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WO2025211472A1 - Procédé et appareil d'émission et de réception de signal dans un système de communication sans fil - Google Patents

Procédé et appareil d'émission et de réception de signal dans un système de communication sans fil

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Publication number
WO2025211472A1
WO2025211472A1 PCT/KR2024/004190 KR2024004190W WO2025211472A1 WO 2025211472 A1 WO2025211472 A1 WO 2025211472A1 KR 2024004190 W KR2024004190 W KR 2024004190W WO 2025211472 A1 WO2025211472 A1 WO 2025211472A1
Authority
WO
WIPO (PCT)
Prior art keywords
information
transmission power
node
signal
power
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/KR2024/004190
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English (en)
Korean (ko)
Inventor
김정인
김우찬
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
Original Assignee
LG Electronics Inc
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Filing date
Publication date
Application filed by LG Electronics Inc filed Critical LG Electronics Inc
Priority to PCT/KR2024/004190 priority Critical patent/WO2025211472A1/fr
Publication of WO2025211472A1 publication Critical patent/WO2025211472A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/10—Monitoring; Testing of transmitters
    • H04B17/11—Monitoring; Testing of transmitters for calibration
    • H04B17/13—Monitoring; Testing of transmitters for calibration of power amplifiers, e.g. gain or non-linearity
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/18—Phase-modulated carrier systems, i.e. using phase-shift keying
    • H04L27/20—Modulator circuits; Transmitter circuits
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. Transmission Power Control [TPC] or power classes
    • H04W52/04—Transmission power control [TPC]
    • H04W52/06—TPC algorithms
    • H04W52/14—Separate analysis of uplink or downlink
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. Transmission Power Control [TPC] or power classes
    • H04W52/04—Transmission power control [TPC]
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/28—TPC being performed according to specific parameters using user profile, e.g. mobile speed, priority or network state, e.g. standby, idle or non-transmission
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. Transmission Power Control [TPC] or power classes
    • H04W52/04—Transmission power control [TPC]
    • H04W52/52—Transmission power control [TPC] using AGC [Automatic Gain Control] circuits or amplifiers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W8/00—Network data management
    • H04W8/22—Processing or transfer of terminal data, e.g. status or physical capabilities
    • H04W8/24—Transfer of terminal data

Definitions

  • the present disclosure relates to a device and method for transmitting and receiving a signal in a wireless communication system. Specifically, the present disclosure relates to a device and method for transmitting and receiving a signal having non-linear characteristics in a wireless communication system.
  • enhanced mobile broadband (eMBB) communication technologies are being proposed, improving upon existing radio access technology (RAT).
  • massive machine type communications (mMTC) which connects numerous devices and objects to provide diverse services anytime and anywhere, as well as communication systems that consider reliability and latency-sensitive services/user equipment (UE), are being proposed.
  • UE latency-sensitive services/user equipment
  • the present disclosure provides a device and method for transmitting and receiving a signal having non-linear characteristics in a wireless communication system.
  • the power information includes information on whether the first node can transmit the signal based on nonlinear power.
  • the transmission power information may include information on a maximum distortion ratio of the power of a signal that the first node can transmit.
  • the transmission power is determined based on one of a plurality of power sections that are preset based on a distortion ratio
  • the transmission power information may include information indicating a power section in which the power of the transmission power is included among the plurality of power sections.
  • the transmission power information may be transmitted based on at least one modulation method among Binary Phase Shift Keying (BPSK) and Quadrature Phase Shift Keying (QPSK).
  • BPSK Binary Phase Shift Keying
  • QPSK Quadrature Phase Shift Keying
  • the transmission power information may be transmitted via a terminal capability (UE-capability) message.
  • UE-capability terminal capability
  • a method of operating a second node in a communication system includes the steps of receiving transmission power information about the second node from a second node that is one of a plurality of nodes constituting a plurality of paths in a network, performing compensation for a channel that receives a signal transmitted from the first node based on the transmission power information, and obtaining the signal based on the compensated channel, wherein the transmission power information may include information about a non-linear characteristic of the transmission power.
