KR20230020937A - Method for transmitting and receiving a high-frequency band uplink signal in a wireless communication system and apparatus therefor - Google Patents

Abstract

A method and apparatus for transmitting and receiving a high-frequency band uplink signal in a wireless communication system are proposed.
Specifically, the method performed by the reflector includes the steps of transmitting signal information including information on reception strength and information on reception angle to a base station based on a synchronization signal of a low frequency band from a terminal, the signal information Receiving beam pattern information for controlling a reflected beam of a high frequency band from the base station based on the base station, and transmitting the uplink signal of the high frequency band received from the terminal to the base station based on the reflected beam of the high frequency band Include steps.

Description

Method for transmitting and receiving a high-frequency band uplink signal in a wireless communication system and apparatus therefor

The present specification relates to a wireless communication system, and more particularly, to a method for determining a reflection pattern of a large intelligent surface (LIS) and an apparatus supporting the same.

A wireless communication system is widely deployed to provide various types of communication services such as voice and data. In general, a wireless communication system is a multiple access system capable of supporting communication with multiple users by sharing available system resources (bandwidth, transmission power, etc.).

Examples of the multiple access system include a Code Division Multiple Access (CDMA) system, a Frequency Division Multiple Access (FDMA) system, a Time Division Multiple Access (TDMA) system, a Space Division Multiple Access (SDMA) system, and an Orthogonal Frequency Division Multiple Access (OFDMA) system. , SC-FDMA (Single Carrier Frequency Division Multiple Access) system, IDMA (Interleave Division Multiple Access) system, and the like.

The present specification provides a method for determining a reflection pattern of a reflector (eg, LIS) of a high frequency band (eg, millimeter wave, terahertz) based on a synchronization signal (eg, a band signal of 6 gigahertz or less) of a low frequency band, and the same We propose a device for

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

The present specification proposes a method of transmitting an uplink signal (or radio wave) of a high frequency band transmitted by a terminal in a wireless communication system to a base station using a reflector. A method performed by a reflection device includes the steps of transmitting signal information including information on reception strength and information on reception angle to a base station based on a synchronization signal of a low frequency band from a terminal, and based on the signal information Receiving beam pattern information for controlling a high-frequency band reflection beam from the base station, and transmitting the high-frequency band uplink signal received from the terminal to the base station based on the high-frequency band reflection beam can do.

In addition, in the method of the present specification, the low frequency band may be a band of 6 gigahertz (GHz) or less, and the high frequency band may be a band of 6 gigahertz (GHz) or more.

In addition, in the method of the present specification, the beam pattern information may include information on a beam pattern index and information on a beam pattern application time.

In addition, the method of the present specification may further include receiving measurement request information for the low-frequency band synchronization signal from the base station and receiving the low-frequency band synchronization signal from the terminal.

In addition, in the method of the present specification, the measurement request information may include resource information of the synchronization signal of the low frequency band.

In addition, in the wireless communication system of the present specification, a reflector for reflecting an uplink signal of a high frequency band includes one or more transceivers, one or more processors functionally connected to the one or more transceivers, and functional functions of the one or more processors. , and includes one or more memories for storing instructions for performing operations, wherein the operations are based on a synchronization signal of a low frequency band from a terminal, and the information on the reception strength and the information on the reception angle Transmitting signal information including a to a base station, receiving beam pattern information for controlling a reflected beam of a high frequency band based on the signal information from the base station, and transmitting the terminal based on the reflected beam of the high frequency band. and transmitting the uplink signal of the high frequency band received from the base station to the base station.

In addition, in the method for controlling the reflected beam of the high frequency band of the reflector in the wireless communication system of the present specification, the method performed by the base station includes information about the reception strength and information about the reception angle of the synchronization signal in the low frequency band. requesting signal information including signal information from a plurality of reflecting devices, receiving the signal information from the plurality of reflecting devices, and beam pattern information for controlling the reflected beam of the high frequency band based on the signal information. and transmitting to the reflecting device.

In addition, in the method of the present specification, the low frequency band may be a band of 6 gigahertz (GHz) or less, and the high frequency band may be a band of 6 gigahertz (GHz) or less.

In addition, in the method of the present specification, the beam pattern information may include information on a beam pattern index and information on a beam pattern application time.

In addition, in the method of the present specification, the beam pattern information is transmitted to the reflecting device having a value greater than a predetermined receiving intensity among the plurality of reflecting devices, and the information on the beam pattern index is , may be determined based on the receiving angle of the reflection device.

In addition, the method of the present specification may further include receiving resource request information for the high-frequency band from a terminal and transmitting transmission request information for the synchronization signal of the low-frequency band to the terminal. .

In addition, in the method of the present specification, the transmission request information may include resource information about the synchronization signal of the low frequency band.

In addition, the method of the present specification may further include transmitting measurement request information for the synchronization signal of the low frequency band to the plurality of reflecting devices.

In addition, in the wireless communication system of the present specification, a base station controlling a reflected beam of a high frequency band of a reflecting device includes one or more transceivers, one or more processors functionally connected to the one or more transceivers, and the one or more processors. It is functionally connected and includes one or more memories for storing instructions for performing operations, wherein the operations include signal information including information on reception strength and information on reception angle of a synchronization signal in a low frequency band. requesting to a plurality of reflecting devices, receiving the signal information from the plurality of reflecting devices, and transmitting beam pattern information for controlling the reflected beam of the high frequency band to the reflecting device based on the signal information. steps may be included.

In addition, in the method for receiving resource information for a high frequency band in the wireless communication system of the present specification, the method performed by the terminal includes the steps of transmitting the resource request information for the high frequency band to a base station, and synchronization of the low frequency band Receiving signal transmission request information from the base station, transmitting the low-frequency band synchronization signal, and receiving resource information for the high-frequency band from the base station based on the low-frequency band synchronization signal. Including, the resource information on the high frequency band may be received after the reflection beam of the high frequency band of the reflection device is determined.

In addition, in the method of the present specification, the low frequency band may be a band of 6 gigahertz (GHz) or less, and the high frequency band may be a band of 6 gigahertz (GHz) or less.

In addition, in the method of the present specification, the reflected beam of the high frequency band may be determined based on beam pattern information including information on a beam pattern index and information on a beam pattern application time.

In addition, in the method of the present specification, beam pattern information may be determined based on the synchronization signal of the low frequency band.

In addition, in the wireless communication system of the present specification, a terminal receiving a high-frequency band resource is functionally connected to one or more transceivers, one or more processors functionally connected to the one or more transceivers, and the one or more processors, , including one or more memories storing instructions for performing operations, wherein the operations include transmitting the resource request information for the high-frequency band to a base station and transmission request information for the synchronization signal of the low-frequency band. Receiving from the base station, transmitting the low-frequency band synchronization signal, and receiving resource information for the high-frequency band from the base station based on the low-frequency band synchronization signal, The resource information for may be received after the reflection beam of the high frequency band of the reflecting device is determined.

According to the present specification, by determining a reflection pattern of a high-frequency band (eg, millimeter wave, terahertz) reflector (eg, LIS) based on a low-frequency band synchronization signal (eg, a band signal of 6 GHz or less), There is an effect of reducing the overhead of a transmission/reception beam search process between a base station and a terminal in a high frequency band.

In addition, according to the present specification, by determining a reflection pattern of a high frequency band reflector based on a low frequency band synchronization signal, there is an effect of improving uplink and/or downlink transmission/reception reliability between a base station and a terminal and reducing communication delay. .

Effects obtainable from the invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below.

The accompanying drawings, which are included as part of the detailed description to aid understanding of the present invention, provide examples of the present invention and describe technical features of the present invention together with the detailed description.
1 illustrates physical channels and typical signal transmission used in a 3GPP system.
2 is a diagram showing an example of a communication structure that can be provided in a 6G system.
3 shows an example of a perceptron structure.
4 shows an example of a multilayer perceptron structure.
5 shows an example of a deep neural network.
6 shows an example of a convolutional neural network.
7 is a diagram illustrating an example of a filter operation in a convolutional neural network.
8 shows an example of a neural network structure in which a circular loop exists.
9 shows an example of an operating structure of a recurrent neural network.
10 shows an example of an electromagnetic spectrum.
11 is a diagram showing an example of a THz communication application.
12 is a diagram illustrating an example of an electronic element-based THz wireless communication transceiver.
13 is a diagram illustrating an example of a method of generating a THz signal based on an optical element.
14 is a diagram showing an example of an optical element-based THz wireless communication transceiver.
15 illustrates the structure of a photoinc source based transmitter.
16 illustrates the structure of an optical modulator.
17 shows an example of a meta-planar structure.
18 is a diagram for explaining the characteristics of a meta atom.
19 shows an example of a scenario in which LOS is secured using LIS.
20 is a diagram illustrating an example of an operation scenario of LIS.
21 is a diagram for explaining a method of determining a reflection pattern of an LIS.
22 is a diagram showing the structure of LIS.
23 shows a procedure for transmitting and receiving a control channel between a base station and an LIS.
24 is a diagram showing the structure of a base station.
25 is a flowchart illustrating a method of determining an LIS reflection beam pattern.
26 is a flowchart illustrating a method of determining an LIS index and a reflection pattern index of a base station.
27 is a flowchart for explaining the operating method of the LIS proposed in this specification.
28 is a flowchart for explaining a method of operating a base station proposed in this specification.
29 is a flowchart for explaining a method of operating a terminal proposed in this specification.
30 illustrates a communication system 10 applied to the present invention.
31 illustrates a wireless device applicable to the present invention.
32 illustrates a signal processing circuit for a transmission signal.
33 shows another example of a wireless device applied to the present invention.
34 illustrates a portable device applied to the present invention.
35 illustrates a vehicle or autonomous vehicle to which the present invention is applied.
36 illustrates a vehicle applied to the present invention.
37 illustrates an XR device applied to the present invention.
38 illustrates a robot applied to the present invention.
39 illustrates an AI device applied to the present invention.

Hereinafter, preferred embodiments according to the present invention will be described in detail with reference to the accompanying drawings. The detailed description set forth below in conjunction with the accompanying drawings is intended to describe exemplary embodiments of the present invention and is not intended to represent the only embodiments in which the present invention may be practiced. The following detailed description includes specific details for the purpose of providing a thorough understanding of the present invention. However, one skilled in the art recognizes that the present invention may be practiced without these specific details.

In some cases, in order to avoid obscuring the concept of the present invention, well-known structures and devices may be omitted or may be shown in block diagram form centering on core functions of each structure and device.

In this specification, a base station has a meaning as a terminal node of a network that directly communicates with a terminal. A specific operation described as being performed by a base station in this document may be performed by an upper node of the base station in some cases. That is, it is obvious that various operations performed for communication with a terminal in a network composed of a plurality of network nodes including a base station may be performed by the base station or other network nodes other than the base station. A 'base station (BS)' is a fixed station, Node B, evolved-NodeB (eNB), base transceiver system (BTS), access point (AP), general NB (gNB, generation NB) may be replaced by terms such as In addition, a 'terminal' may be fixed or mobile, and may include user equipment (UE), mobile station (MS), user terminal (UT), mobile subscriber station (MSS), subscriber station (SS), and AMS ( Advanced Mobile Station), wireless terminal (WT), machine-type communication (MTC) device, machine-to-machine (M2M) device, device-to-device (D2D) device, and the like.

Hereinafter, downlink (DL) means communication from a base station to a terminal, and uplink (UL) means communication from a terminal to a base station. In downlink, a transmitter may be part of a base station and a receiver may be part of a terminal. In uplink, a transmitter may be a part of a terminal and a receiver may be a part of a base station.

Specific terms used in the following description are provided to aid understanding of the present invention, and the use of these specific terms may be changed into other forms without departing from the technical spirit of the present invention.

The following techniques may be used in various radio access systems such as CDMA, FDMA, TDMA, OFDMA, SC-FDMA, and the like. CDMA may be implemented with a radio technology such as Universal Terrestrial Radio Access (UTRA) or CDMA2000. TDMA may be implemented with a radio technology such as Global System for Mobile communications (GSM)/General Packet Radio Service (GPRS)/Enhanced Data Rates for GSM Evolution (EDGE). OFDMA may be implemented with radio technologies such as IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802-20, and Evolved UTRA (E-UTRA). UTRA is part of the Universal Mobile Telecommunications System (UMTS). 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) is a part of Evolved UMTS (E-UMTS) using E-UTRA, and LTE-A (Advanced) / LTE-A pro is an evolved version of 3GPP LTE. 3GPP NR (New Radio or New Radio Access Technology) is an evolved version of 3GPP LTE/LTE-A/LTE-A pro. 3GPP 6G may be an evolved version of 3GPP NR.

Embodiments of the present invention may be supported by standard documents disclosed in at least one of IEEE 802, 3GPP, and 3GPP2, which are wireless access systems. That is, steps or parts not described to clearly reveal the technical idea of the present invention among the embodiments of the present invention may be supported by the above documents. In addition, all terms disclosed in this document can be explained by the standard document.

For clarity of explanation, the description is based on a 3GPP communication system (eg, LTE, NR, etc.), but the technical spirit of the present invention is not limited thereto. LTE refers to technology after 3GPP TS 36.xxx Release 8. In detail, LTE technology after 3GPP TS 36.xxx Release 10 is referred to as LTE-A, and LTE technology after 3GPP TS 36.xxx Release 13 is referred to as LTE-A pro. 3GPP NR refers to technology after TS 38.xxx Release 15. 3GPP 6G may mean technology after TS Release 17 and/or Release 18. "xxx" means standard document detail number. LTE/NR/6G may be collectively referred to as a 3GPP system. For background art, terms, abbreviations, etc. used in the description of the present invention, reference may be made to matters described in standard documents published prior to the present invention. For example, you can refer to the following document.

3GPP LTE

- 36.211: Physical channels and modulation

- 36.212: Multiplexing and channel coding

- 36.213: Physical layer procedures

- 36.300: Overall description

- 36.331: Radio Resource Control (RRC)

3GPP NRs

- 38.211: Physical channels and modulation

- 38.212: Multiplexing and channel coding

- 38.213: Physical layer procedures for control

- 38.214: Physical layer procedures for data

- 38.300: NR and NG-RAN Overall Description

- 38.331: Radio Resource Control (RRC) protocol specification

Physical Channels and Frame Structure

Physical channels and general signal transmission

1 illustrates physical channels and typical signal transmission used in a 3GPP system. In a wireless communication system, a terminal receives information from a base station through downlink (DL), and the terminal transmits information to the base station through uplink (UL). Information transmitted and received between the base station and the terminal includes data and various control information, and various physical channels exist according to the type/use of the information transmitted and received by the base station and the terminal.

