102] Measurements in RRC_CONNECTED are described below. See Section 9.2.4 of 3GPP TS 38.300 v17.6.0.

[0103] Figure 8 shows an example of a high-level measurement model in NR.

[0104] In RRC_CONNECTED, the UE measures multiple beams (at least one) of the cell and the measurement results (power values) are averaged to obtain the cell quality. In this way, the UE is configured to consider a subset of the detected beams, i.e., the N best beams above an absolute threshold. Filtering is performed at two different levels, i.e., at the physical layer to derive the beam quality and then at the RRC level to derive the cell quality from the multiple beams. The cell quality from the beam measurements is obtained in the same way for the serving cell(s) and the non-serving cell(s). The measurement report may include the measurement results of the X best beams, if the UE is configured to do so by the gNB.

[0105] Referring to Fig. 8, it is described in more detail below.

[0106] The K beams correspond to measurements on SSB or CSI-RS resources configured by the base station for L3 mobility and detected by the terminal in L1.

[0107] 'A' are measurements (beam specific samples) within the physical layer.

[0108] 'Layer 1 filtering' refers to internal Layer 1 filtering of the inputs measured at point A. The exact filtering is implementation-dependent. How the measurement (input A and Layer 1 filtering) is actually performed at the physical layer by the implementation is not restricted by the standard.

[0109] 'A 1 ' are measurements reported by Layer 3 from Layer 1 after Layer 1 filtering (i.e. beam specific measurements).

[0110] 'Beam Consolidation / Selection' is to consolidate beam-specific measurements to derive cell quality when N > 1, and to select the best beam measurement to derive cell quality when N = 1. The operation of beam consolidation / selection is standardized, and the configuration of this module is provided by RRC signaling. The reporting cycle in B is A 1 is equal to one measurement cycle in .

[0111] 'B' is a measurement (i.e. cell quality) derived from beam specific measurements reported to layer 3 after beam integration / selection.

[0112] 'Layer 3 filtering for cell quality' is filtering performed on measurements provided at point B. The operation of Layer 3 filters is standardized, and their configuration is provided via RRC signaling. The filtering reporting cycle at point C is the same as one measurement cycle at point B.

[0113] 'C' is the measurement after processing in the Layer 3 filter. The reporting rate is the same as the reporting rate at Point B. This measurement is used as input to one or more reporting criteria evaluations.

[0114] 'Evaluation of reporting criteria' is to determine whether actual measurement reporting is required at point D. The evaluation can be performed based on measurements of one or more flows at reference point C, for example, to compare different measurements. This can be done by inputting C and C 1 . The terminal is indicated by the new measurement results at points C and C 1 The reporting criteria must be evaluated at least hourly in the reporting. The reporting criteria are standardized and their settings are provided by RRC signaling (UE measurements).

[0115] 'D' is the measurement report information (message) transmitted over the radio interface.

[0116] 'L3 beam filtering' is filtering performed on measurements provided at point A1 (i.e. beam-specific measurements). The operation of beam filters is standardized, and their configuration is provided by RRC signaling. The filtering reporting cycle at point E is the same as that at point A. 1 is equal to one measurement cycle in .

[0117] 'E' is the post-processing measurement in the beam filter (i.e., beam-specific measurement). The reporting rate is equal to the reporting rate at point A1. This measurement is used as input to select X measurements to be reported.

[0118] 'Beam Selection for beam reporting' selects X measurements from the measurements provided at point E. The operation of beam selection is standardized and the configuration of this module is provided by RRC signaling.

[0119] 'F' is beam measurement information included in the measurement report (transmitted) over the wireless interface.

[0120] Layer 1 filtering introduces a certain level of measurement averaging. How and when the terminal performs the required measurements is implemented specifically to ensure that the output from B meets the performance requirements set forth in 3GPP TS 38.133.

[0121] Layer 3 filtering for cell quality and the associated parameters used are specified in 3GPP TS 38.331 and do not delay sample availability between points B and C. Points C and C 1Measurements at are inputs used for event evaluation. L3 beam filtering and associated parameters used are specified in 3GPP TS 38.331 and do not delay sample availability between E and F.

