Method and device for performing communication in wireless communication system

Abstract

Provided are a method by which a first device performs wireless communication and a device supporting same. The method may comprise the steps in which: the first device acquires sensing data; the first device acquires accuracy related to the sensing data; and the first device reports the sensing data and the accuracy related to the sensing data.

Description

Method and device for performing communication in a wireless communication system

[0001] The present disclosure relates to a wireless communication system.

[0002] 5G NR, the successor to LTE (long-term evolution), is a new clean-slate mobile communications system characterized by 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.

[0003] The 6G (wireless communication) system aims to achieve (i) very high data rates per device, (ii) a very large number of connected devices, (iii) global connectivity, (iv) very low latency, (v) low energy consumption for battery-free Internet of Things (IoT) devices, (vi) ultra-reliable connectivity, and (vii) connected intelligence with machine learning capabilities. The vision of the 6G system can be divided into four aspects: intelligent connectivity, deep connectivity, holographic connectivity, and ubiquitous connectivity, and the 6G system can satisfy the requirements as shown in Table 1 below. For example, Table 1 can represent an example of the requirements of a 6G system.

[0004] Maximum data rate per device: 1 Tbps, E2E latency: 1 ms, Maximum spectral efficiency: 100 bps / Hz, Mobility support: Up to 1000 km / hr, Satellite integration: Fully AI, Fully autonomous driving, Fully XR, Fully haptic communication

[0005] According to one embodiment of the present disclosure, a method may be provided. For example, the method may include: a first device obtaining sensing data; a first device obtaining an accuracy associated with the sensing data; and a first device reporting the sensing data and the accuracy associated with the sensing data.

[0006] According to one embodiment of the present disclosure, a first device may be provided. For example, the first device may include at least one transceiver; at least one processor; and at least one memory coupled to the at least one processor and storing instructions. For example, the instructions, based on execution by the at least one processor, may cause the first device to: acquire sensing data; acquire an accuracy associated with the sensing data; and report the sensing data and the accuracy associated with the sensing data.

[0007] According to one embodiment of the present disclosure, a processing device (configured to control a first device) may be provided. For example, the processing device may include at least one processor; and at least one memory coupled to the at least one processor and storing instructions. For example, the instructions, based on execution by the at least one processor, may cause the first device to: acquire sensing data; acquire an accuracy associated with the sensing data; and report the sensing data and the accuracy associated with the sensing data.

[0008] According to one embodiment of the present disclosure, a non-transitory computer-readable storage medium storing commands may be provided. For example, the commands, when executed, may cause a first device to: acquire sensing data; acquire accuracy associated with the sensing data; and report the sensing data and the accuracy associated with the sensing data.

[0009] According to one embodiment of the present disclosure, a method may be provided. For example, the method may include: a step of a second device receiving a plurality of sensing data; a step of the second device receiving a plurality of accuracies associated with the plurality of sensing data; and a step of the second device obtaining final sensing data based on the plurality of sensing data and the plurality of accuracies associated with the plurality of sensing data.

[0010] According to one embodiment of the present disclosure, a second device may be provided. For example, the second device may include at least one transceiver; at least one processor; and at least one memory coupled to the at least one processor and storing instructions. For example, the instructions, based on execution by the at least one processor, may cause the second device to: receive a plurality of sensing data; receive a plurality of accuracies associated with the plurality of sensing data; and obtain final sensing data based on the plurality of sensing data and the plurality of accuracies associated with the plurality of sensing data.

[0011] According to one embodiment of the present disclosure, a processing device (configured to control a second device) may be provided. For example, the processing device may include at least one processor; and at least one memory coupled to the at least one processor and storing instructions. For example, the instructions, based on execution by the at least one processor, may cause the second device to: receive a plurality of sensing data; receive a plurality of accuracies associated with the plurality of sensing data; and obtain final sensing data based on the plurality of sensing data and the plurality of accuracies associated with the plurality of sensing data.

[0012] According to one embodiment of the present disclosure, a non-transitory computer-readable storage medium having instructions recorded thereon may be provided. For example, the instructions, when executed, may cause a second device to: receive a plurality of sensing data; receive a plurality of accuracies associated with the plurality of sensing data; and obtain final sensing data based on the plurality of sensing data and the plurality of accuracies associated with the plurality of sensing data.

[0013] Figure 1 illustrates a device-to-device communication procedure according to one embodiment of the present disclosure.

[0014] FIG. 2 illustrates a radio protocol architecture according to one embodiment of the present disclosure.

[0015] FIG. 3 illustrates the structure of a wireless frame according to one embodiment of the present disclosure.

[0016] FIG. 4 illustrates a slot structure of a frame according to one embodiment of the present disclosure.

[0017] FIG. 5 illustrates an example of a BWP according to one embodiment of the present disclosure.

[0018] FIG. 6 illustrates a communication structure that can be provided in a 6G system according to one embodiment of the present disclosure.

[0019] FIG. 7 illustrates an example of a communication scenario based on a 6G system according to one embodiment of the present disclosure.

[0020] FIGS. 8A and 8B illustrate a non-terrestrial network scenario according to one embodiment of the present disclosure.

[0021] FIG. 9 illustrates an example of a sensing operation according to one embodiment of the present disclosure.

[0022] FIG. 10 illustrates the relationship between RCS, range (D), and power according to one embodiment of the present disclosure.

[0023] FIG. 11 illustrates an example of a protocol layer used to support transmission of an LTE positioning protocol (LPP) message between a location management function (LMF) and a UE according to an embodiment of the present disclosure.

[0024] FIG. 12 illustrates an example of an ISAC service according to one embodiment of the present disclosure.

[0025] FIG. 13 illustrates various integrated sensing and communication (ISAC) systems according to one embodiment of the present disclosure.

[0026] FIG. 14 is a diagram for comparing and explaining V2X communication based on RAT prior to NR and V2X communication based on NR according to one embodiment of the present disclosure.

[0027] FIG. 15 illustrates a procedure related to accuracy-based sensing data according to one embodiment of the present disclosure.

[0028] FIG. 16 illustrates a procedure related to accuracy-based sensing data according to one embodiment of the present disclosure.

[0029] FIG. 17 illustrates a procedure related to accuracy-based sensing data according to one embodiment of the present disclosure.

[0030] FIG. 18 illustrates a method for a first device to perform wireless communication according to one embodiment of the present disclosure.

[0031] FIG. 19 illustrates a method for a second device to perform wireless communication according to one embodiment of the present disclosure.

[0032] Fig. 20 illustrates a communication system (1) according to one embodiment of the present disclosure.

[0033] FIG. 21 illustrates a wireless device according to one embodiment of the present disclosure.

[0034] FIG. 22 illustrates a signal processing circuit for a transmission signal according to one embodiment of the present disclosure.

[0035] FIG. 23 illustrates a wireless device according to one embodiment of the present disclosure.

[0036] FIG. 24 illustrates a mobile device according to an embodiment of the present disclosure.

[0037] In this disclosure, "A or B" can mean "only A," "only B," or "both A and B." In other words, "A or B" in this disclosure can be interpreted as "A and / or B." For example, "A, B or C" in this disclosure can mean "only A," "only B," "only C," or "any combination of A, B and C."

[0038] As used herein, a slash ( / ) or a comma may mean "and / or." For example, "A / B" may mean "A and / or B." Accordingly, "A / B" may mean "only A," "only B," or "both A and B." For example, "A, B, C" may mean "A, B, or C."

[0039] In the present disclosure, “at least one of A and B” may mean “only A,” “only B,” or “both A and B.” Additionally, in the present disclosure, the expressions “at least one of A or B” or “at least one of A and / or B” may be interpreted identically to “at least one of A and B.”

[0040] Additionally, in the present disclosure, “at least one of A, B and C” can mean “only A,” “only B,” “only C,” or “any combination of A, B and C.” Additionally, “at least one of A, B or C” or “at least one of A, B and / or C” can mean “at least one of A, B and C.”

[0041] Additionally, parentheses used in the present disclosure may mean "for example." Specifically, when indicated as "control information (PDCCH)", "PDCCH" may be proposed as an example of "control information." In other words, "control information" in the present disclosure is not limited to "PDCCH," and "PDCCH" may be proposed as an example of "control information." Furthermore, even when indicated as "control information (e.g., PDCCH)", "PDCCH" may be proposed as an example of "control information."

[0042] In the following explanation, ‘when, if, in case of’ can be replaced with ‘based on’.

[0043] Technical features individually described in one drawing in this disclosure may be implemented individually or simultaneously.

[0044] In the present disclosure, higher layer parameters may be parameters set for the terminal, preset, or predefined. For example, a base station or network may transmit higher layer parameters to the terminal. For example, the higher layer parameters may be transmitted via radio resource control (RRC) signaling or medium access control (MAC) signaling.

[0045] In the present disclosure, "setting or defining" may be interpreted as being set or preset to a device through predefined signaling (e.g., SIB, MAC, RRC, DCI (downlink control information), etc.) from a base station or a network. In the present disclosure, "setting or defining" may be interpreted as being set or preset to a device through predefined signaling (e.g., MAC, RRC, SCI (sidelink control information), device-to-device signaling control information, etc.) from another device. In the present disclosure, "setting or defining" may be interpreted as being set or preset to a device.

[0046] In the present disclosure, a user equipment (UE) may refer to a device, a portable device, a wireless device, etc. In the present disclosure, a base station (BS) may refer to a radio access network (RAN) node, a non-terrestrial network (NTN) cell / node, a transmission reception point (TRP), a network, an integrated access and backhaul (IAB) node, a device, a portable device, a wireless device, etc.

[0047] The technology proposed in the present disclosure 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, E-UTRA (evolved UTRA), LTE (long term evolution), and 5G NR.

[0048] The technology proposed in this disclosure can be implemented with 6G wireless technology and applied to various 6G systems. For example, 6G systems can have key factors such as enhanced mobile broadband (eMBB), ultra-reliable low latency communications (URLLC), massive machine-type communication (mMTC), artificial intelligence (AI) integrated communication, tactile internet, high throughput, high network capacity, high energy efficiency, low backhaul and access network congestion, and enhanced data security.

[0049] FIG. 1 illustrates a device-to-device communication procedure according to one embodiment of the present disclosure. The embodiment of FIG. 1 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0050] Referring to FIG. 1, in step S101, a first device and a second device can perform synchronization. For example, the first device can be a terminal and / or at least one of the devices proposed in the present disclosure. For example, the second device can be a base station, a network, a RAN node, an NTN node / cell, a TRP, a terminal and / or at least one of the devices proposed in the present disclosure. For example, the first device can perform an initial cell search operation. For example, the first device can detect at least one synchronization signal transmitted by the second device according to a predefined rule. Here, for example, the synchronization signal can include a plurality of synchronization signals classified according to a structure or purpose (e.g., a primary synchronization signal, a secondary synchronization signal, etc.). Through this, the first device can identify the boundaries of the frame, subframe, time unit, slot, and / or symbol of the second device, and the first device can obtain information about the second device (e.g., a cell identifier).

[0051] In step S103, the first device can obtain system information transmitted by the second device. For example, the system information may include information related to the properties, characteristics, and / or capabilities of the second device required to connect to the second device and use the service. For example, the system information may be classified according to content (e.g., whether it is essential for connection), transmission structure (e.g., the channel used, whether it is provided on-demand), etc. For example, the system information may be classified into a master information block (MIB) and a system information block (SIB). For example, if necessary, the first device may transmit a signal requesting system information before receiving the system information. For example, the request and provision of system information may be performed after a random access procedure described below.

[0052] In step S105, the first device and the second device can perform a random access procedure. For example, the first device can transmit and / or receive at least one message (e.g., a random access preamble, a random access response message, etc.) for the random access procedure based on information related to a random access channel of the second device obtained through system information (e.g., channel location, channel structure, structure of supported preamble, etc.). For example, the first device can transmit a preamble (e.g., Msg1) through the random access channel, the first device can receive a random access response message (e.g., Msg2), the first device can transmit a message (e.g., Msg3) including information related to the first device (e.g., identification information) to the second device using scheduling information included in the random access response message, and the first device can receive a message (e.g., Msg4) for contention resolution and / or connection establishment. For example, Msg1 and Msg3 can be sent and received as one message (e.g., MsgA), and / or Msg2 and Msg4 can be sent and received as one message (e.g., MsgB).

[0053] In step S107, the first device and the second device may perform signaling of control information. Here, for example, the control information may be defined in various layers, such as a layer that controls a connection (e.g., a radio resource control (RRC) layer), a layer that handles mapping between logical channels and transport channels (e.g., a media access control (MAC) layer), a layer that handles physical channels (e.g., a physical (PHY) layer), etc. For example, the first device and the second device may perform at least one of signaling for establishing a connection, signaling for determining settings related to communication, and / or signaling for indicating allocated resources. For example, the control information may be signaled / transmitted via a control channel. For example, the control information and / or the control channel may be used to schedule at least one of data, a data channel (e.g., a shared channel), and / or control information on the data channel.

[0054] In step S109, the first device and the second device may transmit and / or receive data. For example, the first device and the second device may process, transmit, and / or receive data based on signaling of control information. For example, when transmitting data, the first device or the second device may perform at least one of channel encoding, rate matching, scrambling, constellation mapping, layer mapping, waveform modulation, antenna mapping, and / or resource mapping on the information bits. For example, when receiving data, the first device or the second device may perform at least one of signal extraction from resources, waveform demodulation for each antenna, signal arrangement considering layer mapping, constellation demapping, descrambling, and / or channel decoding.