When the terminal is turned on or newly enters a cell, the terminal performs an initial cell search operation such as synchronizing with the base station (S11). To this end, the terminal may receive a primary synchronization signal (PSS) and a secondary synchronization signal (SSS) from the base station to synchronize with the base station and obtain information such as a cell ID. After that, the terminal can acquire intra-cell broadcast information by receiving a physical broadcast channel (PBCH) from the base station. Meanwhile, the terminal may check the downlink channel state by receiving a downlink reference signal (DL RS) in the initial cell search step.

After completing the initial cell search, the UE acquires more detailed system information by receiving a Physical Downlink Control Channel (PDCCH) and a Physical Downlink Shared Channel (PDSCH) according to the information carried on the PDCCH. It can (S12).

Meanwhile, when accessing the base station for the first time or when there is no radio resource for signal transmission, the terminal may perform a random access procedure (RACH) for the base station (S13 to S16). To this end, the UE transmits a specific sequence as a preamble through a physical random access channel (PRACH) (S13 and S15), and responds to the preamble through a PDCCH and a corresponding PDSCH (RAR (Random Access Channel) Response message) may be received In the case of contention-based RACH, a contention resolution procedure may be additionally performed (S16).

After performing the above procedure, the UE receives PDCCH/PDSCH (S17) and physical uplink shared channel (PUSCH)/physical uplink control channel (PUSCH) as a general uplink/downlink signal transmission procedure. Control Channel; PUCCH) transmission (S18) may be performed. In particular, the terminal may receive downlink control information (DCI) through the PDCCH. Here, the DCI includes control information such as resource allocation information for the terminal, and different formats may be applied depending on the purpose of use.

On the other hand, the control information that the terminal transmits to the base station through the uplink or the terminal receives from the base station is a downlink / uplink ACK / NACK signal, CQI (Channel Quality Indicator), PMI (Precoding Matrix Index), RI (Rank Indicator) ) and the like. The UE may transmit control information such as the aforementioned CQI/PMI/RI through PUSCH and/or PUCCH.

Structure of uplink and downlink channels

Downlink channel structure

The base station transmits a related signal to the terminal through a downlink channel described later, and the terminal receives the related signal from the base station through a downlink channel described later.

(1) Physical Downlink Shared Channel (PDSCH)

PDSCH carries downlink data (eg, DL-shared channel transport block, DL-SCH TB), and modulation methods such as Quadrature Phase Shift Keying (QPSK), 16 Quadrature Amplitude Modulation (QAM), 64 QAM, and 256 QAM are used. Applied. A codeword is generated by encoding the TB. PDSCH can carry multiple codewords. Scrambling and modulation mapping are performed for each codeword, and modulation symbols generated from each codeword are mapped to one or more layers (Layer mapping). Each layer is mapped to a resource along with a demodulation reference signal (DMRS), generated as an OFDM symbol signal, and transmitted through a corresponding antenna port.

(2) Physical Downlink Control Channel (PDCCH)

The PDCCH carries downlink control information (DCI) and a QPSK modulation method or the like is applied. One PDCCH is composed of 1, 2, 4, 8, or 16 Control Channel Elements (CCEs) according to an Aggregation Level (AL). One CCE is composed of 6 REGs (Resource Element Groups). One REG is defined as one OFDM symbol and one (P)RB.

The UE obtains DCI transmitted through the PDCCH by performing decoding (aka, blind decoding) on a set of PDCCH candidates. A set of PDCCH candidates decoded by the UE is defined as a PDCCH search space set. The search space set may be a common search space or a UE-specific search space. The UE may obtain DCI by monitoring PDCCH candidates in one or more search space sets configured by MIB or higher layer signaling.

Uplink channel structure

The terminal transmits a related signal to the base station through an uplink channel described later, and the base station receives the related signal from the terminal through an uplink channel described later.

(1) Physical Uplink Shared Channel (PUSCH)

PUSCH carries uplink data (e.g., UL-shared channel transport block, UL-SCH TB) and/or uplink control information (UCI), and CP-OFDM (Cyclic Prefix - Orthogonal Frequency Division Multiplexing) waveform , Discrete Fourier Transform-spread-Orthogonal Frequency Division Multiplexing (DFT-s-OFDM) waveform. When the PUSCH is transmitted based on the DFT-s-OFDM waveform, the UE transmits the PUSCH by applying transform precoding. For example, when transform precoding is impossible (eg, transform precoding is disabled), the terminal transmits a PUSCH based on the CP-OFDM waveform, and when transform precoding is possible (eg, transform precoding is enabled), the terminal transmits the CP-OFDM The PUSCH may be transmitted based on a waveform or a DFT-s-OFDM waveform. PUSCH transmission is dynamically scheduled by the UL grant in DCI or semi-static based on higher layer (eg, RRC) signaling (and/or Layer 1 (L1) signaling (eg, PDCCH)) It can be scheduled (configured grant). PUSCH transmission may be performed on a codebook basis or a non-codebook basis.

(2) Physical Uplink Control Channel (PUCCH)

PUCCH carries uplink control information, HARQ-ACK and/or scheduling request (SR), and may be divided into multiple PUCCHs according to PUCCH transmission length.

6G system general

6G (radio communications) systems are characterized by (i) very high data rates per device, (ii) very large number of connected devices, (iii) global connectivity, (iv) very low latency, (v) battery- It aims to lower energy consumption of battery-free IoT devices, (vi) ultra-reliable connectivity, and (vii) connected intelligence with machine learning capabilities. The vision of the 6G system can be four aspects such as intelligent connectivity, deep connectivity, holographic connectivity, and ubiquitous connectivity, and the 6G system can satisfy the requirements shown in Table 1 below. That is, Table 1 is a table showing an example of requirements for a 6G system.

6G systems include Enhanced mobile broadband (eMBB), Ultra-reliable low latency communications (URLLC), massive machine-type communication (mMTC), AI integrated communication, Tactile internet, High throughput, High network capacity, High energy efficiency, Low backhaul and It can have key factors such as access network congestion and enhanced data security.

2 is a diagram showing an example of a communication structure that can be provided in a 6G system.

6G systems are expected to have 50 times higher simultaneous radiocommunication connectivity than 5G radiocommunication systems. URLLC, a key feature of 5G, will become even more important in 6G communications by providing end-to-end latency of less than 1 ms. The 6G system will have much better volume spectral efficiency as opposed to the frequently used area spectral efficiency. 6G systems can provide very long battery life and advanced battery technology for energy harvesting, so mobile devices will not need to be charged separately in 6G systems. New network characteristics in 6G may be as follows.

- Satellites integrated network: 6G is expected to be integrated with satellites to serve the global mobile population. Integration of terrestrial, satellite and public networks into one wireless communication system is critical for 6G.

- Connected intelligence: unlike previous generations of wireless communication systems, 6G is revolutionary and will update the wireless evolution from “connected things” to “connected intelligence.” each procedure of processing).

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

- Ubiquitous super 3D connectivity: Access to networks and core network capabilities of drones and very low Earth orbit satellites will make super 3D connectivity in 6G ubiquitous.

In the new network characteristics of 6G as above, some general requirements can be as follows.

- Small cell networks: The idea of small cell networks has been introduced to improve received signal quality resulting in improved throughput, energy efficiency and spectral efficiency in cellular systems. As a result, small cell networks are an essential feature of 5G and Beyond 5G (5GB) and beyond communication systems. Therefore, the 6G communication system also adopts the characteristics of the small cell network.

- Ultra-dense heterogeneous network: Ultra-dense heterogeneous networks will be another important feature of 6G communication systems. Multi-tier networks composed of heterogeneous networks improve overall QoS and reduce costs.

- High-capacity backhaul: A backhaul connection is characterized by a high-capacity backhaul network to support high-capacity traffic. High-speed fiber and free space optical (FSO) systems may be possible solutions to this problem.

- Radar technology integrated with mobile technology: High-precision localization (or location-based service) through communication is one of the features of 6G wireless communication systems. Thus, radar systems will be integrated with 6G networks.

- Softwarization and virtualization: Softwarization and virtualization are two important features fundamental to the design process in 5GB networks to ensure flexibility, reconfigurability and programmability. In addition, billions of devices can be shared in a shared physical infrastructure.

Core implementation technology of 6G system

Artificial Intelligence

The most important and newly introduced technology for the 6G system is AI. AI was not involved in the 4G system. 5G systems will support partial or very limited AI. However, the 6G system will be AI-enabled for full automation. Advances in machine learning will create more intelligent networks for real-time communication in 6G. Introducing AI in communications can simplify and enhance real-time data transmission. AI can use a plethora of analytics to determine how complex target tasks are performed. In other words, AI can increase efficiency and reduce processing delays.

Time-consuming tasks such as handover, network selection, and resource scheduling can be performed instantly by using AI. AI can also play an important role in machine-to-machine, machine-to-human and human-to-machine communications. In addition, AI can be a rapid communication in BCI (Brain Computer Interface). AI-based communication systems can be supported by metamaterials, intelligent structures, intelligent networks, intelligent devices, intelligent cognitive radios, self-sustaining wireless networks, and machine learning.

Recently, there have been attempts to integrate AI with wireless communication systems, but these have been focused on the application layer and network layer, especially deep learning in the field of wireless resource management and allocation. However, these studies are gradually developing into the MAC layer and the physical layer, and in particular, attempts to combine deep learning with wireless transmission are appearing in the physical layer. AI-based physical layer transmission means applying a signal processing and communication mechanism based on an AI driver rather than a traditional communication framework in fundamental signal processing and communication mechanisms. For example, deep learning-based channel coding and decoding, deep learning-based signal estimation and detection, deep learning-based MIMO mechanism, AI-based resource scheduling and may include allocations, etc.

Machine learning may be used for channel estimation and channel tracking, and may be used for power allocation, interference cancellation, and the like in a downlink (DL) physical layer. Machine learning can also be used for antenna selection, power control, symbol detection, and the like in a MIMO system.

However, the application of DNN for transmission in the physical layer may have the following problems.

AI algorithms based on deep learning require a lot of training data to optimize training parameters. However, due to limitations in acquiring data in a specific channel environment as training data, a lot of training data is used offline. This is because static training on training data in a specific channel environment may cause a contradiction between dynamic characteristics and diversity of a radio channel.

In addition, current deep learning mainly targets real signals. However, the signals of the physical layer of wireless communication are complex signals. In order to match the characteristics of wireless communication signals, further research on a neural network for detecting complex domain signals is needed.

Hereinafter, machine learning will be described in more detail.

Machine learning refers to a set of actions that train a machine to create a machine that can do tasks that humans can or cannot do. Machine learning requires data and a running model. In machine learning, data learning methods can be largely classified into three types: supervised learning, unsupervised learning, and reinforcement learning.

Neural network training is aimed at minimizing errors in the output. Neural network learning repeatedly inputs training data to the neural network, calculates the output of the neural network for the training data and the error of the target, and backpropagates the error of the neural network from the output layer of the neural network to the input layer in a direction to reduce the error. ) to update the weight of each node in the neural network.

Supervised learning uses training data in which correct answers are labeled in the learning data, and unsupervised learning may not have correct answers labeled in the learning data. That is, for example, learning data in the case of supervised learning related to data classification may be data in which each learning data is labeled with a category. Labeled training data is input to the neural network, and an error may be calculated by comparing the output (category) of the neural network and the label of the training data. The calculated error is back-propagated in a reverse direction (ie, from the output layer to the input layer) in the neural network, and the connection weight of each node of each layer of the neural network may be updated according to the back-propagation. The amount of change in the connection weight of each updated node may be determined according to a learning rate. The neural network's computation of input data and backpropagation of errors can constitute a learning cycle (epoch). The learning rate may be applied differently according to the number of iterations of the learning cycle of the neural network. For example, a high learning rate is used in the early stages of neural network learning to increase efficiency by allowing the neural network to quickly achieve a certain level of performance, and a low learning rate can be used in the late stage to increase accuracy.

The learning method may vary depending on the characteristics of the data. For example, in a case where the purpose of the receiver is to accurately predict data transmitted by the transmitter in a communication system, it is preferable to perform learning using supervised learning rather than unsupervised learning or reinforcement learning.

The learning model corresponds to the human brain, and the most basic linear model can be considered. ) is called

The neural network cord used as a learning method is largely divided into deep neural networks (DNN), convolutional deep neural networks (CNN), and recurrent Boltzmann Machine (RNN). there is.

An artificial neural network is an example of connecting several perceptrons.

3 shows an example of a perceptron structure.

Referring to FIG. 3, when the input vector x=(x1,x2,...,xd) is input, each component is multiplied by a weight (W1,W2,...,Wd), and after summing up the results, The entire process of applying the activation function σ() is called a perceptron. The huge artificial neural network structure may extend the simplified perceptron structure shown in FIG. 3 and apply input vectors to different multi-dimensional perceptrons. For convenience of description, an input value or an output value is referred to as a node.

Meanwhile, the perceptron structure shown in FIG. 3 can be described as being composed of a total of three layers based on input values and output values. An artificial neural network in which H number of (d + 1) dimensional perceptrons exist between the 1st layer and the 2nd layer and K number of (H + 1) dimensional perceptrons between the 2nd layer and the 3rd layer can be expressed as shown in FIG. 4 . 4 shows an example of a multilayer perceptron structure.

The layer where the input vector is located is called the input layer, the layer where the final output value is located is called the output layer, and all the layers located between the input layer and the output layer are called hidden layers. In the example of FIG. 4 , three layers are disclosed, but when counting the number of layers of an actual artificial neural network, since the count excludes the input layer, it can be regarded as a total of two layers. The artificial neural network is composed of two-dimensionally connected perceptrons of basic blocks.

The above-described input layer, hidden layer, and output layer can be jointly applied to various artificial neural network structures such as CNN and RNN, which will be described later, as well as multi-layer perceptrons. As the number of hidden layers increases, the artificial neural network becomes deeper, and a machine learning paradigm that uses a sufficiently deep artificial neural network as a learning model is called deep learning. In addition, the artificial neural network used for deep learning is called a deep neural network (DNN).