[0122] Measurement reports have the following characteristics:

[0123] 1) Measurement reports contain the measurement identifier of the relevant measurement setting that triggered the report;

[0124] 2) Cell and beam measurement quantities to be included in measurement reports are configured by the network;

[0125] 3) The number of non-serving cells to be reported may be limited by network settings;

[0126] 4) Cells that belong to the exclude-list set by the network are not used for event evaluation and reporting. Conversely, if an allow-list is set by the network, only cells that belong to the allow-list are used for event evaluation and reporting.

[0127] 5) The beam measurements to be included in the measurement reports are set by the network (beam identifier only, measurement results and beam identifier, or no beam report).

[0128] In 3GPP Release-18, research was conducted on technologies that apply AI / ML models to use cases such as beam management (BM), positioning, and CSI feedback. As a result of the research, it was decided to begin full-scale work on AI / ML specifications to improve the accuracy of beam management and positioning in Release-19. Based on these research results, attempts to apply AI / ML to communication technology are underway in various fields, and it is expected that new research will begin under the leadership of RAN2 on the topic of AI / ML based mobility in Release-19.

[0129] In the case of BM discussed in RAN1, research on 'AI / ML for BM' was conducted with the aim 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 perform handovers (HOs) between cells, and beam link failures can lead to frequent handovers or handover failures. Therefore, NR mobility enhancement has been continuously discussed to solve this problem, and the following features have been defined.

[0130] - CHO (Conditional HO) in Rel-16;

[0131] - ICBM (Inter-Cell Beam Management) in Rel-17;

[0132] - LTM (Lower-layer Triggered Mobility) in Rel-18.

[0133] That is, not only HO but also BM can be considered as one of the key elements for mobility, and similar to the 'AI / ML for BM' research conducted in Release-18, various techniques can be proposed to reduce the measurement burden as well as the delay of HO by measuring only some surrounding cells by applying AI / ML models as a new method to ensure seamless mobility between 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 by measuring only some beams of surrounding cells. Alternatively, by predicting the timing of reporting the measurement results and the timing of HO execution through the measurement of surrounding cells at the current point in time and preparing for HO in advance, it is expected that the interruption time can be minimized and the HO accuracy can be improved.

[0134] As mentioned above, 3GPP has consistently performed measurements of neighboring cells, as well as the serving cell, to ensure link connectivity for mobile terminals. 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 are burdened with measuring a greater 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 have been studied as key issues for 5G.

[0135] However, since the existing measurement relaxation is performed based on base station settings, the problem of not being able to perform HO in a timely manner may occur, which ultimately causes HO delay and link disconnection problems.

[0136] With the recent application of AI / ML technologies in various communications fields, numerous attempts have been proposed to address these overhead and complexity issues. Utilizing AI / ML models that predict signal strength / quality or movement timing for neighboring cells is expected to not only reduce the burden of cell measurement on terminals but also improve HO complexity by ensuring inter-cell movement occurs at the most optimal time.

[0137] To predict signal strength / quality for surrounding cells based on AI / ML models, a new signaling technique needs to be defined between the base station and the terminal. Specifically, if signal strength / quality for all candidate cells is to be predicted based solely on signal strength / quality measurements for the cells used as inputs to the model, rather than measuring all surrounding cells, the base station needs a method to instruct the terminal on the candidate cells to be output as the model and the measurement cells to be used as inputs.

[0138] In this specification, we propose a method for measuring and reporting surrounding cells of a terminal when the terminal predicts the signal strength of surrounding cells using an AI / ML model.

[0139] Figure 9 is a flowchart illustrating a method of operating a terminal according to one embodiment of the present specification.

