KR20240077712A - Method and apparatus for controlling beam in indoor environment - Google Patents

Abstract

A method of controlling a beam through RIS in a wireless communication system can be provided. Here, the RIS is turned on to perform a connection with the base station, the RIS sets the first beamforming between the RIS and the base station, the RIS senses channel information and environment information, and based on the sensed channel information and environment information Deriving an optimized value through artificial intelligence, determining a RIS pattern based on the optimized value obtained through AI and first beamforming, radiating RIS radio waves based on the RIS pattern, and connecting the base station and the terminal. It may include steps.

Description

Method and apparatus for controlling beam in indoor environment {METHOD AND APPARATUS FOR CONTROLLING BEAM IN INDOOR ENVIRONMENT}

This disclosure relates to a method and device for controlling beams in an indoor environment. Specifically, the present disclosure relates to a method and device for controlling a beam based on an intelligent reflector (reconfigurable intelligence surface, RIS) in an indoor environment.

Beamforming (or precoding) technology is a technology that focuses transmission signals in a specific direction using multiple antennas. In particular, it is easy to secure a wide bandwidth in ultra-high frequency channels such as sub-terahertz communication considered in the beyond 5G mobile communication system, and hundreds or thousands of antennas can be used due to the very short wavelength, forming a narrow beam width. High path attenuation can be overcome.

Additionally, when communication is performed through a beam with a narrow beam width, communication may not be smooth in an environment where obstacles exist due to high path attenuation, and communication may not be smooth due to narrowed coverage. In this environment, a method of performing communication using an intelligent reflector (RIS) may be necessary, and this is described below.

The technical problems to be achieved by this disclosure are not limited to the technical problems mentioned above, and other technical problems not mentioned can be clearly understood by those skilled in the art from the description below. You will be able to.

This specification relates to a method and device for controlling a beam based on RIS.

This specification relates to a method and device for controlling a beam through RIS, taking into account that the influence on the radio wave environment is maximized in the high frequency band.

This specification relates to a method and device for performing optimization using artificial intelligence (AI) and deriving a beam in consideration of the propagation environment of a high frequency band.

This specification relates to a method and device for controlling a beam through RIS considering indoor and outdoor environments.

In a method of controlling a beam through an intelligent reflector (reconfigurable intelligence surface, RIS) in a wireless communication system according to an aspect of the present disclosure,

The RIS is turned on to perform a connection with the base station, the RIS sets up the first beamforming between the RIS and the base station, the RIS senses channel information and environment information, and artificial intelligence is generated based on the sensed channel information and environment information. A step of deriving an optimization value through artificial intelligence (AI), a step of determining a RIS pattern based on the optimization value obtained through AI and first beamforming, and radiating RIS radio waves based on the RIS pattern, and a base station It may include the step of connecting the terminal to the terminal.

Additionally, according to an aspect of the present disclosure, channel information and environmental information may include at least one of built-in information, sensor information, location information, network information, and big data-based information.

Additionally, according to one aspect of the present disclosure, the optimal path between the base station and the RIS and the optimal path between the RIS and the terminal in the collaborative network may be determined based on artificial intelligence.

According to the present disclosure, a method for controlling a beam based on RIS in a wireless communication system can be provided.

According to the present disclosure, a method of controlling a beam through RIS can be provided, taking into account that the influence on the radio wave environment is maximized in the high frequency band.

According to the present disclosure, it is possible to provide a method of performing optimization using artificial intelligence (AI) and deriving a beam in consideration of the propagation environment of a high frequency band.

According to the present disclosure, it is possible to provide a method of controlling a beam through RIS considering the indoor environment and outdoor environment.

The effects that can be obtained from the present disclosure are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the description below. will be.

1 is a diagram showing a new communication system applicable to the present disclosure.
Figure 2a is a diagram showing a capacity increase technology applicable to the present disclosure.
FIG. 2B is a diagram illustrating an operation based on a sub-array within an antenna applicable to the present disclosure.
FIG. 2C is a diagram illustrating an operation based on a sub-array within an antenna applicable to the present disclosure.
FIG. 3A is a diagram illustrating spatial orthogonal multiple modes applicable to the present disclosure.
Figure 4 is a diagram showing a technology for expanding transmission coverage in a new communication system applicable to the present disclosure.
Figure 5 is a diagram showing a multi-user access technology applicable to the present disclosure.
FIG. 6A is a diagram showing a method of controlling a beam based on an intelligent reflector (RIS) applicable to the present disclosure.
FIG. 6B is a diagram showing a method of controlling a beam based on a sub-array in an intelligent reflector (RIS) applicable to the present disclosure.
Figure 7a is a diagram showing various types of RIS applicable to the present disclosure.
Figure 7b may be a scenario based on RIS applied to this disclosure.
FIG. 8A is a diagram showing a RIS operation mode applicable to the present disclosure.
Figure 8b is a diagram showing a RIS structure applicable to the present disclosure.
Figure 9 is a diagram showing environment and network information provided for path optimization applicable to the present disclosure.
FIG. 10 is a diagram illustrating a method of performing a RIS operation based on environment and network information applicable to the present disclosure.
FIG. 11 is a diagram illustrating a method of performing a RIS operation based on environment and network information applicable to the present disclosure.
FIG. 12 is a diagram illustrating a method of performing signal transmission or data communication relay through RIS based on sensor information applicable to the present disclosure.
Figure 13 is a diagram showing a method of setting an optimal route in a cooperative network based on big data-based information applicable to the present disclosure.
Figure 14 is a diagram showing a metamaterial (MTM) radome applicable to the present disclosure.
Figure 15a is a diagram showing an embodiment of an intelligent reflector composed of a plurality of radiators applicable to the present disclosure.
Figure 15b is a diagram showing a method of controlling a beam based on an intelligent reflector (RIS) applicable to the present disclosure.
FIG. 16 is a diagram showing a method of controlling a beam based on RIS in an indoor environment applicable to the present disclosure.
FIG. 17 is a diagram showing a method of controlling a beam based on RIS in an indoor environment applicable to the present disclosure.
FIG. 18 is a diagram showing a method of controlling a beam based on RIS in an indoor environment applicable to the present disclosure.
FIG. 19 is a diagram illustrating a method of performing beam control in an indoor environment applicable to the present disclosure.
Figure 20 is a diagram showing a method of performing beam control in an indoor environment applicable to the present disclosure.
FIG. 21 is a diagram illustrating a method of performing beam control in an indoor environment applicable to the present disclosure.
FIG. 22 is a diagram illustrating a method of performing beam control in an indoor environment applicable to the present disclosure.
Figure 23 is a diagram showing a method of performing beam control in an indoor environment applicable to the present disclosure.
Figure 24 is a diagram showing a method of performing beam control in an indoor environment applicable to the present disclosure.
Figure 25 is a diagram showing a method of forming a beam based on AI applicable to the present disclosure.
Figure 26 is a diagram showing a method of forming a beam based on AI applicable to the present disclosure.
Figure 27 is a diagram showing a method of forming a beam based on AI applicable to the present disclosure.
Figure 28 is a diagram showing a method of forming a beam based on AI applicable to the present disclosure.
Figure 29 is a diagram showing a RIS control method applicable to the present disclosure.
Figure 30 is a diagram showing a base station device and a terminal device to which the present disclosure can be applied.
31 is a diagram showing a network configuration to which the present disclosure can be applied.