The deep neural network shown in FIG. 5 is a multi-layer perceptron composed of 8 hidden layers + 8 output layers. The multilayer perceptron structure is expressed as a fully-connected neural network. In a fully-connected neural network, there is no connection relationship between nodes located on the same layer, and a connection relationship exists only between nodes located on adjacent layers. DNN has a fully-connected neural network structure and is composed of a combination of multiple hidden layers and activation functions, so it can be usefully applied to identify the correlation characteristics between inputs and outputs. Here, the correlation characteristic may mean a joint probability of input and output.

'On the other hand, depending on how a plurality of perceptrons are connected to each other, various artificial neural network structures different from the aforementioned DNN can be formed.

In DNN, nodes located inside one layer are arranged in a one-dimensional vertical direction. However, in FIG. 6, it can be assumed that the nodes are two-dimensionally arranged with w nodes horizontally and h nodes vertically (convolutional neural network structure of FIG. 6). In this case, a weight is added for each connection in the connection process from one input node to the hidden layer, so a total of hХw weights must be considered. Since there are hХw nodes in the input layer, a total of h2w2 weights are required between two adjacent layers.

The convolutional neural network of FIG. 6 has a problem that the number of weights increases exponentially according to the number of connections, so instead of considering all mode connections between adjacent layers, it is assumed that there is a filter with a small size. As shown in , weighted sum and activation function calculations are performed for overlapping filters.

One filter has weights corresponding to the number of filters, and learning of weights can be performed so that a specific feature on an image can be extracted as a factor and output. In FIG. 7 , a 3Х3 size filter is applied to the 3Х3 region at the top left of the input layer, and an output value obtained by performing a weighted sum and an activation function operation for a corresponding node is stored in z22.

While scanning the input layer, the filter performs weighted sum and activation function calculations while moving horizontally and vertically at regular intervals, and places the output value at the position of the current filter. This operation method is similar to the convolution operation for images in the field of computer vision, so the deep neural network of this structure is called a convolutional neural network (CNN), and the hidden layer generated as a result of the convolution operation is called a convolutional layer. Also, a neural network having a plurality of convolutional layers is referred to as a deep convolutional neural network (DCNN).

In the convolution layer, the number of weights can be reduced by calculating a weighted sum by including only nodes located in a region covered by the filter from the node where the current filter is located. This allows one filter to be used to focus on features for a local area. Accordingly, CNN can be effectively applied to image data processing in which a physical distance in a 2D area is an important criterion. Meanwhile, in the CNN, a plurality of filters may be applied immediately before the convolution layer, and a plurality of output results may be generated through a convolution operation of each filter.

Meanwhile, there may be data whose sequence characteristics are important according to data attributes. Considering the length variability and precedence relationship of these sequence data, input each element on the data sequence one by one at each time step, and input the output vector (hidden vector) of the hidden layer output at a specific time point together with the next element on the sequence A structure in which this method is applied to an artificial neural network is called a recurrent neural network structure.

8 shows an example of a neural network structure in which a circular loop exists.

Referring to FIG. 8, a recurrent neural network (RNN) assigns an element (x1(t), x2(t), ,..., xd(t)) of a line t on a data sequence to a fully connected neural network. During the input process, the immediately preceding time point t-1 is a structure in which a weighted sum and an activation function are applied by inputting the hidden vectors (z1(t1), z2(t1), ..., zH(t1)) together. The reason why the hidden vector is transmitted to the next time point in this way is that information in the input vector at previous time points is regarded as being accumulated in the hidden vector of the current time point.

9 shows an example of an operating structure of a recurrent neural network.

Referring to FIG. 9 , the recurrent neural network operates in a sequence of predetermined views with respect to an input data sequence.

The input vector at time point 1 = (x1(t), x2(t), ,..., xd(t)) is input to the recurrent neural network and the hidden vector = (z1(1),z2(1),... .,zH(1)) is input together with the input vector of time 　2 (x1(2),x2(2),...,xd(2)), and the vector of the hidden layer 　 (z1( 2),z2(2) ,...,zH(2)). This process is repeatedly performed until time point 2, point 3, ,,, point T.

Meanwhile, when a plurality of hidden layers are arranged in a recurrent neural network, it is referred to as a deep recurrent neural network (DRNN). Recurrent neural networks are designed to be usefully applied to sequence data (eg, natural language processing).

As a neural network core used as a learning method, in addition to DNN, CNN, and RNN, Restricted Boltzmann Machine (RBM), deep belief networks (DBN), and Deep Q-Network It includes various deep learning techniques such as computer vision, voice recognition, natural language processing, and voice/signal processing.

Recently, there have been attempts to integrate AI with wireless communication systems, but these have been focused on the application layer and network layer, especially deep learning in the field of wireless resource management and allocation. However, these studies are gradually developing into the MAC layer and the physical layer, and in particular, attempts to combine deep learning with wireless transmission are appearing in the physical layer. AI-based physical layer transmission means applying a signal processing and communication mechanism based on an AI driver rather than a traditional communication framework in fundamental signal processing and communication mechanisms. For example, deep learning-based channel coding and decoding, deep learning-based signal estimation and detection, deep learning-based MIMO mechanism, AI-based resource scheduling and may include allocations, etc.

Terahertz (THz) communication

The data rate can be increased by increasing the bandwidth. This can be done using sub-THz communication with wide bandwidth and applying advanced massive MIMO technology. THz waves, also known as submillimeter radiation, typically represent a frequency band between 0.1 THz and 10 THz with corresponding wavelengths in the range of 0.03 mm-3 mm. The 100 GHz-300 GHz band range (sub THz band) is considered a major part of the THz band for cellular communications. Adding to the Sub-THz band mmWave band will increase 6G cellular communications capacity. Among the defined THz bands, 300 GHz-3 THz is in the far infrared (IR) frequency band. The 300 GHz-3 THz band is part of the broad band, but is at the border of the wide band, just behind the RF band. Thus, this 300 GHz-3 THz band exhibits similarities to RF. 10 shows an example of an electromagnetic spectrum.

The main characteristics of THz communications include (i) widely available bandwidth to support very high data rates, and (ii) high path loss at high frequencies (highly directional antennas are indispensable). The narrow beamwidth produced by the highly directional antenna reduces interference. The small wavelength of the THz signal allows a much larger number of antenna elements to be incorporated into devices and BSs operating in this band. This enables advanced adaptive array technology to overcome range limitations.

Optical wireless technology

OWC technology is intended for 6G communications in addition to RF-based communications for all possible device-to-access networks. These networks access network-to-backhaul/fronthaul network connections. OWC technology is already in use after the 4G communication system, but will be more widely used to meet the needs of the 6G communication system. OWC technologies such as light fidelity, visible light communication, optical camera communication, and FSO communication based on a wide band are already well-known technologies. Communications based on optical wireless technology can provide very high data rates, low latency and secure communications. LiDAR can also be used for ultra-high resolution 3D mapping in 6G communication based on broadband.

FSO backhaul network

The transmitter and receiver characteristics of an FSO system are similar to those of a fiber optic network. Thus, data transmission in FSO systems is similar to fiber optic systems. Therefore, FSO can be a good technology to provide backhaul connectivity in 6G systems along with fiber optic networks. With FSO, very long-distance communication is possible even at a distance of 10,000 km or more. FSO supports high-capacity backhaul connectivity for remote and non-remote locations such as ocean, space, underwater and isolated islands. FSO also supports cellular BS connections.

Massive MIMO technology

One of the key technologies to improve spectral efficiency is to apply MIMO technology. As MIMO technology improves, so does the spectral efficiency. Therefore, massive MIMO technology will be important in 6G systems. Since MIMO technology uses multiple paths, multiplexing technology and beam generation and operation technology suitable for the THz band must be considered as important so that data signals can be transmitted through more than one path.

block chain

Blockchain will be an important technology for managing large amounts of data in future communication systems. Blockchain is a form of distributed ledger technology, where a distributed ledger is a database that is distributed across numerous nodes or computing devices. Each node replicates and stores an identical copy of the ledger. Blockchain is managed as a peer-to-peer network. It can exist without being managed by a centralized authority or server. Data on a blockchain is collected together and organized into blocks. Blocks are linked together and protected using cryptography. Blockchain is the perfect complement to the IoT at scale with inherently improved interoperability, security, privacy, reliability and scalability. Thus, blockchain technology provides multiple capabilities such as interoperability between devices, traceability of large amounts of data, autonomous interaction of other IoT systems, and large-scale connection reliability in 6G communication systems.

3D Networking

The 6G system integrates terrestrial and air networks to support vertical expansion of user communications. 3D BS will be provided via low-orbit satellites and UAVs. Adding a new dimension in terms of height and related degrees of freedom makes 3D connections quite different from traditional 2D networks.

quantum communication

In the context of 6G networks, unsupervised reinforcement learning of networks is promising. Supervised learning approaches cannot label the vast amount of data generated by 6G. Labeling is not required in unsupervised learning. Thus, this technique can be used to autonomously build representations of complex networks. Combining reinforcement learning and unsupervised learning allows networks to operate in a truly autonomous way.

drone

Unmanned Aerial Vehicles (UAVs) or drones will be an important element in 6G wireless communications. In most cases, high-speed data wireless connectivity is provided using UAV technology. BS entities are installed on UAVs to provide cellular connectivity. UAVs have certain features not found in fixed BS infrastructures, such as easy deployment, strong line-of-sight links, and degrees of freedom with controlled mobility. During emergencies, such as natural disasters, the deployment of terrestrial communications infrastructure is not economically feasible and cannot provide services in sometimes volatile environments. UAVs can easily handle this situation. UAVs will become a new paradigm in the field of wireless communication. This technology facilitates three basic requirements of a wireless network: eMBB, URLLC and mMTC. UAVs can also support multiple purposes, such as enhancing network connectivity, fire detection, disaster emergency services, security and surveillance, pollution monitoring, parking monitoring, accident monitoring, and more. Therefore, UAV technology is recognized as one of the most important technologies for 6G communication.

Cell-free Communication

The tight integration of multiple frequencies and heterogeneous communication technologies is critical for 6G systems. As a result, users can seamlessly move from one network to another without having to make any manual configuration on the device. The best network is automatically selected from available communication technologies. This will break the limitations of the cell concept in wireless communication. Currently, user movement from one cell to another causes too many handovers in high-density networks, resulting in handover failures, handover delays, data loss and ping-pong effects. 6G cell-free communication will overcome all of this and provide better QoS. Cell-free communication will be achieved through multi-connectivity and multi-tier hybrid technologies and different heterogeneous radios of devices.

Integration of wireless information and energy transmission

WIET uses the same fields and waves as wireless communication systems. In particular, sensors and smartphones will be charged using wireless power transfer during communication. WIET is a promising technology for extending the lifetime of battery charging wireless systems. Thus, battery-less devices will be supported in 6G communications.

Integration of sensing and communication

Autonomous radio networks are capable of continuously sensing dynamically changing environmental conditions and exchanging information between different nodes. In 6G, sensing will be tightly integrated with communications to support autonomous systems.

Integration of access backhaul networks

In 6G, the density of access networks will be enormous. Each access network is connected by fiber and backhaul connections such as FSO networks. To cope with the very large number of access networks, there will be tight integration between access and backhaul networks.

Holographic Beamforming

Beamforming is a signal processing procedure that adjusts an antenna array to transmit radio signals in a specific direction. A subset of smart antennas or advanced antenna systems. Beamforming technology has several advantages such as high call-to-noise ratio, interference avoidance and rejection, and high network efficiency. Hologram beamforming (HBF) is a new beamforming method that differs significantly from MIMO systems because it uses software-defined antennas. HBF will be a very effective approach for efficient and flexible transmission and reception of signals in multi-antenna communication devices in 6G.

big data analytics

Big data analysis is a complex process for analyzing various large data sets or big data. This process ensures complete data management by finding information such as hidden data, unknown correlations and customer preferences. Big data is collected from various sources such as videos, social networks, images and sensors. This technology is widely used to process massive data in 6G systems.

Large Intelligent Surface (LIS)

In the case of THz band signals, there may be many shadow areas due to obstructions due to strong linearity. By installing LIS near these shadow areas, LIS technology that expands the communication area, strengthens communication stability, and provides additional additional services becomes important. An LIS is an artificial surface made of electromagnetic materials and can change the propagation of incoming and outgoing radio waves. LIS can be seen as an extension of massive MIMO, but its array structure and operating mechanism are different from massive MIMO. LIS also has low power consumption in that it operates as a reconfigurable reflector with passive elements, i.e. it only passively reflects signals without using an active RF chain. There are advantages to having In addition, since each passive reflector of the LIS must independently adjust the phase shift of an incident signal, it may be advantageous for a wireless communication channel. By properly adjusting the phase shift through the LIS controller, the reflected signal can be collected at the target receiver to boost the received signal power.

Terahertz (THz) wireless communication general

THz wireless communication uses wireless communication using THz waves having a frequency of approximately 0.1 to 10 THz (1 THz = 1012 Hz), and may mean terahertz (THz) band wireless communication using a very high carrier frequency of 100 GHz or more. . THz waves are located between RF (Radio Frequency)/millimeter (mm) and infrared bands, and (i) transmit non-metal/non-polarizable materials better than visible light/infrared rays, and have a shorter wavelength than RF/millimeter waves and have high straightness. Beam focusing may be possible. In addition, since the photon energy of the THz wave is only a few meV, it is harmless to the human body. A frequency band expected to be used for THz wireless communication may be a D-band (110 GHz to 170 GHz) or H-band (220 GHz to 325 GHz) band with low propagation loss due to molecular absorption in the air. Standardization discussions on THz wireless communication are being discussed centering on the IEEE 802.15 THz working group in addition to 3GPP, and standard documents issued by the IEEE 802.15 Task Group (TG3d, TG3e) can specify or supplement the content described in this specification. there is. THz wireless communication may be applied to wireless cognition, sensing, imaging, wireless communication, THz navigation, and the like. 11 is a diagram showing an example of a THz communication application.

As shown in FIG. 11, THz wireless communication scenarios can be classified into macro networks, micro networks, and nanoscale networks. In macro networks, THz wireless communication can be applied to vehicle-to-vehicle connections and backhaul/fronthaul connections. In micro networks, THz wireless communication is applied to indoor small cells, fixed point-to-point or multi-point connections such as wireless connections in data centers, and near-field communication such as kiosk downloading. It can be.

Table 2 below is a table showing an example of a technique that can be used in THz waves.

