Method and device for frequency division duplexing communication using reconfigurable intelligent surface in wireless communication system

Abstract

The present disclosure relates to a method for operating a base station in a wireless communication system. The method comprises the steps in which the base station: performs a radio resource control (RRC) connection establishment procedure with a terminal via a reconfigurable intelligent surface; estimates uplink channel state information on the basis of a reference signal received from the terminal; receives downlink channel state information from the terminal; determines an uplink precoder, a downlink precoder, and an RIS reflection pattern related to data transmission and reception on the basis of the uplink channel state information and the downlink channel state information; and transmits the determined RIS reflection pattern to the RIS and transmits the uplink precoder to the terminal.

Description

Frequency division duplex communication method and device using reconfigurable intelligent surfaces in a wireless communication system

[0001] The following description relates to a wireless communication system, and to a device and method for simultaneously optimizing uplink and downlink channels of frequency division duplexing (FDD) communication in a wireless communication system using a reconfigurable intelligent surface (RIS).

[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 simultaneously optimizing uplink and downlink data transmission rates of frequency division duplexing (FDD) communication using a reconfigurable intelligent surface (RIS).

[0005] The present disclosure can provide a method for transmitting and receiving signals between a terminal and a base station using RIS in a wireless communication system.

[0006] The present disclosure may provide a method for a base station to perform an initial connection with a terminal and an RIS in a wireless communication system.

[0007] The present disclosure can provide an algorithm for simultaneously optimizing uplink and downlink data transmission rates using RIS.

[0008] The present disclosure provides a method for a base station to simultaneously optimize uplink and downlink data transmission rates for a terminal using multiple antennas.

[0009] The present disclosure relates to a device and method for transmitting a plurality of transport blocks (TBs) as a single unit in a wireless communication system.

[0010] 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.

[0011] As an example of the present disclosure, in a method of operating a base station in a wireless communication system, the base station establishes an RRC (radio resource control) connection with a terminal through a reconfigurable intelligent surface (RIS).

[0012] n establishment) procedure, a step of estimating uplink channel state information based on a reference signal received from the terminal, a step of receiving downlink channel state information from the terminal, a step of determining an uplink precoder, a downlink precoder, and a RIS reflection pattern related to data transmission and reception based on the uplink channel state information and the downlink channel state information, and a step of transmitting the determined RIS reflection pattern to the RIS and transmitting the uplink precoder to the terminal.

[0013] As an example of the present disclosure, a method for operating a terminal in a wireless communication system may include a step in which the terminal performs an RRC (radio resource control) connection establishment procedure with a base station through a reconfigurable intelligent surface (RIS), a step in which an uplink reference signal is transmitted to the base station, a step in which downlink channel state information is transmitted based on the reference signal received from the base station, and a step in which the uplink channel state information based on the uplink reference signal and the uplink precoder determined based on the downlink channel state information are received from the base station.

[0014] As an example of the present disclosure, in a wireless communication system, a base station comprises: a transceiver; and a processor connected to the transceiver, wherein the processor performs an RRC (radio resource control) connection establishment procedure with a terminal through a reconfigurable intelligent surface (RIS), estimates uplink channel state information based on a reference signal received from the terminal, receives downlink channel state information from the terminal, determines an uplink precoder, a downlink precoder, and an RIS reflection pattern related to data transmission and reception based on the uplink channel state information and the downlink channel state information, transmits the determined RIS reflection pattern to the RIS, and transmits the uplink precoder to the terminal.

[0015] As an example of the present disclosure, in a wireless communication system, a terminal includes a transceiver and a processor connected to the transceiver, wherein the processor is configured to perform an RRC (radio resource control) connection establishment procedure with a base station through a reconfigurable intelligent surface (RIS), transmit an uplink reference signal to the base station, transmit downlink channel state information based on the reference signal received from the base station, and receive, from the base station, uplink channel state information based on the uplink reference signal and an uplink precoder determined based on the downlink channel state information.

[0016] 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 direct operations when executed by the at least one processor, wherein the operations may include performing an RRC (radio resource control) connection establishment procedure with a terminal through a reconfigurable intelligent surface (RIS), estimating uplink channel state information based on a reference signal received from the terminal, receiving downlink channel state information from the terminal, determining an uplink precoder, a downlink precoder, and an RIS reflection pattern related to data transmission and reception based on the uplink channel state information and the downlink channel state information, transmitting the determined RIS reflection pattern to the RIS, and transmitting the uplink precoder to the terminal.

[0017] As an example of the present disclosure, a non-transitory computer-readable medium storing at least one instruction, the at least one instruction being executable by a processor, wherein the at least one instruction causes a device to perform an RRC (radio resource control) connection establishment procedure with a terminal through a reconfigurable intelligent surface (RIS), estimate uplink channel state information based on a reference signal received from the terminal, receive downlink channel state information from the terminal, determine an uplink precoder, a downlink precoder, and a RIS reflection pattern related to data transmission and reception based on the uplink channel state information and the downlink channel state information, transmit the determined RIS reflection pattern to the RIS, and transmit the uplink precoder to the terminal.

[0018] 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.

[0019] The following effects may be achieved by embodiments based on the present disclosure.

[0020] According to the present disclosure, a terminal and a base station can efficiently transmit and receive signals using a reconfigurable intelligent surface (RIS) in a wireless communication system.

[0021] According to the present disclosure, a terminal and a base station having multiple antennas in a wireless communication system can perform optimization considering downlink and uplink simultaneously.

[0022] According to the present disclosure, in a wireless communication system, a terminal and a base station can efficiently transmit and receive signals by performing optimization based on a wireless communication traffic environment.

[0023] 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.

[0024] 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.

[0025] FIG. 1 is a diagram illustrating an example of a communication system applicable to the present disclosure.

[0026] FIG. 2 is a drawing showing an example of a wireless device applicable to the present disclosure.

[0027] FIG. 3 is a diagram showing another example of a wireless device applicable to the present disclosure.

[0028] FIG. 4 is a drawing showing an example of a mobile device applicable to the present disclosure.

[0029] FIG. 5 is a drawing showing an example of a vehicle or autonomous vehicle applicable to the present disclosure.

[0030] Figure 6 is a diagram showing an example of AI (Artificial Intelligence) applicable to the present disclosure.

[0031] FIG. 7 is a diagram illustrating a method for processing a transmission signal applicable to the present disclosure.

[0032] FIG. 8 is a diagram showing an example of a communication structure that can be provided in a 6G system applicable to the present disclosure.

[0033] Figure 9 is a diagram showing an electromagnetic spectrum applicable to the present disclosure.

[0034] Fig. 10 is a diagram showing a THz communication method applicable to the present disclosure.

