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

Abstract

Disclosed are a method and a device for transmitting or receiving channel state information in a wireless communication system. A method according to one embodiment of the present disclosure may comprise the steps of: receiving, by a UE, configuration information related to a CSI report from a base station; receiving, by the UE, a CSI-RS from the base station; and transmitting, by the UE, CSI derived using the CSI-RS to the base station.

Description

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

[0001] The present disclosure relates to a wireless communication system, and more particularly, to a method and device for transmitting and receiving channel state information (CSI) in a wireless communication system.

[0002] The fifth generation (5G) wireless communication system, the successor to 4G LTE (long-term evolution), is a new, clean-slate mobile communication system characterized by high performance, low latency, and high availability. 5G NR (New Radio) can utilize all available spectrum resources, from low-frequency bands below 1 GHz, to intermediate-frequency bands between 1 GHz and 10 GHz, and to high-frequency (or millimeter wave) bands above 24 GHz. 6G wireless communication systems are being developed based on the underlying technologies of 5G wireless communication.

[0003] The 6G wireless communication system is being developed with the goals of (i) very high data rates per device, (ii) a very large number of connected devices, (iii) global connectivity, (iv) very low latency, (v) reduced energy consumption of battery-free Internet of Things (IoT) devices, (vi) ultra-reliable connectivity, and (vii) connected intelligence with machine learning capabilities. The vision of the 6G system can be divided into four aspects: intelligent connectivity, deep connectivity, holographic connectivity, and ubiquitous connectivity. Considering the requirements of the 6G system, such as a peak data rate of 1 Tbps per device, an end-to-end latency of 1 ms, a maximum spectrum efficiency of 100 bps / Hz, support for mobility of 1000 km / h, satellite integration, artificial intelligence (AI), autonomous vehicles, extended reality (XR), and haptic communication, various technologies are being researched.

[0004] The technical problem of the present disclosure is to provide a method and device for transmitting and receiving channel state information reflecting far-field and near-field characteristics.

[0005] The technical problems to be achieved in the present disclosure are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by a person having ordinary skill in the technical field to which the present disclosure belongs from the description below.

[0006] A method according to an aspect of the present disclosure may include: receiving, by a user equipment (UE), configuration information related to channel state information (CSI) reporting from a base station; receiving, by the UE, a CSI-reference signal (CSI-RS) from the base station; and transmitting, by the UE, to the base station CSI derived using the CSI-RS. The CSI includes a first index associated with a first precoding matrix or channel-related matrix and a second index associated with a second precoding matrix or channel-related matrix, wherein the precoding matrix or channel-related matrix may be derived from at least one of the first precoding matrix or channel-related matrix and the second precoding matrix or channel-related matrix.

[0007] A method according to an additional aspect of the present disclosure may include: transmitting, by a base station, configuration information related to channel state information (CSI) reporting to a user equipment (UE); transmitting, by the base station, a CSI-reference signal (CSI-RS) to the UE; and receiving, by the base station, the CSI from the UE. The CSI includes a first index associated with a first precoding matrix or channel-related matrix and a second index associated with a second precoding matrix or channel-related matrix, wherein the precoding matrix or channel-related matrix may be derived from at least one of the first precoding matrix or channel-related matrix and the second precoding matrix or channel-related matrix.

[0008] According to an embodiment of the present disclosure, accurate channel state information for a wireless channel can be transmitted and received in a high-frequency band ultra-large-scale multi-antenna system.

[0009] Additionally, according to an embodiment of the present disclosure, beamforming / precoding gain for a near-field terminal can be improved in a high-frequency band ultra-large-scale multi-antenna system.

[0010] The effects that can be obtained from the present disclosure are not limited to the effects mentioned above, and other effects that are not mentioned will be clearly understood by a person having ordinary skill in the art to which the present disclosure pertains from the description below.

[0011] The accompanying drawings, which are incorporated in and are part of the detailed description to aid in understanding the present disclosure, provide embodiments of the present disclosure and, together with the detailed description, describe the technical features of the present disclosure.

[0012] Figure 1 illustrates a flexible network topology to which some examples of the present disclosure may be applied.

[0013] FIG. 2 illustrates an example of a communication system to which some examples of the present disclosure may be applied.

[0014] FIG. 3 illustrates an example of a wireless device to which some examples of the present disclosure may be applied.

[0015] FIG. 4 exemplarily illustrates a communication procedure between a first node and a second node to which some examples of the present disclosure may be applied.

[0016] FIG. 5 exemplarily illustrates a functional framework for AI / ML operations to which some examples of the present disclosure may be applied.

[0017] FIG. 6 illustrates an example of a communication procedure based on an AI / ML model between a first node and a second node to which some examples of the present disclosure may be applied.

[0018] FIG. 7 illustrates an electromagnetic spectrum to which some examples of the present disclosure may be applied.

[0019] FIG. 8 exemplarily illustrates a system information transmission / reception procedure to which some examples of the present disclosure may be applied.

[0020] FIG. 9 illustrates an exemplary beam management procedure to which some examples of the present disclosure may be applied.

[0021] FIG. 10 is a diagram comparing the near-field region according to the number of antennas in a wireless communication system to which the present disclosure can be applied.

[0022] FIG. 11 is a diagram illustrating the operation of a UE for a method for transmitting and receiving channel state information according to one embodiment of the present disclosure.

[0023] FIG. 12 is a diagram illustrating the operation of a base station for a method for transmitting and receiving channel state information according to one embodiment of the present disclosure.

[0024] Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. The detailed description set forth below, together with the accompanying drawings, is intended to explain exemplary embodiments of the present disclosure and is not intended to represent the only embodiments in which the present disclosure may be practiced. The following detailed description includes specific details to provide a thorough understanding of the present disclosure. However, one of ordinary skill in the art will appreciate that the present disclosure may be practiced without these specific details.

[0025] In some cases, to avoid obscuring the concepts of the present disclosure, known structures and devices may be omitted or illustrated in block diagram form focusing on the core functions of each structure and device.

[0026] In the present disclosure, when a component is said to be "connected," "coupled," or "connected" to another component, this may include not only a direct connection but also an indirect connection in which another component exists between them. Furthermore, the terms "comprises" or "has" in the present disclosure specify the presence of the mentioned features, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or groups thereof.

[0027] In this disclosure, terms such as "first," "second," etc. are used only to distinguish one component from another, are not used to limit the components, and do not limit the order or importance of components unless specifically stated otherwise. Accordingly, within the scope of this disclosure, a first component in one embodiment may be referred to as a second component in another embodiment, and similarly, a second component in one embodiment may be referred to as a first component in another embodiment.

[0028] The terminology used in this disclosure is for the purpose of describing particular embodiments and is not intended to limit the scope of the claims. As used in the description of the embodiments and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise.

[0029] In this disclosure, "A or B" can mean "only A," "only B," or "both A and B." In other words, "A or B" in this disclosure can be interpreted as "A and / or B." For example, "A, B or C" in this disclosure can mean "only A," "only B," "only C," or "any combination of A, B and C."

[0030] As used herein, a slash ( / ) or a comma may mean "and / or." For example, "A / B" may mean "A and / or B." Accordingly, "A / B" may mean "only A," "only B," or "both A and B." For example, "A, B, C" may mean "A, B, or C."

[0031] In the present disclosure, “at least one of A and B” may mean “only A,” “only B,” or “both A and B.” Additionally, in the present disclosure, the expressions “at least one of A or B” or “at least one of A and / or B” may be interpreted identically to “at least one of A and B.”

[0032] Additionally, in the present disclosure, “at least one of A, B and C” can mean “only A,” “only B,” “only C,” or “any combination of A, B and C.” Additionally, “at least one of A, B or C” or “at least one of A, B and / or C” can mean “at least one of A, B and C.”

[0033] Additionally, parentheses used in the present disclosure may mean "for example." Specifically, when indicated as "control information (PDCCH)", "PDCCH" may be described as an example of "control information." In other words, "control information" in the present disclosure is not limited to "PDCCH," and "PDCCH" may be described as an example of "control information." Furthermore, even when indicated as "control information (i.e., PDCCH)", "PDCCH" may be described as an example of "control information."

[0034] In the following description, 'when, if, in case of' can be replaced with 'based on'.

[0035] Technical features individually described in one drawing in this disclosure may be implemented individually or simultaneously.

[0036] In the present disclosure, a terminal or user equipment (UE) may be a portable device and may be a first node that receives a signal from a base station / second node / IAB (integrated access backhaul) node.

[0037] In the present disclosure, a base station (BS) may be a second node / IAB node / Transmission-Reception Point (TRP).

[0038] In the present disclosure, higher layer parameters may be parameters configured, pre-configured, or pre-defined for the terminal. For example, a base station or a network may transmit higher layer parameters to the terminal. For example, the higher layer parameters may be transmitted via radio resource control (RRC) signaling or medium access control (MAC) signaling.

[0039] In the present disclosure, "setting or defining" may be interpreted as being set to a device through predefined signaling (e.g., SIB (system information block), MAC, RRC) from a base station or network. In the present disclosure, "setting or defining" may be interpreted as being set to a device through separate signaling or being defined in advance without separate signaling.

[0040] In the present disclosure, transmitting or receiving a channel means transmitting or receiving information or a signal through the channel. For example, transmitting a control channel means transmitting control information or a signal through the control channel. Similarly, transmitting a data channel means transmitting data information or a signal through the data channel.

[0041] The technology described in the present disclosure can be used in various wireless communication systems such as CDMA (code division multiple access), FDMA (frequency division multiple access), TDMA (time division multiple access), OFDMA (orthogonal frequency division multiple access), and SC-FDMA (single carrier frequency division multiple access). CDMA can be implemented with wireless technologies such as UTRA (universal terrestrial radio access) or CDMA2000. TDMA can be implemented with wireless technologies such as GSM (global system for mobile communications) / GPRS (general packet radio service) / EDGE (enhanced data rates for GSM evolution). OFDMA can be implemented with wireless technologies such as IEEE (Institute of Electrical and Electronics Engineers) 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802-20, E-UTRA (evolved UTRA), LTE (long term evolution), and 5G NR.

[0042] The technology described in the present disclosure can be implemented with 6G wireless technology and applied to various 6G systems. For example, the 6G system can have key factors such as enhanced mobile broadband (eMBB), ultra-reliable low latency communications (URLLC), massive machine-type communication (mMTC), artificial intelligence (AI) integrated communication, tactile internet, high throughput, high network capacity, high energy efficiency, low backhaul and access network congestion, and enhanced data security.

[0043] Network structure

[0044] Figure 1 illustrates a flexible network topology to which some examples of the present disclosure may be applied.

[0045] To compensate for incomplete network coverage areas, a network topology that allows for more flexible and resilient split radio access networks (RANs) may be considered. For this purpose, various nodes, such as integrated access backhaul (IAB) nodes, relays, and radio frequency (RF) repeaters, as illustrated in Figure 1, may be applied, or a non-terrestrial network (NTN) may be integrated. For example, an IAB node may correspond to a node that provides wireless backhaul. For example, a relay may refer to any intermediate point, and in the case of a sidelink relay where a terminal functions as a relay, it may collectively refer to a terminal-to-network (U2N) relay and a terminal-to-terminal (U2U) relay. For example, an RF repeater may correspond to a node that simply performs the function of signal amplification and forwarding, or in the case of a network-controlled repeater, it may not only amplify and forward signals but also adjust its transmission and reception settings based on information provided by the network. For example, NTN nodes could be satellites or aircraft that provide NTN coverage that terrestrial networks struggle to provide. Beyond these examples, various intermediate points can be introduced to improve the network topology.

[0046] Referring to Figure 1, a split RAN can support the division of a base station into a centralized unit (CU) and one or more distributed units (DUs). The CU and DU can correspond to logical units. The CU can be further divided into a control plane (CP) portion and one or more user plane (UP) portions. Since a failure in the CU-CP affects not only the CU-UP but also the DUs, various intermediate points can be introduced to compensate for this.

[0047] An intermediate point may correspond to a terminal or a base station, depending on its relationship to other nodes. For example, an IAB node may include a mobile-termination (MT) portion and a unit (DU). The MT may connect the IAB node to a donor node. The unit (DU) of an IAB node may serve other terminals or connect to other IAB nodes to provide multi-hop wireless backhaul to the terminal. For example, an IAB node may correspond to a base station in its relationship to a user-side node, and to a terminal in its relationship to a network-side node.

[0048] In some examples of the present disclosure, the description of a terminal may equally apply not only to a user-side endpoint, but also to an intermediate point corresponding to a terminal in a relative relationship with a network-side endpoint. Similarly, in some examples of the present disclosure, the description of a base station may equally apply not only to a network-side endpoint, but also to an intermediate point corresponding to a base station in a relative relationship with a user-side endpoint. In most cases where there is no additional description of the operations of three or more entities, the communicating entities in the present disclosure are briefly described as terminals and / or base stations (or first nodes and / or second nodes), where the terms terminal and / or base stations (or first nodes and / or second nodes) are interpreted to include / replace any endpoint or any intermediate point in relation to other nodes.

[0049] As such, in some examples of the present disclosure, for the sake of simplicity of explanation, the subjects of the operation may be referred to as terminals and / or base stations (or first nodes and / or second nodes). In addition, the terms terminal and / or base station (or first node and / or second node) may also be interpreted / replaced as in the following examples: For example, the terminal (or first node) and the base station (or second node) may respectively correspond to the first endpoint and the second endpoint; may respectively correspond to the endpoint and the intermediate point; may respectively correspond to the intermediate point and the endpoint; or may respectively correspond to the first intermediate point and the second intermediate point.

[0050] In the present disclosure, there may be zero or more intermediate points between the base station and the terminal. If an intermediate point exists, it may correspond to an IAB node / relay / RF repeater / NTN node, or a node supporting other functions. The intermediate point may be a node with a fixed location or a node with an unfixed location.

[0051] Systems applicable to this disclosure

[0052] FIG. 2 illustrates an example of a communication system to which some examples of the present disclosure may be applied.