[0055] For example, the layers of a radio interface protocol between a first device and a second device can be divided into L1 (layer 1), L2 (layer 2), L3 (layer 3), etc. For example, a physical layer belonging to the first layer can provide an information transfer service using a physical channel, and an RRC (radio resource control) layer located in the third layer can play a role in controlling radio resources between the first device and the second device. For this purpose, for example, the RRC layer can exchange RRC messages between the first device and the second device.

[0056] FIG. 2 illustrates a radio protocol architecture according to an embodiment of the present disclosure. The embodiment of FIG. 2 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted. For example, (a) of FIG. 2 may illustrate a radio protocol stack of a user plane for uplink communication or downlink communication, and (b) of FIG. 2 may illustrate a radio protocol stack of a control plane for uplink communication or downlink communication. For example, (c) of FIG. 2 may illustrate a radio protocol stack of a user plane for device-to-device communication, and (d) of FIG. 2 may illustrate a radio protocol stack of a control plane for device-to-device communication.

[0057] For example, the physical layer can provide information transmission services to upper layers using physical channels. For example, the physical layer can be connected to the upper layer, the medium access control (MAC) layer, through a transport channel. For example, data can be transmitted between the MAC layer and the physical layer through the transport channel. For example, transport channels can be classified according to how and with what characteristics data is transmitted over the wireless interface. For example, data can be transmitted between different physical layers, for example, between the physical layers of a first device and a second device, through a physical channel. For example, the physical channel can be modulated using an orthogonal frequency division multiplexing (OFDM) scheme, and time and frequency can be utilized as radio resources.

[0058] For example, the MAC layer can provide services to the upper layer, the radio link control (RLC) layer, through logical channels. For example, the MAC layer can provide a mapping function from multiple logical channels to multiple transport channels. For example, the MAC layer can provide a logical channel multiplexing function by mapping multiple logical channels to a single transport channel. For example, the MAC sublayer can provide data transmission services on logical channels.

[0059] For example, the RLC layer can perform concatenation, segmentation, and reassembly of RLC service data units (SDUs). For example, to guarantee the various quality of service (QoS) required by radio bearers (RBs), the RLC layer can provide three operating modes: transparent mode (TM), unacknowledged mode (UM), and acknowledged mode (AM). For example, AM RLC can provide error correction through automatic repeat request (ARQ).

[0060] For example, the RRC (radio resource control) layer can be defined only in the control plane. For example, the RRC layer can be responsible for controlling logical channels, transport channels, and physical channels in relation to the configuration, re-configuration, and release of radio bearers. For example, an RB can mean a logical path provided by a first layer (e.g., a physical layer) and a second layer (e.g., a MAC layer, an RLC layer, a PDCP (packet data convergence protocol) layer, a SDAP (service data adaptation protocol) layer, etc.) for data transmission between a first device and a second device.

[0061] For example, the functions of the PDCP layer in the user plane may include forwarding of user data, header compression, and ciphering. For example, the functions of the PDCP layer in the control plane may include forwarding of control plane data and ciphering / integrity protection.

[0062] For example, establishing an RB can refer to the process of defining the characteristics of the radio protocol layer and channel to provide a specific service, and setting specific parameters and operating methods for each. For example, RBs can be divided into two types: signaling radio bearers (SRBs) and data radio bearers (DRBs). For example, SRBs can be used as a channel to transmit RRC messages in the control plane, while DRBs can be used as a channel to transmit user data in the user plane.

[0063] For example, if an RRC connection is established between the RRC layer of the terminal and the RRC layer of the base station, the terminal will be in the RRC_CONNECTED state, and if not, it may be in the RRC_IDLE state. For example, in the case of NR, the RRC_INACTIVE state is additionally defined, and a terminal in the RRC_INACTIVE state can release the connection with the base station while maintaining the connection with the core network.

[0064] For example, a downlink transmission channel may include at least one of a broadcast channel (BCH) for transmitting system information, and / or a downlink shared channel (SCH) for transmitting user traffic or control messages. For example, traffic or control messages of a downlink multicast or broadcast service may be transmitted through the downlink SCH, or may be transmitted through a separate downlink multicast channel (MCH). Meanwhile, an uplink transmission channel may include at least one of a random access channel (RACH) for transmitting initial control messages, and / or an uplink shared channel (SCH) for transmitting user traffic or control messages. For example, a logical channel located above a transmission channel and mapped to the transmission channel may include at least one of a broadcast control channel (BCCH), a paging control channel (PCCH), a common control channel (CCCH), a multicast control channel (MCCH), and / or a multicast traffic channel (MTCH).

[0065] FIG. 3 illustrates the structure of a wireless frame according to an embodiment of the present disclosure. The embodiment of FIG. 3 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0066] Referring to FIG. 3, for example, a radio frame may be used in uplink transmission, downlink transmission, and / or device-to-device transmission. For example, a radio frame may have a length of 10 ms and may be defined as two 5 ms half-frames (HF). For example, a half-frame may include five 1 ms subframes (SF). For example, a subframe may be divided into one or more slots, and the number of slots within a subframe may be determined according to a subcarrier spacing (SCS). For example, each slot may include 12 or 14 OFDM (A) symbols, depending on a cyclic prefix (CP).

[0067] For example, when normal CP is used, each slot can contain 14 symbols. For example, when extended CP is used, each slot can contain 12 symbols. Here, for example, the symbols can contain OFDM symbols (or CP-OFDM symbols), SC-FDMA (single carrier-FDMA) symbols (or DFT-s-OFDM (Discrete Fourier Transform-spread-OFDM) symbols).

[0068] Table 2 below shows the number of symbols per slot (N) depending on the SCS setting (u) when normal CP or extended 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.

[0069] CP type SCS (15*2 u )N slot symb N frame,u slot N subframe,u slotNormal CP15kHz (u=0)1410130kHz (u=1)1420260kHz (u=2)14404120kHz (u=3)14808240kHz (u=4)1416016Extended CP60kHz (u=2)12404

[0070] For example, 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 time resources (e.g., subframes, slots, or transmit time intervals (TTIs)) composed of the same number of symbols may be set differently between the merged cells. For example, in the present disclosure, time resources such as subframes, slots, TTIs, etc. may be referred to as time units.

[0071] For example, multiple numerologies, or SCSs, may be supported to support various services. For example, a 15 kHz SCS may support wide areas in traditional cellular bands, while a 30 kHz / 60 kHz SCS may support dense urban areas, lower latency, and wider carrier bandwidth. For example, a 60 kHz or higher SCS may support bandwidths greater than 24.25 GHz to overcome phase noise.

[0072] FIG. 4 illustrates a slot structure of a frame according to an embodiment of the present disclosure. The embodiment of FIG. 4 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0073] Referring to FIG. 4, for example, a slot may include multiple symbols in the time domain. For example, a carrier may include multiple subcarriers in the frequency domain. For example, a resource block (RB) may be defined as multiple consecutive subcarriers in the frequency domain. For example, a bandwidth part (BWP) may be defined as multiple consecutive (P)RBs ((physical) resource blocks) in the frequency domain, and may correspond to one numerology (e.g., SCS, CP length, etc.). For example, a carrier may include at most N BWPs (where N is a positive integer). For example, data communication may be performed through an activated BWP. For example, each element may be referred to as a resource element (RE) in the resource grid, and one complex symbol may be mapped to it.

[0074] For example, a BWP may be a contiguous set of PRBs in a given numerology. For example, a PRB may be selected from a contiguous subset of common resource blocks (CRBs) for a given numerology on a given carrier.

[0075] For example, the BWP may be at least one of an active BWP, an initial BWP, and / or a default BWP. For example, the UE may not monitor the downlink radio link quality in a DL BWP other than the active DL BWP on the PCell (primary cell). For example, the UE may not receive a physical downlink control channel (PDCCH), a physical downlink shared channel (PDSCH), or a channel state information-reference signal (CSI-RS) (except for radio resource management (RRM)) outside of the active DL BWP. For example, the UE may not trigger channel state information (CSI) reporting for an inactive DL BWP. For example, the UE may not transmit a physical uplink control channel (PUCCH) or a physical uplink shared channel (PUSCH) outside of the active UL BWP. For example, for downlink, the initial BWP can be given as a set of consecutive resource blocks (RBs) for the remaining minimum system information (RMSI) CORESET (control resource set) (set by the physical broadcast channel (PBCH)). For uplink, for example, the initial BWP can be given by the system information block (SIB) for the random access procedure. For example, the default BWP can be set by a higher layer. For example, the initial value of the default BWP can be the initial DL BWP.For energy saving, if a terminal does not detect DCI (downlink control information) for a certain period of time, the terminal may switch its active BWP to a default BWP.

[0076] FIG. 5 illustrates an example of a BWP according to an embodiment of the present disclosure. The embodiment of FIG. 5 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted. In the embodiment of FIG. 5, it is assumed that there are three BWPs.

[0077] Referring to FIG. 5, for example, a common resource block (CRB) may be a carrier resource block numbered from one end of a carrier band to the other, and a PRB may be a numbered resource block within each BWP. For example, point A may indicate a common reference point for a resource block grid.

[0078] For example, BWP is point A, offset from point A (N start BWP ) and bandwidth (N size BWP ) can be set by. For example, point A can be an outer reference point of the PRB of a carrier where subcarrier 0 of all numerologies (e.g., all numerologies supported by the network on that carrier) aligns. 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.

[0079] 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 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0080] As core implementation technologies of the 6G system, technologies such as artificial intelligence (AI), THz (terahertz) communication, optical wireless technology, free-space optical transmission (FSO) backhaul networks, massive MIMO (multiple input multiple output) technology, blockchain, 3D networking, quantum communication, unmanned aerial vehicles, cell-free communication, wireless information and energy transfer (WIET), integration of sensing and communication, integration of access backhaul networks, holographic beamforming, big data analysis, and large intelligent surface (LIS) can be adopted.

[0081] - 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. For example, 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. AI can also 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.

[0082] - 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. Key characteristics of THz communications include (i) the widely available bandwidth to support very high data rates and (ii) the high path loss that occurs at high frequencies (requiring highly directional antennas). The narrow beamwidths generated by highly directional antennas reduce interference. The small wavelength of THz signals allows for a significantly larger number of antenna elements to be integrated into devices and base stations operating in this band. This enables the use of advanced adaptive array technologies to overcome range limitations.

[0083] - Large-scale MIMO technology

[0084] - Hologram beamforming (HBF)

[0085] - Optical wireless technology

[0086] - Free-space optical transmission backhaul network (FSO backhaul network)

[0087] - Quantum communication

[0088] - Cell-free communication

[0089] - Integration of wireless information and power transmission

[0090] - Integration of wireless communication and sensing

[0091] - Integrated access and backhaul network

[0092] - Big data analysis

[0093] - Reconfigurable intelligent surface

[0094] - metaverse

[0095] - Block chain

[0096] Advanced Air Mobility (AAM): AAM can be a broad concept encompassing urban air mobility (UAM), regional air mobility (RAM), and uncrewed aerial systems (UAS). For example, AAM can include UAM, RAM, UAS, and uncrewed aerial vehicles (UAVs).

[0097] - 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) wireless communication and vehicle to infrastructure (V2I) wireless communication.

[0098] Non-terrestrial network (NTN): NTN can refer to a network or network segment that utilizes radio frequency (RF) resources mounted on satellites (or UAS platforms). NTN services may be considered to secure wider coverage or provide wireless communication services in locations where the installation of wireless communication base stations is difficult.

[0099] - 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.

[0100] - Reconfigurable intelligent surface (RIS): RIS can be used to manipulate and enhance signal propagation in wireless communication environments. For example, a RIS can be composed of many small antennas, or metasurfaces, arranged on a surface, each of which can actively control the phase, amplitude, polarization, etc. of the reflected signal. For example, a RIS can improve signal reception by controlling the path, phase, and / or intensity of the propagating signal. For example, in the case of a RIS, power consumption can be very low because power is consumed only for controlling the phase and amplitude of the small antennas. For example, because a RIS can be reconfigured to suit different environments, it can meet various communication requirements and operate effectively in dynamic network environments.

[0101] FIG. 7 illustrates an example of a communication scenario based on a 6G system, according to an embodiment of the present disclosure. The embodiment of FIG. 7 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0102] Referring to FIG. 7, NTN communication can be performed based on satellite networks, high-altitude platform stations (HAPS) as international mobile telecommunications (IMT) base stations (BS), and terminals capable of aerial communication (e.g., AAMs). For example, to improve coverage, etc., devices such as satellite networks, HIBS, and terminals capable of aerial communication (e.g., AAMs) can act as relays. For example, an AAM can communicate with a base station, a satellite network, etc., and / or an AAM can communicate directly with a terminal, another AAM, etc.

[0103] Figures 8a and 8b illustrate a non-terrestrial network scenario according to an embodiment of the present disclosure. The embodiments of Figures 8a and 8b may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0104] Figure 8a illustrates a non-terrestrial network scenario based on a transparent payload, and Figure 8b illustrates a non-terrestrial network scenario based on a regenerative payload. For example, a non-terrestrial network may typically include the following elements:

[0105] - One or more satellite gateways connecting non-terrestrial networks to public data networks.

