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WO2025211465A1 - Procédé et appareil de transmission et de réception de signal dans un système de communication sans fil - Google Patents

Procédé et appareil de transmission et de réception de signal dans un système de communication sans fil

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Publication number
WO2025211465A1
WO2025211465A1 PCT/KR2024/004169 KR2024004169W WO2025211465A1 WO 2025211465 A1 WO2025211465 A1 WO 2025211465A1 KR 2024004169 W KR2024004169 W KR 2024004169W WO 2025211465 A1 WO2025211465 A1 WO 2025211465A1
Authority
WO
WIPO (PCT)
Prior art keywords
signal
rat
information
wireless
present disclosure
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/KR2024/004169
Other languages
English (en)
Korean (ko)
Inventor
정재훈
박준범
김성민
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
LG Electronics Inc
Korea Advanced Institute of Science and Technology KAIST
Original Assignee
LG Electronics Inc
Korea Advanced Institute of Science and Technology KAIST
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by LG Electronics Inc, Korea Advanced Institute of Science and Technology KAIST filed Critical LG Electronics Inc
Priority to PCT/KR2024/004169 priority Critical patent/WO2025211465A1/fr
Publication of WO2025211465A1 publication Critical patent/WO2025211465A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/12—Wireless traffic scheduling
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W74/00—Wireless channel access
    • H04W74/08—Non-scheduled access, e.g. ALOHA
    • H04W74/0833—Random access procedures, e.g. with 4-step access

Definitions

  • the present disclosure relates to a method and device for transmitting and receiving signals between heterogeneous communication devices in a wireless communication system. Specifically, the present disclosure relates to a method and device for transmitting and receiving signals between heterogeneous communication devices using a simulated signal.
  • Wireless access systems are widely deployed to provide various types of communication services, such as voice and data.
  • wireless access systems are multiple access systems that support communications with multiple users by sharing available system resources (e.g., bandwidth, transmission power).
  • multiple access systems include code division multiple access (CDMA), frequency division multiple access (FDMA), time division multiple access (TDMA), orthogonal frequency division multiple access (OFDMA), and single-carrier frequency division multiple access (SC-FDMA).
  • CDMA code division multiple access
  • FDMA frequency division multiple access
  • TDMA time division multiple access
  • OFDMA orthogonal frequency division multiple access
  • SC-FDMA single-carrier frequency division multiple access
  • interference signals from different wireless protocols can degrade communication quality.
  • the 6 GHz band is currently used by WiFi 6E
  • interference from WiFi 6E signals can degrade NR (New Radio) communication quality.
  • NR New Radio
  • the technology to address these issues between heterogeneous communication networks can be defined as spectrum sharing. Because spectrum sharing between NR and WiFi has not been actively discussed in the past, further discussion is needed.
  • the present disclosure provides a device and method for performing signal transmission and reception in a wireless communication system.
  • the first imitation signal may include signal length information for transmitting the data signal.
  • the length information may be a value obtained by subtracting one symbol length from an integer multiple of a Transmission Time Interval (TTI) of the first RAT.
  • TTI Transmission Time Interval
  • the second simulated signal may include length information about a backoff time that may be additionally performed after the backoff is terminated.
  • the method further includes a step of transmitting configuration information related to the backoff to the terminal, wherein the configuration information related to the backoff may be transmitted via at least one of an RRC reconfiguration message and Downlink Control Information (DCI).
  • DCI Downlink Control Information
  • a method performed by a second node supporting a second radio access technology (RAT) in a wireless communication system includes the steps of receiving a data signal including at least one simulated signal based on the second RAT from a first node supporting the first RAT, and performing a back-off for the second RAT based on the data signal, wherein the first simulated signal may be included in a first symbol of the data signal, and the second simulated signal may be included in a last symbol of the data signal.
  • RAT radio access technology
  • FIG. 2 is a diagram illustrating the system structure of a New Generation Radio Access Network (NG-RAN).
  • NG-RAN New Generation Radio Access Network
  • Figure 11 is a schematic diagram illustrating an example of a neural network structure in which a recurrent loop exists.
  • Figure 12 is a diagram schematically illustrating an example of the operating structure of a recurrent neural network.
  • Figure 13 is a diagram illustrating an example of the electromagnetic spectrum.
  • FIG. 16 is a diagram illustrating an example of a method for generating a THz signal based on an optical element.
  • Fig. 18 is a diagram illustrating the structure of a photon source-based transmitter.
  • Figure 19 is a drawing showing the structure of an optical modulator.
  • Figure 20 is a diagram for explaining cross-technology communication.
  • Figure 21 is a diagram for explaining heterogeneous communication technologies between NR and WiFi.
  • FIG. 22 is a drawing for explaining an example of symbol arrangement applicable to the present disclosure.
  • FIG. 23 is a drawing for explaining an SSB (Synchronization Signal Block) applicable to the present disclosure.
  • SSB Synchronization Signal Block
  • FIG. 24 is a diagram for explaining resource allocation of reference signals applicable to the present disclosure.
  • FIG. 25 is another diagram for explaining resource allocation of reference signals applicable to the present disclosure.
  • Figure 26 is a drawing for explaining a simulated signal applicable to the present disclosure.
  • Figure 28 is a diagram for explaining the control plane protocol.
  • FIG. 32 illustrates a communication system (1) applicable to various embodiments of the present disclosure.
  • FIG. 33 illustrates a wireless device that can be applied to various embodiments of the present disclosure.
  • FIG. 34 illustrates another example of a wireless device that can be applied to various embodiments of the present disclosure.
  • Figure 35 illustrates a signal processing circuit for a transmission signal.
  • FIG. 36 illustrates another example of a wireless device applicable to various embodiments of the present disclosure.
  • FIG. 37 illustrates a portable device applicable to various embodiments of the present disclosure.
  • FIG. 38 illustrates a vehicle or autonomous vehicle applicable to various embodiments of the present disclosure.
  • FIG. 39 illustrates a vehicle applicable to various embodiments of the present disclosure.
  • FIG. 41 illustrates a robot applicable to various embodiments of the present disclosure.
  • FIG. 42 illustrates an AI device applicable to various embodiments of the present disclosure.
  • a or B may mean “only A,” “only B,” or “both A and B.” In other words, in various embodiments of the present disclosure, “A or B” may be interpreted as “A and/or B.” For example, in various embodiments of the present disclosure, “A, B or C” may mean “only A,” “only B,” “only C,” or “any combination of A, B and C.”
  • “at least one of A, B and C” can mean “only A,” “only B,” “only C,” or “any combination of A, B and C.” Additionally, “at least one of A, B or C” or “at least one of A, B and/or C” can mean “at least one of A, B and C.”
  • CDMA can be implemented using wireless technologies such as UTRA (Universal Terrestrial Radio Access) or CDMA2000.
  • TDMA can be implemented using wireless technologies such as GSM (Global System for Mobile communications)/GPRS (General Packet Radio Service)/EDGE (Enhanced Data Rates for GSM Evolution).
  • OFDMA can be implemented using wireless technologies such as IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802-20, and E-UTRA (Evolved UTRA).
  • UTRA is a part of UMTS (Universal Mobile Telecommunications System).
  • 3GPP 3rd Generation Partnership Project
  • LTE Long Term Evolution
  • E-UMTS Evolved UMTS
  • LTE-A Advanced/LTE-A pro
  • 3GPP NR New Radio or New Radio Access Technology
  • 3GPP 6G may be an evolved version of 3GPP NR.
  • LTE refers to technology after 3GPP TS 36.xxx Release 8.
  • LTE technology after 3GPP TS 36.xxx Release 10 is referred to as LTE-A
  • LTE technology after 3GPP TS 36.xxx Release 13 is referred to as LTE-A pro
  • 3GPP NR refers to technology after TS 38.
  • 3GPP 6G may refer to technology after TS Release 17 and/or Release 18.
  • “xxx” refers to a standard document detail number.
  • LTE/NR/6G may be collectively referred to as a 3GPP system.
  • RRC Radio Resource Control
  • Figure 1 is a diagram illustrating an example of physical channels and general signal transmission used in a 3GPP system.
  • a terminal receives information from a base station via the downlink (DL) and transmits it to the base station via the uplink (UL).
  • the information transmitted and received between the base station and the terminal includes data and various control information, and various physical channels exist depending on the type and purpose of the information being transmitted and received.
  • a terminal When a terminal is powered on or enters a new cell, it performs an initial cell search operation, such as synchronizing with the base station (S11). To this end, the terminal receives 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. Afterwards, the terminal can receive a Physical Broadcast Channel (PBCH) from the base station to obtain broadcast information within the cell. Meanwhile, the terminal can receive a Downlink Reference Signal (DL RS) during the initial cell search phase to check the downlink channel status.
  • PSS Primary Synchronization Signal
  • SSS Secondary Synchronization Signal
  • PBCH Physical Broadcast Channel
  • DL RS Downlink Reference Signal
  • the terminal that has performed the procedure described above can then perform PDCCH/PDSCH reception (S17) and physical uplink shared channel (PUSCH)/physical uplink control channel (PUCCH) transmission (S18) as general uplink/downlink signal transmission procedures.
  • the terminal can receive downlink control information (DCI) through the PDCCH.
  • DCI downlink control information
  • the DCI includes control information such as resource allocation information for the terminal, and different formats can be applied depending on the purpose of use.
  • control information that the terminal transmits to the base station via the uplink or that the terminal receives from the base station may include downlink/uplink ACK/NACK signals, CQI (Channel Quality Indicator), PMI (Precoding Matrix Index), RI (Rank Indicator), etc.
  • the terminal may transmit the above-described control information such as CQI/PMI/RI via PUSCH and/or PUCCH.
  • the base station transmits a related signal to the terminal through a downlink channel described below, and the terminal receives the related signal from the base station through a downlink channel described below.
  • PDSCH Physical Downlink Shared Channel
  • PDSCH carries downlink data (e.g., DL-shared channel transport block, DL-SCH TB) and applies modulation methods such as Quadrature Phase Shift Keying (QPSK), 16 Quadrature Amplitude Modulation (QAM), 64 QAM, and 256 QAM.