Hereinafter, with reference to the attached drawings, embodiments of the present disclosure will be described in detail so that those skilled in the art can easily practice them. However, the present disclosure may be implemented in many different forms and is not limited to the embodiments described herein.

In describing embodiments of the present disclosure, if it is determined that detailed descriptions of known configurations or functions may obscure the gist of the present disclosure, detailed descriptions thereof will be omitted. In addition, in the drawings, parts that are not related to the description of the present disclosure are omitted, and similar parts are given similar reference numerals.

In the present disclosure, when a component is said to be “connected,” “coupled,” or “connected” to another component, this is not only a direct connection relationship, but also an indirect connection relationship where another component exists in between. It may also be included. In addition, when a component is said to “include” or “have” another component, this does not mean excluding the other component, but may further include another component, unless specifically stated to the contrary. .

In the present disclosure, terms such as first and second are used only for the purpose of distinguishing one component from other components, and do not limit the order or importance of the components unless specifically mentioned. Accordingly, within the scope of the present disclosure, a first component in one embodiment may be referred to as a second component in another embodiment, and similarly, the second component in one embodiment may be referred to as a first component in another embodiment. It may also be called.

In the present disclosure, distinct components are intended to clearly explain each feature, and do not necessarily mean that the components are separated. That is, a plurality of components may be integrated to form one hardware or software unit, or one component may be distributed to form a plurality of hardware or software units. Accordingly, even if not specifically mentioned, such integrated or distributed embodiments are also included in the scope of the present disclosure.

In the present disclosure, components described in various embodiments do not necessarily mean essential components, and some may be optional components. Accordingly, embodiments consisting of a subset of the elements described in one embodiment are also included in the scope of the present disclosure. Additionally, embodiments that include other components in addition to the components described in the various embodiments are also included in the scope of the present disclosure.

This disclosure describes a wireless communication network, and operations performed in the wireless communication network are performed in the process of controlling the network and transmitting or receiving signals in a system (e.g., a base station) in charge of the wireless communication network, or This can be done in the process of transmitting or receiving a signal from a terminal connected to a wireless network.

1 is a diagram showing a new communication system applicable to the present disclosure. Referring to Figure 1, a new communication system can be designed considering capacity increase technology, coverage expansion technology, and multiple access technology to provide smooth services. For example, a new communication system can be designed with a transmission speed of up to 1 Tbps, a user perceived speed of 1 Gbps, and a wireless transmission delay of 0.1 ms or less. In addition, there is a need to reduce transmission speed by 50 times, user perceived speed by 10 times, and wireless transmission delay by 1/10 compared to existing systems, and for this purpose, optical technology, new materials, and artificial intelligence technology can be utilized. In addition, capacity increase technology and coverage expansion technology considering LoS (line of sight) and NLoS environments can be applied, and technology that allows multiple users to access without conflict can be applied. However, the new communication system can be designed in various ways and is not limited to the above-described embodiments.

As a specific example, the base station 110 may increase transmission capacity based on high-frequency band broadband communication and other technologies. Additionally, transmission coverage can be increased based on RIS 120, repeaters, and other technologies. In particular, considering that radio wave attenuation is high in broadband communications in high frequency bands, there is a need to apply transmission coverage technology. In addition, it may be necessary to provide services for existing terminals, IoT (internet of things) terminals, vehicle terminals (130-1, 130-2, 130-3), and various other types of terminals, and these terminals (or users) ) may require multiple access technologies, and in new communication systems, service provision efficiency can be improved by considering the above-described technologies.

Figure 2a is a diagram showing a capacity increase technology applicable to the present disclosure. Referring to FIG. 2, there is a need to increase transmission capacity between the transmitting end 201 and the receiving end 202. New communication systems may require high-capacity data transmission and processing, and technology to increase transmission capacity may be needed for this. As an example, transmission capacity can be increased based on spatial multi-mode, and for this purpose, a spatial orthogonal multi-mode transmission technology such as OAM (orbital angular momentum) can be considered. In addition, spatial multi-mode transmission technology can be considered by utilizing the subarray operation configuration of a large array antenna, or transmission technology using RIS (HIS), etc. can be considered. As another example, transmission technology applying various spatial modulation techniques in the Fresnel zone can be considered, and transmission capacity can be increased based on the above. However, this is only an example and may not be limited to the above-described embodiment.

As a specific example, in an existing communication system, the channel rank may be maintained depending on the distance. On the other hand, when communication is performed considering the Fresnel zone in a new communication system, the channel rank may be determined based on distance and antenna size. More specifically, at the same distance, the larger the antenna size, the larger the channel rank can be. Additionally, for the same antenna size, the channel rank may decrease as the distance increases. Referring to FIG. 2b, in consideration of a new communication system, there is a need to operate based on a sub-array within the antenna. A plurality of sub-arrays may exist within the antenna, and each sub-array may correspond to respective users 211, 212, and 213.

Referring to FIG. 2C, a sub-array within an antenna having a large size can be configured based on the distance of the terminal. For example, a short-distance terminal 221 with low QoS can configure a sub-array based on adjacent unit elements within an antenna, and because it is a short-distance terminal, the channel rank can be maintained. Additionally, the short-distance terminal 222 with high QoS can configure a sub-array by increasing the unit elements within the antenna in consideration of the high QoS, and since it is short-distance, the channel rank can be maintained.

On the other hand, because the remote terminal 223 is far from the antenna, the channel rank may not be maintained. In consideration of the above, unit elements within the antenna may not be adjacent to each other but may have a preset interval, and the unit elements may form one sub-array. That is, the sub-array within the antenna can be determined considering the distance between the terminal and the antenna and the antenna size.

FIG. 3A is a diagram illustrating spatial orthogonal multiple modes applicable to the present disclosure. Referring to FIG. 3A, the HG (Hermite Gauss) mode or pattern can be set as a spatial orthogonal multi-mode based on the Fresnel region. Different streams can be transmitted independently based on HG mode or pattern. However, since the transmitted beam may become wider depending on the distance, there is a need to increase the antenna size according to the distance, and for this, a design that takes the distance and antenna size into consideration may be necessary.

The entire antenna can be used for the above-described HG mode, but since the transmitted power may vary depending on the distance, a sub-array configuration that takes this into account may be necessary. As an example, referring to FIG. 3B, the main receiving antennas of HG modes HG (0,1), (1,1), and (2,1) in FIG. 3A may be areas corresponding to the circles at the top or bottom, The middle area may be an area with a small signal size. Therefore, in the case of a remote user, communication can be performed based on the HG mode based on the area corresponding to the upper or lower circle. Referring to FIG. 3C, sub-arrays 311 can be configured at the top and bottom of the antenna for communication with long-distance users based on HG mode. Here, since the middle area has low power and may hardly be recognized from a distance, sub-arrays 321, 322, and 323 for each of the short-distance users may be set in the middle area, and communication can be performed respectively based on this. . Additionally, the above-described antenna configuration can be similarly applied to RIS and is not limited to a specific embodiment.

