Device and method for performing communication by using reconfigurable intelligent surface in wireless communication system

Abstract

The present disclosure is for performing communication by using a reconfigurable intelligent surface (RIS) in a wireless communication system. An operation method of a first base station may comprise the steps of: transmitting a reference signal to a first terminal; receiving, from the first terminal, first channel information measured on the basis of the reference signal; receiving second channel information from a second base station; determining a reflection pattern of a reconfigurable intelligent surface (RIS) on the basis of the first channel information and the second channel information; and transmitting a data signal to the first terminal.

Description

Device and method for performing communication using a reconfigurable intelligent surface in a wireless communication system

[0001] The following description relates to a wireless communication system, and to a device and method for performing communication using a reconfigurable intelligent surface (RIS) in a wireless communication system.

[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 may provide a device and method for efficiently performing communication using a reconfigurable intelligent surface (RIS) in a wireless communication system.

[0005] The present disclosure can provide a device and method for transmitting a signal to a user in a shadow area using RIS in a wireless communication system.

[0006] The present disclosure may provide a device and method for optimizing the reflection pattern of an RIS in a wireless communication system.

[0007] The present disclosure may provide a device and method for determining a reflection pattern of an RIS based on a total transmission rate in a wireless communication system.

[0008] The present disclosure may provide a device and method for obtaining channel information of a surrounding base station to determine a reflection pattern of an RIS in a wireless communication system.

[0009] The present disclosure may provide a device and method for reducing the gain for a channel between a user who does not use RIS and an RIS in a wireless communication system.

[0010] The present disclosure can provide a device and method for operating RIS without reducing the communication performance of other service providers in a wireless communication system.

[0011] The present disclosure can provide a device and method for determining a weight between a user using RIS and a user not using RIS in a wireless communication system based on a channel environment.

[0012] The present disclosure can provide a device and method for optimizing the reflection pattern of an RIS using a Riemannian conjugate gradient (RCG) algorithm in a wireless communication system.

[0013] 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.

[0014] As an example of the present disclosure, a method performed by a first base station in a wireless communication system may include the steps of transmitting a reference signal to a first terminal, receiving first channel information measured based on the reference signal from the first terminal, receiving second channel information from a second base station, determining a reflection pattern of a reconfigurable intelligent surface (RIS) based on the first channel information and the second channel information, and transmitting a data signal to the first terminal. The first channel information may include information related to a first RIS channel including a channel between the first base station and the RIS and a channel between the RIS and the first terminal, and the second channel information may include information related to a second RIS channel including a channel between the second base station and the RIS and a channel between the RIS and the second terminal.

[0015] As an example of the present disclosure, a method performed by a first terminal in a wireless communication system may include the steps of receiving a reference signal from a first base station, transmitting first channel information measured based on the reference signal to the first base station, and receiving a data signal from the first base station through a reconfigurable intelligent surface (RIS). A reflection pattern of the RIS may be determined based on a first RIS channel and a second RIS channel, and the first RIS channel may include a channel between the first base station and the RIS and a channel between the RIS and the first terminal, and the second RIS channel may include a channel between the second base station and the RIS and a channel between the RIS and the second terminal.

[0016] As an example of the present disclosure, in a wireless communication system, a first base station includes a transceiver and a processor connected to the transceiver, wherein the processor transmits a reference signal to a first terminal, receives first channel information measured based on the reference signal from the first terminal, receives second channel information from a second base station, determines a reflection pattern based on the first channel information and the second channel information, and controls to transmit a data signal to the first terminal, wherein the first channel information includes information related to a first RIS channel including a channel between the first base station and the RIS and a channel between the RIS and the first terminal, and the second channel information includes information related to a second RIS channel including a channel between the second base station and the RIS and a channel between the RIS and a second terminal. In a wireless communication system, a first terminal comprises a transceiver and a processor connected to the transceiver, wherein the processor receives a reference signal from a first base station, receives first channel information measured based on the reference signal from the first base station, and receives a data signal from the first base station through a reconfigurable intelligent surface (RIS), wherein a reflection pattern of the RIS is determined based on a first RIS channel and a second RIS channel, and the first RIS channel includes a channel between the first base station and the RIS and a channel between the RIS and the first terminal, and the second RIS channel includes a channel between the second base station and the RIS and a channel between the RIS and the second terminal.

[0017] As an example of the present disclosure, a communication device includes at least one processor, and at least one computer memory connected to the at least one processor and storing instructions that, when executed by the at least one processor, direct operations, wherein the operations may include: transmitting a reference signal to a first terminal; receiving first channel information measured based on the reference signal from the first terminal; receiving second channel information from a second base station; determining a reflection pattern of a reconfigurable intelligent surface (RIS) based on an objective function generated based on the first channel information and the second channel information; and transmitting a data signal to the first terminal. The first channel information may include information related to a first RIS channel including a channel between the communication device and the RIS and a channel between the RIS and the first terminal, and the second channel information may include information related to a second RIS channel including a channel between the second base station and the RIS and a channel between the RIS and the second terminal.

[0018] As an example of the present disclosure, a non-transitory computer-readable medium storing at least one instruction includes at least one instruction executable by a processor, wherein the at least one instruction controls a device to transmit a reference signal to a first terminal, receive first channel information measured based on the reference signal from the first terminal, receive second channel information from a second base station, determine a reflection pattern of a reconfigurable intelligent surface (RIS) based on an objective function generated based on the first channel information and the second channel information, and transmit a data signal to the first terminal, wherein the first channel information includes information related to a first RIS channel including a channel between the device and the RIS and a channel between the RIS and the first terminal, and the second channel information includes information related to a second RIS channel including a channel between the second base station and the RIS and a channel between the RIS and the second terminal.

[0019] 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.

[0020] The following effects may be achieved by embodiments based on the present disclosure.

[0021] According to the present disclosure, communication can be performed efficiently using a reconfigurable intelligent surface (RIS).

[0022] The effects that can be obtained from the embodiments of the present disclosure are not limited to the effects mentioned above, and other effects that are 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 that result from implementing the configuration described in the present disclosure can also be derived by those skilled in the art from the embodiments of the present disclosure.

[0023] The accompanying drawings are intended to aid in understanding the present disclosure and, together with detailed descriptions, may provide embodiments of the present disclosure. 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.

[0024] Figure 1 illustrates an example of a communication system applicable to the present disclosure.

[0025] FIG. 2 illustrates an example of a wireless device applicable to the present disclosure.

[0026] FIG. 3 illustrates another example of a wireless device applicable to the present disclosure.

[0027] FIG. 4 illustrates an example of a portable device applicable to the present disclosure.

[0028] FIG. 5 illustrates an example of a vehicle or autonomous vehicle applicable to the present disclosure.

[0029] Figure 6 illustrates an example of AI (Artificial Intelligence) applicable to the present disclosure.

[0030] FIG. 7 illustrates a method for processing a transmission signal applicable to the present disclosure.

[0031] FIG. 8 illustrates an example of a communication structure that can be provided in a 6G system applicable to the present disclosure.

[0032] Figure 9 illustrates an electromagnetic spectrum applicable to the present disclosure.

[0033] Figure 10 illustrates a THz communication method applicable to the present disclosure.

[0034] FIG. 11 illustrates a wireless channel environment according to one embodiment of the present disclosure.

[0035] FIG. 12 illustrates an intelligent wireless environment according to one embodiment of the present disclosure.

[0036] FIG. 13 illustrates an existing wireless channel environment and an intelligent wireless channel environment according to one embodiment of the present disclosure.

[0037] FIG. 14 illustrates an example of a communication environment considering multiple service providers according to one embodiment of the present disclosure.

[0038] FIG. 15 illustrates an example of a procedure in which a first base station determines a beamformer and a reconfigurable intelligent surface (RIS) reflection pattern by considering channel information of a second base station according to one embodiment of the present disclosure.

[0039] FIG. 16 illustrates an example of a procedure using a Riemannian conjugate gradient (RCG) algorithm to optimize the reflection pattern of an RIS according to one embodiment of the present disclosure.

[0040] FIG. 17 illustrates an example of a procedure in which a first terminal performs communication using a reflection pattern of an RIS that takes into account channel information of a second base station according to one embodiment of the present disclosure.

[0041] FIG. 18 illustrates an example of signaling for performing communication using a reflection pattern of RIS determined based on channel information of a first base station and channel information of a second base station according to one embodiment of the present disclosure.

[0042] FIG. 19 illustrates an example of a simulation environment for a comparative experiment according to one embodiment of the present disclosure.

[0043] FIG. 20 illustrates an example of a comparative experiment in which the total transmission rate varies based on the transmission power according to one embodiment of the present disclosure.

[0044] Figure 21 is a balance parameter according to one embodiment of the present disclosure. An example of the performance of the total transmission rate according to .

[0045] The following embodiments combine 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.

[0046] 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.

[0047] 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.

[0048] 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.

[0049] 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.

[0050] Additionally, in 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).

[0051] 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.

[0052] 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 5G (5th generation) 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.

[0053] Furthermore, the embodiments of the present disclosure may be applied to other wireless access systems and are not limited to the aforementioned systems. For example, they may be applicable to systems implemented after the 3GPP 5G NR system, and are not limited to a specific system.

[0054] 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.

[0055] 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.

[0056] Additionally, specific terms used in the embodiments of the present disclosure are provided to aid in understanding 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.

[0057] 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).

[0058] In order to make the following description clear, the following description is based on a 3GPP communication system (e.g., LTE, NR, etc.), but the technical idea of ​​the present invention 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.

[0059] For background information, terms, abbreviations, etc. used in this disclosure, reference may be made to standard documents published prior to the invention of the present invention. For example, reference may be made to the 36.xxx and 38.xxx standard documents.

[0060] Communication system applicable to the present disclosure

[0061] 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.

[0062] 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.

[0063] FIG. 1 is a diagram illustrating an example of a communication system applied to the present disclosure.

[0064] 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., 5G NR, LTE) 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.