  • Codewords are generated by encoding the TBs.
  • 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 resources along with a Demodulation Reference Signal (DMRS), generated as an OFDM symbol signal, and transmitted through the corresponding antenna port.
  • DMRS Demodulation Reference Signal
  • the PDCCH carries downlink control information (DCI) and employs modulation methods such as QPSK.
  • DCI downlink control information
  • a PDCCH consists of 1, 2, 4, 8, or 16 Control Channel Elements (CCEs), depending on the Aggregation Level (AL).
  • CCEs Control Channel Elements
  • Each CCE is comprised of six Resource Element Groups (REGs). Each REG is defined by one OFDM symbol and one (P)RB.
  • PUSCH Physical Uplink Shared Channel
  • new radio access technology new RAT, NR.
  • next-generation communication As more and more communication devices demand greater communication capacity, the need for improved mobile broadband communication compared to existing radio access technology (RAT) is emerging.
  • massive Machine Type Communications (MTC) which connects numerous devices and objects to provide various services anytime, anywhere, is also a key issue to be considered in next-generation communication.
  • communication system design that considers reliability and latency-sensitive services/terminals is being discussed.
  • next-generation radio access technologies that take into account enhanced mobile broadband communication, massive MTC, and URLLC (Ultra-Reliable and Low Latency Communication) is being discussed, and in various embodiments of the present disclosure, such technologies are conveniently referred to as new RAT or NR.
  • FIG. 2 is a diagram illustrating the system structure of a New Generation Radio Access Network (NG-RAN).
  • NG-RAN New Generation Radio Access Network
  • the gNB can provide functions such as inter-cell radio resource management (Inter Cell RRM), radio bearer management (RB control), connection mobility control (Connection Mobility Control), radio admission control (Radio Admission Control), measurement configuration and provision, and dynamic resource allocation.
  • the AMF can provide functions such as NAS security and idle state mobility processing.
  • the UPF can provide functions such as mobility anchoring and PDU processing.
  • the SMF Session Management Function
  • Figure 4 is a diagram illustrating an example of a 5G usage scenario.
  • the 5G usage scenario illustrated in FIG. 4 is merely exemplary, and the technical features of various embodiments of the present disclosure can also be applied to other 5G usage scenarios not illustrated in FIG. 4.
  • the three key requirement areas for 5G include (1) enhanced mobile broadband (eMBB), (2) massive machine type communication (mMTC), and (3) ultra-reliable and low latency communications (URLLC).
  • eMBB enhanced mobile broadband
  • mMTC massive machine type communication
  • URLLC ultra-reliable and low latency communications
  • KPI key performance indicator
  • eMBB focuses on improving data speeds, latency, user density, and overall capacity and coverage of mobile broadband connections. It targets throughputs of around 10 Gbps. eMBB significantly exceeds basic mobile internet access, enabling rich interactive experiences, media and entertainment applications in the cloud, and augmented reality. Data is a key driver of 5G, and for the first time, dedicated voice services may not be available in the 5G era. In 5G, voice is expected to be handled as an application, simply using the data connection provided by the communication system. The increased traffic volume is primarily due to the increasing content size and the growing number of applications that require high data rates. Streaming services (audio and video), interactive video, and mobile internet connectivity will become more prevalent as more devices connect to the internet.
  • Cloud storage and applications are rapidly growing on mobile communication platforms, and this can be applied to both work and entertainment.
  • Cloud storage is a particular use case driving the growth of uplink data rates.
  • 5G is also used for remote work in the cloud, requiring significantly lower end-to-end latency to maintain a superior user experience when tactile interfaces are used.
  • cloud gaming and video streaming are other key factors driving the demand for mobile broadband.
  • Entertainment is essential on smartphones and tablets, regardless of location, including in highly mobile environments like trains, cars, and airplanes.
  • Another use case is augmented reality and information retrieval for entertainment, where augmented reality requires extremely low latency and instantaneous data volumes.
  • mMTC is designed to enable communication between a large number of low-cost, battery-powered devices, supporting applications such as smart metering, logistics, field, and body sensors.
  • mMTC targets a battery life of approximately 10 years and/or a population of approximately 1 million devices per square kilometer.
  • mMTC enables seamless connectivity of embedded sensors across all sectors and is one of the most anticipated 5G use cases.
  • the number of IoT devices is projected to reach 20.4 billion by 2020.
  • Industrial IoT is one area where 5G will play a key role, enabling smart cities, asset tracking, smart utilities, agriculture, and security infrastructure.
  • URLLC is ideal for vehicle communications, industrial control, factory automation, remote surgery, smart grids, and public safety applications by enabling devices and machines to communicate with high reliability, very low latency, and high availability.
  • URLLC targets latency on the order of 1 ms.
  • URLLC encompasses new services that will transform industries through ultra-reliable, low-latency links, such as remote control of critical infrastructure and autonomous vehicles. This level of reliability and latency is essential for smart grid control, industrial automation, robotics, and drone control and coordination.
  • Automotive is expected to be a significant new driver for 5G, with numerous use cases for in-vehicle mobile communications. For example, passenger entertainment demands both high capacity and high mobile broadband, as future users will consistently expect high-quality connectivity regardless of their location and speed.
  • Another automotive application is augmented reality dashboards.
  • An AR dashboard allows drivers to identify objects in the dark on top of what they see through the windshield. The AR dashboard overlays information to inform the driver about the distance and movement of objects.
  • wireless modules will enable vehicle-to-vehicle communication, information exchange between vehicles and supporting infrastructure, and information exchange between vehicles and other connected devices (e.g., devices accompanying pedestrians).
  • Safety systems can guide drivers to safer driving behaviors, reducing the risk of accidents.
  • the next step will be remotely controlled or autonomous vehicles, which require highly reliable and fast communication between different autonomous vehicles and/or between vehicles and infrastructure.
  • autonomous vehicles will perform all driving tasks, leaving drivers to focus solely on traffic anomalies that the vehicle itself cannot detect.
  • the technological requirements for autonomous vehicles will require ultra-low latency and ultra-high-speed reliability, increasing traffic safety to levels unattainable by humans.
  • Smart cities and smart homes often referred to as smart societies, will be embedded with dense wireless sensor networks.
  • a distributed network of intelligent sensors will identify conditions for cost- and energy-efficient maintenance of cities or homes. Similar setups can be implemented for individual homes.
  • Temperature sensors, window and heating controllers, burglar alarms, and appliances will all be wirelessly connected. Many of these sensors typically require low data rates, low power, and low cost. However, for example, real-time HD video may be required from certain types of devices for surveillance purposes.
  • Smart grids interconnect these sensors using digital information and communication technologies to collect and act on information. This information can include the behavior of suppliers and consumers, enabling smart grids to improve efficiency, reliability, economic efficiency, sustainable production, and the automated distribution of fuels like electricity. Smart grids can also be viewed as another low-latency sensor network.
  • Telecommunications systems can support telemedicine, which provides clinical care in remote locations. This can help reduce distance barriers and improve access to health services that are otherwise unavailable in remote rural areas. It can also be used to save lives in critical care and emergency situations.
  • Mobile-based wireless sensor networks can provide remote monitoring and sensors for parameters such as heart rate and blood pressure.
  • Wireless and mobile communications are becoming increasingly important in industrial applications. Wiring is expensive to install and maintain. Therefore, the potential to replace cables with reconfigurable wireless links presents an attractive opportunity for many industries. However, achieving this requires wireless connections to operate with similar latency, reliability, and capacity to cables, while simplifying their management. Low latency and extremely low error rates are new requirements for 5G connectivity.
  • Logistics and freight tracking are important use cases for mobile communications, enabling the tracking of inventory and packages anywhere using location-based information systems. Logistics and freight tracking typically require low data rates but may require wide-range and reliable location information.
  • next-generation communications e.g., 6G
  • 6G next-generation communications
  • the 6G (wireless communication) system aims to achieve (i) very high data rates per device, (ii) a very large number of connected devices, (iii) global connectivity, (iv) very low latency, (v) low energy consumption for battery-free IoT devices, (vi) ultra-reliable connectivity, and (vii) connected intelligence with machine learning capabilities.
  • the vision of the 6G system can be divided into four aspects: intelligent connectivity, deep connectivity, holographic connectivity, and ubiquitous connectivity, and the 6G system can satisfy the requirements as shown in Table 1 below.
  • Table 1 is a table showing an example of the requirements of a 6G system.
  • Figure 5 is a diagram illustrating an example of a communication structure that can be provided in a 6G system.
  • 6G systems are expected to have 50 times the simultaneous wireless connectivity of 5G systems.
  • URLLC a key feature of 5G, will become even more crucial in 6G communications by providing end-to-end latency of less than 1 ms.
  • 6G systems will have significantly higher volumetric spectral efficiency, compared to the commonly used area spectral efficiency.
  • 6G systems can offer extremely long battery life and advanced battery technologies for energy harvesting, eliminating the need for separate charging for mobile devices in 6G systems.
  • New network characteristics in 6G may include:
  • 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.
  • WIET wireless information and energy transfer
  • Ultra-dense heterogeneous networks will be another key feature of 6G communication systems.
  • Multi-tier networks comprised of heterogeneous networks improve overall QoS and reduce costs.
  • High-capacity backhaul Backhaul connections are characterized by high-capacity backhaul networks to support high-volume traffic.
  • High-speed fiber optics and free-space optics (FSO) systems may be potential solutions to this problem.
  • High-precision localization (or location-based services) through communications is a key feature of 6G wireless communication systems. Therefore, radar systems will be integrated with 6G networks.
  • Softwarization and virtualization are two critical features that form the foundation of the design process for 5GB networks to ensure flexibility, reconfigurability, and programmability. Furthermore, billions of devices can be shared on a shared physical infrastructure.
  • AI can also play a crucial role in machine-to-machine (M2M), machine-to-human, and human-to-machine communications. Furthermore, AI can facilitate rapid communication in brain-computer interfaces (BCIs). AI-based communication systems can be supported by metamaterials, intelligent structures, intelligent networks, intelligent devices, intelligent cognitive radios, self-sustaining wireless networks, and machine learning.
