WO2025041869A1 - Method and apparatus for transmitting and receiving pss based on orthogonal chirp signal in wireless communication system - Google Patents

Abstract

According to various embodiments of the present disclosure, a method performed by a user equipment (UE) in a wireless communication system may comprise the steps of: receiving, from a base station (BS), orthogonal chirp signals including a plurality of orthogonal chirps, and a primary synchronization signal (PSS) generated on the basis of a PSS sequence; acquiring the PSS sequence from the PSS; and performing synchronization with the base station on the basis of the PSS sequence.

Description

Method and device for transmitting and receiving PSS based on orthogonal chirp signal in wireless communication system

The present disclosure relates to a wireless communication system. In particular, the present disclosure relates to a method and device for transmitting and receiving a primary synchronization signal (PSS) based on an orthogonal chirp signal in a wireless communication system.

Wireless access systems are being widely deployed to provide various types of communication services such as voice and data. In general, wireless access systems are multiple access systems that can support communication with multiple users by sharing available system resources (bandwidth, transmission power, etc.). Examples of multiple access systems include CDMA (code division multiple access) systems, FDMA (frequency division multiple access) systems, TDMA (time division multiple access) systems, OFDMA (orthogonal frequency division multiple access) systems, and SC-FDMA (single carrier frequency division multiple access) systems.

In particular, as many communication devices require large communication capacity, enhanced mobile broadband (eMBB) communication technology is being proposed compared to the existing radio access technology (RAT). In addition, a communication system that considers reliability and latency-sensitive services/UE (user equipment) as well as mMTC (massive machine type communications) that connects a large number of devices and objects to provide various services anytime and anywhere is being proposed. Various technology configurations are being proposed for this.

Meanwhile, among the factors that degrade the performance of the communication system in the THz (terahertz) band communication system, the representative ones are the occurrence of CFO (carrier frequency offset) and PN (phase noise). CFO can generally be caused by RF interference and the Doppler effect, and PN can be caused by RF interference. The occurrence of these CFOs and PNs can cause problems in which PSS detection of the terminal becomes difficult.

To solve the above-described problems, the present disclosure provides a method and device for transmitting and receiving a primary synchronization signal (PSS) based on an orthogonal chirp signal in a wireless communication system.

To address the above-mentioned problems, the present disclosure provides a PSS robust to CFO and PN in the THz band.

A method performed by a user equipment (UE) in a wireless communication system according to one embodiment of the present disclosure may include the steps of receiving, from a base station (BS), orthogonal chirp signals including a plurality of orthogonal chirps and a primary synchronization signal (PSS) generated based on a PSS sequence, obtaining the PSS sequence from the PSS, and performing synchronization with the base station based on the PSS sequence.

The above orthogonal chirp signals can be generated based on the number of the plurality of orthogonal chirps and the periods of the plurality of orthogonal chirps.

The above orthogonal chirp signals can be generated based on the number of the plurality of orthogonal chirps, the period of the plurality of orthogonal chirps, and the carrier frequency offset (CFO).

The above PSS sequence may not be an m-sequence.

A user equipment (UE) operating in a communication system according to one embodiment of the present disclosure may include one or more transceivers, one or more processors controlling the one or more transceivers, and a memory including one or more instructions to be executed by the one or more processors, wherein the one or more instructions may include the steps of receiving, from a base station (BS), orthogonal chirp signals including a plurality of orthogonal chirps and a primary synchronization signal (PSS) generated based on a PSS sequence, the step of obtaining the PSS sequence from the PSS, and the step of performing synchronization with the BS based on the PSS sequence.

A method performed by a base station (BS) in a wireless communication system according to one embodiment of the present disclosure may include a step of generating a primary synchronization signal (PSS) based on orthogonal chirp signals including a plurality of orthogonal chirps and a PSS sequence, a step of transmitting the PSS to a user equipment (UE), and a step of performing synchronization with the UE.

The above orthogonal chirp signals can be generated based on the number of the plurality of orthogonal chirps and the periods of the plurality of orthogonal chirps.

The above orthogonal chirp signals can be generated based on the number of the plurality of orthogonal chirps, the period of the plurality of orthogonal chirps, and the carrier frequency offset (CFO).

The above PSS sequence may not be an m-sequence.

A base station (BS) operating in a communication system according to one embodiment of the present disclosure may include one or more transceivers, one or more processors controlling the one or more transceivers, and a memory including one or more instructions to be executed by the one or more processors, wherein the one or more instructions may include a step of generating a primary synchronization signal (PSS) based on orthogonal chirp signals including a plurality of orthogonal chirps and a PSS sequence, a step of transmitting the PSS to a user equipment (UE), and a step of performing synchronization with the UE.

A device including one or more memories and one or more processors functionally connected to the one or more memories according to one embodiment of the present disclosure may be operable to receive from a base station (BS) orthogonal chirp signals including a plurality of orthogonal chirps and a primary synchronization signal (PSS) generated based on a PSS sequence, obtain the PSS sequence from the PSS, and perform synchronization with the BS based on the PSS sequence.

One or more non-transitory computer-readable media storing one or more commands according to one embodiment of the present disclosure, the computer-readable media being operable to receive from a base station (BS) orthogonal chirp signals including a plurality of orthogonal chirps and a primary synchronization signal (PSS) generated based on a PSS sequence, obtain the PSS sequence from the PSS, and perform synchronization with the BS based on the PSS sequence.

According to the present disclosure, a PSS robust to CFO and PN can be generated by generating the PSS based on an orthogonal chirp signal.

According to the present disclosure, the PSS search probability can be increased in a communication system of the THz band by performing synchronization using a PSS generated based on an orthogonal chirp signal.

According to the present disclosure, flexible sequence selection can be achieved by generating PSS based on orthogonal chirp signals.

The drawings attached below are intended to aid in understanding the present disclosure and may provide embodiments of the present disclosure together with detailed descriptions. 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 a new embodiment. Reference numerals in each drawing may mean structural elements.

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

FIG. 2 is a drawing showing an example of a wireless device applicable to this specification.

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

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

FIG. 5 is a drawing showing an example of a portable device applicable to this specification.

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

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

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

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

Figure 10 shows an example of a perceptron structure.

Figure 11 shows an example of a multilayer perceptron structure.

Figure 12 shows an example of a deep neural network.

Figure 13 shows an example of a convolutional neural network.

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

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

Figure 16 shows an example of the operational structure of a recurrent neural network.

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

Fig. 18 is a drawing showing a THz communication method applicable to this specification.

FIG. 19 is a diagram illustrating a THz wireless communication transceiver applicable to the present specification.

FIG. 20 is a diagram illustrating a THz signal generation method applicable to the present specification.

FIG. 21 is a diagram illustrating a wireless communication transceiver applicable to this specification.

Figure 22 is a drawing showing a transmitter structure applicable to this specification.

Figure 23 is a drawing showing a modulator structure applicable to this specification.

Figure 24 is a diagram illustrating an example of a PN model in a wireless communication system.

Figure 25 is a conceptual diagram illustrating an example of PSS search probability in a wireless communication system.

Figure 26 is a diagram illustrating an example of ICI occurrence in a wireless communication system.

Figure 27 is a diagram illustrating an example of BER according to the SNR of each CFO in a wireless communication system.

Figure 28 is a diagram illustrating a linear chirp signal in a wireless communication system on the time/magnitude axis.

Figure 29 is a diagram illustrating a linear chirp signal in a wireless communication system on the time/frequency axis.

Figure 30 is a diagram illustrating an example of a typical chirp signal in a wireless communication system.

FIG. 31 is a diagram illustrating an example of an orthogonal chirp signal in a wireless communication system.

FIG. 32 is a diagram illustrating an example of an OFDM signal in a wireless communication system.

FIG. 33 is a diagram illustrating an example of an OCDM signal in a wireless communication system.

Figures 34 and 35 are diagrams illustrating examples of NR PSS autocorrelation in a wireless communication system.

Figures 36 and 37 are diagrams illustrating examples of NR PSS cross-correlation in a wireless communication system.

FIG. 38 is a diagram illustrating an example of autocorrelation of an orthogonal chirp PSS according to an embodiment of the present disclosure in a wireless communication system.

FIG. 39 is a diagram illustrating an example of cross-correlation of orthogonal chirp PSSs according to an embodiment of the present disclosure in a wireless communication system.