  • the transmission power information may include information on whether the first node can transmit the signal based on nonlinear power.
  • the transmission power information may include information on a maximum distortion ratio of the power of a signal that the first node can transmit.
  • the transmission power is determined based on one of a plurality of power sections that are preset based on a distortion ratio
  • the transmission power information may include information indicating a power section in which the power of the transmission power is included among the plurality of power sections.
  • the transmission power information may be received based on at least one modulation method among Binary Phase Shift Keying (BPSK) and Quadrature Phase Shift Keying (QPSK).
  • BPSK Binary Phase Shift Keying
  • QPSK Quadrature Phase Shift Keying
  • the reception power information can be received via a terminal capability (UE-capability) message.
  • UE-capability terminal capability
  • a second node operating in a communication system includes a transceiver, at least one processor, and at least one memory operably connectable to the at least one processor and storing instructions that, when executed by the at least one processor, perform operations, wherein the operations may include all steps of a method of operating the second node according to various embodiments of the present disclosure.
  • one or more non-transitory computer-readable media storing one or more commands, wherein the one or more commands, when executed by one or more processors, perform operations, wherein the operations may include all steps of a method of operating a first node of a terminal according to various embodiments of the present disclosure.
  • one or more non-transitory computer-readable media storing one or more instructions, wherein the one or more instructions, when executed by one or more processors, perform operations, the operations including all steps of a method of operating a second node according to various embodiments of the present disclosure.
  • a device and method for transmitting and receiving a signal having non-linear characteristics in a wireless communication system can be provided.
  • 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 5 is a diagram illustrating an example of a communication structure that can be provided in a 6G system.
  • Figure 7 is a schematic diagram illustrating an example of a multilayer perceptron structure.
  • Figure 8 is a schematic diagram illustrating an example of a deep neural network.
  • Figure 9 is a schematic diagram illustrating an example of a convolutional neural network.
  • Figure 10 is a schematic diagram illustrating an example of a filter operation in a convolutional neural network.
  • Fig. 15 is a diagram illustrating an example of an electronic component-based THz wireless communication transmitter and receiver.
  • FIG. 21 is a drawing for explaining a transmitter and receiver structure applicable to the present disclosure.
  • FIG. 22 is a drawing for explaining a signal transmission method applicable to the present disclosure.
  • Figure 23 is a diagram for explaining the RRC connection process.
  • Figure 24 is a diagram for explaining a terminal capability (UE-capability) message.
  • FIG. 25 is a diagram for explaining parameters included in a terminal performance message applicable to the present disclosure.
  • FIG. 26 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.
  • FIG. 27 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.
  • FIG. 28 illustrates a communication system (1) applicable to various embodiments of the present disclosure.
  • FIG. 29 illustrates a wireless device that can be applied to various embodiments of the present disclosure.
  • FIG. 30 illustrates another example of a wireless device that can be applied to various embodiments of the present disclosure.
  • Figure 31 illustrates a signal processing circuit for a transmission signal.
  • FIG. 33 illustrates a portable device applicable to various embodiments of the present disclosure.
  • FIG. 34 illustrates a vehicle or autonomous vehicle applicable to various embodiments of the present disclosure.
  • FIG. 35 illustrates a vehicle applicable to various embodiments of the present disclosure.
  • FIG. 36 illustrates an XR device applicable to various embodiments of the present disclosure.
  • FIG. 37 illustrates a robot applicable to various embodiments of the present disclosure.
  • FIG. 38 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.”
  • 6G is expected to integrate with satellites to provide a global mobile network.
  • the integration of terrestrial, satellite, and airborne networks into a single wireless communications system is crucial for 6G.
  • 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.