  • M2M machine-to-machine
  • BCIs brain-computer interfaces
  • AI-based physical layer transmission refers to the application of AI-based signal processing and communication mechanisms, rather than traditional communication frameworks, in the fundamental signal processing and communication mechanisms. For example, this may include deep learning-based channel coding and decoding, deep learning-based signal estimation and detection, deep learning-based MIMO mechanisms, and AI-based resource scheduling and allocation.
  • Machine learning can be used for channel estimation and channel tracking, as well as for power allocation and interference cancellation in the physical layer of the downlink (DL). Furthermore, machine learning can be used for antenna selection, power control, and symbol detection in MIMO systems.
  • Deep learning-based AI algorithms require a large amount of training data to optimize training parameters.
  • a large amount of training data is used offline. This means that static training on training data in specific channel environments can lead to conflicts with the dynamic characteristics and diversity of the wireless channel.
  • Machine learning refers to a series of operations that train machines to perform tasks that humans can or cannot perform. Machine learning requires data and a learning model. Data learning methods in machine learning can be broadly categorized into three types: supervised learning, unsupervised learning, and reinforcement learning.
  • Neural network training aims to minimize output errors. It involves repeatedly inputting training data into a neural network, calculating the neural network output and target error for the training data, and backpropagating the neural network error from the output layer to the input layer to update the weights of each node in the neural network to reduce the error.
  • Supervised learning uses labeled training data, while unsupervised learning may not have labeled training data.
  • the training data may be data in which each training data category is labeled.
  • Labeled training data is input to a neural network, and the error can be calculated by comparing the output (categories) of the neural network with the training data labels.
  • the calculated error is backpropagated through the neural network in the backward direction (i.e., from the output layer to the input layer), and the connection weights of each node in each layer of the neural network can be updated through backpropagation.
  • the amount of change in the connection weights of each updated node can be determined by the learning rate.
  • Learning methods may vary depending on the characteristics of the data. For example, if the goal is to accurately predict data transmitted by a transmitter in a communication system, supervised learning is preferable to unsupervised learning or reinforcement learning.
  • the learning model corresponds to the human brain, and the most basic linear model can be thought of, but the machine learning paradigm that uses highly complex neural network structures, such as artificial neural networks, as learning models is called deep learning.
  • Figure 6 is a schematic diagram illustrating an example of a perceptron structure.
  • a large-scale artificial neural network structure can extend the simplified perceptron structure illustrated in Fig. 6 to apply the input vector to perceptrons of different dimensions. For convenience of explanation, input values or output values are called nodes.
  • the perceptron structure illustrated in Fig. 6 can be explained as consisting of a total of three layers based on input and output values.
  • An artificial neural network in which there are H perceptrons of (d+1) dimensions between the 1st layer and the 2nd layer, and K perceptrons of (H+1) dimensions between the 2nd layer and the 3rd layer can be expressed as in Fig. 7.
  • Figure 7 is a schematic diagram illustrating an example of a multilayer perceptron structure.
  • the aforementioned input, hidden, and output layers can be applied jointly not only to multilayer perceptrons but also to various artificial neural network structures, such as CNNs and RNNs, which will be described later.
  • the machine learning paradigm that uses sufficiently deep artificial neural networks as learning models is called deep learning.
  • the artificial neural network used for deep learning is called a deep neural network (DNN).
  • Figure 8 is a schematic diagram illustrating an example of a deep neural network.
  • the deep neural network illustrated in Figure 8 is a multilayer perceptron consisting of eight hidden layers and eight output layers.
  • the multilayer perceptron structure is referred to as a fully connected neural network.
  • a fully connected neural network there is no connection between nodes located in the same layer, and there is a connection only between nodes located in adjacent layers.
  • DNN has a fully connected neural network structure and is composed of a combination of multiple hidden layers and activation functions, and can be usefully applied to identify correlation characteristics between inputs and outputs.
  • the correlation characteristic can mean the joint probability of inputs and outputs.
  • Figure 9 is a schematic diagram illustrating an example of a convolutional neural network.
  • Fig. 9 can assume a case where nodes are arranged two-dimensionally, with w nodes in width and h nodes in height (the convolutional neural network structure of Fig. 9).
  • a weight is added to each connection in the connection process from one input node to the hidden layer, a total of h ⁇ w weights must be considered. Since there are h ⁇ w nodes in the input layer, a total of h2w2 weights are required between two adjacent layers.
  • Each filter has a weight corresponding to its size, and weight learning can be performed to extract and output a specific feature on the image as a factor.
  • weight learning can be performed to extract and output a specific feature on the image as a factor.
  • a 3x3 filter is applied to the upper left 3x3 region of the input layer, and the output value resulting from performing weighted sum and activation function operations on the corresponding node is stored in z22.
  • the above filter performs weighted sum and activation function operations while moving at a certain horizontal and vertical interval while scanning the input layer, and places the output value at the current filter position.
  • This operation method is similar to the convolution operation for images in the field of computer vision, so a deep neural network with 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.
  • a neural network with multiple convolutional layers is called a deep convolutional neural network (DCNN).
  • the number of weights can be reduced by calculating a weighted sum that includes only the nodes located in the area covered by the filter, starting from the node where the current filter is located. This allows a single filter to focus on features within a local area. Accordingly, CNNs can be effectively applied to image data processing where physical distance in a two-dimensional area is an important criterion for judgment. Meanwhile, CNNs can apply multiple filters immediately before the convolutional layer, and can generate multiple output results through the convolution operation of each filter.
  • a structure that applies a method of inputting one element of the data sequence at each timestep and inputting the output vector (hidden vector) of the hidden layer output at a specific timestep together with the immediately following element in the sequence is called a recurrent neural network structure.
  • a recurrent neural network is a structure that inputs elements (x1(t), x2(t), ,..., xd(t)) of a data sequence at a time point t into a fully connected neural network, and then inputs the hidden vectors (z1(t-1), z2(t-1),..., zH(t-1)) of the immediately preceding time point t-1 together and applies a weighted sum and activation function.
  • the reason for transmitting the hidden vector to the next time point in this way is because the information in the input vectors of the preceding time points is considered to be accumulated in the hidden vector of the current time point.
  • Figure 12 is a diagram schematically illustrating an example of the operating structure of a recurrent neural network.
  • the recurrent neural network operates in a predetermined order of time for the input data sequence.
  • the hidden vector (z1(1), z2(1),..., zH(1)) is input together with the input vector (x1(2), x2(2),..., xd(2)) at time point 2, and the vector (z1(2), z2(2),..., zH(2)) of the hidden layer is determined through a weighted sum and an activation function. This process is repeatedly performed until time point 2, time point 3, ,,, time point T.
  • Recurrent neural networks are designed to be useful for processing sequence data (e.g., natural language processing).
  • THz waves also known as sub-millimeter waves, typically refer to the frequency range between 0.1 THz and 10 THz, with corresponding wavelengths ranging from 0.03 mm to 3 mm.
  • the 100 GHz to 300 GHz band (sub-THz band) is considered a key part of the THz band for cellular communications. Adding the sub-THz band to the mmWave band will increase the capacity of 6G cellular communications.
  • 300 GHz to 3 THz lies in the far infrared (IR) frequency band. While part of the optical band, the 300 GHz to 3 THz band lies at the boundary of the optical band, immediately following the RF band. Therefore, this 300 GHz to 3 THz band exhibits similarities to RF.
  • Figure 13 is a diagram illustrating an example of the electromagnetic spectrum.
  • THz communications Key characteristics include (i) the widely available bandwidth to support very high data rates and (ii) the high path loss that occurs at high frequencies (requiring highly directional antennas).
  • the narrow beamwidths generated by highly directional antennas reduce interference.
  • the small wavelength of THz signals allows for a significantly larger number of antenna elements to be integrated into devices and base stations operating in this band. This enables the use of advanced adaptive array technologies to overcome range limitations.
  • FSO can be a promising technology for providing backhaul connectivity in 6G systems, in conjunction with fiber-optic networks.
  • FSO supports high-capacity backhaul connectivity for remote and non-remote areas, such as the ocean, space, underwater, and isolated islands.
  • FSO also supports cellular base station (BS) connections.
  • BS base station
  • MIMO technology One of the key technologies for improving spectral efficiency is the application of MIMO technology. As MIMO technology improves, spectral efficiency also improves. Therefore, massive MIMO technology will be crucial in 6G systems. Because MIMO technology utilizes multiple paths, multiplexing technology must be considered to ensure that data signals can be transmitted along more than one path, as well as beam generation and operation technologies suitable for the THz band.
  • Blockchain will become a crucial technology for managing massive amounts of data in future communication systems.
  • Blockchain is a form of distributed ledger technology.
  • a distributed ledger is a database distributed across numerous nodes or computing devices. Each node replicates and stores an identical copy of the ledger.
  • Blockchains are managed by a peer-to-peer network and can exist without being managed by a central authority or server. Data on a blockchain is collected and organized into blocks. Blocks are linked together and protected using cryptography.
  • Blockchain perfectly complements large-scale IoT with its inherently enhanced interoperability, security, privacy, reliability, and scalability. Therefore, blockchain technology offers several features, such as interoperability between devices, traceability of large amounts of data, autonomous interaction with other IoT systems, and the massive connectivity stability of 6G communication systems.
  • 3D BS will be provided via low-orbit satellites and UAVs. Adding a new dimension in altitude and associated degrees of freedom, 3D connections differ significantly from existing 2D networks.
  • Tight integration of multiple frequencies and heterogeneous communication technologies is crucial in 6G systems. As a result, users will be able to seamlessly move from one network to another without requiring any manual configuration on their devices. The best network will be automatically selected from available communication technologies. This will break the limitations of the cell concept in wireless communications. Currently, user movement from one cell to another in dense networks results in excessive handovers, resulting in handover failures, handover delays, data loss, and a ping-pong effect. 6G cell-free communications will overcome all of these challenges and provide better QoS. Cell-free communications will be achieved through multi-connectivity and multi-tier hybrid technologies, as well as heterogeneous radios on devices.
