Method and apparatus for transmitting and receiving channel state information in wireless communication system

Abstract

A method and an apparatus for transmitting and receiving channel state information in a wireless communication system are disclosed. A method according to an embodiment of the present disclosure may comprise the steps of: receiving configuration information related to CSI from a base station; calculating CSI by deriving a channel measurement and / or an interference measurement from one or more CMRs and / or one or more IMRs determined based on the CSI reference resource; and transmitting the CSI to the base station.

Description

Technical Field

[0001] The present disclosure relates to a wireless communication system, and more particularly, to a method and apparatus for transmitting and receiving channel state information in a wireless communication system. Background Art

[0002] A mobile communication system has been developed to provide voice services while ensuring user mobility. However, the mobile communication system has been extended to data services as well as voice services, and currently, the explosive growth of services has led to resource shortages, and users have demanded faster services, thus requiring more advanced mobile communication systems.

[0003] The overall requirement for the next generation of mobile communication systems should be able to support the accommodation of explosive data services, a significant increase in the transmission rate per user, the accommodation of a significantly increased number of connected devices, very low end-to-end latency, and high energy efficiency. To this end, various technologies have been studied, including dual connectivity, massive multiple-input multiple-output (massive MIMO), in-band full-duplex, non-orthogonal multiple access (NOMA), ultra-wideband support, and device networking. Summary of the invention

[0004] Technical issues

[0005] The technical purpose of the present disclosure is to provide a method and device for sending and receiving CSI.

[0006] In addition, an additional technical objective of the present disclosure is to provide a method and apparatus for determining a CSI reference resource for calculating CSI.

[0007] In addition, an additional technical objective of the present disclosure is to provide a method and apparatus for determining channel measurement resources and / or interference measurement resources for deriving channel and / or interference measurement to calculate CSI.

[0008] The technical objectives achieved by the present disclosure are not limited to the above-mentioned technical objectives, and other technical objectives not described herein will be clearly understood by those skilled in the relevant art from the following description.

[0009] Technical Solution

[0010] A method performed by a user equipment (UE) in a wireless communication system according to one aspect of the present disclosure may include: receiving configuration information related to channel state information (CSI) from a base station; calculating CSI by deriving channel measurement and / or interference measurement based on one or more channel measurement resources (CMRs) and / or one or more interference measurement resources (IMRs) determined based on CSI reference resources; and sending CSI to the base station. The CSI reference resource may be determined as a time slot in the time domain that is later than a time slot in which the CSI is reported.

[0011] According to an additional aspect of the present disclosure, a method performed by a base station in a wireless communication system may include: sending configuration information related to channel state information (CSI) to a user equipment (UE); and receiving CSI from the UE. The CSI may be calculated by deriving channel measurement and / or interference measurement based on one or more channel measurement resources (CMRs) and / or one or more interference measurement resources (IMRs) determined based on a CSI reference resource, and the CSI reference resource may be determined as a time slot in the time domain that is later than a time slot in which the CSI is reported.

[0012] Technical Effects

[0013] According to the embodiments of the present disclosure, the channel aging effect of CSI can be minimized.

[0014] In addition, according to the embodiments of the present disclosure, it is possible to improve downlink transmission performance by inferring / predicting a channel at a time close to actual downlink transmission.

[0015] Effects achievable by the present disclosure are not limited to the above-described effects, and other effects not described herein may be clearly understood by those skilled in the relevant art from the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings, which are included as a part of the detailed description for understanding the present disclosure, provide embodiments of the present disclosure and describe technical features of the present disclosure through the detailed description.

[0017] Figure 1 The diagram shows a structure of a wireless communication system to which the present disclosure can be applied.

[0018] Figure 2 The figure illustrates a frame structure in a wireless communication system to which the present disclosure can be applied.

[0019] Figure 3 The diagram illustrates a resource grid in a wireless communication system to which the present disclosure may be applied.

[0020] Figure 4 The figure illustrates physical resource blocks in a wireless communication system to which the present disclosure can be applied.

[0021] Figure 5 The diagram illustrates a time slot structure in a wireless communication system to which the present disclosure can be applied.

[0022] Figure 6 Physical channels used in a wireless communication system to which the present disclosure can be applied and a general signal transmission and reception method using the physical channels are illustrated.

[0023] Figure 7 Illustration of the classification of artificial intelligence.

[0024] Figure 8 Diagram of a feedforward neural network.

[0025] Fig. 9 Diagram of a recurrent neural network.

[0026] Fig.10 Diagram of a convolutional neural network.

[0027] Fig.11 Shows the autoencoder.

[0028] Fig.12 Diagram of the functional framework for AI operations.

[0029] Fig.13 It is a diagram illustrating segmentation AI inference.

[0030] Fig.14 The diagram illustrates the application of the functional framework in a wireless communication system.

[0031] Fig.15 The diagram illustrates the application of the functional framework in a wireless communication system.

[0032] Fig.16 The diagram illustrates the application of the functional framework in a wireless communication system.

[0033] Fig.17 is a diagram illustrating a method for configuring CSI reference resources according to an embodiment of the present disclosure.

[0034] Fig.18 is a diagram illustrating a method for configuring CSI reference resources according to an embodiment of the present disclosure.

[0035] Fig.19 is a diagram illustrating a signaling process between a network and a UE for a method for transmitting and receiving channel state information according to an embodiment of the present disclosure.

[0036] Fig. 20 is a diagram illustrating an operation of a UE for a method of transmitting and receiving channel state information according to an embodiment of the present disclosure.

[0037] Fig.21 is a diagram illustrating an operation of a base station for a method of transmitting and receiving channel state information according to an embodiment of the present disclosure.

[0038] Fig. 22 A block diagram of a wireless communication device according to an embodiment of the present disclosure is illustrated. DETAILED DESCRIPTION

[0039] Hereinafter, embodiments according to the present disclosure will be described in detail with reference to the accompanying drawings. The detailed description to be disclosed by the accompanying drawings is intended to describe exemplary embodiments of the present disclosure, rather than to represent the only embodiment in which the present disclosure can be implemented. The following detailed description includes specific details to provide a complete understanding of the present disclosure. However, those skilled in the relevant art will appreciate that the present disclosure can be implemented without these specific details.

[0040] In some cases, well-known structures and devices may be omitted, or may be shown in the form of a block diagram based on the core functions of each structure and device in order to prevent ambiguity in the concepts of the present disclosure.

[0041] In the present disclosure, when an element is referred to as being "connected", "combined" or "linked" to another element, it may include an indirect connection relationship between another element and a direct connection relationship. In addition, in the present disclosure, the term "comprising" or "having" specifies the presence of the mentioned features, steps, operations, components and / or elements, but does not exclude the presence or addition of one or more other features, stages, operations, components, elements and / or groups thereof.

[0042] In the present invention, terms such as "first", "second", etc. are only used to distinguish one element from another element and are not used to limit the elements, and unless otherwise specified, they do not limit the order or importance between the elements. Therefore, within the scope of the present disclosure, the first element in an embodiment may be referred to as the second element in another embodiment, and similarly, the second element in an embodiment may be referred to as the first element in another embodiment.

[0043] The terms used in this disclosure are intended to describe specific embodiments rather than to limit the claims. As used in the description of the embodiments and the appended claims, the singular form is intended to include the plural form unless the context clearly indicates otherwise. The term "and / or" used in this disclosure may refer to one of the related enumerated items, or mean that it refers to and includes any and all possible combinations of two or more of them. In addition, unless otherwise stated, the " / " between words in the present invention has the same meaning as "and / or".

[0044] The present disclosure describes a wireless communication network or a wireless communication system, and operations performed in the wireless communication network can be performed in a process in which a device (e.g., a base station) controlling the corresponding wireless communication network controls the network and sends or receives signals, or can be performed in a process in which a terminal associated with the corresponding wireless network sends or receives signals between the network or the terminal.

[0045] In the present disclosure, sending or receiving a channel includes the meaning of sending or receiving information or signals through the corresponding channel. For example, sending a control channel means sending control information or control signals through the control channel. Similarly, sending a data channel means sending data information or data signals through the data channel.

[0046] In the following, downlink (DL) means communication from a base station to a terminal, and uplink (UL) means communication from a terminal to a base station. In the downlink, the transmitter may be part of a base station, and the receiver may be part of a terminal. In the uplink, the transmitter may be part of a terminal, and the receiver may be part of a base station. The base station may be expressed as a first communication device, and the terminal may be expressed as a second communication device. The base station (BS) may be replaced by terms such as a fixed station, a node B, an eNB (evolved node B), a gNB (next generation node B), a BTS (base station transceiver system), an access point (AP), a network (5G network), an AI (artificial intelligence) system / module, an RSU (roadside unit), a robot, a drone (UAV: unmanned aerial vehicle), an AR (augmented reality) device, a VR (virtual reality) device, and the like. In addition, the terminal can be fixed or mobile, and can be replaced by terms such as UE (user equipment), MS (mobile station), UT (user terminal), MSS (mobile subscriber station), SS (subscriber station), AMS (advanced mobile station), WT (wireless terminal), MTC (machine type communication) device, M2M (machine to machine) device, D2D (device to device) device, vehicle, RSU (roadside unit), robot, AI (artificial intelligence) module, drone (UAV: unmanned aerial vehicle), AR (augmented reality) device, VR (virtual reality) device, etc.

[0047] The following description can be used for various radio access systems, such as CDMA, FDMA, TDMA, OFDMA, SC-FDMA, etc. CDMA can be implemented by UTRA (Universal Terrestrial Radio Access) or CDMA2000. TDMA can be implemented by radio technologies such as GSM (Global System for Mobile Communications) / GPRS (General Packet Radio Service) / EDGE (Data Rate Enhanced GSM Evolution). OFDMA can be implemented by radio technologies such as IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE802-20, E-UTRA (Evolved UTRA), etc. 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) using E-UTRA, and LTE-A (Advanced) / LTE-A pro is an advanced version of 3GPP LTE. 3GPP NR (New Radio or New Radio Access Technology) is an advanced version of 3GPP LTE / LTE-A / LTE-A pro.

[0048] In order to make the description clearer, the description is based on the 3GPP communication system (e.g., LTE-A, NR), but the technical idea of ​​the present disclosure is not limited to this. LTE means the technology after 3GPP TS (Technical Specification) 36.xxx version 8. Specifically, the LTE technology in or after 3GPP TS 36.xxx version 10 is called LTE-A, and the LTE technology in or after 3GPP TS 36.xxx version 13 is called LTE-A pro. 3GPP NR means the technology in or after TS 38.xxx version 15. LTE / NR can be referred to as a 3GPP system. "xxx" means the detailed number of the standard document. LTE / NR can generally be referred to as a 3GPP system. For the background technology, terms, abbreviations, etc. used to describe the present disclosure, reference can be made to the matters described in the standard documents disclosed before the present disclosure. For example, reference can be made to the following documents.

[0049] For 3GPP LTE, reference may be made to TS 36.211 (Physical Channels and Modulation), TS 36.212 (Multiplexing and Channel Coding), TS 36.213 (Physical Layer Procedures), TS 36.300 (Overall Description), and TS 36.331 (Radio Resource Control).

[0050] For 3GPP NR, you can refer to TS 38.211 (Physical channels and modulation), TS 38.212 (Multiplexing and channel coding), TS 38.213 (Physical layer procedures for control), TS 38.214 (Physical layer procedures for data), TS 38.300 (NR and NG-RAN (Next Generation Radio Access Network) overall description), and TS 38.331 (Radio Resource Control Protocol Specification).

[0051] Abbreviations of terms that may be used in the present disclosure are defined as follows.

[0052] -BM: Beam Management

[0053] -CQI: Channel Quality Indicator

[0054] -CRI: Channel State Information-Reference Signal Resource Indicator

[0055] -CSI: Channel State Information

[0056] -CSI-IM: Channel State Information-Interference Measurement

[0057] -CSI-RS: Channel State Information-Reference Signal

[0058] -DMRS: Demodulation Reference Signal

[0059] -FDM: Frequency Division Multiplexing

[0060] -FFT: Fast Fourier Transform

[0061] -IFDMA: Interleaved Frequency Division Multiple Access

[0062] -IFFT: Inverse Fast Fourier Transform

[0063] -L1-RSRP: Layer 1 reference signal received power

[0064] -L1-RSRQ: Layer 1 reference signal reception quality

[0065] -MAC: Media Access Control

[0066] -NZP: Non-Zero Power

[0067] -OFDM: Orthogonal Frequency Division Multiplexing

[0068] –PDCCH: Physical Downlink Control Channel

[0069] -PDSCH: Physical Downlink Shared Channel

[0070] -PMI: Precoding matrix indicator

[0071] -RE: Resource Element

[0072] -RI: Rank indicator

[0073] -RRC: Radio Resource Control

[0074] -RSSI: Received Signal Strength Indicator

[0075] -Rx: Receive

[0076] -QCL: Quasi Co-sited

[0077] -SINR: Signal to Interference and Noise Ratio

[0078] -SSB (or SS / PBCH block): synchronization signal block (including PSS (primary synchronization signal), SSS (secondary synchronization signal) and PBCH (physical broadcast channel))

[0079] -TDM: Time Division Multiplexing

[0080] -TRP: Transmit and Receive Point

[0081] -TRS: Tracking Reference Signal

[0082] -Tx: Send

[0083] -UE: User Equipment

[0084] -ZP: Zero Power

[0085] Overall system

[0086] As more communication devices require higher capacity, there has been a demand for improved mobile broadband communications compared to existing radio access technologies (RATs). In addition, large-scale MTC (machine type communication) that provides various services anytime and anywhere by connecting multiple devices and things is also one of the main issues to be considered in the next generation of communications. In addition, the design of communication systems considering services / terminals that are sensitive to reliability and latency is also discussed. Therefore, the introduction of next-generation RATs considering eMBB (enhanced mobile broadband communication), mMTC (massive MTC), URLLC (ultra-reliable low-latency communication), etc. is discussed, and for convenience, the corresponding technology is referred to as NR in this disclosure. NR is an expression representing an example of 5G RAT.

[0087] The new RAT system including NR uses an OFDM transmission method or a transmission method similar thereto. The new RAT system may follow OFDM parameters different from those of LTE. Alternatively, the new RAT system follows the parameters of the existing LTE / LTE-A as is, but may support a wider system bandwidth (e.g., 100 MHz). Alternatively, a cell may support multiple parameter sets. In other words, terminals operating according to different parameter sets may coexist in one cell.

[0088] A parameter set corresponds to one subcarrier spacing in the frequency domain. As the reference subcarrier spacing is scaled by an integer N, different parameter sets can be defined.

[0089] Figure 1 The diagram illustrates a structure of a wireless communication system to which the present disclosure can be applied.

[0090] refer to Figure 1 , NG-RAN is configured with gNBs that provide the control plane (RRC) protocol side for the NG-RA (NG Radio Access) user plane (i.e., the new AS (Access Stratum) sublayer / PDCP (Packet Data Convergence Protocol) / RLC (Radio Link Control) / MAC / PHY) and the UE. The gNBs are interconnected through the Xn interface. In addition, the gNBs are connected to the NGC (Next Generation Core) through the NG interface. More specifically, the gNB is connected to the AMF (Access and Mobility Management Power) through the N2 interface, and to the UPF (User Plane Function) through the N3 interface.

[0091] Figure 2 The diagram illustrates a frame structure in a wireless communication system to which the present disclosure may be applied.

[0092] The NR system may support multiple parameter sets. Here, the parameter set may be defined by subcarrier spacing and cyclic prefix (CP) overhead. Here, multiple subcarrier spacings may be derived by scaling the basic (reference) subcarrier spacing by an integer N (or, μ). In addition, although it is assumed that very low subcarrier spacings are not used in very high carrier frequencies, the parameter set used may be selected independently of the frequency band. In addition, various frame structures according to multiple parameter sets may be supported in the NR system.