THz wireless communication can be classified based on the method for generating and receiving THz. The THz generation method can be classified as an optical device or an electronic device based technology. 12 is a diagram showing an example of an electronic device-based THz wireless communication transceiver. A method of generating THz using an electronic device includes a method using a semiconductor device such as a resonant tunneling diode (RTD), a local oscillator, and a multiplier. There are a method using a method using a compound semiconductor HEMT (High Electron Mobility Transistor) based integrated circuit, an MMIC (Monolithic Microwave Integrated Circuits) method using a compound semiconductor HEMT (High Electron Mobility Transistor) based integrated circuit, and a method using a Si-CMOS based integrated circuit. In the case of FIG. D2, a doubler, tripler, or multiplier is applied to increase the frequency, and the radiation passes through the subharmonic mixer and is radiated by the antenna. Since the THz band forms high frequencies, a multiplier is essential. Here, the multiplier is a circuit that makes the output frequency N times greater than the input, matches the desired harmonic frequency, and filters out all other frequencies. In addition, beamforming may be implemented by applying an array antenna or the like to the antenna of FIG. 12 . 12, IF denotes an intermediate frequency, tripler and multipler denote a multiplier, PA denotes a power amplifier, LNA denotes a low noise amplifier, and PLL denotes a phase-locked circuit (Phase -Locked Loop).

13 is a diagram illustrating an example of a method for generating a THz signal based on an optical device, and FIG. 14 is a diagram illustrating an example of a THz wireless communication transceiver based on an optical device.

Optical device-based THz wireless communication technology refers to a method of generating and modulating a THz signal using an optical device. An optical element-based THz signal generation technology is a technology that generates an ultra-high speed optical signal using a laser and an optical modulator and converts it into a THz signal using an ultra-high speed photodetector. Compared to a technique using only an electronic device, this technique can easily increase the frequency, generate a high-power signal, and obtain a flat response characteristic in a wide frequency band. In order to generate a THz signal based on an optical device, as shown in FIG. D3, a laser diode, a broadband optical modulator, and a high-speed photodetector are required. In the case of FIG. 13 , a THz signal corresponding to a wavelength difference between the lasers is generated by multiplexing light signals of two lasers having different wavelengths. In FIG. D3, an optical coupler means a semiconductor device that transmits an electrical signal using light waves in order to provide electrical isolation and coupling between circuits or systems, and UTC-PD (Uni-Traveling Carrier Photo- Detector is one of the photodetectors, which uses electrons as active carriers and reduces the movement time of electrons through bandgap grading. UTC-PD is capable of photodetection above 150 GHz. In FIG. D4, EDFA (Erbium-Doped Fiber Amplifier) represents an erbium-added optical fiber amplifier, PD (Photo Detector) represents a semiconductor device capable of converting an optical signal into an electrical signal, and OSA represents various optical communication functions (photoelectric conversion, light-to-optical conversion, etc.) represents an optical module (Optical Sub Assembly) that is modularized into one component, and DSO represents a digital storage oscilloscope.

The structure of the photoelectric converter (or photoelectric converter) will be described with reference to FIGS. 15 and 16 . 15 illustrates a structure of a transmitter based on a photoinc source, and FIG. 16 illustrates a structure of an optical modulator.

In general, a phase or the like of a signal may be changed by passing an optical source of a laser through an optical wave guide. At this time, data is loaded by changing electrical characteristics through a microwave contact or the like. Accordingly, the optical modulator output is formed as a modulated waveform. A photoelectric modulator (O/E converter) is an optical rectification operation by a nonlinear crystal, an O/E conversion by a photoconductive antenna, and a bundle of electrons in light flux. THz pulses can be generated according to emission from relativistic electrons, etc. A THz pulse generated in the above manner may have a unit length of femto second to pico second. An O/E converter uses non-linearity of a device to perform down conversion.

Considering the THz spectrum usage, it is necessary to use several contiguous GHz bands for fixed or mobile service for terahertz systems. more likely to use According to outdoor scenario criteria, available bandwidth may be classified based on oxygen attenuation of 10^2 dB/km in a spectrum up to 1 THz. Accordingly, a framework in which the available bandwidth is composed of several band chunks may be considered. As an example of the framework, if the length of a THz pulse for one carrier is set to 50 ps, the bandwidth (BW) becomes about 20 GHz.

Effective down conversion from the IR band to the THz band depends on how to utilize the nonlinearity of the O/E converter. That is, in order to down-convert to the desired terahertz band (THz band), the photoelectric converter (O / E converter) having the most ideal non-linearity to move to the corresponding terahertz band (THz band) design is required. If an O/E converter that does not fit the target frequency band is used, there is a high possibility that an error will occur with respect to the amplitude and phase of the corresponding pulse.

In a single carrier system, a terahertz transmission/reception system may be implemented using one photoelectric converter. Although it depends on the channel environment, as many photoelectric converters as the number of carriers may be required in a multi-carrier system. In particular, in the case of a multi-carrier system using several broadbands according to a plan related to the above-mentioned spectrum use, the phenomenon will be conspicuous. In this regard, a frame structure for the multi-carrier system may be considered. A signal down-frequency converted based on the photoelectric converter may be transmitted in a specific resource region (eg, a specific frame). The frequency domain of the specific resource domain may include a plurality of chunks. Each chunk may consist of at least one component carrier (CC).

In 5G/6G communication, it is expected to use ultra-high frequency (e.g., millimeter, Terahertz) bands that are easy to secure broadband frequency resources for large-capacity data transmission. The terahertz band is characterized by a greater path loss than the lower 6 GHz band. Beamforming based on UM-MIMO (Ultra Massive MIMO) is essential to secure coverage while overcoming such a large path loss. Through UM-MIMO-based beamforming, the number of beams increases due to the narrowed beam width, and the time required to search for transmission/reception beams between the base station and the terminal can be increased.

In addition, the corresponding terahertz band may be a communication environment in which Line of Sight (LOS) is the main focus. Accordingly, in view of high-frequency characteristics, the linearity of the signal is strong, and a shadow area may occur where the signal transmitted through beamforming does not reach depending on the location of the receiver. Therefore, it is necessary to secure LOS between the transmitting and receiving stages.

In this way, in order to secure the LOS, a large intelligent surface (or a reconfigurable intelligent surface, RIS) may be used. LIS is an electromagnetic wave reflector implemented as a metasurface, and can adjust the reflection pattern of incident electromagnetic waves.

17 shows an example of a meta-planar structure.

Referring to FIG. 17 , the meta plane 1700 can be implemented by two-dimensionally arranging several meta-atoms 1701 having a size smaller than the wavelength of the signal. A programmable switch 1702 exists in the meta atom 1701, and the phase characteristics of the reflected wave can be adjusted by adjusting the switch 1702.

18 is a diagram for explaining the characteristics of a meta atom. 18(a) is an example of a meta atom integrated with one PIN diode. 18(b) is an example of a meta atom with an actual biasing architecture. The biasing circuit may be elaborately designed to separate a DC signal and a radio frequency signal. 18(c) is a circuit in the ON state of the PIN diode, and FIG. 18(d) is a circuit in the OFF state of the PIN diode. FIG. 18(e) is a graph showing the reflection amplitude of the meta atom, FIG. 18(f) is a graph showing the reflection phase of the meta atom, and FIG. 18(g) shows the meta atom. It is a graph showing the difference in the reflection phase of an atom.

By adjusting the phase of each meta atom 1701, the width and direction of a beam reflected from the meta plane 1700 can be adjusted. This may be a principle similar to that of an array antenna.

19 shows an example of a scenario in which LOS is secured using LIS.

Referring to FIG. 19 , a location discovery system 1901 confirms the location of a terminal 1902 and transmits the location to a setting server 1903 . And/or, the setting server 1903 controls the LIS 1904 disposed on the wall based on 1902 of the terminal. And/or, the LIS 1904 forms a communication path between the terminal 1902 and the base station 1905 based on the control of the setting server.

In this way, in an environment where LOS is not secured between the base station and the terminal due to obstacles, if the reflection angle of the electromagnetic wave is adjusted using the LIS, an LOS propagation path can be created between the base station, the LIS, and the terminal.

On the other hand, as shown in FIG. 20, a base station (or AP (access point), BS (base station)) using a mixture of low frequency (B6G) and ultra high frequency (A6G) bands to provide indoor wireless mobile communication service (2010) can be installed.

For example, the low frequency band may be used for basic call setup between the terminal 2020 and the base station 2010. The ultra-high frequency band may be additionally used in the low-frequency band for transmitting and receiving large amounts of data. As shown in FIG. 20, the LIS 2030 may be arranged and used to improve communication quality in the shadow area of the ultra-high frequency band. Since the LIS 2030 is used to provide an LOS environment between the base station 2010 and the terminal 2020, the base station 2020 and the LOS environment may be installed.

In the case of the ultra-high frequency band, a process of searching for beams of the base station 2010 and the terminal 2020 is required. Since the LIS 2030 exists, a process of searching for a reflected beam of the LIS 2030 is additionally required.

In the case of an ultra-high frequency band, a massive array antenna system is used to overcome path loss. As a result, the width of the beam may be narrow and the number of beams may be increased.

Since it is necessary to find the reflected beam of the LIS 2030 as well as the transmission and reception beams of the base station 2010 and the terminal 2020, a lot of time may be required for a beam search time.

The present specification proposes a structure and method of an LIS capable of reducing the time required to determine a reflection pattern of the LIS in an ultra-high frequency band using a synchronization signal of a low frequency band transmitted from a terminal to a base station.

21 is a diagram for explaining a method of determining a reflection pattern of an LIS.

Referring to FIG. 21, the procedure or method for determining the LIS reflection pattern will be briefly described in two steps. As shown in FIG. , After measuring the state of the synchronization signal (received signal strength, AoA), it can be reported to the base station. The base station may determine i) LIS and ii) LIS reflection beam pattern to be used for the corresponding terminal based on the measurement values received from the LIS.

As shown in (b) of FIG. 21, the base station may transfer the LIS reflection beam pattern index to the LIS to control the reflection pattern of the LIS.

As described above, according to the present specification, a delay time caused by searching for a reflection beam pattern of an LIS together in a process of finding a transmission/reception beam between a base station and a terminal can be reduced.

Hereinafter, the present specification looks at i) the LIS structure, ii) the structure of the base station, and iii) the LIS reflection beam determination method for implementing the LIS reflection beam determination method in more detail.

Structure of LIS

22 is a diagram showing the structure of LIS.

22, the LIS includes a meta plane 2210, a meta plane controller 2220, a low frequency band receiver 2230, a signal processor 2240, an LIS control channel transceiver 2250, and/or an LIS controller 2260. can include

(meta plane)

The meta plane 2210 may be composed of numerous unit atoms (eg, meta-atoms). Each unit atom has a switch, so control is possible based on the voltage value transmitted from the meta-plane control unit 2220. The reflection pattern of the electromagnetic wave incident on the meta plane can be adjusted by adjusting the voltage value applied to the unit atoms.

(meta-plane control)

The meta-plane control unit 2220 may control the meta-plane 2210 by transforming the LIS reflection beam pattern index of the meta-plane 2210 into a voltage value of unit atoms corresponding to the corresponding value.

The base station may determine a reflection beam pattern of the meta plane 2210 . The LIS may receive beam pattern information through the LIS control channel transmission/reception unit 2250 and the LIS control unit 2260. For example, the beam pattern information may include information on a beam pattern index (eg, RSS) and information on a beam pattern application time (eg, AoA).

(low frequency band receiver)

The low frequency band receiving unit 2230 may be configured as a radio frequency (RF) chain for receiving a synchronization signal of a low frequency band transmitted by a terminal. Based on the low-frequency band synchronization signal received by the low-frequency band receiving unit, the signal processing unit 2240 determines the angle of arrival (AoA) and/or received signal strength of the signal (low-frequency band synchronization signal) arriving from the terminal. It may be configured in the form of an array antenna to calculate state information (or signal information) such as signal strength (RSS). The LIS may be implemented as a device attached to a structure such as a wall and may be suitable for placement in the form of an array antenna in a low frequency band. At this time, when the center frequency is 3 gigahertz (GHz), about 5 centimeters (cm) may be required as an interval between antennas.

(Signal processing unit)

The signal processor 2240 may receive resource information (eg, resource information, preamble ID) of a synchronization signal of a low frequency band to be measured, which is transmitted through the LIS controller. The signal processing unit 2240 may measure state information (eg, RSS, AoA) of the synchronization signal of the terminal based on the resource information.

(LIS control channel transceiver)

The LIS control channel transceiver 2250 may be configured as an RF chain capable of transmitting and receiving a control channel between the base station and the LIS. The corresponding control channel can use a low frequency (B6G) band or a separate frequency band.

23 shows a procedure for transmitting and receiving a control channel between a base station and an LIS.

Referring to FIG. 23, the base station transmits a LIS synchronization message to the LIS. And/or, the LIS transmits an LIS Measurement Request message to the base station in step S2301. And/or, the base station may transmit an LIS Measurement Report message to the LIS in step S2302. And/or the base station may transmit the LIS beam configuration LIS in step S2303.

The control message transmitted and received through the control channel between the base station and the LIS will be described as follows.

LIS synchronous message

The LIS synchronization message may perform synchronization acquisition of a link between the base station and the LIS for obtaining a message transmitted from the base station.

LIS measurement request message

The LIS measurement request message (or measurement request information for a low-frequency synchronization signal) includes resource information of a synchronization signal to be measured by the LIS. For example, the resource information may include time and frequency resource information and/or a preamble ID. And/or, in the case of a preamble ID, the synchronization signal may allocate resources based on non-contention. The corresponding preamble ID may be a resource allocated exclusively for the purpose of LIS measurement. The base station may not transmit a random access response for the corresponding preamble ID.

LIS measurement report message

The LIS measurement report message may include state information (or signal information) of a synchronization signal measured by the LIS. For example, the state information may include Received Signal Strength (RSS) and/or Angle of Arrival (AoA).

LIS Beam Setup Message

The LIS beam setting message may include LIS reflection beam pattern setting information (or beam pattern information). For example, the setting information may include an LIS reflection beam pattern index and/or an application time point of the corresponding reflection beam pattern.

(LIS control unit)

The LIS controller 2260 may transmit reflection beam pattern information (or beam pattern information) to the metaplane controller 2220 at a specific time point. The LIS control unit 2260 may transmit resource information of a synchronization signal to be measured by the LIS to the signal processing unit 2240 .

base station structure

24 is a diagram showing the structure of a base station.

Referring to FIG. 24 , the base station may include an LIS reflection pattern management unit 2410, an LIS control unit 2420, and an LIS control channel transmission/reception unit 2430.

(LIS reflection pattern management unit)

The LIS reflection pattern management unit 2410 may store LIS reflection beam pattern indexes mapped to AoAs in a database.