  • 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 The most crucial and newly introduced technology for 6G systems is AI. 4G systems did not involve AI. 5G systems will support partial or very limited AI. However, 6G systems will fully support AI for automation. Advances in machine learning will create more intelligent networks for real-time communications in 6G. Incorporating AI into communications can streamline and improve real-time data transmission. AI can use numerous analyses to determine how complex target tasks should be performed. In other words, AI can increase efficiency and reduce processing delays.
  • 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
  • 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.
  • the neural network cores used in learning methods are mainly divided into deep neural networks (DNN), convolutional deep neural networks (CNN), and recurrent boltzmann machines (RNN).
  • DNN deep neural networks
  • CNN convolutional deep neural networks
  • RNN recurrent boltzmann machines
  • 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.
  • the layer where the input vector is located is called the input layer
  • the layer where the final output value is located is called the output layer
  • all layers located between the input layer and the output layer are called hidden layers.
  • the example in Fig. 7 shows three layers, but when counting the number of layers in an actual artificial neural network, the input layer is excluded, so it can be viewed as a total of two layers.
  • An artificial neural network is composed of perceptrons, which are basic blocks, connected in two dimensions.
  • 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.
  • the convolutional neural network of Fig. 9 has a problem in that the number of weights increases exponentially according to the number of connections. Therefore, instead of considering the connections of all modes between adjacent layers, it assumes that there are small filters, and performs weighted sum and activation function operations on the overlapping portions of the filters, as in Fig. 10.
  • 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).
  • 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.
  • 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.
  • 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
  • THz waves are located between the RF (Radio Frequency)/millimeter (mm) and infrared bands, and (i) compared to visible light/infrared light, they penetrate non-metallic/non-polarizable materials well, and compared to RF/millimeter waves, they have a shorter wavelength, so they have high linearity and can focus beams.
  • the photon energy of THz waves is only a few meV, they have the characteristic of being harmless to the human body.
  • 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.
  • Figure 14 is a diagram illustrating an example of a THz communication application.
  • 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.
  • Table 2 below shows examples of technologies that can be used in THz waves.
  • Transceiver Device Available immatures UTC-PD, RTD and SBD Modulation and Coding Low order modulation techniques (OOK, QPSK), LDPC, Reed Soloman, Hamming, Polar, Turbo Antenna Omni and Directional, phased array with low number of antenna elements Bandwidth 69GHz (or 23GHz) at 300GHz Channel models Partially Data rate 100Gbps Outdoor deployment No Free space loss High Coverage Low Radio Measurements 300GHz indoor Device size Few micrometers
  • 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. 16 is a diagram illustrating an example of a method for generating a THz signal based on an optical element.
  • 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.
  • Figure 19 is a drawing showing the structure of an optical modulator.
  • 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.
  • Effective down-conversion from the infrared band (IR band) to the terahertz band (THz band) depends on how to utilize the nonlinearity of the optical/electrical converter (O/E converter).
  • O/E converter optical/electrical converter
  • 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 wireless communication process can be summarized as the process of receiving a radio signal radiated from a transmitter antenna through a receiver antenna. Since the signal's size decreases in proportion to the square of the distance it travels, extending the range of wireless communication requires the transmitter antenna to emit a signal with the highest possible output. This high-output signal can be generated by the transmitter's power amplifier.
  • transmitting a signal through an antenna requires amplifying a small electrical signal using a power amplifier.
  • a power amplifier performs the function of amplifying the input electrical signal by a predetermined gain before outputting it.
  • the power amplifier can be composed of semiconductor devices.
  • the operating range in which the output of the power amplifier outputs a signal with a fixed gain is called the linear range, and the operating range in which the signal is not output with a fixed gain is called the non-linear range.
  • the power amplifier of the transmitter In order to secure the best signal quality at the receiver, it is desirable for the power amplifier of the transmitter to operate in the linear range.
  • the transmitter power amplifier may inevitably operate in a nonlinear region.