[0093] In the following, OFDM parameter sets and frame structures that can be considered in the NR system are described. Multiple OFDM parameter sets supported in the NR system can be defined as shown in Table 1 below.

[0094] [Table 1]

[0095] μ <![CDATA[Δf=2 μ ·15[kHz]]]> CP 0 15 normal 1 30 normal 2 60 Normal, Extended 3 120 normal 4 240 normal

[0096] NR supports multiple parameter sets (or subcarrier spacing (SCS)) for supporting various 5G services. For example, when the SCS is 15kHz, a wide area of ​​the traditional cellular band is supported; and when the SCS is 30kHz, the 5G service is supported. z / 60kH z When SCS is 60kHz or higher, bandwidth exceeding 24.25GHz is supported to overcome phase noise.

[0097] The NR band is defined as two types of frequency ranges (FR1, FR2). FR1, FR2 can be configured as shown in Table 2 below. In addition, FR2 may mean millimeter wave (mmW).

[0098] [Table 2]

[0099] Frequency range specification Corresponding frequency range Subcarrier spacing FR1 410MHz--7125MHz 15, 30, 60kHz FR2 24250MHz--52600MHz 60, 120, 240kHz

[0100] Regarding the frame structure in the NR system, the sizes of various fields in the time domain are expressed as T c =1 / (Δf max ·N f ) is a multiple of the time unit. Here, Δf max i is 480·10 3 Hz, and N f is 4096. Downlink and uplink transmissions are configured (organized) to have duration T f =1 / (Δf max N f / 100)·T c =10ms radio frame. Here, the radio frame is configured with 10 subframes, each of which has T sf =(Δf max N f / 1000)·T c In this case, there may be one frame set for the uplink and one frame set for the downlink. Furthermore, the transmission in the i-th uplink frame from the terminal should start T earlier than the corresponding downlink frame in the corresponding terminal. TA =(N TA +N TA,offset )T c For subcarrier spacing configuration μ, the time slots are arranged in n subframes. s μ ∈{0,...,N slot subframe,μ -1} and in the radio frame the number is incremented by n s，f μ ∈{0,...,N slot frame,μ-1}. A time slot is configured with N symb slot consecutive OFDM symbols, and N symb slot Determined according to CP. Time slot n in a subframe s μ The beginning of the OFDM symbol n in the same subframe s μ N symb slot All terminals may not perform transmission and reception at the same time, which means that all OFDM symbols of a downlink time slot or an uplink time slot may not be used.

[0101] Table 3 shows the number of OFDM symbols per time slot in a normal CP (N symb slot ), the number of time slots per radio frame (N slot frame,μ ) and the number of time slots per subframe (N slot subframe,μ ), and Table 4 represents the number of OFDM symbols per slot, the number of slots per radio frame, and the number of slots per subframe in the extended CP.

[0102] [Table 3]

[0103] μ <![CDATA[N symb slot ]]> <![CDATA[N slot frame，μ ]]> <![CDATA[N slot subframe，μ ]]> 0 14 10 1 1 14 20 2 2 14 40 4 3 14 80 8 4 14 160 16

[0104] [Table 4]

[0105] μ <![CDATA[N symb slot ]]> <![CDATA[N slot frame，μ ]]> <![CDATA[N slot subframe,μ ]]> 2 12 40 4

[0106] Figure 2 μ=2(SCS is 60kH z ), see Table 3, 1 subframe may include 4 time slots. Figure 2 1 subframe={1, 2, 4} shown in is an example, and the number of slots that may be included in 1 subframe is as defined in Table 3 or Table 4. In addition, a mini-slot may include 2, 4, or 7 symbols or more or less symbols.

[0107] Regarding the physical resources in the NR system, antenna ports, resource grids, resource elements, resource blocks, carrier parts, etc. can be considered. Hereinafter, the physical resources that can be considered in the NR system will be described in detail.

[0108] First, with respect to antenna ports, the antenna ports are defined so that the channel carrying the symbol in the antenna port can be inferred from the channel carrying other symbols in the same antenna port. When the large-scale properties of the channel on which the symbol in one antenna port is carried can be inferred from the channel carrying the symbol of another antenna port, it can be said that the two antenna ports are in a QC / QCL (quasi-co-located or quasi-co-located) relationship. In this case, the large-scale properties include at least one of delay spread, Doppler spread, frequency shift, average received power, and receive timing.

[0109] Figure 3 A resource grid in a wireless communication system to which the present disclosure may be applied is illustrated.

[0110] refer to Figure 3 , which graphically depicts a resource grid configuration with N in the frequency domain RB μ N sc RB subcarriers, and one subframe is configured with 14·2 μ OFDM symbols, but not limited to this. In the NR system, the transmitted signal consists of 2 μ N symb (μ) OFDM symbols and N RB μ N sc RB Here, N RB μ ≤N RB max，μ . N RB max,μ represents the maximum transmission bandwidth, which may differ between uplink and downlink and between parameter sets. In this case, one resource grid can be configured for each μ and antenna port p. Each element of the resource grid for μ and antenna port p is called a resource element and is uniquely identified by an index pair (k, 1′). Here, k = 0, ..., N RB μ N sc RB -1 is the index in the frequency domain, and 1′=0,...,2 μ N symb (μ) -1 refers to the symbol position in the subframe. When referencing a resource element in a slot, the index pair (k, 1) is used. Here, 1 = 0, ..., N symb μ -1. The resource element (k, l') for μ and antenna port p corresponds to the complex value a k,l' (p,μ)When there is no risk of confusion or when no specific antenna port or parameter set is specified, the indices p and μ may be dropped and the complex value may be a k,l' (p) or a k,l' In addition, a resource block (RB) is defined as N in the frequency domain. sc RB =12 consecutive subcarriers.

[0111] Point A serves as a common reference point for the resource block grid and is obtained as follows.

[0112] -OffsetToPointA for the primary cell (PCell) downlink represents the frequency offset between point A and the lowest subcarrier of the lowest resource block overlapping with the SS / PBCH block, which is used by the terminal for initial cell selection. Assuming a subcarrier spacing of 15kHz is used for FR1 and a subcarrier spacing of 60kHz is used for FR2, it is expressed in resource blocks.

[0113] -absoluteFrequencyPointA represents the frequency position of point A, expressed in ARFCN (Absolute Radio Frequency Channel Number).

[0114] For subcarrier spacing configuration μ, the common resource blocks are numbered from 0 upwards in the frequency domain. The center of subcarrier 0 of common resource block 0 for subcarrier spacing configuration μ is the same as "point A". Common resource block number n for subcarrier spacing configuration μ in the frequency domain CRB μ The relationship between and resource element (k, l) is given as follows in Equation 1.

[0115] [Formula 1]

[0116]

[0117] In Equation 1, k is defined relative to point A, so that k=0 corresponds to a subcarrier centered at point A. Physical resource blocks are spaced from 0 to N in a bandwidth part (BWP). BWP,i size,μ -1 numbering and i is the number of the BWP. Physical resource block n in BWP i PRB and public resource block n CRB The relationship between is given by the following formula 2.

[0118] [Formula 2]

[0119]

[0120] N BWP,i start,μ is the common resource block where the BWP starts relative to common resource block 0.

[0121] Figure 4 The figure illustrates a physical resource block in a wireless communication system to which the present disclosure can be applied. Figure 5 The diagram illustrates a time slot structure in a wireless communication system to which the present disclosure may be applied.

[0122] refer to Figure 4 and Figure 5 , a slot includes a plurality of symbols in the time domain. For example, for a normal CP, 1 slot includes 7 symbols, but for an extended CP, 1 slot includes 6 symbols.

[0123] A carrier includes 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) resource blocks in the frequency domain and may correspond to a parameter set (e.g., SCS, CP length, etc.). A carrier may include up to N (e.g., 5) BWPs. Data communication may be performed through an activated BWP, and only one BWP may be activated for a terminal. In a resource grid, each element is called a resource element (RE) and may map a complex symbol.

[0124] In the NR system, each component carrier (CC) can support up to 400MHz. If a terminal operating in such a wideband CC always operates to turn on the radio frequency (FR) chip for the entire CC, the terminal battery consumption may increase. Alternatively, when considering multiple application scenarios operating in a wideband CC (e.g., eMBB, URLLC, Mmtc, V2X, etc.), different parameter sets (e.g., subcarrier spacing, etc.) can be supported in each frequency band in the corresponding CC. Alternatively, each terminal may have different capabilities for the maximum bandwidth. Taking this into account, the base station can instruct the terminal to operate only in part of the bandwidth instead of the full bandwidth of the wideband CC, and for convenience, the corresponding partial bandwidth is defined as a bandwidth part (BWP). BWP can be configured with continuous RBs on the frequency axis and can correspond to a parameter set (e.g., subcarrier spacing, CP length, slot / microslot duration).

[0125] At the same time, even in one CC configured to the terminal, the base station can configure multiple BWPs. For example, a BWP occupying a relatively small frequency domain can be configured in the PDCCH monitoring time slot, and the PDSCH indicated by the PDCCH can be scheduled in a larger BWP. Alternatively, when the UE is congested in a specific BWP, other BWPs can be configured for some terminals for load balancing. Alternatively, considering the frequency domain inter-cell interference elimination between adjacent cells, some full-bandwidth intermediate spectrums can be excluded, and BWPs on two edges can be configured in the same time slot. In other words, the base station can configure at least one DL / UL BWP to a terminal associated with a broadband CC. The base station can activate at least one DL / UL BWP in the configured DL / UL BWP at a specific time (through L1 signaling or MAC CE (control element) or RRC signaling, etc.). In addition, the base station can indicate switching to other configured DL / UL BWPs (through L1 signaling or MAC CE or RRC signaling, etc.). Alternatively, based on a timer, when the timer value expires, it can switch to a determined DL / UL BWP. Here, the activated DL / UL BWP is defined as the active DL / UL BWP. However, when the terminal performs the initial access procedure or sets up the RRC connection, the configuration on the DL / UL BWP may not be received, so the DL / UL BWP assumed by the terminal in these cases is defined as the initial active DL / UL BWP.

[0126] Figure 6 Physical channels used in a wireless communication system to which the present disclosure can be applied and a general signal transmission and reception method using the physical channels are illustrated.

[0127] In a wireless communication system, a terminal receives information from a base station through a downlink and transmits information to the base station through an uplink. The information sent and received by the base station and the terminal includes data and various control information, and there are various physical channels according to the type / purpose of the information they send and receive.

[0128] When the terminal is turned on or newly enters a cell, it performs an initial cell search including synchronization with a base station (S601). For the initial cell search, the terminal can synchronize with the base station by receiving a primary synchronization signal (PSS) and a secondary synchronization signal (SSS) from the base station, and obtain information such as a cell identifier (ID). Then, the terminal can obtain broadcast information in the cell by receiving a physical broadcast channel (PBCH) from the base station. At the same time, the terminal can check the downlink channel status by receiving a downlink reference signal (DL RS) in the initial cell search phase.

[0129] The terminal that has completed the initial cell search may obtain more detailed system information by receiving a physical downlink control channel (PDCCH) and a physical downlink shared channel (PDSCH) according to information carried in the PDCCH (S602).

[0130] At the same time, when the terminal accesses the base station for the first time or there are no radio resources for signal transmission, it can perform a random access (RACH) process (S603 to S606) on the base station. For the random access process, the terminal can send a specific sequence as a preamble through a physical random access channel (PRACH) (S603 and S605), and can receive a response message to the preamble through a PDCCH and a corresponding PDSCH (S604 and S606). The contention-based RACH can additionally perform a contention resolution process.

[0131] The terminal that subsequently performs the above process may perform PDCCH / PDSCH reception (S607) and PUSCH (Physical Uplink Shared Channel) / PUCCH (Physical Uplink Control Channel) transmission (S608) as a general uplink / downlink signal transmission process. Specifically, the terminal receives downlink control information (DCI) via PDCCH. Here, DCI includes control information such as resource allocation information for the terminal, and the format varies according to its purpose of use.

[0132] At the same time, the control information sent by the terminal to the base station through the uplink or received by the terminal from the base station includes downlink / uplink ACK / NACK (acknowledgement / non-acknowledgement) signal, CQI (channel instruction indicator), PMI (precoding matrix indicator), RI (rank indicator), etc. For the 3GPP LTE system, the terminal can send the above-mentioned CQI / PMI / RI and other control information through PUSCH and / or PUCCH.

[0133] Table 5 shows an example of the DCI format in the NR system.

[0134] [Table 5]

[0135]

[0136] Referring to Table 5, DCI formats 0_0, 0_1 and 0_2 may include resource information (e.g., UL / SUL (supplementary UL), frequency resource allocation, time resource allocation, frequency hopping, etc.), information related to transport blocks (TBs) (e.g., MCS (modulation coding and scheme), NDI (new data indicator), RV (redundancy version)), etc.), information related to HARQ (Hybrid-Automatic Repeat and Request) (e.g., process number, DAI (downlink assignment index), PDSCH-HARQ feedback timing, etc.), information related to multiple antennas (e.g., DMRS sequence initialization information, antenna port, CSI request, etc.), power control information related to the scheduling of PUSCH (e.g., PUSCH power control, etc.), and the control information included in each DCI format may be predefined.

[0137] DCI format 0_0 is used to schedule PUSCH in one cell. Information included in DCI format 0_0 is CRC (Cyclic Redundancy Check) scrambled by C-RNTI (Cell Radio Network Temporary Identifier) ​​or CS-RNTI (Configured Scheduling RNTI) or MCS-C-RNTI (Modulation Coding Scheme Cell RNTI) and transmitted.

[0138] DCI format 0_1 ​​is used to indicate the scheduling of one or more PUSCHs or to configure grant (CG) downlink feedback information to a terminal in a cell. The information included in DCI format 0_1 ​​is scrambled and transmitted by C-RNTI or CS-RNTI or SP-CSI-RNTI (semi-persistent CSI RNTI) or MCS-C-RNTI.

[0139] DCI format 0_2 is used to schedule PUSCH in one cell. Information included in DCI format 0_2 is scrambled and transmitted by C-RNTI, CS-RNTI, SP-CSI-RNTI, or MCS-C-RNTI.

[0140] Next, DCI formats 1_0, 1_1 and 1_2 may include resource information (e.g., frequency resource allocation, time resource allocation, VRB (virtual resource block) -PRB (physical resource block) mapping, etc.), information related to transport blocks (TBs) (e.g., MCS, NDI, RV, etc.), information related to HARQ (e.g., process number, DAI, PDSCH-HARQ feedback timing, etc.), information related to multiple antennas (e.g., antenna ports, TCI (transmission configuration indicator), SRS (sounding reference signal) requests, etc.), information related to PUCCH scheduling regarding PDSCH (e.g., PUCCH power control, PUCCH resource indicator, etc.), and the control information included in each DCI format may be predefined.

[0141] DCI format 1_0 is used to schedule a PDSCH in one DL cell. Information included in DCI format 1_0 is a CRC scrambled and transmitted by a C-RNTI or a CS-RNTI or an MCS-C-RNTI.

[0142] DCI format 1_1 is used to schedule PDSCH in one cell. Information included in DCI format 1_1 is CRC scrambled and transmitted by C-RNTI or CS-RNTI or MCS-C-RNTI.

[0143] DCI format 1_2 is used to schedule PDSCH in one cell. Information included in DCI format 1_2 is CRC scrambled and transmitted by C-RNTI, CS-RNTI, or MCS-C-RNTI.