[0053] The communication system (100) applied to the present disclosure includes a wireless device (110), a network device (120), and a network (130). Here, the wireless device (110) refers to a device that performs communication using a wireless access technology (e.g., LTE, LTE-A, LTE-A pro, NR, 5G, 5G-A, 6G) and may be referred to as a communication / wireless / 5G / 6G device. Although not limited thereto, the wireless device (110) may include a robot (110a), a vehicle (110b-1, 110b-2), an XR (extended reality) device (110c), a hand-held device (110d), a home appliance (110e), an IoT (Internet of Things) device (110f), and an AI (artificial intelligence) device / server (110g). For example, the vehicle may include a vehicle equipped with a wireless communication function, an autonomous vehicle, a vehicle capable of performing vehicle-to-vehicle communication, etc. Here, the vehicle (110b-1, 110b-2) may include an unmanned aerial vehicle (UAV) (e.g., a drone). The XR device (110c) includes an augmented reality (AR) / virtual reality (VR) / mixed reality (MR) device, and may be implemented in the form of a head-mounted device (HMD), a head-up display (HUD) equipped in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, digital signage, a vehicle, a robot, etc. The portable device (110d) may include a smartphone, a smart pad, a wearable device (e.g., a smart watch, smart glasses), a computer (e.g., a laptop, etc.), etc. The home appliance (110e) may include a TV, a refrigerator, a washing machine, etc. The IoT device (110f) may include a sensor, a smart meter, etc. The wireless device (110) may correspond to a terminal (or first node) or an intermediate point.The network device (120) may correspond to a base station (or second node) or another intermediate point. For example, the network device (120) may also be implemented as a wireless device (110), and a specific wireless device (120a) may act as a network device (120) to another wireless device (110).

[0054] Wireless devices (110a to 110f) can be connected to a network (130) via a network device (120). AI technology can be applied to the wireless devices (110a to 110f), and the wireless devices (110a to 110f) can be connected to an AI server (110g) via a network (130). The network (130) can be configured using a 3G network, a 4G (e.g., LTE) network, a 5G (e.g., NR), or a 6G network. The wireless devices (110a to 110f) can communicate with each other via the network device (120) / network (130), but can also communicate directly (e.g., sidelink communication) without going through the network device (120) / network (130). For example, vehicles (110b-1, 110b-2) can communicate directly (e.g., V2V (vehicle to vehicle) / V2X (vehicle to everything) communication). Additionally, an IoT device (110f) (e.g., a sensor) can communicate directly with another IoT device (e.g., a sensor) or another wireless device (110a to 110f).

[0055] Wireless communication / connection (150a, 150b, 150c) can be established between wireless devices (110a to 110f) / network devices (120), network devices (120) / network devices (120). Here, the wireless communication / connection can be established through various wireless access technologies such as uplink / downlink communication (150a), sidelink communication (150b) (or D2D communication), and communication between network devices (150c) (e.g., relay, IAB (integrated access backhaul)). Through the wireless communication / connection (150a, 150b, 150c), the wireless device and the network device / wireless device, and the network device and the network device can transmit / receive wireless signals to each other. For example, the wireless communication / connection (150a, 150b, 150c) can transmit / receive signals through various physical channels. To this end, based on various descriptions of the present disclosure, at least some of various configuration information setting processes for transmitting / receiving wireless signals, various signal processing processes (e.g., channel encoding / decoding, modulation / demodulation, resource mapping / demapping, etc.), resource allocation processes, etc., may be performed.

[0056] Device applicable to the present disclosure

[0057] FIG. 3 illustrates an example of a wireless device to which some examples of the present disclosure may be applied.

[0058] Referring to FIG. 3, the wireless device (200) can transmit and receive wireless signals via various wireless access technologies (e.g., LTE, LTE-A, LTE-A pro, NR, 5G, 5G-A, 6G). The wireless device (200) includes at least one processor (202) and at least one memory (204), and may additionally include at least one transceiver (206) and / or at least one antenna (208).

[0059] The processor (202) controls the memory (204) and / or the transceiver (206), and may be configured to implement the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. For example, the processor (202) may process information in the memory (204) to generate first information / signal, and then transmit a wireless signal including the first information / signal via the transceiver (206). In addition, the processor (202) may receive a wireless signal including second information / signal via the transceiver (206), and then store information obtained from signal processing of the second 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 instructions for performing some or all of the processes controlled by the processor (202), or for performing the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed herein. Here, the processor (202) and the memory (204) may be part of a communication modem / circuit / chip designed to implement wireless communication technology. The transceiver (206) may be connected to the processor (202) and may transmit and / or receive wireless signals via at least one antenna (208). The transceiver (206) may include a transmitter and / or a receiver. The transceiver (206) may be used interchangeably with an RF (radio frequency) unit. In the present disclosure, a wireless device may also mean a communication modem / circuit / chip.

[0060] Hereinafter, the hardware elements of the wireless device (200) will be described in more detail. Although not limited thereto, at least one protocol layer may be implemented by at least one processor (202). For example, at least one processor (202) may implement at least one layer (e.g., a functional layer such as physical (PHY), media access control (MAC), radio link control (RLC), packet data convergence protocol (PDCP), radio resource control (RRC), and service data adaptation protocol (SDAP)). At least one processor (202) may generate at least one Protocol Data Unit (PDU) and / or at least one Service Data Unit (SDU) according to the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. At least one processor (202) may generate a message, control information, data, or information according to the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. At least one processor (202) can generate a signal (e.g., a baseband signal) comprising a PDU, an SDU, a message, control information, data or information according to the functions, procedures, proposals and / or methods disclosed in this document, and provide the signal to at least one transceiver (206). At least one processor (202) can receive a signal (e.g., a baseband signal) from at least one transceiver (206) and obtain the PDU, SDU, message, control information, data or information according to the descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed in this document.

[0061] At least one processor (202) may be referred to as a controller, a microcontroller, a microprocessor, or a microcomputer. The at least one processor (202) may be implemented by hardware, firmware, software, or a combination thereof. For example, at least one application specific integrated circuit (ASIC), at least one digital signal processor (DSP), at least one digital signal processing device (DSPD), at least one programmable logic device (PLD), or at least one field programmable gate array (FPGA) may be included in the at least one processor (202). The descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document may be implemented using firmware or software, and the firmware or software may be implemented to include modules, procedures, functions, etc. The descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document may be included in the at least one processor (202), or may be stored in at least one memory (204) and executed by the at least one processor (202). The descriptions, functions, procedures, suggestions, methods and / or flowcharts disclosed in this document may be implemented using firmware or software in the form of code, instructions and / or sets of instructions.

[0062] At least one memory (204) can be connected to at least one processor (202) and can store various forms of data, signals, messages, information, programs, codes, instructions and / or commands. The at least one memory (204) can be configured as a read only memory (ROM), a random access memory (RAM), an erasable programmable read only memory (EPROM), a flash memory, a hard drive, a register, a cache memory, a computer readable storage medium and / or a combination thereof. The at least one memory (204) can be located internally and / or externally to the at least one processor (202). In addition, the at least one memory (204) can be connected to the at least one processor (202) via various technologies such as a wired or wireless connection.

[0063] At least one transceiver (206) can transmit user data, control information, wireless signals / channels, etc., mentioned in the methods and / or flowcharts of this document to at least one other device. At least one transceiver (206) can receive user data, control information, wireless signals / channels, etc. mentioned in the descriptions, functions, procedures, proposals, methods and / or flowcharts disclosed in this document from at least one other device. For example, at least one transceiver (206) can be connected to at least one processor (202) and can transmit and receive wireless signals. For example, at least one processor (202) can control at least one transceiver (206) to transmit user data, control information, or wireless signals to at least one other device. Furthermore, at least one processor (202) can control at least one transceiver (206) to receive user data, control information, or wireless signals from at least one other device. Additionally, at least one transceiver (206) may be connected to at least one antenna (208), and at least one transceiver (206) may be configured to transmit and receive user data, control information, wireless signals / channels, etc. mentioned in the descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed in this document via at least one antenna (208). In this document, at least one antenna may be a plurality of physical antennas or a plurality of logical antennas (e.g., antenna ports). At least one transceiver (206) may convert the received wireless signals / channels, etc. from RF band signals to baseband signals in order to process the received user data, control information, wireless signals / channels, etc. using at least one processor (202).At least one transceiver (206) may convert user data, control information, wireless signals / channels, etc. processed by at least one processor (202) from a baseband signal to an RF band signal. For this purpose, at least one transceiver (206) may include an (analog) oscillator and / or filter.

[0064] The components of the wireless device described with reference to FIG. 3 may be referred to by different terms in terms of functionality. For example, the processor (202) may be referred to as a control unit, the transceiver (206) as a communication unit, and the memory (204) as a storage unit. In some cases, the communication unit may be used to mean at least a portion of the processor (202) and the transceiver (206).

[0065] The structure of the wireless device described with reference to FIG. 3 can be understood as the structure of at least a portion of various devices. For example, the structure of the wireless device illustrated in FIG. 3 can be at least a portion of various devices described with reference to FIG. 2 (e.g., a robot (110a), a vehicle (110b-1, 110b-2), an XR device (110c), a portable device (110d), a home appliance (110e), an IoT device (110f), an AI device / server (110g)). Furthermore, according to various embodiments, in addition to the components illustrated in FIG. 3, the device may further include other components.

[0066] For example, the device may be a portable device such as a smartphone, a smart pad, a wearable device (e.g., a smart watch, smart glasses), or a portable computer (e.g., a laptop, etc.). In this case, the device may further include at least one of a power supply unit that supplies power and includes a wired / wireless charging circuit, a battery, etc., an interface unit that includes at least one port for connection with another device (e.g., an audio input / output port, a video input / output port), and an input / output unit for inputting and outputting image information / signals, audio information / signals, data, and / or information input from a user.

[0067] For example, the device may be a mobile device such as a mobile robot, a vehicle, a train, an aerial vehicle (AV), a ship, etc. In this case, the device may further include at least one of a driving unit including at least one of an engine, a motor, a power train, wheels, brakes, and a steering unit of the device, a power supply unit including a wired / wireless charging circuit, a battery, etc. that supplies power, a sensor unit that senses status information, environmental information, and user information of the device or its surroundings, an autonomous driving unit that performs functions such as path maintenance, speed control, and destination setting, and a position measurement unit that obtains location information of the mobile device through a global positioning system (GPS) and various sensors.

[0068] For example, the device may be an XR device such as an HMD, a head-up display (HUD) installed in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, a digital signage, a vehicle, a robot, etc. In this case, the device may further include at least one of a power supply unit that supplies power and includes a wired / wireless charging circuit, a battery, etc., an input / output unit that obtains control information, data, etc. from the outside and outputs the generated XR object, and a sensor unit that senses status information, environmental information, and user information of the device or the surroundings of the device.

[0069] For example, the device may be a robot that can be classified into industrial, medical, household, military, etc. types depending on the purpose or field of use. In this case, the device may further include at least one of a sensor unit that senses status information, environmental information, and user information of the device or its surroundings, and a driving unit that performs various physical actions, such as moving the robot joints.

[0070] For example, the device may be an AI device such as a TV, a projector, a smartphone, a PC, a laptop, a digital broadcasting terminal, a tablet PC, a wearable device, a set-top box (STB), a radio, a washing machine, a refrigerator, digital signage, a robot, a vehicle, etc. In this case, the device may further include at least one of an input unit that acquires various types of data from the outside, an output unit that generates output related to sight, hearing, or touch, a sensor unit that senses status information, environmental information, and user information of the device or its surroundings, and a training unit that trains a model composed of an artificial neural network using learning data.

[0071] The structure of the wireless device illustrated in FIG. 3 may be understood as a part of a terminal (or first node), or as a part of an intermediate point, or as a part of a base station (or second node). If the device illustrated in FIG. 3 is a base station (or second node), the device may further include a wired transceiver for front haul and / or back haul communications. If the front haul and / or back haul communications are based on wireless communications, at least one transceiver (206) illustrated in FIG. 3 may be used for front haul and / or back haul communications, and a wired transceiver may not be included.

[0072] Communication procedures

[0073] FIG. 4 exemplarily illustrates a communication procedure between a first node and a second node to which some examples of the present disclosure may be applied.

[0074] FIG. 4 illustrates operations of a first node (110) (e.g., a terminal) and a second node (120) (e.g., a base station) transmitting and / or receiving data and operations performed prior thereto.

[0075] In step S101, the first node (110) and the second node (120) can perform synchronization. For example, the terminal (110) performs an initial cell search operation. Specifically, the terminal (110) can detect at least one synchronization signal transmitted from the base station (120) according to a predefined rule. Here, the synchronization signal can include a plurality of synchronization signals (e.g., a primary synchronization signal, a secondary synchronization signal) classified according to a structure or purpose. Through this, the terminal (110) can confirm the boundaries of the frame, subframe, slot, and / or symbol of the base station (120) and obtain information (e.g., a cell identifier) ​​about the base station (120).

[0076] In step S103, the first node (110) can obtain system information transmitted from the second node (120). For example, the system information is information related to the properties, characteristics, and / or capabilities of the base station (120) required to access the base station (120) and use the service, and can be classified according to the content (e.g., whether it is essential for access), transmission structure (e.g., channel used, whether it is provided in an on-demand manner), etc., and can be classified into, for example, a master information block (MIB) and a system information block (SIB). If necessary, the terminal (110) can transmit a signal requesting system information before receiving the system information. Such requesting and providing of system information may be performed after a random access procedure described below.

[0077] In step S105, the first node (110) and the second node (120) can perform a random access procedure. For example, the terminal (110) can transmit and / or receive at least one message (e.g., a random access preamble, a random access response (RAR) message, etc.) for a random access procedure based on information related to a random access channel of the base station (120) obtained through system information (e.g., channel position, channel structure, structure of a supported preamble, etc.). For example, the terminal (110) may transmit a preamble (e.g., message 1 (MSG1)) over a random access channel, receive a random access response (RAR) message (e.g., message 2 (MSG2)), transmit a message (e.g., message 3 (MSG3)) including information related to the terminal (110) (e.g., identification information) using scheduling information included in the RAR message to the base station (120), and receive a message for contention resolution and / or connection establishment (e.g., message 4 (MSG4)). As another example, MSG1 and MSG3 may be transmitted and received as one message (e.g., message A (MSG A)), or MSG2 and MSG4 may be transmitted and received as one message (e.g., message B (MSG B)).

