Method and apparatus for back-off of wi-fi ap in wireless communication system

Abstract

A method performed by a first node in a wireless communication system, according to one embodiment of the present disclosure, comprises the steps of: receiving, from a first base station (BS), a first signal including a legacy short training field (L-STF), a legacy long training field (L-LTF), and a legacy signal (L-SIG) field; acquiring, from the L-SIG field included in the first signal, information related to the transmission time of a second signal to be transmitted from a second BS to a second node; and performing back-off on the basis of the information related to the transmission time of the second signal, wherein the first signal can be generated through the steps of: adjusting a sampling rate for a wireless fidelity (Wi-Fi) signal; performing a fast Fourier transform (FFT) on the Wi-Fi signal with the adjusted sampling rate; demodulating the Wi-Fi signal on which FFT has been performed; and performing channel coding-related reverse engineering on the demodulated Wi-Fi signal.

Description

Method and device for back-off of WIFI AP in wireless communication system

[0001] The present disclosure relates to a wireless communication system. In particular, the present disclosure relates to a back-off method and device for a WiFi (wireless fidelity) access point (AP).

[0002] Wireless access systems are widely deployed to provide various types of communication services, such as voice and data. Typically, wireless access systems are multiple access systems that support communications with multiple users by sharing available system resources (e.g., bandwidth, transmission power). Examples of 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).

[0003] In particular, as numerous communication devices demand greater communication capacity, enhanced mobile broadband (eMBB) communication technologies are being proposed, improving upon existing radio access technology (RAT). Furthermore, massive machine type communications (mMTC), which connects multiple 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. Various technological configurations are being proposed for these solutions.

[0004] Mobile radio access networks (RANs) are actively exploring new frequency bands to address the continued growth in data usage. In particular, there has been a recent push to utilize the ISM bands (2.4 GHz / 5 GHz / 6 GHz), which offer relatively superior frequency characteristics compared to mmWave, for mobile communication services. However, unlicensed bands are shared by multiple wireless protocols, which means they face more stringent regulations to address coexistence issues, such as transmission power, than licensed bands. Furthermore, interference from other wireless protocols can degrade communication quality.

[0005] Meanwhile, NR-U utilizes unlicensed bands and shares frequency bands with multiple wireless protocols, which may result in degradation of NR-U downlink communication quality due to interference signals from other wireless protocols, such as WiFi. In particular, the 6 GHz (5.925 GHz to 7.125 GHz) band, which NR-U primarily intends to utilize, is a band that both NR-U and WiFi utilize, and NR-U signals have the problem that downlink communication quality may deteriorate due to WiFi interference signals in the 6 GHz band.

[0006] To solve the above-described problems, the present disclosure provides a coexistence scheme between WiFi and NR-U, thereby improving NR-U downlink communication quality in the ISM (Industry-Science-Medical) band.

[0007] In a wireless communication system according to one embodiment of the present disclosure, a method performed by a first node includes the steps of receiving a first signal including an L-STF (Legacy Short Training Field), an L-LTF (Legacy Long Training Field), and an L-SIG (Legacy Signal) field from a first base station (BS), obtaining information regarding a transmission time of a second signal that a second base station intends to transmit to a second node from the L-SIG field included in the first signal, and performing a back-off based on the information regarding the transmission time of the second signal, wherein the first signal may be generated through the steps of: adjusting a sampling rate for a WiFi (Wireless Fidelity) signal, performing an FFT (fast Fourier transform) on the WiFi signal with the adjusted sampling rate, performing demodulation on the WiFi signal on which the FFT was performed, and performing reverse engineering on channel coding on the WiFi signal on which the demodulation was performed.

[0008] The step of obtaining information about the transmission time of the second signal that the second base station intends to transmit to the second node from the L-SIG field included in the first signal may include the step of obtaining length information of the second signal from the L-SIG field and the step of obtaining information about the transmission time of the second signal based on the length information of the second signal.

[0009] The step of performing demodulation on the WiFi signal on which the FFT has been performed may include the step of mapping a PRB (physical resource block) to which the WiFi signal has been mapped to a VRB (virtual resource block), the step of performing demapping on the VRB to which the WiFi signal has been mapped, the step of performing antenna port demapping on the WiFi signal on which the VRB has been demapping, the step of performing layer demapping on the WiFi signal on which the antenna port demapping has been performed, the step of performing demodulation on the WiFi signal on which the layer demapping has been performed, and the step of performing descrambling on the WiFi signal on which the demodulation has been performed.

[0010] The step of performing reverse engineering on channel coding for the WiFi signal on which the demodulation was performed may include the steps of separating a code block included in the WiFi signal on which the demodulation was performed, performing rate dematching on the code block, performing reverse engineering on channel coding for the code block on which the rate dematching was performed, removing a CRC from the code block on which the channel coding was reverse engineered, combining the code blocks from which the CRC was removed to generate a transport block, and removing the CRC from the transport block to generate a first signal.

[0011] In a wireless communication system according to one embodiment of the present disclosure, a method performed by a first base station (BS) includes the steps of generating a first signal including an L-STF (Legacy Short Training Field), an L-LTF (Legacy Long Training Field), and an L-SIG (Legacy Signal) field based on a WiFi (Wireless Fidelity) signal, and transmitting the first signal to a first node, wherein the first signal can be generated through the steps of adjusting a sampling rate for the signal, performing an FFT (fast Fourier transform) on the WiFi signal with the adjusted sampling rate, performing demodulation on the WiFi signal on which the FFT has been performed, and performing channel decoding on the WiFi signal on which the demodulation has been performed.

[0012] The step of performing demodulation on the WiFi signal on which the FFT has been performed may include the step of mapping a PRB (physical resource block) to which the WiFi signal has been mapped to a VRB (virtual resource block), the step of performing demapping on the VRB to which the WiFi signal has been mapped, the step of performing antenna port demapping on the WiFi signal on which the VRB has been demapping, the step of performing layer demapping on the WiFi signal on which the antenna port demapping has been performed, the step of performing demodulation on the WiFi signal on which the layer demapping has been performed, and the step of performing descrambling on the WiFi signal on which the demodulation has been performed.

[0013] The step of performing reverse engineering on channel coding for the WiFi signal on which the demodulation was performed may include the steps of separating a code block included in the WiFi signal on which the demodulation was performed, performing rate dematching on the code block, performing reverse engineering on channel coding for the code block on which the rate dematching was performed, removing a CRC from the code block on which the channel coding was reverse engineered, combining the code blocks from which the CRC was removed to generate a transport block, and generating data for generating a first signal by removing the CRC from the transport block.

[0014] In a communication system according to one embodiment of the present disclosure, a first node comprises 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, the operations include: receiving a first signal including an L-STF (Legacy Short Training Field), an L-LTF (Legacy Long Training Field), and an L-SIG (Legacy Signal) field from a first base station (BS); obtaining information about a transmission time of a second signal that a second base station intends to transmit to a second node from the L-SIG field included in the first signal; and performing a back-off based on the information about the transmission time of the second signal, wherein the first signal comprises: adjusting a sampling rate for a WiFi (Wireless Fidelity) signal; performing a fast Fourier transform (FFT) on the WiFi signal with the adjusted sampling rate; and performing demodulation on the WiFi signal with the FFT performed. The step can be generated through a step of performing channel decoding on the WiFi signal for which the above demodulation has been performed.

[0015] In a communication system according to one embodiment of the present disclosure, a base station (BS) 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, the operations including: generating a first signal including a Legacy Short Training Field (L-STF), a Legacy Long Training Field (L-LTF), and a Legacy Signal (L-SIG) field based on a WiFi (Wireless Fidelity) signal; and transmitting the first signal to a first node, wherein the first signal may be generated through a step of adjusting a sampling rate for the signal, a step of performing a fast Fourier transform (FFT) on the WiFi signal with the adjusted sampling rate, a step of performing demodulation on the WiFi signal on which the FFT has been performed, and a step of performing reverse engineering on channel coding on the WiFi signal on which the demodulation has been performed.

[0016] In one embodiment of the present disclosure, a control device for controlling an electronic device in a communication system comprises at least one processor and at least one memory operably connected to the at least one processor, wherein the at least one memory stores instructions for performing operations based on being executed by the at least one processor, the operations comprising: receiving a first signal including an L-STF (Legacy Short Training Field), an L-LTF (Legacy Long Training Field) and an L-SIG (Legacy Signal) field from a first base station (BS), obtaining information about a transmission time of a second signal that a second base station intends to transmit to a second node from the L-SIG field included in the first signal, and performing a back-off based on the information about the transmission time of the second signal, wherein the first signal adjusts a sampling rate for a WiFi (Wireless Fidelity) signal, performs an FFT (fast Fourier transform) on the WiFi signal with the adjusted sampling rate, and performs an FFT on the WiFi signal on which the FFT is performed. It can be operated to perform demodulation and then perform reverse engineering on channel coding for the WiFi signal on which the demodulation was performed.

[0017] In one embodiment of the present disclosure, a control device for controlling an electronic device in a communication system comprises: at least one processor; and at least one memory operably connected to the at least one processor, wherein the at least one memory stores instructions for performing operations based on being executed by the at least one processor, wherein the operations are operable to generate a first signal including an L-STF (Legacy Short Training Field), an L-LTF (Legacy Long Training Field), and an L-SIG (Legacy Signal) field based on a WiFi (Wireless Fidelity) signal, and transmit the first signal to a first node, and the first signal is generated by adjusting a sampling rate for the signal, performing an FFT (fast Fourier transform) on the WiFi signal with the adjusted sampling rate, performing demodulation on the WiFi signal on which the FFT was performed, and performing channel decoding on the WiFi signal on which the demodulation was performed.

[0018] In one embodiment of the present disclosure, one or more non-transitory computer-readable media storing one or more commands, wherein the one or more commands, based on being executed by one or more processors, perform operations, the operations including: receiving a first signal including an L-STF (Legacy Short Training Field), an L-LTF (Legacy Long Training Field) and an L-SIG (Legacy Signal) field from a first base station (BS), obtaining information about a transmission time of a second signal that a second base station intends to transmit to a second node from the L-SIG field included in the first signal, and performing a back-off based on the information about the transmission time of the second signal, wherein the first signal adjusts a sampling rate for a WiFi (Wireless Fidelity) signal, performs an FFT (fast Fourier transform) on the WiFi signal with the adjusted sampling rate, performs demodulation on the WiFi signal on which the FFT is performed, and, on the WiFi signal on which the demodulation is performed, It can be generated by performing reverse engineering on the Korean channel coding.

[0019] In one embodiment 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 being operable to generate a first signal including a Legacy Short Training Field (L-STF), a Legacy Long Training Field (L-LTF), and a Legacy Signal (L-SIG) field based on a WiFi (Wireless Fidelity) signal, and transmit the first signal to a first node, wherein the first signal is generated by adjusting a sampling rate for the signal, performing a fast Fourier transform (FFT) on the WiFi signal with the adjusted sampling rate, performing demodulation on the WiFi signal on which the FFT was performed, and performing channel decoding on the WiFi signal on which the demodulation was performed.

[0020] According to the present disclosure, by utilizing the asymmetric sensitivity difference of WiFi, a simulated signal is recognized as a WiFi wireless protocol, and at the same time, an AP (access point) or STA (station) determines that the channel is in use for a specific period of time and causes a back-off, thereby mitigating interference during data transmission of NR-U.

[0021] According to the present disclosure, the NR system can practically utilize unlicensed bands.

[0022] The accompanying drawings are intended to aid in understanding the present disclosure and, together with detailed descriptions, may provide embodiments of the present disclosure. However, the technical features of the present disclosure are not limited to specific drawings, and the features disclosed in each drawing may be combined with each other to form new embodiments. Reference numerals in each drawing may indicate structural elements.

