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

Abstract

A method and apparatus for transmitting or 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, the configuration information including information on a plurality of CSI-RS burst modes, and each of the plurality of CSI-RS burst modes including one or more CSI-RS resources; and receiving a CSI-RS in the plurality of CSI-RS burst modes from the base station; 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 pattern for channel measurement resources and / or interference measurement resources, and deriving channel and / or interference measurements based on the pattern to calculate CSI.

[0007] In addition, an additional technical objective of the present disclosure is to provide a method and apparatus for transmitting and receiving channel state information reflecting channel / interference for multiple time instances.

[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] According to one aspect of the present disclosure, a method performed by a user equipment (UE) in a wireless communication system may include: receiving configuration information related to channel state information (CSI) from a base station, wherein the configuration information includes information about multiple CSI-RS (CSI reference signal) burst patterns, and each of the multiple CSI-RS burst patterns includes one or more CSI-RS resources; receiving CSI-RS from the multiple CSI-RS burst patterns from the base station; and sending CSI to the base station. The CSI may be calculated based on multiple time instances using channel and / or interference measurements for a CSI-RS burst pattern determined among the multiple CSI-RS burst patterns, the CSI may include an indicator indicating the determined CSI-RS burst pattern, and the multiple time instances for calculating the CSI may be determined based on the determined CSI-RS burst pattern.

[0011] According to additional aspects 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), wherein the configuration information includes information about multiple CSI-RS (CSI reference signal) burst patterns, and each of the multiple CSI-RS burst patterns includes one or more CSI-RS resources; sending CSI-RS from the multiple CSI-RS burst patterns to the UE; and receiving CSI from the UE. The CSI may be calculated based on multiple time instances using channel and / or interference measurements for a CSI-RS burst pattern determined among the multiple CSI-RS burst patterns, the CSI may include an indicator indicating the determined CSI-RS burst pattern, and multiple time instances for calculating the CSI may be determined based on the determined CSI-RS burst pattern.

[0012] Technical Effects

[0013] According to an embodiment of the present disclosure, it is possible to determine a pattern for optimal channel measurement resources and / or interference measurement resources, and derive channel and / or interference measurements based on the pattern to send and receive CSI.

[0014] In addition, according to the embodiments of the present disclosure, downlink transmission performance can be improved by calculating CSI reflecting channels for multiple time instances.

[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 PMIs for multiple time instances no earlier than CSI reference resources in a wireless communication system to which the present disclosure can be applied are illustrated.

[0034] Fig.18 The diagram illustrates PMIs for multiple time instances no later than CSI reference resources in a wireless communication system to which the present disclosure can be applied.

[0035] Fig.19 A signaling process between a network and a UE is illustrated in accordance with 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 may 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 may 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] Hereinafter, 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 a part of a base station, and the receiver may be a part of a terminal. In the uplink, the transmitter may be a part of a terminal, and the receiver may be a 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 may be fixed or mobile, and may 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 may be used for various radio access systems such as CDMA, FDMA, TDMA, OFDMA, SC-FDMA, etc. CDMA may be implemented by, for example, UTRA (Universal Terrestrial Radio Access) or CDMA2000. TDMA may be implemented by radio technologies such as GSM (Global System for Mobile Communications) / GPRS (General Packet Radio Service) / EDGE (Enhanced Data Rates for GSM Evolution). OFDMA may 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, one 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]

[0096] NR supports multiple parameter sets (or subcarrier spacing (SCS)) for supporting various 5G services. For example, when the SCS is 15kHz, it supports wide areas of traditional cellular bands; and when the SCS is 30kHz / 60kHz, it supports dense cities, lower latency and wider carrier bandwidth; and when the SCS is 60kHz or higher, it supports bandwidths exceeding 24.25GHz 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]

[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 Nsymb 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]

[0104] [Table 4]

[0105]

[0106] Figure 2 This is an example of μ=2 (SCS is 60kHz), see Table 3, 1 subframe can include 4 time slots. Figure 2 1 subframe = {1, 2, 4} shown in is an example, and the number of slots that can be included in 1 subframe is defined as 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, regarding antenna ports, antenna ports are defined so that the channel carrying symbols 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 symbols in one antenna port are carried can be inferred from the channel carrying the symbols of another antenna port, the two antenna ports can be said to be 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, l'). Here, k = 0, ..., N RB μ N sc RB -1 is the index in the frequency domain, and l'=0,...,2 μ N symb （μ） -1 refers to the symbol position in the subframe. When referencing resource elements in a slot, an index pair (k, l) is used. Here, l = 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 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 for FR1 and a subcarrier spacing of 60kHz 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 elements (k, l) is given by the following 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 numbered 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 one 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 activated BWPs, and only one BWP may be activated for one terminal. In a resource grid, each element is called a resource element (RE) and may map one 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 one wideband CC (e.g., eMBB, URLLC, Mmtc, V2X, etc.), different parameter sets (e.g., subcarrier spacing, etc.) may 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 may instruct the terminal to operate only in part of the bandwidth, rather than in the full bandwidth of the wideband CC, and for convenience, the corresponding part of the bandwidth is defined as a bandwidth part (BWP). The BWP may be configured with continuous RBs on the frequency axis and may 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, etc., some full-bandwidth middle 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] Meanwhile, when the terminal accesses the base station for the first time or has no radio resources for signal transmission, it may perform a random access (RACH) procedure on the base station (S603 to S606). For the random access procedure, the terminal may send a specific sequence as a preamble through a physical random access channel (PRACH) (S603 and S605), and may receive a response message to the preamble through a PDCCH and a corresponding PDSCH (S604 and S606). The contention-based RACH may additionally perform a contention resolution procedure.

[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) through the 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 a transport block (TB) (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 scheduling of PUSCH (e.g., PUSCH power control, etc.), and 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 one 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 PDSCH in one DL cell. Information included in DCI format 1_0 is CRC scrambled and transmitted by C-RNTI or CS-RNTI or 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., transmit / receive power of each base station, transmit power of each UE, precoder / beam of base station / UE, time / frequency resource allocation for each UE, duplex method of each base station, etc.) according to various environmental parameters (e.g., distribution / location of base stations, distribution / location / material of buildings / furniture, etc., 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 algorithms are inspired by biological nervous systems, or neural networks, and rely on multi-layer networks 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 changing data.

[0158] Building AI systems using only online learning, so that 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-directed 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. Kernels (or filters) 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), the 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 can perform 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 transformation).

[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 inference 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 transformation).

[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 may 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 drawings 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 FIG. 1 may be implemented by collaboration between two or more entities, such as the RAN, a network node, an OAM of a network operator, or a 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 (eg, a core network node, an OAM of a network operator, etc.) and the AI ​​model inference function is performed by a RAN node (eg, a base station, a TRP, a CU of a base station, 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 may 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 (eg, user equipment, UE) receives CSI-related configuration information from a base station (eg, 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 reportConfigType parameter indicating the time domain behavior and a reportQuantity parameter indicating the CSI related quantity to be reported. 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 is triggered or configuration repetition is configured. 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. Additionally, each port emulates the interference layer with (desirable channel sum) pre-coded NZP CSI-RS in 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 measurements 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] - Consider the EPRE (Energy Per Resource Element) ratio of all interfering transmission layers of the NZP CSI-RS port for interference measurement.

[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 an 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 refers to 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 (e.g., 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, regarding AP CSI reporting timing, the PUSCH symbol / slot position is dynamically indicated by DCI. In addition, the candidate slot offset is 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') is 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] Method for transmitting and receiving CSI

[0347] According to the Release-18 MIMO work item, the purpose of Type-II codebook enhancement is to help the base station better perform link-level adaptation to time-varying channels due to the high mobility of the UE.

[0348] Specifically, the enhanced type-II codebook with time-domain compression is able to provide the base station with precoding information for multiple time instances instead of a single time instance that is susceptible to channel aging, enabling the base station to track and predict the time-varying channel direction and ultimately schedule a better modulation and coding scheme (MCS) and precoder.

[0349] - Channel measurement for Type II codebook enhancement:

[0350] Because Type II codebook enhancement via time domain (TD) compression requires multi-channel measurements on the UE side, existing UEs must perform multi-channel measurements. According to the current specification, the base station is able to enable / disable time domain channel / interference measurement restrictions. When time domain channel / interference measurement restrictions are enabled (timeRestrictionForChannelMeasurements is set), the UE measures the latest CMR (channel measurement resource) / IMR (interference measurement resource) before the CSI reference resource, so a single measurement is used for channel estimation on the CSI reference resource. When time domain channel / interference measurement restrictions are disabled (timeRestrictionForChannelMeasurements is not set), the UE is able to measure multiple CMR / IMR instances before the CSI reference resource, and how these multiple measurements are used to estimate the channel in the CSI reference resource depends on the UE implementation. With this unrestricted measurement setting, the UE is already able to use multiple measurements to calculate the CSI. When codebook enhancement via TD compression is introduced in Release-18, this unrestricted measurement setting is required to allow the UE to calculate PMI for multiple time instances.