[0035] FIG. 11 is a diagram illustrating a wireless channel environment according to one embodiment of the present disclosure.

[0036] FIG. 12 is a diagram illustrating an intelligent wireless environment according to one embodiment of the present disclosure.

[0037] FIG. 13 is a diagram illustrating an existing wireless channel environment and an intelligent wireless channel environment according to one embodiment of the present disclosure.

[0038] FIG. 14 is a diagram illustrating a communication environment of an intelligent wireless channel environment according to one embodiment of the present disclosure.

[0039] FIG. 15 is a diagram illustrating a procedure for a base station to move a point in a manifold optimization-based algorithm according to one embodiment of the present disclosure.

[0040] FIG. 16 is a flowchart illustrating an algorithm for optimizing a reconfigurable intelligent surface (RIS) reflection pattern according to one embodiment of the present disclosure.

[0041] FIG. 17 is a diagram showing a weighted sum transmission rate according to the number of external repetitions according to one embodiment of the present disclosure.

[0042] FIG. 18 is a diagram showing a weighted sum transmission rate according to the number of elements (L) of RIS according to one embodiment of the present disclosure.

[0043] FIG. 19 is a diagram showing a performance comparison of weighted sum transmission rate according to downlink transmission power according to one embodiment of the present disclosure.

[0044] FIG. 20 is a diagram showing a data transmission rate according to a weighting parameter according to one embodiment of the present disclosure.

[0045] FIG. 21 is a diagram illustrating a procedure for a base station to transmit and receive data using RIS based on uplink and downlink channel information according to one embodiment of the present disclosure.

[0046] FIG. 22 is a diagram illustrating a procedure for a terminal to transmit and receive data using RIS based on uplink and downlink channel information according to one embodiment of the present disclosure.

[0047] FIG. 23 is a diagram illustrating signaling for a base station, an RIS, and a terminal to simultaneously optimize uplink and downlink according to one embodiment of the present disclosure.

[0048] FIG. 24 is a diagram illustrating a timing diagram for channel estimation and data communication according to one embodiment of the present disclosure.

[0049] 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.

[0050] 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.

[0051] 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.

[0052] 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.

[0053] 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.

[0054] 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).

[0055] 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.

[0056] 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.

[0057] 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.

[0058] 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.

[0059] 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.

[0060] 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.

[0061] 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).

[0062] 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.

[0063] 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.

[0064]

[0065] Communication system applicable to the present disclosure

[0066] 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.

[0067] 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.

[0068] FIG. 1 is a diagram illustrating an example of a communication system applied to the present disclosure.

[0069] 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.

[0070] 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).

[0071] 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.

[0072]

[0073] Communication system applicable to the present disclosure

[0074] FIG. 2 is a diagram illustrating an example of a wireless device applicable to the present disclosure.

[0075] 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.

[0076] 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.

[0077] 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 commands 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.

[0078] 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.

[0079] 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.

[0080] 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.

[0081] 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.

[0082]

[0083] Wireless device structure applicable to the present disclosure

[0084] FIG. 3 is a diagram illustrating another example of a wireless device applicable to the present disclosure.

[0085] 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).

[0086] 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.

[0087] 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.

[0088]

[0089] Mobile devices to which the present disclosure applies

[0090] FIG. 4 is a drawing illustrating an example of a mobile device applied to the present disclosure.

[0091] 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).

[0092] 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.

[0093] 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.

[0094] 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).

[0095]

[0096] Types of wireless devices to which the present disclosure applies

[0097] FIG. 5 is a drawing illustrating an example of a vehicle or autonomous vehicle to which the present disclosure applies.

[0098] 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.

[0099] 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.

[0100] 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).

[0101] 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.

[0102] 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.

[0103] 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).

[0104] 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.

[0105] 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).

[0106] 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.

[0107] 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).

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113]

[0114] 6G communication system

[0115] 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) reduced energy consumption of battery-free IoT devices, (vi) ultra-reliable connectivity, and (vii) connected intelligence with machine learning capabilities. The vision of the 6G system can be divided into four aspects: "intelligent connectivity," "deep connectivity," "holographic connectivity," and "ubiquitous connectivity," and the 6G system can satisfy the requirements as shown in Table 1 below. That is, [Table 1] is a table showing the requirements of the 6G system.

[0116] Per device peak data rate1 TbpsE2E latency1 msMaximum spectral efficiency100 bps / HzMobility supportup to 1000 km / hrSatellite integrationFullyAIFullyAutonomous vehicleFullyXRFullyHaptic CommunicationFully

[0117] 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.

[0118] 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.

[0119] Referring to Figure 8, 6G systems are expected to have 50 times higher simultaneous wireless communication connectivity than 5G wireless communication systems. URLLC, a key feature of 5G, is expected to become an even more crucial technology in 6G communications by providing end-to-end latency of less than 1 ms. Furthermore, 6G systems will have significantly superior 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, so mobile devices in 6G systems may not need to be charged separately.

[0120]

[0121] Core implementation technology of 6G systems

[0122] - Artificial Intelligence (AI)

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] However, the application of DNN for transmission at the physical layer may have the following problems.

[0128] 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.

[0129] 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.

[0130] Below, we will look at machine learning in more detail.

[0131] 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. Data learning methods in machine learning can be broadly categorized into three types: supervised learning, unsupervised learning, and reinforcement learning.

[0132] 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.

[0133] 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. 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 according to the 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.

[0134] 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.

[0135] 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.

[0136] The neural network cores used in learning methods are mainly deep neural networks (DNN), convolutional deep neural networks (CNN), and recurrent Boltzmann machines (RNN), and these learning models can be applied.

[0137]

[0138] THz (Terahertz) communication

[0139] 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.

[0140] 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.

[0141] 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.

[0142]

[0143] Terahertz (THz) wireless communications

[0144] FIG. 10 is a diagram illustrating a THz communication method applicable to the present disclosure.

[0145] 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.

[0146] Specific embodiments of the present invention

[0147] Below, we propose a method and device for simultaneous optimization of uplink and downlink in a frequency division duplexing (FDD) system using a reconfigurable intelligent surface (RIS). The RIS may be an intelligent reflect surface (IRS), but is not limited to a specific designation. For convenience of explanation, the following description focuses on the RIS, but is not limited to that designation.

[0148] For example, current wireless communication technology 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 increase transmission efficiency by adjusting at least one of beamforming, power control, and adaptive modulation to the channel environment (H) between the transmitter and receiver. At this time, the channel environment can be random, uncontrolled, and naturally fixed. That is, in existing communication systems, the channel environment can be fixed and each endpoint can be controlled to optimize for the channel environment. Therefore, the transmitter and receiver must perform optimization to adapt to the channel and transmit and receive data through this. However, in environments with high signal loss and low multipath, such as NLOS (non-line of sight) in shaded areas or 6G THz, endpoint optimization alone may not be enough to overcome Shannon's Capacity Limit, and telecommunications operators may struggle to achieve the desired throughput.