Table 3 is an example of a mapping table between AoA and LIS reflection beam pattern indices.

In Table 3, AoA may be an azimuth angle of reception of an electromagnetic wave incident to the LIS. And/or, AoA may be defined using both a reception azimuth and an elevation angle.

Table 3 is an example, and the LIS reflection beam pattern index may be determined based on a plurality of information and/or parameters such as RSS as well as AoA. And/or, when the LIS reflection beam pattern index is determined based on a plurality of pieces of information and/or parameters, the LIS reflection beam pattern index may be determined by AI technology such as machine learning described with reference to FIGS. 3 to 9 there is. And/or, not only the LIS reflection beam pattern index but also the application timing of the corresponding index may be determined by AoA and/or RSS.

(LIS control unit)

The LIS control unit 2420 may select an LIS that provides an optimal channel condition to the terminal based on state information of a synchronization signal measured by the LIS connected to the base station.

The LIS control unit 2420 may determine a reflection pattern providing an optimal channel condition with the terminal using the corresponding LIS. When the UE requests A6G band resources, the LIS control unit 2420 may request generation (or reporting) of an LIS measurement report message to be delivered to LISs connected to the corresponding base station.

(LIS control channel transceiver)

The LIS control channel transceiver 2430 may be configured as an RF chain capable of transmitting and receiving a control channel between a base station and an LIS. The corresponding control channel may use a low frequency (B6G) band or may use a separate frequency band.

The type of control message between the base station and the LIS is the same as that of the LIS.

LIS reflection beam pattern determination method

25 is a flowchart illustrating a method of determining an LIS reflection beam pattern.

Referring to FIG. 25, a terminal and an access point (AP) (or base station (BS)) may transmit and receive B6G band-based data in step S2501. In other words, data transmission and reception may be performed between the base station and the terminal based on the B6G band.

And/or, the terminal may request A6G band resources from the base station in step S2502. When the use of the A6G band is required for large-capacity data transmission, the terminal may request resources from the base station.

And/or, the base station may request an uplink synchronization signal based on the information transmitted to the terminal (eg, resource information of the uplink synchronization signal) in step S2503. Here, the information transmitted to the terminal may be resource and transmission power information of an uplink synchronization signal.

If the base station does not measure the state of the synchronization signal that satisfies the reference value, the terminal (and/or base station, LIS) may repeat steps S2503 to S2508 while increasing the power of the uplink synchronization signal.

And/or, the base station may transmit an LIS measurement request message to LISs connected to the corresponding base station in step S2504. For example, the base station may request the LIS to measure the state of the uplink synchronization signal. The base station may transmit resource information of an uplink synchronization signal.

And/or, in step S2505, the UE may transmit the synchronization signal through uplink.

And/or, the LIS may measure state information (eg, received signal strength, AoA) of the corresponding sync signal in step S2506.

And/or, the LIS may report state information (or an LIS measurement report message) of the measured synchronization signal to the base station in step S2507.

And/or, the base station may determine the LIS index and the reflection pattern index in step S2508.

Referring to step S2508 in detail with reference to FIG. 26 , the base station may receive state information of uplink synchronization signals measured in connected LISs in step S2601 .

And/or, in step S2602, the base station may check whether there exists an LIS in which the received RSS exceeds the reference value (P _th ) among the LIS.

And/or, in step S2603, the base station may select LIS reflection beam pattern indices corresponding to AoAs measured for LISs exceeding the reference value when LIS exceeding the reference value exist.

And/or, in step S2604, the base station may check whether there is room to increase the transmission power of the uplink synchronization signal when there is no LIS exceeding the reference value.

And/or, in step S2605, the base station may re-request transmission of the uplink synchronization signal by increasing the transmission power of the uplink synchronization signal when there is room for increasing the transmission power.

And/or, in step S2606, the base station may not control the LIS when there is no room left to increase the transmission power. In other words, steps S2508 to S2509 may not be performed.

Again, referring to FIG. 25 , the base station may transmit the LIS beam setup message in step S2509. The base station may transmit the LIS reflection beam pattern index to the determined LIS.

Next, the LIS may change the reflection pattern in step S2510. The LIS may adjust the reflected beam pattern based on the received LIS reflected beam pattern index.

Next, the base station and the terminal may perform A6G band-based transmit/receive beam search in step S2511. Based on the LIS set (or determined) through the above steps S2501 to S2510, a transmission/reception beam search process may be performed between the base station and the terminal in the A6G band.

27 is a flowchart for explaining a method of operating a reflection device proposed in this specification.

Referring to FIG. 27, a reflection device (e.g., LIS) (e.g., 1000/2000 in FIG. 22 or FIGS. 30 to 39) provides information on reception strength (e.g., RSS) based on a synchronization signal of a low frequency band from a terminal. And signal information (or state information of a synchronization signal) including information on a reception angle (eg, AoA) may be transmitted to the base station (S2701).

For example, an operation in which the reflection device transmits signal information to the base station in step S2701 may be implemented by the devices of FIGS. 22 and 30 to 39 . For example, referring to FIG. 31 , one or more processors 1020 may control one or more memories 1040 and/or one or more RF units 1060 to transmit signal information, and one or more RF units. 1060 may transmit signal information. And/or, referring to FIG. 22, the LIS controller 2260 can control the LIS control channel transceiver 2250 to transmit signal information, and the LIS control channel transceiver 2250 transmits signal information. can

And/or, the reflection device (1000/2000 of FIG. 22 or FIGS. 30 to 39) may receive beam pattern information for controlling a reflection beam of a high frequency band based on the signal information from the base station (S2702). For example, the beam pattern information may include information on a beam pattern index (eg, LIS reflection beam pattern index) and information on a beam pattern application time point. For example, beam pattern information may be generated and/or determined based on Table 3.

For example, an operation of receiving beam pattern information by the reflecting device in step S2702 may be implemented by the devices of FIGS. 22 and 30 to 39 . For example, referring to FIG. 31 , one or more processors 1020 may control one or more memories 1040 and/or one or more RF units 1060 to receive beam pattern information, and one or more RF Unit 1060 may receive beam pattern information. And/or, referring to FIG. 22, the LIS controller 2260 may control the LIS control channel transceiver 2250 to receive beam pattern information, and the LIS control channel transceiver 2250 may control the beam pattern information. can receive

And/or, the reflection device (1000/2000 in FIG. 22 or FIGS. 30 to 39) transmits the high-frequency band uplink signal received from the terminal to the base station (or in the direction of the base station) based on the high-frequency band reflection beam. Yes (S2703). For example, the reflector may change the direction of the uplink signal of the high frequency band transmitted from the terminal to the direction of the base station.

For example, an operation in which the reflection device transmits the high-frequency band uplink signal in step S2703 may be implemented by the devices of FIGS. 22 and 30 to 39 . For example, referring to FIG. 22, the metaplane control unit 2220 and/or the LIS control unit 2260 may control the metaplane 2210 and the like to transmit a high-frequency band uplink signal, and the metaplane ( 2210) may transmit an uplink signal of a high frequency band.

And/or, the low frequency band may be a band of 6 gigahertz (GHz) or less, and the high frequency band may be a band of 6 gigahertz (GHz) or more (eg, a terahertz band).

And/or, the reflection device may receive measurement request information for a low-frequency band synchronization signal from the base station and receive a low-frequency band synchronization signal (eg, an uplink synchronization signal) from the terminal. And/or, the measurement request information may include resource information of a synchronization signal in a low frequency band. In this case, the resource information of the synchronization signal of the low frequency band may be generated or determined based on AI technology such as machine learning described with reference to FIGS. 3 to 9 .

Since the operation of the reflector described with reference to FIG. 27 is the same as the operation of the reflector described with reference to FIGS. 1 to 26 , detailed descriptions are omitted.

The above-described signaling and operation may be implemented by the apparatus of the present specification (eg, FIGS. 22 and 30 to 39). For example, the above-described signaling and operation may be processed by one or more processors 1010 and 2020 of FIGS. 30 to 39, and the above-described signaling and operation may be performed by at least one processor (eg, 1010, 2020) may be stored in a memory (eg, 1040, 2040) in the form of a command/program (eg, instruction, executable code) for driving. And/or, the above-described signaling and operation may be processed by the control units 2220 and 2260 or the signal processing unit 2240 of FIG. 2260) or a signal processing unit (eg, 2240) may be stored in a memory in the form of a command/program (eg, instruction, executable code).

For example, in a device including one or more memories and one or more processors functionally connected to the one or more memories, the one or more processors enable the device to perform a synchronization signal of a low frequency band from a terminal Transmits signal information including information on reception strength and information on reception angle to a base station, receives beam pattern information for controlling a reflected beam of a high frequency band based on the signal information from the base station, and It can be configured to transmit the high-frequency band uplink signal transmitted from the terminal to the base station based on.

As another example, in a non-transitory computer readable medium (CRM) storing one or more instructions, the one or more instructions executable by one or more processors may cause the reflection device to synchronize the low frequency band from the beam terminal. Transmitting signal information including information on reception strength and information on reception angle based on the signal to a base station, receiving beam pattern information for controlling a reflected beam in a high frequency band based on the signal information from the base station, Based on the reflected beam of the band, the uplink signal of the high frequency band received from the terminal may be transmitted to the base station.

28 is a flowchart for explaining a method of operating a base station proposed in this specification.

Referring to FIG. 28, a base station (1000/2000 in FIG. 24 or FIGS. 30 to 39) provides information on the reception strength (eg, RSS) and information on the reception angle (eg, AoA) of a synchronization signal in a low frequency band. ) may be requested from a plurality of reflecting devices for signal information (or state information) including (S2801).

For example, the base station requesting signal information in step S2801 may be implemented by the devices of FIGS. 24 and 30 to 39 . For example, referring to FIG. 31 , one or more processors 1020 may control one or more memories 1040 and/or one or more RF units 1060 to request signal information, and one or more RF units. 1060 may request signaling information. And/or, referring to FIG. 24, the LIS controller 2420 may control the LIS control channel transceiver 2430 to request signal information, and the LIS control channel transceiver 2430 requests signal information. can

And/or, the base station (1000/2000 in FIGS. 24 and 30 to 39) may receive signal information from a plurality of reflecting devices (S2802).

For example, the base station receiving signal information in step S2802 may be implemented by the devices of FIGS. 24 and 30 to 39 . For example, referring to FIG. 31 , one or more processors 1020 may control one or more memories 1040 and/or one or more RF units 1060 to receive signal information, and one or more RF units. 1060 may receive signal information. And/or, referring to FIG. 24, the LIS controller 2420 may control the LIS control channel transceiver 2430 to receive signal information, and the LIS control channel transceiver 2430 receives signal information. can do.

And/or, the base station (1000/2000 of FIGS. 24 and 30 to 39) may transmit beam pattern information for controlling the reflection beam of the high frequency band to the reflection device based on the signal information (S2803). Here, the reflecting device may be a device having an RSS equal to or greater than a reference value among the plurality of reflecting devices. There may be more than one such reflecting device.

For example, the beam pattern information may include information on a beam pattern index (eg, LIS reflection beam pattern index) and information on a beam pattern application time point. The reflection device may have a reflection beam pattern corresponding to a corresponding LIS reflection beam pattern index at a specific point in time based on information about the beam pattern application time point.

For example, the base station may determine the LIS reflection beam pattern index corresponding to the corresponding AoA value based on Table 3, and transmit the LIS reflection beam pattern index to the reflecting device.

And/or, the beam pattern information may be transmitted to a reflector having a reception intensity greater than a preset reception intensity among a plurality of reflectors, and information on a beam pattern index may be determined based on a reception angle of the reflector. .

For example, an operation in which the base station transmits beam pattern information in step S2803 may be implemented by the devices of FIGS. 24 and 30 to 39. For example, referring to FIG. 27 , one or more processors 1020 may control one or more memories 1040 and/or one or more RF units 1060 to transmit beam pattern information, and one or more RF Unit 1060 may transmit beam pattern information. And/or, referring to FIG. 24, the LIS reflection pattern management unit 2410 and/or the LIS control unit 2420 may control the LIS control channel transceiver 2430 and the like to transmit beam pattern information, and control the LIS. The channel transceiver 2430 may transmit beam pattern information.

And/or, the low frequency band may be a band of 6 gigahertz (GHz) or less, and the high frequency band may be a band of 6 gigahertz (GHz) or less (eg, a terahertz band).

And/or, the base station may receive resource request information for the high frequency band from the terminal, and/or the base station may transmit transmission request information for the synchronization signal of the low frequency band to the terminal.

And/or, the transmission request information may include resource information about a synchronization signal in a low frequency band.

And/or, the base station may transmit measurement request information for the synchronization signal of the low frequency band to a plurality of reflecting devices.

Since the operation of the base station described with reference to FIG. 28 is the same as the operation of the base station described with reference to FIGS. 1 to 27, detailed descriptions other than those described are omitted.

The above-described signaling and operation may be implemented by the apparatus of the present specification (eg, FIGS. 24 and 30 to 39). For example, the above-described signaling and operation may be processed by one or more processors 1010 and 2020 of FIGS. 30 to 39, and the above-described signaling and operation may be performed by at least one processor (eg, 1010, 2020) may be stored in a memory (eg, 1040, 2040) in the form of a command/program (eg, instruction, executable code) for driving. And/or, the above-described signaling and operation may be processed by the LIS reflection pattern manager 2410 and/or the LIS control unit 2420 of FIG. 24, and the above-described signaling and operation may be performed by the LIS reflection pattern manager 2410 of FIG. ) and/or may be stored in memory in the form of instructions/programs (eg, instructions, executable code) for driving the LIS control unit 2420.

For example, in an apparatus including one or more memories and one or more processors functionally connected to the one or more memories, the one or more processors enable the apparatus to determine the reception strength of a synchronization signal in a low frequency band. Requests signal information including information and reception angle information from a plurality of reflecting devices, receives signal information from the plurality of reflecting devices, and reflects beam pattern information for controlling a reflected beam of a high frequency band based on the signal information. Can be set to transmit to the device.

As another example, in a non-transitory computer readable medium (CRM) storing one or more instructions, the one or more instructions executable by one or more processors may cause a base station to determine the reception strength of a synchronization signal of a low frequency band. Beam pattern information for requesting signal information including information on and reception angles from a plurality of reflecting devices, receiving signal information from the plurality of reflecting devices, and controlling a reflected beam of a high frequency band based on the signal information can be sent to the reflector.