Figure 4 is a diagram showing a technology for expanding transmission coverage in a new communication system applicable to the present disclosure. In new communication systems, communication is performed over a high-frequency, wide-bandwidth, so radio wave attenuation may be significant. Therefore, transmission coverage expansion technology may be needed. As a specific example, referring to FIG. 4(a), transmission coverage can be expanded based on an embedded IoT device. The signal transmitted from the transmitter 411 may be transmitted to other embedded IoT devices or other terminals through embedded IoT devices, and transmission coverage may be expanded based on the above. Additionally, referring to FIG. 4(b), transmission coverage can be expanded based on RIS. As an example, RIS can transmit signals in an NLOS environment. Specifically, the signal transmitted from the transmitting end 421 may be transmitted to the receiving end through at least one RIS (422-1, 422-2), through which transmission coverage can be expanded. Additionally, referring to Figure 4(c), RIS/EM cloaking technology can be considered to overcome shadow areas or obstacles. That is, the transmitting end 431 may transmit a signal to the receiving end 432 through RIS/EM cloaking technology, but may not be limited to this.

Figure 5 is a diagram showing a multi-user access technology applicable to the present disclosure. Referring to FIG. 5, a new communication system may require multi-user access technology in consideration of various types of terminals (or users). As an example, referring to FIGS. 5(a) and 5(b), the transmitting terminals 510 and 520 allocate multiple channels through artificial intelligence and other technologies and apply free-duplex (Full-duplex) technology. This can provide multi-user access. Specifically, referring to FIG. 5(a), AI-based multi-channel allocation may be performed for a plurality of terminals based on CSI information. Here, AI-based multi-channel allocation can be performed through training with simulation data and through inference of a model that reflects the training results. As an example, training on an AI/ML model may be performed through multi-access communication simulation data. Additionally, referring to FIG. 5(b), channel state modeling may be performed based on communication. Specifically, channel state modeling builds a channel state model based on information about communication between the base station and the terminal, allows the channel state to be estimated through inference of the constructed model, and the information can be converted back into the channel state model. Feedback can be provided. Additionally, channel state generation can be performed based on AI, and communication using this can be performed.

Additionally, referring to FIG. 5(c), the transmitting terminals 531 and 532S can provide multi-user access by allocating multiple channels through spatial analysis and interference control through control of multiple RIS (HIS). Specifically, the transmitting terminals 531 and 532 can communicate directly with the terminal or transmit and receive with the terminal through RIS (HIS), and are not limited to a specific embodiment.

FIG. 6A is a diagram showing a method of controlling a beam based on an intelligent reflector (RIS) applicable to the present disclosure. Referring to FIG. 6, beams can be controlled and communication can be performed based on the RIS 620. Here, the RIS 620 may include each unit element of the RIS. At this time, the beam direction can be controlled by controlling each element in the RIS (620), and each element of the RIS (620) can be controlled by a controller. As an example, the RIS 620 receives a beam-based signal from the transmitter 610, and based on this, controls each element in the RIS 620 to form a beam in a desired direction to transmit a beam to at least one terminal (or user, Signals can be transmitted to 630-1, 630-2, 630-3, and 630-4). In other words, RIS can improve signal transmission efficiency in an NLOS environment by receiving signals from the base station (or transmitter) and transmitting them to other terminals. Here, as an example, each element of the RIS can be turned on/off as a passive element or have a set voltage value, and the beam direction can be controlled based on the above. As another example, the RIS may only reflect signals from the transmitter by controlling unit elements or may function as a repeater, and is not limited to a specific embodiment.

FIG. 6B is a diagram showing a method of controlling a beam based on a sub-array in an intelligent reflector (RIS) applicable to the present disclosure. The RIS 620 may include a plurality of unit elements, and a sub-array may be configured similar to the unit elements in the antenna described above. Here, the sub-array in the RIS 620 can be set to form a beam for a plurality of terminals 631-1, 631-2, 631-3, and 631-4. As an example, the sub-array within the RIS 620 may also be determined based on the RIS size and the distance to the terminal. For example, a sub-array for a terminal 631-4 located far from the RIS may be composed of a set of unit elements spaced apart from each other in consideration of the channel rank, as shown in FIG. 2C. However, it may not be limited to this.

Figure 7a is a diagram showing various types of RIS applicable to the present disclosure. Referring to FIG. 7A, the RIS 710 may include a plurality of unit elements, as described above. Here, the RIS 710 may be attached to a building or other device. As an example, RIS 721 coupled to a vehicle, RIS 722 coupled to a building ceiling, and RIS 723 coupled to building glass may be considered, but may not be limited thereto. That is, the RIS 710 may be attached to another device or building to relay or support communication. As another example, a plurality of RISs 724 and 725 may be installed in a building to transmit signals to terminals. Additionally, the RIS may be configured with a straight edge shape 726 or a circular surface 727, but is not limited to a specific embodiment.

Figure 7b may be a scenario based on RIS applied to this disclosure. As an example, in a new communication system, communication may be performed based on a cooperative network. Here, in the cooperative network, not only the transmitter 731 but also the RIS 732, repeater 733, vehicle 734, IoT terminal, and other devices that relay or transmit communication may be constructed. More specifically, since the new communication system performs high-frequency broadband communication and the cell size becomes smaller, a method of performing efficient communication through a cooperative network may be needed. As an example, a cooperative network may include a device that relays signals at a fixed location and a device that relays signals based on mobility. In a cooperative network, it may be necessary to determine and operate an optimal path by considering the movement of devices or signal transmission based on mobility, and a method for the above-described operation may be necessary.

FIG. 8A is a diagram showing a RIS operation mode applicable to the present disclosure. Referring to FIG. 8A, the RIS 810 may operate based on each mode to deliver an optimal path for signal transmission in a cooperative network. As an example, the RIS 810 may be configured as a metal scatterer in a state where power is not supplied. In other words, the RIS (810) acts as a simple metal scatterer and can be considered for performance improvement in a multi-pass environment.

As another example, the RIS 810 may be in a state where power is supplied. Here, the RIS (810) is either in an online mode that operates using AI (artificial intelligence) or big data, or an offline mode (off) in which only power is supplied and it acts as a reflective or transmissive relay repeater in a passive form. -line mode) can be determined.

When the RIS 810 operates in online mode, the operation mode of the RIS 810 may be determined. As an example, the operation mode may perform at least one of reflection, refraction, transmission, blocking, and multiplexing. As an example, the reflection mode may be a mode in which radio waves incident on the RIS 810 are transmitted in a reflected form. Additionally, the refraction mode may be a mode in which radio waves incident on the RIS 810 are transmitted in the target direction in the form of refraction. The transmission mode may be a mode in which radio waves incident on the RIS 810 are transmitted as is. The blocking mode may be a mode that blocks radio waves incident on the RIS 810 rather than passing them through. The multiplexing mode may be a mode in which radio waves incident on the RIS 810 are expanded and transmitted in the form of multiple beams. That is, the RIS 810 can reflect signals in a desired direction, refract them at a certain angle, transmit only certain signals and block other signals, or transmit signals in various forms based on multiplexing.

The RIS 810 can sense environmental and network information, perform route optimization based on this, and set an optimal route based on the above-described operation mode. The environment and network information may include at least one of built-in information in a building, sensor information, location information, network information, and big data-based information, and is not limited to a specific embodiment. That is, an optimized path for signal transmission can be derived based on the operation mode of the RIS 810, the surrounding environment, and network information.

