KR20240077713A - Method and apparatus for controlling beam to perform communication in an outdoor 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 is setting the first beamforming between the RIS and the base station, the RIS is a RIS installed in an outdoor environment, and the RIS is sensing the environment and network information. As such, the environment and network information includes at least one of built-in information, sensor information, location information, network information, and big data-based information, and whether or not to directly relay and cooperate between the base station and the terminal based on the sensed environment and network information It may include determining whether to set an optimal route based on the network.

Description

Method and device for performing communication by controlling beam in outdoor environment {METHOD AND APPARATUS FOR CONTROLLING BEAM TO PERFORM COMMUNICATION IN AN OUTDOOR ENVIRONMENT}

This disclosure relates to a method and device for performing communication by controlling beams in an outdoor environment. Specifically, the present disclosure relates to a method and device for performing communication by controlling beams through an intelligent reflector (reconfigurable intelligence surface, RIS) in an outdoor 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, and the RIS is the second control between the RIS and the base station. 1 As a step to set up beamforming, RIS is a RIS installed in an outdoor environment, and as a step in which RIS senses environmental and network information, the environmental and network information is based on built-in information, sensor information, location information, network information, and big data. It may include at least one of the information and determine whether to directly relay the base station and the terminal based on the sensed environment and network information and whether to set an optimal path based on the cooperative network.

Additionally, according to an aspect of the present disclosure, when the RIS directly relays the base station and the terminal, the beam between the base station and the RIS and the beam between the RIS and the terminal may be determined based on artificial intelligence.

In addition, according to an aspect of the present disclosure, when setting an optimal path based on a cooperative network, the optimal path between the base station and the RIS and the optimal path between the RIS and the terminal in the cooperative network are based on artificial intelligence. can be decided.

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.
Figure 10 is a diagram showing 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 outdoor environment applicable to the present disclosure.
FIG. 17 is a diagram illustrating a method of performing settings based on a channel environment in an outdoor environment applicable to the present disclosure.
18 may be an operation in a multi-user environment applicable to this disclosure.
FIG. 19 is a diagram illustrating a method of performing data communication through the RIS of a mobile object in an outdoor environment applicable to the present disclosure.
FIG. 20 is a diagram illustrating a method of performing beam control in an outdoor environment applicable to the present disclosure.
FIG. 21 is a diagram illustrating a method of performing beam control in an outdoor environment applicable to the present disclosure.
Figure 22 is a diagram showing a method of forming a beam based on AI applicable to the present disclosure.
Figure 23 is a diagram showing a method of forming a beam based on AI applicable to the present disclosure.
Figure 24 is a diagram showing a method of forming a beam based on AI 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 RIS control method applicable to the present disclosure.
Figure 27 is a diagram showing a base station device and a terminal device to which the present disclosure can be applied.
Figure 28 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.

In addition, referring to Figure 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.

FIG. 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 embodiment. 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.

FIG. 16 is a diagram showing a method of controlling a beam based on RIS in an outdoor environment applicable to the present disclosure. Referring to FIG. 16, the transmitter 1610 can obtain the above-described environment and network information. Here, the transmitting end can obtain location information where the RIS (1620) is installed and sensing information around the RIS (1620) as built-in information. Additionally, the transmitter 1610 may check the non-line of sight (NLoS) environment for at least one terminal (1630-1, 1630-2, 1630-3, 1630-4). As a specific example, the transmitter 1610 can sense whether a specific terminal is in an LoS environment. Here, a separate sensor may exist to sense whether it is a LoS environment. As another example, the transmitter 1610 transmits a reference signal to at least one terminal (1630-1, 1630-2, 1630-3, 1630-4), measures the channel state, and determines whether it is in an LoS environment. can do. The transmitting end 1610 obtains measurement information from at least one terminal (1630-1, 1630-2, 1630-3, and 1630-4), and transmits measurement information to a terminal that has measurement information smaller than a preset value that exists in the NLoS environment. It can be recognized as a terminal. In addition, the transmitting terminal 1610 includes environment and network information including location information of the transmitting terminal 1610, location information of the RIS 1620, and at least one terminal 1630-1, 1630-2, 1630-3, and 1630-4. At least one of the location information for can be obtained. Additionally, the transmitter 1610 can use network information to check whether to perform individual transmission through the RIS 1620 without a separate cooperative network. Here, if relay is needed based on a device other than the RIS 1620, the optimal path can be derived, as described above. Additionally, the transmitter 1610 can use big data information to check at least one of the shortest path information, movement pattern information of individual terminals, and terminal environment event information based on terrain information. That is, the transmitting end 1610 acquires environment and network information based on at least one terminal (1630-1, 1630-2, 1630-3, 1630-4), and transmits a signal through the RIS (1620) based on this. You can decide whether to relay or establish an optimal route through a cooperative network.

