Apparatus and method for transmitting or receiving wireless signal by using intermediate node in wireless communication system

Abstract

The purpose of the present disclosure is to transmit or receive a signal by using an intermediate node in a wireless communication system using the intermediate node. A method performed by a base station in a wireless communication system may include the steps of: transmitting system information to a terminal; performing an initial access procedure with the terminal; transmitting configuration information of channel measurement to the terminal; performing a channel measurement procedure on the basis of the configuration information; determining a beamformer coefficient and a reflection coefficient of an intermediate node on the basis of the sum of minimum transmission rates of terminals, derived on the basis of the variance of channel and channel state information errors measured in the channel measurement procedure; transmitting resource allocation information to the terminal; and transmitting a data signal to the terminal through the intermediate node on the basis of the beamformer coefficient and the reflection coefficient.

Description

Device and method for transmitting or receiving a wireless signal using an intermediate node in a wireless communication system

[0001] The present disclosure relates to a wireless communication system, and to a device and method for transmitting or receiving a wireless signal using an intermediate node in a wireless communication system using an intermediate node.

[0002] Wireless access systems are widely deployed to provide various types of communication services, such as voice and data. Typically, wireless access systems are multiple access systems that support communications with multiple users by sharing available system resources (e.g., bandwidth, transmission power). Examples of multiple access systems include code division multiple access (CDMA), frequency division multiple access (FDMA), time division multiple access (TDMA), orthogonal frequency division multiple access (OFDMA), and single-carrier frequency division multiple access (SC-FDMA).

[0003] In particular, as numerous communication devices demand greater communication capacity, enhanced mobile broadband (eMBB) communication technologies are being proposed, improving upon existing radio access technology (RAT). Furthermore, massive machine type communications (mMTC), which connects multiple devices and objects to provide diverse services anytime and anywhere, as well as communication systems that consider reliability and latency-sensitive services / user equipment (UE), are being proposed. Various technological configurations are being proposed for these solutions.

[0004] The present disclosure relates to a device and method for performing wireless communication using an intermediate node capable of changing the phase of an incident signal in a wireless communication system.

[0005] The present disclosure relates to a device and method for determining a beamformer coefficient of a base station and a reflection coefficient of an intermediate node in a wireless communication system.

[0006] The present disclosure relates to a device and method for optimizing parameter values ​​using an objective function that takes into account channel estimation errors in a wireless communication system.

[0007] The present disclosure relates to a device and method for optimizing parameter values ​​based on the sum of minimum transmission rates of terminals in a wireless communication system.

[0008] The present disclosure relates to a device and method for optimizing parameter values ​​based on the sum of lower bounds of minimum transmission rates of terminals in a wireless communication system.

[0009] The present disclosure relates to a device and method for determining values ​​of parameters for communication using an alternating optimization algorithm in a wireless communication system.

[0010] The present disclosure relates to a device and method for performing communication using an active reconfigurable intelligent surface (active RIS) in a wireless communication system.

[0011] The present disclosure relates to a device and method for changing the phase and intensity of an incident signal using an active RIS in a wireless communication system.

[0012] The present disclosure relates to a device and method for providing communication services to terminals existing in a shadow area in a wireless communication system.

[0013] The present disclosure relates to a device and method for transmitting or receiving a signal by utilizing channel reciprocity of an uplink channel and a downlink channel during a correlation time in a wireless communication system.

[0014] The present disclosure relates to a device and method for obtaining channel information for generating an objective function for optimization in a wireless communication system.

[0015] The technical objectives to be achieved in the present disclosure are not limited to those mentioned above, and other technical tasks not mentioned can be considered by a person having ordinary skill in the technical field to which the technical configuration of the present disclosure is applied from the embodiments of the present disclosure described below.

[0016] As an example of the present disclosure, a method performed by a base station in a wireless communication system may include the steps of transmitting system information to a terminal, performing an initial connection procedure with the terminal, transmitting configuration information regarding channel measurement to the terminal, performing a channel measurement procedure based on the configuration information, determining a beamformer coefficient and a reflection coefficient of an intermediate node based on a sum of minimum transmission rates of terminals derived based on a distribution of channel and channel state information errors measured in the channel measurement procedure, transmitting resource allocation information to the terminal, and transmitting a data signal to the terminal through the intermediate node based on the beamformer coefficient and the reflection coefficient.

[0017] As an example of the present disclosure, a method of operation performed by a terminal in a wireless communication system includes the steps of: receiving system information from a base station; performing an initial connection procedure with the base station; receiving configuration information regarding channel measurement from the base station; performing a channel measurement procedure based on the configuration information; and receiving a data signal from the base station, wherein the data signal is received through the intermediate node based on a beamformer coefficient and a reflection coefficient of the intermediate node, and the beamformer coefficient and the reflection coefficient can be determined based on a sum of minimum transmission rates of terminals derived based on a variance of a channel and channel state information error measured in the channel measurement procedure.

[0018] As an example of the present disclosure, in a wireless communication system, a base station includes a transceiver and a processor connected to the transceiver, wherein the processor is configured to transmit system information to a terminal, perform an initial connection procedure with the terminal, transmit setting information regarding channel measurement to the terminal, perform a channel measurement procedure based on the setting information, determine a beamformer coefficient and a reflection coefficient of an intermediate node based on a sum of minimum transmission rates of terminals derived based on a variance of channel and channel state information errors measured in the channel measurement procedure, transmit resource allocation information to the terminal, and transmit a data signal to the terminal through the intermediate node based on the beamformer coefficient and the reflection coefficient.

[0019] As an example of the present disclosure, in a wireless communication system, a terminal includes a transceiver and a processor connected to the transceiver, wherein the processor is configured to receive system information from a base station, perform an initial connection procedure with the base station, receive setting information regarding channel measurement from the base station, perform a channel measurement procedure based on the setting information, and receive a data signal from the base station, wherein the data signal is received through the intermediate node based on a beamformer coefficient and a reflection coefficient of an intermediate node, and the beamformer coefficient and the reflection coefficient can be determined based on a sum of minimum transmission rates of terminals derived based on a variance of a channel and channel state information error measured in the channel measurement procedure.

[0020] As an example of the present disclosure, a communication device may include at least one processor, at least one computer memory connected to the at least one processor and storing instructions that direct operations when executed by the at least one processor, wherein the operations may include: transmitting system information to a terminal; performing an initial connection procedure with the terminal; transmitting configuration information regarding channel measurement to the terminal; performing a channel measurement procedure based on the configuration information; determining a beamformer coefficient and a reflection coefficient of an intermediate node based on a sum of minimum transmission rates of terminals derived based on a variance of channel and channel state information errors measured in the channel measurement procedure; transmitting resource allocation information to the terminal; and transmitting a data signal to the terminal through the intermediate node based on the beamformer coefficient and the reflection coefficient.

[0021] As an example of the present disclosure, a non-transitory computer-readable medium storing at least one instruction, the at least one instruction being executable by a processor, wherein the at least one instruction is configured to cause a device to transmit system information to a terminal, perform an initial connection procedure with the terminal, transmit configuration information regarding channel measurement to the terminal, perform a channel measurement procedure based on the configuration information, determine a beamformer coefficient and a reflection coefficient of an intermediate node based on a sum of minimum transmission rates of terminals derived based on a variance of channel and channel state information errors measured in the channel measurement procedure, transmit resource allocation information to the terminal, and transmit a data signal to the terminal through the intermediate node based on the beamformer coefficient and the reflection coefficient.

[0022] The above-described aspects of the present disclosure are only some of the preferred embodiments of the present disclosure, and various embodiments reflecting the technical features of the present disclosure can be derived and understood by a person having ordinary skill in the art based on the detailed description of the present disclosure to be described below.

[0023] The following effects may be achieved by embodiments based on the present disclosure.

[0024] According to the present disclosure, communication can be performed efficiently using an intermediate node.

[0025] The effects that can be obtained from the embodiments of the present disclosure are not limited to the effects mentioned above, and other effects not mentioned can be clearly derived and understood by those skilled in the art to which the technical configuration of the present disclosure is applied, from the description of the embodiments of the present disclosure below. In other words, unintended effects resulting from implementing the configuration described in the present disclosure can also be derived from the embodiments of the present disclosure by those skilled in the art.

[0026] The accompanying drawings are intended to aid understanding of the present disclosure and may provide embodiments of the present disclosure along with detailed descriptions. However, the technical features of the present disclosure are not limited to specific drawings, and the features disclosed in each drawing may be combined with each other to form new embodiments. Reference numerals in each drawing may indicate structural elements.

[0027] Figure 1 illustrates an example of a communication system applicable to the present disclosure.

[0028] FIG. 2 illustrates an example of a wireless device applicable to the present disclosure.

[0029] FIG. 3 illustrates a method for processing a transmission signal applicable to the present disclosure.

[0030] Figure 4 illustrates a communication procedure between a terminal and a base station applicable to the present disclosure.

[0031] FIG. 5 illustrates an example of a communication structure that can be provided in a 6G (6th generation) system applicable to the present disclosure.

[0032] Figure 6 illustrates an electromagnetic spectrum applicable to the present disclosure.

[0033] Figure 7 illustrates a THz communication method applicable to the present disclosure.

[0034] Figure 8 illustrates a THz signal generation method applicable to the present disclosure.

[0035] FIG. 9 illustrates a wireless communication transceiver applicable to the present disclosure.

[0036] Figure 10 illustrates a transmitter structure applicable to the present disclosure.

[0037] Figure 11 illustrates a system information transmission procedure applicable to the present disclosure.

[0038] Figure 12 illustrates a beam management procedure applicable to the present disclosure.

[0039] FIG. 13 illustrates an example of a communication scenario using a reconfigurable intelligent surface (RIS) according to one embodiment of the present disclosure.

[0040] FIG. 14 illustrates an example of a procedure in which a base station transmits and / or receives a data signal using an intermediate node according to one embodiment of the present disclosure.

[0041] FIG. 15 illustrates an example of a procedure in which a terminal transmits a data signal using an intermediate node according to one embodiment of the present disclosure.

[0042] FIG. 16 illustrates an example of a procedure in which a base station determines beamformer coefficients and reflection coefficients of intermediate nodes based on measurement results according to one embodiment of the present disclosure.

[0043] FIG. 17 illustrates an example of a timing diagram according to one embodiment of the present disclosure.

[0044] FIG. 18 illustrates an example of signaling for transmitting and / or receiving a data signal in a communication environment in which an intermediate node (1820) according to one embodiment of the present disclosure is used.

[0045] FIG. 19 illustrates a first example of a sum transmission rate according to a transmission power of a base station according to an embodiment of the present disclosure.

[0046] FIG. 20 illustrates a second example of a sum transmission rate according to a transmission power of a base station according to an embodiment of the present disclosure.

[0047] FIG. 21 illustrates an example of a sum transmission rate according to the maximum amplification gain of each RIS element according to one embodiment of the present disclosure.

[0048] Figure 22 illustrates an example of a wireless device applicable to the present disclosure.

[0049] Figure 23 illustrates an example of a portable device applicable to the present disclosure.

[0050] FIG. 24 illustrates an example of a vehicle or autonomous vehicle applicable to the present disclosure.

[0051] Figure 25 illustrates an example of a vehicle applicable to the present disclosure.

[0052] FIG. 26 illustrates an example of an XR device applicable to the present disclosure.

[0053] Figure 27 illustrates an example of a robot applicable to the present disclosure.

[0054] Figure 28 illustrates an example of an AI device applicable to the present disclosure.

[0055] The following embodiments combine the components and features of the present disclosure in a predetermined form. Each component or feature may be considered optional unless explicitly stated otherwise. Each component or feature may be implemented without being combined with other components or features. Furthermore, some components and / or features may be combined to form embodiments of the present disclosure. 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.

[0056] In the description of the drawings, procedures or steps that may obscure the gist of the present disclosure are not described, and procedures or steps that can be understood by a person skilled in the art are also not described.

[0057] Throughout the specification, when a part is said to "comprising" or "including" a component, this does not mean that other components may be included, but rather that other components may be excluded, unless otherwise specifically stated. In addition, terms such as "...part," "...unit," and "module" described in the specification mean a unit that processes at least one function or operation, which may be implemented by hardware, software, or a combination of hardware and software. In addition, the words "a" or "an," "one," "the," and similar related words may be used in the context of describing the present disclosure (especially in the context of the claims below) to include both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context.

[0058] Embodiments of the present disclosure described herein focus on the data transmission and reception relationship between a base station and a mobile station. Here, the base station is understood as a terminal node of a network that directly communicates with the mobile station. Certain operations described herein as being performed by the base station may, in some cases, be performed by an upper node of the base station.

[0059] That is, in a network consisting of multiple network nodes including a base station, various operations performed for communication with a mobile station may be performed by the base station or other network nodes other than the base station. In this case, the term 'base station' may be replaced by terms such as fixed station, Node B, eNB (eNode B), gNB (gNode B), ng-eNB, advanced base station (ABS), or access point.