[0140] Based on the AI / ML model information supported by the terminal, the base station transmits a measurement configuration message including an indicator for indicating information about a cell to be used as an input value of the model (hereinafter referred to as Cell_SetB) and information about a cell to be derived as an output value of the model (hereinafter referred to as Cell_SetA), and the terminal receiving the measurement configuration message uses the signal strength measurement for the cells belonging to Cell_SetB as an input value of the AI / ML model and predicts the signal strength for the cells belonging to Cell_SetA. If there is a cell that satisfies the event set by the base station among the predicted cells, the predicted / measured signal strength is reported to the base station.

[0141] Referring to FIG. 9, a terminal receives a message including information indicating at least one cell (Set B) for performing measurement and at least one cell (Set A) for performing prediction from a base station (S901). Based on the received information, the terminal measures cell quality for a cell indicated as Set B (S902), and predicts cell quality for a cell indicated as Set A using the measured cell quality as an input value of an AI / ML model (S903). Thereafter, the terminal evaluates a reporting condition based on the predicted cell quality for a cell belonging to Set A, and if satisfied, transmits a reporting message to the base station (S904).

[0142] The AI / ML model assumes that the input values ​​are measured values ​​for some surrounding cells (Cell_SetB), and predicts the predicted signal strength / quality for all surrounding cells (Cell_SetA). This model can predict the current / future signal strength for surrounding cells based on the terminal's movement characteristics (e.g., speed, direction, etc.).

[0143] Figures 10a and 10b show examples of cell measurements.

[0144] FIGS. 10A to 10B illustrate examples of a terminal performing peripheral cell measurements, and in particular, FIG. 10B illustrates an example of performing cell measurements based on an AI / ML model.

[0145] The terminal begins measuring surrounding cells based on the settings received from the base station. At this time, the terminal supporting the AI / ML model performs measurements only for the cell(s) designated as Cell_SetB by the base station, and uses the information of the measured cell(s) as input values ​​for the model to predict the signal strength of the cell(s) designated as Cell_SetA. Here, Cell_SetB may be a subset of Cell_SetA, or may be composed of the same or different cells.

[0146] The base station transmits to the terminal a measurement configuration containing information related to neighboring cell measurement for neighboring cells, and an indicator indicating a cell to be used as an input value of the AI / ML model by the terminal (i.e., a cell on which the terminal must perform measurement, Cell_SetB) and a cell to be derived as an output value (i.e., a cell on which the terminal performs prediction, Cell_SetA). Here, the indicator may additionally define a predicted cell list associated with the cell list in addition to the cell list defined in the measurement object. Alternatively, the terminal may define to distinguish between the cells to be measured (Cell_SetB list) and the cells to be predicted (Cell_SetA list) by explicitly indicating them through the definition of a new measurement object for AI / ML (e.g., MeasObjectAIML). Here, Cell_SetB may be a subset of Cell_SetA. If Cell_SetB is a subset of Cell_SetA, it means that Cell_SetA actually contains the cell quality for Cell_SetB derived through measurement.

[0147] The terminal obtains a cell list on which measurements must be performed and performs serving / surrounding cell measurements through this. However, if a predicted cell list associated with the cell list is additionally obtained in addition to the cell list defined in the measurement object, the cell quality results for the cells belonging to the cell list are used as input values ​​for the AI / ML model, and the results for the cells indicated by the predicted cell list are predicted as output values ​​of the model. Accordingly, a decision is made on whether to transmit a report message based on the predicted neighboring cell quality results derived by the AI / ML model.

[0148] Meanwhile, when a new measurement object for AI / ML (e.g., MeasObjectAIML) is defined to explicitly indicate a list of cells to be measured (Cell_SetB list) and a list of cells to be predicted (Cell_SetA list), measurements are performed on cells belonging to the explicitly indicated Cell_SetB list, which are used as input values ​​for the AI / ML model, and the results for the cells indicated by the Cell_SetA list are predicted as model output values. In this case as well, a decision is made on whether to send a report message based on the predicted surrounding cell quality results derived by the AI / ML model.

[0149] Figures 11a and 11b show further examples of cell measurements.