FIGS. 40 to 44 are diagrams illustrating examples of autocorrelation performance comparisons of NR PSS and orthogonal chirp PSS according to an embodiment of the present disclosure in a wireless communication system.

FIGS. 45 to 46 are diagrams illustrating examples of the effect of orthogonal chirp PSS according to one embodiment of the present disclosure in a wireless communication system.

Figure 47 is a flowchart of a signal transmission and reception method according to one embodiment of the present disclosure.

FIG. 48 is a flowchart of a signal transmission and reception method according to another embodiment of the present disclosure.

The following embodiments combine the components and features of the present specification in a predetermined form. Each component or feature may be considered optional unless otherwise explicitly stated. Each component or feature may be implemented in a form that is not combined with other components or features. In addition, some components and/or features may be combined to form an embodiment of the present specification. The order of operations described in the embodiments of the present 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.

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 those skilled in the art are also not described.

Throughout the specification, when a part is said to "comprising" or "including" a component, this does not mean that other components are excluded, but rather that other components can be included, unless otherwise specifically stated. In addition, terms such as "part," "unit," "module," etc. 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, "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 the context.

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 meant as a terminal node of a network that directly communicates with a mobile station. A specific operation described as being performed by the base station in this specification may in some cases be performed by an upper node of the base station.

That is, in a network consisting of a plurality of 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 'base station' may be replaced by terms such as a fixed station, a Node B, an eNode B (eNB), a gNode B (gNB), an ng-eNB, an advanced base station (ABS), or an access point.

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).

In addition, the transmitter refers to a fixed and/or mobile node that provides data service or voice service, and the receiver refers to a fixed and/or mobile node that receives data service or voice service. Accordingly, in the case of uplink, a mobile station can be a transmitter and a base station can be a receiver. Similarly, in the case of downlink, a mobile station can be a receiver and a base station can be a transmitter.

Embodiments of the present specification may be supported by standard documents disclosed in at least one of wireless access systems, namely 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.

In addition, the embodiments of the present specification may be applied to other wireless access systems and are not limited to the above-described system. For example, they may be applied to systems applied after the 3GPP 5G NR system and are not limited to a specific system.

That is, obvious steps or parts that are not described in the embodiments of this specification can be described by referring to the above documents. In addition, all terms disclosed in this specification can be described by the above standard documents.

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 explain exemplary embodiments of the present specification and is not intended to represent the only embodiments in which the technical configuration of the present specification may be implemented.

In addition, specific terms used in the embodiments of this specification are provided to help understanding of this specification, and the use of such specific terms may be changed to other forms without departing from the technical spirit of this specification.

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).

In the following, for the sake of clarity, the description is based on a 3GPP communication system (e.g., LTE, NR, etc.), but the technical spirit 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.

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 standard documents 36.xxx and 38.xxx.

Communication systems applicable to this specification

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

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

FIG. 1 is a diagram illustrating an example of a communication system applied to the present specification. Referring to FIG. 1, a communication system (100) applied to the present specification includes a wireless device, a base station, and a network. Here, the wireless device means 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 Thing) 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 a head-mounted device (HMD), a head-up display (HUD) equipped in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, digital signage, a vehicle, a robot, etc. The portable devices (100d) may include a smartphone, a smart pad, a wearable device (e.g., a smart watch, smart glasses), a computer (e.g., a laptop, etc.), etc. The home appliances (100e) may include a TV, a refrigerator, a washing machine, etc. The IoT devices (100f) may include sensors, smart meters, etc. For example, the base station (120) and 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.

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). Additionally, IoT devices (100f) (e.g., sensors) can communicate directly with other IoT devices (e.g., sensors) or other wireless devices (100a to 100f).

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 communication between base stations (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 the base station and base station can transmit/receive wireless signals to 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.

Communication systems applicable to this specification

FIG. 2 is a drawing illustrating an example of a wireless device to which the present specification can be applied.

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.

A first wireless device (200a) includes one or more processors (202a) and one or more memories (204a), and may additionally include one or more transceivers (206a) and/or one or more antennas (208a). The processor (202a) controls the memory (204a) and/or the transceiver (206a), and may be configured to implement the descriptions, functions, procedures, suggestions, methods, and/or operational flowcharts disclosed herein. For example, the processor (202a) may process information in the memory (204a) to generate first information/signal, and then transmit a wireless signal including the first information/signal via the transceiver (206a). In addition, the processor (202a) may receive a wireless signal including second information/signal via the transceiver (206a), and then store information obtained from signal processing of the second information/signal 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 codes including instructions for performing the descriptions, functions, procedures, proposals, methods, and/or operational 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.

The second wireless device (200b) includes one or more processors (202b), one or more memories (204b), and may additionally include one or more transceivers (206b) and/or one or more antennas (208b). The processor (202b) may control the memories (204b) and/or the transceivers (206b), and may be configured to implement the descriptions, functions, procedures, suggestions, 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 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 codes including instructions for performing the descriptions, functions, procedures, proposals, methods, and/or operational 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.

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), 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, 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.

The one or more processors (202a, 202b) may be referred to as a controller, a microcontroller, a microprocessor, or a microcomputer. The 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 the one or more processors (202a, 202b). The descriptions, functions, procedures, suggestions, 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 operational flowcharts disclosed in this specification may be implemented using firmware or software configured to perform the descriptions, functions, procedures, suggestions, methods and/or operational flowcharts disclosed in this specification may be included in 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 operational flowcharts disclosed in this specification may be implemented using firmware or software in the form of codes, instructions and/or sets of instructions.

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 comprised of 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.

One or more transceivers (206a, 206b) can transmit user data, control information, wireless signals/channels, etc., referred to 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., referred to in the descriptions, functions, procedures, suggestions, methods and/or flowcharts of this specification from one or more other devices. For example, one or more transceivers (206a, 206b) can be coupled 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 coupled 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, and the like, as referred to in the descriptions, functions, procedures, suggestions, 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 transceivers (206a, 206b) may convert received user data, control information, wireless signals/channels, etc. from RF band signals to baseband signals for processing using one or more processors (202a, 202b). One or more transceivers (206a, 206b) may convert processed user data, control information, wireless signals/channels, etc. from baseband signals to RF band signals using one or more processors (202a, 202b). For this purpose, one or more transceivers (206a, 206b) may include an (analog) oscillator and/or filter.

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 operation/function of FIG. 3 may be performed in the processor (202a, 202b) and/or the transceiver (206a, 206b) of FIG. 2. In addition, as an example, the hardware elements of FIG. 3 may be implemented in the processor (202a, 202b) and/or the transceiver (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.

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 can include a transport block (e.g., a UL-SCH transport block, a DL-SCH transport block). The wireless signal can 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 can include ID information of a wireless device, etc. The scrambled bit sequence can be modulated into a modulation symbol sequence by a modulator (320). The modulation scheme can include pi/2-BPSK (pi/2-binary phase shift keying), m-PSK (m-phase shift keying), m-QAM (m-quadrature amplitude modulation), etc.

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

The resource mapper (350) can map modulation symbols of each antenna port to time-frequency resources. The time-frequency resources can include a plurality of symbols (e.g., CP-OFDMA symbols, DFT-s-OFDMA symbols) in the time domain and a plurality of 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, etc.

The signal processing process for receiving signals in a wireless device can be configured in reverse order of the signal processing process (310 to 360) of FIG. 3. For example, a wireless device (e.g., 200a and 200b of FIG. 2) can receive a wireless signal from the outside through an antenna port/transceiver. The received wireless signal can be converted into a baseband signal through a signal restorer. To this end, 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 descramble process. The codeword can be restored to an original information block through decoding. Accordingly, a signal processing circuit (not shown) for a received signal may include a signal restorer, a resource de-mapper, a postcoder, a demodulator, a de-scrambler and a decoder.

Wireless device structure applicable to this specification

FIG. 4 is a drawing illustrating another example of a wireless device to which the present specification applies.

Referring to FIG. 4, the wireless device (400) corresponds to the wireless device (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 overall operations of the wireless device. For example, the control unit (420) may control electrical/mechanical operations of the wireless device based on programs/codes/commands/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).

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.

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 the 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 one or more processor sets. 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.

Mobile devices to which this specification applies

FIG. 5 is a drawing illustrating an example of a portable device to which the present specification applies.