[0106] - Feeder link or wireless link between the satellite gateway and the satellite (or UAS platform).

[0107] - Service link or wireless link between user equipment and satellite (or UAS platform)

[0108] - A satellite (or UAS platform) capable of implementing transparent or regenerative (including onboard processing) payloads. For example, a satellite (or UAS platform) may generate multiple beams over a given service area, typically bounded by a field of view. For example, the beam footprint may be typically elliptical in shape. 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, for transparent payloads, radio frequency filtering, frequency conversion, and amplification may be performed. Therefore, the repetitive waveform signal in the payload may remain unchanged. For example, for regenerative payloads, radio frequency filtering, frequency conversion, and amplification, as well as demodulation / decoding, switching and / or routing, and coding / modulation may be performed. This may effectively be equivalent to onboarding all base station functions onto the satellite (or UAS platform).

[0109] - Optionally, inter-satellite link (ISL)

[0110] - User equipment can be serviced by satellites (or UAS platforms) within the target service area.

[0111] For example, a terminal can obtain information about the environment and / or the characteristics of objects within the environment by using radio frequency sensing to determine the instantaneous linear velocity, angle, distance (range), etc. of an object. Since 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., unmanned aerial vehicles, smart homes, V2X, factories, railways, public safety, etc.), enabling applications that provide, for example, intruder detection, assisted vehicle steering and navigation, trajectory tracking, collision avoidance, traffic management, health and traffic management, and more. In some cases, wireless sensing can use non-3GPP type sensors (e.g., radar, cameras) to additionally support 3GPP-based sensing. For example, the operation of wireless sensing services, e.g., sensing operations, may depend on the transmission, reflection, and scattering of wireless sensing signals. Therefore, wireless sensing offers an opportunity to enhance existing communication systems from a communications network to a wireless communication and sensing network.

[0112] FIG. 9 illustrates an example of a sensing operation according to an embodiment of the present disclosure. The embodiment of FIG. 9 can be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted. Specifically, (a) of FIG. 9 illustrates an example of sensing using a sensing receiver and a sensing transmitter located at the same location (e.g., monostatic sensing), and (b) of FIG. 9 illustrates an example of sensing using a separated sensing receiver and sensing transmitter (e.g., bistatic sensing).

[0113] Referring to FIG. 9, a sensing transmitter can transmit a sensing signal for sensing one or more objects (and / or an environment around the objects). For example, the sensing signal can be a radio (frequency) signal defined to be transmittable by a base station / terminal. For example, a sensing receiver can receive a signal scattered / reflected by one or more objects (and / or an environment around the objects) from a sensing signal transmitted from the sensing transmitter. For example, in the sensing receiver, sensing data can be derived from the scattered / reflected signal, and a sensing result can be generated / obtained through processing the sensing data. Here, for example, the sensing result can include characteristic information (e.g., position, distance, speed, angle, etc.) about one or more objects (and / or an environment around the objects). For example, the sensing results generated / obtained in this way may be utilized for wireless sensing services (e.g., detection, tracking, etc. of objects and / or environments) or provided / disclosed to a trusted third party.

[0114] For example, a sensing transmitter may be a base station or terminal that transmits a sensing signal to be used for a sensing service to operate, and the sensing transmitter may be located in the same or different base station or terminal as a sensing receiver. For example, a sensing receiver may be a base station or terminal that receives a sensing signal to be used for a sensing service to operate, and the sensing receiver may be located in the same or different base station or terminal as a sensing transmitter. For example, a sensing target may be an object to be detected by deriving characteristics of an object in the environment from a sensing signal. For example, a background environment may be a background that is not a sensing target (e.g., clutter, environmental objects, etc.). For example, an environment object may be an object whose location is known other than a sensing target. For example, monostatic sensing may be sensing in which a sensing transmitter and a sensing receiver coexist in the same base station or terminal. For example, bistatic sensing may be sensing in which the sensing transmitter and the sensing receiver are located in different base stations or terminals. For example, multistatic sensing may be sensing in which there are multiple sensing transmitters and / or multiple sensing receivers for a (single) sensing target. For example, monostatic sensing, bistatic sensing, and / or multistatic sensing may be distinguished based on the angle between the sensing transmitter, the sensing target, and the sensing receiver. For example, if the angle between the sensing transmitter, the sensing target, and the sensing receiver is less than or equal to a threshold, it may be defined as monostatic sensing or semi-monostatic sensing. For example, if the angle between the sensing transmitter, the sensing target, and the sensing receiver is greater than or equal to a threshold, it may be defined as bistatic sensing or multistatic sensing.For example, the terminal may transmit a sensing signal over a wireless interface that can be used for sensing purposes. For example, the terminal may transmit a sensing signal over a 3GPP wireless interface that can be used for sensing purposes.

[0115] For example, the common framework of the ISAC channel model can be composed of target channel components and background channel components. For example, this can be obtained based on mathematical equation 1.

[0116]

[0117] Here, for example, target channel H target may include all [multipath] components affected by the sensing target. For example, background channel H Background may contain other [multipath] components that do not belong to the target channel.

[0118] For example, radar cross-section (RCS) may be a measure of how well a radar sensor can detect a target. Therefore, it is often referred to as an electromagnetic characteristic of the target. For example, a larger RCS may indicate that the target is more easily detectable. For example, in a radar sensor measurement, power may be transmitted toward the target, and the target may reflect some of the power back to the receiver. For example, the received power may be based on the RCS of the target, among other factors. For example, the received power may be proportional to the RCS. For example, the RCS of a target may be based on at least one of the frequency of the radar signal, the target material, the target shape, the target size, the direction of the incident and reflected waves relative to the target, the target movement, and / or the target illumination.

[0119] FIG. 10 illustrates the relationship between RCS, range (D), and power according to one embodiment of the present disclosure. The embodiment of FIG. 10 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0120] Referring to Fig. 10, the RCS of a radar target may be a virtual area required to intercept the power density transmitted from the target. For example, the relevant radar mathematical formula may be defined as in Equation 2.

[0121]

[0122] Here, for example, P TX can be the transmitter power [W], and G TXcan be the gain of the transmitting antenna [dimensionless], D can be the distance between the equipment under test (EUT) and the target [m], and RCS can be the radar cross section [m 2 ] can be, P RX can be the power [W] received back by the EUT from the object, and A eff is the effective area of ​​the receiving antenna [m 2 ] can be. For example, A eff can be obtained based on mathematical formula 3.

[0123]

[0124] Here, for example, G RX can be the gain of the receiving antenna [dimensionless], λ can be the wavelength of the radio signal [m], λ = c / f, c can be the speed of light 299792458 [m / s], and f can be the frequency [Hz].

[0125] For example, if the transmitter and receiver are co-located and the same antenna is used for both transmission and reception (G TX = G RX = G), the related radar mathematical formula can be defined as in mathematical formula 4.

[0126]

[0127] Here, for example, P TX can be the transmitter power [W], G can be the gain of the transmitting antenna [dimensionless], D can be the distance between the equipment under test (EUT) and the target [m], and RCS can be the radar cross section [m 2 ] can be, P RX can be the power [W] received back by the EUT from the object.

[0128] FIG. 11 illustrates an example of a protocol layer used to support transmission of an LTE positioning protocol (LPP) message between a location management function (LMF) and a UE, according to an embodiment of the present disclosure. The embodiment of FIG. 11 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0129] LPP PDUs can be transmitted via non-access stratum (NAS) PDUs between an access and mobility management function (AMF) and a UE. Referring to FIG. 11, LPP can be terminated between a target device (e.g., a UE in the control plane or a secure user plane location (SUPL) enabled terminal (SET) in the user plane) and a location server (e.g., an LMF in the control plane or a secure user plane location (SUPL) location platform (SLP) in the user plane). LPP messages can be conveyed in the form of transparent PDUs over an intermediate network interface using a suitable protocol, such as NGAP (NG application protocol) over the NG-C (NG-control plane) interface, NAS / RRC over the LTE-Uu and NR-Uu interfaces. The LPP protocol enables positioning for NR and LTE using various positioning methods.

[0130] For example, a target device and a location server can exchange capability information, positioning assistance data, and / or location information via the LPP protocol. For example, LPP messages can be used to exchange error information and / or indicate the termination of an LPP procedure.

[0131] In the description below, various names are illustrative and can be considered to perform the same / similar function (regardless of their name) based on what is described in each step.

[0132] In this disclosure, the following terms may be used.

[0133] - LMF: Location Management Function

[0134] - UE-triggered SL positioning: SL (sidelink) positioning where the procedure is triggered by the UE.

[0135] - SL positioning triggered by base station / LMF: SL positioning where the procedure is triggered by base station / LMF.

[0136] - UE-controlled SL positioning: SL positioning where the SL positioning group is created by the UE.

[0137] - SL positioning controlled by the base station: SL positioning where the SL positioning group is generated by the base station.

[0138] - UE-based SL positioning: SL positioning where the UE location is calculated by the UE.

[0139] - UE-assisted SL positioning: SL positioning where the UE position is calculated by the base station / LMF.

[0140] - SL positioning group: UEs participating in SL positioning

[0141] - T-UE (Target UE): UE whose position is calculated

[0142] - S-UE (Server UE): UE that assists T-UE's positioning

[0143] - Anchor UE: A UE that assists T-UE's positioning

[0144] - MG: Measurement gap where only SL PRS transmission is allowed

[0145] - MW: Measurement window where both SL data and SL PRS can be transmitted in a multiplexed way

[0146] - SL PRS: Sidelink positioning reference signal

[0147] - CCH: Control Channel

[0148] - IUC (Inter-UE coordination) message: A message received by a TX UE from other UEs, including a RX UE, that includes information about a set of resources suitable for transmission by the TX UE to the RX UE (preferred resources) and / or information about a set of resources not suitable for transmission (non-preferred resources).

[0149] - UE-based: The way the UE calculates its own location is described as "UE-based".

[0150] - TP (Transmission point): A set of transmitting antennas (e.g., an antenna array (with one or more antenna elements)) geographically co-located for a cell, a portion of a cell, or a DL PRS-only TP. A transmission point may include a base station (ng-eNB or gNB) antenna, a remote radio head, a remote antenna of a base station, an antenna of a DL PRS-only TP, etc. A cell may include one or more transmission points. In a homogeneous deployment, each transmission point may correspond to one cell.

[0151] - Reception point (RP): A set of receiving antennas (e.g., an antenna array (with one or more antenna elements)) geographically co-located for a cell, a portion of a cell, or a UL SRS (sounding reference signal)-only RP. A reception point may include a base station (ng-eNB or gNB) antenna, a remote radio head, a remote antenna of a base station, an antenna of a UL SRS-only RP, etc. A cell may include one or more reception points. In a homogeneous deployment, each reception point may correspond to one cell.

[0152] - PRS-only TP: A TP that transmits only PRS signals for PRS-based terrestrial beacon system (TBS) positioning and is not connected to a cell.

[0153] - TRP (transmission-reception point): A set of geographically co-located antennas (e.g., an antenna array (with one or more antenna elements)) that support TP and / or RP functions.

[0154] - SRS-only RP: RP that receives only SRS signals for UL-only positioning and is not associated with a cell.

[0155] In the present disclosure, the TRP and the base station may be replaced and used as the same entity.

[0156] For example, an SL PRS transmission resource may be composed of an SL PRS resource set consisting of the following information:

[0157] - SL PRS resource set ID

[0158] - SL PRS Resource ID List: List of SL PRS resource IDs within the SL PRS resource set.

[0159] - SL PRS resource type: can be set to periodic or aperiodic or semi-persistent or on-demand

[0160] - Alpha for SL PRS power control

[0161] - P0 for SL PRS power control

[0162] - Path loss reference for SL PRS power control: Can be set to SL SSB or DL ​​PRS or UL SRS or UL SRS for positioning or PSCCH DMRS or PSSCH DMRS or PSFCH or SL CSI RS, etc.

[0163] For example, the above SL PRS resource set may be composed of SL PRS resources composed of the following information.

[0164] - SL PRS resource ID

[0165] - SL PRS comb size: Interval between REs where SL PRS is transmitted within a symbol

[0166] - SL PRS comb offset: RE index where SL PRS is first transmitted within the first SL PRS symbol.

[0167] - SL PRS comb cyclic shift: A cyclic shift used to generate the sequence that constitutes the SL PRS.

[0168] - SL PRS start position: The index of the first symbol transmitting SL PRS within a slot.

[0169] - Number of SL PRS symbols: The number of symbols that make up the SL PRS in one slot.

[0170] - Frequency domain shift: The lowest frequency position (index) at which the SL PRS is transmitted in the frequency domain.

[0171] - SL PRS BW: Frequency bandwidth used for SL PRS transmission

[0172] - SL PRS resource type: can be set to periodic or aperiodic or semi-persistent or on-demand

[0173] - SL PRS periodicity: the period in the time domain between SL PRS resources, a unit of physical or logical slot in the resource pool where SL PRS is transmitted.

[0174] - SL PRS Offset: The offset in the time domain from the start of the first SL PRS resource to the reference timing, in units of physical or logical slots in the resource pool where the SL PRS is transmitted. The reference timing may be SFN=0 or DFN=0, or the time of successful reception or decoding of RRC / MAC-CE / DCI / SCI associated with the SL PRS resource.