[0060] Additionally, in the embodiments of the present disclosure, the term terminal may be replaced with terms such as user equipment (UE), mobile station (MS), subscriber station (SS), mobile subscriber station (MSS), mobile terminal, or advanced mobile station (AMS).

[0061] Additionally, a transmitter refers to a fixed and / or mobile node that provides data or voice services, and a receiver refers to a fixed and / or mobile node that receives data or voice services. Therefore, for uplink, a mobile station can be the transmitter, and a base station can be the receiver. Similarly, for downlink, a mobile station can be the receiver, and a base station can be the transmitter.

[0062] Embodiments of the present disclosure may be supported by standard documents disclosed in at least one of wireless access systems, such as IEEE 802.xx system, 3rd Generation Partnership Project (3GPP) system, 3GPP Long Term Evolution (LTE) system, 3GPP 5th generation (5G) NR (New Radio) system and 3GPP2 system, and in particular, embodiments of the present disclosure may be supported by 3GPP TS (technical specification) 38.211, 3GPP TS 38.212, 3GPP TS 38.213, 3GPP TS 38.321 and 3GPP TS 38.331 documents.

[0063] Furthermore, the embodiments of the present disclosure can be applied to other wireless access systems and are not limited to the systems described above. For example, they can be applied to systems implemented after the 3GPP 5G NR system and are not limited to a specific system.

[0064] That is, obvious steps or parts not described in the embodiments of the present disclosure can be explained by referring to the above documents. In addition, all terms disclosed in this document can be explained by the above standard documents.

[0065] Hereinafter, preferred embodiments according to 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 illustrate exemplary embodiments of the present disclosure and is not intended to represent the only embodiments in which the technical configurations of the present disclosure may be implemented.

[0066] Additionally, specific terms used in the embodiments of the present disclosure are provided to aid in understanding of the present disclosure, and the use of such specific terms may be changed to other forms without departing from the technical spirit of the present disclosure.

[0067] The following technology can be applied to various wireless access 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).

[0068]

[0069] For clarity, the following description is based on 3GPP communication systems (e.g., LTE, NR, etc.), but the technical spirit of the present disclosure is not limited thereto. LTE may refer to technology after 3GPP TS 36.xxx Release 8. Specifically, LTE technology after 3GPP TS 36.xxx Release 10 may be referred to as LTE-A, and LTE technology after 3GPP TS 36.xxx Release 13 may be referred to as LTE-A pro. 3GPP NR may refer to technology after TS 38.xxx Release 15. 3GPP 6G may refer to technology after TS Release 17 and / or Release 18. "xxx" refers to a standard document detail number. LTE / NR / 6G may be collectively referred to as a 3GPP system.

[0070] For background information, terms, abbreviations, etc. used in this disclosure, reference may be made to standard documents published prior to this disclosure. For example, reference may be made to standard documents 36.xxx and 38.xxx.

[0071]

[0072] Communication system applicable to the present disclosure

[0073] Although not limited thereto, the various descriptions, functions, procedures, proposals, methods and / or operational flowcharts of the present disclosure disclosed in this document may be applied to various fields requiring wireless communication / connectivity (e.g., 5G) between devices.

[0074] Hereinafter, more specific examples will be provided with reference to the drawings. In the drawings / descriptions below, the same drawing reference numerals may represent identical or corresponding hardware blocks, software blocks, or functional blocks, unless otherwise described.

[0075] Figure 1 illustrates an example of a communication system applied to the present disclosure.

[0076] Referring to FIG. 1, a communication system (100) applied to the present disclosure includes a wireless device, a base station, and a network. Here, the wireless device 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 device. Although not limited thereto, the wireless device may include a robot (100a), a vehicle (100b-1, 100b-2), an XR (extended reality) device (100c), a hand-held device (100d), a home appliance (100e), an IoT (Internet of Things) device (100f), and an AI (artificial intelligence) device / server (100g). 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 vehicles (100b-1, 100b-2) may include unmanned aerial vehicles (UAVs) (e.g., drones). The XR devices (100c) include augmented reality (AR) / virtual reality (VR) / mixed reality (MR) devices, and may be implemented in the form of head-mounted devices (HMDs), head-up displays (HUDs) installed in vehicles, televisions, smartphones, computers, wearable devices, home appliances, digital signage, vehicles, robots, etc. The portable devices (100d) may include smartphones, smart pads, wearable devices (e.g., smartwatches, smart glasses), computers (e.g., laptops, etc.), etc. The home appliances (100e) may include TVs, refrigerators, washing machines, etc. The IoT devices (100f) may include sensors, smart meters, etc.For example, the base station (120) and the network (130) may also be implemented as wireless devices, and a specific wireless device (120a) may act as a base station / network node to other wireless devices.

[0077] Wireless devices (100a to 100f) can be connected to a network (130) via a base station (120). AI technology can be applied to the wireless devices (100a to 100f), and the wireless devices (100a to 100f) can be connected to an AI server (100g) 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 (100a to 100f) can communicate with each other via the base station (120) / network (130), but can also communicate directly (e.g., sidelink communication) without going through the base station (120) / network (130). For example, vehicles (100b-1, 100b-2) can communicate directly (e.g., V2V (vehicle to vehicle) / V2X (vehicle to everything) communication). Additionally, an IoT device (100f) (e.g., a sensor) can communicate directly with another IoT device (e.g., a sensor) or another wireless device (100a to 100f).

[0078] Wireless communication / connection (150a, 150b, 150c) can be established between wireless devices (100a to 100f) / base stations (120), and base stations (120) / base stations (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 base station-to-base station communication (150c) (e.g., relay, IAB (integrated access backhaul)). Through the wireless communication / connection (150a, 150b, 150c), the wireless device and base station / wireless device, and base stations and base stations can transmit / receive wireless signals to / from 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 proposals 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.

[0079]

[0080] Devices applicable to the present disclosure

[0081] FIG. 2 illustrates an example of a wireless device applicable to the present disclosure.

[0082] Referring to FIG. 2, 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).

[0083] 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.

[0084] 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) including 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.

[0085] 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.

[0086] 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.

[0087] 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. In addition, 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 operation flowcharts disclosed in this document through 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 the processed user data, control information, wireless signals / channels, etc. from baseband signals to RF band signals using at least one processor (202).For this purpose, at least one transceiver (206) may include an (analog) oscillator and / or filter.

[0088] The components of the wireless device described with reference to FIG. 2 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).

[0089] The structure of the wireless device described with reference to FIG. 2 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. 2 can be at least a portion of various devices described with reference to FIG. 1 (e.g., a robot (100a), a vehicle (100b-1, 100b-2), an XR device (100c), a portable device (100d), a home appliance (100e), an IoT device (100f), an AI device / server (100g)). Furthermore, according to various embodiments, in addition to the components illustrated in FIG. 2, the device may further include other components.

[0090] 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.

[0091] 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.

[0092] 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.

[0093] 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.

[0094] 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.

[0095] The structure of the wireless device illustrated in FIG. 2 may be understood as a part of a RAN node (e.g., base station, DU, RU, RRㅗ, etc.). That is, the device illustrated in FIG. 2 may be a RAN node. In this case, the device may further include a wired transceiver for front haul and / or back haul communication. However, if the front haul and / or back haul communication is based on wireless communication, at least one transceiver (206) illustrated in FIG. 2 may be used for front haul and / or back haul communication, and a wired transceiver may not be included.

[0096]

[0097] FIG. 3 illustrates a method for processing a transmission signal applicable to the present disclosure. For example, the transmission signal may be processed by a signal processing circuit. At this time, the signal processing circuit (300) may include a scrambler (310), a modulator (320), a layer mapper (330), a precoder (340), a resource mapper (350), and a signal generator (360). At this time, as an example, the operations / functions of FIG. 3 may be performed in the processor (202) and / or the transceiver (206) of FIG. 2. Furthermore, as an example, the hardware elements of FIG. 3 may be implemented in the processor (202) and / or the transceiver (206) of FIG. 2. As an example, blocks 310 to 360 may be implemented in the processor (202) of FIG. 2. Additionally, blocks 310 to 350 may be implemented in the processor (202) of FIG. 2, and block 360 may be implemented in the transceiver (206) of FIG. 2, and are not limited to the above-described embodiment.

[0098] The codeword can be converted into a wireless signal through the signal processing circuit (300) of FIG. 3. Here, the codeword is an encoded bit sequence of an information block. The information block may include a transport block (e.g., a UL-SCH transport block, a DL-SCH transport block). Here, the information block may include data related to AI (e.g., training data, AI model data, input data, output data, etc.), and the codeword may be an encoded bit sequence corresponding to the data related to AI. The wireless signal may be transmitted through various physical channels (e.g., PUSCH, PDSCH). Specifically, the codeword may be converted into a bit sequence scrambled by a scrambler (310). The scramble sequence used for scrambling is generated based on an initialization value, and the initialization value may include ID information of the wireless device, etc. The scrambled bit sequence may be modulated into a modulation symbol sequence by a modulator (320). Modulation schemes may include pi / 2-BPSK (pi / 2-binary phase shift keying), m-PSK (m-phase shift keying), m-QAM (m-quadrature amplitude modulation), etc.

[0099] A complex modulation symbol sequence can be mapped to at least one transport layer by a layer mapper (330). Here, a transport layer is a logical resource unit for mapping a signal or data transmitted through spatial resources to antenna ports, and one transport layer can correspond to one stream or one antenna port. Each of the complex modulation symbols included in the complex modulation symbol sequence is mapped to at least one transport layer, thereby determining which antenna port it will be transmitted through. The modulation symbols of each transport layer can be mapped to the corresponding antenna port(s) by a precoder (340). The output z of the precoder (340) can be obtained by multiplying the output y of the layer mapper (330) by a precoding matrix W of NХM. Here, N is the number of antenna ports, and M is the number of transport layers. Here, the precoder (340) may perform precoding after performing transform precoding (e.g., discrete Fourier transform (DFT) transform) on complex modulation symbols. Additionally, the precoder (340) may perform precoding without performing transform precoding.

[0100] The resource mapper (350) can map modulation symbols of each antenna port to time-frequency resources. The time-frequency resources can include multiple symbols (e.g., CP-OFDMA symbols, DFT-s-OFDMA symbols) in the time domain and multiple subcarriers in the frequency domain. The signal generator (360) generates a wireless signal from the mapped modulation symbols, and the generated wireless signal can be transmitted to another device through each antenna. To this end, the signal generator (360) can include an inverse fast Fourier transform (IFFT) module, a cyclic prefix (CP) inserter, a digital-to-analog converter (DAC), a frequency uplink converter, and the like.

[0101] The signal processing process for a received signal in a wireless device may be configured in reverse order of the signal processing process (310 to 360) of FIG. 3. For example, a wireless device (e.g., 200 of FIG. 2) may receive a wireless signal from the outside through an antenna port / transceiver. The received wireless signal may be converted into a baseband signal through a signal restorer. For this purpose, the signal restorer may include a frequency downlink converter, an analog-to-digital converter (ADC), a CP remover, and a fast Fourier transform (FFT) module. Thereafter, the baseband signal may be restored to a codeword through a resource demapper process, a postcoding process, a demodulation process, and a descrambling process. The codeword may be restored to the original information block through decoding. Therefore, a signal processing circuit (not shown) for a received signal may include a signal restorer, a resource demapper, a postcoder, a demodulator, a descrambler, and a decoder.

[0102]

[0103] Figure 4 illustrates a communication procedure between a terminal and a base station applicable to the present disclosure. Figure 4 illustrates operations of a terminal (410) and a base station (420) transmitting and / or receiving data and operations performed prior thereto.

[0104] Referring to FIG. 4, in step 401, the terminal (410) and the base station (420) perform synchronization. For example, the terminal (410) performs an initial cell search operation. Specifically, the terminal (410) can detect at least one synchronization signal transmitted from the base station (420) according to a predefined rule. Here, the synchronization signal can include multiple synchronization signals classified according to structure or purpose (e.g., primary synchronization signal, secondary synchronization signal). Through this, the terminal (410) can check the boundary of the frame, subframe, slot, and / or symbol of the base station (420) and obtain information about the base station (420) (e.g., cell identifier).

[0105] In step 403, the terminal (410) obtains system information transmitted from the base station (420). The system information is information related to the properties, characteristics, and / or capabilities of the base station (420) required to access the base station (420) and use the service, and may be classified by content (e.g., whether it is essential for access), transmission structure (e.g., channel used, whether provided on-demand), etc., and may be classified into, for example, a master information block (MIB) and a system information block (SIB). If necessary, the terminal (410) may transmit a signal requesting system information before receiving the system information. The system information may include information related to an AI function. For example, the system information may include at least one of information related to an AI model, information related to training, and information related to inference / prediction, as information required for operations performed based on AI. However, the request and provision of the system information may be performed after a random access procedure described below.