  • the output signal may not be proportional to the input signal, but rather a distorted signal. If the receiver receives this distorted signal, system performance may deteriorate. While methods such as pre-distortion can be applied to address this issue, these methods increase the transmitter's complexity and cost.
  • the present disclosure proposes a method for improving the quality of a signal by compensating for a signal distorted by nonlinear characteristics at a receiver.
  • the present disclosure proposes a method for dividing the nonlinear characteristic range of a transmitter power amplifier into multiple operating ranges based on the degree of distortion, and defining the operating range of the transmitter power amplifier according to a procedure established between the transmitter and receiver according to a wireless communication situation.
  • the transmitter can transmit information about the operating range to the receiver, and the receiver can perform demodulation to restore data by reflecting the information in channel compensation.
  • wireless communication is performed in an operating section with linear signal characteristics.
  • wireless communication may be performed in a section with nonlinear signal characteristics.
  • the present disclosure may be applied to cases where a power amplifier operates in a nonlinear operating section.
  • the difference between the size of the ideal output signal (ideal PA output) and the size of the actual output (real PA output) may be defined as signal distortion, and the operating section may be divided according to the degree of distortion.
  • the operating sections of the power amplifier may be divided into P0.1dB, P1.0dB, P3.0dB, P5.0dB, etc., and information about the divided operating sections may be transmitted to the receiver through an initial access process.
  • the receiver may store information about the divided operating sections according to the degree of distortion.
  • information about the divided operating sections may be referred to as operating section profile information.
  • Figure 23 is a diagram for explaining the RRC connection process.
  • Figure 24 is a diagram for explaining a terminal capability (UE-capability) message.
  • Figure 24 illustrates the UE Capability Message transmission process.
  • the UE Upon receiving a UE Capability Enquiry from a base station, the UE can transmit its capability information to the base station. This procedure can be performed after AS security activation. Transmitter power amplifier operation information can be defined as a single element within the UE Capability Message.
  • TxPowerAmpMaxDistortionRange can indicate the maximum distortion ratio at which the transmission output can operate.
  • the distortion ratio can be predefined for each range.
  • the distortion ratio can be defined as P0.1dB, P1.0dB, P2.0dB, P3.0dB ⁇ , etc.
  • TxPowerAmpMaxDistortionRang can indicate the maximum nonlinear power value that can be used for transmission.
  • TxPowerAmpCurrentOutputRange can indicate the nonlinear range of the currently transmitting transmission power.
  • the transmission power range can be predefined.
  • the transmission power range can be defined as P0.1dB, P1.0dB, P2.0dB, P3.0dB ⁇ , etc.
  • the range or distortion ratio that the power amplifier is currently outputting can be transmitted using a control channel, etc.
  • the present disclosure may propose the following configuration.
  • the present disclosure proposes a method for dividing an operating section of a transmitter power amplifier in a wireless communication system into certain steps including a nonlinear characteristic section.
  • the present disclosure proposes a method for transmitting information about a nonlinear characteristic range in which a transmitter power amplifier of a wireless communication system can operate during a wireless link connection process such as an initial connection.
  • the present disclosure proposes a method of performing demodulation by predicting signal distortion using information about the operating section of a power amplifier during a signal restoration process of a receiver and reflecting it in channel compensation.
  • a wireless communication system only needs to control the operating section of a power amplifier and does not require separate signal processing technology, so it can be easily implemented in a general transmitter structure and has the effect of reducing power consumption.
  • the present disclosure may be suitable for configuring a communication system in the THz band.
  • 3GPP 38.331, 3GPP 38.214, and 3GPP 38.306 may be referenced in interpreting this disclosure.
  • FIG. 26 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.
  • the first node and the second node may correspond to one of a transmitter, a receiver, a terminal, and a base station.
  • the first node may correspond to a transmitter or a terminal
  • the second node may correspond to a receiver or a base station.