[0351] Whether multi-channel measurements can be performed depends on the periodicity of CMR / IMR and the time domain measurement restrictions as described above. For aperiodic (AP) CMR / IMR, only a single measurement can be performed because there is only one CMR / IMR instance without periodicity. On the other hand, periodic (P) / semi-persistent (SP) CMR / IMR can provide the UE with multiple opportunities for channel / interference measurements. However, because the minimum periodicity of CSI-RS resources is 4 time slots according to the current specification, it is necessary to consider whether sufficiently frequent measurement instances can be provided for high-speed UEs. If the CSI-RS resources are too sparse, PMI accuracy may deteriorate due to poor TD compression, and if the CSI-RS resources are too dense, CSI-RS overhead may increase.

[0352] - A number of time instances represented by the enhanced Type-II codebook using TD compression are as follows:

[0353] Similar to the legacy Type-II codebook using frequency domain (FD) compression that represents PMI for multiple subbands, the new Type-II codebook using TD compression represents PMI for multiple time instances, so a method for determining these multiple time instances should be discussed. The legacy CSI including PMI / RI / CQI represents a channel for a single time point, called a CSI reference resource. However, the Type-II codebook applying TD compression should be able to provide PMI not only in the CSI reference resource, but also in other time slots / symbols. Basically, these time instances can be defined as after (i.e., in the future) the CSI reference resource (in Fig.17 ) or before (i.e., past) the CSI reference resource (in Fig.18 This may have different impacts on UE implementations.

[0354] The CSI reference resource may mean a frequency and time unit (ie, resource) to which the UE assumes that the PDSCH is allocated / transmitted when calculating / deriving the CSI, and may be defined as follows:

[0355] The CSI reference resources for the serving cell are defined as follows:

[0356] - In the frequency domain, the CSI reference resources are defined as a set of downlink physical resource blocks (PRBs) corresponding to the frequency band to which the derived CSI is related.

[0357] - In the frequency domain, the CSI reference resources used for CSI reporting in uplink time slot n' consist of a single downlink time slot Definition. Here, K offset is a parameter configured by higher layers, as specified in Section 4.2 of TS 38.213. And, μ Koffset Is used for K offset The subcarrier spacing (SCS) configuration of the frame. For FR 1, its value is 0.

[0358] here, , μ DL and μ UL are the SCS configurations for DL ​​and UL respectively. slot, offset CA and μ offset Determined by the ca-SlotOffset configured by higher layers for the cell transmitting uplink and downlink, as defined in section 4.5 of TS 38.211.

[0359] 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 μDLThe minimum value of n such that the CSI reference resource corresponds to a valid downlink time slot, or 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 makes the CSI reference resource correspond to a valid downlink time slot.

[0360] In addition, here, for aperiodic CSI reporting, if the DCI instructs the UE to report CSI in the same time slot as the CSI request, n is determined. CSI-ref , so that the CSI reference resource and the 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 effective downlink time slot, where Z' corresponds to the delay requirement as defined in section 5.4 of TS 38.214.

[0361] Fig.17 PMIs for multiple time instances no earlier than CSI reference resources in a wireless communication system to which the present disclosure can be applied are illustrated.

[0362] refer to Fig.17 , UE calculates the existing PMI based on the DL channel of the CSI reference resource ref_rsc , which can be derived from the periodic CMR no later than the CSI reference resource. In addition, the UE calculates the PMI based on the DL channel of the CSI reference resource + τ slots and the CSI reference resource + 2τ slots respectively. ref_rsc+τ and PMI ref_rsc+2τ , which is predicted from the periodic CMR no later than the CSI reference resource. Finally, the PMI is quantized using an enhanced type II codebook with TD compression. ref_rsc 、PMI ref_rsc+τ and PMI ref_rsc+2τ Compression is performed to reduce PMI feedback overhead. Because this codebook includes the future PMIs required for the UE to predict the DL channel following the CSI reference resource, it is robust to channel aging and can be used by the base station to achieve better link adaptation.

[0363] Fig.18 The diagram illustrates PMIs for multiple time instances no later than CSI reference resources in a wireless communication system to which the present disclosure can be applied.

[0364] refer to Fig.18 UE is the same as above Fig.17 The legacy PMI is calculated in the same way as described in ref_rsc However, with Fig.17Different, UE calculates PMI based on DL channels in CSI reference resource - τ time slot and CSI reference resource - 2τ time slot ref_rsc-τ and PMIref_rsc-2τ , which are periodic CMRs that are no later than the reference resource. Figure 2 An example of periodic CMR in CSI reference resource, CSI reference resource - τ slot and CSI reference resource - 2τ slot is shown. Finally, the enhanced type II codebook with TD compression is used to quantize the PMI ref_rsc 、PMI ref_rsc-τ and PMI ref_rsc-2τ Compression is performed to reduce PMI feedback overhead. Since the secondary codebook includes past PMIs, the UE does not need to predict additional DL channels and is faster than Fig.17 Less complexity. However, there is PMI ref_rsc-τ and PMI ref_rsc-2τ Compared with the existing PMI ref_rsc Older problem.

[0365] A time instance may refer to a point in time (eg, a time slot) at which the PMI is calculated. Fig.17 In , the time instance represents CSI reference resource (time slot), CSI reference resource + τ time slot and CSI reference resource + 2τ time slot. Fig.18 In , the time instance represents CSI reference resource (time slot), CSI reference resource - τ time slot and CSI reference resource - 2τ time slot.

[0366] In order to determine Fig.17 and Fig.18 The base station may perform the following signaling to the UE for the time instance of the channel expressed by the PMI shown in. For example, it may be indicated as a parameter of the RRC signaling for codebook configuration.

[0367] For example, first, it can be indicated / signaled how many time instances are to be expressed as PMI. Fig.17 and 18 In the example of , the number of time instances is illustrated as 3, but the present disclosure is not limited thereto. Taking into account the time variability of the channel, the number of time instances can be configured in various ways, and for such a configuration, the UE can report its speed information, Doppler information (Doppler shift / spread), etc. to the base station. Alternatively, the UE can report its preferred number of time instances from its speed or Doppler information, etc. to the base station, and the base station can confirm or make a final selection (e.g., select a different number of time instances). For example, the UE can report candidate values ​​for the number of time instances as a capability to the base station.

[0368] In addition, for example, it is possible to indicate / signal the intervals between time instances, which indicates that Fig.17 and18 τ value expressed in . The τ value can be configured in various ways considering the time variability of the channel, and for such configuration, the UE can report its speed information, Doppler information (Doppler shift / spread), etc. to the base station. Alternatively, the UE can report its preferred τ value from its speed or Doppler information, etc. to the base station, and the base station can confirm or make a final selection (e.g., determine a different τ value). For example, the τ value can be expressed in absolute time (e.g., ms, etc.), time slot, OFDM symbol, etc. The UE can report candidate values ​​for the τ value to the base station as a capability.

[0369] In addition, for example, it can be indicated / signaled in which time slot / symbol the time instance is located. For example, a time instance offset can be signaled, and the time instance offset can be determined based on the CSI reference resource. In other words, it can be indicated / signaled which time instance among the configured time instances the CSI reference resource corresponds to. Fig.17 In , the CSI reference resource is configured to the first time instance among the three time instances, and the base station can configure / indicate that the time instance offset of the CSI reference resource is 0 to indicate this. Because the CSI reference resource is configured to the first time instance, the remaining time instances after the first time instance are configured after the CSI reference resource. Fig.18 , the CSI reference resource is configured to the last (third) time instance among the three time instances, and the base station can configure / indicate the time instance offset of the CSI reference resource to be 2 to indicate this. Because the CSI reference resource is configured to the third time instance, the remaining time instances before the third time instance are configured before the CSI reference resource. Taking into account the time variation of the channel, the time instance offset can be configured in various ways, and for such configuration, the UE can report its speed information, Doppler information (Doppler shift / spread), etc. to the base station. Alternatively, the UE can report its preferred time instance offset from its speed or Doppler information, etc. to the base station, and the base station can confirm or make a final selection (e.g., determine different time instance offset values). In addition, depending on the implementation of the UE, the UE can be divided into a UE that can only configure the time instance offset (i.e., CSI reference resource) to the last time instance, as in Fig.18 , and UEs capable of configuring time instance offsets (i.e., CSI reference resources) to other time instances than the last time instance, such as in Fig.17 and the UE can report this as a capability to the base station. Fig.18 ) is simpler to implement because the UE does not need to perform channel prediction, but the latter (in Fig.17 More specifically, in the latter case (in Fig.17 In the case of ), the UE can additionally report to the base station the minimum value of the configurable time instance offset or candidate values ​​of the configurable time instance offset. The smaller the minimum value, the more predictions need to be performed, so the UE implementation may be complex.