[0065] 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) network, etc. 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). In addition, IoT devices (100f) (e.g., sensors) can communicate directly with other IoT devices (e.g., sensors) or other wireless devices (100a to 100f).

[0066] 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 (e.g., 5G NR) 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.

[0067] Communication system applicable to the present disclosure

[0068] FIG. 2 is a diagram illustrating an example of a wireless device applicable to the present disclosure.

[0069] Referring to FIG. 2, the first wireless device (200a) and the second wireless device (200b) can transmit and receive wireless signals via various wireless access technologies (e.g., LTE, NR). Here, {the first wireless device (200a), the second wireless device (200b)} can correspond to {the wireless device (100x), the base station (120)} and / or {the wireless device (100x), the wireless device (100x)} of FIG. 1.

[0070] A first wireless device (200a) includes one or more processors (202a) and one or more memories (204a), and may further include one or more transceivers (206a) and / or one or more antennas (208a). The processor (202a) controls the memories (204a) and / or the transceivers (206a), and may be configured to implement the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. For example, the processor (202a) may process information in the memory (204a) to generate first information / signals, and then transmit a wireless signal including the first information / signals via the transceivers (206a). In addition, the processor (202a) may receive a wireless signal including second information / signals via the transceivers (206a), and then store information obtained from signal processing of the second information / signals in the memory (204a). The memory (204a) may be connected to the processor (202a) and may store various information related to the operation of the processor (202a). For example, the memory (204a) may perform some or all of the processes controlled by the processor (202a), or may store software code including instructions for performing the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. Here, the processor (202a) and the memory (204a) may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). The transceiver (206a) may be connected to the processor (202a) and may transmit and / or receive wireless signals via one or more antennas (208a). The transceiver (206a) may include a transmitter and / or a receiver. The transceiver (206a) 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.

[0071] The second wireless device (200b) includes one or more processors (202b), one or more memories (204b), and may further include one or more transceivers (206b) and / or one or more antennas (208b). The processor (202b) controls the memories (204b) and / or the transceivers (206b), and may be configured to implement the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. For example, the processor (202b) may process information in the memory (204b) to generate third information / signals, and then transmit a wireless signal including the third information / signals via the transceivers (206b). In addition, the processor (202b) may receive a wireless signal including fourth information / signals via the transceivers (206b), and then store information obtained from the signal processing of the fourth information / signals in the memory (204b). The memory (204b) may be connected to the processor (202b) and may store various information related to the operation of the processor (202b). For example, the memory (204b) may perform some or all of the processes controlled by the processor (202b), or may store software code including instructions for performing the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. Here, the processor (202b) and the memory (204b) may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). The transceiver (206b) may be connected to the processor (202b) and may transmit and / or receive wireless signals via one or more antennas (208b). The transceiver (206b) may include a transmitter and / or a receiver. The transceiver (206b) may be used interchangeably with an RF unit. In the present disclosure, a wireless device may also mean a communication modem / circuit / chip.

[0072] Hereinafter, hardware elements of the wireless device (200a, 200b) will be described in more detail. Although not limited thereto, one or more protocol layers may be implemented by one or more processors (202a, 202b). For example, one or more processors (202a, 202b) may implement one or more layers (e.g., functional layers 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)). One or more processors (202a, 202b) may generate one or more Protocol Data Units (PDUs) and / or one or more Service Data Units (SDUs) according to the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. One or more processors (202a, 202b) may generate messages, control information, data or information according to the descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed herein. One or more processors (202a, 202b) may generate signals (e.g., baseband signals) including PDUs, SDUs, messages, control information, data or information according to the functions, procedures, proposals and / or methods disclosed herein, and provide the signals to one or more transceivers (206a, 206b). One or more processors (202a, 202b) may receive signals (e.g., baseband signals) from one or more transceivers (206a, 206b) and obtain PDUs, SDUs, messages, control information, data or information according to the descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed herein.

[0073] One or more processors (202a, 202b) may be referred to as a controller, a microcontroller, a microprocessor, or a microcomputer. One or more processors (202a, 202b) may be implemented by hardware, firmware, software, or a combination thereof. For example, one or more application specific integrated circuits (ASICs), one or more digital signal processors (DSPs), one or more digital signal processing devices (DSPDs), one or more programmable logic devices (PLDs), or one or more field programmable gate arrays (FPGAs) may be included in one or more processors (202a, 202b). The descriptions, functions, procedures, proposals, methods, and / or operational 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, suggestions, methods and / or operation flowcharts disclosed in this document may be implemented using firmware or software configured to perform one or more processors (202a, 202b) or stored in one or more memories (204a, 204b) and executed by one or more processors (202a, 202b). The descriptions, functions, procedures, suggestions, methods and / or operation flowcharts disclosed in this document may be implemented using firmware or software in the form of codes, instructions and / or sets of instructions.

[0074] One or more memories (204a, 204b) may be coupled to one or more processors (202a, 202b) and may store various forms of data, signals, messages, information, programs, codes, instructions, and / or commands. The one or more memories (204a, 204b) may be configured as read only memory (ROM), random access memory (RAM), erasable programmable read only memory (EPROM), flash memory, hard drives, registers, cache memory, computer readable storage media, and / or combinations thereof. The one or more memories (204a, 204b) may be located internally and / or externally to the one or more processors (202a, 202b). Additionally, the one or more memories (204a, 204b) may be coupled to the one or more processors (202a, 202b) via various technologies, such as wired or wireless connections.

[0075] One or more transceivers (206a, 206b) can transmit user data, control information, wireless signals / channels, etc., as mentioned in the methods and / or flowcharts of this document, to one or more other devices. One or more transceivers (206a, 206b) can receive user data, control information, wireless signals / channels, etc., as mentioned in the descriptions, functions, procedures, proposals, methods and / or flowcharts of this document, from one or more other devices. For example, one or more transceivers (206a, 206b) can be coupled to one or more processors (202a, 202b) and can transmit and receive wireless signals. For example, one or more processors (202a, 202b) can control one or more transceivers (206a, 206b) to transmit user data, control information, or wireless signals to one or more other devices. Additionally, one or more processors (202a, 202b) may control one or more transceivers (206a, 206b) to receive user data, control information, or wireless signals from one or more other devices. Additionally, one or more transceivers (206a, 206b) may be coupled to one or more antennas (208a, 208b), and one or more transceivers (206a, 206b) may be configured to transmit and receive user data, control information, wireless signals / channels, or the like, as referred to in the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document, via one or more antennas (208a, 208b). In this document, one or more antennas may be multiple physical antennas or multiple logical antennas (e.g., antenna ports). One or more transceivers (206a, 206b) can convert received user data, control information, 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 one or more processors (202a, 202b).One or more transceivers (206a, 206b) may convert user data, control information, wireless signals / channels, etc. processed by one or more processors (202a, 202b) from baseband signals to RF band signals. For this purpose, one or more transceivers (206a, 206b) may include an (analog) oscillator and / or filter.

[0076] Wireless device structure applicable to the present disclosure

[0077] FIG. 3 is a diagram illustrating another example of a wireless device applicable to the present disclosure.

[0078] Referring to FIG. 3, the wireless device (300) corresponds to the wireless devices (200a, 200b) of FIG. 2 and may be composed of various elements, components, units, and / or modules. For example, the wireless device (300) may include a communication unit (310), a control unit (320), a memory unit (330), and additional elements (340). The communication unit may include a communication circuit (312) and a transceiver(s) (314). For example, the communication circuit (312) may include one or more processors (202a, 202b) and / or one or more memories (204a, 204b) of FIG. 2. For example, the transceiver(s) (314) may include one or more transceivers (206a, 206b) and / or one or more antennas (208a, 208b) of FIG. 2. The control unit (320) is electrically connected to the communication unit (310), the memory unit (330), and the additional elements (340) and controls the overall operation of the wireless device. For example, the control unit (320) may control the electrical / mechanical operation of the wireless device based on the program / code / command / information stored in the memory unit (330). In addition, the control unit (320) may transmit information stored in the memory unit (330) to an external device (e.g., another communication device) via a wireless / wired interface through the communication unit (310), or store information received from an external device (e.g., another communication device) via a wireless / wired interface in the memory unit (330).

[0079] The additional element (340) may be configured in various ways depending on the type of the wireless device. For example, the additional element (340) may include at least one of a power unit / battery, an input / output unit, a driving unit, and a computing unit. Although not limited thereto, the wireless device (300) 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, 140), a base station (Fig. 1, 120), a network node, etc. Wireless devices may be mobile or stationary depending on the use / service.

[0080] In FIG. 3, various elements, components, units / parts, and / or modules within the wireless device (300) may be entirely interconnected via a wired interface, or at least some may be wirelessly connected via a communication unit (310). For example, within the wireless device (300), the control unit (320) and the communication unit (310) may be wired, and the control unit (320) and the first unit (e.g., 130, 140) may be wirelessly connected via the communication unit (310). In addition, each element, component, unit / part, and / or module within the wireless device (300) may further include one or more elements. For example, the control unit (320) may be composed of a set of one or more processors. For example, the control unit (320) 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 (330) may be composed of RAM, DRAM (dynamic RAM), ROM, flash memory, volatile memory, non-volatile memory, and / or a combination thereof.

[0081] Mobile devices to which the present disclosure applies

[0082] FIG. 4 is a drawing illustrating an example of a mobile device applied to the present disclosure.

[0083] Figure 4 illustrates an example of a mobile device applicable to the present disclosure. The mobile device may include a smartphone, a smart pad, a wearable device (e.g., a smart watch, smart glasses), or a portable computer (e.g., a laptop, etc.). The mobile device may be referred to as a mobile station (MS), a user terminal (UT), a mobile subscriber station (MSS), a subscriber station (SS), an advanced mobile station (AMS), or a wireless terminal (WT).

[0084] Referring to FIG. 4, the portable device (400) may include an antenna unit (408), a communication unit (410), a control unit (420), a memory unit (430), a power supply unit (440a), an interface unit (440b), and an input / output unit (440c). The antenna unit (408) may be configured as a part of the communication unit (410). Blocks 410 to 430 / 440a to 440c correspond to blocks 310 to 330 / 340 of FIG. 3, respectively.