  • Autonomous wireless networks are capable of continuously sensing dynamically changing environmental conditions and exchanging information between different nodes.
  • sensing will be tightly integrated with communications to support autonomous systems.
  • each access network will be connected to backhaul connections, such as fiber optics and FSO networks. To accommodate the massive number of access networks, there will be tight integration between access and backhaul networks.
  • Beamforming is a signal processing procedure that adjusts an antenna array to transmit a wireless signal in a specific direction. It is a subset of smart antennas or advanced antenna systems. Beamforming technology offers several advantages, including high signal-to-noise ratio, interference avoidance and rejection, and high network efficiency.
  • Holographic beamforming (HBF) is a novel beamforming method that differs significantly from MIMO systems because it uses software-defined antennas. HBF will be a highly effective approach for efficient and flexible signal transmission and reception in multi-antenna communication devices in 6G.
  • THz-band signals have strong linearity, which can create many shadow areas due to obstacles.
  • LIS technology which enables expanded communication coverage, enhanced communication stability, and additional value-added services by installing LIS near these shadow areas, is becoming increasingly important.
  • LIS is an artificial surface made of electromagnetic materials that can alter the propagation of incoming and outgoing radio waves. While LIS can be viewed as an extension of massive MIMO, it differs from massive MIMO in its array structure and operating mechanism. Furthermore, LIS operates as a reconfigurable reflector with passive elements, passively reflecting signals without using active RF chains, which offers the advantage of low power consumption. Furthermore, because each passive reflector in LIS must independently adjust the phase shift of the incoming signal, this can be advantageous for wireless communication channels. By appropriately adjusting the phase shift via the LIS controller, the reflected signal can be collected at the target receiver to boost the received signal power.
  • THz Terahertz
  • the frequency bands expected to be used for THz wireless communication may be the D-band (110 GHz to 170 GHz) or H-band (220 GHz to 325 GHz), which have low propagation loss due to molecular absorption in the air. Discussions on standardization of THz wireless communication are being centered around the IEEE 802.15 THz working group in addition to 3GPP, and standard documents issued by the IEEE 802.15 Task Group (TG3d, TG3e) may specify or supplement the contents described in various embodiments of the present disclosure. THz wireless communication can be applied to wireless cognition, sensing, imaging, wireless communication, THz navigation, etc.
  • THz wireless communication scenarios can be categorized into macro networks, micro networks, and nanoscale networks.
  • THz wireless communication can be applied to vehicle-to-vehicle and backhaul/fronthaul connections.
  • THz wireless communication can be applied to fixed point-to-point or multi-point connections, such as indoor small cells, wireless connections in data centers, and near-field communications, such as kiosk downloads.
  • Methods for generating THz using electronic components include a method using semiconductor components such as a resonant tunneling diode (RTD), a method using a local oscillator and a multiplier, a MMIC (Monolithic Microwave Integrated Circuits) method using an integrated circuit based on a compound semiconductor HEMT (High Electron Mobility Transistor), and a method using a Si-CMOS-based integrated circuit.
  • a multiplier doubler, tripler, multiplier
  • a multiplier is essential.
  • the multiplier is a circuit that has an output frequency that is N times that of the input, and matches it to the desired harmonic frequency and filters out all remaining frequencies.
  • beamforming can be implemented by applying an array antenna or the like to the antenna of Fig. 15.
  • IF represents intermediate frequency
  • tripler and multiplexer represent multipliers
  • PA represents power amplifier
  • LNA low noise amplifier
  • PLL phase-locked loop.
  • Fig. 17 is a diagram illustrating an example of an optical element-based THz wireless communication transceiver.
  • an optical coupler refers to a semiconductor device that transmits an electrical signal using optical waves to provide electrical isolation and coupling between circuits or systems
  • a UTC-PD Uni-Travelling Carrier Photo-Detector
  • the UTC-PD is capable of detecting light at 150 GHz or higher.
  • an EDFA Erbium-Doped Fiber Amplifier
  • a PD Photo Detector
  • an OSA optical module (Optical Sub Assembly) that modularizes various optical communication functions (photoelectric conversion, electro-optical conversion, etc.) into a single component
  • a DSO represents a digital storage oscilloscope.
  • the phase of a signal can be changed by passing the optical source of a laser through an optical wave guide. At this time, data is loaded by changing the electrical characteristics through a microwave contact, etc. Therefore, the optical modulator output is formed as a modulated waveform.
  • An opto-electrical modulator (O/E converter) can generate THz pulses by optical rectification operation by a nonlinear crystal, photoelectric conversion by a photoconductive antenna, emission from a bunch of relativistic electrons, etc. Terahertz pulses generated in the above manner can have a length in units of femtoseconds to picoseconds.
  • An optical/electronic converter (O/E converter) performs down conversion by utilizing the non-linearity of the device.
  • the available bandwidth can be classified based on the oxygen attenuation of 10 ⁇ 2 dB/km in the spectrum up to 1 THz. Accordingly, a framework in which the available bandwidth is composed of multiple band chunks can be considered. As an example of the above framework, if the THz pulse length for one carrier is set to 50 ps, the bandwidth (BW) becomes approximately 20 GHz.
  • a terahertz transmission and reception system can be implemented using a single optical-to-electrical converter.
  • the number of optical-to-electrical converters may be equal to the number of carriers. This phenomenon will be particularly noticeable in a multi-carrier system that utilizes multiple broadbands according to the aforementioned spectrum usage plan.
  • a frame structure for the multi-carrier system may be considered.
  • a signal down-converted using an optical-to-electrical converter may be transmitted in a specific resource region (e.g., a specific frame).
  • the frequency domain of the specific resource region may include multiple chunks. Each chunk may be composed of at least one component carrier (CC).
  • the number of wireless devices is estimated to reach approximately 19 billion by 2024, and this explosive growth is expected to continue, driven by the proliferation of various Internet of Things (IoT) applications, such as smart buildings and smart hospitals.
  • IoT Internet of Things
  • Wireless devices are not only increasing in number but also evolving in diversity.
  • Figure 20 is a drawing for explaining heterogeneous communication technology.
  • CTC Cross-Technology Communication
  • various CTCs can be defined for different communication system technologies, and these typically mimic each other's signals, enabling signal transmission and reception between heterogeneous communication systems.
  • FIG 20 illustrates an example of CTC between WiFi and ZigBee.
  • WiFi uses OFDM QAM modulation, and by utilizing appropriate constellation points, a signal similar to ZigBee can be generated. That is, since a specific bit pattern in WiFi can correspond to a specific constellation point, a WiFi signal can be emulated as a ZigBee signal. Accordingly, the signal can be received by a commercial ZigBee device.
  • signals such as Bluetooth can be generated using WiFi, and ZigBee signals can be generated from Bluetooth.
  • the present disclosure describes an example of emulating a WiFi signal via NR, but the scope of the present disclosure is not limited thereto and can be applied to signal transmission and reception between various heterogeneous communication technologies.
  • WiFi can transmit signals by occupying the channel through the Listen-Before-Talk (LBT) method, and the channel status can be monitored through the CCA-ED (Energy Detection) method and the CCA-PD (Preamble Detection) method.
  • LBT Listen-Before-Talk
  • CCA-ED Charge Detection
  • CCA-PD Preamble Detection
  • the MAC layer of the base station includes a dynamic resource scheduler that allocates downlink and uplink physical layer (PHY) resources.
  • the dynamic resource scheduler can be composed of Scheduler Operation, Signaling of Scheduler Decisions, and Measurements to Support Scheduler Operation functions.
  • signals can be scheduled and transmitted in Transmit Time Intervals (TTIs), which are scheduling units.
  • TTIs can mean one slot in NR. Meanwhile, a TTI can be dynamically changed depending on the utilized subcarrier spacing (SCS).
  • SCS subcarrier spacing
  • the present disclosure proposes an NR scheduling method that can improve NR downlink communication quality by efficiently utilizing WiFi signals simulated through NR. Specifically, the present disclosure proposes considerations for the NR scheduling phase when transmitting PDSCH symbols for transmitting simulated signals, a method for performing continuous back-off at a WiFi AP (Access Point), and a method for exchanging information between a terminal and a base station for this purpose.
  • a WiFi AP Access Point
  • NR-U When utilizing unlicensed bands to provide communication services in wireless communications, downlink communication quality may deteriorate due to interference signals from other wireless protocols.
  • NR-U is considering using the 6 GHz band, which has been newly designated as an unlicensed band and offers excellent frequency characteristics and wide bandwidth.
  • WiFi 6E uses the 6 GHz band to provide higher WiFi data transmission rates and speeds, and plans to apply it to applications such as VR/AR, video streaming, and IoT that require high data throughput and low latency over short distances in the future.
  • various wireless protocols, not just WiFi may utilize the 6 GHz band in the future. Therefore, the present disclosure proposes a method for efficiently utilizing WiFi signals simulated by an NR system to ensure efficient spectrum sharing between WiFi 6E and NR-U.
  • the 6 GHz band utilized by WiFi 6E and NR-U can be utilized more efficiently, and based on this, NR-U downlink communication quality can be improved.
  • back-off may refer to an operation in which a base station, AP, or node detects a resource conflict or a medium being busy and delays or stops data transmission for a certain period of time.
  • different heterogeneous communication networks are described as NR and WiFi, respectively, but this is only an example, and NR and WiFi may be replaced with various RATs (Radio Access Technologies).
  • NR and WiFi may be replaced with a first RAT and a second RAT, respectively.
  • the operations of an NR base station and a WiFi AP are described, but this is only an example, and the NR base station and WiFi AP may be replaced with nodes of a communication system.
  • the NR base station and the WiFi AP may be replaced with a first node and a second node, respectively.
  • FIG. 22 is a drawing for explaining an example of symbol arrangement applicable to the present disclosure.
  • Figure 22 illustrates a PDSCH symbol layout combination for mock signal transmission.
