Method for transmitting message in wireless communication system, and device therefor

Abstract

According to various embodiments, a device can receive a first message including state information of a user equipment (UE), determine, on the basis of collection information collected in relation to the UE and the state information of the UE, whether to generate auxiliary data for supporting collision risk evaluation of the UE, and transmit, on the basis of the generation of the auxiliary data, a second message including the auxiliary data to the UE.

Description

Method for transmitting a message in a wireless communication system and device therefor

[0001] It relates to a method for transmitting and receiving messages between devices and a network in a wireless communication system and a device therefor.

[0002] Wireless communication systems are multiple access systems that support communication with multiple users by sharing available system resources (e.g., bandwidth, transmission power, etc.). Examples of multiple access systems include code division multiple access (CDMA), frequency division multiple access (FDMA), time division multiple access (TDMA), orthogonal frequency division multiple access (OFDMA), single carrier frequency division multiple access (SC-FDMA), and multi-carrier frequency division multiple access (MC-FDMA).

[0003] Sidelink (SL) refers to a communication method that establishes a direct link between user equipment (UE), allowing voice or data to be exchanged directly between terminals without going through a base station (BS). SL is being considered as a solution to address the burden on base stations due to rapidly increasing data traffic.

[0004] V2X (vehicle-to-everything) refers to a communication technology that exchanges information with other vehicles, pedestrians, and infrastructure-based objects through wired / wireless communication. V2X can be divided into four types: V2V (vehicle-to-vehicle), V2I (vehicle-to-infrastructure), V2N (vehicle-to-network), and V2P (vehicle-to-pedestrian). V2X communication can be provided through the PC5 interface and / or Uu interface.

[0005] Meanwhile, as more and more communication devices demand greater communication capacity, the need for improved mobile broadband communication compared to existing radio access technology (RAT) is emerging. Accordingly, communication systems that consider services or terminals sensitive to reliability and latency are being discussed. Next-generation wireless access technologies that consider improved mobile broadband communication, massive machine type communication (MTC), and ultra-reliable and low latency communication (URLLC) can be called new radio access technology (RAT) or new radio (NR). NR can also support vehicle-to-everything (V2X) communication.

[0006] Figure 1 is a diagram for comparing and explaining V2X communication based on RAT before NR and V2X communication based on NR.

[0007] In relation to V2X communication, in RATs prior to NR, methods for providing safety services based on V2X messages such as Basic Safety Message (BSM), Cooperative Awareness Message (CAM), and Decentralized Environmental Notification Message (DENM) were mainly discussed. V2X messages may include location information, dynamic information, attribute information, etc. For example, a terminal may transmit a CAM of a periodic message type and / or a DENM of an event triggered message type to another terminal.

[0008] For example, a CAM may include basic vehicle information such as dynamic vehicle status information, such as direction and speed, static vehicle data, such as dimensions, external lighting conditions, and route history. For example, a terminal may broadcast a CAM, and the latency of the CAM may be less than 100 ms. For example, in the event of an emergency, such as a vehicle breakdown or accident, a terminal may generate a DENM and transmit it to other terminals. For example, all vehicles within the transmission range of the terminal may receive the CAM and / or DENM. In this case, the DENM may have a higher priority than the CAM.

[0009] Since then, various V2X scenarios have been proposed in NR in relation to V2X communications. For example, various V2X scenarios may include vehicle platooning, advanced driving, extended sensors, and remote driving.

[0010] For example, based on vehicle platooning, vehicles can dynamically form groups and move together. For example, to perform platoon operations based on vehicle platooning, vehicles in the group can receive periodic data from the lead vehicle. For example, vehicles in the group can use this periodic data to narrow or widen the gap between vehicles.

[0011] For example, based on improved driving, vehicles can become semi-autonomous or fully automated. For example, each vehicle can adjust its trajectories or maneuvers based on data acquired from local sensors of nearby vehicles and / or nearby logical entities. Furthermore, for example, each vehicle can share driving intentions with nearby vehicles.

[0012] For example, based on extended sensors, raw data, processed data, or live video data acquired through local sensors can be exchanged between vehicles, logical entities, pedestrian terminals, and / or V2X application servers. Thus, for example, a vehicle can perceive its environment better than it can perceive using its own sensors.

[0013] For example, based on remote driving, a remote driver or V2X application can operate or control the remote vehicle for people who cannot drive or for remote vehicles located in hazardous environments. For example, in cases where the route is predictable, such as public transportation, cloud computing-based driving can be utilized to operate or control the remote vehicle. Additionally, access to a cloud-based back-end service platform, for example, can be considered for remote driving.

[0014] Meanwhile, a method to specify service requirements for various V2X scenarios, such as vehicle platooning, enhanced driving, expanded sensors, and remote driving, is being discussed in NR-based V2X communication.

[0015] The technical problem to be achieved by the present invention is to provide a method for transmitting and receiving data / messages more accurately and efficiently.

[0016] The technical challenges are not limited to the technical challenges mentioned above, and other technical challenges not mentioned will be clearly understood by those skilled in the art to which the present invention pertains from the description below.

[0017] A method by a network according to one aspect comprises the steps of: receiving a first message including status information of a user equipment (UE); determining whether to generate auxiliary data for supporting a collision risk assessment of the UE based on collected information related to the UE and the status information of the UE; and transmitting a second message including the auxiliary data to the UE based on the auxiliary data being generated, wherein the network can determine whether to additionally include fidelity level information for the auxiliary data in the second message based on a collision risk value of the UE.

[0018] Alternatively, the second message may include fidelity level information for the auxiliary data only when the collision risk value of the UE is above a certain threshold.

[0019] Alternatively, the network may input the collection information and the state information into a first model to generate the auxiliary data at a first fidelity level, or input the collection information and the state information into a second model to generate the auxiliary data at a second fidelity level higher than the first fidelity level.

[0020] Alternatively, the network may generate the auxiliary data using the first model based on the collision risk value of the UE being greater than or equal to a specific threshold, and may generate the auxiliary data using the second model based on the collision risk value of the UE being less than or equal to the specific threshold.

[0021] Alternatively, the fidelity level may be included in the second message to adjust the sensitivity in determining the risk of collision of the UE based on the auxiliary data.

[0022] Alternatively, the auxiliary data may be generated based on the sensing distance of the UE being less than a specific threshold distance, the number of peripheral devices associated with the UE being greater than or equal to a specific threshold number, or the fidelity level of the status information of the UE being less than a specific threshold level.

[0023] Alternatively, the fidelity level of the status information of the UE may be determined based on at least one of the sensor type that acquired the status information and the device type of the UE.

[0024] Alternatively, the second message may further include guidance information for changing at least one of the moving direction and moving speed of the UE.

[0025] Alternatively, the collection information may be obtained based on multiple messages received from multiple devices located around the UE.

[0026] Alternatively, the collision risk value of the UE may be determined based on the collision risk value.

[0027] According to another aspect, at least one non-transitory computer-readable medium comprises instructions that, when executed by at least one processor, perform operations, including: receiving a first message comprising status information of a user equipment (UE); determining whether to generate auxiliary data to support a collision risk assessment of the UE based on collected information related to the UE and the status information of the UE; and transmitting a second message comprising the auxiliary data to the UE based on the auxiliary data being generated, wherein the second message may further include fidelity level information for the auxiliary data, based on a collision risk value of the UE.

[0028] According to another aspect, a network includes a Radio Frequency (RF) transceiver; and a processor connected to the RF transceiver, wherein the processor controls the RF transceiver to receive a first message including status information of a user equipment (UE), determines whether to generate auxiliary data for supporting a collision risk assessment of the UE based on collected information related to the UE and the status information of the UE, and transmits a second message including the auxiliary data to the UE based on the generated auxiliary data, wherein the second message may additionally include fidelity level information for the auxiliary data based on a collision risk value of the UE.

[0029] According to another aspect, a processing device for controlling a network comprises at least one processor; and at least one memory connected to the at least one processor and storing instructions that, when executed by the at least one processor, perform operations, the operations comprising: receiving a first message including status information of a user equipment (UE); determining whether to generate auxiliary data for supporting a collision risk assessment of the UE based on collected information related to the UE and the status information of the UE; and transmitting a second message including the auxiliary data to the UE based on the generated auxiliary data, wherein the second message may further include fidelity level information for the auxiliary data based on a collision risk value of the UE.

[0030] According to another aspect, a method by a UE (user equipment) comprises the steps of: transmitting a first message including status information of the UE to a network; receiving a second message from the network including auxiliary data generated based on collected information related to the UE and the status information of the UE; and evaluating a collision risk based on the auxiliary data, wherein based on whether the second message includes fidelity level information of the auxiliary data, the UE can determine whether to adjust an evaluation sensitivity of the collision risk.

[0031] According to another aspect, a network performing the method described above may be provided.

[0032] According to various embodiments, data / messages can be transmitted and received more accurately and efficiently in a wireless communication system. For example, the network can effectively support the UE's safety services by providing auxiliary information for UE risk assessment, and dynamically adjust the fidelity level of the auxiliary information based on the UE's collision risk value.

[0033] The effects that can be obtained in various embodiments are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art to which the present invention pertains from the description below.

[0034] The drawings attached to this specification are intended to provide an understanding of the present invention, illustrate various embodiments of the present invention, and together with the description of the specification serve to explain the principles of the present invention.

[0035] Figure 1 is a diagram for comparing and explaining V2X communication based on RAT before NR and V2X communication based on NR.

[0036] Figure 2 shows the structure of the LTE system.

[0037] Figure 3 shows the structure of the NR system.

[0038] Figure 4 shows the structure of a radio frame of NR.

[0039] Figure 5 shows the slot structure of an NR frame.

[0040] FIG. 6 illustrates a communication structure that can be provided in a 6G system according to one embodiment of the present disclosure.

[0041] FIG. 7 illustrates an electromagnetic spectrum according to one embodiment of the present disclosure.

[0042] FIG. 8 illustrates an example of a typical scenario of an NTN based on a transparent payload, according to one embodiment of the present disclosure.

[0043] FIG. 9 illustrates an example of a typical scenario of an NTN based on a regenerative payload, according to one embodiment of the present disclosure.

[0044] FIG. 10 illustrates an example of a sensing operation according to one embodiment of the present disclosure.

[0045] Figure 11 shows a radio protocol architecture for SL communication.

[0046] Figure 12 shows a terminal performing V2X or SL communication.

[0047] Figure 13 shows resource units for V2X or SL communication.

[0048] FIG. 14 illustrates an example of a BWP according to one embodiment of the present disclosure.

[0049] FIG. 15 illustrates a procedure for a terminal to perform V2X or SL communication according to a resource allocation mode, according to one embodiment of the present disclosure.

[0050] Figure 16 is a diagram for explaining the AMQP protocol for transmitting V2N messages.

[0051] Figure 17 is a diagram for explaining the MQTT protocol for transmitting V2N messages.

[0052] Figure 18 is a diagram illustrating how a V2X infrastructure or server operates a digital twin for a terminal.

[0053] FIG. 19, FIG. 20 and FIG. 21 are diagrams illustrating a method for a V2X infrastructure to provide additional analysis information to a terminal based on collected data.

[0054] FIG. 22 is a diagram illustrating a method for a network to provide auxiliary data to a UE for collision risk assessment.

[0055] Figure 23 is a diagram illustrating a method for a UE to receive auxiliary data for determining collision risk.

[0056] Figure 24 illustrates a communication system applied to the present invention.

[0057] Figure 25 illustrates a wireless device applicable to the present invention.

[0058] Figure 26 illustrates another example of a wireless device applicable to the present invention. The wireless device may be implemented in various forms depending on the use case / service.

[0059] Figure 27 illustrates a vehicle or autonomous vehicle to which the present invention is applied.

[0060] A wireless communication system is a multiple access system that supports communication with multiple users by sharing available system resources (e.g., bandwidth, transmission power, etc.). Examples of multiple access systems include code division multiple access (CDMA), frequency division multiple access (FDMA), time division multiple access (TDMA), orthogonal frequency division multiple access (OFDMA), single carrier frequency division multiple access (SC-FDMA), and multi-carrier frequency division multiple access (MC-FDMA).

[0061] Sidelink refers to a communication method that establishes a direct link between user equipment (UE), allowing voice or data to be exchanged directly between terminals without going through a base station (BS). Sidelink is being considered as a solution to address the burden on base stations due to rapidly increasing data traffic.

[0062] V2X (vehicle-to-everything) refers to a communication technology that exchanges information with other vehicles, pedestrians, and infrastructure-based objects through wired / wireless communication. V2X can be divided into four types: V2V (vehicle-to-vehicle), V2I (vehicle-to-infrastructure), V2N (vehicle-to-network), and V2P (vehicle-to-pedestrian). V2X communication can be provided through the PC5 interface and / or Uu interface.

[0063] Meanwhile, as more and more communication devices demand greater communication capacity, the need for improved mobile broadband communication compared to existing radio access technology (RAT) is emerging. Accordingly, communication systems that consider services or terminals sensitive to reliability and latency are being discussed. Next-generation wireless access technologies that consider improved mobile broadband communication, massive MTC, and URLLC (Ultra-Reliable and Low Latency Communication) can be called new radio access technology (RAT) or new radio (NR). NR can also support V2X (vehicle-to-everything) communication.

[0064] The following technologies can be used in various wireless communication 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). CDMA can be implemented with wireless technologies such as UTRA (universal terrestrial radio access) or CDMA2000. TDMA can be implemented with wireless technologies such as GSM (global system for mobile communications) / GPRS (general packet radio service) / EDGE (enhanced data rates for GSM evolution). OFDMA can be implemented with wireless technologies such as IEEE (Institute of Electrical and Electronics Engineers) 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802-20, and E-UTRA (evolved UTRA). IEEE 802.16m is an evolution of IEEE 802.16e, providing backward compatibility with systems based on IEEE 802.16e. UTRA is part of UMTS (universal mobile telecommunications system). 3GPP (3rd generation partnership project) LTE (long term evolution) is a part of E-UMTS (evolved UMTS) that uses E-UTRA (evolved-UMTS terrestrial radio access), employing OFDMA in the downlink and SC-FDMA in the uplink.LTE-A (advanced) is an evolution of 3GPP LTE.

[0065] 5G NR, the successor to LTE-A, is a new clean-slate mobile communications system featuring high performance, low latency, and high availability. 5G NR can utilize all available spectrum resources, from low-frequency bands below 1 GHz, mid-frequency bands between 1 GHz and 10 GHz, and high-frequency (millimeter wave) bands above 24 GHz.

[0066] For clarity, the description will focus on LTE-A or 5G NR, but the technical ideas of the embodiment(s) are not limited thereto.

[0067] Figure 2 illustrates the architecture of an applicable LTE system. This may be referred to as an Evolved-UMTS Terrestrial Radio Access Network (E-UTRAN) or a Long Term Evolution (LTE) / LTE-A system.

[0068] Referring to FIG. 2, the E-UTRAN includes a base station (20; BS) that provides a control plane and a user plane to a terminal (10). The terminal (10) may be fixed or mobile, and may be referred to by other terms such as a mobile station (MS), a user terminal (UT), a subscriber station (SS), a mobile terminal (MT), a wireless device, etc. The base station (20) refers to a fixed station that communicates with the terminal (10), and may be referred to by other terms such as an evolved-NodeB (eNB), a base transceiver system (BTS), an access point, etc.