[0023] Figure 1 is a drawing showing an example of a communication system applicable to this specification.

[0024] Figure 2 is a drawing showing an example of a wireless device applicable to this specification.

[0025] FIG. 3 is a diagram illustrating a method for processing a transmission signal applicable to the present specification.

[0026] FIG. 4 is a drawing showing another example of a wireless device applicable to this specification.

[0027] FIG. 5 is a drawing showing an example of a mobile device applicable to this specification.

[0028] Figure 6 is a diagram showing physical channels applicable to this specification and a signal transmission method using them.

[0029] Figure 7 is a diagram showing the structure of a wireless frame applicable to this specification.

[0030] Figure 8 is a drawing showing a slot structure applicable to this specification.

[0031] FIG. 9 is a diagram showing an example of a communication structure that can be provided in a 6G system applicable to this specification.

[0032] Figure 10 shows an example of a perceptron structure.

[0033] Figure 11 shows an example of a multilayer perceptron structure.

[0034] Figure 12 shows an example of a deep neural network.

[0035] Figure 13 shows an example of a convolutional neural network.

[0036] Figure 14 is a diagram showing an example of a filter operation in a convolutional neural network.

[0037] Figure 15 shows an example of a neural network structure in which a recurrent loop exists.

[0038] Figure 16 shows an example of the operating structure of a recurrent neural network.

[0039] Figure 17 is a diagram showing an electromagnetic spectrum applicable to this specification.

[0040] Figure 18 is a drawing showing a transmitter structure applicable to this specification.

[0041] Fig. 19 is a drawing showing a modulator structure applicable to this specification.

[0042] FIG. 20 is a diagram showing an example of CTC between WiFi and ZigBee applicable to this specification.

[0043] FIG. 21 is a diagram illustrating an example of an interference scenario due to asymmetric sensitivities of ED and PD applicable to this specification.

[0044] FIG. 22 is a diagram illustrating an example of an NR PHY-layer encoding procedure applicable to the present specification.

[0045] Figure 23 is a diagram showing an example of a channel coding performance result applicable to this specification.

[0046] Figures 24 and 25 are diagrams showing examples of rate matching applicable to this specification.

[0047] FIGS. 26 to 28 are diagrams showing examples of a WiFi legacy signal simulation procedure according to one embodiment of the present specification.

[0048] FIG. 29 is a diagram showing an example of demodulation according to one embodiment of the present specification.

[0049] FIG. 30 is a diagram illustrating an example of reverse engineering for channel coding according to one embodiment of the present specification.

[0050] FIG. 31 is a diagram illustrating an example of a signal transmission and reception method according to one embodiment of the present specification.

[0051] FIG. 32 is a diagram illustrating an example of a signal transmission and reception method according to another embodiment of the present specification.

[0052] The following embodiments combine the components and features of this specification in a predetermined form. Each component or feature may be considered optional unless explicitly stated otherwise. Each component or feature may be implemented without being combined with other components or features. Furthermore, some components and / or features may be combined to form embodiments of this specification. The order of operations described in the embodiments of this specification may be changed. Some components or features of one embodiment may be included in another embodiment or may be replaced with corresponding components or features of another embodiment.

[0053] In the description of the drawings, procedures or steps that may obscure the gist of the present specification are not described, and procedures or steps that can be understood by a person skilled in the art are also not described.

[0054] Throughout the specification, when a part is said to "comprising" (or including) a certain component, this does not mean that other components are excluded, but rather that other components can be included, unless specifically stated otherwise. In addition, terms such as "...part," "...unit," and "module" described in the specification mean a unit that processes at least one function or operation, which may be implemented by hardware, software, or a combination of hardware and software. In addition, the words "a" or "an," "one," "the," and similar related words may be used in the context of describing this specification (especially in the context of the claims below) to include both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context.

[0055] The embodiments of this specification have been described with a focus on the data transmission and reception relationship between a base station and a mobile station. Here, the base station is understood as a terminal node of a network that directly communicates with the mobile station. Certain operations described herein as being performed by the base station may, in some cases, be performed by an upper node of the base station.

[0056] That is, in a network consisting of multiple network nodes including a base station, various operations performed for communication with a mobile station may be performed by the base station or other network nodes other than the base station. In this case, the term 'base station' may be replaced by terms such as fixed station, Node B, eNB (eNode B), gNB (gNode B), ng-eNB, advanced base station (ABS), or access point.

[0057] Additionally, in the embodiments of the present specification, the term terminal may be replaced with terms such as user equipment (UE), mobile station (MS), subscriber station (SS), mobile subscriber station (MSS), mobile terminal, or advanced mobile station (AMS).

[0058] Additionally, a transmitter refers to a fixed and / or mobile node that provides data or voice services, and a receiver refers to a fixed and / or mobile node that receives data or voice services. Therefore, for uplink, a mobile station can be the transmitter, and a base station can be the receiver. Similarly, for downlink, a mobile station can be the receiver, and a base station can be the transmitter.

[0059] Embodiments of the present specification may be supported by standard documents disclosed in at least one of wireless access systems, such as IEEE 802.xx system, 3rd Generation Partnership Project (3GPP) system, 3GPP Long Term Evolution (LTE) system, 3GPP 5G (5th generation) NR (New Radio) system and 3GPP2 system, and in particular, embodiments of the present specification may be supported by 3GPP TS (technical specification) 38.211, 3GPP TS 38.212, 3GPP TS 38.213, 3GPP TS 38.321 and 3GPP TS 38.331 documents.

[0060] Furthermore, the embodiments of this specification may be applied to other wireless access systems and are not limited to the aforementioned systems. For example, they may also be applicable to systems implemented after the 3GPP 5G NR system, and are not limited to a specific system.

[0061] That is, obvious steps or parts not described in the embodiments of this specification may be explained by reference to the above documents. In addition, all terms disclosed in this specification may be explained by the above standard documents.

[0062] Hereinafter, preferred embodiments according to the present specification will be described in detail with reference to the accompanying drawings. The detailed description set forth below, together with the accompanying drawings, is intended to illustrate exemplary embodiments of the present specification and is not intended to represent the only embodiments in which the technical components of the present specification may be implemented.

[0063] Additionally, specific terms used in the embodiments of this specification are provided to aid in understanding of this specification, and the use of these specific terms may be changed to other forms without departing from the technical spirit of this specification.

[0064] The following technology can be applied to various wireless access systems such as CDMA (code division multiple access), FDMA (frequency division multiple access), TDMA (time division multiple access), OFDMA (orthogonal frequency division multiple access), and SC-FDMA (single carrier frequency division multiple access).

[0065] In order to make the following description clear, the following description is based on a 3GPP communication system (e.g., LTE, NR, etc.), but the technical idea of ​​the present invention is not limited thereto. LTE may refer to technology after 3GPP TS 36.xxx Release 8. Specifically, LTE technology after 3GPP TS 36.xxx Release 10 may be referred to as LTE-A, and LTE technology after 3GPP TS 36.xxx Release 13 may be referred to as LTE-A pro. 3GPP NR may refer to technology after TS 38.xxx Release 15. 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.

[0066] For background information, terms, abbreviations, etc. used in this specification, reference may be made to standard documents published prior to the invention of the present invention. For example, reference may be made to the 36.xxx and 38.xxx standard documents.

[0067] Communication systems applicable to this specification

[0068] Although not limited thereto, the various descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed herein may be applied to various fields requiring wireless communication / connectivity (e.g., 5G) between devices.

[0069] Hereinafter, more specific examples will be provided with reference to the drawings. In the drawings / descriptions below, the same drawing reference numerals may represent identical or corresponding hardware blocks, software blocks, or functional blocks, unless otherwise described.

[0070] FIG. 1 is a diagram illustrating an example of a communication system applicable to the present specification. Referring to FIG. 1, a communication system (100) applicable to the present specification includes a wireless device, a base station, and a network. Here, a wireless device refers to a device that performs communication using a wireless access technology (e.g., 5G NR, LTE) and may be referred to as a communication / wireless / 5G device. Although not limited thereto, 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 (artificial intelligence) device / server (100g). For example, 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. Here, the vehicles (100b-1, 100b-2) may include unmanned aerial vehicles (UAVs) (e.g., drones). The XR devices (100c) include augmented reality (AR) / virtual reality (VR) / mixed reality (MR) devices, and may be implemented in the form of head-mounted devices (HMDs), head-up displays (HUDs) installed in vehicles, televisions, smartphones, computers, wearable devices, home appliances, digital signage, vehicles, robots, etc. The portable devices (100d) may include smartphones, smart pads, wearable devices (e.g., smartwatches, smart glasses), computers (e.g., laptops, etc.), etc. The home appliances (100e) may include TVs, refrigerators, washing machines, etc. The IoT devices (100f) may include sensors, smart meters, etc.For example, the base station (120) and the network (130) may also be implemented as wireless devices, and a specific wireless device (120a) may act as a base station / network node to other wireless devices.

[0071] Wireless devices (100a to 100f) can be connected to a network (130) via a base station (120). 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 (100g) via a network (130). The network (130) can be configured using a 3G network, a 4G (e.g., LTE) network, a 5G (e.g., NR) network, etc. The wireless devices (100a to 100f) can communicate with each other via the base station (120) / network (130), but can also communicate directly (e.g., sidelink communication) without going through the base station (120) / network (130). For example, vehicles (100b-1, 100b-2) can communicate directly (e.g., V2V (vehicle to vehicle) / V2X (vehicle to everything) communication). In addition, IoT devices (100f) (e.g., sensors) can communicate directly with other IoT devices (e.g., sensors) or other wireless devices (100a to 100f).

[0072] Wireless communication / connection (150a, 150b, 150c) can be established between wireless devices (100a to 100f) / base stations (120), and base stations (120) / base stations (120). Here, the wireless communication / connection can be established 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)). Through the wireless communication / connection (150a, 150b, 150c), the wireless device and base station / wireless device, and base stations and base stations can transmit / receive wireless signals to / from each other. For example, the wireless communication / connection (150a, 150b, 150c) can transmit / receive signals through various physical channels. To this end, at least some of the 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 may be performed based on various proposals of this specification.

[0073] Communication systems applicable to this specification

[0074] FIG. 2 is a diagram illustrating an example of a wireless device applicable to this specification.

[0075] Referring to FIG. 2, the first wireless device (200a) and the second wireless device (200b) can transmit and receive wireless signals via various wireless access technologies (e.g., LTE, NR). Here, {the first wireless device (200a), the second wireless device (200b)} can correspond to {the wireless device (100x), the base station (120)} and / or {the wireless device (100x), the wireless device (100x)} of FIG. 1.

[0076] A first wireless device (200a) includes one or more processors (202a) and one or more memories (204a), and may further include one or more transceivers (206a) and / or one or more antennas (208a). The processor (202a) controls the memories (204a) and / or the transceivers (206a), and may be configured to implement the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed herein. For example, the processor (202a) may process information in the memory (204a) to generate first information / signals, and then transmit a wireless signal including the first information / signals via the transceivers (206a). In addition, the processor (202a) may receive a wireless signal including second information / signals via the transceivers (206a), and then store information obtained from signal processing of the second information / signals in the memory (204a). The memory (204a) may be connected to the processor (202a) and may store various information related to the operation of the processor (202a). For example, the memory (204a) may perform some or all of the processes controlled by the processor (202a), or may store software code including commands for performing the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed herein. Here, the processor (202a) and the memory (204a) may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). The transceiver (206a) may be connected to the processor (202a) and may transmit and / or receive wireless signals via one or more antennas (208a). The transceiver (206a) may include a transmitter and / or a receiver. The transceiver (206a) may be used interchangeably with an RF (radio frequency) unit. In this specification, wireless device may also mean a communication modem / circuit / chip.