[0144] Artificial Intelligence (AI) Operation

[0145] With the technological advancement of artificial intelligence / machine learning (AI / ML), nodes and UEs in wireless communication networks are becoming more intelligent / advanced. Specifically, due to the intelligence of the network / base station, it is expected to be possible to quickly optimize and derive / apply various network / base station decision parameter values ​​(e.g., the transmit / receive power of each base station, the transmit power of each UE, the precoder / beam of the base station / UE, the time / frequency resource allocation for each UE, the duplex method of each base station, etc.) according to various environmental parameters (e.g., the distribution / location of base stations, the distribution / location / material of buildings / furniture, etc., the location / moving direction / speed of UE, climate information, etc.). Following this trend, many standardization organizations (e.g., 3GPP, O-RAN) are considering the introduction, and research on this is also actively underway.

[0146] The AI-related descriptions and operations described below can be applied in combination with the method proposed in the present disclosure described later, or can be supplemented to clarify the technical features of the method proposed in the present disclosure.

[0147] Figure 7 Illustration of the classification of artificial intelligence.

[0148] refer to Figure 7 , Artificial Intelligence (AI) corresponds to all automation in which machines are able to replace work that should be done by humans.

[0149] Machine learning (ML) refers to techniques in which machines learn decision-making patterns from data on their own without explicitly programmed rules.

[0150] Deep learning is a model based on artificial neural networks that allows machines to instantly perform feature extraction and decision making from unstructured data. The algorithm is inspired by biological nervous systems, or neural networks, and relies on a multi-layer network of interconnected nodes for feature extraction and transformation. Common deep learning network architectures include deep neural networks (DNNs), recurrent neural networks (RNNs), and convolutional neural networks (CNNs).

[0151] AI (or AI / ML) can be narrowly referred to as artificial intelligence based on deep learning, but the present disclosure is not limited thereto. That is, in the present disclosure, AI (or AI / ML) can be collectively referred to as automation technology applied to intelligent machines (e.g., UE, RAN, network nodes, etc.) that can perform tasks like humans.

[0152] AI (or AI / ML) can be classified according to various criteria as follows.

[0153] 1. Offline / Online Learning

[0154] a) Offline learning

[0155] Offline learning follows a sequential process of database collection, learning, and prediction. That is, collection and learning can be performed offline, and the completed program can be installed in the field and used for prediction work. For offline learning, the system does not learn incrementally, the learning is performed using all available collected data, and the learning is applied to the system without further learning. If learning about new data is necessary, learning can be restarted using all new data.

[0156] b) Online learning

[0157] This refers to a method that gradually improves performance by incrementally learning additional data using data generated in real time, and more recently, by taking advantage of the fact that data that can be used for learning is constantly being generated over the Internet. Learning is performed in real time for each (bundle) of specific data collected online, allowing the system to quickly adapt to the changing data.

[0158] AI systems are built using only online learning, so learning can be performed only with data generated in real time, or after performing offline learning using a predetermined data set, additional learning can be performed using additional real-time data (online + offline learning).

[0159] 2. Classification based on AI / ML framework concepts

[0160] a) Focused learning

[0161] In centralized learning, training data collected from multiple different nodes are reported to a centralized node, and all data resources / storage / learning (e.g., supervised learning, unsupervised learning, reinforcement learning, etc.) are performed in one centralized node.

[0162] b) Federated Learning

[0163] b) Federated learning is a collective model built on data that exists across distributed data owners. Instead of collecting data into the model, the AI / ML model is imported into the data source, allowing local nodes / single devices to collect data and train their own copies of the model, eliminating the need to report source data to a central node. In federated learning, the parameters / weights of the AI / ML model can be sent back to the centralized node to support general model training. Federated learning has advantages in increasing computing speed and information security. In other words, the process of uploading personal data to a central server is not necessary, preventing the leakage and abuse of personal information.

[0164] c) Distributed Learning

[0165] Distributed learning refers to a concept in which the machine learning process is scaled and distributed across a cluster of nodes. The trained model is partitioned and shared across multiple nodes running simultaneously to accelerate model training.

[0166] 3. Classification by learning method

[0167] a) Supervised Learning

[0168] Supervised learning is a machine learning task where the goal is to learn a mapping function from input to output given a labeled dataset. The input data is called training data and has known labels or outcomes. An example of supervised learning is as follows.

[0169] -Regression: linear regression, logistic regression

[0170] - Example-based algorithm: k-nearest neighbor (KNN)

[0171] -Decision Tree Algorithm: Classification and Regression Trees (CART)

[0172] -Support Vector Machine (SVM)

[0173] -Bayesian algorithm: Naive Bayes

[0174] - Fusion algorithm: Extreme Gradient Boosting, Bagging method: Random Forest

[0175] Supervised learning can be further divided into regression and classification problems, where classification is predicting a label and regression is predicting a quantity.

[0176] b) Unsupervised Learning

[0177] Unsupervised learning is a machine learning task that aims to learn features that describe hidden structure in unlabeled data. The input data is not labeled and no known outcome exists. Some examples of unsupervised learning include K-means clustering, principal component analysis (PCA), nonlinear independent component analysis (ICA), and long short-term memory (LSTM).

[0178] c) Reinforcement Learning (RL)

[0179] In reinforcement learning (RL), an agent aims to optimize a long-term goal by interacting with the environment based on a trial-and-error process and is goal-oriented learning based on interactions with the environment. An example of an RL algorithm is as follows.

[0180] -Q-Learning

[0181] - Multi-armed bandit learning

[0182] -Deep Q Network

[0183] - State-Action-Reward-State-Action (SARSA)

[0184] -Temporal Difference Learning

[0185] -Actuator-Evaluator Reinforcement Learning

[0186] -Deep Deterministic Policy Gradient (DDPG)

[0187] -Monte-Carlo tree search

[0188] In addition, reinforcement learning can be divided into model-based reinforcement learning and model-free reinforcement learning as follows.

[0189] -Model-based reinforcement learning: refers to RL algorithms that use predictive models. Using a model of the various dynamic states of the environment and which states bring rewards, it obtains the probability of transitioning between states.

[0190] - Model-free reinforcement learning: refers to RL algorithms based on values ​​or policies that maximize future rewards. The multi-agent environment / state is less computationally complex and does not require an accurate representation of the environment.

[0191] In addition, RL algorithms can also be divided into value-based RL and policy-based RL, policy-based RL and non-policy RL, etc.

[0192] In the following, representative models of deep learning are illustrated with examples.

[0193] Figure 8 Diagram of a feedforward neural network.

[0194] Feedforward neural network (FFNN) consists of input layer, hidden layer and output layer.

[0195] In FFNN, information is sent only from the input layer to the output layer, and if there is a hidden layer, the information passes through it.

[0196] Fig. 9 Diagram of a recurrent neural network.

[0197] A recurrent neural network (RNN) is an artificial neural network in which hidden nodes are connected to directed edges to form a directed cycle. This model is suitable for processing data that appears sequentially, such as speech and text.

[0198] exist Fig. 9 , A represents a neural network, xt represents an input value, and ht represents an output value. Here, ht may refer to a state value representing a current state based on time, and ht-1 may represent a previous state value.

[0199] One type of RNN is LSTM (Long Short-Term Memory), which has a structure that adds a cell state to the hidden state of the RNN. LSTM is able to erase unnecessary memory by adding an input gate, a forget gate, and an output gate to the RNN cell (the memory cell of the hidden layer). Compared to RNN, LSTM adds a cell state.

[0200] Fig.10 Diagram of a convolutional neural network.

[0201] Convolutional Neural Networks (CNNs) are used for two purposes: reducing model complexity and extracting superior features by applying convolution operations commonly used in the field of image processing or image processing.

[0202] - Kernel or filter: refers to a unit / structure that applies weights to the input of a specific range / unit. The kernel (or filter) can be changed through learning.

[0203] -Stride: refers to how far to move the kernel within the input.

[0204] - Feature map: refers to the result of applying the kernel to the input. Multiple feature maps can be extracted to ensure robustness to distortion, changes, etc.

[0205] -Padding: refers to the value added to resize the feature map.

[0206] -Pooling: refers to the operation of reducing the size of feature maps by downsampling them (e.g., max pooling, average pooling).

[0207] Fig.11 Graph of an autoencoder.

[0208] An autoencoder refers to a neural network that receives as input a feature vector x(x1, x2, x3, ...) and outputs the same or a similar vector x'(x'1, x'2, x'3, ...)'.

[0209] An autoencoder has the same properties as an input node and an output node. Since the autoencoder reconstructs the input, the output can be called a reconstruction. In addition, an autoencoder is a type of unsupervised learning.

[0210] Based on the difference between the input and output Fig.11 The loss function of the autoencoder is illustrated in , and based on this, the degree of input loss is identified and an optimization process is performed in the autoencoder to minimize the loss.

[0211] Hereinafter, for a more specific explanation of AI (or AI / ML), terms can be defined as follows.

[0212] -Data Collection: Data collected from network nodes, management entities or UEs as the basis for AI model training, data analysis and inference.

[0213] -AI Model: A data-driven algorithm that applies AI techniques and generates a set of outputs consisting of prediction information and / or decision parameters based on a set of inputs.

[0214] AI / ML training: The online or offline process of training an AI model by learning the features and patterns that best represent the data and obtaining a trained AI / ML model for inference.

[0215] AI / ML Inference: The process of using a trained AI / ML model to make predictions or guide decisions based on collected data and the AI / ML model.

[0216] Fig.12 Diagram of the functional framework for AI operations.

[0217] refer to Fig.12 , the data collection function (10) is a function of collecting input data and providing the processed input data to the model training function (20) and the model inference function (30).

[0218] Examples of input data may include measurements from the UE or different network entities, feedback from actuators, outputs from AI models.

[0219] The data collection function (10) performs data preparation based on the input data and provides the input data processed by the data preparation. Here, the data collection function (10) does not perform specific data preparation (e.g., data preprocessing and cleaning, formatting, and conversion) for each AI algorithm, and is capable of performing data preparation common to the AI ​​algorithm.

[0220] After performing the data preparation process, the model training function (10) provides training data (11) to the model training function (20), and provides inference data (12) to the model inference function (30). Here, the training data (11) is data required as input for the AI ​​model training function (20). The inference data (12) is data required as input for the AI ​​model inference function (30).

[0221] The data collection function (10) may be performed by a single entity (e.g., UE, RAN node, network node, etc.), but may also be performed by multiple entities. In this case, the training data (11) and the inference data (12) can be provided from the multiple entities to the model training function (20) and the model inference function (30), respectively.

[0222] The model training function (20) is a function that performs AI model training, validation, and testing, which can generate model performance metrics as part of the model testing process. If necessary, based on the training data (11) delivered by the data collection function (10), the model training function (20) is also responsible for data preparation (e.g., data preprocessing and cleaning, formatting, and conversion).

[0223] Here, model deployment / update (13) is used to initially deploy a trained, validated, and tested AI model to the model inference function (30) or to deliver an updated model to the model inference function (30).

[0224] The model inference function (30) is a function that provides AI model inference output (16) (e.g., predictions or decisions). When applicable, the model inference function (30) can provide model performance feedback (14) to the model training function (20). If necessary, based on the inferred data (12) delivered by the data collection function (10), the model inference function (30) is also responsible for data preparation (e.g., data preprocessing and cleaning, formatting and conversion).

[0225] Here, output (16) refers to the inferred output of the AI ​​model produced by the model inference function (30), and the details of the inferred output can be use case specific.

[0226] Model performance feedback (14) can be used to monitor the performance of the AI ​​model (when available), and this feedback can be omitted.

[0227] The actuator function (40) is a function that receives the output (16) from the model inference function (30) and triggers or performs corresponding actions. The actuator function (40) can trigger actions for other entities (e.g., one or more UEs, one or more RAN nodes, one or more network nodes, etc.) or for itself.

[0228] Feedback (15) can be used to derive training data (11), infer data (12), or monitor the performance of the AI ​​model and its impact on the network, etc.

[0229] Meanwhile, the definition of training / validation / testing in datasets used in AI / ML can be divided as follows.

[0230] -Training data: refers to the dataset used to learn the model.

[0231] - Validation data: This refers to a dataset used to validate the model that has already been learned. In other words, it usually refers to a dataset used to prevent overfitting of the training dataset.

[0232] It also refers to the data set used to select the best model among the various models learned during the learning process. Therefore, it can also be considered a type of learning.

[0233] -Test data: refers to the data set used for final evaluation. This data is not related to learning.

[0234] In the case of a dataset, if the training set is generally divided, then within the entire training set, the training data and validation data can be divided into 8:2 or 7:3, and if testing is included, 6:2:2 (training: validation: testing) can be used.

[0235] Depending on the capabilities of the AI / ML functions between the base station and the UE, the cooperation levels can be defined as follows, and can be modified by combining the following multiple levels or separating any one level.

[0236] Cat 0a) No collaboration framework: AI / ML algorithms are purely implementation based and do not require any air interface changes.

[0237] Cat 0b) This level corresponds to a framework without collaboration but with a modified air interface tailored for efficient implementation-based AI / ML algorithms.

[0238] Cat 1) This involves inter-node support to improve the AI / ML algorithms of each node. This applies if the UE receives support from the gNB (for training, adaptation, etc.) and vice versa. At this level, no model exchange between network nodes is required.

[0239] Cat 2) can perform joint ML tasks between UE and gNB. This level requires AI / ML model commands and exchanges between network nodes.

[0240] Previously in Fig.12 The functions illustrated in the figure may be implemented in a RAN node (eg, a base station, a TRP, a base station central unit (CU) etc.), a network node, an Operation Administration and Maintenance (OAM) of a network operator or a UE.

[0241] Alternatively, in Fig.12 The functions illustrated in the figure may be implemented by cooperation between two or more entities in the RAN, network nodes, network operator's OAM or UE. For example, one entity may perform Fig.12 Some of the functions of the other entity can be performed and other entities can perform the remaining functions. Fig.12 Some functions illustrated in the figure are performed by a single entity (e.g., UE, RAN node, network node, etc.), so the transmission / provision of data / information between each function can be omitted. For example, if the model training function (20) and the model inference function (30) are performed by the same entity, the deployment / update of the model (13) and the delivery / provision of the model performance feedback (14) can be omitted.

[0242] Alternatively, in Fig.12 Any of the functions illustrated in the figure may be performed by collaboration between two or more entities among the RAN, network nodes, network operator's OAM or UE. This can be referred to as split AI operation.

[0243] Fig.13 It is a diagram illustrating segmentation AI inference.

[0244] Fig.13 The diagram illustrates a situation where, in a split AI operation, the model inference function is performed in collaboration with an end device such as a UE and a network AI / ML endpoint.

[0245] In addition to the model inference function, the model training function, executor, and data collection functions are divided into multiple parts depending on the current task and environment, and can be executed collaboratively by multiple entities.

[0246] For example, the computationally intensive and energy-intensive parts can be executed at the network endpoint, while the personal information-sensitive and latency-sensitive parts can be executed at the end device. In this case, the end device is able to execute the task / model from the input data to a specific part / layer, and then send the intermediate data to the network endpoint. The network endpoint executes the remaining parts / layers and provides inference output to one or more devices that perform the action / task.

[0247] Fig.14 The diagram illustrates the application of the functional framework in a wireless communication system.

[0248] Fig.14 The diagram illustrates a situation where the AI ​​model training function is performed by a network node (e.g., a core network node, a network operator's OAM, etc.) and the AI ​​model inference function is performed by a RAN node (e.g., a base station, a TRP, a base station's CU, etc.).

[0249] Step 1: RAN Node 1 and RAN Node 2 send input data (i.e., training data) for AI model training to the network node. Here, RAN Node 1 and RAN Node 2 can send data collected from UEs (e.g., UE measurements related to RSRP, RSRQ, SINR of serving cells and neighboring cells, UE location, speed, etc.) to the network node.