Additionally, the transmitting end (Tx), receiving end (Rx), and RIS operation beams can be controlled in consideration of the outdoor environment, and beam control can be performed in consideration of the outdoor climate environment. The outdoor climate environment may include at least one of temperature (high temperature/low temperature/room temperature), humidity, rainfall, snowfall, and air quality environment, and is not limited to the above-described embodiments. Additionally, beam control technology utilizing moving objects such as IoT (internet of things) and smart cars can be considered in outdoor environments, and this will be described later. Additionally, placement technology may be needed to configure multiple paths based on the transmitting end (Tx), receiving end (Rx), and RIS, which will be described later.

FIG. 17 is a diagram illustrating a method of performing settings based on a channel environment in an outdoor environment applicable to the present disclosure. Referring to FIG. 17, a channel environment setting operation can be performed in an outdoor environment based on RIS. (S1710) Here, the channel environment can be set by considering the radio wave attenuation variable in the outdoor environment. (S1720) Radio wave attenuation variable can take into account atmospheric/climate environmental information. For example, outdoor environment information may be information obtained through sensing (sensing information) or data obtained from outside (big data information), and may not be limited to a specific form. As a specific example, radio wave attenuation may be large in high frequency bands, so outdoor environmental information can be considered as a radio wave attenuation variable. Additionally, since it is an outdoor environment, atmospheric/climate environmental information may have an influence. Next, channel and path optimization can be performed. (S1730) Channel and path optimization can be performed based on at least one of radio wave environment information (terrain information) and RIS placement/operation information. For example, in an outdoor environment, the radio wave environment may vary depending on obstacles or surrounding terrain, and there is a need to consider radio wave environment information.

In addition, it may be determined whether to transmit the signal to the terminal using the RIS alone or whether to transmit the signal to the terminal by setting an optimal path through at least one device based on a cooperative network. RIS placement information may be considered for the above. Optimization for RIS may be performed according to radio wave environment information and RIS placement information, and channel and path optimization may be performed based on this. Afterwards, optimization is performed considering LoS and NLoS (S1740), and data communication can be performed by setting up an outdoor wireless link (S1750). That is, by considering radio wave attenuation variables and channel and path optimization in the outdoor 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,

18 may be an operation in a multi-user environment. Referring to FIG. 18, a channel environment setting operation can be performed in an outdoor environment based on RIS. (S1810) At this time, the channel environment can be set by considering the radio wave attenuation variable in the outdoor environment. (S1820) Here, the radio wave attenuation variable can be set. Attenuation variables can take atmospheric/climatic environmental information into account. Outdoor environment information may be information acquired through sensing (sensing information) or data obtained from outside (big data information), and may not be limited to a specific form. As a specific example, radio wave attenuation may be large in a high frequency band, so outdoor environmental information can be considered as a radio wave attenuation variable, and is not limited to a specific embodiment. Here, since it is an outdoor environment, atmospheric/climate environmental information may have an influence. Next, channel and path optimization can be performed (S1830). Here, channel and path optimization can be performed based on at least one of radio wave environment information (topographic information) and RIS placement/operation information. Additionally, since communication is performed with multiple terminals (or users) even in an outdoor environment, settings that take multiple terminals into account may be necessary to optimize channels and paths. Additionally, in an outdoor environment, the radio wave environment may vary depending on obstacles or surrounding terrain, and there is a need to consider radio wave environment information.