FIG. 5 illustrates an example of a mobile device to which the present specification applies. The mobile device may include a smart phone, a smart pad, a wearable device (e.g., a smart watch, a smart glass), 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).

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.

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 image information/signals, audio information/signals, data, and/or information input from a user. The input/output unit (540c) can include a camera, a microphone, a user input unit, a display unit (540d), a speaker, and/or a haptic module.

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) converts the information/signals stored in the memory into wireless signals, and can directly transmit the converted wireless signals to other wireless devices or to a base station. 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).

Physical channels and general signal transmission

In a wireless access system, a terminal can receive information from a base station through the downlink (DL) and transmit information to the base station through the uplink (UL). The information transmitted and received by the base station and the terminal includes general data information and various control information, and various physical channels exist depending on the type/purpose of the information they transmit and receive.

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

When a terminal is powered on again from a powered off state or enters a new cell, it performs an initial cell search task such as synchronizing with the base station at step S611. To do this, the terminal can receive 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 a cell ID.

Thereafter, the terminal can receive a physical broadcast channel (PBCH) signal from the base station to obtain broadcast information within the cell. Meanwhile, the terminal can receive a downlink reference signal (DL RS) in the initial cell search phase to check the downlink channel status. After completing the initial cell search, the terminal can receive a physical downlink control channel (PDCCH) and a physical downlink shared channel (PDSCH) according to the physical downlink control channel information in step S612 to obtain more specific system information.

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).

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.

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 acknowledgement/negative-ACK (HARQ-ACK/NACK), scheduling request (SR), channel quality indication (CQI), precoding matrix indication (PMI), rank indication (RI), beam indication (BI) information, etc. In this case, 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 aperiodically transmit UCI through PUSCH upon request/instruction from the network.

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

Uplink and downlink transmission 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 by two 5 ms half-frames (half-frames, HF). One half-frame can be defined by five 1 ms subframes (subframes, SF). One subframe is divided into one or more slots, and the number of slots in a subframe can depend on subcarrier spacing (SCS). At this time, each slot can include 12 or 14 OFDM (A) symbols depending on CP (cyclic prefix). When normal CP is used, each slot can include 14 symbols. When extended CP is used, each slot can include 12 symbols. Here, the symbol may include an OFDM symbol (or CP-OFDM symbol), an SC-FDMA symbol (or DFT-s-OFDM symbol).

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 CP is used.

In the above Tables 1 and 2, N ^slot _symb may represent the number of symbols in a slot, N ^frame,μ _slot may represent the number of slots in a frame, and N ^subframe,μ _slot may represent the number of slots in a subframe.

In addition, 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 that are merged into one terminal. Accordingly, the (absolute time) section of a time resource (e.g., SF, slot or TTI) (conveniently, collectively called TU (time unit)) consisting of the same number of symbols may be set differently between the merged cells.

NR can support multiple numerologies (or subcarrier spacing (SCS)) to support various 5G services. For example, when the SCS is 15 kHz, it supports wide area in traditional cellular bands, when the SCS is 30 kHz/60 kHz, it supports dense-urban, lower latency and wider carrier bandwidth, and when the SCS is 60 kHz or higher, it can support bandwidths larger than 24.25 GHz to overcome phase noise.

The NR frequency band is defined by two types of frequency ranges (FR1, FR2). FR1 and FR2 can be configured as shown in the table below. In addition, FR2 can mean millimeter wave (mmW).

In addition, as an example, the numerology described above may be set differently in a communication system to which the present specification is applicable. As an 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 larger than that of 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.

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

A slot contains multiple symbols in the time domain. For example, in the case of normal CP, a slot contains 7 symbols, but in the case of extended CP, a slot may contain 6 symbols. A carrier contains multiple subcarriers in the frequency domain. An RB (Resource Block) can be defined as multiple (e.g., 12) consecutive subcarriers in the frequency domain.

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.).

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

6G communication system

The 6G (wireless communication) system aims at (i) very high data rates per device, (ii) a very large number of connected devices, (iii) global connectivity, (iv) very low latency, (v) lower energy consumption of battery-free IoT devices, (vi) ultra-reliable connectivity, and (vii) connected intelligence with machine learning capabilities. The vision of the 6G system can be 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. That is, Table 4 is a table showing the requirements of the 6G system.

At this time, 6G systems 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.

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

Referring to Fig. 9, the 6G system is expected to have 50 times higher simultaneous wireless communication connectivity than the 5G wireless communication system. URLLC, a key feature of 5G, is expected to become a more important technology in 6G communication by providing end-to-end delay of less than 1 ms. At this time, the 6G system will have much better volumetric spectral efficiency than the frequently used area spectral efficiency. The 6G system can provide very long battery life and advanced battery technology for energy harvesting, so that mobile devices in the 6G system may not need to be charged separately. In addition, new network characteristics in 6G may be as follows.

- Satellite integrated network: 6G is expected to be integrated with satellites to provide a global mobile constellation. The integration of terrestrial, satellite and airborne networks into a single wireless communication system could be crucial for 6G.

- Connected intelligence: Unlike previous generations of wireless communication systems, 6G is revolutionary and will update the wireless evolution from “connected things” to “connected intelligence.” AI can be applied at each stage of the communication process (or at each stage of signal processing, as described below).

- 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.

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

Some general requirements from the new network characteristics of 6G as mentioned above can be as follows:

- Small cell networks: The idea of small cell networks was introduced to improve the quality of received signals as a result of increased throughput, energy efficiency, and spectrum efficiency in cellular systems. As a result, small cell networks are an essential feature for 5G and beyond 5G (5GB) communication systems. Accordingly, 6G communication systems also adopt the characteristics of small cell networks.

- Ultra-dense heterogeneous network: Ultra-dense heterogeneous networks will be another important feature of 6G communication systems. A multi-tier network composed of heterogeneous networks improves overall QoS and reduces costs.

- High-capacity backhaul: Backhaul connections are characterized by high-capacity backhaul networks to support high-capacity traffic. High-speed fiber optics and free-space optics (FSO) systems may be possible solutions to this problem.

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

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

Core implementation technology of 6G system

- Artificial Intelligence (AI)

The most important and newly introduced technology in the 6G system is AI. The 4G system did not involve AI. The 5G system will support partial or very limited AI. However, the 6G system will be fully AI-supported for automation. Advances in machine learning will create more intelligent networks for real-time communications in 6G. Introducing AI in communications can simplify and improve real-time data transmission. AI can use numerous analyses to determine how complex target tasks are performed. In other words, AI can increase efficiency and reduce processing delays.

Time-consuming tasks such as handover, network selection, and resource scheduling can be performed instantly using AI. AI can also play a significant role in M2M, machine-to-human, and human-to-machine communication. AI can also be a rapid communication in brain computer interface (BCI). AI-based communication systems can be supported by metamaterials, intelligent structures, intelligent networks, intelligent devices, intelligent cognitive radios, self-sustaining wireless networks, and machine learning.

Recently, there have been attempts to integrate AI with wireless communication systems, but these have been focused on the application layer, network layer, and especially deep learning in the field of wireless resource management and allocation. However, these studies are gradually developing into the MAC layer and physical layer, and in particular, there are attempts to combine deep learning with wireless transmission in the physical layer. AI-based physical layer transmission means applying signal processing and communication mechanisms based on AI drivers rather than traditional communication frameworks in terms of fundamental signal processing and communication mechanisms. For example, it can 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.

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

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

Deep learning-based AI algorithms require a large amount of training data to optimize training parameters. However, due to limitations in obtaining data in a specific channel environment as training data, a large amount of training data is used offline. This is because static training on training data in a specific channel environment can cause a conflict between the dynamic characteristics and diversity of the wireless channel.

In addition, current deep learning mainly targets real signals. However, the signals of the physical layer of wireless communication are complex signals. In order to match the characteristics of wireless communication signals, more research is needed on neural networks that detect complex domain signals.

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

Machine learning refers to a series of operations that teach machines to create machines that can perform tasks that people can or cannot do. Machine learning requires data and a learning model. In machine learning, data learning methods can be broadly divided into three: supervised learning, unsupervised learning, and reinforcement learning.

Neural network learning is to minimize the error of the output. Neural network learning is a process of repeatedly inputting learning data into the neural network, calculating the neural network output and target error for the learning data, and backpropagating the neural network error from the output layer of the neural network to the input layer in the direction of reducing the error, thereby updating the weights of each node of the neural network.