[0370] In the above proposals, the grid of time instances is configured by the number and interval (ie, τ value) of time instances, and the time slot / symbol at which the grid of time instances is located can be determined by the time instance offset for the CSI reference resource.

[0371] In a similar but different expression, the grid of time instances can be determined by configuring a window of time instances as time slots / symbols and configuring the number of time instances within the window. That is, the time instances can be configured to be equally spaced as the number of time instances within the window. For example, if the window (which can be called a CSI reporting window) is configured as 3 time slots and the number of time instances is configured as 3, the grid of time instances is expressed as 3 consecutive time slots. Here, if the time instance offset is 0, the last time instance is configured as a CSI reference resource slot, a CSI reference resource + 1 slot, and a CSI reference resource + 2 slot.

[0372] In the above example, the time instances are configured to be equally spaced from each other. However, if the channel time variability changes over time and is predictable, this uniformly spaced distribution may be inefficient. For example, when N time instances are configured, if the channel time variability is severe in the front part of the entire time interval represented by the PMI and the channel time variability is small in the back part, then arranging the time instances densely in the front part and sparsely in the back part can increase the compression efficiency and accuracy for TD compression. For example, if the CSI reference resource is located at the first time instance, the second time instance can be located at the CSI reference resource + 1 time slot, the third time instance can be located at the CSI reference resource + 2 time slot, and the fourth time instance can be located at the CSI reference resource + 5 time slot. Therefore, the intervals between the time instances may not be equally spaced, and for this reason, the UE can report the time instance position to the base station (together with the CSI). Alternatively, the base station can indicate / configure the time instance position to the UE. For example, triggering an AP CSI report can be indicated in the UL DCI.

[0373] Some parameters related to the proposed time instance configuration are fixed (have predefined values) and the rest can be configured by the base station or reported by the UE.

[0374] In the above proposal, the time instance offset is described based on the CSI reference resource, but this is only an example and the present disclosure is not limited thereto. For example, the time instance offset can be configured based on the CSI reporting time (i.e., the time when the CSI is reported / sent) or the last time point of the CSI measurement window. Here, the CSI measurement window means a time interval in which the channel / interference can be measured for CSI calculation. For example, the offset (e.g., the number of time slots) between the first time instance among the time instances of the CSI reporting time or the last time point of the CSI measurement window can be configured as the time instance offset.

[0375] In the above proposal, the time instance offset can be configured as a negative value, or a value greater than or equal to the number of time instances (or the number of time instances * the interval between time instances). For example, when the time instance offset is configured based on the CSI reference resource, if the time instance offset is negative, the time instance can only exist in the future after the CSI reference resource. For example, when the number of time instances is 3, the interval between time instances is 1 time slot, and the time instance offset configured based on the CSI reference resource is -1, the time instance can be configured as CSI reference resource + 1 time slot, CSI reference resource + 2 time slot, CSI reference resource + 3 time slot.

[0376] On the other hand, if it is configured as a value greater than the number of time instances (or the number of time instances * the interval between time instances), the time instance can only exist in the past before the CSI reference resource. For example, when the number of time instances is 3, the interval between time instances is 1 time slot, and the time instance offset set based on the CSI reference resource is 4, the time instances can be configured as CSI reference resource-3 time slot, CSI reference resource-2 time slot, and CSI reference resource-1 time slot.

[0377] The range of values ​​that can be configured as this time instance offset can be reported by the UE to the base station (as a capability), and in this case the base station can indicate / configure a time instance offset value within this range.

[0378] When the base station indicates the parameter / configuration value related to the proposed method to the UE, in the case of AP CSI reporting, it can be indicated together through the AP CSI report trigger field of the DCI. Alternatively, it can be indicated through configuration information related to CSI reporting (e.g., CSI-ReportConfig IE) or in configuration information related to the PMI codebook.

[0379] In addition, the UE may report (as a capability) to the base station a maximum value for the number of time instances and / or the time instance interval. Because the number of time instances and / or the time instance interval may increase as the UE requires more calculations for CSI calculation, the UE may report the maximum value to the base station, and the base station may configure the number of time instances and / or the time instance interval to the UE within the range not exceeding the maximum value. Alternatively, the UE may report (as a capability) a combination of the number and interval of time instances to the base station. For example, when the number of time instances is N1, the UE may report the maximum interval time slot to the base station, and when the number of time instances is N2, the UE may report the maximum interval time slot to the base station. In other words, the UE may report to the base station the maximum time instance interval that can be supported by the number of each time instance. Alternatively, the UE may report to the base station the maximum number of time instances that can be supported by each time instance interval. As the number of time instances increases, the maximum interval supported by the UE may decrease, so this reporting method may be effective.

[0380] By replacing the interval of the time instance with the window of the time instance, this reporting method can be applied even when the window of the time instance is used instead of the interval of the time instance. That is, the UE can report to the base station the maximum window of the time instance that can be supported for each number of time instances. Alternatively, the UE can report to the base station the maximum number of time instances that can be supported by the window for each time instance.

[0381] The time instance for deriving CSI (or PMI) can be finally applied / determined by a combination / combination of the above proposals.

[0382] As mentioned above, in order for the UE to predict and report PMI for multiple time instances, the UE needs to measure the channel at a narrower time interval than the existing CMR (channel measurement resource) / IMR (interference measurement resource). To this end, the standardization meeting is discussing two alternatives (alt) on how to set burst CSI-RS (or burst channel measurement (or burst CMR) or burst interference measurement (or burst IMR)) that can measure the same channel / interference at shorter time intervals.

[0383] When describing the present disclosure, for convenience of explanation, the multiple time instances related to the above-mentioned CSI report are referred to as CSI reporting windows, but the present disclosure is not limited thereto.

[0384] In addition, in the present disclosure, a burst CSI-RS (or burst CSI-RS resource, CSI-RS burst, CSI-RS resource burst) may mean a set / a group of CSI-RS resources used for measurement to report CSI for multiple time instances.

[0385] Alt 1: Method for configuring a single CSI-RS resource at narrow time intervals

[0386] Alt 2: A method for configuring K (K>1) CSI-RS resources at a narrow time interval, and for a UE to measure the same channel (or the same interference) through the K CSI-RS resources (i.e., the UE assumes that a port (port i) of each CSI-RS resource constituting the K CSI-RS resources is the same port and measures the channel / interference).

[0387] Hereinafter, in the description of the present disclosure, for convenience of explanation, the description is mainly based on Alt 2, but the present invention is not limited thereto, and the proposed method can also be applied to Alt 1.

[0388] Basic CSI reporting is configured in the following manner.

[0389] M NZP CSI-RS resources are configured by the configuration information of the NZP CSI-RS resource set (e.g., NZP-CSI-RS-ResourceSet) in the configuration information (e.g., nzp-CSI-RS-ResourceSetList) in the configuration information (e.g., CSI-ResourceConfig) for CSI resources configured in the configuration information for CSI reporting (e.g., CSI-ReportConfig) (only when it is more than 1 set for AP CSI-RS). Here, for Release-17 MTRP CSI, M=M1+M2, the first M1 CSI-RS resources are configured as group 1, the remaining CSI-RS resources are configured as group 2, and one CSI-RS resource of group 1 and one CSI-RS resource of group 2 are connected as a configured pair, and up to 2 pairs can be configured in total.

[0390] In other words, a specific CSI report is configured with configuration information for a CSI report (e.g., CSI-ReportConfig), and a CMR (channel measurement resource) and an IMR (interference measurement resource) are respectively configured with configuration information for CSI resources (e.g., CSI-ResourceConfig). The configuration information for CSI resources (e.g., CSI-ResourceConfig) includes configuration information for an NZP CSI-RS resource set list (e.g., nzp-CSI-RS-ResourceSetList), the configuration information for an NZP CSI-RS resource set list (e.g., nzp-CSI-RS-ResourceSetList) includes configuration information for one or more NZP CSI-RS resource sets (e.g., NZP-CSI-RS-ResourceSet), and the configuration information for an NZP CSI-RS resource set (e.g., NZP-CSI-RS-ResourceSet) includes M NZP CSI-RS resources.