Here, for channel and path optimization, placement information of other devices may be considered based on RIS placement information or cooperative networks. For example, since a plurality of terminals must be considered, radio wave environment information and RIS placement information for each of the plurality of terminals can be considered. RIS placement information is determined by considering the location information and channel information for each of the plurality of terminals, and path optimization can be performed through this. Additionally, optimization for RIS may be performed based on radio wave environment information and RIS placement information, and channel and path optimization may be performed based on this. Afterwards, optimization is performed considering LoS and NLoS (S1840), and data communication can be performed by setting up an indoor/outdoor wireless link (S1850). That is, by considering radio wave attenuation variables and channel and path optimization in the outdoor environment. RIS can be optimized and data communication can be performed.

FIG. 19 is a diagram illustrating a method of performing data communication through the RIS of a mobile object in an outdoor environment applicable to the present disclosure. Referring to FIG. 19, the transmitter 1910 can transmit a signal to another device through the RIS provided in the mobile object (or device). For example, as shown in FIG. 7A, RIS may be provided in a mobile unit, and based on this, a cooperation network may be established as shown in FIG. 7B to determine the optimal route. Alternatively, a signal may be transmitted to another device based on the RIS provided in the mobile body. As a specific example, referring to FIG. 19, the transmitter 1910 can obtain environment and network information. Here, it can be confirmed from the built-in information that the first mobile unit 1920-1 and the second mobile unit 1920-2 are equipped with a RIS. In addition, mobile objects (1920-1, 1920-2) equipped with a location and RIS for at least one device (1920-3, 1920-4, 1920-5) to perform communication based on sensor information and location information. You can check the location. Additionally, the transmitter 1910 may recognize whether at least one device 1920-3, 1920-4, or 1920-5 with which to perform communication is in an LoS environment based on sensor information and location information. Additionally, the transmitter 1910 can obtain connection status information of each mobile object and device based on network information, and obtain information about the surrounding environment of each mobile object and device based on big data information. Based on the above, the transmitter 1910 can confirm the optimal path to transmit the signal or the arrangement of the RIS to relay the signal based on the cooperative network. As an example, the transmitter 1910 may transmit a signal to the third mobile unit 1920-3 in the NLoS environment through the RIS of the first mobile unit 1920-1. However, both the first mobile object 1920-1 and the third mobile object 1920-3 may be moving, and the mobile object that transmits the signal can be changed based on location information. For example, in FIG. 19, the transmitter 1910 transmits a signal from the first mobile unit 1920-1 to the second mobile unit 1920-2 equipped with RIS to transmit a signal to the third mobile unit 1920-3 based on location information. ), you can change the path. That is, the transmitter 1910 can change the optimal path for signal transmission using at least one of a fixed device and a moving device. Here, as an example, devices that transmit signals may be frequently changed based on each optimal path. Considering the above, the transmitter 1910 needs to determine the optimal path or RIS arrangement by utilizing environment and network information. As another example, the transmitter 1910 may determine the optimal path or RIS arrangement based on AI, which will be described later.

20 and 21 are diagrams showing a method of performing beam control in an outdoor environment applicable to the present disclosure. Referring to FIG. 20, the transmitting end 2010 can relay a signal based on a fixed RIS (2020). The transmitting end 2010 can obtain environmental and network information and perform data communication in an outdoor environment based on this. As an example, installation information about the RIS (2020) fixed as built-in information can be obtained. The transmitting end 2010 can set a beam for the fixed RIS 2020, and the beam can be preset and used continuously. As another example, the beam may be changed based on a preset period or sensing information of the surrounding environment, but the beam is not limited to this. Additionally, it can be confirmed whether at least one terminal to perform communication is located in the LoS environment based on the sensing information and location information. As an example, a terminal located in an LoS environment can directly communicate with the transmitter 2010. On the other hand, a terminal located in an NLoS environment can perform data communication through a fixed RIS (2020). Here, if data communication is not possible even through the fixed RIS (2020), an optimal path can be established through other devices in the cooperative network. As a specific example, the transmitter 2010 may transmit a signal through a beam to a fixed RIS 2020, and the fixed RIS 2020 may transmit a signal to another device or a RIS installed in a building. Afterwards, the RIS can relay signals to terminals located in an indoor environment, and an optimal path can be set based on the above.