[0175] - SL PRS sequence ID

[0176] - SL PRS spatial relation: can be set to SL SSB or DL ​​PRS or UL SRS or UL SRS for positioning or PSCCH DMRS or PSSCH DMRS or PSFCH or SL CSI RS, etc.

[0177] - SL PRS CCH: SL PRS control channel. Can signal SL PRS resource configuration information and resource location, etc.

[0178] Previously, NR positioning up to Release 17 could only support network-based Uu positioning, which performed location search under the connection between the target UE and the network (gNB / LMF). Meanwhile, starting from NR Release 18, sidelink positioning (SL positioning) using sidelink communication can be supported. Sidelink positioning can be a new method that can perform positioning operations by exchanging positioning reference signals through a direct connection with anchor UEs around the target UE, rather than the base station. Positioning operations at the physical layer can be performed by transmitting and measuring SL PRS (sidelink positioning reference signal) between the target UE and the anchor UE.

[0179] Uu positioning can use the LPP protocol. An LPP session can be a point-to-point communication protocol between a target UE and an LMF. Through the LPP protocol, the target UE can receive positioning information from the LMF. The LMF can configure the target UE and the base station (gNB) through the LPP protocol and the NRPPa protocol, exchange positioning-related messages, and perform positioning operations. Meanwhile, in Release 18 sidelink positioning, positioning operations can be performed by exchanging sidelink positioning protocol messages with the target UE, server UE (or LMF), and anchor UEs. Sidelink positioning can use the sidelink positioning protocol (SLPP) to configure and exchange messages between UEs.

[0180] Positioning methods (e.g., sidelink positioning) require the target to possess a communication terminal, and signaling messages must be exchanged between the transmitter and the target for position measurement. This increases the overhead of signal processing between the target and the transmitter, and fundamentally limits positioning if the target does not possess a separate communication terminal.

[0181] In contrast, Integrated Sensing and Communication (ISAC) can accurately detect the presence and movement of a target, regardless of whether the target is carrying a communication terminal. Furthermore, it can reliably acquire detailed sensing information, such as the target's distance, speed, and angle. ISAC can estimate the target's characteristics simply by analyzing the information reflected from the target's signal emitted by the transmitter, without requiring a separate response signal or message from the target. Accordingly, ISAC significantly reduces the amount of signaling compared to positioning methods, significantly lowering overhead and enabling more efficient and flexible sensing and communication operations simultaneously.

[0182] FIG. 12 illustrates an example of an ISAC service according to an embodiment of the present disclosure. The embodiment of FIG. 12 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0183] Referring to Figure 12, examples of various application areas where ISAC can be applied are illustrated. Specifically, ISAC can support predictive maintenance and employee localization and authorization in smart manufacturing and industrial IoT, and provide weather prediction, pollution monitoring, rain monitoring, and insect monitoring in environmental monitoring.

[0184] Additionally, in the field of Sensing as a Service, it can be utilized in drone monitoring and management, mobile crowd sensing, channel knowledge map construction, and cooperative localization and imaging.

[0185] Furthermore, in the field of remote sensing, it can support satellite imaging and broadcasting, drone swarm SAR imaging, and in the field of smart homes, it can be utilized for human proximity detection, spatial-aware control, sensing-aided wireless charging, fall detection, and vital signal monitoring.

[0186] Additionally, in the field of human-computer interaction (HCI), it enables gesture recognition, keystroke recognition, and arm / head activity recognition, and in the field of vehicle-to-everything (V2X) communication, it can provide various services such as high precision location, vehicle platooning, extended sensor, simultaneous localization and mapping, and secure hands-free access.

[0187] Integrated Sensing and Communication (ISAC) technology, which integrates target sensing and user communication functions in recent 6th-generation (6G) mobile communication systems, is attracting attention as a key standardization target. ISAC technology, as shown in Figure 12, is emerging as an essential technology in diverse industries, including autonomous driving, smart factories, drones, and healthcare, based on its advantages such as efficient frequency utilization, reuse of existing communication infrastructure, and cost savings due to integrated sensing and communication.

[0188] FIG. 13 illustrates various integrated sensing and communication (ISAC) systems according to an embodiment of the present disclosure. Specifically, (a) of FIG. 13 illustrates an example of a network-based monostatic ISAC system, (b) of FIG. 13 illustrates an example of a network-based bistatic ISAC system, and (c) of FIG. 13 illustrates an example of a network-UE-based bistatic ISAC system (①) and a network-coordinated UE bistatic ISAC system (①+②). In addition, (d) of FIG. 13 may show an example of a UE-based mono-static ISAC system, (e) of FIG. 13 may show an example of a UE-network bi-static ISAC system, and (f) of FIG. 13 may show an example of a UE-based bi-static ISAC system. For example, the network may be a TRP. For example, the network may be a base station. The embodiment of FIG. 13 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0189] Referring to FIG. 13, various ISAC systems may be considered in the present disclosure to include various ISAC service embodiments. For example, in the present disclosure, a base station may be represented as a BS. For example, in the present disclosure, a terminal may be represented as a UE. For example, a transmitter may transmit a signal for sensing, and a receiver may perform sensing based on a signal reflected from an object. FIG. 13(a) may represent a network-based monostatic ISAC system. In this system, a BS transmits an ISAC signal to multiple targets and receives the reflected signal to estimate the distance and velocity of the targets. Here, the targets may be UEs. FIG. 13(b) may represent a network-based bistatic ISAC system. In this system, two BSs may cooperate to estimate the distance and velocity of the same multiple targets. BS 1 may be a transmitter and BS 2 may be a receiver. BS 2 may receive the ISAC signals transmitted by BS 1 that are reflected by targets. BS 2 may then estimate the distance and velocity of the targets. Unlike monostatic systems, bistatic ISAC systems may not have information about the transmitted signals. Therefore, bistatic ISAC systems can obtain radar information matrices of targets through pilot signals that are already known to both the transmitter and receiver. Figure 13 (c) may be a network-UE-based bistatic ISAC system. In this system, the BS may transmit an ISAC signal. The BS may use a beamforming technique to direct most of the reflected signals toward the UE or to return some of the reflected signals to the BS.In the former case, the UE can receive most of the signals transmitted by the BS and perform target range and velocity estimation. While this allows the UE to quickly obtain the necessary target information, the UE performs all the processing, potentially increasing computational complexity. In contrast, in the latter case, the BS first estimates the target range and velocity, similar to a monostatic ISAC system, and then, based on the estimation results, informs the UE of an appropriate target estimation technique. This allows the UE to immediately perform target estimation using the technique provided by the BS, thereby reducing complexity.

[0190] Figure 13(d) may be a UE-based monostatic ISAC system. The system can directly estimate the target range and velocity at the UE. Figure 13(e) may be a UE-network bistatic ISAC system. The BS can estimate the range and velocity of multiple targets by receiving the ISAC signal transmitted by the UE reflected from the target. Figure 13(f) may be a UE-based bistatic ISAC system. In the system, the range and velocity of targets can be estimated through bistatic between different UEs.

[0191] 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).

[0192] 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.

[0193] 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.

[0194] 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.

[0195] FIG. 14 is a diagram for explaining and comparing V2X communication based on RAT prior to NR and V2X communication based on NR according to one embodiment of the present disclosure. The embodiment of FIG. 14 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0196] 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.

[0197] 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.

[0198] 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.

[0199] 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.

[0200] 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.

[0201] 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.

[0202] 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.

[0203] 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.

[0204] The present disclosure relates to a method for cooperatively recognizing vehicle identification information that may not be accurately identified by a single vehicle or sensor.

[0205] Since the accuracy of identification may vary for each vehicle or sensor and the sensing environment may be different, the information accurately identified by each vehicle / sensor may also vary.

[0206] In these cases, even if each vehicle / sensor fails to obtain perfect information, as more vehicles / sensors sense the same target, the amount of information they cannot identify gradually decreases. Therefore, combining this information can result in increasingly accurate information.

[0207] The present disclosure aims to address the problem of incomplete or uncertain results in object recognition and event determination processes based solely on sensing data provided by vehicles or sensors. Conventional methods have resulted in varying recognition accuracy across vehicles, and even for the same object, different recognition results have been produced depending on environmental conditions such as day / night, weather conditions, distance, and speed. In these situations, the sensing data and reliability provided by a single device are limited, leading to residual uncertainty in the recognition process for specific objects (e.g., vehicle license plates). Therefore, a method is needed that overcomes the limitations of individual devices and enhances the reliability of event recognition and object identification by cooperatively utilizing sensing data and accuracy acquired from multiple vehicles or sensors.

[0208] For example, when an event such as an accident risk occurs, multiple vehicles / sensors can collectively recognize the (same) event or related vehicles and trigger necessary actions related to the event. For example, sensor information collected from each vehicle / sensor can be collated to clearly detect uncertain information related to the event / vehicle.

[0209] For example, a specific vehicle may transmit all object or vehicle information collected from the vehicle's sensors (e.g., cameras) to an upper network such as an RSU or server. Here, for example, the vehicle may transmit the sensor / image information itself, or may transmit detected objects or object-related information.

[0210] For example, objects included in images obtained from the above sensors can be identified based on their respective reference points. For example, whether the same object / vehicle was sensed from different vehicles can be determined by comparing the reference points.

[0211] For example, the reference point of the object may be a reference point at the front or rear of the object, or a center point, depending on the direction of movement of the object (based on the sensor being sensed). For example, in the case of a vehicle, the reference point may be a license plate at the front or rear, or a specific point related to the license plate. For example, the license plate area may be obtained by applying edge detection, Hough transform, etc. to the object / vehicle detected in the image.

[0212] For example, license plate images acquired from individual vehicles / sensors can be synthesized to accurately recognize the license plate content. Similarly, license plate images acquired from individual vehicles / sensors can be independently processed and the recognition results combined to produce a single result.

[0213] 1. Video data collection

[0214] For example, in a situation where images transmitted by each vehicle / sensor or object information detected are collected and collated by an upper network entity such as an RSU or server, images collected from multiple vehicles / sensors or object information detected may be managed by always or as needed by being aligned and / or collated. For example, if object information aligned by the sensing information is always identified, the target vehicle / object can be specified simply by comparing information about the time and location even in a specific event situation. For example, in a situation where each of the sensing information is being collected, necessary information can be aligned and / or collated when a specific event occurs.

[0215] 2. Obtaining object identification information

[0216] For example, a first image sensed from a first vehicle may be transmitted and forwarded to a higher-level network, or information on a first object detected from the first image may be transmitted and forwarded to a higher-level network. Similarly, a second image sensed from a second vehicle may be transmitted and forwarded to a higher-level network, or information on a second object detected from the second image may be transmitted and forwarded to a higher-level network.

[0217] For example, when a first image or a second image is transmitted to a higher network, a network entity such as a server can detect a first object or a second object from the first image or the second image. For example, when the error between the results of tracking the first object and the second object is very small or the correlation is very large so that they are determined to be the same object, the two objects can be determined to be matched with each other. Here, for example, if additional identification information for each object can be obtained, the matching process can be simplified. For example, if the license plate information obtained from each object is the same, each object can be determined to be the same object.

[0218] For example, if the objects are aligned, it can be determined that the identification information for each object is also the same. For example, if the objects are aligned but identification information for each cannot be obtained, for example, if additional information such as car license plate information cannot be obtained from each object, the identification information obtained from each object can be combined to obtain a single identification information. For example, when a first identification image is obtained from a first object and a second identification image is obtained from a second object, the first identification image and the second identification image can be combined and synthesized to obtain the final identification information, or the first identification information obtained from the first identification image and the second identification information obtained from the second identification image can be combined and synthesized to obtain the final identification information.

[0219] 3. Cooperative

[0220] For example, if the target vehicle / object (first target vehicle / first target object) is related to a specific event, such as having caused an accident or being at risk of an accident (e.g., speeding), multiple vehicles / sensors can commonly recognize the event, and the vehicle(s), surrounding vehicles, or associated network entities can trigger information about the event or behavior related thereto. Here, for example, the information sensed by each vehicle / sensor may not necessarily be accurate information. In particular, if the identification of the target vehicle must be solely dependent on the sensor, it may be affected by various environmental variables and variables, such as light intensity, weather, and object speed. Therefore, for example, by collecting information from multiple sensors performing sensing on the same object, the uncertain information can be clearly detected or determined.

[0221] 3.1. Event Detection and Transmission

[0222] For example, the above event situation may be independently determined by a higher-level network entity such as an RSU or server. For example, since vehicles surrounding the event target vehicle may be able to more accurately determine the event situation, the presence of the event may be recognized based on the surrounding vehicles transmitting event-related information (sensing images, detection information, etc.) or judging and reporting the event.

[0223] For example, when a vehicle driving while sensing surrounding vehicle information senses a speeding vehicle or a stationary vehicle and can determine an event or potential event related to this, the event-related content can be included in a related V2X message (e.g., DENM (decentralized environmental notification message)) and transmitted to surrounding vehicles, infrastructure (e.g., direct communication), or higher-level network entities.

[0224] [Direct communication-based collaborative cognition]

[0225] The reporting of the above event may be performed by multiple vehicles at the same time or at similar times (for example, within 1 second intervals), but the detection of the event may be performed by only one vehicle / sensor (for example, the first vehicle) because the detection operation of the event may operate differently for each sensor and depending on the sensing environment. Here, for example, the first vehicle may not receive a message containing event information related to the same target vehicle (for example, the first target vehicle) transmitted by a surrounding vehicle, and in this case, the surrounding vehicles (the second vehicle, the third vehicle, the fourth vehicle, ...) that received the event-related message (the first message) transmitted by the first vehicle can identify the vehicle that is the target of sensing (the first target vehicle) through the first message, thereby allowing the surrounding vehicles to determine whether sensing is possible (for example, determine whether the event was determined within the sensing coverage).