Supervised learning uses training data with correct answers labeled in the training data, while unsupervised learning may not have correct answers labeled in the training data. That is, for example, in the case of supervised learning for data classification, the training data may be data in which each category is labeled in the training data. The labeled training data is input to the neural network, and the error can be calculated by comparing the output (category) of the neural network with the label of the training data. The calculated error is backpropagated in the neural network in the reverse 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 according to the backpropagation. The amount of change in the connection weights of each node that is updated can be determined according to 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 repetitions of the learning cycle of the neural network. For example, in the early stages of learning a neural network, a high learning rate can be used to allow the network to quickly achieve a certain level of performance, thereby increasing efficiency, while in the later stages of learning, a low learning rate can be used to increase accuracy.

Depending on the characteristics of the data, the learning method may vary. For example, if the goal is to accurately predict data transmitted from the transmitter to the receiver in a communication system, it is preferable to perform learning using supervised learning rather than unsupervised learning or reinforcement learning.

The learning model corresponds to the human brain, and the most basic linear model can be thought of, but the machine learning paradigm that uses highly complex neural network structures, such as artificial neural networks, as learning models is called deep learning.

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

An artificial neural network is an example of multiple perceptrons connected together.

Figure 10 shows an example of a perceptron structure.

Referring to Fig. 10, when an input vector x=(x1,x2,...,xd) is input, the entire process of multiplying each component by a weight (W1,W2,...,Wd), adding up all the results, and then applying the activation function σ() is called a perceptron. A large artificial neural network structure can extend the simplified perceptron structure illustrated in Fig. 10 to apply the input vector to perceptrons of different dimensions. For convenience of explanation, input values or output values are called nodes.

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.

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 shows three layers, but when counting the number of actual artificial neural network layers, the input layer is excluded, so it can be viewed as a total of two layers. The artificial neural network is composed of perceptrons of basic blocks connected in two dimensions.

The above-mentioned input layer, hidden layer, and output layer can be applied jointly not only to multilayer perceptron but also to various artificial neural network structures such as CNN and RNN, which will be described later. The more hidden layers there are, the deeper the artificial neural network becomes, and the machine learning paradigm that uses a sufficiently deep artificial neural network as a learning model is called deep learning. In addition, the artificial neural network used for deep learning is called a deep neural network (DNN: Deep neural network).

The deep neural network illustrated in Fig. 12 is a multilayer perceptron composed of eight hidden layers and eight output layers. The multilayer perceptron structure is expressed as a fully-connected neural network. In a fully-connected neural network, there is no connection relationship between nodes located in the same layer, and there is a connection relationship 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.

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

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.

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 is a small filter, and performs weighted sum and activation function operations on the overlapping portions of the filters, as in Fig. 7.

One filter has a weight corresponding to the number of its size, and learning of the weight can be performed so that a specific feature on the image can be extracted as a factor and output. In Fig. 14, a 3×3 sized filter is applied to the 3×3 area at the upper left of the input layer, and the output value resulting from performing weighted sum and activation function operations for the corresponding node is stored in z22.

The above filter performs weighted sum and activation function operations while moving a certain distance horizontally and vertically 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).

In the convolution layer, the number of weights can be reduced by calculating the weighted sum by including only the nodes located in the area covered by the filter from the node where the current filter is located. As a result, one filter can be used to focus on the features of the local area. Accordingly, CNN can be effectively applied to image data processing where the physical distance in a two-dimensional area is an important judgment criterion. Meanwhile, CNN can apply multiple filters immediately before the convolution layer, and can also generate multiple output results through the convolution operation of each filter.

On the other hand, there may be data for which sequence characteristics are important depending on the data properties. Considering the length variability and chronological relationship of these sequence data, the structure that applies the method of inputting one element of the data sequence at each time step and inputting the output vector (hidden vector) of the hidden layer output at a specific time together with the next element in the sequence to an artificial neural network is called a recurrent neural network structure.

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

Referring to Fig. 15, a recurrent neural network (RNN) is a structure that inputs elements (x1(t), x2(t), ,..., xd(t)) of a certain time point t in a data sequence into a fully connected neural network, and applies a weighted sum and an activation function together with the hidden vector (z1(t-1), z2(t-1),..., zH(t-1)) of the immediately previous time point t-1. 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 previous time points is considered to be accumulated in the hidden vector of the current time point.

Figure 16 shows an example of the operational structure of a recurrent neural network.

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

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 hidden layer vector (z1(2), z2(2),..., zH(2)) is determined through the weighted sum and activation function. This process is repeatedly performed until time points 2, 3, ,,, and T.

Meanwhile, when multiple hidden layers are arranged in a recurrent neural network, it is called a deep recurrent neural network (DRNN). Recurrent neural networks are designed to be usefully applied to sequence data (e.g. natural language processing).

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.

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

THz(Terahertz) communication

THz communication can be applied in 6G systems. For example, the data transmission rate can be increased by increasing the bandwidth. This can be done by using sub-THz communication with a wide bandwidth and applying advanced massive MIMO technology.

FIG. 17 is a diagram illustrating an electromagnetic spectrum applicable to the present specification. As an example, referring to FIG. 17, THz waves, also known as sub-millimeter radiation, typically represent a frequency band between 0.1 THz and 10 THz with a corresponding wavelength in the range of 0.03 mm-3 mm. The 100 GHz-300 GHz band range (Sub THz band) is considered to be a major part of the THz band for cellular communications. Adding the Sub-THz band to the mmWave band will increase the capacity of 6G cellular communications. Among the defined THz bands, 300 GHz-3 THz is in the far infrared (IR) frequency band. The 300 GHz-3 THz band is a part of the optical band, but is at the boundary of the optical band, just behind the RF band. Therefore, this 300 GHz-3 THz band exhibits similarities with RF.

Key characteristics of THz communications include (i) widely available bandwidth to support very high data rates, and (ii) high path loss at high frequencies (highly directional antennas are essential). The narrow beam widths generated by highly directional antennas reduce interference. The small wavelength of THz signals allows a much larger number of antenna elements to be integrated into devices and BSs operating in this band. This allows the use of advanced adaptive array techniques to overcome range limitations.

optical wireless technology

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

FSO Backhaul Network

The characteristics of the transmitter and receiver of the FSO system are similar to those of the optical fiber network. Therefore, the data transmission of the FSO system is similar to that of the optical fiber system. Therefore, FSO can be a good technology to provide backhaul connections in 6G systems together with optical fiber networks. With FSO, very long-distance communication is possible even at distances of more than 10,000 km. FSO supports large-capacity backhaul connections for remote and non-remote areas such as the ocean, space, underwater, and isolated islands. FSO also supports cellular base station connections.

Massive MIMO technology

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

Blockchain

Blockchain will be an important technology for managing large amounts of data in future communication systems. Blockchain is a form of distributed ledger technology, where a distributed ledger is a database distributed across a large number of nodes or computing devices. Each node replicates and stores an identical copy of the ledger. Blockchain is managed by a peer-to-peer (P2P) network. It can exist without being managed by a central authority or server. Data in a blockchain is collected together 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 of other IoT systems, and large-scale connection stability of 6G communication systems.

3D Networking

6G systems support vertical expansion of user communications by integrating terrestrial and air networks. 3D BS will be provided via low-orbit satellites and UAVs. Adding a new dimension in terms of altitude and associated degrees of freedom makes 3D connections significantly different from existing 2D networks.

Quantum Communication

In the context of 6G networks, unsupervised reinforcement learning of networks is promising. Supervised learning methods cannot label the massive amount of data generated by 6G. 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 can allow networks to operate in a truly autonomous manner.

unmanned aerial vehicle

Unmanned aerial vehicles (UAVs) or drones will be a key element in 6G wireless communications. In most cases, high-speed data wireless connectivity is provided using UAV technology. Base station entities are installed on UAVs to provide cellular connectivity. UAVs have certain features that are not found in fixed base station infrastructure such as easy deployment, robust line-of-sight links, and freedom of movement with controlled mobility. During emergency situations such as natural disasters, deployment of terrestrial communication infrastructure is not economically feasible and sometimes cannot provide services in volatile environments. UAVs can easily handle such situations. UAVs will be a new paradigm in wireless communications. This technology facilitates three basic requirements of wireless networks namely eMBB, URLLC, and mMTC. UAVs can also support several 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.