Figure 8b is a diagram showing a RIS structure applicable to the present disclosure. Referring to FIG. 8B, the RIS 810 may be the metal scatterer described above, but may be configured to operate in various forms based on a power source and controller. As an example, the RIS (810) includes a network connection (or transceiver, 821), a power source (822), an RF controller (823), a baseband controller (824), a sensor (825), a CPU (826), and an AI processor (827). ) may include at least one of, and is not limited to a specific example. Here, the RIS (810) may be equipped with a function to amplify the signal based on Power Amp. Additionally, the RIS 810 may have a function to control a beam or shield a beam based on a unit element. Additionally, the RIS 810 may have a function for multiplexing beams based on the above-described sub-array, and is not limited to a specific embodiment.

Figure 9 is a diagram showing environment and network information provided for path optimization applicable to the present disclosure. Referring to FIG. 9, the environment and network information 960 includes at least one of built-in information 910, sensor information 920, location information 930, network information 940, and big data-based information 950. It can be included. Built-in information 910 may be information set when RIS is installed in a building or device. For example, built-in information is all information related to RIS installation, and may include building walls, glass, home appliances, indoor/outdoor installation information, and other information, and is not limited to a specific form. Additionally, the sensor information 920 may be information acquired by an image sensor, lidar sensor, radar sensor, and other sensors. The sensor information 920 is information obtained from sensors provided in RIS, IoT devices, and other devices, and may also acquire information about surrounding information or indoor and outdoor radio wave environment medium, and is not limited to a specific embodiment.

The location information 930 may be small-unit location information based on indoor positioning as well as GPS-based location information. The location information 930 may include all real-time location information obtained based on GPS and location estimation technology for RIS, IoT devices, and other devices. The network information 940 may be information that takes into account smaller cells or other network environments. The network information 940 may include real-time information about a cooperative network that can be configured in RIS, IoT devices, and other devices. Additionally, the network information 940 may include data traffic, network operator information, and device identification of each device. It may include information and other information.

Big data-based information 950 may be information provided based on big data composed of various information that can affect communication. Big data-based information 950 may be external information that can affect RIS, IoT devices, and other devices. As an example, the big data-based information 950 may include vehicle traffic volume, climate impact information, real-time disaster and accident information, administrative information that may affect communication, and other information. Additionally, the environment and network information 960 may further include other information and may not be limited to a specific form.

Figure 10 is a diagram showing a method of performing a RIS operation based on environment and network information applicable to the present disclosure. Referring to FIG. 10, when power is connected to the RIS, the RIS can perform a network connection confirmation operation (S1010). When the network is connected to the RIS, it can operate based on online mode (S1020), and related to this. This will be described later in Figure 11. On the other hand, if the network is not connected to the RIS, only power is supplied and it can be determined to be in an off-line mode, performing the role of a reflective or transmissive relay repeater in a passive form. (S1030) At this time, the RIS transmits signals or communicates. The communication status can be checked for relaying. (S1040) If communication is not being performed as a result of checking the communication status, the RIS can operate based on standby mode. (S1050) On the other hand, if communication is performed as a result of checking the communication status, the AMP can be turned on (S1060) and signal transmission or data communication relay can be performed (S1070).

FIG. 11 is a diagram illustrating a method of performing a RIS operation based on environment and network information applicable to the present disclosure. Referring to FIG. 11, when power is connected to the RIS, the RIS can perform a network connection confirmation operation (S1110). If the network is not connected to the RIS, only power is supplied and it acts as a reflective or transmissive relay repeater in a passive form. may be determined to be an offline mode, which may be the same as the above-mentioned FIG. 10 (S1120). On the other hand, when a network is connected to the RIS, it may operate based on the online mode (S1130). As an example, a RIS operating based on an online mode can turn on a sensor. (S1140) The central control device of the RIS includes the built-in information (or installation information), sensor information, location information, big data information, and network of FIG. 9. At least one of the information can be obtained. (S1150) After that, the central control device can perform optimization using externally or internally configured AI. (S1160) After that, the optimal path can be calculated. (S1170), and the RIS can relay data communication (S1180). At this time, as an example, the operation of devices on the optimal path can be controlled to calculate the optimal path. Additionally, for data communication relay, the RIS may operate in an operation mode based on at least one of reflection, refraction, transmission, blocking, and multiplexing, and data communication relay can be performed through the above.

FIG. 12 is a diagram illustrating a method of performing signal transmission or data communication relay through RIS based on sensor information applicable to the present disclosure. Referring to FIG. 12(a), the RIS 1210 may relay data communication to a plurality of terminals 1220-1 and 1220-2. Here, the RIS 1210 can recognize that there are no obstacles indoors based on sensor information and can perform transmission in a line of sight (LoS) environment. Additionally, referring to FIGS. 12(b) and 12(c), optimal path information can be derived by checking medium information and indoor structure information as sensor information. As an example, referring to FIG. 12(d), refractive index, transmittance, and absorption rate information may be considered as propagation constant information when identifying a medium, and the corresponding information may be obtained using big data, but is not limited to this. You can. As a specific example, in FIGS. 12(b) and 12(c), the RIS (1210) provides terminal 1 (1220-1) with information about the metal wall and information about medium 1 to determine the optimal path to the metal wall. It is possible to relay data communication by setting an optimal path through medium 1 to terminal 2 (1220-2), but this is only an example and is not limited to the above-described embodiment.

Figure 13 is a diagram showing a method of setting an optimal route in a cooperative network based on big data-based information applicable to the present disclosure. Big data-based information may be information that can affect route optimization. As an example, big data-based information may be climate and atmospheric information, but may not be limited thereto. As a specific example, in ① of FIG. 13, the case where the influence of climate or atmospheric information is small and the attenuation state is low based on big data can be considered. When the RIS 1310 sets the optimal path based on the cooperative network with the devices 1320 and 1330, the attenuation state is low, so the optimal path can be configured by selecting only a small number of devices or repeaters. On the other hand, in ② of Figure 13, the case of high attenuation can be considered due to the high influence of climate or atmospheric information based on big data. Based on this, cases where the influence of climate or atmospheric information is small and the attenuation state is low can be considered. When the RIS (1310) sets the optimal path with the devices (1320, 1330) based on the cooperative network, the attenuation state is high, so multiple devices or repeaters for data relay can be configured. That is, when data communication is relayed or signals are transmitted within a collaborative network or based on RIS, path optimization may vary depending on sensor information, big data-based information, and other information.

Figure 14 is a diagram showing a metamaterial (MTM) radome applicable to the present disclosure. Referring to FIG. 14(a), the RIS or transmit/receive antenna 1410 can transmit and receive signals. Here, in a new communication system, beam-based communication may be required and a beam control technique may be required. Here, the beam can be controlled based on the MTM radome (1420) spatial filter. Specifically, the MTM radome 1420 may be implemented using graphene or other materials, and control based on DC voltage may be possible, so it may be applicable even in terahertz. Figure 14(b) may be a specific embodiment in which an MTM radome exists on an array antenna. Referring to FIG. 14(b), the array antenna may be composed of a plurality of antennas based on unit elements. An MTM radome exists above the array antenna, and the MTM radome is a spatial filter that can control the signal generated from the array antenna based on FIG. 14(a), and the beam can be controlled based on this.