[0077] The second wireless device (200b) includes one or more processors (202b), one or more memories (204b), and may further include one or more transceivers (206b) and / or one or more antennas (208b). The processor (202b) controls the memories (204b) and / or the transceivers (206b), and may be configured to implement the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed herein. For example, the processor (202b) may process information in the memory (204b) to generate third information / signals, and then transmit a wireless signal including the third information / signals via the transceivers (206b). In addition, the processor (202b) may receive a wireless signal including fourth information / signals via the transceivers (206b), and then store information obtained from the signal processing of the fourth information / signals in the memory (204b). The memory (204b) may be connected to the processor (202b) and may store various information related to the operation of the processor (202b). For example, the memory (204b) may perform some or all of the processes controlled by the processor (202b), or may store software code including commands for performing the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed herein. Here, the processor (202b) and the memory (204b) may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). The transceiver (206b) may be connected to the processor (202b) and may transmit and / or receive wireless signals via one or more antennas (208b). The transceiver (206b) may include a transmitter and / or a receiver. The transceiver (206b) may be used interchangeably with an RF unit. In this specification, wireless device may also mean a communication modem / circuit / chip.

[0078] Hereinafter, hardware elements of the wireless device (200a, 200b) will be described in more detail. Although not limited thereto, one or more protocol layers may be implemented by one or more processors (202a, 202b). For example, one or more processors (202a, 202b) may implement one or more layers (e.g., functional layers such as physical (PHY), media access control (MAC), radio link control (RLC), packet data convergence protocol (PDCP), radio resource control (RRC), and service data adaptation protocol (SDAP)). One or more processors (202a, 202b) may generate one or more Protocol Data Units (PDUs) and / or one or more Service Data Units (SDUs) according to the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed herein. One or more processors (202a, 202b) may generate messages, control information, data or information according to the descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed herein. One or more processors (202a, 202b) may 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 (206a, 206b). One or more processors (202a, 202b) may receive signals (e.g., baseband signals) from one or more transceivers (206a, 206b) and obtain PDUs, SDUs, messages, control information, data or information according to the descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed herein.

[0079] One or more processors (202a, 202b) may be referred to as a controller, a microcontroller, a microprocessor, or a microcomputer. One or more processors (202a, 202b) may be implemented by hardware, firmware, software, or a combination thereof. For example, one or more application specific integrated circuits (ASICs), one or more digital signal processors (DSPs), one or more digital signal processing devices (DSPDs), one or more programmable logic devices (PLDs), or one or more field programmable gate arrays (FPGAs) may be included in one or more processors (202a, 202b). The descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed herein 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 specification may be implemented using firmware or software configured to perform one or more processors (202a, 202b) or stored in one or more memories (204a, 204b) and executed by one or more processors (202a, 202b). The descriptions, functions, procedures, suggestions, methods and / or operation flowcharts disclosed in this specification may be implemented using firmware or software in the form of codes, instructions and / or sets of instructions.

[0080] One or more memories (204a, 204b) may be coupled to one or more processors (202a, 202b) and may store various forms of data, signals, messages, information, programs, codes, instructions, and / or commands. The one or more memories (204a, 204b) may be configured as read only memory (ROM), random access memory (RAM), erasable programmable read only memory (EPROM), flash memory, hard drives, registers, cache memory, computer readable storage media, and / or combinations thereof. The one or more memories (204a, 204b) may be located internally and / or externally to the one or more processors (202a, 202b). Additionally, the one or more memories (204a, 204b) may be coupled to the one or more processors (202a, 202b) via various technologies, such as wired or wireless connections.

[0081] One or more transceivers (206a, 206b) can transmit user data, control information, wireless signals / channels, etc., mentioned in the methods and / or flowcharts of this specification to one or more other devices. One or more transceivers (206a, 206b) can receive user data, control information, wireless signals / channels, etc. mentioned in the descriptions, functions, procedures, proposals, methods and / or flowcharts of this specification from one or more other devices. For example, one or more transceivers (206a, 206b) can be connected to one or more processors (202a, 202b) and can transmit and receive wireless signals. For example, one or more processors (202a, 202b) can control one or more transceivers (206a, 206b) to transmit user data, control information, or wireless signals to one or more other devices. Additionally, one or more processors (202a, 202b) may control one or more transceivers (206a, 206b) to receive user data, control information, or wireless signals from one or more other devices. Additionally, one or more transceivers (206a, 206b) may be connected to one or more antennas (208a, 208b), and one or more transceivers (206a, 206b) may be configured to transmit and receive user data, control information, wireless signals / channels, etc., as mentioned in the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed herein, via one or more antennas (208a, 208b). In the present specification, one or more antennas may be multiple physical antennas or multiple logical antennas (e.g., antenna ports). One or more transmitters / receivers (206a, 206b) can convert received user data, control information, wireless signals / channels, etc. from RF band signals to baseband signals in order to process the received user data, control information, wireless signals / channels, etc. using one or more processors (202a, 202b).One or more transceivers (206a, 206b) may convert user data, control information, wireless signals / channels, etc. processed by one or more processors (202a, 202b) from baseband signals to RF band signals. For this purpose, one or more transceivers (206a, 206b) may include an (analog) oscillator and / or filter.

[0082] FIG. 3 is a diagram illustrating a method for processing a transmission signal applied to the present specification. For example, the transmission signal may be processed by a signal processing circuit. At this time, the signal processing circuit (300) may include a scrambler (310), a modulator (320), a layer mapper (330), a precoder (340), a resource mapper (350), and a signal generator (360). At this time, as an example, the operations / functions of FIG. 3 may be performed in the processors (202a, 202b) and / or the transceivers (206a, 206b) of FIG. 2. In addition, as an example, the hardware elements of FIG. 3 may be implemented in the processors (202a, 202b) and / or the transceivers (206a, 206b) of FIG. 2. For example, blocks 310 to 350 may be implemented in the processor (202a, 202b) of FIG. 2, and block 360 may be implemented in the transceiver (206a, 206b) of FIG. 2, and are not limited to the above-described embodiments.

[0083] The codeword can be converted into a wireless signal through the signal processing circuit (300) of FIG. 3. Here, the codeword is an encoded bit sequence of an information block. The information block may include a transport block (e.g., a UL-SCH transport block, a DL-SCH transport block). The wireless signal may be transmitted through various physical channels (e.g., a PUSCH, a PDSCH) of FIG. 6. Specifically, the codeword can be converted into a bit sequence scrambled by a scrambler (310). 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 (320). The modulation scheme may include pi / 2-binary phase shift keying (pi / 2-BPSK), m-phase shift keying (m-PSK), m-quadrature amplitude modulation (m-QAM), etc.

[0084] A complex modulation symbol sequence can be mapped to one or more transmission layers by a layer mapper (330). The modulation symbols of each transmission layer can be mapped to the corresponding antenna port(s) by a precoder (340) (precoding). The output z of the precoder (340) can be obtained by multiplying the output y of the layer mapper (330) by an N*M precoding matrix W. Here, N is the number of antenna ports, and M is the number of transmission layers. Here, the precoder (340) can perform precoding after performing transform precoding (e.g., discrete Fourier transform (DFT) transform) on the complex modulation symbols. In addition, the precoder (340) can perform precoding without performing transform precoding.

[0085] The resource mapper (350) 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 (360) generates a wireless signal from the mapped modulation symbols, and the generated wireless signal can be transmitted to another device through each antenna. To this end, the signal generator (360) can include an inverse fast Fourier transform (IFFT) module, a cyclic prefix (CP) inserter, a digital-to-analog converter (DAC), a frequency uplink converter, and the like.

[0086] The signal processing process for receiving signals in a wireless device can be configured in reverse order of the signal processing process (310-360) of FIG. 3. For example, a wireless device (e.g., 200a, 200b of FIG. 2) can receive wireless signals from the outside through an antenna port / transmitter / receiver. The received wireless signals can be converted into baseband signals through a signal restorer. For this purpose, 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. Thereafter, the baseband signal can be restored to a codeword through a resource demapper process, a postcoding process, a demodulation process, and a descrambling process. The codewords can be restored to the original information blocks through decoding. Accordingly, a signal processing circuit (not shown) for a received signal may include a signal restorer, a resource de-mapper, a postcoder, a demodulator, a de-scrambler, and a decoder.

[0087] Wireless device structure applicable to this specification

[0088] FIG. 4 is a diagram illustrating another example of a wireless device to which the present specification applies.

[0089] Referring to FIG. 4, the wireless device (400) corresponds to the wireless devices (200a, 200b) of FIG. 2 and may be composed of various elements, components, units / units, and / or modules. For example, the wireless device (400) may include a communication unit (410), a control unit (420), a memory unit (430), and additional elements (440). The communication unit may include a communication circuit (412) and a transceiver(s) (414). For example, the communication circuit (412) may include one or more processors (202a, 202b) and / or one or more memories (204a, 204b) of FIG. 2. For example, the transceiver(s) (414) may include one or more transceivers (206a, 206b) and / or one or more antennas (208a, 208b) of FIG. 2. The control unit (420) is electrically connected to the communication unit (410), the memory unit (430), and the additional elements (440) and controls the overall operation of the wireless device. For example, the control unit (420) may control the electrical / mechanical operation of the wireless device based on the program / code / command / information stored in the memory unit (430). In addition, the control unit (420) may transmit information stored in the memory unit (430) to an external device (e.g., another communication device) via a wireless / wired interface through the communication unit (410), or store information received from an external device (e.g., another communication device) via a wireless / wired interface in the memory unit (430).

[0090] The additional element (440) may be configured in various ways depending on the type of the wireless device. For example, the additional element (440) may include at least one of a power unit / battery, an input / output unit, a driving unit, and a computing unit. Although not limited thereto, the wireless device (400) may be implemented in the form of a robot (Fig. 1, 100a), a vehicle (Fig. 1, 100b-1, 100b-2), an XR device (Fig. 1, 100c), a portable device (Fig. 1, 100d), a home appliance (Fig. 1, 100e), an IoT device (Fig. 1, 100f), a digital broadcasting terminal, a hologram device, a public safety device, an MTC device, a medical device, a fintech device (or a financial device), a security device, a climate / environmental device, an AI server / device (Fig. 1, 140), a base station (Fig. 1, 120), a network node, etc. Wireless devices may be mobile or stationary depending on the use / service.

[0091] In FIG. 4, various elements, components, units / parts, and / or modules within the wireless device (400) may be entirely interconnected via a wired interface, or at least some may be wirelessly connected via a communication unit (410). For example, within the wireless device (400), the control unit (420) and the communication unit (410) may be wired, and the control unit (420) and a first unit (e.g., 430, 440) may be wirelessly connected via the communication unit (410). In addition, each element, component, unit / part, and / or module within the wireless device (400) may further include one or more elements. For example, the control unit (420) may be composed of a set of one or more processors. For example, the control unit (420) 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. As another example, the memory unit (430) may be composed of RAM, DRAM (dynamic RAM), ROM, flash memory, volatile memory, non-volatile memory, and / or a combination thereof.

[0092] Mobile devices to which this specification applies

[0093] FIG. 5 is a drawing illustrating an example of a mobile device to which the present specification applies.

[0094] Figure 5 illustrates an example of a mobile device applicable to the present specification. The mobile device may include a smartphone, a smart pad, a wearable device (e.g., a smart watch, smart glasses), 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).