[0150] As described above with respect to FIGS. 10a and 10b, the terminal may additionally receive beam setting information for cells belonging to Cell_SetB. Using the received beam setting information, beam measurement based on SSB / CSI-RS is performed. Here, the AI / ML model may be instructed to be applied once more to derive results for beams belonging to Cell_SetB. This means that the terminal acquires beam intensity / quality results of beams related to the cell (Cell_SetB) for which it is instructed to perform actual measurement using the AI / ML model. FIGS. 11a and 11b illustrate examples of performing cell measurement using beam measurement result values ​​for cells belonging to Cell_SetB, and in particular, FIG. 11b illustrates an example of performing cell measurement through AI / ML model-based beam measurement.

[0151] Referring to Fig. 11a, by measuring all beams (SSB / CSI-RS) set for some cells among the surrounding cells, the cell quality can be derived using the measured beam results, and the cell quality for cells belonging to Cell_SetA can be predicted based on the derived cell quality for cells belonging to Cell_SetB. As another example, as shown in Fig. 11b, the cell quality for cells belonging to Cell_SetB can be derived using beam prediction. This has the effect of reducing the overall beam measurement burden and DL (downlink) RS (reference signal) overhead by deriving the results of beams set for cells set to Cell_SetB using an AI / ML model. To this end, the base station can include information on SetA / B (Beam_SetA / Beam_SetB) of beams (SSB / CSI-RS) belonging to Cell_SetB in the measurement configuration and transmit it. The measurement results for beams belonging to the Cell_SetB instructed in this way are used to predict Beam_SetA for Cell_SetB, and the cell quality for Cell_SetB is derived using the predicted beam results belonging to Beam_SetA by the 'AI / ML for BM' model, and the derived cell quality of Cell_SetB is used as an input value of the 'AI / ML for mobility' model to predict the cell quality for the entire Cell_SetA.

[0152] Figure 12 shows a procedure of a terminal and a base station according to one embodiment of the present specification.

[0153] Hereinafter, terminal operation is described in detail with reference to FIG. 12.

[0154] The terminal receives an RRC message containing measurement configuration (measConfig) from the base station (S1201). The message may be an RRC reconfiguration message and may include at least one of the following information:

[0155] - Cell list (cell list, cellList)

[0156] - predicted cell list (predicted cell list, predictedCellList) associated with the cell list

[0157] Here, the cell list is used as the input of the AI / ML model, and the predicted cell list is used as the output of the AI / ML model. The predicted cell list may include the cell list, or the predicted cell list may include cell information less than or equal to the cell list.

[0158] The terminal performs measurements on cells in the cell list based on information received from the base station (S1202). Specifically, the beam intensity for cells in the cell list is measured, and cell quality is derived from this.

[0159] The terminal uses the derived cell quality for the corresponding cell list as the input value for the relevant AI / ML model. Furthermore, the received predicted cell list is used as the output value of the AI / ML model. Through this, the terminal performs predictions on the cells in the predicted cell list (S1203). In other words, the terminal uses the AI / ML model to derive the predicted cell quality for the cells in the predicted cell list.

[0160] Thereafter, the predicted cell quality derived for the cells belonging to the predicted cell list is used to evaluate the reporting criteria (S1204). If there is a criteria (event) that is satisfied, a measurement report message including cell information set by the base station is transmitted to the base station (S1205).

[0161] Hereinafter, the operation of the base station is described in detail with reference to FIG. 12.

[0162] The base station transmits an RRC message containing measurement configuration (measConfig) suitable for the AI / ML model / function of the terminal to the terminal (S1201). The message may be an RRC reconfiguration message and may include at least one of the following information:

[0163] - Cell list (cell list, cellList)

[0164] - predicted cell list (predicted cell list, predictedCellList) associated with the cell list

[0165] Here, the cell list is used as the input of the AI / ML model, and the predicted cell list is used as the output of the AI / ML model. The predicted cell list may include the cell list, or the predicted cell list may include cell information less than or equal to the cell list.

[0166] Thereafter, the base station receives a measurement report message including result values ​​for cells belonging to a predicted cell list from the terminal (S1205).

[0167] Fig. 13 is a flowchart illustrating a method of operating a terminal according to another embodiment of the present specification.