Cell-free Communication

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

Integrated wireless information and energy transfer (WIET)

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

Integration of sensing and communication

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.

Integration of Access Backhaul Networks

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

Holographic Beamforming

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

Big Data Analysis

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

large intelligent surface (LIS)

In the case of THz band signals, since the straightness is strong, many shadow areas may be created due to obstacles. LIS technology becomes important because it can expand the communication area, enhance communication stability, and provide additional value-added services by installing LIS near these shadow areas. LIS is an artificial surface made of electromagnetic materials and can change the propagation of incoming and outgoing radio waves. LIS can be seen as an extension of massive MIMO, but it has different array structures and operating mechanisms from massive MIMO. In addition, LIS has the advantage of low power consumption because it operates as a reconfigurable reflector with passive elements, that is, it passively reflects signals without using an active RF chain. In addition, since each passive reflector of LIS must independently adjust the phase shift of the incident signal, it 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.

Terahertz (THz) wireless communications

FIG. 18 is a diagram illustrating a THz communication method applicable to this specification.

Referring to Fig. 18, THz wireless communication is a wireless communication using THz waves having a frequency of approximately 0.1 to 10 THz (1 THz = 1012 Hz), and may refer to terahertz (THz) band wireless communication using a very high carrier frequency of 100 GHz or higher. THz waves are located between the RF (Radio Frequency)/millimeter (mm) and infrared bands, and (i) compared to visible light/infrared rays, they penetrate non-metallic/non-polarizable materials well, and compared to RF/millimeter waves, they have a shorter wavelength, so they have high straightness and can enable beam focusing.

In addition, since the photon energy of THz waves is only a few meV, it has the characteristic of being harmless to the human body. The frequency band expected to be used for THz wireless communication may be the D-band (110 GHz to 170 GHz) or H-band (220 GHz to 325 GHz) bands where propagation loss due to absorption of molecules in the air is small. In addition to 3GPP, standardization discussions for THz wireless communication are being centered around the IEEE 802.15 THz WG (working group), and standard documents issued by the TG (task group) of IEEE 802.15 (e.g., TG3d, TG3e) can specify or supplement the contents described in this specification. THz wireless communication can be applied to wireless cognition, sensing, imaging, wireless communication, THz navigation, etc.

Specifically, referring to FIG. 18, THz wireless communication scenarios can be classified into a macro network, a micro network, and a nanoscale network. In a macro network, THz wireless communication can be applied to V2V (vehicle-to-vehicle) connections and backhaul/fronthaul connections. In a micro network, THz wireless communication can be applied to fixed point-to-point or multi-point connections such as indoor small cells, wireless connections in data centers, and near-field communications such as kiosk downloading. Table 5 below is a table showing examples of technologies that can be used in THz waves.

FIG. 19 is a diagram illustrating a THz wireless communication transceiver applicable to the present specification.

Referring to Figure 19, THz wireless communication can be classified based on the method for THz generation and reception. THz generation methods can be classified into optical device or electronic device-based technologies.

At this time, methods for generating THz using electronic components include a method using a semiconductor component such as a resonant tunneling diode (RTD), a method using a local oscillator and a multiplier, a MMIC (monolithic microwave integrated circuits) method using an integrated circuit based on a compound semiconductor HEMT (high electron mobility transistor), and a method using a Si-CMOS-based integrated circuit. In the case of Fig. 19, a doubler (tripler, multiplier, multiplier) is applied to increase the frequency, and it passes through a subharmonic mixer and is radiated by an antenna. Since the THz band forms a high frequency, a doubler is essential. Here, the multiplier is a circuit that has an output frequency that is N times that of the input, and matches it to a desired harmonic frequency and filters out all remaining frequencies. In addition, beamforming can be implemented by applying an array antenna, etc. to the antenna of Fig. 19. In Figure 19, IF represents intermediate frequency, tripler and multipler represent multipliers, PA represents a power amplifier, LNA represents a low noise amplifier, and PLL represents a phase-locked loop.

FIG. 20 is a diagram illustrating a THz signal generation method applicable to the present specification. In addition, FIG. 21 is a diagram illustrating a wireless communication transceiver applicable to the present specification.

Referring to FIGS. 20 and 21, the optical device-based THz wireless communication technology refers to a method of generating and modulating a THz signal using an optical device. The optical device-based THz signal generation technology is a technology that generates an ultra-high-speed optical signal using a laser and an optical modulator, and converts it into a THz signal using an ultra-high-speed optical detector. Compared to a technology that uses only electronic devices, this technology makes it easy to increase the frequency, enables high-power signal generation, and obtains flat response characteristics in a wide frequency band. In order to generate a THz signal based on an optical device, a laser diode, a wideband optical modulator, and an ultra-high-speed optical detector are required, as illustrated in FIG. 20. In the case of FIG. 20, light signals of two lasers with different wavelengths are combined to generate a THz signal corresponding to the wavelength difference between the lasers. In Fig. 20, an optical coupler refers to a semiconductor device that transmits an electrical signal using optical waves to provide electrical isolation and coupling between circuits or systems, and a uni-travelling carrier photo-detector (UTC-PD) is one of the photodetectors, which uses electrons as active carriers and is a device that reduces the travel time of electrons by bandgap grading. UTC-PD is capable of detecting light at 150 GHz or higher. In Fig. 20, EDFA (erbium-doped fiber amplifier) represents an erbium-doped fiber amplifier, PD (photo detector) represents a semiconductor device that can convert an optical signal into an electrical signal, OSA represents an optical sub assembly that modularizes various optical communication functions (e.g., photoelectric conversion, electro-optical conversion, etc.) into a single component, and DSO represents a digital storage oscilloscope.

Fig. 22 is a drawing illustrating a transmitter structure applicable to the present specification. In addition, Fig. 23 is a drawing illustrating a modulator structure applicable to the present specification.

Referring to FIGS. 22 and 23, a general optical source of a laser can be passed through an optical wave guide to change the phase of a signal, etc. 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 optical/electrical modulator (O/E converter) can generate a THz pulse according to an optical rectification operation by a nonlinear crystal, an optical/electrical 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 the unit of femto second to pico second. An optical/electronic converter (O/E converter) performs down conversion by utilizing the non-linearity of the device.

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

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). That is, in order to down convert to a desired terahertz band (THz band), it is required to design an optical/electrical converter (O/E converter) that has the most ideal nonlinearity for moving to the terahertz band (THz band). If an optical/electrical converter (O/E converter) that does not match the target frequency band is used, there is a high possibility that errors will occur in the amplitude and phase of the pulse.

In a single carrier system, a terahertz transmit/receive system can be implemented using one optical-to-electrical converter. Depending on the channel environment, in a multi-carrier system, as many optical-to-electrical converters as the number of carriers may be required. In particular, in the case of a multi-carrier system that utilizes multiple widebands according to a plan related to the aforementioned spectrum usage, this phenomenon will be prominent. In this regard, a frame structure for the multi-carrier system can be considered. A signal down-converted based on an optical-to-electrical converter can be transmitted in a specific resource area (e.g., a specific frame). The frequency area of the specific resource area can include a plurality of chunks. Each chunk can be composed of at least one component carrier (CC).

Here, the wireless communication technology implemented in the wireless device (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 device (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, the 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, the ZigBee technology can create PAN (personal area networks) related to small/low-power digital communication based on various standards such as IEEE 802.15.4, and can be called by various names.

Typical factors that degrade the performance of a communication system in the THz band include the occurrence of carrier frequency offset (CFO) and the occurrence of phase noise (PN). CFO can generally be caused by RF impairment and the Doppler effect, and PN can be caused by RF impairment. RF impairment can mean a frequency mismatch of a local oscillator between a transmitter and a receiver. The transmitter and receiver may be a base station and a terminal, respectively, but are not limited thereto. The CFO normalized by OFDM SCS can be expressed as the following mathematical expression 1.

은 OFDM SCS로 정규화된 CFO일 수 있고,

는 송신단의반송파 및 수신단의 반송파 사이의 편차일 수 있고,

는 수신단의 이동속도일 수 있고,

는 빛의 속도일 수 있고,

는 OFDM 부반송파 주파수일 수 있다.In mathematical expression 1,

can be a CFO normalized to OFDM SCS,

can be the deviation between the carrier of the transmitter and the carrier of the receiver,

can be the moving speed of the receiver,

can be the speed of light,

may be an OFDM subcarrier frequency.