[0069] Base stations (20) can be connected to each other via the X2 interface. The base station (20) is connected to an EPC (Evolved Packet Core, 30) via the S1 interface, more specifically, to an MME (Mobility Management Entity) via the S1-MME, and to an S-GW (Serving Gateway) via the S1-U.

[0070] The EPC (30) consists of an MME, an S-GW, and a P-GW (Packet Data Network-Gateway). The MME holds information about terminal access and capabilities, and this information is primarily used for terminal mobility management. The S-GW is a gateway with the E-UTRAN as its endpoint, and the P-GW is a gateway with the PDN as its endpoint.

[0071] The layers of the radio interface protocol between the terminal and the network can be divided into L1 (Layer 1), L2 (Layer 2), and L3 (Layer 3) based on the three lower layers of the Open System Interconnection (OSI) standard model, which is widely known in communication systems. Among these, the physical layer belonging to Layer 1 provides an information transfer service using a physical channel, and the RRC (Radio Resource Control) layer located in Layer 3 controls radio resources between the terminal and the network. To this end, the RRC layer exchanges RRC messages between the terminal and the base station.

[0072] Figure 3 shows the structure of the NR system.

[0073] Referring to FIG. 3, the NG-RAN may include a gNB and / or an eNB that provides user plane and control plane protocol termination to the UE. FIG. 7 illustrates a case where only a gNB is included. The gNB and eNB are connected to each other via an Xn interface. The gNB and eNB are connected to the 5th generation core network (5G Core Network: 5GC) via the NG interface. More specifically, the gNB is connected to the access and mobility management function (AMF) via the NG-C interface, and the gNB is connected to the user plane function (UPF) via the NG-U interface.

[0074] Figure 4 shows the structure of a radio frame of NR.

[0075] Referring to FIG. 4, radio frames can be used for uplink and downlink transmission in NR. A radio frame has a length of 10 ms and can be defined as two 5 ms half-frames (Half-Frames, HF). A half-frame can include five 1 ms sub-frames (Subframes, SF). A sub-frame can be divided into one or more slots, and the number of slots within a sub-frame can be determined by the Subcarrier Spacing (SCS). Each slot can include 12 or 14 OFDM (A) symbols depending on the cyclic prefix (CP).

[0076] When normal CP is used, each slot can contain 14 symbols. When extended CP is used, each slot can contain 12 symbols. Here, the symbols can include OFDM symbols (or CP-OFDM symbols), SC-FDMA (Single Carrier - FDMA) symbols (or DFT-s-OFDM (Discrete Fourier Transform-spread-OFDM) symbols).

[0077] Table 1 below shows the number of symbols per slot ((N)) depending on the SCS setting (u) when normal CP is used. slot symb ), number of slots per frame ((N frame,u slot ) and the number of slots per subframe ((N subframe,u slot ) is an example.

[0078] SCS (15*2 u )N slot symb N frame,u slot N subframe,u slot 15KHz (u=0)1410130KHz (u=1)1420260KHz (u=2)14404120KHz (u=3)14808240KHz (u=4)1416016

[0079] Table 2 illustrates the number of symbols per slot, the number of slots per frame, and the number of slots per subframe according to SCS when extended CP is used.

[0080] SCS (15*2 u )N slot symb N frame,u slot N subframe,u slot 60KHz (u=2)12404

[0081] In an NR system, OFDM(A) numerology (e.g., SCS, CP length, etc.) may be set differently between multiple cells that are merged into a single terminal. Accordingly, the (absolute time) interval of a time resource (e.g., subframe, slot, or TTI) (conveniently referred to as TU (Time Unit)) consisting of the same number of symbols may be set differently between the merged cells.

[0082] In NR, multiple numerologies, or SCSs, can be supported to support various 5G services. For example, a 15 kHz SCS can support wide areas in traditional cellular bands, while a 30 kHz / 60 kHz SCS can support dense urban areas, lower latency, and wider carrier bandwidth. A 60 kHz or higher SCS can support bandwidths greater than 24.25 GHz to overcome phase noise.

[0083] The NR frequency band can be defined by two types of frequency ranges. The two types of frequency ranges can be FR1 and FR2. The numerical values ​​of the frequency ranges can be changed, and for example, the two types of frequency ranges can be as shown in Table 3 below. Among the frequency ranges used in the NR system, FR1 can mean the "sub 6 GHz range", and FR2 can mean the "above 6 GHz range" and can be called millimeter wave (mmW).

[0084] Frequency Range designationCorresponding frequency rangeSubcarrier Spacing (SCS)FR1450MHz - 6000MHz15, 30, 60kHzFR224250MHz - 52600MHz60, 120, 240kHz

[0085] As described above, the numerical value of the frequency range of the NR system can be changed. For example, FR1 may include a band from 410 MHz to 7125 MHz, as shown in Table 4 below. That is, FR1 may include a frequency band above 6 GHz (or 5850, 5900, 5925 MHz, etc.). For example, the frequency band above 6 GHz (or 5850, 5900, 5925 MHz, etc.) included within FR1 may include an unlicensed band. The unlicensed band may be used for various purposes, such as for vehicular communications (e.g., autonomous driving).

[0086] Frequency Range designationCorresponding frequency rangeSubcarrier Spacing (SCS)FR1410MHz - 7125MHz15, 30, 60kHzFR224250MHz - 52600MHz60, 120, 240kHz

[0087] Figure 5 shows the slot structure of an NR frame.

[0088] Referring to Figure 5, a slot includes multiple symbols in the time domain. For example, in the case of a normal CP, one slot may include 14 symbols, but in the case of an extended CP, one slot may include 12 symbols. Alternatively, in the case of a normal CP, one slot may include 7 symbols, but in the case of an extended CP, one slot may include 6 symbols.

[0089] A carrier includes multiple subcarriers in the frequency domain. An RB (Resource Block) can be defined as multiple (e.g., 12) consecutive subcarriers in the frequency domain. A BWP (Bandwidth Part) can be defined as multiple consecutive (P)RBs ((Physical) Resource Blocks) in the frequency domain, and can correspond to one numerology (e.g., SCS, CP length, etc.). A carrier can include up to N (e.g., 5) BWPs. Data communication can be performed through activated BWPs. Each element can be referred to as a Resource Element (RE) in the resource grid, and one complex symbol can be mapped to it.

[0090] Meanwhile, the wireless interface between terminals or between terminals and a network may be composed of an L1 layer, an L2 layer, and an L3 layer. In various embodiments of the present disclosure, the L1 layer may refer to a physical layer. Furthermore, for example, the L2 layer may refer to at least one of a MAC layer, an RLC layer, a PDCP layer, and an SDAP layer. Furthermore, for example, the L3 layer may refer to an RRC layer.

[0091] FIG. 6 illustrates a communication structure that can be provided in a 6G system according to an embodiment of the present disclosure. The embodiment of FIG. 6 can be combined with various embodiments of the present disclosure.

[0092] New network characteristics in 6G may include:

[0093] - Satellite integrated network

[0094] - Connected Intelligence: Unlike previous generations of wireless communication systems, 6G is revolutionary, upgrading the wireless evolution from "connected objects" to "connected intelligence." AI can be applied at every stage of the communication process (or at every signal processing step, as described below).

[0095] - Seamless integration of wireless information and energy transfer

[0096] - Ubiquitous super 3D connectivity: Access to networks and core network functions of drones and very low Earth orbit satellites will create super 3D connectivity in 6G ubiquitous.

[0097] Some general requirements for the new network characteristics of 6G, such as the above, may be as follows:

[0098] - small cell networks

[0099] - Ultra-dense heterogeneous network

[0100] - High-capacity backhaul

[0101] - Radar technology integrated with mobile technology: High-precision localization (or location-based services) through communications is a key feature of 6G wireless communication systems. Therefore, radar systems will be integrated with 6G networks.

[0102] - Softwarization and virtualization

[0103] Below, the core implementation technologies of the 6G system are described.

[0104] - Artificial Intelligence: Incorporating AI into communications can streamline and improve real-time data transmission. AI can use numerous analytics to determine how complex target tasks should be performed. This means AI can increase efficiency and reduce processing delays. Time-consuming tasks such as handovers, network selection, and resource scheduling can be performed instantly using AI. AI can also play a crucial role in machine-to-machine (M2M), machine-to-human, and human-to-machine communications. Furthermore, AI can facilitate rapid communication in brain-computer interfaces (BCIs). AI-based communication systems can be supported by metamaterials, intelligent structures, intelligent networks, intelligent devices, intelligent cognitive radios, self-sustaining wireless networks, and machine learning.

[0105] - THz communication (terahertz communication): Data rates can be increased by increasing the bandwidth. This can be achieved by using sub-THz communication with wide bandwidths and applying advanced massive MIMO technology. THz waves, also known as sub-millimeter waves, typically refer to the frequency range between 0.1 THz and 10 THz, with corresponding wavelengths ranging from 0.03 mm to 3 mm. The 100 GHz to 300 GHz band (sub-THz band) is considered a key part of the THz spectrum for cellular communications. Adding the sub-THz band to the mmWave band will increase the capacity of 6G cellular communications. Among the defined THz bands, 300 GHz to 3 THz lies in the far infrared (IR) frequency band. While part of the optical band, the 300 GHz to 3 THz band lies at the boundary of the optical band, immediately following the RF band. Therefore, this 300 GHz to 3 THz band exhibits similarities to RF.

[0106] Figure 7 illustrates the electromagnetic spectrum according to one embodiment of the present disclosure. The embodiment of Figure 7 can be combined with various embodiments of the present disclosure. Key characteristics of THz communications include (i) a widely available bandwidth to support very high data rates, and (ii) high path loss at high frequencies (highly directional antennas are essential). The narrow beamwidth generated by the highly directional antenna reduces interference. The small wavelength of THz signals allows for a much larger number of antenna elements to be integrated into devices and base stations operating in this band. This enables the use of advanced adaptive array techniques to overcome range limitations.

[0107] - Large-scale MIMO technology

[0108] - Hologram beamforming (HBF)

[0109] - Optical wireless technology

[0110] - Free-space optical transmission backhaul network (FSO backhaul network)

[0111] - Quantum communication

[0112] - Cell-free communication

[0113] - Integration of wireless information and power transmission

[0114] - Integration of wireless communication and sensing

[0115] - Integrated access and backhaul network

[0116] - Big data analysis

[0117] - Reconfigurable intelligent surface

[0118] - metaverse

[0119] - Blockchain

[0120] Unmanned aerial vehicles (UAVs): UAVs, or drones, will be a key element in 6G wireless communications. In most cases, high-speed data wireless connectivity can be provided using UAV technology. Base stations (BSs) can be installed on UAVs to provide cellular connectivity. UAVs may offer specific capabilities not found in fixed BS infrastructure, such as easy deployment, robust line-of-sight links, and controlled mobility. During emergencies such as natural disasters, deploying terrestrial communications infrastructure is not economically feasible and sometimes cannot provide services in volatile environments. UAVs can easily handle these situations. UAVs will become a new paradigm in wireless communications. This technology facilitates three fundamental requirements for wireless networks: enhanced mobile broadband (eMBB), URLLC, and mMTC. UAVs can also support various purposes, such as enhancing network connectivity, fire detection, disaster emergency services, security and surveillance, pollution monitoring, parking monitoring, and accident monitoring. Therefore, UAV technology is recognized as one of the most important technologies for 6G communications.

[0121] - Autonomous driving (self-driving): V2X (vehicle to everything), a key element in building autonomous driving infrastructure, can be a technology that allows cars to communicate and share with various elements on the road for autonomous driving, such as vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless communication. Fast transmission speeds and low-latency technologies are essential to maximize autonomous driving performance and ensure high safety. Furthermore, in the future, autonomous driving will go beyond simply providing warnings or guidance messages to drivers and may require active intervention in vehicle operation and direct control of the vehicle in dangerous situations. To this end, the amount of information that needs to be transmitted and received may become enormous, so 6G is expected to maximize autonomous driving with faster transmission speeds and lower latency than 5G.

[0122] - Non-terrestrial networks (NTN): NTN may refer to a network or network segment that uses radio frequency (RF) resources mounted on a satellite (or unmanned aerial system (UAS) platform). FIG. 8 illustrates an example of a typical NTN scenario based on a transparent payload according to an embodiment of the present disclosure. FIG. 9 illustrates an example of a typical NTN scenario based on a regenerative payload according to an embodiment of the present disclosure. The embodiments of FIG. 8 or FIG. 9 may be combined with various embodiments of the present disclosure. Referring to FIG. 8, a satellite (or UAS platform) may create a service link with a UE. The satellite (or UAS platform) may be connected to a gateway via a feeder link. The satellite may be connected to a data network via the gateway. A beam footprint may refer to an area where a signal transmitted by a satellite can be received. Referring to Figure 9, a satellite (or UAS platform) can establish a service link with a UE. A satellite (or UAS platform) connected to a UE can be connected to another satellite (or UAS platform) via an inter-satellite link (ISL). The other satellite (or UAS platform) can be connected to a gateway via a feeder link. Based on the replay payload, a satellite can be connected to a data network through another satellite and the gateway. If an ISL does not exist between a satellite and another satellite, a feeder link between the satellite and the gateway may be required. Figures 8 and 9 are merely examples of NTN scenarios, and NTN can be implemented based on various scenarios.For example, a satellite (or UAS platform) may implement a transparent or regenerative (with onboard processing) payload. For example, a satellite (or UAS platform) may generate multiple beams over a designated service area depending on the field of view of the satellite (or UAS platform). For example, the field of view of the satellite (or UAS platform) may vary depending on the onboard antenna diagram and minimum elevation angle. For example, a transparent payload may include radio frequency filtering, frequency conversion, and amplification. Therefore, the waveform signal repeated by the payload may not be altered. For example, a regenerative payload may include radio frequency filtering, frequency conversion and amplification, demodulation / decoding, switching and / or routing, and coding / modulation. For example, a regenerative payload may be substantially equivalent to equipping the satellite (or UAS platform) with all or part of the base station functionality.

[0123] - Integrated Sensing and Communication (ISAC): Wireless sensing is a technology that uses radio frequencies to determine the instantaneous linear velocity, angle, distance (range), etc. of an object, thereby obtaining information about the characteristics of the environment and / or objects within the environment. Because radio frequency sensing does not require a device to connect to the object through a network, it can provide a service for object positioning without a device. The ability to obtain range, velocity, and angle information from radio frequency signals can enable a wide range of new capabilities, such as various object detection, object recognition (e.g., vehicles, humans, animals, UAVs), and high-precision localization, tracking, and activity recognition. Wireless sensing services can provide information to a variety of industries (e.g., drones, smart homes, V2X, factories, railways, public safety, etc.), enabling applications such as intruder detection, assisted vehicle steering and navigation, trajectory tracking, collision avoidance, traffic management, and health and traffic management. In some cases, wireless sensing can utilize non-3GPP type sensors (e.g., radar, cameras) to further support 3GPP-based sensing. For example, the operation of a wireless sensing service, i.e., a sensing operation, may depend on the transmission, reflection, and scattering of wireless sensing signals. Therefore, wireless sensing may provide an opportunity to enhance existing communication systems from a communication network to a wireless communication and sensing network. FIG. 10 illustrates an example of a sensing operation according to an embodiment of the present disclosure. The embodiment of FIG. 10 may be combined with various embodiments of the present disclosure. Specifically, FIG. 10 (a) illustrates an example of sensing using a sensing receiver and a sensing transmitter located at the same location (e.g., monostatic sensing), and FIG. 10 (b) illustrates an example of sensing using a separated sensing receiver and a sensing transmitter (e.g., bistatic sensing).