[0085] The communication unit (410) can transmit and receive signals (e.g., data, control signals, etc.) with other wireless devices and base stations. The control unit (420) can control components of the portable device (400) to perform various operations. The control unit (420) can include an AP (application processor). The memory unit (430) can store data / parameters / programs / codes / commands required for operating the portable device (400). In addition, the memory unit (430) can store input / output data / information, etc. The power supply unit (440a) supplies power to the portable device (400) and can include a wired / wireless charging circuit, a battery, etc. The interface unit (440b) can support connection between the portable device (400) and other external devices. The interface unit (440b) can include various ports (e.g., audio input / output ports, video input / output ports) for connection with external devices. The input / output unit (440c) can input or output video information / signals, audio information / signals, data, and / or information input from a user. The input / output unit (440c) may include a camera, a microphone, a user input unit, a display unit (440d), a speaker, and / or a haptic module.

[0086] For example, in the case of data communication, the input / output unit (440c) 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 (430). The communication unit (410) can convert the information / signals stored in the memory into wireless signals, and transmit the converted wireless signals directly to other wireless devices or to a base station. In addition, the communication unit (410) 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 (430) and then output in various forms (e.g., text, voice, image, video, haptic) through the input / output unit (440c).

[0087] Types of wireless devices to which the present disclosure applies

[0088] FIG. 5 is a drawing illustrating an example of a vehicle or autonomous vehicle to which the present disclosure applies.

[0089] Figure 5 illustrates a vehicle or autonomous vehicle applicable to the present disclosure. The vehicle or autonomous vehicle may be implemented as a mobile robot, car, train, manned / unmanned aerial vehicle (AV), ship, etc., and is not limited to the form of a vehicle.

[0090] Referring to FIG. 5, a vehicle or autonomous vehicle (500) may include an antenna unit (508), a communication unit (510), a control unit (520), a driving unit (540a), a power supply unit (540b), a sensor unit (540c), and an autonomous driving unit (540d). The antenna unit (550) may be configured as a part of the communication unit (510). Blocks 510 / 530 / 540a to 540d correspond to blocks 410 / 430 / 440 of FIG. 4, respectively.

[0091] The communication unit (510) 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, etc.), servers, etc. The control unit (520) can control elements of a vehicle or autonomous vehicle (500) to perform various operations. The control unit (520) can include an electronic control unit (ECU).

[0092] Figure 6 is a diagram illustrating an example of an AI device applicable to the present disclosure. For example, the AI ​​device may be implemented as a fixed or mobile device, such as a TV, projector, smartphone, PC, laptop, digital broadcasting terminal, tablet PC, wearable device, set-top box (STB), radio, washing machine, refrigerator, digital signage, robot, or vehicle.

[0093] Referring to FIG. 6, the AI ​​device (600) may include a communication unit (610), a control unit (620), a memory unit (630), an input / output unit (640a / 640b), a learning processor unit (640c), and a sensor unit (640d). Blocks 610 to 630 / 640a to 640d may correspond to blocks 310 to 330 / 340 of FIG. 3, respectively.

[0094] The communication unit (610) can transmit and receive wired and wireless signals (e.g., sensor information, user input, learning models, control signals, etc.) with external devices such as other AI devices (e.g., FIG. 1, 100x, 120, 140) or AI servers (FIG. 1, 140) using wired and wireless communication technology. To this end, the communication unit (610) can transmit information within the memory unit (630) to the external device or transfer a signal received from the external device to the memory unit (630).

[0095] The control unit (620) may determine at least one executable operation of the AI ​​device (600) based on information determined or generated using a data analysis algorithm or a machine learning algorithm. In addition, the control unit (620) may control components of the AI ​​device (600) to perform the determined operation. For example, the control unit (620) may request, search, receive, or utilize data from the learning processor unit (640c) or the memory unit (630), and may control components of the AI ​​device (600) to perform a predicted operation or an operation determined to be desirable among at least one executable operation. In addition, the control unit (620) may collect history information including the operation contents of the AI ​​device (600) or user feedback on the operation, and store the collected history information in the memory unit (630) or the learning processor unit (640c), or transmit the collected history information to an external device such as an AI server (FIG. 1, 140). The collected history information may be used to update a learning model.

[0096] The memory unit (630) can store data that supports various functions of the AI ​​device (600). For example, the memory unit (630) can store data obtained from the input unit (640a), data obtained from the communication unit (610), output data of the learning processor unit (640c), and data obtained from the sensing unit (640). In addition, the memory unit (630) can store control information and / or software codes necessary for the operation / execution of the control unit (620).

[0097] The input unit (640a) can obtain various types of data from the outside of the AI ​​device (600). For example, the input unit (620) can obtain learning data for model learning, input data to which the learning model will be applied, etc. The input unit (640a) may include a camera, a microphone, and / or a user input unit. The output unit (640b) may generate output related to vision, hearing, or touch. The output unit (640b) may include a display unit, a speaker, and / or a haptic module, etc. The sensing unit (640) can obtain at least one of internal information of the AI ​​device (600), information about the surrounding environment of the AI ​​device (600), and user information using various sensors. The sensing unit (640) 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.

[0098] The learning processor unit (640c) can train a model composed of an artificial neural network using learning data. The learning processor unit (640c) can perform AI processing together with the learning processor unit of the AI ​​server (Fig. 1, 140). The learning processor unit (640c) can process information received from an external device via the communication unit (610) and / or information stored in the memory unit (630). In addition, the output value of the learning processor unit (640c) can be transmitted to an external device via the communication unit (610) and / or stored in the memory unit (630).

[0099] FIG. 7 is a diagram illustrating a method for processing a transmission signal applied to the present disclosure. For example, the transmission signal may be processed by a signal processing circuit. At this time, the signal processing circuit (700) may include a scrambler (710), a modulator (720), a layer mapper (730), a precoder (740), a resource mapper (750), and a signal generator (760). At this time, as an example, the operations / functions of FIG. 7 may be performed in the processors (202a, 202b) and / or the transceivers (206a, 206b) of FIG. 2. Furthermore, as an example, the hardware elements of FIG. 7 may be implemented in the processors (202a, 202b) and / or the transceivers (206a, 206b) of FIG. 2. As an example, blocks 710 to 760 may be implemented in the processors (202a, 202b) of FIG. 2. Additionally, blocks 710 to 750 may be implemented in the processor (202a, 202b) of FIG. 2, and block 760 may be implemented in the transceiver (206a, 206b) of FIG. 2, and are not limited to the above-described embodiments.

[0100] The codeword can be converted into a wireless signal through the signal processing circuit (700) of FIG. 7. 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). The wireless signal may be transmitted through various physical channels (e.g., a PUSCH, a PDSCH). Specifically, the codeword can be converted into a bit sequence scrambled by a scrambler (710). 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 can be modulated into a modulation symbol sequence by a modulator (720). The modulation scheme may include pi / 2-binary phase shift keying (pi / 2-BPSK), m-phase shift keying (m-PSK), m-quadrature amplitude modulation (m-QAM), etc.

[0101] A complex modulation symbol sequence can be mapped to one or more transmission layers by a layer mapper (730). The modulation symbols of each transmission layer can be mapped to the corresponding antenna port(s) by a precoder (740) (precoding). The output z of the precoder (740) can be obtained by multiplying the output y of the layer mapper (730) by an N*M precoding matrix W. Here, N is the number of antenna ports, and M is the number of transmission layers. Here, the precoder (740) can perform precoding after performing transform precoding (e.g., discrete Fourier transform (DFT) transform) on the complex modulation symbols. In addition, the precoder (740) can perform precoding without performing transform precoding.

[0102] The resource mapper (750) 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 (760) 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 (760) 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.

[0103] The signal processing process for receiving signals in a wireless device can be configured in reverse order of the signal processing process (710 to 760) of FIG. 7. For example, a wireless device (e.g., 200a and 200b of FIG. 2) can receive wireless signals from the outside through an antenna port / transceiver. The received wireless signals can be converted into baseband signals through a signal restorer. For this purpose, the signal restorer can 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 can be restored to a codeword through a resource demapper process, a postcoding process, a demodulation process, and a descrambling process. The codewords can be restored to the original information blocks through decoding. Accordingly, a signal processing circuit (not shown) for a received signal may include a signal restorer, a resource de-mapper, a postcoder, a demodulator, a de-scrambler, and a decoder.

[0104] 6G communication system

[0105] The 6G (wireless communication) system aims to achieve (i) very high data rates per device, (ii) a very large number of connected devices, (iii) global connectivity, (iv) very low latency, (v) low energy consumption for 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 satisfy the requirements as shown in Table 1 below. In other words, Table 1 is a table showing the requirements of the 6G system.

[0106] Per device peak data rate1 TbpsE2E latency1 msMaximum spectral efficiency100 bps / HzMobility supportup to 1000 km / hrSatellite integrationFullyAIFullyAutonomous vehicleFullyXRFullyHaptic CommunicationFully

[0107] 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.

[0108] FIG. 8 is a diagram illustrating an example of a communication structure that can be provided in a 6G system applicable to the present disclosure.

[0109] Referring to Figure 8, 6G systems are expected to have 50 times higher simultaneous wireless connectivity than 5G wireless systems. URLLC, a key feature of 5G, is expected to become a more prominent technology in 6G communications, providing end-to-end latency of less than 1 ms. Furthermore, 6G systems will have significantly better volumetric spectral efficiency, unlike 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.

[0110] Core implementation technology of 6G systems

[0111] - Artificial Intelligence (AI)

[0112] The most crucial and newly introduced technology for 6G systems is AI. 4G systems did not involve AI. 5G systems will support partial or very limited AI. However, 6G systems will fully support AI for automation. Advances in machine learning will create more intelligent networks for real-time communications in 6G. Incorporating AI into communications can streamline and improve real-time data transmission. AI can use numerous analyses to determine how complex target tasks should be performed. In other words, AI can increase efficiency and reduce processing delays.