  • a method of operating a first node in a communication system includes a step (S2610) of determining transmission power for a signal to be transmitted to a second node, which is one of a plurality of nodes constituting a plurality of paths in a network, a step (S2620) of transmitting transmission power information about the transmission power to the second node, and a step (S2630) of transmitting the signal to the second node based on the transmission power, wherein the transmission power information may include information about a non-linear characteristic of the transmission power.
  • the method further comprises a step of performing an initial access procedure with the second node, wherein profile information regarding a nonlinear power characteristic that the reception power of the signal may have may be transmitted during the initial access procedure.
  • the power information includes information on whether the first node can transmit the signal based on nonlinear power.
  • the transmission power information may include information on a maximum distortion ratio of the power of a signal that the first node can transmit.
  • the transmission power is determined based on one of a plurality of power sections that are preset based on a distortion ratio
  • the transmission power information may include information indicating a power section in which the power of the transmission power is included among the plurality of power sections.
  • the transmission power information may be transmitted based on at least one modulation method among Binary Phase Shift Keying (BPSK) and Quadrature Phase Shift Keying (QPSK).
  • BPSK Binary Phase Shift Keying
  • QPSK Quadrature Phase Shift Keying
  • the transmission power information may be transmitted via a UE-capability message.
  • a first node may be provided in a communication system.
  • the terminal 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 first node according to FIG. 26.
  • one or more non-transitory computer-readable media storing one or more instructions may be provided.
  • the one or more instructions when executed by one or more processors, perform operations, and the operations may include the operating method of the first node according to FIG. 26.
  • a method of operating a second node in a communication system includes a step (S2710) of receiving transmission power information about a second node from a second node that is one of a plurality of nodes constituting a plurality of paths in a network, a step (S2720) of performing compensation for a channel that receives a signal transmitted from the first node based on the transmission power information, and a step (S2730) of obtaining the signal based on the compensated channel, wherein the transmission power information may include information about a non-linear characteristic of the transmission power.
  • the transmission power information may be received based on at least one modulation method among Binary Phase Shift Keying (BPSK) and Quadrature Phase Shift Keying (QPSK).
  • BPSK Binary Phase Shift Keying
  • QPSK Quadrature Phase Shift Keying
  • 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.
  • 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.
  • 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 32 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. 29 and may be composed of various elements, components, units/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. 28.
  • the transceiver(s) (114) may include one or more transceivers (106, 206) and/or one or more antennas (108, 208) of FIG. 29.
  • 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).
  • 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. 28, 100a), a vehicle (Fig. 28, 100b-1, 100b-2), an XR device (Fig. 28, 100c), a portable device (Fig. 28, 100d), a home appliance (Fig. 28, 100e), an IoT device (Fig.
  • Wireless devices may be mobile or stationary depending on the use/service.
  • FIG 33 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. 32, 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 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. 34 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. 32, respectively.
  • the communication unit (110) can transmit and receive signals (e.g., data, control signals, etc.) with external devices such as other vehicles, base stations (e.g., base stations, road side units, etc.), and servers.
  • the control unit (120) can control elements of the vehicle or autonomous vehicle (100) to perform various operations.
  • the control unit (120) can include an ECU (Electronic Control Unit).
  • the drive unit (140a) can drive the vehicle or autonomous vehicle (100) on the ground.
  • the drive unit (140a) can include an engine, a motor, a power train, wheels, brakes, a steering device, etc.
  • the power supply unit (140b) supplies power to the vehicle or autonomous vehicle (100) and can include a wired/wireless charging circuit, a battery, etc.
  • 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 autonomous driving unit (140d) may implement a technology for maintaining a driving lane, a technology for automatically controlling speed such as adaptive cruise control, a technology for automatically driving along a set path, a technology for automatically setting a path and driving when a destination is set, etc.
  • the communication unit (110) can receive map data, traffic information data, etc. from an external server.