[0124] Figure 11 illustrates a radio protocol architecture for SL communication. Specifically, Figure 11 (a) illustrates the user plane protocol stack of NR, and Figure 11 (b) illustrates the control plane protocol stack of NR.

[0125] Below, the SL synchronization signal (Sidelink Synchronization Signal, SLSS) and synchronization information are described.

[0126] SLSS is an SL-specific sequence and may include a Primary Sidelink Synchronization Signal (PSSS) and a Secondary Sidelink Synchronization Signal (SSSS). The PSSS may be referred to as a Sidelink Primary Synchronization Signal (S-PSS), and the SSSS may be referred to as a Sidelink Secondary Synchronization Signal (S-SSS). For example, length-127 M-sequences may be used for the S-PSS, and length-127 Gold sequences may be used for the S-SSS. For example, a terminal may detect an initial signal and acquire synchronization using the S-PSS. For example, a terminal may acquire detailed synchronization and detect a synchronization signal ID using the S-PSS and the S-SSS.

[0127] PSBCH (Physical Sidelink Broadcast Channel) may be a (broadcast) channel that transmits basic (system) information that a terminal must know first before transmitting or receiving an SL signal. For example, the basic information may be information related to SLSS, duplex mode (DM), TDD UL / DL (Time Division Duplex Uplink / Downlink) configuration, resource pool-related information, type of application related to SLSS, subframe offset, broadcast information, etc. For example, in NR V2X, for evaluating PSBCH performance, the payload size of PSBCH may be 56 bits, including a 24-bit CRC.

[0128] S-PSS, S-SSS and PSBCH may be included in a block format supporting periodic transmission (e.g., SL SS (Synchronization Signal) / PSBCH block, hereinafter referred to as S-SSB (Sidelink-Synchronization Signal Block)). The S-SSB may have the same numerology (i.e., SCS and CP length) as the PSCCH (Physical Sidelink Control Channel) / PSSCH (Physical Sidelink Shared Channel) in the carrier, and the transmission bandwidth may be within a (pre-)configured SL BWP (Sidelink BWP). For example, the bandwidth of the S-SSB may be 11 RBs (Resource Blocks). For example, the PSBCH may span 11 RBs. And, the frequency location of the S-SSB may be (pre-)configured. Therefore, the terminal does not need to perform hypothesis detection in the frequency to discover the S-SSB in the carrier.

[0129] Meanwhile, in the NR SL system, multiple numerologies having different SCS and / or CP lengths may be supported. In this case, as the SCS increases, the length of the time resource for a transmitting terminal to transmit an S-SSB may become shorter. Accordingly, the coverage of the S-SSB may decrease. Therefore, in order to ensure the coverage of the S-SSB, the transmitting terminal may transmit one or more S-SSBs to a receiving terminal within one S-SSB transmission period according to the SCS. For example, the number of S-SSBs that the transmitting terminal transmits to the receiving terminal within one S-SSB transmission period may be pre-configured or configured for the transmitting terminal. For example, the S-SSB transmission period may be 160 ms. For example, an S-SSB transmission period of 160 ms may be supported for all SCSs.

[0130] For example, when the SCS is 15 kHz at FR1, the transmitting terminal can transmit one or two S-SSBs to the receiving terminal within one S-SSB transmission period. For example, when the SCS is 30 kHz at FR1, the transmitting terminal can transmit one or two S-SSBs to the receiving terminal within one S-SSB transmission period. For example, when the SCS is 60 kHz at FR1, the transmitting terminal can transmit one, two, or four S-SSBs to the receiving terminal within one S-SSB transmission period.

[0131] For example, when the SCS is 60 kHz at FR2, the transmitting terminal can transmit 1, 2, 4, 8, 16, or 32 S-SSBs to the receiving terminal within one S-SSB transmission period. For example, when the SCS is 120 kHz at FR2, the transmitting terminal can transmit 1, 2, 4, 8, 16, 32, or 64 S-SSBs to the receiving terminal within one S-SSB transmission period.

[0132] Meanwhile, when the SCS is 60 kHz, two types of CP may be supported. In addition, the structure of the S-SSB transmitted by the transmitting terminal to the receiving terminal may be different depending on the CP type. For example, the CP type may be Normal CP (NCP) or Extended CP (ECP). Specifically, for example, when the CP type is NCP, the number of symbols to which the PSBCH is mapped within the S-SSB transmitted by the transmitting terminal may be 9 or 8. On the other hand, for example, when the CP type is ECP, the number of symbols to which the PSBCH is mapped within the S-SSB transmitted by the transmitting terminal may be 7 or 6. For example, the PSBCH may be mapped to the first symbol within the S-SSB transmitted by the transmitting terminal. For example, the receiving terminal receiving the S-SSB may perform an Automatic Gain Control (AGC) operation in the first symbol section of the S-SSB.

[0133] Figure 12 shows a terminal performing V2X or SL communication.

[0134] Referring to FIG. 12, the term "terminal" in V2X or SL communication may primarily refer to a user's terminal. However, if a network device such as a base station transmits and receives signals according to a communication method between terminals, the base station may also be considered a type of terminal. For example, terminal 1 may be a first device (100), and terminal 2 may be a second device (200).

[0135] For example, terminal 1 can select a resource unit corresponding to a specific resource within a resource pool, which represents a set of resources. Then, terminal 1 can transmit an SL signal using the resource unit. For example, terminal 2, which is a receiving terminal, can be configured with a resource pool in which terminal 1 can transmit a signal, and can detect a signal from terminal 1 within the resource pool.

[0136] Here, if terminal 1 is within the connection range of the base station, the base station can inform terminal 1 of the resource pool. On the other hand, if terminal 1 is outside the connection range of the base station, another terminal can inform terminal 1 of the resource pool, or terminal 1 can use a pre-configured resource pool.

[0137] In general, a resource pool can be composed of multiple resource units, and each terminal can select one or multiple resource units to use for its SL signal transmission.

[0138] Figure 13 shows resource units for V2X or SL communication.

[0139] Referring to Figure 13, the entire frequency resources of the resource pool can be divided into NF units, and the entire time resources of the resource pool can be divided into NT units. Therefore, a total of NF * NT resource units can be defined within the resource pool. Figure 13 illustrates an example where the resource pool repeats with a cycle of NT subframes.

[0140] As illustrated in Figure 13, a single resource unit (e.g., Unit #0) may appear periodically and repeatedly. Alternatively, to achieve diversity effects in the time or frequency dimensions, the index of the physical resource unit to which a single logical resource unit is mapped may change in a predetermined pattern over time. In this resource unit structure, a resource pool may refer to a set of resource units that a terminal wishing to transmit an SL signal can use for transmission.

[0141] Resource pools can be subdivided into several categories. For example, based on the content of the SL signal transmitted from each resource pool, resource pools can be categorized as follows:

[0142] (1) Scheduling Assignment (SA) may be a signal that includes information such as the location of resources used by a transmitting terminal for transmission of an SL data channel, MCS (Modulation and Coding Scheme) or MIMO (Multiple Input Multiple Output) transmission method required for demodulation of other data channels, and TA (Timing Advance). SA may also be transmitted multiplexed with SL data on the same resource unit, in which case the SA resource pool may mean a resource pool in which SA is multiplexed with SL data and transmitted. SA may also be called an SL control channel.

[0143] (2) The SL data channel (Physical Sidelink Shared Channel, PSSCH) may be a resource pool used by a transmitting terminal to transmit user data. If SA is multiplexed and transmitted together with SL data on the same resource unit, only the SL data channel excluding SA information may be transmitted from the resource pool for the SL data channel. In other words, the REs (Resource Elements) that were used to transmit SA information on individual resource units within the SA resource pool may still be used to transmit SL data in the resource pool of the SL data channel. For example, the transmitting terminal may transmit the PSSCH by mapping it to consecutive PRBs.

[0144] (3) A discovery channel may be a resource pool for transmitting terminals to transmit information such as their IDs. Through this, transmitting terminals can enable neighboring terminals to discover them.

[0145] Even if the content of the SL signal described above is the same, different resource pools may be used depending on the transmission and reception properties of the SL signal. For example, even if it is the same SL data channel or discovery message, it may be again divided into different resource pools depending on the transmission timing determination method of the SL signal (for example, whether it is transmitted at the time of reception of a synchronization reference signal or whether it is transmitted by applying a certain timing advance at the time of reception), the resource allocation method (for example, whether the base station designates transmission resources for individual signals to individual transmitting terminals or whether individual transmitting terminals independently select individual signal transmission resources within the resource pool), the signal format (for example, the number of symbols each SL signal occupies in one subframe or the number of subframes used for transmission of one SL signal), the signal strength from the base station, the transmission power strength of the SL terminal, etc.

[0146] FIG. 14 illustrates an example of a BWP according to an embodiment of the present disclosure. The embodiment of FIG. 14 can be combined with various embodiments of the present disclosure. In the embodiment of FIG. 14, it is assumed that there are three BWPs.

[0147] Referring to Figure 14, a common resource block (CRB) may be a carrier resource block numbered from one end of a carrier band to the other. Furthermore, a PRB may be a numbered resource block within each BWP. Point A may indicate a common reference point for the resource block grid.

[0148] The BWP can be set by Point A, an offset from Point A (NstartBWP), and a bandwidth (NsizeBWP). For example, Point A can be an outer reference point of a PRB of a carrier where subcarrier 0 of all numerologies (e.g., all numerologies supported by the network on that carrier) are aligned. For example, the offset can be the PRB spacing between the lowest subcarrier in a given numerology and Point A. For example, the bandwidth can be the number of PRBs in a given numerology.

[0149] SLSS (Sidelink Synchronization Signal) is a SL (sidelink) specific sequence and may include PSSS (Primary Sidelink Synchronization Signal) and SSSS (Secondary Sidelink Synchronization Signal). The PSSS may be referred to as S-PSS (Sidelink Primary Synchronization Signal) and the SSSS may be referred to as S-SSS (Sidelink Secondary Synchronization Signal). For example, length-127 M-sequences may be used for S-PSS and length-127 Gold sequences may be used for S-SSS. For example, a terminal may detect an initial signal (signal detection) and obtain synchronization using S-PSS. For example, the terminal can obtain detailed synchronization using S-PSS and S-SSS and detect a synchronization signal ID.

[0150] PSBCH (Physical Sidelink Broadcast Channel) may be a (broadcast) channel that transmits basic (system) information that a terminal must know first before transmitting or receiving an SL signal. For example, the basic information may be information related to SLSS, duplex mode (DM), TDD UL / DL (Time Division Duplex Uplink / Downlink) configuration, resource pool-related information, type of application related to SLSS, subframe offset, broadcast information, etc. For example, in order to evaluate PSBCH performance, in NR V2X, the payload size of PSBCH may be 56 bits, including a 24-bit CRC (Cyclic Redundancy Check).

[0151] S-PSS, S-SSS and PSBCH may be included in a block format supporting periodic transmission (e.g., SL SS (Synchronization Signal) / PSBCH block, hereinafter referred to as S-SSB (Sidelink-Synchronization Signal Block)). The S-SSB may have the same numerology (i.e., SCS and CP length) as the PSCCH (Physical Sidelink Control Channel) / PSSCH (Physical Sidelink Shared Channel) in the carrier, and the transmission bandwidth may be within a (pre-)configured SL BWP (Sidelink BWP). For example, the bandwidth of the S-SSB may be 11 RBs (Resource Blocks). For example, the PSBCH may span 11 RBs. And, the frequency location of the S-SSB may be (pre-)configured. Therefore, the terminal does not need to perform hypothesis detection in the frequency to discover the S-SSB in the carrier.

[0152] FIG. 15 illustrates a procedure for a terminal to perform V2X or SL communication according to a resource allocation mode, according to one embodiment of the present disclosure. The embodiment of FIG. 15 may be combined with various embodiments of the present disclosure.

[0153] Referring to (a) of FIG. 15, in resource allocation mode 1, the base station may schedule SL resources to be used by the terminal for SL transmission. For example, in step S1500, the base station may transmit information related to SL resources and / or information related to UL resources to the first terminal. For example, the UL resources may include PUCCH resources and / or PUSCH resources. For example, the UL resources may be resources for reporting SL HARQ feedback to the base station.

[0154] For example, a first terminal may receive information related to a dynamic grant (DG) resource and / or information related to a configured grant (CG) resource from a base station. For example, a CG resource may include a CG type 1 resource or a CG type 2 resource. In this specification, a DG resource may be a resource that a base station configures / allocates to the first terminal via downlink control information (DCI). In this specification, a CG resource may be a (periodic) resource that a base station configures / allocates to the first terminal via DCI and / or an RRC message. For example, in the case of a CG type 1 resource, the base station may transmit an RRC message including information related to the CG resource to the first terminal. For example, in the case of a CG type 2 resource, the base station may transmit an RRC message including information related to the CG resource to the first terminal, and the base station may transmit a DCI related to activation or release of the CG resource to the first terminal.

[0155] In step S1510, the first terminal may transmit a PSCCH (e.g., Sidelink Control Information (SCI) or 1st-stage SCI) to the second terminal based on the resource scheduling. In step S1520, the first terminal may transmit a PSSCH (e.g., 2nd-stage SCI, MAC PDU, data, etc.) related to the PSCCH to the second terminal. In step S1530, the first terminal may receive a PSFCH related to the PSCCH / PSSCH from the second terminal. For example, HARQ feedback information (e.g., NACK information or ACK information) may be received from the second terminal via the PSFCH. In step S1540, the first terminal may transmit / report HARQ feedback information to the base station via a PUCCH or a PUSCH. For example, the HARQ feedback information reported to the base station may be information generated by the first terminal based on the HARQ feedback information received from the second terminal. For example, the HARQ feedback information reported to the base station may be information generated by the first terminal based on a rule set in advance. For example, the DCI may be DCI for scheduling SL.

[0156] Referring to (b) of FIG. 15, in resource allocation mode 2, a terminal can determine SL transmission resources within SL resources set by a base station / network or preset SL resources. For example, the set SL resources or preset SL resources may be a resource pool. For example, the terminal can autonomously select or schedule resources for SL transmission. For example, the terminal can perform SL communication by selecting resources by itself within the set resource pool. For example, the terminal can select resources by itself within a selection window by performing sensing and resource (re)selection procedures. For example, the sensing can be performed on a subchannel basis. For example, in step S1510, a first terminal that has selected resources by itself within a resource pool can transmit a PSCCH (e.g., Sidelink Control Information (SCI) or 1st-stage SCI) to a second terminal using the resources. In step S1520, the first terminal may transmit a PSSCH (e.g., 2nd-stage SCI, MAC PDU, data, etc.) related to the PSCCH to the second terminal. In step S1530, the first terminal may receive a PSFCH related to the PSCCH / PSSCH from the second terminal.