[0391] When Alt 1 is supported, each CSI-RS resource has (or forms) a burst CSI-RS pattern that appears multiple times in a narrow time interval, and each CSI-RS resource can have (or form) a different burst CSI-RS pattern. For example, CSI-RS resource 1 can be configured with a burst CSI-RS pattern with a 1-slot interval, and CSI-RS resource 2 can be configured with a burst CSI-RS pattern with a 2-slot interval. In this case, the UE can select a specific CSI-RS resource through a CSI-RS resource indicator (CRI).

[0392] On the other hand, if Alt 2 is supported, NZP-CSI-RS-ResourceSet consists of K (K is a natural number) CSI-RS resources, and multiple such CSI-RS resource sets can be configured through nzp-CSI-RS-ResourceSetList. Here, the value of K can be different for each CSI-RS resource set. That is, CSI-RS resource set i can be configured with K iCSI-RS resources, and the CSI-RS resources constituting each CSI-RS resource set can be interpreted as a burst CSI-RS. In this case, the UE can select one (or more) NZP-CSI-RS-ResourceSet from the CSI-RS resource sets in the nzp-CSI-RS-ResourceSetList and report it through CRI or a new CSI report quantity similar to CRI. That is, the UE can select one or more CSI-RS resource sets from the CSI-RS resource sets and report them to the base station.

[0393] Alternatively, only one CSI-RS resource set may be configured, and for the M CSI-RS resources configured in one CSI-RS resource set, multiple CSI-RS resource groups may be configured, each CSI-RS resource group consisting of K i CSI-RS resources. That is, group i consists of K i CSI-RS resources, and the CSI-RS resources configured in each group can be interpreted as a burst CSIRS. In this case, the UE can select one (or more) CSI-RS resource groups by CRI or a new CSI report number similar to CRI, and report it to the base station. That is, the UE can select one or more CSI-RS resource groups among the CSI-RS resource groups in the CSI-RS resource set and report it to the base station.

[0394] As described above, if Alt 1 or Alt 2 is supported, the UE can select one of several burst measurement modes via CRI (or a newly defined CSI report number to select a burst CSI-RS). For example, the following can be considered.

[0395] Example 1)

[0396] - Burst mode 1 (ie, CSIRS resource 1 or NZP-CSI-RS-ResourceSet 1 or CSI-RS resource group 1): CSI-RS is configured as 4 measurement opportunities at 1 slot interval.

[0397] - Burst mode 2 (ie, CSIRS resource 2 or NZP-CSI-RS-ResourceSet 2 or CSI-RS resource group 2): CSI-RS measurement opportunities are set 8 times at 2 slot intervals.

[0398] In Example 1, in burst mode 1, for 4 time slots, CSI-RS resources are configured in each time slot, and in burst mode 2, for 16 time slots, CSI-RS resources are configured in 2 time slot intervals. That is, mode 2 can perform channel / interference measurements at a higher frequency and for a longer period of time than mode 1. Therefore, when mode 2 is used, the channel for a future time point can be predicted more accurately. Therefore, the CSI reporting window can change depending on which burst mode the UE selects as the CRI (or the number of reports used to indicate the selected burst mode). Here, the CSI reporting window can mean a time instance of a channel expressed by PMI / CQI, and can include the interval between time instances or the number of time instances.

[0399] For example, if burst mode 1 is selected by the UE, the UE is able to generate / report PMI by configuring the CSI reporting window as {number of time instances = 2, time instance interval (duration) = 1 time slot, time instance offset = 1 time slot}. If burst mode 2 is selected by the UE, the UE is able to generate / report PMI by configuring the CSI reporting window as {number of time instances = 4, time instance interval = 1 time slot, time instance offset = 2 time slots}. As a specific case, when the number of time instances is 2 (i.e., for burst mode 1), the PMI overhead reduction effect due to time domain (TD) / Doppler domain (DD) compression is not significant, so PMI can be reported without TD / DD compression, and the PMI value related to the spatial domain (SD) / frequency domain (FD) / TD / DD basis selection is reported only once and is generally applied to multiple time instances, and the coefficients (i.e., W2) applied to the linear combination between the bases can be reported independently for each time instance.

[0400] The interval between time instances can be configured by the base station to the UE as one of the codebook parameters in time units, or the UE can report it to the base station. For example, the interval between time instances can be configured as n time slots or n symbols. And the number of time instances can be equal to the DD / TD basis vector length (=N4) selected to perform DD or TD compression.

[0401] Example 2)

[0402] - Burst mode 1 (ie, CSIRS resource 1 or NZP-CSI-RS-ResourceSet 1 or CSI-RS resource group 1): CSI-RS is configured as 4 measurement opportunities at 1 slot interval.

[0403] - Burst mode 2 (ie, CSIRS resource 2 or NZP-CSI-RS-ResourceSet 2 or CSI-RS resource set 2): Same as the existing CSI-RS configuration, however, 1 measurement opportunity is configured. That is, it is not actually a burst mode.

[0404] In Example 2, if burst mode 2 is selected, the UE reports PMI / CQI for a single time instance to the base station using the existing Release-17 Type II codebook. For example, if the UE performs CSI prediction using burst mode 1 but determines that the prediction accuracy is low (e.g., if the accuracy drops below a threshold configured by the base station or determined in advance), the UE may select burst mode 2 using the CRI (or the number of reports indicating the selected burst mode) to fall back to the existing operation of reporting the existing CSI without prediction. Here, the CSI-RS for burst mode 2 may be configured as a subset of the CSI-RS for burst mode 1.

[0405] For example, burst mode 2 may be configured with 1 CSI-RS resource (e.g., ID=0), and burst mode 1 may be configured with 4 CSIRS resources (e.g., ID=0, 1, 2, 3, respectively). In this case, if the UE performs channel measurement and calculates CSI through burst mode 1, it is not sufficient to perform additional channel measurement or calculate additional CSI for burst mode 2. Therefore, a CSI processing unit (CPU) for burst mode 2 may not be additionally (i.e., separately) allocated.

[0406] The above proposal assumes the case where multiple burst CSI-RS patterns for CMR / IMR are configured for one CSI report, and whether to configure a CSI reporting window or whether to perform prediction depends on which pattern the UE selects using CRI (or the number of reports for indicating the selected burst mode). In order to prevent the CSI reporting window configuration and whether to perform prediction from being changed depending on CRI (or the number of reports for indicating the selected burst mode), when the base station configures multiple burst CSI-RSs, the UE may not expect the base station to configure the number of measurement opportunities, the time interval between occasions, or the measurement window differently for each burst CSI-RS.

[0407] When the burst mode selected by CRI (or the number of reports indicating the selected burst mode) is changed, the Z value (i.e., the minimum time from the DCI trigger time to the CSI reporting time in the non-periodic report, i.e., the minimum guaranteed time for CSI calculation) and Z' (the minimum time from the last symbol of the CMR / IMR to the CSI reporting time in the non-periodic report) value for the corresponding CSI report may be changed depending on the CRI (or the number of reports indicating the selected burst mode) value (i.e., depending on the selected burst mode). For example, when burst mode 2 is selected in the above-mentioned example 1, because the measurement window is long, it may take more time to perform channel measurement, and it may also take more time to infer measurement to perform channel prediction, and therefore, the Z and Z' values ​​may be set larger than those of burst mode 1.

[0408] As described above, if the Z value and / or Z' value is changed according to the CRI (or the number of reports used to indicate the selected burst mode) value (i.e., according to the selected burst mode), there will be a problem that the base station cannot know the Z, Z' values ​​before receiving the CSI report from the UE.

[0409] Therefore, in order to solve this problem, the maximum value among the Z values ​​calculated based on each burst mode can be determined as the final Z value for the corresponding CSI report.

[0410] In addition, a maximum value among Z' values ​​calculated based on each burst mode can be determined as a final Z' value for a corresponding CSI report.

[0411] In addition, the maximum number of CPUs calculated based on each burst mode can be determined as the final occupied (or used) number of CPUs for the corresponding CSI report.

[0412] Reporting CSI for multiple time instances can be performed by configuring one CMR for CSI calculation to be continuously burst in a short time interval (e.g., each time slot or each symbol), configuring a codebook that uses TD / DD compression for PMI reporting, configuring one W1 and multiple W2s corresponding to different time instances for PMI reporting, or configuring multiple time instances / multiple CSI reference resources.

[0413] Additionally, the operation of reporting CSI for multiple time instances according to the present disclosure can be ultimately applied through a combination / combination of the above-mentioned proposals.