[0095] Referring to FIG. 5, the portable device (500) may include an antenna unit (508), a communication unit (510), a control unit (520), a memory unit (530), a power supply unit (540a), an interface unit (540b), and an input / output unit (540c). The antenna unit (508) may be configured as a part of the communication unit (510). Blocks 510 to 530 / 540a to 540c correspond to blocks 410 to 430 / 440 of FIG. 4, respectively.

[0096] The communication unit (510) can transmit and receive signals (e.g., data, control signals, etc.) with other wireless devices and base stations. The control unit (520) can control components of the portable device (500) to perform various operations. The control unit (520) can include an AP (application processor). The memory unit (530) can store data / parameters / programs / codes / commands required for operating the portable device (500). In addition, the memory unit (530) can store input / output data / information, etc. The power supply unit (540a) supplies power to the portable device (500) and can include a wired / wireless charging circuit, a battery, etc. The interface unit (540b) can support connection between the portable device (500) and other external devices. The interface unit (540b) can include various ports (e.g., audio input / output ports, video input / output ports) for connection with external devices. The input / output unit (540c) can input or output video information / signals, audio information / signals, data, and / or information input from a user. The input / output unit (540c) may include a camera, a microphone, a user input unit, a display unit (540d), a speaker, and / or a haptic module.

[0097] For example, in the case of data communication, the input / output unit (540c) 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 (530). The communication unit (510) can convert the information / signals stored in the memory into wireless signals, and transmit the converted wireless signals directly to other wireless devices or to a base station. In addition, the communication unit (510) 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 (530) and then output in various forms (e.g., text, voice, image, video, haptic) through the input / output unit (540c).

[0098] Physical channels and general signal transmission

[0099] In a wireless access system, a terminal can receive information from a base station via the downlink (DL) and transmit it to the base station via the uplink (UL). The information transmitted and received between the base station and the terminal includes general data and various control information, and various physical channels exist depending on the type and purpose of the information being transmitted and received.

[0100] FIG. 6 is a diagram illustrating physical channels applicable to this specification and a signal transmission method using them.

[0101] When a terminal is powered on again from a powered-off state or newly enters a cell, it performs an initial cell search operation, such as synchronizing with the base station, in step S611. To this end, the terminal receives a primary synchronization channel (P-SCH) and a secondary synchronization channel (S-SCH) from the base station to synchronize with the base station and obtain information such as the cell ID.

[0102] After that, the terminal can obtain broadcast information within the cell by receiving a physical broadcast channel (PBCH) signal from the base station. Meanwhile, the terminal can check the downlink channel status by receiving a downlink reference signal (DL RS) in the initial cell search phase. After completing the initial cell search, the terminal can obtain more specific system information by receiving a physical downlink control channel (PDCCH) and a physical downlink shared channel (PDSCH) based on the physical downlink control channel information in step S612.

[0103] Thereafter, the terminal may perform a random access procedure such as steps S613 to S616 to complete connection to the base station. To this end, the terminal may transmit a preamble through a physical random access channel (PRACH) (S613) and receive a random access response (RAR) for the preamble through a physical downlink control channel and a physical downlink shared channel corresponding thereto (S614). The terminal may transmit a physical uplink shared channel (PUSCH) using scheduling information in the RAR (S615) and perform a contention resolution procedure such as receiving a physical downlink control channel signal and a physical downlink shared channel signal corresponding thereto (S616).

[0104] A terminal that has performed the procedure described above can then perform reception of a physical downlink control channel signal and / or a physical downlink shared channel signal (S617) and transmission of a physical uplink shared channel (PUSCH) signal and / or a physical uplink control channel (PUCCH) signal (S618) as a general uplink / downlink signal transmission procedure.

[0105] Control information transmitted from a terminal to a base station is collectively referred to as uplink control information (UCI). UCI includes hybrid automatic repeat and request acknowledgment / negative ACK (HARQ-ACK / NACK), scheduling request (SR), channel quality indication (CQI), precoding matrix indication (PMI), rank indication (RI), and beam indication (BI) information. UCI is generally transmitted periodically through PUCCH, but depending on the embodiment (e.g., when control information and traffic data must be transmitted simultaneously), it may be transmitted through PUSCH. In addition, the terminal may transmit UCI aperiodically through PUSCH upon request / instruction from the network.

[0106] Figure 7 is a diagram illustrating the structure of a wireless frame applicable to this specification.

[0107] Uplink and downlink transmissions based on the NR system can be based on frames such as those in FIG. 7. At this time, one radio frame has a length of 10 ms and can be defined as two 5 ms half-frames (HF). One half-frame can be defined as five 1 ms subframes (SF). One subframe is divided into one or more slots, and the number of slots within a subframe can depend on the subcarrier spacing (SCS). At this time, each slot can contain 12 or 14 OFDM (A) symbols depending on the cyclic prefix (CP). When a normal CP is used, each slot can contain 14 symbols. When an extended CP is used, each slot can contain 12 symbols. Here, the symbol may include an OFDM symbol (or CP-OFDM symbol), an SC-FDMA symbol (or DFT-s-OFDM symbol).

[0108] Table 1 shows the number of symbols per slot, the number of slots per frame, and the number of slots per subframe according to SCS when a general CP is used, and Table 2 shows the number of symbols per slot, the number of slots per frame, and the number of slots per subframe according to SCS when an extended CSP is used.

[0109] [Table 1]

[0110]

[0111] [Table 2]

[0112]

[0113] In Table 1 and Table 2 above, N slot symb represents the number of symbols in the slot, and N frame,μ slot represents the number of slots in the frame, and N subframe,μ slotcan indicate the number of slots within a subframe.

[0114] Additionally, in a system to which the present specification is applicable, OFDM(A) numerologies (e.g., SCS, CP length, etc.) may be set differently between multiple cells merged into a single terminal. Accordingly, the (absolute time) interval of a time resource (e.g., SF, slot, or TTI) (conveniently referred to as TU (time unit)) consisting of the same number of symbols may be set differently between the merged cells.

[0115] NR can support multiple numerologies (or subcarrier spacing (SCS)) to support various 5G services. For example, a 15 kHz SCS supports wide areas in traditional cellular bands; a 30 kHz / 60 kHz SCS supports dense urban areas, lower latency, and wider carrier bandwidth; and a 60 kHz or higher SCS can support bandwidths greater than 24.25 GHz to overcome phase noise.

[0116] The NR frequency band is defined by two types of frequency ranges (FR1 and FR2). FR1 and FR2 can be configured as shown in the table below. FR2 can also refer to millimeter wave (mmW).

[0117] [Table 3]

[0118]

[0119] In addition, as an example, the numerology described above may be set differently in a communication system to which the present specification is applicable. For example, a terahertz wave (THz) band may be used as a frequency band higher than the FR2 described above. In the THz band, the SCS may be set to be larger than in the NR system, and the number of slots may also be set differently, and is not limited to the above-described embodiment. The THz band will be described later.

[0120] Figure 8 is a drawing illustrating a slot structure applicable to this specification.

[0121] A single slot contains multiple symbols in the time domain. For example, a slot contains seven symbols in a regular CP, but a slot may contain six symbols in an extended CP. A carrier contains multiple subcarriers in the frequency domain. A Resource Block (RB) can be defined as multiple (e.g., 12) consecutive subcarriers in the frequency domain.

[0122] Additionally, a Bandwidth Part (BWP) is defined as multiple consecutive (P)RBs in the frequency domain, and can correspond to one numerology (e.g., SCS, CP length, etc.).

[0123] A carrier can contain up to N (e.g., 5) BWPs. Data communication is performed through an activated BWP, and only one BWP can be activated per terminal. Each element in the resource grid is referred to as a Resource Element (RE), to which a single complex symbol can be mapped.

[0124] 6G communication system

[0125] 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 4 below. In other words, Table 4 is a table showing the requirements of the 6G system.

[0126] [Table 4]

[0127]

[0128] At this time, the 6G system may have key factors such as enhanced mobile broadband (eMBB), ultra-reliable low latency communications (URLLC), massive machine type communications (mMTC), AI integrated communication, tactile internet, high throughput, high network capacity, high energy efficiency, low backhaul and access network congestion, and enhanced data security.

[0129] FIG. 9 is a diagram illustrating an example of a communication structure that can be provided in a 6G system applicable to this specification.

[0130] Referring to Figure 9, 6G systems are expected to have 50 times higher simultaneous wireless communication connectivity than 5G wireless communication systems. URLLC, a key feature of 5G, is expected to become a more prominent technology in 6G communications by providing end-to-end latency of less than 1 ms. Furthermore, 6G systems will have significantly better volumetric spectral efficiency, unlike 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. Furthermore, new network characteristics in 6G may include:

[0131] - Satellite integrated network: 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 could be crucial for 6G.

[0132] Connected Intelligence: Unlike previous generations of wireless communication systems, 6G is revolutionary, upgrading the wireless evolution from "connected objects" to "connected intelligence." AI can be applied at every stage of the communication process (or at every signal processing step, as described below).

[0133] - Seamless integration of wireless information and energy transfer: 6G wireless networks will transfer power to charge the batteries of devices such as smartphones and sensors. Therefore, wireless information and energy transfer (WIET) will be integrated.

[0134] - Ubiquitous super 3-dimension connectivity: Access to networks and core network functions from drones and very low Earth orbit satellites will create super 3-dimension connectivity in 6G ubiquitous.

[0135] Some general requirements for the new network characteristics of 6G, such as the above, may be as follows:

[0136] - Small cell networks: The concept of small cell networks was introduced to improve received signal quality in cellular systems by increasing throughput, energy efficiency, and spectral efficiency. Consequently, small cell networks are essential for 5G and beyond-5G (5GB) communication systems. Accordingly, 6G communication systems also adopt the characteristics of small cell networks.

[0137] Ultra-dense heterogeneous networks: 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.

[0138] 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.

[0139] - Radar technology integrated with mobile technology: 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.

[0140] - Softwarization and virtualization: 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.

[0141] Core implementation technology of 6G systems

[0142] - Artificial Intelligence (AI)

[0143] 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.

[0144] Time-consuming tasks such as handover, network selection, and resource scheduling can be performed instantly using AI. 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.

[0145] Recent attempts to integrate AI into wireless communication systems have focused on the application layer and network layer, particularly deep learning in wireless resource management and allocation. However, this research is increasingly evolving to the MAC layer and physical layer, with attempts to combine deep learning with wireless transmission, particularly in the physical layer. AI-based physical layer transmission refers to applying 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 multiple input multiple output (MIMO) mechanisms, and AI-based resource scheduling and allocation.

[0146] Machine learning can be used for channel estimation and channel tracking, as well as for power allocation and interference cancellation at the physical layer of the downlink (DL). Machine learning can also be used for antenna selection, power control, and symbol detection in MIMO systems.

[0147] However, the application of DNN for transmission at the physical layer may have the following problems.

[0148] Deep learning-based AI algorithms require a large amount of training data to optimize training parameters. However, due to limitations in obtaining training data from specific channel environments, 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.

[0149] Furthermore, current deep learning primarily targets real-world signals. However, signals at the physical layer of wireless communications are complex signals. Further research is needed on neural networks capable of detecting complex domain signals to match the characteristics of wireless communication signals.

[0150] Below, we will look at machine learning in more detail.

[0151] 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. In machine learning, data learning methods can be broadly categorized into three types: supervised learning, unsupervised learning, and reinforcement learning.

[0152] 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.