[0106] In step 405, the terminal (410) and the base station (420) perform a random access procedure. The terminal (410) may transmit and / or receive at least one message (e.g., a random access preamble, a random access response (RAR) message, etc.) for the random access procedure based on information related to the random access channel of the base station (420) obtained through system information (e.g., channel position, channel structure, supported preamble structure, etc.). For example, the terminal (410) may transmit a preamble (e.g., MSG1) through the random access channel, receive an RAR message (e.g., MSG2), transmit a message (e.g., MSG3) including information related to the terminal (410) (e.g., identification information) to the base station (420) using scheduling information included in the RAR message, and receive a message (e.g., MSG4) for contention resolution and / or connection establishment. As another example, MSG1 and MSG3 may be sent and received as one message, or MSG2 and MSG4 may be sent and received as one message.

[0107] In step 407, the terminal (410) and the base station (420) perform signaling of control information. Here, the control information may 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 transport 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 (410) and the base station (420) may perform at least one of signaling for establishing a connection, signaling for determining settings related to communication, and signaling for indicating allocated resources. In addition, the signaling of the control information may be performed to convey information related to an AI function. For example, the information related to an AI function is information necessary for an operation performed based on AI, and may include at least one of information related to an AI model, information related to training, and information related to inference / prediction. More specifically, information related to the AI ​​function signaled in step 407 may be combined and / or combined with information related to the AI ​​function signaled in step 403, and the two may be defined in a hierarchical, mutually complementary, or substitutive structure.

[0108] In step 409, the terminal (410) and the base station (420) transmit and / or receive data. In other words, the terminal (410) and the base station (420) can process, transmit, and / or receive data based on the signaling of the control information. For example, when transmitting data, the terminal (410) or the base station (420) can perform at least one of channel encoding, rate matching, scrambling, constellation mapping, layer mapping, waveform modulation, antenna mapping, and resource mapping on the information bits. Conversely, when receiving data, the terminal (410) or the base station (420) 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. Here, the transmitted data is data related to AI, and may include, for example, data for AI-based operations or data generated by AI-based operations.

[0109] Steps 401 to 409 illustrated with reference to FIG. 4 do not necessarily have to be performed in the order illustrated in FIG. 4, and the order of at least some of the steps may vary. Furthermore, at least some of steps 401 to 409 may be combined into a single step or omitted. That is, the steps illustrated in FIG. 4 may be performed in various modified forms.

[0110]

[0111] 6G communication systems and core implementation technologies of 6G systems

[0112] The 5G system defines various operating bands within FR1 (frequency range 1), which covers 410 MHz to 7125 MHz, and FR2 (frequency range 2), which covers 24,250 MHz to 71,000 MHz. Various frequencies are being discussed as operating bands for the subsequent 6G system, and the use of higher frequencies than 5G systems is also being considered for wider bandwidth and higher transmission speeds. One such band is the THz (terahertz) frequency band, which covers approximately 100 GHz to 10 THz. The THz frequency band is a band that has both the transparency of radio waves and the straightness of light waves, and communications using the THz frequency band are expected to play a transitional role from existing radio-centered communications to lightwave-based communications.

[0113] 6G systems utilizing the THz frequency band have the following goals: 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 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,” and the 6G system can be designed to satisfy the requirements as shown in [Table 1] below.

[0114] Per device peak data rate1 TbpsE2E latency1 msMaximum spectral efficiency100 bps / HzMobility supportup to 1000 km / hrSatellite integrationFullyAIFullyAutonomous vehicleFullyXRFullyHaptic CommunicationFully

[0115] At this time, the 6G system may have key factors such as enhanced mobile broadband (eMBB), ultra-reliable low latency communications (URLLC), massive machine type communications (mMTC), AI integrated communication, tactile internet, high throughput, high network capacity, high energy efficiency, low backhaul and access network congestion, and enhanced data security. FIG. 5 illustrates an example of a communication structure that can be provided in a 6G system applicable to the present disclosure. Referring to FIG. 5, the 6G system is expected to have simultaneous wireless communication connectivity that is 50 times higher than that of a 5G wireless communication system. URLLC, a key feature of 5G, is expected to become an even more crucial technology in 6G communications, offering end-to-end latency of less than 1 ms. Furthermore, 6G systems will boast significantly higher volumetric spectral efficiency than the commonly used area spectral efficiency. 6G systems can offer extremely long battery life and advanced battery technologies for energy harvesting, eliminating the need for separate charging for mobile devices in 6G systems. New network characteristics in 6G may include:

[0116] - Satellite integrated network: 6G is expected to integrate with satellites to provide a global mobile network. The integration of terrestrial, satellite, and airborne networks into a single wireless communications system is crucial for 6G.

[0117] Connected Intelligence: Unlike previous generations of wireless communication systems, 6G is revolutionary, upgrading the wireless evolution from "connected objects" to "connected intelligence." AI can be applied at every stage of the communication process (or at every signal processing step, as described below).

[0118] - Seamless integration of wireless information and energy transfer: 6G wireless networks will transfer power to charge the batteries of devices such as smartphones and sensors. Therefore, wireless information and energy transfer (WIET) will be integrated.

[0119] - Ubiquitous super 3D connectivity: Access to networks and core network functions of drones and very low Earth orbit satellites will create super 3D connectivity in 6G ubiquitous.

[0120] Some general requirements for the new network characteristics of 6G, such as the above, may be as follows:

[0121] - Small cell networks: The concept of small cell networks was introduced to improve received signal quality in cellular systems by increasing throughput, energy efficiency, and spectral efficiency. Consequently, small cell networks are essential for 5G and beyond-5G (5GB) communication systems. Accordingly, 6G communication systems also adopt the characteristics of small cell networks.

[0122] Ultra-dense heterogeneous networks: Ultra-dense heterogeneous networks will be another key feature of 6G communication systems. Multi-tier networks comprised of heterogeneous networks improve overall QoS and reduce costs.

[0123] High-capacity backhaul: Backhaul connections are characterized by high-capacity backhaul networks to support high-volume traffic. High-speed fiber optics and free-space optics (FSO) systems may be potential solutions to this problem.

[0124] - Radar technology integrated with mobile technology: High-precision localization (or location-based services) through communications is a key feature of 6G wireless communication systems. Therefore, radar systems will be integrated with 6G networks.

[0125] - Softwarization and virtualization: Softwarization and virtualization are two critical features that form the foundation of the design process for 5GB networks to ensure flexibility, reconfigurability, and programmability. Furthermore, billions of devices can be shared on a shared physical infrastructure.

[0126] To satisfy the above-mentioned characteristics, the core implementation technologies of the 6G system may include artificial intelligence (AI), THz (terahertz) communication, optical wireless technology, FSO backhaul network, massive MIMO 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).

[0127] For example, THz communication can be utilized in 6G systems. THz communication is a communication that utilizes a spectrum in a frequency band between 0.3 THz and 3 THz with a corresponding wavelength in the range of 0.1 mm to 1 mm, as shown in FIG. 6. Referring to FIG. 6, the frequency band of THz waves is located in the middle region between the infrared band and the millimeter wave band, and therefore, THz waves can be understood as radio waves with the shortest wavelength and light waves with the longest wavelength. Therefore, THz waves share some of the characteristics of infrared and microwave waves, and specifically, they can simultaneously have the transparency of electromagnetic waves and the straightness of light waves.

[0128]

[0129] Fig. 7 illustrates a THz communication method applicable to the present disclosure. Referring to Fig. 7, THz wireless communication refers to wireless communication using THz waves having a frequency of approximately 0.1 to 10 THz (1 THz = 1012 Hz), and may refer to terahertz (THz) band wireless communication using a very high carrier frequency of 100 GHz or higher. THz waves are located between the RF (Radio Frequency) / millimeter (mm) and infrared bands, and (i) compared to visible light / infrared rays, they penetrate non-metallic / non-polarizable materials well, and compared to RF / millimeter waves, they have a shorter wavelength, thus having high linearity and enabling beam focusing.

[0130] In addition, since the photon energy of THz waves is only a few meV, it has the characteristic of being harmless to the human body. The frequency band expected to be used for THz wireless communication may be the D-band (110 GHz to 170 GHz) or H-band (220 GHz to 325 GHz) bands where propagation loss due to absorption of molecules in the air is small. In addition to 3GPP, standardization discussions for THz wireless communication are being centered around the IEEE 802.15 THz WG (working group), and standard documents issued by the IEEE 802.15 TG (task group) (e.g., TG3d, TG3e) can specify or supplement the contents described in this specification. THz wireless communication can be applied to wireless cognition, sensing, imaging, wireless communication, THz navigation, etc.

[0131] Specifically, referring to Fig. 7, THz wireless communication scenarios can be categorized into macro networks, micro networks, and nanoscale networks. In macro networks, THz wireless communication can be applied to vehicle-to-vehicle (V2V) connections and backhaul / fronthaul connections. In micro networks, THz wireless communication can be applied to fixed point-to-point or multi-point connections such as indoor small cells, wireless connections in data centers, and near-field communication such as kiosk downloading. Table 2 below shows examples of technologies that can be utilized in THz waves.

[0132] Transceivers DeviceAvailable immature: UTC-PD, RTD and SBDModulation and codingLow order modulation techniques (OOK, QPSK), LDPC, Reed Soloman, Hamming, Polar, TurboAntennaOmni and Directional, phased array with low number of antenna elementsBandwidth69 GHz (or 23 GHz) at 300 GHzChannel modelsPartiallyData rate100 GbpsOutdoor deploymentNoFee space lossHighCoverageLowRadio Measurements300 GHz inddorDevice sizeFew micrometers

[0133] FIG. 8 illustrates a THz signal generation method applicable to the present disclosure. FIG. 9 also illustrates a wireless communication transceiver applicable to the present disclosure. Referring to FIGS. 8 and 9, the optical device-based THz wireless communication technology refers to a method of generating and modulating a THz signal using an optical device. The optical device-based THz signal generation technology is a technology that generates an ultra-high-speed optical signal using a laser and an optical modulator, and converts it into a THz signal using an ultra-high-speed photodetector. Compared to a technology that uses only electronic devices, this technology makes it easy to increase the frequency, enables high-power signal generation, and obtains a flat response characteristic over a wide frequency band. For the optical device-based THz signal generation, as illustrated in FIG. 8, a laser diode, a wideband optical modulator, and an ultra-high-speed photodetector are required. In the case of FIG. 8, light signals from two lasers with different wavelengths are combined to generate a THz signal corresponding to the wavelength difference between the lasers. In Fig. 8, an optical coupler refers to a semiconductor device that transmits an electrical signal using optical waves to provide electrical isolation and coupling between circuits or systems, and a uni-travelling carrier photo-detector (UTC-PD) is a type of photodetector that uses electrons as active carriers and reduces the travel time of electrons through bandgap grading. The UTC-PD is capable of photodetection at 150 GHz or higher.In Fig. 9, EDFA (erbium-doped fiber amplifier) ​​represents an erbium-doped fiber amplifier, PD (photo detector) represents a semiconductor device that can convert an optical signal into an electrical signal, OSA represents an optical module (optical sub assembly) that modularizes various optical communication functions (e.g., photoelectric conversion, electro-optical conversion, etc.) into a single component, and DSO represents a digital storage oscilloscope.

[0134] Figure 10 illustrates a transmitter structure applicable to the present disclosure.

[0135] Referring to Figure 10, in order to modulate data into an optical signal, an optical source such as a laser can be passed through an optical wave guide to change the phase of the signal, etc. At this time, data is loaded by changing the electrical characteristics through a microwave contact, etc. Therefore, the optical modulator output is formed as a modulated waveform.

[0136] Data may be provided from a data signal generator. Here, the data may include various user data, configuration information, control information, etc. transmitted through a channel. Furthermore, the data may include data related to AI-based operations, such as information for configuring an AI model, input / output data for tasks of the AI ​​model, etc. To this end, components related to AI functions (e.g., an AI processing unit) may be included in the data signal generator or may be linked to the data signal generator.

[0137] An optical / electronic converter (O / E converter) can generate THz pulses by optical rectification using a nonlinear crystal, photoelectric conversion using a photoconductive antenna, or emission from a bunch of relativistic electrons. The THz pulse generated in the above manner can have a length in the range of femtoseconds to picoseconds. The optical / electronic converter (O / E converter) performs down conversion by utilizing the nonlinearity of the device.

[0138] Considering the THz spectrum usage, it is likely that multiple contiguous GHz bands will be used for THz systems, either fixed or for mobile services. For an outdoor scenario, the available bandwidth can be categorized based on an oxygen attenuation of 10^2 dB / km in the spectrum up to 1 THz. Accordingly, a framework in which the available bandwidth is divided into multiple band chunks can be considered. As an example of this framework, if the THz pulse length for a single carrier is set to 50 ps, ​​the bandwidth (BW) becomes approximately 20 GHz.