[0250] Step 2: The network nodes use the received training data to train the AI ​​model.

[0251] Step 3: The network node distributes / updates the AI ​​model to RAN node 1 and / or RAN node 2. RAN node 1 (and / or RAN node 2) may continue to perform model training based on the received AI model.

[0252] For convenience of explanation, it is assumed that the AI ​​model has been distributed / updated only to RAN node 1 .

[0253] Step 4: RAN node 1 receives input data for AI model inference (i.e., inference data) from UE and RAN node 2.

[0254] Step 5: RAN node 1 performs AI model inference using the received inference data to generate output data (e.g., prediction or decision).

[0255] Step 6: If applicable, the RAN node 1 may send model performance feedback to the network node.

[0256] Step 7: RAN node 1, RAN node 2 and UE (or "RAN node 1 and UE", or "RAN node 1 and RAN node 2") perform actions based on the output data. For example, in the case of a load balancing operation, the UE may move from RAN node 1 to RAN node 2.

[0257] Step 8: RAN node 1 and RAN node 2 send feedback information to the network node.

[0258] Fig.15 The diagram illustrates the application of the functional framework in a wireless communication system.

[0259] Fig.15The diagram illustrates a situation where both the AI ​​model training function and the AI ​​model inference function are performed by a RAN node (e.g., a base station, a TRP, a CU of a base station, etc.).

[0260] Step 1: UE and RAN node 2 send input data (i.e., training data) for AI model training to RAN node 1.

[0261] Step 2: RAN node 1 uses the received training data to train the AI ​​model.

[0262] Step 3: RAN node 1 receives input data for AI model inference (i.e., inference data) from UE and RAN node 2.

[0263] Step 4: RAN node 1 performs AI model inference using the received inference data to generate output data (e.g., prediction or decision).

[0264] Step 5: RAN node 1, RAN node 2 and UE (or "RAN node 1 and UE", or "RAN node 1 and RAN node 2") perform actions based on the output data. For example, in the case of a load balancing operation, the UE may move from RAN node 1 to RAN node 2.

[0265] Step 6: RAN node 2 sends feedback information to RAN node 1.

[0266] Fig.16 The diagram illustrates the application of the functional framework in a wireless communication system.

[0267] Fig.16 The diagram illustrates a situation in which the AI ​​model training function is performed by a RAN node (e.g., a base station, a TRP, a CU of a base station, etc.) and the AI ​​model inference function is performed by a UE.

[0268] Step 1: The UE sends input data (i.e., training data) for AI model training to the RAN node. Here, the RAN node can collect data from various UEs and / or from other RAN nodes (e.g., UE measurements related to RSRP, RSRQ, SINR of the serving cell and neighboring cells, UE location, speed, etc.).

[0269] Step 2: The RAN node uses the received training data to train the AI ​​model.

[0270] Step 3: The RAN node distributes / updates the AI ​​model to the UE. The UE can continue to perform model training based on the received AI model.

[0271] Step 4: The UE receives input data for AI model inference (i.e., inference data) from the RAN node (and / or from other UEs).

[0272] Step 5: The UE performs AI model inference using the received inference data to generate output data (e.g., prediction or decision).

[0273] Step 6: If applicable, the UE may send model performance feedback to the RAN node.

[0274] Step 7: The UE and RAN nodes perform actions based on the output data.

[0275] Step 8: The UE sends feedback information to the RAN node.

[0276] CSI (Channel State Information) related operations

[0277] In NR (New Radio) systems, CSI-RS (Channel State Information-Reference Signal) is used for time and / or frequency tracking, CSI calculation, L1 (Layer 1)-RSRP (Reference Signal Received Power) calculation and mobility. Here, CSI calculation is related to CSI acquisition, while L1-RSRP calculation is related to beam management (BM).

[0278] CSI (Channel State Information) collectively refers to information that may indicate the quality of a radio channel (or also referred to as a link) formed between a terminal and an antenna port.

[0279] -In order to perform one of the uses of CSI-RS, a terminal (e.g., user equipment, UE) receives CSI-related configuration information from a base station (e.g., generalized Node B, gNB) through RRC (Radio Resource Control) signaling.

[0280] The CSI-related configuration information may include at least one of information related to CSI-IM (interference management) resources, information related to CSI measurement configuration, information related to CSI resource configuration, information related to CSI-RS resources, or information related to CSI report configuration.

[0281] i) Information related to CSI-IM resources may include CSI-IM resource information, CSI-IM resource set information, etc. A CSI-IM resource set is identified by a CSI-IM resource set ID (identifier), and a resource set includes at least one CSI-IM resource. Each CSI-IM resource is identified by a CSI-IM resource ID.

[0282] ii) Information related to CSI resource configuration may be expressed as CSI-ResourceConfig IE. The information related to CSI resource configuration defines a group including at least one of an NZP (non-zero power) CSI-RS resource set, a CSI-IM resource set, or a CSI-SSB resource set. In other words, the information related to CSI resource configuration may include a CSI-RS resource set list, and the CSI-RS resource set list may include at least one of an NZP CSI-RS resource set list, a CSI-IM resource set list, or a CSI-SSB resource set list. A CSI-RS resource set is identified by a CSI-RS resource set ID, and one resource set includes at least one CSI-RS resource. Each CSI-RS resource is identified by a CSI-RS resource ID.

[0283] Each NZP CSI-RS resource set may be configured with parameters indicating the usage of the CSI-RS (eg, a "repeat" parameter related to BM, a "trs-Info" parameter related to tracking).

[0284] iii) Information related to CSI report configuration includes a report configuration type (reportConfigType) parameter indicating the time domain behavior and a report quantity (reportQuantity) parameter indicating the CSI related quantity for reporting. The time domain behavior can be periodic, aperiodic or semi-persistent.

[0285] -The terminal measures the CSI based on the configuration information related to the CSI.

[0286] The CSI measurement may include (1) a process in which a terminal receives a CSI-RS and (2) a process in which a CSI is calculated through the received CSI-RS, and a detailed description thereof is described later.

[0287] For CSI-RS, the RE (resource element) mapping of CSI-RS resources in the time domain and frequency domain is configured through the higher layer parameter CSI-RS-ResourceMapping.

[0288] -The terminal reports the measured CSI to the base station.

[0289] In this case, when the number of CSI-ReportConfig is configured as "None (or No Report)", the terminal can omit the report. However, although the number is configured as "None (or No Report)", the terminal can also perform reporting to the base station. When the number is configured as "None", a non-periodic TRS or configuration repetition is triggered. In this case, the terminal's report can be omitted only when repetition is configured as "On".

[0290] 1) CSI measurement

[0291] The NR system supports more flexible and dynamic CSI measurement and reporting. Here, CSI measurement may include the process of receiving CSI-RS and obtaining CSI by calculating the received CSI-RS.

[0292] As time domain behavior of CSI measurement and reporting, aperiodic / semi-persistent / periodic CM (channel measurement) and IM (interference measurement) are supported. A 4-port NZP CSI-RS RE pattern is used for CSI-IM configuration.

[0293] NR's CSI-IM based IMR has a similar design to LTE's CSI-IM and is configured independently of the ZP CSI-RS resources for PDSCH rate matching. In addition, each port simulates the interference layer with (desirable channel sum) pre-coded NZP CSI-RS in the NZP CSI-RS based IMR. Because it is about intra-cell interference measurement for multi-user cases, it mainly targets MU interference.

[0294] The base station sends the precoded NZP CSI-RS to the terminal in each port of the configured NZP CSI-RS based IMR.

[0295] The terminal assumes a channel / interference layer and measures the interference for each port in the resource set.

[0296] When there is no PMI and RI feedback for a channel, multiple resources are configured in a set, and the base station or network indicates a subset of NZP CSI-RS resources through DCI for channel / interference measurement.

[0297] Describes resource settings and resource setting configuration in more detail.

[0298] 2) Resource settings

[0299] Each CSI resource setting "CSI-ResourceConfig" includes the configuration for S≥1 CSI resource sets (given by the higher layer parameter csi-RS-ResourceSetList). The CSI resource setting corresponds to CSI-RS-resourcesetlist. Here, S represents the number of configured CSI-RS resource sets. Here, the configuration for S≥1 CSI resource sets includes each CSI resource set, which includes SS / PBCH block (SSB) resources and CSI-RS resources (configured with NZP CSI-RS or CSI-IM) for L1-RSRP calculation.

[0300] Each CSI resource setting is located at a DL BWP (bandwidth part) identified by a higher layer parameter bwp-id. In addition, all CSI resource settings linked to a CSI reporting setting have the same DL BWP.

[0301] The time domain behavior of the CSI-RS resources in the CSI resource settings included in the CSI-ResourceConfig IE may be indicated by the higher layer parameter resourceType and may be configured as aperiodic, periodic or semi-persistent. For periodic and semi-persistent CSI resource settings, the number of configured CSI-RS resource sets (S) is limited to "1". For periodic and semi-persistent CSI resource settings, the configured periodicity and slot offset are given by the parameter set of the associated DL BWP, as given by bwp-id.

[0302] When the UE is configured with multiple CSI-ResourceConfigs including the same NZP CSI-RS resource ID, the same time domain behavior is configured for the CSI-ResourceConfigs.

[0303] When the UE is configured with multiple CSI-ResourceConfigs including the same CSI-IM resource ID, the same time domain behavior is configured for the CSI-ResourceConfigs.

[0304] One or more CSI resource settings for channel measurement (CM) and interference measurement (IM) are configured through higher layer signaling as follows.

[0305] -CSI-IM resources for interference measurements

[0306] -NZP CSI-RS resources for interference measurement

[0307] -NZP CSI-RS resources for channel measurement

[0308] In other words, the CMR (channel measurement resource) may be the NZP CSI-RS used for CSI acquisition, and the IMR (interference measurement resource) may be the NZP CSI-RS used for CSI-IM and IM.

[0309] In this case, CSI-IM (or ZP CSI-RS for IM) is mainly used for inter-cell interference measurement.

[0310] In addition, the NZP CSI-RS for IM is mainly used for intra-cell interference measurement from multiple users.

[0311] The UE may assume that the CSI-RS resources for channel measurement and the CSI-IM / NZP CSI-RS resources for interference measurement configured for one CSI report are "QCL-Type D" for each resource.

[0312] 3) Resource settings configuration

[0313] As mentioned above, a resource setting may mean a list of resource sets.

[0314] For aperiodic CSI, each trigger state configured using the higher layer parameter CSI-AperiodicTriggerState is associated with one or more CSI-ReportConfigs, each CSI-ReportConfig being linked to a periodic, semi-persistent or aperiodic resource setting.

[0315] One report setup can be linked to up to 3 resource setups.

[0316] - When configuring a resource setting, the resource setting (given by the higher layer parameter resourcesForChannelMeasurement) is about the channel measurement for L1-RSRP calculation.

[0317] - When two resource settings are configured, the first resource setting (given by the higher layer parameter resourcesForChannelMeasurement) is used for channel measurement and the second resource setting (given by csi-IM-ResourcesForInterference or nzp-CSI-RS-ResourcesForInterference) is used for interference measurements performed in CSI-IM or NZP CSI-RS.

[0318] -When three resource settings are configured, the first resource setting (given by resourcesForChannelMeasurement) is used for channel measurement, the second resource setting (given by csi-IM-ResourcesForInterference) is used for CSI-IM based interference measurement, and the third resource setting (given by nzp-CSI-RS-ResourcesForInterference) is used for NZP CSI-RS based interference measurement.

[0319] For semi-persistent or periodic CSI, each CSI-ReportConfig is linked to a periodic or semi-persistent resource setting.

[0320] - When a resource setting is configured (given by resourcesForChannelMeasurement), this resource setting is about the channel measurement for L1-RSRP calculation.

[0321] - When two resource settings are configured, the first resource setting (given by resourcesForChannelMeasurement) is used for channel measurement and the second resource setting (given by the higher layer parameter csi-IM-ResourcesForInterference) is used for interference measurements performed in CSI-IM.

[0322] 4) CSI calculation

[0323] When interference measurement is performed in CSI-IM, each CSI-RS resource used for channel measurement is associated with the CSI-IM resource of each resource in the order of CSI-RS resources and CSI-IM resources in the corresponding resource set. The number of CSI-RS resources used for channel measurement is the same as the number of CSI-IM resources.

[0324] In addition, when performing interference measurement in NZP CSI-RS, the UE does not expect that one or more NZP CSI-RS resources are configured in the resource set associated in the resource setting for channel measurement.

[0325] A terminal configured with the higher layer parameter nzp-CSI-RS-ResourcesForInterference does not expect that 18 or more NZP CSI-RS ports will be configured in the NZP CSI-RS resource set.

[0326] For CSI measurement, the terminal assumes the following.

[0327] - Each NZP CSI-RS port configured for interference measurement corresponds to an interfering transmission layer.

[0328] - All interfering transmission layers of the NZP CSI-RS port for interference measurement consider the EPRE (Energy Per Resource Element) ratio.

[0329] - Different interference signals in REs of NZP CSI-RS resources for channel measurement, NZP CSI-RS resources for interference measurement, or CSI-IM resources for interference measurement

[0330] 5) CSI Report

[0331] For CSI reporting, the time and frequency resources that the UE can use are controlled by the base station.

[0332] CSI (channel state information) may include at least one of a channel quality indicator (CQI), a precoding matrix indicator (PMI), a CSI-RS resource indicator (CRI), a SS / PBCH block resource indicator (SSBRI), a layer indicator (LI), a rank indicator (RI), or L1-RSRP.

[0333] For CQI, PMI, CRI, SSBRI, LI, RI, L1-RSRP, the terminal is configured by a higher layer with N≥1 CSI-ReportConfig report settings, M≥1 CSI-ResourceConfig resource settings and a list of one or two trigger states (provided by aperiodicTriggerStateList and semiPersistentOnPUSCH-TriggerStateList). Each trigger state in aperiodicTriggerStateList includes an associated CSI-ReportConfigs list, which indicates the channel and optional resource set ID for interference. In semiPersistentOnPUSCH-TriggerStateList, each trigger state includes an associated CSI-ReportConfig.

[0334] In addition, the time domain behavior of CSI reports supports periodic, semi-persistent, and aperiodic.

[0335] i) Periodic CSI reporting is performed in short PUCCH and long PUCCH. The periodicity and slot offset of periodic CSI reporting can be configured by RRC and referred to as CSI-ReportConfig IE.

[0336] ii) SP (semi-periodic) CSI reporting is performed in short PUCCH, long PUCCH or PUSCH.

[0337] For SP CSI in short / long PUCCH, the periodicity and slot offset are configured by RRC, and CSI reporting is activated / deactivated by a separate MAC CE / DCI.

[0338] For SP CSI in PUSCH, the periodicity of SP CSI reporting is configured by RRC, but the slot offset is not configured by RRC, and SP CSI reporting is activated / deactivated by DCI (format 0_1). For SP CSI reporting in PUSCH, a separate RNTI (SP-CSI C-RNTI) is used.

[0339] The initial CSI reporting timing follows the PUSCH time domain allocation value indicated by the DCI, and the subsequent CSI reporting timing follows the periodicity configured by the RRC.

[0340] DCI format 0_1 ​​may include a CSI request field and activate / deactivate a specific configured SP-CSI triggering state. SP CSI reporting has the same or similar activation / deactivation mechanism as data transmission in SPS PUSCH.

[0341] iii) Aperiodic CSI reporting is performed in PUSCH and triggered by DCI. In this case, information related to aperiodic CSI reporting triggering can be delivered / indicated / configured via MAC-CE.