[0153] Supervised learning uses labeled training data, while unsupervised learning may not have labeled training data. For example, in the case of supervised learning for data classification, the training data may be data in which each training data category is labeled. The 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. The neural network's calculation of the input data and the backpropagation of the error can constitute a learning cycle (epoch). The learning rate can be applied differently depending on the number of iterations of the neural network's learning cycle. For example, in the early stages of training a neural network, a high learning rate can be used to quickly allow the network to achieve a certain level of performance, thereby increasing efficiency. In the later stages of training, a low learning rate can be used to increase accuracy.

[0154] 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.

[0155] 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.

[0156] The neural network cores used in learning methods are largely divided into deep neural networks (DNN), convolutional deep neural networks (CNN), and recurrent Boltzmann machines (RNN), and these learning models can be applied.

[0157] An artificial neural network is an example of a network of multiple perceptrons.

[0158] Figure 10 shows an example of a perceptron structure.

[0159] Referring to Fig. 10, when the input vector x=(x1,x2,...,xd) is input, each component is multiplied by the weight (W1,W2,...,Wd), and all the results are added up, and then the activation function σ( ) is called a perceptron. A large artificial neural network structure can extend the simplified perceptron structure shown in Fig. 10 to apply input vectors to different multi-dimensional perceptrons. For convenience of explanation, input values ​​or output values ​​are called nodes.

[0160] Meanwhile, the perceptron structure illustrated in Fig. 10 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. 4. Fig. 11 shows an example of a multilayer perceptron structure.

[0161] The layer where the input vector is located is called the input layer, the layer where the final output value is located is called the output layer, and all layers located between the input layer and the output layer are called hidden layers. The example in Fig. 4 discloses 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.

[0162] 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 greater the number of hidden layers, the deeper the artificial neural network. The machine learning paradigm that uses sufficiently deep artificial neural networks as learning models is called deep learning. Furthermore, the artificial neural network used for deep learning is called a deep neural network (DNN).

[0163] The deep neural network illustrated in Figure 12 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. In 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. Here, the correlation characteristic can mean the joint probability of inputs and outputs.

[0164] Meanwhile, depending on how multiple perceptrons are connected to each other, various artificial neural network structures different from the aforementioned DNN can be formed.

[0165] In DNN, nodes located within a single layer are arranged in a one-dimensional vertical direction. However, Fig. 13 can assume a case where nodes are arranged two-dimensionally, with w nodes in width and h nodes in height (convolutional neural network structure of Fig. 6). In this case, since 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.

[0166] The convolutional neural network of Fig. 13 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. 7.

[0167] 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. In Fig. 14, a 3×3 filter is applied to the upper left 3×3 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.

[0168] 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. In addition, a neural network with multiple convolutional layers is called a deep convolutional neural network (DCNN).

[0169] In the convolutional layer, 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.

[0170] Meanwhile, depending on the data properties, there may be data for which sequence characteristics are important. Considering the length variability and chronological relationship of such sequence data, 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.

[0171] Figure 15 shows an example of a neural network structure in which a recurrent loop exists.

[0172] Referring to Figure 15, a recurrent neural network (RNN) 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.

[0173] Figure 16 shows an example of the operating structure of a recurrent neural network.

[0174] Referring to Figure 16, the recurrent neural network operates in a predetermined order of time for the input data sequence.

[0175] When the input vector (x1(t), x2(t), ,..., xd(t)) at time point 1 is input to the recurrent neural network, 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 points 2, 3, ,,, T.

[0176] Meanwhile, when multiple hidden layers are placed within a recurrent neural network, it is called a deep recurrent neural network (DRNN). Recurrent neural networks are designed to be useful for processing sequence data (e.g., natural language processing).

[0177] It is a neural network core used in a learning manner, and includes various deep learning techniques such as DNN, CNN, RNN, Restricted Boltzmann Machine (RBM), Deep Belief Network (DBN), and Deep Q-Network, and can be applied to fields such as computer vision, speech recognition, natural language processing, and speech / signal processing.

[0178] Recent attempts to integrate AI into wireless communication systems have focused on the application layer, network layer, and especially deep learning in wireless resource management and allocation. However, this research is increasingly evolving to the MAC layer and physical layer, with attempts to combine deep learning with wireless transmission, particularly at the physical layer. 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.

[0179] THz (Terahertz) communication

[0180] THz communications can be applied in 6G systems. For example, data transmission rates can be increased by increasing bandwidth. This can be achieved by using sub-THz communications with wide bandwidths and applying advanced massive MIMO technology.

[0181] Figure 17 is a diagram illustrating the electromagnetic spectrum applicable to the present specification. For example, referring to Figure 17, THz waves, also known as sub-millimeter radiation, generally represent a frequency band between 0.1 THz and 10 THz with a corresponding wavelength ranging from 0.03 mm to 3 mm. The 100 GHz to 300 GHz band (Sub-THz band) is considered a major portion of the THz band for cellular communications. Adding the Sub-THz band to the mmWave band will increase the capacity of 6G cellular communications. Among the defined THz bands, 300 GHz to 3 THz is in the far infrared (IR) frequency band. Although the 300 GHz to 3 THz band is part of the optical band, it is at the boundary of the optical band and immediately follows the RF band. Therefore, this 300 GHz to 3 THz band exhibits similarities to RF.

[0182] Key characteristics of THz communications 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.

[0183] optical wireless technology

[0184] Optical wireless communication (OWC) technology is planned for 6G communications, in addition to RF-based communications for all possible device-to-access networks. These networks connect to network-to-backhaul / fronthaul networks. OWC technology has already been used in 4G communication systems, but it will be used more widely to meet the demands of 6G communication systems. OWC technologies such as light fidelity, visible light communication, optical camera communication, and wideband-based free space optical (FSO) communication are already well-known. Optical wireless communication can provide very high data rates, low latency, and secure communications. Light detection and ranging (LiDAR) can also be used for ultra-high-resolution 3D mapping in 6G communications based on wideband technology.

[0185] FSO backhaul network

[0186] The characteristics of the transmitter and receiver of an FSO system are similar to those of a fiber-optic network. Therefore, data transmission in an FSO system is similar to that of a fiber-optic system. Therefore, FSO can be a promising technology for providing backhaul connectivity in 6G systems, alongside fiber-optic networks. Using FSO, ultra-long-distance communications are possible, even over distances exceeding 10,000 km. 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 connections.

[0187] Massive MIMO technology

[0188] 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.

[0189] Blockchain

[0190] 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 (P2P) 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.

[0191] 3D networking

[0192] 6G systems integrate terrestrial and airborne networks to support vertically expanded user communications. 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.

[0193] Quantum communication

[0194] Unsupervised reinforcement learning holds promise in the context of 6G networks. Supervised learning approaches cannot label the massive amounts of data generated by 6G networks. Unsupervised learning does not require labeling. Therefore, this technology can be used to autonomously build representations of complex networks. Combining reinforcement learning and unsupervised learning allows for truly autonomous network operation.

[0195] drone

[0196] Unmanned aerial vehicles (UAVs), or drones, will be a key element in 6G wireless communications. In most cases, high-speed wireless connections will be provided using UAV technology. Base stations are installed on UAVs to provide cellular connectivity. UAVs offer specific capabilities not found in fixed base station infrastructure, such as easy deployment, robust line-of-sight links, and controlled mobility. During emergencies such as natural disasters, deploying terrestrial communications infrastructure is not economically feasible, and sometimes, volatile environments make it impossible to provide services. UAVs can easily handle these situations. UAVs will become a new paradigm in wireless communications. This technology facilitates three fundamental requirements for wireless networks: enhanced mobile broadband (eMBB), URLLC, and mMTC. UAVs can also support various purposes, such as enhancing network connectivity, fire detection, disaster emergency services, security and surveillance, pollution monitoring, parking monitoring, and accident monitoring. Therefore, UAV technology is recognized as one of the most important technologies for 6G communications.

[0197] cell-free communication

[0198] 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.

[0199] Wireless Information and Energy Transfer (WIET)

[0200] WIET uses the same fields and waves as wireless communication systems. Specifically, sensors and smartphones will be charged using wireless power transfer during communication. WIET is a promising technology for extending the life of battery-powered wireless systems. Therefore, battery-less devices will be supported by 6G communications.

[0201] Integration of sensing and communication

[0202] Autonomous wireless networks are capable of continuously sensing dynamically changing environmental conditions and exchanging information between different nodes. In 6G, sensing will be tightly integrated with communications to support autonomous systems.

[0203] Integration of Access Backhaul Networks

[0204] In 6G, the density of access networks will be enormous. 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.

[0205] Holographic beamforming

[0206] 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.

[0207] Big data analysis

[0208] Big data analytics is a complex process for analyzing diverse, large-scale data sets, or "big data." This process uncovers hidden data, unknown correlations, and customer trends, ensuring complete data management. Big data is collected from various sources, such as video, social networks, images, and sensors. This technology is widely used to process massive amounts of data in 6G systems.

[0209] large intelligent surface (LIS)

[0210] 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 may 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.

[0211] Fig. 18 is a diagram illustrating a transmitter structure applicable to this specification. In addition, Fig. 19 is a diagram illustrating a modulator structure applicable to this specification.

[0212] Referring to FIGS. 18 and 19, a signal phase, etc. can generally be changed by passing an 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 (O / E) converter can generate a THz pulse according to an optical rectification operation by a nonlinear crystal, an O / E conversion by a photoconductive antenna, an emission from a bunch of relativistic electrons, etc. A terahertz pulse (THz pulse) 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.

[0213] Considering the THz spectrum usage, it is likely that THz systems will use multiple contiguous gigahertz bands for fixed or mobile service purposes. Based on the outdoor scenario criteria, 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.

[0214] Effective down-conversion from the infrared band to the terahertz band (THz band) depends on how to utilize the nonlinearity of the optical / electrical converter (O / E converter). In other words, to down-convert to the desired terahertz band (THz band), it is necessary to design an O / E converter with the most ideal non-linearity for transferring to the corresponding terahertz band (THz band). If an O / E converter that is not suitable for the target frequency band is used, errors are likely to occur in the amplitude and phase of the corresponding pulse.

[0215] In a single-carrier system, a terahertz transmission and reception system can be implemented using a single optical-to-electrical converter. Depending on the channel environment, in a multi-carrier system, 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. In this regard, 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 a plurality of chunks. Each chunk may be composed of at least one component carrier (CC).

[0216] Here, the wireless communication technology implemented in the wireless devices (200a, 200b) of the present specification may include not only LTE, NR, and 6G, but also Narrowband Internet of Things for low-power communication. At this time, for example, NB-IoT technology may be an example of LPWAN (Low Power Wide Area Network) technology, and may be implemented with standards such as LTE Cat NB1 and / or LTE Cat NB2, and is not limited to the above-described names. Additionally or alternatively, the wireless communication technology implemented in the wireless devices (XXX, YYY) of the present specification may perform communication based on LTE-M technology. At this time, for example, LTE-M technology may be an example of LPWAN technology, and may be called by various names such as eMTC (enhanced Machine Type Communication). For example, LTE-M technology can be implemented by at least one of various standards such as 1) LTE CAT 0, 2) LTE Cat M1, 3) LTE Cat M2, 4) LTE non-BL (non-Bandwidth Limited), 5) LTE-MTC, 6) LTE Machine Type Communication, and / or 7) LTE M, and is not limited to the above-described names. Additionally or alternatively, the wireless communication technology implemented in the wireless device (200a, 200b) of the present specification can include at least one of ZigBee, Bluetooth, and Low Power Wide Area Network (LPWAN) considering low-power communication, and is not limited to the above-described names. For example, ZigBee technology can create personal area networks (PAN) related to small / low-power digital communication based on various standards such as IEEE 802.15.4, and can be called by various names.