Here, referring to FIG. 21, the transmitter 2110 may utilize at least one of built-in information, sensing information, location information, network information, and big data information to select the optimal path or optimal RIS. As an example, referring to FIG. 21, the terminal to which the transmitter 2110 will transmit the signal may be located in a high-rise environment. Here, the transmitter 2110 can select a RIS (2120) suitable for a high-rise environment and relay the signal through the corresponding RIS (2120). On the other hand, when the terminal is located in a low-rise environment, the transmitter 2110 can select a RIS (2130) suitable for the low-rise environment and relay the signal through the corresponding RIS (2130). Here, whether the terminal is located on a high or low floor can be confirmed through sensing information or location information. Additionally, as an example, whether the terminal is located on a high or low floor can be determined by further utilizing big data information or network information, and is not limited to a specific embodiment. That is, the transmitting end can obtain environmental and network information based on the outdoor environment, set the optimal RIS or optimal path based on the obtained information, and relay the signal.

Figure 22 is a diagram showing a method of forming a beam based on AI applicable to the present disclosure. Referring to FIG. 22, the transmitting end (or base station, 2210) may transmit a signal to the terminal 2230 through the RIS 2220. Here, AI may be provided in the RIS 2220, and optimization of the beam and path may be performed based on AI.

More specifically, when the RIS 2220 is turned on, channel information and environment information between the transmitter 2210 and the RIS 2220 can be sensed. For example, when the RIS 2220 is turned on, environment and network information can be determined, and the beam and path between the transmitter 2210 and the RIS 2220 can be optimized based on this. For example, the beam between the transmitter 2210 and the RIS 2220 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 2220 and the terminal 2230 can be sensed. For example, when the RIS 2220 is turned on, environment and network information can be determined, and the beam and path between the RIS 2220 and the terminal 2230 can be optimized based on this. When LoS between the terminal 2230 and the RIS 2220 is guaranteed, the RIS 2220 can set a beam to the terminal 2230 based on terminal location information. On the other hand, when LoS is not guaranteed, the RIS 2230 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 (2220). For example, since the RIS (2220) relays the signal between the transmitting end (2210) and the terminal (2230), AI needs to be located in the RIS (2220), and obtains environmental and network information to perform beam and path optimization. You can. Afterwards, the RIS 2220 can deliver the optimized information to the transmitter 2210 and the terminal 2230, respectively. The transmitter 2210 may determine a beam to be transmitted to the RIS 2220 or a cooperative network path based on information received from the RIS 2220. Additionally, the RIS 2220 may also deliver optimization information to the terminal 2230 and determine a beam or cooperative network path to be transmitted to the terminal 2230 based on this.

Figure 23 is a diagram showing a method of forming a beam based on AI applicable to the present disclosure. Referring to FIG. 23, the transmitting end (or base station, 2310) may transmit a signal to the terminal 2330 through the RIS 2320. Here, the transmitting end 2310 may be equipped with AI, and optimization of the beam and path may be performed based on AI.

More specifically, when the RIS 2320 is turned on, channel information and environmental information between the transmitter 2310 and the RIS 2320 can be sensed. For example, when the RIS 2320 is turned on, environment and network information can be determined, and the beam and path between the transmitter 2310 and the RIS 2320 can be optimized based on this. For example, the beam between the transmitter 2310 and the RIS 2320 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 2320 and the terminal 2330 can be sensed. For example, when the RIS 2320 is turned on, environment and network information can be determined, and the beam and path between the RIS 2320 and the terminal 2330 can be optimized based on this. When LoS between the terminal 2330 and the RIS 2320 is guaranteed, the RIS 2320 can set a beam to the terminal 2330 based on terminal location information. On the other hand, when LoS is not guaranteed, the RIS 2330 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 2310 and can receive information sensed from the RIS (2320). As an example, considering AI operation or power consumption, AI may be located at the transmitting end 2310. That is, the RIS 2320 can transmit at least one of directly sensed information and information acquired from the terminal 2330 to the transmitter 2310. In other words, the transmitter 2310 can obtain environmental and network information and perform beam and path optimization through AI. Afterwards, the transmitter 2310 can transmit the optimized information to the RIS (2320). The transmitter 2310 may determine a beam to be transmitted to the RIS 2320 or a cooperative network path based on the optimization information. Additionally, the transmitter 2310 may determine a beam or cooperative network path to be transmitted from the RIS 2320 to the terminal 2330 based on optimization. Afterwards, the transmitting end 2310 transfers the corresponding information to the RIS 2320, and the RIS 2320 can perform initial connection with the terminal 2330 to create a beam or optimal path, as described above.