[0149] Considering the above, the new communication system can perform communication based on a smart radio environment. In this smart radio environment, RIS can be used as a controllable factor, similar to a transmitter and receiver.

[0150] 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.

[0151] FIG. 11 is a diagram illustrating a wireless channel environment according to an embodiment of the present disclosure. Referring to FIG. 11, in an existing communication system, the wireless channel environment (H) may be naturally fixed and may be in an uncontrollable random state. Therefore, the transmitter (1110) and the receiver (1120) may find an optimized transmission and reception method by adapting to the channel. The transmitter (1110) and the receiver (1120) may 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 where signal loss is high and multipath application is difficult, and in an NLOS environment such as a shadow area, there may be limitations in data transmission. For example, the following [Mathematical Formula 1] may 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, the channel If the size is small, there may be a limit to increasing the channel capacity.

[0152] In a fixed wireless channel environment, there may be a limit to increasing the 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 the above-described channel That is, in an intelligent wireless environment, the wireless channel environment based on RIS can be an adjustable factor, thereby increasing the channel capacity.

[0153]

[0154] As an example, FIG. 12 is a diagram illustrating 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 can be a factor for optimization. More specifically, in the above-described Fig. 11, optimization can be performed in the transmitter (1110) and the receiver (1120) based on "max{f(Tx, Rx)}" as an endpoint optimization, as described above. However, in Fig. 12, optimization can be performed in the transmitter (1210) and the receiver (1220) based on "max{f(Tx, Rx, H)}" as an endpoint optimization. That is, in an intelligent wireless environment, the channel can be optimized based on an intelligent reflector. can be used as a factor for optimization.

[0155] FIGS. 13A and 13B are diagrams illustrating 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.

[0156] 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.

[0157] Therefore, communication methods using RIS are attracting attention as a technique for improving communication performance in post-5G communications. By controlling the amplitude or phase of a signal in real time through RIS, base stations can achieve high data rates or energy efficiency. Previous research has primarily focused on time division duplexing (TDD) systems to leverage channel reciprocity between uplink and downlink. However, frequency division duplexing (FDD) systems are widely used in current wireless communication systems and can be more efficient than TDD systems in scenarios requiring low latency and symmetrical traffic between uplink and downlink. Therefore, research on FDD systems is necessary in systems utilizing RIS.

[0158] One of the key features of FDD systems is that uplink and downlink signal transmission can occur simultaneously. Since the base station can control the phase shift of a single RIS at a single point in time, the reflection coefficient in the RIS must be optimized to support both uplink and downlink transmissions simultaneously. In systems where a terminal has a single antenna, the problem of simultaneous optimization of uplink and downlink has been addressed. Little research has been conducted on terminals with multiple antennas, and the present disclosure provides a method and device for optimizing signals for terminals with multiple antennas.

[0159] [Table 2] is a table showing symbols to be used in this disclosure.

[0160] - : Transpose of matrix A- : Hermitian transpose matrix of matrix A- : Element-wise conjugate matrix of matrix A- : Set of complex numbers- : A set of complex matrices of size - : matrix of th row- , , : Each square matrix Determinant, trace and inverse matrix- : vector A diagonal matrix with elements as diagonal components- : vector of -norm value- : matrix Frobenius-norm value of - :average vector and covariance matrix Multivariate normal distribution with - : Identity matrix of size- , , , Each complex number The magnitude, conjugate, angle and real part of - : Kronecker product- : Hadamard product- : big-O representation

[0161] [Table 3] is a table showing the notation of terms to be used in this disclosure.

[0162] Number of BS (base station) antennas Number of user antennas Total number of RIS components RIS horizontal element count RIS vertical element count Horizontal length of one RIS element Vertical length of one RIS element Distance between BS antennas Distance between user antennas Number of downlink data streams Number of uplink data streams Downlink BS-RIS channel Uplink BS-RIS channel Downlink RIS-User Channel Uplink RIS-User Channel RIS reflection coefficient matrix Precoder in BS Precoder from the user Transmission signal vector at BS Transmission signal vector from the user Noise from users Noise in BS Noise distribution in users Noise distribution in BS Downlink carrier frequency Uplink carrier frequency BS's highest transmission power User's maximum transmission power

[0163] FIG. 14 is a diagram illustrating a communication environment in an intelligent wireless channel environment according to one embodiment of the present disclosure. FIG. 14 illustrates an environment to be considered for simultaneous optimization of uplink and downlink in a single-user multiple-input multiple-output (SU-MIMO) system assuming FDD. The channel between a base station (1410) and a terminal (1430) that does not pass through an RIS (1420) may be blocked by obstacles. The signals received by the base station (1410) and the terminal (1430) in uplink and downlink transmissions can be expressed by the following [Mathematical Formula 2].

[0164]

[0165] In [Equation 2], is an uplink signal received by the base station (1410), is a downlink signal received by the terminal (1430). In one embodiment of the present disclosure, a geometric channel model may be used as the channel model. The antenna of the base station (1410) and the antenna of the terminal (1430) may have a uniform linear array (ULA) structure. The RIS (1420) may have a uniform planar array (UPA) structure. Therefore, the downlink channel between the downlink base station (1410) and the RIS (1420) can be expressed as in [Mathematical Formula 3] below.

[0166]

[0167] In [Equation 3], means the number of multipaths of the BS-RIS link, is in the downlink It means the channel coefficient of the th path, refers to the downlink array response vector of the base station (1410), refers to the downlink array response vector of RIS (1420).

[0168] Downlink array response vector of base station (1410) can be expressed as in [Mathematical Formula 4] below.

[0169]

[0170] In [Equation 4], stands for angle of departure (AoD), means the effective starting angle, refers to the speed of light in a vacuum.

[0171] Downlink array response vector of RIS (1420) can be expressed as in [Mathematical Formula 5] below.

[0172]

[0173] In [Equation 5], means the vertical downlink array response vector of RIS (1420), refers to the horizontal downlink array response vector of RIS (1420).

[0174] Downlink array response vector in the vertical direction of RIS (1420) and horizontal downlink array response vector of RIS (1420) can be expressed as in [Mathematical Formula 6] below.

[0175]

[0176] In [Equation 6], refers to the effective angle of arrival (AoA) in the vertical direction of RIS (1420), refers to the effective horizontal arrival angle of RIS (1420), means the azimuth arrival angle, refers to the elevation angle of arrival.