Referring to mathematical expression 1, CFO may increase as the deviation between the carrier of the transmitter and the carrier of the receiver increases, as the moving speed of the receiver increases, and as the OFDM subcarrier frequency increases. CFO may cause performance degradation in the signal acquisition stage for performing synchronization between the transmitter and the base station. In particular, in a communication system of the THz band using a large carrier frequency, the performance in the signal acquisition stage by CFO may be further degraded. Therefore, it may be advantageous to design a PSS using a waveform that is robust to a large CFO in a communication system of the THz band.

In addition, PTRS (Phase Tracking Reference Signal) has been introduced to compensate for PN of data channel from mmWave band of 5G NR. Also, increasing the frequency band of subcarrier used to solve the problem caused by PN is being considered. PN can be expressed as the following mathematical expression 2 based on Leeson's equation.

는 PN일 수 있고,

는 동작 주파수(operating frequency)일 수 있고,

는 발진기의 로드된 Q 값(loaded Q-value of the oscillator)일 수 있고,

은 오프셋 주파수(offset frequency)일 수 있고,

는 1/f 컷오프 주파수(1/f cutoff frequency)일 수 있고,

는 버퍼 증폭기의 잡음 지수(noise figure of the buffer amplifier)일 수 있고,

는 볼츠만 상수(Boltzmann's constant)일 수 있고,

는 켈빈 온도(temperature in Kelvin)일 수 있고

는 발진기의 출력 파워(output power of the oscillator)일 수 있다.In mathematical expression 2,

can be PN,

can be the operating frequency,

can be the loaded Q-value of the oscillator,

can be an offset frequency,

can be the 1/f cutoff frequency,

can be the noise figure of the buffer amplifier,

can be Boltzmann's constant,

can be temperature in Kelvin

can be the output power of the oscillator.

Referring to Equation 2, for example, when the operating frequency doubles, PN can increase by 6 dB. It can be important to solve the problem caused by PN in THz band communication systems using high carrier frequencies.

The symbols/abbreviations/terms used in this specification are as follows.

- AWGN: Additive White Gaussian Noise

- CP: Cyclic Prefix

- CFO: Channel Frequency Offset

- DFnT: Discrete Fresnel Transform

- ICI: Inter Carrier Interference

- OCDM: Orthogonal Chirp Division Multiplexing

- OFDM: Orthogonal Frequency Division Multiplexing

- PN: Phase Noise

-PSS: Primary Synchronization Signal

- SCS: Sub Carrier Spacing

- THz: Tera-Hertz

Figure 24 is a diagram illustrating an example of a PN model in a wireless communication system.

PTRS (Phase Tracking Reference Signal) has been introduced to compensate for the PN of the data channel from the mmWave band of 5G NR. PTRS can be a reference signal introduced to compensate for the PN of the data channel. The receiver can detect the synchronization signal without compensating for the PN in the synchronization phase.

Referring to Fig. 24, if the subcarrier is enlarged without compensating the PN separately in the synchronization step, it can be robust to PN. Conversely, if the subcarrier is enlarged, the length of the OFDM symbol and CP can be reduced. Due to this, multipath fading may occur in the channel in the case of indoor propagation environment as one of the use cases of multi-cell, distributed MIMO, RIS (Reconfigurable Intelligent Surface), or THz communication system. If multipath fading occurs in the channel, the signal may be distorted due to inter symbol interference (ISI). Therefore, increasing the subcarrier to be robust to PN may have limitations as the carrier frequency increases.

Figure 25 is a conceptual diagram illustrating an example of PSS search probability in a wireless communication system.

Fig. 25 shows the results of generating a PN according to a carrier frequency using a 3GPP PN model (e.g., multi pole zero) and detecting a sector ID using the existing PSS (primary synchronization signal) structure in 3GPP NR. Fig. 25 shows the PSS detection probability according to SNR when the subcarrier frequency is 240 kHz and the carrier is 150 GHz or 350 GHz.

Referring to Fig. 25, the size of the PN that occurs when the carrier frequency increases may also increase. When the size of the PN increases, the sector ID detection performance of the PSS may deteriorate. Therefore, even when the SNR increases, the PSS sector ID may not be detected.

However, designing a PSS using a robust chirp signal in PN can help increase the PSS detection probability in the sub-THz band.

Fig. 26 is a diagram illustrating an example of ICI occurrence in a wireless communication system. Fig. 27 is a diagram illustrating an example of BER according to the SNR of each CFO in a wireless communication system.

)가 0, 0.03, 0.06 또는 0.1인 경우 SNR에 따른 BER을 나타낸다.Figure 26 shows that when CFO occurs in an OFDM system, orthogonality is broken between orthogonal frequencies, causing ICI. Figure 27 shows that when CFO occurs in an OFDM system, ICI occurs between orthogonal frequencies.

) represents the BER according to SNR when 0, 0.03, 0.06, or 0.1.

Referring to Fig. 26, if orthogonality between frequencies is maintained, signals of adjacent frequencies can become 0, but if orthogonality is broken by CFO, components of adjacent frequencies can be received and act as interference. When ICI occurs by CFO, the reception symbol of the receiver can be expressed as in the following mathematical expression 3.

In mathematical expression 3, r can be a receiving symbol, x can be a transmitting symbol of the transmitter, I can be ICI, and w can be AWGN. In addition, the ICI generated by CFO can be expressed as in the following mathematical expression 4.

은 CFO일 수 있다. 수학식 4를 참조하면, CFO가 증가함에 따라 ICI가 증가할 수 있다. In mathematical expression 4,

can be CFO. Referring to Equation 4, ICI can increase as CFO increases.

Referring to Fig. 27, when the CFO increases, the BER performance may deteriorate at the same SNR. For communication systems in the THz band or sub-THz band, the CFO may increase compared to the NR, which may result in increased ICI. Therefore, for communication systems in the THz band or sub-THz band, an additional algorithm may be required to compensate for the CFO, which may result in additional overhead.

Fig. 28 is a diagram illustrating a linear chirp signal in a wireless communication system along the time/magnitude axis. Fig. 29 is a diagram illustrating a linear chirp signal in a wireless communication system along the time/frequency axis.

Referring to FIGS. 28 and 29, the chirp signal may be a signal used in the LoRA (long range) standard for long-distance transmission of FMCW (frequency modulation continuous wave) radar or IoT (internet of things) devices. The chirp signal may have robust characteristics to CFO and PN due to the characteristics of chirp spreading spectrum. The chirp signal may include a linear chirp signal and a nonlinear chirp signal. The linear chirp signal may be expressed as in the following mathematical expression 5.

는 선형 처프 신호일 수 있고,

는 처프 레이트일 수 있고,

은 초기 위상값일 수 있다. 여기에서, 처프 레이트는 처프 신호의 기울기를 결정하는 변수일 수 있다. 일반적으로, 처프 레이트가 클수록 시간/주파수 축에서 기울기(예를 들어, 도 29의 직선의 기울기)가 급변할 수 있다.In mathematical expression 5,

can be a linear chirp signal,

can be a chirp rate,

may be an initial phase value. Here, the chirp rate may be a variable that determines the slope of the chirp signal. In general, the larger the chirp rate, the more abruptly the slope (e.g., the slope of the straight line in Fig. 29) may change in the time/frequency axis.

Fig. 30 is a diagram illustrating an example of a typical chirp signal in a wireless communication system. Fig. 31 is a diagram illustrating an example of an orthogonal chirp signal in a wireless communication system. Fig. 32 is a diagram illustrating an example of an OFDM signal in a wireless communication system. Fig. 33 is a diagram illustrating an example of an OCDM signal in a wireless communication system.

Referring to FIGS. 30 to 31, a general chirp signal must use different frequency bands at the same time, but an orthogonal chirp signal can use multiple chirp signals by superimposing them at the same time and at the same frequency band. This characteristic of an orthogonal chirp signal can be considered in the same way as the method of utilizing the orthogonality of frequencies in an OFDM system. An orthogonal chirp signal used in an OCDM system can be expressed as shown in the following mathematical expression 6.