[0078] In step S107, the first node (110) and the second node (120) can perform signaling of control information. For example, the control information can be defined in various layers, such as a layer that controls a connection (e.g., a radio resource control (RRC) layer), a layer that handles mapping between logical channels and transmission channels (e.g., a media access control (MAC) layer), and a layer that handles physical channels (e.g., a physical (PHY) layer). For example, the terminal (110) and the base station (120) can perform at least one of signaling for establishing a connection, signaling for determining settings related to communication, and signaling for indicating allocated resources.

[0079] In step S109, the first node (110) and the second node (120) can transmit and / or receive data. For example, the terminal (110) and the base station (120) can process, transmit, and / or receive data based on signaling of control information. For example, when transmitting data, the terminal (110) or the base station (120) can perform at least one of channel encoding, rate matching, scrambling, constellation mapping, layer mapping, waveform modulation, antenna mapping, and resource mapping on information bits. For example, when receiving data, the terminal (110) or the base station (120) can perform at least one of signal extraction from resources, waveform demodulation for each antenna, signal arrangement considering layer mapping, constellation demapping, descrambling, and channel decoding.

[0080] 6G system core technologies

[0081] As core implementation technologies of the 6G system, technologies such as artificial intelligence (AI), THz (terahertz) communication, optical wireless technology, free space optics (FSO) backhaul network, massive MIMO (multiple input multiple output) technology, blockchain, 3D networking, quantum communication, unmanned aerial vehicles, cell-free communication, wireless information and energy transfer (WIET), integration of sensing and communication, integration of access backhaul networks, holographic beamforming, big data analysis, and large intelligent surface (LIS) can be adopted.

[0082] artificial intelligence

[0083] Incorporating AI into communications can streamline and improve real-time data transmission. AI can use numerous analytics to determine how complex target tasks should be performed. This means AI can increase efficiency and reduce processing delays. Time-consuming tasks such as handovers, network selection, and resource scheduling can be performed instantly using AI. AI can also play a crucial role in machine-to-machine (M2M), machine-to-human, and human-to-machine communications. Furthermore, AI can facilitate rapid communication in brain-computer interfaces (BCIs). AI-based communication systems can be supported by metamaterials, intelligent structures, intelligent networks, intelligent devices, intelligent cognitive radios, self-sustaining wireless networks, and machine learning.

[0084] The following describes a functional framework for AI / ML operations.

[0085] Below, to explain AI (or AI / ML) more specifically, the terms can be defined as follows.

[0086] - Data collection: Data collected from network nodes, management entities, or terminals as a basis for AI model training, data analysis, and inference.

[0087] - AI Model: A data-driven algorithm that applies AI technology to generate a set of outputs containing predictive information and / or decision parameters based on a set of inputs.

[0088] - AI / ML Training: An online or offline process of training an AI model by learning features and patterns that best represent the data and obtain a trained AI / ML model for inference.

[0089] - AI / ML Inference: The process of making predictions or inducing decisions based on collected data and the AI ​​model using a trained AI model.

[0090] Life Cycle Management (LCM) procedures for AI / ML models (i.e., model training, model deployment, model inference, model monitoring, model updates, etc.) can be divided into functionality-based LCM and model-based LCM. In functionality-based LCM, AI / ML models may not be identified by the network, and the network can direct the activation / deactivation / fallback / switching of AI / ML functionality. In model-ID (identifier)-based LCM, AI / ML models can be identified by the network, and the network / terminal can activate / deactivate / select / switch AI / ML models based on the model ID.

[0091] FIG. 5 exemplarily illustrates a functional framework for AI / ML operations to which some examples of the present disclosure may be applied.

[0092] Figure 5 illustrates a general functional architecture relevant to both Functionality-based LCM and Model-based LCM. Some of the functions or some of the data / information / command flows (i.e., arrows) illustrated in Figure 5 may be omitted.

[0093] Referring to FIG. 5, a general functional framework can be configured to include a data collection function (10), a model training function (20), a management function (30), an inference function (40), and a model storage function (50).

[0094] The Data Collection function (10) is a function that provides input data to the Model Training function (20), Management function (30), and Inference function (40). The Data Collection function (10) can perform data preparation based on raw data and provide input data processed through data preparation. Examples of raw data may include received data / measurement data from terminals or other network entities, inference / output of AI / ML models, etc. The Data Collection function (10) may be performed by a single entity (e.g., terminal, network node, etc.) or may be performed by multiple entities.

[0095] Here, training data (11) refers to data required as input for the AI / ML Model Training function (20). Monitoring data (12) refers to data required as input for the Management (30) of the AI / ML model or AI / ML function. Inference data (13) refers to data required as input for the AI / ML Inference function (30).

[0096] The Model Training function (20) is a function that performs AI / ML model training, validation, and testing, which can generate model performance metrics that can be used as part of the AI / ML model testing procedure. The Model Training function (20) can perform data preparation (e.g., data pre-processing and cleaning, forming, and transformation) based on the Training Data (11) transferred from the Data Collection function (10), if necessary.

[0097] Trained / Updated Model (21): If there is a Model Storage function (50), it is used to pass a trained, validated and tested AI / ML model to the Model Storage function (50) or to pass an updated version of the model to the Model Storage function (50).

[0098] The Management function (30) is a function that supervises the operation of the AI / ML model or AI / ML function. In addition, the Management function (30) may perform decisions to ensure appropriate inference operations based on data received from the Data Collection function (10) (i.e., Monitoring Data (12)) and / or data received from the Inference function (40) (i.e., Inference Output (41)).

[0099] Management Instruction (32) is information required as input to manage the Inference function (40). The relevant information may include selection / (de)activation / switching of an AI / ML model or AI / ML-based function, and may also include fallback to non-AI / ML operations (i.e., not relying on the inference process).

[0100] A Model Transfer / Delivery Request (33) can be used to request model(s) from Model Storage (50).

[0101] A Performance Feedback / Retraining Request (31) refers to information required as input to the Model Training function (20) (e.g., for the purpose of (re)training or updating the model).

[0102] The Inference function (40) is a function that provides output from the process of applying an AI / ML model or AI / ML function using data (i.e., Inference Data (13)) provided by Data Collection (10) as input. Data preparation (e.g., data preprocessing and cleaning, formatting, and transformation) may also be performed based on the Inference Data (13) delivered by Data Collection (10). If necessary, the Inference function (40) may also perform data preparation (e.g., data preprocessing and cleaning, forming, and transformation) based on the Inference Data (13) provided by Data Collection function (10).

[0103] Inference Output (41) is data used in the Management function (30) to monitor the performance of an AI / ML model or AI / ML function. Inference Output (41) may include the inference output of the AI / ML model generated by the Inference function (30), and the details of the inference output may vary depending on the use case.

[0104] The Model Storage function (50) stores a learned / updated model that can be used to perform the Inference function (40). The Model Storage function (50) illustrated in FIG. 2 can be used as a reference point (if any) when applicable to protocol termination, model transmission / delivery, and related processes. Furthermore, the Model Storage function (50) is merely an example and is not intended to limit the storage location of actual AI / ML models, and may be omitted.

[0105] Model Transfer / Delivery (51) is used to transfer AI / ML models to inference functions.

[0106] The level of cooperation can be defined as follows depending on the capability of AI / ML functions between multiple nodes, and variations due to combination of multiple levels or separation of any one level are also possible.

[0107] Cat 0a) No collaboration framework: AI / ML algorithms are purely implementation-based and do not require any changes to the wireless interface.

[0108] Cat 0b) This level corresponds to a framework with a modified wireless interface tailored to efficient implementation-based AI / ML algorithms, but without collaboration.

[0109] Category 1) involves inter-node support to improve the AI / ML algorithms of each node. For example, this applies when a specific node receives support from another node (for training, adaptation, etc.) and vice versa. At this level, model exchange between network nodes is not required.

[0110] Category 2) Joint AI / ML tasks can be performed across multiple nodes. This level requires the exchange of AI / ML model commands or network nodes.

[0111] FIG. 5 is a diagram illustrating an overall functional framework for an AI / ML model, and not all functions and / or all data / information / command signals illustrated in FIG. 5 may be performed within a specific node, but only some of them may be performed.

[0112] AI / ML models can be divided into one-side models and two-side models depending on whether training and / or inference are performed on a single node or jointly / sequentially on multiple nodes.

[0113] A one-side model can refer to an AI / ML model in which inference is performed entirely by a single node (e.g., a terminal or network). Here, AI / ML model training can also be performed entirely by a single node. AI / ML model training and inference can be performed by the same node, or they can be performed by separate nodes.

[0114] A two-side model can refer to an AI / ML model in which joint inference is performed across multiple nodes (e.g., terminals and networks). Joint inference refers to inference being performed jointly across multiple nodes. For example, the first part of the inference may be performed by a first node, and the remaining part by a second node. Two-side models can be categorized into several types depending on the training method of the AI / ML model, as follows:

[0115] - First type: AI / ML models can be trained on a single node. In this case, joint training can be performed. The trained model can then be distributed to other nodes / objects.

[0116] - Second type: Joint training of AI / ML models can be performed on multiple nodes / entities (e.g., networks and terminals). Joint training can mean that model generation (e.g., CSI generation part) and model reconstruction (CSI compression by sub-use case) are trained in the same loop for forward activation and backward gradient. In this type, joint training can include both simultaneous training (i.e., model generation training and model reconstruction training are performed simultaneously) and sequential training (i.e., model reconstruction training is performed after model generation training).

[0117] - Third type: Separate training of AI / ML models can be performed on multiple nodes (e.g., networks and terminals). Separate training may mean that training begins sequentially on one node and continues on other nodes. In this case, the first node first performs the AI / ML model and shares the training data with the second node. The second node can then use the shared training data to perform the AI / ML model. For example, training for the CSI generation part may be performed by the terminal, while CSI reconstruction may be performed by the network.

[0118] FIG. 6 illustrates an example of a communication procedure based on an AI / ML model between a first node and a second node to which some examples of the present disclosure may be applied.

[0119] Step 1: In the description of the present disclosure described below, signaling (e.g., information / data / channel / signal, etc.) or a set of signaling between a specific node (e.g., a terminal, a network, etc.) and another node may be interpreted as the signaling or set of signaling of Step 1 used to perform an operation based on an AI / ML model, even if not otherwise mentioned. For example, it may correspond to training data for training (i.e., generation and / or reconstruction) the AI / ML model of FIG. 2, or correspond to inference data used for inference of the AI / ML model, or correspond to feedback for the AI / ML model, etc. If signaling between nodes is not required prior to an operation based on an AI / ML model in the present disclosure, Step 1 may be omitted. If a one-side model is used in the present disclosure, the unidirectional / bidirectional signaling (set) in the present disclosure may correspond to the signaling of Step 1. In addition, when a two-side model is used in the present disclosure, the one-way / two-way signaling in the present disclosure may correspond to one-stage signaling, and also, a repetitive signaling operation may correspond to one-stage signaling.

[0120] For example, in AI / ML model-based beam management (BM), if a base station predicts (i.e., infers) beam(s) with good quality based on an AI / ML model, the base station can receive quality / intensity information for multiple beams from a terminal. Furthermore, if a terminal predicts (i.e., infers) beam(s) with good quality based on an AI / ML model, the terminal can receive multiple beams from the base station.

[0121] Step 2: In the description of the present disclosure described below, an operation (e.g., calculation, selection, prediction, etc.) in a specific node (e.g., terminal, network, etc.) or a joint operation (e.g., calculation, selection, prediction, etc.) in multiple nodes (e.g., terminal, network, etc.) may correspond to a step 2 operation based on one or more functions in the functional framework of the AI / ML model, even if not mentioned separately. For example, it may correspond to training (i.e., generation and / or reconstruction) of the AI / ML model in FIG. 2, or it may correspond to inference of the AI / ML model, etc. When a one-side model is used, an operation performed by a single node in the present disclosure may correspond to a step 2 operation, and also, when a two-side model is used, a joint operation performed by multiple nodes in the present disclosure may correspond to a step 2 operation.

[0122] For example, in an AI / ML model-based BM, the base station can use quality / intensity information for multiple beams received from the terminal as inference data to predict (i.e., infer) beam(s) with good quality based on the AI / ML model. Furthermore, the terminal can measure multiple beams received from the base station and use the measurement results as inference data to predict (i.e., infer) beam(s) with good quality based on the AI / ML model.

[0123] Step 3: In the description of the present disclosure described below, the signaling (e.g., information / data / channel / signal, etc.) or set of signaling between a specific node (e.g., terminal, network, etc.) and another node may be interpreted as a three-step signaling or set of signaling generated due to (as a result of) an operation based on an AI / ML model, even if not otherwise mentioned. For example, it may correspond to an output resulting from inference of the AI / ML model in FIG. 2. If signaling between nodes is not required as a result of an operation based on an AI / ML model in the present disclosure, Step 3 may be omitted. If a one-side model is used in the present disclosure, the one-way / two-way signaling (set) in the present disclosure may correspond to the three-step signaling. In addition, if a two-side model is used in the present disclosure, the one-way / two-way signaling in the present disclosure may correspond to the three-step signaling, and furthermore, a repetitive signaling operation may correspond to the three-step signaling.

[0124] For example, in an AI / ML model-based BM, the base station can transmit to the terminal the beam(s) predicted based on the AI / ML model as candidates so that the terminal can determine the optimal beam. Furthermore, the terminal can report to the base station the beam(s) predicted based on the AI / ML model to request the base station to transmit the candidate beams as candidates for determining the optimal beam.

[0125] THz communication (terahertz communication)

[0126] Data transmission rates can be increased by increasing bandwidth. This can be achieved by utilizing sub-THz communications with wide bandwidths and applying advanced massive MIMO technology. THz waves, also known as sub-millimeter waves, typically refer to the frequency range between 0.1 THz and 10 THz, with corresponding wavelengths ranging from 0.03 mm to 3 mm. The 100 GHz to 300 GHz band (the sub-THz band) is considered a key part of the THz spectrum for cellular communications. Adding the sub-THz band to the mmWave band will increase 6G cellular capacity. Among the defined THz bands, 300 GHz to 3 THz lies in the far infrared (IR) frequency band. While part of the optical band, the 300 GHz to 3 THz band lies at the boundary of the optical band, immediately following the RF band. Therefore, this 300 GHz to 3 THz band exhibits similarities to RF.