[0217] Background Technology

[0218] Massive heterogeneous IoT

[0219] 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 IoT applications such as smart buildings and smart hospitals. Not only is the number of wireless devices increasing, but their diversity is also expanding. Wireless devices equipped with various wireless communication technologies (e.g., Bluetooth, ZigBee, Zwave, LoRa, etc.) are emerging, tailored to various applications, such as distance and energy consumption.

[0220] In other words, wireless technologies are rapidly becoming more mass-produced and diversified (heterogeneous), which means efficient operation between heterogeneous devices is becoming increasingly difficult. Numerous studies have demonstrated IoT instability due to frequency shortages in heterogeneous environments, and this problem is expected to worsen with the growth of IoT. In other words, the number of wireless devices using unlicensed bands (e.g., the Industry-Science-Medical (ISM) band) is increasing, inevitably leading to performance degradation due to interference between heterogeneous communications.

[0221] CTC (cross-technology communication)

[0222] Heterogeneous communication technology, commonly referred to as CTC, is a general term for technologies that enable communication between devices with different communication technologies (e.g., WiFi and Bluetooth) without separate hardware. Various CTCs exist across many communication technologies, and they all operate by mimicking each other's signals. For example, CTC between WiFi and ZigBee can be expressed as follows.

[0223] FIG. 20 is a diagram showing an example of CTC between WiFi and ZigBee applicable to this specification.

[0224] Referring to Fig. 20, WiFi uses OFDM QAM (Quadrature Amplitude Modulation) modulation, and can generate signals similar to ZigBee through appropriate constellation points. In other words, a specific bit pattern in WiFi can mimic a ZigBee signal. That is, a specific bit pattern in WiFi corresponds to a specific constellation and can mimic a ZigBee signal. The mimicked ZigBee signal can be received by a commercial ZigBee device. Similarly, signals such as Bluetooth can be generated using WiFi, and ZigBee signals can also be generated from Bluetooth. The present disclosure relates to WiFi signal simulation using NR.

[0225] Spectrum Sharing

[0226] As data traffic continues to grow, mobile communications services require more frequency bands to meet growing demand. However, securing new frequency bands is becoming increasingly difficult. To address this, spectrum sharing technologies, which allow different wireless protocols and services to share the same frequency band, are gaining attention.

[0227] To ensure fair spectrum sharing, interference is minimized through various coexistence methods such as temporal separation and spatial separation. Additionally, transmission power limitation and CCA (Clear Channel Assessment) are utilized to ensure smooth provision of each wireless protocol and service. In particular, WiFi can occupy and transmit channels through the LBT (Listen-Before-Talk) method, and the channel status is checked through the CCA-ED (Energy Detection) method and CCA-PD (Preamble Detection) method. As it becomes difficult to find additional frequency bands in mobile communications, there is an active movement to utilize the ISM band, and NR-U, which utilizes unlicensed bands, also utilizes the LBT method like WiFi.

[0228] CTS (Cross-technology signaling)

[0229] The newly designated unlicensed 6 GHz band is being used competitively by communication technologies such as WiFi (802.11ax), LTE, and NR. The use of these heterogeneous communication technologies can lead to interference between them. For example, interference between NR and WiFi can occur as follows:

[0230] FIG. 21 is a diagram illustrating an example of an interference scenario between NR and WiFi due to asymmetric sensitivities of ED and PD applicable to the present specification.

[0231] Referring to Fig. 21, NR is transmitting data to a user, and a WiFi access point (AP) may be located near the user. In Fig. 21, the ED of WiFi may be -62 dBm and the PD of WiFi may be -82 dBm. Existing communication technologies competitively use channels through the Clear Channel Assessment (CCA) of the MAC layer. However, due to the asymmetric sensitivity of the Energy Detection (ED) and Preamble Detection (PD) and the difference in the preambles of NR and WiFi, WiFi located between the ED and PD may transmit signals without being able to back off. This may act as interference between heterogeneous communications that interferes with the NR signal, and may degrade the overall communication performance.

[0232] Detailed description of the present disclosure

[0233] This disclosure relates to a method for enabling PD on the WiFi side, even with NR signals, by utilizing signal emulation, a core technology of CTC. The overall process of this technology is as follows.

[0234] Step 1: Transmit a signal that emulates the WiFi preamble in one OFDM symbol of NR (Signal Emulation).

[0235] Step 2: The WiFi AP that recognizes the WiFi preamble simulated as an NR signal performs a back-off.

[0236] Step 3: NR signals perform secure communication without WiFi interference.

[0237] Many technologies may be required to realize the above-described process. This disclosure describes (i) a method for controlling the back-off time of a simulated target signal and a WiFi AP, and (ii) a method for simulating a WiFi preamble using NR. First, i) a method for controlling the back-off time of a simulated target signal and a WiFi AP will be described as follows.

[0238] (i) Method for controlling the back-off time of the simulated target signal and the WiFi AP

[0239] WiFi has asymmetric sensitivity of ED and PD, and takes higher sensitivity for the same WiFi radio protocol so that it can determine that the channel is occupied even with a small signal strength (i.e., the signal strength of an AP or STA (station) located further away).

[0240] The present invention can have a scenario in which a simulated signal is recognized as a WiFi wireless protocol by utilizing the difference in asymmetric sensitivity of WiFi, and at the same time, an AP or STA stops transmitting for a specific period of time and causes a back-off to mitigate interference during data transmission of NR-U.

[0241] A signal that satisfies this scenario may be a WiFi legacy preamble. The WiFi legacy preamble may be a 20us signal that includes a legacy short training field (L-STF), a legacy long training field (L-LTF), and a legacy signal (L-SIG) field. The L-SIG field may include length information that can estimate the transmission time of the entire WiFi packet to be transmitted. The length information may be used to adjust the time at which the WiFi AP performs back-off. That is, the WiFi AP can calculate the expected transmission time of the PDed WiFi packet using the length information, and perform back-off based on the calculation result.

[0242] Since a signal that mimics a WiFi legacy preamble is transmitted in one OFDM symbol of NR, the NR signal transmitted after the OFDM symbol may not be interfered with by a WiFi signal for a certain period of time, and secure communication may be possible.

[0243] (ii) A method of simulating a WiFi preamble via NR.

[0244] Reverse engineering of the encoding process of the NR PHY layer can be performed to emulate the WiFi legacy preamble signal via NR.

[0245] The encoding procedure of the NR PHY layer can be defined by the 3GPP TS 38.211 and 3GPP TS 38.212 documents. Each of the 3GPP TS 38.211 and 3GPP TS 38.212 documents can include a Physical channels and modulation part and a Multiplexing and Channel coding part including channel coding. For example, the NR PHY layer encoding procedure can be expressed as follows.

[0246] Figure 22 is a diagram illustrating an example of an NR PHY-layer encoding procedure applicable to the present specification. Figure 23 is a diagram illustrating an example of a channel coding performance result applicable to the present specification. Figures 24 and 25 are diagrams illustrating examples of rate matching applicable to the present specification.

[0247] Referring to FIG. 22, the NR PHY-layer encoding procedure may include the channel coding procedure (S2210) included in 3GPP TS 38.212 and the modulation procedure (S2220) included in TS 38.211. For example, the base station may perform encoding on data through steps S2210 and S2220. The data may be, but is not limited to, PDSCH.

[0248] The channel coding procedure (S2210) may include 1) a transport block CRC attachment step (S2211), 2) an LDPC base graph selection step (S2212), 3) a code block segmentation and CRC attachment step (S2213), 4) a channel coding step (S2214), 5) a rate matching step (S2215), and 6) a code block concatenation step (S2216). Each step is described as follows.

[0249] Transmission block CRC addition step (S2211)

[0250] The base station may add a transmission block CRC to the data. For example, the CRC may be 24 bits, but is not limited thereto.

[0251] LDPC (Low Density Parity Check) base graph selection step (S2212)

[0252] The LDPC base graph selection step can be a trade-off between the complexity of LDPC due to its large computational load and NR performance. The LDPC base graph can be automatically selected once the transport block size and code rate are determined. The base station can select the LDPC base graph based on the transport block size and code rate. This enables efficient channel coding, ensuring stable data transmission and optimized performance.

[0253] Code block segmentation and CRC addition step (S2213)

[0254] The base station can divide a transport block with a transport block CRC into code block units. The base station can add a CRC to the code block.

[0255] Channel coding step (S2214)

[0256] The base station can perform channel coding on the code block to which the CRC is appended. For example, the channel coding can be LDPC coding. For example, referring to FIG. 26, the output bits resulting from the channel coding can be composed of information bits (systematic bits) and parity bits. If there are multiple code blocks to which the CRC is appended, the base station can perform channel coding on a per-code block basis.

[0257] Rate matching step (S2215)

[0258] The base station can perform rate matching on the code blocks on which channel coding has been performed. For example, the rate matching can be NR rate matching. NR rate matching can consist of bit selection and bit interleaving. The base station can adjust the length of the output based on the code rate. If there are multiple code blocks on which channel coding has been performed, the base station can perform rate matching for each code block. Referring to Figure 28, for example, the number of columns is determined so that the bits of the code blocks after channel coding are written one row at a time, creating a total of 8 rows (based on 256QAM). The number of rows can be a fixed value depending on the QAM order (i.e., QPSK-2 bits, 16QAM-4 bits, 64QAM-6 bits, 256QAM-8 bits, or 1,024QAM-10 bits), and the ratio of information bits and parity bits can vary depending on the code rate, and also, the code block size can vary. When all matrices are written, rate matching can be completed by reading one column at a time. In addition, referring to FIG. 29, when rate matching is performed, the output bits can be in the form of a parity bit added to the last part of the information bits.

[0259] Code block combination step (S2216)

[0260] The base station can combine code blocks for which rate matching has been performed. Meanwhile, if there is only one code block, step S2216 may be omitted.

[0261] The modulation procedure (S2220) may include 1) a scrambling step (S2221), 2) a modulation step (S2222), 3) a layer mapping step (S2223), 4) an antenna port mapping step (S2224), 5) a step of mapping to a VRB (Virtual Resource Block) (S2225), and 6) a step of mapping the VRB to a PRB (Physical resource block) (S2226). Each step is described as follows.

[0262] Scrambling step (S2221)

[0263] Scrambling can be a process that adds randomness to transmitted data, thereby ensuring uniform power distribution, mitigating interference, improving data privacy, and enhancing channel estimation accuracy. The base station can perform scrambling on the combined code blocks in step S2216.

[0264] Modulation step (S2222)

[0265] The modulation step may be essential for converting a binary data stream into IQ symbols suitable for wireless transmission. NR can support QPSK, 16QAM, 64QAM, 256QAM, or 1024QAM modulation schemes. The base station can perform modulation on the scrambled code blocks.

[0266] Layer mapping step (S2223)

[0267] The layer mapping step may be the step of distributing modulated symbols across one or more layers for transmission using multiple antennas. This may be a function for multi-input, multi-output (MIMO) and beamforming, and NR can support up to eight layers. The base station can perform layer mapping for the code block on which modulation has been performed.

[0268] Antenna Port Mapping Step (S2224)

[0269] The antenna port mapping step may be a step for mapping data for which layer mapping has been performed to a physical antenna port for a MIMO function. The base station may perform antenna port mapping for a code block for which layer mapping has been performed.

[0270] Step for mapping to VRB (S2225)

[0271] The step of mapping to a VRB may be a step of filling the resource element with PDSCH data while moving from the lowest frequency within the resource grid to a higher frequency, and when the highest frequency is reached, moving to the lowest frequency of the next OFDM symbol. The base station may map the code block for which antenna mapping has been performed to the VRB.

[0272] Step of mapping VRB to PRB (S2226)

[0273] There are two methods for mapping VRBs to PRBs: non-interleaved mapping and interleaved mapping. In NR, the initial configuration may be non-interleaved mapping. The base station can map VRBs with mapped code blocks to PRBs.