[0226] For example, if sensing is possible, an event-related message can be set to be sent after receiving the first event-related message (e.g., including the received first message ID, timestamp, etc.) to indicate that sensing has been performed for the event, and if sensing is not possible, an event-related message can be set to be sent after receiving the first event-related message but indicating that sensing has failed.

[0227] For example, among the event-related contents, information about the event situation (e.g., sensing video, image, etc.) rather than the final identification information or judgment content related to the vehicle / object may be transmitted in the form of a payload of the first message. For example, this may not necessarily be information that must be transmitted to surrounding vehicles and / or infrastructure. Therefore, for example, the information may be transmitted in a form that is only necessary for a network entity (e.g., a V2X server) in a different form of message. For example, in a state where the video or image has already been transmitted, information such as a timestamp (or frame number) indicating the event and a related event-related video area (e.g., GPS location information, reference point x, y coordinate information, bounding box, polygon shape, or pixel map shape for segmentation, etc.) may be transmitted so that only the necessary part can be extracted from the network entity.

[0228] [Cellular (long range or Uu interface, etc.) communication-based cooperative cognition]

[0229] If the first vehicle transmits event information to a higher network (e.g., a V2X server) through cellular communication and a Uu interface, etc., and other surrounding vehicles do not transmit messages containing event information related to the same target vehicle (e.g., the first target vehicle), the V2X server, etc. can retransmit the message or transmit related messages to surrounding vehicles (e.g., a second vehicle, a third vehicle, etc.) based on the information and message transmitted by the first vehicle.

[0230] The above message may include information about the vehicle / object (e.g., the first target vehicle) related to the event and the type of the event, the time of occurrence, etc., and the method in which the vehicles designated as vehicles around the first target vehicle (e.g., the second vehicle, the third vehicle, etc.) sense and transmit the event-related information is the same as the above method.

[0231] 3.2. Cooperation with identification information

[0232] In this disclosure, sensing data may include identification information. While this disclosure discusses "identification information," it is not limited to this term. For example, in this disclosure, identification information may be sensing data.

[0233] FIG. 15 illustrates a procedure related to accuracy-based sensing data, according to one embodiment of the present disclosure. The embodiment of FIG. 15 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0234] Referring to FIG. 15, in step S1510, for example, a first device may acquire sensing data. In step S1520, for example, the first device may acquire an accuracy associated with the sensing data. In step S1530, for example, the first device may transmit the sensing data and an accuracy associated with the sensing data to a second device. In step S1540, for example, the second device may acquire final sensing data based on the acquired sensing data and the acquired accuracies.

[0235] For example, identification information for the first target vehicle can be cooperatively recognized by collecting information on the first vehicle (single vehicle) alone or information on available vehicles in the vicinity, such as the second vehicle and the third vehicle.

[0236] [Collection of information for each judgment (inference)]

[0237] In this disclosure, sensing data may include identification information. While this disclosure discusses "identification information," it is not limited to this term. For example, in this disclosure, identification information may be sensing data.

[0238] FIG. 16 illustrates a procedure related to accuracy-based sensing data, according to one embodiment of the present disclosure. The embodiment of FIG. 16 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0239] Referring to Fig. 16, for example, the identification information determined by each of the first to third vehicles can be comprehensively determined by an upper network such as a V2X server to derive the final identification information.

[0240] For example, the information with the largest number of identification information transmitted by the surrounding vehicles can be determined as the final identification information. For example, if the first vehicle transmits identification information of 123ga4567, the second vehicle transmits identification information of 123ga4569, and the third vehicle transmits identification information of 123ga4567, the information 123ga4567 transmitted by the majority of vehicles can be determined as the identification information of the first target vehicle.

[0241] For example, if there is no identical identification information or no multiple identification information among the identification information transmitted by the surrounding vehicles, the multiple information can be distinguished for each digit of the identification information transmitted by the surrounding vehicles and determined as the final identification information. For example, if the first vehicle transmitted identification information of 123ga4567, the second vehicle transmitted identification information of 124ga4587, and the third vehicle transmitted identification information of 123ra4569 as shown in FIG. 16, the multiple information for each digit can be collected and 123ga4567 can be determined as the identification information of the first target vehicle.

[0242] For example, the final identification information can be determined based on the unanimity of the entire identification information above, and the final identification information can be determined based on the unanimous information for each digit of the identification information. For example, if the first vehicle transmits identification information such as 123ga4567, the second vehicle transmits identification information such as 124ga4587, and the third vehicle transmits identification information such as 123ra4569, the unanimous information for each digit can be collected to determine 12xx45xx as the identification information of the first target vehicle. Here, for example, x for each digit can mean that the collected identification information is not unanimous.

[0243] For example, the final identification information can be determined based on unanimous information. If the first vehicle transmits identification information such as 123ga4567, the second vehicle transmits identification information such as 124ga4587, and the third vehicle transmits identification information such as 123ra4569, the unanimous information for each digit can be collected to determine 12xx45xx as the identification information for the first target vehicle. Here, for example, an x ​​in each digit can mean that the collected identification information is not unanimous.

[0244] [Collect each (video) information and make a judgment (inference)]

[0245] In this disclosure, sensing data may include identification information. While this disclosure discusses "identification information," it is not limited to this term. For example, in this disclosure, identification information may be sensing data.

[0246] FIG. 17 illustrates a procedure related to accuracy-based sensing data, according to one embodiment of the present disclosure. The embodiment of FIG. 17 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0247] Referring to Fig. 17, for example, before making a judgment (inference) on the information transmitted by each of the first to third vehicles, the final identification information can be derived by combining / synthesizing in an upper network such as a V2X server.

[0248] For example, among the images transmitted by the first or third vehicles, an area that can serve as identification information (e.g., a car license plate) is taken, and all of them are synthesized with the same size and the same offset (e.g., only the license plate area is cut out into an exact rectangle and the image is resized identically to the actual ratio of the license plate), and then the identification information can be determined (inferred) based on the obtained final image. In this case, for example, the principle of determining identification information based on the above-mentioned unanimous or majority information can be reflected to some extent.

[0249] For example, in the above synthesis process, there may be a score for the information detected for each digit of the identification information area, and this can be taken into consideration for synthesis (based on information previously identified for each vehicle / sensor). For example, if the identification information 123ga4567 from the first vehicle, 124ga4587 from the second vehicle, and 123ra4569 from the third vehicle were derived in advance, the first and second digits can all be synthesized with the same weight, or the identification information 1 and 2 can be derived directly without synthesizing the images. For example, if the third digit senses different information for each vehicle, for example, if the first vehicle determines the value 3 with 90% accuracy (or score), the second vehicle determines the value 4 with 60% accuracy (or score), and the third vehicle determines the value 3 with 80% accuracy (or score), the image of the first vehicle can be synthesized with a weight of 90% (or 0.9), the image of the second vehicle with a weight of 60% (or 0.6), and the image of the third vehicle with a weight of 80% (or 0.8), and the image obtained in this way can be normalized by dividing it by the sum of the weights (0.9+0.6+0.8=2.3).

[0250] For example, the accuracy is not limited to a simple object recognition confidence value, but can be calculated multidimensionally by reflecting multiple input factors. For example, the accuracy can be calculated based on at least one of confidence, environmental conditions (e.g., brightness, weather, fog, day / night, relative speed, distance, etc.), sensor type and performance (e.g., camera, LiDAR, radar, etc.), temporal continuity (whether detection occurs in consecutive frames), multi-sensor fusion, and matching rate with adjacent vehicles. For example, the accuracy can be applied with different basic weights depending on the sensor type. For example, camera-based accuracy can be adjusted according to image resolution and light intensity. For example, LiDAR-based accuracy can be adjusted according to distance to the object and reflectivity. For example, radar-based accuracy can be adjusted according to relative speed and SNR.

[0251] For example, the accuracy calculation can be dynamically performed by applying a correction algorithm. For example, the correction algorithm may include at least one of a (pre-trained) machine learning model, Bayesian inference, or reinforcement learning.

[0252] For example, if the confidence value of the CNN-based license plate recognition engine is 0.85 when a correction algorithm is applied, a correction of -0.2 is applied due to the night environment, and a correction of +0.15 is applied due to fusion detection with the lidar, the final accuracy can be calculated as 0.8.

[0253] For example, the above correction algorithm may be included in an object recognition engine and produce accuracy together with the recognition result, or it may exist separately from the object recognition engine and produce accuracy by using identification information and confidence output from the object recognition engine as input.

[0254] For example, the above accuracy can be obtained based on an object recognition engine.

[0255] For example, the object recognition engine may include a machine learning or deep learning-based neural network structure. Here, for example, deep learning, as a sub-concept of machine learning, may refer to a learning method using a multi-layer neural network (Deep Neural Network, DNN). For example, the deep learning may be implemented using at least one of a convolutional neural network (CNN), a recurrent neural network (RNN), or a transformer-based model.

[0256] For example, the object recognition engine may be implemented in various forms. For example, the object recognition engine may include software or hardware modules such as a license plate recognition engine, an optical character recognition (OCR) engine, or an object detection engine. For example, the object detection engine may be implemented based on machine learning or deep learning.

[0257] For example, the accuracy-based merging process described above can be dynamically adjusted based on system conditions, rather than being performed according to fixed rules. For example, if communication delays are high, the accuracy reflection ratio of a local vehicle may be increased. For example, if an accident event occurs around a specific vehicle, the accuracy of that vehicle may be weighted upward. For example, if a sensor failure is detected in a specific vehicle, the accuracy of that vehicle may be limited to a minimum value.

[0258] For example, the dynamic weight adjustment can be performed by a central server or RSU calculating and broadcasting optimized weights based on the reports from all vehicles. Alternatively, a hybrid approach can be used, where each vehicle adjusts its weights based on local conditions and the server then combines them.

[0259] For example, the accuracy may be related to past collaborative recognition results. For example, the present disclosure may include a function to learn the optimal accuracy calculation ratio for each environment by comparing past collaborative recognition results with the actual correct answer (ground truth). For example, in a nighttime / rainy environment, if applying a higher ratio of lidar correction factors than the confidence-based value more closely matches the actual result, the system may automatically adjust the ratio when calculating accuracy in the future based on this experience. For example, if multiple vehicles report the same object with unanimous agreement, the accuracy for that digit may be set to the maximum value.

[0260] The term "accuracy" used in this disclosure refers to a value indicating the reliability of a specific object recognition result, but is not limited thereto. For example, the term "accuracy" used in this disclosure may be interpreted as a concept identical to or similar to "weight" or "score." For example, in the embodiments of this disclosure, accuracy is not limited to a simple confidence value, but may also be used as a weight value for combining or correcting identification information. For example, accuracy may also be utilized as an indicator that quantitatively represents recognition accuracy. For example, the term "accuracy" may be used interchangeably with "weight" or "score."

[0261] For example, in the present disclosure, sensing information (or sensing data) may include at least one of object information and event information. For example, in the present disclosure, sensing information (or sensing data) may be interpreted as being replaced with at least one of object information and event information.

[0262] The above methods proposed in this disclosure can be applied to both 3GPP sensing data and non-3GPP sensing data.

[0263] For example, in the present disclosure, the sensing data may be data derived by a sensing wireless measurement entity based on a wireless signal that is influenced (e.g., reflected, refracted, or diffracted) by an object or environment of interest for sensing purposes. For example, this data may be raw measurements and optionally be further processed within the sensing wireless measurement entity. For example, the sensing data may include at least one of 3GPP sensing data or non-3GPP sensing data.

[0264] For example, in the present disclosure, 3GPP sensing data is data obtained from 3GPP wireless signals that have been affected (e.g., reflected, refracted, diffracted) by an object or environment of interest for sensing purposes, and may optionally be processed within a 5G system.

[0265] For example, in the present disclosure, non-3GPP sensing data may be data provided by a non-3GPP sensor (e.g., video, LiDAR, sonar) about an object or environment of interest for sensing purposes.

[0266] For example, in the present disclosure, 5G / 6G wireless sensing may be a 5GS / 6GS capability that provides the ability to acquire information about characteristics of an environment and / or objects within the environment (e.g., shape, size, orientation, speed, position, distance, relative motion between objects, etc.) using NR radio frequency signals, and in some cases may be extended by information generated through capabilities previously defined in the EPC and / or E-UTRAN.

[0267] For example, in the present disclosure, sensing assistance information may be provided to the 5G system from a trusted third party and may be used to support the derivation of sensing results. This information may not include 3GPP sensing data. Examples of sensing assistance information may include map information, area information, a UE identifier (ID) attached to or located near a sensing target, UE location information, UE speed information, and the like.

[0268] For example, in the present disclosure, sensing context information may be information that a 5G / 6G system exposes to a trusted third party along with sensing results, providing context regarding the conditions under which the sensing results were derived. This information may not include 3GPP sensing data. For example, examples of sensing context information may include map information, area information, capture time, UE location, and ID. This context information may be required in scenarios where sensing results must be combined with data from other sources outside of 5GS.