15A and 15B are diagrams showing a method of controlling a beam based on an intelligent reflector (RIS) applicable to the present disclosure. RIS may be composed of a meta surface structure. Specifically, referring to FIG. 15A, RIS formed as a metasurface structure may be composed of a set of RIS unit structures. Here, the MTM radome described above on the RIS basic structure is provided as a spatial filter to control the beam. Here, the MTM radome can control the beam through DC voltage control through graphene, as described above. As an example, referring to FIG. 15b, the beam direction can be controlled by applying a DC voltage based on the MTM radome grouping on the RIS unit structure. The MTM radome shaded in Figure 15b may be in an on state. Specifically, in the first RIS, the MTM radome group in the central portion of the RIS unit structure may be on based on MTM radome grouping, and a beam may be formed accordingly. On the other hand, the second RIS may have the MTM radome group on the right side of the RIS unit structure based on the MTM radome grouping, and the third RIS may have the MTM radome group on the left side within the RIS unit structure based on the MTM radome grouping. The group may be on. Here, the second RIS and the third RIS may each have corresponding beams set. That is, in the RIS structure composed of a set of each RIS unit structure, the desired beam direction and intensity can be set and controlled according to voltage changes based on MTM grouping. However, FIGS. 15A and 15B are only one example for implementing RIS and may not be limited to the above-described embodiment.

In the following, a method of performing communication based on RIS will be described when communication is performed based on sub-THz and THz bands of hundreds of GHz in ultra-high frequency bands. Here, unlike the frequency (e.g. frequencies below mmWave) band operation of existing communication systems (e.g. 5G), the impact on the radio wave environment can be maximized in the ultra-high frequency band. As a specific example, in the sub-THz and THz bands, there is a need to consider attenuation due to dust, etc., changes in attenuation due to the roughness of the metal surface, and characteristic instability due to temperature, etc., unlike existing frequencies. In addition, in a new communication system in the ultra-high frequency band, the difference in radio wave characteristics depending on the medium and the climatic environment is expected to increase, so a communication system that takes this into account may be needed.

Here, in the new communication system, the influence of various information such as transmission/reflection/refraction/scattering/diffraction of radio waves and transmission/reflection/refraction/scattering/diffraction of radio waves through numerous media and the climate environment may be highly influential, unlike the database required for existing radio wave environment channels. Therefore, new communication systems may require systems that utilize big data and AI, as described above. In the following, the RIS-based operation method is described based on the above.

16 to 18 are diagrams showing a method of controlling a beam based on RIS in an indoor environment applicable to the present disclosure.

Referring to FIG. 16, the RISs 1620 and 1640 control beams in an indoor environment to transmit signals received from the base station 1610 to at least one terminal 1630-1, 1630-2, 1630-3, and 1630-4. ) can be transmitted. Here, at least one RIS (1620, 1640) may be installed in an indoor space. The first RIS (1620) can transmit signals to at least one terminal (1630-1, 1630-2, 1630-3, 1630-4) in an indoor space. Here, the operation mode may be determined for the first RIS 1620 based on at least one of the sensor information, location information, network information, and big data information described above. More specifically, the presence of an indoor LoS environment can be sensed using sensor information for the first RIS (1620). Additionally, the first RIS (1620) can check the location information of the second RIS (1640) and the location information of individual terminals. Additionally, for the first RIS 1620, it can be confirmed whether individual transmission is performed through RIS without separate cooperative communication using network information. Additionally, individual users' movement patterns and terminal environment event information may be provided as big data-based information for the first RIS (1620). However, it is not limited to this. Here, the first RIS 1620 may determine the operation mode based on the above-described information. As a specific example, the second RIS 1640 may be a RIS installed on glass to transmit a signal to the base station 1610, and the information in FIG. 9 may also be considered for the second RIS 1640. Here, the second RIS (1640) is a RIS that is installed on glass and allows signals to pass through, and its operating mode may be set to a transmission amplification mode. That is, the signal transmitted from the transmitting end 1610 may pass through the second RIS (1620), be amplified, and then be transmitted to the first RIS (1640). Thereafter, the first RIS (1640) may operate in at least one of reflection, refraction, blocking, and multiplexing modes as an operation mode, and operates at least one terminal (1630-1, 1630-2, 1630-3) in an indoor environment. , 1630-4), the signal can be transmitted.

In indoor environments, adaptive beam control may be necessary depending on the attenuation environment of sub-THz and THz radio waves. Specifically, optimal beam control may be required based on at least one of the transmitting end (Tx), receiving end (Rx), and RIS. In addition, based on RIS, optimal beam control may be necessary considering the maximum radio wave arrival distance according to the width and height in the indoor space, which will be described later. In addition, as an example, at least one of information on the absorption rate of the indoor media in the indoor space, information on the attenuation due to the transmission of the medium, atmospheric attenuation information according to indoor humidity and air quality, and other information related to the medium in the indoor space is provided. The beam can be controlled taking into account For example, the beam may be controlled based on at least one of reflectance/refractive index information of the indoor composition medium, indoor wireless device location information, usage frequency information, indoor population density information, fluidity information, and medium information, and in this regard, This will be described later. Additionally, as an example, the beam may be controlled based on calibration information for changes in RIS device performance depending on indoor temperature in an indoor environment, which will be described later.

As an example, referring to FIG. 17, a channel environment setting operation can be performed in an indoor environment based on RIS (S1710). At this time, the channel environment can be set considering the radio wave attenuation variable in the indoor environment (S1720). Here, the information in FIG. 9 described above can be considered as indoor environment information as the radio wave attenuation variable. As a specific example, radio wave attenuation may be large in a high frequency band, so indoor environmental information can be considered as a radio wave attenuation variable, and is not limited to a specific embodiment.

Next, channel and path optimization can be performed (S1730). Here, channel and path optimization can be performed based on indoor medium information and RIS optimization. For example, beamforming for the RIS may be determined from an external base station, and channel and path optimization may be performed through optimization for the RIS in consideration of at least one terminal located in an indoor environment. Afterwards, optimization is performed considering LoS and NLoS (S1740), and data communication can be performed by setting up an indoor and outdoor wireless link (S1750). That is, by considering radio wave attenuation variables and channel and path optimization in an indoor environment. RIS can be optimized and data communication can be performed. Here, as an example, Figure 17 may be an operation in a single-user environment, and Figure 18 may be an operation in a multi-user environment.

Referring to FIG. 18, a channel environment setting operation can be performed in an indoor environment based on RIS. (S1810) At this time, the channel environment can be set considering the radio wave attenuation variable in the indoor environment. (S1820) Here, the radio wave attenuation variable can be set. The information in FIG. 9 described above can be considered as indoor environment information as the attenuation variable. As a specific example, radio wave attenuation may be large in a high frequency band, so indoor environmental information can be considered as a radio wave attenuation variable, and is not limited to a specific embodiment.