Figure 24 is a diagram showing a method of forming a beam based on AI applicable to the present disclosure. Referring to FIG. 24, the transmitting end (or base station, 2410) may transmit a signal to the terminal 2430 through the RIS 2420. Here, the terminal 2430 may be equipped with AI, and optimization of the beam and path may be performed based on AI.

More specifically, when the RIS 2420 is turned on, channel information and environmental information between the transmitter 2410 and the RIS 2420 can be sensed. For example, when the RIS 2420 is turned on, environmental and network information can be determined, and the beam and path between the transmitter 2410 and the RIS 2420 can be optimized based on this. For example, the beam between the transmitter 2410 and the RIS 2420 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 2420 and the terminal 2430 can be sensed. For example, when the RIS 2420 is turned on, environment and network information can be determined, and the beam and path between the RIS 2420 and the terminal 2430 can be optimized based on this. When LoS between the terminal 2430 and the RIS 2420 is guaranteed, the RIS 2420 can set a beam to the terminal 2430 based on terminal location information. On the other hand, when LoS is not guaranteed, the RIS 2420 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 2430 and can receive information sensed from the RIS (2420). Additionally, the RIS 2420 can also transmit channel information and environment information of the transmitter 2410 to the terminal 2430. That is, the RIS 2420 can transmit at least one of directly sensed information and information obtained from the transmitter 2410 to the terminal 2430. That is, the terminal 2430 can acquire environment and network information and perform beam and path optimization through AI. Afterwards, the terminal 2430 can transmit the optimized information to the RIS 2420, and the RIS 2420 can transmit the optimized information to the transmitter 2410. The transmitter 2410 may determine a beam to be transmitted to the RIS 2420 or a cooperative network path based on the optimization information. Additionally, the transmitter 2410 may determine a beam or cooperative network path to be transmitted from the RIS 2420 to the terminal 2430 based on optimization. Afterwards, the RIS 2420 may perform initial connection with the terminal 2430 to create a beam or optimal path, as described above.

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, the transmitting end 2510 may be equipped with AI, and optimization of the beam and path may be performed based on AI.

More specifically, when the RIS (2520) is turned on, connection may be performed between the transmitting end (2510) and the RIS (2520) and between the RIS (2520) and the terminal (2530). That is, the transmitter 2510 can build a beam or cooperation network for signal transmission to the RIS 2520. 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, the transmitter 2510 can obtain environment and network information based on AI and perform beam or path optimization. To this end, the transmitting end 2510 can transmit a reference signal to the RIS 2520, and the RIS 2520 can transmit the reference signal to the terminal 2530. Afterwards, channel measurement can be performed based on the reference signal in each of the RIS 2520 and the terminal 2530. Afterwards, the terminal 2530 can feed back the measured channel information to the RIS (2520). Additionally, the RIS 2520 may transmit information received from the terminal 2530 and information directly measured by the RIS 2520 to the transmitter 2510. Afterwards, training can be performed based on the AI of the transmitter 2510. Here, the transmitter 2510 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 26 is a diagram showing a RIS control method applicable to the present disclosure. Referring to FIG. 26, when the RIS is turned on, it can be connected to the base station. (S2610) After that, beamforming between the base station and the RIS can be confirmed (S2620). Here, the RIS may be a RIS installed in an outdoor environment. . As a specific example, RIS may be installed in a mobile device or in a fixed device, and may directly relay data communication between a base station and a terminal or may relay data communication by setting an optimal path based on a cooperative network. Afterwards, the RIS can sense the environment and network information. (S2630) Here, the environment and network information may include at least one of the above-described built-in information, sensor information, location information, network information, and big data-based information. You can. Afterwards, the RIS may decide whether to directly relay the base station and the terminal based on the sensed environment and network information or to set an optimal path based on the cooperative network. (S2640) As an example, the sensed environment and network If the UE and LoS environment are guaranteed based on information, RIS can directly relay data communication between the base station and the UE. On the other hand, when the RIS and the LoS environment are not guaranteed based on the sensed environment and network information, the RIS can set the optimal path for relaying data communication between the base station and the terminal in the cooperative network. For example, when the RIS directly relays data communication between the base station and the terminal, the beam between the base station and the RIS and the beam between the RIS and the terminal can be optimized through AI. As another example, when RIS sets the optimal path based on a cooperative network, the optimal path between the base station and RIS and the optimal path between RIS and the terminal can be optimized through AI, as described above. same.