[0127] FIG. 7 illustrates an electromagnetic spectrum to which some examples of the present disclosure may be applied.

[0128] Key characteristics of THz communications include (i) the widely available bandwidth to support very high data rates, and (ii) the high path loss at high frequencies (which necessitates highly directional antennas). The narrow beamwidths generated by highly directional antennas reduce interference. The small wavelength of THz signals allows for a significantly larger number of antenna elements to be integrated into devices and base stations operating in this band. This enables the use of advanced adaptive array technologies to overcome range limitations.

[0129] Transmitting system information (e.g., MIB) in a cell in the THz frequency band can be inefficient because the beam width in high-frequency bands narrows, requiring more beam sweeps to cover the entire cell area. This method is particularly inefficient when there are only a few users within the cell.

[0130] FIG. 8 exemplarily illustrates a system information transmission / reception procedure to which some examples of the present disclosure may be applied.

[0131] The example of Fig. 8 is applicable not only to THz communication environments but also to 6G communication environments where THz communication is not applicable. Furthermore, the procedure illustrated in Fig. 8 can be combined with various embodiments of the present disclosure described below. For example, the embodiments described below can be performed based on system information acquired through the procedure illustrated in Fig. 8.

[0132] In step S810, the second node (120) (e.g., base station) can transmit system information of cell #1 through cell #2. For example, the base station provides at least two cells, cell #1 uses a THz frequency band, and cell #2 uses a frequency band other than the THz frequency band. Here, the system information may include at least one of an SFN (system frame number), a PDCCH configuration for SIB1, cell barring, cell re-selection, and subcarrier spacing generated in a higher layer, and may include at least one of an SFN, a half frame indicator, and an SSB index (synchronization signal / PBCH (physical broadcast channel) block index) generated in a physical layer. For this purpose, as an example, cell #1 and cell #2 may have a relationship of a secondary cell and a primary cell.

[0133] At step S830, the first node (110) (e.g., a terminal) can acquire synchronization for cell #1. Synchronization can be acquired by detecting a synchronization signal. Typically, synchronization is acquired before receiving system information. However, since the system information for cell #1 is received from cell #2, synchronization acquisition for cell #1 can be performed after receiving the system information. For example, the terminal can acquire synchronization based on the system information. Alternatively, synchronization acquisition can be performed before step S1010.

[0134] At step S850, the first node (110) may transmit a signal for accessing cell #1. For example, the signal may include a random access preamble. The structure of this signal and the resources (e.g., channels) for transmitting the signal may be identified through system information. Thereafter, at step S1070, the first node (110) and the second node (120) may perform an access procedure for cell #1 and communicate.

[0135] The procedure described with reference to FIG. 8 may be performed when the first node (110) initially connects to cell #1 of the second node (120). Alternatively, a similar procedure may be performed when the first node (110) performs a handover to cell #1 of the second node (120). However, in the case of a handover, the system information of cell #1 may be received from a cell of a base station other than cell #2 of the second node (120).

[0136] Communications in the THz band are expected to experience extremely severe path loss, and to overcome this, terminals and base stations may be required to use very sharp beams. The use of sharp beams means that terminals and base stations must perform beam control in addition to beamforming, and the number of beams used increases significantly. Consequently, it takes a very long time to align the transmit and receive beams between the base station and terminals. Furthermore, if the beam alignment between the base station and terminals is misaligned due to movement or movement of the terminals, frequent re-alignment is required, which can lead to link instability.

[0137] FIG. 9 illustrates an exemplary beam management procedure to which some examples of the present disclosure may be applied.

[0138] Although FIG. 9 illustrates an example of a procedure for searching and / or selecting beams for THz communication, this procedure is not limited to a THz environment and can also be applied to a 6G communication environment where THz communication is not applied.

[0139] Here, beam may be interpreted as other terms having equivalent technical meanings that can distinguish beams, such as 'spatial domain filter', 'spatial domain transmit filter', 'spatial domain receive filter', reference signal (RS) resource that distinguishes beams, SSB index, etc.

[0140] In step S910, the second node (120) (e.g., a base station) can set resources for beam management to the first node (110) (e.g., a terminal). Here, the resources may include at least one of time-frequency resources, channels, and spatial resources (e.g., antenna ports). For example, the base station may utilize a beam search signal (BSS) that is transmitted spatially separated from an existing downlink signal / channel for beam search. Here, the BSS may be transmitted based on a dedicated port for beam search. The dedicated port may be a different port from a port for transmitting an existing downlink signal / channel (e.g., SSB, PDSCH (physical downlink shared channel), etc.). BSS is a term defined for convenience of explanation, and the technical concept according to the present embodiment is not limited to the term BSS itself. For example, a signal transmitted based on a dedicated port defined / set for beam search may be included in the technical concept according to the present embodiment.

[0141] In step S930, the second node (120) (e.g., a base station) transmits measurement signals using a plurality of transmission beams. For example, the measurement signals may include at least one of a reference signal and a synchronization signal. At this time, the measurement signals may be transmitted as many times as the number of beams that require measurement, and may also be transmitted in a multi-beam transmission method that forms a plurality of beams simultaneously to reduce sweeping time. Here, the multi-beam transmission may be performed based on at least one of a multi-panel, a sub-array, and a true time delay (TTD).

[0142] At step S950, a first node (110) (e.g., a terminal) may transmit a feedback signal to a second node (120) (e.g., a base station). The feedback signal may indicate at least one beam selected by the terminal. The terminal may select at least one preferred beam based on the measurement signals received at step S1030.

[0143] In step S970, the first node (110) and the second node (120) can perform communication. For example, the second node (120) can perform transmission to the first node (110) using the reception beam of the first node (110) selected in step S1050. If channel reciprocity is established, the transmission beam of the first node (110) can also be determined through steps S1030 and S1050, so that the transmission operation from the first node (110) can also be performed using a beam that has a reciprocal relationship with the beam selected in step S1050. If channel reciprocity is not established, a procedure including transmission of measurement signal(s) by the first node (110) and transmission of feedback signal(s) by the second node (120) may be performed first to determine the transmission beam of the first node (110).

[0144] Actions related to channel state information (CSI)

[0145] In NR (New Radio) systems, CSI-RS (channel state information-reference signal) is used for time / frequency tracking, CSI computation, L1 (layer 1)-RSRP (reference signal received power) computation, and mobility. Here, CSI computation is related to CSI acquisition, and L1-RSRP computation is related to beam management (BM).

[0146] CSI (channel state information) is a general term for information that can indicate the quality of the wireless channel (or link) formed between the terminal and the antenna port.

[0147] - In order to perform one of the purposes of the CSI-RS as described above, a terminal (e.g., user equipment, UE) receives configuration information related to CSI from a base station (e.g., general Node B, gNB) through RRC (radio resource control) signaling.

[0148] The configuration information related to the above CSI may include at least one of CSI-IM (interference management) resource related information, CSI measurement configuration related information, CSI resource configuration related information, CSI-RS resource related information, or CSI report configuration related information.

[0149] i) CSI-IM resource-related information 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 one resource set includes at least one CSI-IM resource. Each CSI-IM resource is identified by a CSI-IM resource ID.

[0150] ii) CSI resource configuration related information can be expressed as CSI-ResourceConfig IE. The CSI resource configuration related information defines a group including at least one of a non-zero power (NZP) CSI-RS resource set, a CSI-IM resource set, or a CSI-SSB resource set. That is, the CSI resource configuration related information includes a CSI-RS resource set list, and the CSI-RS resource set list can 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.

[0151] Parameters indicating the purpose of CSI-RS (e.g., BM-related 'repetition' parameter, tracking-related 'trs-Info' parameter) can be set for each NZP CSI-RS resource set.

[0152] iii) Information related to the CSI report configuration includes a report configuration type parameter (reportConfigType) indicating time domain behavior and a report quantity parameter (reportQuantity) indicating the CSI-related quantity to be reported. The time domain behavior may be periodic, aperiodic, or semi-persistent.

[0153] - The terminal measures CSI based on configuration information related to the above CSI.

[0154] The above CSI measurement may include (1) a process of receiving a CSI-RS of a terminal, and (2) a process of calculating CSI using the received CSI-RS, which will be described in detail later.

[0155] CSI-RS sets the RE (resource element) mapping of CSI-RS resources in the time and frequency domains by the higher layer parameter CSI-RS-ResourceMapping.

[0156] - The terminal reports the measured CSI to the base station.

[0157] Here, if the quantity of CSI-ReportConfig is set to 'none (or No report)', the terminal can skip the report. However, even if the quantity is set to 'none (or No report)', the terminal can still report to the base station. The case where the quantity is set to 'none' is when aperiodic TRS is triggered or repetition is set. Here, the terminal's report can be skipped only when repetition is set to 'ON'.

[0158] 1) CSI measurement

[0159] The NR system supports more flexible and dynamic CSI measurement and reporting. Here, the CSI measurement may include a procedure for receiving a CSI-RS and computing the received CSI-RS to acquire CSI.

[0160] As a time-domain behavior for CSI measurement and reporting, aperiodic / semi-persistent / periodic channel measurement (CM) and interference measurement (IM) are supported. A 4-port NZP CSI-RS RE pattern is used to configure CSI-IM.

[0161] 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. Furthermore, in the NZP CSI-RS-based IMR, each port emulates an interference layer with (preferred channel and) precoded NZP CSI-RS. This is for intra-cell interference measurement in multi-user cases, primarily targeting MU interference.

[0162] The base station transmits precoded NZP CSI-RS to the terminal on each port of the configured NZP CSI-RS-based IMR.

[0163] The terminal assumes a channel / interference layer for each port in the resource set and measures interference.

[0164] For a channel, if there is no PMI and RI feedback, multiple resources are configured in a set, and the base station or network indicates a subset of NZP CSI-RS resources via DCI for channel / interference measurement.

[0165] Let's take a closer look at resource settings and resource setting configuration.

[0166] 2) Resource setting

[0167] Each CSI resource setting 'CSI-ResourceConfig' contains a configuration for S≥1 CSI resource sets (given by the higher layer parameter csi-RS-ResourceSetList). A CSI resource setting corresponds to a CSI-RS-resourcesetlist, where S represents the number of configured CSI-RS resource sets. Here, the configuration for S≥1 CSI resource sets contains each CSI resource set containing CSI-RS resources (consisting of NZP CSI-RS or CSI-IM) and SS / PBCH block (SSB) resources used for L1-RSRP computation.

[0168] Each CSI resource setting is located in a DL bandwidth part (BWP) identified by the higher layer parameter bwp-id. All CSI resource settings linked to a CSI reporting setting have the same DL BWP.

[0169] The time domain behavior of CSI-RS resources within a CSI resource setting included in the CSI-ResourceConfig IE is indicated by the higher layer parameter resourceType, and can be set to 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 in the numerology of the associated DL BWP, as given by bwp-id.

[0170] When a UE is configured with multiple CSI-ResourceConfigs containing the same NZP CSI-RS resource ID, the same time domain behavior is configured for the CSI-ResourceConfigs.

[0171] When a UE is configured with multiple CSI-ResourceConfigs containing the same CSI-IM resource ID, the same time domain behavior is configured for the CSI-ResourceConfigs.

[0172] One or more CSI resource settings for channel measurement (CM) and interference measurement (IM) are configured via higher layer signaling.

[0173] - CSI-IM resource for interference measurement.

[0174] - NZP CSI-RS resources for interference measurement.

[0175] - NZP CSI-RS resources for channel measurement.

[0176] That is, the CMR (channel measurement resource) can be NZP CSI-RS for CSI acquisition, and the IMR (Interference measurement resource) can be NZP CSI-RS for CSI-IM and IM.

[0177] Here, CSI-IM (or ZP CSI-RS for IM) is mainly used for inter-cell interference measurement.

[0178] And, NZP CSI-RS for IM is mainly used for intra-cell interference measurement from multi-user.

[0179] The UE may assume that the CSI-RS resource(s) for channel measurement and the CSI-IM / NZP CSI-RS resource(s) for interference measurement configured for one CSI reporting are 'QCL-TypeD' per resource.

[0180] 3) Resource setting configuration

[0181] As we have seen, resource setting can mean a resource set list.

[0182] For aperiodic CSI, each trigger state set using the higher layer parameter CSI-AperiodicTriggerState is associated with one or more CSI-ReportConfigs, each of which links to a periodic, semi-persistent, or aperiodic resource setting.

[0183] One reporting setting can be linked to up to three resource settings.

[0184] - When a resource setting is set, the resource setting (given by the higher layer parameter resourcesForChannelMeasurement) is for channel measurement for L1-RSRP computation.

[0185] - When two resource settings are set, the first resource setting (given by the higher layer parameter resourcesForChannelMeasurement) is for channel measurement, and the second resource setting (given by csi-IM-ResourcesForInterference or nzp-CSI-RS -ResourcesForInterference) is for interference measurement performed on CSI-IM or NZP CSI-RS.

[0186] - When three resource settings are set, the first resource setting (given by resourcesForChannelMeasurement) is for channel measurement, the second resource setting (given by csi-IM-ResourcesForInterference) is for CSI-IM based interference measurement, and the third resource setting (given by nzp-CSI-RS-ResourcesForInterference) is for NZP CSI-RS based interference measurement.

[0187] For semi-persistent or periodic CSI, each CSI-ReportConfig is linked to a periodic or semi-persistent resource setting.

[0188] - When one resource setting (given by resourcesForChannelMeasurement) is set, the resource setting is for channel measurement for L1-RSRP computation.

[0189] - When two resource settings are set, the first resource setting (given by resourcesForChannelMeasurement) is for channel measurement, and the second resource setting (given by the higher layer parameter csi-IM-ResourcesForInterference) is used for interference measurement performed on CSI-IM.

[0190] 4) CSI computation

[0191] When interference measurements are performed on CSI-IM, each CSI-RS resource for channel measurements is associated with a CSI-IM resource in the order of the CSI-RS resources and CSI-IM resources within the corresponding resource set. The number of CSI-RS resources for channel measurements is equal to the number of CSI-IM resources.