[0177] Unlike TDD systems, FDD systems can primarily use different frequency bands for uplink and downlink. However, spatial reciprocity can be achieved when the communication frequency of the FDD system is used within a specific frequency range. Therefore, the number of AoDs of the downlink channel, AoA of the downlink channel, and multipaths of the downlink channel can be the same as those of the uplink channel. In this case, the uplink channel of the base station (1410) and the RIS (1420) can be expressed as in [Mathematical Formula 7] below.

[0178]

[0179] In [Equation 7] is the uplink It means the channel coefficient of the th path, means the uplink array response vector of the base station (1410), refers to the uplink array response vector of RIS (1420).

[0180] Uplink array response vector of base station (1410) can be expressed as in [Mathematical Formula 8] below.

[0181]

[0182] In [Equation 8], means the angle of arrival, means the effective angle of arrival, refers to the speed of light in a vacuum.

[0183] Uplink array response vector of RIS (1420) can be expressed as in [Mathematical Formula 9] below.

[0184]

[0185] In [Equation 9], means the vertical uplink array response vector of RIS (1420), refers to the horizontal uplink array response vector of RIS (1420).

[0186] Uplink array response vector in the vertical direction of RIS (1420) and horizontal uplink array response vector of RIS (1420) can be expressed as in [Mathematical Formula 10] below.

[0187]

[0188] In [Equation 10], refers to the effective departure angle in the vertical direction of RIS (1420), refers to the effective horizontal departure angle of RIS (1420), means the azimuth departure angle, means the elevation departure angle.

[0189] That is, using [Mathematical Formula 3] and [Mathematical Formula 7], the downlink channel between the base station (1410) and the RIS (1420) and uplink channel of base station (1410) and RIS (1420) can be defined. In the same form, the downlink channel of the terminal (1430) and RIS (1420) and uplink channel of terminal (1430) and RIS (1420) can be defined.

[0190] Valid downlink channel and valid uplink channels It can be expressed as [Mathematical Formula 11].

[0191]

[0192] Therefore, the achievable transmission rate can be expressed as in [Mathematical Formula 12] below.

[0193]

[0194] In [Equation 12], is the downlink achievable transmission rate, is the uplink achievable transmission rate.

[0195] In an FDD system, since uplink and downlink signals are transmitted simultaneously within different frequency bands, an optimization problem needs to be designed to simultaneously maximize the uplink data rate and the downlink data rate.

[0196] Therefore, as an example of the present disclosure, problem (P1) can be designed as in [Mathematical Formula 13] so that the weighted sum transmission rate of the uplink transmission rate and the downlink transmission rate is maximized.

[0197]

[0198] In [Equation 13] refers to the weighting parameter between downlink and uplink.

[0199] Objective function in (P1) is the reflection coefficient matrix in RIS Non-concave function for and is the weighted sum of . Due to this, the unit modulus constraint can be a non-convex constraint. Precoding matrix and Is Since it is determined based on, a lot of effort is required to solve the optimization problem (P1). In one embodiment of the present disclosure, an alternating optimization algorithm can be used to solve this problem. First, By fixing , (P1) can be decomposed into downlink and uplink subproblems. The optimal precoder can be obtained by eigenmode transmission. and About, An equivalent problem for (P1) can be designed.

[0200] Specifically When is fixed, (P1) can be divided into downlink and uplink subproblems. First, the subproblem of (P1) for the downlink can be expressed as [Mathematical Formula 14] below.

[0201]

[0202] In the above [Equation 14], the optimal can be determined through power allocation using singular value decomposition (SVD) of the downlink effective channel and water-filling technique. The truncated SVD of the downlink effective channel , can be expressed as , and the optimal can be expressed as in [Mathematical Formula 15] below.

[0203]

[0204] In [Equation 15], refers to the downlink power allocation matrix obtained through the water filling technique, Is It means the optimal power allocated to the th data stream.

[0205] At this time, , And, silver can be satisfied. The uplink subproblem can also be defined in the same way, and the optimal can be expressed as in [Mathematical Formula 16] below.

[0206]

[0207] In [Equation 16], Is means the right singular matrix of , refers to the uplink power allocation matrix obtained through the water filling technique.

[0208] The optimal determined from [Equation 15] and [Equation 16] and By fixing, Optimization can proceed. Fixed and For , the equivalent problem of (P1) for the phase transition of RIS can be expressed as [Mathematical Formula 17] below.

[0209]

[0210] Non-convex constraint Due to this, finding an optimal solution requires a lot of effort. Therefore, a manifold optimization-based algorithm or a two-way alternating optimization algorithm can be proposed to optimize the phase transition of RIS to handle the unit modulus constraint, which is a non-convex constraint. Below, we first describe the manifold optimization-based algorithm.

[0211] Figure 15 is a diagram illustrating a procedure for a base station to move a point in a manifold optimization-based algorithm according to one embodiment of the present disclosure. The objective function of [Mathematical Formula 17] is continuous and differentiable. is a complex circle manifold can be formed. The objective function of [Mathematical Formula 17] The Riemannian conjugate gradient (RCG) algorithm can be used to determine the stationary point of a function. The Riemannian conjugate gradient algorithm can efficiently solve optimization problems with non-convex constraints, such as unit modulus constraints.

[0212] In step S1501, the base station determines the Riemann gradient. The Riemann gradient is a point It can be defined in the direction in which the objective function increases the most, restricted to the tangent space in [Mathematical Formula 17]. Therefore, the objective function The Riemann slope for can be expressed as [Mathematical Formula 18] below.

[0213]

[0214] In [Equation 18], silver It refers to the Euclidean gradient.

[0215] The base station is To find it, first can be decided. of The partial derivative for can be expressed as [Mathematical Formula 19] below.

[0216]

[0217] In complex calculus, and can be treated as an independent variable. Therefore, , and only the calculation of the first part in [Equation 19] may be required. Therefore, first, of The Euclidean slope for can be expressed as [Mathematical Formula 20] below.

[0218]

[0219] of The second column If expressed as, of The partial derivative for can be expressed as [Mathematical Formula 21] below.

[0220]

[0221] Based on [Equation 20] and [Equation 21], [Equation 19] can be determined. Therefore, the base station can be determined by [Mathematical Formula 22].

[0222]

[0223] The base station is of The partial derivative for is of The second column By defining it as, In the same way as how to determine can be decided.

[0224] In step S1503, the base station determines a transport operator that can move the search direction vector from the previous tangent space to another tangent space. The transport operator can map the gradient vector from one tangent space to another. Complex circular manifold The vector movement in can be expressed as in [Mathematical Formula 23] below.

[0225]

[0226] The search direction can be updated based on the Riemann gradient determined in [Equation 18], and the conjugate gradient method can be used as the update method. Search direction can be expressed as in [Mathematical Formula 24] below.