[0139] Effective down-conversion from the infrared band to the THz band depends on how to utilize the nonlinearity of the optical / electrical converter (O / E converter). In other words, to down-convert to the desired THz band, it is necessary to design an O / E converter with the most ideal non-linearity for transferring to the THz band. If an O / E converter that is not suitable for the target frequency band is used, errors in the amplitude and phase of the pulse are likely to occur.

[0140] A THz transmission and reception system can be implemented using a single optical-to-electrical converter in a single-carrier system. Depending on the channel environment, optical-to-electrical converters may be required as many as the number of carriers in a multi-carrier system. This phenomenon will be particularly noticeable in a multi-carrier system that utilizes multiple broadbands according to the aforementioned spectrum usage plan. In this regard, a frame structure for the multi-carrier system may be considered. A signal down-frequency converted based on an optical-to-electrical converter may be transmitted in a specific resource region (e.g., a specific frame). The frequency region of the specific resource region may include multiple chunks. Each chunk may be composed of at least one component carrier (CC).

[0141] Transmitting system information (e.g., MIB) in the THz frequency band can be inefficient because the beam width becomes narrower in high-frequency bands, requiring more beam sweeps to cover the entire cell area. This method of transmitting system information is particularly inefficient when there are only a few users within the cell. Accordingly, a system information transmission procedure, such as that illustrated in FIG. 11, may be employed.

[0142] Figure 11 illustrates a system information transmission procedure applicable to the present disclosure. Figure 11 illustrates an example of a procedure for transmitting system information for THz communication. The procedure illustrated in Figure 11 can be combined with various embodiments of the present disclosure described below. For example, the embodiments described below can be performed based on the system information acquired by the procedure illustrated in Figure 11. As another example, information and / or data transmitted in the procedure illustrated in Figure 11 can be generated and / or processed according to the embodiments described below.

[0143] Referring to FIG. 11, in step 1101, the base station (1120) transmits system information of cell #1 through cell #2. That is, the base station (1120) 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, 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 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.

[0144] In step 1103, UE (1110) acquires synchronization for cell #1. Synchronization can be acquired by detecting a synchronization signal. Typically, synchronization is acquired before receiving system information. However, since 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, UE (1110) can acquire synchronization based on system information. However, unlike FIG. 11, in another example, synchronization acquisition can be performed before step 1101.

[0145] In step 1105, UE (1110) transmits a signal for accessing cell #1. For example, the signal may include a random access preamble. The structure of the signal and the resources (e.g., channels) for transmitting the signal can be identified through system information. Thereafter, in step 1107, UE (1110) and base station (1120) perform an access procedure for cell #1 and communicate. In this step, operations according to various embodiments described below may be performed.

[0146] The procedure described with reference to FIG. 11 may be performed when UE (1101) first connects to cell #1 of base station (1120). Alternatively, a similar procedure may be performed when UE (1101) hands over to cell #1 of base station (1120). However, in the case of handover, system information of cell #1 may be received from a cell of a base station other than cell #2 of base station (1120).

[0147]

[0148] Communications in the THz band are expected to experience extremely severe path loss, and to overcome this, terminals and base stations must use extremely 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 the movement or movement of the terminals, frequent re-alignment of the beams is required, which can lead to link instability. Accordingly, a beam management procedure, as illustrated in FIG. 12 below, may be used.

[0149] FIG. 12 illustrates a beam management procedure applicable to the present disclosure. FIG. 12 illustrates an example of a procedure for searching and / or selecting beams for THz communication. The procedure illustrated in FIG. 12 may be combined with various embodiments of the present disclosure described below. For example, the embodiments described below may be performed using at least one beam acquired by the procedure illustrated in FIG. 11. As another example, information and / or data transmitted in the procedure illustrated in FIG. 12 may be generated and / or processed according to the embodiments described below. Herein, a beam may be referred to as a 'spatial domain filter', a 'spatial domain transmit filter', a 'spatial domain receive filter', and other terms having equivalent technical meanings thereto.

[0150] Referring to FIG. 12, in step 1201, a base station (1220) configures resources for beam management. 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 (1220) 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, 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. That is, a signal transmitted based on a dedicated port defined / configured for beam search may be included in the technical concept according to the present embodiment.

[0151] In step 1203, the base station (1201) transmits measurement signals using multiple 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 be transmitted in a multi-beam transmission method that forms multiple 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).

[0152] In step 1205, the UE (1210) transmits a feedback signal to the base station (1220). The feedback signal indicates at least one beam selected by the UE (1210). The UE (1210) may select at least one preferred beam based on the measurement signals received in step 1203. In step 1207, the UE (1210) and the base station (1220) perform communication. At this time, the UE (1210) and the base station (1220) may perform communication using the beam selected in step 1205. If channel reciprocity is established, the transmission beam of the UE (1210) may also be determined through steps 1203 and 1205, and thus, the transmission operation of the UE (1210) may also be performed using the beam selected in step 1205. If channel reciprocity is not established, a procedure including transmitting measurement signals of the UE (1210) and transmitting feedback signals of the base station (1220) may be performed to determine the transmission beam of the UE (1210). In step 1207, operations according to various embodiments described below may be performed.

[0153] Specific embodiments of the present disclosure

[0154] The present disclosure relates to a technology for transmitting or receiving a wireless signal in a wireless communication system, and for more efficiently using a channel by using a third device between a base station and a terminal. Here, the third device is a device that can change the phase and / or intensity of a signal incident on the device, and may be referred to as a reconfigurable intelligent surface (RIS), an active RIS, an intelligent reflecting surface (IRS), an intelligent reflecting surface, an intelligent surface, a coverage enhancement device, an adaptive coverage device, an intelligent coverage device, a channel control device, a reconfigurable device, a reconfigurable relay node, an intermediate node, or other terms having equivalent technical meanings thereto, and is not limited to a particular name.

[0155] Figure 13 illustrates an example of a communication scenario using RIS according to one embodiment of the present disclosure. In 6G mobile communications, which require high spectral efficiency, the use of ultra-high frequency bands is essential, and RIS is attracting attention as a key candidate technology to compensate for the resulting low penetration and coverage. RIS, which can artificially reconstruct the wireless radio environment, can achieve high system gain and coverage at low cost. For convenience of explanation, the following describes a case where a base station uses RIS, but it is not limited to RIS. The methods and procedures described in this disclosure can be performed between a base station and a terminal using a device capable of changing the phase and / or intensity of an incident signal.

[0156] RIS (1330) improves communication performance by securing a non-line of sight (NLoS) path when the line of sight path between a base station (BS) (1310) and user equipment (UE) (1320) is blocked, as shown in FIG. 13. RIS (1330) converts an incident radio wave into a specific reflected wave or refracted wave. At this time, the surface of RIS (1330) is configured with unit cells made of reconfigurable elements appropriately arranged. RIS (1330) dynamically adjusts the amplitude, phase, polarization, etc. of the radio wave by independently programmable the unit cells constituting the surface, and generally controls the unit cells through IC-based elements. This element can be implemented through a transistor-based IC chip such as a varactor diode or a PIN diode. The impedance of this element is determined according to the applied bias voltage, and the effective permittivity and reflection coefficient change as parameters accordingly. This allows for additional phase shift during the reflection process, which can be used to change the boundary conditions to create any desired reflection angle.

[0157] However, there is a drawback that the signal reflected through RIS suffers from high path loss. To overcome this, an active reconfigurable intelligent surface (active RIS) has been proposed that can not only adjust the phase of the signal when reflecting the signal from RIS, but also amplify the signal intensity. Since active RIS can control the signal intensity, communication performance can be improved compared to when using a RIS composed of conventional passive components.

[0158] However, existing methods assume that the base station has accurate channel state information (CSI). However, estimation errors inevitably occur during the channel estimation process, making it impossible for the base station to accurately obtain the channel state through channel measurements, etc. When active RIS is used, the ability to amplify the incident signal can increase the impact of estimation errors, potentially resulting in serious performance degradation. Therefore, to utilize active RIS in a communication system, channel estimation errors must be considered when configuring the base station's beamformer and the RIS reflection coefficients.

[0159] The symbols used in this disclosure are as follows.

[0160] x: Vertical vectorx, indicated in bold.

[0161] A: Matrix A, indicated in bold.

[0162] and : Transpose and Hermitian transpose of matrix A

[0163] : vector a value

[0164] : Frobenius-norm value of matrix A

[0165] : A diagonal matrix with each element of vector a as a diagonal component

[0166] : A vector of size m×1 with all terms being 0

[0167] : unit matrix of size m×m

[0168] : Mean vector and covariance Multivariate normal distribution with

[0169] : Differential entropy

[0170] : Mutual information

[0171] : The set of all positive matrices of size m×n

[0172] : The set of all complex matrices of size m×n

[0173] The terms used in this disclosure are as follows.

[0174] : Number of base station antennas

[0175] : Number of users

[0176] : Total number of RIS components

[0177] : Base station and Downlink channel between the th user

[0178] : Base station and Estimated channel between the th user

[0179] : Base station and Estimation error of the channel between the th user

[0180] : Base station and Estimated error variance of the channel between the th user

[0181] : RIS and Downlink channel between the th user

[0182] : RIS and Estimated channel between the th user

[0183] : RIS and Estimation error of the channel between the th user

[0184] : RIS and Estimated error variance of the channel between the th user

[0185] : Downlink channel between base station and RIS

[0186] : The relative amount of uncertainty in channel state information

[0187] : Transmission symbol for the th user

[0188] : Beamformer for the th user

[0189] : Reflection coefficient matrix of RIS

[0190] : Reflection coefficient vector of RIS

[0191] : Maximum amplification gain of each RIS element

[0192] Noise from the th user

[0193] : Noise generated by RIS

[0194] : Noise variance at the kth user

[0195] : Noise distribution in RIS

[0196] : Maximum transmission power at BS

[0197] : Maximum power at RIS

[0198] The present disclosure proposes a method for determining beamformer coefficients of a base station and reflection coefficients of RIS considering channel estimation errors in a multi-user multiple-input single-output (MU-MISO) downlink system utilizing Active RIS.

[0199] In a MU-MISO downlink system utilizing Active RIS, the downlink signal received by the kth user can be expressed as in [Mathematical Formula 1] below.

[0200]

[0201] In [Equation 1], means the reflection coefficient matrix of RIS, means that the reflection coefficient matrix is ​​expressed as a vector.

[0202] Here, the size that can amplify the signal to the maximum for each RIS element is can be limited to. The noise generated in RIS can be modeled as . In active RIS, since noise is also amplified when a signal is amplified, if the noise generated in RIS is not taken into account, optimization may not be performed to the desired communication quality. In addition, in active RIS, since an amplifier is used together with a phase shift circuit for each element, power consumption in RIS occurs as shown in [Mathematical Formula 2] below.

[0203]

[0204] In [Equation 2], refers to the strength of the signal reflected through RIS, means maximum power in RIS.

[0205] Since RIS does not have baseband signal processing capabilities, it may be difficult for the base station to obtain accurate channel state information for individual channels related to RIS. Therefore, in this disclosure, it is assumed that there are estimation errors for the channel between the base station and the user and the channel between the RIS and the user. Channel between the base station and the kth user and the channel between RIS and the kth user can be expressed as in [Mathematical Formula 3] below.

[0206]

[0207] In [Equation 3], denotes the estimated channel between the base station and the kth user, denotes the estimated channel between RIS and the kth user, means the estimation error of the channel between the base station and the kth user, represents the estimation error of the channel between RIS and the kth user. Each estimation error is subject to a statistical channel state information error model, and each estimation error is multivariately normal distributed. and Follows.

[0208] The locations of the base station and the RIS can be fixed, unlike the user, and the base station is assumed to have acquired perfect channel state information about the channel between the base station and the RIS.

[0209] In a communication environment using active RIS, the estimation error is amplified, so the beamformer coefficient of the base station and the reflection coefficient of the RIS cannot be determined based on the sum rate. Therefore, the present disclosure proposes a method for determining the beamformer coefficient of the base station and the reflection coefficient of the RIS based on the minimum transmission rate that considers the worst case for each user. The problem (P1) of determining the beamformer coefficient and the reflection coefficient of the base station based on the minimum transmission rate can be expressed as in [Mathematical Equation 4] below.

[0210]

[0211] In [Equation 4], refers to the beamformer coefficient of the base station, means the reflection coefficient of RIS, refers to the sum of the minimum transmission rates of users, means the minimum transmission rate of the kth user.

[0212] Assuming a statistical channel state information error model, it can be expressed as in [Mathematical Formula 5] below.

[0213]

[0214] In [Equation 5], denotes the effective estimated channel between the base station and the kth user, stands for interference-plus-noise, which takes into account the statistical characteristics of the estimation error of the channel.