[0342] For AP CSI with AP CSI-RS, the AP CSI-RS timing is configured by RRC and the timing of AP CSI reporting is dynamically controlled by DCI.

[0343] In NR, the method of dividing and reporting CSI in multiple reporting instances of PUCCH-based CSI reporting in LTE (for example, sending in the order of RI, WB PMI / CQI, SB PMI / CQI) is not applied. Instead, in NR, there is a restriction that specific CSI reports are not configured in short / long PUCCH, and CSI omission rules are defined. In addition, with respect to AP CSI reporting timing, the PUSCH symbol / slot position is dynamically indicated by DCI. In addition, the candidate slot offsets are configured by RRC. For CSI reporting, one slot offset (Y) is configured for each reporting setting. For UL-SCH, the slot offset K2 is configured separately.

[0344] Two CSI latency categories (low latency category, high latency category) are defined regarding CSI computational complexity. Low latency CSI is WB CSI, which includes up to 4 ports of type I codebook or up to 4 ports of non-PMI feedback CSI. High latency CSI refers to CSI other than low latency CSI. For ordinary terminals, (Z, Z') are defined in units of OFDM symbols. Here, Z represents the minimum CSI processing time from the receipt of a non-periodic CSI triggering DCI until the CSI report is performed. In addition, Z' refers to the minimum CSI processing time from the receipt of the CSI-RS for the channel / interference until the CSI report is performed.

[0345] In addition, the terminal reports the number of CSIs that can be calculated simultaneously.

[0346] CSI transmission and reception method

[0347] In order to perform the above-mentioned CSI related operations, the CSI reference resource may mean a frequency and time unit (ie, resource) assumed to be allocated / transmitted by the PDSCH when the UE calculates / derives the CSI, and may be defined as follows.

[0348] The CSI reference resources for the serving cell are defined as follows:

[0349] – In the frequency domain, the CSI reference resources are defined by the downlink physical resource block groups corresponding to the frequency band to which the derived CSI is related.

[0350] – In the time domain, the CSI reference resources for CSI reporting in uplink time slot n’ consist of a single downlink time slot Definition. Here, K offset is a parameter set by higher layers as specified in clause 4.2 of TS 38.213. And, μ Koffset It is for K offset The subcarrier spacing (SCS) setting for FR 1 is 0.

[0351] here, and μDL and μUL are the subcarrier spacing configurations for DL ​​and UL, respectively. slot , offset CA and μ offset Determined by ca-SlotOffset configured by higher layers for the cell transmitting uplink and downlink as defined in clause 4.5 of TS 38.211.

[0352] Here, for periodic and semi-persistent CSI reporting, i) if a single CSI-RS / SSB resource is configured for channel measurement, then n CSI_ref is greater than or equal to 4·2 μDL ii) if multiple CSI-RS / SSB resources are configured for channel measurement, then n CSI_ref is greater than or equal to 5.2 μDL The minimum value of so that it corresponds to a valid downlink time slot.

[0353] In addition, for aperiodic CSI reporting, if the DCI instructs the UE to report CSI in the same timeslot as the CSI request, then n CSI-ref The reference resource and the corresponding CSI request are located in the same valid downlink time slot. Otherwise, n CSI-ref is greater than or equal to The minimum value of time slot nn CSI_ref corresponds to an active downlink time slot, where Z' corresponds to the delay requirement defined in clause 5.4 of TS 38.214.

[0354] When periodic or semi-persistent CSI-RS / CSI-IM or SSB is used for channel / interference measurement, the UE does not expect to measure channel / interference on the CSI-RS / CSI-IM / SSB received from its last OFDM symbol until Z' symbols before the transmission time of the first OFDM symbol of the aperiodic CSI report.

[0355] In the above description, if i) the timeslot of the serving cell is a timeslot including at least one downlink or flexible symbol configured by a higher layer, and ii) the timeslot of the serving cell is not within a measurement gap configured for the UE, the timeslot of the serving cell is considered to be a valid downlink timeslot.

[0356] In addition, based on the above-mentioned CSI reference resources, CQI is defined as follows, and the channel measurement resources (CMR) and / or interference measurement resources (IMR) used for CQI calculation can be restricted as follows depending on the measurement restriction (MR) (ie, depending on whether the MR is set).

[0357] The CQI index and its explanation are given in Table 5.2.2.1-2 or Table 5.2.2.1-4 of clause 5.2.2.1 of TS 38.214 for reporting CQI based on QPSK, 16QAM and 64QAM. The CQI index and its explanation are given in Table 5.2.2.1-3 of clause 5.2.2.1 of TS 38.214 for reporting CQI based on QPSK, 16QAM, 64QAM and 256QAM. The CQI index and its explanation are given in Table 5.2.2.1-5 of clause 5.2.2.1 of TS 38.214 for reporting CQI based on QPSK, 16QAM, 64QAM, 256QAM and 1024QAM.

[0358] Based on an unrestricted observation interval in time (unless otherwise specified) and an unrestricted observation interval in frequency, the UE shall derive, for each CQI value reported in uplink timeslot n, the highest CQI index that satisfies the following conditions:

[0359] A single PDSCH transport block with a combination of modulation scheme, target code rate and transport block size corresponding to the CQI index and occupying a set of downlink physical resource blocks called CSI reference resources can be received with a transport block error probability not exceeding:

[0360] -0.1, if the higher layer parameter cqi-Table in CSI-ReportConfig is configured with "table1" (corresponding to Table 5.2.2.1-2) or "table2" (corresponding to Table 5.2.2.1-3), or if the higher layer parameter cqi-Table in CSIReportConfig is configured with "table4-r17" (corresponding to Table 5.2.2.1-5), or

[0361] -0.00001, if the higher layer parameter cqi-Table in CSI-ReportConfig is configured as "table3" (corresponding to Table 5.2.2.1-4).

[0362] If the higher layer parameter timeRestrictionForChannelMeasurements is set to 'notConfigured' (i.e. if no time restriction is configured for channel measurements), the UE shall derive channel measurements for calculating the CSI value reported in uplink timeslot n only based on NZP CSI-RS not later than the CSI reference resource associated with the CSI resource configuration.

[0363] If the higher layer parameter timeRestrictionForChannelMeasurements in CSI-ReportConfig is set to "Configured" (i.e. if time restrictions are configured for channel measurements), the UE shall derive channel measurements for calculating the CSI reported in uplink timeslot n based only on the most recent NZP CSI-RS occasion associated with the CSI resource setting that is no later than the CSI reference resource.

[0364] If the higher layer parameter timeRestrictionForInterferenceMeasurements is set to 'notConfigured' (i.e. if no time restriction is configured for interference measurements), the UE shall derive interference measurements for calculating the reported CSI value in uplink timeslot n only based on CSI-IM and / or NZP CSI-RS for interference measurements that are no later than the CSI reference resources associated with the CSI resource settings.

[0365] If the higher layer parameter timeRestrictionForInterferenceMeasurements in CSI-ReportConfig is set to "Configured" (i.e. if time restrictions are configured for interference measurements), the UE shall derive the interference measurement for calculating the reported CSI value in uplink timeslot n based on the most recent CSI-IM and / or NZP CSI-RS occasion associated with the CSI resource setting used for interference measurement, not later than the CSI reference resource.

[0366] Hereinafter, the embodiments / methods proposed in the present disclosure can be applied to a system having a function / capability of providing output (e.g., CSI calculation from CSI reference resources) from reasoning data (input) (e.g., channel measurements from CMR and / or interference measurements from IMR) through an AI / ML model (e.g., see Fig.12 ) UE (or, for convenience, referred to as AI UE).

[0367] Problem 1: Because the CSI reference resource is configured as the CSI reporting time or the time before the CSI reporting time, there is a difference between the time when the CSI is calculated and the time when the UE actually receives the PDSCH, which is susceptible to channel aging.

[0368] Fig.17 is a diagram illustrating a method for configuring CSI reference resources according to an embodiment of the present invention.

[0369] refer to Fig.17 According to the existing operation, the UE reports CSI (1702) based on the existing CSI reference resource (1701), and the base station can schedule the PDSCH (1705) using the DCI (1704) using the received CSI. In this case, since there is a difference between the time when the actual PDSCH (1705) is transmitted and the time when the CSI reference resource (1701) is transmitted, the CSI (1702) reported by the UE may have a difference in the transmission channel of the actual PDSCH (1705).

[0370] Embodiment 1: In order to improve the above-mentioned problem 1, a method of configuring CSI reference resources to the time when CSI is reported or after the time when CSI is reported is proposed.

[0371] refer to Fig.17 , the UE reports CSI (1702) based on the proposed CSI reference resource (1703), and the base station is able to schedule PDSCH (1705) using DCI (1704) using the received CSI.

[0372] In order to configure the CSI reference resource at or after the CSI reporting time, for example, the variable n used to determine the CSI reference resource can be set to CSI_ref is determined as the minimum value among the values ​​greater than or equal to a specific value (hereinafter referred to as M), so that the time slot nn CSI ref (or time slot ) corresponds to a valid downlink time slot.

[0373] Here, unlike the existing standards, M can be a negative number, and when the value of M is a negative number, it can be configured after the time of CSI report (1702). Fig.17 The proposed CSI reference resource (1703) is shown.

[0374] As described above, if i) the timeslot of the serving cell includes at least one downlink or flexible symbol configured by a higher layer and ii) the timeslot of the serving cell is not included in the measurement gap configured for the UE, the timeslot of the serving cell may be considered as a valid downlink timeslot.

[0375] The higher the channel prediction capability of the AI ​​UE, the smaller the M value that can be supported (i.e., a smaller negative value), and by applying a smaller M value, the CSI reference resource configuration can be configured farther than the CSI reporting time.

[0376] The UE may report the candidate (and / or range) of the M value and the channel prediction accuracy for each candidate (and / or the M value belonging to the range) to the base station (if a range is used, the unit of the available value of the M value may be predefined). The base station may determine the M value based on the channel prediction accuracy of each candidate (and / or the M value within the range) received from the UE and configure it to the UE. Alternatively, the UE may determine the M value and send the M value and its channel prediction accuracy to the base station together with the CSI.

[0377] In addition, the base station may indicate the candidate (and / or range) of the M value to the UE, and the UE may report the candidate prediction accuracy of each candidate (and / or the M value belonging to the range) to the base station. In this case, the base station may determine the M value based on the channel prediction accuracy of each candidate (and / or the M value belonging to the range) received from the UE and configure it to the UE.

[0378] In addition, the base station can configure / indicate a threshold for channel prediction accuracy, and the UE can report M values ​​exceeding the threshold to the base station. For example, the UE can report only the maximum M value exceeding the threshold to the base station, or can report one or more M values ​​exceeding the threshold to the base station. In addition, when reporting one or more M values ​​exceeding the threshold to the base station, the UE can also report the channel prediction accuracy of each M value to the base station. If more than one M value is reported to the base station, the base station can determine the M value based on the channel prediction accuracy of each M value and configure it to the UE.

[0379] In addition, (in addition to the above operations), the UE may report to the base station information about the measurement window required to achieve a specific M channel prediction accuracy. For example, the UE may report to the base station that it needs w2 CMRs and / or IMRs during w1 time slots, during which it performs channel measurement for CSI calculation. In this case, the base station may ensure this (i.e., configure the CMRs and / or IMRs so that w2 CMRs and / or IMRs exist during w1 time slots), so that the UE can achieve a specific M channel prediction accuracy.

[0380] In the above description, channel prediction means that the UE predicts the channel of the CSI reference resource based on the CMR used for measurement. In addition, the prediction accuracy of channel prediction means the accuracy of the UE prediction, not the accuracy between the actual channel and the predicted channel in the CSI reference resource. In other words, even if the UE reports a prediction accuracy of 100%, the actual channel and the predicted channel may be different.

[0381] In addition, the UE can calculate CSI for each of multiple CSI reference resources for multiple M values. For example, the UE can calculate CSI for a CSI reference resource configured / determined based on M=-2, and CSI for a CSI reference resource configured / determined based on M=-5, and the UE can send both CSIs to the base station. In this case, by sending the difference of the remaining CSI based on a specific CSI among the two CSIs (e.g., the CSI for a larger (or smaller) M), the CSI feedback overhead can be reduced. Alternatively, the UE can send the CSI calculated for an existing CSI reference resource (i.e., a CSI reference resource configured before the CSI reporting time) together with M CSIs for one or more M values, and in this case, only the difference of the CSI calculated for the existing reference resources can be sent to the base station.

[0382] In the case of non-periodic (AP) CSI reporting, the base station can indicate the M value and / or the threshold for channel prediction accuracy by triggering DCI. For example, if a single M value is indicated, the CSI reference resource can be determined using the corresponding M value. Alternatively, if a threshold for channel prediction accuracy is indicated, the CSI reference resource can be determined using an M value exceeding the threshold. If there are multiple M values ​​exceeding the threshold, the CSI reference resource can be determined using the M value with the maximum channel prediction accuracy.

[0383] Meanwhile, the CSI reference resource proposed in the above-mentioned embodiment 1 is calculated based on time slot n' as the CSI reporting time, however, the proposed CSI reference resource can be determined based on the existing CSI reference resource (i.e., the CSI reference resource configured before the CSI reporting time). For example, assuming that the existing CSI reference resource is time slot R, the proposed CSI reference resource can be determined as the nearest valid downlink time slot in the time slot less than or equal to time slot R+R' (R' is a natural number).

[0384] In addition, together with the CSI, the UE is able to additionally report the valid time of the CSI to the base station. That is, the UE is able to report time information applicable to the CSI to the base station. For example, the UE is able to report to the base station that the corresponding CSI is valid within K time slots starting from the CSI reporting time slot n' (e.g., K=2, where K is a natural number). That is, in this way, the UE is able to inform the base station that the CSI accurately reflects the state of the DL channel during time slot n', time slot n'+1, and time slot n'+2, so that the base station can use the corresponding CSI to perform DL transmission (e.g., PDSCH), and after time slot n'+2, the DL channel changes, so that when the corresponding CSI (i.e., the CSI reported in the CSI reporting time slot n') is used for DL ​​transmission, the DL performance will deteriorate. For example, if the CMR / IMR is a periodic / semi-persistent CSI-RS, the UE is able to report the measurement window to the base station according to the RS period.

[0385] Problem 2: When the CSI reference resource proposed in Embodiment 1 is used, problems may occur in existing measurement operations from CMR and / or IMR.

[0386] Fig.18 is a diagram illustrating a method for configuring CSI reference resources according to an embodiment of the present disclosure.

[0387] Fig.18 The diagram illustrates CSI reporting with periodic (P) / semi-persistent (SP) CMR configuration, and CSI reference resource configuration and PDSCH transmission according thereto.

[0388] In this case, when the CSI reference resource (1804) proposed in Embodiment 1 is used, a problem may occur in the existing measurement operation (from CMR or IMR (1802)). More specifically, according to the existing measurement operation, when the measurement restriction (MR) is on / enabled, the UE is restricted to perform measurement using the CMR most recently configured in the CSI reference resource slot or in the previous time, and when the MR is off / deactivated, the UE can perform measurement using multiple CMRs in the reference resource slot or in the previous time. Therefore, according to the existing measurement operation, the UE must predict the channel of the CSI reference resource proposed in Embodiment 1 from the channels estimated using these CMRs.

[0389] However, since the CSI reference resource (1804) proposed in Embodiment 1 is configured / determined after the CSI reporting (1803) time, if the existing MR configuration is applied, it is defined that the measurement is performed using CMRs 4, 5 configured at or after the CSI reporting (1803) time. In this case, since the UE cannot use the CMR configured at or after the CSI reporting (1803) time, there is a problem that such measurement is no longer valid.

[0390] Embodiment 2: In order to solve the above problem 2, a method is proposed to limit the use of CMR (or IMR) before the CSI reporting time for measurement.