[0168] Referring to FIG. 13, the terminal receives information on a first cell list and information on a second cell list associated with the first cell list from a base station (S1301), and measures the quality of at least one first cell belonging to the first cell list (S1302). In addition, the terminal predicts quality information of at least one second cell belonging to the second cell list (S1303). Here, the quality information of at least one second cell is predicted using an AI (artificial intelligence) / ML (machine learning) model based on the measured quality of at least one first cell.

[0169] The terminal can evaluate a measurement report condition based on predicted quality information of at least one second cell, and transmit a measurement report to the base station based on satisfaction of the evaluated measurement report condition.

[0170] Meanwhile, the first cell list may be associated with the input of the AI / ML model, and the second cell list may be associated with the output of the AI / ML model. In addition, the second cell list may include the first cell list.

[0171] Additionally, the information of the first cell list and the information of the second list can be received from the base station through an RRC (radio resource control) message including measurement settings.

[0172] Fig. 14 is a flowchart illustrating an operation method of a base station according to one embodiment of the present specification.

[0173] Referring to FIG. 14, the base station transmits information on a first cell list and information on a second cell list associated with the first cell list to the terminal (S1401). Thereafter, a measurement report based on quality information of at least one second cell belonging to the second cell list is received from the terminal (S1402). Here, the quality information of at least one second cell is predicted using an artificial intelligence (AI) / machine learning (ML) model based on the measured quality of at least one first cell.

[0174] Meanwhile, the first cell list may be associated with the input of the AI / ML model, and the second cell list may be associated with the output of the AI / ML model. In addition, the second cell list may include the first cell list.

[0175] Additionally, the information of the first cell list and the information of the second list can be transmitted from the base station to the terminal via an RRC (radio resource control) message including measurement settings.

[0176] The concepts disclosed in this specification may be applied independently or may be combined and operated in any form. Furthermore, while this specification is based on a 5G NR system, the scope of this specification encompasses all cases in which the concepts of this specification apply, regardless of the specific wireless communication technology.

[0177] Figure 15 illustrates a device according to one embodiment of the present specification.

[0178] Referring to FIG. 15, the wireless communication system may include a first device (100a) and a second device (100b).

[0179] The first device (100a) may be a base station, a network node, a transmitting terminal, a receiving terminal, a wireless device, a wireless communication device, a vehicle, a vehicle equipped with an autonomous driving function, a connected car, a drone (Unmanned Aerial Vehicle, UAV), an AI (Artificial Intelligence) module, a robot, an AR (Augmented Reality) device, a VR (Virtual Reality) device, an MR (Mixed Reality) device, a hologram device, a public safety device, an MTC device, an IoT device, a medical device, a fintech device (or a financial device), a security device, a climate / environmental device, a device related to 5G services, or any other device related to the 4th industrial revolution field.

[0180] The second device (100b) may be a base station, a network node, a transmitting terminal, a receiving terminal, a wireless device, a wireless communication device, a vehicle, a vehicle equipped with an autonomous driving function, a connected car, a drone (Unmanned Aerial Vehicle, UAV), an AI (Artificial Intelligence) module, a robot, an AR (Augmented Reality) device, a VR (Virtual Reality) device, an MR (Mixed Reality) device, a hologram device, a public safety device, an MTC device, an IoT device, a medical device, a fintech device (or a financial device), a security device, a climate / environmental device, a device related to 5G services, or any other device related to the 4th industrial revolution field.

[0181] The first device (100a) may include at least one processor, such as a processor (1020a), at least one memory, such as a memory (1010a), and at least one transceiver, such as a transceiver (1031a). The processor (1020a) may perform the functions, procedures, and / or methods described above. The processor (1020a) may perform one or more protocols. For example, the processor (1020a) may perform one or more layers of a wireless interface protocol. The memory (1010a) may be connected to the processor (1020a) and may store various types of information and / or commands. The transceiver (1031a) may be connected to the processor (1020a) and may be controlled to transmit and receive wireless signals.