Next, channel and path optimization can be performed (S1830). Here, channel and path optimization can be performed based on indoor medium information and RIS optimization. Additionally, as an example, a multi-user environment can be considered in Figure 18. That is, a case where there are multiple terminals (or users) that communicate based on RIS in an indoor environment can be considered, and optimization can be performed based on the location and channel information of multiple users. For example, beamforming for the RIS may be determined from an external base station, and channel and path optimization may be performed through optimization for the RIS considering a plurality of terminals located in an indoor environment. Afterwards, optimization is performed considering LoS and NloS (S1840), and data communication can be performed by setting up an indoor and outdoor wireless link (S1850). That is, by considering radio wave attenuation variables and channel and path optimization in the indoor environment. RIS can be optimized and data communication can be performed.

Figure 19 is a diagram showing a method of performing beam control in an indoor environment applicable to the present disclosure.

Referring to FIG. 19, the transmitting end 1910 can transmit a signal to the RIS 1920, and the RIS 1920 can transmit the signal to the terminals 1930-1, 1930-2, and 1930-3. Here, as an example, environment and network information for the RIS (1920) may be determined. As an example, the environment and network information may include location information where the RIS (1920) is installed as built-in information. As a specific example, RIS (1920) may be installed on an indoor wall. Here, the location information may include indoor RIS (1920) location information and location estimation information of individual terminals, through which path map information for signal transmission can be generated. Additionally, the sensor information may confirm indoor structure and environmental medium information and include environmental information at the locations of the terminals 1930-1, 1930-2, and 1930-3. Additionally, as an example, the big data information may be movement pattern information and other information for each of the terminals 1930-1, 1930-2, and 1930-3. The RIS 1920 may include a control unit and may allocate power to each of the terminals 1930-1, 1930-2, and 1930-3 based on the above-described environment and network information. As a specific example, the RIS 1920 may allocate power distribution to terminals for which LoS is secured. Additionally, in a LoS environment, the radio wave reach distance can be estimated through location information, RIS transmission power, and signal noise ratio (SNR) information of the receiver. Here, when signal transmission is difficult, the RIS (1920) can transmit signals based on other nearby devices through a cooperative network. Additionally, the RIS 1920 may determine the operation mode based on the above-described information.

Additionally, as an example, a preset beam between the transmitter 1910 and the RIS 1920 may be set based on installation information as built-in information of the RIS 1920. Specifically, the RIS (1920) can estimate the radio wave reach distance by checking the installed space and height in the indoor space, and allocate power to each of the terminals (1930-1, 1930-2, and 1930-3) based on this. It can be distributed. Additionally, as an example, indices for beams used by the RIS 1920 may be set based on the above-described information. As a specific example, beam indexes may be set considering the direction in the indoor space based on the location where the RIS 1920 is installed, but this may not be limited to a specific embodiment.

20 to 22 are diagrams showing a method of performing beam control in an indoor environment applicable to the present disclosure. Referring to FIG. 20, the transmitting terminal 2010 transmits a signal to at least one RIS (2020-1, 2020-2, 2020-3) in consideration of indoor space to transmit a signal to at least one terminal (2030-1, 2030-3). 2, 2030-3) can transmit the signal. Here, path optimization can be performed based on environment and network information about RISs (2020-1, 2020-2, 2020-3). In other words, route optimization can be performed using built-in information, sensor information, location information, network information, and big data information as environment and network information for RIS (2020-1, 2020-2, 2020-3). As another example, the indoor space is separated for each floor, so RIS is installed on each floor to transmit signals to terminals on each floor.

As another example, referring to FIG. 21, when the LoS environment is guaranteed for each floor in an open interior, the RIS 2120 can be installed indoors and transmit signals to each floor. As another example, referring to FIG. 22, the RIS 2220 may be installed externally and receive a signal from the transmitter 2210. Here, the externally installed RIS (2220) may be connected to at least one internal transmission RIS (2230-1, 2230-2, 2230-3), and the internal transmission RIS (2230-1, 2230-2, 2230-3) ) can each receive a signal from an externally installed RIS (2220). Afterwards, the internal transmission RISs 2230-1, 2230-2, and 2230-3 can deliver signals to terminals for which LoS is guaranteed. Here, as an example, identification information may be provided for the externally installed RIS (2220) and at least one internal transmission RIS (2230-1, 2230-2, 2230-3), and the terminals may be assigned based on the identification information. A signal can be transmitted to.

FIG. 23 is a diagram illustrating a method of performing beam control in an indoor environment applicable to the present disclosure. Referring to FIG. 23(a), the transmitting terminal 2310-1 transmits a signal to the RIS 2320-1, and the RIS 2320-1 transmits a signal to the terminals 2330-1 and 2330-2. -1) Signals can be transmitted. For example, the RIS (2320-1) may be initially installed and fixed indoors, and the transmitter (2310-1) may also be the same. That is, the transmitter 2310-1 that transmits a signal to the RIS 2320-1 can be fixed, and the beam between the transmitter 2310-1 and the RIS 2320-1 can be fixed. Here, the terminals 2330-1 and 2330-2 within the indoor space can move, and the RIS 2320-1 receives a signal from the transmitter 2310-1 based on a fixed beam, and the terminals 2330-1 and 2330-2 within the indoor space can move. The beam can be configured to vary based on the mobility of the terminals 2330-1 and 2330-2. Here, terminals 2330-1 and 2330-2 within the indoor space may be registered or connected to the RIS 2320-1. For example, when terminals 2330-1 and 2330-2 in an indoor space enter the indoor space, they can connect to the RIS 2320-1. Afterwards, when a signal to be received is generated from the transmitter 2310-1, the signal can be received through the RIS 2320-1.

As another example, referring to FIG. 23(b), the transmitting terminal 2310-2 transmits a signal to the RIS 2320-2, and the RIS 2320-2 transmits a signal to the terminal 2330-3. -2) Signals can be transmitted. For example, the RIS (2320-2) may be initially installed and fixed indoors, but the transmitting end (2310-2) may be changed. More specifically, signal transmission may not be smooth based on the medium or climate environment between the transmitter 2310-2 and the RIS 2320-2 based on environmental and network information. At this time, the transmitter 2310-3 that transmits the signal to the RIS (2320-2) may be changed, and the beam transmitted to the RIS (2320-2) may also be changed. That is, the transmitter 2310-2 that transmits a signal to the RIS 2320-1 can be changed, and the beam between the transmitter 2310-2 and the RIS 232021 can be changed. Here, the terminal 2330-3 in the indoor space can move, the RIS 2320-2 receives a signal from the transmitter 2310-3 based on the determined beam, and the terminal 2330-3 in the indoor space can move. The beam can be configured to vary based on its mobility. Here, the terminal 2330-3 in the indoor space may be registered or connected to the RIS 2320-2. For example, when the terminal 2330-3 in an indoor space enters the indoor space, it can connect to the RIS 2320-2. Afterwards, when a signal to be received is generated from the transmitter 2310-3, the signal can be received through the RIS 2320-2.

Figure 24 is a diagram showing a method of performing beam control in an indoor environment applicable to the present disclosure. Referring to FIG. 24(a), the RIS 2420-1 can set a beam based on environment and network information. Here, indoor space feature information can be derived from environment and network information. For example, in Figure 24(a), the indoor space can be formed low and wide, and information about this can be obtained as environment and network information. At this time, the RIS (2420-1) can form a horizontal beam and transmit signals suited to the indoor space. On the other hand, in Figure 24(b), the indoor space may be formed high and narrow. At this time, the RIS (2420-2) can form a vertical beam based on environment and network information to deliver signals suited to the indoor space.