[0391] More specifically, when MR (measurement restriction) is on, the use of the CMR (or IMR) configured most recently before the CSI report is restricted, and when MR is off, multiple CMRs (or IMRs) at the time before the CSI report can be used. Fig.18 When CSI reporting (1803) is performed based on the CSI reference resource (1804) proposed in Embodiment 1, it is possible to derive channel measurements for calculating CSI based on the CMR (or IMR) (1802) before the CSI reporting (1803) (i.e., Fig.18 CMR (or IMR) 1, CMR (or IMR) 2, CMR (or IMR) 3).

[0392] Here, if the CSI report and CMR are configured too close to each other, the UE's processing time (e.g., the CSI processing time z' defined in the NR standard, where z' represents the minimum CSI processing time from receiving the CSI-RS for channel / interference (i.e., CMR / IMR) to performing CSI reporting) is insufficient to measure / calculate and report CSI from the corresponding CMR. Fig.18In the example, CMR (or IMR) 3 is configured too close in time to the CSI report (1803) so that the UE cannot utilize it in view of the CSI processing time. Therefore, it is desirable to configure / define a certain time offset in view of the CSI processing time.

[0393] That is, in Embodiment 2, instead of defining MR based on CSI reporting time, MR can be defined based on {CSI reporting time-offset} value. In other words, CMR (or IMR) before {CSI reporting time-offset} can be limited for measurement. Therefore, Fig.18 CMR (or IMR) 3 of the CSI report cannot be used for measurement (1803) of the CSI report, and CMR (or IMR) 1 or 2 can be used for measurement. For example, when MR is off, both CMR (or IMR) 1 and 2 can be used for measurement, and when MR is on, only CMR (or IMR) 2 can be used for measurement.

[0394] Alternatively, in order to solve the above-mentioned problem 2, MR can be defined based on the existing CSI reference resource (i.e., the CSI reference resource set before the CSI reporting time). That is, when MR is turned on, it is limited to use the CMR that is most recently configured from the existing CSI reference resource time slot or the previous time, and when MR is turned off, multiple CMRs starting from the existing CSI reference resource time slot or the previous time can be used. Here, of course, the existing CSI reference resource is only used to define MR, and the actual CSI reference resource can be used as the proposed CSI reference resource. Therefore, in Fig.18 In the embodiment, when MR is turned off, the UE can use CMR (or IMR) 1, 2, and when MR is turned on, it can use CMR (or IMR) 2 to perform measurement.

[0395] Problem 3: In order to accurately estimate the channel of the CSI reference resource proposed according to Embodiment 1, extrapolation from multiple CMRs measured at different times is required. Therefore, the existing MR-on operation using only one CMR may be accurate or inaccurate, depending on the AI / ML capability of the UE. In addition, the number of CMRs required for prediction may vary depending on the AI / ML capability of the UE.

[0396] Embodiment 3: To solve the above problem 3, MR on can be defined as several levels.

[0397] Here, the UE can report these MR levels (and / or the prediction accuracy according to each MR level) to the base station.

[0398] Alternatively, the base station can indicate the MR level to the UE or request prediction accuracy according to the MR level.Alternatively, the base station can configure the UE to report the MR level whose prediction accuracy exceeds a threshold.

[0399] For example, MR levels can be defined as follows:

[0400] - MR level 0 (= existing MR on): restricts the use of the most recently configured CMR (or IMR) to a specific time (eg, existing CSI reference resources (ie, CSI reference resources configured before the CSI reporting time) or CSI reporting time) or earlier.

[0401] - MR level 1: Restricts the use of CMRs (or IMRs) configured at a specific time (eg, an existing CSI reference resource (ie, a CSI reference resource configured before a CSI reporting time) or a CSI reporting time) or the two most recently configured CMRs before.

[0402] MR level 2: restricting the use of the three CMRs (or IMRs) configured at a specific time (eg, an existing CSI reference resource (ie, a CSI reference resource configured before a CSI reporting time) or a CSI reporting time) or before the most recently configured time.

[0403] For example, when using Fig.18 In the case of MR level 0 of the existing CSI reference resource (1801) in, CMR (or IMR) 2 can be used for measurement. In addition, in the case of using MR level 1, CMR (or IMR) 1 and 2 can be used for measurement.

[0404] The UE can calculate CSI for each of a plurality of MR levels and report the plurality of CSI calculated in this manner to the base station. In this case, the feedback overhead can be reduced by reporting the difference of the remaining CSI based on the CSI measured using a specific MR level (e.g., MR level 0).

[0405] The UE may report / request to the base station that the time interval between the CMR most recently received before the proposed CSI reference resource and the proposed CSI reference resource is less than a certain value (e.g., T1) to ensure prediction accuracy, and / or may report / request to the base station that the time interval between P / SP CMRs is less than a certain value (e.g., T2). Here, if these time conditions are not met, the UE may not report the corresponding CSI, or may report the most recently reported CSI without calculation.

[0406] In the above embodiments 1 to 3, when the UE reports multiple CSIs, the above method based on the specific CSI report difference may be used, and / or some CSIs (i.e., some information / indications within the CSI) may be assumed to be common CSI and reported only once to the base station without repetition. For example, because the RI may not change significantly depending on the CSI reference resource, the UE may report only one common value of the RI to the base station, and calculate and report the remaining PMI / CQI, etc., respectively according to the CSI reference resource.

[0407] In addition, in the above-mentioned embodiments 1 to 3, for the sake of convenience of explanation, the explanation is mainly focused on CMR, but the same method can also be applied to IMR.

[0408] In addition, any one of the methods suggested in the above-mentioned Embodiments 1 to 3 may be applied, and a plurality of the proposed methods may be combined / aggregated and finally applied.

[0409] In addition, the base station can indicate to the UE whether to apply the methods suggested in the above embodiments 1 to 3 through signaling such as RRC / MAC-CE / DCI (eg, DCI activating SP CSI reporting or DCI triggering AP CSI reporting, etc.).

[0410] Fig.19 is a diagram illustrating a signaling process between a network and a UE for a method for transmitting and receiving channel state information according to an embodiment of the present disclosure.

[0411] Fig.18 The diagram shows signaling between a network (e.g., TRP 1, TRP 2) and a UE to which the method proposed in the present disclosure (e.g., a combination of one or more of the methods proposed in Embodiments 1 to 3, Embodiments 1 to 3) can be applied. Here, UE / network is only an example and can be replaced by various devices. Fig.19 It is only for the convenience of explanation and does not limit the scope of the present disclosure. In addition, depending on the situation and / or setting, it can be omitted. Fig.19 Some of the steps are shown in the figure.

[0412] Fig.19The signaling method described in can be extended and applied to signaling between multiple TRPs and multiple UEs. In the following description, the network can be a base station including multiple TRPs, and can be a cell including multiple TRPs. For example, an ideal / non-ideal backhaul can be configured between TRP 1 and TRP 2 that constitute the network. In addition, the following description is based on multiple TRPs, but it can be equally extended and applied to transmission through multiple panels. In addition, in the present disclosure, the operation of UE receiving a signal from TRP1 / TRP2 can also be interpreted / described as the operation of UE receiving a signal from the network (via / using TRP1 / 2) (or can be its operation), and the operation of UE sending a signal to TRP1 / TRP2 can also be interpreted / described as the operation of UE sending a signal to the network (via / using TRP1 / TRP2) (or can be its operation), and vice versa.

[0413] A base station may be a general term for an object that performs data transmission and reception with a UE. For example, a base station may be a concept including one or more TPs (transmission points), one or more TRPs (transmission and reception points), and the like. In addition, a TP and / or a TRP may include a panel, a transmission and reception unit, and the like of a base station. In addition, "TRP" may be applied by replacing it with expressions such as a panel, an antenna array, a cell (e.g., a macro cell / small cell / micro cell, etc.), a transmission point, a base station (gNB, etc.). As described above, TRPs can be distinguished based on information (e.g., an index, an ID) about a relevant CORESET group (or CORESET pool). As described above, TRPs can be distinguished based on information (e.g., an index, an ID) about a relevant CORESET group (or CORESET pool). For example, if one UE is configured to perform transmission and reception with multiple TRPs (or cells), this may mean configuring multiple CORESET groups (or CORESET pools) for one UE. The configuration of such a CORESET group (or CORESET pool) can be performed via higher layer signaling (e.g., RRC signaling, etc.).

[0414] The UE can receive configuration information from the network (S1901).

[0415] The configuration information may include information related to network configuration (e.g., TRP configuration) / information related to M-TRP-based transmission and reception (e.g., resource allocation, etc.). Here, the configuration information may be sent via higher layer signaling (e.g., RRC signaling, MAC-CE, etc.).

[0416] The configuration information may include the CSI-related configuration information described in the above-mentioned methods (eg, embodiments 1 to 3, or a combination of one or more of the methods proposed in embodiments 1 to 3).

[0417] The CSI-related configuration information may include at least one of information related to CSI-IM (interference management) resources, information related to CSI measurement configuration, information related to CSI resource configuration, or information related to CSI report configuration.

[0418] Here, the CSI-related configuration information may include configuration information related to CSI reporting (i.e., CSI reporting configuration) (e.g., RRC IE "CSI-ReportConfig") (hereinafter referred to as the first configuration information) and configuration information related to CSI resources (i.e., CSI resource configuration) (e.g., RRC IE "CSI-ResourceConfig") (hereinafter referred to as the second configuration information).

[0419] Here, multiple CSI-RS resources for CSI calculation / measurement can be configured for the UE through configuration information related to CSI resources (i.e., CSI resource settings). In addition, one or more channel measurement resources (CMRs) (e.g., NZP CSI-RS) and / or one or more interference measurement resources (IMRs) (e.g., CSI-IM and / or NZP CSI-RS) can be configured through configuration information related to CSI resources (i.e., CSI resource settings). CMRs and IMRs may be collectively referred to as CSI resources.

[0420] In addition, configuration information related to CSI resources (i.e., CSI resource settings) can be connected / associated with configuration information related to specific CSI reports (i.e., CSI report settings), and based on the report quantity (reportQuantity) in the CSI report settings, the UE can be configured with CSI reports (e.g., CRI, PMI, RI, CQI, LI, etc.) for multiple CSI resources configured by the connected / associated CSI resource settings.

[0421] The UE receives CSI-RS from a plurality of CSI resources configured by configuration information (eg, CSI resource setting) from a network (S1902).

[0422] The UE can receive downlink control information (DCI) from the network (S1903).

[0423] Here, the DCI may be a DCI that triggers aperiodic CSI reporting to the UE, or may be a DCI that activates semi-persistent CSI reporting.

[0424] In addition, DCI can be sent via a downlink control channel (e.g., PDCCH, etc.), and in addition to triggering / activating CSI reporting, it can also schedule a downlink data channel (e.g., PDSCH) / uplink data channel (e.g., PUSCH).

[0425] The UE sends (reports) CSI to the network (S1904).

[0426] Here, CSI may include at least one of CQI, PMI, RI, CRI, and LI.

[0427] As described above, the UE may report CSI to the network based on the configuration information related to CSI reporting (and according to the triggering / activation of DCI). For example, the configuration information related to CSI reporting may configure the CSI reporting type, such as periodic CSI reporting, semi-persistent CSI reporting, and aperiodic CSI reporting, and may configure which information (e.g., CRI, CQI, PMI, RI, LI, etc.) should be reported in the CSI, and in the case of periodic CSI reporting, may also configure the periodicity and time slot offset, etc.

[0428] According to the above-mentioned embodiments 1 to 3, CSI can be calculated / obtained by deriving / performing channel measurement and / or interference measurement according to one or more CSI resources (ie, one or more CMRs and / or one or more IMRs) determined based on CSI reference resources.

[0429] Here, according to the above-mentioned embodiment 1, the CSI reference resource may be determined as a time slot in the time domain that is later than the time slot in which the CSI is reported. To this end, for example, the CSI reference resource may be determined based on a time slot n-nCSI_ref that is later than the uplink time slot n' in which the CSI is reported, and nCSI_ref may be determined to be greater than or equal to the minimum value of the variable (M) so that the CSI reference resource corresponds to a valid downlink time slot.

[0430] Here, the value of the variable (M) may be provided by configuration information (e.g., configuration information related to CSI reporting) or downlink control information (DCI) triggering CSI reporting. Here, the UE can send / report the variable (M) and the candidate for the channel prediction accuracy for each time slot to the network based on the candidate for the variable (M) (i.e., the UE assumes that the channel prediction accuracy is calculated by applying the CSI reference resource determined by the variable (M)). In this case, the network can also determine the variable (M) based on this and provide it to the UE.

[0431] In addition, the UE may determine the variable (M) and send / report the variable (M) and the channel prediction accuracy for the time slot according to the variable (M) to the network. For example, the variable (M) and the channel prediction accuracy for the time slot according to the variable (M) may be sent to the network together with (or included in) the CSI.

[0432] In addition, the network configures a threshold (or determines / defines a threshold in advance), and the UE can send / report to the network a variable (M) for a time slot in which the channel prediction accuracy exceeds the threshold. For example, the variable (M) can be sent to the network together with (or included in) the CSI.

[0433] In addition, although Fig.19 , but the UE may send information about a measurement window required to achieve a channel prediction accuracy for a time slot according to a specific variable (M) higher than a specific level to the network before reporting CSI to the network. Here, the information about the measurement window may include the number of time slots, the number of CMRs, and / or the number of IMRs.

[0434] In addition, the CSI may include N CSIs for each of the N CSI reference resources according to N variables (M) (N is a natural number). For example, the CSI finally reported to the network may include both the first CSI for the first CSI reference resource determined by applying the first variable (M1) and the second CSI for the second CSI reference resource determined by applying the second variable (M2). In such a case, the CSI may also include N variables (M).

[0435] In addition, the CSI may include information about the time when the corresponding CSI is valid.

[0436] In addition, according to the above-mentioned embodiment 2, channel measurement and / or interference measurement can be derived / performed based on one or more CMRs and / or one or more IMRs before the uplink time slot in which the CSI is reported or before the offset from the uplink time slot in which the CSI is reported, so as to calculate the CSI. That is, the one or more CMRs and / or one or more IMRs used to calculate the CSI can be limited to before the uplink time slot in which the CSI is reported or before the offset from the uplink time slot in which the CSI is reported.

[0437] In addition, according to the above-mentioned embodiment 3, the measurement restriction (MR) can be defined as a plurality of levels. In this case, the number of CMRs and / or IMRs used for calculating CSI can be determined according to the level of the measurement restriction.

[0438] Meanwhile, the above-mentioned operation of calculating CSI (i.e., the operation of calculating CSI by predicting the channel) (or the operation of calculating the channel prediction accuracy) can be performed by the UE (or an external device installed or connected to the UE), and is used for the above-mentioned operation of calculating CSI (or channel prediction accuracy) Fig.12 At least one function of the AI / ML operation (particularly, model inference) can be performed by the UE (or an external device installed or connected to the UE). In addition, the UE (or an external device installed or connected to the UE) can also perform the above Fig.16The process (specifically 5. Model inference) determines the mapping pattern.

[0439] Fig. 20 is a diagram illustrating an operation of a UE for a method of transmitting and receiving channel state information according to an embodiment of the present disclosure.

[0440] refer to Fig. 20 , Fig. 20 The operation of the UE based on the proposed method (eg, a combination of one or more of the methods proposed in Embodiments 1 to 3 or Embodiments 1 to 3) is illustrated. Fig. 20 The examples are for convenience of explanation and do not limit the scope of the present disclosure. Depending on the situation and / or setting, the Fig. 20 In addition, Fig. 20 The UE in the example is only an example and can be implemented as follows Fig. 22 The device shown in the figure. For example, Fig. 22 The processor (102 / 202) can control the transceiver (106 / 206) to send and receive channels / signals / data / information, etc., and can also control Fig. 22 The processor (102 / 202) stores the transmitted or received channel / signal / data / information etc. in the memory (104 / 204).