[0414] For convenience of explanation, the above proposal is explained based on configuring the burst mode for CMR, but the burst mode can also be configured for IMR, and the proposed method can also be applied in this case.

[0415] For convenience of explanation, the above proposal is explained as an example of a codebook to which TD compression using a TD basis is applied, but the proposed method can be extended and applied to a codebook to which DD compression using a DD basis is applied.

[0416] The above proposal can also be applied when the AI / ML UE predicts future CSI (eg, CSI for a channel after a CSI reporting time) and reports it to the base station.

[0417] The parameters in the above proposal, whether to apply the proposal, etc. can be indicated by the base station to the UE (for example, RRC signaling), reported by the UE to the base station, or configured as fixed values.

[0418] Fig.19 A signaling process between a network and a UE is illustrated in accordance with a method for transmitting and receiving channel state information according to an embodiment of the present disclosure.

[0419] Fig.19 The signaling between the network (eg, TRP 1, TRP 2) and the UE used for the method proposed in the present disclosure is illustrated. Here, UE / network is only an example and can be replaced with various devices. Fig.19 This is only for the convenience of explanation and does not limit the scope of the present disclosure. Fig.19 Some of the steps illustrated in the figure may be omitted depending on the situation and / or setting, etc.

[0420] Fig.19 The signaling scheme described in the specification 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 established between TRP 1 and TRP 2 constituting the network. In addition, although the following description is based on multiple TRPs, it can be similarly 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 UE (via / using TRP1 / 2) receiving a signal from the network (or can be the operation of UE (via / using TRP1 / 2) receiving a signal from the network), and the operation of the terminal sending a signal to TRP1 / TRP2 can also be interpreted / described as UE (via / using TRP1 / TRP2) sending a signal to the network (or can be the operation of UE (via / using TRP1 / TRP2) sending a signal to the network), and vice versa.

[0421] 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 / pico cell, etc.), a TP (transmission point), a base station (gNB, etc.). As described above, a TRP may be distinguished according to information (e.g., an index, an ID) about a CORESET group (or a CORESET pool). For example, if a UE is configured to transmit and receive using multiple TRPs (or cells), this may mean configuring multiple CORESET groups (or CORESET pools) for the UE. Configuration of such a CORESET group (or CORESET pool) may be performed via higher layer signaling (e.g., RRC signaling, etc.).

[0422] The UE receives configuration information from the network ( S1901 ).

[0423] The configuration information may include information related to the configuration of the network (e.g., TRP configuration) / information related to transmission and reception based on M-TRP (e.g., resource allocation, etc.). At this time, the configuration information may be sent via higher layer signaling (e.g., RRC signaling, MAC-CE, etc.).

[0424] The configuration information may include configuration information related to the CSI described in the above proposed method.

[0425] The CSI-related configuration information may include at least one of CSI-IM (interference management) resource related information, CSI measurement configuration related information, CSI resource configuration related information, or CSI report configuration related information.

[0426] 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, first configuration information) and configuration information related to CSI resources (i.e., CSI resource configuration) (e.g., RRC IE "CSI-ResourceConfig") (hereinafter, second configuration information).

[0427] Here, multiple CSI-RS resources for CSI calculation / measurement may be configured for the UE through configuration information related to CSI resources (i.e., CSI resource configuration). 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) may 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 (or CSI-RS resources).

[0428] In addition, configuration information related to CSI resources (or CSI-RS resources) (i.e., CSI resource settings) can be connected / associated with specific configuration information related to CSI reporting (i.e., CSI report settings), and based on the report quantity (reportQuantity) in the CSI report setting, the UE can be configured with CSI reports (e.g., CRI, PMI, RI, CQI, LI, etc.) for multiple CSI resources configured for the connected / associated CSI resource setting.

[0429] In addition, the CSI-related configuration information may include information about a plurality of CSI-RS burst patterns, and each of the plurality of CSI-RS burst patterns may include one or more CSI-RS resources.

[0430] Here, the CSI-RS burst pattern corresponds to one (periodic) CSI-RS resource, and multiple CSI-RS burst patterns may correspond to multiple CSI-RS resources with different patterns. In such a case, the UE may report to the base station using the CRI indicating the specific CSI-RS resource to report the determined / selected (one or more) CSI-RS burst pattern to the base station.

[0431] In addition, the CSI-RS burst mode corresponds to a CSI-RS resource set including M (M is a natural number) CSI-RS resources, and multiple CSI-RS burst modes may correspond to multiple CSI-RS resource sets with different modes. In such a case, the UE may report to the base station using information / indicator indicating a specific CSI-RS resource set, so as to report the determined / selected (one or more) CSI-RS burst mode to the base station.

[0432] In addition, the CSI-RS burst mode corresponds to a CSI-RS resource group including K (K is a natural number) CSI-RS resources in a CSI-RS resource set, and multiple CSI-RS burst modes may correspond to multiple CSI-RS resource groups with different modes. In this case, the UE may report to the base station using information / indicator indicating a specific CSI-RS resource group, so as to report the determined / selected (one or more) CSI-RS burst modes to the base station.

[0433] The UE receives CSI-RS from a plurality of CSI resources configured by configuration information from a network ( S1902 ).

[0434] Here, the UE can receive CSI-RS in a plurality of CSI-RS burst patterns configured by the configuration information.

[0435] As described above, if one CSI-RS resource set corresponds to one CSI-RS burst mode, the UE can assume that all M CSI-RS resources included in the CSI-RS resource set are the same antenna port. Similarly, if one CSI-RS resource group corresponds to one CSI-RS burst mode, the UE can assume that all K CSI-RS resources included in the CSI-RS resource group are the same antenna port.

[0436] The UE can receive downlink control information (DCI) from the network ( S1903 ).

[0437] 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.

[0438] In addition, DCI may be transmitted via a downlink control channel (eg, PDCCH, etc.), and in addition to triggering / activating CSI reporting, may also schedule a downlink data channel (eg, PDSCH) / uplink data channel (eg, PUSCH).

[0439] The UE transmits (reports) the CSI to the network ( S1904 ).

[0440] Here, the CSI may include at least one of CQI, PMI, RI, CRI, and LI.

[0441] As described above, the UE can report CSI to the network based on the configuration information related to CSI reporting (and when triggered / activated by DCI). For example, the configuration information related to CSI reporting can configure the CSI reporting type, such as periodic CSI reporting, semi-persistent CSI reporting, and aperiodic CSI reporting, and it can configure which information should be reported in the CSI (e.g., CRI, CQI, PMI, RI, LI, etc.). In addition, in the case of periodic CSI reporting, the periodicity and time slot offset, etc. can also be configured.

[0442] According to the method proposed above, it is possible to calculate / derive CSI based on multiple time instances using channel and / or interference measurements for a CSI-RS burst mode determined from among multiple CSI-RS burst modes. In other words, the UE can perform channel and / or interference measurements based on the CSI-RS resources in the determined CSI-RS burst mode, and calculate or predict CSI based on each of the multiple time instances using channel and / or interference measurements. Here, for example, in the case of PMI, the value calculated / predicted in each time instance can be TD compressed and included in the CSI. In addition, in the case of CQI, it can be included in the CSI as one value (e.g., a value calculated / predicted from a CSI reference resource) or two values ​​for multiple time instances. In addition, in the case of RI, it can be included in the CSI as a common value for multiple time instances.

[0443] In addition, the CSI may include information / indicator indicating the determined CSI-RS burst pattern. If multiple CSI-RS burst patterns correspond to multiple CSI-RS resources with different patterns, the UE may use the CRI indicating the specific CSI-RS resource to report the determined / selected (one or more) CSI-RS burst patterns to the base station. In addition, if multiple CSI-RS burst patterns correspond to multiple CSI-RS resource sets with different patterns or multiple CSI-RS resource groups with different patterns, the UE may use information / indicator to indicate a specific CSI-RS resource set or a specific CSI-RS resource group to report the determined / selected (one or more) CSI-RS burst patterns to the base station.

[0444] In addition, multiple time instances (i.e., CSI reporting windows) used to calculate CSI can be determined based on the determined CSI-RS burst mode. Here, multiple time instances can be configured with the number of time instances, the intervals between time instances, and the time instance offset. In addition, multiple time instances can be configured by the base station or selected by the UE for at least one of the number of time instances, the intervals between time instances, and the time instance offset. Here, when configured by the base station, multiple time instances can be reported to the base station as a capability of the UE for at least one of the number of time instances, the intervals between time instances, and the time instance offset as a preference value. In addition, the time instance offset can be configured based on the CSI reference resource, the last time point of the determined CSI-RS burst mode, or the reporting time point of the CSI.