[0157] Referring to (a) or (b) of FIG. 15, for example, a first terminal may transmit an SCI to a second terminal on a PSCCH. Or, for example, the first terminal may transmit two consecutive SCIs (e.g., 2-stage SCIs) to the second terminal on the PSCCH and / or the PSSCH. In this case, the second terminal may decode the two consecutive SCIs (e.g., 2-stage SCIs) to receive the PSSCH from the first terminal. In this specification, an SCI transmitted on a PSCCH may be referred to as a 1st SCI, a 1st SCI, a 1st-stage SCI, or a 1st-stage SCI format, and an SCI transmitted on a PSSCH may be referred to as a 2nd SCI, a 2nd SCI, a 2nd-stage SCI, or a 2nd-stage SCI format.

[0158] Referring to (a) or (b) of FIG. 15, in step S1530, the first terminal may receive a PSFCH. For example, the first terminal and the second terminal may determine PSFCH resources, and the second terminal may use the PSFCH resources to transmit HARQ feedback to the first terminal.

[0159] Referring to (a) of FIG. 15, in step S1540, the first terminal may transmit SL HARQ feedback to the base station via PUCCH and / or PUSCH.

[0160] Meanwhile, the aforementioned sidelink can be defined as terminal-to-terminal communication or direct communication between terminals. In this case, the PSCCH can be defined as a physical control channel for terminal-to-terminal communication, the PSSCH as a physical data channel or physical shared channel for terminal-to-terminal communication, and the PSFCH as a physical feedback transmission channel between terminals.

[0161] Meanwhile, the SoftV2X service or SoftV2X system is a system in which a SoftV2X server receives a VRU message or a PSM (Personal Safety Message) from a VRU (Vulnerable Road User) or a V2X vehicle through a UU interface for V2X communication, and transmits information on surrounding VRUs or vehicles based on the VRU message or PSM message, or analyzes the road conditions on which surrounding VRUs or vehicles are moving, and transmits a message to notify surrounding VRUs or vehicles of a collision warning based on the analyzed information. Here, the VRU message or PSM message is a message transmitted to the SoftV2X server through the UU interface, and may include mobility information on the VRU, such as the location, moving direction, moving path, and speed of the VRU. In other words, the SoftV2X system receives mobility information on VRUs and / or vehicles related to V2X communication through the UU interface, and the softV2X server, such as a network, controls the driving path of the VRU, the VRU movement flow, etc. based on the received mobility information. Alternatively, the SoftV2X system can be configured in relation to V2N communications.

[0162] Below, we describe in detail how a network can provide V2X services based on a message protocol.

[0163] MQTT / AMQP protocol

[0164] Figure 16 is a diagram for explaining AMQP (Advanced Message Queuing Protocol) for transmitting V2N messages, and Figure 17 is a diagram for explaining MQTT (Message Queuing Telemetry Transport) protocol for transmitting V2N messages.

[0165] Referring to Figure 16 (a), the AMQP protocol can be a message protocol that operates as a composition of a publisher, a broker, and a subscriber. The AMQP 1.0 protocol is an open standard protocol for asynchronous message transmission. This protocol standardizes communication between message-oriented middleware and clients, and can provide a high level of reliability, security, and interoperability. AMQP supports message orientation, queuing, routing (point-to-point, publish / subscribe), reliable, and secure transmission. It is widely used in various enterprise messaging applications. The AMQP 1.0 protocol message format is a binary protocol, enabling efficient message processing. The message structure consists of several parts, such as a header, properties, and a body, to support complex communication requirements.

[0166] Meanwhile, C-Road leverages AMQP 1.0 in the transportation and mobility fields to achieve reliable data exchange. They leverage AMQP's extensible and flexible framework for communication between various transportation management systems and devices. Referring to Figure 16 (b), the AMQP protocol format can consist of header, delivery-annotations, message-annotations, properties, application properties, application data, and footer fields. Here, C-Road's application properties can provide metadata describing the message content. Application properties contain information necessary for the receiver to interpret and appropriately process the message, thereby improving the efficiency and accuracy of communication. Furthermore, providing metadata through application properties can play a crucial role in ensuring that messages reach their intended destinations appropriately.

[0167] The MQTT protocol features lightweight network traffic and low bandwidth requirements, making it suitable for resource-constrained environments such as IoT devices and mobile applications. The MQTT protocol is based on a publish / subscribe model, enabling efficient message delivery and ensuring secure message delivery even in unstable network environments. The MQTT protocol is being adopted by various IoT platforms and V2N services due to its simple implementation and lightweight protocol structure, which facilitates widespread adoption.

[0168] Referring to Fig. 17 (a), the MQTT protocol may be a message protocol having a structure that operates as a composition of a publisher (or client), a broker, and a subscriber (or client or client device). Here, subscription and publication of messages may be performed based on topics. For example, a subscriber may receive only messages corresponding to its requested topic from the broker, and a publisher may transmit a message to the broker with a topic set to specify the target to receive its message. For example, a broker may filter messages to be published to a subscriber based on topics.

[0169] Referring to Fig. 17 (b), the MQTT protocol format can be composed of a fixed header, a variable header, and a payload. Referring to Fig. 17 (c), the fixed header of the MQTT protocol can always be included in all MQTT messages and contains message type and message length information. The variable header is optional and can contain different information depending on the message type. The payload contains the actual message data and can be defined according to the message type. The fixed header included in the MQTT control packet can define essential information including the packet type. This is because the 4th to 7th bits of the first byte of the packet define various MQTT states from CONNECT to DISCONNECT. Flags that provide additional information and functions can be set differently depending on the specific control packet type and can play a role in controlling the operation of the packet in detail. Remaining Length can tell you the total length of the control packet, including the variable header and payload.

[0170] The variable header includes a packet identifier and a property length, and the information allocated through these can play a significant role in the processing and routing of the message. In this regard, the MQTT 5.0 standard added a new section that allows user-defined properties (User Properties) to be included in the variable header. The User Properties can allow users to include additional information in the message. For example, a sender can define additional information for specific purposes or management from a service perspective. The User Properties are a way to exchange user-defined data between a client and a server, and can be defined multiple times for various information in a single message. The MQTT standard states that User Properties are not limited and are maintained universally, but can be extended as needed by users. Additionally, control packets of various states, such as CONNECT, CONNACK, PUBLISH, Will Properties, PUBACK, PUBREC, PUBREL, PUBCOMP, SUBSCRIBE, SUBACK, UNSUBSCRIBE, UNSUBACK, DISCONNECT, and AUTH, may contain user properties. These properties must be composed of UTF-8 (Unicode Transformation Format - 8-bit) character string pairs, and can be expressed in the form of Key and Value.

[0171] V2X infrastructure including digital twin

[0172] Figure 18 is a diagram illustrating how a V2X infrastructure or server operates a digital twin for a terminal.

[0173] Predicting a terminal's path and accident risk is highly important and useful, but prediction is very difficult, and the amount / quality of available information and the terminal's processing capabilities may be insufficient for the terminal to make precise / accurate predictions on its own. To address these issues, the concept or configuration of a digital twin (DT) for the terminal in the cloud can be introduced, enabling precise path prediction for the terminal through the digital twin based on various surrounding environmental information and collected data. For example, the digital twin can perform accident risk prediction for the terminal on behalf of the terminal based on various surrounding environmental information and collected data, and provide the predicted accident risk information to the terminal. Through such operations, it may be possible to reduce the accident risk for the terminal while increasing the effectiveness of cooperative driving.

[0174] Here, the concept of V2X for digital twin can be hierarchically distinguished. For example, as illustrated in Fig. 18 (a), analysis and service provision based on a digital twin configured in a cloud composed of Global DT (Cloud), Local DT (Edge), etc. may be possible, and learning, information processing, and inference related to the digital twin may be performed comprehensively by utilizing sensor information acquired through an RSU (road side unit) or / and information acquired by a server through V2N communication. For example, the cloud may include a pre-learned digital twin to predict a dangerous situation / movement path of the terminal based on sensing information / acquisition / collected information related to the terminal. Alternatively, as illustrated in Fig. 18 (b), an on-device digital twin may perform learning, information processing, and inference of a digital twin (or digital twin) module within the terminal by utilizing sensor information about the vehicle / mobile device and information acquired through V2I / V2N / V2V. For example, a terminal / device can configure a digital twin corresponding to itself, and the digital twin can be pre-trained to predict the movement path of the terminal / device based on the sensed information / acquisition information. This method is simply structured in a hierarchy for convenience of explanation, but the hierarchy can be further subdivided or simplified, and the gist of the method is to improve the analysis accuracy of the movement path of the device / terminal, etc. through collaboration between multiple entities, and to determine an appropriate analysis performer and level according to the analysis purpose of the required service.

[0175] Meanwhile, defining the role of digital twins in improving the performance of road user route and accident risk prediction, and defining under what circumstances and what information to utilize for digital twin-based analysis, may be a key issue. At this time, negotiation may be necessary between the server and the terminal to determine the entity performing the analysis and whether to utilize digital twins based on environmental factors (e.g., when the terminal's driving characteristics / environment make it difficult for the terminal to predict its own location based on information acquired on its own) and / or terminal-specific factors (e.g., when the terminal has limited capabilities (accuracy issues, analysis resources, battery, etc.), when the terminal has sufficient capabilities, objects detected by sensors of infrastructure or other UEs, etc.). For example, the terminal may need a method to receive information corrected / inferred with the help of Cloud / DT using ITS messages.

[0176] Dynamic analysis method and device using multi-data in V2X infrastructure

[0177] In the past, metrics such as time-to-collision (TTC) have been mainly used as a means / parameter for evaluating the collision risk of devices / terminals in safety services related to V2X-based collision risk prevention / assessment. TTC, which is calculated based on the distance between objects (or devices / terminals), has the following limitations. Since TTC is calculated under the assumption that the object / vehicle / device maintains the current speed and path, the predicted value related to TTC may fluctuate significantly when the behavior of the object / vehicle / device suddenly changes. In addition, the accuracy of the TTC may decrease in situations where multiple objects / vehicles / devices interact or when the accuracy and resolution of the sensor are low. In particular, in the case of Vulnerable Road User (VRU) or pedestrian devices, there may not be a terminal capable of broadcasting to the surrounding terminals. In addition, even if a VRU device or a pedestrian device transmits the status information of the VRU to surrounding vehicles through a V2X infrastructure (or network, server), the GPS accuracy included in the status information is relatively low, and it is difficult to predict the path based on the status information, so the collision risk assessment may not be accurate compared to vehicle-to-vehicle. For example, if a dynamic object that has not been recognized / detected suddenly appears / appears in a blind spot, it may be difficult to provide a safety service through risk prediction in a VRU device or pedestrian device. Or, even if the location and status information of the VRU is transmitted in a blind spot, the location and status information of the VRU may not be accurate due to geographical factors, and there may be a high possibility that the VRU or pedestrian may be exposed to a dangerous situation due to an error in risk prediction based on such inaccurate information.

[0178] To address these issues, in a V2X environment where various types of V2X infrastructure (terminals, RSUs, analysis networks, servers, clouds, etc.; hereinafter referred to as V2X infrastructure) are connected, it may be necessary to fuse and utilize various data, or cooperation between terminals and V2X infrastructure may be required. However, the fidelity and trust levels of data collected from V2X infrastructure may differ. Therefore, a method may be needed to optimize resources on the V2X infrastructure side by considering the fidelity and trust levels between data, while addressing various issues (uncertainty management, data insufficiency issues), and improving computational efficiency.

[0179] Hereinafter, a method / device capable of efficiently analyzing / providing appropriate additional information (or auxiliary information) according to the situation through data analysis based on dynamic fidelity adjustment when information from multiple data sources is collected in a V2X infrastructure to which various terminals (vehicles, VRUs, RSUs, etc.) are connected is described. For example, a V2X infrastructure can collect information / data about various types of terminals. Based on the collected information / data, the V2X infrastructure can provide information on whether a dangerous situation exists to a vehicle / terminal / VRU terminal. For example, even if a vehicle does not recognize a VRU in a blind spot, the terminal of the vehicle can receive dangerous situation detection information evaluated / produced by the V2X infrastructure and recognize the VRU located in the blind spot based on the transmitted dangerous situation detection information. Here, the V2X infrastructure can collect / acquire location / status information of the VRU related to the vehicle in advance based on data / information received from an RSU, a smartphone, and surrounding terminals. At this time, the V2X infrastructure can collect data with different fidelity, and based on the received data, it can judge / decide whether intervention of the V2X infrastructure is necessary in relation to risk assessment / collision risk judgment for the vehicle or VRU. For example, the V2X infrastructure can classify the collected data based on the fidelity of the data, adaptively sample the necessary information from the collected data, and selectively utilize data with higher accuracy / precision through adaptive sampling. In addition, the V2X infrastructure can dynamically adjust the degree of analysis (or depth) of the collected data by considering the availability level of the collected data in the current traffic situation and the provision time of information (or, additional information / auxiliary information) necessary for risk assessment of the terminal / device.For example, the V2X infrastructure can generate / provide additional information / auxiliary information, which is additional analysis information (e.g., collision risk) for the terminal, by integrating and operating a low-fidelity surrogate model and a high-fidelity surrogate model with different analysis accuracies or fidelities of the collected data (e.g., operating a multi-fidelity surrogate model). In this way, the V2X infrastructure can supplement / improve the prediction accuracy of collision risk at the terminal through collision risk analysis based on a multi-fidelity surrogate model. In addition, in terms of information provision of the V2X infrastructure, a risk response guideline can be established in which the provision of additional information (or auxiliary information) and / or the intervention authority of the V2X infrastructure are classified by risk level based on the risk prediction value results analyzed by the V2X infrastructure.

[0180] Meanwhile, the term “fidelity” or “fidelity level” can refer to a technical indicator of how closely certain data (e.g., auxiliary information, sensing results, prediction results, etc.) matches the actual environment or ground truth. Fidelity can be a value calculated by quantitatively or qualitatively evaluating the quality, reliability, accuracy, or prediction error range of the data after the data is generated or received through internal or external sensors, algorithms, network collection, etc. of the system. Quantitative fidelity can be expressed as a real number in the range [0, 1], for example, or provided as a probability-based confidence score (e.g., 95% confidence), and qualitative fidelity levels can be classified into grades or intervals such as “high,” “medium,” and “low.” This fidelity level can be determined by considering various environmental and technical factors such as the situation in which the data was generated, the distribution of training data of the algorithm used, the quality of the communication path, the accuracy of the sensor, and the latency factor, and can be used as a key judgment criterion for the terminal or network system to evaluate the reliability of the data or adjust the risk judgment criteria.

[0181] Hereinafter, a method / device capable of performing data analysis based on dynamic fidelity adjustment when data / information is collected from multiple data sources by a V2X infrastructure connected to various terminals (terminals included in a vehicle, VRU, RSU, and server) and efficiently analyzing / providing appropriate additional / assistant information (hereinafter, additional information) according to the situation is described in detail. Meanwhile, the V2X infrastructure may be a network, server, base station, or cloud capable of providing V2X services, and as described above, may estimate / determine the status of a UE / device based on data / information collected from multiple data sources by utilizing the configuration of a digital twin.