29 is a flowchart for explaining a method of operating a terminal proposed in this specification.

Referring to FIG. 29, a terminal (1000/2000 of FIGS. 30 to 39) may transmit resource request information for a high-frequency band to a base station (S2901).

For example, an operation in which the terminal transmits resource request information in step S2901 may be implemented by the devices of FIGS. 30 to 39 to be described below. For example, referring to FIG. 31 , one or more processors 1020 may control one or more memories 1040 and/or one or more RF units 1060 to transmit resource request information, and one or more RF units. Unit 1060 may transmit resource request information.

And/or, the terminal (1000/2000 of FIGS. 30 to 39) may receive transmission request information for the synchronization signal of the low frequency band from the base station (S2902).

For example, an operation in which the terminal receives transmission request information in step S2902 may be implemented by the devices of FIGS. 30 to 39 to be described below. For example, referring to FIG. 31 , one or more processors 1020 may control one or more memories 1040 and/or one or more RF units 1060 to receive transmission request information, and one or more RF Unit 1060 may receive transmission request information.

And/or, the terminal (1000/2000 of FIGS. 30 to 39) may transmit a low-frequency band synchronization signal (S2903).

For example, an operation in which the terminal transmits a synchronization signal of a low frequency band in step S2903 may be implemented by the devices of FIGS. 30 to 39 to be described below. For example, referring to FIG. 31 , one or more processors 1020 may control one or more memories 1040 and/or one or more RF units 1060 to transmit synchronization signals of a low frequency band, and one The above RF unit 1060 may transmit a synchronization signal of a low frequency band.

And/or, the terminal (1000/2000 of FIGS. 30 to 39) may receive resource information on a high-frequency band from the base station based on the synchronization signal of the low-frequency band (S2904). The resource information for the high frequency band may be generated or determined based on, for example, AI technology such as machine learning described with reference to FIGS. 3 to 9 .

For example, an operation in which the terminal receives resource information on a high-frequency band in step S2904 may be implemented by the devices of FIGS. 30 to 39 to be described below. For example, referring to FIG. 31, one or more processors 1020 may control one or more memories 1040 and/or one or more RF units 1060 to receive resource information on a high frequency band, One or more RF units 1060 may receive resource information on a high frequency band.

In particular, the resource information on the high frequency band may be received after the reflection beam of the high frequency band of the reflector is determined.

And/or, the low frequency band may be a band of 6 gigahertz (GHz) or less, and the high frequency band may be a band of 6 gigahertz (GHz) or less (eg, a terahertz band).

And/or, the reflection beam of the high frequency band may be determined based on beam pattern information including beam pattern index information (eg, LIS reflection beam pattern index) and beam pattern application time information.

And/or, beam pattern information may be determined based on a synchronization signal of a low frequency band.

Since the operation of the terminal described with reference to FIG. 29 is the same as the operation of the terminal described with reference to FIGS. 1 to 28, detailed descriptions other than those described are omitted.

The above-described signaling and operation may be implemented by a device (eg, FIGS. 30 to 39) to be described below. For example, the above-described signaling and operation may be processed by one or more processors 1010 and 2020 of FIGS. 30 to 39, and the above-described signaling and operation may be performed by at least one processor (eg, 1010, 2020) may be stored in a memory (eg, 1040, 2040) in the form of a command/program (eg, instruction, executable code) for driving.

For example, in an apparatus including one or more memories and one or more processors functionally connected to the one or more memories, the one or more processors transmit resource request information for a high-frequency band to a base station. and receives transmission request information for a synchronization signal of a low frequency band from the base station, transmits a synchronization signal of a low frequency band, and receives resource information for a high frequency band from the base station based on the synchronization signal of the low frequency band, The resource information on the high frequency band may be received after a reflection beam of the high frequency band of the reflecting device is determined.

As another example, in a non-transitory computer readable medium (CRM) storing one or more instructions, one or more instructions executable by one or more processors may cause a terminal to transmit resource request information for a high-frequency band to a base station. To transmit, receive transmission request information for a synchronization signal of a low frequency band from the base station, transmit a synchronization signal of a low frequency band, and receive resource information for a high frequency band from the base station based on the synchronization signal of the low frequency band. , the resource information for the high frequency band may be received after the reflection beam of the high frequency band of the reflector is determined.

Examples of communication systems to which the present invention is applied

Although not limited thereto, various descriptions, functions, procedures, proposals, methods and / or operational flowcharts of the present invention disclosed in this document can be applied to various fields requiring wireless communication / connection (eg, 5G) between devices. there is.

Hereinafter, it will be exemplified in more detail with reference to the drawings. In the following drawings/description, the same reference numerals may represent the same or corresponding hardware blocks, software blocks, or functional blocks unless otherwise specified.

30 illustrates a communication system 10 applied to the present invention.

Referring to FIG. 30, a communication system 10 applied to the present invention includes a wireless device, a base station, and a network. Here, the wireless device means a device that performs communication using a radio access technology (eg, 5G New RAT (NR), Long Term Evolution (LTE)), and may be referred to as a communication/wireless/5G device. Although not limited thereto, wireless devices include robots 1000a, vehicles 1000b-1 and 1000b-2, XR (eXtended Reality) devices 1000c, hand-held devices 1000d, and home appliances 1000e. ), an Internet of Thing (IoT) device 1000f, and an AI device/server 4000. For example, the vehicle may include a vehicle equipped with a wireless communication function, an autonomous vehicle, a vehicle capable of performing inter-vehicle communication, and the like. Here, the vehicle may include an Unmanned Aerial Vehicle (UAV) (eg, a drone). XR devices include Augmented Reality (AR)/Virtual Reality (VR)/Mixed Reality (MR) devices, Head-Mounted Devices (HMDs), Head-Up Displays (HUDs) installed in vehicles, televisions, smartphones, It may be implemented in the form of a computer, wearable device, home appliance, digital signage, vehicle, robot, and the like. A portable device may include a smart phone, a smart pad, a wearable device (eg, a smart watch, a smart glass), a computer (eg, a laptop computer, etc.), and the like. Home appliances may include a TV, a refrigerator, a washing machine, and the like. IoT devices may include sensors, smart meters, and the like. For example, a base station and a network may also be implemented as a wireless device, and a specific wireless device 2000a may operate as a base station/network node to other wireless devices.

The wireless devices 1000a to 1000f may be connected to the network 3000 through the base station 2000. AI (Artificial Intelligence) technology may be applied to the wireless devices 1000a to 1000f, and the wireless devices 1000a to 1000f may be connected to the AI server 4000 through the network 300. The network 3000 may be configured using a 3G network, a 4G (eg LTE) network, or a 5G (eg NR) network. The wireless devices 1000a to 1000f may communicate with each other through the base station 2000/network 3000, but may also communicate directly (e.g. sidelink communication) without going through the base station/network. For example, the vehicles 1000b-1 and 1000b-2 may perform direct communication (e.g. Vehicle to Vehicle (V2V)/Vehicle to everything (V2X) communication). In addition, IoT devices (eg, sensors) may directly communicate with other IoT devices (eg, sensors) or other wireless devices 1000a to 1000f.

Wireless communication/connection 1500a, 1500b, and 1500c may be performed between the wireless devices 1000a to 1000f/base station 2000 and the base station 2000/base station 2000. Here, wireless communication/connection refers to various wireless connections such as uplink/downlink communication 1500a, sidelink communication 1500b (or D2D communication), and base station communication 1500c (e.g. relay, Integrated Access Backhaul (IAB)). This can be achieved through technology (eg, 5G NR) Wireless communication/connection (1500a, 1500b, 1500c) allows wireless devices and base stations/wireless devices, and base stations and base stations to transmit/receive radio signals to each other. For example, wireless communication/connection (1500a, 1500b, 1500c) can transmit/receive signals through various physical channels.To this end, based on various proposals of the present invention, for transmission/reception of radio signals At least some of various configuration information setting processes, various signal processing processes (eg, channel encoding/decoding, modulation/demodulation, resource mapping/demapping, etc.), resource allocation processes, etc. may be performed.

Examples of wireless devices to which the present invention is applied

31 illustrates a wireless device applicable to the present invention.

Referring to FIG. 31 , a first wireless device 1000 and a second wireless device 2000 may transmit and receive wireless signals through various wireless access technologies (eg, LTE and NR). Here, {the first wireless device 1000 and the second wireless device 2000} refer to the {wireless device 1000x and the base station 2000} of FIG. 32 and/or {the wireless device 1000x and the wireless device 1000x. } can correspond.

The first wireless device 1000 includes one or more processors 1020 and one or more memories 1040, and may further include one or more transceivers 1060 and/or one or more antennas 1080. Processor 1020 controls memory 1040 and/or transceiver 1060 and may be configured to implement the descriptions, functions, procedures, suggestions, methods, and/or flowcharts of operations disclosed herein. For example, the processor 1020 may process information in the memory 1040 to generate first information/signal, and transmit a radio signal including the first information/signal through the transceiver 1060. In addition, the processor 1020 may receive a radio signal including the second information/signal through the transceiver 1060 and store information obtained from signal processing of the second information/signal in the memory 1040. The memory 1040 may be connected to the processor 1020 and may store various information related to the operation of the processor 1020 . For example, memory 1040 may perform some or all of the processes controlled by processor 1020, or instructions for performing the descriptions, functions, procedures, suggestions, methods, and/or operational flowcharts disclosed herein. It may store software codes including them. Here, the processor 1020 and the memory 1040 may be part of a communication modem/circuit/chip designed to implement a wireless communication technology (eg, LTE, NR). The transceiver 1060 may be connected to the processor 1020 and may transmit and/or receive radio signals through one or more antennas 1080 . The transceiver 1060 may include a transmitter and/or a receiver. The transceiver 1060 may be used interchangeably with a radio frequency (RF) unit. In the present invention, a wireless device may mean a communication modem/circuit/chip.

The second wireless device 2000 includes one or more processors 2020 and one or more memories 2040, and may further include one or more transceivers 2060 and/or one or more antennas 2080. Processor 2020 controls memory 2040 and/or transceiver 2060 and may be configured to implement the descriptions, functions, procedures, suggestions, methods, and/or flowcharts of operations disclosed herein. For example, the processor 2020 may process information in the memory 2040 to generate third information/signal, and transmit a radio signal including the third information/signal through the transceiver 2060. In addition, the processor 2020 may receive a radio signal including the fourth information/signal through the transceiver 2060 and store information obtained from signal processing of the fourth information/signal in the memory 2040. The memory 2040 may be connected to the processor 2020 and may store various information related to the operation of the processor 2020. For example, the memory 2040 may perform some or all of the processes controlled by the processor 2020, or instructions for performing the descriptions, functions, procedures, suggestions, methods, and/or operational flowcharts disclosed herein. It may store software codes including them. Here, the processor 2020 and the memory 2040 may be part of a communication modem/circuit/chip designed to implement a wireless communication technology (eg, LTE, NR). The transceiver 2060 may be connected to the processor 2020 and may transmit and/or receive wireless signals through one or more antennas 2080 . The transceiver 2060 may include a transmitter and/or a receiver. The transceiver 2060 may be used interchangeably with an RF unit. In the present invention, a wireless device may mean a communication modem/circuit/chip.

Hereinafter, hardware elements of the wireless devices 1000 and 2000 will be described in more detail. Although not limited to this, one or more protocol layers may be implemented by one or more processors 1020, 2020. For example, one or more processors 1020 and 2020 may implement one or more layers (eg, functional layers such as PHY, MAC, RLC, PDCP, RRC, and SDAP). One or more processors 1020, 2020 may generate one or more Protocol Data Units (PDUs) and/or one or more Service Data Units (SDUs) according to descriptions, functions, procedures, proposals, methods, and/or operational flowcharts disclosed in this document. can create One or more processors 1020, 2020 may generate messages, control information, data or information according to the descriptions, functions, procedures, suggestions, methods and/or operational flowcharts disclosed herein. One or more processors 1020 and 2020 generate signals (eg, baseband signals) including PDUs, SDUs, messages, control information, data, or information according to the functions, procedures, proposals, and/or methods disclosed herein. , may be provided to one or more transceivers 1060 and 2060. One or more processors 1020, 2020 may receive signals (eg, baseband signals) from one or more transceivers 1060, 2060, and descriptions, functions, procedures, proposals, methods, and/or operational flowcharts disclosed herein PDUs, SDUs, messages, control information, data or information can be obtained according to these.

One or more processors 1020 and 2020 may be referred to as a controller, microcontroller, microprocessor or microcomputer. One or more processors 1020 and 2020 may be implemented by hardware, firmware, software, or a combination thereof. For example, one or more Application Specific Integrated Circuits (ASICs), one or more Digital Signal Processors (DSPs), one or more Digital Signal Processing Devices (DSPDs), one or more Programmable Logic Devices (PLDs), or one or more Field Programmable Gate Arrays (FPGAs). May be included in one or more processors (1020, 2020). The descriptions, functions, procedures, proposals, methods and/or operational flowcharts disclosed in this document may be implemented using firmware or software, and the firmware or software may be implemented to include modules, procedures, functions, and the like. Firmware or software configured to perform the descriptions, functions, procedures, proposals, methods and/or operational flowcharts disclosed in this document is included in one or more processors 1020 or 2020 or stored in one or more memories 1040 or 2040 and It may be driven by the above processors 1020 and 2020. The descriptions, functions, procedures, suggestions, methods and/or operational flow charts disclosed in this document may be implemented using firmware or software in the form of codes, instructions and/or sets of instructions.

One or more memories 1040, 2040 may be coupled with one or more processors 1020, 2020 and may store various types of data, signals, messages, information, programs, codes, instructions and/or instructions. One or more memories 1040, 2040 may be comprised of ROM, RAM, EPROM, flash memory, hard drives, registers, cache memory, computer readable storage media, and/or combinations thereof. One or more memories 1040 and 2040 may be located inside and/or external to one or more processors 1020 and 2020 . In addition, one or more memories 1040 and 2040 may be connected to one or more processors 1020 and 2020 through various technologies such as wired or wireless connections.