[0192] And, if interference measurement is performed on NZP CSI-RS, the UE does not expect to be configured with more than one NZP CSI-RS resource in the associated resource set within the resource setting for channel measurement.

[0193] A terminal with the higher layer parameter nzp-CSI-RS-ResourcesForInterference set does not expect more than 18 NZP CSI-RS ports to be set within the NZP CSI-RS resource set.

[0194] For CSI measurement, the terminal assumes the following:

[0195] - Each NZP CSI-RS port configured for interference measurement corresponds to an interference transport layer.

[0196] - All interference transmission layers of the NZP CSI-RS port for interference measurement consider the EPRE (energy per resource element) ratio.

[0197] - Other interference signals on RE(s) of NZP CSI-RS resource for channel measurement, NZP CSI-RS resource for interference measurement or CSI-IM resource for interference measurement.

[0198] 5) CSI Report

[0199] For CSI reporting, the time and frequency resources available to the UE are controlled by the base station.

[0200] 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), an SS / PBCH block resource indicator (SSBRI), a layer indicator (LI), a rank indicator (RI), or an L1-RSRP.

[0201] For CQI, PMI, CRI, SSBRI, LI, RI, and L1-RSRP, the UE is configured by a higher layer with N≥1 CSI-ReportConfig reporting 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 the aperiodicTriggerStateList includes a list of associated CSI-ReportConfigs indicating channel and optionally resource set IDs for interference. Each trigger state in the semiPersistentOnPUSCH-TriggerStateList includes one associated CSI-ReportConfig.

[0202] Additionally, the time domain behavior of CSI reporting supports periodic, semi-persistent, and aperiodic.

[0203] i) Periodic CSI reporting is performed on short PUCCH and long PUCCH. The periodicity and slot offset of periodic CSI reporting can be configured via RRC, and refer to the CSI-ReportConfig IE.

[0204] ii) SP (semi-periodic) CSI reporting is performed on short PUCCH, long PUCCH, or PUSCH.

[0205] In case of SP CSI on short / long PUCCH, the period and slot offset are set by RRC, and CSI reporting is activated / deactivated with a separate MAC CE / DCI.

[0206] In the case of SP CSI on PUSCH, the periodicity of SP CSI reporting is set to RRC, but the slot offset is not set to RRC, and SP CSI reporting is activated / deactivated by DCI (format 0_1). For SP CSI reporting on PUSCH, a separate RNTI (SP-CSI C-RNTI) is used.

[0207] The initial CSI reporting timing follows the PUSCH time domain allocation value indicated in the DCI, and subsequent CSI reporting timing follows the cycle set by RRC.

[0208] DCI format 0_1 ​​contains a CSI request field and can activate / deactivate a specific configured SP-CSI trigger state. SP CSI reporting has the same or similar activation / deactivation mechanism as data transmission on the SPS PUSCH.

[0209] iii) Aperiodic CSI reporting is performed on PUSCH and is triggered by DCI. In this case, information related to the triggering of aperiodic CSI reporting can be transmitted / indicated / configured via MAC-CE.

[0210] For AP CSI with AP CSI-RS, AP CSI-RS timing is set by RRC, and timing for AP CSI reporting is dynamically controlled by DCI.

[0211] NR does not apply the method of dividing CSI into multiple reporting instances (e.g., transmitting in the order of RI, WB PMI / CQI, and SB PMI / CQI) used for PUCCH-based CSI reporting in LTE. Instead, NR restricts specific CSI reporting on short / long PUCCHs and defines CSI omission rules. Furthermore, with respect to AP CSI reporting timing, PUSCH symbol / slot locations are dynamically indicated by DCI. Candidate slot offsets are configured by RRC. For CSI reporting, the slot offset (Y) is configured for each reporting setting. For UL-SCH, the slot offset K2 is configured separately.

[0212] Two CSI latency classes (low latency class, high latency class) are defined from the perspective of CSI computation complexity. Low latency CSI is WB CSI including up to 4 ports Type-I codebook or up to 4-port non-PMI feedback CSI. High latency CSI refers to any CSI other than low latency CSI. For a normal terminal, (Z, Z') is defined in units of OFDM symbols. Here, Z represents the minimum CSI processing time from receiving an aperiodic CSI triggering DCI to performing a CSI report. In addition, Z' represents the minimum CSI processing time from receiving a CSI-RS for channel / interference to performing a CSI report.

[0213] Additionally, the terminal reports the number of CSIs it can calculate simultaneously.

[0214] Activation / deactivation of a semi-persistent CSI-RS / CSI-IM resource set is indicated by the network via a specific MAC CE. The configured semi-persistent CSI-RS / CSI-IM resource set is initially deactivated upon configuration and after a handover. The MAC entity that receives the MAC CE informs the lower layer (e.g., PHY) of information related to the MAC CE.

[0215] Aperiodic CSI trigger state subselection is indicated by the network through a specific MAC CE, and an aperiodic CSI trigger state can be selected from among the configured AP CSI trigger states of the serving cell. The MAC entity that receives the MAC CE indicates information related to the MAC CE to the lower layer (e.g., PHY).

[0216] How to operate a CSI codebook considering the near field

[0217] Regarding the bandwidth for building 6G communication systems, the 7-24 GHz band, known as the upper-mid band, is attracting attention, and channel model studies related to this band have begun in 3GPP Rel-19. Furthermore, the use of mmWave and THz bands for wideband transmission is also being considered. Meanwhile, 5G-advanced communication systems are improving system performance by utilizing a large number of antennas (e.g., 64Tx, 128Tx) compared to existing systems, and this trend is expected to continue and develop in 6G systems. Ultimately, 6G communication systems are likely to be built through the implementation of tens to hundreds of massive antennas in bands above 7 GHz.

[0218] Traditionally, precoders / beamformers were designed assuming a planar wavefront propagation environment in the far field to search for transmit and receive beams. That is, because the distance between the base station and the terminal is significantly greater than the distance between the antennas, a planar wavefront propagation environment could be assumed. However, in ultra-large-scale multi-antenna systems operating in high-frequency bands, as described above, the near-field region between the base station and the user expands, making existing precoders / beamformer designs that assume a far-field environment unsuitable.

[0219] FIG. 10 is a diagram comparing the near-field region according to the number of antennas in a wireless communication system to which the present disclosure can be applied.

[0220] Figure 10 shows examples of the near-field and far-field regions in a multi-antenna system with a relatively small number of antennas and in a very large-scale multi-antenna system, respectively.

[0221] In Fig. 10, the near-field and far-field regions are exemplified when the carrier frequency is f_c=30 GHz and the number of antennas of a base station equipped with a uniform linear array (ULA) is N_t=16 (Fig. 10(a)) and N_t=512 (Fig. 10(b)), respectively. As illustrated in Fig. 10, in the case of an ultra-large-scale multi-antenna system, as the area occupied by the near-field within the coverage area expands, the probability that a user exists in the near-field region increases.

[0222] In the present disclosure, ' / ' means 'and', 'or', or 'and / or' depending on the context. 'Beam' in the present disclosure may mean (source / reference) RS for 'spatial Tx / Rx filter' or 'spatial relation', and may be interpreted as QCL (source / reference) RS or (DL / UL / joint) TCI state or (in case of uplink) spatial relation RS (corresponding ID).

[0223] As described above, future communication systems based on high frequencies and / or large antennas, such as 6G, require MIMO precoders / beams to be designed to take into account not only the far-field characteristics traditionally considered, but also the near-field characteristics. This disclosure proposes methods for designing and operating a CSI codebook that reflects these far-field and near-field characteristics. While the proposed methods are described based on downlink (DL) CSI, they can also be applied to codebooks for uplink (UL) or sidelink (SL).

[0224] In this regard, in the reference literature [M. Cui and L. Dai, "Channel estimation for extremely large-scale MIMO: Far-field or near-field?" IEEE Trans. Commun., vol. 70, no. 4, pp. 2663-2677, Apr. 2022], a channel model in the near-field is proposed, a transform matrix is ​​constructed so that the sparse characteristics of the channel matrix can be well expressed, and a channel estimation method based on this is proposed. In constructing the transform matrix, steering vectors are constructed by sampling angles and distances. Based on the contents of the literature, the characteristics of the near-field channel are analyzed below.

[0225] Assuming a uniform linear array (ULA) of the base station and one terminal receiving antenna, the channel between the base station and the terminal is modeled as in mathematical equation 1 below.

[0226]

[0227] Here, L is the number of distances, α l , θ l , r l represents the gain, spatial angle, and distance of the lth position, respectively. Spatial angle is the actual physical starting point coordinate φ of the lth path l It is defined based on the sine of . In addition, a(·) represents the array response vector. In the far field, the array response vector is expressed as in mathematical equation 2 according to the plane wavefront propagation.

[0228]

[0229] Here, λ represents the signal wavelength, d represents the antenna spacing, and θ represents the spatial angle from the first antenna. Meanwhile, in the near field, the array response vector according to the spherical wavefront propagation is expressed as in mathematical equation 3.

[0230]

[0231] Here, represents the distance to the nth antenna (n=1,2,...,N t ), r represents the distance to the first antenna. That is, the array response vector in the far field depends only on the angle, but the array response vector in the near field is affected by both the angle and the distance.

[0232] Using the Fresnel approximation utilized in the above reference, r n (θ) can be simplified and expressed as in mathematical expression 4.

[0233]

[0234] By substituting this into mathematical expression 3, the element for the nth antenna of the array response vector can be simplified as in mathematical expression 5.

[0235]

[0236] Here, , Assume that.

[0237] In the above formula, f n(θ) is determined only with respect to angle and it can be observed that it has a form in which the phase increases linearly with respect to angle, like the array response vector for the far field. On the other hand, s n (θ,r) can be observed to have a value that changes not only with angle but also with distance, and to have a form in which the phase increases nonlinearly (in proportion to the square) with respect to angle and distance.

[0238] Additionally, we can observe the following about the two components above:

[0239] - The further the distance (r), the larger the second term (term) s n (θ,r) approaches 1 regardless of the angle, so the first term f n (θ) becomes dominant, i.e., it approaches the array response vector for the far field.

[0240] - If the angle is very far from the reference (boresight) direction and the sine value is close to 1 (e.g. ±90 degrees relative to the boresight direction), i.e. If so, the second term s n As (θ,r) approaches 1, the first term f n (θ) becomes dominant, i.e., it approaches the array response vector for the far field.

[0241] - Conversely, the closer the distance and / or the closer to the boresight direction, the higher the second term s n The influence of (θ,r) increases.

[0242] If we expand Equation 5 further, it can be expressed as follows.

[0243]

[0244] Here, , , and the operator ⊙ means Hadamard product (or element-by-element product) between matrices / vectors. The Hadamard product operation between matrices / vectors is equivalent to the Kronecker product between matrices / vectors. It can also be expressed as a sub-matrix of the operation result.

[0245] Although the above analysis assumes ULA, even if the base station antenna is in the form of a uniform rectangular array in a 2D (2-dimensional) planar array, if it is decomposed into horizontal domain channels and vertical domain channels, it can be regarded as ULA in each domain (e.g., first / second domain, first / second parameter), so it can be said to have the same properties as above. The final channel response vector can be expressed as the Kronecker product of the response vector for the horizontal domain and the response vector for the vertical domain. In addition / and, in the case of a cross-polarization antenna, the channel for each polarization (abbreviated as pol) can be expressed as above.

[0246] And / or, if we extend to the case where the terminal has multiple antennas, the channel for each terminal antenna can be expressed as the h vector in Equation 1, so the vectors for each terminal antenna can be stacked to express the channel matrix H. Similarly, the remaining mathematical equations can be applied as equations for each terminal antenna. For example, for the i-th receiving antenna, the angle θ i and distance r i The array response vector according to a near (θ i ,r i) can be expressed as follows. At this time, if it is assumed that the distance between the antennas of the terminal is much closer than the distance between the base station and the terminal, θ i =θ, r i It is also possible to simplify it as =r. That is, it can be assumed that a common array response vector is applied to each terminal antenna.

[0247] Number of base station antennas N t , number of terminal antennas N UE Transmission rank N in a MIMO communication system r Assume that we perform precoding. Assuming linear precoding, N UE The received signal vector y is N as shown in the mathematical expression 7 below. r Х1 transmission vectorx, N t ХN r MIMO precoder W, N UE ХN t It can be expressed as a wireless channel H. Here, the wireless channel can be assumed to be a stacked form in which the vector h of the above mathematical expression 1 is extended to each UE antenna.

[0248]

[0249] Here N UE ×1 Vector z represents interference and noise entering the receiver, and in the above formula, transmission for a single symbol is assumed for convenience. In case of multiple symbol transmission, only the dimensions of vectors x, y, and z need to be expanded by the number of transmission symbols (e.g., if the dimension of vector x is N UE ×N symbols (Extension to matrix) Also, in a multi-carrier system such as OFDM, the above mathematical equation can be a transmission and reception relationship in a specific subcarrier. And it is assumed that transmission power and path loss are reflected in the channel matrix H.