[0182] For example, in safety services related to conventional V2X-based collision risk prevention, metrics such as TTC are widely used as a means of assessing collision risk. Metrics such as TTC, which are calculated based on the distance between objects, can be derived under the assumption that accurate location and status information between objects are recognized. However, the accuracy / performance of sensors may differ among current V2X terminals, or they may not include the same communication modules (e.g., PC5 interface, Uu interface, Hybrid, etc.). In particular, VRU devices may not include V2X devices, or the performance of the sensors / communication modules included in VRU devices (e.g., smartphones, Aftermarket V2X Devices, etc.) may be relatively low, and they may often only include the function of long-range communication. In this respect, VRU devices may have limitations in that VRU status information (e.g., kernel, location information / sensor information, etc.) may be inaccurate compared to terminals or OBUs (On-Board Units) equipped with various sensors. To address these limitations, safety services for VRU devices need to be provided through the convergence of various data / information applications in the V2N environment. However, as described above, the fidelity, accuracy, and reliability levels of information / data collected from various terminals / devices in the V2X infrastructure may differ. For example, if the key information required for collision risk prediction for a terminal / device is missing, or even if the required key information is present, the accuracy is very low, or there is a time difference in the received information for each terminal, or if various types of objects (devices) are mixed, issues may arise where the fidelity / reliability levels of the data / information collected in collision risk analysis between terminals differ.

[0183] For example, the road environment is subject to numerous influencing factors and variables, and changes in the road environment can occur in real time due to interactions between various physical objects / devices / terminals / vehicles. TTC, which is primarily used in collision risk prediction, may have the following limitations, as described above. TTC can be calculated under the assumption that two objects / devices / terminals / vehicles maintain their current speed and path without changes in acceleration or deceleration. However, in actual traffic conditions, if a driver suddenly brakes or changes direction, risk prediction based on the pre-calculated TTC may become meaningless. In particular, interactions between multiple objects / devices / vehicles / terminals can occur in complex environments, and as the number of objects / devices / vehicles / terminals increases, TTC-based collision risk predictions may become inaccurate. In addition to interactions between dynamic objects / devices / vehicles / terminals, geographical characteristics can also increase the inaccuracy of TTC-based collision risk predictions. For example, TTC calculation may become complicated when an object / device / vehicle / terminal moves along a curved path rather than a straight path, such as a non-linear path. In this way, since TTC predicts the risk of collision based on the distance between objects / devices / vehicles / terminals, the accuracy and resolution of the sensor may directly affect the accuracy of TTC calculation. In particular, the TTC may be calculated based on status information received / transmitted through V2X messages, etc., rather than values ​​directly recognized / sensed and calculated by high-performance sensors of the terminal, such as radar / lidar. In this case, the reliability / accuracy of the risk assessment may be directly affected by the reliability / accuracy of the received status information.For example, if a vehicle terminal receives location / status information of a VRU approaching an alleyway through a V2X message, the vehicle terminal may receive inaccurate location / status information of the VRU due to an error in the GPS value of the VRU, and may calculate inaccurate TTC based on this, and the inaccuracy of the TTC may result in a collision between the vehicle and the VRU.

[0184] Risk prediction based on a single, established rule can be extremely risky. Therefore, a method may be needed to improve risk prediction accuracy by comprehensively considering the influencing factors described above and adjusting the data and depth of analysis appropriate to the situation.

[0185] FIG. 19, FIG. 20 and FIG. 21 are diagrams illustrating a method for a V2X infrastructure to provide additional analysis information to a terminal based on collected data.

[0186] The V2X infrastructure can determine / determine whether additional analysis is required for assessing the risk of collision for a terminal (e.g., a VRU device / V2X device) based on the collected data / information (e.g., device status / mobility information obtained from messages received from V2X devices, VRU devices, device status information obtained from RSUs, etc., sensing information obtained from sensors / cameras of the RSUs, etc.). In this regard, the V2X infrastructure can receive a request for the additional analysis from the terminal, or determine whether to generate additional analysis / additional information for analyzing / assessing the risk situation of the terminal based on a received message from the terminal.

[0187] Specifically, referring to FIG. 19, a terminal can generate V2X information (e.g., mobility information of the terminal) and perform basic safety services through its own analysis. The terminal directly performs basic analysis related to the safety service, but if it determines that additional analysis for the safety service is necessary, it can transmit a message requesting additional analysis to the V2X infrastructure. In this case, the terminal can independently identify and display the fidelity of the currently collected / generated data by transmitting a message including the currently collected / generated data (Optional). The V2X infrastructure can select information / data related to the terminal from among data collected from peripheral devices based on information included in the message of the terminal (e.g., mobility information / status information of the terminal, fidelity), and evaluate and classify the fidelity / reliability / accuracy of the selected information / data. The V2X infrastructure can adjust resource optimization and analysis level based on the required calculation / computation time calculated / predicted for the additional analysis by taking into account the current traffic situation of the terminal and data availability, etc. The V2X infrastructure can perform additional analysis according to an appropriately adjusted analysis level and provide additional analysis information (or, corrected information or additional information) to the terminal. For example, if there is sufficient calculation / computation time for the additional analysis, the V2X infrastructure can generate high-precision analysis information (analysis information based on high-precision simulation, high-fidelity surrogate model, AI / ML, etc.), and if there is not sufficient calculation / computation time for the additional analysis, it can generate low-precision analysis information (analysis information based on low-precision simulation, low-fidelity surrogate model). In this case, the V2X infrastructure can provide the terminal with a message that additionally indicates the fidelity or trust level information (e.g., fidelity flag) for the low-precision analysis information.The V2X infrastructure can transmit generated analysis information or additional information to the terminal and surrounding terminals. The terminal can perform safety-related responses / actions based on the received analysis / additional information, and, if necessary, adjust the sensitivity of the response / action based on the fidelity level of the additional information. For example, if additional information (e.g., low-precision analysis / additional information) with fidelity or confidence level information is received, the terminal can adjust the sensitivity of the response / action or parameters related to collision risk assessment.

[0188] Alternatively, the V2X infrastructure can determine whether additional analysis information (or, auxiliary information, additional information) is required based on the collected information. Here, the provision of additional analysis information may include provision of additional data, data reinforcement / correction / combination, additional analysis, provision of analysis information, provision of notifications / warnings, etc. In general road conditions, in the case of vehicle-to-vehicle collision risk, it may be helpful in terms of safety to directly calculate and respond at the terminal side rather than the V2X infrastructure. Therefore, by setting a trigger condition for inferring a situation requiring intervention of the V2X infrastructure, it can be flexibly operated so that whether or not to provide the additional analysis information is determined based on the trigger condition. However, as future technologies develop, the status information / mobility information of the terminal may be collected / linked in real time in the V2X infrastructure or a virtual environment. In this case, online analysis (e.g., analysis for providing additional analysis information) can be performed at all times regardless of whether the intervention of the V2X infrastructure is required. Here, the intervention of the V2X infrastructure can be possible in both cases where the terminal itself determines the necessity and requests it, as explained with reference to FIG. 19, or where the V2X infrastructure determines the necessity of generating / providing additional analysis information for evaluating the risk situation of the terminal based on the collected information / data, as illustrated in FIG. 20.

[0189] As illustrated in Figure 20, the V2X infrastructure can determine whether it is necessary to provide additional analysis information, such as for assessing the risk situation of the terminal, based on the collected information / data. In this case, the V2X infrastructure can consider the following conditions as trigger conditions for generating / providing the additional analysis information, or as criteria for increasing the priority.

[0190] - When mutual recognition between terminals is difficult due to the terminal's own sensor (e.g., the distance between terminals is not recognized) <threshold; 여기서, threshold는 상기 단말에 제공되는 서비스의 최소 안전 보장을 위한 주변 환경 인식 거리일 수 있음)

[0191] - When complex interactions occur between terminals (e.g., number of relevant objects / obstacles (which can be weighted in the case of VRU) > threshold number)

[0192] - When there is a large difference in the fidelity / trust level between data (e.g., fidelity gap > critical gap, or when the difference between the fidelity / trust level of the data of the terminal and the fidelity / trust level of the data of the peripheral device / terminal is greater than the critical gap)

[0193] - When the quality and / or fidelity of key information / parameters (for the terminal) is generally low (e.g., Confidence < critical quality; e.g., when the quality of key information / parameters of the terminal is below critical quality)

[0194] - When there is a mismatch in the synchronization between the received data / information for each terminal (e.g., Time gap > Critical time gap)

[0195] If the V2X infrastructure determines that additional analysis information is needed, an adaptive sampling or data filtering step may be required to classify the fidelity of the collected data / information and determine which information requires reinforcement / correction. Here, the first and / or second methods described below may be considered as methods for the V2X infrastructure to determine the fidelity of data received from a terminal.

[0196] The first method may be a method for analyzing / judging the fidelity of the data (or collected data) of the terminal using the confidence value of the data / parameter generated or detected / sensed by the terminal. The second method may be a method for the V2X infrastructure to analyze / judgment the fidelity of the data of the terminal or the collected data based on the type of device that generated the received data (e.g., the type of data source device). For example, as defined in Table 5, the V2X infrastructure may classify received / collected data including high-performance sensor information such as lidar and radar as high-fidelity data. Conversely, the V2X infrastructure may classify received / collected data including low-resolution sensor information such as smartphone GPS as low-fidelity data. Alternatively, the V2X infrastructure may be capable of making corrections for various causes (device defects / abnormalities, communication performance degradation sections, etc.) based on past data analysis (e.g., analysis of data / information previously received from the terminal). High-fidelity data generally has a large data volume, so V2X infrastructure can optimize resources by prioritizing low-fidelity data and collecting / receiving it over a wide area, while selectively and flexibly collecting / using high-fidelity data when needed. The collected data of various fidelity levels can be converted into a consistent format for analysis in the V2X infrastructure, and a preprocessing process to remove / correct noise can be performed in advance. Here, high-fidelity data generally provides high accuracy and reliability, and can refer to data used for high-precision applications such as autonomous driving systems and traffic safety-related services. Low-fidelity data can refer to data used for basic applications such as general navigation, basic object recognition, and lane keeping assistance, although relatively inaccurate, and have low collection and processing costs and little direct relevance to safety services.

[0197] High fidelity dataLow fidelity dataRaw dataHigh-performance device data - High-performance sensors (Lidar, radar, etc.) - High-resolution camera footage - Precision GPS data - HD MapV2X messages - High-performance device generation - High Accuracy / Confidence valuesLow-performance device data - Low-performance sensors - Low-resolution camera footage - General GPS data (e.g. smartphones, etc.) - General maps - Legacy data (e.g. detectors, etc.)V2X messages - Low-performance device generation (e.g. AVD, etc.) - Low Accuracy / Confidence values ​​- VRU's Path prediction Information processing / analysis dataHigh fidelity simulation dataPrecision AI / ML analysis / prediction dataVirtual environment linked analysis data (e.g. digital twin, etc.)Low fidelity simulation dataSimple statistical model / formula calculationSync correction value (simple interpolation)

[0198] Meanwhile, although two fidelity levels are arbitrarily classified in Table 5, they may be classified into more detailed fidelity levels. For example, by defining the basic fidelity level or trust level for V2X-related devices in detail, the transmitting terminal can transmit information about the fidelity level or trust level by including it in the V2X message, or the receiving terminal / V2X infrastructure can determine / determine the fidelity level or trust level of the data / information included in the V2X message based on the type of the transmitting terminal. In addition, the fidelity level or trust level may be dynamically adjusted according to the current status of the transmitting terminal, surrounding traffic conditions, etc. In addition, when information / data is collected / generated from various devices within an individual terminal, data elements with different fidelities may be included even within the data of one terminal. Accordingly, the transmitting terminal may transmit a V2X message including data / information in which fidelity is indicated for each data / information (e.g., parameter, data element (DE), etc.).

[0199] Furthermore, a method for predicting / analyzing collision risks appropriate to the adjusted / determined analysis level may be required. Here, prediction / analysis can encompass various levels of analysis / prediction, such as high-precision and low-precision traffic simulations (macro / micro) and AI / ML analysis, in addition to simple parameter calculations. The aforementioned multi-fidelity surrogate model can be a method for combining / integrating data from multiple sources of varying fidelity to create a more accurate and efficient prediction model. First, the timing / point in time when additional analysis information for the terminal is required may need to be determined / determined. Analysis can be performed by optimizing resources according to the situation, taking multiple factors into account. For example, a pedestrian may emerge from an alley without the vehicle and pedestrian recognizing each other. In this case, the vehicle can surrogately calculate TTC information with the pedestrian and provide it to the pedestrian's device. Warning information should be provided so that the TTC is longer than the response time. In general, it may be more advantageous for the V2X infrastructure to provide pedestrian location information to the vehicle's terminal to enable the vehicle's terminal to determine a hazardous situation, rather than calculating the TTC for the terminal / device on behalf of the terminal / device. However, due to the nature of the alley, the GPS information of the pedestrian's terminal (e.g., smartphone) may be inaccurate, and situations may arise where the vehicle fails to recognize the VRU. Therefore, the V2X infrastructure can provide additional analysis information for each situation, taking into account the calculation time (urgency) calculated in the two steps, as follows.

[0200] For example, the calculation / operation time can be calculated considering the currently available data level for processing / analyzing the information required at the terminal or receiving terminal and the response time of the terminal. For example, the V2X infrastructure can calculate the calculation / operation time of safety-related information based on parameters such as relative distance between objects, relative speed, TTC related to collision risk, etc., and determine the level of precision for data analysis (e.g., additional analysis information) based on the calculated calculation time. For example, the V2X infrastructure can determine the level of accuracy / fidelity of the additional information by comparing the time required for processing / analyzing the additional information and the TTC calculated for the terminal. For example, the V2X infrastructure may determine whether to generate / process the additional information using a low-fidelity surrogate model or a high-fidelity surrogate model based on whether the TTC for the terminal is greater than or equal to a threshold time (wherein the threshold time is preset based on the time required for each fidelity level).

[0201] (1) Low fidelity surrogate model

[0202] Generating additional analytical information using a low-fidelity surrogate model or low-fidelity model is necessary when the urgency (or risk of collision) is high (e.g., TTC <threshold)에 수행될 수 있다.

[0203] Here, the collision risk value is a value determined based on the time interval or urgency until the time at which the UE is predicted to collide with another object / device / UE, and may be set to a larger value as the time interval until the time at which the UE is predicted to collide with another object / device / UE becomes smaller, and may be set to a smaller value as the time interval until the time at which the UE is predicted to collide with another object / device / UE becomes smaller. Alternatively, the collision risk value may be expressed as a numerical value for the accident risk of the UE. Alternatively, the collision risk value may be determined based on the TTC. For example, when the TTC is less than a specific time threshold / a specific threshold, the collision risk value may be determined to be a value lower than a specific value (e.g., 0.5), and when the TTC is greater than or equal to the specific time threshold / a specific threshold, the collision risk value may be determined to be a value higher than a specific value (e.g., 0.5).