[0227]

[0228] In [Equation 24] can be chosen as the Polak-Riebiere parameter.

[0229] At step S1505, the base station performs vector retraction. Point Navigation direction in can be defined as the step size of the point in the direction of the tangent vector. If a point moves by that much, the moved point may not exist on the manifold. Therefore, the following contraction operator corresponds to the manifold in the tangent space. It can be expressed as [Mathematical Formula 25].

[0230]

[0231] By using the contraction operator, the point moved It can be expressed as [Mathematical Formula 26].

[0232]

[0233] [Table 4] shows the RCG-based algorithm for solving problem (P2).

[0234] Algorithm 1RCG-based Algorithm for Problem (P2)1:Initialization:Set t = 02:repeat3: Choose the Armijo backtracking line search step size 4: Find the next point using the retraction in [equation 26]5: Compute the Euclidean gradient according to [equation 19]6: Compute the Riemannian gradient according to [equation 18]7: Compute the transport according to [equation 23]8: Calculate the conjugate direction according to [equation 24]9: t ← t +110:until 11:Output:

[0235] Using the algorithm in [Table 4], it is guaranteed that the objective function converges to a critical point. Based on Algorithm 1 in [Table 4], the algorithm for solving the optimization problem of problem (P1) can be expressed as in [Table 5] below.

[0236] Algorithm 2Proposed Manifold Optimization-based Algorithm for Problem (P1)1:Input: 2:Initialization:Set t = 0, and randomly generate and obtain the optimal and for the channel realization3:repeat4:Compute based onAlgorithm 1with fixed and 5: Compute and according to [equation 15] and [equation 16] with fixed 6: t ← t +17:until 8:Output:

[0237] The initial value of the RIS reflection coefficient can be randomly generated, and the base station can determine the transmission precoder of the base station and terminal based on the initial value of the RIS reflection coefficient. The reflection coefficient to be updated t+1 can be determined by Algorithm 1, and the transmission precoder can be updated based on the updated reflection coefficient. The algorithm has an objective function of a threshold value If it does not increase beyond this, it may be terminated.

[0238] According to one embodiment of the present disclosure, the phase transition of RIS can be optimized using a bidirectional alternating optimization algorithm. First, all other variables are fixed, th reflection coefficient By designing subproblems of problem (P2), it can be derived as a problem of obtaining a sub-optimal closed-form solution. By repeatedly performing the subproblems of problem (P2), a local optimal solution of problem (P2) can be obtained.

[0239] For this, a new matrix , This can be defined. , are each and of It represents the th row. The objective function of [Mathematical Formula 17] Is In this fixed state can be expressed in terms of . That is, It can be expressed as, and can be expressed as in [Mathematical Formula 27] below.

[0240]

[0241] In [Equation 27] , , and can be expressed as in [Mathematical Formula 28] below.

[0242]

[0243] this and Because it only depends on, Equivalent problem of problem (P2) (P2- ) can be designed as shown in [Mathematical Formula 29] below.

[0244]

[0245]

[0246] and This objective function Since the characteristics of the two matrices play an important role, the optimization problem can be solved by distinguishing the characteristics of the two matrices. and Since the maximum rank it can have is 1, if some of the two matrices have rank 0, then some of the objective functions can be independent of each other. For example, If the rank is 0 (eg ), silver , and the optimal phase transition is The optimization problem can be solved by considering only the rank 1 case. In the case of rank 1, two sub-cases can be considered: the diagonalizable case and the non-diagonalizable case. or The condition for diagonalization is or These are necessary and sufficient conditions.

[0247]

[0248] First, and All cases can be considered diagonalizable. In this case, and By using eigenvalue decomposition (EVD), it can be decomposed as shown in [Mathematical Formula 30] below.

[0249]

[0250] In [Equation 30], , , and is the only non-zero eigenvalue.

[0251] and cast and The first row of , and and Each of them and If defined as the first column of , and can be expressed as in [Mathematical Formula 31] below.

[0252]

[0253] In [Equation 31], silver means the first element of, silver corresponds to the first element of , silver means the first element of, silver means the first element of .

[0254] Problem (P2- ), Von Neumann's trace inequality can be used. Any singular value and Having complex matrix and About, This is established. Therefore, The upper bound of can be expressed as in [Mathematical Formula 32] below.

[0255]

[0256] In [Mathematical Formula 32], the inequality (a) in front is established by von Neumann's trace inequality, and the equality (b) in the back is This can be established because is a rank 1 matrix. silver can be equal to the minimum singular value of , and has a value very close to 1. Therefore, In this case, [Equation 32] is Based on can be simplified to

[0257] By [equation 32], and The upper bounds of each are approximately and It can be. and The singular value of can be greatly affected by the RIS channel. RIS is used to support signals to terminals in shadow areas to expand the signal coverage, and the signal reflected on RIS travels a long distance, so when a weak signal is received by the terminal, and can be assumed to be sufficiently small. Also, , Because of this and can have a small value. Therefore, in [Equation 31] Around Applying the first-order Taylor approximation of the problem The problem is as follows [Mathematical Formula 33] can be expressed as

[0258]

[0259] problem objective function can be expressed as a weighted sum of two cosine functions as in [Mathematical Formula 34] below.

[0260]

[0261] In [Mathematical Formula 34], A represents the amplitude of the equivalent cosine function, refers to the phase of the equivalent cosine function.

[0262] Trigonometric identities If we apply [Equation 34] to [Equation 35] below, and can be expressed.

[0263]

[0264] According to [Equation 35], can be expressed as in [Mathematical Formula 36] below.

[0265]

[0266] By [equation 34] silver can be expressed as, objective function The maximum value of is the one that satisfies [Mathematical Formula 37] below. can be at its maximum.

[0267]

[0268] Secondly, or This non-diagonalizable case can be considered. or In this non-diagonalizable case, or go can be independent of each other. Therefore, The optimal phase shift of the RIS element can be optimized by setting only one of the uplink or downlink as a variable. That is, or It can be.

[0269] Thirdly, the case where both matrices are non-diagonalizable can be considered. In this case, any phase transition can be the optimal value, i.e., without loss of generality. can be expressed as

[0270] In summary, the problem (P2) using the two-way alternating optimization algorithm The reflection coefficient solution of the element of the th RIS can be expressed as [Mathematical Formula 38] below.

[0271]

[0272] The overall two-way alternating optimization algorithm can be represented as shown in [Table 6] below.