[0250] In the MIMO transmission and reception system as above, the terminal can select a preferred precoding matrix W from the received signal y and report it to the base station. For example, the terminal can select a preferred N as a rank indicator (RI). r The value, precoding matrix indicator (PMI), can be used to report the index related to the preferred W to the base station. In this procedure, the terminal typically uses W as a predefined codebook C={W1,W2,...,W M} is selected and reported. The matrix W is N for each layer. t The Х1 beamforming vector is configured by stacking the total number of layers, and it may be desirable for the precoding vector for each layer to be in a form that matches the array response vector for the wireless channel. In particular, when rank = 1, the Hermitian / conjugate of the array response vector may be the optimal configuration (e.g., , ρ is a scaling value that takes into account the transmission power, normalization, etc.) That is, the vector shape that is the same as the channel response vector but with the opposite sign of the phase may be optimal. In the case of rank > 1, it may be good for the beamformer for each layer to correspond to rays (clusters) with excellent SINR (signal-to-interference plus noise ratio) in the channel between the base station and the terminal (e.g., in the direction of reflectors or scatterers). However, in rank > 1 transmission, not only the reception quality of each layer but also the interference between layers must be considered, and the transmission power distribution between layers also affects the performance. Therefore, the optimal precoder W may differ depending on which performance metric, such as capacity, throughput, signal-to-noise ratio (SNR), signal-to-interference ratio (SIR), SINR, and error rate, is to be optimized for the MIMO precoder, and the optimal precoder W may also differ depending on whether it is a single user (SU) or multi-user (MU) perspective. For example, a zero-forcing precoder (e.g., ), MMSE precoder (e.g., ), SVD (singular value decomposition) precoder, etc. In LTE / NR systems, considering the feedback payload size, performance, computational complexity, etc., in many cases, the codebook is designed based on a DFT (Discrete Fourier Transform) matrix that reflects the characteristics of the far-field beam (e.g., the phase varies linearly with respect to the antenna port index) as in Equation 2 in the precoding vector for each layer while having orthogonality between the precoding vectors of each layer (e.g., the precoding vector for each layer has the same magnitude for each element, the phase varies linearly with respect to the antenna-related index, and the precoding vectors of different layers are orthogonal).

[0251] In addition, considering the planar / 2D array structure of the base station and the cross-polarization antenna in the NR / LTE system, the codebook was designed by extending the DFT matrix / vector-based design method to apply it to each horizontal / vertical dimension and each polarization. For example, the precoding matrices constituting the codebook are configured in the following form.

[0252]

[0253] Here, the two diagonal submatrices of W1 correspond to the antenna ports for the corresponding polarizations, and each submatrices is generated by the Kronecker product of the vertical beam vector(s) and the horizontal beam vector(s). These W v W hConceptually, L 3D beam vectors are selected / generated and stacked as a combination of (vertical beam, horizontal beam) (however, in the actual standard, the expression vertical / horizontal is not defined, and DFT beams are generated and multiplied for the first and second dimensions). Here, the vector(s) corresponding to the vertical / horizontal beam reflect the characteristics of the far-field beam vector in Equation 2. These characteristics are the characteristics that the coefficients are linearly proportional to the base station antenna port index n and the phase changes (e.g., e j(na+b)where α and β are values ​​that do not change with n (e.g., b=0). As described above, DFT vectors / matrices are often used to easily generate vector sets with these characteristics (also, DFT matrices are often used because of their characteristic of making it easy to select / generate orthogonal beam vectors when rank>1). Each beam vector generated by W1 is expressed as a combination of a vertical beam and a horizontal beam (the value of L is set by the base station). W2 can select some of the L beam vectors generated by W1 for each polarization and then perform co-phasing to match the phases of the beams selected for each polarization (e.g., NR Type-I codebook). Alternatively, in order to support a higher resolution codebook, W2 can generate a beam vector by synthetically combining the beam vectors generated by W1 (e.g., NR Type-II codebook). For Rank 2 or higher, beam vectors can be selected for each layer, or a beam matrix in the form of as many vectors as the number of layers being stacked can be selected (at once). In the case of a wideband system, precoding matrix information must be fed back for each frequency unit (e.g., subband, FD basis), but in order to reduce the amount of such feedback, the index(es) related to W1 (e.g., index related to which L beams to generate) can be fed back as a single / common index(es) for the entire band, and the index(es) related to W2 (e.g., index related to selection / synthesis / co-phasing for the L beams) can be fed back in the frequency unit (e.g., subband, FD basis (e.g., FD compression codebook introduced in NR Rel-17)).Note that in Equation 8, it is assumed that the same beam vector / matrix is ​​generated for each polarization, but different beam vectors / matrices may be generated / selected for each polarization. In this case, the two diagonal submatrices of W1 are different W. v and / orW h It can be composed of. And / or, the function in W2 (e.g., beam selection / synthesis / co-phasing) can also be the same or different depending on the polarization. For reference, the FD (frequency domain) compression codebook introduced in Rel-17 NR is an addition of matrix W3 related to transform / selection in the dual codebook structure to the FD basis, and the shape / characteristics of the beam vector / matrix generated in each FD basis are the same as the characteristics of the 2D / planar cross-pol antenna array.

[0254] Unlike the above methods, an explicit feedback method that feeds back information about the wireless channel H instead of information about the precoding matrix W can also be considered. Explicit feedback methods can be variously considered, such as quantizing each coefficient of the wireless channel H and transmitting it, or transforming the wireless channel H into some basis and then transmitting the coefficients (e.g., transmitting eigenvectors and eigenvalue(s), transmitting selection information about a spatial domain basis and coefficient information in the basis, etc.). In addition, explicit feedback methods can transmit wireless channel-related information (e.g., covariance matrix, channel matrix averaged over time / frequency windows, (average) received power, Doppler property, delay spread, time / frequency offset, etc.) in addition to or instead of the above information(s).

[0255] In this disclosure, based on the characteristics of the far-field / near-field channels and the characteristics of the NR / LTE codebook analyzed above, the following method is proposed to support channel / beamforming / precoding for the near-field as well as the far-field.

[0256] Example 1: When a terminal reports CSI to a base station, the terminal may feed back first index(es) and second index(es) for a precoding matrix (e.g., W) or a matrix related to a wireless channel (e.g., H, filtered H (e.g., mean(H) (mean of H), var(H) (variance of H), eigenvectors / eigenvalues ​​of H, etc.)) to the base station.

[0257] Here, the first index(es) may mean index(es) related to the first parameter(s) constituting the first matrix F or the precoding / channel matrix, and the second index(es) may mean index(es) related to the second matrix S or the second parameter(s) constituting the precoding / channel matrix.

[0258] In other words, the first index(es) may be index(es) related to the far field, and the second index(es) may be index(es) related to the (far field and) near field.

[0259] In addition, the first matrix F or the first parameter(s) may have the same / similar characteristics as the matrix / parameter(s) constituting the existing LTE / NR codebook or the characteristics of the far-field codebook / channel. The second matrix S or the second parameter(s) may be configured to include other parameter(s) in addition to the matrix / parameter(s) constituting the LTE / NR codebook, and may reflect the characteristics of the near-field codebook / channel (either through combination with the first matrix F or by the second matrix S alone). For example, the vector(s) constituting the first matrix F (e.g., N for W) r Vectors,N for H UE The coefficients (or elements) of the first parameter(s) or the first vectors have a characteristic (e.g., e) whose phase changes linearly proportionally as the base station antenna port index n increases (or decreases). j(na+b) The shape, where a and b, can be designed / set based on vector(s) / matrix(s) having values ​​that do not change with n (e.g., b=0). And, the coefficients (or elements) of the vector(s) or second parameter(s) constituting the second matrix have a characteristic that the phase changes in proportion to the square of the index n as the base station antenna port index n increases (or decreases) (e.g., The shape can be designed / set based on vector(s) / matrix(s) having a shape (where δ, ε are values ​​that do not change with n).

[0260] And / or, the first matrix(s) may be designed / configured based on a DFT matrix, and the second matrix(s) may be designed / configured based on a non-DFT matrix (e.g., generated based on a CAZAC (Constant Amplitude Zero AutoCorrelation) sequence, a DCT / DST (discrete cosine / sine transform) matrix, generated by an operation (e.g., Kronecker product) of two DFT / DCT / DST matrices, a householder matrix, composed of vectors based on computer searching (e.g., composed of vectors found based on a Chordal distance minimization / maximization criterion)). Alternatively, the second matrix may be a DFT matrix generated with an oversampling factor different from that of the first matrix.

[0261] Additionally, as can be seen in Equation 5 / 6, the phase scaling factor δ value for the coefficients (or elements) of the vector(s) or the second parameter(s) constituting the second matrix may have a characteristic of being inversely proportional to a specific parameter r (related to the distance between the base station and the terminal or the base station and the reflector / scatter, etc.). Here, the parameter r (since it is a parameter related to the distance) may be a value generated as a new parameter / factor different from existing parameters related to the base station antenna (e.g., values ​​of N1, N2, O1, O2, where N1 and N2 are the number of base station antenna ports in each dimension, and O1 and O2 are oversampling factors related to beam generation for each dimension). Additionally, the phase scaling factor δ value may have a characteristic of having a corresponding value that varies depending on the index related to the selected beam (e.g., the index related to W1 and / or W2). Conceptually, the generated / selected beam may have a characteristic that the boresight angle φ decreases as it approaches from 0 to ±90 degrees. In a dual codebook structure such as Equation 8, different δ values ​​may be applied depending on the set of (L) beams generated by W1. And / or, different δ values ​​may be applied depending on the beam selected / synthesized by W2. For example, may have a relationship such as . Here, each parameter may be composed of a single or multiple parameters. For example, the θ value may be expressed by the N1 / N2 / O1 / O2 values ​​and the selected index(es) in the corresponding 2D DFT beam set.

[0262] In the above example, the δ value can be sampled to construct the codebook, or both the θ value and the r value can be sampled.

[0263] And / or, if rank > 1, the vectors for each layer or UE antenna port constituting the second matrix or the vector(s) determined by the second parameter(s) may have a characteristic in which different scaling values ​​(δ) are applied. This is because, due to the characteristics of the near-field, not only the target angle but also the distance may be different for each layer.

[0264] As an example for the above embodiment 1, when the terminal selects the first index(es) and the second index(es), a precoding matrix or a matrix related to a wireless channel may be selected (e.g., PMI / RI is selected) by forming a Hadamard product or a Kronecker product of the first matrix or some of the matrices constituting the first matrix and the second matrix or some of the matrices constituting the second matrix. For example, if the first matrix is ​​expressed as a matrix product of N (F=F1F2...F N ), when the second matrix is ​​expressed as a product of M matrices (S=S1S2...S M ), can be composed of N first indices and M second indices. Also, if N or M is 1, the matrix can be expressed as a single index. For example, the precoding matrix W or the wireless channel matrix H can be F⊙S, (F1⊙S)F2...F N ,F1(F2⊙S1)...F N , (F1⊙S1)(F2⊙S2)...(F N ⊙S N ) can be expressed in various forms, such as:

[0265] In this disclosure, for the convenience of explanation, when describing based on matrices F and S, F is F v ,F h RoS is S v ,S h It can be understood as a replacement for .

[0266] In the above description, the Hadamard product or Kronecker product operation of the first matrix and the second matrix can be understood as the same as the addition / subtraction operation between the phase components in the exponential of each element of the matrix. As described above, the scaling factor δ for the phase component of the second matrix approaches 0 as the distance between the base station and the terminal increases and as the terminal is located in a direction away from the boresight, and accordingly, the values ​​of all elements of the second matrix become similar / identical (e.g., a matrix in which all elements are 1). In other words, the influence of the second matrix on the final precoding matrix or channel matrix becomes smaller. In other words, the precoding / channel matrix becomes almost identical / similar to the first matrix. Based on this characteristic, unlike the methods of the above examples, the precoding / channel matrix can be configured by selecting or combining the first matrix that reflects the far-field characteristics and the second matrix that reflects the near-field characteristics. If the examples described above assume that the near-field channel characteristics are reflected when the first and second matrices are combined, the above method may differ in that it is designed to reflect the near-field channel characteristics using only the second matrix. For example, it can be defined as W = αF + (1-α)S, and when the far-field channel characteristics are strong, an α value of 1 or close to 1 can be used, and when the near-field characteristics are strong, an α value of 0 or close to 0 can be used. Alternatively, only one of the two matrices can be selectively used.

[0267] Example 1-1: In Example 1, a precoding matrix or a matrix related to a wireless channel can be constructed through operations on the first matrix and the second matrix.

[0268] In the first method, a precoding matrix or a matrix related to a wireless channel can be constructed by Hadamard multiplying (part of) the first matrix and (part of) the second matrix and Kronecker multiplying (part of).

[0269] In a second method, a precoding matrix or a matrix related to a wireless channel can be constructed by combining / selecting (part of) the first matrix and (part of) the second matrix.

[0270] In the first method, the reflection ratio of the far-field characteristics and the near-field characteristics can be adjusted by the above-described phase scaling factor δ value, and in the second method, by the combining factor α value.

[0271] Here, the factors that control the proportion between the first matrix / parameter / index and the second matrix / parameter / index (e.g., the scaling factor δ, the combining factor α in the examples described above) can be set layer / rank-commonly or layer (group) / rank (group)-specifically. When set layer (group) / rank (group)-specifically, different factors can be set / reported for each layer (group) or rank (group). In addition, when the distance between the base station and the terminal is greater than a certain threshold (e.g., r > Rayleigh distance), the factors can be defined to have specific values ​​such that only the matrices / parameters for the far field are applied (e.g., δ=0, α=1). Conversely, when the distance is less than a certain threshold, the factors can be defined to have specific values ​​such that only the matrices / parameters for the near field are applied (e.g., δ=large value or a=0, α=0).

[0272] Additionally, if the far-field characteristic is strong, it may be desirable to allocate more bits to the first index(es) than to the second index(es) for feedback, and vice versa, if the near-field characteristic is strong, it may be desirable to allocate more bits to the second index(es) for feedback. A detailed explanation of this is as follows.

[0273] Example 1-2: In Example 1, the number of bits (or ratio of bits) allocated to the first index(es) and the second index(es) can be set / indicated by the base station or determined by the terminal and reported to the base station.

[0274] For example, the first index(es) is reported by default, and whether or not to report the second index and the amount / ratio of reporting information can be optionally instructed / set by the base station or selected / reported by the terminal.

[0275] Here, when the base station sets / indicates the number of bits (or the ratio of the number of bits), it may be an effective method when the base station can determine / infer the distance / direction of the terminal, etc. through uplink sounding, positioning techniques, etc. For example, the amount / ratio of information may be determined by parameters related to the distance and / or angle between the base station and the terminal.

[0276] On the other hand, if the terminal reports the number of bits (or the ratio of the number of bits), the terminal can determine the number of bits (or the ratio of the number of bits) of the first index(es) and the second index(es) by understanding the near-field / far-field channel characteristics and adjust / determine the number of bits (or the ratio of the number of bits) of the first index(es) and the second index(es) accordingly and report it to the base station. Such a report may be an independent (e.g., stand-alone) report or a report performed together with a CSI report. If performed together with a CSI report, it may be more desirable to report as part 1 UCI when encoding multi-part UCI since the uplink control information (UCI) payload configuration is changed by the information.