  • S represents the starting position
  • L represents the number of symbols. Since essential signals exist for exchanging information between the terminal and the base station, the PDSCH for mock signal transmission must be scheduled with this in mind.
  • the base station can transmit SSB (Synchronization Signal Block) to the terminal at regular intervals according to a preset cycle (5, 10, 20, 40, 80, 160 ms) in downlink transmission.
  • SSB Synchronization Signal Block
  • FIG. 23 is a drawing for explaining an SSB (Synchronization Signal Block) applicable to the present disclosure.
  • SSB Synchronization Signal Block
  • Base stations typically transmit SSB at 20ms intervals, and since the mock signal must utilize all resources corresponding to 106RBs, the mock signal can be allocated to slots where SSB is not transmitted. SSB transmission can begin on the 3rd and 9th symbols within a slot, utilizing four symbols. Additionally, in the unlicensed band, a total of five slots can be used: slot 0, slot 1, slot 2, slot 3, and slot 4.
  • resources can be utilized based on the following mathematical expression 1.
  • NR can utilize four reference signals to enhance the performance and efficiency of communication systems: the Demodulate Reference Signal (DMRS), the Phase-Tracking Reference Signal (PT-RS), the Sounding Reference Signal (SRS), and the Channel State Information - Reference Signal (CSI-RS). Therefore, when allocating resources for PDSCH symbol transmission, the aforementioned reference signals and the PSS/SSS must be considered.
  • DMRS Demodulate Reference Signal
  • PT-RS Phase-Tracking Reference Signal
  • SRS Sounding Reference Signal
  • CSI-RS Channel State Information - Reference Signal
  • FIG. 24 is a diagram for explaining resource allocation of reference signals applicable to the present disclosure.
  • Figure 24 is a diagram illustrating the resource allocation of DMRS.
  • DMRS supports channel estimation and accurate demodulation between terminals and base stations, and can be used by receivers to compensate for distortions such as fading, noise, and interference.
  • the location, structure, and pattern of DMRS can be defined as follows to efficiently utilize resources.
  • I 0 can indicate the starting index of the slot where DRMS begins relative to data.
  • - PDSCH DMRS can be located in the 3rd or 4th OFDM symbol.
  • the PDSCH length can be 3 to 14 OFDM symbols in case of normal CP and 3 to 12 OFDM symbols in case of extended CP.
  • DMRS and PDSCH can be defined as follows.
  • - PDSCH DMRS can be located in the first OFDM symbol.
  • - PDSCH can be transmitted from the 1st to 13th OFDM symbols.
  • - PDSCH length can be 2, 4, or 7 OFDM symbols for normal CP, and 2, 4, or 6 OFDM symbols for extended CP.
  • FIG. 25 is another diagram for explaining resource allocation of reference signals applicable to the present disclosure.
  • FIG 25 is a diagram illustrating resource allocation for PT-RS.
  • PT-RS may be a reference signal used for phase tracking in a wireless communication system. Specifically, PT-RS may be utilized for CSI and phase error compensation. Utilizing PT-RS may improve accurate signal reception and data transmission reliability.
  • PT-RS may be configured via DMRS-DownlinkConfig.
  • L PT-RS may represent time density.
  • CSI-RS is a downlink signal received by a terminal from a base station. It can be used to extract CSI, evaluate and measure the channel, and report to the base station.
  • CSI-RS can be assigned to any symbol or slot, but may not be assigned to symbols/slots assigned for specific purposes.
  • the specific purpose may be at least one of SSB, slots configured for UL in TDD, CORESET, and PDSCH DMRS.
  • a mock signal may be included in the first OFDM symbol and the last OFDM symbol to perform continuous backoff of the WiFi AP.
  • the mock signal placed in the last OFDM symbol can trigger a short backoff from the WiFi AP, allowing the base station to have priority in the LBT backoff.
  • the length information of the last mock signal can contain a value that is probabilistically advantageous in competing with the WiFi AP, rather than a large value.
  • the reason for the small length information may be to enable the WiFi AP in receive mode to detect the mock signal preceding the next scheduled NR signal.
  • the front copy signal may be intended to improve the quality of the scheduled NR data signal, and the back copy signal may be intended to obtain priority when the next channel is occupied.
  • the purpose and length of the first and last symbols may be as follows.
  • Figure 28 is a diagram for explaining the control plane protocol.
  • the control plane protocol between the terminal and the base station can be defined as an L3 layer (NAS, RRC), an L2 layer (PDCP, RLC, MAC), and an L1 layer (PHY), as illustrated in FIG. 28.
  • a method for configuring a control signal for transmitting a mock signal can be proposed as at least one of a semi-static method utilizing RRC settings in the L3 layer and a dynamic method utilizing DCI in a PDCCH symbol in the PHY layer.
  • the RRC layer transmits control signals based on channel and connection status for terminals to communicate with the base station, and can relay, maintain, and manage cell information to terminals.
  • a control signal between a terminal and a base station can be configured by utilizing an RRC reconfiguration message, which is one of the messages defined in the RRC layer.
  • the base station may transmit information on how to transmit a mock signal to the terminal through at least one of PDSCH-Config, PDSCH-ConfigCommon, and PDSCH-TimeDomainResourceAllocationList, and the previously defined reference signal configuration information may also be configured and transmitted using the above information.
  • DCI formats for PDSCH scheduling can be DCI Format 1_0 and DCI Format 1_2.
  • DCI Downlink Control Information
  • DCI can provide terminals with necessary information, such as downlink/uplink resource allocation and HARQ.
  • HARQ Downlink Control Information
  • DCI Format 1_0, 1_1, and 1_2 contain downlink scheduling information, and to support various situations, multiple fields are configured, and these can be utilized after scrambling with RNTI (Radio Network Temporary Identity). It is composed of PDCCH decoding - Parse DCI step, and the base station can determine where the data is allocated through DCI, and check MCS (Modulation and Coding Scheme), HARQ information, antenna port, number of layers, etc.
  • RNTI Radio Network Temporary Identity
  • DCI Format 1_1 which is a non-fallback format, can be considered, which can support all functions of NR.
  • DCI Format 1_1 transmits by CRC scrambling with C-RNTI (cell RNTI), CS-RNTI (configured scheduling RNTI), and MCS-C-RNTI (MCS-C-RNTI: Modulation Coding Scheme cell RNTI), and can configure a control signal between a base station and a terminal by utilizing frequency domain resource assignment and time domain resource assignment among the transmitted information.
  • C-RNTI cell RNTI
  • CS-RNTI configured scheduling RNTI
  • MCS-C-RNTI Modulation Coding Scheme cell RNTI
  • control signal through RRC configuration information may have a higher priority than the control signal through DCI.
  • Unlicensed bands are used by multiple wireless protocols, and therefore, compared to licensed bands, they have more regulations to address coexistence issues, such as transmission power, and may also experience degradation in communication quality due to interference signals from other wireless protocols.
  • the downlink communication quality of NR-U can be improved by replicating a WiFi legacy signal with NR.
  • the present disclosure proposes a method for enabling NR systems to practically utilize unlicensed bands by preventing degradation in communication quality of NR-U downlinks through time and frequency resource allocation of the replica signal.
  • a base station can not only respond to various scenarios but also operate so that backoff can be performed at many APs.
  • Figure 29 is another diagram illustrating a back off scenario applicable to the present disclosure.
  • Figure 29 illustrates an example of an experiment verifying whether backoff is actually performed in a WiFi AP.
  • a signal simulated in NR can be transmitted through a transmitting USRP (Universal Software Radio Peripheral) in an environment where a WiFi AP (802.11ax) and a terminal (station: STA) are connected and a large file is being downloaded.
  • the base station can check and analyze the signals surrounding the WiFi AP through the receiving USRP next to the WiFi AP, and can estimate whether backoff is actually performed for a specific period of time through the simulated signal seen by the WiFi AP.
  • the experiment in Figure 29 utilized MATLAB and GNU Radio programs, and the experimental AP model was a TP-link AXE5400 model.
  • FIG. 30 is a diagram illustrating an example of a method for a first node to transmit and receive a signal in a system applicable to the present disclosure.
  • a method performed by a first node supporting a first radio access technology (RAT) in a wireless communication system includes a step (S3010) of generating a data signal including at least one simulated signal simulated based on a second RAT, and a step (S3020) of transmitting the data signal to a second node supporting the second RAT, wherein the second node performs a back-off for the second RAT based on the data signal, and a first simulated signal may be included in a first symbol of the data signal, and a second simulated signal may be included in a last symbol of the data signal.
  • RAT radio access technology
  • the first and second mock signals may include a preamble for the second RAT.
  • At least one of the first simulated signal and the second simulated signal may include the preamble in duplicate two or more times.
  • the first imitation signal may include signal length information for transmitting the data signal.
  • the length information may be a value obtained by subtracting one symbol length from an integer multiple of a Transmission Time Interval (TTI) of the first RAT.
  • TTI Transmission Time Interval
  • the second simulated signal may include length information about a backoff time that may be additionally performed after the backoff is terminated.
  • the method further comprises a step of transmitting configuration information related to the backoff to the second node, wherein the configuration information related to the backoff may be transmitted via at least one of an RRC reconfiguration message and Downlink Control Information (DCI).
  • DCI Downlink Control Information
  • a first node supporting a first radio access technology (RAT) may be provided in a communication system.
  • the terminal may include a transceiver and at least one processor, and the at least one processor may be configured to perform the operating method of the terminal according to FIG. 30.
  • a device for controlling a first node supporting a first radio access technology (RAT) in a communication system may be provided.
  • the device may include at least one processor and at least one memory operably connected to the at least one processor.
  • the at least one memory may be configured to store instructions for performing an operating method of a terminal according to FIG. 30 based on instructions executed by the at least one processor.
  • one or more non-transitory computer-readable media storing one or more commands may be provided.
  • the one or more commands when executed by one or more processors, perform operations, and the operations may include an operating method of a terminal according to FIG. 30.