[0204] V2X infrastructure reduces collision risk to terminals (e.g., TTC) <threshold 인 경우)이 있는 것으로 판단한 경우, V2X 인프라는 우선적으로 상기 단말의 존재 및 위치 인지를 위한 단순 상태 정보 (충돌 위험이 있는 객체 / 장치의 위치, 상기 단말의 위치, 충돌 위성에 대한 경고 정보 등)를 주변 단말 또는 상기 단말에게 포워딩 (forwarding)하거나, 상기 단말과 관련된 데이터 / 정보를 저-충실도 모델에 입력하여 저-충실도 모델로부터 출력된 결과인 추가 정보 (또는, 추가 분석 정보)를 상기 단말 및 / 또는 주변 단말에게 제공할 수 있다. 이 때, V2X 인프라는 상기 추가 정보와 함께 불확실성 (예컨대, Fidelity level이 낮다고 표시)에 대한 표시 정보 / 지시 정보를 포함하는 메시지를 상기 단말에게 전송 / 전달할 수 있다. 이 경우, 정확도 높은 충돌 위험에 대한 계산 시간 여유가 없을 경우에도 상기 추가 정보를 포함하는 메시지를 수신한 단말은 상기 추가 정보에 기반하여 더 주의 깊은 주행을 하거나 비상 대응을 할 준비를 할 수 있다. 예컨대, 상기 단말은 상기 메시지에 포함된 충실도 레벨에 기반하여 서비스 (경고 / 알림 등) 동작의 민감도 (Sensitivity)를 조정 / 조절할 수 있다. 예컨대, VRU가 차량에게 센싱되지 않는 골목길에 존재하나, 빌딩 숲으로 인해 VRU의 위치 정확도가 매우 부정확할 경우나, 충실도가 낮음에 대한 지시 정보를 포함하는 상기 추가 정보가 수신된 경우, 단말은 기존 정의된 위험 알림을 위한 임계 값을 보다 보수적으로 변경할 수 있다. 예컨대, 단말은 기존에 충돌 위험을 경고하기 위한 제1 임계 거리를 상기 제1 임계 거리보다 더 긴 제2 임계 거리로 변경할 수 있다.

[0205] (2) High fidelity surrogate model

[0206] The V2X infrastructure may generate additional information based on a high-fidelity surrogate model or a high-fidelity model when the urgency (or collision risk value) for the terminal is low (e.g., TTC>threshold).

[0207] The V2X infrastructure may perform an operation to improve the quality of the additional information when it is determined that there is sufficient time to evaluate / calculate the collision risk for the terminal after forwarding the received status information of the terminal to the surrounding devices (e.g., TTC>threshold). For example, the V2X infrastructure may perform an operation to improve the quality of the additional information, such as a position and path prediction value of the terminal corrected based on accumulated past data (e.g., empirical data), such as the past path history of the terminal (e.g., VRU) and / or information on the movement history in the area / section where the terminal is located, or (additionally) perform high-precision simulation and AI / ML analysis, etc. to provide the terminal and / or surrounding terminals with improved accuracy comprehensive risk information that reflects the correlation with the surrounding environment. Here, the V2X infrastructure needs to provide the additional information by taking sufficient time for the terminal to respond into consideration.

[0208] Alternatively, a surrogate model can be built that flexibly and complementarily combines / fuses high-fidelity data and low-fidelity data according to the situation. Various methodologies can be used to build such combined / integrated models, such as hierarchical Kriging, proper orthogonal decomposition, LSTM, and Bayesian models, depending on the main problem to be solved in the current traffic situation. The output value of the low-fidelity model can be classified / generated into low-precision simulation information, simple correction / analysis information that can be processed in a very short time, etc. based on information (raw data) generated / collected through devices / V2X messages, etc. For example, the low-fidelity model can be a pre-trained model that outputs / generates the above-mentioned additional information through AI / ML analysis based on simple input information, such as information / data (raw data) included in devices / V2X messages, low-precision simulation information, and simple correction / analysis information that can be processed in a very short time. The output value of the high-fidelity model may be a model trained to classify / generate AI / ML analysis information, etc. by reflecting high-precision simulation information and correlations with surrounding objects. For example, the high-fidelity model may be a model trained in advance to generate / output the above-mentioned additional information through AI / ML analysis that reflects not only information / data (raw data) included in the device / V2X message, but also high-precision simulation information and information on correlations with surrounding objects.

[0209] In this way, the V2X infrastructure can determine the appropriate level of analysis / accuracy of the additional information for each situation based on the level of data fidelity and the urgency of the current traffic situation. The risk information can be expressed in various ways, such as TTC or other metric values ​​for each target object corrected with a more precise path prediction value. Alternatively, the risk information can be provided by replacing it with a probability value between 0 and 1 in a form that is easy to include in a V2X message. In addition, the risk information can be classified into the current integrated risk of the overall terminal and the individual risk between each individual surrounding terminal. In this case, the V2X infrastructure can transmit a message that includes the fidelity level of the analysis result together with the risk information (or information on the risk prediction value). The risk information calculated using the multi-fidelity surrogate model can be defined as in the following mathematical equation 1. Here, the correlation function (p(x)) can have a particularly important influence when the relationship between the two models is nonlinear, and can be a function learned based on a Gaussian process or an artificial neural network, etc. Through this, the V2X infrastructure can train the low-fidelity model or the multi-fidelity surrogate model to output a prediction value of the low-fidelity model that is close to the prediction value of the high-fidelity model.

[0210] [Mathematical Formula 1]

[0211]

[0212] Here, R(x) may be the final collision risk prediction value, f_low(x) may be the prediction value of the low-fidelity model, f_high(x) may be the prediction value of the high-fidelity model, and ρ(x) may be a scaling function for the correlation between the low-fidelity model and the high-fidelity model.

[0213] Meanwhile, in calculating the collision risk using mathematical expression 1, etc., the V2X infrastructure may need to make an appropriate level of correction and / or weight adjustment by considering the characteristics of the analysis section (or road environment or surrounding environment) or the types of related objects (e.g., types of objects for which collision risk is determined). This is because there is a large difference in the general driving speed and performance level of the terminal depending on the road type (highway, general road, alley, etc.), terminal type, surrounding traffic environment, etc.

[0214] In terms of information utilization, the V2X infrastructure can establish a risk response guideline by classifying information provision (e.g., classifying the type of information provided by risk level) / intervention authority of the V2X infrastructure by risk level based on the analyzed risk prediction value (e.g., probability value between 0 and 1). For example, if the analyzed / calculated risk prediction value is higher than a first specific threshold value, the V2X infrastructure can provide a message including content related to providing a warning to the terminal (e.g., additional data) to the corresponding terminal. If the analyzed / calculated risk prediction value is higher than a second specific threshold value (a second specific threshold value greater than the first specific threshold value), the V2X infrastructure can transmit a message including guidance information recommending / requesting a path change to the corresponding terminal / device, as illustrated in FIG. 21. If the analyzed / calculated risk prediction value is higher than a third specific threshold value (a third specific threshold value greater than the second specific threshold value), the V2X infrastructure may transmit a request message to the terminal / device requesting authorization to participate in the driving of the terminal / device. In this way, the information provided may be different or various response guidelines may be defined depending on the risk level according to the calculated risk prediction value. And / or, in addition to the above-described information provision aspect, the risk prediction value may be considered in determining the criteria for safety services, or may be used in determining / setting reference parameters such as whether to intervene in the infrastructure of autonomous vehicles, ODD (Object Detection and Distance) judgment, and the trust level for future technology services such as cooperative driving / control. The V2X infrastructure may provide the terminal / device with information on the response guidelines for each detailed threshold value described above, or may apply the response guidelines for each detailed threshold value described above according to the sensitivity level set by the terminal itself.

[0215] (3) Providing risk and guidance information in complex interrelationship situations.

[0216] The V2X infrastructure can analyze prediction information of a terminal / device on its behalf and provide it to the terminal / device. For example, the V2X infrastructure can analyze the comprehensive collision risk of the terminal / device in a road situation / surrounding environment where complex interactions occur, and provide the analyzed risk information and information on path prediction values ​​calculated for each of all terminals / devices connected to the V2X infrastructure to the terminal / device in order to reduce the overall collision risk. For example, as illustrated in FIG. 21, in a traffic situation where terminals / devices included in multiple vehicles form complex interrelationships, the V2X infrastructure can analyze / produce individual collision risk information of each of the multiple terminals / devices and comprehensive risk information in the traffic situation. At this time, the risk information can be expressed not only as TTC information, but also as a probability value between 0 and 1 estimated based on modeling / analysis, etc. Meanwhile, if the subject terminal / device drives (or the V2X infrastructure controls the driving of the subject terminal / device) to increase the distance from the object (or device / terminal) with the highest risk, the risk with respect to other objects may change conversely. At this time, the V2X infrastructure can share a path prediction value (or path prediction guide value) that changes for each terminal / device, thereby notifying surrounding terminals / devices in advance of information about changes in the speed or trajectory of the terminal / device, and can help select an optimal route to reduce the risk between each terminal / device. For example, if the risk of collision between terminal / device 1 and terminal / device 2 is the highest and terminal / device 1 decelerates (or if the risk of collision between terminal / device 1 and terminal / device 2 is the highest and the V2X infrastructure instructs terminal / device 1 to decelerate), terminal / device 3, which was driving behind terminal / device 1, may also need to decelerate.In this case, the V2X infrastructure can share in advance with the terminal / device 1 the path prediction / planning information and the future path information of the terminal / device 3. By sharing such information, the V2X infrastructure can effectively reduce the risk of collision through cooperation between multiple terminals / devices. Here, the path information or infrastructure guidance message information (or risk information, future path, path prediction / planning information) recommending risk and change may be provided by utilizing a new protocol / message (and / or an existing standardized message), a combination of existing standard messages, a combination of new messages, or a combination of an existing standard message and a new message. For example, the path information or infrastructure guidance message information may be included in the path prediction field of the terminal's existing status message (e.g., Basic Safety Message (BSM), Cooperative Awareness Message (CAM), Personal Safety Message (PSM), VRU Awareness Message (VAM)), may be included in the extended field of the terminal's existing status message (e.g., BSM, CAM, PSM, VAM), may be transmitted individually, or may be transmitted in aggregate via sensor messages (e.g., Sensor Data Sharing Message (SDSM), Collective Perception Message (CPM)). The path information or infrastructure guidance message information may also be used as information for recommendation or negotiation regarding a maneuver using maneuver-related messages (e.g., Maneuver Coordination Message (MCM), Maneuver Sharing and Coordination Message (MCSM)). Alternatively, the path information or infrastructure guidance message information may be provided via a separate new message analyzed and generated by the V2X infrastructure on its behalf.

[0217] The V2X infrastructure can monitor the post-results and evaluate the performance of the low-fidelity model and / or high-fidelity model described above through historical data, or, if necessary, continuously improve the low-fidelity model and / or high-fidelity model using active learning techniques.

[0218] Meanwhile, the above-described methods are described from the perspective of V2X infrastructure, assuming that sufficient processing power can be secured using a low-fidelity model and / or a high-fidelity model. However, as technology advances in the future, if sufficient processing power for processing and analysis is secured in local terminals such as RSUs and general terminals, it is natural that the above-described methods can be applied to the RSUs, general terminals, local terminals, etc. In addition, at least one or more of the above-described methods can be combined. For example, a device that combines two or more of the above-described methods can be implemented.

[0219] FIG. 22 is a diagram illustrating a method for a network to provide auxiliary data to a UE for collision risk assessment.

[0220] The network may relay a message received from the UE to peripheral terminals associated with the UE (or peripheral terminals for which a subscription topic that subscribes to the publication topic of the message is set). In addition, the network may determine whether to provide the auxiliary data related to collision risk assessment / evaluation of the UE based on the status information of the UE included in the message of the UE and / or the collected information collected from the peripheral terminals (and / or RSU) as described above. When the network determines that the provision of auxiliary data to the UE is necessary, the network may generate the auxiliary data using a low-fidelity model (hereinafter, the first model) and / or a high-fidelity model (hereinafter, the second model) as described above. As described above, the auxiliary data may include information related to collision risk assessment of the UE, such as information correcting the status information of the UE and a collision risk assessment value.

[0221] Here, the auxiliary data may be generated using at least one of the models as described above. For example, the network may input the status information of the UE and the collection information into the first model to obtain auxiliary data for risk assessment of the UE from the first model. Here, the first model may be trained to analyze / correct mobility information such as speed, location, and direction of the UE included in the status information based on the collection information and the status information (for example, to analyze / correct with a focus on mobility information of the UE itself without reflecting correlations with surrounding devices), and may output the analyzed / corrected mobility information for the UE as the auxiliary data. And / or, the network may input the status information of the UE and the collection information into the second model to obtain auxiliary data for risk assessment of the UE from the second model. Here, the second model can be trained to analyze / correct mobility information such as speed, location, and direction of the UE included in the status information based on the collected information and the status information, and even analyze the risk of collision through high-precision simulation that considers correlations with surrounding devices / objects. The network can generate the auxiliary data by using the second model, which is analysis / evaluation information on the risk of collision through high-precision simulation that considers the analyzed / corrected mobility information of the UE and the correlations with surrounding devices / objects. In this way, the second model can output auxiliary data with a higher fidelity level (e.g., a second fidelity level) than the first model that only corrects / analyzes the attributes / mobility information of the UE itself without considering correlations with surrounding devices, etc., in that it outputs comprehensive analysis / judgment results according to the correlations with various surrounding objects and high-precision simulation.Meanwhile, the first model can output auxiliary data at a lower fidelity level (e.g., the first fidelity level) than the auxiliary data of the second model. However, the second model may require a relatively longer computation / analysis time than the first model because it must also reflect surrounding correlations, etc., whereas the first model can output the auxiliary data in a considerably shorter time.

[0222] Specifically, referring to FIG. 22, the network may receive a first message including status information of a UE (user equipment) (S221). Here, the status information of the UE may include mobility information of the UE, surrounding sensing information acquired from a sensor of the UE, etc. The first message may be a message based on the MQTT message protocol as described above, and may include a publication topic of the UE. In this case, the network may relay / transmit the first message to adjacent / peripheral terminals / devices that have set a subscription topic corresponding to the publication topic. In addition, the network may collect information / data related to the UE through messages from the surrounding terminals / devices and / or data transmitted from infrastructure equipment such as RSUs. The messages from the surrounding terminals / devices and / or data transmitted from infrastructure equipment such as RSUs may include mobility information of the surrounding terminals / devices, sensor information on the surrounding environment / peripheral objects acquired through sensors, etc.

[0223] Next, the network may determine whether to generate auxiliary data based on the collected information related to the UE and the status information of the UE (S223). For example, the network may estimate / determine the sensing distance of the UE, the fidelity level of the status information of the UE (e.g., based on the sensor type of the UE that acquired the status information and the device type of the UE as defined in Table 5), and the number of peripheral terminals / objects / devices located around the UE based on the status information / collected information of the UE included in the first message as described above. At this time, if the sensing distance of the UE is less than a specific threshold distance, the fidelity level of the status information of the UE is less than a specific threshold level, or the number of peripheral devices related to the UE is greater than or equal to a specific threshold number, the network may determine that generation of auxiliary data for the UE is necessary and may generate the auxiliary data. Alternatively, the first message may include request information requesting generation of the auxiliary data, and the network may determine generation of the auxiliary data based on the request information.