[0113] Time-consuming tasks such as handover, network selection, and resource scheduling can be performed instantly using AI. AI can also play a crucial role in machine-to-machine (M2M), machine-to-human, and human-to-machine communications. Furthermore, AI can facilitate rapid communication in brain-computer interfaces (BCIs). AI-based communication systems can be supported by metamaterials, intelligent structures, intelligent networks, intelligent devices, intelligent cognitive radios, self-sustaining wireless networks, and machine learning.

[0114] Recent attempts to integrate AI into wireless communication systems have focused on the application layer and network layer, particularly deep learning in wireless resource management and allocation. However, this research is increasingly evolving to the MAC layer and physical layer, with attempts to combine deep learning with wireless transmission, particularly in the physical layer. AI-based physical layer transmission refers to applying AI-based signal processing and communication mechanisms, rather than traditional communication frameworks, in the fundamental signal processing and communication mechanisms. For example, this may include deep learning-based channel coding and decoding, deep learning-based signal estimation and detection, deep learning-based multiple input multiple output (MIMO) mechanisms, and AI-based resource scheduling and allocation.

[0115] Machine learning can be used for channel estimation and channel tracking, as well as for power allocation and interference cancellation at the physical layer of the downlink (DL). Machine learning can also be used for antenna selection, power control, and symbol detection in MIMO systems.

[0116] However, the application of DNN for transmission at the physical layer may have the following problems.

[0117] Deep learning-based AI algorithms require a large amount of training data to optimize training parameters. However, due to limitations in obtaining training data from specific channel environments, a large amount of training data is used offline. This means that static training on training data in specific channel environments can lead to conflicts with the dynamic characteristics and diversity of the wireless channel.

[0118] Furthermore, current deep learning primarily targets real-world signals. However, signals at the physical layer of wireless communications are complex signals. Further research is needed on neural networks capable of detecting complex domain signals to match the characteristics of wireless communication signals.

[0119] Below, we will look at machine learning in more detail.

[0120] Machine learning refers to a series of operations that train machines to perform tasks that humans can or cannot perform. Machine learning requires data and a learning model. In machine learning, data learning methods can be broadly categorized into three types: supervised learning, unsupervised learning, and reinforcement learning.

[0121] Neural network training aims to minimize output errors. It involves repeatedly inputting training data into a neural network, calculating the neural network output and target error for the training data, and backpropagating the neural network error from the output layer to the input layer to update the weights of each node in the neural network to reduce the error.

[0122] Supervised learning uses labeled training data, while unsupervised learning may not have labeled training data. For example, in the case of supervised learning for data classification, the training data may be data in which each training data category is labeled. The labeled training data is input to a neural network, and the error can be calculated by comparing the output (categories) of the neural network with the training data labels. The calculated error is backpropagated through the neural network in the backward direction (i.e., from the output layer to the input layer), and the connection weights of each node in each layer of the neural network can be updated through backpropagation. The amount of change in the connection weights of each updated node can be determined by the learning rate. The neural network's calculation of the input data and the backpropagation of the error can constitute a learning cycle (epoch). The learning rate can be applied differently depending on the number of iterations of the neural network's learning cycle. For example, in the early stages of training a neural network, a high learning rate can be used to quickly allow the network to achieve a certain level of performance, thereby increasing efficiency. In the later stages of training, a low learning rate can be used to increase accuracy.

[0123] Learning methods may vary depending on the characteristics of the data. For example, if the goal is to accurately predict data transmitted by a transmitter in a communication system, supervised learning is preferable to unsupervised learning or reinforcement learning.

[0124] The learning model corresponds to the human brain, and the most basic linear model can be thought of, but the machine learning paradigm that uses highly complex neural network structures, such as artificial neural networks, as learning models is called deep learning.

[0125] The neural network cores used in learning methods are largely divided into deep neural networks (DNN), convolutional deep neural networks (CNN), and recurrent Boltzmann machines (RNN), and these learning models can be applied.

[0126] THz (Terahertz) communication

[0127] THz communications can be applied in 6G systems. For example, data transmission rates can be increased by increasing bandwidth. This can be achieved by using sub-THz communications with wide bandwidths and applying advanced massive MIMO technology.

[0128] FIG. 9 is a diagram illustrating an electromagnetic spectrum applicable to the present disclosure. For example, referring to FIG. 9, THz waves, also known as sub-millimeter radiation, typically represent a frequency band between 0.1 THz and 10 THz with a corresponding wavelength ranging from 0.03 mm to 3 mm. The 100 GHz to 300 GHz band (Sub-THz band) is considered a major portion of the THz band for cellular communications. Adding the Sub-THz band to the mmWave band will increase the capacity of 6G cellular communications. Among the defined THz bands, 300 GHz to 3 THz is in the far infrared (IR) frequency band. Although the 300 GHz to 3 THz band is part of the optical band, it is at the boundary of the optical band and lies just behind the RF band. Therefore, this 300 GHz to 3 THz band exhibits similarities to RF.

[0129] Key characteristics of THz communications include (i) the widely available bandwidth to support very high data rates and (ii) the high path loss that occurs at high frequencies (requiring highly directional antennas). The narrow beamwidths generated by highly directional antennas reduce interference. The small wavelength of THz signals allows for a significantly larger number of antenna elements to be integrated into devices and base stations operating in this band. This enables the use of advanced adaptive array technologies to overcome range limitations.

[0130] Terahertz (THz) wireless communications

[0131] FIG. 10 is a diagram illustrating a THz communication method applicable to the present disclosure.

[0132] Referring to Fig. 10, THz wireless communication is a wireless communication using THz waves with 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, so they have high straightness and can enable beam focusing.

[0133] Specific embodiments of the present disclosure

[0134] The present disclosure relates to the control of a reconfigurable intelligent surface (RIS) in a system utilizing the RIS, and proposes a technique for determining a reflection pattern applicable to the RIS. Furthermore, the present disclosure proposes a technique for operating the RIS in a communications environment that considers multiple service providers.

[0135] RIS may also be referred to as an intelligent reflective surface (IRS), but is not limited to a specific name. For convenience of explanation in this disclosure, the description focuses on RIS, but is not limited to that name. Specifically, in the various embodiments described below, the structure and operations related to an RIS equipped with a reflector are described, but the RIS may be replaced with a relay station or an integrated access and backhaul (IAB) node with limited functionality. Here, limited functionality means that the RIS is implemented with low hardware capabilities or operates with some functions blocked depending on the operating mode.

[0136] Current wireless communication technologies can be controlled through endpoint optimization that adapts to the channel environment (H). When optimization is performed at the transmitter and receiver, the transmitter and receiver can adjust at least one of beamforming, power control, and adaptive modulation to the channel environment (H) between the transmitter and receiver to increase transmission efficiency. At this time, the channel environment can be random, uncontrolled, and naturally fixed. In other words, in existing communication systems, the channel environment was fixed, and each endpoint could be controlled to optimize for the channel environment. Therefore, the transmitter and receiver must optimize to adapt to the channel and transmit and receive data through this optimization. However, in environments with high signal loss and low multipath, such as 6G THz, such as non-line-of-sight (NLOS) environments in shadow areas, endpoint optimization alone may not be enough to overcome Shannon's Capacity Limit, and carriers may struggle to achieve the desired throughput.

[0137] Considering the above, new communication systems can perform communication based on a smart radio environment. In this smart radio environment, RIS can be used to control the wireless channel as a controllable factor, similar to a transmitter and receiver.

[0138] That is, factors related to the wireless channel can be added as factors used to optimize wireless communication transmission. This can enable channel reconfiguration and overcoming Shannon's channel capacity limit, which are insurmountable problems in existing communication systems. However, in an intelligent wireless environment, the measurement of the additional channel due to RIS and the simultaneous consideration of RIS with the transmitter and receiver are necessary to optimize wireless communication transmission, which can complicate the optimization process.

[0139] FIG. 11 illustrates a wireless channel environment according to an embodiment of the present disclosure. Referring to FIG. 11, in a conventional communication system, the wireless channel environment (H) may be naturally fixed and in an uncontrollable random state. Accordingly, the transmitter (1110) and the receiver (1120) can adapt to the channel and find an optimized transmission and reception method. The transmitter (1110) and the receiver (1120) can be controlled to measure the channel state through a signal (e.g., a reference signal) and perform optimization based on the measured channel state. However, as described above, in a terahertz environment with high signal loss and difficult multipath application, as well as in an NLOS environment such as a shadow area, there may be limitations in data transmission. For example, the following [Mathematical Formula 1] can represent Shannon's capacity limit. In this case, even if the transmission signal P in [Mathematical Formula 1] is increased by applying precoding and processing, there may be limitations in increasing the channel capacity if the size of the channel |H| is small.

[0140] In a fixed wireless channel environment, there may be limitations in increasing channel capacity based on [Mathematical Formula 1]. In this case, communication using RIS can secure multiple paths between the transmitter (1110) and the receiver (1120), and can increase the channel |H| described above. In other words, in an intelligent wireless environment, the wireless channel environment based on RIS can be an adjustable factor, and through this, the channel capacity can be increased.

[0141]

[0142] In [Mathematical Formula 1], C is the channel capacity, |HP| 2 is the transmission signal power passing through the channel, and σ is the standard deviation of noise.

[0143] For example, FIG. 12 illustrates an intelligent wireless environment according to an embodiment of the present disclosure. Referring to FIG. 12, in an intelligent wireless channel environment, a wireless channel |H| may be a factor for optimization. More specifically, in FIG. 11 described above, optimization may be performed at the transmitter (1110) and the receiver (1120) based on "max{f(Tx, Rx)}" as an end-point optimization, as described above. However, in FIG. 12, optimization may be performed at the transmitter (1210) and the receiver (1220) based on "max{f(Tx, Rx, H)}" as an end-point optimization. That is, in an intelligent wireless environment, a channel |H| may be used as a factor for optimization based on an intelligent reflector.