  • the autonomous driving unit (140d) can generate an autonomous driving route and driving plan based on the acquired data.
  • the control unit (120) can control the drive unit (140a) so that the vehicle or autonomous vehicle (100) moves along the autonomous driving route according to the driving plan (e.g., speed/direction control).
  • the communication unit (110) can irregularly/periodically acquire the latest traffic information data from an external server and can acquire surrounding traffic information data from surrounding vehicles.
  • the sensor unit (140c) can acquire vehicle status and surrounding environment information.
  • the autonomous driving unit (140d) can update the autonomous driving route and driving plan based on newly acquired data/information.
  • 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 35 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. 32, 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).
  • the memory unit (130) of the XR device (100a) may include information (e.g., data, etc.) required for creating an XR object (e.g., AR/VR/MR object).
  • the input/output unit (140a) may obtain a command to operate the XR device (100a) from the user, and the control unit (120) may operate the XR device (100a) according to the user's operating command. For example, when a user attempts to watch a movie, news, etc. through the XR device (100a), the control unit (120) may transmit content request information to another device (e.g., a mobile device (100b)) or a media server through the communication unit (130).
  • another device e.g., a mobile device (100b)
  • a media server e.g., a media server
  • 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. 32, respectively.
  • 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. 28, 400).
  • the collected history information may be used to update a learning model.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
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  • Nonlinear Science (AREA)
  • Electromagnetism (AREA)
  • Databases & Information Systems (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

Selon divers modes de réalisation divulgués ici, un procédé de fonctionnement d'un premier nœud dans un système de communication peut comprendre les étapes consistant à : déterminer une puissance d'émission pour un signal transmis à un second nœud qui est un nœud d'une pluralité de nœuds constituant une pluralité de chemins dans un réseau ; transmettre au second nœud des informations de puissance d'émission concernant la puissance d'émission ; et transmettre le signal au second nœud sur la base de la puissance d'émission, les informations de puissance d'émission pouvant comprendre des informations concernant une caractéristique non linéaire de la puissance d'émission.
PCT/KR2024/004190 2024-04-01 2024-04-01 Procédé et appareil d'émission et de réception de signal dans un système de communication sans fil Pending WO2025211472A1 (fr)

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190059060A1 (en) * 2017-08-16 2019-02-21 Qualcomm Incorporated Input power backoff signaling
US20190058545A1 (en) * 2017-08-16 2019-02-21 Qualcomm Incorporated Techniques for distortion correction at a receiver device
US20200083934A1 (en) * 2017-12-12 2020-03-12 At&T Intellectual Property I, L.P. Detection scheme utilizing transmitter-supplied non-linearity data in the presence of transmitter non-linearity
KR20230112455A (ko) * 2022-01-20 2023-07-27 삼성전자주식회사 무선 통신 시스템에서 송신단의 비선형성을 보상하기 위한 비선형성 상태 정보 전송 방법 및 장치
US20230246657A1 (en) * 2022-02-03 2023-08-03 Qualcomm Incorporated Power characteristics reporting for signaling using single carrier modulation

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190059060A1 (en) * 2017-08-16 2019-02-21 Qualcomm Incorporated Input power backoff signaling
US20190058545A1 (en) * 2017-08-16 2019-02-21 Qualcomm Incorporated Techniques for distortion correction at a receiver device
US20200083934A1 (en) * 2017-12-12 2020-03-12 At&T Intellectual Property I, L.P. Detection scheme utilizing transmitter-supplied non-linearity data in the presence of transmitter non-linearity
KR20230112455A (ko) * 2022-01-20 2023-07-27 삼성전자주식회사 무선 통신 시스템에서 송신단의 비선형성을 보상하기 위한 비선형성 상태 정보 전송 방법 및 장치
US20230246657A1 (en) * 2022-02-03 2023-08-03 Qualcomm Incorporated Power characteristics reporting for signaling using single carrier modulation

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