[0215] Valid estimation channel Interference and noise considering the statistical characteristics of the estimation error can be expressed as in [Mathematical Formula 6] below.

[0216]

[0217] That is, referring to the above [Mathematical Equations 5] and [Mathematical Equations 6], the minimum transmission rate of the kth user can be determined based on the variance of the estimation error, and thus the variance of the channel state information error can be taken into account. The variance of the estimation error is assumed to have been previously acquired at the base station.

[0218] For convenience of explanation, below is a set containing channel information known to the base station. is defined as follows. For the kth user, the mutual information between the transmitted symbol and the received signal can be expressed as differential entropy as in [Mathematical Formula 7] below.

[0219]

[0220] In [Equation 7], refers to the channel information known to the base station, denotes the transmission symbol for the kth user, means the reception signal of the kth user in downlink transmission, Is If , it means the mutual information between the transmitted symbol and the received signal for the kth user, Is Given, denotes the differential entropy of the transmitted symbol for the kth user, Is and Given, it means the differential entropy of the transmitted symbol for the kth user.

[0221] Assuming that the transmitted symbols follow a normal distribution, can be expressed as the second term of [Equation 7]. The upper bound of can be expressed as in [Mathematical Formula 8] below.

[0222]

[0223] In [Equation 8], represents an arbitrary constant. Inequality (a) holds because entropy decreases when a condition is added, and inequality (b) holds because the normal distribution has the largest entropy among probability distributions with the same variance. Afterwards, the result shown in [Mathematical Formula 9] below can be obtained.

[0224]

[0225] In [Equation 9], Is It means the correlation between Is It means the dispersion of .

[0226] To minimize the upper bound of the constant If we set the weight of the minimum mean squared error, it can be expressed as in [Mathematical Formula 10] below.

[0227]

[0228] Using [Equation 10] The variance can be calculated as shown in [Mathematical Formula 11] below.

[0229]

[0230] thus, The upper limit can be expressed as in [Mathematical Formula 12] below.

[0231]

[0232] thus silver Assuming that [Equation 7] is rearranged into [Equation 12], the lower bound of the mutual information can be obtained as in [Equation 13] below.

[0233]

[0234] The objective function of problem (P1) is and are not jointly concave, and the constraint of problem (P1) is It is also non-convex for the variables. Therefore, problem (P1) cannot be considered a convex optimization problem. Therefore, while optimization through problem (P1) is possible, it may require very complex computations.

[0235] The present disclosure is to solve the non-convex problem (P1), We propose a method for optimization using the lower bound of . Specifically, for each problem (P1), It is transformed into a method that maximizes the sum of the lower bounds of . The lower bound of can be determined in a manner similar to the method of weighted minimum mean squared error minimization. Specifically, The lower bound of is from the following proposition [Mathematical Formula 14] can be derived as follows.

[0236]

[0237] In [Equation 14], , means auxiliary variable, constant c and function is as follows [Mathematical Formula 15].

[0238]

[0239] Below, a method for proving proposition [Equation 14] is described.

[0240] First, the function and the point that satisfies the first-order optimality condition is defined as If defined as such, the equations of [Mathematical Formula 16] below must be satisfied.

[0241]

[0242] If we calculate the point that satisfies the equations of [Equation 16], it is as shown in [Equation 17] below.

[0243]

[0244] function If we substitute the variables obtained in [Equation 17], is established. Function Considering the concavity of Since the inequality holds, the following [Mathematical Formula 18] is satisfied.

[0245]

[0246] Since [Equation 18] is the same as [Equation 14], proposition [Equation 14] is proven.

[0247] Therefore, by using the lower bound derived from [Equation 14], problem (P1) can be converted into problem (P2) as in [Equation 19] below.

[0248]

[0249] In [Equation 19], and means auxiliary variable.

[0250] Although the lower bound of the minimum transmission rate, which is easy to handle for optimizing the parameters through problem (P2), is considered, the objective function of problem (P2) is variable , , and are not jointly concave. However, the objective function of problem (P2) has the characteristic of being concave for each variable when other variables are fixed. Therefore, the present disclosure proposes a method using an alternating optimization algorithm to efficiently solve problem (P2).

[0251] First, and and fix the auxiliary variable and Optimization is performed on all constraints of (P2). and Since only the problem (P2) is related, the problem (P2) can be simplified and expressed as the problem (P2.1) as shown in [Mathematical Formula 20] below.

[0252]

[0253] The optimal solutions of the objective function of [Equation 20] and can be determined in the same way as [Mathematical Formula 17].

[0254] Second, the beamformer coefficient of the base station Optimize. At this time, All other variables are fixed. If terms not related to the beamformer coefficients are omitted, problem (P2) can be expressed as problem (P2.2) as in [Mathematical Equation 21] below.

[0255]

[0256] In [Equation 21], the function at Expanding the terms expressed as squares of absolute values ​​and the terms expressed as squares of absolute values Is can be expressed in quadratic form. Therefore, Is For each column vector of , it is convex and according to the definition of a convex function Is is convex. Therefore, since the objective function is convex and all constraints in problem (P2.2) are also convex sets, (P2.2) is a convex optimization problem, and the optimal solution is can be obtained.

[0257] Finally, fixing other variables, the reflection coefficient vector of RIS Optimize. In this case, problem (P2) can be expressed as problem (P2.3) as in [Mathematical Formula 22] below.

[0258]

[0259] In [Mathematical Formula 22], the function Control the order of the variables If we organize the terms expressed as squares of the absolute values, Is is expressed in the quadratic form, is convex. Therefore, the objective function is The objective function is convex as in is convex, and the two constraints in (P2.3) are also convex sets. Therefore, the problem (P2.3) has an optimal solution. It can be solved as a convex optimization problem where .

[0260] An example of an algorithm for optimizing beamformer coefficients and reflection coefficients can be presented as shown in [Table 3] below.

[0261] Algorithm 1Proposed robust transmission design for active RIS-aided MU-MISO systemsInitialize1: Set , , and 2: Initialize and Iterative update3:for do4: Calculate and by [Equation 16]5: Obtain from (P2.2)6: Obtain from (P2.3)7: Calculate by [Equation 5]8:if then9:Break10:end if11:end for

[0262] The base station adjusts the beamformer coefficients to satisfy the base station's transmit power limit and the power limit in the RIS. and reflection coefficient of RIS Sets the initial value of . The initial value can be determined randomly within a range that satisfies the constraints, or can be determined as a pre-configured setting value.

[0263] Afterwards, the shift optimization algorithm is performed. The base station Fixing and through the problem (P2.1) can be obtained. Specifically can be derived through [Mathematical Formula 17]. The base station is Fix and through the problem (P2.2) can be obtained. The base station is , and through the problem (P2.3) can be obtained.

[0264] The algorithm in [Table 3] is the sum of the minimum transmission rates. The increase in the threshold is or less or iteration number This maximum value is It is repeated until the optimal solution is reached. Since the optimal solution is obtained at each stage of Problem (P2.1), Problem (P2.2) and Problem (P2.3), increases monotonically with each iteration of the algorithm. Due to the power limitations of the base station and RIS, There exists an upper bound. Therefore, due to the nature of a monotonically increasing sequence with an upper bound, Algorithm 1 is guaranteed to converge to a specific value. Therefore, the base station can be configured to terminate the algorithm when the sum of the minimum transmission rates of the previous step and the minimum transmission rate of the current step is less than or equal to a preset threshold value.

[0265] FIG. 14 illustrates an example of a procedure in which a base station transmits and / or receives a data signal using an intermediate node according to one embodiment of the present disclosure. In FIG. 14 , the intermediate node refers to a device capable of transmitting a reflected signal of an incident signal transmitted by the base station to a terminal. Here, the reflected signal may be a signal in which the phase and / or intensity of the incident signal is changed by the intermediate node. The intermediate node is assumed to be controlled by the base station. For convenience of explanation, in FIG. 14 , the intermediate node is assumed to be a reflective surface capable of simultaneously changing the phase of the reflected signal and amplifying the reflected signal through an active element.

[0266] Referring to Figure 14, at step S1401, the base station performs a connection establishment procedure with the terminal. To perform the connection establishment procedure, the base station may perform an initial connection procedure with the terminal. The initial connection procedure may be performed using a combination of all or part of the procedures described above in Figure 11, and may be performed based on a synchronization signal.

[0267] In step S1403, the base station performs a channel measurement procedure. Channel measurement can be performed by the terminal or the base station. If the base station performs channel measurement, the base station can request the terminal to transmit a reference signal. The base station receives the reference signal from the terminal and performs channel measurement based on the received reference signal. Through the measurement procedure, the base station can obtain information about the channel between the base station and the terminal, the channel between the base station and the intermediate node, and the channel between the intermediate node and the terminal.

[0268] In step S1405, the base station determines control information of the beamformer and the intermediate node based on the channel measurement. The base station can determine control information of the beamformer and the intermediate node such that the sum of the minimum transmission rates of each user being served is maximized. Here, the beamformer information may include a beamformer coefficient. The control information of the intermediate node may be referred to as a reflection coefficient of the intermediate node, a transmission coefficient of the intermediate node, a relay coefficient of the intermediate node, etc. The control information of the intermediate node may include information about a phase change value of an incident signal and / or a strength change value of the incident signal. The base station may use an objective function generated based on the sum of the lower bounds of the minimum transmission rates to determine the control information of the beamformer and the intermediate node.

[0269] In step S1407, the base station transmits resource allocation information to the terminal. This resource allocation information may be transmitted to the terminal using downlink control information (DCI). The resource allocation information may include information regarding frequency resources or time resources for performing communication.

[0270] In step S1409, the base station controls the intermediate node based on the control information of the determined intermediate node. If the control information of the intermediate node supported by the intermediate node is predetermined, the control information of the intermediate node can be indicated by an index value using a table. In this case, the base station transmits the index value using the table, and the intermediate node can reflect the incident signal through the control information of the intermediate node corresponding to the index value. Therefore, the base station can control the signal transmitted by the intermediate node to the terminal by transmitting the control information of the intermediate node or the index value corresponding to the control information of the intermediate node to the intermediate node. If the intermediate node has a separate controller, the base station can transmit the reflection coefficient to the controller, and the controller of the intermediate node can change the characteristics of the active elements.

[0271] In step S1411, the base station transmits and / or receives data signals to the terminal via an intermediate node. The base station can form a beam based on optimized beamformer coefficients and transmit and / or receive data signals via the intermediate node.

[0272] FIG. 15 illustrates an example of a procedure in which a terminal transmits a data signal using an intermediate node according to one embodiment of the present disclosure. In FIG. 15 , the intermediate node refers to a device capable of transmitting a reflected signal of an incident signal transmitted by a base station to the terminal. Here, the reflected signal may be a signal in which the phase and / or intensity of the incident signal is changed by the intermediate node. The intermediate node is assumed to be controlled by the base station. For convenience of explanation, in FIG. 15 , the intermediate node is assumed to be a reflective surface capable of simultaneously changing the phase of the reflected signal and amplifying the reflected signal through an active element.

[0273] Referring to Figure 15, at step S1501, the terminal performs a connection establishment procedure with the base station. To perform the connection establishment procedure, the terminal may perform an initial connection procedure with the base station. The initial connection procedure may be performed using a combination of all or part of the procedures described above in Figure 11, and may be performed based on a synchronization signal.

[0274] In step S1503, the terminal performs a channel measurement procedure. The channel measurement may be performed by the terminal or the base station. If the base station performs the channel measurement, the terminal may receive a request for reference signal transmission from the base station and transmit a reference signal to the base station in response to the request for reference signal transmission. If the terminal performs the channel measurement, the terminal receives a reference signal from the base station and performs measurement based on the received reference signal. The terminal may transmit measured channel information to the base station. Through the measurement procedure, information about the channel between the base station and the terminal, the channel between the base station and the intermediate node, and the channel between the intermediate node and the terminal may be obtained.

[0275] In step S1505, the terminal receives resource allocation information from the base station. The resource allocation information may be included in downlink control information (DCI). The resource allocation information may include information regarding frequency resources or time resources for performing communications.

[0276] In step S1507, the terminal transmits and / or receives data signals from the base station via an intermediate node. The terminal can receive data signals via a beam formed based on optimized beamformer coefficients determined based on measurement results. The intermediate node can be controlled by the base station based on the measurement results.

[0277] FIG. 16 illustrates an example of a procedure for a base station to determine beamformer coefficients and reflection coefficients of intermediate nodes based on measurement results according to one embodiment of the present disclosure. In FIG. 16, it is assumed that the base station has acquired information about a channel between the base station and a terminal, a channel between the base station and an intermediate node, and a channel between an intermediate node and a terminal based on the measurement procedure. The beamformer coefficients and the reflection coefficients of the intermediate nodes may be included in the control information of the beamformer and intermediate nodes of the base station.