  • FIG. 31 is a diagram illustrating an example of a method for a second node to transmit and receive signals in a system applicable to the present disclosure.
  • a method performed by a second node supporting a second RAT (radio access technology) in a wireless communication system includes a step (S3110) of receiving a data signal including at least one simulated signal based on the second RAT from a first node supporting the first RAT, and a step (S3120) of performing a back-off for the second RAT based on the data signal, wherein the first simulated signal may be included in a first symbol of the data signal, and the second simulated signal may be included in a last symbol of the data signal.
  • At least one of the first simulated signal and the second simulated signal may include the preamble in duplicate two or more times.
  • the first imitation signal may include signal length information for transmitting the data signal.
  • the length information may be a value obtained by subtracting one symbol length from an integer multiple of a Transmission Time Interval (TTI) of the first RAT.
  • TTI Transmission Time Interval
  • the method further comprises the step of receiving configuration information related to the backoff from the first node, wherein the configuration information related to the backoff can be transmitted via at least one of an RRC reconfiguration message and Downlink Control Information (DCI).
  • DCI Downlink Control Information
  • a second node supporting a second radio access technology may be provided in a communication system.
  • the base station may include a transceiver and at least one processor, wherein the at least one processor may be configured to perform the operating method of the base station according to FIG. 31.
  • a device for controlling a second node supporting a second radio access technology (RAT) in a communication system may be provided.
  • the device may include at least one processor and at least one memory operably connected to the at least one processor.
  • the at least one memory may be configured to store instructions for performing an operating method of a base station according to FIG. 31 based on instructions executed by the at least one processor.
  • one or more non-transitory computer-readable media storing one or more commands may be provided.
  • the one or more commands when executed by one or more processors, perform operations, and the operations may include an operating method of a base station according to FIG. 31.
  • a communication system (1) applied to various embodiments of the present disclosure includes a wireless device, a base station, and a network.
  • the wireless device refers to a device that performs communication using a wireless access technology (e.g., 5G NR (New RAT), LTE (Long Term Evolution), 6G wireless communication), and may be referred to as a communication/wireless/5G device/6G device.
  • 5G NR New RAT
  • LTE Long Term Evolution
  • 6G wireless communication e.g., 6G wireless communication
  • the wireless device may include a robot (100a), a vehicle (100b-1, 100b-2), an XR (eXtended Reality) device (100c), a hand-held device (100d), a home appliance (100e), an IoT (Internet of Things) device (100f), and an AI device/server (400).
  • the vehicle may include a vehicle equipped with a wireless communication function, an autonomous vehicle, a vehicle capable of performing vehicle-to-vehicle communication, etc.
  • the vehicle may include an Unmanned Aerial Vehicle (UAV) (e.g., a drone).
  • UAV Unmanned Aerial Vehicle
  • Wireless devices (100a to 100f) can be connected to a network (300) via a base station (200). Artificial Intelligence (AI) technology can be applied to the wireless devices (100a to 100f), and the wireless devices (100a to 100f) can be connected to an AI server (400) via the network (300).
  • the network (300) can be configured using a 3G network, a 4G (e.g., LTE) network, a 5G (e.g., NR) network, or a 6G network.
  • the wireless devices (100a to 100f) can communicate with each other via the base station (200)/network (300), but can also communicate directly (e.g., sidelink communication) without going through the base station/network.
  • vehicles can communicate directly (e.g., V2V (Vehicle to Vehicle)/V2X (Vehicle to everything) communication).
  • IoT devices e.g., sensors
  • IoT devices can communicate directly with other IoT devices (e.g., sensors) or other wireless devices (100a to 100f).
  • Wireless communication/connection can be established between wireless devices (100a ⁇ 100f)/base stations (200), and base stations (200)/base stations (200).
  • wireless communication/connection can be achieved through various wireless access technologies (e.g., 5G NR) such as uplink/downlink communication (150a), sidelink communication (150b) (or D2D communication), and base station-to-base station communication (150c) (e.g., relay, IAB (Integrated Access Backhaul).
  • 5G NR wireless access technologies
  • uplink/downlink communication 150a
  • sidelink communication 150b
  • base station-to-base station communication 150c
  • wireless devices and base stations/wireless devices, and base stations and base stations can transmit/receive wireless signals to each other.
  • wireless communication/connection can transmit/receive signals through various physical channels.
  • various configuration information setting processes for transmitting/receiving wireless signals various signal processing processes (e.g., channel encoding/decoding, modulation/demodulation, resource mapping/demapping, etc.), and resource allocation processes can be performed based on various proposals of various embodiments of the present disclosure.
  • FR1 may include a band from 410 MHz to 7125 MHz, as shown in Table 4 below. That is, FR1 may include a frequency band above 6 GHz (or 5850, 5900, 5925 MHz, etc.). For example, the frequency band above 6 GHz (or 5850, 5900, 5925 MHz, etc.) included within FR1 may include an unlicensed band. The unlicensed band may be used for various purposes, such as for vehicular communications (e.g., autonomous driving).
  • vehicular communications e.g., autonomous driving
  • the communication system (1) can support terahertz (THz) wireless communication.
  • the 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 where propagation loss due to absorption of molecules in the air is small.
  • FIG. 33 illustrates a wireless device that can be applied to various embodiments of the present disclosure.
  • the first wireless device (100) and the second wireless device (200) can transmit and receive wireless signals via various wireless access technologies (e.g., LTE, NR).
  • ⁇ the first wireless device (100), the second wireless device (200) ⁇ can correspond to ⁇ the wireless device (100x), the base station (200) ⁇ and/or ⁇ the wireless device (100x), the wireless device (100x) ⁇ of FIG. 31.
  • the memory (204) may be connected to the processor (202) and may store various information related to the operation of the processor (202). For example, the memory (204) may perform some or all of the processes controlled by the processor (202), or may store software code including commands for performing the descriptions, functions, procedures, proposals, methods, and/or operation flowcharts disclosed in this document.
  • the processor (202) and the memory (204) may be part of a communication modem/circuit/chip designed to implement wireless communication technology (e.g., LTE, NR).
  • the transceiver (206) may be connected to the processor (202) and may transmit and/or receive wireless signals via one or more antennas (208).
  • the transceiver (206) may include a transmitter and/or a receiver.
  • the transceiver (206) may be used interchangeably with an RF unit.
  • a wireless device may also mean a communication modem/circuit/chip.
  • One or more processors (102, 202) may generate messages, control information, data, or information according to the descriptions, functions, procedures, proposals, methods, and/or operation flowcharts disclosed in this document.
  • One or more processors (102, 202) can generate signals (e.g., baseband signals) including PDUs, SDUs, messages, control information, data or information according to the functions, procedures, proposals and/or methods disclosed herein, and provide the signals to one or more transceivers (106, 206).
  • One or more processors (102, 202) can receive signals (e.g., baseband signals) from one or more transceivers (106, 206) and obtain PDUs, SDUs, messages, control information, data or information according to the descriptions, functions, procedures, proposals, methods and/or operational flowcharts disclosed herein.
  • signals e.g., baseband signals
  • the descriptions, functions, procedures, proposals, methods, and/or operational flowcharts disclosed in this document may be implemented using firmware or software, and the firmware or software may be implemented to include modules, procedures, functions, etc.
  • the descriptions, functions, procedures, suggestions, methods and/or operation flowcharts disclosed in this document may be implemented using firmware or software configured to perform one or more processors (102, 202) or stored in one or more memories (104, 204) and executed by one or more processors (102, 202).
  • the descriptions, functions, procedures, suggestions, methods and/or operation flowcharts disclosed in this document may be implemented using firmware or software in the form of codes, instructions and/or sets of instructions.
  • One or more memories (104, 204) may be coupled to one or more processors (102, 202) and may store various forms of data, signals, messages, information, programs, codes, instructions, and/or commands.
  • the one or more memories (104, 204) may be configured as ROM, RAM, EPROM, flash memory, hard drives, registers, cache memory, computer-readable storage media, and/or combinations thereof.
  • the one or more memories (104, 204) may be located internally and/or externally to the one or more processors (102, 202). Additionally, the one or more memories (104, 204) may be coupled to the one or more processors (102, 202) via various technologies, such as wired or wireless connections.
  • One or more transceivers (106, 206) can transmit user data, control information, wireless signals/channels, etc., as mentioned in the methods and/or flowcharts of this document, to one or more other devices.
  • One or more transceivers (106, 206) can receive user data, control information, wireless signals/channels, etc., as mentioned in the descriptions, functions, procedures, proposals, methods and/or flowcharts of this document, from one or more other devices.
  • one or more transceivers (106, 206) can be connected to one or more processors (102, 202) and can transmit and receive wireless signals.
  • one or more processors (102, 202) can control one or more transceivers (106, 206) to transmit user data, control information, or wireless signals to one or more other devices. Additionally, one or more processors (102, 202) may control one or more transceivers (106, 206) to receive user data, control information, or wireless signals from one or more other devices.
  • One or more transceivers (106, 206) may convert processed user data, control information, wireless signals/channels, etc. from baseband signals to RF band signals using one or more processors (102, 202).
  • one or more transceivers (106, 206) may include an (analog) oscillator and/or a filter.
  • the difference between the example of the wireless device described in FIG. 33 and the example of the wireless device in FIG. 34 is that in FIG. 33, the processor (102, 202) and the memory (104, 204) are separated, but in the example of FIG. 34, the memory (104, 204) is included in the processor (102, 202).
  • processor 102, 202
  • memory 104, 204
  • transceiver 106, 206
  • antennas 108, 208
  • Figure 35 illustrates a signal processing circuit for a transmission signal.
  • the signal processing circuit (1000) may include a scrambler (1010), a modulator (1020), a layer mapper (1030), a precoder (1040), a resource mapper (1050), and a signal generator (1060).
  • the operations/functions of FIG. 35 may be performed in the processor (102, 202) and/or the transceiver (106, 206) of FIG. 33.
  • the hardware elements of FIG. 34 may be implemented in the processor (102, 202) and/or the transceiver (106, 206) of FIG. 33.