[0273] Algorithm 3Proposed Two-way Alternating Optimization based Algorithm for Problem (P1)1:Input: 2:Initialization:Set t = 0, and randomly generate and obtain the optimal and for the channel realization3:repeat4: for do5: Compute , , and according to [equation 28]6: Obtain according to [equation 38]7: end for8: Compute and according to [equation 15] and [equation 16] with fixed 9: t ← t +110:until 11:Output:

[0274] By utilizing the above-described manifold optimization-based algorithm (Algorithm 2) and the bidirectional alternating optimization algorithm (Algorithm 3), the base station can reduce the resources required to optimize the reflection pattern of the RIS element. In the case of the manifold optimization-based algorithm, in the RCG-based algorithm (Algorithm 1), the Euclidean gradient The operation that determines can have the greatest complexity. In this case, and The complexity required for the calculation of each is and It can be expressed as follows. The complexity required in Algorithm 2 can be expressed as [Mathematical Formula 39] below.

[0275]

[0276] In [Equation 39], means the number of outer iterations, refers to the number of inner iterations of Algorithm 1.

[0277] For the two-way alternating optimization algorithm, and Given, and The complexity required to calculate each is and can be expressed as . At this time, class The complexity required to calculate each is , It can be expressed as , and the complexity required for Algorithm 3 can be expressed as [Mathematical Formula 40] below.

[0278]

[0279] In [Equation 40], means the number of external repetitions.

[0280] , Assuming that, the complexity of Algorithm 2 and Algorithm 3 are respectively , can be simply expressed as . Comparing the complexity of the two algorithms, in the case of Algorithm 2, the RCG algorithm requires Because of this additional existence, the complexity of Algorithm 2 may be higher than Algorithm 3.

[0281] Fig. 16 is a flowchart illustrating an algorithm for optimizing an RIS reflection pattern according to an embodiment of the present disclosure. In step S1601, the base station optimizes the RIS reflection pattern based on the previously measured channel information. In step S1603, the base station can randomly generate a RIS phase transition as an initial value of the algorithm, and determine a downlink precoder based on the generated RIS phase transition. and uplink precoder Determine , and set t=0.

[0282] In step S1605, the base station updates the phase transition. The method for updating the phase transition may use the aforementioned manifold optimization-based algorithm or the bidirectional alternating optimization algorithm. In step S1607, the base station may update the downlink precoder and the uplink precoder using [Mathematical Formula 16] based on the updated phase transition. In step S1609, if the objective function change exceeds a threshold value, the base station returns to step S1605 and updates the phase transition again. If the change does not exceed the threshold value, the base station may update the phase transition again. and The algorithm can be terminated by outputting . By using this method, the phase transition for all elements of the RIS can be efficiently optimized.

[0283] FIG. 17 is a diagram illustrating a weighted sum transmission rate according to the number of external repetitions according to one embodiment of the present disclosure. In FIG. 17, the values ​​of each parameter for calculating the weighted sum transmission rate are assumed as shown in [Table 7] below.

[0284] Number of antennas at the base station: N = 16 Number of antennas at the terminal: K = 8 Number of multipath channels: Number of data streams: Uplink carrier frequency: Downlink carrier frequency: Base station antenna spacing, terminal antenna spacing, and RIS element spacing: Uplink and downlink noise distribution: Threshold for algorithm convergence: Transmit power: Weighting parameters: Total number of RIS components: Base station location: (0 m, 0 m)RIS location: (750 m, 5 m)Terminal location: (800 m, 0 m)

[0285] The path-loss model based on distance and frequency is assumed as in [Mathematical Formula 41] below, which is the model used in 3GPP.

[0286]

[0287] In [Equation 41], means link distance, means carrier frequency, means the reference distance, means the reference frequency.

[0288] Under the conditions described above, referring to [Figure 17], it can be confirmed that the objective function converges within approximately 20 outer iterations using Algorithm 2 and Algorithm 3 proposed in this disclosure. The manifold optimization-based algorithm (Algorithm 2) can have a higher weighted sum transmission rate than the bidirectional alternating optimization-based algorithm (Algorithm 3) because the phase transitions in all elements of the RIS are simultaneously optimized.

[0289] Fig. 18 is a diagram showing the weighted sum transmission rate according to the number of elements (L) of RIS according to one embodiment of the present disclosure. For performance comparison with other algorithms, an alternate optimization algorithm that considers only the downlink (e.g. ), a shift optimization algorithm that considers only the uplink (e.g. ), and the performance of the random phase shifts technique that randomly generates the phase shift of RIS were plotted and compared. Assumptions about the remaining parameters except for the number of RIS elements are as shown in [Table 7]. Since the approximation used in Algorithm 3 is relatively well established when the number of RIS elements is small, the performance difference between Algorithm 3 and Algorithm 2 may be small. In addition, it can be confirmed that the weighted sum transmission rate of Algorithm 2 and Algorithm 3 proposed in this disclosure is higher than that of the alternating optimization algorithm that considers only the downlink and the alternating optimization algorithm that considers only the uplink. Therefore, by considering the uplink and downlink simultaneously, better communication performance can be achieved than the existing method.

[0290] FIG. 19 is a diagram showing a performance comparison of the weighted sum transmission rate according to the downlink transmission power according to one embodiment of the present disclosure. Assumptions for the remaining parameters excluding the transmission power are as in [Table 7]. Referring to FIG. 19, it can be seen that the algorithm proposed in the present disclosure implements a high weighted sum transmission rate regardless of the downlink transmission power because it performs optimization that simultaneously considers the uplink and downlink. When the downlink transmission power is small, the performance of the alternating algorithm that considers only the uplink can be similar to the performance of Algorithm 2 and Algorithm 3 proposed in the present disclosure because the uplink power is relatively large. In the same principle, it can be confirmed that the performance of the alternating algorithm that considers only the downlink increases as the downlink transmission power gradually increases.

[0291] Figure 20 is a diagram showing data transmission rates according to weighting parameters according to one embodiment of the present disclosure. Assumptions for the remaining parameters, excluding the weighting parameters, are as shown in [Table 7]. In this case, When nearby The value can be maximum. The base station is a weighting parameter By controlling the priority of uplink and downlink communication, the base station can adjust the transmission rate according to the uplink transmission traffic and downlink transmission traffic, thereby performing efficient communication.

[0292] Figure 21 is a diagram illustrating a procedure for a base station to transmit and receive data using RIS based on uplink and downlink channel information according to one embodiment of the present disclosure. The base station can optimize the precoder and reflection pattern by considering both uplink and downlink.

[0293] In step S2101, the base station establishes an RRC connection with the terminal. There may be limitations on the reflection patterns that the RIS can change. At this time, a codebook for the phase change patterns of the RIS elements can be configured, and information about the codebook can be transmitted to the terminal via the RRC connection. Furthermore, the base station and terminal may include multiple antennas, and the terminal may transmit the precoder codebook types it can use via a capability information message.