[0269] For example, in the present disclosure, a sensing group may be a set of sensing transmitters and sensing receivers whose locations are known and capable of synchronously collecting sensing data.

[0270] For example, in the present disclosure, a sensing receiver may be an entity that receives sensing signals used by a sensing service in its operation. The sensing receiver may be part of a RAN node or a UE. The sensing receiver may be located in the same entity as the sensing transmitter or in a different entity.

[0271] For example, in the present disclosure, the sensing result may be processed 3GPP sensing data requested by a service consumer.

[0272] For example, in the present disclosure, a sensing signal may be a transmission signal on a 3GPP radio interface that can be used for sensing purposes. For example, this definition may refer to a NR radio frequency signal, and in some cases, may be extended to information generated from existing functions of the EPC and / or E-UTRAN.

[0273] For example, a sensing transmitter may be an entity that transmits sensing signals used by a sensing service in its operation. The sensing transmitter may be part of a RAN node or a UE. The sensing transmitter may be located in the same entity as the sensing receiver or in a different entity.

[0274] For example, a target sensing service area may be a location area in Cartesian coordinates that satisfies a specific sensing service quality and that is to sense the environment and / or object characteristics within the environment derived from (e.g., reflected, refracted, diffracted) 3GPP radio signals. This may include both indoor and outdoor environments.

[0275] For example, the present disclosure may be applied to a base station (e.g., a TRP) and / or a terminal monostatic. For example, the present disclosure may also be applied to a base station-base station (e.g., a TRP-TRP), a base station-UE (e.g., a TRP-UE), a UE-base station (e.g., a UE-TRP), and / or a UE-UE bistatic.

[0276] For example, in the present disclosure, a “specific threshold” may mean a threshold that is defined in advance or set (in advance) by a higher layer (including an application layer) of a network or a base station or a terminal. For example, in the present disclosure, a “specific set value” may mean a value that is defined in advance or set (in advance) by a higher layer (including an application layer) of a network or a base station or a terminal. For example, in the present disclosure, “set by the network / base station” may mean an operation in which the base station sets (in advance) to the UE via higher layer RRC signaling, sets / signals to the UE via MAC CE, or signals to the UE via DCI.

[0277] For example, in the present disclosure, a message may be interpreted as being replaced with at least one of a control message, a data message, a signal, a data signal, and / or a control signal. For example, in the present disclosure, various names are exemplary and may be replaced / considered with other names that perform the same / similar function based on the content described in each step (regardless of the name).

[0278] For example, whether (some) of the proposed methods / rules of the present disclosure are applicable and / or their associated parameters (e.g., thresholds) can be set resource pool-specifically (or differently or independently). For example, whether (some) of the proposed methods / rules of the present disclosure are applicable and / or their associated parameters (e.g., thresholds) can be set congestion level-specifically (or differently or independently). For example, whether (some) of the proposed methods / rules of the present disclosure are applicable and / or their associated parameters (e.g., thresholds) can be set service priority-specifically (or differently or independently). For example, whether (some) of the proposed methods / rules of the present disclosure are applicable and / or their associated parameters (e.g., thresholds) can be set service type-specifically (or differently or independently). For example, whether (some) of the proposed schemes / rules of the present disclosure are applicable and / or related parameters (e.g., thresholds) can be set specifically (or differently or independently) for QoS requirements (e.g., latency, reliability). For example, whether (some) of the proposed schemes / rules of the present disclosure are applicable and / or related parameters (e.g., thresholds) can be set specifically (or differently or independently) for PQI (5QI (5G QoS identifier) ​​for PC5). For example, whether (some) of the proposed schemes / rules of the present disclosure are applicable and / or related parameters (e.g., thresholds) can be set specifically (or differently or independently) for traffic types (e.g., periodic generation or aperiodic generation). For example, whether (some) of the proposed schemes / rules of the present disclosure are applicable and / or related parameters (e.g., thresholds) can be set specifically (or differently or independently) for SL transmission resource allocation modes (e.g., mode 1 or mode 2).For example, whether (some) of the proposed methods / rules of the present disclosure are applicable and / or related parameters (e.g., thresholds) may be configured specifically (or differently or independently) for a Tx profile (e.g., a Tx profile indicating that the service supports sidelink DRX operation or a Tx profile indicating that the service does not need to support sidelink DRX operation).

[0279] For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be specifically (or differently or independently) set depending on whether PUCCH configuration is supported (e.g., when PUCCH resources are configured or when PUCCH resources are not configured). For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be specifically (or differently or independently) set for a resource pool (e.g., a resource pool where PSFCH is configured or a resource pool where PSFCH is not configured). For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be specifically (or differently or independently) set for a type of service / packet. For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be specifically (or differently or independently) set for a priority of a service / packet. For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) for a QoS profile or QoS requirement (e.g., URLLC / EMBB traffic, reliability, latency). For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) for a PQI. For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) for a PFI. For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) for a cast type (e.g., unicast, groupcast, broadcast). For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) for a (resource pool) congestion level (e.g., CBR).For example, whether the proposed rule of the present disclosure is applicable and / or the related parameter setting value can be set specifically (or differently or independently) for an SL HARQ feedback scheme (e.g., NACK-only feedback, ACK / NACK feedback). For example, whether the proposed rule of the present disclosure is applicable and / or the related parameter setting value can be set specifically (or differently or independently) for HARQ Feedback Enabled MAC PDU transmission. For example, whether the proposed rule of the present disclosure is applicable and / or the related parameter setting value can be set specifically (or differently or independently) for HARQ Feedback Disabled MAC PDU transmission. For example, whether the proposed rule of the present disclosure is applicable and / or the related parameter setting value can be set specifically (or differently or independently) depending on whether a PUCCH-based SL HARQ feedback reporting operation is set. For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) depending on whether pre-emption or pre-emption-based resource reselection is performed. For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) depending on whether re-evaluation or re-evaluation-based resource reselection is performed. For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) for (L2 or L1) (source and / or destination) identifiers. For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) for (L2 or L1) (a combination of source ID and destination ID) identifiers.For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) for an identifier (L2 or L1) (a combination of a pair of source ID and destination ID and a cast type). For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) for a direction of a pair of source layer ID and destination layer ID. For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) for a PC5 RRC connection / link. For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) depending on whether SL DRX is performed. For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) depending on whether SL DRX is supported. For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) for the SL mode type (e.g., resource allocation mode 1 or resource allocation mode 2). For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) for the case of performing (a)periodic resource reservation. For example, whether the proposed rule of the present disclosure applies and / or the related parameter setting values ​​can be set specifically (or differently or independently) for a Tx profile (e.g., a Tx profile indicating that the service supports sidelink DRX operation or a Tx profile indicating that the service does not need to support sidelink DRX operation).

[0280] The applicability of the proposals and proposed rules of the present disclosure (and / or related parameter settings) may also be applied to mmWave sidelink operation.

[0281] For example, whether the rule applies and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed service type-specifically (or differently or independently). For example, whether the rule applies and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed (or differently or independently) (LCH or service) priority-specifically. For example, whether the rule applies and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed (or differently or independently) QoS requirements (e.g., latency, reliability, minimum communication range)-specifically. For example, whether the rule applies and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed PQI parameter-specifically (or differently or independently). For example, whether the rule applies and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed SL HARQ feedback ENABLED LCH / MAC PDU (transmission)-specifically (or differently or independently). For example, whether the rule is applied and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed specifically (or differently or independently) for SL HARQ feedback DISABLED LCH / MAC PDU (transmission). For example, whether the rule is applied and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed specifically (or differently or independently) for CBR measurement values ​​of resource pools. For example, whether the rule is applied and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed specifically (or differently or independently) for SL cast types (e.g., unicast, groupcast, broadcast).For example, whether the rule is applied and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed specifically (or differently or independently) for SL groupcast HARQ feedback options (e.g., NACK only feedback, ACK / NACK feedback, NACK only feedback based on TX-RX distance). For example, whether the rule is applied and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed specifically (or differently or independently) for SL mode 1 CG type (e.g., SL CG type 1 or SL CG type 2). For example, whether the rule is applied and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed specifically (or differently or independently) for SL mode type (e.g., mode 1 or mode 2). For example, whether the rule is applied and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed specifically (or differently or independently) for resource pool. For example, whether the rule applies and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed specifically (or differently or independently) whether the PSFCH resource is a configured resource pool. For example, whether the rule applies and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed specifically (or differently or independently) for a source (L2) ID. For example, whether the rule applies and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed specifically (or differently or independently) for a destination (L2) ID. For example, whether the rule applies and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed specifically (or differently or independently) for a PC5 RRC connection link.For example, whether the rule is applied and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed specifically (or differently or independently) for an SL link. For example, whether the rule is applied and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed specifically (or differently or independently) for a connection state (with a base station) (e.g., RRC CONNECTED state, IDLE state, INACTIVE state). For example, whether the rule is applied and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed specifically (or differently or independently) for an SL HARQ process (ID). For example, whether the rule is applied and / or the parameter values ​​related to the proposed method / rule of the present disclosure can be set / allowed specifically (or differently or independently) for whether the SL DRX operation (of a TX UE or an RX UE) is performed. For example, whether the rule applies and / or the parameter values ​​related to the proposed scheme / rule of the present disclosure can be set / allowed specifically (or differently or independently) depending on whether the UE is power saving (TX or RX). For example, whether the rule applies and / or the parameter values ​​related to the proposed scheme / rule of the present disclosure can be set / allowed specifically (or differently or independently) if (from a specific UE perspective) PSFCH TX and PSFCH RX overlap (and / or multiple PSFCH TXs (which exceed the UE capability)) (and / or if PSFCH TX (and / or PSFCH RX) are omitted). For example, whether the rule applies and / or the parameter values ​​related to the proposed scheme / rule of the present disclosure can be set / allowed specifically (or differently or independently) depending on whether the RX UE actually (successfully) receives a PSCCH (and / or PSSCH) (re)transmission from a TX UE.

[0282] For example, in the present disclosure, the setting (or designation) wording can be extended to include a form in which a base station notifies a terminal through a predefined (physical layer or upper layer) channel / signal (e.g., SIB, RRC, MAC CE) (and / or a form provided through pre-configuration and / or a form in which a terminal notifies another terminal through a predefined (physical layer or upper layer) channel / signal (e.g., SL MAC CE, PC5 RRC)).

[0283] For example, in the present disclosure, the PSFCH wording can be extended to (NR or LTE) PSSCH (and / or (NR or LTE) PSCCH) (and / or (NR or LTE) SL SSB (and / or UL channel / signal)). In addition, the proposed method of the present disclosure can be extended (in a new form) by being combined with each other.

[0284] For example, in the present disclosure, a specific threshold value may mean a threshold value that is defined in advance, or set (in advance) by a higher layer (including an application layer) of a network or a base station or a terminal. For example, in the present disclosure, a specific setting value may mean a value that is defined in advance, or set (in advance) by a higher layer (including an application layer) of a network or a base station or a terminal. For example, an operation set by a network / base station may mean an operation that a base station sets (in advance) to a UE via a higher layer RRC signaling, sets / signals to the UE via MAC CE, or signals to the UE via DCI.

[0285] In embodiments of the present disclosure, a message may be interpreted as a control message or a data message or a signal or a data signal or a control signal.

[0286] In embodiments of the present disclosure, the beam management operation may be interpreted as being replaced with beam selection or spatial filter selection or beam pairing or spatial filter pairing or beam failure recovery or spatial filter recovery or beam sweeping or spatial filter sweeping or beam switching or spatial filter switching or measurement of reference signal resources or measurement reporting of reference signal resources or beam reporting or spatial filter reporting, etc.

[0287] In embodiments of the present disclosure, the beam may be interpreted as being replaced by an RS or RS resource or a spatial filter resource.

[0288] In embodiments of the present disclosure, RS may be interpreted as being replaced with RS resources or spatial filter resources.

[0289] In the embodiments of the present disclosure, the transmitting terminal may be interpreted as a terminal transmitting a beam, a terminal transmitting a beam RS, a terminal transmitting a beam RS resource, etc.

[0290] In the embodiments of the present disclosure, the receiving terminal may be interpreted as a terminal that receives a beam, a terminal that receives a beam RS, a terminal that receives a beam RS resource, etc.

[0291] In an embodiment of the present disclosure, the transmission beam or reception beam information transmitted and received by the terminal may be interpreted as being replaced with resource information of an RS (reference signal) associated with the transmission beam and resource information of an RS (reference signal) associated with the reception beam.

[0292] In embodiments of the present disclosure, the direct communication request (DCR) and / or direct communication accept (DCA) messages may be interpreted as being replaced with PC5-S DCR and / or PC5-S DCA messages.

[0293] In embodiments of the present disclosure, spatial setting and / or transmission configuration indication (TCI) information and / or quasi-co-location (QCL) information and / or beams, etc. may refer to each other and / or may be interpreted as being replaced with beam-related information, beam direction, spatial domain transmission or reception filter, etc.

[0294] In embodiments of the present disclosure, a beam may be interpreted as a transmit beam or a receive beam or a spatial filter or a spatial transmit (TX) filter or a spatial domain transmit (TX) filter or a spatial receive (RX) filter or a spatial domain receive (RX) filter.

[0295] In embodiments of the present disclosure, the transmit / transmit beam may be interpreted as being replaced by a spatial transmit (TX) filter or a spatial domain transmit (TX) filter.