[0182] The second device (100b) may include at least one processor, such as a processor (1020b), at least one memory device, such as a memory (1010b), and at least one transceiver, such as a transceiver (1031b). The processor (1020b) may perform the functions, procedures, and / or methods described above. The processor (1020b) may implement one or more protocols. For example, the processor (1020b) may implement one or more layers of a wireless interface protocol. The memory (1010b) may be connected to the processor (1020b) and may store various types of information and / or commands. The transceiver (1031b) may be connected to the processor (1020b) and may be controlled to transmit and receive wireless signals.

[0183] The memory (1010a) and / or the memory (1010b) may be connected internally or externally to the processor (1020a) and / or the processor (1020b), or may be connected to another processor via various technologies such as a wired or wireless connection.

[0184] The first device (100a) and / or the second device (100b) may have one or more antennas. For example, the antenna (1036a) and / or the antenna (1036b) may be configured to transmit and receive wireless signals.

[0185] Fig. 16 is a block diagram showing the configuration of a terminal according to one embodiment of the present specification.

[0186] In particular, FIG. 16 is a drawing illustrating the device of FIG. 15 in more detail.

[0187] The device includes a memory (1010), a processor (1020), a transceiver (1031), a power management module (1091), a battery (1092), a display (1041), an input unit (1053), a speaker (1042), and a microphone (1052), a subscriber identification module (SIM) card, and one or more antennas.

[0188] The processor (1020) may be configured to implement the proposed functions, procedures, and / or methods described herein. Layers of a radio interface protocol may be implemented in the processor (1020). The processor (1020) may include an application-specific integrated circuit (ASIC), other chipsets, logic circuits, and / or data processing devices. The processor (1020) may be an application processor (AP). The processor (1020) may include at least one of a digital signal processor (DSP), a central processing unit (CPU), a graphics processing unit (GPU), and a modem (modulator and demodulator). Examples of the processor (1020) may be a SNAPDRAGON™ series processor manufactured by Qualcomm®, an EXYNOSTM series processor manufactured by Samsung®, an A series processor manufactured by Apple®, a HELIO™ series processor manufactured by MediaTek®, an ATOM™ series processor manufactured by INTEL®, a KIRINTM series processor manufactured by HiSilicon®, or a corresponding next-generation processor.

[0189] The power management module (1091) manages power to the processor (1020) and / or the transceiver (1031). The battery (1092) supplies power to the power management module (1091). The display (1041) outputs the results processed by the processor (1020). The input unit (1053) receives input to be used by the processor (1020). The input unit (1053) can be displayed on the display (1041). A SIM card is an integrated circuit used to securely store an international mobile subscriber identity (IMSI) and its associated keys, which are used to identify and authenticate subscribers in mobile devices such as mobile phones and computers. Contact information can also be stored on many SIM cards.

[0190] The memory (1010) is operably coupled to the processor (1020) and stores various information for operating the processor (610). The memory (1010) may include a read-only memory (ROM), a random access memory (RAM), flash memory, a memory card, a storage medium, and / or other storage devices. When the embodiment is implemented in software, the techniques described herein may be implemented as modules (e.g., procedures, functions, etc.) that perform the functions described herein. The modules may be stored in the memory (1010) and executed by the processor (1020). The memory (1010) may be implemented within the processor (1020). Alternatively, the memory (1010) may be implemented external to the processor (1020) and communicatively connected to the processor (1020) via various means known in the art.

[0191] The transceiver (1031) is operably coupled to the processor (1020) and transmits and / or receives a radio signal. The transceiver (1031) includes a transmitter and a receiver. The transceiver (1031) may include baseband circuitry for processing a radio frequency signal. The transceiver controls one or more antennas to transmit and / or receive a radio signal. The processor (1020) transmits command information to the transceiver (1031) to initiate communication, for example, to transmit a radio signal constituting voice communication data. The antenna functions to transmit and receive radio signals. Upon receiving a radio signal, the transceiver (1031) may transmit the signal to the processor (1020) for processing and convert the signal to baseband. The processed signal may be converted into audible or readable information output through the speaker (1042).