One or more transceivers 1060, 2060 may transmit user data, control information, radio signals/channels, etc. mentioned in methods and/or operational flowcharts of this document to one or more other devices. One or more transceivers 1060, 2060 may receive user data, control information, radio signals/channels, etc. referred to in descriptions, functions, procedures, proposals, methods and/or operational flowcharts disclosed in this document from one or more other devices. there is. For example, one or more transceivers 1060 and 2060 may be connected to one or more processors 1020 and 2020 and may transmit and receive radio signals. For example, one or more processors 1020 and 2020 may control one or more transceivers 1060 and 2060 to transmit user data, control information, or radio signals to one or more other devices. In addition, one or more processors 1020 and 2020 may control one or more transceivers 1060 and 2060 to receive user data, control information, or radio signals from one or more other devices. In addition, one or more transceivers 1060 and 2060 may be connected to one or more antennas 1080 and 2080, and one or more transceivers 1060 and 2060 may be connected to one or more antennas 1080 and 2080 according to the description and functions disclosed in this document. , procedures, proposals, methods and / or operation flowcharts, etc. can be set to transmit and receive user data, control information, radio signals / channels, etc. In this document, one or more antennas may be a plurality of physical antennas or a plurality of logical antennas (eg, antenna ports). One or more transceivers (1060, 2060) convert the received radio signals/channels from RF band signals in order to process the received user data, control information, radio signals/channels, etc. using one or more processors (1020, 2020). It can be converted into a baseband signal. One or more transceivers 1060 and 2060 may convert user data, control information, and radio signals/channels processed by one or more processors 1020 and 2020 from baseband signals to RF band signals. To this end, one or more of the transceivers 1060 and 2060 may include (analog) oscillators and/or filters.

Signal processing circuit example to which the present invention is applied

32 illustrates a signal processing circuit for a transmission signal.

Referring to FIG. 32 , a signal processing circuit 10000 may include a scrambler 10100, a modulator 10200, a layer mapper 10300, a precoder 10400, a resource mapper 10500, and a signal generator 10600. there is. Although not limited thereto, the operations/functions of FIG. 27 may be performed by processors 1020 and 2020 and/or transceivers 1060 and 2060 of FIG. 31 . The hardware elements of FIG. 32 may be implemented in the processors 1020 and 2020 and/or the transceivers 1060 and 2060 of FIG. 31 . For example, blocks 10100 to 10600 may be implemented in the processors 1020 and 2020 of FIG. 31 . Also, blocks 10100 to 10500 may be implemented in processors 1020 and 2020 of FIG. 31 , and block 10600 may be implemented in transceivers 1060 and 2060 of FIG. 31 .

The codeword may be converted into a radio signal through the signal processing circuit 10000 of FIG. 32 . Here, a codeword is an encoded bit sequence of an information block. Information blocks may include transport blocks (eg, UL-SCH transport blocks, DL-SCH transport blocks). Radio signals may be transmitted through various physical channels (eg, PUSCH, PDSCH).

Specifically, the codeword may be converted into a scrambled bit sequence by the scrambler 10100. A scramble sequence used for scrambling is generated based on an initialization value, and the initialization value may include ID information of a wireless device. The scrambled bit sequence may be modulated into a modulation symbol sequence by modulator 10200. The modulation scheme may include pi/2-Binary Phase Shift Keying (pi/2-BPSK), m-Phase Shift Keying (m-PSK), m-Quadrature Amplitude Modulation (m-QAM), and the like. The complex modulation symbol sequence may be mapped to one or more transport layers by the layer mapper 10300. Modulation symbols of each transport layer may be mapped to corresponding antenna port(s) by the precoder 10400 (precoding). The output z of the precoder 10400 can be obtained by multiplying the output y of the layer mapper 10300 by the N*M precoding matrix W. Here, N is the number of antenna ports and M is the number of transport layers. Here, the precoder 10400 may perform precoding after performing transform precoding (eg, DFT transformation) on complex modulation symbols. Also, the precoder 10400 may perform precoding without performing transform precoding.

The resource mapper 10500 may map modulation symbols of each antenna port to time-frequency resources. The time-frequency resource may include a plurality of symbols (eg, CP-OFDMA symbols and DFT-s-OFDMA symbols) in the time domain and a plurality of subcarriers in the frequency domain. The signal generator 10600 generates a radio signal from the mapped modulation symbols, and the generated radio signal can be transmitted to other devices through each antenna. To this end, the signal generator 10600 may include an inverse fast Fourier transform (IFFT) module, a cyclic prefix (CP) inserter, a digital-to-analog converter (DAC), a frequency uplink converter, and the like. .

The signal processing process for the received signal in the wireless device may be configured in reverse to the signal processing process 10100 to 10600 of FIG. 34 . For example, wireless devices (eg, 1000 and 2000 in FIG. 33 ) may receive a wireless signal from the outside through an antenna port/transceiver. The received radio signal may be converted into a baseband signal through a signal restorer. To this end, the signal restorer may include a frequency downlink converter, an analog-to-digital converter (ADC), a CP remover, and a fast Fourier transform (FFT) module. Thereafter, the baseband signal may be restored to a codeword through a resource de-mapper process, a postcoding process, a demodulation process, and a de-scramble process. The codeword may be restored to an original information block through decoding. Accordingly, a signal processing circuit (not shown) for a received signal may include a signal restorer, a resource demapper, a postcoder, a demodulator, a descrambler, and a decoder.

Example of using a wireless device to which the present invention is applied

33 shows another example of a wireless device applied to the present invention.

A wireless device may be implemented in various forms according to use-case/service.

Referring to FIG. 33, wireless devices 1000 and 2000 correspond to the wireless devices 1000 and 2000 of FIG. 31, and include various elements, components, units/units, and/or modules. (module). For example, the wireless devices 1000 and 2000 may include a communication unit 1100, a control unit 1200, a memory unit 1300, and an additional element 1400. The communication unit may include communication circuitry 1120 and transceiver(s) 1140 . For example, communication circuitry 1120 may include one or more processors 1020 and 2020 of FIG. 31 and/or one or more memories 1040 and 2040 . For example, transceiver(s) 1140 may include one or more transceivers 1060 and 2060 of FIG. 31 and/or one or more antennas 1080 and 2080. The control unit 1200 is electrically connected to the communication unit 1100, the memory unit 1300, and the additional element 1400 and controls overall operations of the wireless device. For example, the control unit 1200 may control electrical/mechanical operations of the wireless device based on programs/codes/commands/information stored in the memory unit 1300. In addition, the control unit 1200 transmits information stored in the memory unit 1300 to the outside (eg, another communication device) through the communication unit 1100 through a wireless/wired interface, or to the outside (eg, another communication device) through the communication unit 1100. Information received through a wireless/wired interface from other communication devices) may be stored in the memory unit 1300 .

The additional element 1400 may be configured in various ways according to the type of wireless device. For example, the additional element 1400 may include at least one of a power unit/battery, an I/O unit, a driving unit, and a computing unit. Although not limited thereto, the wireless device may be a robot (Fig. 30, 1000a), a vehicle (Fig. 30, 1000b-1, 1000b-2), an XR device (Fig. 30, 1000c), a mobile device (Fig. 30, 1000d), a home appliance. (FIG. 30, 1000e), IoT device (FIG. 30, 1000f), digital broadcasting terminal, hologram device, public safety device, MTC device, medical device, fintech device (or financial device), security device, climate/environmental device, It may be implemented in the form of an AI server/device (Fig. 30, 4000), a base station (Fig. 30, 2000), a network node, and the like. Wireless devices can be mobile or used in a fixed location depending on the use-case/service.

In FIG. 33 , various elements, components, units/units, and/or modules in the wireless devices 1000 and 2000 may all be interconnected through a wired interface, or at least some of them may be wirelessly connected through the communication unit 1100. For example, in the wireless devices 1000 and 2000, the control unit 1200 and the communication unit 1100 are connected by wire, and the control unit 1200 and the first units (eg, 1300 and 1400) are connected through the communication unit 1100. Can be connected wirelessly. Additionally, each element, component, unit/unit, and/or module within the wireless devices 1000 and 2000 may further include one or more elements. For example, the control unit 1200 may be composed of one or more processor sets. For example, the controller 1200 may include a set of a communication control processor, an application processor, an electronic control unit (ECU), a graphic processing processor, a memory control processor, and the like. As another example, the memory unit 1300 may include random access memory (RAM), dynamic RAM (DRAM), read only memory (ROM), flash memory, volatile memory, and non-volatile memory. volatile memory) and/or a combination thereof.

34 illustrates a portable device applied to the present invention.

A portable device may include a smart phone, a smart pad, a wearable device (eg, a smart watch, a smart glass), and a portable computer (eg, a laptop computer). A mobile device may be referred to as a mobile station (MS), a user terminal (UT), a mobile subscriber station (MSS), a subscriber station (SS), an advanced mobile station (AMS), or a wireless terminal (WT).

Referring to FIG. 34, a portable device 1000 includes an antenna unit 1080, a communication unit 1100, a control unit 1200, a memory unit 1300, a power supply unit 1400a, an interface unit 1400b, and an input/output unit 1400c. ) may be included. The antenna unit 1080 may be configured as a part of the communication unit 1100. Blocks 1100 to 1300/1400a to 1400c respectively correspond to blocks 1100 to 1300/1400 of FIG. 33 .

The communication unit 1100 may transmit/receive signals (eg, data, control signals, etc.) with other wireless devices and base stations. The controller 1200 may perform various operations by controlling components of the portable device 1000 . The controller 1200 may include an application processor (AP). The memory unit 1300 may store data/parameters/programs/codes/commands necessary for driving the portable device 1000 . Also, the memory unit 1300 may store input/output data/information. The power supply unit 1400a supplies power to the portable device 1000 and may include a wired/wireless charging circuit, a battery, and the like. The interface unit 1400b may support connection between the portable device 1000 and other external devices. The interface unit 1400b may include various ports (eg, audio input/output ports and video input/output ports) for connection with external devices. The input/output unit 1400c may receive or output image information/signal, audio information/signal, data, and/or information input from a user. The input/output unit 1400c may include a camera, a microphone, a user input unit, a display unit 1400d, a speaker, and/or a haptic module.

For example, in the case of data communication, the input/output unit 1400c obtains information/signals (eg, touch, text, voice, image, video) input from the user, and the acquired information/signals are stored in the memory unit 1300. can be stored The communication unit 1100 may convert the information/signal stored in the memory into a wireless signal, and directly transmit the converted wireless signal to another wireless device or to a base station. In addition, the communication unit 1100 may receive a radio signal from another wireless device or base station and then restore the received radio signal to original information/signal. After the restored information/signal is stored in the memory unit 1300, it may be output in various forms (eg, text, voice, image, video, haptic) through the input/output unit 1400c.

35 illustrates a vehicle or autonomous vehicle to which the present invention is applied. Vehicles or autonomous vehicles may be implemented as mobile robots, vehicles, trains, manned/unmanned aerial vehicles (AVs), ships, and the like.

Referring to FIG. 35 , a vehicle or autonomous vehicle 1000 includes an antenna unit 1080, a communication unit 1100, a control unit 1200, a driving unit 1400a, a power supply unit 1400b, a sensor unit 1400c, and autonomous driving. A portion 1400d may be included. The antenna unit 1080 may be configured as a part of the communication unit 1100. Blocks 1100/1300/1400a to 1400d respectively correspond to blocks 1100/1300/1400 of FIG. 33 .

The communication unit 1100 may transmit/receive signals (eg, data, control signals, etc.) with external devices such as other vehicles, base stations (e.g. base stations, roadside base stations, etc.), servers, and the like. The controller 1200 may perform various operations by controlling elements of the vehicle or autonomous vehicle 1000 . The controller 1200 may include an Electronic Control Unit (ECU). The driving unit 1400a may drive the vehicle or autonomous vehicle 1000 on the ground. The driving unit 1400a may include an engine, a motor, a power train, a wheel, a brake, a steering device, and the like. The power supply unit 1400b supplies power to the vehicle or autonomous vehicle 1000, and may include a wired/wireless charging circuit, a battery, and the like. The sensor unit 1400c may obtain vehicle conditions, surrounding environment information, and user information. The sensor unit 1400c includes an inertial measurement unit (IMU) sensor, a collision sensor, a wheel sensor, a speed sensor, an inclination sensor, a weight detection sensor, a heading sensor, a position module, and a vehicle forward. /Can include a reverse sensor, battery sensor, fuel sensor, tire sensor, steering sensor, temperature sensor, humidity sensor, ultrasonic sensor, illuminance sensor, pedal position sensor, and the like. The autonomous driving unit 1400d includes a technology for maintaining a driving lane, a technology for automatically adjusting speed such as adaptive cruise control, a technology for automatically driving along a predetermined route, and a technology for automatically setting a route when a destination is set and driving. technology can be implemented.

For example, the communication unit 1100 may receive map data, traffic information data, and the like from an external server. The autonomous driving unit 1400d may create an autonomous driving route and a driving plan based on the acquired data. The controller 1200 may control the driving unit 1400a so that the vehicle or the autonomous vehicle 1000 moves along the autonomous driving path according to the driving plan (eg, speed/direction adjustment). During autonomous driving, the communication unit 1100 may non/periodically obtain the latest traffic information data from an external server and obtain surrounding traffic information data from surrounding vehicles. In addition, during autonomous driving, the sensor unit 1400c may obtain vehicle state and surrounding environment information. The autonomous driving unit 1400d may update an autonomous driving route and a driving plan based on newly acquired data/information. The communication unit 1100 may transmit information about a vehicle location, an autonomous driving route, a driving plan, and the like to an external server. The external server may predict traffic information data in advance using AI technology based on information collected from the vehicle or self-driving vehicles, and may provide the predicted traffic information data to the vehicle or self-driving vehicles.

36 illustrates a vehicle applied to the present invention. A vehicle may be implemented as a means of transportation, a train, an air vehicle, a ship, and the like.

Referring to FIG. 36 , a vehicle 1000 may include a communication unit 1100, a control unit 1200, a memory unit 1300, an input/output unit 1400a, and a position measurement unit 1400b. Here, blocks 1100 to 1300/1400a to 1400b respectively correspond to blocks 1100 to 1300/1400 of FIG. 33 .

The communication unit 1100 may transmit/receive signals (eg, data, control signals, etc.) with other vehicles or external devices such as base stations. The controller 1200 may perform various operations by controlling components of the vehicle 1000 . The memory unit 1300 may store data/parameters/programs/codes/commands supporting various functions of the vehicle 1000 . The input/output unit 1400a may output an AR/VR object based on information in the memory unit 1300. The input/output unit 1400a may include a HUD. The location measurement unit 1400b may obtain location information of the vehicle 1000 . The location information may include absolute location information of the vehicle 1000, location information within a driving line, acceleration information, and location information with neighboring vehicles. The location measuring unit 1400b may include GPS and various sensors.