[0274] The present disclosure relates to improving the downlink communication quality of NR-U while minimizing modifications to existing NR systems, and can emulate WiFi signals by reverse engineering the NR encoding procedure of FIG. 26. The WiFi signal may be a WiFi legacy preamble. The procedure for emulating the WiFi signal is as follows.

[0275] Figures 26 through 28 illustrate examples of WiFi legacy signal simulation procedures according to one embodiment of the present disclosure. Figure 29 illustrates an example of demodulation according to one embodiment of the present disclosure. Figure 30 illustrates an example of re-engineering for channel coding according to one embodiment of the present disclosure.

[0276] Referring to FIGS. 26 to 28, the WiFi legacy signal simulation procedure may include a sampling rate adjustment procedure (S2610) and a fast Fourier transform (FFT) procedure (S2620), a reverse engineering procedure (S2630) of a modulation procedure (S2220 of FIG. 22) included in 3GPP TS 38.211, and a reverse engineering procedure (S2640) of a channel coding procedure (S2210 of FIG. 22) included in 3GPP TS 38.212. The reverse engineering procedure (S2630) of the modulation procedure (S2220 of FIG. 22) may be a demodulation procedure, and the reverse engineering procedure (S2640) of the channel coding procedure (S2210 of FIG. 22) may be a reverse process of channel coding.

[0277] The reverse engineering procedure (S2630) of the modulation procedure may include 1) a step of mapping a PRB to a VRB (S2631), 2) a step of performing demapping on a signal mapped to a VRB (S2632), 3) an antenna port demapping step (S2633), 4) a layer demapping step (S2634), 5) a demodulation step (S2635), and 6) a descrambling step (S2636).

[0278] The reverse engineering procedure (S2640) of the channel coding procedure may include 1) a code block separation step (S2641), 2) a rate dematching step (S2642), 3) a channel decoding step (S2643), 4) a CRC removal and code block combination step (S2644), and 5) a transport block CRC removal step (S2645).

[0279] The base station can perform WiFi signal simulation through the above S2610 to S2640. The procedures and steps included in the above S2610 to S2640 are described in detail as follows.

[0280] Sampling rate adjustment procedure (S2610)

[0281] The sampling rate of WiFi is 20MHz, and the sampling rate of NR is 30.72MHz, so the sampling rates can be different. The base station can perform upsampling on the WiFi signal. Here, the WiFi signal can be a WiFi legacy preamble or a time domain signal. For example, the base station performs a resampling operation of 400 (20us*20MHz) sample points to 614.4 (20us*30.72MHz). To explain this in detail, the base station can perform 7.68x upsampling (from 400 to 3,072) to not distort the waveform, and then perform 1 / 5x downsampling (from 3,072 to 614). The base station can perform zero padding in the time domain by inserting 614 sample points (20 us) into a frame (66.67 us) consisting of 2,048 zero values ​​corresponding to one NR OFDM symbol. The subcarrier spacing (SCS) can be 15 kHz.

[0282] FTT Procedure (S2620)

[0283] NR utilizes OFDM, and most NR reverse engineering procedures are performed in the frequency domain. Base stations can perform FFTs on WiFi signals. They can convert time-domain WiFi signals into frequency-domain signals. For example, base stations can perform a 2,048-bit FFT.

[0284] Reverse Engineering Procedures for Modification Procedures (S2630)

[0285] Step of mapping PRB to VRB (S2631)

[0286] A base station can map WiFi signals mapped to PRBs to VRBs. For example, a base station can map WiFi signals mapped to PRBs to VRBs using a non-interleaved mapping method.

[0287] Step for performing demapping on signals mapped to VRB (S2632)

[0288] The base station can perform de-mapping on WiFi signals mapped to VRBs. In this case, the PDSCH can be assigned to the third OFDM symbol within the resource grid that can be assigned to PDSCH. Since the base station simulates a signal in the 20 MHz band, if the SCS is 15 kHz, it can consider IQ values ​​corresponding to a total of 106 resource blocks (1,272 subcarriers).

[0289] Antenna port demapping step (S2633)

[0290] The base station can perform demapping on WiFi signals mapped to antenna ports, where the antenna ports can be single antenna ports.

[0291] Layer demapping step (S2634)

[0292] The base station can perform demapping on WiFi signals mapped to layers, where there can be only one layer.

[0293] Demodulation stage (S2635)

[0294] The base station can perform demodulation on the modulated WiFi signal. Referring to FIG. 30, the base station can perform demodulation on the WiFi signal by mapping the IQ value to the nearest constellation, which may result in a simulation error.

[0295] Referring to Fig. 29, however, the error may be small when a more sophisticated modulation (or demodulation) method is used compared to the target signal to be simulated, the WiFi signal. That is, the WiFi signal may be a signal created through a low-order modulation scheme such as BPSK modulation, and in this case, the modulation error may be small even if the base station utilizes QPSK, 16QAM, or 64QAM of a lower order than 256QAM.

[0296] Descrambling step (S2636)

[0297] The base station can perform descrambling on the demodulated WiFi signal. Here, descrambling may be identical to scrambling. Here, the NCellID, which indicates cell information, may be set to an arbitrary value of 0, and the RNTI, which identifies the UE within the cell, may be set to an arbitrary value of 11.

[0298] Reverse Engineering Procedure for Channel Coding Procedures (S2640)

[0299] Code block separation step (S2641)

[0300] The code block step may be a step for separating a combined code block. The base station may separate the combined code block contained in the WiFi signal. The base station may separate the combined code block if the code block contained in the WiFi signal exceeds the maximum length. Meanwhile, if there is only one code block, step S2641 may be omitted.

[0301] Rate dematching step (S2642)

[0302] The base station can perform rate dematching on the separated code blocks in S2641. Referring to FIG. 27, the rear part of each column of the separated code blocks may contain uncontrollable parity bits, and the output may also contain parity bits in the middle. This may result in additional degradation of the simulation similarity.

[0303] Referring to Fig. 29, it can be experimentally confirmed that the WiFi AP performs back-off by searching for a simulated signal, similar to Fig. 28, due to the fact that the number of rows is related to the QAM order and the parity bits are located at the end. Here, since there is no need to consider a scenario of retransmission via HARQ, we consider RV (Redundancy version) = 0, which is used in the very first transmission.

[0304] In addition, in the present disclosure, by considering 256QAM (i.e., QAM order = 8) and a code block of 10,176 bits, it can be expressed in the form of an (8 * 1,272) matrix. Through this process, information bits and parity bits derived from LDPC coding are interleaved, and the length of the output bits can be determined according to the code rate. In the matrix form, one column can mean the IQ value of one resource element. In addition, since there is no need to consider a scenario of retransmission through HARQ, the RV (Redundancy version) used at the very first transmission can be = 0.

[0305] Channel decoding step (S2643)

[0306] The base station can perform channel decoding on the code block on which rate dematching has been performed. If there are multiple code blocks, the base station can perform channel decoding for each code block. The base station can recover the input bits for the WiFi signal by decoding the information bits and parity bits included in the code block. The output generated after LDPC coding in NR can include the information bits (i.e., the input bits). The base station can utilize a one-to-one mapping method that estimates the input bits using the information bits. This eliminates the need to reverse engineer the LDPC coding scheme itself, and the high degree of simulation similarity may enable the WiFi AP to perform back-off.

[0307] CRC removal and code block combination step (S2644)

[0308] The base station can remove the CRC from the code block for which channel decoding has been performed. If there are multiple code blocks, the base station can remove the CRC from each of the multiple code blocks and combine the code blocks from which the CRC has been removed. The base station can combine the code blocks to generate a transport block. Meanwhile, if the size of the transport block does not exceed the maximum code block size of 8448 bits, step S2644 may be omitted.

[0309] Transmission block CRC removal step (S2645)

[0310] A base station can generate a replica of a WiFi signal by removing the CRC from the transmission block. Meanwhile, the size of the CRC can be very small compared to the transmission block size (e.g., 1% of the transmission block size) and may not significantly affect the replica's similarity.

[0311] In the present disclosure, the downlink communication quality of NR-U is improved while minimizing deformation of the existing NR system through the above-described method, and a WiFi legacy preamble signal can be imitated by performing reverse engineering of the NR encoding procedure introduced above.

[0312] FIG. 31 is a diagram illustrating an example of a signal transmission and reception method according to one embodiment of the present specification.

[0313] In Fig. 31, the first node and the second node may be WiFi APs, but are not limited thereto.

[0314] Referring to FIG. 31, a first node may receive a first signal from a first base station (S3110). The first signal may be a simulated signal related to a WiFi signal, and the WiFi signal may be a WiFi legacy preamble. In addition, the first signal may include a Legacy Short Training Field (L-STF), a Legacy Long Training Field (L-LTF), and a Legacy Signal (L-SIG) field. The L-SIG field may include information on the length of a second signal that the second base station intends to transmit to the second node.

[0315] Additionally, the first signal may be generated through a step of adjusting a sampling rate for a WiFi signal, a step of performing FFT on the WiFi signal with the adjusted sampling rate, a step of performing demodulation on the WiFi signal on which the FFT was performed, and a step of performing reverse engineering on channel coding on the WiFi signal on which the demodulation was performed.

[0316] The steps of performing demodulation on a WiFi signal on which FFT has been performed may include 1) a step of mapping a PRB to which a WiFi signal has been mapped to a VRB, 2) a step of performing demapping on the VRB to which the WiFi signal has been mapped, 3) a step of performing antenna port demapping on the WiFi signal on which demapping on the VRB has been performed, 4) a step of performing layer demapping on the WiFi signal on which antenna port demapping has been performed, 5) a step of demodulating the WiFi signal on which layer demapping has been performed, and 6) a step of descrambling the WiFi signal on which demodulation has been performed.

[0317] The step of performing channel decoding on a WiFi signal on which demodulation has been performed may include 1) a step of separating a code block included in the WiFi signal on which demodulation has been performed, 2) a step of rate dematching on the code block, 3) a step of performing reverse engineering on channel coding on the code block on which rate dematching has been performed, 4) a step of removing a CRC from the code block on which reverse engineering on channel coding has been performed and combining the code blocks from which the CRC has been removed to generate a transport block, and 5) a step of generating a first signal by removing the CRC from the transport block.

[0318] The first node can obtain information related to the transmission time of the second signal that the second base station intends to transmit to the second node based on the first signal (S3120). The first node can obtain information about the length of the second signal that the second base station intends to transmit to the second node from the L-SIG field included in the first signal. The first node can obtain information related to the transmission time of the second signal based on the information about the length of the second signal.

[0319] The first node can perform back-off based on information about the transmission time of the second signal (S3130).

[0320] FIG. 32 is a diagram illustrating an example of a signal transmission and reception method according to another embodiment of the present specification.

[0321] In Fig. 32, the first node and the second node may be WiFi APs.

[0322] Referring to FIG. 32, a first base station may generate a first signal related to a WiFi signal (S3210). Here, the first signal may be a simulated signal related to a WiFi signal, and the WiFi signal may be a WiFi legacy preamble. In addition, the first signal may include a Legacy Short Training Field (L-STF), a Legacy Long Training Field (L-LTF), and a Legacy Signal (L-SIG) field. The L-SIG field may include information on the length of a second signal that the second base station intends to transmit to the second node.

[0323] Additionally, the first signal may be generated through a step of adjusting a sampling rate for a WiFi signal, a step of performing FFT on the WiFi signal with the adjusted sampling rate, a step of performing demodulation on the WiFi signal on which the FFT was performed, and a step of performing reverse engineering on channel coding on the WiFi signal on which the demodulation was performed.