Figure 27 is a diagram showing a device to which the present disclosure can be applied.

Device 2700 may include a processor 2710, memory 2720, antenna 2727, and transceiver 2740.

The processor 2710 can perform baseband-related signal processing and execute commands stored in the memory 2720. Additionally, the memory 2720 may store information about commands and operations executed by the processor 2710. Additionally, the memory 2720 may store information processed by the processor 2710, software related to the operation of the device 2700, an operating system, applications, etc., and may also include components such as buffers.

Additionally, the antenna 2727 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 2730 may include a radio frequency (RF) transmitter and an RF receiver. The processor 2710 of the device 2700 may be configured to implement the operations in the embodiments described above.

Additionally, the device 2700 can communicate with another device 2750. Here, the other device 2750 may also include a processor 2760, a memory 2770, an antenna 2730, and a transceiver 2740. As an example, device 2700 and another device 2750 may be a base station and a terminal. As another example, both the device 2700 and another device 2750 may be terminals. As another example, the device 2700 and the other device 2750 may be the above-described RIS, repeater, IoT device, vehicle, and other devices, and are not limited to a specific embodiment. That is, the device 2700 and the other device 2750 may refer to devices that perform communication based on the above-described embodiments, and may not be limited to specific embodiments.

Figure 28 is a diagram showing a network configuration to which the present disclosure can be applied.

Referring to FIG. 28, devices 2840 and 2850 can communicate through a network (Internet, 2810). Additionally, the devices 2840 and 2850 may be connected to an edge computing server (edge computing server, 2830). Here, a cloud data center (or big data server, 2820) may be connected to the network 2810. The network 2810 may transmit information obtained directly from the devices 2840 and 2850 or through the edge computing server 2830 to the cloud center 2820. The cloud center 2820 can build a model by performing training based on the AI/ML or deep learning model 2821. As an example, the constructed model can provide inference related to the operation of the devices 2840 and 2850, thereby improving communication efficiency. In addition, each of the devices 2840 and 2850 includes a processor 2841 and 2851, a network device 2842 and 2852, a sensor unit 2843 and 2853, a memory 2844 and 2854, and a digital signal processing unit 2845 and 2855. It may include at least one of RF transceivers (2846, 2856) and antennas (2847, 2857), which may be as shown in FIG. 27. Specifically, network devices 2842 and 2852 may provide functions necessary to connect to the network 2810. Additionally, the sensor units 2843 and 2853 may perform the operation of sensing the above-described environment and network information. In addition, the digital signal processing units 2845 and 2855 can perform signal processing for information transmission, and can perform communication by forming beams with the antennas 2847 and 2857 through the RF transceivers 2846 and 2856. 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: 2700
Processor at the transmitting end: 2710
Memory of transmitter: 2720
Antenna at the transmitting end: 2730
Transceiver at transmitting end: 2740
Receiving end: 2750
Processor at the receiving end: 2760
Memory of receiving end: 2770
Antenna at the receiving end: 2780
Transceiver at the receiving end: 2780

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;
A step of the RIS setting up first beamforming between the RIS and the base station, wherein the RIS is a RIS installed in an outdoor environment;
A step in which the RIS senses environment and network information, wherein the environment and network information includes at least one of built-in information, sensor information, location information, network information, and big data-based information;
A method of controlling a beam through RIS, including determining whether to directly relay a base station and a terminal based on the sensed environment and network information and whether to set an optimal path based on a cooperative network.
According to claim 1,
When the RIS directly relays the base station and the terminal, a method of controlling a beam through the RIS, determining a beam between the base station and the RIS and a beam between the RIS and the terminal based on artificial intelligence.
According to claim 1,
When setting the optimal path based on the cooperative network, the optimal path between the base station and the RIS and the optimal path between the RIS and the terminal in the cooperative network are determined based on artificial intelligence. How to control the beam through.

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