[0278] Referring to Fig. 16, in step S1601, the base station defines an objective function using the lower bound of the minimum transmission rates of each user. The base station can define the sum of the minimum transmission rates of the terminals as the objective function, as in [Mathematical Formula 4], and determine the beamformer coefficients and the reflection coefficients of the intermediate nodes so that the objective function is maximized. Here, the minimum transmission rates of the terminals can be defined based on the statistical characteristics of the channel estimation error, as in [Mathematical Formula 5]. In Fig. 16, the base station can determine the beamformer coefficients and the reflection coefficients of the intermediate nodes so that the sum of the lower bounds of the minimum transmission rates of the terminals is maximized, as in [Mathematical Formula 19], in order to reduce the complexity of the optimization problem.

[0279] In step S1603, the base station initializes variables related to the objective function. The base station can initialize beamformer coefficients and intermediate node reflection coefficients, and the initialization can be determined to satisfy constraints such as the maximum amplification gain of each element of the intermediate node, the maximum transmission power of the intermediate node, and the maximum transmission power of the base station. The beamformer coefficients and the reflection coefficients of the intermediate nodes can be determined to arbitrary values ​​that satisfy the constraints, or pre-determined initial values ​​can be used.

[0280] In step S1605, the base station performs an alternating optimization algorithm. The base station can determine the beamformer coefficients and the reflection coefficients of the intermediate nodes that maximize the objective function. At this time, an alternating optimization algorithm can be performed to reduce the complexity of the problem. Therefore, first, the base station can fix the beamformer coefficients and the reflection coefficients of the intermediate nodes, as in problem (P2.1) of [Equation 20], and perform optimization on the auxiliary variables first. Second, the base station can fix the remaining variables, as in problem (P2.2) of [Equation 21], and perform optimization on the beamformer coefficients. Third, the base station can fix the remaining variables, as in problem (P2.3) of [Equation 22], and perform optimization on the reflection coefficients of the intermediate nodes.

[0281] At step S1607, the base station determines whether the objective function has converged. If the change in the objective function is less than a preset threshold, the base station can determine that the objective function has converged. If the objective function has converged, the base station uses the beamformer coefficients and the reflection coefficients of the intermediate nodes at the time of convergence to communicate with the terminal.

[0282] Although the alternating optimization algorithm is performed in the order of problem (P2.1), problem (P2.2), and problem (P2.3) in Fig. 16, the alternating optimization algorithm may be performed in a different order. For example, the alternating optimization algorithm may be performed in the order of problem (P2.1), problem (P2.3), and problem (P2.2), and the order of problem (P2.1), problem (P2.2), and problem (P2.3) may be determined in various ways.

[0283] Figure 17 illustrates an example of a timing diagram according to an embodiment of the present disclosure. The base station may assume that channels do not change within a specific correlation time. Referring to Figure 17, represents the coherence time, and it can be assumed that the channel between the base station and the terminal, the channel between the base station and the intermediate node, and the channel between the intermediate node and the terminal do not change during the time interval. If the base station and the terminal perform time division duplex communication, During this time, the base station receives pilot signals from the terminal and estimates the uplink channel. The base station estimates the channels between the base station and the user, and the channels between the intermediate node and the user. After calculating the value and setting the relative amount δ of uncertainty of channel state information, the beamformer coefficient of the base station and the reflection coefficient of the intermediate node can be calculated using the algorithm proposed in this disclosure. In time division duplex communication, the channel reciprocity of the uplink and downlink can be utilized. The base station can consider the estimated uplink channel to be the same as the downlink channel. Downlink data transmission can be performed during the time.

[0284] Additionally, the base station can optimize the reflection coefficient of the intermediate node using the procedure of FIG. 16 based on information related to the estimated channel. At this time, the base station can assume that the channel between the base station and the terminal, the channel between the base station and the intermediate node, and the channel between the intermediate node and the terminal remain unchanged during the coherence time period. Therefore, the base station can maintain information about the corresponding channels during the coherence time period and optimize the beamformer coefficient and the reflection coefficient of the intermediate node.

[0285] FIG. 18 illustrates an example of signaling for transmitting and / or receiving a data signal in a communication environment in which an intermediate node (1820) is utilized according to one embodiment of the present disclosure. In FIG. 18 , for convenience of explanation, it is assumed that a terminal (1830) transmits a reference signal. However, this does not necessarily mean that the terminal (1830) must transmit the reference signal. Therefore, the procedure can be replaced with one in which the base station (1810) transmits a reference signal to the terminal, and the terminal transmits the measurement results of the received reference signal to the base station (1810).

[0286] Referring to FIG. 18, in steps S1801 and S1803, the base station (1810) transmits a reference signal request message to the terminal (1830), and the terminal (1830) transmits a reference signal to the base station (1810). At this time, in order to estimate all of the channels between the base station (1810) and the terminal (1830), the channels between the base station (1810) and the intermediate node (1820), and the channels between the intermediate node (1820) and the terminal (1830), steps S1801 and S1803 may be repeatedly performed by changing the active element control values ​​of the intermediate node (1820).

[0287] In step S1805, the base station (1810) determines the beamformer coefficient and the reflection coefficient of the intermediate node (1820). The information about the channel estimated in steps S1801 and S1803 can be used to determine the beamformer coefficient and the reflection coefficient of the intermediate node (1820). By utilizing the characteristic of channel reciprocity, the uplink channel information can be directly used for downlink data transmission. The beamformer coefficient and the reflection coefficient of the intermediate node (1820) can be determined based on the estimated channel information so that the sum of the minimum transmission rates of the terminals is maximized. Here, the minimum transmission rate of the terminals can be defined based on the statistical characteristics of the channel estimation error as in [Mathematical Formula 5]. The base station can assume that the downlink channel is also the same by utilizing the uplink channel estimation result by utilizing the characteristic of channel reciprocity. For example, the base station can determine that the corresponding channel measurement is valid during the correlation time defined in FIG. 17. Therefore, the base station can set the communication to be performed using the beamformer coefficient and reflection coefficient optimized in step S1805 during the correlation time. Here, the correlation time can be measured using a timer.

[0288] In step S1807, the base station (1810) transmits control information of the intermediate node (1820) to the intermediate node (1820). The control information of the intermediate node (1820) includes information regarding the reflection coefficient of the intermediate node (1820) and can be transmitted to the intermediate node (1820) in a wired or wireless manner.

[0289] In step S1807, the terminal (1830) transmits and / or receives a data signal to the base station (1810). Before receiving the data signal, the terminal (1830) may receive resource allocation information from the base station (1810). The base station (1810) may determine the setting values ​​of the elements of the intermediate node (1820) based on channel measurement, and transmit and / or receive downlink data from the terminal.

[0290] Using the procedures described above in this disclosure, beamformer coefficients and reflection coefficients of intermediate nodes can be optimized considering channel estimation errors, and efficient communication can be achieved using the optimized parameters. In particular, when the intermediate node is an active RIS capable of modifying both the phase and intensity of an incident signal, the effect of channel estimation errors can be amplified, so that the intermediate node can be efficiently controlled in a communication environment with channel estimation errors. Below, the performance of the proposed technique is described through specific embodiments of the present disclosure.

[0291] The base station is arranged in a uniform planar array (UPA) form. With a dog's antenna It is assumed that the base station is supporting 8 users. The intermediate node uses active RIS, and it is assumed that there are M=8×8 or M=12×8 active elements arranged in the UPA configuration. The base station is located at (0m, 0m), the active RIS is located at (500m, 20m), and the users are assumed to be randomly placed within a circle with a center at (500m, 0m) and a radius of 10m. The noise power spectrum density is set to -174dBm with a bandwidth of 10MHz, and the noise distribution of the active RIS and the users is was set to . The power limit of active RIS is is assumed. Also, the estimated channels , , Rician fading is assumed as in [Mathematical Equation 4]. The path loss at a distance of 1 m is assumed to be -30 dB. In addition, the path-loss exponents of the channels between the base station and the user, the channels between the active RIS and the user, and the channels between the base station and the active RIS are assumed to be 4.0, 2.3, and 2.5, respectively. The estimation error variance of the channel state information is and It appears as represents the relative amount of CSI uncertainty.

[0292] The performance analysis of the technique proposed in this disclosure is performed based on the performance indicator, the sum transmission rate. The performance indicator is as shown in [Mathematical Equation 23] below.

[0293]

[0294] In [Equation 23], refers to the valid downlink channel between the base station and the kth user.

[0295] To compare performance, situations in which channel state information is obtained without measurement errors (hereinafter referred to as perfect CSI) and situations in which it is not robust to measurement errors (hereinafter referred to as non-robust) were considered. In the case of perfect CSI, since all channels are known accurately, the beamformer coefficients of the base station are adjusted to maximize the sum transmission rate of [Equation 23]. and reflection coefficient in active RIS are jointly optimized.

[0296] In the non-robust case, the reflection coefficients in the beamformer and active RIS are optimized similarly to the perfect CSI case, but the estimated channels are used instead of the actual accurate channel values. and In both cases, the problem is transformed into maximizing the lower bound of the objective function, similar to the proposed technique, and the solution is assumed to be obtained using the alternating optimization technique.

[0297] Fig. 19 illustrates a first example of a sum transmission rate according to the transmission power of a base station according to an embodiment of the present disclosure. Fig. 20 illustrates a second example of a sum transmission rate according to the transmission power of a base station according to an embodiment of the present disclosure. Figs. 19 and 20 illustrate that the maximum amplification gain of each active RIS element is was set to be . Figure 19 shows the relative amount of uncertainty in channel state information. 20 shows the performance when the relative amount of uncertainty in the channel state information is The performance when channel state information is acquired without measurement errors is indicated as perfect CSI, the situation that is not robust to measurement errors is indicated as non-robust, and the technique proposed in this disclosure is indicated as 'Proposed'.

[0298] It can be seen that the proposed technique in this disclosure achieves a higher sum transmission rate than in non-robust situations. The uncertainty is greater. It was confirmed that the performance difference gradually increases as the base station's transmission power increases. Therefore, the proposed method of this disclosure can significantly improve performance in communication environments where the transmission power is high and the impact of estimation errors is significant, and can be effectively used in cases where channel conditions are poor. On the other hand, in non-robust situations, since only the estimated channel is utilized, significant performance degradation occurs when the transmission power increases.

[0299] Fig. 21 illustrates an example of the sum transmission rate according to the maximum amplification gain of each active RIS element according to one embodiment of the present disclosure. In Fig. 21, the transmission power of the base station is is assumed, and the relative amount of uncertainty is is assumed. Referring to Fig. 21, it is confirmed that the technique proposed in this disclosure shows better performance than the non-robust situation as the maximum amplification gain increases. In particular, when the maximum amplification gain value of each active RIS element is large, the technique proposed in this disclosure shows excellent performance. This is because as the maximum amplification gain of each active RIS element increases, the channel estimation error between the active RIS and the user can be further amplified through the active RIS. Therefore, a large mismatch in the effective channel can appear.

[0300] Additionally, in FIGS. 19 to 21, it can be seen that when the number of active RIS elements is greater, the technique proposed in the present disclosure exhibits higher sum transmission rate performance than in non-robust situations.

[0301] Referring to Figures 19 to 21, utilizing the techniques proposed in this disclosure can enable efficient communication while taking channel estimation errors into account. To achieve this, the reflection coefficients of the base station's beamformer and the active RIS are optimized. Using the techniques proposed in this disclosure can achieve a higher total transmission rate than optimizing solely using the estimated channel without considering estimation errors. Therefore, in situations where estimation errors are significantly impacted, such as systems with active RIS, utilizing the techniques proposed in this disclosure can enhance communication efficiency.

[0302] Below, examples of wireless device utilization to which various embodiments of the present disclosure are applied are described.

[0303] Figure 22 illustrates an example of a wireless device applicable to the present disclosure. The wireless device may be implemented in various forms depending on the use case / service (see Figure 1).

[0304] Referring to FIG. 22, the wireless device (200) corresponds to the wireless device (200) of FIG. 2 and may be composed of various elements, components, units / units, and / or modules. For example, the wireless device (200) may include a communication unit (210), a control unit (220), a memory unit (230), and additional elements (240). The communication unit may include a communication circuit (212) and a transceiver(s) (214). For example, the communication circuit (212) may include one or more processors (202) and / or one or more memories (204) of FIG. 2. For example, the transceiver(s) (214) may include one or more transceivers (206) and / or one or more antennas (208) of FIG. 2. The control unit (220) is electrically connected to the communication unit (210), the memory unit (230), and the additional elements (240) and controls the overall operations of the wireless device. For example, the control unit (220) can control the electrical / mechanical operations of the wireless device based on the program / code / command / information stored in the memory unit (230). In addition, the control unit (220) can transmit information stored in the memory unit (230) to an external device (e.g., another communication device) via a wireless / wired interface through the communication unit (210), or store information received from an external device (e.g., another communication device) via a wireless / wired interface in the memory unit (230).