[0296] In embodiments of the present disclosure, the receive beam may be interpreted by replacing it with a spatial receive (RX) filter or a spatial domain receive (RX) filter.

[0297] In an embodiment of the present disclosure, the same spatial setting information (or beam information) for transmission may mean that the spatial domain TX filter of the terminal is the same for two different transmission signals. In an embodiment of the present disclosure, the same spatial setting information (or beam information) for reception may mean that two different reception signals are in a QCL 'TypeD' relationship and / or use the same spatial RX parameters.

[0298] For example, the control message (or signal) and / or data message (or signal) in the present disclosure may mean a control message (or signal) and / or data message (or signal) for wireless communication (e.g., LTE communication, NR communication, 6G communication, Wi-Fi communication, Bluetooth communication, and / or other wireless communication) other than a radar signal.

[0299] For example, the source ID and destination ID disclosed in the present disclosure may mean a source layer 1 ID and a destination layer 1 ID, and / or may mean a source layer 2 ID and a destination layer 2 ID.

[0300] FIG. 18 illustrates a method for a first device to perform wireless communication according to an embodiment of the present disclosure. The embodiment of FIG. 18 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0301] Referring to FIG. 18, for example, in step S1810, the first device may acquire sensing data. For example, in step S1820, the first device may acquire accuracy associated with the sensing data. For example, in step S1830, the first device may report the sensing data and the accuracy associated with the sensing data.

[0302] For example, the sensing data may include identification information.

[0303] For example, the accuracy may be related to environmental conditions.

[0304] For example, the environmental conditions may include fog, or whether it is day or night.

[0305] For example, the accuracy may be related to at least one of the type of sensor or the performance of the sensor.

[0306] For example, the type of sensor may include at least one of LiDAR or radar.

[0307] For example, the performance of the sensor may include reflectance.

[0308] For example, the accuracy can be increased based on the sensing data being acquired by both the lidar and the radar.

[0309] For example, the accuracy may be related to past collaborative cognitive outcomes.

[0310] For example, the accuracy may be related to at least one of network latency, event occurrence location, and sensor failure.

[0311] For example, the accuracy can be obtained based on a correction algorithm. For example, the correction algorithm can include at least one of machine learning, Bayesian estimation, or reinforcement learning.

[0312] For example, the accuracy may be obtained based on an object recognition engine. For example, the object recognition engine may include at least one of a license plate recognition engine, an optical character recognition engine, or a deep learning-based object detection engine.

[0313] For example, the deep learning-based object recognition engine may be associated with at least one of a convolutional neural network (CNN), a recurrent neural network (RNN), or a transformer-based model.

[0314] The above proposed method can be applied to a first device according to various embodiments of the present disclosure. For example, first, the processor (102) of the first device (100) can obtain sensing data (for example, the processor (102) of the first device (100) can control the transceiver (106) to obtain the sensing data). For example, and then, the processor (102) of the first device (100) can obtain accuracy related to the sensing data (for example, the processor (102) of the first device (100) can control the transceiver (106) to obtain accuracy related to the sensing data). For example, the processor (102) of the first device (100) can report the sensing data and the accuracy associated with the sensing data (e.g., the processor (102) of the first device (100) can control the transceiver (106) to report the sensing data and the accuracy associated with the sensing data).

[0315] According to one embodiment of the present disclosure, a first device may be provided. For example, the first device may include at least one transceiver; at least one processor; and at least one memory coupled to the at least one processor and storing instructions. For example, the instructions, based on execution by the at least one processor, may cause the first device to: acquire sensing data; acquire an accuracy associated with the sensing data; and report the sensing data and the accuracy associated with the sensing data.

[0316] For example, the sensing data may include identification information.

[0317] For example, the accuracy may be related to environmental conditions.

[0318] For example, the environmental conditions may include fog, or whether it is day or night.

[0319] For example, the accuracy may be related to at least one of the type of sensor or the performance of the sensor.

[0320] For example, the type of sensor may include at least one of LiDAR or radar.

[0321] For example, the performance of the sensor may include reflectance.

[0322] For example, the accuracy can be increased based on the sensing data being acquired by both the lidar and the radar.

[0323] For example, the accuracy may be related to past collaborative cognitive outcomes.

[0324] For example, the accuracy may be related to at least one of network latency, event occurrence location, and sensor failure.

[0325] For example, the accuracy can be obtained based on a correction algorithm. For example, the correction algorithm can include at least one of machine learning, Bayesian estimation, or reinforcement learning.

[0326] For example, the accuracy may be obtained based on an object recognition engine. For example, the object recognition engine may include at least one of a license plate recognition engine, an optical character recognition engine, or a deep learning-based object detection engine.

[0327] For example, the deep learning-based object recognition engine may be associated with at least one of a convolutional neural network (CNN), a recurrent neural network (RNN), or a transformer-based model.

[0328] According to one embodiment of the present disclosure, a processing device (configured to control a first device) may be provided. For example, the processing device may include at least one processor; and at least one memory coupled to the at least one processor and storing instructions. For example, the instructions, based on execution by the at least one processor, may cause the first device to: acquire sensing data; acquire an accuracy associated with the sensing data; and report the sensing data and the accuracy associated with the sensing data.

[0329] According to one embodiment of the present disclosure, a non-transitory computer-readable storage medium storing commands may be provided. For example, the commands, when executed, may cause a first device to: acquire sensing data; acquire accuracy associated with the sensing data; and report the sensing data and the accuracy associated with the sensing data.

[0330] FIG. 19 illustrates a method for a second device to perform wireless communication according to an embodiment of the present disclosure. The embodiment of FIG. 19 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0331] Referring to FIG. 19, for example, in step S1910, the second device may receive a plurality of sensing data. For example, in step S1920, the second device may receive a plurality of accuracies associated with the plurality of sensing data. For example, in step S1930, the second device may obtain final sensing data based on the plurality of sensing data and the plurality of accuracies associated with the plurality of sensing data.

[0332] For example, the plurality of sensing data may include identification information.

[0333] For example, the above multiple accuracies may be related to environmental conditions.

[0334] For example, the environmental conditions may include fog, or whether it is day or night.

[0335] For example, the plurality of accuracies may be related to at least one of the type of sensor or the performance of the sensor.

[0336] For example, the type of sensor may include at least one of LiDAR or radar.

[0337] For example, the performance of the sensor may include reflectance.

[0338] For example, the plurality of accuracies may be increased based on the plurality of sensing data being acquired by both the lidar and the radar.

[0339] For example, the above multiple accuracies may be related to past collaborative recognition results.

[0340] For example, the plurality of accuracies may be related to at least one of network delay, event occurrence location, and sensor failure.

[0341] For example, the above multiple accuracies can be obtained based on a correction algorithm. For example, the correction algorithm can include at least one of machine learning, Bayesian estimation, or reinforcement learning.

[0342] For example, the plurality of accuracies may be obtained based on an object recognition engine. For example, the object recognition engine may include at least one of a license plate recognition engine, an optical character recognition engine, or a deep learning-based object detection engine.

[0343] For example, the deep learning-based object recognition engine may be associated with at least one of a convolutional neural network (CNN), a recurrent neural network (RNN), or a transformer-based model.

[0344] The above proposed method can be applied to devices according to various embodiments of the present disclosure. For example, first, the processor (202) of the second device (200) can receive a plurality of sensing data (for example, the processor (202) of the second device (200) can control the transceiver (206) to receive the plurality of sensing data). For example, and then, the processor (202) of the second device (200) can receive a plurality of accuracies related to the plurality of sensing data (for example, the processor (202) of the second device (200) can control the transceiver (206) to receive a plurality of accuracies related to the plurality of sensing data). For example, the processor (202) of the second device (200) can obtain final sensing data based on the plurality of sensing data and the plurality of accuracies associated with the plurality of sensing data (for example, the processor (202) of the second device (200) can control the transceiver (206) to obtain final sensing data based on the plurality of sensing data and the plurality of accuracies associated with the plurality of sensing data).

[0345] According to one embodiment of the present disclosure, a second device may be provided. For example, the second device may include at least one transceiver; at least one processor; and at least one memory coupled to the at least one processor and storing instructions. For example, the instructions, based on execution by the at least one processor, may cause the second device to: receive a plurality of sensing data; receive a plurality of accuracies associated with the plurality of sensing data; and obtain final sensing data based on the plurality of sensing data and the plurality of accuracies associated with the plurality of sensing data.

[0346] For example, the plurality of sensing data may include identification information.

[0347] For example, the above multiple accuracies may be related to environmental conditions.

[0348] For example, the environmental conditions may include fog, or whether it is day or night.

[0349] For example, the plurality of accuracies may be related to at least one of the type of sensor or the performance of the sensor.

[0350] For example, the type of sensor may include at least one of LiDAR or radar.

[0351] For example, the performance of the sensor may include reflectance.

[0352] For example, the plurality of accuracies may be increased based on the plurality of sensing data being acquired by both the lidar and the radar.

[0353] For example, the above multiple accuracies may be related to past collaborative recognition results.

[0354] For example, the plurality of accuracies may be related to at least one of network delay, event occurrence location, and sensor failure.

[0355] For example, the above multiple accuracies can be obtained based on a correction algorithm. For example, the correction algorithm can include at least one of machine learning, Bayesian estimation, or reinforcement learning.

[0356] For example, the plurality of accuracies may be obtained based on an object recognition engine. For example, the object recognition engine may include at least one of a license plate recognition engine, an optical character recognition engine, or a deep learning-based object detection engine.

[0357] For example, the deep learning-based object recognition engine may be associated with at least one of a convolutional neural network (CNN), a recurrent neural network (RNN), or a transformer-based model.

[0358] According to one embodiment of the present disclosure, a processing device (configured to control a second device) may be provided. For example, the processing device may include at least one processor; and at least one memory coupled to the at least one processor and storing instructions. For example, the instructions, based on execution by the at least one processor, may cause the second device to: receive a plurality of sensed data; receive a plurality of accuracies associated with the plurality of sensed data; and obtain final sensed data based on the plurality of sensed data and the plurality of accuracies associated with the plurality of sensed data.

[0359] According to one embodiment of the present disclosure, a non-transitory computer-readable storage medium having instructions recorded thereon may be provided. For example, the instructions, when executed, may cause a second device to: transmit a signal for sensing. For example, a signal reflected from an object may be received. For example, sensing may be performed based on the reflected signal. For example, the instructions, when executed, may cause the second device to: receive a plurality of sensed data; receive a plurality of accuracies associated with the plurality of sensed data; and obtain final sensed data based on the plurality of sensed data and the plurality of accuracies associated with the plurality of sensed data.

[0360] According to the present disclosure, when attempting to identify a specific object or vehicle with a single sensor or vehicle, inaccuracy persists. However, by requesting a following vehicle to sense and compiling the information obtained therefrom to fill in the missing information, the inaccuracy can be reduced.

[0361] According to the present disclosure, the first device reports not only the sensing data but also the accuracy associated with said sensing data, thereby providing the information provided to the network not only as raw data but also with added reliability and quality information. Accordingly, a higher-level network or other vehicles can collect data on the same object or event from multiple vehicles and align it using majority voting, weighting, or unanimity criteria, thereby improving the accuracy of object recognition.

[0362] Therefore, it can overcome the imperfections of sensing or environmental constraints caused by a single vehicle or sensor, and secure accurate and reliable identification information for objects related to specific events. Furthermore, by enabling multiple vehicles to cooperatively sense and report on the same event without redundant reporting, it reduces unnecessary waste of wireless resources and improves network processing efficiency. Consequently, the present disclosure can achieve the following benefits through collaborative cognition: improved object recognition accuracy, reliable event judgment, and improved network resource efficiency.

[0363] The various embodiments of the present disclosure may be combined with each other, and some descriptions, functions, procedures, proposals, methods and / or operations of the various embodiments may be omitted.

[0364] The above proposed method can be applied to the device described below. First, the processor (202) of the receiving terminal can set at least one partial bandwidth (e.g., BWP; bandwidth part). Then, the processor (202) of the receiving terminal can control the transceiver (206) of the receiving terminal to receive a physical channel related to terminal-to-terminal communication (e.g., SL communication) and / or a reference signal related to terminal-to-terminal communication (e.g., SL communication) from the transmitting terminal on at least one partial bandwidth (e.g., BWP).

[0365] Below, a description is given of devices to which various embodiments of the present disclosure can be applied.

[0366] Although not limited thereto, the various descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed in this document may be applied to various fields requiring wireless communication / connectivity (e.g., 5G) between devices.

[0367] 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.

[0368] FIG. 20 illustrates a communication system (1) according to one embodiment of the present disclosure. The embodiment of FIG. 20 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0369] Referring to FIG. 20, a communication system (1) to which various embodiments of the present disclosure are applied 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) and / or an Aerial Vehicle (AV) (e.g., an Advanced Air Mobility (AAM)). The XR device may include an Augmented Reality (AR) / Virtual Reality (VR) / Mixed Reality (MR) device, and may be implemented in the form of a Head-Mounted Device (HMD), a Head-Up Display (HUD) equipped in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, a digital signage, a vehicle, a robot, etc. The portable device may include a smartphone, a smart pad, a wearable device (e.g., a smart watch, smart glasses), a computer (e.g., a laptop, etc.), etc. The home appliance may include a TV, a refrigerator, a washing machine, etc. The IoT device may include a sensor, a smart meter, etc. For example, a base station and a network may also be implemented as a wireless device, and a specific wireless device (200a) may operate as a base station / network node to other wireless devices.