[0324] The steps of performing demodulation on a WiFi signal on which FFT has been performed may include 1) a step of mapping a PRB to which a WiFi signal has been mapped to a VRB, 2) a step of performing demapping on the VRB to which the WiFi signal has been mapped, 3) a step of performing antenna port demapping on the WiFi signal on which demapping on the VRB has been performed, 4) a step of performing layer demapping on the WiFi signal on which antenna port demapping has been performed, 5) a step of demodulating the WiFi signal on which layer demapping has been performed, and 6) a step of descrambling the WiFi signal on which demodulation has been performed.

[0325] The step of performing channel decoding on a WiFi signal on which demodulation has been performed may include 1) a step of separating a code block included in the WiFi signal on which demodulation has been performed, 2) a step of rate dematching on the code block, 3) a step of performing reverse engineering on channel coding on the code block on which rate dematching has been performed, 4) a step of removing a CRC from the code block on which reverse engineering on channel coding has been performed and combining the code blocks from which the CRC has been removed to generate a transport block, and 5) a step of obtaining a first signal by removing the CRC from the transport block.

[0326] The first base station can transmit the first signal to the first node (S3220).

[0327] The embodiments described above are combinations of the components and features of the present disclosure in a predetermined form. Each component or feature should be considered optional unless explicitly stated otherwise. Each component or feature may be implemented without being combined with other components or features. Furthermore, it is also possible to combine some components and / or features to form an embodiment of the present disclosure. The order of operations described in the embodiments of the present disclosure may be changed. Some components or features of one embodiment may be included in another embodiment or may be replaced with corresponding components or features of another embodiment. It is self-evident that claims that do not have an explicit citation relationship in the scope of the patent may be combined to form an embodiment or may be incorporated as a new claim through a post-application amendment.

[0328] Embodiments according to the present specification may be implemented by various means, for example, hardware, firmware, software, or a combination thereof. In the case of hardware implementation, an embodiment of the present invention may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, etc.

[0329] When implemented via firmware or software, an embodiment of the present specification may be implemented in the form of a module, procedure, function, or the like that performs the functions or operations described above. The software code may be stored in memory and executed by a processor. The memory may be located within or external to the processor and may exchange data with the processor via various known means.

[0330] It will be apparent to those skilled in the art that this specification may be embodied in other specific forms without departing from the essential characteristics thereof. Therefore, the foregoing detailed description should not be construed in any way as limiting but rather as illustrative. The scope of this specification should be determined by a reasonable interpretation of the appended claims, and all changes within the scope of equivalents herein are intended to be included within the scope of this specification.

Claims

1. A method performed by a first node in a wireless communication system, A step of receiving a first signal including an L-STF (Legacy Short Training Field), an L-LTF (Legacy Long Training Field) and an L-SIG (Legacy Signal) field from a first base station (BS); A step of obtaining information about the transmission time of a second signal that the second base station intends to transmit to the second node from the L-SIG field included in the first signal; and Comprising a step of performing back off based on information about the transmission time of the second signal, The first signal above is, Step for adjusting the sampling rate for WiFi (Wireless Fidelity) signals; A step of performing FFT (fast Fourier transform) on the WiFi signal with the adjusted sampling rate; A step of performing demodulation on the WiFi signal on which the above FFT has been performed; and A method, which is generated through a step of performing reverse engineering on channel coding for a WiFi signal on which the above demodulation has been performed.

2. In paragraph 1, The step of obtaining information about the transmission time of the second signal that the second base station wants to transmit to the second node from the L-SIG field included in the first signal is, A step of obtaining length information of the second signal from the L-SIG field; and A method comprising the step of obtaining information about the transmission time of the second signal based on length information of the second signal.

3. In paragraph 1, The step of performing demodulation on the WiFi signal on which the above FFT has been performed is as follows: A step of mapping the PRB (physical resource block) to which the above WiFi signal is mapped to a VRB (virtual resource block); A step of performing demapping for the VRB to which the WiFi signal is mapped; A step of performing antenna port demapping for a WiFi signal for which demapping has been performed for the above VRB; A step of performing layer demapping on a WiFi signal on which the above antenna port demapping has been performed; A step of performing demodulation on a WiFi signal on which the above layer demapping has been performed; and A method comprising the step of performing descrambling on a WiFi signal on which the above demodulation has been performed.

4. In paragraph 1, The step of performing channel decoding on the WiFi signal for which the above demodulation has been performed is as follows: A step of separating a code block included in the WiFi signal on which the above demodulation has been performed; A step of performing rate dematching for the above code block; A step of performing reverse engineering on channel coding for a code block on which the above rate dematching is performed; A step of removing a CRC from a code block on which reverse engineering regarding the channel coding has been performed, and generating a transmission block by combining the code blocks from which the CRC has been removed; and A method comprising the step of generating a first signal by removing a CRC from the above transmission block.

5. In a method performed by a first base station (BS) in a wireless communication system, A step of generating a first signal including an L-STF (Legacy Short Training Field), an L-LTF (Legacy Long Training Field) and an L-SIG (Legacy Signal) field based on a WiFi (Wireless Fidelity) signal; and comprising a step of transmitting the first signal to the first node; The first signal above is, Step for adjusting the sampling rate for the above signal A step of performing FFT (fast Fourier transform) on the WiFi signal with the adjusted sampling rate; A step of performing demodulation on the WiFi signal on which the above FFT has been performed; and A method, which is generated through a step of performing reverse engineering on channel coding for a WiFi signal on which the above demodulation has been performed.

6. In paragraph 5, The step of performing demodulation on the WiFi signal on which the above FFT has been performed is as follows: A step of mapping the PRB (physical resource block) to which the above WiFi signal is mapped to a VRB (virtual resource block); A step of performing demapping for the VRB to which the WiFi signal is mapped; A step of performing antenna port demapping for a WiFi signal for which demapping has been performed for the above VRB; A step of performing layer demapping on a WiFi signal on which the above antenna port demapping has been performed; A step of performing demodulation on a WiFi signal on which the above layer demapping has been performed; and A method comprising the step of performing descrambling on a WiFi signal on which the above demodulation has been performed.

7. In paragraph 5, The step of performing channel decoding on the WiFi signal for which the above demodulation has been performed is as follows: A step of separating a code block included in the WiFi signal on which the above demodulation has been performed; A step of performing rate dematching for the above code block; A step of performing reverse engineering on channel coding for a code block on which the above rate dematching is performed; A step of removing a CRC from a code block on which reverse engineering regarding the channel coding has been performed, and generating a transmission block by combining the code blocks from which the CRC has been removed; and A method comprising the step of generating data for generating the first signal by removing a CRC from the transmission block.

8. In the first node of the communication system, Transmitter and receiver; at least one processor; and At least one memory operably connectable to said at least one processor and storing instructions that, when executed by said at least one processor, perform operations; The above actions are, A step of receiving a first signal including an L-STF (Legacy Short Training Field), an L-LTF (Legacy Long Training Field) and an L-SIG (Legacy Signal) field from a first base station (BS); A step of obtaining information about the transmission time of a second signal that the second base station intends to transmit to the second node from the L-SIG field included in the first signal; and Comprising a step of performing back off based on information about the transmission time of the second signal, The first signal above is, Step for adjusting the sampling rate for WiFi (Wireless Fidelity) signals; A step of performing FFT (fast Fourier transform) on the WiFi signal with the adjusted sampling rate; A step of performing demodulation on the WiFi signal on which the above FFT has been performed; and A first node generated through a step of performing reverse engineering on channel coding for a WiFi signal on which the above demodulation has been performed.

9. In a communication system, at a base station (BS), Transmitter and receiver; at least one processor; and At least one memory operably connectable to said at least one processor and storing instructions that, when executed by said at least one processor, perform operations; The above actions are, A step of generating a first signal including an L-STF (Legacy Short Training Field), an L-LTF (Legacy Long Training Field) and an L-SIG (Legacy Signal) field based on a WiFi (Wireless Fidelity) signal; and comprising a step of transmitting the first signal to the first node; The first signal above is, A step of adjusting the sampling rate for the above signal; A step of performing FFT (fast Fourier transform) on the WiFi signal with the adjusted sampling rate; A step of performing demodulation on the WiFi signal on which the above FFT has been performed; and A base station generated through a step of performing reverse engineering on channel coding for a WiFi signal on which the above demodulation has been performed.

10. In a control device that controls electronic devices in a communication system, at least one processor; and comprising at least one memory operably connected to at least one of said processors; The at least one memory stores instructions for performing operations based on being executed by the at least one processor, The above actions are, Receive a first signal including an L-STF (Legacy Short Training Field), an L-LTF (Legacy Long Training Field) and an L-SIG (Legacy Signal) field from a first base station (BS), Obtain information about the transmission time of the second signal that the second base station intends to transmit to the second node from the L-SIG field included in the first signal, and, Comprising a step of performing back off based on information about the transmission time of the second signal, The first signal above is, Adjust the sampling rate for WiFi (Wireless Fidelity) signals, Perform FFT (fast Fourier transform) on the WiFi signal with the above-mentioned adjusted sampling rate, Demodulation is performed on the WiFi signal on which the above FFT has been performed, and A control device operative to perform reverse engineering on channel coding of a WiFi signal on which the above demodulation has been performed.

11. In a control device that controls electronic devices in a communication system, at least one processor; and comprising at least one memory operably connected to at least one of said processors; The at least one memory stores instructions for performing operations based on being executed by the at least one processor, The above actions are, Generating a first signal including an L-STF (Legacy Short Training Field), an L-LTF (Legacy Long Training Field) and an L-SIG (Legacy Signal) field based on a WiFi (Wireless Fidelity) signal, and, Transmitting the first signal to the first node, The first signal above is, Adjust the sampling rate for the above signal, Perform FFT (fast Fourier transform) on the WiFi signal with the above-mentioned adjusted sampling rate, Perform demodulation on the WiFi signal on which the above FFT has been performed, A control device operative to perform reverse engineering of channel coding for a WiFi signal on which the above demodulation has been performed.

12. In one or more non-transitory computer-readable media storing one or more instructions, The one or more instructions perform operations based on being executed by one or more processors, The above actions are, Receive a first signal including an L-STF (Legacy Short Training Field), an L-LTF (Legacy Long Training Field) and an L-SIG (Legacy Signal) field from a first base station (BS), Obtain information about the transmission time of the second signal that the second base station intends to transmit to the second node from the L-SIG field included in the first signal, and, Comprising a step of performing back off based on information about the transmission time of the second signal, The first signal above is, Adjust the sampling rate for WiFi (Wireless Fidelity) signals, Perform FFT (fast Fourier transform) on the WiFi signal with the above-mentioned adjusted sampling rate, Demodulation is performed on the WiFi signal on which the above FFT has been performed, and A computer-readable medium operable to perform reverse engineering on channel coding of a WiFi signal on which the above demodulation has been performed.

13. In one or more non-transitory computer-readable media storing one or more instructions, The one or more instructions perform operations based on being executed by one or more processors, The above actions are, Generating a first signal including an L-STF (Legacy Short Training Field), an L-LTF (Legacy Long Training Field) and an L-SIG (Legacy Signal) field based on a WiFi (Wireless Fidelity) signal, and, Transmitting the first signal to the first node, The first signal above is, Adjust the sampling rate for the above signal, Perform FFT (fast Fourier transform) on the WiFi signal with the above-mentioned adjusted sampling rate, Perform demodulation on the WiFi signal on which the above FFT has been performed, A computer-readable medium operable to perform reverse engineering on channel coding of a WiFi signal on which the above demodulation has been performed.

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