[0445] In addition, a minimum CSI processing time (Z) from receiving CSI triggering downlink control information (DCI) for reporting CSI to reporting CSI may be determined as a maximum value among Z values ​​for each of a plurality of CSI-RS burst patterns.

[0446] Additionally, a minimum CSI processing time (Z') from receiving a CSI-RS for channel and / or interference measurement for reporting CSI to reporting CSI may be determined as a maximum value among Z' values ​​for each of a plurality of CSI-RS burst patterns.

[0447] In addition, the number of CSI processing units (CPUs) occupied for reporting CSI may be determined as a maximum value among the numbers of CPUs for each of a plurality of CSI-RS burst patterns.

[0448] In addition, a subset of a CSI-RS burst pattern among multiple CSI-RS burst patterns may correspond to another CSI-RS burst pattern. For example, if the multiple CSI-RS burst patterns include a first CSI-RS burst pattern and a second CSI-RS burst pattern, and the first CSI-RS burst pattern includes the second CSI-RS burst pattern, a CPU may not be allocated to the second CSI-RS burst pattern.

[0449] Meanwhile, the above-mentioned operation of calculating CSI (ie, 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 on the UE or connected to the UE), and is used for the above-mentioned Fig.12 At least one function of the AI / ML operation (especially model inference) to calculate CSI (or channel prediction accuracy) can be performed by the UE (or an external device installed on or connected to the UE). In addition, the UE (or an external device installed on or connected to the UE) can be performed by the above Fig.16The process (particularly 5. Model inference) is used to determine multiple time instances (ie, CSI reporting windows) (eg, the number of time instances, the intervals between time instances, and the time instance offsets) expressed by the CSI in the determined CSI-RS burst pattern.

[0450] 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.

[0451] refer to Fig. 20 , Fig. 20 The operation of the UE based on the method proposed in the present disclosure is illustrated. Fig. 20 The examples are for convenience of explanation and do not limit the scope of the present disclosure. Fig. 20 Some of the steps illustrated in the figure may be omitted depending on the situation and / or setting. Fig. 20 The UE in the example is only an example and can be implemented as follows Fig. 22 For example, Fig. 22 The processor (102 / 202) can control to send and receive channels / signals / data / information, etc. using the transceiver (106 / 206), and can also control to store the sent or received channels / signals / data / information, etc. in the memory (104 / 204).

[0452] 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 command / program (eg, instructions, executable code) of at least one processor (eg, 102, 202) is stored in a memory (eg, Fig. 22 in one or more memories (104, 204).

[0453] The UE receives configuration information related to channel state information (CSI) from a base station ( S2001 ).

[0454] The CSI-related configuration information may include the CSI-related configuration information described in the above-proposed method.

[0455] The CSI-related configuration information may include at least one of CSI-IM (interference management) resource related information, CSI measurement configuration related information, CSI resource configuration related information, or CSI report configuration related information.

[0456] 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, first configuration information) and configuration information related to CSI resources (i.e., CSI resource configuration) (e.g., RRC IE "CSI-ResourceConfig") (hereinafter, second configuration information).

[0457] Here, multiple CSI-RS resources for CSI calculation / measurement may be configured for the UE through configuration information related to CSI resources (i.e., CSI resource configuration). 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) may 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 (or CSI-RS resources).

[0458] In addition, the configuration information related to the CSI resource (or CSI-RS resource) (i.e., CSI resource setting) can be connected / associated with the specific configuration information related to the CSI report (i.e., CSI report setting), and according to the report quantity (reportQuantity) in the CSI report setting, the UE can be configured with CSI reports (e.g., CRI, PMI, RI, CQI, LI, etc.) for multiple CSI resources configured for the connected / associated CSI resource setting.

[0459] In addition, the CSI-related configuration information may include information about a plurality of CSI-RS burst patterns, and each of the plurality of CSI-RS burst patterns may include one or more CSI-RS resources.

[0460] Here, the CSI-RS burst pattern corresponds to one (periodic) CSI-RS resource, and multiple CSI-RS burst patterns may correspond to multiple CSI-RS resources with different patterns. In such a case, the UE may report to the base station using the CRI indicating the specific CSI-RS resource to report the determined / selected (one or more) CSI-RS burst pattern to the base station.

[0461] In addition, the CSI-RS burst mode corresponds to a CSI-RS resource set including M (M is a natural number) CSI-RS resources, and multiple CSI-RS burst modes may correspond to multiple CSI-RS resource sets with different modes. In such a case, the UE may report to the base station using information / indicator indicating a specific CSI-RS resource set, so as to report the determined / selected (one or more) CSI-RS burst mode to the base station.

[0462] In addition, the CSI-RS burst mode corresponds to a CSI-RS resource group including K (K is a natural number) CSI-RS resources in a CSI-RS resource set, and multiple CSI-RS burst modes may correspond to multiple CSI-RS resource groups with different modes. In this case, the UE may report to the base station using information / indicator indicating a specific CSI-RS resource group, so as to report the determined / selected (one or more) CSI-RS burst modes to the base station.

[0463] The UE receives CSI-RS from a plurality of CSI resources configured by configuration information from a base station ( S2002 ).

[0464] Here, the UE can receive CSI-RS from the base station in a plurality of CSI-RS burst patterns configured by the configuration information.

[0465] As described above, if one CSI-RS resource set corresponds to one CSI-RS burst mode, the UE can assume that all M CSI-RS resources included in the CSI-RS resource set are the same antenna port. Similarly, if one CSI-RS resource group corresponds to one CSI-RS burst mode, the UE can assume that all K CSI-RS resources included in the CSI-RS resource group are the same antenna port.

[0466] Despite 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).

[0467] The UE sends (reports) CSI to the base station ( S2003 ).

[0468] Here, the CSI may include at least one of CQI, PMI, RI, CRI, and LI.

[0469] The UE can report CSI to the base station based on the configuration information related to CSI reporting (and when triggered / activated by DCI). For example, the configuration information related to CSI reporting can configure the CSI reporting type, such as periodic CSI reporting, semi-persistent CSI reporting, and aperiodic CSI reporting, and it can configure which information should be reported in the CSI (e.g., CRI, CQI, PMI, RI, LI, etc.). In addition, in the case of periodic CSI reporting, the periodicity and time slot offset, etc. can also be configured.

[0470] According to the method proposed above, it is possible to calculate / derive CSI based on multiple time instances using channel and / or interference measurements for a CSI-RS burst mode determined from among multiple CSI-RS burst modes. In other words, the UE can perform channel and / or interference measurements based on the CSI-RS resources in the determined CSI-RS burst mode, and calculate or predict CSI based on each of the multiple time instances using channel and / or interference measurements. Here, for example, in the case of PMI, the value calculated / predicted in each time instance can be TD compressed and included in the CSI. In addition, in the case of CQI, it can be included in the CSI as one value (e.g., a value calculated / predicted from a CSI reference resource) or two values ​​for multiple time instances. In addition, in the case of RI, it can be included in the CSI as a common value for multiple time instances.

[0471] In addition, the CSI may include information / indicator indicating the determined CSI-RS burst pattern. If multiple CSI-RS burst patterns correspond to multiple CSI-RS resources with different patterns, the UE may use the CRI indicating the specific CSI-RS resource to report the determined / selected (one or more) CSI-RS burst patterns to the base station. In addition, if multiple CSI-RS burst patterns correspond to multiple CSI-RS resource sets with different patterns or multiple CSI-RS resource groups with different patterns, the UE may use information / indicator to indicate a specific CSI-RS resource set or a specific CSI-RS resource group to report the determined / selected (one or more) CSI-RS burst patterns to the base station.

[0472] In addition, multiple time instances (i.e., CSI reporting windows) used to calculate CSI can be determined based on the determined CSI-RS burst mode. Here, multiple time instances can be configured with the number of time instances, the intervals between time instances, and the time instance offset. In addition, multiple time instances can be configured by the base station or selected by the UE for at least one of the number of time instances, the intervals between time instances, and the time instance offset. Here, when configured by the base station, multiple time instances can be reported to the base station as a capability of the UE for at least one of the number of time instances, the intervals between time instances, and the time instance offset as a preference value. In addition, the time instance offset can be configured based on the CSI reference resource, the last time point of the determined CSI-RS burst mode, or the reporting time point of the CSI.

[0473] In addition, a minimum CSI processing time (Z) from receiving CSI triggering downlink control information (DCI) for reporting CSI to reporting CSI may be determined as a maximum value among Z values ​​for each of a plurality of CSI-RS burst patterns.