Figure 25 is a diagram showing a method of forming a beam based on AI applicable to the present disclosure. Referring to FIG. 25, the transmitting end (or base station, 2510) may transmit a signal to the terminal 2530 through the RIS 2520. Here, AI may be provided in the RIS 2520, and optimization of the beam and path may be performed based on AI.

More specifically, when the RIS 2520 is turned on, channel information and environment information between the transmitter 2510 and the RIS 2520 can be sensed. For example, when the RIS 2520 is turned on, environmental and network information can be determined, and the beam and path between the transmitter 2510 and the RIS 2520 can be optimized based on this. For example, the beam between the transmitter 2510 and the RIS 2520 may be determined directly or the signal may be transmitted through other devices based on a cooperative network, and is not limited to a specific form. Additionally, channel information and environmental information between the RIS 2520 and the terminal 2530 can be sensed. For example, when the RIS 2520 is turned on, environment and network information can be determined, and the beam and path between the RIS 2520 and the terminal 2530 can be optimized based on this. When LoS between the terminal 2530 and the RIS 2520 is guaranteed, the RIS 2520 can set a beam to the terminal 2530 based on terminal location information. On the other hand, when LoS is not guaranteed, the RIS (2530) can deliver a signal to the terminal through a cooperative network and is not limited to a specific form. Here, beam and path optimization needs to be performed based on environmental information and network information. However, environmental information and network information can be vast, and there may be limitations in creating optimal beams and paths by taking this into consideration. Considering the above, beam and path optimization can be performed utilizing AI. Here, AI may be combined with RIS (2520). For example, since the RIS (2520) relays signals between the transmitting end (2510) and the terminal (2530), AI needs to be located in the RIS (2520), and obtains environmental and network information to perform beam and path optimization. You can. Afterwards, the RIS 2520 can deliver the optimized information to the transmitter 2510 and the terminal 2530, respectively. The transmitter 2510 may determine a beam to be transmitted to the RIS 2520 or a cooperative network path based on information received from the RIS 2520. Additionally, the RIS 2520 may also deliver optimization information to the terminal 2530 and determine a beam or cooperative network path to be transmitted to the terminal 2530 based on this.

Figure 26 is a diagram showing a method of forming a beam based on AI applicable to the present disclosure. Referring to FIG. 26, the transmitting end (or base station, 2610) may transmit a signal to the terminal 2630 through the RIS 2620. Here, the transmitting end 2610 may be equipped with AI, and optimization of the beam and path may be performed based on the AI.

More specifically, when the RIS 2620 is turned on, channel information and environment information between the transmitter 2610 and the RIS 2620 can be sensed. For example, when the RIS 2620 is turned on, environment and network information can be determined, and the beam and path between the transmitter 2610 and the RIS 2620 can be optimized based on this. For example, the beam between the transmitter 2610 and the RIS 2620 may be determined directly or the signal may be transmitted through other devices based on a cooperative network, and is not limited to a specific form. Additionally, channel information and environmental information between the RIS 2620 and the terminal 2630 can be sensed. For example, when the RIS (2620) is turned on, environmental and network information can be determined, and the beam and path between the RIS (2620) and the terminal 2630 can be optimized based on this. When LoS between the terminal 2630 and the RIS 2620 is guaranteed, the RIS 2620 can set a beam to the terminal 2630 based on terminal location information. On the other hand, when LoS is not guaranteed, the RIS 2630 can deliver a signal to the terminal through a cooperative network and is not limited to a specific form. Here, beam and path optimization needs to be performed based on environmental information and network information. However, environmental information and network information can be vast, and there may be limitations in creating optimal beams and paths by taking this into consideration. Considering the above, beam and path optimization can be performed utilizing AI. Here, the AI is combined with the transmitter 2610 and can receive information sensed from the RIS 2620. As an example, considering AI operation or power consumption, AI may be located at the transmitting end 2610. That is, the RIS 2620 can transmit at least one of directly sensed information and information acquired from the terminal 2630 to the transmitter 2610. In other words, the transmitter 2610 can obtain environmental and network information and perform beam and path optimization through AI. Afterwards, the transmitter 2610 can transmit the optimized information to the RIS (2620). The transmitter 2610 may determine a beam to be transmitted to the RIS 2620 or a cooperative network path based on the optimization information. Additionally, the transmitter 2610 may determine a beam or cooperative network path to be transmitted from the RIS 2620 to the terminal 2630 based on optimization. Afterwards, the transmitting end 2610 transfers the corresponding information to the RIS 2620, and the RIS 2620 can perform initial connection with the terminal 2630 to create a beam or optimal path, as described above.

Figure 27 is a diagram showing a method of forming a beam based on AI applicable to the present disclosure. Referring to FIG. 27, the transmitting end (or base station, 2710) may transmit a signal to the terminal 2730 through the RIS 2720. Here, the terminal 2730 may be equipped with AI, and optimization of the beam and path may be performed based on AI.

More specifically, when the RIS 2720 is turned on, channel information and environmental information between the transmitter 2710 and the RIS 2720 can be sensed. For example, when the RIS 2720 is turned on, environment and network information can be determined, and the beam and path between the transmitter 2710 and the RIS 2720 can be optimized based on this. For example, the beam between the transmitter 2710 and the RIS 2720 may be determined directly or the signal may be transmitted through other devices based on a cooperative network, and is not limited to a specific form. Additionally, channel information and environmental information between the RIS (2720) and the terminal (2730) can be sensed. For example, when the RIS 2720 is turned on, environment and network information can be determined, and the beam and path between the RIS 2720 and the terminal 2730 can be optimized based on this. When LoS between the terminal 2730 and the RIS 2720 is guaranteed, the RIS 2720 can set a beam to the terminal 2730 based on terminal location information. On the other hand, when LoS is not guaranteed, the RIS (2730) can deliver a signal to the terminal through a cooperative network and is not limited to a specific form. Here, beam and path optimization needs to be performed based on environmental information and network information. However, environmental information and network information can be vast, and there may be limitations in creating optimal beams and paths by taking this into consideration. Considering the above, beam and path optimization can be performed utilizing AI. Here, the AI is combined with the terminal 2730 and can receive information sensed from the RIS (2720). Additionally, the RIS 2720 can also transmit channel information and environment information of the transmitter 2710 to the terminal 2730. That is, the RIS 2720 can transmit at least one of directly sensed information and information obtained from the transmitter 2710 to the terminal 2730. In other words, the terminal 2730 can acquire environment and network information and perform beam and path optimization through AI. Afterwards, the terminal 2730 can transmit the optimized information to the RIS 2720, and the RIS 2720 can transmit the optimized information to the transmitter 2710. The transmitter 2710 may determine a beam to be transmitted to the RIS 2720 or a cooperative network path based on the optimization information. Additionally, the transmitting end 2710 may determine a beam or cooperative network path to be transmitted from the RIS 2720 to the terminal 2730 based on optimization. Afterwards, the RIS 2720 may perform initial connection with the terminal 2730 to create a beam or optimal path, as described above.