[0144] FIGS. 13A and 13B illustrate an existing wireless channel environment and an intelligent wireless channel environment according to an embodiment of the present disclosure. For example, referring to FIG. 13A, the existing wireless channel environment may be P1. Also, referring to FIG. 13B, the intelligent wireless channel environment may be P2. At this time, in FIGS. 13A and 13B, when signal x is transmitted from a transmitter through a wireless channel, the receiver may receive signal y. At this time, the probability of P1 in the existing wireless channel environment is fixed, and the receiver (decoder) may transmit feedback to the transmitter through measurement of the transmitted signal. The transmitter may perform optimization to adapt to the wireless channel environment through the feedback from the receiver. As a more specific example, the receiver may measure a channel quality indicator (CQI) for the transmitted signal based on a reference signal transmitted by the transmitter and feed it back. The transmitter can adjust the MCS (modulation coding scheme) based on the fed-back information and provide the information to the receiver to perform communication.

[0145] On the other hand, referring to Fig. 13b, in an intelligent wireless channel environment, the wireless channel environment P2 is recognized, and the wireless channel environment can be changed through RIS control. At the same time, the receiver can perform measurements on the received transmission signal and transmit feedback thereon to the transmitter. In other words, the transmitter can perform optimization by receiving feedback information based on RIS control and feedback information from the receiver. At this time, the transmitter can change the wireless channel environment by adjusting RIS, and optimization can be performed considering the wireless channel environment and the transmitter.

[0146] Due to these characteristics, RIS is attracting attention as a key technology for improving communication systems for various purposes in post-5G wireless communication systems, and research related to RIS is actively underway. Existing communication systems have been able to improve communication performance by utilizing multiple antennas for antenna gain and beamforming gain. However, communication systems using active components, such as radio frequency chains, can consume significant power. RIS, however, consists of passive components capable of changing phase. Therefore, communication systems utilizing RIS can achieve the performance improvements previously achieved through the use of multiple antennas at relatively low cost and power consumption.

[0147] However, communication systems utilizing RIS can encounter the problem of altering the communication environments of different service providers. In a communication environment that considers multiple service providers, each service provider has its own cell, and the base stations for each cell operate in different frequency bands. Since one service provider operates a different frequency band than the other, interference between cells of different service providers is not considered. However, RIS, which consists of passive components, does not have signal processing capabilities in the baseband. Therefore, RIS can cause phase shifts across the entire band, not just affecting signals in a specific band. Therefore, if a specific service provider uses RIS to increase channel gain, etc., users communicating in other frequency bands may also receive reflected signals through RIS, resulting in unintended performance degradation due to the interaction of reflected and direct signals. Therefore, the present disclosure proposes a technique for utilizing RIS that can achieve the purpose of RIS operation while reducing this performance degradation.

[0148] In this disclosure, vertical vectors and matrices are denoted by boldface letters, and their transpose and Hermitian transpose are and is expressed as . The set of complex numbers is It is expressed as, Is represents a set of complex matrices of size . For a square matrix A, Tr(A) represents the sum of the diagonal elements of A. For a vector a, the diagonal matrix whose elements are diagonal elements is denoted by diag(a). The ℓ2-norm value of vector a is It is expressed as , and the Frobenius-norm value of matrix A is It is expressed as: mean μ and variance The normal distribution has It is expressed as . Is It represents the identity matrix of size. and represent the magnitude and real part of the complex number a, respectively. represents the Hadamard product. represents the big-O representation.

[0149] Additionally, the symbols used to describe the proposed technology in this disclosure can be interpreted as shown in [Table 2] below.

[0150] Number of antennas of the i-th base station Number of users in the i-th cell Number of components in RIS of the i-th cell The signal of the th user of the i-th cell Beamformer corresponding to the th user Maximum transmission power of the i-th base station Downlink channel between the i-th base station and the RIS of the i-th cell Downlink channel between the th user and RIS The second base station and the second cell Downlink channel between the th user Reflection coefficient matrix in RIS

[0151] The present disclosure proposes a technique for operating RIS in a communications environment that considers multiple service providers. Different service providers typically use different operating frequencies. Therefore, interference between cells operated by different providers can be ignored. However, if a first service provider installs an RIS comprised of passive components, the channel environment of the frequency band used by a second service provider may also change. In other words, users served by the second service provider simultaneously receive signals via the direct channel and signals reflected from the RIS installed by the first service provider. If the first service provider controls the RIS, users of the service may experience performance degradation.

[0152] FIG. 14 illustrates an example of a communication environment considering multiple service providers according to one embodiment of the present disclosure. In FIG. 14 , the first base station (1420-1) and the second base station (1420-2) represent base stations belonging to different service providers. The first cell users (1410-1) include at least one terminal serviced by the first base station (1420-1), and the second cell users (1410-2) include at least one terminal serviced by the second base station (1420-2).

[0153] Considering beamforming at base station i, the transmitted signal vector for users in the i-th cell Is It can be assumed that satisfies . In addition, the beamforming matrix corresponding to the transmission signal vector Is satisfies . That is, the transmission power is the maximum transmission power of base station i. It is desirable that it does not exceed . In the present disclosure, the set of users in the i-th cell is is defined as . At this time, the first cell users Users (1410-1) belonging to have a direct channel with the base station blocked, and to overcome this, as shown in FIG. 14, the first service provider installs and operates RIS (1430) in the first cell.

[0154] set Belonging to The downlink reception signal of the th user can be expressed as in [Mathematical Formula 2] below.

[0155]

[0156] In [Equation 2], is a set Belonging to The downlink reception signal of the th user, is the i-th cell Downlink channel between the th user and RIS (1430), is the reflection coefficient matrix of RIS(1430), is the downlink channel between base station i and RIS (1430), is the set of users in the i-th cell, is the i-th cell Beamformer corresponding to the th user, is the i-th cell The signal of the th user, means noise. Here, each element of RIS (1430) is a passive element, and the diagonal vector of the reflection coefficient matrix The element values ​​of Satisfies.

[0157] Since RIS (1430) does not have signal processing capability in the baseband, it can equally affect all frequency bands. Therefore, users (1410-2) in the second cell are also affected by RIS (1430) installed in the first cell. At this time, the set Belonging to The downlink reception signal from the th user can be expressed as in [Mathematical Formula 3] below.

[0158]

[0159] In [Equation 3], is a set Belonging to Downlink reception signal from the th user, is the second base station (1420-2) and the second cell. Downlink channel between the th user, is the i-th cell Downlink channel between the th user and RIS (1430), is the reflection coefficient matrix of RIS(1430), is the element value vector of the passive element of RIS (1430), is the downlink channel between base station i and RIS (1430), is the i-th cell Beamformer corresponding to the th user, is the i-th cell The signal of the th user, means noise.

[0160] In a channel environment such as FIG. 14, a procedure for the first base station (1420-1) to acquire channel-related information may be necessary to optimize the reflection pattern of the RIS (1430). Accordingly, the present disclosure proposes various embodiments in which the first base station (1420-1) acquires channel-related information of not only the first cell user (141-1) but also the second cell user (1410-2), and controls the RIS (1430) based on the acquired information.

[0161] As shown in Fig. 14, various paths are formed between the base station and the terminal depending on the use of the RIS. For example, a path between the base station and the terminal, a path between the base station and the RIS, and a path between the RIS and the terminal are formed. For the convenience of the following description, in the present disclosure, a channel on a path between the base station and the terminal is referred to as a 'direct channel'. In addition, a channel on a path including a path between the base station and the RIS and a path between the RIS and the terminal, through which a signal transmitted from the base station, reflected by the RIS, and then reaching the first terminal experiences may be referred to as a 'reflection channel', a 'RIS channel', a 'RIS reflection channel', or other terms having an equivalent technical meaning thereto.

[0162] FIG. 15 illustrates an example of a procedure for determining a beamformer and RIS reflection pattern by a first base station considering channel information of a second base station according to one embodiment of the present disclosure. FIG. 15 illustrates a method performed by the first base station, wherein the first base station can receive channel information for optimizing the beamformer and RIS reflection pattern using the procedure of FIG. 15.

[0163] Referring to FIG. 15, in step S1501, the first base station transmits a reference signal to the first terminal. At this time, the reference signal may reach the terminal after being reflected by the RIS. Here, the reference signal may include at least one of a channel state information reference signal (CSI-RS), a demodulate reference signal (DMRS), and a phase-tracking reference signal (PT-RS).

[0164] In step S1503, the first base station receives first channel information measured based on a reference signal from the first terminal. The first channel information may include information related to a reflection channel through the RIS. Here, the reflection channel includes a channel between the first base station and the RIS and a channel between the RIS and the first terminal. That is, the first channel information may include information related to a first RIS channel including a channel between the first base station and the RIS and a channel between the RIS and the first terminal. At this time, the information related to the first RIS channel is information about an integrated channel passing through the first base station-RIS-first terminal, and information about the channel between the first base station and the RIS and information about the channel between the RIS and the first terminal may not be individually expressed.

[0165] If information about the channel between the first base station and the RIS and information about the channel between the RIS and the first terminal are individually required to optimize the reflection pattern of the RIS, additional procedures may be required.

[0166] For example, if the first base station and the RIS are used in a fixed manner, the channel value between the first base station and the RIS may be a fixed value measured in advance. Accordingly, the first base station can estimate information related to the channel between the RIS and the first terminal based on the first channel information and the channel value between the first base station and the RIS.

[0167] As another example, the first base station and the RIS can perform separate procedures for estimating the channel between the first base station and the RIS. That is, the first base station can transmit a reference signal to the RIS and receive channel information between the first base station and the RIS from the RIS. The first base station can estimate channel information between the RIS and the terminal using the first channel information received from the first terminal and the channel information between the first base station and the RIS received from the RIS.

[0168] In step S1505, the first base station receives second channel information from the second base station. The second channel information may include channel information related to the second terminal. The second base station may perform a channel estimation procedure with the second terminal to generate the second channel information. That is, the second base station may transmit a reference signal to the second terminal and receive second channel information from the second terminal. Thereafter, the second base station may transmit the second channel information to the first base station. The second channel information may include channel information related to the RIS. For example, the second channel information may include information related to a second RIS channel, which includes a channel between the second base station and the RIS and a channel between the RIS and the second terminal.