[0474] Additionally, a minimum CSI processing time (Z') from receiving a CSI-RS for channel and / or interference measurement for reporting CSI to reporting CSI may be determined as a maximum value among Z' values ​​for each of a plurality of CSI-RS burst patterns.

[0475] In addition, the number of CSI processing units (CPUs) occupied for reporting CSI may be determined as a maximum value among the numbers of CPUs for each of a plurality of CSI-RS burst patterns.

[0476] In addition, a subset of a CSI-RS burst pattern among multiple CSI-RS burst patterns may correspond to another CSI-RS burst pattern. For example, if the multiple CSI-RS burst patterns include a first CSI-RS burst pattern and a second CSI-RS burst pattern, and the first CSI-RS burst pattern includes the second CSI-RS burst pattern, a CPU may not be allocated to the second CSI-RS burst pattern.

[0477] Meanwhile, the above-mentioned operation of calculating CSI (ie, 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 on the UE or connected to the UE), and is used for the above-mentioned Fig.12 At least one function of the AI / ML operation (especially model inference) to calculate CSI (or channel prediction accuracy) can be performed by the UE (or an external device installed on or connected to the UE). In addition, the UE (or an external device installed on or connected to the UE) can be performed by the above Fig.16The process (particularly 5. Model inference) is used to determine multiple time instances (ie, CSI reporting windows) (eg, the number of time instances, the intervals between time instances, and the time instance offsets) expressed by the CSI in the determined CSI-RS burst pattern.

[0478] 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.

[0479] refer to Fig.21 , Fig.21 The operation of the base station based on the method proposed in the present disclosure is illustrated. Fig.21 The examples are for convenience of explanation and do not limit the scope of the present disclosure. Fig.21 Some of the steps illustrated in the figure may be omitted depending on the situation and / or setting. Fig.21 The base station in is only an example and can be implemented as follows Fig. 22 For example, Fig. 22 The processor (102 / 202) can control to send and receive channels / signals / data / information, etc. using the transceiver (106 / 206), and can also control to store the sent or received channels / signals / data / information, etc. in the memory (104 / 204).

[0480] in addition, Fig.21 The operation can be done by Fig. 22 One or more processors (102, 202) of the processor, and Fig.21 The operation can be used to drive Fig. 22 The command / program (eg, instructions, executable code) of at least one processor (eg, 102, 202) is stored in a memory (eg, Fig. 22 in one or more memories (104, 204).

[0481] The base station sends configuration information related to channel state information (CSI) to the UE ( S2101 ).

[0482] The CSI-related configuration information may include the CSI-related configuration information described in the above-proposed method.

[0483] The CSI-related configuration information may include at least one of CSI-IM (interference management) resource related information, CSI measurement configuration related information, CSI resource configuration related information, or CSI report configuration related information.

[0484] 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, first configuration information) and configuration information related to CSI resources (i.e., CSI resource configuration) (e.g., RRC IE "CSI-ResourceConfig") (hereinafter, second configuration information).

[0485] Here, multiple CSI-RS resources for CSI calculation / measurement may be configured for the UE through configuration information related to CSI resources (i.e., CSI resource configuration). 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) may 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 (or CSI-RS resources).

[0486] In addition, configuration information related to CSI resources (or CSI-RS resources) (i.e., CSI resource settings) can be connected / associated with specific configuration information related to CSI reporting (i.e., CSI report settings), and based on the report quantity (reportQuantity) in the CSI report setting, 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.

[0487] In addition, the CSI-related configuration information may include information about a plurality of CSI-RS burst patterns, and each of the plurality of CSI-RS burst patterns may include one or more CSI-RS resources.

[0488] Here, a CSI-RS burst pattern corresponds to one (periodic) CSI-RS resource, and multiple CSI-RS burst patterns may correspond to multiple CSI-RS resources with different patterns. In such a case, the UE may receive a CRI indicating a specific CSI-RS resource from the UE to report the determined / selected (one or more) CSI-RS burst pattern to the base station.

[0489] In addition, the CSI-RS burst mode corresponds to a CSI-RS resource set including M (M is a natural number) CSI-RS resources, and multiple CSI-RS burst modes may correspond to multiple CSI-RS resource sets with different modes. In this case, with respect to reporting the determined / selected (one or more) CSI-RS burst modes, the base station may receive information / indicator from the UE to indicate a specific CSI-RS resource set.

[0490] In addition, the CSI-RS burst mode corresponds to a CSI-RS resource group including K (K is a natural number) CSI-RS resources in a CSI-RS resource set, and multiple CSI-RS burst modes may correspond to multiple CSI-RS resource groups with different modes. In this case, with respect to the determined / selected (one or more) CSI-RS burst mode reports, the base station may receive information / indicator from the UE to indicate a specific CSI-RS resource group.

[0491] The base station transmits CSI-RS to the UE from a plurality of CSI resources configured by the configuration information ( S2102 ).

[0492] Here, the base station can transmit CSI-RS to the UE from a plurality of CSI-RS burst patterns configured by the configuration information.

[0493] As described above, if one CSI-RS resource set corresponds to one CSI-RS burst mode, the UE can assume that all M CSI-RS resources included in the CSI-RS resource set are the same antenna port. Similarly, if one CSI-RS resource group corresponds to one CSI-RS burst mode, the UE can assume that all K CSI-RS resources included in the CSI-RS resource group are the same antenna port.

[0494] Despite Fig.21 Although not shown in the figure, the base station can send downlink control information (DCI) to the UE. Here, the DCI can be a DCI that triggers aperiodic CSI reporting to the UE, or it can be a DCI that activates semi-persistent CSI reporting. In addition, the 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).

[0495] The base station receives CSI from the UE ( S2103 ).

[0496] Here, the CSI may include at least one of CQI, PMI, RI, CRI, and LI.

[0497] The UE can report CSI to the base station based on the configuration information related to CSI reporting (and when triggered / activated by DCI). For example, the configuration information related to CSI reporting can configure the CSI reporting type, such as periodic CSI reporting, semi-persistent CSI reporting, and aperiodic CSI reporting, and it can configure which information should be reported in the CSI (e.g., CRI, CQI, PMI, RI, LI, etc.). In addition, in the case of periodic CSI reporting, the periodicity and time slot offset, etc. can also be configured.

[0498] According to the method proposed above, it is possible to calculate / derive CSI based on multiple time instances using channel and / or interference measurements for a CSI-RS burst mode determined from among multiple CSI-RS burst modes. In other words, the UE can perform channel and / or interference measurements based on the CSI-RS resources in the determined CSI-RS burst mode, and calculate or predict CSI based on each of the multiple time instances using channel and / or interference measurements. Here, for example, in the case of PMI, the value calculated / predicted in each time instance can be TD compressed and included in the CSI. In addition, in the case of CQI, it can be included in the CSI as one value (e.g., a value calculated / predicted from a CSI reference resource) or two values ​​for multiple time instances. In addition, in the case of RI, it can be included in the CSI as a common value for multiple time instances.

[0499] In addition, the CSI may include information / indicator indicating the determined CSI-RS burst mode. If multiple CSI-RS burst modes correspond to multiple CSI-RS resources with different patterns, the UE may use the CRI indicating the specific CSI-RS resource to report the determined / selected (one or more) CSI-RS burst mode to the base station. In addition, when multiple CSI-RS burst modes correspond to multiple CSI-RS resource sets with different patterns or multiple CSI-RS resource groups with different patterns, regarding reporting the determined / selected (one or more) CSI-RS burst modes, the base station may receive information / indicator from the UE to indicate a specific CSI-RS resource set or a specific CSI-RS resource group.

[0500] In addition, multiple time instances (i.e., CSI reporting windows) used to calculate CSI can be determined based on the determined CSI-RS burst mode. Here, multiple time instances can be configured with the number of time instances, the intervals between time instances, and the time instance offset. In addition, multiple time instances can be configured by the base station or selected by the UE for at least one of the number of time instances, the intervals between time instances, and the time instance offset. Here, when configured by the base station, the base station can receive from the UE a preference value for at least one of the number of time instances, the intervals between time instances, and the time instance offset as a capability of the UE. In addition, the time instance offset can be configured based on the CSI reference resource, the last time point of the determined CSI-RS burst mode, or the reporting time point of the CSI.

[0501] In addition, a minimum CSI processing time (Z) from receiving CSI triggering downlink control information (DCI) for reporting CSI to reporting CSI may be determined as a maximum value among Z values ​​for each of a plurality of CSI-RS burst patterns.