[0192] The speaker (1042) outputs sound-related results processed by the processor (1020). The microphone (1052) receives sound-related input to be used by the processor (1020).

[0193] A user inputs command information, such as a phone number, for example, by pressing (or touching) a button on an input unit (1053) or by voice activation using a microphone (1052). The processor (1020) receives this command information and processes it to perform an appropriate function, such as dialing a phone number. Operational data can be extracted from a SIM card or memory (1010). In addition, the processor (1020) can display command information or operation information on a display (1041) for the user's recognition and convenience.

[0194] Figure 17 shows a block diagram of a processor in which the disclosure of this specification is implemented.

[0195] As can be seen from FIG. 17, the processor (1020) implementing the disclosure of the present specification may include multiple circuits to implement the proposed functions, procedures, and / or methods described herein. For example, the processor (1020) may include a first circuit (1020-1), a second circuit (1020-2), and a third circuit (1020-3). Furthermore, although not shown, the processor (1020) may include more circuits. Each circuit may include multiple transistors.

[0196] The above processor (1020) may be called an application-specific integrated circuit (ASIC) or an application processor (AP), and may include at least one of a digital signal processor (DSP), a central processing unit (CPU), and a graphics processing unit (GPU).

[0197] Fig. 18 is a block diagram showing in detail the transmitter / receiver of the first device illustrated in Fig. 15 or the transmitter / receiver unit of the device illustrated in Fig. 16.

[0198] Referring to FIG. 18, the transceiver unit (1031) includes a transmitter (1031-1) and a receiver (1031-2). The transmitter (1031-1) includes a Discrete Fourier Transform (DFT) unit (1031-11), a subcarrier mapper (1031-12), an IFFT unit (1031-13), a CP insertion unit (1031-14), and a wireless transmitter unit (1031-15). The transmitter (1031-1) may further include a modulator. In addition, for example, the transmitter may further include a scramble unit (not shown), a modulation mapper (not shown), a layer mapper (not shown), and a layer permutator (not shown), which may be arranged before the DFT unit (1031-11). That is, in order to prevent an increase in PAPR (peak-to-average power ratio), the transmitter (1031-1) first passes the information through a DFT (1031-11) before mapping the signal to a subcarrier. The signal spread (or precoded in the same sense) by the DFT unit (1031-11) is mapped to a subcarrier through a subcarrier mapper (1031-12) and then passes through an IFFT (Inverse Fast Fourier Transform) unit (1031-13) to be converted into a signal on the time axis.

[0199] The DFT unit (1031-11) performs DFT on the input symbols and outputs complex-valued symbols. For example, if Ntx symbols are input (where Ntx is a natural number), the DFT size is Ntx. The DFT unit (1031-11) may be called a transform precoder. The subcarrier mapper (1031-12) maps the complex symbols to each subcarrier in the frequency domain. The complex symbols may be mapped to resource elements corresponding to resource blocks allocated for data transmission. The subcarrier mapper (1031-12) may be called a resource element mapper. The IFFT unit (1031-13) performs IFFT on the input symbols and outputs a baseband signal for data, which is a time-domain signal. The CP insertion unit (1031-14) copies a portion of the rear portion of the baseband signal for data and inserts it into the front portion of the baseband signal for data. CP insertion prevents ISI (Inter-Symbol Interference) and ICI (Inter-Carrier Interference), thereby maintaining orthogonality even in multipath channels.

[0200] On the other hand, the receiver (1031-2) includes a wireless reception unit (1031-21), a CP removal unit (1031-22), an FFT unit (1031-23), and an equalization unit (1031-24). The wireless reception unit (1031-21), the CP removal unit (1031-22), and the FFT unit (1031-23) of the receiver (1031-2) perform the inverse functions of the wireless transmission unit (1031-15), the CP insertion unit (1031-14), and the IFF unit (1031-13) of the transmitter (1031-1). The receiver (1031-2) may further include a demodulator.