[0370] Here, the wireless communication technology implemented in the wireless devices (100a to 100f) of the present specification may include not only LTE, NR, and 6G, but also Narrowband Internet of Things for low-power communication. At this time, for example, NB-IoT technology may be an example of LPWAN (Low Power Wide Area Network) technology, and may be implemented with standards such as LTE Cat NB1 and / or LTE Cat NB2, and is not limited to the above-described names. Additionally or alternatively, the wireless communication technology implemented in the wireless devices (100a to 100f) of the present specification may perform communication based on LTE-M technology. At this time, for example, LTE-M technology may be an example of LPWAN technology, and may be called by various names such as eMTC (enhanced Machine Type Communication). For example, LTE-M technology can be implemented by at least one of various standards such as 1) LTE CAT 0, 2) LTE Cat M1, 3) LTE Cat M2, 4) LTE non-BL (non-Bandwidth Limited), 5) LTE-MTC, 6) LTE Machine Type Communication, and / or 7) LTE M, and is not limited to the above-described names. Additionally or alternatively, the wireless communication technology implemented in the wireless devices (100a to 100f) of the present specification can include at least one of ZigBee, Bluetooth, and Low Power Wide Area Network (LPWAN) considering low-power communication, and is not limited to the above-described names. For example, ZigBee technology can create personal area networks (PAN) related to small / low-power digital communication based on various standards such as IEEE 802.15.4, and can be called by various names.

[0371] 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).

[0372] 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 disclosure.

[0373] FIG. 21 illustrates a wireless device according to an embodiment of the present disclosure. The embodiment of FIG. 21 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0374] Referring to FIG. 21, the first wireless device (100) and the second wireless device (200) can transmit and receive wireless signals via various wireless access technologies (e.g., LTE, NR). 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. 20.

[0375] 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). Furthermore, 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 / chip designed to implement a 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 disclosure, a wireless device may also mean a communication modem / circuit / chip.

[0376] A 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 disclosure, a wireless device may also mean a communication modem / circuit / chip.

[0377] 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.

[0378] 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.

[0379] 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.

[0380] 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.

[0381] FIG. 22 illustrates a signal processing circuit for a transmission signal according to an embodiment of the present disclosure. The embodiment of FIG. 22 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0382] Referring to FIG. 22, the signal processing circuit (1000) may include a scrambler (1010), a modulator (1020), a layer mapper (1030), a precoder (1040), a resource mapper (1050), and a signal generator (1060). Although not limited thereto, the operations / functions of FIG. 22 may be performed in the processor (102, 202) and / or the transceiver (106, 206) of FIG. 21. The hardware elements of FIG. 22 may be implemented in the processor (102, 202) and / or the transceiver (106, 206) of FIG. 21. For example, blocks 1010 to 1060 may be implemented in the processor (102, 202) of FIG. 21. Additionally, blocks 1010 to 1050 may be implemented in the processor (102, 202) of FIG. 21, and block 1060 may be implemented in the transceiver (106, 206) of FIG. 21.

[0383] The codeword can be converted into a wireless signal through the signal processing circuit (1000) of FIG. 22. Here, the codeword is an encoded bit sequence of an information block. The information block can include a transport block (e.g., an UL-SCH transport block, a DL-SCH transport block). The wireless signal can be transmitted through various physical channels (e.g., a PUSCH or a PDSCH).

[0384] Specifically, the codeword can be converted into a bit sequence scrambled by a scrambler (1010). The scramble sequence used for scrambling is generated based on an initialization value, and the initialization value may include ID information of the wireless device, etc. The scrambled bit sequence can be modulated into a modulation symbol sequence by a modulator (1020). The modulation method may include pi / 2-BPSK (pi / 2-Binary Phase Shift Keying), m-PSK (m-Phase Shift Keying), m-QAM (m-Quadrature Amplitude Modulation), etc. The complex modulation symbol sequence can be mapped to one or more transmission layers by a layer mapper (1030). The modulation symbols of each transmission layer can be mapped to the corresponding antenna port(s) by a precoder (1040) (precoding). The output z of the precoder (1040) can be obtained by multiplying the output y of the layer mapper (1030) by a precoding matrix W of N*M. Here, N is the number of antenna ports, and M is the number of transmission layers. Here, the precoder (1040) can perform precoding after performing transform precoding (e.g., DFT transform) on complex modulation symbols. In addition, the precoder (1040) can perform precoding without performing transform precoding.

[0385] The resource mapper (1050) can map modulation symbols of each antenna port to time-frequency resources. The time-frequency resources can include multiple symbols (e.g., CP-OFDMA symbols, DFT-s-OFDMA symbols) in the time domain and multiple subcarriers in the frequency domain. The signal generator (1060) generates a wireless signal from the mapped modulation symbols, and the generated wireless signal can be transmitted to another device through each antenna. To this end, the signal generator (1060) can include an Inverse Fast Fourier Transform (IFFT) module, a Cyclic Prefix (CP) inserter, a Digital-to-Analog Converter (DAC), a frequency uplink converter, etc.

[0386] The signal processing process for receiving signals in a wireless device can be configured in reverse order of the signal processing process (1010 to 1060) of FIG. 22. For example, a wireless device (e.g., 100, 200 of FIG. 21) can receive wireless signals from the outside through an antenna port / transceiver. The received wireless signals can be converted into baseband signals through a signal restorer. For this purpose, the signal restorer can include a frequency downlink converter, an analog-to-digital converter (ADC), a CP remover, and a fast Fourier transform (FFT) module. Thereafter, the baseband signal can be restored to a codeword through a resource demapper process, a postcoding process, a demodulation process, and a descrambling process. The codewords can be restored to the original information blocks through decoding. Accordingly, a signal processing circuit (not shown) for a received signal may include a signal restorer, a resource de-mapper, a postcoder, a demodulator, a de-scrambler, and a decoder.

[0387] Figure 23 illustrates a wireless device according to an embodiment of the present disclosure. The wireless device may be implemented in various forms depending on the use case / service (see Figure 20). The embodiment of Figure 23 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0388] Referring to FIG. 23, the wireless device (100, 200) corresponds to the wireless device (100, 200) of FIG. 21 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. 21. For example, the transceiver(s) (114) may include one or more transceivers (106, 206) and / or one or more antennas (108, 208) of FIG. 21. 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).

[0389] 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. 20, 100a), a vehicle (Fig. 20, 100b-1, 100b-2), an XR device (Fig. 20, 100c), a portable device (Fig. 20, 100d), a home appliance (Fig. 20, 100e), an IoT device (Fig. 20, 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. 20, 400), a base station (Fig. 20, 200), a network node, etc. Wireless devices may be mobile or stationary depending on the use / service.

[0390] In FIG. 23, 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 the 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 one or more processor sets. 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 a random access memory (RAM), a dynamic RAM (DRAM), a read only memory (ROM), a flash memory, a volatile memory, a non-volatile memory, and / or a combination thereof.

[0391] Below, the implementation example of Fig. 23 is described in more detail with reference to the drawings.

[0392] FIG. 24 illustrates a mobile device according to an embodiment of the present disclosure. The mobile device may include a smartphone, a smart pad, a wearable device (e.g., a smartwatch, smartglasses), or a portable computer (e.g., a laptop, etc.). The mobile device may be referred to as a Mobile Station (MS), a User Terminal (UT), a Mobile Subscriber Station (MSS), a Subscriber Station (SS), an Advanced Mobile Station (AMS), or a Wireless Terminal (WT). The embodiment of FIG. 24 may be combined with various embodiments of the present disclosure, and some descriptions, functions, procedures, proposals, methods, and / or operations of the embodiments may be omitted.

[0393] Referring to FIG. 24, the portable device (100) may include an antenna unit (108), a communication unit (110), a control unit (120), a memory unit (130), a power supply unit (140a), an interface unit (140b), and an input / output unit (140c). The antenna unit (108) may be configured as a part of the communication unit (110). Blocks 110 to 130 / 140a to 140c correspond to blocks 110 to 130 / 140 of FIG. 23, respectively.

[0394] The communication unit (110) can transmit and receive signals (e.g., data, control signals, etc.) with other wireless devices and base stations. The control unit (120) can control components of the mobile device (100) to perform various operations. The control unit (120) can include an AP (Application Processor). The memory unit (130) can store data / parameters / programs / codes / commands required for operating the mobile device (100). In addition, the memory unit (130) can store input / output data / information, etc. The power supply unit (140a) supplies power to the mobile device (100) and can include a wired / wireless charging circuit, a battery, etc. The interface unit (140b) can support connection between the mobile device (100) and other external devices. The interface unit (140b) can include various ports (e.g., audio input / output ports, video input / output ports) for connection with external devices. The input / output unit (140c) can input or output video information / signals, audio information / signals, data, and / or information input from a user. The input / output unit (140c) may include a camera, a microphone, a user input unit, a display unit (140d), a speaker, and / or a haptic module.

[0395] For example, in the case of data communication, the input / output unit (140c) obtains information / signals (e.g., touch, text, voice, image, video) input by the user, and the obtained information / signals can be stored in the memory unit (130). The communication unit (110) converts the information / signals stored in the memory into wireless signals, and can directly transmit the converted wireless signals to other wireless devices or to a base station. In addition, the communication unit (110) can receive wireless signals from other wireless devices or base stations, and then restore the received wireless signals to the original information / signals. The restored information / signals can be stored in the memory unit (130) and then output in various forms (e.g., text, voice, image, video, haptic) through the input / output unit (140c).

Claims

1. In the method, A first device, a step of acquiring sensing data; The first device obtains accuracy related to the sensing data; and A method comprising: a step of reporting, by the first device, the sensing data and an accuracy associated with the sensing data; 2. In paragraph 1, A method wherein the sensing data includes identification information.

3. In paragraph 1, The above accuracy is related to environmental conditions, method.

4. In paragraph 3, The above environmental conditions include fog, or whether it is day or night.

5. In paragraph 1, The above accuracy is related to at least one of the type of sensor or the performance of the sensor.

6. In paragraph 5, A method wherein the type of the sensor comprises at least one of LiDAR or radar.

7. In paragraph 5, The performance of the above sensor includes reflectivity.

8. In paragraph 5, The above accuracy is increased based on the sensing data being acquired by both the lidar and the radar.

9. In paragraph 1, The above accuracy is related to past collaborative recognition results, method.

10. In paragraph 1, The above accuracy is related to at least one of network delay, event occurrence location, and sensor failure.

11. In paragraph 1, The above accuracy is obtained based on a correction algorithm, and A method wherein the above correction algorithm comprises at least one of machine learning, Bayesian estimation, or reinforcement learning.

12. In paragraph 1, The above accuracy is obtained based on the object recognition engine, and A method wherein the object recognition engine comprises at least one of a license plate recognition engine, an optical character recognition engine, or a deep learning-based object detection engine.

13. In paragraph 12, The above deep learning-based object recognition engine is related to at least one of a convolutional neural network (CNN), a recurrent neural network (RNN), or a transformer-based model.

14. In the first device, At least one transmitter / receiver; at least one processor; and At least one memory connected to said at least one processor and storing instructions, said instructions being executed by said at least one processor, wherein said first device causes: Acquire sensing data; To obtain accuracy related to the above sensing data; and A first device that reports the sensing data and the accuracy associated with the sensing data.

15. In the processing device, at least one processor; and At least one memory connected to said at least one processor and storing instructions, said instructions being executed by said at least one processor, wherein said first device causes: Acquire sensing data; To obtain accuracy related to the above sensing data; and A processing device that reports the sensing data and the accuracy associated with the sensing data.

16. A non-transitory computer-readable storage medium that records commands, The above commands, when executed, cause the first device to: Acquire sensing data; To obtain accuracy related to the above sensing data; and A non-transitory computer-readable storage medium that reports the sensing data and the accuracy associated with the sensing data.

17. In the method, A second device receiving a plurality of sensing data; A step in which the second device receives a plurality of accuracies related to the plurality of sensing data; and A method comprising: a step of obtaining final sensing data based on the plurality of sensing data and the plurality of accuracies related to the plurality of sensing data by the second device; 18. In the second device, At least one transmitter / receiver; at least one processor; and At least one memory connected to said at least one processor and storing instructions, said instructions being executed by said at least one processor, wherein said second device causes: Receive multiple sensing data; Receive a plurality of accuracies related to the plurality of sensing data; and A second device that obtains final sensing data based on the plurality of sensing data and the plurality of accuracies related to the plurality of sensing data.

19. In the processing device, at least one processor; and At least one memory connected to said at least one processor and storing instructions, said instructions being executed by said at least one processor, wherein said second device causes: Receive multiple sensing data; Receive a plurality of accuracies related to the plurality of sensing data; and A processing device that obtains final sensing data based on the plurality of sensing data and the plurality of accuracies related to the plurality of sensing data.

20. A non-transitory computer-readable storage medium that records commands, The above commands, when executed, cause the second device to: Receive multiple sensing data; Receive a plurality of accuracies related to the plurality of sensing data; and A non-transitory computer-readable storage medium that obtains final sensing data based on the plurality of sensing data and the plurality of accuracies related to the plurality of sensing data.

Images