[0294] In step S2103, the base station estimates uplink channel state information based on the reference signal received from the terminal. The sounding reference signal (SRS) transmitted by the terminal may be used.

[0295] In step S2105, the base station transmits a reference signal for measuring downlink channel information to the terminal. The reference signal transmitted by the base station may use at least one of a channel state information reference signal (CSI-RS) and a demodulation reference signal (DMSR), and the reference signal may use a Zadoff chu sequence. The base station receives downlink channel state information from the terminal. The terminal may measure the channel state based on the reference signal and transmit the channel state information to the base station. The terminal may transmit the estimated downlink channel state information using a precoding matrix indicator (PMI).

[0296] In step S2107, the base station determines the reflection patterns of the uplink precoder, downlink precoder, and RIS. As described above, algorithms used to optimize the precoder and reflection patterns may include manifold optimization-based algorithms and bidirectional alternating optimization algorithms. There may be limitations to the values ​​that can be set for the phase shifts of the precoder vectors and RIS elements. For example, depending on the implementation of the RIS elements, only certain phase shift values ​​may be available. Furthermore, to reduce communication traffic, the reflection patterns of the precoder and RIS may be defined through a codebook. In this case, even if the phase shift values ​​of the precoder and RIS elements are optimized by the above-described algorithm, they may not match the codebook. For example, among the combinations of precoder and reflection pattern values ​​that can be selected, the index values ​​closest to the optimized weighted sum transmission rate may be selected. Alternatively, the index values ​​may simply be determined based on the most similar values ​​in the index. The method for determining the index values ​​based on the optimized values ​​is not limited to any particular method.

[0297] In step S2109, the base station transmits an optimized RIS reflection pattern to the RIS and an optimized precoder to the terminal. As described above, the optimized reflection pattern and optimized precoder can be transmitted in the form of a codebook index. The base station can only transmit the uplink precoder that the terminal will use among the optimized precoders.

[0298] Based on optimized parameters, the base station can transmit and receive data with the terminal. Furthermore, depending on traffic conditions, the base station can efficiently manage uplink and downlink resources by using optimized precoders and RIS reflection patterns. For example, if downlink traffic increases and the downlink transmission rate must be increased, the base station can adjust the weighting variables included in the objective function of the algorithm described above. By increasing the weight variable, the downlink transmission rate can be set to increase further. Similarly, when the uplink traffic increases, the base station sets the weight variable can reduce.

[0299] Figure 22 is a diagram illustrating a procedure for a terminal to transmit and receive data using RIS based on uplink and downlink channel information according to one embodiment of the present disclosure. The terminal can perform efficient communication by receiving an uplink precoder that considers both uplink and downlink.

[0300] In step S2201, the terminal establishes an RRC connection with the base station. The terminal can communicate using the RRC connection establishment procedure with the base station. At this time, the terminal can send a capability information message (e.g., UECapabilityInformation) to the base station. Through this capability information message, the terminal can transmit information about the codebook types supported by the terminal to the base station.

[0301] In step S2203, the terminal transmits a reference signal to the base station to estimate uplink channel information. The reference signal transmitted by the terminal may be a sounding reference signal (SRS).

[0302] In step S2205, the terminal receives a reference signal for measuring downlink channel information from the base station and transmits downlink channel state information to the base station. The reference signal may be at least one of a channel state information reference signal (CSI-RS) and a demodulation reference signal (DMSR). A Zadoff chu sequence may be used as the reference signal. The terminal may transmit channel information to the base station through a CIS-RS report message and may transmit the estimated downlink channel state information in the form of a PMI (precoding matrix indicator).

[0303] In step S2207, the terminal receives an uplink precoder from the base station. The uplink precoder can be determined using a manifold optimization-based algorithm and a bidirectional alternating optimization algorithm. At this time, the available precoder codebook transmitted by the terminal may be considered, thereby selecting the precoder index most similar to the optimized precoder.

[0304] In FIGS. 21 and 22, the order in which the base station and terminal transmit reference signals may be changed. Furthermore, uplink channel and downlink channel information estimation may be performed in different ways and is not limited to a specific method.

[0305] FIG. 23 is a diagram illustrating signaling for a base station (2310), an RIS (2320), and a terminal (2330) to simultaneously optimize uplink and downlink according to one embodiment of the present disclosure.

[0306] The base station (2310) can determine the capabilities of the terminal (2330) by establishing an RRC connection with the terminal (2330) and can determine the precoder information that can be utilized. If the base station (2310) transmits a first reference signal and the terminal (2330) transmits a channel state information report based on the received reference signal, the base station (2310) can estimate the downlink channel. For uplink channel estimation, the terminal (2330) can transmit a second reference signal to the base station (2310). At this time, the second reference signal can be transmitted periodically or aperiodically, and the base station (2310) can transmit a reference signal request message to the terminal (2330). The base station (2310) can estimate the uplink channel using the second reference signal. The base station can optimize the reflection pattern of the precoder and the RIS (2320) based on the estimated downlink and uplink channels. As described above, the algorithm used for optimization may include a manifold optimization-based algorithm and a bidirectional alternating optimization algorithm. The base station (2310) may transmit an optimized uplink precoder to the terminal (2330), and the uplink precoder may be transmitted through an index value of a codebook. In addition, the base station (2310) may transmit the optimized reflection pattern of the RIS (2320) to the RIS (2320), and at this time, the transmission may be through an index value of a reflection pattern codebook. In a communication environment in which the precoder and reflection pattern are optimized, the base station (2310) and the terminal (2330) may transmit and receive data.

[0307] FIG. 24 is a diagram illustrating a timing diagram for channel estimation and data communication according to one embodiment of the present disclosure.

[0308] refers to the coherence time, and during the coherence time, it can be assumed that neither the channel between the base station and the RIS nor the channel between the terminal and the RIS changes. This allows the base station to prevent indiscriminate optimization. Therefore, During this time, the base station and terminal can estimate the channel by transmitting and receiving reference signals. The terminal transmits the estimated downlink channel information to the base station. The base station can optimize the precoder and RIS reflection channel based on the estimated channel information. During this time, the base station and terminal can transmit and receive data based on the optimized precoder and RIS reflection channel.

[0309] The correlation time settings can vary depending on the communication designer. Base stations and terminals can periodically transmit and receive reference signals to optimize the communication environment. Furthermore, the base station can initiate the optimization phase by requesting reference signals from terminals when communication quality falls below a threshold. Optimization can also be performed based on the discontinuous reception (DRX) cycle. For example, the base station can perform data transmission and reception and channel measurements during the on-duration period, and perform optimization calculations during the DRX sleep period when there is no communication.

[0310] 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).

[0311] 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.