[0305] The additional element (240) may be configured in various ways depending on the type of the wireless device. For example, the additional element (240) may include at least one of a power unit / battery, an input / output unit (I / O unit), a driving unit, and a computing unit. Although not limited thereto, the wireless device may be implemented in the form of a robot (Fig. 1, 100a), a vehicle (Fig. 1, 100b-1, 100b-2), an XR device (Fig. 1, 100c), a portable device (Fig. 1, 100d), a home appliance (Fig. 1, 100e), an IoT device (Fig. 1, 100f), a digital broadcasting terminal, a hologram device, a public safety device, an MTC device, a medical device, a fintech device (or a financial device), a security device, a climate / environmental device, an AI server / device (Fig. 1, 400), a base station (Fig. 1, 200), a network node, etc. Wireless devices may be mobile or stationary depending on the use / service.

[0306] In FIG. 22, various elements, components, units / parts, and / or modules within the wireless device (200) may be entirely interconnected via a wired interface, or at least some may be wirelessly connected via a communication unit (210). For example, within the wireless device (200), the control unit (220) and the communication unit (210) may be wired, and the control unit (220) and a first unit (e.g., 230, 240) may be wirelessly connected via the communication unit (210). In addition, each element, component, unit / part, and / or module within the wireless device (200) may further include one or more elements. For example, the control unit (220) may be composed of a set of one or more processors. For example, the control unit (220) may be composed of a set of a communication control processor, an application processor, an electronic control unit (ECU), a graphics processing processor, a memory control processor, etc. As another example, the memory unit (130) may be composed of RAM (Random Access Memory), DRAM (Dynamic RAM), ROM (Read Only Memory), flash memory, volatile memory, non-volatile memory, and / or a combination thereof.

[0307] Below, the implementation example of Fig. 22 is described in more detail with reference to the drawings.

[0308] Figure 23 illustrates examples of portable devices applicable to the present disclosure. Portable devices may include smartphones, smart pads, wearable devices (e.g., smartwatches, smartglasses), and portable computers (e.g., laptops). Portable devices may also be referred to as mobile stations (MS), user terminals (UT), mobile subscriber stations (MSS), subscriber stations (SS), advanced mobile stations (AMS), or wireless terminals (WT).

[0309] Referring to FIG. 23, the portable device (200) may include an antenna unit (208), a communication unit (210), a control unit (220), a memory unit (230), a power supply unit (240a), an interface unit (240b), and an input / output unit (240c). The antenna unit (208) may be configured as a part of the communication unit (210). Blocks 210 to 230 / 240a to 240c of FIG. 23 correspond to blocks 210 to 230 / 240 of FIG. 22, respectively.

[0310] The communication unit (210) can transmit and receive signals (e.g., data, control signals, etc.) with other wireless devices and base stations. The control unit (220) can control components of the mobile device (200) to perform various operations. The control unit (220) can include an AP (Application Processor). The memory unit (230) can store data / parameters / programs / codes / commands required for operating the mobile device (200). In addition, the memory unit (230) can store input / output data / information, etc. The power supply unit (240a) supplies power to the mobile device (200) and can include a wired / wireless charging circuit, a battery, etc. The interface unit (240b) can support connection between the mobile device (200) and other external devices. The interface unit (240b) can include various ports (e.g., audio input / output ports, video input / output ports) for connection with external devices. The input / output unit (240c) can input or output video information / signals, audio information / signals, data, and / or information input from a user. The input / output unit (240c) may include a camera, a microphone, a user input unit, a display unit (240d), a speaker, and / or a haptic module.

[0311] For example, in the case of data communication, the input / output unit (240c) obtains information / signals (e.g., touch, text, voice, image, video) input by the user, and the obtained information / signals can be stored in the memory unit (230). The communication unit (210) converts the information / signals stored in the memory into wireless signals, and can directly transmit the converted wireless signals to other wireless devices or to a base station. In addition, the communication unit (210) can receive wireless signals from other wireless devices or base stations, and then restore the received wireless signals to the original information / signals. The restored information / signals can be stored in the memory unit (230) and then output in various forms (e.g., text, voice, image, video, haptic) through the input / output unit (240c).

[0312] Figure 24 illustrates examples of vehicles or autonomous vehicles applicable to the present disclosure. The vehicles or autonomous vehicles may be implemented as mobile robots, cars, trains, manned or unmanned aerial vehicles (AVs), ships, etc.

[0313] Referring to FIG. 24, a vehicle or autonomous vehicle (200-1) may include an antenna unit (208-1), a communication unit (210-1), a control unit (220-1), a driving unit (240a-1), a power supply unit (240b-1), a sensor unit (240c-1), and an autonomous driving unit (240d-1). The antenna unit (208-1) may be configured as a part of the communication unit (210-1). Blocks 210-1 / 230-1 / 240a-1 to 240d-1 of FIG. 24 correspond to blocks 210 / 230 / 240 of FIG. 22, respectively.

[0314] The communication unit (210-1) can transmit and receive signals (e.g., data, control signals, etc.) with external devices such as other vehicles, base stations (e.g., base stations, roadside base stations (ROS), etc.), and servers. The control unit (220-1) can control elements of the vehicle or autonomous vehicle (200-1) to perform various operations. The control unit (220-1) may include an ECU (Electronic Control Unit). The drive unit (240a-1) can drive the vehicle or autonomous vehicle (200-1) on the ground. The drive unit (240a-1) may include an engine, a motor, a power train, wheels, brakes, a steering device, etc. The power supply unit (240b-1) supplies power to the vehicle or autonomous vehicle (200-1) and may include a wired / wireless charging circuit, a battery, etc. The sensor unit (240c-1) can obtain vehicle status, surrounding environment information, user information, etc. The sensor unit (240c-1) may include an IMU (inertial measurement unit) sensor, a collision sensor, a wheel sensor, a speed sensor, an incline sensor, a weight detection sensor, a heading sensor, a position module, a vehicle forward / backward sensor, a battery sensor, a fuel sensor, a tire sensor, a steering sensor, a temperature sensor, a humidity sensor, an ultrasonic sensor, an illuminance sensor, a pedal position sensor, etc. The autonomous driving unit (240d-1) may implement a technology for maintaining a driving lane, a technology for automatically controlling speed such as adaptive cruise control, a technology for automatically driving along a set path, a technology for automatically setting a path and driving when a destination is set, etc.

[0315] For example, the communication unit (210-1) can receive map data, traffic information data, etc. from an external server. The autonomous driving unit (240d-1) can generate an autonomous driving route and driving plan based on the acquired data. The control unit (220-1) can control the drive unit (240a-1) so that the vehicle or autonomous vehicle (200-1) moves along the autonomous driving route according to the driving plan (e.g., speed / direction control). During autonomous driving, the communication unit (210-1) can irregularly / periodically acquire the latest traffic information data from an external server and can acquire surrounding traffic information data from surrounding vehicles. In addition, during autonomous driving, the sensor unit (240c-1) can acquire vehicle status and surrounding environment information. The autonomous driving unit (240d-1) can update the autonomous driving route and driving plan based on newly acquired data / information. The communication unit (210-1) can transmit information regarding the vehicle location, autonomous driving route, driving plan, etc. to an external server. The external server can predict traffic information data in advance using AI technology, etc. based on information collected from the vehicle or autonomous vehicles, and provide the predicted traffic information data to the vehicle or autonomous vehicles. If the device (220-2) is an autonomous vehicle, it can perform the same procedure as the vehicle or autonomous vehicle (200-1). In addition, if the device (220-2) is a base station or a roadside base station, the device (220-2) can transmit data, control signals, etc. to the vehicle or autonomous vehicle (200-1) through the communication unit (210-2).

[0316] Figure 25 illustrates an example of a vehicle applicable to the present disclosure. The vehicle may also be implemented as a means of transportation, a train, an aircraft, a ship, etc. Referring to Figure 25, the vehicle (200) may include a communication unit (210), a control unit (220), a memory unit (230), an input / output unit (240a), and a position measurement unit (240b). Here, blocks 210 to 230 / 240a to 240b correspond to blocks 210 to 230 / 240 of Figure 22, respectively.

[0317] The communication unit (210) can transmit and receive signals (e.g., data, control signals, etc.) with other vehicles or external devices such as base stations. The control unit (220) can control components of the vehicle (200) to perform various operations. The memory unit (230) can store data / parameters / programs / codes / commands that support various functions of the vehicle (100). The input / output unit (240a) can output AR / VR objects based on information in the memory unit (230). The input / output unit (240a) can include a HUD. The position measurement unit (240b) can obtain position information of the vehicle (200). The position information can include absolute position information of the vehicle (200), position information within a driving line, acceleration information, position information with respect to surrounding vehicles, etc. The position measurement unit (240b) can include GPS and various sensors.

[0318] For example, the communication unit (210) of the vehicle (200) can receive map information, traffic information, etc. from an external server and store them in the memory unit (230). The location measurement unit (240b) can obtain vehicle location information through GPS and various sensors and store the information in the memory unit (230). The control unit (220) can create a virtual object based on the map information, traffic information, and vehicle location information, and the input / output unit (240a) can display the created virtual object on the vehicle window (240a-1, 240a-2). In addition, the control unit (220) can determine whether the vehicle (200) is being driven normally within the driving line based on the vehicle location information. If the vehicle (200) abnormally deviates from the driving line, the control unit (220) can display a warning on the vehicle window through the input / output unit (240a). Additionally, the control unit (220) can broadcast a warning message regarding driving abnormalities to surrounding vehicles through the communication unit (210). Depending on the situation, the control unit (220) can transmit vehicle location information and information regarding driving / vehicle abnormalities to relevant authorities through the communication unit (210).

[0319] Figure 26 illustrates examples of XR devices applicable to the present disclosure. The XR devices may be implemented as HMDs, head-up displays (HUDs) installed in vehicles, televisions, smartphones, computers, wearable devices, home appliances, digital signage, vehicles, robots, and the like.

[0320] Referring to FIG. 26, the XR device (200a) may include a communication unit (210), a control unit (220), a memory unit (230), an input / output unit (240a), a sensor unit (240b), and a power supply unit (240c). Here, blocks 210 to 230 / 240a to 240c of FIG. 26 correspond to blocks 210 to 230 / 240 of FIG. 22, respectively.

[0321] The communication unit (210) can transmit and receive signals (e.g., media data, control signals, etc.) with external devices such as other wireless devices, portable devices, or media servers. The media data can include videos, images, sounds, etc. The control unit (220) can control components of the XR device (200a) to perform various operations. For example, the control unit (220) can be configured to control and / or perform procedures such as video / image acquisition, (video / image) encoding, metadata generation and processing, etc. The memory unit (230) can store data / parameters / programs / codes / commands required for driving the XR device (200a) / generating XR objects. The input / output unit (240a) can obtain control information, data, etc. from the outside, and output the generated XR object. The input / output unit (240a) can include a camera, a microphone, a user input unit, a display unit, a speaker, and / or a haptic module. The sensor unit (240b) can obtain the XR device status, surrounding environment information, user information, etc. The sensor unit (240b) may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an RGB sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, a light sensor, a microphone, and / or a radar. The power supply unit (240c) supplies power to the XR device (200a) and may include a wired / wireless charging circuit, a battery, etc.

[0322] For example, the memory unit (230) of the XR device (200a) may include information (e.g., data, etc.) required for creating an XR object (e.g., AR / VR / MR object). The input / output unit (240a) may obtain a command to operate the XR device (200a) from the user, and the control unit (220) may operate the XR device (200a) according to the user's operating command. For example, when the user attempts to watch a movie, news, etc. through the XR device (200a), the control unit (220) may transmit content request information to another device (e.g., a mobile device (200b)) or a media server through the communication unit (230). The communication unit (230) may download / stream content such as movies and news from another device (e.g., a mobile device (200b)) or a media server to the memory unit (230). The control unit (220) controls and / or performs procedures such as video / image acquisition, (video / image) encoding, and metadata generation / processing for content, and can generate / output an XR object based on information about surrounding space or real objects acquired through the input / output unit (240a) / sensor unit (240b).

[0323] In addition, the XR device (200a) is wirelessly connected to the mobile device (200b) through the communication unit (210), and the operation of the XR device (200a) can be controlled by the mobile device (200b). For example, the mobile device (200b) can act as a controller for the XR device (200a). To this end, the XR device (200a) can obtain 3D location information of the mobile device (200b), and then generate and output an XR object corresponding to the mobile device (200b).

[0324] Figure 27 illustrates examples of robots applicable to the present disclosure. Robots can be classified into industrial, medical, household, and military types, depending on their intended use or field.