[0277] Considering a planar / 2D array of base stations, the features for the first matrix / vector and the second matrix / vector described above can be represented for each antenna port index (e.g., horizontal antenna port index, vertical antenna port index) for each dimension. The first matrix / second matrix can be constructed by computing (e.g., Kronecker product) the subvectors / submatrices composed of the corresponding features as in Equation 8. In addition, when considering a cross-polar antenna, the features can be represented for each antenna port group corresponding to each polarization. For example, in a dual codebook structure as in Equation 8, the features mentioned above can be represented as W v and / orW h may appear in. Also,W v and / orW h can be generated through the Hadamard product or Kronecker product of the first matrix and the second matrix. Considering the planar array and cross-pol antenna structure as in Equation 8, W v and / orW h The above proposed structure can be applied to the following. An example is as follows.

[0278]

[0279] Here, W v =F v ⊙S v ,W h =F h ⊙S h It is assumed that it consists of . As other examples, the following structures can also be considered.

[0280]

[0281]

[0282] Alternatively, the elements of the second matrix can be represented as separate matrices. Examples of this are given below.

[0283] -W=W1W2=F1SW2

[0284] -W=W1W2=F1W2S

[0285] -W=W1W2=SF1W2

[0286] In the above example, the same precoder is assumed for each polarization (pol), but different precoders may be used for each pol. For example, instead of Equation 9, Equation 12 below, which generates different spatial domain (SD) basis sets for each pol, may be applied (in Equation 12, matrices with ' denote matrices for the second polarization (second pol). In the description of the present disclosure, for the sake of convenience of explanation (unless otherwise stated), indices related to pol are omitted, but this is not a limitation, and may be applied as pol-common matrices / parameters or pol-specific matrices / parameters.

[0287]

[0288] In the case of applying Example 1-2 in the above structure, the second matrix / parameter / index may be set / defined to be applied only in one of the vertical (v)-domain and the horizontal (h)-domain, or may be applied in both domains, but the number of bits (or the ratio of the number of bits) in the v-domain and the h-domain may be set by the base station or reported by the terminal to adjust (e.g., the base station may set / indicate the domain to be applied). Alternatively, the second matrix / parameter / index may be defined / set only in a specific domain as a standard. If applied only in one domain, the matrix for the other domain in the above mathematical equations may not be applied. For example, if mathematical equation 9 is applied only in the v-domain, the second matrix may be set / defined to be applied as in mathematical equation 13 below. Or, when mathematical equation 9 is applied, S hIt can be set / defined to apply to a matrix in which all elements have the same value, such as an all-one matrix (a matrix in which all elements are 1), or an identity matrix (e.g., expressed as the product of the first matrix and the second matrix).

[0289]

[0290] In the above examples, F v WowF h is a feature of the first matrix (e.g., generated based on the DFT matrix, such as the LTE / NR codebook), and S v ,S h ,S may be a matrix exhibiting the characteristics of the second matrix mentioned above (e.g., non-DFT, phase increasing as a square).

[0291] When performing the 2nd index(es) as wideband reporting, candidates can be selected by considering distances when selecting L beams with the index for W1. On the other hand, when performing the 2nd index(es) as subband reporting, it can be understood that after selecting L beam candidates for various distances with the index for W1, when performing combining / synthesizing / selecting / co-phasing for the L beams with the index for W2, beams (combinations) for different distances are considered for each subband. From this perspective, when feeding back the 2nd index for the 2nd matrix per subband (or FD / TD-basis), it may be more desirable to apply a larger L value than when not feeding back the 2nd index. For example, instead of the L value, L multiplication or addition of X value may be applied (e.g., X value may be a prescribed / defined value, a value set by the base station, or a value determined based on a rule (e.g., determined by a value related to the distance / angle from the base station)), or the candidate values ​​of L value may be configured to include larger values.

[0292] In the above methods / examples, it is assumed that a matrix S that can reflect the characteristics of the near field is separately defined along with a matrix F that reflects the characteristics of the far field. However, instead of defining a separate matrix as above, a component for the near field can be defined together with a component for the far field in the formula related to the precoding / channel matrix. In this case, the first index can mean a component that has the beam characteristics of the existing codebook (e.g., a first-order term whose phase changes linearly as the antenna port index n increases / decreases), and the second index can mean a component that deviates from the above characteristics (e.g., a component whose phase changes nonlinearly as the antenna port index n increases / decreases, a term whose phase changes as the square of the phase as the antenna port index n increases / decreases). For example, coefficients generated based on a CAZAC sequence, etc. or In a vector / matrix composed of coefficients of the form, the second parameter may be a value related to the δ value and the first parameter may be a value related to the a value.

[0293] In the examples related to W=W1W2 described above, it was assumed that beam vector candidates were generated by reflecting the near-field characteristics. Here, in addition to the method for generating beam vector candidates, W2, which is responsible for combining / selecting the L beam vectors selected from W1, can be configured by dividing it into parameters / matrix for beam selection / combination in the angular domain and parameters / matrix for beam selection / combination in the distance domain.

[0294] Example 1-3: The first indices may be composed of 1-1 index(es) related to a wideband and 1-2 index(es) related to a subband / FD-domain, respectively, and the second indices may be composed of 2-1 index(es) related to a wideband and 2-2 index(es) related to a subband / FD-domain. Here, the 1-1 / 2-1 index(es) generate a beam vector set, and the 1-2 / 2-2 index(es) combine / select / co-phasing the beam vector sets generated by the 1-1 / 2-1 index(es).

[0295] In embodiment 1-3, the 2-1 index(es) may have a feature that is designed based on sampling parameters (e.g., parameters related to distance) different from the sampling parameters considered in the 1-1 index(es) (e.g., angle, N1 / N2 / O1 / O2 values ​​in the NR codebook). And / or, the 2-2 index(es) may perform selection / combination / co-phasing of beam vectors together with the 1-2 index(es).

[0296] The above 2-1 index(es) and 2-2 index(es) may only be applied to one of the two. The 2-2 index(es) may perform additional beam selection / combination for the beam vectors selected from the 1-2 index(es). Alternatively, the 1-2 index(es) may perform the function of selecting beam vectors through the 2-2 index(es) and performing additional beam selection / combination for the beam vectors thus selected. The parameter(s) of the beam vectors selected / combined in the 2-2 index(es) may be different from the parameter(s) of the beam vectors selected / combined in the 1-2 index(es). For example, L beam vectors selected from W1 are w1,...,w L When , the parameters that constitute each beam vector are w iIf we distinguish as (θ,r), the 1st-2nd index(es) can perform selection / combination related to parameter θ, and the 2nd-2nd index(es) can perform selection / combination related to parameter r.

[0297] When constructing the above codebook, each matrix / vector can construct F(θ) and S(θ,r) by sampling the component θ or φ for angle and the component r for distance (θ=[θ1...θ Nr ],r=[r1...r Nr ], θ i , r iis a factor for generating the ith vector constituting the corresponding codeword (matrix). Uniform or non-uniform sampling can be performed on the θ or φ values ​​for the angles. Here, the angular values ​​can be configured by considering the maximum / minimum angular values ​​considered by the system. For example, these maximum / minimum values ​​can be values ​​set by the base station or values ​​specified by the standard. Alternatively, the terminal can report / propose the relevant values ​​to the base station. As an example of a non-uniform method, sampling in the boresight direction can be performed more densely considering the distribution of the terminals. Here, the boresight direction can be an index close to the first / last index in the selection index for the beam set generated by the codebook, or an index close to the middle value among all indices. Sampling for the r value can also be configured in the codebook through uniform or non-uniform sampling. As an example of a non-uniform method, as suggested in the above-mentioned paper, sampling may be performed more densely as the distance is closer (e.g., sampling in proportion to the 1 / s value, s=0,1,...). Here, the distance values ​​may be configured considering the maximum / minimum distance considered by the system. For example, the maximum / minimum values ​​may be values ​​set by the base station or values ​​specified by the standard. Alternatively, the terminal may report / propose the relevant values ​​to the base station. In the case of the above sampling methods, in the case of a planar / 2D array, sampling may be performed for each dimension (e.g., vertical component, horizontal component) or for a combination of them (e.g., component = angle or distance). In the case of cross-polarization, sampling may be performed for each polarization (pol) or for a combination of components for the two polarizations (poles).

[0298] As observed in Figure 10 and the mathematical equations, during this sampling process, the near-field tends to decrease as one moves away from the boresight direction. Considering this phenomenon, the following method is proposed to more efficiently construct the codebook.

[0299] Example 1-4: The number of bits / amount of information assigned to the second index(es) may vary depending on the selected first index(es). Or / and, the number of bits / amount of information assigned to the first index(es) may vary depending on the selected second index(es).

[0300] For example, if codeword(s) / matrix(s) / vector(s) corresponding to an angle close to the boresight direction are selected by the first index(es), more bits / information amount may be allocated to the second index(es), and if codeword(s) / matrix(s) / vector(s) corresponding to an angle far from the boresight direction are selected, less bits / information amount may be allocated to the second index(es). As another example, if codeword(s) / matrix(s) / vector(s) corresponding to a far distance are selected by the second index(es), more bits / information amount may be allocated to the first index(es) (since it is likely to be a far-field terminal), and if codeword(s) / matrix(s) / vector(s) corresponding to a near distance are selected, less bits / information amount may be allocated to the first index(es). In this process, the variability of the overall amount of feedback can be reduced by increasing the number of bits / information amount for the second index(es) to decrease the number of bits / information amount for the first index(es), and vice versa, by decreasing the number of bits / information amount for the second index(es) to increase the number of bits / information amount for the first index(es). Furthermore, considering the variable amount of feedback information, information related to the number of bits / information amount of the first index(es) and / or the second index(es) (e.g., number of bits, range of bits, bit ratio between the first / second indices, etc.) can be reported in part-1 using a multi-part UCI encoding technique such as 2-part encoding.

[0301] In connection with the methods proposed in this disclosure, terminal capability information related to the codebook settings supported by the terminal may be transmitted to the base station. For example, whether the terminal supports codebooks (parameters) related to the near field / second matrix / second index(es), the range of supported parameters, etc. may be reported to the base station.

[0302] FIG. 11 is a diagram illustrating the operation of a UE for a method for transmitting and receiving channel state information according to one embodiment of the present disclosure.

[0303] FIG. 11 illustrates the operation of a UE based on the previously proposed method. The example in FIG. 11 is provided for convenience of explanation and does not limit the scope of the present disclosure. Some of the step(s) illustrated in FIG. 11 may be omitted depending on the situation and / or setting. In addition, the UE in FIG. 11 is only an example and may be implemented as the device illustrated in FIG. 3 below. For example, the processor (102 / 202) in FIG. 3 may control the transceiver (106 / 206) to transmit and receive channels / signals / data / information, etc., and may also control the storage of transmitted or received channels / signals / data / information, etc., in the memory (104 / 204).

[0304] Referring to FIG. 11, the UE receives configuration information related to channel state information (CSI) reporting from the base station (S1101).

[0305] Here, the configuration information for the proposed method described above may be included in relation to the CSI report.

[0306] The UE receives CSI-RS from the base station (S1102).

[0307] Here, the UE can receive CSI-RS through one or more antenna ports on one or more CSI-RS resources. For example, the UE can receive CSI-RS through one or more antenna ports on one or more CSI-RS resources based on configuration information related to the CSI-RS resources. In this case, although not illustrated in FIG. 11, the UE can receive configuration information related to the CSI-RS resources from the base station. In this case, the configuration information related to the CSI report can include configuration information related to the CSI-RS resource associated with the CSI report.

[0308] The UE transmits channel state information (CSI) (feedback / report) to the base station (S1103).

[0309] Here, channel state information (CSI) (feedback / report) may be transmitted via an uplink physical layer channel (e.g., PUCCH or PUSCH). In addition, the CSI may include at least one of PMI, CQI, RI, and LI.

[0310] The CSI reported by the UE to the base station can be derived / generated based on the proposed method described above using CSI-RS.

[0311] The CSI may include a first index associated with a first precoding matrix or a channel-related matrix and a second index associated with a second precoding matrix or a channel-related matrix. For example, if the first index is associated with a first precoding matrix and the second index is associated with a second precoding matrix, the first index and the second index may correspond to indices of a codebook for indicating the precoding matrix(s). Conversely, if the first index is associated with a first channel-related matrix and the second index is associated with a second channel-related matrix, the first index and the second index may be associated with vectors or parameters constituting the first channel-related matrix and the second channel-related matrix, respectively.

[0312] In this case, the precoding matrix or channel-related matrix can be derived from at least one of the first precoding matrix or channel-related matrix and the second precoding matrix or channel-related matrix. For example, the precoding matrix or channel-related matrix can be derived i) by performing a Hadamard product or a Kronecker product of all or a part of the first precoding matrix or channel-related matrix and all or a part of the second precoding matrix or channel-related matrix, or ii) by combining or selecting all or a part of the first precoding matrix or channel-related matrix and all or a part of the second precoding matrix or channel-related matrix.

[0313] For example, the first precoding matrix or channel-related matrix may have far-field characteristics, and the second precoding matrix or channel-related matrix may have near-field characteristics.

[0314] As another example, elements (or coefficients) of one or more vectors constituting the first precoding matrix or channel-related matrix may have their phases changed linearly in proportion to the antenna port index of the base station, and elements (or coefficients) of one or more vectors constituting the second precoding matrix or channel-related matrix may have their phases changed in proportion to the square of the antenna port index of the base station.

[0315] Additionally, a scaling factor for elements (or coefficients) of one or more vectors constituting the second precoding matrix or channel-related matrix may be inversely proportional to a parameter related to the distance from the base station (e.g., a parameter related to the distance between the base station and the UE / reflector / scatter, etc.).

[0316] Additionally, the scaling factors for the elements (or coefficients) of one or more vectors constituting the second precoding matrix or the channel-related matrix may have different values ​​depending on the index associated with the beam selected by the terminal (e.g., the index associated with W1 and / or W2).