[0224] At this time, the network can generate the auxiliary data using the first model and / or the second model as described above. Specifically, the network can calculate the collision risk value (e.g., TTC value) of the UE based on the status information / collected information (or, the collision risk value / TTC information of the UE can be included in the status information of the UE). In this case, the network can determine / select a model for generating the auxiliary data from among the first model and the second model based on the collision risk value (e.g., TTC value) of the UE. As described above, when the collision risk value is above / above a specific threshold (or, the TTC value is below / below a specific time threshold), the network can generate the auxiliary data of the first fidelity level using the first model. Conversely, when the collision risk value is below / below a specific threshold (or, the TTC value is above / above a specific time threshold), the network can generate the auxiliary data using the second model. Here, a specific threshold can be determined / set based on the time required for operation / processing in the first model and the time required for operation / processing in the second model.

[0225] Next, the network may transmit a second message including the auxiliary data to the UE when the auxiliary data is generated (S225). At this time, the network may determine whether to additionally include fidelity level information for the auxiliary data in the second message based on a collision risk value of the UE (e.g., a TTC value). For example, if the collision risk value is above / above a specific threshold (or the TTC value is below / below a specific time threshold), the network may additionally include a fidelity level (e.g., a first fidelity level) of the auxiliary data included in the second message. Conversely, if the collision risk value is below / below a specific threshold (or the TTC value is above / above a specific time threshold), the network may not include information about a fidelity level (e.g., a second fidelity level) of the auxiliary data included in the second message. This may be to inform the UE that the sensitivity of the collision risk assessment based on the auxiliary data included in the second message needs to be adjusted, since the accuracy of the auxiliary data generated / obtained through the first model may be significantly lower than that of the auxiliary data generated / obtained through the second model when the collision risk value is above / above a specific threshold (or the TTC value is below / below a specific time threshold). Alternatively, as described above, the second message may further include guidance information for guiding a change in the UE's movement path / movement speed, etc.

[0226] Figure 23 is a diagram illustrating a method for a UE to receive auxiliary data for determining collision risk.

[0227] A UE can provide its status information to a network via a Uu interface. Based on the MQTT message protocol, the UE can set a publication topic for its message, and the message can be delivered to peripheral devices / terminals of the UE based on the publication topic. In addition, the UE can receive messages containing status information about peripheral devices / terminals from the network. In this case, the UE can determine / assess the risk of collision with other objects while driving based on its own status information (and / or sensing information) and the status information / sensing information about the peripheral devices / terminals (and / or objects). In addition, as described above, the UE can additionally receive auxiliary information from the network to improve the accuracy of the collision risk determination / assessment. In this case, the UE can determine / assess the collision risk based on the auxiliary information as well as the status information / sensing information.

[0228] Referring to FIG. 23, a UE may transmit a first message including its own status information (e.g., mobility information, device type information, sensing information, etc.) (S231). The first message may be a message based on the MQTT message protocol as described above and may include a topic published by the UE. Meanwhile, the UE may also obtain / collect status information of surrounding devices / terminals from other devices / terminals in the network.

[0229] Next, the UE may receive a second message including the auxiliary data from the network (S233). Here, the auxiliary data may be data directly analyzed / corrected / generated by the network to support the UE in relation to the collision risk assessment of the UE as described above. For example, as described above, if the UE requests the generation of the auxiliary data through the first message, or even without a separate request, whether to generate / transmit the auxiliary data may be determined based on the first message. At this time, whether to additionally provide information on the fidelity level of the auxiliary data may be determined based on the collision risk value of the UE (e.g., TTC value) through the second message. For example, if the collision risk value exceeds / is above a specific threshold (or, the TTC value is below / is below a specific time threshold), the UE may additionally receive information on the fidelity level (e.g., first fidelity level) of the auxiliary data through the second message. Alternatively, if the collision risk value is below / below a specific threshold (or the TTC value is above / exceeds a specific time threshold), the fidelity level information of the auxiliary data may not be provided through the second message. Alternatively, the second message may further include guidance information that guides the UE's driving speed, driving direction, etc.

[0230] Next, the UE may assess the risk of collision based on at least one of the auxiliary data (and / or the guidance information), the status information of the UE, and the status information of the peripheral devices / terminals (S235). At this time, the UE may adjust the sensitivity (or reference value) related to the collision risk assessment if information on the fidelity level is additionally provided through the second message. For example, the UE may assess the risk of collision with other objects / devices using a more conservative criterion in the assessment of the risk of collision based on the auxiliary information, etc. For example, the UE may lower the speed reference value related to the collision risk assessment than the existing value, or raise the safety distance threshold value related to the collision risk assessment than the existing value.

[0231] In this way, the proposed invention can effectively improve the risk response capabilities of a terminal that lacks location measurement capabilities and sensing capabilities by having the network directly generate / provide auxiliary data for risk status analysis. Alternatively, the proposed invention can adaptively adjust the fidelity level of the auxiliary data based on the collision risk value (e.g., TTC value) calculated for the terminal, thereby providing the auxiliary data at a time appropriate to the terminal's situation. Alternatively, the proposed invention can provide additional fidelity level information when the fidelity of the auxiliary data is low, thereby providing an opportunity to effectively respond to errors in the terminal's collision risk assessment that may arise due to the auxiliary data.

[0232] Examples of communication systems to which the invention applies

[0233] Although not limited thereto, the various descriptions, functions, procedures, proposals, methods and / or operational flowcharts of the present invention disclosed in this document may be applied to various fields requiring wireless communication / connection (e.g., 5G) between devices.

[0234] Hereinafter, more specific examples will be provided with reference to the drawings. In the drawings / descriptions below, the same drawing reference numerals may represent identical or corresponding hardware blocks, software blocks, or functional blocks, unless otherwise described.

[0235] Figure 24 illustrates a communication system applied to the present invention.

[0236] Referring to FIG. 24, a communication system (1) applied to the present invention includes a wireless device, a base station, and a network. Here, the wireless device refers to a device that performs communication using a wireless access technology (e.g., 5G NR (New RAT), LTE (Long Term Evolution)) and may be referred to as a communication / wireless / 5G device. Although not limited thereto, the wireless device may include a robot (100a), a vehicle (100b-1, 100b-2), an XR (eXtended Reality) device (100c), a hand-held device (100d), a home appliance (100e), an IoT (Internet of Things) device (100f), and an AI device / server (400). 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 vehicle may include an Unmanned Aerial Vehicle (UAV) (e.g., a drone). XR devices include AR (Augmented Reality) / VR (Virtual Reality) / MR (Mixed Reality) devices, and can be implemented in the form of HMD (Head-Mounted Device), HUD (Head-Up Display) installed in a vehicle, television, smartphone, computer, wearable device, home appliance, digital signage, vehicle, robot, etc. Mobile devices can include smartphone, smart pad, wearable device (e.g., smart watch, smart glass), computer (e.g., laptop, etc.), etc. Home appliances can include TV, refrigerator, washing machine, etc. IoT devices can include sensors, smart meters, etc. For example, base stations and networks can also be implemented as wireless devices, and a specific wireless device (200a) can act as a base station / network node to other wireless devices.

[0237] Wireless devices (100a to 100f) can be connected to a network (300) via a base station (200). Artificial Intelligence (AI) technology can be applied to the wireless devices (100a to 100f), and the wireless devices (100a to 100f) can be connected to an AI server (400) via the network (300). The network (300) can be configured using a 3G network, a 4G (e.g., LTE) network, a 5G (e.g., NR) network, etc. The wireless devices (100a to 100f) can communicate with each other via the base station (200) / network (300), but can also communicate directly (e.g., sidelink communication) without going through the base station / network. For example, vehicles (100b-1, 100b-2) can communicate directly (e.g., V2V (Vehicle to Vehicle) / V2X (Vehicle to Everything) communication). In addition, IoT devices (e.g., sensors) can communicate directly with other IoT devices (e.g., sensors) or other wireless devices (100a to 100f).

[0238] Wireless communication / connection (150a, 150b, 150c) can be established between wireless devices (100a~100f) / base stations (200), and base stations (200) / base stations (200). Here, wireless communication / connection can be achieved through various wireless access technologies (e.g., 5G NR) such as uplink / downlink communication (150a), sidelink communication (150b) (or D2D communication), and communication between base stations (150c) (e.g., relay, IAB (Integrated Access Backhaul). Through wireless communication / connection (150a, 150b, 150c), wireless devices and base stations / wireless devices, and base stations and base stations can transmit / receive wireless signals to each other. For example, wireless communication / connection (150a, 150b, 150c) can transmit / receive signals through various physical channels. To this end, at least some of various configuration information setting processes for transmitting / receiving wireless signals, various signal processing processes (e.g., channel encoding / decoding, modulation / demodulation, resource mapping / demapping, etc.), and resource allocation processes can be performed based on various proposals of the present invention.

[0239] Examples of wireless devices to which the present invention is applied

[0240] Figure 25 illustrates a wireless device applicable to the present invention.

[0241] Referring to FIG. 25, the first wireless device (100) and the second wireless device (200) can transmit and receive wireless signals through various wireless access technologies (e.g., LTE, NR). Here, {the first wireless device (100), the second wireless device (200)} can correspond to {the wireless device (100x), the base station (200)} and / or {the wireless device (100x), the wireless device (100x)} of FIG. 24.

[0242] A first wireless device (100) includes one or more processors (102) and one or more memories (104), and may further include one or more transceivers (106) and / or one or more antennas (108). The processor (102) controls the memories (104) and / or the transceivers (106), and may be configured to implement the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. For example, the processor (102) may process information in the memory (104) to generate first information / signal, and then transmit a wireless signal including the first information / signal via the transceiver (106). In addition, the processor (102) may receive a wireless signal including second information / signal via the transceiver (106), and then store information obtained from signal processing of the second information / signal in the memory (104). The memory (104) may be connected to the processor (102) and may store various information related to the operation of the processor (102). For example, the memory (104) may perform some or all of the processes controlled by the processor (102), or may store software code including commands for performing the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. Here, the processor (102) and the memory (104) may be part of a communication modem / circuit / chipset designed to implement wireless communication technology (e.g., LTE, NR). The transceiver (106) may be connected to the processor (102) and may transmit and / or receive wireless signals via one or more antennas (108). The transceiver (106) may include a transmitter and / or a receiver. The transceiver (106) may be used interchangeably with an RF (Radio Frequency) unit. In the present invention, a wireless device may also mean a communication modem / circuit / chipset.

[0243] A first wireless device or network (100) may include a processor (102), a memory (104), and a transceiver (106). The memory (104) may include at least one program capable of performing operations related to the embodiments described in FIGS. 18 to 23. The operations include receiving a first message including status information of a user equipment (UE); determining whether to generate auxiliary data based on collected information related to the UE and the status information of the UE; and transmitting a second message including the auxiliary data to the UE based on the generated auxiliary data, wherein the second message may further include fidelity level information for the auxiliary data, based on a collision risk value (e.g., a TTC value) of the UE.

[0244] Alternatively, a processing device may be configured, including at least one processor (102) for controlling a network and a memory (104). In this case, the processing device may include at least one processor; and at least one memory coupled to the at least one processor and storing instructions that perform operations when executed by the at least one processor. The operations include receiving a first message including status information of a user equipment (UE); determining whether to generate auxiliary data based on collected information related to the UE and the status information of the UE; and transmitting a second message including the auxiliary data to the UE based on the generated auxiliary data, wherein the second message may further include fidelity level information for the auxiliary data, based on a collision risk value (e.g., a TTC value) of the UE. In addition, at least one non-transitory computer-readable medium including instructions for performing the operations may be configured.

[0245] The second wireless device (200) includes one or more processors (202), one or more memories (204), and may further include one or more transceivers (206) and / or one or more antennas (208). The processor (202) controls the memories (204) and / or the transceivers (206), and may be configured to implement the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. For example, the processor (202) may process information in the memory (204) to generate third information / signals, and then transmit a wireless signal including the third information / signals via the transceivers (206). In addition, the processor (202) may receive a wireless signal including fourth information / signals via the transceivers (206), and then store information obtained from signal processing of the fourth information / signals in the memory (204). The memory (204) may be connected to the processor (202) and may store various information related to the operation of the processor (202). For example, the memory (204) may perform some or all of the processes controlled by the processor (202), or may store software code including commands for performing the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. Here, the processor (202) and the memory (204) may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). The transceiver (206) may be connected to the processor (202) and may transmit and / or receive wireless signals via one or more antennas (208). The transceiver (206) may include a transmitter and / or a receiver. The transceiver (206) may be used interchangeably with an RF unit. In the present invention, a wireless device may also mean a communication modem / circuit / chip.

[0246] A second wireless device or UE / device (200) may include a transceiver (206), a processor (202), and a memory (204). The memory (204) may include at least one program capable of performing operations related to the embodiments described in FIGS. 18 to 23. The operations may include transmitting a first message including status information of the UE to a network, receiving a second message from the network including auxiliary data generated based on collected information related to the UE and the status information of the UE, and evaluating a collision risk based on the auxiliary data. Here, whether to adjust the assessment sensitivity of the collision risk may be determined based on whether the second message includes fidelity level information of the auxiliary data.

[0247] Hereinafter, the hardware elements of the wireless device (100, 200) will be described in more detail. Although not limited thereto, one or more protocol layers may be implemented by one or more processors (102, 202). For example, one or more processors (102, 202) may implement one or more layers (e.g., functional layers such as PHY, MAC, RLC, PDCP, RRC, SDAP). One or more processors (102, 202) 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 operation flowcharts disclosed in this document. One or more processors (102, 202) may generate messages, control information, data, or information according to the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. One or more processors (102, 202) can generate signals (e.g., baseband signals) including PDUs, SDUs, messages, control information, data or information according to the functions, procedures, proposals and / or methods disclosed herein, and provide the signals to one or more transceivers (106, 206). One or more processors (102, 202) can receive signals (e.g., baseband signals) from one or more transceivers (106, 206) and obtain PDUs, SDUs, messages, control information, data or information according to the descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed herein.

[0248] One or more processors (102, 202) may be referred to as a controller, a microcontroller, a microprocessor, or a microcomputer. One or more processors (102, 202) may be implemented by hardware, firmware, software, or a combination thereof. For example, one or more Application Specific Integrated Circuits (ASICs), one or more Digital Signal Processors (DSPs), one or more Digital Signal Processing Devices (DSPDs), one or more Programmable Logic Devices (PLDs), or one or more Field Programmable Gate Arrays (FPGAs) may be included in one or more processors (102, 202). The descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document may be implemented using firmware or software, and the firmware or software may be implemented to include modules, procedures, functions, etc. The descriptions, functions, procedures, suggestions, methods and / or operation flowcharts disclosed in this document may be implemented using firmware or software configured to perform one or more processors (102, 202) or stored in one or more memories (104, 204) and executed by one or more processors (102, 202). The descriptions, functions, procedures, suggestions, methods and / or operation flowcharts disclosed in this document may be implemented using firmware or software in the form of codes, instructions and / or sets of instructions.