[0169] In step S1507, the first base station determines the reflection pattern of the RIS based on the first channel information and the second channel information. The first base station determines an objective function so that the gain of the first RIS channel of a user belonging to the first base station is increased and the gain of the second RIS channel of a user belonging to the second base station is decreased, and the reflection pattern of the RIS can be optimized based on the objective function.

[0170] At step S1509, the first base station transmits a data signal to the first terminal using the RIS. The first base station can control the RIS using the determined reflection pattern of the RIS. That is, the first base station transmits a control signal to the RIS so that the signal is reflected according to the determined reflection pattern. Accordingly, the first base station can transmit a data signal to the first terminal using the RIS.

[0171] In the embodiment described with reference to FIG. 15, the base station determines the reflection pattern of the RIS based on an objective function. According to one embodiment, the objective function may be defined based on the gain of the first RIS channel and the gain of the second RIS channel. For example, the objective function may be determined based on a function obtained by subtracting a weighted value from a value related to the gain of the second RIS channel from a value related to the gain of the first RIS channel. Accordingly, the first base station may perform optimization in the direction in which the objective function increases, thereby increasing the gain of the first RIS channel and reducing the impact of the RIS on the channel of the second terminal. In addition, the first base station may adjust the weights according to the channel environment, and by adjusting the weights, may determine whether to focus on increasing the gain of the first RIS channel or on reducing the gain of the second RIS channel. The first base station may optimize the reflection pattern of the RIS using the determined objective function, and the optimization may be performed through various algorithms. For example, as an optimization algorithm, the Riemannian conjugate gradient (RCG) algorithm described below can be used.

[0172] According to various embodiments, the first base station comprises a first beamformer F1 and a reflection pattern of the RIS. To this end, the procedure disclosed in Fig. 15 may be used, and the first base station may receive the necessary channel information from the second base station. However, the second base station Direct channel information between users belonging to The second beamformer is determined using only the RIS. That is, the second base station can perform communication without considering the RIS.

[0173] Each beamformer matrix can be determined using SLNR (signal-to-leakage-and-noise-ratio)-based beamforming using given channel information, and can be determined so that equal power can be distributed to each user. Since the beamformer can be determined before optimizing the RIS reflection pattern, it is determined based on the initial RIS reflection pattern. The initial RIS reflection pattern can be determined in various ways, such as random or preset RIS reflection patterns.

[0174] Referring to [Equation 3], RIS is It can also affect users belonging to . In addition, since the second base station determines F2 only through direct channel information, RIS If you design only for users who belong to Users belonging to each base station may experience severe performance degradation. Therefore, the primary base station must determine the RIS reflection pattern by considering all users belonging to each base station.

[0175] In [Equation 2] The RIS reflection channel of the th user can be expressed as follows [Mathematical Formula 4].

[0176]

[0177] In [Equation 4], is the i-th cell Downlink channel between the th user and RIS, is the reflection coefficient matrix of RIS, is the element value vector of the passive components of RIS, is the downlink channel between base station i and RIS, silver It means.

[0178] Using [Equation 4] The sum of the channel gains through the reflection channels of all users belonging to can be expressed as in [Mathematical Formula 5] below.

[0179]

[0180] In [Equation 5] means the element value vector of the passive element of RIS, silver It means, silver It means.

[0181] Here, cast can be understood as a full reflection channel of all users belonging to . Similarly, The unintended channel that users belonging to are affected by RIS can be expressed in the same way as [Mathematical Formula 4], and can be expressed as [Mathematical Formula 6] below.

[0182]

[0183] In [Equation 6], is the i-th cell Downlink channel between the th user and RIS, is the reflection coefficient matrix of RIS, is the element value vector of the passive components of RIS, is the downlink channel between base station i and RIS, Is It means.

[0184] Here, Is It can be understood as an unintended channel for all users belonging to .

[0185] The first base station is Because RIS is used to overcome obstacles and other problems that occur in the direct path of users belonging to [Mathematical Formula 5], The reflection pattern of the RIS can be optimized for the purpose of designing so that the value can be maximized. In addition, the first base station It is necessary to prevent users belonging to the RIS from experiencing unintended performance degradation. Therefore, the first base station It can be optimized in a way that reduces the value. Therefore, the base station Value and Optimization needs to be performed by considering all values. Therefore, if the two objectives described above are designed as a single optimization problem, problem (P1) can be derived as shown in [Mathematical Formula 7] below.

[0186]

[0187] In [Equation 7], is the element value vector of the passive components of RIS, is the weight, Is Frobenius norm of the total reflection channel of all users belonging to Is Frobenius norm of the unintended channel of all users belonging to , where M is the number of elements in RIS.

[0188] In problem (P1), the relative weights for the two objectives can be adjusted by λ. For example, the first base station is controlled by the RIS controlled by the first base station. A high λ value can be used to give a strong weight to minimizing the change in the channel environment of users belonging to . Conversely, the first base station A low λ value can be used to weight the channel gain of users belonging to . Therefore, the first base station can adjust the λ value based on the channel environment. For example, if the channel gain is sufficient to satisfy the service quality, It is secured for users belonging to For users belonging to , in the case of an unsecured situation, the first base station uses a high λ value. can be optimized by assigning more weight to the performance changes for users belonging to . In the opposite case, the first base station uses a low λ value. It can be optimized by assigning more weight to the performance improvement of users belonging to .

[0189] Hermitian matrix with the size of matrix M×M in [Mathematical Formula 7] Using [Equation 7], [Equation 8] can be organized as follows.

[0190]

[0191] In [Equation 8], Is , is the element value vector of the passive elements of RIS, and M represents the number of elements of RIS.

[0192] The objective function of problem (P1′) is can be expressed in the form of a simple quadratic function, but There is a constraint that each element of must have size 1. Therefore, problem (P1′) is not a convex problem. Therefore, various methods can be used to solve problem (P1′), which is not a convex problem. For example, the RCG algorithm can be used. The objective function of problem (P1′) is continuous and differentiable, A complex circle manifold Therefore, the first base station can obtain a stationary point using the RCG algorithm.

[0193] FIG. 16 illustrates an example of a procedure using the RCG algorithm to optimize the reflection pattern of an RIS according to one embodiment of the present disclosure. FIG. 16 illustrates a method performed by a first base station.

[0194] Referring to Fig. 16, in step S1601, the first base station determines the Riemann gradient. In the present disclosure, the objective function of [Mathematical Formula 8] is expressed as . The Riemann slope is at some point In the tangent space, the objective function is defined as the direction in which it increases the most. The Riemann slope can be determined through the projection onto the tangent space based on the Euclidean slope. The Euclidean slope of the objective function is can be expressed as . Therefore, the first base station is a Riemann gradient can be determined as shown in [Mathematical Formula 9] below.

[0195]

[0196] In [Equation 9], is the Riemann slope at the t-th point, is the t-th point of the tangent space, is the Euclidean slope of the objective function, means Hadamard product.

[0197] In step S1603, the base station determines a transport operator that can move the search direction vector in the previous tangent space to another tangent space. The first base station obtains the Riemann gradient Search direction using can be obtained similarly to the conjugate gradient method in Euclidean space. However, when the first base station performs optimization in a manifold, the two search directions are and may not be located in the same tangent space. The first base station cannot simply add the two search directions if they are not located in the same tangent space. Therefore, the mapping process between the two search directions can be performed using a shift operator. Manifold The movement operator used in can be expressed as in [Mathematical Formula 10] below.

[0198]

[0199] In [Equation 10], is the search direction vector in the previous contact space A move operator that can move to the next space, is the t-th point of the tangent space, is the tth search direction, is the Hadamard product, and Re(a) represents the real part of the complex number a.

[0200] Therefore, the first base station uses the movement operator to find the next search direction as shown in [Mathematical Formula 11] below. can be decided.

[0201]

[0202] In [Equation 11], is the Riemann slope at the t+1th point, is the t+1th search direction, is the search direction vector in the previous contact space A move operator that can move to the next space, means the parameter of the move operator.

[0203] In [Equation 11] can be determined by parameters of various methods. For example, the first base station may use parameters determined using either the Polak-Riebiere method or the Fletcher-Reeves method.

[0204] The Polak-Riebiere method uses a ratio calculated by dividing the current slope by the previous slope minus the current slope, and is known to be advantageous when the slope changes significantly. The Fletcher-Reeves method uses a ratio calculated by dividing the length of the current slope by the length of the previous slope, and is generally known to have a fast convergence speed. Therefore, a method for determining parameters can be determined based on the computing power of the first base station, channel conditions, etc. In this disclosure, it is assumed that the parameters are determined using the Polak-Riebiere method.

[0205] In step S1605, the first base station performs vector contraction. The first base station must perform the vector contraction process to move to the next point using the search direction acquired in step S1603. The point on the manifold is a certain step size. About If the point moves by a certain amount, the point after the movement may not exist on the manifold. Therefore, the first base station must perform a vector contraction process, which can be expressed as [Mathematical Equation 12] below, so that the point can exist on the corresponding manifold in the tangent space.

[0206]

[0207] In [Equation 12], is the t-th point of the tangent space, is the step size to move on the manifold, is the tth search direction, is a reflection pattern It means the transpose matrix with the size of the elements changed to 1.

[0208] After that, the first base station Steps S1601 to S1605 are repeated until convergence occurs. The initial settings for using the RCG algorithm can be implemented in various ways and are not limited to a specific method. Therefore, the first base station uses the RCG algorithm to optimize the reflection pattern vector as shown in [Table 3] below. can be decided.