  • blocks 1010 to 1060 may be implemented in the processor (102, 202) of FIG. 33.
  • blocks 1010 to 1050 may be implemented in the processor (102, 202) of FIG. 33
  • block 1060 may be implemented in the transceiver (106, 206) of FIG. 33.
  • the codeword can be converted into a wireless signal through the signal processing circuit (1000) of FIG. 35.
  • the codeword is an encoded bit sequence of an information block.
  • the information block may include a transport block (e.g., an UL-SCH transport block, a DL-SCH transport block).
  • the wireless signal may be transmitted through various physical channels (e.g., a PUSCH or a PDSCH).
  • the codeword can be converted into a bit sequence scrambled by a scrambler (1010).
  • the scramble sequence used for scrambling is generated based on an initialization value, and the initialization value may include ID information of the wireless device, etc.
  • the scrambled bit sequence can be modulated into a modulation symbol sequence by a modulator (1020).
  • the modulation method may include pi/2-BPSK (pi/2-Binary Phase Shift Keying), m-PSK (m-Phase Shift Keying), m-QAM (m-Quadrature Amplitude Modulation), etc.
  • the complex modulation symbol sequence can be mapped to one or more transmission layers by a layer mapper (1030).
  • the modulation symbols of each transmission layer can be mapped to the corresponding antenna port(s) by a precoder (1040) (precoding).
  • the output z of the precoder (1040) can be obtained by multiplying the output y of the layer mapper (1030) by a precoding matrix W of N*M.
  • N is the number of antenna ports
  • M is the number of transmission layers.
  • the precoder (1040) can perform precoding after performing transform precoding (e.g., DFT transform) on complex modulation symbols.
  • the precoder (1040) can perform precoding without performing transform precoding.
  • the resource mapper (1050) can map modulation symbols of each antenna port to time-frequency resources.
  • the time-frequency resources can include multiple symbols (e.g., CP-OFDMA symbols, DFT-s-OFDMA symbols) in the time domain and multiple subcarriers in the frequency domain.
  • the signal generator (1060) generates a wireless signal from the mapped modulation symbols, and the generated wireless signal can be transmitted to another device through each antenna.
  • the signal generator (1060) can include an Inverse Fast Fourier Transform (IFFT) module, a Cyclic Prefix (CP) inserter, a Digital-to-Analog Converter (DAC), a frequency uplink converter, etc.
  • IFFT Inverse Fast Fourier Transform
  • CP Cyclic Prefix
  • DAC Digital-to-Analog Converter
  • the signal processing process for receiving signals in a wireless device can be configured in reverse order of the signal processing process (1010 to 1060) of FIG. 35.
  • a wireless device e.g., 100, 200 of FIG. 33
  • the received wireless signals can be converted into baseband signals through a signal restorer.
  • the signal restorer can include a frequency downlink converter, an analog-to-digital converter (ADC), a CP remover, and a fast Fourier transform (FFT) module.
  • ADC analog-to-digital converter
  • FFT fast Fourier transform
  • the baseband signal can be restored to a codeword through a resource demapper process, a postcoding process, a demodulation process, and a descrambling process.
  • a signal processing circuit for a received signal may include a signal restorer, a resource de-mapper, a postcoder, a demodulator, a de-scrambler, and a decoder.
  • Figure 36 illustrates another example of a wireless device applicable to various embodiments of the present disclosure.
  • the wireless device may be implemented in various forms depending on the use case/service.
  • the wireless device (100, 200) corresponds to the wireless device (100, 200) of FIG. 33 and may be composed of various elements, components, units, and/or modules.
  • the wireless device (100, 200) may include a communication unit (110), a control unit (120), a memory unit (130), and additional elements (140).
  • the communication unit may include a communication circuit (112) and a transceiver(s) (114).
  • the communication circuit (112) may include one or more processors (102, 202) and/or one or more memories (104, 204) of FIG. 33.
  • the transceiver(s) (114) may include one or more transceivers (106, 206) and/or one or more antennas (108, 208) of FIG. 33.
  • the control unit (120) is electrically connected to the communication unit (110), the memory unit (130), and the additional elements (140) and controls the overall operation of the wireless device.
  • the control unit (120) may control the electrical/mechanical operation of the wireless device based on the program/code/command/information stored in the memory unit (130).
  • control unit (120) may transmit information stored in the memory unit (130) to an external device (e.g., another communication device) via a wireless/wired interface through the communication unit (110), or store information received from an external device (e.g., another communication device) via a wireless/wired interface in the memory unit (130).
  • the additional element (140) may be configured in various ways depending on the type of the wireless device.
  • the additional element (140) may include at least one of a power unit/battery, an input/output unit (I/O unit), a driving unit, and a computing unit.
  • the wireless device may be implemented in the form of a robot (Fig. 32, 100a), a vehicle (Fig. 32, 100b-1, 100b-2), an XR device (Fig. 32, 100c), a portable device (Fig. 32, 100d), a home appliance (Fig. 32, 100e), an IoT device (Fig.
  • Wireless devices may be mobile or stationary depending on the use/service.
  • various elements, components, units/parts, and/or modules within the wireless device (100, 200) may be entirely interconnected via a wired interface, or at least some may be wirelessly connected via a communication unit (110).
  • the control unit (120) and the communication unit (110) may be wired, and the control unit (120) and a first unit (e.g., 130, 140) may be wirelessly connected via the communication unit (110).
  • each element, component, unit/part, and/or module within the wireless device (100, 200) may further include one or more elements.
  • the control unit (120) may be composed of a set of one or more processors.
  • control unit (120) may be composed of a set of a communication control processor, an application processor, an electronic control unit (ECU), a graphics processing processor, a memory control processor, etc.
  • memory unit (130) may be composed of RAM (Random Access Memory), DRAM (Dynamic RAM), ROM (Read Only Memory), flash memory, volatile memory, non-volatile memory, and/or a combination thereof.
  • FIG 37 illustrates a mobile device applicable to various embodiments of the present disclosure.
  • the mobile device may include a smartphone, a smart pad, a wearable device (e.g., a smartwatch, smartglasses), or a portable computer (e.g., a laptop, etc.).
  • the mobile device may be referred to as a Mobile Station (MS), a User Terminal (UT), a Mobile Subscriber Station (MSS), a Subscriber Station (SS), an Advanced Mobile Station (AMS), or a Wireless Terminal (WT).
  • MS Mobile Station
  • UT User Terminal
  • MSS Mobile Subscriber Station
  • SS Subscriber Station
  • AMS Advanced Mobile Station
  • WT Wireless Terminal
  • the portable device (100) may include an antenna unit (108), a communication unit (110), a control unit (120), a memory unit (130), a power supply unit (140a), an interface unit (140b), and an input/output unit (140c).
  • the antenna unit (108) may be configured as a part of the communication unit (110).
  • Blocks 110 to 130/140a to 140c correspond to blocks 110 to 130/140 of FIG. 36, respectively.
  • the communication unit (110) can transmit and receive signals (e.g., data, control signals, etc.) with other wireless devices and base stations.
  • the control unit (120) can control components of the mobile device (100) to perform various operations.
  • the control unit (120) can include an AP (Application Processor).
  • the memory unit (130) can store data/parameters/programs/codes/commands required for operating the mobile device (100). In addition, the memory unit (130) can store input/output data/information, etc.
  • the power supply unit (140a) supplies power to the mobile device (100) and can include a wired/wireless charging circuit, a battery, etc.
  • the interface unit (140b) can support connection between the mobile device (100) and other external devices.
  • the interface unit (140b) can include various ports (e.g., audio input/output ports, video input/output ports) for connection with external devices.
  • the input/output unit (140c) can input or output video information/signals, audio information/signals, data, and/or information input from a user.
  • the input/output unit (140c) may include a camera, a microphone, a user input unit, a display unit (140d), a speaker, and/or a haptic module.
  • the input/output unit (140c) obtains information/signals (e.g., touch, text, voice, image, video) input by the user, and the obtained information/signals can be stored in the memory unit (130).
  • the communication unit (110) converts the information/signals stored in the memory into wireless signals, and can directly transmit the converted wireless signals to other wireless devices or to a base station.
  • the communication unit (110) can receive wireless signals from other wireless devices or base stations, and then restore the received wireless signals to the original information/signals.
  • the restored information/signals can be stored in the memory unit (130) and then output in various forms (e.g., text, voice, image, video, haptic) through the input/output unit (140c).
  • FIG. 38 illustrates a vehicle or autonomous vehicle applicable to various embodiments of the present disclosure.
  • Vehicles or autonomous vehicles can be implemented as mobile robots, cars, trains, manned or unmanned aerial vehicles (AVs), ships, etc.
  • AVs unmanned aerial vehicles
  • a vehicle or autonomous vehicle may include an antenna unit (108), a communication unit (110), a control unit (120), a driving unit (140a), a power supply unit (140b), a sensor unit (140c), and an autonomous driving unit (140d).
  • the antenna unit (108) may be configured as a part of the communication unit (110).
  • Blocks 110/130/140a to 140d correspond to blocks 110/130/140 of FIG. 36, respectively.
  • the sensor unit (140c) can obtain vehicle status, surrounding environment information, user information, etc.
  • the sensor unit (140c) may include an IMU (inertial measurement unit) sensor, a collision sensor, a wheel sensor, a speed sensor, an incline sensor, a weight detection sensor, a heading sensor, a position module, a vehicle forward/backward sensor, a battery sensor, a fuel sensor, a tire sensor, a steering sensor, a temperature sensor, a humidity sensor, an ultrasonic sensor, an illuminance sensor, a pedal position sensor, etc.
  • IMU intial measurement unit
  • the communication unit (110) can transmit information regarding the vehicle location, autonomous driving route, driving plan, etc. to the external server.
  • External servers can predict traffic information data in advance using AI technology or other technologies based on information collected from vehicles or autonomous vehicles, and provide the predicted traffic information data to the vehicles or autonomous vehicles.
  • Figure 39 illustrates a vehicle applicable to various embodiments of the present disclosure.
  • the vehicle may also be implemented as a means of transportation, a train, an aircraft, a ship, or the like.