는 k번째 직교 처프 신호일 수 있고 N은 직교 처프 신호에 포함된 직교 처프의 개수일 수 있고, T는 전송 주기일 수 있다. In mathematical expression 6,

can be the kth orthogonal chirp signal, N can be the number of orthogonal chirps included in the orthogonal chirp signal, and T can be a transmission period.

로 동일할 수 있다.Referring to Equation 6, the chirp rate of all orthogonal chirp signals is

can be identical to

When a CFO such as mathematical expression 1 is considered, the kth orthogonal chirp signal can be expressed as the following mathematical expression 7.

는 CFO가 고려된 k번째 직교 처프 신호일 수 있다.In mathematical expression 7,

can be the kth orthogonal chirp signal considering CFO.

Referring to FIGS. 32 and 33, for example, when there are 17 subcarriers, an OFDM signal can be represented as in FIG. 31, and when N is 17 in mathematical expression 7, an OCDM signal can be represented as in FIG. 32.

Meanwhile, a PSS using an orthogonal chirp signal according to one embodiment of the present disclosure (hereinafter, orthogonal chirp PSS) can be expressed as in the following mathematical expressions 8 to 10.

는 직교 처프 PSS일 수 있고,

는 PSS 시퀀스 일 수 있고,

는 L개의 직교 처프를 포함하는 직교 처프 신호일 수 있고, 신호일 수 있고,

은 시퀀스의 길이일 수 있고,

은 N개의 직교 처프를 포함하는 직교 처프 신호일 수 있다. 수학식 10에서 N=L인 경우,

은

일 수 있고,

및

의 행렬곱을 바로 수행하여

를 생성할 수 있다. 수학식 10에서 N>L의 경우에는 필요에 따라

에 포함된 N개의 직교 처프 중 L개의 직교 처프를 선택할 수 있고(즉,

를 생성함),

및

의 행렬곱을 수행하여

를 생성할 수 있다. 무선 통신 시스템에서 실제로 CFO가 발생하는 경우, 수학식 10의 각 요소가 수학식 6이 아닌 수학식 7로 대체되어 수학식 8에 반영되어 PSS가 생성될 수 있다. 이 경우, 수신단은 수학식 6을 기초로 생성된 수학식 10의 PSS를 기대하고 자기 상관(autocorrelation)을 시도할 수 있다.In mathematical expressions 8 to 10,

can be an orthogonal chirp PSS,

can be a PSS sequence,

may be an orthogonal chirp signal comprising L orthogonal chirps, and may be a signal,

can be the length of the sequence,

can be an orthogonal chirp signal containing N orthogonal chirps. In Equation 10, when N = L,

silver

It can be,

and

By performing the matrix multiplication directly

can be generated. In mathematical expression 10, in the case of N>L, as needed,

Among the N orthogonal chirps included in , L orthogonal chirps can be selected (i.e.,

),

and

By performing matrix multiplication of

can be generated. When CFO actually occurs in a wireless communication system, each element of Equation 10 can be replaced with Equation 7 instead of Equation 6 and reflected in Equation 8 to generate PSS. In this case, the receiver can expect the PSS of Equation 10 generated based on Equation 6 and attempt autocorrelation.

Figures 34 and 35 are diagrams illustrating examples of NR PSS autocorrelation in a wireless communication system. Figures 36 and 37 are diagrams illustrating examples of NR PSS cross-correlation in a wireless communication system.

Fig. 34 shows an example of NR PSS autocorrelation on the transmitter side. Fig. 35 shows an example of NR PSS autocorrelation on the receiver side. Fig. 36 shows an example of NR PSS crosscorrelation on the transmitter side. Fig. 37 shows an example of NR PSS crosscorrelation on the receiver side.

In Figures 34 to 35, the autocorrelation may be the autocorrelation between the ideal NR PSS and the NS PSS in which the CFO occurred. The ideal NR PSS may be the NS PSS in which the CFO did not occur.

인 m-시퀀스를 내적하여 생성된 것일 수 있다. 예를 들어, NR PSS는 OFDM의 127개의 부반송파에 길이가 127인 m-시퀀스를 내적하여 생성된 것일 수 있다.In Figs. 36 and 37, NR PSS is a subcarrier of OFDM with a length of

may be generated by multiplying an m-sequence of length 127 by the 127 subcarriers of OFDM. For example, NR PSS may be generated by multiplying an m-sequence of length 127 by the 127 subcarriers of OFDM.

의 시퀀스 길이를 가질 수밖에 없다. 이러한 m-시퀀스의 특성은 길이의 늘리고 줄임의 유연함이 매우 부족한 특징을 가지는데 이는 향후 무선 통신 표준에서 최적의 성능을 가지는 PSS 길이가 127이 아닐 수 있음에도 시퀀스 길이에 대한 선택의 폭이 좁아 사용할 수밖에 없는 상황이 생길 수 있다. 하지만 직교 처프 PSS는 유연한 길이의 시퀀스 또는 코드를 같은 수의 직교 처프와 내적하여 생성할 수 있기 때문에 최적의 PSS를 생성하는데 도움을 줄 수 있다. 또한 직교 처프 신호는 OFDM 신호 생성 체계와의 호환성이 좋다고 알려져 있어 OFDM 시스템을 사용하는 환경에서도 높은 PSS 탐색 성능을 위해서 선택적으로 사용할 수 있다.Referring to Figures 34 to 37, NR PSS is characterized by the m-sequence

has to have a sequence length of 127. This characteristic of m-sequences has a very poor flexibility in increasing and decreasing the length, which may lead to a situation where the PSS length with optimal performance in future wireless communication standards is not 127 and therefore has to be used due to the limited range of sequence length choices. However, since the orthogonal chirp PSS can generate a flexible length sequence or code by dot-producting it with the same number of orthogonal chirps, it can help generate the optimal PSS. In addition, since the orthogonal chirp signal is known to have good compatibility with the OFDM signal generation system, it can be selectively used for high PSS search performance even in an environment using an OFDM system.

FIG. 38 is a diagram illustrating an example of autocorrelation of orthogonal chirp PSS according to an embodiment of the present disclosure in a wireless communication system. FIG. 39 is a diagram illustrating an example of cross-correlation of orthogonal chirp PSS according to an embodiment of the present disclosure in a wireless communication system.

In Fig. 38, the autocorrelation can be the autocorrelation between the ideal orthogonal chirp PSS and the orthogonal chirp PSS in which the CFO occurred. The ideal orthogonal chirp PSS can be the orthogonal chirp PSS in which the CFO did not occur.

In Figs. 38 and 39, the orthogonal chirp PSS may be generated by taking the inner product of an arbitrary orthogonal chirp signal and an m-sequence of the same size as the arbitrary orthogonal chirp signal. For example, the orthogonal chirp PSS may be generated by taking the inner product of seven arbitrary orthogonal chirp signals, each of which has 128 orthogonal chirps, and seven arbitrary orthogonal chirp signals.

Referring to FIGS. 38 to 39, both autocorrelation and cross-correlation show a slight deterioration in the autocorrelation side-lobe characteristics compared to the autocorrelation characteristic results of the existing 5G NR PSS, but while OFDM must use all 127 subcarriers, it is possible to obtain the same performance as FIGS. 37 to 38 with only 7 orthogonal chirps.

This means that resources such as PDSCH can be additionally allocated to chirp resources other than 7, which allows for more efficient resource allocation. In addition, although the present disclosure demonstrates performance with a PSS using 7 orthogonal chirps and an m-sequence with a length of 7, it has the advantage of being able to flexibly design a PSS with any length of sequence and any number of orthogonal chirps.

FIGS. 40 to 44 are diagrams illustrating examples of autocorrelation performance comparisons of NR PSS and orthogonal chirp PSS according to an embodiment of the present disclosure in a wireless communication system.

Figures 40 to 44 show a comparison of the autocorrelation performance between an ideal NR PSS and a CFO-induced NR PSS, and between an ideal orthogonal chirp PSS and a CFO-induced orthogonal chirp PSS.

In FIGS. 40 to 44, OCDM w/CFO may be an orthogonal chirp PSS according to an embodiment of the present disclosure, and OFDM w/CFO may be a conventional NR PSS. In FIGS. 39 to 43, the orthogonal chirp PSS according to an embodiment of the present disclosure may be generated by multiplying seven orthogonal chirp signals and an m-sequence having a length of 127, and the conventional NR PSS may be generated by multiplying an m-sequence having a length of 127 with 127 subcarriers of OFDM. In FIGS. 39 to 43, the CFO values may be 0.2, 0.4, 0.5, 1.0, and 1.2, respectively. In addition, when the CFO value is 1.0 as in FIG. 42, it may mean that the CFO occurs as much as the subcarrier interval.