[0441] in addition, Fig. 20 The operation can be done by Fig. 22 One or more processors (102, 202) of the processor, and Fig. 20 The operation can be used to drive Fig. 22 The instructions / programs (eg, instructions, executable codes) of at least one processor (eg, 102, 202) are stored in a memory (eg, Fig. 22 in one or more memories (104, 204)).

[0442] The UE receives configuration information related to channel state information (CSI) from a base station (S2001).

[0443] The CSI-related configuration information may include the CSI-related configuration information described in the above-mentioned methods (eg, embodiments 1 to 3, or a combination of one or more of the methods proposed in embodiments 1 to 3).

[0444] The CSI-related configuration information may include at least one of information related to CSI-IM (interference management) resources, information related to CSI measurement configuration, information related to CSI resource configuration, or information related to CSI report configuration.

[0445] Here, the CSI-related configuration information may include configuration information related to CSI reporting (i.e., CSI reporting configuration) (e.g., RRC IE "CSI-ReportConfig") (hereinafter referred to as the first configuration information) and configuration information related to CSI resources (i.e., CSI resource configuration) (e.g., RRC IE "CSI-ResourceConfig") (hereinafter referred to as the second configuration information).

[0446] Among them, multiple CSI-RS resources for CSI calculation / measurement can be configured for the UE through the configuration information related to the CSI resource (i.e., CSI resource setting). In addition, one or more channel measurement resources (CMR) (e.g., NZP CSI-RS) and / or one or more interference measurement resources (IMR) (e.g., CSI-IM and / or NZP CSI-RS) can be configured through the configuration information related to the CSI resource (i.e., CSI resource setting). CMR and IMR can be collectively referred to as CSI resources.

[0447] In addition, it is possible to connect / associate configuration information related to CSI resources (i.e., CSI resource settings) with configuration information related to specific CSI reports (i.e., CSI report settings), and to configure CSI reports (e.g., CRI, PMI, RI, CQI, LI, etc.) for the UE for multiple CSI resources configured through the connected / associated CSI resource settings according to the report quantity (reportQuantity) in the CSI report settings.

[0448] Although Fig. 20 Although not shown in the figure, the UE may receive downlink control information (DCI) from the base station. Here, the DCI may be a DCI that triggers aperiodic CSI reporting to the UE, or may be a DCI that activates semi-persistent CSI reporting. In addition, the DCI may be sent via a downlink control channel (e.g., PDCCH, etc.), and in addition to triggering / activating CSI reporting, may also schedule a downlink data channel (e.g., PDSCH) / uplink data channel (e.g., PUSCH).

[0449] The UE calculates / obtains CSI (S2002) by deriving / performing channel measurement and / or interference measurement based on one or more CSI resources (i.e., one or more CMRs and / or one or more IMRs) determined based on the CSI reference resource. In addition, the UE sends (reports) the CSI to the network (S2003). Here, the CSI may include at least one of CQI, PMI, RI, CRI, and LI.

[0450] That is, the UE receives CSI-RS from multiple CSI resources configured by configuration information (e.g., CSI resource settings), and calculates CSI based on one or more CSI resources (i.e., one or more CMRs and / or one or more IMRs) determined based on the CSI reference resource. In addition, the UE may report CSI to the network based on the configuration information related to CSI reporting (and based on triggering / activation through DCI). For example, the configuration information related to CSI reporting may configure CSI reporting types, such as periodic CSI reporting, semi-persistent CSI reporting, and aperiodic CSI reporting, and may configure which information should be reported in the CSI (e.g., CRI, CQI, PMI, RI, LI, etc.), and in the case of periodic CSI reporting, may also configure the period and time slot offset, etc.

[0451] According to the above-mentioned embodiments 1 to 3, CSI can be calculated / obtained by deriving / performing channel measurement and / or interference measurement based on one or more CSI resources (ie, one or more CMRs and / or one or more IMRs) determined based on CSI reference resources.

[0452] Here, according to the above-mentioned embodiment 1, the CSI reference resource can be determined as a time slot in the time domain that is later than the time slot in which the CSI is reported. To this end, for example, the CSI reference resource can be determined based on a time slot n-nCSI_ref that is later than the uplink time slot n' in which the CSI is reported, and nCSI_ref can be determined to be greater than or equal to the minimum value of the variable (M) so that the CSI reference resource corresponds to a valid downlink time slot.

[0453] The value of the variable (M) may be provided by configuration information (e.g., configuration information related to CSI reporting) or downlink control information (DCI) that triggers CSI reporting. Here, the UE is able to send / report to the base station the candidate for the variable (M) and the candidate channel prediction accuracy for each time slot according to the candidate for the variable (M) (i.e., the UE assumes that the channel prediction accuracy is calculated by applying the CSI reference resource determined by the variable (M)). In this case, the base station is also able to determine the variable (M) based on this and provide it to the UE.

[0454] In addition, the UE may determine the variable (M) and transmit / report the variable (M) and the channel prediction accuracy for the time slot according to the variable (M) to the base station. For example, the variable (M) and the channel prediction accuracy for the time slot according to the variable (M) may be transmitted to the base station together with (or included in) the CSI.

[0455] In addition, the base station configures a threshold (or determines / defines a threshold in advance), and the UE can send / report to the base station a variable (M) for a time slot where the channel prediction accuracy exceeds the threshold. For example, the variable (M) can be sent to the base station together with (or included in) the CSI.

[0456] In addition, although Fig. 20 , but the UE may send information about a measurement window required to achieve a channel prediction accuracy higher than a certain level for a time slot according to a certain variable (M) to the network before reporting CSI to the network. Here, the information about the measurement window may include the number of time slots, the number of CMRs, and / or the number of IMRs.

[0457] In addition, the CSI may include N CSIs for each of the N CSI reference resources according to N variables (M) (N is a natural number). For example, the CSI finally reported to the network may include both the first CSI for the first CSI reference resource determined by applying the first variable (M1) and the second CSI for the second CSI reference resource determined by applying the second variable (M2). In such a case, the CSI may also include N variables (M).

[0458] In addition, the CSI may include information about the time when the corresponding CSI is valid.

[0459] In addition, according to the above-mentioned embodiment 2, channel measurement and / or interference measurement can be derived / performed based on one or more CMRs and / or one or more IMRs before the uplink time slot in which CSI is reported or before the offset from the uplink time slot in which CSI is reported, so as to calculate CSI. That is, one or more CMRs and / or one or more IMRs used to calculate CSI can be limited to before the uplink time slot in which CSI is reported or before the offset from the uplink time slot in which CSI is reported.

[0460] In addition, according to the above-mentioned embodiment 3, the measurement restriction (MR) can be defined as a plurality of levels. In this case, the number of CMRs and / or IMRs used for calculating CSI can be determined according to the level of the measurement restriction.

[0461] Meanwhile, the above-mentioned operation of calculating CSI (i.e., the operation of calculating CSI by predicting the channel) (or the operation of calculating the channel prediction accuracy) can be performed by the UE (or an external device installed or connected to the UE), and is used for the above-mentioned operation of calculating CSI (or channel prediction accuracy) Fig.12 At least one function of the AI / ML operation (particularly, model inference) can be performed by the UE (or an external device installed or connected to the UE). In addition, the UE (or an external device installed or connected to the UE) can also perform the above Fig.16The process (specifically 5. Model inference) determines the mapping pattern.

[0462] Fig.21 is a diagram illustrating an operation of a base station for a method of transmitting and receiving channel state information according to an embodiment of the present disclosure.

[0463] refer to Fig.21 , Fig.21 The diagram illustrates the operation of the base station based on the proposed method (eg, a combination of one or more of the methods proposed in Embodiments 1 to 3 or Embodiments 1 to 3). Fig.21 The examples are for convenience of explanation and do not limit the scope of the present disclosure. Depending on the situation and / or setting, the Fig.21 In addition, Fig.21 The base station in is only an example and can be implemented as follows Fig. 22 The device shown in the figure. For example, Fig. 22 The processor (102 / 202) can control the transceiver (106 / 206) to send and receive channels / signals / data / information, etc., and can also control Fig. 22 The processor (102 / 202) stores the transmitted or received channel / signal / data / information etc. in the memory (104 / 204).

[0464] in addition, Fig.21 The operation can be done by Fig. 22 One or more processors (102, 202) of the processor, and Fig. 20 The operation can be used to drive Fig. 22 The instructions / programs (eg, instructions, executable codes) of at least one processor (eg, 102, 202) are stored in a memory (eg, Fig. 22 in one or more memories (104, 204)).

[0465] The base station sends configuration information related to channel state information (CSI) to the UE (S2101).

[0466] The CSI-related configuration information may include the CSI-related configuration information described in the above-mentioned methods (eg, embodiments 1 to 3, or a combination of one or more of the methods proposed in embodiments 1 to 3).

[0467] The CSI-related configuration information may include at least one of information related to CSI-IM (interference management) resources, information related to CSI measurement configuration, information related to CSI resource configuration, or information related to CSI report configuration.

[0468] Here, the CSI-related configuration information may include configuration information related to CSI reporting (i.e., CSI reporting configuration) (e.g., RRC IE "CSI-ReportConfig") (hereinafter referred to as the first configuration information) and configuration information related to CSI resources (i.e., CSI resource configuration) (e.g., RRC IE "CSI-ResourceConfig") (hereinafter referred to as the second configuration information).

[0469] Among them, multiple CSI-RS resources for CSI calculation / measurement can be configured for the UE through the configuration information related to the CSI resource (i.e., CSI resource setting). In addition, one or more channel measurement resources (CMR) (e.g., NZP CSI-RS) and / or one or more interference measurement resources (IMR) (e.g., CSI-IM and / or NZP CSI-RS) can be configured through the configuration information related to the CSI resource (i.e., CSI resource setting). CMR and IMR can be collectively referred to as CSI resources.

[0470] In addition, it is possible to connect / associate configuration information related to CSI resources (i.e., CSI resource settings) with configuration information related to specific CSI reports (i.e., CSI report settings), and to configure CSI reports (e.g., CRI, PMI, RI, CQI, LI, etc.) for the UE for multiple CSI resources configured through the connected / associated CSI resource settings according to the report quantity (reportQuantity) in the CSI report settings.

[0471] Although Fig.21 Not shown, but the base station may send downlink control information (DCI) to the UE. Here, the DCI may be a DCI that triggers aperiodic CSI reporting to the UE, or may be a DCI that activates semi-persistent CSI reporting. In addition, the DCI may be sent via a downlink control channel (e.g., PDCCH, etc.), and in addition to triggering / activating CSI reporting, may also schedule a downlink data channel (e.g., PDSCH) / uplink data channel (e.g., PUSCH).

[0472] The base station receives CSI from the UE (S2102). Here, the CSI may include at least one of CQI, PMI, RI, CRI, and LI.

[0473] Here, the CSI is calculated / obtained by deriving / performing channel measurement and / or interference measurement according to one or more CSI resources (ie, one or more CMRs and / or one or more IMRs) determined based on the CSI reference resource.

[0474] That is, the CSI-RS is sent to the UE from a plurality of CSI resources configured by configuration information (e.g., CSI resource setting), and the CSI is calculated based on one or more CSI resources (i.e., one or more CMRs and / or one or more IMRs) determined based on the CSI reference resource. In addition, the base station is able to receive CSI from the UE based on the configuration information related to the CSI report (and based on the triggering / activation through the DCI). For example, according to the configuration information related to the CSI report, CSI report types such as periodic CSI report, semi-persistent CSI report, and non-periodic CSI report can be configured, and which information should be reported in the CSI (e.g., CRI, CQI, PMI, RI, LI, etc.) can be configured, and in the case of periodic CSI report, periodicity and time slot offset, etc. can also be configured.

[0475] According to the above-mentioned embodiments 1 to 3, CSI can be calculated / obtained by deriving / performing channel measurement and / or interference measurement according to one or more CSI resources (ie, one or more CMRs and / or one or more IMRs) determined based on CSI reference resources.

[0476] Here, according to the above-mentioned embodiment 1, the CSI reference resource can be determined as a time slot in the time domain that is later than the time slot in which the CSI is reported. To this end, for example, the CSI reference resource can be determined based on a time slot n-nCSI_ref that is later than the uplink time slot n' in which the CSI is reported, and nCSI_ref can be determined to be greater than or equal to the minimum value of the variable (M) so that the CSI reference resource corresponds to a valid downlink time slot.

[0477] Here, the value of the variable (M) may be provided by configuration information (e.g., configuration information related to CSI reporting) or downlink control information (DCI) triggering CSI reporting. Here, the UE is able to send / report to the base station the candidate for the variable (M) and the candidate channel prediction accuracy for each time slot according to the candidate for the variable (M) (i.e., the UE assumes that the channel prediction accuracy is calculated by applying the CSI reference resource determined by the variable (M)). In this case, the base station is also able to determine the variable (M) based on this and provide it to the UE.

[0478] In addition, the base station can receive the variable (M) determined by the UE and the channel prediction accuracy for the time slot according to the variable (M) from the UE. For example, the variable (M) and the channel prediction accuracy for the time slot according to the variable (M) can be received from the UE together with the CSI (or included in the CSI).

[0479] In addition, a variable (M) for a time slot in which the channel prediction accuracy exceeds a threshold configured by the base station (or a predetermined / defined threshold) can be received from the UE. For example, the variable (M) and the CSI can be received from the UE (or included in the CSI).

[0480] In addition, although Fig.21 Although not shown in the figure, the base station may receive information about a measurement window required to achieve a channel prediction accuracy higher than a certain level for a time slot according to a certain variable (M) from the UE before receiving CSI from the UE. Here, the information about the measurement window may include the number of time slots, the number of CMRs, and / or the number of IMRs.

[0481] In addition, the CSI may include N CSIs for each of the N CSI reference resources according to N variables (M) (N is a natural number). For example, the CSI finally reported to the network may include both the first CSI for the first CSI reference resource determined by applying the first variable (M1) and the second CSI for the second CSI reference resource determined by applying the second variable (M2). In such a case, the CSI may also include N variables (M).

[0482] In addition, the CSI may include information about the time when the corresponding CSI is valid.

[0483] In addition, according to the above-mentioned embodiment 2, channel measurement and / or interference measurement can be derived / performed based on one or more CMRs and / or one or more IMRs before the uplink time slot in which CSI is reported or before the offset from the uplink time slot in which CSI is reported, so as to calculate CSI. That is, one or more CMRs and / or one or more IMRs used to calculate CSI can be limited to before the uplink time slot in which CSI is reported or before the offset from the uplink time slot in which CSI is reported.

[0484] In addition, according to the above-mentioned embodiment 3, the measurement restriction (MR) can be defined as a plurality of levels. In this case, the number of CMRs and / or IMRs used for calculating CSI can be determined according to the level of the measurement restriction.

[0485] Meanwhile, the above-mentioned operation of calculating CSI (i.e., the operation of calculating CSI by predicting the channel) (or the operation of calculating the channel prediction accuracy) can be performed by the UE (or an external device installed or connected to the UE), and is used for the above-mentioned operation of calculating CSI (or channel prediction accuracy) Fig.12 At least one function of the AI / ML operation (particularly, model inference) can be performed by the UE (or an external device installed or connected to the UE). In addition, the UE (or an external device installed or connected to the UE) can also perform the above Fig.16The process (specifically 5. Model inference) determines the mapping pattern.