[0209] Algorithm 1Proposed balancing RIS reflection coefficients designInitialization1: Initialize point 2: Initialize search direction 3: Iteration counter t = 0Iterative update4:repeat5: Choose step size 6: Find the next point by retraction in [equation 12]7: Compute Riemannian gradient according to [equation 9]8: Choose 9: Conduct vector transport to update as in [equation 11]10: t ← t+111:untilConvergenceOutput:

[0210] The first base station is optimized based on the above-described method for the reflection pattern coefficient vector φ. * can be determined. The first base station uses the first beamformer vector F1 as the first reflection pattern coefficient for optimization calculation. can be determined based on. In addition, for additional optimization, the first base station can update the first beamformer vector F1 based on the channel information to which the determined reflection pattern is applied. Fig. 17 illustrates an example of a procedure in which a first terminal performs communication using the reflection pattern of an RIS considering the channel information of a second base station according to an embodiment of the present disclosure. Fig. 17 illustrates a method performed by the first terminal.

[0211] Referring to Figure 17, in step S1701, the first terminal receives a reference signal from the first base station. The first base station requires channel information between the first base station and the first terminal to determine the RIS reflection pattern. Accordingly, the first base station and the first terminal can perform a measurement procedure.

[0212] In step S1703, the first terminal transmits first channel information to the first base station. The first terminal may determine the first channel information based on a reference signal received from the base station and transmit the first channel information to the base station. For example, the first channel information may include channel information regarding RIS.

[0213] In step S1705, the first terminal receives a signal from the first base station through the RIS. At this time, the RIS can be controlled by the first base station. The reflection pattern of the RIS can be determined based on first channel information and second channel information. At this time, the second channel information can include channel information between the first base station service provider and a second base station and the second terminal of another service provider. The reflection pattern of the RIS can be determined in a direction in which the channel gain from the first base station to the first terminal increases, and the channel gain that the second terminal is unintentionally affected by the RIS control decreases. For example, the reflection pattern of the RIS can be determined through an RCG algorithm as shown in [Table 4].

[0214] FIG. 18 illustrates an example of signaling for performing communication using a RIS (1830) reflection pattern determined based on channel information of a first base station (1820-1) and channel information of a second base station (1820-2) according to one embodiment of the present disclosure.

[0215] Referring to FIG. 18, in step S1801, base stations (1820-1, 1820-2), terminals (1810-1, 1810-1), and RIS (1830) perform an RRC connection procedure. The first base station (1820-1) and the second base station (1820-2) are base stations operated by different service providers, and a procedure for establishing a connection (e.g., Xn connection) between the first base station (1820-1) and the second base station (1820-2) may be required to transmit second channel information. In addition, when the first base station (1820-1) wirelessly controls the RIS (1830), a procedure for establishing a connection between the first base station (1820-1) and the RIS (1830) may be required. Additionally, in order to measure channel information, a procedure for establishing a connection (e.g., an RRC connection) between a first base station (1820-1) and a first terminal (1830-1) may be performed, and further, a procedure for establishing a connection between a second base station (1820-2) and a second terminal (1810-2) may be performed. Furthermore, an initial connection procedure may be performed between the first base station (1820-1) and the first terminal (1830-1), and between the second base station (1820-2) and the second terminal (1810-2).

[0216] In step S1803, the first base station (1820-1) transmits a first reflection pattern to the RIS (1830). The first reflection pattern is an initial reflection pattern and may be configured to measure first channel information. In step S1805, the first base station (1820-1) transmits a first reference signal to the first terminal (1830-1). For example, the first reference signal may include one of a CSI-RS, a DMRS, and a PT-RS. In step S1807, the first terminal (1830-1) transmits first channel information to the first base station (1820-1). The first channel information is information determined based on channel information between the first base station (1820-1) and the RIS (1830) and channel information between the RIS (1830) and the first terminal (1830-1), and refers to information related to the channel used by the first base station (1820-1) and the first terminal (1830-1).

[0217] In step S1809, the second base station (1820-2) transmits a second reference signal to the second terminal (1810-2). In step S1811, the second terminal (1810-2) transmits second channel information to the second base station (1820-2). The second channel information may include information related to a second RIS channel, which includes a channel between the second base station (1820-2) and the RIS (1830) and a channel between the RIS and the second terminal (1810-2). In step S1813, the second base station (1820-2) transmits the second channel information to the first base station (1820-1). In order to optimize the reflection pattern of the RIS, the first base station (1820-1) may need information related to terminals served by the second base station. For example, the second channel information may include the number of terminals served by the second base station (1820-2).

[0218] At step S1815, the first base station (1820-1) optimizes the RIS (1830) beamformer and reflection pattern. The first base station (1820-1) can obtain all channel information necessary for optimization based on the first channel information and the second channel information. The first base station (1820-1) can determine the second reflection pattern based on the increase or decrease in channel gain caused by the RIS (1830). For example, the second reflection pattern can be optimized to increase the gain of a first RIS (1830) channel, which includes a channel between a first base station (1820-1) and a RIS (1830) and a channel between a RIS (1830) and a first terminal (1830-1), and to decrease the gain of a second RIS (1830) channel, which includes a channel between a second base station (1820-2) and a RIS (1830) and a channel between a RIS (1830) and a second terminal (1810-2). According to one embodiment, for optimization, the first base station (1820-1) can use the objective function of [Mathematical Formula 7] and determine weight values ​​based on the channel environment.

[0219] The method for determining the beamforming vector can be implemented in various ways based on the channel environment and the computing power of the base station. For example, the first base station (1820-1) can determine the beamforming vector based on the signal-to-leakage-and-noise-ratio (SLNR) for a given channel environment. For example, the first base station (1820-1) can determine the first beamformer vector, F1, based on channel information to which the determined reflection pattern is applied for additional optimization.

[0220] At this time, the first base station (1820-1) can determine the beamforming vector F1 so that equal power distribution can be achieved for each user. However, the second base station (1820-2) determines the beamforming vector F2 using only the second channel information, i.e., direct channel information, without regard to the RIS (1830). Therefore, additional optimization of the beamforming vector F2 may not be performed.

[0221] In step S1817, the first base station (1820-1) transmits a second reflection pattern to the RIS (1830). The second reflection pattern includes an optimized reflection pattern. Therefore, the RIS (1830) can adjust the passive components based on the received second reflection pattern. In step S1819, the first base station (1820-1) transmits a data signal to the first terminal (1830-1). The first terminal (1830-1) can receive the data signal through the reflection channel formed by the first RIS (1830) based on the optimized reflection pattern and beamforming.

[0222] In step S1821, the second base station (1820-2) transmits a data signal to the second terminal (1810-2). Since the second reflection pattern determined by the first base station (1820-1) reduces the influence on the second RIS (1830) channel, the second terminal (1810-2) can receive the data signal from the second base station (1820-2).

[0223] The theoretical complexity of the algorithm proposed in this disclosure can be expressed as follows, assuming N1 = N2 = N and K1 = K2 = K. First, for the given RIS(1830) reflection coefficient vector The complexity required to compute the value is It can be expressed as . The complexity of the RCG algorithm mainly occurs in calculating the Euclidean gradient, can be expressed as . Therefore, the overall complexity of the final algorithm is is expressed as , where I represents the total number of iterations of the algorithm proposed in this disclosure.

[0224] This disclosure describes the results of a comparative experiment between the optimization method disclosed in this disclosure and existing methods. The comparative experiment demonstrates that the optimization method disclosed in this disclosure enables efficient transmission and reception.

[0225] Fig. 19 illustrates an example of a simulation environment for a comparative experiment according to one embodiment of the present disclosure. Fig. 19 is a drawing showing the comparative experiment environment set in the present disclosure based on a 3D coordinate system.

[0226] Figure 19 illustrates the positions of the first base station (BS 1) and the second base station (BS 2), and the terminals belonging to each base station, on the xy plane. Users can arbitrarily determine their positions within each indicated area. In addition, the heights of each base station are set to 15 m, the height of the RIS is 10 m, and the heights of the users are set to 1 m. In addition, it is assumed that the first base station, the second base station, and the RIS have a uniform planar array (UPA) structure.

[0227] In addition, all communication channels were assumed to have a Rician channel model, and the angles of the line of sight (LOS) channels were calculated according to the locations of the transmitter and receiver. The angles of the non-line of sight (NLoS) channels were arbitrarily determined to have a specific dispersion based on the LOS channel. The entire system bandwidth was assumed to have 10 MHz, and the path loss exponent in large-scale fading was assumed to be 4.5 for the channel between each base station and each user, 2.4 for the channel between the RIS and each user, and 2.5 for the channel between each base station and the RIS.

[0228] Regarding the number of NLoS channels, the number of NLoS channels between each base station and each user was assumed to be 8, the number of NLoS channels between RIS and each user was assumed to be 4, and the number of NLoS channels between each base station and RIS was assumed to be 8. In addition, for the Rassian elements, the channel between each base station and each user was assumed to be 3 db, the channel between RIS and each user was assumed to be 5 db, and the channel between each base station and RIS was assumed to be 5 db. In addition, in order to consider the homogeneity between each cell, the number of antennas of each base station was set to be the same as N1 = N2 = N, and the number of users belonging to each base station was set to be the same as K1 = K2 = K. In addition, the maximum transmission power of each branch station was also P T,1 = P T,2 = P T was set to the same.

[0229] The performance indicator used is the sum of the transmission rates of users in each cell. Belonging to The maximum transmission rate achievable for the th user can be expressed as follows [Mathematical Formula 13].

[0230]

[0231] In [Equation 13], Is Belonging to The maximum achievable transmission rate for the th user, is the element value vector of the passive components of RIS, Is , is the i-th cell Beamformer corresponding to the th user, silver It refers to the variance of noise experienced by the th user.

[0232] likewise Belonging to The maximum transmission rate achievable for the th user can be expressed as [Mathematical Formula 14].

[0233]

[0234] In [Equation 14], Is Belonging to The maximum achievable transmission rate for the th user, is the element value vector of the passive components of RIS, is the i-th cell Beamformer corresponding to the th user, Is , silver It refers to the variance of noise experienced by the th user.