[0201] Although the preferred embodiments have been described above by way of example, the disclosure of this specification is not limited to these specific embodiments, and may be modified, changed, or improved in various forms within the scope described in the spirit and claims of this specification.

[0202] In the exemplary system described above, the methods are described based on a flowchart as a series of steps or blocks. However, the order of the steps described is not limited, and some steps may occur in a different order or simultaneously with other steps described above. Furthermore, those skilled in the art will understand that the steps depicted in the flowchart are not exclusive, and other steps may be included, or one or more steps in the flowchart may be deleted without affecting the scope of the invention.

[0203] The claims set forth in this specification may be combined in various ways. For example, the technical features of the method claims of this specification may be combined and implemented as a device, and the technical features of the device claims of this specification may be combined and implemented as a method. Furthermore, the technical features of the method claims and the technical features of the device claims of this specification may be combined and implemented as a device, and the technical features of the method claims and the technical features of the device claims of this specification may be combined and implemented as a method.

Claims

1. In a method of operating a terminal in a wireless communication system, A step of receiving information of a first cell list and information of a second cell list associated with the first cell list; A step of measuring the quality of at least one first cell belonging to the first cell list; and Comprising a step of predicting quality information of at least one second cell belonging to the second cell list, A method wherein the quality information of at least one second cell is predicted using an artificial intelligence (AI) / machine learning (ML) model based on the measured quality of at least one first cell.

2. In paragraph 1, A method further comprising the step of evaluating a measurement reporting condition based on the predicted quality information of at least one second cell.

3. In paragraph 2, A method further comprising the step of transmitting a measurement report based on satisfaction of the above evaluated measurement report conditions.

4. In paragraph 1, A method wherein the first cell list is associated with an input of the AI / ML model, and the second cell list is associated with an output of the AI / ML model.

5. In paragraph 4, A method wherein the second cell list includes the first cell list.

6. In paragraph 1, A method wherein information of the first cell list and information of the second list are received via an RRC (radio resource control) message including measurement settings.

7. In a method of operating a base station in a wireless communication system, A step of transmitting information of a first cell list and information of a second cell list associated with the first cell list; and Comprising a step of receiving a measurement report based on quality information of at least one second cell belonging to the second cell list, A method wherein the quality information of at least one second cell is predicted using an AI (artificial intelligence) / ML (machine learning) model based on the measured quality of at least one first cell belonging to the first cell list.

8. In paragraph 7, A method wherein the first cell list is associated with an input of the AI / ML model, and the second cell list is associated with an output of the AI / ML model.

9. In paragraph 8, A method wherein the second cell list includes the first cell list.

10. In paragraph 7, A method wherein information of the first cell list and information of the second list are transmitted via an RRC (radio resource control) message including measurement settings.

11. As a terminal in a wireless communication system, at least one processor; and At least one memory storing instructions and being operably electrically connected to said at least one processor, wherein the operations performed based on the instructions being executed by said at least one processor are: A step of receiving information of a first cell list and information of a second cell list associated with the first cell list; A step of measuring the quality of at least one first cell belonging to the first cell list, and Comprising a step of predicting quality information of at least one second cell belonging to the second cell list, A terminal wherein the quality information of at least one second cell is predicted using an artificial intelligence (AI) / machine learning (ML) model based on the measured quality of at least one first cell.

12. In paragraph 11, Based on the above instruction being executed by the at least one processor, the operations performed are: A terminal further comprising a step of evaluating a measurement reporting condition based on the predicted quality information of at least one second cell.

13. In paragraph 12, Based on the above instruction being executed by the at least one processor, the operations performed are: A terminal further comprising a step of transmitting a measurement report based on satisfaction of the above evaluated measurement report conditions.

14. In paragraph 11, A terminal, wherein the first cell list is associated with the input of the AI / ML model, and the second cell list is associated with the output of the AI / ML model.

15. In paragraph 14, A terminal, wherein the second cell list includes the first cell list.

16. In paragraph 11, A terminal, wherein the information of the first cell list and the information of the second list are received via an RRC (radio resource control) message including measurement settings.

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