[0486] General equipment to which the present disclosure can be applied

[0487] Fig. 22 is a diagram illustrating a block diagram of a wireless communication device according to an embodiment of the present disclosure.

[0488] refer to Fig. 22 , the first wireless device 100 and the second wireless device 200 can send and receive wireless signals through a variety of radio access technologies (e.g., LTE, NR).

[0489] The first wireless device 100 may include one or more processors 102 and one or more memories 104, and may further include one or more transceivers 106 and / or one or more antennas 108. The processor 102 may control the memory 104 and / or the transceiver 106 and may be configured to implement the description, function, process, proposal, method and / or operation flowchart disclosed in the present disclosure. For example, the processor 102 may send a wireless signal including the first information / signal through the transceiver 106 after generating the first information / signal by processing the information in the memory 104. In addition, the processor 102 may receive a wireless signal including the second information / signal through the transceiver 106, and then store the information obtained by signal processing of the second information / signal in the memory 104. The memory 104 may be connected to the processor 102 and may store various information related to the operation of the processor 102. For example, the memory 104 may store software code including commands for executing all or part of the process controlled by the processor 102 or for executing the description, function, process, proposal, method and / or operation flowchart disclosed in the present disclosure. Here, the processor 102 and the memory 104 may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). The transceiver 106 may be connected to the processor 102 and may send and / or receive wireless signals through one or more antennas 108. The transceiver 106 may include a transmitter and / or a receiver. The transceiver 106 may be used in conjunction with an RF (radio frequency) unit. In the present disclosure, a wireless device may refer to a communication modem / circuit / chip.

[0490] The second wireless device 200 may include one or more processors 202 and one or more memories 204, and may further include one or more transceivers 206 and / or one or more antennas 208. The processor 202 may control the memory 204 and / or the transceiver 206 and may be configured to implement the description, function, process, proposal, method and / or operation flowchart disclosed in the present disclosure. For example, the processor 202 may generate third information / signal by processing the information in the memory 204, and then transmit the wireless signal including the third information / signal through the transceiver 206. In addition, the processor 202 may receive a wireless signal including fourth information / signal through the transceiver 206, and then store the information obtained by signal processing of the fourth information / signal in the memory 204. The memory 204 may be connected to the processor 202 and may store various information related to the operation of the processor 202. For example, the memory 204 may store software code including commands for executing all or part of the process controlled by the processor 202 or for executing the description, function, process, proposal, method and / or operation flowchart disclosed in the present disclosure. Here, the processor 202 and the memory 204 may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). The transceiver 206 may be connected to the processor 202 and may send and / or receive wireless signals through one or more antennas 208. The transceiver 206 may include a transmitter and / or a receiver. The transceiver 206 may be used in conjunction with an RF unit. In the present disclosure, a wireless device may refer to a communication modem / circuit / chip.

[0491] In the following, the hardware elements of the wireless device 100, 200 will be described in more detail. It is not limited to this, and one or more protocol layers can be implemented by one or more processors 102, 202. For example, one or more processors 102, 202 can implement one or more layers (e.g., functional layers such as PHY, MAC, RLC, PDCP, RRC, SDAP). One or more processors 102, 202 can generate one or more PDUs (protocol data units) and / or one or more SDUs (service data units) according to the description, function, process, proposal, method and / or operation flow chart included in the present disclosure. One or more processors 102, 202 can generate messages, control information, data or information according to the description, function, process, proposal, method and / or operation flow chart disclosed in the present disclosure. One or more processors 102, 202 can generate signals (e.g., baseband signals) including PDUs, SDUs, messages, control information, data or information according to the functions, processes, proposals and / or methods disclosed in the present disclosure to provide them to one or more transceivers 106, 206. One or more processors 102, 202 may receive signals (e.g., baseband signals) from one or more transceivers 106, 206 and obtain PDUs, SDUs, messages, control information, data, or information according to the descriptions, functions, processes, proposals, methods, and / or operational flow charts disclosed in the present disclosure.

[0492] One or more processors 102, 202 may be referred to as controllers, microcontrollers, microprocessors, or microcomputers. One or more processors 102, 202 may be implemented by hardware, firmware, software, or a combination thereof. In an example, one or more ASICs (Application Specific Integrated Circuits), one or more DSPs (Digital Signal Processors), one or more DSPDs (Digital Signal Processing Devices), one or more PLDs (Programmable Logic Devices), or one or more FPGAs (Field Programmable Gate Arrays) may be included in one or more processors 102, 202. The descriptions, functions, processes, proposals, methods, and / or operational flowcharts disclosed in the present disclosure may be implemented using firmware or software and the firmware or software may be implemented to include modules, processes, functions, etc. Firmware or software configured to execute the descriptions, functions, processes, proposals, methods, and / or operational flowcharts disclosed in the present disclosure may be included in one or more processors 102, 202 or may be stored in one or more memories 104, 204 and driven by one or more processors 102, 202. The descriptions, functions, processes, proposals, methods, and / or operational flowcharts disclosed in the present disclosure may be implemented by firmware or software in the form of codes, commands, and / or command sets.

[0493] One or more memories 104, 204 may be connected to one or more processors 102, 202 and may store data, signals, messages, information, programs, codes, instructions, and / or commands in various forms. One or more memories 104, 204 may be configured with ROM, RAM, EPROM, flash memory, hard drive, registers, cache memory, computer-readable storage media, and / or combinations thereof. One or more memories 104, 204 may be located inside and / or outside one or more processors 102, 202. In addition, one or more memories 104, 204 may be connected to one or more processors 102, 202 via a variety of technologies such as wired or wireless connections.

[0494] One or more transceivers 106, 206 may send user data, control information, wireless signals / channels, etc. mentioned in the methods and / or operation flow charts, etc. of the present disclosure to one or more other devices. One or more transceivers 106, 206 may receive user data, control information, wireless signals / channels, etc. mentioned in the description, function, process, proposal, method and / or operation flow chart, etc. disclosed in the present disclosure from one or more other devices. For example, one or more transceivers 106, 206 may be connected to one or more processors 102, 202 and may send and receive wireless signals. For example, one or more processors 102, 202 may control one or more transceivers 106, 206 to send user data, control information or wireless signals to one or more other devices. In addition, one or more processors 102, 202 may control one or more transceivers 106, 206 to receive user data, control information or wireless signals from one or more other devices. In addition, one or more transceivers 106, 206 may be connected to one or more antennas 108, 208, and one or more transceivers 106, 206 may be configured to send and receive user data, control information, wireless signals / channels, etc. mentioned in the description, functions, processes, proposals, methods and / or operation flow charts disclosed in the present disclosure through one or more antennas 108, 208. In the present invention, one or more antennas may be multiple physical antennas or multiple logical antennas (e.g., antenna ports). One or more transceivers 106, 206 may convert received wireless signals / channels, etc. from RF band signals to baseband signals by using one or more processors 102, 202 to process received user data, control information, wireless signals / channels, etc. One or more transceivers 106, 206 may convert user data, control information, wireless signals / channels, etc. processed by using one or more processors 102, 202 from baseband signals to RF band signals. Therefore, one or more transceivers 106, 206 may include (analog) oscillators and / or filters.

[0495] The above-mentioned embodiments are elements and features of the present disclosure combined in a predetermined form. Unless otherwise explicitly mentioned, each element or feature should be considered optional. Each element or feature can be implemented in a form that is not combined with other elements or features. In addition, the embodiments of the present disclosure may include combined partial elements and / or features. The order of the operations described in the embodiments of the present disclosure may be changed. Some elements or features of an embodiment may be included in other embodiments, or may be replaced by corresponding elements or features of other embodiments. It is clear that an embodiment may include a combined claim without an explicit dependency in the claim, or may be included as a new claim by modification after application.

[0496] It is clear to those skilled in the art that the present disclosure can be implemented in other specific forms within the scope of the essential features of the present disclosure. Therefore, the above detailed description should not be interpreted restrictively in every aspect, but should be considered as illustrative. The scope of the present invention should be determined by the reasonable interpretation of the attached claims, and all changes within the equivalent scope of the present disclosure are included in the scope of the present invention.

[0497] The scope of the present disclosure includes software or machine executable commands (e.g., operating systems, applications, firmware, programs, etc.) that perform operations in a device or computer according to the methods of various embodiments, and non-transitory computer-readable media that store such software or commands, etc. and can be executed in a device or computer. Commands that can be used to program a processing system that performs the features described in the present disclosure can be stored in a storage medium or a computer-readable storage medium, and the features described in the present disclosure can be implemented by using a computer program product that includes such a storage medium. The storage medium may include a high-speed random access memory, such as DRAM, SRAM, DDR RAM, or other random access solid-state storage devices, but is not limited thereto, and it may include non-volatile memory, such as one or more disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state storage devices. The memory optionally includes one or more storage devices located away from the processor. The memory or alternatively, the non-volatile memory device in the memory includes a non-transitory computer-readable storage medium. The features described in this disclosure may be stored in any machine-readable medium to control the hardware of a processing system, and may be integrated into software and / or firmware that allows the processing system to interact with other mechanisms using the results from embodiments of the present disclosure. Such software or firmware may include, but is not limited to, application code, device drivers, operating systems, and execution environments / containers.

[0498] Here, the wireless communication technology implemented in the wireless devices 100 and 200 of the present disclosure may include narrowband Internet of Things for low-power communication, as well as LTE, NR and 6G. Here, for example, NB-IoT technology may be an example of LPWAN (Low Power Wide Area Network) technology, which may be implemented in standards such as LTE Cat NB1 and / or LTE Cat NB2, and is not limited to the above names. In addition or alternatively, the wireless communication technology implemented in the wireless devices 100 and 200 of the present disclosure may perform communication based on LTE-M technology. Here, in the example, LTE-M technology may be an example of LPWAN technology and may be referred to as various names such as eMTC (enhanced machine type communication). For example, LTE-M technology may be implemented in at least any one of the various standards including 1) LTE CAT 0, 2) LTE Cat M1, 3) LTE Cat M2, 4) LTE non-BL (non-bandwidth limited), 5) LTE-MTC, 6) LTE machine type communication, and / or 7) LTE M, etc., and is not limited to the above names. Additionally or alternatively, the wireless communication technology implemented in the wireless devices 100, 200 of the present disclosure may include at least any one of ZigBee, Bluetooth, and a low power wide area network (LPWAN) considering low power communication, and it is not limited to the above names. In an example, the ZigBee technology may generate a PAN (Personal Area Network) related to small / low power digital communication based on various standards such as IEEE 802.15.4, etc., and may be referred to as various names.

[0499] Industrial availability

[0500] The method proposed in the present invention is mainly described by taking the application in 3GPP LTE / LTE-A and 5G systems as an example, but can also be applied to various wireless communication systems other than 3GPP LTE / LTE-A and 5G systems.

Claims

1. A method performed by a user equipment (UE) in a wireless communication system, the method comprising: receiving configuration information related to channel state information (CSI) from a base station; calculating the CSI by deriving a channel measurement and / or an interference measurement based on one or more channel measurement resources (CMRs) and / or one or more interference measurement resources (IMRs) determined based on a CSI reference resource; as well as sending the CSI to the base station, The CSI reference resource is determined as a time slot later than a time slot in which the CSI is reported in the time domain.

2. The method according to claim 1, wherein: The CSI reference resource is based on a downlink time slot nn later than the uplink time slot n' in which the CSI is reported. CSI_ref Determined, and Among them, the n CSI_ref is determined to be greater than or equal to a minimum value of the variable (M) so that the CSI reference resource corresponds to a valid downlink time slot.

3. The method according to claim 1, wherein: The value of the variable (M) is provided by downlink control information (DCI) or the configuration information that triggers the reporting of the CSI.

4. The method according to claim 3, further comprising: The candidates of the variable (M) and the channel prediction accuracy for each time slot according to the candidates of the variable (M) are transmitted to the base station.

5. The method according to claim 2, wherein: The variable (M) determined by the UE and a channel prediction accuracy for a time slot according to the variable (M) are transmitted together with the CSI.

6. The method according to claim 2, wherein: A variable (M) for a time slot having a channel prediction accuracy exceeding a threshold determined or configured in advance by the base station is transmitted together with the CSI.

7. The method according to claim 2, further comprising: sending to the base station information about a measurement window required to achieve a channel prediction accuracy for a time slot according to a specific variable (M) above a specific level, The information about the measurement window includes the number of time slots, and the number of CMRs and / or IMRs.

8. The method according to claim 2, wherein: The CSI includes N CSIs for each of N CSI reference resources according to N variables (M) (N is a natural number).

9. The method according to claim 1, wherein: Information about the time during which the CSI is valid is transmitted together with the CSI.

10. The method according to claim 1, wherein: To calculate the CSI, channel measurements and / or interference measurements are derived based on the one or more CMRs and / or the one or more IMRs before an uplink timeslot in which the CSI is reported or before an offset from an uplink timeslot in which the CSI is reported.

11. The method according to claim 1, wherein: The number of CMRs and / or IMRs used to calculate the CSI is determined based on the measurement restriction level.

12. A user equipment (UE) operating in a wireless communication system, the UE comprising: at least one transceiver, the at least one transceiver configured to send and receive wireless signals; as well as at least one processor configured to control the at least one transceiver, Wherein, the at least one processor is configured to: receiving configuration information related to channel state information (CSI) from a base station; calculating the CSI by deriving a channel measurement and / or an interference measurement based on one or more channel measurement resources (CMRs) and / or one or more interference measurement resources (IMRs) determined based on a CSI reference resource; and sending the CSI to the base station, The CSI reference resource is determined as a time slot later than a time slot in which the CSI is reported in the time domain.

13. At least one non-transitory computer-readable medium storing at least one instruction, wherein the at least one instruction executable by at least one processor controls a user equipment (UE): receiving configuration information related to channel state information (CSI) from a base station; calculating the CSI by deriving a channel measurement and / or an interference measurement based on one or more channel measurement resources (CMRs) and / or one or more interference measurement resources (IMRs) determined based on a CSI reference resource; and sending the CSI to the base station, in, The CSI reference resource is determined as a time slot later in the time domain than a time slot in which the CSI is reported.

14. A processing device, the processing device being configured to control a user equipment (UE) in a wireless communication system, the processing device comprising: at least one processor; as well as At least one computer memory operably connected to the at least one processor and storing instructions that upon execution by the at least one processor perform operations including: receiving configuration information related to channel state information (CSI) from a base station; calculating the CSI by deriving a channel measurement and / or an interference measurement based on one or more channel measurement resources (CMRs) and / or one or more interference measurement resources (IMRs) determined based on a CSI reference resource; as well as sending the CSI to the base station, The CSI reference resource is determined as a time slot later in the time domain than a time slot in which the CSI is reported.

15. A method performed by a base station in a wireless communication system, the method comprising: Sending configuration information related to channel state information (CSI) to a user equipment (UE); as well as receiving the CSI from the UE, wherein the CSI is calculated by deriving a channel measurement and / or an interference measurement based on one or more channel measurement resources (CMRs) and / or one or more interference measurement resources (IMRs) determined based on a CSI reference resource, and The CSI reference resource is determined as a time slot later than a time slot in which the CSI is reported in the time domain.

16. A base station operating in a wireless communication system, the base station comprising: at least one transceiver, the at least one transceiver configured to send and receive wireless signals; as well as at least one processor configured to control the at least one transceiver, Wherein, the at least one processor is configured to: sending configuration information related to channel state information (CSI) to a user equipment (UE); and receiving the CSI from the UE, wherein the CSI is calculated by deriving a channel measurement and / or an interference measurement based on one or more channel measurement resources (CMRs) and / or one or more interference measurement resources (IMRs) determined based on a CSI reference resource, and The CSI reference resource is determined as a time slot later than a time slot in which the CSI is reported in the time domain.

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