Figure 28 is a diagram showing a method of forming a beam based on AI applicable to the present disclosure. Referring to FIG. 28, the transmitting end (or base station, 2810) may transmit a signal to the terminal 2830 through the RIS 2820. Here, the transmitting end 2810 may be equipped with AI, and optimization of the beam and path may be performed based on the AI.

More specifically, when the RIS 2820 is turned on, a connection may be performed between the transmitter 2810 and the RIS 2820 and between the RIS 2820 and the terminal 2830. That is, the transmitter 2810 can build a beam or cooperation network for signal transmission to the RIS 2820. When LoS between the terminal 2830 and the RIS 2820 is guaranteed, the RIS 2820 can set a beam to the terminal 2830 based on terminal location information. On the other hand, when LoS is not guaranteed, the RIS (2830) can deliver a signal to the terminal through a cooperative network and is not limited to a specific form. Here, the transmitter 2810 can obtain environment and network information based on AI and perform beam or path optimization. To this end, the transmitting end 2810 can transmit a reference signal to the RIS 2820, and the RIS 2820 can transmit the reference signal to the terminal 2830. Afterwards, channel measurement can be performed based on the reference signal in each of the RIS 2820 and the terminal 2830. Afterwards, the terminal 2830 can feed back the measured channel information to the RIS (2820). Additionally, the RIS 2820 can transmit information received from the terminal 2830 and information directly measured by the RIS 2820 to the transmitter 2810. Afterwards, training can be performed based on the AI of the transmitter 2810. Here, the transmitter 2810 can determine whether to change beam or path optimization based on training. Based on the above, beam or path optimization can be performed in an aperiodic manner based on a preset period or event triggering.

Figure 29 is a diagram showing a RIS control method applicable to the present disclosure. Referring to FIG. 29, when the RIS is turned on, it can be connected to the base station. (S2910) After that, beamforming between the base station and RIS can be confirmed (S2920). Also, as an example, the optimal path between the base station and RIS can be determined based on the collaboration network. After that, the RIS can derive an optimization value using AI based on channel information and sensing environmental information (S2930). That is, the optimization value can be derived using AI based on the environmental information and network information described above. Afterwards, the RIS may determine the RIS pattern according to the AI optimization value and the beamforming (or optimal path) between the base station and the RIS. (S2940) After that, the RIS radiates the radio wave received from the base station through the determined RIS pattern. This can be done, and through this, the base station and the terminal can be connected. (S2950)

Figure 30 is a diagram showing a device to which the present disclosure can be applied.

Device 3000 may include a processor 3010, memory 3020, antenna 3030, and transceiver 3040.

The processor 3010 can perform baseband-related signal processing and execute commands stored in the memory 3020. Additionally, the memory 3020 may store information about commands and operations executed by the processor 3010. Additionally, the memory 3020 may store information processed by the processor 3010, software related to the operation of the device 3000, an operating system, applications, etc., and may also include components such as buffers.

Additionally, the antenna 3030 may include one or more physical antennas, and when it includes multiple antennas, it may support Multiple Input Multiple Output (MIMO) transmission and reception. Transceiver 3030 may include a radio frequency (RF) transmitter and an RF receiver. The processor 3010 of the device 3000 may be configured to implement the operations in the embodiments described above.

Additionally, the device 3000 can communicate with another device 3050. Here, the other device 3050 may also include a processor 3060, a memory 3070, an antenna 3030, and a transceiver 3040. As an example, the device 3000 and another device 3050 may be a base station and a terminal. As another example, both the device 3000 and another device 3050 may be terminals. As another example, the device 3000 and the other device 3050 may be the above-described RIS, repeater, IoT device, vehicle, and other devices, and are not limited to specific embodiments. That is, the device 3000 and the other device 3050 may refer to devices that perform communication based on the above-described embodiments, and may not be limited to specific embodiments.

Figure 31 is a diagram showing a network configuration to which the present disclosure can be applied.

Referring to FIG. 31, devices 3140 and 3150 can communicate through a network (Internet, 3110). Additionally, the devices 3140 and 3150 may be connected to an edge computing server (3130). Here, a cloud data center (or big data server, 3120) may be connected to the network 3110. The network 3110 may transmit information obtained directly from the devices 3140 and 3150 or through the edge computing server 3130 to the cloud center 3120. The cloud center 3120 can build a model by performing training based on the AI/ML or deep learning model 3121. As an example, the constructed model can provide inference related to the operation of the devices 3140 and 3150, thereby improving communication efficiency. In addition, each of the devices 3140 and 3150 includes a processor 3141 and 3151, a network device 3142 and 3152, a sensor unit 3143 and 3153, a memory 3144 and 3154, and a digital signal processing unit 3145 and 3155. It may include at least one of RF transceivers (3146, 3156) and antennas (3147, 3157), which may be as shown in FIG. 30. Specifically, network devices 3142 and 3152 may provide functions necessary to connect to the network 3110. Additionally, the sensor units 3143 and 3153 may perform the operation of sensing the above-described environment and network information. In addition, the digital signal processing units 3145 and 3155 can perform signal processing for information transmission, and can perform communication by forming beams with the antennas 3147 and 3157 through the RF transceivers 3146 and 3156. This is the same as described above.

The various embodiments of the present disclosure do not list all possible combinations but are intended to explain representative aspects of the present disclosure, and matters described in the various embodiments may be applied independently or in combination of two or more.

Additionally, various embodiments of the present disclosure may be implemented by hardware, firmware, software, or a combination thereof. For hardware implementation, one or more ASICs (Application Specific Integrated Circuits), DSPs (Digital Signal Processors), DSPDs (Digital Signal Processing Devices), PLDs (Programmable Logic Devices), FPGAs (Field Programmable Gate Arrays), general purpose It can be implemented by a processor (general processor), controller, microcontroller, microprocessor, etc.

The scope of the present disclosure is software or machine-executable instructions (e.g., operating system, application, firmware, program, etc.) that cause operations according to the methods of various embodiments to be executed on a device or computer, and such software or It includes non-transitory computer-readable medium in which instructions, etc. are stored and can be executed on a device or computer.

Transmitter: 3000
Processor at the transmitting end: 3010
Memory of transmitter: 3020
Antenna at the transmitting end: 3030
Transceiver at the transmitting end: 3040
Receiving end: 3050
Processor at the receiving end: 3060
Memory of receiving end: 3070
Antenna at the receiving end: 3080
Transceiver at the receiving end: 3080

Claims (3)

In a method of controlling a beam through an intelligent reflector (reconfigurable intelligence surface, RIS) in a wireless communication system,
Turning on the RIS to connect to a base station;
the RIS setting up first beamforming between the RIS and the base station;
the RIS sensing channel information and environmental information, and deriving an optimization value through artificial intelligence (AI) based on the sensed channel information and environmental information;
determining a RIS pattern based on the optimization value obtained through the AI and the first beamforming; and
A method of controlling a beam through RIS, comprising the steps of radiating RIS radio waves based on the RIS pattern and connecting the base station and the terminal.
According to claim 1,
The channel information and environment information include at least one of built-in information, sensor information, location information, network information, and big data-based information.
According to claim 1,
A method of controlling a beam through a RIS, wherein the optimal path between the base station and the RIS and the optimal path between the RIS and the terminal in a cooperative network are determined based on the artificial intelligence.

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