[0249] One or more memories (104, 204) may be coupled to one or more processors (102, 202) and may store various forms of data, signals, messages, information, programs, codes, instructions, and / or commands. The one or more memories (104, 204) may be configured as ROM, RAM, EPROM, flash memory, hard drives, registers, cache memory, computer-readable storage media, and / or combinations thereof. The one or more memories (104, 204) may be located internally and / or externally to the one or more processors (102, 202). Additionally, the one or more memories (104, 204) may be coupled to the one or more processors (102, 202) via various technologies, such as wired or wireless connections.

[0250] One or more transceivers (106, 206) can transmit user data, control information, wireless signals / channels, etc., as mentioned in the methods and / or flowcharts of this document, to one or more other devices. One or more transceivers (106, 206) can receive user data, control information, wireless signals / channels, etc., as mentioned in the descriptions, functions, procedures, proposals, methods and / or flowcharts of this document, from one or more other devices. For example, one or more transceivers (106, 206) can be connected to one or more processors (102, 202) and can transmit and receive wireless signals. For example, one or more processors (102, 202) can control one or more transceivers (106, 206) to transmit user data, control information, or wireless signals to one or more other devices. Additionally, one or more processors (102, 202) may control one or more transceivers (106, 206) to receive user data, control information, or wireless signals from one or more other devices. Additionally, one or more transceivers (106, 206) may be coupled to one or more antennas (108, 208), and one or more transceivers (106, 206) may be configured to transmit and receive user data, control information, wireless signals / channels, or the like, as referred to in the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed herein, via one or more antennas (108, 208). In this document, one or more antennas may be multiple physical antennas or multiple logical antennas (e.g., antenna ports). One or more transceivers (106, 206) can convert received user data, control information, wireless signals / channels, etc. from RF band signals to baseband signals in order to process the received user data, control information, wireless signals / channels, etc. using one or more processors (102, 202).One or more transceivers (106, 206) may convert user data, control information, wireless signals / channels, etc. processed by one or more processors (102, 202) from baseband signals to RF band signals. For this purpose, one or more transceivers (106, 206) may include an (analog) oscillator and / or filter.

[0251] Examples of wireless devices to which the present invention is applied

[0252] Figure 26 illustrates another example of a wireless device applicable to the present invention. The wireless device may be implemented in various forms depending on the use case / service (see Figure 24).

[0253] Referring to FIG. 26, the wireless device (100, 200) corresponds to the wireless device (100, 200) of FIG. 25 and may be composed of various elements, components, units / units, and / or modules. For example, the wireless device (100, 200) may include a communication unit (110), a control unit (120), a memory unit (130), and additional elements (140). The communication unit may include a communication circuit (112) and a transceiver(s) (114). For example, the communication circuit (112) may include one or more processors (102, 202) and / or one or more memories (104, 204) of FIG. 26. For example, the transceiver(s) (114) may include one or more transceivers (106, 206) and / or one or more antennas (108, 208) of FIG. 25. The control unit (120) is electrically connected to the communication unit (110), the memory unit (130), and the additional elements (140) and controls the overall operation of the wireless device. For example, the control unit (120) may control the electrical / mechanical operation of the wireless device based on the program / code / command / information stored in the memory unit (130). In addition, the control unit (120) may transmit information stored in the memory unit (130) to an external device (e.g., another communication device) via a wireless / wired interface through the communication unit (110), or store information received from an external device (e.g., another communication device) via a wireless / wired interface in the memory unit (130).

[0254] The additional element (140) may be configured in various ways depending on the type of the wireless device. For example, the additional element (140) may include at least one of a power unit / battery, an input / output unit (I / O unit), a driving unit, and a computing unit. Although not limited thereto, the wireless device may be implemented in the form of a robot (Fig. 24, 100a), a vehicle (Fig. 24, 100b-1, 100b-2), an XR device (Fig. 24, 100c), a portable device (Fig. 24, 100d), a home appliance (Fig. 24, 100e), an IoT device (Fig. 24, 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. 24, 400), a base station (Fig. 24, 200), a network node, etc. Wireless devices may be mobile or stationary depending on the use / service.

[0255] In FIG. 26, various elements, components, units / parts, and / or modules within the wireless device (100, 200) may be entirely interconnected via a wired interface, or at least some may be wirelessly connected via a communication unit (110). For example, within the wireless device (100, 200), the control unit (120) and the communication unit (110) may be wired, and the control unit (120) and a first unit (e.g., 130, 140) may be wirelessly connected via the communication unit (110). In addition, each element, component, unit / part, and / or module within the wireless device (100, 200) may further include one or more elements. For example, the control unit (120) may be composed of a set of one or more processors. For example, the control unit (120) may be composed of a set of a communication control processor, an application processor, an electronic control unit (ECU), a graphics processing processor, a memory control processor, etc. As another example, the memory unit (130) may be composed of RAM (Random Access Memory), DRAM (Dynamic RAM), ROM (Read Only Memory), flash memory, volatile memory, non-volatile memory, and / or a combination thereof.

[0256] Examples of vehicles or autonomous vehicles to which the present invention is applied

[0257] Figure 27 illustrates a vehicle or autonomous vehicle applicable to the present invention. The vehicle or autonomous vehicle may be implemented as a mobile robot, car, train, manned / unmanned aerial vehicle (AV), ship, etc.

[0258] Referring to FIG. 27, a vehicle or autonomous vehicle (100) may include an antenna unit (108), a communication unit (110), a control unit (120), a driving unit (140a), a power supply unit (140b), a sensor unit (140c), and an autonomous driving unit (140d). The antenna unit (108) may be configured as a part of the communication unit (110). Blocks 110 / 130 / 140a to 140d correspond to blocks 110 / 130 / 140 of FIG. 26, respectively.

[0259] The communication unit (110) can transmit and receive signals (e.g., data, control signals, etc.) with external devices such as other vehicles, base stations (e.g., base stations, road side units, etc.), and servers. The control unit (120) can control elements of the vehicle or autonomous vehicle (100) to perform various operations. The control unit (120) can include an ECU (Electronic Control Unit). The drive unit (140a) can drive the vehicle or autonomous vehicle (100) on the ground. The drive unit (140a) can include an engine, a motor, a power train, wheels, brakes, a steering device, etc. The power supply unit (140b) supplies power to the vehicle or autonomous vehicle (100) and can include a wired / wireless charging circuit, a battery, etc. The sensor unit (140c) can obtain vehicle status, surrounding environment information, user information, etc. The sensor unit (140c) may include an IMU (inertial measurement unit) sensor, a collision sensor, a wheel sensor, a speed sensor, an incline sensor, a weight detection sensor, a heading sensor, a position module, a vehicle forward / backward sensor, a battery sensor, a fuel sensor, a tire sensor, a steering sensor, a temperature sensor, a humidity sensor, an ultrasonic sensor, an illuminance sensor, a pedal position sensor, etc. The autonomous driving unit (140d) may implement a technology for maintaining a driving lane, a technology for automatically controlling speed such as adaptive cruise control, a technology for automatically driving along a set path, a technology for automatically setting a path and driving when a destination is set, etc.

[0260] For example, the communication unit (110) can receive map data, traffic information data, etc. from an external server. The autonomous driving unit (140d) can generate an autonomous driving route and driving plan based on the acquired data. The control unit (120) can control the drive unit (140a) so that the vehicle or autonomous vehicle (100) moves along the autonomous driving route according to the driving plan (e.g., speed / direction control). During autonomous driving, the communication unit (110) can irregularly / periodically acquire the latest traffic information data from an external server and can acquire surrounding traffic information data from surrounding vehicles. In addition, during autonomous driving, the sensor unit (140c) can acquire vehicle status and surrounding environment information. The autonomous driving unit (140d) can update the autonomous driving route and driving plan based on newly acquired data / information. The communication unit (110) can transmit information regarding the vehicle location, autonomous driving route, driving plan, etc. to the external server. External servers can predict traffic information data in advance using AI technology or other technologies based on information collected from vehicles or autonomous vehicles, and provide the predicted traffic information data to the vehicles or autonomous vehicles.

[0261] The wireless communication technology implemented in the wireless device (XXX, YYY) of this specification may include LTE, NR, and 6G, as well as Narrowband Internet of Things for low-power communication. 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 this specification may perform communication based on LTE-M technology. For example, LTE-M technology may be an example of LPWAN technology, and may be called by various names such as eMTC (enhanced Machine Type Communication). For example, LTE-M technology can be implemented by at least one of various standards such as 1) LTE CAT 0, 2) LTE Cat M1, 3) LTE Cat M2, 4) LTE non-BL (non-Bandwidth Limited), 5) LTE-MTC, 6) LTE Machine Type Communication, and / or 7) LTE M, and is not limited to the above-described names. Additionally or alternatively, the wireless communication technology implemented in the wireless device (XXX, YYY) of the present specification can include at least one of ZigBee, Bluetooth, and Low Power Wide Area Network (LPWAN) considering low-power communication, and is not limited to the above-described names. For example, ZigBee technology can create 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.

[0262] The embodiments described above are combinations of components and features of the present invention in a predetermined form. Each component or feature should be considered optional unless explicitly stated otherwise. Each component or feature may be implemented without being combined with other components or features. Furthermore, it is also possible to form an embodiment of the present invention by combining some components and / or features. The order of operations described in the embodiments of the present invention may be changed. Some components or features of one embodiment may be included in another embodiment or may be replaced with corresponding components or features of another embodiment. It is self-evident that claims that do not have an explicit citation relationship in the patent claims may be combined to form an embodiment or may be incorporated as a new claim through a post-application amendment.

[0263] In this document, embodiments of the present invention have been described primarily focusing on the signal transmission and reception relationship between a terminal and a base station. This transmission and reception relationship is equally / similarly extended to signal transmission and reception between a terminal and a relay or a base station and a relay. Certain operations described as being performed by a base station in this document may, in some cases, be performed by its upper node. That is, it is obvious that various operations performed for communication with a terminal in a network composed of multiple network nodes including a base station may be performed by the base station or other network nodes other than the base station. The base station may be replaced by terms such as fixed station, Node B, eNode B (eNB), and access point. In addition, the terminal may be replaced by terms such as UE (User Equipment), MS (Mobile Station), MSS (Mobile Subscriber Station).

[0264] Embodiments of the present invention may be implemented by various means, for example, hardware, firmware, software, or a combination thereof. In the case of hardware implementation, an embodiment of the present invention may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, etc.

[0265] When implemented via firmware or software, an embodiment of the present invention may be implemented in the form of modules, procedures, functions, etc. that perform the functions or operations described above. The software code may be stored in a memory unit and executed by a processor. The memory unit may be located within or outside the processor and may exchange data with the processor via various known means.

[0266] It will be apparent to those skilled in the art that the present invention can be embodied in other specific forms without departing from the scope of the invention. Therefore, the above detailed description should not be construed as limiting in any respect, but rather as illustrative. The scope of the present invention should be determined by a reasonable interpretation of the appended claims, and all modifications within the scope of equivalents of the present invention are intended to be included within the scope of the present invention.

[0267] The embodiments of the present invention as described above can be applied to various mobile communication systems.

Claims

1. In the network method, A step of receiving a first message including status information of a UE (user equipment); A step of determining whether to generate auxiliary data to support collision risk assessment of the UE based on the collected information related to the UE and the status information of the UE; and A step of transmitting a second message including the auxiliary data to the UE based on the auxiliary data being generated, A method wherein the network determines whether to additionally include fidelity level information for the auxiliary data in the second message based on the collision risk value of the UE.

2. In paragraph 1, A method wherein the second message includes fidelity level information for the auxiliary data only when the collision risk value of the UE is above a certain threshold.

3. In paragraph 1, A method wherein the network inputs the collected information and the state information into a first model to generate the auxiliary data at a first fidelity level, or inputs the collected information and the state information into a second model to generate the auxiliary data at a second fidelity level higher than the first fidelity level.

4. In paragraph 3, A method wherein the network generates the auxiliary data using the first model based on the collision risk value of the UE being greater than or equal to a specific threshold, and generates the auxiliary data using the second model based on the collision risk value of the UE being less than or equal to the specific threshold.

5. In paragraph 1, A method wherein the above fidelity level information is included in the second message to adjust the sensitivity in determining the collision risk of the UE based on the auxiliary data.

6. In paragraph 1, A method wherein the auxiliary data is generated based on whether the sensing distance of the UE is less than a specific threshold distance, the number of peripheral devices associated with the UE is greater than or equal to a specific threshold number, or the fidelity level of the status information of the UE is less than a specific threshold level.

7. In paragraph 6, A method in which the fidelity level of the status information of the UE is determined based on at least one of the sensor type that acquired the status information and the device type of the UE.

8. In paragraph 1, A method wherein the second message further includes guidance information for changing at least one of the moving direction and moving speed of the UE.

9. In paragraph 1, A method in which the above-mentioned collection information is obtained based on a plurality of messages received from a plurality of devices located around the UE.

10. In paragraph 1, A method wherein the collision risk value of the above UE is determined based on time-to-collision (TTC).

11. In at least one non-transitory computer-readable medium, Contains instructions that perform operations when executed by at least one processor, The above actions are, Receive a first message containing status information of UE (user equipment); Determining whether to generate auxiliary data to support collision risk assessment of the UE based on the collected information related to the UE and the status information of the UE; and Based on the auxiliary data being generated, transmitting a second message including the auxiliary data to the UE, At least one non-transitory computer-readable medium recording medium, wherein the second message determines whether to additionally include fidelity level information for the auxiliary data based on a collision risk value of the UE.

12. In the network, RF (Radio Frequency) transmitter and receiver; and A processor connected to the RF transceiver, The processor controls the RF transceiver to receive a first message including status information of a UE (user equipment), determines whether to generate auxiliary data to support collision risk assessment of the UE based on collected information related to the UE and status information of the UE, and transmits a second message including the auxiliary data to the UE based on the auxiliary data being generated. The second message is a network in which it is determined whether to additionally include fidelity level information for the auxiliary data based on the collision risk value of the UE.

13. In a processing device that controls a network, at least one processor; and At least one memory connected to said at least one processor and storing instructions that perform operations when executed by said at least one processor, The above actions are, Receive a first message containing status information of UE (user equipment); Determining whether to generate auxiliary data to support collision risk assessment of the UE based on the collected information related to the UE and the status information of the UE; and Based on the auxiliary data being generated, transmitting a second message including the auxiliary data to the UE, A processing device in which the second message determines whether to additionally include fidelity level information for the auxiliary data based on the collision risk value of the UE.

14. In the method by UE (user equipment), A step of transmitting a first message including status information of the UE to the network; A step of receiving a second message from the network including auxiliary data generated based on collected information related to the UE and status information of the UE; and Including a step of evaluating the risk of collision based on the above auxiliary data, A method in which the UE determines whether to adjust the assessment sensitivity of the collision risk based on whether the second message includes fidelity level information of the auxiliary data.

15. In UE (user equipment), RF (Radio Frequency) transmitter and receiver; and A processor connected to the RF transceiver, The processor controls the RF transceiver to transmit a first message including status information of the UE to the network, receives a second message including auxiliary data generated based on collected information related to the UE and the status information of the UE from the network, and evaluates the risk of collision based on the auxiliary data. A UE wherein the processor determines whether to adjust the assessment sensitivity of the collision risk based on whether the second message includes fidelity level information of the auxiliary data.

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