[0317] Additionally, a scaling factor for elements (or coefficients) of one or more vectors constituting the second precoding matrix or channel-related matrix may have a different value applied to each of the one or more vectors.

[0318] Additionally, the number of bits or the ratio of the number of bits allocated to the first index and the second index may be i) set by the base station or ii) determined by the terminal and reported to the base station.

[0319] Additionally, the first index may include a 1-1 index related to a wideband and a 1-2 index related to a subband, and the second index may include a 2-1 index related to a wideband and a 2-2 index related to a subband.

[0320] Additionally, i) the number of bits allocated to the second index or the amount of information indicated by the second index may be determined based on the value of the first index, or ii) the number of bits allocated to the first index or the amount of information indicated by the first index may be determined based on the value of the second index.

[0321] FIG. 12 is a diagram illustrating the operation of a base station for a method for transmitting and receiving channel state information according to one embodiment of the present disclosure.

[0322] FIG. 12 illustrates the operation of a base station based on the previously proposed method. The example in FIG. 12 is provided for convenience of explanation and does not limit the scope of the present disclosure. Some of the step(s) illustrated in FIG. 12 may be omitted depending on circumstances and / or settings. Furthermore, the base station in FIG. 12 is merely an example and may be implemented as the device illustrated in FIG. 3 below. For example, the processor (102 / 202) in FIG. 3 may control the transceiver (106 / 206) to transmit and receive channels / signals / data / information, etc., and may also control the storage of transmitted or received channels / signals / data / information, etc., in the memory (104 / 204).

[0323] Referring to FIG. 12, the base station transmits configuration information related to channel state information (CSI) reporting to the UE (S1201).

[0324] Here, the configuration information for the proposed method described above may be included in relation to the CSI report.

[0325] The base station transmits CSI-RS to the UE (S1202).

[0326] Here, the base station can transmit CSI-RS through one or more antenna ports on one or more CSI-RS resources. For example, the base station can transmit CSI-RS through one or more antenna ports on one or more CSI-RS resources based on configuration information related to the CSI-RS resources. In this case, although not illustrated in FIG. 12, the base station can receive configuration information related to the CSI-RS resources from the UE. In this case, the configuration information related to the CSI report can include configuration information related to the CSI-RS resource associated with the CSI report.

[0327] The base station receives channel state information (CSI) (feedback / report) from the UE (S1203).

[0328] Here, channel state information (CSI) (feedback / report) may be transmitted via an uplink physical layer channel (e.g., PUCCH or PUSCH). In addition, the CSI may include at least one of PMI, CQI, RI, and LI.

[0329] The CSI reported by the UE to the base station can be derived / generated based on the proposed method described above using CSI-RS.

[0330] The CSI may include a first index associated with a first precoding matrix or a channel-related matrix and a second index associated with a second precoding matrix or a channel-related matrix. For example, if the first index is associated with a first precoding matrix and the second index is associated with a second precoding matrix, the first index and the second index may correspond to indices of a codebook for indicating the precoding matrix(s). Conversely, if the first index is associated with a first channel-related matrix and the second index is associated with a second channel-related matrix, the first index and the second index may be associated with vectors or parameters constituting the first channel-related matrix and the second channel-related matrix, respectively.

[0331] In this case, the precoding matrix or channel-related matrix can be derived from at least one of the first precoding matrix or channel-related matrix and the second precoding matrix or channel-related matrix. For example, the precoding matrix or channel-related matrix can be derived i) by performing a Hadamard product or a Kronecker product of all or a part of the first precoding matrix or channel-related matrix and all or a part of the second precoding matrix or channel-related matrix, or ii) by combining or selecting all or a part of the first precoding matrix or channel-related matrix and all or a part of the second precoding matrix or channel-related matrix.

[0332] For example, the first precoding matrix or channel-related matrix may have far-field characteristics, and the second precoding matrix or channel-related matrix may have near-field characteristics.

[0333] As another example, elements (or coefficients) of one or more vectors constituting the first precoding matrix or channel-related matrix may have their phases changed linearly in proportion to the antenna port index of the base station, and elements (or coefficients) of one or more vectors constituting the second precoding matrix or channel-related matrix may have their phases changed in proportion to the square of the antenna port index of the base station.

[0334] Additionally, a scaling factor for elements (or coefficients) of one or more vectors constituting the second precoding matrix or channel-related matrix may be inversely proportional to a parameter related to the distance from the base station (e.g., a parameter related to the distance between the base station and the UE / reflector / scatter, etc.).

[0335] Additionally, the scaling factors for the elements (or coefficients) of one or more vectors constituting the second precoding matrix or the channel-related matrix may have different values ​​depending on the index associated with the beam selected by the terminal (e.g., the index associated with W1 and / or W2).

[0336] Additionally, a scaling factor for elements (or coefficients) of one or more vectors constituting the second precoding matrix or channel-related matrix may have a different value applied to each of the one or more vectors.

[0337] Additionally, the number of bits or the ratio of the number of bits allocated to the first index and the second index may be i) set by the base station or ii) determined by the terminal and reported to the base station.

[0338] Additionally, the first index may include a 1-1 index related to a wideband and a 1-2 index related to a subband, and the second index may include a 2-1 index related to a wideband and a 2-2 index related to a subband.

[0339] Additionally, i) the number of bits allocated to the second index or the amount of information indicated by the second index may be determined based on the value of the first index, or ii) the number of bits allocated to the first index or the amount of information indicated by the first index may be determined based on the value of the second index.

[0340] The embodiments described above are combinations of components and features of the present disclosure in a predetermined form. Each component or feature should be considered optional unless explicitly stated otherwise. Each component or feature may be implemented without being combined with other components or features. Furthermore, it is also possible to form embodiments of the present disclosure by combining some components and / or features. The order of operations described in the embodiments of the present disclosure may be changed. Some components or features of one embodiment may be included in another embodiment or may be replaced with corresponding components or features of another embodiment. It is self-evident that claims that do not have an explicit citation relationship in the patent claims may be combined to form embodiments or incorporated as new claims through post-application amendments.

[0341] It will be apparent to those skilled in the art that the present disclosure may be embodied in other specific forms without departing from the essential characteristics thereof. Therefore, the above detailed description should not be construed as limiting in any respect, but rather as illustrative. The scope of the present disclosure should be determined by a reasonable interpretation of the appended claims, and all modifications within the scope of equivalents of the present disclosure are intended to be included within the scope of the present disclosure.

[0342] The scope of the present disclosure includes software or machine-executable instructions (e.g., an operating system, an application, firmware, a program, etc.) that cause operations according to the methods of various embodiments to be executed on a device or a computer, and a non-transitory computer-readable medium having such software or instructions stored thereon and executable on the device or computer. Instructions that can be used to program a processing system to perform the features described in the present disclosure can be stored on / in a storage medium or a computer-readable storage medium, and a computer program product including such a storage medium can be used to implement the features described in the present disclosure. The storage medium can include, but is not limited to, high-speed random access memory, such as DRAM, SRAM, DDR RAM, or other random access solid state memory devices, and can 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 remotely located from the processor(s). The memory or, alternatively, the non-volatile memory device(s) within the memory comprise a non-transitory computer-readable storage medium. The features described in this disclosure may be incorporated into software and / or firmware stored on any of the machine-readable media, which may control the hardware of the processing system and allow the processing system to interact with other mechanisms that utilize results according to 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.

[0343] Here, the wireless communication technology implemented in the device of the present disclosure may include not only LTE, NR, and 6G, but also Narrowband Internet of Things for low-power communication. For example, NB-IoT technology may be an example of LPWAN (Low Power Wide Area Network) technology and may be implemented with standards such as LTE Cat NB1 and / or LTE Cat NB2, and is not limited to the above-described names. Additionally or alternatively, the wireless communication technology implemented in the device of the present disclosure may perform communication based on LTE-M technology. For example, LTE-M technology may be an example of LPWAN technology and may be called by various names such as eMTC (enhanced Machine Type Communication). For example, LTE-M technology can be implemented by at least one of various standards such as 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, and is not limited to the above-described names. Additionally or alternatively, the wireless communication technology implemented in the device (100, 200) of the present disclosure can include at least one of ZigBee, Bluetooth, and Low Power Wide Area Network (LPWAN) considering low-power communication, and is not limited to the above-described names. For example, ZigBee technology can create personal area networks (PAN) related to small / low-power digital communication based on various standards such as IEEE 802.15.4, and can be called by various names.

[0344] The method proposed in this disclosure is explained with a focus on examples applied to 3GPP LTE / LTE-A, 5G, and 6G systems, but can be applied to various wireless communication systems in addition to 3GPP LTE / LTE-A, 5G, and 6G systems.

Claims

1. A step of receiving, by a user equipment (UE), configuration information related to channel state information (CSI) reporting from a base station; A step of receiving a CSI-reference signal (CSI-RS) from the base station by the UE; and A step of transmitting, by the UE, the CSI derived using the CSI-RS to the base station, The CSI includes a first index associated with a first precoding matrix or channel-related matrix and a second index associated with a second precoding matrix or channel-related matrix, A method wherein a precoding matrix or channel-related matrix is ​​derived from at least one of the first precoding matrix or channel-related matrix and the second precoding matrix or channel-related matrix.

2. In paragraph 1, The above first precoding matrix or channel-related matrix has far-field characteristics, A method wherein the second precoding matrix or channel-related matrix has a near-field characteristic.

3. In paragraph 1, The elements of one or more vectors constituting the first precoding matrix or the channel-related matrix have phase changes linearly proportional to the antenna port index of the base station, A method wherein the elements of one or more vectors constituting the second precoding matrix or the channel-related matrix have a phase that changes in proportion to the square of the antenna port index of the base station.

4. In paragraph 1, A method wherein a scaling factor for elements of one or more vectors constituting the second precoding matrix or the channel-related matrix is ​​inversely proportional to a parameter related to the distance from the base station.

5. In paragraph 1, A method wherein the scaling factors for the elements of one or more vectors constituting the second precoding matrix or the channel-related matrix have different values ​​depending on the index associated with the beam selected by the terminal.

6. In paragraph 1, A method in which a scaling factor for elements of one or more vectors constituting the second precoding matrix or channel-related matrix is ​​applied to different values ​​for each of the one or more vectors.

7. In paragraph 1, A method wherein the precoding matrix or channel-related matrix is ​​derived i) by performing a Hadamard product or a Kronecker product of all or part of the first precoding matrix or channel-related matrix and all or part of the second precoding matrix or channel-related matrix, or ii) by combining or selecting all or part of the first precoding matrix or channel-related matrix and all or part of the second precoding matrix or channel-related matrix.

8. In paragraph 1, A method wherein the number of bits or the ratio of the number of bits allocated to the first index and the second index is i) set by the base station or ii) determined by the terminal and reported to the base station.

9. In paragraph 1, The above first index includes a 1-1 index related to a wideband and a 1-2 index related to a subband, A method wherein the second index includes a 2-1 index related to a wideband and a 2-2 index related to a subband.

10. In paragraph 1, i) A method in which the number of bits allocated to the second index or the amount of information indicated by the second index is determined based on the value of the first index, or ii) the number of bits allocated to the first index or the amount of information indicated by the first index is determined based on the value of the second index.

11. One or more transceivers for transmitting and receiving wireless signals; and comprising one or more processors controlling one or more of the above transceivers, One or more of the above processors: Receive configuration information related to channel state information (CSI) reporting from a base station; Receive a CSI-reference signal (CSI-RS) from the base station; and It is set to transmit the CSI derived using the CSI-RS to the base station, The CSI includes a first index associated with a first precoding matrix or channel-related matrix and a second index associated with a second precoding matrix or channel-related matrix, A user device, wherein the precoding matrix or channel-related matrix is ​​derived from at least one of the first precoding matrix or channel-related matrix and the second precoding matrix or channel-related matrix.

12. One or more non-transitory computer-readable media storing one or more instructions, The one or more instructions are executed by one or more processors so that the user device: Receive configuration information related to channel state information (CSI) reporting from a base station; Receive a CSI-reference signal (CSI-RS) from the base station; and Control to transmit the CSI derived using the CSI-RS to the base station, The CSI includes a first index associated with a first precoding matrix or channel-related matrix and a second index associated with a second precoding matrix or channel-related matrix, A computer-readable medium, wherein a precoding matrix or channel-related matrix is ​​derived from at least one of the first precoding matrix or channel-related matrix and the second precoding matrix or channel-related matrix.

13. In a processing device configured to control a user device, the processing device: one or more processors; and One or more computer memories operatively connected to said one or more processors and storing instructions that perform operations based on being executed by said one or more processors, The above actions are: A step of receiving configuration information related to channel state information (CSI) reporting from a base station; A step of receiving a CSI-reference signal (CSI-RS) from the base station; and A step of transmitting CSI derived using the CSI-RS to the base station, The CSI includes a first index associated with a first precoding matrix or channel-related matrix and a second index associated with a second precoding matrix or channel-related matrix, A processing device, wherein the precoding matrix or channel-related matrix is ​​derived from at least one of the first precoding matrix or channel-related matrix and the second precoding matrix or channel-related matrix.

14. A step of transmitting configuration information related to channel state information (CSI) reporting to a user equipment (UE) by a base station; A step of transmitting a CSI-reference signal (CSI-RS) to the UE by the base station; and A step of receiving the CSI from the UE by the base station, The CSI includes a first index associated with a first precoding matrix or channel-related matrix and a second index associated with a second precoding matrix or channel-related matrix, A method wherein a precoding matrix or channel-related matrix is ​​derived from at least one of the first precoding matrix or channel-related matrix and the second precoding matrix or channel-related matrix.

15. One or more transceivers for transmitting and receiving wireless signals; and comprising one or more processors controlling one or more of the above transceivers, One or more of the above processors: Transmit configuration information related to reporting channel state information (CSI) to a user equipment (UE); Transmitting a CSI-reference signal (CSI-RS) to the UE; and is set to receive the CSI from the UE, The CSI includes a first index associated with a first precoding matrix or channel-related matrix and a second index associated with a second precoding matrix or channel-related matrix, A base station, wherein the precoding matrix or channel-related matrix is ​​derived from at least one of the first precoding matrix or channel-related matrix and the second precoding matrix or channel-related matrix.

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