For example, the communication unit 1100 of the vehicle 1000 may receive map information, traffic information, and the like from an external server and store them in the memory unit 1300 . The location measurement unit 1400b may acquire vehicle location information through GPS and various sensors and store it in the memory unit 130 . The controller 120 may generate a virtual object based on map information, traffic information, vehicle location information, etc., and the input/output unit 1400a may display the created virtual object on a window in the vehicle (14100, 14200). In addition, the controller 1200 may determine whether the vehicle 1000 is normally operated within the driving line based on the vehicle location information. When the vehicle 1000 abnormally deviate from the driving line, the controller 1200 may display a warning on a window in the vehicle through the input/output unit 1400a. In addition, the controller 1200 may broadcast a warning message about driving abnormality to surrounding vehicles through the communication unit 1100 . Depending on circumstances, the controller 1200 may transmit vehicle location information and information on driving/vehicle abnormality to related organizations through the communication unit 1100 .

37 illustrates an XR device applied to the present invention. The XR device may be implemented as an HMD, a head-up display (HUD) provided in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, a digital signage, a vehicle, a robot, and the like.

Referring to FIG. 37, an XR device 1000a may include a communication unit 1100, a control unit 1200, a memory unit 1300, an input/output unit 1400a, a sensor unit 1400b, and a power supply unit 1400c. . Here, blocks 1100 to 1300/1400a to 1400c respectively correspond to blocks 1100 to 1300/1400 of FIG. 33 .

The communication unit 1100 may transmit/receive signals (eg, media data, control signals, etc.) with external devices such as other wireless devices, portable devices, or media servers. Media data may include video, image, sound, and the like. The controller 1200 may perform various operations by controlling components of the XR device 1000a. For example, the controller 1200 may be configured to control and/or perform procedures such as video/image acquisition, (video/image) encoding, and metadata generation and processing. The memory unit 1300 may store data/parameters/programs/codes/commands necessary for driving the XR device 1000a/creating an XR object. The input/output unit 1400a may acquire control information, data, etc. from the outside and output the created XR object. The input/output unit 1400a may include a camera, a microphone, a user input unit, a display unit, a speaker, and/or a haptic module. The sensor unit 1400b may obtain XR device status, surrounding environment information, user information, and the like. The sensor unit 1400b may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an RGB sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, an optical sensor, a microphone, and/or a radar. there is. The power supply unit 1400c supplies power to the XR device 100a and may include a wired/wireless charging circuit, a battery, and the like.

For example, the memory unit 1300 of the XR device 1000a may include information (eg, data, etc.) necessary for generating an XR object (eg, AR/VR/MR object). The input/output unit 1400a may obtain a command to operate the XR device 1000a from a user, and the controller 1200 may drive the XR device 1000a according to the user's driving command. For example, when a user tries to watch a movie, news, etc. through the XR device 1000a, the controller 1200 transmits content request information through the communication unit 1300 to another device (eg, the mobile device 1000b) or can be sent to the media server. The communication unit 130 may download/stream content such as movies and news from other devices (eg, the portable device 1000b) or a media server to the memory unit 1300 . The control unit 120 controls and/or performs procedures such as video/image acquisition, (video/image) encoding, metadata generation/processing, etc. for content, and acquisition through the input/output unit 1400a/sensor unit 1400b. An XR object may be created/output based on information about a surrounding space or a real object.

In addition, the XR device 1000a is wirelessly connected to the mobile device 1000b through the communication unit 1100, and the operation of the XR device 1000a may be controlled by the mobile device 1000b. For example, the portable device 1000b may operate as a controller for the XR device 1000a. To this end, the XR device 1000a may obtain 3D location information of the portable device 1000b, and then generate and output an XR object corresponding to the portable device 1000b.

38 illustrates a robot applied to the present invention. Robots may be classified into industrial, medical, household, military, and the like depending on the purpose or field of use.

Referring to FIG. 38 , the robot 1000 may include a communication unit 1100, a control unit 1200, a memory unit 1300, an input/output unit 1400a, a sensor unit 1400b, and a driving unit 1400c. Here, blocks 1100 to 1300/1400a to 1400c respectively correspond to blocks 1100 to 1300/1400 of FIG. 33 .

The communication unit 1100 may transmit/receive signals (eg, driving information, control signals, etc.) with external devices such as other wireless devices, other robots, or control servers. The controller 1200 may perform various operations by controlling components of the robot 1000 . The memory unit 1300 may store data/parameters/programs/codes/commands supporting various functions of the robot 1000. The input/output unit 1400a may obtain information from the outside of the robot 100 and output the information to the outside of the robot 1000. The input/output unit 1400a may include a camera, a microphone, a user input unit, a display unit, a speaker, and/or a haptic module. The sensor unit 1400b may obtain internal information of the robot 1000, surrounding environment information, user information, and the like. The sensor unit 1400b may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, an optical sensor, a microphone, a radar, and the like. The driving unit 1400c may perform various physical operations such as moving a robot joint. Also, the driving unit 1400c may cause the robot 1000 to run on the ground or fly in the air. The driving unit 1400c may include actuators, motors, wheels, brakes, propellers, and the like.

39 illustrates an AI device applied to the present invention. AI devices include fixed or mobile devices such as TVs, projectors, smartphones, PCs, laptops, digital broadcasting terminals, tablet PCs, wearable devices, set-top boxes (STBs), radios, washing machines, refrigerators, digital signage, robots, and vehicles. It can be implemented with possible devices and the like.

Referring to FIG. 39, the AI device 1000 includes a communication unit 1100, a control unit 1200, a memory unit 1300, an input/output unit 1400a/1400b, a running processor unit 1400c, and a sensor unit 1400d. can include Blocks 1100 to 1300/1400a to 1400d respectively correspond to blocks 1100 to 1300/1400 of FIG. 33 .

The communication unit 1100 transmits wired and wireless signals (eg, sensor information, user input, and learning) to external devices such as other AI devices (eg, FIG. models, control signals, etc.) can be transmitted and received. To this end, the communication unit 1100 may transmit information in the memory unit 1300 to an external device or transmit a signal received from the external device to the memory unit 1300 .

The controller 1200 may determine at least one executable operation of the AI device 1000 based on information determined or generated using a data analysis algorithm or a machine learning algorithm. In addition, the controller 1200 may perform the determined operation by controlling components of the AI device 1000. For example, the controller 1200 may request, retrieve, receive, or utilize data from the learning processor unit 1400c or the memory unit 1300, and may perform a predicted operation among at least one feasible operation or an operation determined to be desirable. Components of the AI device 1000 may be controlled to execute an operation. In addition, the control unit 1200 collects history information including user feedback on the operation contents or operation of the AI device 1000 and stores it in the memory unit 1300 or the running processor unit 1400c, or the AI server ( 32, 4000) can be transmitted to an external device. The collected history information can be used to update the learning model.

The memory unit 1300 may store data supporting various functions of the AI device 1000. For example, the memory unit 1300 may store data obtained from the input unit 1400a, data obtained from the communication unit 1100, output data from the learning processor unit 1400c, and data obtained from the sensing unit 1400. Also, the memory unit 1300 may store control information and/or software codes required for operation/execution of the controller 1200 .

The input unit 1400a may acquire various types of data from the outside of the AI device 1000. For example, the input unit 1200 may obtain learning data for model learning and input data to which the learning model is to be applied. The input unit 1400a may include a camera, a microphone, and/or a user input unit. The output unit 1400b may generate an output related to sight, hearing, or touch. The output unit 1400b may include a display unit, a speaker, and/or a haptic module. The sensing unit 1400 may obtain at least one of internal information of the AI device 1000, surrounding environment information of the AI device 1000, and user information by using various sensors. The sensing unit 1400 may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an RGB sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, an optical sensor, a microphone, and/or a radar. there is.

The learning processor unit 1400c may learn a model composed of an artificial neural network using learning data. The running processor unit 1400c may perform AI processing together with the running processor unit of the AI server (FIG. 32, 4000). The learning processor unit 1400c may process information received from an external device through the communication unit 1100 and/or information stored in the memory unit 1300 . In addition, the output value of the learning processor unit 1400c may be transmitted to an external device through the communication unit 1100 and/or stored in the memory unit 1300.

The embodiments described above are those in which elements and features of the present invention are combined in a predetermined form. Each component or feature should be considered optional unless explicitly stated otherwise. Each component or feature may be implemented in a form not combined with other components or features. In addition, it is also possible to configure an embodiment of the present invention by combining some components and/or features. The order of operations described in the embodiments of the present invention may be changed. Some components or features of one embodiment may be included in another embodiment, or may be replaced with corresponding components or features of another embodiment. It is obvious that claims that do not have an explicit citation relationship in the claims can be combined to form an embodiment or can be included as new claims by amendment after filing.

An embodiment according to the present invention may be implemented by various means, for example, hardware, firmware, software, or a combination thereof. In the case of hardware implementation, one embodiment of the present invention provides one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), FPGAs ( field programmable gate arrays), processors, controllers, microcontrollers, microprocessors, etc.

In the case of implementation by firmware or software, an embodiment of the present invention may be implemented in the form of a module, procedure, or function that performs the functions or operations described above. The software code can be stored in memory and run by a processor. The memory may be located inside or outside the processor and exchange data with the processor by various means known in the art.

It is apparent to those skilled in the art that the present invention can be embodied in other specific forms without departing from the essential characteristics of the present invention. Accordingly, the foregoing detailed description should not be construed as limiting in all respects and should be considered illustrative. The scope of the present invention should be determined by reasonable interpretation of the appended claims, and all changes within the equivalent scope of the present invention are included in the scope of the present invention.

The method for transmitting and receiving high-frequency band uplink signals in the wireless communication system of this specification has been described focusing on examples applied to 3GPP LTE / LTE-A system and 5G system (New RAT system), but applied to various wireless communication systems It is possible.

Claims (19)

A method for reflecting an uplink signal of a high frequency band in a wireless communication system, the method performed by a reflecting device,
Transmitting signal information including information on reception strength and information on reception angle to a base station based on a synchronization signal of a low frequency band from a terminal;
Receiving beam pattern information for controlling a reflected beam of a high frequency band based on the signal information from the base station; and
and transmitting the uplink signal of the high frequency band received from the terminal to the base station based on the reflected beam of the high frequency band. According to claim 1,
The low frequency band is a band of 6 gigahertz (GHz) or less,
The high frequency band is a band of 6 gigahertz (GHz) or higher. According to claim 1,
The beam pattern information includes information on a beam pattern index and information on a beam pattern application time. According to claim 1,
receiving measurement request information for the synchronization signal of the low frequency band from the base station; and
The method further comprising receiving the synchronization signal of the low frequency band from the terminal. According to claim 4,
The measurement request information includes resource information of the synchronization signal of the low frequency band. A reflector for reflecting an uplink signal of a high frequency band in a wireless communication system,
one or more metaplanes;
one or more transceivers;
one or more processors operatively coupled with the one or more metaplanes and the one or more transceivers;
comprising one or more memories functionally coupled to the one or more processors and storing instructions for performing operations;
These actions are
Transmitting signal information including information on the reception strength and information on the reception angle to a base station based on a synchronization signal of a low frequency band from a terminal;
Receiving beam pattern information for controlling a reflected beam of a high frequency band based on the signal information from the base station; and
and transmitting the uplink signal of the high frequency band received from the terminal to the base station based on the reflected beam of the high frequency band. A method for controlling a reflected beam of a high frequency band of a reflector in a wireless communication system, the method performed by a base station, comprising:
requesting signal information including information on reception strength and information on reception angles of a synchronization signal in a low frequency band from a plurality of reflecting devices;
receiving the signal information from the plurality of reflecting devices; and
and transmitting beam pattern information for controlling a reflected beam of the high frequency band to the reflecting device based on the signal information. According to claim 7,
The low frequency band is a band of 6 gigahertz (GHz) or less,
The high frequency band is a band of 6 gigahertz (GHz) or less. According to claim 7,
The beam pattern information includes information on a beam pattern index and information on a beam pattern application time. According to claim 9,
The beam pattern information is transmitted to the reflecting device having a value greater than a predetermined receiving intensity among the plurality of reflecting devices,
The information on the beam pattern index is determined based on the reception angle of the reflecting device. According to claim 7,
Receiving resource request information for the high frequency band from a terminal; and
The method further comprising transmitting transmission request information for the synchronization signal of the low frequency band to the terminal. According to claim 11,
The transmission request information includes resource information for the synchronization signal of the low frequency band. According to claim 7,
The method further comprises transmitting measurement request information for the synchronization signal of the low frequency band to the plurality of reflecting devices. In a base station for controlling a reflected beam of a high frequency band of a reflector in a wireless communication system,
one or more transceivers;
one or more processors operatively coupled with the one or more transceivers;
comprising one or more memories functionally coupled to the one or more processors and storing instructions for performing operations;
These actions are
requesting signal information including information on reception strength and information on reception angles of a synchronization signal in a low frequency band from a plurality of reflecting devices;
receiving the signal information from the plurality of reflecting devices; and
and transmitting beam pattern information for controlling a reflected beam of the high frequency band to the reflector based on the signal information. In a method for receiving resource information for a high frequency band in a wireless communication system, the method performed by a terminal comprises:
Transmitting resource request information for the high frequency band to a base station;
Receiving transmission request information for a synchronization signal of a low frequency band from the base station;
Transmitting the synchronization signal of the low frequency band; and
Receiving resource information for the high frequency band from the base station based on the synchronization signal of the low frequency band,
The resource information for the high frequency band is received after the reflection beam of the high frequency band of the reflector is determined. According to claim 15,
The low frequency band is a band of 6 gigahertz (GHz) or less,
The high frequency band is a band of 6 gigahertz (GHz) or less. According to claim 15,
The reflected beam of the high frequency band,
A method determined based on beam pattern information including information on a beam pattern index and information on a beam pattern application time. According to claim 17,
The beam pattern information is determined based on the synchronization signal of the low frequency band. In a terminal receiving a resource of a high frequency band in a wireless communication system,
one or more transceivers;
one or more processors operatively coupled with the one or more transceivers;
comprising one or more memories functionally coupled to the one or more processors and storing instructions for performing operations;
These actions are
Transmitting resource request information for the high frequency band to a base station;
Receiving transmission request information for a synchronization signal of a low frequency band from the base station;
Transmitting the synchronization signal of the low frequency band; and
Receiving resource information for the high frequency band from the base station based on the synchronization signal of the low frequency band,
The resource information for the high frequency band is received after a reflection beam of the high frequency band of the reflector is determined.

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