[0235] Using [Equation 13] and [Equation 14], The sum of the transmission rates of users belonging to can be calculated as, The sum of the transmission rates of users belonging to can be calculated as

[0236] Each beamforming matrix can be determined based on SLNR (signal-to-leakage-and-noise-ratio) beamforming for a given channel, and is determined so that equal power can be distributed to each user. As described above, since the second base station does not consider RIS, the beamformer vector F2 of the second base station only has direct channel information. It is decided only through .

[0237] The proposed technique compared to the technique shown in Figures 20 and 21 is shown as follows. First, the optimization that sets the λ value defined in each [Mathematical Formula 7] to 0 can be seen as not considering the channel gain for the second base station at all because it calculates the value for the channel gain for the second base station as 0. That is, the first base station The channels of users belonging to are not considered at all, This can be seen as a case where the reflection coefficient of RIS is determined to maximize the gain through the RIS channel of users belonging to . When λ = 0, the total transmission rate related to the first base station is expressed as 'λ = 0 - Cell 1', and the total transmission rate related to the second base station is expressed as 'λ = 0 - Cell 2'. In addition, in an environment that considers the channel of the second base station using the technique using the algorithm proposed in this disclosure, the total transmission rate related to the first base station is expressed as 'Proposed - Cell 1', and the total transmission rate related to the second base station is expressed as 'Proposed - Cell 2'. Finally, in the case where RIS does not exist, the first base station If there is no impact on users belonging to the second base station, the total transmission rate related to the second base station is indicated as 'No RIS - Cell 2'.

[0238] Fig. 20 illustrates an example of a comparative experiment in which the total transmission rate varies based on the transmission power according to one embodiment of the present disclosure. Fig. 20 shows the total transmission rate of each cell according to the transmission power, with N=8, M=96, K=6, and λ=20 dbm set.

[0239] First, Fig. 20 shows that as the transmission power increases, the overall total transmission rate increases. In addition, it can be seen that the transmission rate of the second base station is higher in the case of No RIS - Cell 2 than in the case of λ = 0 - Cell 2. These results indicate that the first base station If you control RIS without considering the users who belong to it, Users belonging to this group experience unintended performance degradation due to the additional channel caused by RIS. In addition, the performance degradation occurs more and more as the transmission power increases. Therefore, Fig. 20 shows that the method proposed in the present disclosure can reduce unintended performance degradation. That is, in the case of Proposed - Cell 1, performance degradation does not occur significantly compared to the case of λ = 0 - Cell 1, and in the case of Proposed - Cell 1, a large performance increase occurs compared to the case of λ = 0 - Cell 2, so that performance degradation caused by RIS can be reduced. Therefore, Fig. 20 shows that the invention proposed in the present disclosure can effectively prevent one service provider from worsening the communication performance of another service provider when using RIS.

[0240] Fig. 21 illustrates an example of the performance of the total transmission rate according to the balance parameter λ according to one embodiment of the present disclosure. The experimental results of Fig. 21 are as follows: N = 8, M = 96, K = 6, P T =The result is derived assuming 30dbm.

[0241] Figure 21 shows that the total transmission rate for the second base station increases as the parameter λ value increases. This result indicates that as the λ value increases, the RIS This means that the degradation of communication performance that occurred to users belonging to the first base station is reduced. Also, Fig. 21 shows that the total transmission rate for the first base station decreases as the λ value increases. This result shows that as the λ value increases, This means that performance for the first cell is reduced because RIS is designed to take into greater consideration the performance degradation that occurs for users belonging to the first cell.

[0242] The method proposed in this disclosure allows a base station to efficiently operate RIS in a communication environment that considers multiple service providers. This disclosure relates to a method that considers the communication environments of other service providers when one service provider uses RIS. Therefore, the method is not limited to the algorithms and procedures described above. Specifically, the base station can optimize the RIS reflection pattern using an algorithm other than the RCG algorithm.

[0243] It is clear that the examples of the proposed methods described above can also be considered as a type of proposed methods, as they can be included as one of the implementation methods of the present disclosure. Furthermore, the proposed methods described above can be implemented independently, but they can also be implemented in the form of a combination (or merge) of some of the proposed methods. Information regarding the applicability of the proposed methods (or information regarding the rules of the proposed methods) can be defined by a rule such that the base station notifies the terminal of the application of the proposed methods through a predefined signal (e.g., a physical layer signal or a higher layer signal).

[0244] 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 do not explicitly cite each other in the claims may be combined to form embodiments or incorporated into new claims through post-filing amendments.

[0245] 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.

[0246] 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.

[0247] 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 first base station in a wireless communication system, A step of transmitting a reference signal to a first terminal; A step of receiving first channel information measured based on the reference signal from the first terminal; A step of receiving second channel information from a second base station; A step of determining a reflection pattern of a reconfigurable intelligent surface (RIS) based on the first channel information and the second channel information; and A step of transmitting a data signal to the first terminal is included, The first channel information includes information related to a first RIS channel, which includes a channel between the first base station and the RIS and a channel between the RIS and the first terminal, A method wherein the second channel information includes information related to a second RIS channel including a channel between the second base station and the RIS and a channel between the RIS and a second terminal.

2. In claim 1, A method in which the above reflection pattern is determined based on an objective function determined based on the first channel information and the second channel information.

3. In claim 2, The above objective function is determined based on a function obtained by subtracting a weighted value multiplied by a value related to the gain of the second RIS channel from a value related to the gain of the first RIS channel, The above reflection pattern is determined in such a way as to maximize the objective function.

4. In claim 3, The above reflection pattern is a method determined by a RCG (Riemannian conjugate gradient) algorithm based on the above objective function.

5. In claim 3, The step of determining the above reflection pattern is: A step of determining a Riemann gradient of the objective function with respect to a first point associated with the RIS reflection pattern; A step of determining a first search direction based on the above Riemann gradient; A step of determining a movement operator that moves from the previous tangent space to the next tangent space; A step of determining a second search direction based on the above movement operator; A step of determining a second point based on the first point and the second search direction; and A method comprising the step of determining a third point indicating the reflection pattern through vector contraction of the second point.

6. In claim 5, The above second search direction is determined based on the value obtained by multiplying the parameter by the movement operator, The above parameters are determined based on a ratio calculated by dividing the length of the current slope by the length of the previous slope.

7. In claim 3, The above weights are determined based on the channel environment of the first base station and the channel environment of the second base station.

8. In claim 1, a step of determining the initial reflection pattern of the above RIS; and Further comprising a step of determining a first beamforming vector, A method in which the first beamforming vector is determined based on the signal-to-leakage-and-noise-ratio (SLNR) using the initial reflection pattern.

9. In claim 8, The step of transmitting a data signal to the first terminal is: A method comprising the step of updating a first beamforming vector to a second beamforming vector based on the reflection pattern determined based on the first channel information and the second channel information.

10. In claim 1, The above first base station and the above second base station use different frequency bands.

11. In claim 1, The above first base station and the above second base station are operated by different service providers.

12. A method performed by a first terminal in a wireless communication system, A step of receiving a reference signal from a first base station; A step of transmitting first channel information measured based on the reference signal to the first base station; and A step of receiving a data signal from the first base station through a reconfigurable intelligent surface (RIS), The reflection pattern of the above RIS is determined based on the first RIS channel and the second RIS channel, The first RIS channel includes a channel between the first base station and the RIS and a channel between the RIS and the first terminal, A method wherein the second RIS channel comprises a channel between a second base station and the RIS and a channel between the RIS and the second terminal.

13. In claim 12, A method in which the above reflection pattern is determined to maximize an objective function determined based on a function obtained by subtracting a weighted value multiplied by a value related to the gain of the second RIS channel from a value related to the gain of the first RIS channel.

14. In claim 12, The above first base station and the above second base station are operated by different service providers.

15. In a first base station in a wireless communication system, Transmitter and receiver; and comprising a processor connected to the above transceiver, The above processor, Transmit a reference signal to the first terminal, Receive first channel information measured based on the reference signal from the first terminal, Receive second channel information from the second base station, Determine the reflection pattern based on the first channel information and the second channel information, Controls to transmit a data signal to the first terminal, The first channel information includes information related to a first RIS channel, which includes a channel between the first base station and the RIS and a channel between the RIS and the first terminal, A first base station, wherein the second channel information includes information related to a second RIS channel, including a channel between the second base station and the RIS and a channel between the RIS and a second terminal.

16. In a wireless communication system, at the first terminal, Transmitter and receiver; and comprising a processor connected to the above transceiver, The above processor, Receive a reference signal from the first base station, Receive first channel information measured based on the reference signal from the first base station, Control to receive a data signal from the first base station through RIS (reconfigurable intelligent surface), The reflection pattern of the above RIS is determined based on the first RIS channel and the second RIS channel, The first RIS channel includes a channel between the first base station and the RIS and a channel between the RIS and the first terminal, The second RIS channel comprises a first terminal including a channel between a second base station and the RIS and a channel between the RIS and the second terminal.

17. In communication devices, At least one processor; At least one computer memory coupled 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 a reference signal to a first terminal; A step of receiving first channel information measured based on the reference signal from the first terminal; A step of receiving second channel information from a second base station; A step of determining a reflection pattern of a RIS (reconfigurable intelligent surface) based on an objective function generated based on the first channel information and the second channel information; and A step of transmitting a data signal to the first terminal is included, The first channel information includes information related to a first RIS channel, including a channel between the communication device and the RIS and a channel between the RIS and the first terminal, A communication device wherein the second channel information includes information related to a second RIS channel including a channel between the second base station and the RIS and a channel between the RIS and the second terminal.

18. 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 a reference signal to the first terminal, Receive first channel information measured based on the reference signal from the first terminal, Receive second channel information from the second base station, Determine the reflection pattern of the RIS (reconfigurable intelligent surface) based on the objective function generated based on the first channel information and the second channel information, Controls to transmit a data signal to the first terminal, The first channel information includes information related to a first RIS channel, including a channel between the device and the RIS and a channel between the RIS and the first terminal, A computer-readable medium including information related to a second RIS channel, wherein the second channel information includes a channel between the second base station and the RIS and a channel between the RIS and the second terminal.

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