Referring to FIGS. 40 and 41, when the CFO value is greater than 0 as in FIGS. 39 and 40, the main lobe value of the autocorrelation of the orthogonal chirp PSS according to an embodiment of the present disclosure may be greater than the main lobe value of the autocorrelation of the existing NR PSS. Accordingly, when the orthogonal chirp PSS according to an embodiment of the present disclosure is used, the PSS detection probability may increase compared to when the existing NR PSS is used.

Referring to FIG. 42, when the CFO value is 0.5 as in FIG. 41, since it is a section where the magnitude of the interference coming from the adjacent subcarrier and the magnitude of the desired signal are equal, PSS may not be detected in OFDM. That is, when the existing NR PSS is used, PSS may not be detected. However, when an orthogonal chirp PSS signal according to an embodiment of the present disclosure is used, even when the CFO value is 0.5, a peak of autocorrelation may occur, so PSS detection may be possible.

Referring to FIGS. 43 to 44, when the CFO value is greater than 1, as in FIGS. 42 to 43, the main lobe of the autocorrelation of the existing NR PSS does not generate a peak, so the PSS may not be detected, but the main lobe of the autocorrelation of the orthogonal chirp PSS generates a peak, so that the PSS may be detected.

FIGS. 45 to 46 are diagrams illustrating examples of the effect of orthogonal chirp PSS according to one embodiment of the present disclosure in a wireless communication system.

Fig. 45 shows the autocorrelation of the orthogonal chirp PSS according to one embodiment of the present disclosure. Fig. 46 shows the cross-correlation of the orthogonal chirp PSS according to one embodiment of the present disclosure.

Figures 45 to 46 may be generated based on an orthogonal chirp signal including 10 orthogonal chirps and an arbitrary sequence having a length of 10.

의 시퀀스 길이만을 가질 수 있는 m-시퀀스를 사용하지 않아도 되기 때문에 기존 NR PSS에 비해 PSS를 보다 유연하게 디자인할 수 있다.Referring to FIGS. 45 to 46, when using an orthogonal chirp PSS according to one embodiment of the present disclosure, as with the existing NR PSS,

The PSS can be designed more flexibly than the existing NR PSS because it does not have to use m-sequences that can only have a sequence length of .

Figure 47 is a flowchart of a signal transmission and reception method according to one embodiment of the present disclosure.

In Fig. 47, the terminal may be the receiving terminal described above, and the base station may be the transmitting terminal described above, but is not limited thereto.

Referring to FIG. 47, the terminal can receive a PSS from a base station (S4710). The terminal can receive a PSS generated based on orthogonal chirp signals including a plurality of orthogonal chirps and a PSS sequence from the base station.

In one embodiment, the orthogonal chirp signals can be generated based on the number of orthogonal chirps and the transmission periods of the orthogonal chirps.

In another embodiment, the orthogonal chirp signals can be generated based on the number of the plurality of orthogonal chirps, the transmission period of the plurality of orthogonal chirps, and the CFO.

개가 아닐 수 있다. m은 정수일 수 있다.In one embodiment, the PSS sequence may not be an m-sequence. That is, the number of PSS sequences is

It may not be a dog. m may be an integer.

The terminal can obtain a PSS sequence from the PSS (S4720). The terminal can perform synchronization with the base station based on the PSS sequence (S4730).

FIG. 48 is a flowchart of a signal transmission and reception method according to another embodiment of the present disclosure.

In Fig. 48, the base station may be the above-described transmitting terminal, and the terminal may be the above-described receiving terminal, but is not limited thereto.

Referring to FIG. 48, the base station can generate a PSS based on an orthogonal chirp signal and a PSS sequence (S4810).

The base station can generate a PSS based on orthogonal chirp signals including a plurality of orthogonal chirps and a PSS sequence.

In one embodiment, the base station can generate orthogonal chirp signals based on the number of the plurality of orthogonal chirps and the transmission periods of the plurality of orthogonal chirps.

In another embodiment, the base station can generate orthogonal chirp signals based on the number of the plurality of orthogonal chirps, the transmission period of the plurality of orthogonal chirps, and the CFO.

In one embodiment, the PSS sequence may not be an m-sequence. That is, the number of PSS sequences may not be 2 ^m -1. m may be an integer.

The base station can transmit PSS to the terminal (S4820). The base station can perform synchronization with the terminal (S4830).

The embodiments described above are combinations of the components and features of the present specification in a given form. Each component or feature should be considered optional unless explicitly stated otherwise. Each component or feature may be implemented in a form that is not combined with other components or features. In addition, it is also possible to combine some components and/or features to form an embodiment of the present specification. The order of the operations described in the embodiments of the present 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. It is obvious 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 included as a new claim by post-application amendment.

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

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

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 of this specification. Accordingly, the above detailed description should not be construed in all respects as restrictive but as illustrative. The scope of this specification should be determined by a reasonable interpretation of the appended claims, and all changes within the equivalency range of this specification are intended to be included in the scope of this specification.

Claims (12)

In a method performed by a user equipment (UE) in a wireless communication system, A step of receiving orthogonal chirp signals including a plurality of orthogonal chirps from a base station (BS) and a primary synchronization signal (PSS) generated based on a PSS sequence; a step of obtaining the PSS sequence from the PSS; and A method comprising: performing synchronization based on the above base station and the PSS sequence. In the first paragraph, The above orthogonal chirp signals are, A method generated based on the number of the plurality of orthogonal chirps and the period of the plurality of orthogonal chirps. In the first paragraph, The above orthogonal chirp signals are, A method generated based on the number of the plurality of orthogonal chirps, the period of the plurality of orthogonal chirps, and the carrier frequency offset (CFO). In the first paragraph, The above PSS sequence is not an m-sequence, but a method. In a terminal (user equipment, UE) operating in a communication system, One or more transmitters and receivers; one or more processors controlling said one or more transceivers; and A memory comprising one or more instructions to be performed by said one or more processors, One or more of the above commands, A step of receiving orthogonal chirp signals including a plurality of orthogonal chirps from a base station (BS) and a primary synchronization signal (PSS) generated based on a PSS sequence; a step of obtaining the PSS sequence from the PSS; and A terminal comprising a step of performing synchronization based on the above base station and the above PSS sequence. In a method performed by a base station (BS) in a wireless communication system, A step of generating a PSS based on orthogonal chirp signals including a plurality of orthogonal chirps and a PSS (Primary synchronization signal) sequence; A step of transmitting the PSS to a terminal (user equipment, UE); and A method comprising the step of performing synchronization with the terminal. In Article 6, The above orthogonal chirp signals are, A method generated based on the number of the plurality of orthogonal chirps and the period of the plurality of orthogonal chirps. In Article 6, The above orthogonal chirp signals are, A method generated based on the number of the plurality of orthogonal chirps, the period of the plurality of orthogonal chirps, and the carrier frequency offset (CFO). In Article 6, The above PSS sequence is not an m-sequence, but a method. In a base station (BS) operating in a communication system, One or more transmitters and receivers; one or more processors controlling said one or more transceivers; and A memory comprising one or more instructions to be performed by said one or more processors, One or more of the above commands, A step of generating a PSS based on orthogonal chirp signals including a plurality of orthogonal chirps and a PSS (Primary synchronization signal) sequence; A step of transmitting the PSS to a terminal (user equipment, UE); and A base station, comprising a step of performing synchronization with the terminal. In a device comprising one or more memories and one or more processors functionally connected to the one or more memories, Receive orthogonal chirp signals including multiple orthogonal chirps from a base station (BS) and a PSS (Primary synchronization signal) generated based on a PSS sequence, Obtaining the PSS sequence from the above PSS, and, A device operable to perform synchronization based on the above base station and the PSS sequence. In one or more non-transitory computer-readable media storing one or more instructions, Receive orthogonal chirp signals including multiple orthogonal chirps from a base station (BS) and a PSS (Primary synchronization signal) generated based on a PSS sequence, Obtaining the PSS sequence from the above PSS, and, A computer-readable medium operable to perform synchronization based on the above base station and the PSS sequence.

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