  • the vehicle (100) may include a communication unit (110), a control unit (120), a memory unit (130), an input/output unit (140a), and a position measurement unit (140b).
  • blocks 110 to 130/140a to 140b correspond to blocks 110 to 130/140 of FIG. 35, respectively.
  • the communication unit (110) can transmit and receive signals (e.g., data, control signals, etc.) with other vehicles or external devices such as base stations.
  • the control unit (120) can control components of the vehicle (100) to perform various operations.
  • the memory unit (130) can store data/parameters/programs/codes/commands that support various functions of the vehicle (100).
  • the input/output unit (140a) can output AR/VR objects based on information in the memory unit (130).
  • the input/output unit (140a) can include a HUD.
  • the position measurement unit (140b) can obtain position information of the vehicle (100).
  • the position information can include absolute position information of the vehicle (100), position information within a driving line, acceleration information, position information with respect to surrounding vehicles, etc.
  • the position measurement unit (140b) can include GPS and various sensors.
  • control unit (120) can display a warning on the vehicle window through the input/output unit (140a). Additionally, the control unit (120) can broadcast a warning message regarding driving abnormalities to surrounding vehicles through the communication unit (110). Depending on the situation, the control unit (120) can transmit vehicle location information and information regarding driving/vehicle abnormalities to relevant authorities through the communication unit (110).
  • Figure 40 illustrates an XR device applicable to various embodiments of the present disclosure.
  • the XR device may be implemented as an HMD, a head-up display (HUD) installed in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, digital signage, a vehicle, a robot, and the like.
  • HMD head-up display
  • FIG. 40 illustrates an XR device applicable to various embodiments of the present disclosure.
  • the XR device may be implemented as an HMD, a head-up display (HUD) installed in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, digital signage, a vehicle, a robot, and the like.
  • HUD head-up display
  • the XR device (100a) may include a communication unit (110), a control unit (120), a memory unit (130), an input/output unit (140a), a sensor unit (140b), and a power supply unit (140c).
  • blocks 110 to 130/140a to 140c correspond to blocks 110 to 130/140 of FIG. 36, respectively.
  • the communication unit (110) can transmit and receive signals (e.g., media data, control signals, etc.) with external devices such as other wireless devices, portable devices, or media servers.
  • the media data can include videos, images, sounds, etc.
  • the control unit (120) can control components of the XR device (100a) to perform various operations.
  • the control unit (120) can be configured to control and/or perform procedures such as video/image acquisition, (video/image) encoding, metadata generation and processing, etc.
  • the memory unit (130) can store data/parameters/programs/codes/commands required for driving the XR device (100a)/generating XR objects.
  • the input/output unit (140a) can obtain control information, data, etc.
  • the input/output unit (140a) can include a camera, a microphone, a user input unit, a display unit, a speaker, and/or a haptic module, etc.
  • the sensor unit (140b) can obtain the XR device status, surrounding environment information, user information, etc.
  • the sensor unit (140b) may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an RGB sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, a light sensor, a microphone, and/or a radar.
  • the power supply unit (140c) supplies power to the XR device (100a) and may include a wired/wireless charging circuit, a battery, etc.
  • the communication unit (130) may download/stream content such as movies and news from another device (e.g., a mobile device (100b)) or a media server to the memory unit (130).
  • the control unit (120) controls and/or performs procedures such as video/image acquisition, (video/image) encoding, and metadata generation/processing for content, and can generate/output an XR object based on information about surrounding space or real objects acquired through the input/output unit (140a)/sensor unit (140b).
  • the XR device (100a) is wirelessly connected to the mobile device (100b) through the communication unit (110), and the operation of the XR device (100a) can be controlled by the mobile device (100b).
  • the mobile device (100b) can act as a controller for the XR device (100a).
  • the XR device (100a) can obtain three-dimensional position information of the mobile device (100b), and then generate and output an XR object corresponding to the mobile device (100b).
  • Figure 41 illustrates robots applicable to various embodiments of the present disclosure. Robots may be classified into industrial, medical, household, and military applications, depending on their intended use or field.
  • the robot (100) may include a communication unit (110), a control unit (120), a memory unit (130), an input/output unit (140a), a sensor unit (140b), and a driving unit (140c).
  • blocks 110 to 130/140a to 140c correspond to blocks 110 to 130/140 of FIG. 36, respectively.
  • the communication unit (110) can transmit and receive signals (e.g., driving information, control signals, etc.) with external devices such as other wireless devices, other robots, or control servers.
  • the control unit (120) can control components of the robot (100) to perform various operations.
  • the memory unit (130) can store data/parameters/programs/codes/commands that support various functions of the robot (100).
  • the input/output unit (140a) can obtain information from the outside of the robot (100) and output information to the outside of the robot (100).
  • the input/output unit (140a) can include a camera, a microphone, a user input unit, a display unit, a speaker, and/or a haptic module.
  • AI devices can be implemented as 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.
  • 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.
  • the AI device (100) may include a communication unit (110), a control unit (120), a memory unit (130), an input/output unit (140a/140b), a learning processor unit (140c), and a sensor unit (140d).
  • Blocks 110 to 130/140a to 140d correspond to blocks 110 to 130/140 of FIG. 36, respectively.
  • the communication unit (110) can transmit and receive wired and wireless signals (e.g., sensor information, user input, learning models, control signals, etc.) with external devices such as other AI devices (e.g., FIG. 39, 100x, 200, 400) or AI servers (200) using wired and wireless communication technology.
  • the communication unit (110) can transmit information within the memory unit (130) to the external device or transfer a signal received from the external device to the memory unit (130).
  • the control unit (120) may determine at least one executable operation of the AI device (100) based on information determined or generated using a data analysis algorithm or a machine learning algorithm. In addition, the control unit (120) may control components of the AI device (100) to perform the determined operation. For example, the control unit (120) may request, search, receive, or utilize data from the learning processor unit (140c) or the memory unit (130), and may control components of the AI device (100) to perform at least one executable operation, a predicted operation, or an operation determined to be desirable.
  • control unit (120) may collect history information including the operation contents of the AI device (100) or user feedback on the operation, and store the collected history information in the memory unit (130) or the learning processor unit (140c), or transmit the collected history information to an external device such as an AI server (FIG. W1, 400).
  • the collected history information may be used to update a learning model.
  • the memory unit (130) can store data that supports various functions of the AI device (100).
  • the memory unit (130) can store data obtained from the input unit (140a), data obtained from the communication unit (110), output data of the learning processor unit (140c), and data obtained from the sensing unit (140).
  • the memory unit (130) can store control information and/or software codes necessary for the operation/execution of the control unit (120).
  • the sensing unit (140) may include a proximity sensor, an illuminance sensor, an acceleration sensor, a magnetic sensor, a gyro sensor, an inertial sensor, an RGB sensor, an IR sensor, a fingerprint recognition sensor, an ultrasonic sensor, a light sensor, a microphone, and/or a radar, etc.
  • the claims described in the various embodiments of the present disclosure may be combined in various ways.
  • the technical features of the method claims of the various embodiments of the present disclosure may be combined and implemented as a device, and the technical features of the device claims of the various embodiments of the present disclosure may be combined and implemented as a method.
  • the technical features of the method claims of the various embodiments of the present disclosure may be combined and implemented as a device, and the technical features of the method claims of the various embodiments of the present disclosure may be combined and implemented as a method.

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  • Computer Networks & Wireless Communication (AREA)
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Abstract

Selon divers modes de réalisation de la présente divulgation, un procédé mis en œuvre par un premier nœud prenant en charge une première technologie d'accès radio (RAT) dans un système de communication sans fil peut comprendre les étapes consistant à : générer un signal de données comprenant au moins un signal de réplique répliqué sur la base d'une seconde RAT ; et transmettre le signal de données à un second nœud prenant en charge la seconde RAT, le second nœud mettant en œuvre une réduction de puissance pour la seconde RAT sur la base du signal de données, un premier signal de réplique étant inclus dans un premier symbole du signal de données, et un second signal de réplique étant inclus dans un dernier symbole du signal de données.
PCT/KR2024/004169 2024-04-01 2024-04-01 Procédé et appareil de transmission et de réception de signal dans un système de communication sans fil Pending WO2025211465A1 (fr)

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Publication number Priority date Publication date Assignee Title
KR20180122951A (ko) * 2017-05-05 2018-11-14 아서스테크 컴퓨터 인코포레이션 무선 통신 시스템에서 데이터 복제를 전송하는 방법 및 장치
US20190104548A1 (en) * 2017-10-02 2019-04-04 Qualcomm Incorporated Universal reservation signal design for wifi and nr-ss
EP3603299B1 (fr) * 2017-03-24 2021-08-11 Convida Wireless, LLC Réglage de délai d'interruption
EP3396885B1 (fr) * 2015-12-21 2021-09-01 LG Electronics Inc. Procédé et appareil destinés à la génération et à la transmission de signal de référence et de données dans un système de communication sans fil
EP3965515A1 (fr) * 2020-09-03 2022-03-09 INTEL Corporation Structure de trame pour la coexistence de canaux d'un système de transport intelligent avec des durées d'intervalle asymétriques

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3396885B1 (fr) * 2015-12-21 2021-09-01 LG Electronics Inc. Procédé et appareil destinés à la génération et à la transmission de signal de référence et de données dans un système de communication sans fil
EP3603299B1 (fr) * 2017-03-24 2021-08-11 Convida Wireless, LLC Réglage de délai d'interruption
KR20180122951A (ko) * 2017-05-05 2018-11-14 아서스테크 컴퓨터 인코포레이션 무선 통신 시스템에서 데이터 복제를 전송하는 방법 및 장치
US20190104548A1 (en) * 2017-10-02 2019-04-04 Qualcomm Incorporated Universal reservation signal design for wifi and nr-ss
EP3965515A1 (fr) * 2020-09-03 2022-03-09 INTEL Corporation Structure de trame pour la coexistence de canaux d'un système de transport intelligent avec des durées d'intervalle asymétriques

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