[0312] 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.

[0313] 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.

[0314] Additionally, embodiments of the present disclosure can be applied to various applications such as autonomous vehicles and drones.

Claims

1. In a method of operating a base station in a wireless communication system, A step in which the base station performs an RRC (radio resource control) connection establishment procedure with a terminal through a reconfigurable intelligent surface (RIS); A step of estimating uplink channel state information based on a reference signal received from the terminal; A step of receiving downlink channel status information from the terminal; A step of determining an uplink precoder, a downlink precoder, and an RIS reflection pattern related to data transmission and reception based on the uplink channel state information and the downlink channel state information; and A method of operating a base station, comprising the step of transmitting the determined RIS reflection pattern to the RIS and transmitting the uplink precoder to the terminal.

2. In paragraph 1, The above uplink precoder, the above downlink precoder and the above RIS reflection pattern are determined so that the objective function has a maximum value, A method of operating a base station, wherein the above objective function is a function set based on a weighted sum transmission rate of an uplink transmission rate and a downlink transmission rate.

3. In paragraph 2, A method of operating a base station, wherein the weight of the above weighted sum transmission rate is changed based on at least one of an uplink traffic environment or a downlink traffic environment.

4. In paragraph 2, A method of operating a base station, wherein the uplink precoder and the downlink precoder are determined based on singular value decomposition (SVD) and water-filling techniques.

5. In paragraph 2, The above uplink precoder and the above downlink precoder and the above RIS reflection pattern are determined based on at least one of a manifold optimization-based algorithm or a bidirectional alternating optimization-based algorithm, A method of operating a base station, wherein at least one of the above-mentioned manifold optimization-based algorithm or the above-mentioned bidirectional alternating optimization-based algorithm is performed until the amount of change in the objective function becomes less than a threshold value.

6. In paragraph 5, A method of operating a base station, wherein the base station determines whether the phase of the RIS reflection pattern is shifted through the manifold optimization-based algorithm based on Riemann gradient, shift operator and vector contraction.

7. In paragraph 5, A method of operating a base station, wherein the base station determines whether to phase-shift the RIS reflection pattern through the bidirectional alternating optimization-based algorithm based on whether the matrix for calculating the objective function value can be diagonalized.

8. In paragraph 5, The above RIS reflection pattern is determined based on a codebook, and the base station's operating method.

9. In paragraph 1, The base station requests transmission of a reference signal related to estimation of uplink channel state information to the terminal, A method of operating a base station, wherein the base station estimates the uplink channel state information by receiving a reference signal related to estimating the uplink channel state information from the terminal.

10. In paragraph 9, A method of operating a base station, wherein the base station transmits a reference signal related to estimating downlink channel state information to the terminal, and the terminal generates the downlink channel state information through the reference signal related to estimating downlink channel state information and transmits the downlink channel state information to the base station.

11. In paragraph 10, The base station determines the uplink precoder, the downlink precoder, and the RIS reflection pattern based on the uplink channel state information and the downlink channel state information during a first time interval, transmits the determined RIS reflection pattern to the RIS, and transmits the uplink precoder to the terminal. An operating method of a base station, which performs data transmission and reception with the terminal based on the RIS reflection pattern and the uplink precoder determined during the second time interval.

12. In paragraph 11, A method of operating a base station, wherein the first time interval is a period in which the base station-RIS channel and the RIS-terminal channel do not change.

13. In a method of operating a terminal in a wireless communication system, A step in which the terminal performs an RRC (radio resource control) connection establishment procedure with a base station through a reconfigurable intelligent surface (RIS); A step of transmitting an uplink reference signal to the base station; A step of transmitting downlink channel state information based on a reference signal received from the base station; and A method of operating a terminal, comprising the step of receiving an uplink precoder determined based on uplink channel state information and downlink channel state information based on an uplink reference signal from the base station.

14. In paragraph 13, The above uplink precoder is determined so that the objective function has a maximum value, A terminal operation method, wherein the above objective function is a function set based on a weighted sum transmission rate of an uplink transmission rate and a downlink transmission rate.

15. In paragraph 14, The above uplink precoder is determined based on at least one of a manifold optimization-based algorithm or a bidirectional alternating optimization-based algorithm, A terminal operating method, wherein at least one of the above-mentioned manifold optimization-based algorithm or the above-mentioned bidirectional alternating optimization-based algorithm is performed until the amount of change in the objective function becomes less than a threshold value.

16. In paragraph 13, A method of operating a terminal, further comprising the step of receiving a request for transmitting a reference signal related to estimating uplink channel state information from the base station.

17. In a base station in a wireless communication system, Transmitter and receiver; and A processor connected to the above transmitter and receiver is included, The above processor, Performs the RRC connection establishment procedure with the terminal through RIS (reconfigurable intelligent surface), Estimating uplink channel state information based on the reference signal received from the terminal, Receive downlink channel status information from the terminal, Based on the above uplink channel state information and the above downlink channel state information, an uplink precoder, a downlink precoder, and an RIS reflection pattern related to data transmission and reception are determined, A base station that transmits the determined RIS reflection pattern to the RIS and transmits the uplink precoder to the terminal.

18. In a wireless communication system, at a terminal, Transmitter and receiver; and A processor connected to the above transmitter and receiver is included, The above processor, The above terminal performs an RRC (radio resource control) connection establishment procedure with the base station through RIS (reconfigurable intelligent surface), Transmit an uplink reference signal to the above base station, Transmit downlink channel status information based on the reference signal received from the base station, A terminal that receives an uplink precoder determined based on uplink channel state information and downlink channel state information based on an uplink reference signal from the base station.

19. In communication devices, At least one processor; At least one computer memory connected to said at least one processor and storing instructions that direct operations when executed by said at least one processor, The above actions are, Performs the RRC connection establishment procedure with the terminal through RIS (reconfigurable intelligent surface), Estimating uplink channel state information based on the reference signal received from the terminal, Receive downlink channel status information from the terminal, Based on the above uplink channel state information and the above downlink channel state information, an uplink precoder, a downlink precoder, and an RIS reflection pattern related to data transmission and reception are determined, A communication device that transmits the determined RIS reflection pattern to the RIS and transmits the uplink precoder to the terminal.

20. 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: Performs the RRC connection establishment procedure with the terminal through RIS (reconfigurable intelligent surface), Estimating uplink channel state information based on the reference signal received from the terminal, Receive downlink channel status information from the terminal, Based on the above uplink channel state information and the above downlink channel state information, an uplink precoder, a downlink precoder, and an RIS reflection pattern related to data transmission and reception are determined, A computer-readable medium for transmitting the determined RIS reflection pattern to the RIS and transmitting the uplink precoder to the terminal.

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