[0502] Additionally, a minimum CSI processing time (Z') from receiving a CSI-RS for channel and / or interference measurement for reporting CSI to reporting CSI may be determined as a maximum value among Z' values ​​for each of a plurality of CSI-RS burst patterns.

[0503] In addition, the number of CSI processing units (CPUs) occupied for reporting CSI may be determined as a maximum value among the numbers of CPUs for each of a plurality of CSI-RS burst patterns.

[0504] In addition, a subset of a CSI-RS burst pattern among multiple CSI-RS burst patterns may correspond to another CSI-RS burst pattern. For example, if the multiple CSI-RS burst patterns include a first CSI-RS burst pattern and a second CSI-RS burst pattern, and the first CSI-RS burst pattern includes the second CSI-RS burst pattern, a CPU may not be allocated to the second CSI-RS burst pattern.

[0505] Meanwhile, the above-mentioned operation of calculating CSI (ie, 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 on the UE or connected to the UE), and is used for the above-mentioned Fig.12 At least one function of the AI / ML operation (especially model inference) to calculate CSI (or channel prediction accuracy) can be performed by the UE (or an external device installed on or connected to the UE). In addition, the UE (or an external device installed on or connected to the UE) can be performed by the above Fig.16The process (particularly 5. Model inference) is used to determine multiple time instances (ie, CSI reporting windows) (eg, the number of time instances, the intervals between time instances, and the time instance offsets) expressed by the CSI in the determined CSI-RS burst pattern.

[0506] General equipment to which the present disclosure can be applied

[0507] Fig. 22 is a diagram illustrating a block diagram of a wireless communication device according to an embodiment of the present disclosure.

[0508] 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).

[0509] 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.

[0510] 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.

[0511] In the following, the hardware elements of the wireless device 100, 200 will be described in more detail. It is not limited thereto, and one or more protocol layers may be implemented by one or more processors 102, 202. For example, one or more processors 102, 202 may implement one or more layers (e.g., functional layers such as PHY, MAC, RLC, PDCP, RRC, SDAP). One or more processors 102, 202 may generate one or more PDUs (protocol data units) and / or one or more SDUs (service data units) according to the descriptions, functions, processes, proposals, methods, and / or operational flow charts included in the present disclosure. One or more processors 102, 202 may generate messages, control information, data, or information according to the descriptions, functions, processes, proposals, methods, and / or operational flow charts disclosed in the present disclosure. One or more processors 102, 202 may 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. The one or more processors 102, 202 may receive signals (e.g., baseband signals) from the 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.

[0512] 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 description, functions, processes, proposals, methods, and / or operational flowcharts disclosed in the present disclosure may be implemented by 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 description, 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 description, 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.

[0513] 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.

[0514] 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.

[0515] 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.

[0516] 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.

[0517] 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 magnetic 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.

[0518] 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 by various names.

[0519] Industrial availability

[0520] 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, wherein the configuration information includes information about a plurality of CSI-RS (CSI reference signal) burst patterns, and each of the plurality of CSI-RS burst patterns includes one or more CSI-RS resources; receiving, from the base station, CSI-RS from the plurality of CSI-RS burst patterns; and sending CSI to the base station, wherein the CSI is calculated based on a plurality of time instances using channel and / or interference measurements for a CSI-RS burst pattern determined among the plurality of CSI-RS burst patterns, wherein the CSI includes an indicator indicating the determined CSI-RS burst mode, and The multiple time instances for calculating the CSI are determined based on the determined CSI-RS burst pattern.

2. The method according to claim 1, wherein: The plurality of time instances are configured with a number of time instances, intervals between time instances, and a time instance offset.

3. The method according to claim 2, wherein: At least one of the number of the time instances, the intervals between the time instances, and the time instance offsets is configured by the base station or selected by the UE.

4. The method according to claim 2, wherein: At least one of the number of the time instances, the intervals between the time instances, and the time instance offsets is reported to the base station as a capability of the UE.

5. The method according to claim 2, wherein: The time instance offset is configured based on a CSI reference resource, a last time point of the determined CSI-RS burst pattern, or a reporting time point of the CSI.

6. The method according to claim 1, wherein: A minimum CSI processing time (Z) from receiving CSI triggering downlink control information (DCI) for reporting the CSI to reporting the CSI is determined as a maximum value among Z values ​​for each of the plurality of CSI-RS burst patterns.

7. The method according to claim 1, wherein: A minimum CSI processing time (Z') from receiving a CSI-RS for channel and / or interference measurement for reporting the CSI to reporting the CSI is determined as a maximum value among Z' values ​​for each of the plurality of CSI-RS burst patterns.

8. The method according to claim 1, wherein: The number of CSI processing units (CPUs) occupied for reporting the CSI is determined to be a maximum value among the numbers of CPUs for each of the plurality of CSI-RS burst patterns.

9. The method according to claim 1, wherein: The multiple CSI-RS burst patterns include a first CSI-RS burst pattern and a second CSI-RS burst pattern, and Wherein, based on the first CSI-RS burst pattern including the second CSI-RS burst pattern, a CSI processing unit (CPU) is not allocated to the second CSI-RS burst pattern.

10. The method according to claim 1, wherein: The multiple CSI-RS burst patterns correspond to multiple CSI-RS resources with different patterns, to multiple CSI-RS resource sets with different patterns, or to multiple CSI-RS resource groups with different patterns within one CSI-RS resource set.

11. 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, wherein the configuration information includes information about a plurality of CSI-RS (CSI reference signal) burst patterns, and each of the plurality of CSI-RS burst patterns includes one or more CSI-RS resources; receiving, from the base station, CSI-RS from the plurality of CSI-RS burst patterns; and sending CSI to the base station, wherein the CSI is calculated based on a plurality of time instances using channel and / or interference measurements for a CSI-RS burst pattern determined among the plurality of CSI-RS burst patterns, wherein the CSI includes an indicator indicating the determined CSI-RS burst mode, and The multiple time instances for calculating the CSI are determined based on the determined CSI-RS burst pattern.

12. 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) to: Receiving configuration information related to channel state information (CSI) from a base station, wherein the configuration information includes information about a plurality of CSI-RS (CSI reference signal) burst patterns, and each of the plurality of CSI-RS burst patterns includes one or more CSI-RS resources; receiving, from the base station, CSI-RS from the plurality of CSI-RS burst patterns; and sending CSI to the base station, wherein the CSI is calculated based on a plurality of time instances using channel and / or interference measurements for a CSI-RS burst pattern determined among the plurality of CSI-RS burst patterns, wherein the CSI includes an indicator indicating the determined CSI-RS burst mode, and The multiple time instances for calculating the CSI are determined based on the determined CSI-RS burst pattern.

13. A processing device 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 operatively connected to the at least one processor and storing instructions that, upon execution by the at least one processor, perform operations comprising: Receiving configuration information related to channel state information (CSI) from a base station, wherein the configuration information includes information about a plurality of CSI-RS (CSI reference signal) burst patterns, and each of the plurality of CSI-RS burst patterns includes one or more CSI-RS resources; receiving, from the base station, CSI-RS from the plurality of CSI-RS burst patterns; and sending CSI to the base station, wherein the CSI is calculated based on a plurality of time instances using channel and / or interference measurements for a CSI-RS burst pattern determined among the plurality of CSI-RS burst patterns, wherein the CSI includes an indicator indicating the determined CSI-RS burst mode, and The multiple time instances for calculating the CSI are determined based on the determined CSI-RS burst pattern.

14. 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), wherein the configuration information includes information about a plurality of CSI-RS (CSI reference signal) burst patterns, and each of the plurality of CSI-RS burst patterns includes one or more CSI-RS resources; transmitting a CSI-RS from the plurality of CSI-RS burst patterns to the UE; and receiving CSI from the UE, wherein the CSI is calculated based on a plurality of time instances using channel and / or interference measurements for a CSI-RS burst pattern determined among the plurality of CSI-RS burst patterns, wherein the CSI includes an indicator indicating the determined CSI-RS burst mode, and The multiple time instances for calculating the CSI are determined based on the determined CSI-RS burst pattern.

15. 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), wherein the configuration information includes information about a plurality of CSI-RS (CSI reference signal) burst patterns, and each of the plurality of CSI-RS burst patterns includes one or more CSI-RS resources; transmitting a CSI-RS from the plurality of CSI-RS burst patterns to the UE; and receiving CSI from the UE, wherein the CSI is calculated based on a plurality of time instances using channel and / or interference measurements for a CSI-RS burst pattern determined among the plurality of CSI-RS burst patterns, wherein the CSI includes an indicator indicating the determined CSI-RS burst mode, and The multiple time instances for calculating the CSI are determined based on the determined CSI-RS burst pattern.

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