[0325] Referring to FIG. 27, the robot (200) may include a communication unit (210), a control unit (220), a memory unit (230), an input / output unit (240a), a sensor unit (240b), and a driving unit (240c). Here, blocks 210 to 230 / 240a to 240c of FIG. 27 correspond to blocks 210 to 230 / 240 of FIG. 22, respectively.

[0326] The communication unit (210) can transmit and receive signals (e.g., driving information, control signals, etc.) with external devices such as other wireless devices, other robots, or control servers. The control unit (220) can control components of the robot (200) to perform various operations. The memory unit (230) can store data / parameters / programs / codes / commands that support various functions of the robot (200). The input / output unit (240a) can obtain information from the outside of the robot (200) and output information to the outside of the robot (200). The input / output unit (240a) can include a camera, a microphone, a user input unit, a display unit, a speaker, and / or a haptic module. The sensor unit (240b) can obtain internal information of the robot (200), surrounding environment information, user information, etc. The sensor unit (240b) may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, a light sensor, a microphone, a radar, etc. The driving unit (240c) may perform various physical operations, such as moving the robot joints. In addition, the driving unit (240c) may enable the robot (200) to drive on the ground or fly in the air. The driving unit (240c) may include an actuator, a motor, wheels, brakes, propellers, etc.

[0327] Figure 28 illustrates an example of an AI device applicable to the present disclosure.

[0328] AI devices can be implemented as fixed or mobile devices, such as TVs, projectors, smartphones, PCs, laptops, digital broadcasting terminals, tablet PCs, wearable devices, set-top boxes (STBs), radios, washing machines, refrigerators, digital signage, robots, and vehicles.

[0329] Referring to FIG. 28, the AI ​​device (200) may include a communication unit (210), a control unit (220), a memory unit (230), an input / output unit (240a / 240b), a learning processor unit (240c), and a sensor unit (240d). Blocks 210 to 230 / 240a to 240d of FIG. 28 correspond to blocks 210 to 230 / 140 of FIG. 22, respectively.

[0330] The communication unit (210) can transmit and receive wired and wireless signals (e.g., sensor information, user input, learning models, control signals, etc.) to and from external devices such as other AI devices (e.g., 100a to 100f, 120 of FIG. 1) or AI servers (e.g., 100g of FIG. 1) using wired and wireless communication technology. To this end, the communication unit (210) can transmit information within the memory unit (230) to the external device or transfer a signal received from the external device to the memory unit (230).

[0331] The control unit (220) may determine at least one executable operation of the AI ​​device (200) based on information determined or generated using a data analysis algorithm or a machine learning algorithm. In addition, the control unit (220) may control components of the AI ​​device (200) to perform the determined operation. For example, the control unit (220) may request, search, receive, or utilize data from the learning processor unit (240c) or the memory unit (230), and may control components of the AI ​​device (200) to perform at least one executable operation, a predicted operation, or an operation determined to be desirable. In addition, the control unit (220) may collect history information including the operation contents of the AI ​​device (200) or user feedback on the operation, and store the collected history information in the memory unit (230) or the learning processor unit (240c), or transmit the collected history information to an external device such as an AI server (FIG. 1, 100g). The collected history information may be used to update a learning model.

[0332] The memory unit (230) can store data that supports various functions of the AI ​​device (200). For example, the memory unit (230) can store data obtained from the input unit (240a), data obtained from the communication unit (210), output data of the learning processor unit (240c), and data obtained from the sensing unit (140). In addition, the memory unit (230) can store control information and / or software codes necessary for the operation / execution of the control unit (220).

[0333] The input unit (240a) can obtain various types of data from the outside of the AI ​​device (200). For example, the input unit (220) can obtain learning data for model learning, input data to which the learning model will be applied, etc. The input unit (240a) may include a camera, a microphone, and / or a user input unit. The output unit (240b) may generate output related to vision, hearing, or touch. The output unit (240b) may include a display unit, a speaker, and / or a haptic module, etc. The sensing unit (140d) can obtain at least one of internal information of the AI ​​device (200), information about the surrounding environment of the AI ​​device (200), and user information using various sensors. The sensing unit (140d) may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an RGB sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, a light sensor, a microphone, and / or a radar, etc.

[0334] The learning processor unit (240c) can train a model composed of an artificial neural network using learning data. The learning processor unit (240c) can perform AI processing together with the learning processor unit of the AI ​​server (Fig. 1, 100g). The learning processor unit (240c) can process information received from an external device via the communication unit (210) and / or information stored in the memory unit (230). In addition, the output value of the learning processor unit (240c) can be transmitted to an external device via the communication unit (210) and / or stored in the memory unit (230).

[0335] The proposed methods described above can be implemented independently, but they can also be implemented as a combination (or merge) of some of the proposed methods. Rules can be defined so that the base station notifies the terminal of the applicability of the proposed methods (or information about the rules of the proposed methods) through a predefined signal (e.g., a physical layer signal or a higher layer signal).

[0336] The present disclosure may be embodied in other specific forms without departing from the technical ideas and essential features described herein. Therefore, the above detailed description should not be construed as limiting in all respects 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 equivalent scope of the present disclosure are intended to be included within the scope of the present disclosure. Furthermore, claims that are not explicitly cited in the claims may be combined to form an embodiment or incorporated into a new claim through a post-filing amendment.

[0337] Embodiments of the present disclosure can be applied to various wireless access systems. Examples of various wireless access systems include the 3rd Generation Partnership Project (3GPP) or 3GPP2 systems.

[0338] The embodiments of the present disclosure can be applied not only to the various wireless access systems described above, but also to all technical fields that utilize these various wireless access systems. Furthermore, the proposed method can also be applied to mmWave and THz communication systems utilizing ultra-high frequency bands.

[0339] Additionally, embodiments of the present disclosure can be applied to various applications such as autonomous vehicles and drones.

Claims

1. A method performed by a base station in a wireless communication system, A step of transmitting system information to a terminal; A step of performing an initial connection procedure with the above terminal; A step of transmitting setting information regarding channel measurement to the terminal; A step of performing a channel measurement procedure based on the above setting information; A step of determining a beamformer coefficient and a reflection coefficient of an intermediate node based on the sum of the minimum transmission rates of terminals derived based on the variance of the channel and channel state information errors measured in the above channel measurement procedure; a step of transmitting resource allocation information to the terminal; and A method comprising the step of transmitting a data signal to the terminal through the intermediate node based on the beamformer coefficient and the reflection coefficient.

2. In paragraph 1, The above intermediate node is a method for simultaneously performing phase change of an incident signal and intensity amplification of the incident signal through an active element.

3. In paragraph 2, The step of determining the beamformer coefficient and the reflection coefficient of the intermediate node is: A step of generating an objective function based on the sum of the minimum transmission rates of terminals derived based on the variance of channel and channel state information errors measured in the above channel measurement procedure; A step of initializing multiple variables of the above objective function; and A step of determining the plurality of variables that maximize the objective function using an alternating optimization algorithm; The above plurality of variables include the beamformer coefficient and the reflection coefficient, A method in which the beamformer coefficient and the reflection coefficient are determined based on whether the objective function converges.

4. In paragraph 3, The above objective function is generated based on the sum of the lower bounds of the minimum transmission rates of the terminals, A method wherein the above plurality of variables further include auxiliary variables of the objective function.

5. In paragraph 4, A method in which the variance of the above channel state information error is determined based on the uncertainty of the channel state information.

6. In paragraph 4, The step of determining the plurality of variables that maximize the objective function using the above-mentioned shift optimization algorithm is: A step of fixing the beamformer coefficient and the reflection coefficient and determining the auxiliary variables at which the objective function is maximized; A step of fixing the auxiliary variables and the reflection coefficient and determining the beamformer coefficient at which the objective function is maximized; and A method comprising the step of fixing the auxiliary variables and the beamformer coefficients and determining the reflection coefficient at which the objective function is maximized.

7. In paragraph 3, A method in which the initialization of the above plurality of variables is determined based on the maximum amplification gain of the active element, the maximum transmission power of the intermediate node, and the maximum transmission power of the base station.

8. In paragraph 1, Further comprising a method of transmitting the reflection coefficient to the intermediate node, The above reflection coefficient is transmitted in the form of an index using a table.

9. In paragraph 1, The step of performing the channel measurement procedure based on the above setting information is: A step of transmitting a channel measurement request message to the terminal; A step of receiving a reference signal from the terminal; A step of performing channel measurement based on the above reference signal; and A method comprising the step of obtaining information about a first channel between the base station and the terminal, a second channel between the base station and the intermediate node, and a third channel between the intermediate node and the terminal based on the channel measurement.

10. In paragraph 9, A method in which information about a first channel between the base station and the terminal, a second channel between the base station and the intermediate node, and a third channel between the intermediate node and the terminal is maintained during a coherence time period.

11. In paragraph 1, The step of performing the channel measurement procedure based on the above setting information is: A step of transmitting a reference signal to the terminal; A step of receiving channel information measured based on the reference signal from the terminal; and A method comprising a step of obtaining information about a first channel between the base station and the terminal, a second channel between the base station and the intermediate node, and a third channel between the intermediate node and the terminal based on the measured channel information.

12. In a method of operation performed by a terminal in a wireless communication system, A step of receiving system information from a base station; A step of performing an initial connection procedure with the above base station; A step of receiving setting information regarding channel measurement from the base station; A step of performing a channel measurement procedure based on the above setting information; and Including a step of receiving a data signal from the above base station, The above data signal is received through the intermediate node based on the beamformer coefficient and the reflection coefficient of the intermediate node, A method in which the beamformer coefficient and the reflection coefficient are determined based on the sum of the minimum transmission rates of terminals derived based on the variance of channel and channel state information errors measured in the channel measurement procedure.

13. In paragraph 12, The step of performing the channel measurement procedure based on the above setting information is: A step of receiving a reference signal from the base station; A step of performing channel measurement based on the above reference signal; Including a step of transmitting the channel measurement result to the base station, The sum of the minimum transmission rates of the terminals is determined based on information about a first channel between the base station and the terminal, a second channel between the base station and the intermediate node, and a third channel between the intermediate node and the terminal, A method in which information about the first channel, the second channel and the third channel is determined by the base station based on the channel measurement results.

14. In a wireless communication system, at a base station, Transmitter and receiver; and A processor connected to the above transmitter and receiver is included, The above processor, Transmit system information to the terminal, Perform the initial connection procedure with the above terminal, Transmits setting information regarding channel measurement to the above terminal, Perform channel measurement procedure based on the above setting information, The beamformer coefficient and the reflection coefficient of the intermediate node are determined based on the sum of the minimum transmission rates of the terminals derived from the variance of the channel and channel state information errors measured in the above channel measurement procedure, Transmit resource allocation information to the above terminal, A base station configured to transmit a data signal to the terminal through the intermediate node based on the beamformer coefficient and the reflection coefficient.

15. In a wireless communication system, at a terminal, Transmitter and receiver; and A processor connected to the above transmitter and receiver is included, The above processor, Receive system information from the base station, Perform the initial connection procedure with the above base station, Receive setting information regarding channel measurement from the above base station, Perform channel measurement procedure based on the above setting information, configured to receive a data signal from the above base station, The above data signal is received through the intermediate node based on the beamformer coefficient and the reflection coefficient of the intermediate node, A terminal in which the beamformer coefficient and the reflection coefficient are determined based on the sum of the minimum transmission rates of the terminals derived based on the variance of the channel and channel state information errors measured in the channel measurement procedure.

16. In communication devices, At least one processor; At least one computer memory connected to said at least one processor and storing instructions that direct operations when executed by said at least one processor, The above actions are, A step of transmitting system information to a terminal; A step of performing an initial connection procedure with the above terminal; A step of transmitting setting information regarding channel measurement to the terminal; A step of performing a channel measurement procedure based on the above setting information; A step of determining a beamformer coefficient and a reflection coefficient of an intermediate node based on the sum of the minimum transmission rates of terminals derived based on the variance of the channel and channel state information errors measured in the above channel measurement procedure; a step of transmitting resource allocation information to the terminal; and A communication device comprising a step of transmitting a data signal to the terminal through the intermediate node based on the beamformer coefficient and the reflection coefficient.

17. In a non-transitory computer-readable medium storing at least one instruction, comprising at least one instruction executable by the processor, At least one of the above commands causes the device to: Transmit system information to the terminal, Perform the initial connection procedure with the above terminal, Transmits setting information regarding channel measurement to the above terminal, Perform channel measurement procedure based on the above setting information, The beamformer coefficient and the reflection coefficient of the intermediate node are determined based on the sum of the minimum transmission rates of the terminals derived from the variance of the channel and channel state information errors measured in the above channel measurement procedure, Transmit resource allocation information to the above terminal, A computer-readable medium configured to transmit a data signal to the terminal through the intermediate node based on the beamformer coefficient and the reflection coefficient.

Images